text
stringlengths 87
880k
| pmid
stringlengths 1
8
| accession_id
stringlengths 9
10
| license
stringclasses 2
values | last_updated
stringlengths 19
19
| retracted
stringclasses 2
values | citation
stringlengths 22
94
| decoded_as
stringclasses 2
values | journal
stringlengths 3
48
| year
int32 1.95k
2.02k
| doi
stringlengths 3
61
| oa_subset
stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|---|
==== Front
Cancer Cell IntCancer Cell International1475-2867BioMed Central London 1475-2867-5-151591069110.1186/1475-2867-5-15Primary ResearchInfluence of RARα gene on MDR1 expression and P-glycoprotein function in human leukemic cells Stromskaya Tatjana P [email protected] Ekaterina Y [email protected] Tatjana N [email protected] Alexander A [email protected] Alla A [email protected] Institute of Carcinogenesis, N.N. Blokhin Russian Cancer Research Centre of the Russian Academy of Medical Sciences, Kashirskoye sh 24, Moscow 115478, Russia2005 24 5 2005 5 15 15 22 10 2004 24 5 2005 Copyright © 2005 Stromskaya et al; licensee BioMed Central Ltd.2005Stromskaya et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Multidrug resistance (MDR) phenotype of malignant cells is the major problem in the chemotherapy of neoplasia. The treatment of leukemia with retinoids is aimed on the induction of leukemic cells differentiation. However the interconnections between retinoid regulated differentiation of leukemic cells and regulation of MDR remains unclear.
Methods
Four lines of cultured leukemic cells of diverse types of differentiation were infected with RARα gene and stable transfectants were isolated. We investigated the differentiation of these cells as well as the expression of RARα and MDR1 genes and P-glycoprotein (Pgp, MDR protein) functional activity in these cells.
Results
All RARα transfected sublines demonstrated the increase in the quantity of RARα mRNA. All these sublines became more differentiated. Intrinsic activity of MDR1 gene (but not Pgp functional activity) was increased in one of the transfectants. All-trans-retinoic acid (ATRA) induced Pgp activity in two of three infectants to a larger extent than in parental cells.
Conclusion
The data show that RARα regulates MDR1/ Pgp activity in human leukemic cells, in the first place, Pgp activity induced by ATRA. These results show that RARα overexpression in leukemic cells could result in MDR.
==== Body
Background
Multidrug resistance (MDR) phenotype of malignant cells is the major problem in the chemotherapy of neoplasia. P-glycoprotein (Pgp) activity is recognised to be one of the major mechanisms responsible for MDR. Pgp transports many structurally diverse compounds across the cell membrane and confers the MDR phenotype in tumor cells [1]. A number of signaling pathways participate in the regulation of MDR1 gene expression and the activity of its product, Pgp [2]. Some of these signaling pathways could participate in coordinated regulation of MDR1/Pgp activity, cell proliferation and cell differentiation. It was shown that retinoic acid (RA) can modulate MDR1 gene expression [3-5]. Retinoids are known to be involved into the regulation of the cell growth, differentiation and apoptosis. In the last decade retinoids became implicated into the treatment of leukemia and some solid tumors [6]. This approach changed the focus of the haematological diseases treatment from the cytotoxicity of the anti-cancer drugs to the reversal of arrested maturation of leukemic cells. Retinoids act via two families of receptors (RARs – RARα, RARβ, RARγ) and RXRs (RXRα, RXRβ, RXRγ). There is the evidence that RARα is the crucial receptor mediating the biological effects during retinoid signaling in some cells [7]. Cell differentiation caused by the stable overexpression of receptor RARα was shown to result in constitutive over expression of MDR1 gene in some cultured cells of solid tumors [4]. However the interconnections between RA/RARα regulated differentiation of leukemic cells and regulation of MDR1/Pgp activity remains unclear. In some leukemic cells RA did not influence MDR1 and/or Pgp activity, while in the others it either augmented or reduced MDR1/Pgp expression [5,8]. The aim of this study is to investigate if effects of all-trans-retinoic acid (ATRA) on MDR1/Pgp activity in leukemic cells are connected with RARα expression and with the leukemic cell differentiation. We isolated sublines of cultured leukemic cells characterized by the stable RARα overexpression and investigated the constitutive and ATRA induced MDR1/Pgp activity in these cells. Our data show that various RARα transformed leukemic cell lines acquired more differentiated phenotype. Constitutive level of MDR1 gene expression increased in one of RARα overexpressing cell sublines. RARα overexpression did not influence Pgp functional activity while Pgp activity induced by ATRA was elevated in all infectants studied. This shows that the main effect of RARα in the cells studied is its influence on the induced functional activity of Pgp.
Methods
Cell lines and culture
Lines of cultured leukemic cells used in the study: H9 cells (acute human T-cell leukemia) [9], KG-1 cell line (cells of acute myelogenous leukemia) [10], K562 cell line (cells obtained from the patient in blast crisis of chronic myeloid leukemia) [11], NB4 (acute promyelocytic leukemia) [12].
Cells were grown in RPMI-1640 medium supplemented with 10% fetal calf serum (Gibco, USA), 2 mM L-glutamine, 50 μg/ml gentamycin at 37°C in a fully humidified atmosphere of 95% air and 5% CO2. All the derived cell lines described in this paper were obtained by retroviral infection and selection with the appropriate antibiotic. ATRA (all-trans-retinoic acid, Sigma, USA) was added to the culture medium at seeding or 24 hours after seeding (see Legends to Figures).
Expression vector and retrovilal infection
The PA317/LRARSN retroviral vector-producing cell line was used. All the procedure was described earlier [4]. In brief, the vector used contains a cDNA fragment harbouring the complete coding sequence of the RARα gene driven by the Moloney murine leukemia virus long-terminal repeat as well as the SV40 early promoter-driving neomycin phosphotransferase gene (neo) as a selectable marker [13]. The cells (4 × 105 per 25-cm2 flask) were seeded 24 h before infection. Conditioned medium from a retrovirus-producing cell line was filtered through a 0.45-μm membrane (Millipore, USA), diluted 1:1 with medium, containing 1% serum and 8 μg /ml Polybrene and added to the cells for 24 h at 37°C, 5% CO2. Further selection were carried out by culturing cells in medium supplemented with 400 μg/ml G418 (Gibco, USA) for at least 21 days. The medium was changed twice a week. The pool of G418-resistant cells was resuspended in culture medium and progressively expanded.
Assay of cell growth, apoptosis and differentiation
Cells were seeded into 24-well plates (1 × 104 cell per well) and the cell number was counted at days 1, 3, 5 and 8 after seeding. The apoptosis in the populations of the parental and RARα infected cell lines was performed using the standard procedure [14]. Cells were collected 24 h after seeding, washed with PBS, and fixed in 70% ethanol overnight at 4°C. Fixed cells were suspended in citric buffer and stained with propidium iodide (5 mcg/ml) in PBS for 1 hour at 4°C. DNA content was subsequently measured by FACScan (Becton Dickinson, USA).
The immunophenotype of the cells was evaluated as previously described [15]. Surface expression of the following antigens was determined: CD3, CD5, CD7, CD8, CD11b, CD13, CD15, CD33, CD34, HAE3 and HAE9. In brief, cells were incubated with phycoerythrin-labelled monoclonal mouse antibodies for 20 min at 4°C (Becton, Dickinson), washed with RPMI 1640 medium and analyzed with a flow cytometer (Becton Dickinson).
Analysis of rhodamine 123 (Rh123) efflux by the cells
The technique used in the study was described in [16]. Cells were loaded with 5 μg/ml Rh123 (Sigma) for 10 min at 37°C, washed twice with cold PBS, pH 7.2, and incubated for 30 min in dye-free medium at 37°C. After the completion of incubation, cell were washed twice with cold PBS. Cell fluorescence was measured on a flow cytometer FACScan (Becton Dickinson, USA). Each measurement counted 5000 events. Non-viable cells were gated out of the analysis on the basis of side scatter.
RNA isolation and reverse transcriptase polymerase chain reaction (RT-PCR) analysis of RARα and MDR1 genes expression
The cells were dissolved in TRI reagent (Sigma, USA). Total RNA was isolated as described in the manufacturer's manual. For analysis, aliquots of isolated RNA were denatured with formamide and subjected to electrophoresis in 1.8% agarose gels. The samples with clearly visualized 18S and 28S RNA bands were used for further procedures. First-strand cDNA was synthesized using reverse transcriptase M-MuLV (MBI Fermentas, Russia) with 4 μg RNA as a template, 2.5 ng random hexamers, 0.25 mM of each deoxynucleotide triphosphate (SibEnzyme, Russia), dithiothreitol, 4 Units of RNAase inhibitor (MBI Fermentas, Russia) and 100 Units of M-MuLV RT. The reaction was performed at 42°C for 50 min, and 1/60 volume of reaction mixture was used for amplification. PCR was done in a total volume of 25 μl using the thermocycler "Tercyc" (DNA-technology, Russia). The PCR mixture consisted of (NH4)2SO4-containing PCR buffer ("MBI Fermentas"), 0.160 mM dNTPs mix ("MBI Fermentas"), 2 mM MgCl2, 20 pmoles of each specific primer and 0.8 Unit of Taq-polymerase ("MBI Fermentas"). PCR was done as follows: 94°C for 2 seconds, Tm (different for each gene) for 10 seconds, 72°C for 5 seconds. Semi-quantitative PCR analysis of RARa and MDR1 genes expression were performed using oligomers amplifying a 333 bp and 167 bp products, respectively. Specific gene primers used for RT-PCR are given in Table 1. The amounts of template cDNAs were normalized by PCR amplification of β2-microglobulin cDNA (internal control). The optimal numbers of PCR cycles were 24 for the b2-microglobulin, 26 for RARα-specific product, 33 for MDR1 (for all cells lines except KG1 and KG1/RAR, for these cells the numbers of PCR cycles MDR1-specific product were 26). These numbers of cycles yielded clearly detectable PCR products within an exponential range. PCR products were amplified in separate tubes, resolved by electrophoresis in 2% agarose gel, stained with ethidium bromide and visualized in UV light.
Table 1 Specific gene primers used for RT-PCR
Gene Product size Primer Sequence
RARα 333 bp F 5'-GTCTTTGCCTTCGCCAACCAG-3'
R 5'-GCCCTCTGAGTTCTCCAACA-3'
MDR1 127 bp F 5'-CCCATCATTGCAATAGCAGG-3'
R 5'-GTTCAAACTTCTGCTCCTGA-3'
β2m 114 bp F 5'-ACCCCCACTGAAAAAGATGA-3'
R 5'-ATCTTCAAACCTCCATGATG-3'
Results
Influence of RARα gene overexpression on cell differentiation, proliferation and spontaneous apoptosis
RARα gene was introduced into the cultured leukemic cells of diverse types of differentiation as described in Methods. The sublines of H9, KG-1, K562 and NB4 cells characterized by the capability to grow in the medium supplemented with G418 were isolated (H9/RAR, KG-1/RAR, K562/RAR and NB4/RAR). Semi-quantitative RT-PCR revealed more pronounced expression of RARα mRNA in all transfected cell lines in comparison with the wild type cells (Fig. 1). ATRA (5 μM applied for 48 h) increased RARα mRNA in some RARα transformed cells (H9/RAR, KG-1/RAR, K562/RAR) to a greater extent than in parental cells (Fig. 1).
Figure 1 Expression of RARα mRNA in parental and RARα transfected cell lines. RT PCRM. k- – water. ATRA (5 μM) was added to cell cultures 24 h after seeding for 48 h. Then the cells were collected and processed as specified in "Methods" (RNA isolation and reverse transcriptase polymerase chain reaction (RT-PCR) analysis of RARα gene expression). This figure is representative of 2 separate experiments.
The investigation of the differentiation status of these cells shows that all RARα transfected sublines differ from the parental cell populations (Fig. 2). RARα transfected H9 culture contains more cell variants expressing CD5 and CD8 antigens than parental cell line (Fig. 2A). Thus the number of cells with antigens of later lymphoid differentiation markers increased in RARα overexpressing H9 cells. There is phenotypic evidence of granulocytic differentiation in KG-1/RAR cell subline as indicated by a reduction in CD13 expression and the increase in the expression of CD11b antigen in comparison with parental cells (Fig. 2B). In KG-1/RAR cell population the portion of CD34 cells decreased and the portion of CD33 cells increased (Fig. 2B). This also testifies to increased differentiation of these RARα overexpressing cells. In K562/RAR population the number of the cells of erythroid differentiation (expressing HAE9 and HAE3 antigens) is larger than in K562 population (Fig. 2C). Hemoglobin synthesis is increased in K562/RAR culture more than 5-fold in comparison with parental cells (not shown). In NB4/RAR population the number of the cells of myelogenous differentiation (expressing CD11b and CD15 antigens) is larger than in NB4 population (Fig. 2D).
Figure 2 Comparison of antigen expression by the parental and RARα infected cell lines. Cells were incubated for 30 min at 4°C in the presence of an appropriate monoclonal antibody. After three washes with PBS, cells were incubated for 30 min at 4°C with goat antimouse IgG labeled with phycoerythrin and then analyzed in flow cytometer (Becton Dickinson).
The percentage of cells undergoing spontaneous apoptosis increased 2-3-fold in all RARα transfected cell populations (Fig. 3). This could be connected with more differentiated phenotype of RARα transformed cells. It seems that in the population of H9/RAR cells the increased number of apoptotic cells could be at least in part connected with increased expression of CD95 (Fas/APO1): in this RARα transformed subline CD95 increased almost 10-fold in comparison with parental cell population (from 2,6% in H9 to 21,4% in H9/RAR culture). However in KG-1 and K562 cell populations the number of CD95 expressing cell did not increase after RARα transformation.
Figure 3 Spontaneous apoptosis in the populations of the parental and RARα infected cell lines. Propidium iodide flow cytometry detection of dead cells was performed using the standard procedure. Cells were collected 24 h after seeding, washed with PBS, and fixed in 70% ethanol overnight at 4°C. Fixed cells were suspended in citric buffer and stained with 5 mcg/ml propidium iodide in PBS for 1 hour at 4°C. DNA content was subsequently measured by FACScan (Becton Dickinson, USA). All cells with sub-G0 DNA content were regarded as dead cells. This figure is representative of 3 separate experiments.
As Fig. 4 shows, RARα transfected KG-1, K562 and NB4 cells proliferated more slowly than parental cells. However H9/RAR cells did not demonstrate slower proliferation rate. Thus, more differentiated status of the RARα transformed cell populations was not necessary connected with the decrease in the proliferation rates. All RARα transformed cells seem to be more sensitive than wild type cells to inhibitory action of ATRA on cell proliferation (Fig. 5).
Figure 4 Proliferation rates of parental and RARα infected cells. Cells were seeded into 24-well plates (1 × 104 cell per well) and the cell number was counted at days 1,3,5,8 after seeding. This figure is representative of 3 separate experiments.
Figure 5 Influence of retinoic acid (ATRA, 5 μM) on the proliferation of parental and RARα transfected cells. Cells were seeded into 24-well plates (1 × 104 cell per well), ATRA was added at seeding and the cell number was counted at days 1, 3, 5 and 8 after seeding. This figure is representative of 3 separate experiments.
Influence of RARα overexpression on MDR1 gene activity
We studied intrinsic and ATRA induced expression of MDR1 gene in all cell lines by semi-quantitative RT-PCR technique. The basal levels of MDR1 mRNA varied in different wild type cells: in H9 and NB4 cells constitutive MDR1 gene expression was not revealed, in K562 wild type cells some MDR1 mRNA was found, in KG-1 cells the quantity of MDR1 mRNA was large (Fig. 6). It is noteworthy that the optimal number of PCR cycles were 33 for MDR1-specific product in all cells while for studies of KG1 and KG1/RAR cells we used 26 PCR cycles. In RARα transfected H9 cells the constitutive expression of MDR1 gene slightly increased, while in KG-1/RAR and NB4/RAR cells the constitutive MDR1 mRNA quantity was not elevated in comparison with the wild type cells, it seems to be even slightly decreased in K562/RAR (Fig. 6). Thus the alterations of the basal level of MDR1 expression in RARα transformed cells seem to vary in different cell lines.
Figure 6 Intrinsic and retinoic acid induced expression of MDR1 gene in parental and RARα transfected cells. k- – water. ATRA (5 μM) was added to cell cultures 24 h after seeding for 48 h. Then the cells were collected and processed as specified in "Methods" (RNA isolation and reverse transcriptase polymerase chain reaction (RT-PCR) analysis of MDR1 gene expression). The optimal numbers of PCR cycles were 33 for MDR1-specific product for all cells lines except KG1 and KG1/RAR, for these cells the numbers of PCR cycles for MDR1-specific product were 26. This figure is representative of 2 separate experiments.
ATRA (5 μM applied for 48 h) increased MDR1 gene expression in all examined cell lines either in parental or RARα transfected cells (Fig. 6). In H9/RAR cells effect of ATRA on MDR1 expression was significantly greater in comparison with parental cells. In other ATRA treated RARα transformed cell sublines MDR1 expression was undistinguishable from ATRA treated parental cells (Fig 6).
Influence of RARα gene transformation on Rh123efflux by the cells
The retention of Rh123 by the cells is considered as a test for Pgp functional activity [16,17]. Rh123 efflux from the cells was increased in K562/RAR cells in comparison with the parental cell population (Fig. 7B, Table 2). In H9 and KG-1 RARα transformed cells there were alterations in the Rh123 retention (Fig. 7A and 7C): in the populations of H9/RAR and KG-1/RAR cultures the fraction of more dull cells decreased in comparison with parental cultures (mean fluorescence intensity of the cell sublines studied are given in the table 2). This shows that Pgp activity was not elevated in these RARα transformed cell populations and suggests that there is some decrease in Pgp functional activity.
Figure 7 Evaluation of Rh123 efflux from the parental and cells RARα transfected cells. Cells were loaded with 5 μg/ml Rh123 for 10 min at 37°C, than washed twice with cold PBS, and incubated for 30 min in dye-free medium at 37°C. After the completion of incubation, cell were washed twice with cold PBS. Cell fluorescence was measured on a flow cytometer FACScan (Becton Dikinson, USA). Each measurement counted 5000 events. Non-viable cells were gated out of the analysis on the basis of side scatter. This figure is representative of 2 separate experiments.
Table 2 Influence of RARα transformation on the intrinsic and induced expression of MDR1 gene
MDR1 expression Rh123 efflux (mean fluorescence intensity)
Cells intrinsic ATRA induced intrinsic ATRA induced
H9 - + 450 457
H9/RAR + ++ 506 416
K562 + ++ 446 370
K562/RAR + ++ 403 333
KG-1 ++ +++ 65,7 38,3
KG-1/RAR ++ +++ 90,7 20,2
NB4 - ++ n.d. n.d.
NB4/RAR - ++ n.d. n.d.
There was increase in the portion of Rh123 dull cells after ATRA treatment both in K562 and K562/RAR cell populations (mean fluorescence intensity of both populations decreased approximately on 17%) (Fig. 8C, D, Table 2). ATRA induced Rh123 efflux from H9/RAR cells, while in H9 parental population this drug had no effect (Fig. 8A, B, Table 2). In KG-1/RAR cells ATRA induced very prominent increase in the number of Rh123 dull cells (more than 70% decrease of mean fluorescence intensity), while in the parental cell population ATRA decreased mean fluorescence intensity to a lesser extent (Fig. 8E, F, Table 2).
Figure 8 Influence of retinoic acid (ATRA) on Rh123 efflux from the parental and cells RARα transfected cells. ATRA (5 μM) was added to cell cultures 24 h after seeding for 48 h. Than cells were loaded with 5 μg/ml Rh123 for 10 min at 37°C, than washed twice with cold PBS, and incubated for 30 min in dye-free medium at 37°C. After the completion of incubation, cell were washed twice with cold PBS. Cell fluorescence was measured on a flow cytometer FACScan (Becton Dikinson, USA). Each measurement counted 5000 events. Non-viable cells were gated out of the analysis on the basis of side scatter. This figure is representative of 2 separate experiments.
Discussion
The treatment of leukemia with retinoids is aimed on the induction of leukemic cells differentiation. The question is: are there interconnections between RA/RARα regulated differentiation of leukemic cells and MDR1/Pgp activity? In this study we have isolated more differentiated variants of the cultured leukemic cells by the introduction into the cells of RARα gene encoding one of RA receptors. All RARα transformed leukemic cell populations were characterized by the higher RARα gene expression in comparison with the parental cells. All RARα transformed leukemic cell populations became more differentiated. This was demonstrated by the studies of the differentiation markers, by the increase in the number of cells dying by spontaneous apoptosis and by the decrease of the proliferation rates of most RARα transfected cell sublines. Thus, RARα overexpression could result in the increase of the differentiation of various leukemic cell populations.
We compared MDR1 gene expression and Pgp functional activity tested by Rh123 retention in parental and RARα transformed cells. The results are summarized in the Table 2. Increased constitutive (uninduced) expression of MDR1 gene was found in one of four cell lines after RARα transformation (H9/RAR, Table 2, Fig. 6). In the previous experiments with melanoma and hepatoblastoma human cells we have shown that constitutive expression of MDR1 gene was increased after RARα transfection in both RARα transformed cell sublines [4]. Thus interconnections between regulation of the basal MDR1 and RARα activities could exist both in the cells of solid tumors and in the leukemic cells. Our data suggest, that in the cell populations of solid tumors RARα overexpression could be accompanied by constitutive MDR1 over-expression more often than in the cells of hematopoietic malignancies.
Our study did not reveal the occurrence of the functional Pgp in leukemic cells studied after RARα transformation. In H9/RAR cells elevation of the constitutive MDR1 expression did not lead to the increase in Rh123 efflux (Fig. 7A, Table 2). Some studies also have described discrepancies between Pgp (protein) or MDR1 mRNA expression and Pgp function in leukemic cells [18,19]. These discrepancies could occur for a variety of reasons. Anyway, our data show that increase in the differentiation of leukemic cell populations induced by RARα overexpression did not result in the elevation of constitutive Pgp functional activity. In our previous study we found that RARα overexpression did not change Pgp functional activity in two RARα transformed sublines of human cells (melanoma and hepatoblastoma) but did change it in the rat cells [4]. It seems that exogeneous RARα in the cells of human malignancies does not influence basal Pgp functional activity.
In KG-1/RAR characterized by the increased differentiaion (Table 1) we had not found increase in the constitutive MDR1 expression and Pgp functional activity decreased (Fig. 7C, Table 2). It is known that blood stem cells and early progenitors expressing CD34 antigen also express high levels of functionally active Pgp [20]. Maturation of these cells is accompanied by the decrease in Pgp expression and even more rapid decrease in Pgp functional activity [21]. It may be suggested that alterations of Pgp function in KG-1/RAR are connected with the differentiation of these cells.
The situation with Pgp functional activity induced by ATRA in the cells studied differs from the situation with constitutive activity of this protein. In all three RARα transfected cells ATRA had induced Pgp fuctional activity (Fig. 8. Table 2). Moreover, in two RARα transformed sublines (H9/RAR and KG-1/RAR) ATRA activated Pgp, while in the parental cells it had either no effect (H9) or activated Pgp to a lesser extent (KG-1) (Table 2). These data suggest that RARα participate in the control of induced, but not in constitutive Pgp functional activity in leukemic cells.
The regulation of MDR1 gene transcription and Pgp functional activities are the complex processes [1,2]. The studies of these processes are underway. Our data show that RARα gene overexpression could influence the induced Pgp functional activity in leukemic cells, i.e. could participate in the occurrence of multidrug resistance in the populations of these malignant cells. It seems that this influence could depend on the cell context.
Acknowledgements
This work was supported by grants 04-04-48613a and 02-04-48200 from the Russian Foundation for Basic Research.
==== Refs
Ambudkar SV Dey S Hrycyna CA Ramachandra M Pastan I Gottesman MM Biochemical, cellular, and pharmacological aspects of the multidrug transporter Annu Rev Pharmacol Toxicol 1999 39 361 398 10331089 10.1146/annurev.pharmtox.39.1.361
Scotto KW Transcriptional regulation of ABC drug transporters Oncogene 2003 22 7496 511 14576854 10.1038/sj.onc.1206950
Bates SE Mickley LA Chen YN Richert N Rudick J Biedler JL Fojo AT Expression of a drug resistance gene in human neuroblastoma cell lines: modulation by retinoic acid-induced differentiation Mol Cell Biol 1989 9 4337 4344 2573830
Stromskaya TP Rybalkina EY Shtil AA Zabotina TN Filippova NA Stavrovskaya AA Influence of exogenous RARα gene on MDR1 expression and P-glycoprotein function in human and rodent cell lines Br J Cancer 1998 77 1718 1725 9667638
Tokura Y Shikami M Miwa H Watarai M Sugamura K Wakabayashi M Satoh A Imamura A Mihara H Katoh Y Kita K Nitta M Augmented expression of P-gp/multi-drug resistance gene by all-trans retinoic acid in monocytic leukemic cells Leuk Res 2002 26 29 36 11734301 10.1016/S0145-2126(01)00094-7
Altucci L Gronemeyer H The promise of retinoids to fight against cancer Nature Rev Cancer 2001 1 181 193 11902573 10.1038/35106036
Schneider SM Offterdinger M Huber H Grunt TW Activation of retinoic acid receptor α is sufficient for full induction of retinoic responses in SK-BR-3 and T47D human breast cancer cells Cancer Res 2000 60 5479 5487 11034091
Zhou DC Marie JP Maisonneuve L Faussat-Suberville AM Zittoun R Effect of differentiating agents on modulation of MDR1 gene expression in multidrug-resistant hematopoietic HL60/DNR cell line Exp Hematol 1993 21 779 784 8099018
Popovic M Sarngadharan MG Read E Gallo RC Detection, isolation and continuous production of cytopathic retroviruses (HTLV III) from patients with AIDS and at risk for AIDS Science 1984 224 497 500 6200935
Koeffler HP Golde DW Acute myelogenous leukemia: a human cell line responsive to colony-stimulating activity Science 1978 200 1153 1154 306682
Lozzio BB Lozzio CB Properties and usefulness of the original K-562 human myelogenous leukemia cell line Leuk Res 1979 3 363 370 95026 10.1016/0145-2126(79)90033-X
Lanotte M Martin-Thouvenin V Najman S. Balerini P Valensi F Berger R NB4, a maturation inducible cell line with t(15;17) marker isolated from human acute promyelocytic leukemia (M3) Blood 1991 77 1080 1086 1995093
Collins SJ Robertson KA Mueller LeM Retinoic acid-induced granulocytic differentiation of HL-60 is mediated directly through the retinoic acid receptor (RARα) Mol Cell Biol 1990 10 2154 2163 1970118
Ohta H Yatomi Y Sweeney EA Hakomory S Igarashi Y A possible role of sphingosine in induction of apoptosis by tumor necrosis factor-alpha in human neutrophils FEBS Lett 1994 355 267 270 7988686 10.1016/0014-5793(94)01218-0
Turkina AG Baryshnikov JuA Sedjakhina NP Folomeshkina SV Sokolova MA Khoroshko ND Stavrovskaya AA Studies of P-glycoprotein in chronic myeloid leukemia patients: expression, activity and correlations with CD34 antigen Bri J Haematol 1996 92 88 96 10.1046/j.1365-2141.1996.273807.x
Egudina SV Stromskaya TP Frolova EA Stavrovskaya AA Early steps of P-glycoprotein expression in cell cultures studied with vital fluorochrome FEBS Letters 1993 329 63 66 8102609 10.1016/0014-5793(93)80194-Y
Feller N Kuiper CM Lankelma J Ruhdal JK Scheper RJ Pinedo HM Broxterman HJ Functional detection of MDR/P170 and MRP/P190 mediated multidrug resistance in tumour cells by flow cytometry Br J Cancer 1995 72 543 549 7669559
Marie J-P Zhou DC Gurbuxani S Legrand O Zittoun R MDR1/P-glycoprotein in haematological neoplasms Eur J Cancer 1996 1034 1038 8763345 10.1016/0959-8049(96)00055-X
Bailly JD Muller C Jaffre'zou JP Demur C Gassar G Bordier C Laurent G Lack of correlation between expression and function of Pgp in acute myeloid leukemia Leukemia 1995 9 799 807 7769842
Chaudhary PM Mechetner EB Roninson IB. Expression and activity of the multidrug resistance P-glycoprotein in human peripheral blood lymphocytes Blood 1992 80 2735 2739 1360267
List AF Role of multidrug resistance and its pharmacological modulation in acute myeloid leukemia Leukemia 1996 10 937 942 8667648
| 15910691 | PMC1166566 | CC BY | 2021-01-04 16:24:17 | no | Cancer Cell Int. 2005 May 24; 5:15 | utf-8 | Cancer Cell Int | 2,005 | 10.1186/1475-2867-5-15 | oa_comm |
==== Front
Cardiovasc DiabetolCardiovascular Diabetology1475-2840BioMed Central London 1475-2840-4-71593509510.1186/1475-2840-4-7Original InvestigationComparison of rosuvastatin and atorvastatin for lipid lowering in patients with type 2 diabetes mellitus: results from the URANUS study Berne Christian [email protected] Annica [email protected] URANUS study investigators 1 University Hospital, Uppsala, Sweden2 AstraZeneca Sverige AB, Sweden2005 3 6 2005 4 7 7 15 4 2005 3 6 2005 Copyright © 2005 Berne et al; licensee BioMed Central Ltd.2005Berne et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Objective
The Use of Rosuvastatin versus Atorvastatin iN type 2 diabetes mellitUS (URANUS) study compared rosuvastatin with atorvastatin for the reduction of low-density lipoprotein cholesterol (LDL-C) in patients with type 2 diabetes.
Methods
After a 6-week dietary run-in, patients aged ≥ 18 years with type 2 diabetes and LDL-C ≥ 3.3 mmol/L were randomised to double-blind treatment with rosuvastatin 10 mg (n = 232) or atorvastatin 10 mg (n = 233) for 4 weeks. Doses were then titrated up to a maximum of rosuvastatin 40 mg or atorvastatin 80 mg over 12 weeks to achieve the 1998 European LDL-C goal (<3.0 mmol/L).
Results
Rosuvastatin reduced LDL-C levels significantly more than atorvastatin during the fixed-dose and titration periods (p < 0.0001). Significantly more patients reached the 1998 LDL-C goal with rosuvastatin 10 mg compared with atorvastatin 10 mg at 4 weeks (81% vs 65%, p < 0.001). At 16 weeks, significantly more patients achieved their LDL-C goal with rosuvastatin compared with atorvastatin (94% vs 88%, p < 0.05) and more patients receiving rosuvastatin remained at their starting dose with reduced requirement for dose titration. At 4 weeks, 65% of rosuvastatin patients had reached their 2003 European LDL-C goal (< 2.5 mmol/L), compared with 33% of atorvastatin patients (p < 0.0001). Both treatments were similarly well tolerated with no unexpected safety concerns.
Conclusion
At the start dose and following dose titration, rosuvastatin was significantly more effective than atorvastatin at reducing LDL-C and achieving European LDL-C goals in patients with type 2 diabetes.
==== Body
Introduction
The prevalence of type 2 diabetes in adults was estimated at 2.8% worldwide in 2000, and predicted to increase to 4.4% by 2030 [1]. Patients with type 2 diabetes have a risk of cardiovascular disease approximately two- to four-times greater than that in the non-diabetic population [2]. Furthermore, their prognosis is worse; in a Swedish study the 5-year mortality rate after myocardial infarction was 55% for patients with diabetes compared with 30% in patients without diabetes (p < 0.001), and the re-infarction rates were 42% and 25%, respectively (p < 0.001) [3]. More recent data reflecting the outcome of new evidence-based interventions in acute myocardial infarction demonstrate that the difference between diabetic and non-diabetic subjects is still present, showing a 1-year mortality in males of 22.3% versus 13.0% in males and 26.1% versus 14.4% in females [4]. In the US National Health and Nutrition Examination Survey (NHANES I), the age-adjusted mortality rate in diabetic patients over 9 years of follow-up was double that in non-diabetic patients, and cardiovascular disease accounted for 75% of the excess mortality in men and 57% in women [5].
The elevated cardiovascular risk in patients with type 2 diabetes is primarily attributed to the clustering of atherogenic risk factors, including dyslipidaemia, hypertension, abdominal obesity, left ventricular hypertrophy, and impaired fibrinolysis [6]. For patients with diabetes, European Diabetes Policy Group guidelines published in 1999 and European guidelines for coronary heart disease prevention published in 1998, both recommend that low-density lipoprotein cholesterol (LDL-C) levels should be <3.0 mmol/L [7,8]. More recent (2003) European guidelines on cardiovascular disease prevention also recognise type 2 diabetes as a risk factor, and recommend more stringent LDL-C reductions to<2.5 mmol/L [9]. In addition, this goal is recommended by both the American Diabetes Association and the US National Cholesterol Education Program Adult Treatment Panel III [10,11].
Statins are recognized as first-line therapy for cholesterol lowering [7,11], and have been proven to reduce cardiovascular morbidity and mortality in large outcome trials in various populations [12-17]. The benefits of statin therapy extend to patients with diabetes, as shown by subgroup analyses of patients with diabetes in several of the major statin outcome studies, including the Cholesterol And Recurrent Events (CARE) study, the Scandinavian Simvastatin Survival Study (4S), the Long-Term Intervention with Pravastatin in Ischemic Disease (LIPID) study and the Heart Protection Study [18-21]. The Collaborative Atorvastatin Diabetes Study (CARDS) recently investigated the effects of lipid lowering with statin therapy specifically in patients with type 2 diabetes [22]. The primary endpoint, time to the first occurrence of acute coronary events, coronary revascularisation or stroke, was significantly reduced by 37% in patients treated with atorvastatin 10 mg compared with placebo (p = 0.001). In addition, LDL-C levels were significantly reduced by 40% in the atorvastatin 10 mg group compared with the placebo group (p < 0.001) [22].
Despite the proven benefits of statin therapy, studies suggest that many patients with diabetes fail to achieve lipid goals in clinical practice [23,24]. Statins differ in their lipid-modifying efficacy and their ability to enable patients to achieve lipid goals [25,26]. Trials in patients with hypercholesterolaemia have shown that rosuvastatin is more effective than atorvastatin at reducing LDL-C and achieving US and/or European LDL-C goals over treatment periods ranging from 6 to 52 weeks [25-30]. The URANUS (Use of Rosuvastatin versus Atorvastatin iN type 2 diabetes mellitUS) study is a direct comparison of the effects of rosuvastatin with atorvastatin on LDL-C, other plasma lipids and LDL-C goal achievement in patients with diabetes. This study was designed to reflect the optimal treatment of diabetic dyslipidaemia in the clinical setting, in that statin dose was titrated upwards from the recommended start dose to that required to enable patients to achieve LDL-C goal.
Methods
Patients
Patients (male or female) aged 18 years or more were eligible for the study if they had a history of type 2 diabetes for at least 3 months; were being treated with diet, oral antidiabetic medication, insulin or a combination of these treatments; and had fasting LDL-C of ≥ 3.3 mmol/L and triglycerides (TG) of<6.0 mmol/L at enrolment. Exclusion criteria included: type 1 diabetes; uncontrolled type 2 diabetes; uncontrolled hypothyroidism or hypertension; nephrotic syndrome or severe renal failure; active liver disease or hepatic dysfunction; active arterial disease (e.g., unstable angina, myocardial infarction, transient ischaemic attack, cerebrovascular accident, coronary artery bypass grafting or percutaneous transluminal coronary angioplasty within 3 months before beginning the study); serum creatinine kinase (CK) levels >3 × the upper limit of normal (ULN); body mass index >35 kg/m2; and known hypersensitivity to statins. All patients gave written informed consent, and the study was conducted in accordance with the Declaration of Helsinki.
Study design
The trial was a randomised, double-blind, parallel-group study (4522SE/0001) conducted in 51 centres in Sweden. The study design is summarised in figure 1. Patients meeting the inclusion and exclusion criteria at enrolment entered a 6-week dietary run-in period and all lipid-lowering therapy was withdrawn at least 14 days before the end of this period. Patients with fasting LDL-C ≥ 3.3 mmol/L were then randomised to a starting dose of either rosuvastatin 10 mg or atorvastatin 10 mg for 4 weeks. This was followed by a 12-week period of dose titration, making a total of 16 weeks of treatment. Patients who had not reached the 1998 European guideline goal of LDL-C<3.0 mmol/L [7] after 4 weeks were titrated up by doubling the statin dose (rosuvastatin 20 mg or atorvastatin 20 mg). Further dose titrations (to rosuvastatin 40 mg, or atorvastatin 40 mg or 80 mg) were performed at 8 weeks and 12 weeks for patients who were still not at their LDL-C goal. Patients whose LDL-C level was below the goal at 4 weeks continued on the initial dose of study medication; if their LDL-C level exceeded the goal at subsequent visits, study medication was up-titrated.
Figure 1 Study design. aIn patients who had not reached the European goal of LDL-C<3.0 mmol/L after 4 weeks, the statin dose was doubled at each visit, up to a maximum of RSV 40 mg and ATV 80 mg RSV: Rosuvastatin, ATV: Atorvastatin, LDL-C: Low-density lipoprotein cholesterol
Concomitant treatment with erythromycin, azole antimycotic agents, vitamin K antagonists, immunosuppressive agents, glitazones or systemic steroids was not permitted during the study. If insulin treatment became necessary, or if the patient took lipid-lowering medication (other than study medication), the patient was discontinued from the trial.
Assessments
Efficacy
The primary endpoint was the percentage change in LDL-C from baseline (randomisation) to 16 weeks. Secondary endpoints included: percentage change in LDL-C from baseline to 4 weeks; percentage of patients achieving the 1998 European LDL-C goal at 4 and 16 weeks; percentage change in total cholesterol (TC), TG, high-density lipoprotein cholesterol (HDL-C), the LDL-C/HDL-C ratio, the non-HDL-C/HDL-C ratio, the TC/HDL-C ratio, apolipoprotein (apo) B, apo A-I and the apo B/apo A-I ratio from baseline to 4 and 16 weeks; and the number of titration steps at 16 weeks. A tertiary endpoint was the difference in overnight urinary albumin excretion (UAE) from baseline to 16 weeks.
All patients were instructed to fast for 8 hours prior to giving blood samples. LDL-C levels were measured using a direct method with enzymatic colorimetry (Genzyme Diagnostics, Genzyme Corporation, Cambridge, MA, USA). All analyses were conducted at a central laboratory.
Safety
Adverse events spontaneously reported by the patients, elicited in response to an open question or revealed by observation, were recorded at each visit. Laboratory safety variables included: blood haemoglobin, platelet count, leucocyte count, serum aspartate aminotransferase (ASAT), serum alanine aminotransferase (ALAT), serum alkaline phosphatase, serum bilirubin, CK, serum creatinine and glycated haemoglobin (HbA1c). All analyses were performed at a central laboratory.
Statistical methods
In order to have a 90% chance of detecting a difference between the two treatment arms of 6% in the primary endpoint (percentage change in LDL-C from baseline to 16 weeks), 212 patients per arm were required to complete the study. The primary efficacy endpoint was determined using analysis of covariance with change in LDL-C as response variable, treatment and centre as factors, and baseline LDL-C as covariate. Percentage change in other lipid variables from baseline to 4 weeks and 16 weeks, and percentage change in UAE, were analysed in the same way as the primary endpoint. The proportion of patients reaching LDL-C goal was analysed using a Mantel-Haenszel test stratified by centre. All tests were two-sided with a significance level of 5%. In addition, 95% confidence intervals were calculated for the treatment differences in all efficacy variables except the percentage of patients reaching LDL-C goal.
All efficacy variables were analysed in the intention-to-treat population (observed data). Analysis of the primary endpoint was also carried out using the last observation carried forward approach. All enrolled patients were evaluated for safety.
Results
Demographics
A total of 469 patients were randomised, and efficacy data were obtained from 465 patients, 232 in the rosuvastatin group and 233 in the atorvastatin group (figure 2). The two groups were well matched at baseline, and demographic details are shown in table 1. Previous statin treatment was received by 31 patients (13%) in the rosuvastatin group and 39 patients (17%) in the atorvastatin group. Eleven patients in the rosuvastatin group and 12 in the atorvastatin group discontinued during the randomised treatment period (figure 2).
Figure 2 Study populations
Table 1 Patient demographics of ITT population
Rosuvastatin (n = 232) Atorvastatin (n = 233)
Gender, male/female (%) 128/104 (55.2/44.8) 136/97 (58.4/41.6)
Race, white (%) 229 (98.7) 229 (98.3)
Mean age, years (SD) 63.5 (8.8) 65.0 (8.6)
Mean weight, kg (SD) 84.8 (14.3) 82.5 (13.5)
Mean BMI, kg/m2 (SD) 29.0 (3.6) 28.4 (3.6)
Mean baseline LDL-C, mmol/L (SD) 4.6 (0.85) 4.6 (0.82)a
Mean baseline HDL-C, mmol/L (SD) 1.2 (0.27) 1.2 (0.27)a
Mean baseline TG, mmol/L (SD) 2.0 (1.0) 2.0 (0.93)a
ITT: Intention to treat, SD: Standard deviation, BMI: Body mass index, LDL-C: Low-density lipoprotein cholesterol, HDL-C: High-density lipoprotein cholesterol, TG: Triglycerides
an = 232
Efficacy
At the end of the titration-to-goal period, rosuvastatin was significantly more effective than atorvastatin on the primary efficacy measure, reducing LDL-C by 52% compared with 46% in the atorvastatin group (p < 0.0001) (table 2). In line with its greater efficacy for LDL-C reduction, significantly more rosuvastatin-treated patients reached the 1998 European LDL-C goal after 16 weeks than atorvastatin-treated patients (94% vs 88%, p < 0.05). Furthermore, more patients achieved the goal on the starting dose of rosuvastatin than atorvastatin (75% vs 54%) (figure 3). The greater ability of rosuvastatin to lower LDL-C was also reflected by the number of dose titrations required by each treatment group; a total of 75 titration steps were required by rosuvastatin-treated patients compared with 155 titrations in the atorvastatin group.
Table 2 Percentage change from baseline in lipid variables at 16 weeks (ITT population). Doses were titrated from week 4 to week 16 in patients who had not reached the 1998 European LDL-C goal (< 3.0 mmol/L)
Variable Least-squares mean percentage change from baseline to 16 weeks Difference (95% CI) p-value
Rosuvastatin 10–40 mg (n = 221) Atorvastatin 10–80 mg (n = 220)
LDL-C -52.3 -45.5 -6.7 (-8.8, -4.7) < 0.0001
TC -35.4 -31.3 -4.1 (-5.8, -2.4) < 0.0001
HDL-C 5.3 4.0 1.3 (-1.3, 3.8) NS
TG -21.2 -21.1 -0.1 (-5.6, 5.3) NS
Non-HDL-C -45.0 -39.6 -5.5 (-7.4, -3.5) < 0.0001
LDL-C/HDL-C ratio -54.1 -47.0 -7.1 (-9.3, -4.9) < 0.0001
Non-HDL-C/HDL-C ratio -47.1 -40.9 -6.2 (-8.6, -3.9) < 0.0001
TC/HDL-C ratio -38.0 -33.1 -5.0 (-6.9, -3.0) < 0.0001
Apo B -45.2 -40.1 -5.1 (-7.2, -3.1) < 0.0001
Apo A-I 2.6 -0.2 2.8 (1.0, 4.6) 0.0024
Apo B/apo A-I ratio -46.3 -39.6 -6.7 (-8.9, -4.6) < 0.0001
ITT: Intention to treat, CI: Confidence interval, LDL-C: Low-density lipoprotein cholesterol, TC: Total cholesterol, HDL-C: High-density lipoprotein cholesterol, TG: Triglycerides, Apo: Apolipoprotein, NS: Not statistically significant
Figure 3 Cumulative percentage of patients to 1998 European LDL-C goal of<3.0 mmol/L [7] by dose at 16 weeks. *p < 0.05 rosuvastatin 10–40 mg vs atorvastatin 10–80 mg RSV: Rosuvastatin, ATV: Atorvastatin, LDL-C: Low-density lipoprotein cholesterol
During the 4-week fixed-dose period, significantly more patients on rosuvastatin 10 mg had reached the 1998 European LDL-C goal compared with patients on atorvastatin 10 mg (figure 4). When data from the fixed-dose period were re-analysed to the more stringent 2003 European LDL-C goal of <2.5 mmol/L, 65% of patients receiving rosuvastatin 10 mg achieved goal compared with 33% of patients receiving atorvastatin 10 mg (p < 0.001; figure 4).
Figure 4 Percentage of patients to 1998 and 2003 European LDL-C goals [7,9] at 4 weeks. *p < 0.001 vs atorvastatin LDL-C: Low-density lipoprotein cholesterol
Rosuvastatin also reduced TC, non-HDL-C, LDL-C/HDL-C ratio, non-HDL-C/HDL-C ratio, and TC/HDL-C ratio significantly (p < 0.0001) more than atorvastatin after 4 weeks of treatment (table 3). Both treatments increased HDL-C and decreased TG from baseline to 4 weeks, but there were no statistically significant differences between the groups (table 3). In addition, rosuvastatin significantly reduced levels of apo B and the apo B/apo A-I ratio, and increased apo A-I levels compared with atorvastatin (p ≤ 0.05) (table 3). Similar significant effects on TC, non-HDL-C, apolipoproteins and lipid ratios were observed at 16 weeks (table 2).
Table 3 Percentage change from baseline in lipid variables at 4 weeks (ITT population)
Variable Least-squares mean percentage change from baseline to 4 weeks Difference (95% CI) p-value
Rosuvastatin 10 mg (n = 232) Atorvastatin 10 mg (n = 231)
LDL-C -47.6 -38.5a -9.1 (-11.4, -6.7) < 0.0001
TC -33.6 -27.9 -5.7 (-7.4, -4.0) < 0.0001
HDL-C 4.4 2.6 1.8 (-0.5, 4.0) NS
TG -19.2 -15.5 -3.7 (-9.5, 2.2) NS
Non-HDL-C -42.6 -35.0 -7.6 (-9.6, -5.7) < 0.0001
LDL-C/HDL-C ratio -49.3 -39.5 -9.8 (-12.2, -7.4) < 0.0001
Non-HDL-C/HDL-C ratio -44.4 -35.9 -8.5 (-10.8, -6.2) < 0.0001
TC/HDL-C ratio -35.8 -29.0 -6.7 (-8.7, -4.8) < 0.0001
Apo B -42.9 -35.3 -7.6 (-9.7, -5.6) < 0.0001
Apo A-I 2.6 0.8 1.8 (0, 3.5) 0.05
Apo B/apo A-I ratio -43.9 -35.4 -8.5 (-10.6, -6.4) < 0.0001
ITT: Intention to treat, CI: Confidence interval, LDL-C: Low-density lipoprotein cholesterol, TC: Total cholesterol, HDL-C: High-density lipoprotein cholesterol, TG: Triglycerides, Apo: Apolipoprotein, NS: Not statistically significant
an = 232
There was no statistically significant difference in UAE rate from baseline to study end, or between the treatment groups, including those patients with baseline microalbuminuria (UAE >20 μg/min).
Safety
Both treatments were well tolerated, with overall incidences of adverse events being similar between the treatment groups (51% with rosuvastatin, 53% with atorvastatin). A total of 10 patients experienced serious adverse events (two in the rosuvastatin group, eight in the atorvastatin group), none of which were considered by the investigator to be related to study treatment. Ten patients discontinued because of adverse events, three in the rosuvastatin group and seven in the atorvastatin group. There were no cases of myopathy. Myalgia was reported by 3.4% of the patients in the study; none of the cases were associated with a clinically important elevation in CK (>5 × ULN). Indeed, there were no clinically important elevations in CK in either group throughout the study and changes in CK were not related to dose of study medication or duration of treatment. The most frequent adverse events overall were nasopharyngitis, myalgia, and inadequately controlled diabetes mellitus (table 4). There were no clinically relevant changes in ALAT or ASAT (>3 × ULN).
Table 4 Adverse events occurring in ≥ 3% of patients in any treatment group
Number (%) of patients with adverse event
Adverse event Rosuvastatin (n = 233) Atorvastatin (n = 236)
Nasopharyngitis 23 (9.9) 19 (8.1)
Myalgia 13 (5.6) 7 (3.0)
Inadequately controlled diabetes mellitus 14 (6.0) 11 (4.6)
Constipation 9 (3.9) 6 (2.5)
Headache 6 (2.6) 7 (3.0)
Urinary tract infection 9 (3.9) 2 (0.9)
Arthralgia 1 (0.4) 9 (3.8)
Discussion
Rosuvastatin provided significantly greater LDL-C reductions than atorvastatin, both at the initial dose of 10 mg and also when titrated over the dose range of 10–40 mg for rosuvastatin and 10–80 mg for atorvastatin. In addition, a significantly higher percentage of patients treated with rosuvastatin achieved the 1998 European LDL-C goal (<3.0 mmol/L), both with the starting dose of 10 mg and after the period of dose titration. These results are consistent with the findings of studies in patients with hypercholesterolaemia that compared rosuvastatin with atorvastatin over 6 weeks [25], 8 weeks [31], 12 weeks [27,28], and 52-week dose titration [28].
Patients with type 2 diabetes commonly have a highly atherogenic lipid profile including elevated LDL-C, increased TG and low HDL-C, which is associated with a high risk of developing cardiovascular disease [32,33]. Statins are recognized as first-line therapy for cholesterol lowering, and their benefits have been shown to extend to patients with diabetes [18-22]. The present study was designed to reflect the treatment of diabetic dyslipidaemia in the clinical setting, in that statin treatment of patients was titrated upwards from the recommended starting dose to that required to achieve the 1998 European target of LDL-C <3.0 mmol/L. The population of the present study was compared with patients with type 2 diabetes in the Swedish National Diabetes Registry and was found to be consistent in terms of baseline characteristics such as age, HbA1c, body mass index, percentage of smokers, blood pressure, and antidiabetic medication [34].
New European guidelines published in 2003 recommend a more stringent target (LDL-C <2.5 mmol/L) [9] than that used when the present study was planned. Further analysis of the 4-week (fixed-dose) LDL-C data indicated that rosuvastatin 10 mg treated significantly more patients to the new 2003 European goal of <2.5 mmol/L than atorvastatin 10 mg. As expected, the absolute percentages of patients achieving the more stringent 2003 goal were lower than the absolute percentages achieving the 1998 goal at 4 weeks, but the greater efficacy of rosuvastatin 10 mg compared with atorvastatin 10 mg remained the same. As more clinical trial evidence becomes available regarding the positive effects of intensive lipid lowering among patients with diabetes, it is likely that even more stringent LDL-C goals will be recommended. Indeed, National Cholesterol Education Program Adult Treatment Panel III recommendations were recently reviewed and a target of LDL-C <70 mg/dL (1.8 mmol/L) was suggested as a therapeutic option for individuals considered to be at very high risk including those with both type 2 diabetes and established cardiovascular disease [35].
The availability of an agent that enables a large number of patients to achieve LDL-C goal at the starting dose is important given that many patients receiving lipid-lowering therapy fail to existing attain lipid targets due to a lack of dose titration and the use of less effective agents [36,37]. A recent observational study, designed to reflect dyslipidaemia treatment in the clinical setting, evaluated the number of hyperlipidaemic patients with coronary heart disease or diabetes who achieved LDL-C goal with their initial statin dose and whether patients were dose titrated [38]. Less than half (48%) achieved LDL-C <2.6 mmol/L with their initial dose and, of those who did not achieve goal, only 45% had their dose titrated. Dose titration increases costs and the need for follow-up, which, while necessary, can be time-consuming and inconvenient. The ability of rosuvastatin to enable greater proportions of patients to achieve LDL-C goal, with reduced requirement for dose titration is highly advantageous.
The benefits of reaching treatment goals have been demonstrated in the Steno-2 study [39], in which patients with type 2 diabetes were randomised to receive conventional treatment or intensive multifactorial intervention to strict treatment goals (including TC<4.5 mmol/L). LDL-C levels were reduced by 47% in those receiving intensive therapy, and the risk of both cardiovascular and microvascular events was reduced by approximately 50% compared with conventional treatment [39].
Rosuvastatin was also more effective than atorvastatin in reducing a range of other lipid variables, including TC, non-HDL-C, LDL-C/HDL-C ratio, non-HDL-C/HDL-C ratio, and TC/HDL-C ratio. Reductions in TC and/or TC/HDL-C are particularly relevant given that the Systemic Coronary Risk Evaluation (SCORE) system advocated in the new European guidelines uses these variables to estimate total risk [9].
In the present study, both treatments produced similar increases in HDL-C, which were lower than those observed previously. In the Measuring Effective Reductions in Cholesterol Using Rosuvastatin therapY (MERCURY I) study involving 3,161 patients with hypercholesterolaemia, 8 weeks' treatment with rosuvastatin 10 mg increased HDL-C by 9.2% and this was significantly greater than atorvastatin 10 mg (6.8%) and atorvastatin 20 mg (5.7%) (p < 0.01) [31]. In the current study, average baseline HDL-C values were higher than would be expected in the diabetic population, which could partly explain the relatively small increases in HDL-C compared with other studies [31,40].
In the present study, the main apolipoprotein in HDL-C, apo A-I, was significantly increased by rosuvastatin compared with atorvastatin (p < 0.05). In addition, significant reductions were also observed in apo B and apo B/apo A-I (p < 0.0001). Changes in apolipoprotein levels may have important implications in the reduction of cardiovascular risk, since results from the Apolipoprotein-related Mortality Risk (AMORIS) study indicate that apo B, apo A-I and apo B/apo A-I are powerful predictors of cardiac events [41]. Taken together with the other changes to lipid variables, the findings of the present study indicate that a less atherogenic lipid profile was achieved with rosuvastatin.
Treatment of diabetic dyslipidaemia may also reduce the incidence of microvascular disease including nephropathy [33]. Statins have been shown to have beneficial effects in diabetic nephropathy by reducing the rate of UAE [42,43]. In the present study, statin treatment did not significantly alter the rate of UAE; however, this may reflect the fact that the treatment period was relatively short. Previously, a reduced UAE rate with statin therapy has been observed after at least 6 months' treatment [42,43].
Both treatments were similarly well tolerated, with no unexpected safety concerns, and tolerability was similar to that previously observed in non-diabetic patient populations [40,44].
In conclusion, rosuvastatin was significantly more effective at reducing LDL-C and achieving European LDL-C goals both during the fixed-dose period and following dose titration than atorvastatin in patients with type 2 diabetes.
Competing interests
This study was supported by AstraZeneca, Södertälje, Sweden, which provided study expenses and covered the article processing charge. Annica Siewert-Delle is an employee of AstraZeneca.
Authors' contributions
Christian Berne and Annica Siewert-Delle participated in the design and coordination of the study and prepared the manuscript. Both authors read and approved the final manuscript.
Acknowledgements
We gratefully acknowledge the investigators, their co-investigators and study co-ordinators, and the patients who participated in this trial.
In addition to the authors of this publication, the following investigators participated in this trial: R Ekesbo, Dalby; L Fröberg, Höganäs; N Henningsen, Malmö; G Ilestam, Malmö; A Fahlbom, Malmö; J Nielsen, Skivarp; S Nordström, Knislinge; N Nörgaard, Höganäs; G Vatnaland, Ängelholm; A-C Knutsson, Ängelholm; J Wiuff, Oskarshamn; C Sjödin, Växjö; T Svensson, Växjö; G Tygesen, Lagan; O Benéus, Partille; L Benéus, Partille; L Lingetun, Falkenberg; I Wallin, Mölndal; J Alvång, Trollhättan; E Angesjö, Borås; P Hellke, Göteborg; L Nord, Stenungsund; C Andersson, Stenungsund; U Thorslund, Göteborg; M Öhberg, Skene; P E:son Jennersjö, Linköping; O Borgholst, Kungsör; B Cöster, Kristinehamn; G Holmberg, Karlstad; W Meyer, Köping; B Finger, Köping; R Baylis, Köping; E Sundequist-Stockhaus, Karlstad; P Sundin, Örebro; K Vetterskog, Västerås; J-E Andersson, Tyresö; G Widerström, Tyresö; A Bröijersen, Stockholm; B Thorsson, Stockholm; B Eriksson, Gustavsberg; H Noppa, Spånga; A Häggmark, Skärholmen; L Held, Skärholmen; H Salminen, Bagarmossen AB; P Nordström, Bagarmossen AB; R Zlatewa-Cuenca, Stockholm; L Hjelmaeus, Stockholm; E Hammarström, Stockholm; K Brismar, Stockholm; I Bäckström, Märsta; S Hellerstedt, Kungsbacka; L Håkansson, Norrtälje; A Lindh, Åkersberga; R-M Brinkeborn, Uppsala; T Lundmark, Kilafors; U Sundström, Kilafors; R Malmström, Sandviken; E Tönnesen, Uppsala; E Edén, Uppsala; K Åresund, Gävle; O Berglund, Umeå; K Henriksson, Krokom; L Lönneborg, Sundsbruk; M Mullaart, Sundsbruk; P Malm, Östersund; G Strömberg, Trehörningsjö; T Lindén, Västra Frölunda.
==== Refs
Wild S Roglic G Green A Sicree R King H Global prevalence of diabetes: estimates for the year 2000 and projections for 2030 Diabetes Care 2004 27 1047 1053 15111519
Laakso M Cardiovascular disease in type 2 diabetes: challenge for treatment and prevention J Intern Med 2001 249 225 235 11285042 10.1046/j.1365-2796.2001.00789.x
Herlitz J Malmberg K Karlson BW Ryden L Hjalmarson A Mortality and morbidity during a five-year follow-up of diabetics with myocardial infarction Acta Med Scand 1988 224 31 38 3046232
Norhammar A Malmberg K Ryden L Tornvall P Stenestrand U Wallentin L Under utilisation of evidence-based treatment partially explains for the unfavourable prognosis in diabetic patients with acute myocardial infarction Eur Heart J 2003 24 838 844 12727151 10.1016/S0195-668X(02)00828-X
Kleinman JC Donahue RP Harris MI Finucane FF Madans JH Brock DB Mortality among diabetics in a national sample Am J Epidemiol 1988 128 389 401 3394705
Haffner SM Statin therapy for the treatment of diabetic dyslipidemia Diabetes Metab Res Rev 2003 19 280 287 12879405 10.1002/dmrr.393
Wood D De Backer G Faergeman O Graham I Mancia G Pyörälä K Prevention of coronary heart disease in clinical practice. Recommendations of the second joint task force of European and other societies on coronary prevention Eur Heart J 1998 19 1434 1503 9820987 10.1053/euhj.1998.1243
European Diabetes Policy Group A desktop guide to type 2 diabetes mellitus Diabet Med 1999 16 716 730 10510947 10.1046/j.1464-5491.1999.00166.x
De Backer G Ambrosioni E Borch-Johnsen K Brotons C Cifkova R Dallongeville J Ebrahim S Faergeman O Graham I Mancia G Cats VM Orth-Gomer K Perk J Pyörälä K Rodicio JL Sans S Sansoy V Sechtem U Silber S Thomsen T Wood D European Society of Cardiology Committee for Practice Guidelines European guidelines on cardiovascular disease prevention in clinical practice: third joint task force of European and other societies on cardiovascular disease prevention in clinical practice Eur J Cardiovasc Prev Rehabil 2003 10 S1 S78 14555889
American Diabetes Association Management of dyslipidemia with diabetes Diabetes Care 2002 25 S74 S77
Expert Panel on Detection, Evaluation and Treatment of High Blood Cholesterol in Adults Executive summary of the third report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation and treatment of high blood cholesterol in adults (Adult Treatment Panel III) JAMA 2001 285 2486 2497 11368702 10.1001/jama.285.19.2486
Scandinavian Simvastatin Survival Study (4S) Randomised trial of cholesterol lowering in 4444 patients with coronary heart disease: the Scandinavian Simvastatin Survival Study (4S) Lancet 1994 344 1383 1389 7968073
Shepherd J Cobbe SM Ford I Isles CG Lorimer AR MacFarlane PW McKillop JH Packard CJ Prevention of coronary heart disease with pravastatin in men with hypercholesterolemia. West of Scotland Coronary Prevention Study Group N Engl J Med 1995 333 1301 1307 7566020 10.1056/NEJM199511163332001
Sacks FM Pfeffer MA Moye LA Rouleau JL Rutherford JD Cole TG Brown L Warnica JW Arnold JM Wun CC Davis BR Braunwald E The effect of pravastatin on coronary events after myocardial infarction in patients with average cholesterol levels N Engl J Med 1996 335 1001 1009 8801446 10.1056/NEJM199610033351401
The Long-term Intervention with Pravastatin in Ischaemic Disease (LIPID) Study Group Prevention of cardiovascular events and death with pravastatin in patients with coronary heart disease and a broad range of initial cholesterol levels N Engl J Med 1998 339 1349 1357 9841303 10.1056/NEJM199811053391902
Downs JR Clearfield M Weis S Whitney E Shapiro DR Beere PA Langendorfer A Stein EA Kruyer W Gotto AM Jr Primary prevention of acute coronary events with lovastatin in men and women with average cholesterol levels. Results of AFCAPS/TexCAPS JAMA 1998 279 1615 1622 9613910 10.1001/jama.279.20.1615
Sever PS Dahlof B Poulter NR Wedel H Beevers G Caulfield M Collins R Kjeldsen SE Kristinsson A McInnes GT Mehlsen J Nieminen M O'Brien E Ostergren J ASCOT investigators Prevention of coronary and stroke events with atorvastatin in hypertensive patients who have average or lower-than-average cholesterol concentrations, in the Anglo-Scandinavian Cardiac Outcomes Trial-Lipid Lowering Arm (ASCOT-LLA): a multicentre randomised controlled trial Lancet 2003 361 1149 1158 12686036 10.1016/S0140-6736(03)12948-0
Pyörälä K Pedersen TR Kjekshus J Faergeman O Olsson AG Thorgeirsson G Cholesterol lowering with simvastatin improves prognosis of diabetic patients with coronary heart disease. A subgroup analysis of the Scandinavian Simvastatin Survival Study (4S) Diabetes Care 1997 20 614 620 9096989
Goldberg RB Mellies MJ Sacks FM Moye LA Howard BV Howard WJ Davis BR Cole TG Pfeffer MA Braunwald E Cardiovascular events and their reduction with pravastatin in diabetic and glucose-intolerant myocardial infarction survivors with average cholesterol levels: subgroup analyses in the Cholesterol And Recurrent Events (CARE) trial Circulation 1998 98 2513 2519 9843456
Keech A Colquhoun D Best J Kirby A Simes RJ Hunt D Hague W Beller E Arulchelvam M Baker J Tonkin A LIPID Study Group Secondary prevention of cardiovascular events with long-term pravastatin in patients with diabetes or impaired fasting glucose: results from the LIPID trial Diabetes Care 2003 26 2713 2721 14514569
Collins R Armitage J Parish S Sleigh P Peto R Heart Protection Study Collaborative Group MRC/BHF Heart Protection Study of cholesterol-lowering with simvastatin in 5963 people with diabetes: a randomised placebo-controlled trial Lancet 2003 361 2005 2016 12814710 10.1016/S0140-6736(03)12475-0
Colhoun HM Betteridge DJ Durrington PN Hitman GA Neil HA Livingstone SJ Thomason MJ Mackness MI Charlton-Menys V Fuller JH CARDS investigators Primary prevention of cardiovascular disease with atorvastatin in type 2 diabetes in the Collaborative Atorvastatin Diabetes Study (CARDS): multicentre randomized placebo-controlled trial Lancet 2004 364 685 696 15325833 10.1016/S0140-6736(04)16895-5
del Canizo-Gomez FJ Moreira-Andres MN Cardiovascular risk factors in patients with type 2 diabetes. Do we follow the guidelines? Diabetes Res Clin Pract 2004 65 125 133 15223224 10.1016/j.diabres.2003.12.002
Betteridge JD Leiter LA AUDIT Investigators The AUDIT Study: regional variations in physicians attitudes to diabetic dyslipidaemia Diabetologia 2004 47 A73
Jones PH Davidson MH Stein EA Bays HE McKenney JM Miller E Cain VA Blasetto JW STELLAR Study Group Comparison of the efficacy and safety of rosuvastatin versus atorvastatin, simvastatin and pravastatin across doses (STELLAR) trial Am J Cardiol 2003 92 152 160 12860216 10.1016/S0002-9149(03)00530-7
Kritharides L Reducing low-density lipoprotein cholesterol – treating to target and meeting new European goals Eur Heart J 2004 6 A1 A7
Davidson M Ma P Stein EA Gotto AM JrRaza A Chitra R Hutchinson H Comparison of effects on low-density lipoprotein cholesterol and high-density lipoprotein cholesterol with rosuvastatin versus atorvastatin in patients with type IIa or IIb hypercholesterolemia Am J Cardiol 2002 89 268 275 11809427 10.1016/S0002-9149(01)02226-3
Olsson AG Istad H Luurila O Ose L Stender S Tuomilehto J Wiklund O Southworth H Pears J Wilpshaar JW Rosuvastatin Investigators Group Effects of rosuvastatin and atorvastatin compared over 52 weeks of treatment in patients with hypercholesterolemia Am Heart J 2002 144 1044 1051 12486429 10.1067/mhj.2002.128049
Strandberg TE Feely J Sigurdsson EL Twelve-week, multicenter, randomized, open-label comparison of the effects of rosuvastatin 10 mg/d and atorvastatin 10 mg/d in high-risk adults: A DISCOVERY study Clin Therapeut 2004 26 1821 1833 10.1016/j.clinthera.2004.11.015
Schuster H Fox JC Investigating cardiovascular risk reduction – the rosuvastatin GALAXY programme Expert Opin Pharmacother 2004 5 1187 1200 15155117
Schuster H Barter PJ Stender S Cheung RC Bonnet J Morrell JM Watkins C Kallend D Raza A Effective Reductions in Cholesterol Using Rosuvastatin Therapy I study group Effects of switching statins on achievement of lipid goals: Measuring Effective Reductions in Cholesterol Using Rosuvastatin Therapy (MERCURY I) study Am Heart J 2004 147 705 713 15077101 10.1016/j.ahj.2003.10.004
Turner RC Millns H Neil HA Stratton IM Manley SE Matthews DR Holman RR Risk factors for coronary artery disease in non-insulin dependent diabetes mellitus: United Kingdom prospective diabetes study (UKPDS:23) BMJ 1998 316 823 828 9549452
Krentz AJ Lipoprotein abnormalities and their consequences for patients with type 2 diabetes Diabetes Obes Metab 2003 5 S19 27 14984018 10.1046/j.1462-8902.2003.0310.x
Gudbjörnsdottir S Cederholm J Nilsson PM Eliasson B Steering Committee of the Swedish National Diabetes Register The National Diabetes Register in Sweden: an implementation of the St. Vincent Declaration for Quality Improvement in Diabetes Care Diabetes Care 2003 26 1270 1276 12663609
Grundy SM Cleeman JI Merz CN Brewer HB JrClark LT Hunninghake DB Pasternak RC Smith SC JrStone NJ National Heart, Lung, and Blood Institute; American College of Cardiology Foundation; American Heart Association Implications of recent clinical trials for the National Cholesterol Education Program Adult Treatment Panel III guidelines Circulation 2004 110 227 239 15249516 10.1161/01.CIR.0000133317.49796.0E
Pearson TA Laurora I Chu H Kafonek S The Lipid Treatment Assessment Project (L-TAP). A multicenter survey to evaluate the percentages of dyslipidemic patients receiving lipid-lowering therapy and achieving low-density lipoprotein cholesterol goals Arch Intern Med 2000 160 459 467 10695686 10.1001/archinte.160.4.459
EUROASPIRE II Study Group Lifestyle and risk factor management and use of drug therapies in coronary patients from 15 countries: principal results from EUROASPIRE II Eur Heart J 2001 22 554 572 11259143 10.1053/euhj.2001.2610
Foley KA Simpson RJ JrCrouse JR 3rdWeiss TW Markson LE Alexander CM Effectiveness of statin titration on low-density lipoprotein cholesterol goal attainment in patients at high risk of atherogenic events Am J Cardiol 2003 92 79 81 12842255 10.1016/S0002-9149(03)00474-0
Gaede P Vedel P Larsen N Jensen GV Parving HH Pedersen O Multifactorial intervention and cardiovascular disease in patients with type 2 diabetes N Engl J Med 2003 348 383 393 12556541 10.1056/NEJMoa021778
Olsson AG McTaggart F Raza A Rosuvastatin: a highly effective new HMG-CoA reductase inhibitor Cardiovasc Drug Rev 2002 20 303 328 12481202
Walldius G Jungner I Holme I Aastveit AH Kolar W Steiner E High apolipoprotein B, low apolipoprotein A-I, and improvement in the prediction of fatal myocardial infarction (AMORIS study): a prospective study Lancet 2001 358 2026 2033 11755609 10.1016/S0140-6736(01)07098-2
Tonolo G Ciccarese M Brizzi P Puddu L Secchi G Calvia P Atzeni MM Melis MG Maioli M Reduction of albumin excretion rate in normotensive microalbuminuric type 2 diabetic patients during long-term simvastatin treatment Diabetes Care 1997 20 1891 1895 9405913
Nakamura T Ushiyama C Hirokawa K Osada S Shimada N Koide H Effect of cerivastatin on urinary albumin excretion and plasma endothelin-1 concentrations in type 2 diabetes patients with microalbuminuria and dyslipidemia Am J Nephrol 2001 21 449 454 11799261 10.1159/000046648
Rosenson RS Rosuvastatin: a new inhibitor of HMG-CoA reductase for the treatment of dyslipidemia Expert Rev Cardiovasc Ther 2003 1 495 505 15030249 10.1586/14779072.1.4.495
| 15935095 | PMC1166567 | CC BY | 2021-01-04 16:25:03 | no | Cardiovasc Diabetol. 2005 Jun 3; 4:7 | utf-8 | Cardiovasc Diabetol | 2,005 | 10.1186/1475-2840-4-7 | oa_comm |
==== Front
Cardiovasc UltrasoundCardiovascular Ultrasound1476-7120BioMed Central London 1476-7120-3-131591670210.1186/1476-7120-3-13ReviewEconomic and biological costs of cardiac imaging Picano Eugenio [email protected] CNR, Institute of Clinical Physiology, Pisa, Italy2005 25 5 2005 3 13 13 16 5 2005 25 5 2005 Copyright © 2005 Picano; licensee BioMed Central Ltd.2005Picano; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Medical imaging market consists of several billion tests per year worldwide. Out of these, at least one third are cardiovascular procedures. Keeping in mind that each test represents a cost, often a risk, and a diagnostic hypothesis, we can agree that every unnecessary and unjustifiable test is one test too many. Small individual costs, risks, and wastes multiplied by billions of examinations per year represent an important population, society and environmental burden. Unfortunately, the appropriateness of cardiac imaging is extra-ordinarily low and there is little awareness in patients and physicians of differential costs, radiological doses, and long term risks of different imaging modalities. For a resting cardiac imaging test, being the average cost (not charges) of an echocardiogram equal to 1 (as a cost comparator), the cost of a CT is 3.1x, of a SPECT 3.27x, of a Cardiovascular Magnetic Resonance imaging 5.51x, of a PET 14.03x, and of a right and left heart catheterization 19.96x. For stress cardiac imaging, compared with the treadmill exercise test equal to 1 (as a cost comparator), the cost of stress echocardiography is 2.1x and of a stress SPECT scintigraphy is 5.7x. Biohazards and downstream long-term costs linked to radiation-induced oncogenesis should also be considered. The radiation exposure is absent in echo and magnetic resonance, and corresponds to 500 chest x rays for a sestamibi cardiac stress scan and to 1150 chest x rays for a thallium scan. The corresponding extra-risk in a lifetime of fatal cancer is 1 in 2000 exposed patients for a sestamibi stress and 1 in 1000 for a thallium scan. Increased awareness of economic, biologic, and environmental costs of cardiac imaging will hopefully lead to greater appropriateness, wisdom and prudence from both the prescriber and the practitioner. In this way, the sustainability of cardiac imaging will eventually improve.
==== Body
The unbearable lightness of being [a cardiac imaging specialist]
A Renaissance of cardiac imaging occurred in the 1980s [1]. New technologies allowed the non-invasive description of cardiac function, perfusion, and metabolism in a polychrome, three-dimensional, overwhelming fashion. Almost unlimited resources were devoted to patient care in the economic framework of the affluent society. At the beginning of the 1990s, The Renaissance made its transition into the splendid decadence of the Baroque. The increasing technological burden in clinical cardiology paradoxically did not bring a parallel increase in the quality of care but rather an increase in cost. The economic climate had changed; the illusion of unlimited economic resources had come to an end [2]. Keeping in mind that each test represents a cost, often a risk, and always a diagnostic hypothesis, we can agree that every unnecessary and unjustifiable test is one test too many. Small individual costs, risks, and wastes multiplied by billions of examinations per year represent an important population [3], society [4] and environmental [5] burden. Unfortunately, the appropriateness of cardiac imaging is usually extra-ordinarily low and there is little awareness among patients and physicians of the elementary physical basis, differential costs, radiological doses, and long term risks of different imaging modalities [6]. It is also well known that – in the words of Bernard Lown – "technology in medicine is frequently untested scientifically, often applied without data relating to cost benefit, and driven by market forces rather than by patient needs." Bernard Lown, 2004 [7].
The cost of cardiac imaging
"Ten years ago, medical imaging wasn't even in the radar screen for most health insurers. In 2004, it' s one of the highest cost items in a health plan's medical budget, and also one of the fastest growing". (Atlantic info service newsletter, 2004) [8]. As an example, in U.S. during the year 2002, 7.8 million cardiac perfusion scans were performed, with a growth of 40% in the last 3 years [9]. Still in U.S., about 10 million CT scans were done in 1993, and about 60 millions in 2001 [10]. Booz Allen Hamilton projects that spending on diagnostic imaging could grow 28 % by 2005, with utilization growing by 9% per year. No doubt that any assessment of costs of medical imaging should also include the often unquestionable downstream benefits, leading to a reduction of overall costs due to more disabling disease prevented. For instance, ultrasound screening for abdominal aneurysms can reduce the risk of death by more than 50 % in men aged 65–74. When projected to 10 years, that screening costs 13.000 dollars per life year gained – a highly favourable result in terms of cost-effectiveness [11]. However, it is beyond question that the explosion in imaging costs is also driven by a number of factors which not always improve the cost-effectiveness. High patient demand for the newest diagnostic tests, physicians eager to use the most effective technologies, and possibly even some providers who may boost utilization to help pay off investments in high-tech equipment. All too often physicians may not have adequate controls on the number of high cost imaging tests they are ordering. For a resting cardiac imaging test, being the average cost (not charges) of an echocardiogram equal to 1 (as a cost comparator), the cost of a CT is 3.1x, of a SPECT 3.27x, of a Cardiovascular Magnetic Resonance imaging 5.51x, of a PET 14.03x, and of a right and left heart catheterization 19.96x (Fig 1) [12]. For stress cardiac imaging, compared with the treadmill exercise test equal to 1 [as a cost comparator], the cost of stress echocardiography is 2.1x and of a stress SPECT scintigraphy is 5.7x [13]. Obviously, the evaluation of costs of medical imaging should also imply the entire clinical context (pre-test likelihood of disease, basic risk profile, target of stress testing, socio-economic characteristics of the health care system, etc.) to be taken into account. Some measures of precision and/or dispersion of each modality as compared to echocardiography may provide a more comprehensive information in the specific health care milieu where these tests are actually performed.
Figure 1 The average costs of CMR and other common cardiac imaging procedures when compared 2 D echocardiography (modified from Pennell, ref. 12).
The individual and social risks of imaging
Current protection standard and practices are based on the premise that any ionising radiation dose, no matter how small, can result in detrimental health effects [14]. These include long-term development of cancer and genetic damage [15]. For the purposes of radiation protection, the dose-response curve for radiation-induced cancer is assumed to be linear at low doses, with no minimum threshold [16]: (Fig. 2). The dose of 50 chest X rays (for example, a lung scintigraphy) corresponds to an extra-risk of cancer of about 1 in 20,000 exposed patients. The dose of 500 chest x rays (such as technetium sestamibi scan) corresponds to an extra-risk of about 1 in 2000 exposed patients. The dose of 1 000 chest x rays (associated with a Thallium scan) corresponds to an extra risk of cancer of about 1 in 1 000 exposed patients [17]. The radiation dose and risk associated with some common imaging examinations are expressed in Table 1 as equivalent dose of natural yearly background radiation, extra-risk of fatal cancer in the lifetime and lost life expectancy per exam [18]. Presented data refer to the best available estimates from the radiological Commission of Radiation Protection and conform to their suggested standards for communicating risk to patients. These estimations are a benchmark for the physicians and are incorporated in the European Commission guidelines for medical imaging. These small individual risks multiplied by billion examinations become significant population risk.
Figure 2 Presentation of cancer risk and radiation dose (in multiples of dose from a simple chest x rays) for some common radiological and nuclear medicine examinations (Modified from Picano E, ref. 37)
Table 1 Radiation doses and estimated cancer risk from common radiological examinations and isotope scans
Type of test Effective radiation dose (mSv) Equivalent period of natural background radiation Lifetime additional risk of cancer/examination Lost life expectancy Equivalent n. of chest x-rays
Chest radiograph 0.01 A few days Negligible risk 2 minutes 1
Skull radiograph 0.1 A few weeks Minimal risk (1 in 100,000 to 1 in1,000,000) 20 minutes 5
Lung isotope scan 1 A few months to a year Very low risk (1 in 10,000 to 1 in 100,000) 3 hrs 50
Cardiac gated study 10 A few years
(4 years) Low risk
(1 in 2,000) 2 days 500
Thallium scan 20 (8 years) (1 in 1,000) 4 days 1000
Use of radiation for medical examinations and test is the largest manmade source of radiation exposure. The medical sources of radiation were about one fifth of the natural radiation in 1987 [18], close to one-half in 1993 [19], and almost 100% of natural radiation in 1997 [20], and the use of procedures with a high load of radiation continues to grow steadily [21].
This impressive amount of ionizing friendly fire translates into a significant population risk. Lifetime risk of developing cancer attributable to diagnostic X-rays is 0.6–3.2% in developed countries [22]. The numbers are striking, but underestimate the biological population burden of medical radiation for three reasons. First, they refer to the radiological volume of 10 years ago – substantially lower than the current radiological volume. Second, they do not consider the practice of nuclear medicine, which adds a further 10 % to the global radiation burden. Third, in addition to the risk of cancer, one should consider the burden of teratogenesis. The risk of radiation – induced damage passed onto the offspring is estimated to represent a fifth of the risk of fatal cancer [23].
Unawareness in imaging
Several recent studies clearly prove that not only general practitioners but also cardiologists, orthopaedics and even radiologists and nuclear physicians usually ignore the dose and the risk of what they do: and the more they do, the more they tend to ignore [24-28]. Radiologists working in an academic US environment frequently underestimate of 100 to 500 times the dose of a common CT and 97 % of UK doctors underestimate of sixteen times the dose of a common CT chest scan. In 1 case out of 10, doctors believe that magnetic resonance employs ionising radiations, and 1 case out of 20 that ultrasound employs ionising radiation [25,27]. The majority of doctors, and even of radiologists, is not aware of the oncogenic risk of common, high dose radiological examinations [26,28]. The vast majority of cardiologists underestimates of 200 up to 1000 times the dose of a stress cardiac perfusion scintigraphy [28]: Figure 3. This unawareness generates inappropriateness, which is an endemic and pervasive disease in the world of cardiac imaging. We need more prudence, wisdom and responsibility in indicating and performing (cardiac) imaging tests. Prudence and responsibility should obviously be especially high for more expensive tests, greater for those exposing the patient to significant ionizing radiation [29], and greatest in special subset particularly vulnerable to the damaging effects of ionizing radiation, such as women in reproductive age [30] and children [31-33].
Figure 3 What cardiologists know about dose of a test they prescribe and/ or perform daily. 2 out of 3 physicians underestimate of 100 to 500 times the dose of a cardiac scintigraphy. The dose is equivalent to 500 chest x rays with technetium sestamibi, and to more than 1000 chest x rays with thallium scan (modified from Correia et al, ref 28)
From benefit to risk-benefit
According to the International Commission of Radiological Protection "Medical exposure is the only category in which large reductions in average dose are possible, and it is therefore highly desirable to reduce applications of medical radiation which are of no benefit to the patients and to minimise useless radiation in the course of medical examinations" [34]
In other words it is desirable to adopt a radiation sparing strategy not only for the physician and the patients but also for the society and the environment. Nuclear medicine and X-ray procedures are intended, as stated by the United Nations Annex on Medical Exposures, "to provide doctors with diagnostic information and in principle conducted with the lowest practicable levels of patient dose to meet clinical objectives" [5]. The clinical counterpart of this concept is that it is not enough that a test is marginally "better" than the other to justify its use: the extra-value should be proportional to the extra-cost and to the extra-risk. Both the physician and the patient should be well aware of the different individual risks and social costs posed by different diagnostic options. As recently stated by guidelines on fluoroscopically guided invasive cardiovascular procedures, " the core principle governing the use of ionizing radiation is ALARA (as low as reasonably achievable). The ALARA principle recognizes that there is no magnitude of radiation exposure that is known to be completely safe. This principle confers a responsibility on all physicians to minimize the radiation injury hazard to their patients, to their professional staff, and to themselves" [35]. If the information is comparable, every effort should be done to orient the patient towards non-ionizing testing. If it is true that "local expertise and availability should guide the selection of imaging techniques" [36], it is also true that the doses and risks associated with the different diagnostic options should be clearly spelled out to allow the patient and the prescriber to make an informed decision. This policy is encouraged by common sense [37], deontologic code [38], European Commission imaging guidelines [14] and the European law [39]. It propels to use a green technique whenever the information supplied is grossly comparable to the red one [40].
The basic concept underlying this cardiac imaging paradigm shift is obvious but is presently neglected. Medical images of heartbreaking beauty when considering the benefit, can be ambiguous when considering the cost-benefit relationship, and unacceptable when considering the risk-benefit. In this transition, we as physicians and imaging specialists, are the critical link. "Health professionals involved in the processes of diagnosis and treatment are the critical link. Training them properly and ensuring intensive information exchange among them are, therefore, probably the most cost-effective ways of achieving patient safety" [4]. (International Action Plan for the radiological Protection of patients).
==== Refs
Roelandt J Sutherland GR Hugenholtz PG The 1980 Renaissance in the cardiac imaging: the role of ultrasound Eur Heart J 1989 10 680 683 2792110
Reicheck N Laennaec and technology: prescription for the year 2000 Circulation 88 1993 1F 1G
Gofman JW Radiation from Medical Procedures in the Pathogenesis of Cancer and Ischemic Heart Disease: Dose-Response Studies with Physicians per 100,000 Population San Francisco, Committee for Nuclear Responsibility Books, Available at UCSF Med Library The Exec 1999
National Research Council [U.S.] Committee on Biological Effects of Ionizing Radiations Health effects of exposure to low levels of ionizing radiation: BEIR V/Committee on Biological Effects of Ionizing Radiations Board of Radiation Effects Research, Commission on Life Science, National Research Council 1990 Washington, DC: National Academy Press
United Nations Scientific Committee on the Sources and Effects of Ionising Radiation Report on the effects of atomic radiation to the general assembly, 2000 Medical radiation exposures New York 2001
Lown B A Cardiologist's Perspective on the Crisis and Challenges of Biotechnology Based on an address delivered at the 5th International Heart Health Conference in Milan, Italy June 16, 2004
Herzog P Rieger CT Risk of cancer from diagnostic X-rays Lancet 2004 363 340 341 15070557 10.1016/S0140-6736(04)15470-6
Atlantic Information services Controlling the soaring costs of medical imaging June 15, 2004
Des Plaines IL IMV Medical Information Division Nuclear medicine Census Market summary report 2003
Kalra MK Maher MM Saini S CT radiation exposure: rationale for concern and strategies for dose reduction Proc SCBT/MR 2003 7 45 54
Multicentre aneurysm screening study [MASS] Cost effectiveness analysis of screening for abdominal aortic aneurysms based on four year results from randomised controlled trial British Medical Journal 2002 325 1135 12433761
Pennell DJ Sechtem UP Higgins CB Manning WJ Pohost GM Rademakers FE van Rossum AC Shaw LJ Yucel EK Society for Cardiovascular Magnetic Resonance; Working Group on Cardiovascular Magnetic Resonance of the European Society of Cardiology Clinical indications for cardiovascular magnetic resonance [CMR]: Consensus Panel report Eur Heart J 2004 25 1940 1965 15522474 10.1016/j.ehj.2004.06.040
Gibbons RJ Abrams J Chatterjee K Daley J Deedwania PC Douglas JS Ferguson TB JrFihn SD Fraker TD JrGardin JM O'Rourke RA Pasternak RC Williams SV American College of Cardiology; American Heart Association Task Force on practice guidelines (Committee on the Management of Patients With Chronic Stable Angina) ACC/AHA 2002 guideline update for the management of patients with chronic stable angina-summary article: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines J Am Coll Cardiol 2003 41 159 168 12570960 10.1016/S0735-1097(02)02848-6
European Commission on Radiation protection 118 Referral guidelines for imaging accessed 23 July 2004
International Commission on Radiation Protection Radiation and your patient: a guide for medical practitioners. A web module produced by Committee 3 of the International Commission on Radiological Protection 2001 United Kingdom: Pergamon Press
International Commission on Radiological Protection Radiological protection in in Biomedical Research 1991 United Kingdom: Pergamon press
Cormack J Towson JEC Flower MA Murray IPC, Ell PG Radiation Protection and dosimetry in clinical practice Nuclear Medicine in Clinical Diagnosis and treatment 1998 Churchill Livingstone 1655
National Council on Radiation Protection and Measurements Ionising radiation exposure of the population of the United States (Report No 93) 1987 Bethesda, MA: NCRP
United Nations Scientific Committee on the Sources and Effects of Ionising Radiation Report on the effects of atomic radiation to the general assembly, 2000 Medical radiation exposures New York 2001
Regulla D Griebel J Nosske D Bauer B Brix G Acquisition and assessment of patient exposure in diagnostic radiology and nuclear medicine Z Med Phys 2003 13 127 135 12868339
Picano E Sustainability of medical imaging. Education and Debate BMJ 2004 328 578 580 15001510 10.1136/bmj.328.7439.578
Berrington de Gonzalez A Darby S Risk of cancer from diagnostic X-rays: estimates for the UK and 14 other countries The Lancet 2004 363 345 51 15070562 10.1016/S0140-6736(04)15433-0
Picano E. Risk of cancer from diagnostic X-rays. Letter The Lancet 2004 363 1909 1910 15183641 10.1016/S0140-6736(04)16373-3
Finestone A Schlesinger T Amir H Richter E Milgrom C Do physicians correctly estimate radiation risks from medical imaging? Arch Environ Health 2003 58 59 61 12747521
Shiralkar S Rennie A Snow M Galland RB Lewis MH Gower-Thomas K Doctors' knowledge of radiation exposure: questionnaire study BMJ 2003 327 371 2 12919987 10.1136/bmj.327.7411.371
Lee CI Haims AH Monico EP Brink JA Forman HP Diagnostic CT scans: assessment of patient, physician, and radiologist awareness of radiation dose and possible risks Radiology 2004 231 393 398 15031431
Jacob K Vivian G Steel JR X-ray dose training: are we exposed to enough? Clin Radiol 2004 59 928 934 15451354 10.1016/j.crad.2004.04.020
Correia MJ Hellies A Ghelarducci B Picano E Lack of Radiological Awareness in a Tertiary Care Cardiological Centre Int J Cardiol 2005 100 354 358
Lattanzi F Magnani M Cortigiani L Mandorla S Zuppiroli A Evaluation of appropriateness of prescribing echocardiography Italian Heart J 2002 3 613 618
The Swedish International Commission on Radiation Protection Project Report 2002 National Medicine System. Valuing quality of life impact progress with the economic equivalents model
FDA Public Health Notification Reducing radiation risk from computed tomography for paediatric and small adult patients November 2, 2001
Brenner DJ Radiation risks potentially associated with low-dose CT screening of adult smokers for lung cancer Radiology 2004 231 440 445 15128988
Hall EJ Radiobiology for the Radiologist 2000 5 Lippincott Williams & Wilkins, Philadelphia PA
International atomic Energy Agency International Action Plan on the Radiological Protection of Patients 2002 IAEA, Vienna
Hirshfeld JW JrBalter S Brinker JA Kern MJ Klein LW Lindsay BD Tommaso CL Tracy CM Wagner LK ACCF/AHA/HRS/SCAI Clinical Competence Statement on Physician Knowledge to Optimize Patient Safety and Image Quality in Fluoroscopically Guided Invasive Cardiovascular Procedures: A Report of the American College of Cardiology Foundation/American Heart Association/American College of Physicians Task Force on Clinical Competence and Training Circulation 2005 111 511 532 15687141 10.1161/01.CIR.0000157946.29224.5D
Mieres JH Shaw LJ Arai A Budoff MJ Flamm SD Hundley WG Marwick TH Mosca L Patel AR Quinones MA Redberg RF Taubert KA Taylor AJ Thomas GS Wenger NK Cardiac Imaging Committee, Council on Clinical Cardiology, and the Cardiovascular Imaging and Intervention Committee, Council on Cardiovascular Radiology and Intervention, American Heart Association Role of noninvasive testing in the clinical evaluation of women with suspected coronary artery disease: consensus statement from the Cardiac Imaging Committee, Council on Clinical Cardiology, and the Cardiovascular Imaging and Intervention Committee, Council on Cardiovascular Radiology and Intervention, American Heart Association Circulation 2005 111 682 696 15687114 10.1161/01.CIR.0000155233.67287.60
Picano E Informed consent and communication of risk from radiological and nuclear medicine examinations. Education and debate BMJ 2004 329 678 681 10.1136/bmj.329.7470.849
ABIM Foundation. American Board of Internal Medicine; ACP-ASIM Foundation. American College of Physicians-American Society of Internal Medicine. European Federation of Internal Medicine Medical professionalism in the new millennium: a physician charter Ann Intern Med 2002 136 243 246 11827500
Council Directive 97/43/Euratom of 30 June 1997 on health protection of individuals against the dangers of ionising radiation in relation to medical exposure, and repealing Directive 84/466/Euratom Official Journal of the European Communities L 180 0022 0027 09/07/1997
Picano E Stress echocardiography: a historical perspective. [Special Article] Am J Med 2003 114 126 130 12586232 10.1016/S0002-9343(02)01427-4
| 15916702 | PMC1166568 | CC BY | 2021-01-04 16:38:32 | no | Cardiovasc Ultrasound. 2005 May 25; 3:13 | utf-8 | Cardiovasc Ultrasound | 2,005 | 10.1186/1476-7120-3-13 | oa_comm |
==== Front
Curr Control Trials Cardiovasc MedCurrent Controlled Trials in Cardiovascular Medicine1468-67081468-6694BioMed Central 1468-6708-6-101591890110.1186/1468-6708-6-10ResearchExercise training improves aerobic endurance and musculoskeletal fitness in female cardiac transplant recipients Haykowsky Mark [email protected] Kenneth [email protected] Linda [email protected] Daniel [email protected] Darren [email protected] Lee [email protected] Wayne [email protected] Faculty of Rehabilitation Medicine, University of Alberta, Edmonton, Alberta, Canada2 Division of Cardiology, Faculty of Medicine, University of Alberta, Edmonton, Alberta, Canada3 School of Human Kinetics, University of British Columbia, Vancouver, British Columbia, Canada4 Program of Cancer Prevention Detection and Control, Duke University Medical Center, Durham, North Carolina, USA2005 26 5 2005 6 1 10 10 10 5 2005 26 5 2005 Copyright © 2005 Haykowsky et al; licensee BioMed Central Ltd.2005Haykowsky et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Aim
Female cardiac transplant recipients' aerobic capacity is 60% lower than sex and age-predicted values. The effect of exercise training on restoring the impaired aerobic endurance and muscle strength in female cardiac transplant recipients is not known. This study examined the effect that aerobic and strength training have on improving aerobic endurance and muscle strength in female cardiac transplant recipients.
Methods
20 female cardiac transplant recipients (51 ± 11 years) participated in this investigation. The subjects performed a baseline six-minute walk test and a leg-press strength test when they were discharged following cardiac transplantation. The subjects then participated in a 12-week exercise program consisting of aerobic and lower extremity strength training. Baseline assessments were repeated following completion of the exercise intervention.
Results
At baseline, the cardiac transplant recipients' aerobic endurance was 50% lower than age-matched predicted values. The training program resulted in a significant increase in aerobic endurance (pre-training: 322 ± 104 m vs. post-training: 501 ± 99 m, p < 0.05) and leg-press strength (pre-training: 48 ± 16 kg. vs. post-training: 78 ± 27 kg, p < 0.05).
Conclusion
Aerobic and strength training are effective interventions that can partially restore the impaired aerobic endurance and strength found in female cardiac transplant recipients.
==== Body
Exercise training is an effective intervention that can partially restore the impaired aerobic capacity and musculoskeletal fitness (i.e. muscle strength) found in cardiac transplant recipients [1,2]. However, previous reports have focused exclusively on the effects of exercise training in men. Therefore, the effect of exercise training on these outcomes in female cardiac transplant recipients is not known [2-7]. Importantly, a majority of female cardiac transplant recipients do not engage in regular physical activity leading to increased levels of fatigue, poor functional status and reduced exercise capacity [8-10]. Based on this rationale, the aim of this study is to examine the effect that exercise training has on improving aerobic endurance (i.e. distance walked in six-minutes) and lower extremity muscle strength in female cardiac transplant recipients. We hypothesized that exercise training would be a feasible and effective intervention to improve aerobic endurance and lower extremity strength in female cardiac transplant recipients.
Methods
Subjects and procedures
The participants for this study consisted of 20 (51 ± 11 years) clinically stable female cardiac transplant recipients who participated in the University of Alberta Post-Transplant Exercise Rehabilitation program between 1997 and 2003. All assessments and exercise training were performed in the Physical Therapy Department at the University of Alberta Hospital. Ethics approval for this study was obtained from the Biomedical Ethics Board at our University.
Outcome Assessments
The six-minute walk test was performed in accordance with the American Thoracic Society guidelines [11]. In addition, the six-minute walk scores were compared with age-matched norms for healthy females published by Gibbons and associates [12]. Leg-press maximal strength testing was performed on a commercially available leg-press machine with the greatest weight lifted while adhering to strict technique being used as the maximal score. All assessments were repeated following the 12-week training program.
Exercise Training Intervention
Exercise training consisted of supervised aerobic (cycling and/or treadmill exercise at an intensity between 12 to 14 on the BORG perceived exertion scale for 30 to 40 minutes/day including warm-up and cool-down, 5 days/week) and lower extremity strength training.
Data analysis
Statistical analysis was performed with a one-way analysis of variance. The alpha level was set "a priori" at p < 0.05. Data are presented as mean ± SD.
Results
Baseline testing was performed 37 ± 27 days after cardiac transplantation.
Aerobic Endurance
At baseline, our participants' aerobic endurance was 50% lower than age-matched predicted values (Figure 1). Twelve weeks of training resulted in a significant increase in aerobic endurance, however, it remained 22% lower than age-predicted values (Figure 1).
Figure 1 Effect of exercise training on the distance walked in six-minutes. *, p < 0.05 vs. pre-training; †, p < 0.05 vs. post-training.
Leg Press
Leg-press maximal strength increased by 64% after three months of training (pre: 48 ± 16 kg vs. post: 78 ± 27 kg, p < 0.05).
Discussion
This is the first study to examine the effect that combined aerobic and strength training have on improving aerobic endurance and musculoskeletal fitness in female cardiac transplant recipients. The main finding of this study is that combined aerobic and strength training is a feasible and effective intervention to partially restore female cardiac transplant recipients' aerobic endurance and leg-press strength.
Cole et al. [9] recently found that female cardiac transplant recipients' aerobic capacity was 60% lower than age-predicted values. Consistent with this finding, our transplant recipients' baseline aerobic endurance was 50% lower than age predicted values. Moreover, our participants pre-training leg-press strength was 36% lower than that found in age-matched male cardiac transplant recipients tested in our laboratory [13]. The mechanisms responsible for the impaired cardiovascular and musculoskeletal fitness are likely secondary to abnormalities in cardiac and skeletal muscle function associated with pre-transplant heart failure, post-transplant deconditioning, cardiac denervation or immunosuppressuion therapy [14].
Several research groups [2,3,13] have demonstrated that exercise training initiated in the early post-operative period is associated with an increase aerobic endurance [13], muscle mass [2], muscle strength [2,13] and bone density [3] in male cardiac transplant recipients. This study extends previous investigations by demonstrating that 12 weeks of combined aerobic and strength training are associated with a significant and marked improvement in aerobic endurance and muscle strength in female cardiac transplant recipients. The mechanisms responsible for the improvement in aerobic endurance was not examined in this study, however, they may be due to favorable improvements in mitochondrial oxidative properties [15,16] that increase arteriovenous oxygen difference during exertion as aerobic training does not alter exercise cardiac output in this population [4,17]. The training mediated increase in leg-press strength that we found is likely secondary to the increase in muscle mass that occurs with aerobic [4] or combined aerobic and strength training [2]. The consequence of our training mediated improvement in cardiorespiratory and musculoskeletal fitness is that it may result in a favorable improvement in mortality. Specifically, Kavanagh et al. [18] reported that cardiac transplant recipients with the greatest training-mediated improvement in aerobic capacity and lean body mass had a lower mortality rate 12 years after cessation of the training program.
A limitation of our investigation is that we did not have a non-exercise control group. However, our cardiac transplant recipients are required to participate in a supervised 12-week exercise program beginning as an inpatient and completed as an outpatient. Despite this limitation, the improvement in aerobic endurance and leg-press strength associated with our training program is similar to that found in male cardiac transplant recipients who participated in our outpatient exercise rehabilitation program [13].
Summary
A majority of female cardiac transplant recipients adhere to a sedentary lifestyle and as result their aerobic capacity is 60% lower than age-predicted values [9]. The effect that exercise training has on improving female cardiac transplant recipients' aerobic endurance and lower extremity strength is not known. The primary finding of this investigation is that 12 weeks of aerobic and strength training is an effective intervention that can improve aerobic endurance and musculoskeletal fitness in recent female cardiac transplant recipients. Moreover, the improvement in aerobic endurance and leg-press strength is similar to that found in male cardiac transplant recipients after combined aerobic and strength training. In summary, female cardiac transplant recipients should be encouraged to perform aerobic and strength training to increase their aerobic endurance and musculoskeletal fitness.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
MH. Conceived the study, performed data analysis and manuscript preparation.
KR. Assisted with data collection and manuscript preparation.
LF. Performed the exercise rehabilitation training and assisted with manuscript preparation.
DK. Assisted with manuscript preparation.
DW. Assisted with manuscript preparation.
LJ. Assisted with manuscript preparation.
WT. Assisted with manuscript preparation.
All authors read and approved the final manuscript.
==== Refs
Kobashigawa JA Leaf DA Lee N Gleeson MP Liu H Hamilton MA Moriguchi JD Kawata N Einhorn K Herlihy E Laks H A controlled trial of exercise rehabilitation after heart transplantation N Engl J Med 1999 340 272 277 9920951 10.1056/NEJM199901283400404
Braith RW Welsch MA Mills RMJ Keller JW Pollock ML Resistance exercise prevents glucocorticoid-induced myopathy in heart transplant recipients Med Sci Sports Exerc 1998 30 483 489 9565927
Braith RW Mills RM Welsch MA Keller JW Pollock ML Resistance exercise training restores bone mineral density in heart transplant recipients J Am Coll Cardiol 1996 28 1471 1477 8917260 10.1016/S0735-1097(96)00347-6
Kavanagh T Yacoub MH Mertens DJ Kennedy J Campbell RB Sawyer P Cardiorespiratory responses to exercise training after orthotopic cardiac transplantation Circulation 1988 77 162 171 3275506
Lampert E Oyono-Enguelle S Mettauer B Freund H Lonsdorfer J Short endurance training improves lactate removal ability in patients with heart transplants Med Sci Sports Exerc 1996 28 801 807 8832532
Ehrman J Keteyian S Fedel F Rhoads K Levine TB Shepard R Cardiovascular responses of heart transplant recipients to graded exercise testing J Appl Physiol 1992 73 260 264 1506378
Keteyian S Shepard R Ehrman J Fedel F Glick C Rhoads K Levine TB Cardiovascular responses of heart transplant patients to exercise training J Appl Physiol 1991 70 2627 2631 1885457
Evangelista LS Doering LV Dracup K Kobashigawa JA Measuring physical activity among female heart transplant recipients. The Journal of Heart and Lung Transplantation 2003 22. S220. 10.1016/S1053-2498(02)00652-6
Cole BT Kobashigawa JA Patel JK Moriguchi J Espejo Vassilakis M Go SE Chait J Lak H Perception is deceiving: The real gender specific exercise capacity of heart transplant recipients. The Journal of Heart and Lung Transplantation 2003 22. S220. 10.1016/S1053-2498(02)01146-4
Reyes CJ Evangelista LS Doering L Dracup K Cesario DA Kobashigawa J Physical and psychological attributes of fatigue in female heart transplant recipients J Heart Lung Transplant 2004 23 614 619 15135379 10.1016/S1053-2498(03)00310-3
ATS statement: guidelines for the six-minute walk test Am J Respir Crit Care Med 2002 166 111 117 12091180
Gibbons WJ Fruchter N Sloan S Levy RD Reference values for a multiple repetition 6-minute walk test in healthy adults older than 20 years J Cardiopulm Rehabil 2001 21 87 93 11314289 10.1097/00008483-200103000-00005
Haykowsky M Eves N Figgures L Koller M Burton J Tymchak W Early initiation of aerobic and resistance training improves peak aerobic power, leg-press maximal strength and distance walked in six minutes in recent cardiac transplant recipients The Journal of Heart and Lung Transplantation 2003 22 S179 10.1016/S1053-2498(02)01020-3
Warburton DE Sheel AW Hodges AN Stewart IB Yoshida EM Levy RD McKenzie DC Effects of upper extremity exercise training on peak aerobic and anaerobic fitness in patients after transplantation Am J Cardiol 2004 93 939 943 15050506 10.1016/j.amjcard.2003.12.030
Zoll J N'Guessan B Ribera F Lampert E Fortin D Veksler V Bigard X Geny B Lonsdorfer J Ventura-Clapier R Mettauer B Preserved response of mitochondrial function to short-term endurance training in skeletal muscle of heart transplant recipients J Am Coll Cardiol 2003 42 126 132 12849672 10.1016/S0735-1097(03)00499-6
Lampert E Mettauer B Hoppeler H Charloux A Charpentier A Lonsdorfer J Skeletal muscle response to short endurance training in heart transplant recipients J Am Coll Cardiol 1998 32 420 426 9708470 10.1016/S0735-1097(98)00227-7
Geny B Saini J Mettauer B Lampert E Piquard F Follenius M Epailly E Schnedecker B Eisenmann B Haberey P Lonsdorfer J Effect of short-term endurance training on exercise capacity, haemodynamics and atrial natriuretic peptide secretion in heart transplant recipients Eur J Appl Physiol Occup Physiol 1996 73 259 266 8781855
Kavanagh T Mertens DJ Shephard RJ Beyene J Kennedy J Campbell R Sawyer P Yacoub M Long-term cardiorespiratory results of exercise training following cardiac transplantation Am J Cardiol 2003 91 190 194 12521633 10.1016/S0002-9149(02)03108-9
| 15918901 | PMC1166569 | CC BY | 2021-01-04 16:47:32 | no | Curr Control Trials Cardiovasc Med. 2005 May 26; 6(1):10 | utf-8 | Curr Control Trials Cardiovasc Med | 2,005 | 10.1186/1468-6708-6-10 | oa_comm |
==== Front
Dyn MedDynamic medicine : DM1476-5918BioMed Central London 1476-5918-4-71593874810.1186/1476-5918-4-7ResearchFree Mg2+ concentration in the calf muscle of glycogen phosphorylase and phosphofructokinase deficiency patients assessed in different metabolic conditions by 31P MRS Malucelli Emil [email protected] Raffaele [email protected] Andrea [email protected] Caterina [email protected] Bruno [email protected] Stefano [email protected] Dipartimento di Medicina Clinica e Biotecnologia Applicata, Università di Bologna; Via Massarenti 9, 40138 Bologna, Italy2005 6 6 2005 4 7 7 10 1 2005 6 6 2005 Copyright © 2005 Malucelli et al; licensee BioMed Central Ltd.2005Malucelli et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
The increase in cytosolic free Mg2+ occurring during exercise and initial recovery in human skeletal muscle is matched by a decrease in cytosolic pH as shown by in vivo phosphorus magnetic resonance spectroscopy (31P MRS). To investigate in vivo to what extent the homeostasis of intracellular free Mg2+ is linked to pH in human skeletal muscle, we studied patients with metabolic myopathies due to different disorders of glycogen metabolism that share a lack of intracellular acidification during muscle exercise.
Methods
We assessed by 31P MRS the cytosolic pH and free magnesium concentration ([Mg2+]) in calf muscle during exercise and post-exercise recovery in two patients with McArdle's disease with muscle glycogen phosphorylase deficiency (McArdle), and two brothers both affected by Tarui's disease with muscle phosphofructokinase deficiency (PFK).
Results
All patients displayed a lack of intracellular acidosis during muscle exercise. At rest only one PFK patient showed a [Mg2+] higher than the value found in control subjects. During exercise and recovery the McArdle patients did not show any significant change in free [Mg2+], while both PFK patients showed decreased free [Mg2+] and a remarkable accumulation of phosphomonoesters (PME). During initial recovery both McArdle patients showed a small increase in free [Mg2+] while in PFK patients the pattern of free [Mg2+] was related to the rate of PME recovery.
Conclusion
i) homeostasis of free [Mg2+] in human skeletal muscle is strongly linked to pH as shown by patients' [Mg2+] pattern during exercise;
ii) the pattern of [Mg2+] during exercise and post-exercise recovery in both PFK patients suggests that [Mg2+] is influenced by the accumulation of the phosphorylated monosaccharide intermediates of glycogenolysis, as shown by the increased PME peak signal.
iii) 31P MRS is a suitable tool for the in vivo assessment of free cytosolic [Mg2+] in human skeletal muscle in different metabolic conditions;
==== Body
Background
Human skeletal muscles contain approximately 35% of total human body magnesium, which is an essential cofactor in a number of cell reactions. Magnesium ions influence the equilibria of many reactions involved in cellular bioenergetics by interacting with phosphorylated molecules and interfere with the kinetics of ion transport across plasma membranes [1]. There is considerable evidence that Mg2+ is actively transported and regulated, although the mechanisms are still largely unknown [2]. In skeletal muscle variations of cytosolic pH, phosphocreatine (PCr) and inorganic phosphate (Pi) concentrations influence the complex multi-equilibrium system of the molecular species binding magnesium ions. As a consequence [Mg2+] changes considerably in different metabolic conditions such as rest, exercise and recovery, showing an increase matched by a decrease of intracellular pH during exercise and recovery [3].
We assessed the cytosolic pH and the [Mg2+] by 31P MRS at rest, during exercise and post-exercise recovery in the calf muscle of two patients with McArdle's disease with muscle glycogen phosphorylase deficiency (McArdle), and two brothers affected by Tarui's disease with muscle phosphofructokinase deficiency (PFK).
These two type of glycogenosis, being characterized by almost absent activity of enzymes involved in glycogenolysis (McArdle) and glycolysis (PFK) pathways, show in general limited/absent production of intracellular lactic acid, depending on the degree of enzyme deficit [4,5]. As consequence, patients with McArdle's and Tarui's disease, typically show a decrease or a lack of intracellular acidification during muscle exercise when studied by 31P MRS [6,7]. We used these diseases as natural experimental models to study the pattern of free Mg2+ during exercise and recovery in the absence of intracellular acidification to understand to what extent homeostasis of intracellular free Mg2+ is linked to pH.
Methods
Patients
We studied 4 patients: two unrelated males both aged 42, with myo-phosphorylase deficiency (named MCArdle I and II respectively) and two brothers aged 18 and 10 years with phosphofructokinase deficiency (named PFK I and II respectively), as detected by histochemical/biochemical analysis of muscle.
Ten healthy volunteers (10 males age: 33 ± 15) were recruited as control subjects. Written informed consent was obtained from all subjects.
Protocol
MR spectra were acquired on a General Electric 1.5 T Signa System whole-body scanner. Radiofrequency pulses at 25.866 MHz with a pulse width of 400 μs and a transmitter power of 0.5 kW were transmitted by a surface coil (20.5 cm diameter; General Electrics) and the resonance signals were collected by a 7.5 cm receiving coil. A data table of 1024 complex points was collected for each FID. The band width was 2 kHz. The delay between transmission and reception was 0.5 ms and the dwell time was 250 μs. The stimulation-response sequence was repeated every 5000 ms (TR = 5000 ms). Magnetic field homogeneity was optimized by shimming the 1H water spectrum (FWMH 0.25–0.35 ppm)
The spectroscopic measurements were performed according to the quantification and quality assessment protocols defined by the EEC Concerted Research Project on "Tissue Characterisation by MRS and MRI", COMAC-BME II.1.3 [8].
Subjects lay supine with a 20.5/7.5 cm diameter transmitter/receiver surface coil centred on the maximal circumference of the right calf muscle. Muscle aerobic incremental exercise consisted of different levels of 1 minute each (12-FIDs) of plantar flexion against a pedal using a pneumatic ergometer [9]. All patients were asked to perform an exercise to reach a PCr depletion of about 50% at the end of exercise. Sixty-four FIDs at rest, and 12 FIDs for each level of work were averaged. During recovery 4-FIDs data blocks (20 s) were recorded for 60 s, while longer time blocks were collected thereafter. The area of each metabolite signal was fitted to a Lorentzian line shape using a time-domain fitting program AMARES/JMRUI[10], the PCr and Pi concentration were calculated by assuming a normal ATP concentration of 8 mM [11]. The cytosolic pH and [Mg2+] are calculated from the chemical shift of Pi and β-ATP respectively, both measured from the resonance of PCr, using an equation which takes into account the mutual influence between pH and [Mg2+] [3]. The simultaneous calculation of [Mg2+] and pH was performed by the specific software package MagicMC, that we developed and made available on the internet [12].
Results
31P MRS spectra of human skeletal muscle typically show the peak signal of: phosphomonoesters (PME) which represents the phosphorylated monosaccharide intermediates of glycogenolysis, inorganic phosphate (Pi), phosphocreatine (PCr) and the three phosphate groups α, β, γ of ATP.
Figure 1 shows 31P MRS spectra acquired at the end of exercise in the calf muscle of McArdle and PFK patients compared to that of a control subject reaching a similar level of PCr depletion. End exercise spectra of both PFK patients show a marked increase in the PME peak.
Figure 1 31P MRS spectra of calf muscle during exercise. End-exercise 31P MRS spectra of calf muscle acquired in patients and in a control subject reaching a PCr depletion of about 50%. PFK patients showed a marked phosphomonoester (PME) accumulation, although to a different extent.
Table 1 reports the rest and end-exercise values of cytosolic [Mg2+] and pH in patients' calf muscle, compared to the mean values obtained in a control group of ten subjects with a comparable end-exercise PCr depletion. At rest all patients showed a cytosolic pH not different from control values. Resting cytosolic [Mg2+] in PFK II patient was 0.45 mM, higher than the control value (0.32 + 0.04 mM) [3], while in PFK I and both McArdle's patients was normal. Both McArdle and PFK I patients reached a similar PCr depletion just above 50%, while PFK II patient stopped at a lower degree of PCr depletion. All patients displayed a lack of intracellular acidosis during exercise, showing pH values higher than controls at the end of exercise. Cytosolic free [Mg2+] at the end of exercise was lower in both PFK patients compared to control values. The variation of free [Mg2+] from rest to end-exercise (Δ[Mg2+]) was negative in both PFK patients and in McArdle II patient.
Table 1 [Mg2+] and pH values at rest and end-exercise
Rest End-Exercise
[Mg2+](mM) pH %PCr [Mg2+](mM) pH Δ[Mg2+] (mM)
McArdle I 0.34 6.98 53.1% 0.39 7.06* + 0.05
McArdle II 0.36 6.95 53.8% 0.32 7.07* - 0.04*
PFK I 0.38 6.95 54.1% 0.23* 7.01* - 0.15*
PFK II 0.45* 6.95 35.3% 0.23* 7.01* - 0.22*
Controls Mean (n = 10) 0.31 6.96 47.7% 0.42 6.8 +0.11
S.D. 0.04 0.02 13.8% 0.06 0.09 0.07
control range [min:max] [0.27:0.40] [6.94:7.00] [22:73] [0.35:0.54] [6.90:6.67] [+0.03:+0.24]
Rest and end-exercise values of cytosolic [Mg2+] and pH assessed by 31P MRS in patients calf muscle, compared to the mean values obtained in a control group of ten healthy subjects with a comparable end-exercise PCr depletion;
Δ[Mg2+]: difference between end-exercise [Mg2+] and rest [Mg2+];
%PCr: percentage of PCr depletion
* denotes values out of the range: control mean ± 2 SD.
Figure 2 reports the patterns of cytosolic free [Mg2+] and pH obtained in patients during exercise (panel A and B) and recovery (panel C and D) compared with typical patterns from a healthy volunteer with comparable PCr depletion. During exercise and recovery the McArdle patients did not show any significant change (McArdle II) or small change (McArdle I) in free [Mg2+], while both PFK patients showed decreased free [Mg2+] during exercise. On the other hand, during recovery the pattern of free [Mg2+] was different in the two PFK patients, with PFK II showing a moderate increase during early recovery.
Figure 2 [Mg2+] and pH patterns during exercise and recovery. Patterns of cytosolic free magnesium concentration and pH at rest, during exercise and recovery in patients compared with typical patterns from a healthy volunteer with comparable PCr depletion. (A): pattern of [Mg2+] during exercise; (C): pattern of [Mg2+] during recovery; (B): pH pattern during exercise; (D): pH pattern during recovery.
Figure 3 report the PME pattern of the two PFK patients during exercise and recovery. PFK I patient shows a slower rate of both PME accumulation and recovery compared to PFK II patient.
Figure 3 PME patterns of PFK patients during exercise and recovery. PFK I patient shows both a slower rate of PME accumulation during exercise and a slower recovery of PME after exercise compared to PFK II patient. PME signal comes from the phosphorylated monosaccharide intermediates of glycogenolysis.
Discussion
In the skeletal muscle variations of cytosolic pH, phosphocreatine and inorganic phosphate concentrations influence the complex multi-equilibrium system of the molecular species which bind magnesium ions. As a consequence free cytosolic [Mg2+] can change considerably in different metabolic conditions such as rest, exercise and recovery. It has been shown by 31P MRS that the increase of cytosolic free [Mg2+] occurring in skeletal muscle of healthy subjects during exercise and initial recovery is matched by a decrease in cytosolic pH, and the changes in cytosolic free [Mg2+] were mainly the result of the predominant effect of [H+]. [3]. This result was attributed to mechanisms of binding competition existing between Mg2+ and H+ towards the molecules negatively charged present in the cell cytosol [3]. However, the causal relationship between pH and [Mg2+] has not been proved yet, as it could be argued that muscular exercise per se elicits an increase in cytosolic free [Mg2+]. Therefore, we used patients with McArdle's and Tarui's disease as experimental models to study the pattern of [Mg2+] during exercise and recovery in the absence of intracellular acidification to understand to what extent homeostasis of intracellular free Mg2+ is linked to pH. Due to the rare nature of these disorders we were able to enrol just two patients for both diseases and therefore we had to deal with a small sample size. The results show that the increase in cytosolic [Mg2+] occurring in skeletal muscle during exercise is actually the consequence of the increase of H+ concentration and not of other mechanisms related to muscle contraction. In addition, we found that both PFK patients showed a reduction of [Mg2+] during exercise concomitant with the PME increase. The decrease of [Mg2+] also persisted during recovery in PFK I patient who displayed a slower PME recovery. The PME peak in the 31P MRS spectra corresponds to the phosphorylated monosaccharide intermediates of glycogenolysis. Therefore, due to the deficit of the phosphofructokinase activity in Tarui's disease, the PME accumulation shown by these patients is likely due to the increase of fructose- 6-phosphate, which represents an additional binding site for cytosolic Mg2+. As a consequence, we interpret the decrease of [Mg2+] concomitant with the PME increase as due to the binding of Mg2+ to fructose-6-phosphate. A previous study (6) reported that the abnormal PME accumulation of PFK patients during exercise was accompanied by a subnormal Pi accumulation. This finding was interpreted as a result of the incorporation of free Pi into phosphorylated glycolytic intermediates. However, both our patients did not show any Pi trap into PME, since we found that the sum of PCr and Pi was constant for the whole exercise duration, while the total phosphates signal increased proportionally to PME increase. Therefore, the [Mg2+] decrease found in PFK patients cannot be ascribed to a diminished Pi build-up.
Moreover, PFK II patient displayed a larger decrease of [Mg2+] from rest to end-exercise compared to PFK I patient. Accidentally, PFK II patient also had a smaller PCr breakdown, nevertheless, this cannot be the cause of the larger decrease of [Mg2+], as a lower [PCr] corresponds to lower calculated [Mg2+] (3).
Conclusion
Our results show that:
i) free [Mg2+] is strongly linked to pH in skeletal muscle homeostasis as previously suggested by a study in healthy volunteers [3], and by computer simulation on a chemical model mimicking muscle cell cytosol [13];
ii) the decrease of free [Mg2+] during exercise in both PFK patients suggests that [Mg2+] is influenced by the accumulation of fructose- 6-phosphate, an additional binding site for cytosolic Mg2+, as shown by the accumulation of the phosphomonoesters peak in the 31P MRS spectra of these patients.
iii) 31P MRS is a suitable tool for the in vivo assessment of free cytosolic [Mg2+] in human skeletal muscle during rest, exercise and recovery;
Authors' contributions
EM participated in the study design, performed the post-processing and statistical analysis, RL and CT participated in the study design and coordinated the data collection, AM participated in the study design, BB participated in the coordination of the study, SI participated in the study design, coordinated the study, and drafted the manuscript. All authors read and approved the final manuscript.
Acknowledgements
This work was supported by Ricerca Fondamentale Orientata (ex quota 60%) and by Programmi di Ricerca Scientifica di Rilevante Interesse Nazionale – Cofin (ex quota 40%).
==== Refs
Lawson RWJ Veech RL Effects of pH and free magnesium ion on the Keq of the creatine kinase reaction and other phosphate hydrolyses and phosphate transfer reactions J Biol Chem 1979 254 6528 6537 36398
Masuda T Dobson GP Veech RL The Gibbs-Donnan near-equilibrium system of heart J Biol Chem 1990 265 20321 20334 2147022
Iotti S Frassineti C Alderighi L Sabatini A Vacca A Barbiroli B In Vivo 31P-MRS assessment of cytosolic [Mg2+] in the human skeletal muscle in different metabolic condition Magn Reson Imag 2000 18 607 614 10.1016/S0730-725X(00)00132-6
McConchie SM Coakley J Edwards RHT Beynon RJ Molecular Heterogeneity in McArdle's disease Biochim Biophys Acta 1991 1096 26 32 2268682
Tsujino S Servidei S Tonin P Shanske S Azan G DiMauro S Identification of three novel mutation in non-Ashkenazi Italian patients with muscle phosphofructokinase deficiency Am J Hum Genet 1994 54 812 819 7513946
Bertocci LA Haller RG Lewis SF Fleckenstein JL Nunnally RL Abnormal high-energy phosphate metabolism in human muscle phosphofructokinase deficiency J Appl Physiol 1991 70 1201 1207 1827789
Sahlin K Areskog NH Haller RG Henriksson KG Jorfeldt L Lewis SF Impaired oxidative metabolism increases adenine nucleotide breakdown in McArdle's disease J Appl Physiol 1990 69 1231 1235 2262440
EEC Concerted Research Project Quality Assessment in in vivo NMR spectroscopy. Results of a Concerted Research Project of the European Economic Community (6 papers) Magn Reson Imag 1995 13 115 176
Zaniol P Serafini S Ferraresi M Golinelli R Bossoli P Canossi I Aprilesi GC Barbiroli B Muscle 31 P-MR spectroscopy performed routinely in a clinical environment by a whole-body Imager/spectromemeter Physica Medica 1992 8 87 91
Magnetic Resonance User Interface Home Page
Harris RC Hultman E Nordesjö LO Glycogen, glycolytic intermediates, and high-energy phosphates determined in biopsy samples of musculus quadriceps femoris of man at rest. Methods and variance of values Scand J Clin Lab Invest 1974 33 109 120 4852173
Centro di Ricerca e Diagnostica Molecolare in vivo
Iotti S Tarducci R Gottardi G Barbiroli B Cytosolic Free [Mg2+] in the human calf muscle in different metabolic conditions: in vivo 31P MRS and computer simulation Proceedings of the Society of Magnetic Resonance in Medicine (seventh scientific meeting and exhibition) 1999 3 Philadelphia, Pennsylvania USA 1540 22–28, May 1999
| 15938748 | PMC1166570 | CC BY | 2021-01-04 16:37:29 | no | Dyn Med. 2005 Jun 6; 4:7 | utf-8 | Dyn Med | 2,005 | 10.1186/1476-5918-4-7 | oa_comm |
==== Front
Immun AgeingImmunity & ageing : I & A1742-4933BioMed Central London 1742-4933-2-81590453410.1186/1742-4933-2-8ReviewInnate immunity and inflammation in ageing: a key for understanding age-related diseases Licastro Federico [email protected] Giuseppina [email protected] Domenico [email protected] Elisa [email protected] Giuseppina [email protected] Claudio [email protected] Calogero [email protected] Dipartimento di Patologia Sperimentale, Università di Bologna, Italy2 Gruppo di Studio sull'Immunosenescenza, Dipartimento di Biopatologia e Metodologie Biomediche, Università di Palermo, Italy3 Istituto Nazionale di Riposo e Cura per Anziani, Ancona, Italy4 Centro Interdipartimentale "L. Galvani", Università di Bologna, Bologna, Italy2005 18 5 2005 2 8 8 5 4 2005 18 5 2005 Copyright © 2005 Licastro et al; licensee BioMed Central Ltd.2005Licastro et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The process of maintaining life for the individual is a constant struggle to preserve his/her integrity. This can come at a price when immunity is involved, namely systemic inflammation. Inflammation is not per se a negative phenomenon: it is the response of the immune system to the invasion of viruses or bacteria and other pathogens. During evolution the human organism was set to live 40 or 50 years; today, however, the immune system must remain active for much a longer time. This very long activity leads to a chronic inflammation that slowly but inexorably damages one or several organs: this is a typical phenomenon linked to ageing and it is considered the major risk factor for age-related chronic diseases. Alzheimer's disease, atherosclerosis, diabetes and even sarcopenia and cancer, just to mention a few – have an important inflammatory component, though disease progression seems also dependent on the genetic background of individuals. Emerging evidence suggests that pro-inflammatory genotypes are related to unsuccessful ageing, and, reciprocally, controlling inflammatory status may allow a better chance of successful ageing. In other words, age-related diseases are "the price we pay" for a life-long active immune system: this system has also the potential to harm us later, as its fine tuning becomes compromised. Our immune system has evolved to control pathogens, so pro-inflammatory responses are likely to be evolutionarily programmed to resist fatal infections with pathogens aggressively. Thus, inflammatory genotypes are an important and necessary part of the normal host responses to pathogens in early life, but the overproduction of inflammatory molecules might also cause immune-related inflammatory diseases and eventually death later. Therefore, low responder genotypes involved in regulation of innate defence mechanisms, might better control inflammatory responses and age-related disease development, resulting in an increased chance of long life survival in a "permissive" environment with reduced pathogen load, medical care and increased quality of life.
Age-related diseasesCytokineInflammationInnate ImmunityLongevity
==== Body
Innate immune system
The first line of immune defence mainly operates by detection of a broad range of molecular patterns foreign to mammalian tissues, called pathogen-associated molecular patterns that induce the activation of the innate immunity and inflammatory response [1]. The constitutive expression of a limited set of pattern recognition receptors by many cell types of the innate immunity does not require clonal expansion of specific cell populations. These germ cell-encoded proteins recognize microbial pathogens or ligands from damaged tissues based on shared molecular structures and induce host responses that localize the spread of infection and enhance systemic resistance to infection. Therefore, the expression of a limited number of highly active genes during the activation of innate immunity is able to induce rapid (minutes to hours) efficient defensive immune responses [2].
Several cell types contribute to innate immunity and the mononuclear phagocyte lineage plays a pivotal role in innate immunity. Monocytes, macrophages and their tissue-differentiated derivatives, such as microglia in the nervous system, express pattern recognition receptors, namely various scavenger and Toll-like receptors [3]. These receptors induce transmembrane signals that activate NF-kB and mitogen dependent protein kinase pathways [4]. Toll-like receptor activation also induces the expression of a wide number of genes encoding proteins, such as cytokines, with regulatory functions upon leukocyte activation and tissue inflammation [5]. Therefore, the capacity of each individual organism to regulate the activation of innate immunity and local inflammatory responses is crucial for initiating defensive action against pathogens, limiting tissue damage and enhancing fast recovery and tissue healing.
The inflammatory response
In response to cell injury elicited by trauma or infection the inflammatory response sets in, constituting a complex network of molecular and cellular interactions directed to facilitate a return to physiological homeostasis and tissue repair. The response is composed of both local events and a systemic activation mediated by cytokines. If tissue health is not restored or in response to stable low grade irritation, inflammation becomes a chronic condition that continuously damages the surrounding tissues. In fact, during chronic inflammatory immune responses, tissue injury and healing proceed simultaneously. The collateral damage caused by this type of inflammation usually accumulates slowly, sometimes asymptomatically for years but can eventually lead to severe tissue deterioration [6].
Cytokines are largely secreted molecules that act on the surrounding microenvironment by providing cell to cell signalling. Cytokines are components of a large, complex signalling network. The effects of cytokines on target cells may be inhibited or enhanced by other cytokines, hormones, and cytokine-receptor antagonists and circulating receptors. Tumor necrosis factor α (TNF-α), Interleukin-1 (IL-1) and IL-6 are the classical pro-inflammatory cytokines. Their ability to activate both local and systemic effects is well established. Locally, they contribute to the activation of the inflammatory cells and together with chemokines, which induce the expression of adhesion molecules, cause their local recruitment. When the causes of the inflammatory reaction are of a high intensity, the production of cytokines is increased and they are released in the circulation provoking the "acute phase response". On the other hand, "inhibitory" cytokines such as IL-10 damp down the activation of some effector functions of T lymphocytes and mononuclear phagocytes, by inhibiting the release of pro-inflammatory cytokines and therefore turning off the inflammatory processes [7,8].
The acute phase response e.g. leukocytosis, fever, somnelence, anorexia and acute phase proteins synthesis, such as C reactive protein (CRP) in the liver, is a highly conserved inflammatory response which is rapidly activated by infections or trauma via pattern recognition molecules. Acute phase protein concentration rapidly increases after infection, and their production is controlled primarily by IL-6- and IL-1-type cytokines. The acute phase proteins provide enhanced protection against microorganisms and modify inflammatory responses by affecting cell trafficking and mediator release. The more traditional view of acute phase proteins has extended beyond that of opsonization of microorganisms. Some acute phase proteins have anti-inflammatory effects while others have important effects on leukocyte activation and trafficking [9].
CRP, named for its capacity to precipitate the somatic C-polysaccharide of Streptococcus pneumoniae, was the first acute-phase protein to be described, and is an exquisitely sensitive systemic marker of inflammation and tissue damage. It is a member of the pentraxin family of plasma proteins, which are part of the lectin fold superfamily of calcium-dependent ligand-binding and lectin (carbohydrate-binding) proteins. In healthy blood donors, the median concentration of CRP is 0.8 mg/l, but following an acute-phase stimulus, values may increase 10 000-fold. In an apparently healthy population the median baseline value is slightly higher and tends to increase with age with females showing slightly higher circulating concentrations. In most, but not all diseases, the circulating value of CRP reflects on-going inflammation much more accurately than do other biochemical parameters of inflammation, such as plasma viscosity or the erythrocyte sedimentation rate [10].
Innate immune system during ageing
Age related changes in clonotypic immune system are well documented. For instance, involution of the thymus gland is an early feature of the immune reconfiguration and several age- related alterations of T or B cell compartments have been described [11-13]. Studies on age-associated changes of the innate immunity are not as advanced as those of the clonotypic immune system. However, investigations from aged mice showed a functional decline of monocytes and macrophages, a low expression level of Toll-like receptors from activated splenic and peritoneal macrophages and an altered secretion of several chemokines and cytokines [14,15]. Aged macrophages also contribute to an impaired the proliferative response of activated peripheral T lymphocytes [16].
Aged phagocytes, such as macrophages and neutrophils, showed an impaired respiratory burst and reactive nitrogen intermediate production with a decreased ability to destroy pathogens. Moreover, aged dendritic cells were less efficient in activating both T and B cell populations and aged NK cells showed a decreased ability in killing tumour cells [17,18].
However, not all immune activities are decreased during ageing. In fact, the 'in vitro' production of pro-inflammatory cytokines, such as IL-1, IL-6 and TNF-α, by mitogen activated peripheral blood monuclear cells from elderly persons was higher than that from young donors [19]. Cytokine production may also be up-regulated 'in vivo' in old subjects resulting in an abnormal elevation of pro-inflammatory cytokines during inflammatory responses [20]. An age- related increase of IL-6 levels has also been reported in plasma, serum and supernatants from healthy elderly and centenarians [19,21,22]. It is interesting to note that 'in vitro' addition of IL-1 and TNF-α to fibroblasts induced an accelerated senescent phenotype which was rescued by anti-oxidant addition [23].
Inflammatory responses during ageing
A dramatic increase in mean life span and life expectancy, coupled with a significant reduction in early mortality, has lead to a large increase in the number of elderly people in modern societies. This demographic phenomenon has been paralleled by an epidemic of chronic disease usually associated with advancing age [24]. Most age-related diseases have complex aetiology and pathogenic mechanisms. The clinical diagnosis and therapy of these diseases requires a multidisciplinary medical approach with progressively increased costs. A body of experimental and clinical evidence suggests that the immune system is implicated, with a variable degree of importance, in almost all age-related or associated diseases. Both innate and the clonotypic immune system are usually involved in the pathogenesis of these chronic diseases [11,25]. However, inflammatory responses appear to be the prevalent triggering mechanism driving tissue damage associated with different age-related diseases and the term "Inflammaging" has been coined to explain the underlining inflammatory changes common to most age-associated diseases [26]. This new term indicates that ageing is accompanied by an age-dependent up-regulation of the inflammatory response, due to the chronic antigenic stress which bombards the innate immune system thorough out life and potentially triggers the onset of inflammatory disease.
Chronic inflammation is considered to be involved in the pathogenesis of all age-related diseases: Alzheimer's disease, atherosclerosis, diabetes, sarcopenia and cancer all have important inflammatory components. Inflammaging, i.e. the up-regulation of a variety of anti-stress responses at the cellular and molecular level, is the consequence of the body's ability to counteract and modulate the effects of a variety of stressors, which cause the accumulation of molecular and cellular scars [26,27]. However, as recently discussed [28], a wide range of different aetiological factors is likely to contribute to increased low-grade inflammatory activity in elderly populations including a decreased production of sex steroids, smoking, subclinical disorders such as arteriosclerosis, asymptomatic bacteruria and a higher relative/absolute amount of fat tissue, which has been suggested to produce pro-inflammatory cytokines [29] (see below). Furthermore, increased levels of circulating inflammatory mediators may result from a constant, low-grade activation of cytokine-producing cells or a dysregulated cytokine response following stimulation [28], which does not readily become damped down. On the other hand, a recent hypothesis suggests that the reduction in lifetime exposure to infectious diseases and other sources of inflammation – the cohort mechanism – may also contribute to the historical decline in old-age mortality [30].
Recent studies have linked an individual's exposure to past infection to levels of chronic inflammation and to increased risk of heart attack, stroke, and cancer. For example, the risk of heart attack is correlated with serum levels of inflammatory proteins such as CRP [31]. Within individuals, CRP levels are also correlated with the number of seropositivities to common pathogens, suggestive of infection history [32].
Low-grade increases in levels of circulating TNF-α, IL-6, soluble IL-2 receptor (sIL-2R), and CRP and low levels of albumin and cholesterol, which also act as inflammatory markers, are strong predictors of all-cause mortality risk in several longitudinal studies of elderly cohorts. The effects of inflammatory mediators upon survival are independent of pre-existing morbidity and other traditional risk factors for death (smoking, blood pressure, physical exercise, total cholesterol, co-morbidity, body mass index, and intake of anti-inflammatory drugs) suggesting that cytokines may induce exaggerated pathological processes. Furthermore these molecules appear to be sensitive markers of pre-clinical disorders in elderly populations [28,33-39].
In the following sections we will focus on the role of innate immunity and inflammation in the most common diseases of elderly in order to direct the reader's interest to these emerging topics in modern gerontology and geriatrics investigations.
Frailty and sarcopenia
Frailty has been defined as an age-related decline in lean body mass, decreased muscle strength, endurance, balance and walking performance, low activity and weight loss accompanied by a high risk of disability, falls, hospitalisation and mortality [28,40]. It has been suggested that this syndrome reflects a metabolic imbalance caused by overproduction of catabolic cytokines and by the diminished availability or action of anabolic hormones, resulting from ageing itself and the presence of associated chronic conditions [28,41]. Sarcopenia is obviously a central part of the frailty syndrome [28]. Sarcopenia is the loss of muscle mass and strength that occurs with normal ageing. In elderly, there is a decline in a variety of neural, hormonal, and environmental trophic signals to muscle. However, the most important endogenous cause may be the irreversible age-related loss of α-motor units in the central nervous system [42-44]. The most important environmental cause of sarcopenia is lack of physical activity which is an age-related phenomenon which shows universal decline with age in industrialized societies; obesity and type 2 diabetes being concomitant epidemics (see below). An emerging issue in the past few years for sarcopenia research has been whether there is also an increased catabolic signal, driven by systemic inflammation [44]. Systemic low-grade inflammation has been associated with decreased muscle mass as well as the development of functional disability in elderly populations [33,44-47]. TNF-α has special effects that may contribute directly to sarcopenia [44], including increased basal energy expenditure, anorexia, loss of muscle and bone mass 'in vivo' and association with wasting/cachexia in chronic inflammatory disorders. Consistent with these findings, muscle protein synthesis was inversely related to local levels of TNF-α protein in skeletal muscles in frail very old humans [48]. In a recent study of nursing home residents aged 85–96 years, systemic low-grade activation of the TNF-α system at baseline was inversely correlated to muscle strength after resistance training for 12 weeks, demonstrating that TNF-α could also be a limiting factor for training-induced improvement in muscle strength in very old people [49]. The role of IL-6 in sarcopenia is not clear. Epidemiological studies have reported that IL-6 is strongly associated with functional disability and loss of muscle mass but experimental studies have not been able to link IL-6 to sarcopenia [28,44]. Human investigations have shown that inflammation impairs muscle strength in elderly people [50] while Insulin Growth Factor 1 and IL-6 plasma levels were synergistically related to disability and mortality in older women [51].
A complicating factor in untangling the cause-effect relationships underlying sarcopenia is the ability of IL-6, TNF-α, physical inactivity, abdominal obesity, and other factors to cause insulin resistance in the elderly [52-54]. Loss of control of the anabolic action of insulin on muscle would be another factor favouring sarcopenia, resulting in the elevation of one or more catabolic signals. Thus, the weight gain that occurs in most adults during middle age may actually predispose to sarcopenia as they age [44].
Obesity, the metabolic syndrome, type II diabetes
Western societies face a health care crisis of epidemic proportion, since the number of people with the metabolic syndrome is rising exponentially. This condition constitutes a major challenge for public health professionals in the field of preventive medicine and estimates suggest that more than 40 million US adults will be affected by the syndrome [55].
There is not known survival advantage of morbid obesity; on the other hand increased body fat is linked to high mortality [56]. In the past, humans have been plagued by famine when survival advantage would have been conferred by genes favouring an available energy source: the so called 'thrifty gene' hypothesis. These genes led to genetic selection toward insulin resistance in the peripheral tissue in order to preserve glucose supply of the brain during starvation [57]. Human obesity shows a clear genetic component, which is usually polygenic and polymorphic variances in a number of 'thrifty' genes could contribute to different susceptibilities to obesity and diabetes [58,59].
Metabolic syndrome may be detected by 5 clinical diagnostic criteria 1) abdominal adiposity, 2) hypertriglyceridemia, 3) low high density lipoprotein, 4) hypertension, 5) fasting hyperglycaemia [55].
An involvement of inflammation with pathogenic mechanisms influencing the development of the metabolic syndrome has been suggested [55,60,61] and elevated CRP, IL-6 and TNF-α, associated with visceral adiposity, have been reported in this syndrome [61]. Adipocytes constitutively express the pro-inflammatory TNF-α [54] which decreases after weight loss [62]. Further work in this area has confirmed increased plasma concentrations of CRP, IL-6, and plasminogen activator inhibitor-1 (PAI-1) [63-65]. Therefore, a complex interplay may exist between inflammatory responses and general metabolism in atherosclerosis, cardiovascular disease, metabolic syndrome.
It is becoming clear that the increased adipose tissue is not a simple reservoir for excess nutrients, but rather an active and dynamic organ capable of expressing several cytokines and other fat-derived peptides (FDP). Some FDP may have a role in the development of the metabolic syndrome but there is no evidence that these FDP are directly causing inflammation. It has been suggested that high levels of inflammatory factors are markers for obesity/abdominal obesity seen with aging, but some of these may not necessarily have a causative role in the development of inflammation [29]. Alternatively, a positive correlation was found between the body mass index and the percentage of resident macrophages, suggesting that fat tissue growth is associated with a recruitment of blood monocytes, responsible for cytokine production [66].
Insulin resistance is due to the reduced ability of peripheral tissues to properly respond to the activation induced by insulin. It is a key feature in the pathogenesis of type II diabetes and this condition may precede by 10–20 years the onset of hyperglycaemia and the clinical manifestation of the disease. Recent data suggests that a defect in insulin activation of glucose transportation in muscle cells could be induced by serine kinase cascade activation, which is down stream mediators of tissue inflammation factors [67].
Data from the Insulin Resistance Atherosclerosis Study showed that insulin resistance, as assessed by frequently sampled glucose tolerance tests, correlated with high blood levels of CRP, fibrinogen and PAI-1 and levels of these inflammatory factors were predictors of type II diabetes development [68]. Increased blood concentrations of TNF-α and IL-6 were associated with obesity and type II diabetes [69]. Finally, results of the population study from the European Prospective Investigation into Cancer and Nutrition Potsdam indicated a significant interaction between plasma IL-1β, IL-6 and type II diabetes development. In fact subjects with detectable IL-1β levels and increased levels of IL-6 showed an independently elevated risk of developing the disease [70].
Inflammation may predispose to a pre-diabetic state by increasing insulin resistance, since pre-diabetic subjects showed increased plasma levels of inflammatory proteins without primary defects of beta cell functions [71]. Sub-clinical inflammation was found significantly related to insulin resistance in a high risk group for diabetes, i.e. in subjects with positive family history of diabetes, obesity and hyper or dyslipoproteinemia [72]. Recent results from the INCHIANTI population study showed that subjects in the upper tertile of insulin resistance had increased serum levels of TNF-α, IL-1R antagonist and IL-6 and low levels of sIL-6R [73].
TNF-α causes an inhibition of auto-phosphorylation of tyrosine residues of the insulin receptor (IR) and an induction of serine phosphorylation of insulin receptor substrate-1, which in turn causes serine phosphorylation of the IR in adipocytes and inhibits tyrosine phosphorylation [74]. More recently, IL-6 has been shown to inhibit insulin signal transduction in hepatocytes [53]. Therefore, cytokines show relevant metabolic effects.
Novel data have now appeared showing that the concomitant presence of the promoter polymorphisms of TNF-α and IL-6, linked to high production of these cytokines increases the risk of conversion to type 2 diabetes in obese subjects with impaired glucose tolerance response [75].
As discussed by Dandona et al. [69], two mechanisms might be involved in the pathogenesis of inflammation. Glucose and macronutrient intake causes oxidative stress and inflammatory changes. Chronic overnutrition (obesity) might thus be a pro-inflammatory state with oxidative stress. The increased concentrations of TNF-α and IL-6, associated with obesity and type 2 diabetes, might interfere with insulin action by suppressing insulin signal transduction, which in turn might promote inflammation. In fact, insulin reduces ROS generation by mononuclear cells, suppresses NADPH oxidase expression and intranuclear NF-kB binding, induces IkB expression and suppresses some inflammatory molecules [69,76].
The well-known beneficial effects of caloric restriction on longevity in animal models by inducing reduced visceral fat mass might also induce a reduced secretion of multiple metabolically active factors, which are potentially responsible for the development of insulin resistance. This decrease in fat mass and its beneficial effects observed in ageing animal models might apply also to human ageing and its related pathology [77].
Cancer diseases
The majority of cancer occurs in subjects over the age of 65 years. Cancer rates increase sharply with age in both sexes: the incidence of cancer is 12–36 times higher in individuals aged 65 years or older compared with individuals aged 25–44 years, and 2–3 times more common than in persons aged 45–64 years. It is worth noting that 70% of deaths attributable to all cancer occur in men and in women aged 65 years or older whereas 35% cancer deaths in men and 46% of cancer deaths in women occur in those aged 75 years or older. The relationship between ageing and cancer is similar for most cancers, and it is well described by the multistage model. So, ageing might be considered not as a determinant of cancer per se, but as a surrogate marker of the duration of exposure to relevant carcinogenic factors [78-80].
Chronic inflammation induced by either biological, chemical, mechanical or physical injuries has been associated with increased incidence of cancer in different human tissues [81]. For instance, inflammatory bowel disease, ulcerative colitis and Crohn's disease are clinical conditions predisposing to cancer development of the large bowel or terminal ileum [81,82].
Helicobacter pylori microorganisms are associated with atrophic gastritis, mucosal dysplasia, gastric adenocarcinoma and an unusual form of gastric lymphoma [81,82]. Schistosome and trematode infections have been associated with cancers of the bladder and the biliary tracts [81].
The recognition of a role for inflammation in the natural history of a tumor has been known stretching from the mid-19th century [83]. The inflammatory microenvironment of tumors is characterised by the presence of host leucocytes both in the supporting stroma and in the tumor area [84]. The question whether the inflammatory infiltrate helps or hinders tumors is still open. In fact, inflammatory cells and cytokines found in tumors can contribute to tumor growth, progression, and immunosuppression as well mounting an effective host anti-tumor response. However, in most cases inflammation plays a role in the development of solid cancer. That is clearly demonstrated by a prospective, nested case-control study of a cohort of 22,887 adults followed for 11 years. A total of 172 colorectal cancer cases were identified. Up to 2 controls (n = 342) were selected for each case and matched by age, sex, race, and date of blood draw. Plasma CRP concentrations were higher among all colorectal cases combined compared with controls and the risk of colon cancer was higher in persons in the highest vs. lowest quartile of CRP [85].
Furthermore, in another recent study, a total of 174 patients considered to have undergone curative resection for cancer were studied. The results show that raised circulating concentrations of CRP, whether measured before or after operation, predict overall and cancer-specific survival in patients undergoing potentially curative surgery for colorectal cancer suggesting that the presence of a systemic inflammatory response predicts a poor outcome [86]. This data supports the hypothesis that inflammation is a risk factor for the development of some kind of solid tumors such as colon cancer.
Cancer susceptibility and severity may also be associated with functional polymorphisms of cytokine genes involved in regulation of inflammation. In particular, as discussed in a recent review [79], a considerable body of data indicates that particular cytokine polymorphisms, especially those involving IL-6 and IL-10 genes, may influence susceptibility to, and in some cases prognosis in neoplastic diseases. It is intriguing that these two cytokines are involved in longevity [87-89]. Discrepant results might depend on confounding factors that affect case-control studies [90] or as discussed by Caruso et al. [79] might also depend on pleiotropic action of cytokines. It is paradigmatic in this respect that the favourable effect of high producer IL-10 genotype on hepatocarcinoma induced by HBV [91], may be due to the relative lack of control of HBV infection by immunosuppressive effects of high IL-10 levels.
On the other hand, several and diverse mechanisms may link inflammation to cancer.
1) Free radical production, derived by oxygen or NO metabolic pathways; the respiratory burst of leukocytes, and the arachidonic acid cascade activation are strongly implicated in DNA modification and protein damage which in turn promotes carcinogenesis [92].
2) High constitutive hyper-expression of NF-kB, an ubiquitous transcription factor with regulatory effect upon different inflammatory, apoptotic and oncogenic genes [82].
3) Alterations of the p53 gene induced by NO derived radicals promoting clonal expansion of aberrant or mutated cells [92].
4) Induction of angiogenesis by inflammatory factors favouring cancer progression [92].
5) Increased release of key pro-inflammatory factors and some cytokines, such as IL-1β, TNF-α and interferon (IFN)-γ, implicated in both the regulation of inflammation and the development of cancer [92,93].
Atherosclerosis and cardiovascular diseases
Atherosclerosis and its complications are a major problem
contributing to large sections of morbidity and mortality in old people. Cardiovascular disease is the leading worldwide cause of morbidity and death in Western societies [94]. However, our understanding of pathogenic mechanisms underling atherosclerosis and its complications is still incomplete, since more than half of patients with atherosclerosis do not show classical risk factors, such as hypercholesterolemia, hypertension, history of smoking, diabetes, obesity and sedentary life style [94,95].
On the other hand, atherosclerosis, formerly considered an inocuous lipid storage disease, actually involves an ongoing inflammatory response (Figure 1). Recent advances in basic science have established a fundamental role for innate immunity in mediating all stages of this disease from initiation through progression and, ultimately, the thrombotic complications of atherosclerosis [96-98]. Clinical studies have shown that the emerging biology of inflammation in atherosclerosis applies directly to human patients. Elevation in markers of inflammation predicts outcomes of patients with acute coronary syndromes, independently of myocardial damage. In addition, low-grade chronic inflammation, as indicated by levels of the inflammatory marker CRP and cytokines, prospectively defines risk of atherosclerotic complications, thus adding to prognostic information provided by traditional risk factors. In fact, levels of CRP or IL-6 have been suggested as significant predictive risk factors for future development of cardiovascular events [31,95,99-103]. Increased levels of serum IL-1β have also been associated with high risk of congestive heart failure and angina pectoris [104]. Altered level of IL-1β is also suggested to be implicated in chronic inflammation underlining high blood pressure [105].
Figure 1 Schematic representation of inflammatory mechanisms involved in pathogenesis of atherosclerosis and plaque formation. Monocytes and macrophages are the protagonists of atherosclerotic processes.
An initiating event is the accumulation of lipids in the vessel wall, which subsequently will become modified and triggers an inflammatory process. Low-density lipoproteins (LDL) are taken up by macrophages through scavenger receptors, leading to foam cells; the lipid deposits become oxidized forming pro-inflammatory lipid peroxides. Monocytes are attracted from the blood and differentiate into macrophages that take up the modified LDL and form lipid-laden foam cells, which is the first hallmark of atherosclerotic plaque development. Later on, inflammatory mediators increase, other immune cells are attracted, and smooth muscle cells are activated and become involved. More advanced stages of plaque development are characterized by increased deposition of extra cellular lipid cores, fibrous material, and often necrosis. Subsequently, these macrophages are further activated, leading to the production of a wide range of cytokines and growth factors. Myocardial infarction may occur as a result of erosion or uneven thinning and rupture of the fibrous cap, often at the shoulders of the lesion where macrophages enter, accumulate and are activated and where apoptosis may occur [7,96-98].
Because genetic traits contribute significantly to the risk of coronary heart disease [106], a number of studies have now addressed the hypothesis that allelic variations in genes of innate immunity may increase the risk of this disease [107,108]. Differences in the genetic regulation of inflammatory processes might partially explain why some people, but not others, develop the disease and why some develop a greater inflammatory response than others. Accordingly, common gene polymorphisms controlling high production of inflammatory molecules have been associated with atherosclerosis and a good control of inflammation might play a protective role against atherosclerosis [107-110]. Recently, a combination of alleles in different inflammatory genes has been associated with increased risk of developing acute myocardial infarction in elderly men [111].
In addition to innate immunity, clonotypic immunity plays also a role in atherosclerosis. Recent findings support the hypothesis that a crucial component of atherosclerosis is represented by T cell-mediated immune responses that are inappropriate in terms of time of onset, intensity, and target [112]. On the other hand, the most direct evidence for the critical role for T cells, IFN-γ, and IFN-γ-driven molecules in atherosclerosis is provided by mice with combined deficiencies of apolipoprotein E (apoE) and the IFN-γ receptor, in which the development of atheroma is significantly reduced in comparison to mice with only apoE deficiency, whereas exogenous IFN-γ enhances atherosclerosis [113,114]. In contrast, the role of B cells has remained unclear. B-cells are not always present and may be protective. In fact, recent studies suggest that this cell type may inhibitthe development of vascular pathology in models of atherosclerosisand restenosis [115]. Finally, Wick et al. [116] have developed an autoimmune-inflammatory concept of atherogenesis based on experimental and clinical models. They argue that atherosclerosis may be the price humans pay for pre-existing immunity to microbial or autologous heat shock protein (HSP) 60. In summary, their autoimmune hypothesis of atherogenesis postulates that HSP60 expression is induced in arterial endothelial cells as a response to the action of stress factors, notably the classical atherosclerotic risk factors. Autologous HSP60 epitopes exposed on the surface of stressed endothelial cells are recognized by either pre-existing humoral and cellular anti-microbial HSP60 immune reactions or by invoking bona fide autoimmunity based on exposure of altered autologous HSP60 epitopes. The authors accept the importance of well-established atherosclerotic risk factors during atherogenesis, but assign a new role for them in the earliest stages of the disease, viz. acting as stressors [116].
Brain degenerative diseases: Alzheimer's disease
Alzheimer's disease (AD), a heterogeneous and progressive neurodegenerative disease which in Western societies mainly accounts for clinical dementia, is expected in the USA to rise from 4.6 today to 16 millions cases in 2050 [117]. Neuro-pathological hallmarks of AD are neuronal and synapsis loss, extracellular amyloid deposits (neuritic plaques) and intracellular deposition of degenerate filaments (neurofibrillary tangles) [118]. Major clinical manifestations of the disease are memory loss and cognitive impairment [119].
Inflammation clearly occurs in pathologically vulnerable regions of the AD brain, and it does so with the full complexity of local peripheral inflammatory responses. In the periphery, degenerating tissue and the deposition of highly insoluble abnormal materials are classical stimulants of inflammation. Likewise, in the AD brain damaged neurons and neuritis, highly insoluble Aβ42 peptide deposits and neurofibrillary tangles provide obvious stimuli for inflammation. Senile plaques in AD brains are associated with reactive astrocytes and activated microglial cells; cytokines and acute phase proteins are also overexpressed in microglia and astrocytes surrounding neuropathological lesions in AD brains. Inflammatory factors, such as cytokines, chemokines, complement components and acute phase proteins co-localize as secondary components in neuritic or senile plaques, or are over-produced in AD brains. Finally, activated microglia surrounds senile plaques and areas of neurodegeneration [120,121]. There is accumulating evidence that Aβ peptide may promote or exacerbate inflammation by inducing glial cells to release immune mediators. Moreover, microglial and astroglial cells surrounding mature plaques in AD brains have been found to express activation markers. Enriched populations of human microglial cells isolated from mixed cell cultures prepared from embryonic human telencephalon tissues are able to express constitutively mRNA transcripts for cytokines and chemokines and treatment with pro-inflammatory stimuli as lipopolysaccharide or Aβ peptide leads to increased expression of mRNA levels of these inflammatory molecules [122].
The role of inflammation is further emphasized by a number of epidemiological studies demonstrating that the long-term use of nonsteroidal anti-inflammatory drugs may protect against AD. There are now a several published observational studies demonstrating that people who are known to be taking anti-inflammatory drugs considerably reduce their odds of developing AD and population studies have confirmed this negative association [123]. However, alternative hypothesises have been proposed. In particular, this effect has been hypothesised as relating to the ability of these drugs to inhibit angiogenesis. In fact, the brain endothelium secretes the precursor substrate for the β-amyloid plaque and a neurotoxic peptide that selectively kills cortical neurons. So, antiangiogenic drugs targeting the abnormal brain endothelial cell might be able to prevent and treat this disease [124]
The long-term prospective association between dementia and the well known inflammation marker CRP was evaluated in a cohort of Japanese American men. These subjects were seen in the second examination of the Honolulu Heart Program (1968–1970) and subsequently were re-examined 25 years later for dementia in the Honolulu-Asia Aging Study (1991–1996). In a random subsample of 1,050 Honolulu-Asia Aging Study cases and noncases, high-sensitivity CRP concentrations were measured from serum taken at the second examination; dementia was assessed in a clinical examination that included neuroimaging and neuropsychological testing and was evaluated using international criteria. Compared with men in the lowest quartile (<0.34 mg/L) of high-sensitivity CRP, men in the upper three quartiles had a 3-fold significantly increased risk for all dementias, mainly Alzheimer's disease and vascular dementia. These data support the view that inflammatory markers may reflect not only peripheral disease, but also cerebral disease mechanisms related to dementia, and that these processes are measurable long before clinical symptoms appear [125].
On the other hand, several other investigations have shown increased blood levels of some cytokines, such as IL-1β and IL-6, and acute phase proteins α-1-antichymotrypsin, (ACT) in patients with clinical AD [126-129]. Therefore, altered immune responses in the brain and the peripheral blood appeared to be associated with the disease. Finally, plasma levels of ACT also correlated with the degree of cognitive impairment in AD patients from a case-control study [126] suggesting that peripheral markers of inflammation or impaired immune responses could be used for monitoring the progression of the disease.
Elevated levels of IL-6 in both brain homogenates and peripheral blood from AD patients have also been reported [130]. These findings suggest that an important, but still largely unknown, interplay between brain and peripheral immune responses may exist in the disease.
In conclusion, the brain lesions associated with AD, which are referred to as neurofibrillary tangles and senile plaques, are characterized by the presence of a broad spectrum of inflammatory mediators, produced by resident brain cells, including neurons. Although secondary to the fundamental pathology caused by the presence of tangles and plaques, there is strong evidence that inflammation exacerbates the neuronal loss. Accordingly, several reports have appeared indicating that the risk of AD is substantially influenced by several polymorphisms in the promoter region, and other untranslated regions, of genes encoding inflammatory mediators. Alleles that favour increased expression of the inflammatory mediators or alleles that favour decreased expression of anti-inflammatory mediators are more frequent in patients with AD than in controls. The polymorphisms are fairly common in the general population, so there is a strong likelihood that any given individual will inherit one or more of the high-risk alleles [121,127,129-135] (Figure 2).
Figure 2 Alzheimer's disease: amyloid deposition is one the main pathogenetic mechanism. Accumulation of Aβ peptide may be caused by 1) gene mutations (PS1, PS2 and APP human mutations in familial Alzheimer's disease) 2) genotype (and/or phenotype) favoring unbalanced inflammatory responses (pro-inflammatory genotype/anti-inflammatory genotype).
Conclusion
In this presentation we have presented evidence linking innate immunity with the pathogenesis of age-related chronic degenerative diseases. Inflammation may be a pivotal and common background shared by the majority of these pathological conditions. Although evidence already presented has focused on innate immunity, clonotypic immunity has support as an emerging mechanism related to the pathogenesis of these diseases [116].
The evidence that a decline in mortality exists when comparing Swedish cohorts born in the middle of the 18th century to those in the 20th suggests important links between mortality in old age and in early life. Cohort mortality during childhood has been linked to cohort mortality in old age, implying that early exposure to infection is important in determining and imprinting the cohort morbidity phenotype [30]. Thus, chronic inflammatory mechanisms carry the imprint of early-life infections into later life morbidity and mortality. Evidence presented suggests that serological indicators of infection and inflammation in present day populations are related to vascular disease and other morbidities of ageing. Such inflammatory responses can be induced by invading pathogens, as well as by trauma or internal tissue injury. Thus, adaptive responses to short term infections or injury can become maladaptive as life progresses -a double-edged sword that evolutionary biologists refer to as antagonistic pleiotropy [136].
The process of life for the individual is the struggle to preserve its biological and immunological integrity. However, the preservation of the integrity of the organism comes with the price of responsiveness to systemic inflammation [137] which must be finely tuned otherwise dysregulation becomes a damaging accompanynt. With ageing, the reason why the innate immune system becomes over-activated is not clear, but increased exposure to infectious agents or cumulative damage to tissues could spark the change. Inflammation is not 'per se' a negative phenomenon: it is the response of the immune system to pathogenic viruses or bacteria. Thorough out evolution, man has been set to live about 40 or 50 years but in today's world the immune system is active for several decades compared with the past centuries. A long period of activitation may lead to chronic inflammation which inexorably damages several/all organs and is the phenotype linked to both ageing and chronic disease. In cardiovascular disease, conventional risk factors remain important, but differential baselines in inflammatory status may explain why cholesterol levels seem not always directly associated with cardiovascular disease [22,109].
Low-grade inflammation is also associated with parameters such as obesity, smoking, and physical inactivity, so inflammatory mediators constitute a link between life style factors, infections and physiological changes in the process of ageing on the one hand, and risk factors for age-related diseases on the other [28]. This immune response also depends on the genetic background of individuals. In fact, emerging evidence suggests that polymorphic alleles of inflammatory cytokines, involved in high cytokine production, are related to 'unsuccessful' ageing as noted previously with respect to atherosclerosis and AD. On the other hand, controlling inflammatory status may enhance individual chance of achieving 'successful' ageing. So, major findings reporting a relationship between cytokine polymorphisms and longevity suggest that those individuals who are genetically predisposed to produce low levels of inflammatory cytokines or high levels of anti-inflammatory cytokines may have an increased capacity to reach the extreme limit of human life-span [87-89,109,138,139].
In other words, age-related diseases are "the price we pay" for an active immune system that defends us in youth but may harm us later on [139,140]. Such data support the notion that antagonistic pleiotropy [136] plays a relevant role in diseases and longevity. Pro-inflammatory genotypes may therefore be both friends and foes. They are an important and necessary part of the normal host responses to pathogens, but the overproduction of inflammatory molecules may aggravate immune-inflammatory-related disease and contribute to earlier death. An immune system evolved to control pathogens is likely to favour a highly charged pro-inflammatory response programmed to resist fatal infections with avoidance of early mortality. However, persons with low responder genotypes may risk earlier mortality in response to serious infection but if they survive may respond less aggressively to age-related disease development. Such conditions might result in an increased chance of longevity in an environment with reduced pathogenic antigen load and/or adequate medical treatment [139,141,142].
Further studies on this field will open the way for new diagnostic approaches for early diagnosis of relevant pre-clinical states of age-related diseases. It may be possible, before clinical manifestations appear, that anti-inflammatory or other treatments might play a decisive role in preventing or significantly retarding the manifestation of the disease. Other studies focused on clarifying the specific contribution of each immune factor to a given disease will also contribute to the discovery of new drugs and/or innovative intervention protocols specific for these diseases related to ageing.
Acknowledgements
Original work of Authors was supported by grants from the Italian Ministry of Education, University and Research, excofin 40% and 60%, to FL, GC, GCR, DL, CF and CC and FIRB to CF and CC, CURA financial support to FL is also acknowledged. Funds from EU 5FP T-CIA project to CF and Ministry of Health to GCR and CF are also acknowledged. The collaboration between thee "Gruppo di Studio sull'immunosenescenza" coordinated by Prof. C. Caruso and INRCA was enhanced by a cooperation contract (Longevity and elderly disability biological markers).
==== Refs
Medzhitov R Janeway C Jr Innate immunity N Engl J Med 2000 343 338 344 10922424 10.1056/NEJM200008033430506
Janeway C JrMedzhitov R Viral interference with IL-1 and toll signaling Annu Rev Immunol 2002 20 197 216 11861602 10.1146/annurev.immunol.20.083001.084359
Krieger M The other side of scavenger receptors: pattern recognition for host defense Curr Opin Lipidol 1997 8 275 280 9335951
Muzio M Natoli G Saccani S Levrero M Mantovani A The human toll signaling pathway: divergence of nuclear factor kappaB and JNK/SAPK activation upstream of tumor necrosis factor receptor-associated factor 6 (TRAF6) J Exp Med 1998 187 2097 2101 9625770 10.1084/jem.187.12.2097
Guha M Mackman N LPS induction of gene expression in human monocytes Cell Signal 2001 13 85 94 11257452 10.1016/S0898-6568(00)00149-2
Mitchell RN Cotran RS Acute and Chronic Inflammation Robbins Basic Pathology 2003 Saunderrs, Philadelphia, USA
Lio D Caruso C Francesco M Marincola IL-10, Genetic Polymorphism and Its Relevance to Age-related Diseases Interleukin-10 © 2004 Eurekah.com
Bidwell J Keen L Gallagher G Kimberly R Huizinga T McDermott MF Oksenberg J McNicholl J Pociot F Hardt C D'Alfonso S Cytokine gene polymorphism in human disease: on-line databases Genes Immun 1999 1 3 19 11197303 10.1038/sj.gene.6363645
Gabay C Kushner I Acute-phase proteins and other systemic responses to inflammation N Engl J Med 1999 340 448 54 9971870 10.1056/NEJM199902113400607
Pepys MB Hirschfield GM C-reactive protein: a critical update J Clin Invest 2003 111 1805 12 12813013 10.1172/JCI200318921
Candore G Colonna-Romano G Lio D Caruso C Immunological and Immunogenetic markers of successful and unsuccessful ageing Advances in Cell Aging and Gerontology 2003 13 29 45
Pawelec G Ouyang Q Colonna-Romano G Candore G Lio D Caruso C Is human immunosenescence clinically relevant? Looking for 'immunological risk phenotypes' Trends Immunol 2002 23 330 2 12103341 10.1016/S1471-4906(02)02255-X
Pawelec G Akbar A Caruso C Effros R Grübeck-Loebenstein B Wikby A Is immunosenescence infectious? Contribution of persistent Herpes viruses to immunosenescence and influence on human longevity Trends Immunol 2004 25 406 10 15275638 10.1016/j.it.2004.05.006
Lloberas J Celada A Effect of aging on macrophage function Exp Geront 2002 37 1325 1331 10.1016/S0531-5565(02)00125-0
Renshaw M Rockwell J Engleman C Gewirtz A Katz J Sambhara S Cutting edge: impaired Toll-like receptor expression and function in aging J Immunol 2002 169 4697 4701 12391175
Pawelec G Solana R Remarque E Mariani E Impact of aging on innate immunity J Leukoc Biol 1998 64 703 712 9850151
Plackett TP Boehmer ED Faunce DE Kovacs EJ Aging and innate immune cells J Lekoc Biol 2004 76 1 9 10.1189/jlb.1103529
Di Lorenzo G Balistreri CR Candore G Cigna D Colombo A Romano GC Colucci AT Gervasi F Listi F Potestio M Caruso C Granulocyte and natural killer activity in the elderly Mech Ageing Dev 1999 108 25 38 10366037 10.1016/S0047-6374(98)00156-0
Fagiolo U Cossarizza A Scala E Fanales-Belasio E Ortolani C Cozzi E Monti D Franceschi C Paganelli R Increased cytokine production in mononuclear cells of healthy elderly people Eur J Immunol 1993 23 2375 2378 8370415
Bruunsgaard H Pedersen M Pedersen BK Aging and proinflammatory cytokines Curr Opin Hematol 2001 131 131 136 11303144 10.1097/00062752-200105000-00001
Ershler WB Keller ET Age-associated increased interleukin-6 gene expression, late-life diseases, and frailty Annu Rev Med 2000 51 245 270 10774463 10.1146/annurev.med.51.1.245
Baggio G Donazzan S Monti D Mari D Martini S Gabelli C Dalla Vestra M Previato L Guido M Pigozzo S Cortella I Crepaldi G Franceschi C Lipoprotein(a) and lipoprotein profile in healthy centenarians: a reappraisal of vascular risk factors FASEB J 1998 12 433 437 9535215
Dumont P Balbeur L Remacle J Toussaint O Appearance of biomarkers of in vitro ageing after successive stimulation of WI-38 fibroblasts with IL-1alpha and TNF-alpha: senescence associated beta-galactosidase activity and morphotype transition J Anat 2000 197 529 537 11197525 10.1046/j.1469-7580.2000.19740529.x
Vasto S Caruso C Immunity & Ageing: a new journal looking at ageing from an immunological point of view Immun Ageing 2005 2 1 15679897 10.1186/1742-4933-2-1
Pawelec G Barnett Y Forsey R Frasca D Globerson A McLeod J Caruso C Franceschi C Fulop T Gupta S Mariani E Mocchegiani E Solana R T cells and aging Front Biosci 2002 7 d1056 1183 11991846
Franceschi C Bonafe M Valensin S Olivieri F De Luca M Ottaviani E De Benedictis G Inflamm-aging. An evolutionary perspective on immunosenescence Ann N Y Acad Sci 2000 908 208 218 10911960
Franceschi C Bonafe M Centenarians as a model for healthy aging Biochem Soc Trans 2003 31 457 461 12653662 10.1042/BST0310457
Krabbe KS Pedersen M Bruunsgaard H Inflammatory mediators in the elderly Exp Gerontol 2004 39 687 699 15130663 10.1016/j.exger.2004.01.009
Rudin E Barzilai N Inflammatory peptides derived from adipose tissue Immun Ageing 2005 2 1 15679897 10.1186/1742-4933-2-1
Finch CE Crimmins EM Inflammatory exposure and historical changes in human life-spans Science 2004 305 1736 1739 15375259 10.1126/science.1092556
Ridker PM Morrow DA C-reactive protein, inflammation, and coronary risk Cardiol Clin 2003 21 315 325 14621448 10.1016/S0733-8651(03)00079-1
Zhu J Quyyumi AA Norman JE Csako G Waclawiw MA Shearer GM Epstein SE Effects of total pathogen burden on coronary artery disease risk and C-reactive protein levels Am J Cardiol 2000 85 140 146 10955367 10.1016/S0002-9149(99)00653-0
Ferrucci L Harris TB Guralnik JM Tracy RP Corti MC Cohen HJ Penninx B Pahor M Wallace R Havlik RJ Serum IL-6 level and the development of disability in older persons J Am Geriatr Soc 1999 47 639 646 10366160
Harris TB Ferrucci L Tracy RP Corti MC Wacholder S Ettinger WH JrHeimovitz H Cohen HJ Wallace R Associations of elevated interleukin-6 and C-reactive protein levels with mortality in the elderly Am J Med 1999 106 506 512 10335721 10.1016/S0002-9343(99)00066-2
Volpato S Guralnik JM Ferrucci L Balfour J Chaves P Fried LP Harris TB Cardiovascular disease, interleukin-6, and risk of mortality in older women: the women's health and aging study Circulation 2001 103 947 953 11181468
Bruunsgaard H Andersen-Ranberg K Hjelmborg JB Pedersen BK Jeune B Elevated levels of tumor necrosis factor alpha and mortality in centenarians Am J Med 2003 115 278 283 12967692 10.1016/S0002-9343(03)00329-2
Bruunsgaard H Ladelund S Pedersen AN Schroll M Jørgensen T Pedersen BK Predicting death from tumor necrosis factor-alpha and interleukin-6 in 80-year-old people Clin Exp Immunol 2003 132 24 31 12653832 10.1046/j.1365-2249.2003.02137.x
Reuben DB Cheh AI Harris TB Ferrucci L Rowe JW Tracy RP Seeman TE Peripheral blood markers of inflammation predict mortality and functional decline in high-functioning community-dwelling older persons J Am Geriatr Soc 2002 50 638 644 11982663 10.1046/j.1532-5415.2002.50157.x
Mysliwska J Bryl E Foerster J Mysliwski A. Increase of interleukin 6 and decrease of interleukin 2 production during the ageing process are influenced by the health status Mech Ageing Dev 1998 100 313 328 9578118 10.1016/S0047-6374(97)00154-1
Fried LP Tangen CM Walston J Newman AB Hirsch C Gottdiener J Seeman T Tracy R Kop WJ Burke G McBurnie MA Frailty in older adults: evidence for a phenotype J Gerontol A Biol Sci Med Sci 2001 56 M146 M156 11253156
Hamerman D Toward an understanding of frailty Ann Intern Med 1999 130 945 950 10375351
Roubenoff R Hughes V Sarcopenia: current concepts J Gerontol A Biol Sci Med Sci 2000 55 M716 M724 11129393
Brown W A method for estimating the number of motor units in thenar muscles and the changes in motor unit count with aging J Neurosurg Psych 1972 35 845 852
Roubenoff R Catabolism of aging: is it an inflammatory process? Curr Opin Clin Nutr Metab Care 2003 6 295 299 12690262 10.1097/00075197-200305000-00005
Pedersen M Bruunsgaard H Weis N Hendel HW Andreassen BU Eldrup E Dela F Pedersen BK Circulating levels of TNF-alpha and IL-6-relation to truncal fat mass and muscle mass in healthy elderly individuals and in patients with type-2 diabetes Mech Ageing Dev 2003 124 495 502 12714258 10.1016/S0047-6374(03)00027-7
Visser M Pahor M Taaffe DR Goodpaster BH Simonsick EM Newman AB Nevitt M Harris TB Relationship of interleukin-6 and tumor necrosis factor-alpha with muscle mass and muscle strength in elderly men and women: the Health ABC study J Gerontol A Biol Sci Med Sci 2002 57 M326 M332 11983728
Ferrucci L Penninx BW Volpato S Harris TB Bandeen-Roche K Balfour J Leveille SG Fried LP Md JM Change in muscle strength explains accelerated decline of physical function in older women with high interleukin-6 serum levels J Am Geriatr Soc 2002 50 1947 1954 12473005 10.1046/j.1532-5415.2002.50605.x
Greiwe JS Cheng B Rubin DC Yarasheski KE Semenkovich CF Resistance exercise decreases skeletal muscle tumor necrosis factor alpha in frail elderly humans FASEB J 2001 15 475 482 11156963 10.1096/fj.00-0274com
Bruunsgaard H Bjerregaard E Schroll M Pedersen BK Muscle strength following resistance training is inversely correlated with baseline levels of soluble tumor necrosis Factor receptors in the oldest old J Am Geriatr Soc 2004 52 237 241 14728633 10.1111/j.1532-5415.2004.52061.x
Barbieri M Ferrucci L Ragno E Corsi A Bandinelli S Bonafe M Olivieri F Giovagnetti S Franceschi C Guralnik JM Paolisso G Chronic inflammation and the effect of IGF-I on muscle strength and power in older persons Am J Physiol Endocrinol Metab 2003 284 E481 487 12419777
Cappola AR Xue QL Ferrucci L Guralnik JM Volpato S Fried LP Insulin-like growth factor I and interleukin-6 contribute synergistically to disability and mortality in older women J Clin Endocrinol Metab 2003 88 2019 2025 12727948 10.1210/jc.2002-021694
Kern PA Ranganathan S Li C Wood L Ranganathan G Adipose tissue tumor necrosis factor and interleukin-6 expression in human obesity and insulin resistance Am J Physiol Endocrinol Metab 2001 280 E745 E751 11287357
Senn J Klover P Nowak I Mooney R Interleukin-6 induces cellular insulin resistance in hepatocytes Diabetes 2002 51 3391 3399 12453891
Hotamisligil GS Shargill NS Spiegelman BM Adipose expression of tumor necrosis factor-alpha: direct role in obesity linked insulin resistance Science 1993 259 87 91 7678183
Kereiakes DJ Willerson JT Metabolic syndrome epidemic Circulation 2003 108 1552 1553 14517151 10.1161/01.CIR.0000093203.00632.2B
Calle EE Thun MJ Petrelli JM Rodriguez C Heath CW Jr Body-mass index and mortality in a prospective cohort of U.S. adults N Engl J Med 1999 341 1097 105 10511607 10.1056/NEJM199910073411501
Neel JV Diabetes mellitus: a "thrifty" genotype rendered detrimental by "progress"? Am J Hum Genet 1962 14 353 362 13937884
Diamond J The double puzzle of diabetes Nature 2003 423 599 602 12789325 10.1038/423599a
Lazar MA How obesity causes diabetes: not a tall tale Science 2005 307 373 375 15662001 10.1126/science.1104342
Tracy RO Inflammation, the metabolic syndrome and cardiovascular risk Int Clin Pract Suppl 2003 134 10 17
Das U Metabolic syndrome X: an inflammatory condition? Curr Hypertens Rep 2004 6 66 73 14972097
Kern PA Saghizadeh M Ong JM Bosch RJ Deem R Simsolo RB The expression of tumor necrosis factor in human adipose tissue. Regulation by obesity, weight loss, and relationship to lipoprotein lipase J Clin Invest 1995 95 2111 2119 7738178
Yudkin JS Stehouwer CD Emeis JJ Coppack SW C-reactive protein in healthy subjects: associations with obesity, insulin resistance, and endothelial dysfunction: a potential role for cytokines originating from adipose tissue? Arterioscler Thromb Vasc Biol 1999 19 972 978 10195925
Mohamed-Ali V Goodrick S Rawesh A Katz DR Miles JM Yudkin JS Klein S Coppack SW Subcutaneous adipose tissue releases interleukin-6, but not tumor necrosis factor-α, in vivo J Clin Endocrinol Metab 1997 82 4196 4200 9398739 10.1210/jc.82.12.4196
Lundgren CH Brown SL Nordt TK Sobel BE Fujii S Elaboration of type-1 plasminogen activator inhibitor from adipocytes. A potential pathogenetic link between obesity and cardiovascular disease Circulation 1996 93 106 110 8616916
Curat CA Miranville A Sengenes C Diehl M Tonus C Busse R Bouloumie A From blood monocytes to adipose tissue-resident macrophages: induction of diapedesis by human mature adipocytes Diabetes 2004 53 1285 1292 15111498
Perseghin G Petersen K Shulman GI Cellular mechanism of insulin resistance: potential links with inflammation Int J Obes Relat Metab Disord 2003 3 s6 11 14704736 10.1038/sj.ijo.0802491
Haffner SM Insulin resistance, inflammation, and the prediabetic state Am J Cardiol 2003 92 18J 26J 12957323 10.1016/S0002-9149(03)00612-X
Dandona P Aljada A Bandyopadhyay A Inflammation: the link between insulin resistance, obesity and diabetes Trends Immunol 2004 25 4 7 14698276 10.1016/j.it.2003.10.013
Spranger J Kroke A Mohlig M Hoffmann K Bergmann MM Ristow M Boeing H Pfeiffer AF Inflammatory cytokines and the risk to develop type 2 diabetes: results of the prospective population-based European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study Diabetes 2003 52 812 817 12606524
Festa A Hanley AJ Tracy RP D'Agostino R JrHaffner SM Inflammation in the prediabetic state is related to increased insulin resistance rather than decreased insulin secretion Circulation 2003 108 1822 1830 14517163 10.1161/01.CIR.0000091339.70120.53
Temelkova-Kurktschiev T Siegert G Bergmann S Henkel E Koehler C Jaross W Hanefeld M Subclinical inflammation is strongly related to insulin resistance but not to impaired insulin secretion in a high risk population for diabetes Metabolism 2002 51 743 749 12037728 10.1053/meta.2002.32804
Abbatecola AM Ferrucci L Grella R Bandinelli S Bonafe M Barbieri M Corsi AM Lauretani F Franceschi C Paolisso G Diverse effect of inflammatory markers on insulin resistance and insulin-resistance syndrome in the elderly J Am Geriatr Soc 2004 52 399 404 14962155 10.1111/j.1532-5415.2004.52112.x
Hotamisligil GS Budavari A Murray D Spiegelman BM Reduced tyrosine kinase activity of the insulin receptor in obesity-diabetes. Central role of tumor necrosis factor-α J Clin Invest 1994 94 1543 1549 7523453
Kubaszek A Pihlajamaki J Komarovski V Lindi V Lindstrom J Eriksson J Valle TT Hamalainen H Ilanne-Parikka P Keinanen-Kiukaanniemi S Tuomilehto J Uusitupa M Laakso M Finnish Diabetes Prevention Study. Promoter polymorphisms of the TNF-alpha (G-308A) and IL-6 (C-174G) genes predict the conversion from impaired glucose tolerance to type 2 diabetes: the Finnish Diabetes Prevention Study Diabetes 2003 52 1872 1876 12829659
Aljada A Ghanim H Mohanty P Kapur N Dandona P Insulin inhibits the pro-inflammatory transcription factor early growth response gene-1 (Egr)-1 expression in mononuclear cells (MNC) and reduces plasma tissue factor (TF) and plasminogen activator inhibitor-1 (PAI-1) concentrations J Clin Endocrinol Metab 2002 87 1419 1422 11889219 10.1210/jc.87.3.1419
Das M Gabriely I Barzilai N Caloric restriction, body fat and ageing in experimental models Obes Rev 2004 5 13 19 14969503 10.1111/j.1467-789X.2004.00115.x
De Pinho RA The age of cancer Nature 2000 408 248 254 11089982 10.1038/35041694
Caruso C Lio D Cavallone L Franceschi C Aging, Longevity, Inflammation, and Cancer Ann NY Acad Sci 2004 1028 1 13 15915584 10.1196/annals.1322.001
Repetto L Venturino A Fratino L Serraino D Troisi G Gianni W Pietropaolo M Geriatric oncology: a clinical approach to the older patient with cancer Eur J Cancer 2003 39 870 880 12706355 10.1016/S0959-8049(03)00062-5
Thun MJ Henley SJ Gansler T Inflammation and cancer: an epidemiological perspective Novartis Found Synp 2004 256 2 21
Macarthur M Hold GL El-Omar EM Inflammation and Cancer II. Role of chronic inflammation and cytokine gene polymorphisms in the pathogenesis of gastrointestinal malignancy Am J Physiol Gastointest Liver Physiol 2004 286 G515 20 10.1152/ajpgi.00475.2003
Brigati C Noonan DM Albini A Benelli R Tumors and inflammatory infiltrates: friends or foes? Clin Exp Metastasis 2002 19 247 258 12067205 10.1023/A:1015587423262
Balkwill F Mantovani A Inflammation and cancer: back to Virchow Lancet 2001 357 539 545 11229684 10.1016/S0140-6736(00)04046-0
Erlinger TP Platz EA Rifai N Helzlsouer KJ C-reactive protein and the risk of incident colorectal cancer JAMA 2004 291 585 90 14762037 10.1001/jama.291.5.585
McMillan DC Canna K McArdle CS Systemic inflammatory response predicts survival following curative resection of colorectal cancer Br J Surg 2003 90 215 219 12555298 10.1002/bjs.4038
Bonafe M Olivieri F Cavallone L Giovagnetti S Mayegiani F Cardelli M Pieri C Marra M Antonicelli R Lisa R Rizzo MR Paolisso G Monti D Franceschi C A gender – dependent genetic predisposition to produce high levels of IL-6 is detrimental for longevity Eur J Immunol 2001 31 2357 2361 11500818 10.1002/1521-4141(200108)31:8<2357::AID-IMMU2357>3.3.CO;2-O
Lio D Scola L Crivello A Colonna-Romano G Candore G Bonafe M Cavallone L Franceschi C Caruso C Gender-specific association between -1082 IL-10 promoter polymorphism and longevity Genes Immun 2002 3 30 33 11857058 10.1038/sj.gene.6363827
Lio D Scola L Crivello A Colonna-Romano G Candore G Bonafe M Cavallone L Marchegiani F Olivieri F Franceschi C Caruso C Inflammation, genetics, and longevity: further studies on the protective effects in men of IL-10 -1082 promoter SNP and its interaction with TNF-alpha -308 promoter SNP J Med Genet 2003 40 296 299 12676903 10.1136/jmg.40.4.296
Caruso C Candore G Colonna Romano G Lio D Bonafe M Valensin S Franceschi C HLA, aging, and longevity: a critical reappraisal Hum Immunol 2000 61 942 249 11053639 10.1016/S0198-8859(00)00168-3
Shin HD Park BL Kim LH Jung JH Kim JY Yoon JH Kim YJ Lee HS Interleukin 10 haplotype associated with increased risk of hepatocellular carcinoma Hum Mol Genet 2003 12 901 906 12668613 10.1093/hmg/ddg104
Hussain SP Hofseth LJ Harris CC Radical causes of cancer Nature Rev Cancer 2003 3 276 285 12671666 10.1038/nrc1046
Szlosarek PW Balkwill FR Tumor necrosis factor alpha: a potential target for the therapy of solid tumors Lancet Oncol 2003 4 565 573 12965278 10.1016/S1470-2045(03)01196-3
Braunwald E Shattuck lecture – cardiovascular medicine at the turn of the millennium: triumphs, concerns, and opportunities N Engl J Med 1997 337 1360 1369 9358131 10.1056/NEJM199711063371906
Libby P Ridker PM Maseri A Inflammation and atherosclerosis Circulation 2002 105 1135 1143 11877368 10.1161/hc0902.104353
Ross R Atherosclerosis: An inflammatory disease N Engl J Med 1999 340 115 126 9887164 10.1056/NEJM199901143400207
Lusis AJ Atherosclerosis Nature 2000 407 233 241 11001066 10.1038/35025203
Libby P Inflammation in atherosclerosis Nature 2002 420 868 874 12490960 10.1038/nature01323
Rifai N Ridker PM Proposed cardiovascular risk assessment algorithm using high-sensitivity C-reactive protein and lipid screening Clin Chem 2001 47 28 30 11148173
Ridker PM Rifai N Stampfer MJ Hennekens CH Plasma concentration of interleukin-6 and the risk of future myocardial infarction among apparently healthy men Circulation 2000 101 1767 1772 10769275
Hansson GK Libby P Schonbeck U Yan ZQ Innate and aquired immunity in the pathogenesis of atherosclerosis Circulation Res 2002 91 281 291 12193460 10.1161/01.RES.0000029784.15893.10
Ridker PM Hennekens CH Buring JE Rifai N C-reactive protein and other markers of inflammation in the prediction of cardiovascular disease in women N Engl J Med 2000 342 836 843 10733371 10.1056/NEJM200003233421202
Ridker PM Rifai N Rose L Buring JE Cook NR Comparison of C-reactive protein and low-density lipoprotein cholesterol levels in the prediction of first cardiovascular events N Engl J Med 2002 347 1557 1565 12432042 10.1056/NEJMoa021993
Di Iorio A Ferrucci L Sparvieri E Cherubini A Volpato S Corsi A Bonafe M Franceschi C Abate G Paganelli R Serum IL-1beta levels in health and disease: a population-based study. 'The InCHIANTI study' Cytokine 2003 22 198 205 12890453 10.1016/S1043-4666(03)00152-2
Barbieri M Ferrucci L Corsi AM Macchi C Lauretani F Bonafe M Olivieri F Giovagnetti S Franceschi C Paolisso G Is chronic inflammation a determinant of blood pressure in the elderly? Am J Hypertens 2003 16 537 543 12850386 10.1016/S0895-7061(03)00861-6
Nabel EG Cardiovascular disease N Engl J Med 2003 349 60 72 12840094 10.1056/NEJMra035098
Andreotti F Porto I Crea F Maseri A Inflammatory gene polymorphisms and ischaemic heart disease: review of population association studies Heart 2002 87 107 112 11796541 10.1136/heart.87.2.107
Stephens JW Humphries SE The molecular genetics of cardiovascular disease: clinical implications J Intern Med 2003 253 120 127 12542551 10.1046/j.1365-2796.2003.01104.x
Lio D Candore G Crivello A Scola L Colonna-Romano L Cavallone L Hoffmann E Caruso M Licastro F Caldarera CM Branzi A Franceschi C Caruso C Opposite effects of IL-10 gene polymorphisms in cardiovascular diseases and in successful ageing: genetic background of male centenarians is prospettive against coronary heart disease J Med Genet 2004 41 790 794 15466015 10.1136/jmg.2004.019885
Listì F Candore G Lio D Cavallone L Colonna-Romano G Caruso M Hoffmann E Caruso C Association between platelet endothelial cellular adhesion molecule 1 (PECAM-1/CD31) polymorphisms and acute myocardial infarction: a study in patients from Sicily Eur J Immunogenet 2004 31 175 178 15265022 10.1111/j.1365-2370.2004.00464.x
Licastro F Chiappelli M Caldarera CM Tampieri C Nanni S Gallina M Branzi A The concomitant presence of polymorphic alleles of interleukin-1beta, interleukin-6 and apolipoprotein E is associated with an increased risk of myocardial infarction in elderly men. Results from a pilot study Mech Ageing Dev 2004 125 575 579 15336915 10.1016/j.mad.2004.06.008
Benagiano M Azzurri A Ciervo A Amedei A Tamburini C Ferrari M Telford JL Baldari CT Romagnani S Cassone A D'Elios MM Del Prete G T helper type 1 lymphocytes drive inflammation in human atherosclerotic lesions. Proc Natl Acad Sci U S A Epub 2003 100 6658 6663
Gupta S Pablo AM Jiang X Wang N Tall AR Schindler C IFN-gamma potentiates atherosclerosis in ApoE knock-out mice J Clin Invest 1997 99 2752 2761 9169506
Whitman SC Ravisankar P Elam H Daugherty A Exogenous interferon-gamma enhances atherosclerosis in apolipoprotein E-/- mice Am J Pathol 2000 157 1819 1824 11106554
Hansson GK The B cell: a good guy in vascular disease? Arterioscler Thromb Vasc Biol 2002 22 523 524 11950684 10.1161/01.ATV.0000015098.68671.1C
Wick G Knoflach M Xu Q Autoimmune and inflammatory mechanisms in atherosclerosis Annu Rev Immunol 2004 22 361 403 15032582 10.1146/annurev.immunol.22.012703.104644
Brookmeyer R Gray S Kawas C Projections of Alzheimer's disease in the United States and the public health impact of delaying disease onset Am J Public Health 1998 88 1337 1342 9736873
Selkoe DJ Alzheimer's disease: genes, proteins, and therapy Physiol Rev 2001 81 741 766 11274343
Ritchie K Lovestone S The dementias Lancet 2002 360 1759 1766 12480441 10.1016/S0140-6736(02)11667-9
McGeer EG McGeer PL The importance of inflammatory mechanisms in Alzheimer disease Exp Geront 1998 33 371 378 10.1016/S0531-5565(98)00013-8
Licastro F Genomics of immune molecules: early detection of cognitive decline and new therapeutic interventions Expert Rev Neurotherapeutics 2002 2 639 645 10.1586/14737175.2.5.639
Lee YB Nagai A Kim SU Cytokines, chemokines, and cytokine receptors in human microglia J Neurosci Res 2002 69 94 103 12111820 10.1002/jnr.10253
In t' Veld BA Ruitenberg A Hofman A Nonsteroidal antiinflammatory drugs and the risk of Alzheimer's disease N Engl J Med 2001 345 1515 1521 11794217 10.1056/NEJMoa010178
Vagnucci AH JrLi WW Alzheimer's disease and angiogenesis Lancet 2003 361 605 608 12598159 10.1016/S0140-6736(03)12521-4
Schmidt R Schmidt H Curb JD Masaki K White LR Launer LJ Early inflammation and dementia: a 25-year follow-up of the Honolulu-Asia Aging Study Ann Neurol 2002 52 168 174 12210786 10.1002/ana.10265
Licastro F Pedrini S Caputo L Annoni G Davis LJ Ferri C Casadei V Grimaldi LM Increased plasma levels of interleukin-1, interleukin-6 and alpha-1-antichymotrypsin in patients with Alzheimer's disease: peripheral inflammation or signals from the brain? J Neuroimmunol 2000 103 97 102 10674995 10.1016/S0165-5728(99)00226-X
Licastro F Pedrini S Ferri C Casadei V Govoni M Pession A Sciacca FL Veglia F Annoni G Bonafe M Olivieri F Franceschi C Grimaldi LM Gene polymorphism affecting alpha1-antichymotrypsin and interleukin-1 plasma levels increases Alzheimer's disease risk Ann Neurol 2000 48 388 391 10976648 10.1002/1531-8249(200009)48:3<388::AID-ANA16>3.0.CO;2-G
De Luigi A Fragiacomo C Lucca U Quadri P Tettamanti M Grazia De Simoni M Inflammatory markers in Alzheimer's disease and multi-infarct dementia Mech Ageing Dev 2001 122 1985 1995 11589916 10.1016/S0047-6374(01)00313-X
Licastro F Chiappelli M Brain immune responses cognitive decline and dementia: relationship with phenotype expression and genetic background Mech Ageing Dev 2003 124 525 528 12714262 10.1016/S0047-6374(03)00034-4
Licastro F Grimaldi LM Bonafe M Martina C Olivieri F Cavallone L Giovanietti S Masliah E Franceschi C Interleukin-6 gene alleles affect the risk of Alzheimer's disease and levels of the cytokine in blood and brain Neurobiol Aging 2003 24 921 926 12928051 10.1016/S0197-4580(03)00013-7
Candore G Balistreri CR Colonna-Romano G Lio D Caruso C Major histocompatibility complex and sporadic Alzheimer's disease: a critical reappraisal Exp Gerontol 2004 39 645 52 15050301 10.1016/j.exger.2003.10.027
Akiyama H Barger S Barnum S Bradt B Bauer J Cole GM Cooper NR Eikelenboom P Emmerling M Fiebich BL Finch CE Frautschy S Griffin WS Hampel H Hull M Landreth G Lue L Mrak R Mackenzie IR McGeer PL O'Banion MK Pachter J Pasinetti G Plata-Salaman C Rogers J Rydel R Shen Y Streit W Strohmeyer R Tooyoma I Van Muiswinkel FL Veerhuis R Walker D Webster S Wegrzyniak B Wenk G Wyss-Coray T Inflammation and Alzheimer's disease Neurobiol Aging 2000 21 383 421 10858586 10.1016/S0197-4580(00)00124-X
Scola L Licastro F Chiappelli M Franceschi C Grimaldi LM Crivello A Colonna-Romano G Candore G Lio D Caruso C Allele frequencies of +874T – > A single nucleotide polymorphism at the first intron of IFN-gamma gene in Alzheimer's disease patients Aging Clin Exp Res 2003 15 292 295 14661818
Lio D Licastro F Scola L Chiappelli M Grimaldi LM Crivello A Colonna-Romano G Candore G Franceschi C Caruso C Interleukin-10 promoter polymorphism in sporadic Alzheimer's disease Genes Immun 2003 4 234 238 12700599 10.1038/sj.gene.6363964
McGeer PL McGeer EG Polymorphisms in inflammatory genes and the risk of Alzheimer disease Arch Neurol 2001 58 1790 1792 11708985 10.1001/archneur.58.11.1790
Nesse RM Williams GC Evolution and Healing. The New Science of Darwinian Medicine 1995 Weidenfeld & Nicolson, UK
Brod SA Unregulated inflammation shortens human functional longevity Inflamm Res 2000 49 561 570 11131295 10.1007/s000110050632
Franceschi C Olivieri F Marchegiani F Cardelli M Cavallone L Capri M Salvioli S Valensin S De Benedictis G Di Iorio A Caruso C Paolisso G Monti D Genes involved in immune response/inflammation, IGF1/insulin pathway and response to oxidative stress play a major role in the genetics of human longevity: the lesson of centenarians Mech Ageing Dev 2005 126 351 361 15621218 10.1016/j.mad.2004.08.028
Caruso C Candore G Colonna-Romano G Lio D Franceschi C Inflammation and life-span Science 2005 307 208 209 15655081 10.1126/science.307.5707.208
Wick G Berger P Jansen-Durr P Grubeck-Loebenstein B A Darwinian-evolutionary concept of age-related diseases Exp Gerontol 2003 38 13 25 12543257 10.1016/S0531-5565(02)00161-4
Mariani L Turchetti G Franceschi C Chronic antigenic stress, immunosenescence and human survivorship over the 3 last centuries: heuristic value of a mathematical model Mech Ageing Dev 2003 124 453 458 12714253 10.1016/S0047-6374(03)00022-8
Balistreri CR Candore G Colonna-Romano G Lio D Caruso M Hoffmann E Franceschi C Caruso C Role of Toll-like receptor 4 in acute myocardial infarction and longevity JAMA 2004 292 2339 2340 15547160 10.1001/jama.292.19.2339
| 15904534 | PMC1166571 | CC BY | 2021-01-04 16:36:31 | no | Immun Ageing. 2005 May 18; 2:8 | utf-8 | Immun Ageing | 2,005 | 10.1186/1742-4933-2-8 | oa_comm |
==== Front
J Circadian RhythmsJournal of Circadian Rhythms1740-3391BioMed Central London 1740-3391-3-91593263710.1186/1740-3391-3-9ResearchEffect of litter separation on 24-hour rhythmicity of plasma prolactin, follicle-stimulating hormone and luteinizing hormone levels in lactating rabbit does Cano Pilar [email protected]énez Vanessa [email protected]Álvarez Maria P [email protected]ño Mario [email protected] Daniel P [email protected] Ana I [email protected] Departamento de Bioquímica y Biología Molecular III, Facultad de Medicina, Universidad Complutense de Madrid, 28040 Madrid, Spain2 Departamento de Biología Celular, Facultad de Medicina, Universidad Complutense de Madrid, 28040 Madrid, Spain3 Departamento de Producción Animal, E.T.S.I. Agrónomos, Universidad Politécnica de Madrid, Spain4 Departamento de Fisiología, Facultad de Medicina, Universidad de Buenos Aires, 1121 Buenos Aires, Argentina2005 2 6 2005 3 9 9 5 4 2005 2 6 2005 Copyright © 2005 Cano et al; licensee BioMed Central Ltd.2005Cano et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
This work describes the effect of a 48-h litter separation on 24-h patterns of plasma prolactin, FSH and LH concentration in female lactating rabbits kept under a 16:8 light-dark photoperiod (lights on at 0800 h).
Methods
Groups of 6–7 female lactating rabbits maintained with their litters or separated from them for 48 h were killed by decapitation on day 11 post-partum, at 6 different time points throughout a 24-h cycle, starting at 0900 h. Plasma levels of prolactin, FSH and LH were measured by specific double antibody radio-immunoassays.
Results
Plasma level of prolactin in control and separated does changed in a similar way throughout the day, showing two maxima, at 0500–0900 h and at 1700–2100 h, respectively. Litter separation significantly augmented plasma FSH and LH and disrupted their 24-h rhythmicity.
Conclusion
Since previous studies had shown that litter separation for short periods of time augmented sexual receptivity and fertility of the doe, the changes in FSH and LH reported may influence the massive release of gonadotropin releasing hormone, LH and FSH triggered by mating or artificial insemination in litter-separated mothers.
==== Body
Introduction
In nursing rabbits, sexual receptivity and fertility achieved after artificial insemination is depressed during the period of lactation, presumably through a hormonal antagonism between prolactin and gonadotropin release [1-3]. Several studies have demonstrated that separation of the doe from its litter for short periods of time, prior to artificial insemination, is very effective in stimulating ovarian activity in the mother [4-6], with endocrine changes that may explain the activation of ovarian function [7-9] Thus, separation of the does from their litters could be an effective procedure to augment breeding efficiency under farm conditions [5-7].
It must be noted that the published studies on the endocrine changes taking place in the doe after litter separation have been performed at single time points in the daily cycle, usually in the morning, which is an important drawback in view of the circadian nature of the secretion of the pituitary hormones involved [10,11]. Indeed a number of circadian functions have been examined in rabbits [12-17], but there is no information on 24-h pattern of hormone release. This prompted us to undertake the present study whose aim was to examine the effect of litter separation for 48 h on 24-h changes in plasma prolactin (PRL), follicle stimulating hormone (FSH) and luteinizing hormone (LH) levels of the doe. Specifically, we sought to answer two questions: (i) did suppression of a major neuroendocrine and circadian stimulus like the stimulation of nipples by the lactating pup affect the 24-h changes in gonadotropin and prolactin release?; (ii) could the changes in circulating hormone levels be related to augmentation of breeding efficiency found after litter separation from the doe?
Materials and methods
Animals
The study was performed in 84 multiparous, lactating Californian x New Zealand White crossbreed female doe rabbits. Animals were housed in the research facilities of the Animal Production Department, Universidad Politécnica de Madrid, under controlled light-dark cycles (LD 16:8, light on at 8:00 h), housed in individual metal cages, fed at libitum using a commercial pellet diet (Lab Rabbit Chow, Purina Mills, Torrejón de Ardoz, Madrid, Spain) and having access to tap water ad libitum. The study was performed according to the CEE Council Directives (86/609, 1986) for the care of experimental animals. Groups of 6–7 female lactating rabbits were maintained with their litters or separated from them for 48 h, starting at different times (i.e., at 09:00, 13:00, 17:00, 21:00, 01:00 or 05:00 h). Ninety five percent of the does suckled the pups between 03:30 and 04:30 h during the dark period, as has been previously described [16]. On day 11 post-partum, the does were killed by decapitation at 6 different time points throughout a 24-hour cycle starting at 0900 h. Blood was collected from the cervical wound and the plasma was separated to measure prolactin and gonadotropin concentration.
Hormone assays
Plasma prolactin, FSH and LH levels were measured in duplicate samples by specific RIA methods [18] using AFP-991086, AFP-472176 and AFP-3120489 antibodies for prolactin, FSH and LH respectively, supplied by the National Institute of Health (NIH, Bethesda, MD, USA) and Dr. A. F. Parlow (Harbour-UCLA Medical Center, CA, USA). Hormones were labeled with 125I by the Chloramine T-method [19]. The antibody titers used were 1:62,500 for prolactin, 1:45,000 for FSH and 1:250,000 for LH assays, respectively. The volume of plasma used was 10 μl (prolactin assay), 75 μl (FSH assay) and 100 μl (LH assay). Staphylococcus aureus (prepared by the Department of Plant Physiology, U.A.M., Madrid, Spain) was used to precipitate the bound fraction [18]. The assays were previously validated in our laboratory [18]. All samples were measured in the same assay run to avoid inter-assay variations. The limits of detection for prolactin, FSH and LH were 0.125, 0.48 and 0.05 ng/mL respectively. The intra-assay coefficient of variation, calculated from a pool of plasma measured ten times in the same assay, was < 5%.
Statistical analysis
After determining that the homogeneity-of-variance assumption was tenable and that the distribution appeared unimodal and nonskewed, the statistical analysis of results was performed by a two-way factorial analysis of variance (ANOVA). Generally, the factorial ANOVA included assessment of the group effect (i.e. the occurrence of differences in mean values between control and separated groups), of time of day effects (the occurrence of daily changes) and of the interaction between the two factors (separation and time, from which inference about differences in timing and amplitude could be obtained). A one-way ANOVA followed by Student-Newman-Keuls' test was then employed to show which time points were significantly different within each experimental group to define the existence of peaks. A Student's t test was performed to assess differences between the experimental groups at particular time intervals. P values lower than 0.05 were considered evidence for statistical significance.
Results
Figure 1 depicts the plasma prolactin levels through a 24-h cycle in control does and in does separated from their litters for 48 h. Analyzed as a main factor in a factorial ANOVA, significant time of day changes occurred (F = 35.4, p < 0.00001) with absence of any significant effect of litter separation. Both in control and separated does, plasma level of prolactin changed throughout the day showing two maxima, at 0500 – 0900 h and at 1700 – 2100 h, respectively (p < 0.001, Figure 1).
Figure 1 24-h changes in plasma prolactin levels in female lactating rabbits. Groups of 6–7 animals maintained with their litters or separated from them for 48 h were killed by decapitation on day 11 post-partum, at 6 different time points throughout a 24-h cycle, starting at 0900 h. The dark bar indicates scotophase duration. Results are the means ± SEM. Letters indicate the existence of significant differences between time points in each group after a one-way ANOVA followed by a Student-Newman-Keuls' test, as follows: ap < 0.05 vs. 09:00 and 17:00 h, bp < 0.01 vs. 09:00 h, p < 0.05 vs 05:00 h. For further statistical analysis, see text.
Figure 2 shows the 24-h changes in plasma FSH concentration in control does and in does separated from their litters for 48 h. Analyzed as a main factor in a factorial ANOVA, litter separation augmented FSH levels by 37 % (F = 104.6, p < 0.00001). A significant effect of time of day and a significant interaction "time of day x litter separation" were found (F = 41.1 and 23.3, p < 0.00001, respectively), i.e., a single maximum in the first half of the light period was seen in controls whereas two maxima, at 0500 – 0900 h and at 1700 – 2100 h, respectively, were found after litter separation.
Figure 2 24-h changes in plasma FSH levels in female lactating rabbits. Groups of 6–7 animals maintained with their litters or separated from thrm for 48 h were killed by decapitation on day 11 post-partum, at 6 different time points throughout a 24-h cycle, starting at 0900 h. The dark bar indicates scotophase duration. Results are the means ± SEM. Asterisks indicate significance differences with control at that particular time interval (Student's t test, * p < 0.05, ** p < 0.01). Letters indicate the existence of significant differences between time points in each group after a one-way ANOVA followed by a Student-Newman-Keuls' test, as follows: ap < 0.01 vs. all remaining groups, bp < 0.05 vs. 17:00 h, cp < 0.01, vs 09:00, 13:00, 21:00 and 05:00 h, p < 0.05 vs. 17:00 h. For further statistical analysis, see text.
Figure 3 displays the 24-h changes in plasma LH concentrations. A significant effect of litter separation and time of day was apparent (F = 16.1, p < 0.0001 and F = 2.51, p < 0.03, factorial ANOVA). Litter separation brought about a small albeit significant 16% increase in mean circulating LH values. As shown by the significant interaction "time of day x litter separation" found (F = 29.4, p< 0.00001), litter separation disrupted the plasma LH rhythm by phase-shifting its maximum by 12 h, from 1300 h in controls to 0100 h in separated mothers (Figure 3).
Figure 3 24-h changes in plasma LH levels in female lactating rabbits. Groups of 6–7 animals maintained with their litters or separated from them for 48 h were killed by decapitation on day 11 post-partum, at 6 different time points throughout a 24-h cycle, starting at 0900 h. The dark bar indicates scotophase duration. Results are the means ± SEM. Asterisks indicate significance differences with control at that particular time interval (Student's t test, * p < 0.05, ** p < 0.01). Letters indicate the existence of significant differences between time points in each group after a one-way ANOVA followed by a Student-Newman-Keuls' test, as follows: ap < 0.05 vs 21:00, 01:00 and 05:00 h, bp < 0.05, vs 05:00 h, cp < 0.01 vs. 09:00, 21:00, 01:00 and 05:00 h, dp < 0.05 vs. 21:00, 01:00 and 05:00 h. For further statistical analysis, see text.
Discussion
The questions posed in the Introduction may now be answered. First, our results indicate that the 24 h patterns of plasma FSH and LH, but not of prolactin, changed significantly in nursing rabbits after litter separation for 48 h. Second, litter separation disrupted the 24-h rhythmicity of plasma FSH and LH concentration and caused a moderate increase in their concentration (when assessed as the mean 24-h values). Previous studies in the rabbit showed that litter separation for short periods of time augmented sexual receptivity and fertility of the doe [4-9]. Thus, the changes in gonadotropins reported herein could be a reflection of the same mechanisms involved in the massive release of gonadotropin releasing hormone (GnRH), LH and FSH triggered by mating or artificial insemination in litter-separated mothers.
The rabbit exhibits an unusual form of maternal care, with a single and very short visit (3–5 min) every day to nurse [20]. This daily nursing visit of the doe is extremely regular, with some individuals showing a day-to-day variability of only a few minutes. Estrogen, androgen, progesterone and prolactin promote the onset of this behavior in does [21] while its maintenance relies on stimuli from the litter (i.e., maternal responsiveness is altered or abolished by prevention of mother/young contact at parturition or during early lactation). From a number of studies on the distribution of estrogen, androgen and prolactin receptors, quantification of expression of immediate-early genes, and lesions of structures of the olfactory system, it was concluded that rabbits rely on the same hormonal and extrahormonal factors that stimulate maternal behavior in other mammals except for the very peculiar circadian nursing pattern that is unique to rabbits [22-24].
Since the early observations by McNeilly and Friesen [25] it is known that postpartum blood levels of prolactin are similar in lactating and postpartum nonlactating females. Such an observation was confirmed in the present study in which plasma prolactin levels, measured at six time intervals in a 24-h cycle (the closest to nursing time was at 05:00 h), were essentially similar in control and litter-separated does. In lactating females, suckling evoked an immediate increase (3- to 5-fold) in circulating prolactin levels, an effect mimicked by the tactile stimulation of the teats [25]. Likewise, in hares, prolactin levels increased significantly during lactation only after suckling stimuli [26]. It must be noted that, in contrast to rabbits, plasma prolactin levels are significantly changed by nursing in most species, the suckling stimulus being an effective masking signal for the 24-h release of prolactin [27,28]. This does not occur in the doe, the circadian changes of plasma prolactin levels remaining essentially unchanged after litter separation (presumably because of the very short nursing period). This suggests that the circadian secretion of prolactin and the prolactin response to physical stimulation of the nipples are independent phenomena that occur throughout the nursing period.
Previous reports using single sampling procedures [8] indicated that litter separation decreased thr doe's prolactin levels and did not affect FSH. Discrepancies are possibly dependent on the sampling frequency and time of day examined. Collectively, the results underline the importance of performing 24-h studies to have a more precise picture of the hormonal changes.
Litter separation disrupted the 24-h rhythmicity of both FSH and LH significantly. McNeilly [29] suggested that a reduction of plasma LH levels found during the light period could be coupled to an increase of pulsatile pattern of hypothalamic GnRH release. In the present study, the does exhibited, after litter separation, an inverse 24-h pattern of LH release with the lowest values during the light phase of daily photoperiod. Presumably, the disrupted 24-h rhythmicity of LH (and FSH) are linked to the greater mating or artificial insemination-induced release of LH and FSH found in does separated from their litters.
In summary, the present study demonstrates the existence of 24-h variations in circulating prolactin, LH and FSH levels in nursing does. Litter separation for short periods of time, an effective procedure to stimulate ovarian activity prior to artificial insemination, markedly influences the secretory patterns of FSH and LH, a finding that can be related to the higher reflex ovulatory response to mating or artificial insemination observed in does separated from their pups. The specific value of the present study in terms of augmenting breeding efficiency should be further explored.
==== Refs
Theau-Clément M Roustan A A study on relationships between receptivity and lactation in the doe and their influence on reproductive performances J Appl Rabbit Res 1992 15 412 421
Fortum L Bolet G Les effects de la lactation sur les performance de reproduction chez la laprine INRA Prod Anim 1995 8 44 56
Ubilla E Rebollar PG Influence of the postpartum day on plasma oestradiol concentrations, sexual behaviour and conception rate, in artificially inseminated lactating rabbits Anim Reprod Sci 1995 38 337 344 10.1016/0378-4320(94)01366-T
Pavois V LeNaour J Ducep O Perrin G Duperray J A natural method to improve sexual receptivity and fertility in artificially inseminated rabbits Gémes Journées de la Recherche Cunicole la Rochelle 1994 2 528 535
Alvariño JMR Del Arco JA Bueno A Effect of mother-litter separation on reproductive performance of lactating rabbit female inseminated on day 4 or 11 post partum World Rabbit Sci 1998 6 191 194
Maertens L Effect of flushing, mother-litter separation and PMSG on the fertility of lactating does and the performance of the litter World Rabbit Sci 1998 6 185 190
Castellini C Canali C Boiti C Effect of mother-litter separation for 24-hour by closing the nestbox or change of cage, on rabbit doe reproduction performance World Rabbit Sci 1998 6 199 203
Ubilla E Rebollar PG Pazo D Esquifino A Alvariño JMR Effects of doe-litter separation on endocrinological and productivity varibles in lactating rabbits Livestock Prod Sci 2000 67 67 74 10.1016/S0301-6226(00)00196-2
Ubilla E Rebollar PG Pazo D Esquifino AI Alvariño JMR Endocrine profiles during doe-litter separation and the subsequent pregnancy in rabbits J Physiol Biochem 2001 57 23 29
García-Bonacho M Esquifino AI Castrillón PO Reyes Toso C Cardinali DP Age-dependent effect of Freund's adjuvant on 24-hour rhythms in plasma prolactin, growth hormone, thyrotropin, insulin, follicle-stimulating hormone, luteinizing hormone and testosterone in rats Life Sci 2000 66 1969 1977 10821121 10.1016/S0024-3205(00)00522-1
Esquifino AI Chacon F Jimenez V Reyes Toso CF Cardinali DP 24-hour changes in circulating prolactin, follicle-stimulating hormone, luteinizing hormone and testosterone in male rats subjected to social isolation J Circadian Rhythms 2004 2 1 14977425 10.1186/1740-3391-2-1
Jilge B Stahle H The internal synchronization of five circadian functions of the rabbit Chronobiol Int 1984 1 195 204 6600026
Jilge B Hornicke H Stahle H Circadian rhythms of rabbits during restrictive feeding Am J Physiol 1987 253 R46 R54 3605390
Jilge B Restricted feeding: a nonphotic zeitgeber in the rabbit Physiol Behav 1992 51 157 166 1741443 10.1016/0031-9384(92)90218-Q
Jilge B Stahle H Restricted food access and light-dark: impact of conflicting zeitgebers on circadian rhythms of the rabbit Am J Physiol 1993 264 R708 R715 8476114
Jilge B Hudson R Diversity and development of circadian rhythms in the European rabbit Chronobiol Int 2001 18 1 26 11247109 10.1081/CBI-100001275
Jilge B Kuhnt B Landerer W Rest S Circadian temperature rhythms in rabbit pups and in their does Lab Anim 2001 35 364 373 11669321 10.1258/0023677011911831
Ubilla E Alvariño JMR Esquifino AI Agrasal C Effects of induction of parturition by administration of a prostaglandin F2 analogue in rabbits: posible modification of prolactin, LH and FSH secretion patterns Anim Reprod Sci 1992 27 13 20 10.1016/0378-4320(92)90066-M
Greenwood FC Hunter WM Glover JS The preparation of 131I labelled human growth hormone of high specific radioactivity Biochem J 1963 89 114 123 14097352
Zarrow MX Denenberg VH Anderson CO Rabbit: frequency of suckling in the pup Science 1965 150 1835 1836 5892995
Gonzalez-Mariscal G Neuroendocrinology of maternal behavior in the rabbit Horm Behav 2001 40 125 132 11534972 10.1006/hbeh.2001.1692
Gonzalez-Mariscal G Jimenez P Beyer C Rosenblatt JS Androgens stimulate specific aspects of maternal nest-building and reduce food intake in rabbits Horm Behav 2003 43 312 317 12694641 10.1016/S0018-506X(02)00046-6
Gonzalez-Mariscal G Chirino R Flores-Alonso JC Rosenblatt JS Beyer C Intracerebroventricular injections of prolactin counteract the antagonistic effect of bromocriptine on rabbit maternal behaviour J Neuroendocrinol 2004 16 949 955 15667449 10.1111/j.1365-2826.2004.01253.x
Gonzalez-Mariscal G Chirino R Rosenblatt JS Beyer C Forebrain implants of estradiol stimulate maternal nest-building in ovariectomized rabbits Horm Behav 2005 47 272 279 15708755 10.1016/j.yhbeh.2004.11.004
McNeilly AS Friesen HG Prolactin during pregnancy and lactation in the rabbit Endocrinology 1978 102 1548 1554 570485
Caillol M Mondain-Monval M McNeilly AS Pattern of serum concentrations of prolactin and progesterone during pregnancy and lactation in the brown hare (Lepus europaeus) J Endocrinol 1990 124 11 17 2299270
Chang NG Nikitovich-Winer MN Correlation between suckling-induced changes in the ultrastructure of mammotrophs and prolactin release Cell Tissue Res 1976 166 399 406 1253239 10.1007/BF00220134
McNelly AS Lactational control reproduction Reprod Fertil Dev 2001 13 583 90 11999309 10.1071/RD01056
McNeilly AS Lactation and fertility J Mammary Gland Biol Neoplasia 1997 2 291 298 10882312 10.1023/A:1026340606252
| 15932637 | PMC1166572 | CC BY | 2021-01-04 16:39:13 | no | J Circadian Rhythms. 2005 Jun 2; 3:9 | utf-8 | J Circadian Rhythms | 2,005 | 10.1186/1740-3391-3-9 | oa_comm |
==== Front
Nutr JNutrition Journal1475-2891BioMed Central London 1475-2891-4-181592152410.1186/1475-2891-4-18ResearchDevelopment of a semi-quantitative food frequency questionnaire for use in United Arab Emirates and Kuwait based on local foods Dehghan Mahshid [email protected] Hamad Nawal [email protected] AfzalHussein [email protected] Fathimunissa [email protected] Salim [email protected] Anwar T [email protected] Hamilton General Hospital, Population Health Research Institute, 237 Barton, Street East, Hamilton, ON L8L 2X2, Canada2 Administration of Food and Nutrition, Ministry of Health, P.O. Box 42432, Shuwaikh 70655, Kuwait3 Cardiology & Cardio Thoracic Centre, Dubai Hospital, Department of Health & Medical Services, P.O.Box – 7272, Dubai, UAE2005 27 5 2005 4 18 18 9 3 2005 27 5 2005 Copyright © 2005 Dehghan et al; licensee BioMed Central Ltd.2005Dehghan et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
The Food Frequency Questionnaire (FFQ) is one of the most commonly used tools in epidemiologic studies to assess long-term nutritional exposure. The purpose of this study is to describe the development of a culture specific FFQ for Arab populations in the United Arab Emirates (UAE) and Kuwait.
Methods
We interviewed samples of Arab populations over 18 years old in UAE and Kuwait assessing their dietary intakes using 24-hour dietary recall. Based on the most commonly reported foods and portion sizes, we constructed a food list with the units of measurement. The food list was converted to a Semi-Quantitative Food Frequency Questionnaire (SFFQ) format following the basic pattern of SFFQ using usual reported portions. The long SFFQ was field-tested, shortened and developed into the final SFFQ.
To estimate nutrients from mixed dishes we collected recipes of those mixed dishes that were commonly eaten, and estimated their nutritional content by using nutrient values of the ingredients that took into account method of preparation from the US Department of Agriculture's Food Composition Database.
Results
The SFFQs consist of 153 and 152 items for UAE and Kuwait, respectively. The participants reported average intakes over the past year. On average the participants reported eating 3.4 servings/d of fruits and 3.1 servings/d of vegetables in UAE versus 2.8 servings/d of fruits and 3.2 servings/d of vegetables in Kuwait. Participants reported eating cereals 4.8 times/d in UAE and 5.3 times/d in Kuwait. The mean intake of dairy products was 2.2/d in UAE and 3.4 among Kuwaiti.
Conclusion
We have developed SFFQs to measure diet in UAE and Kuwait that will serve the needs of public health researchers and clinicians and are currently validating those instruments.
==== Body
Background
The residents of the Arab countries in the Persian Gulf region have become more sedentary and have dramatically changed their diet over the last two decades. They consume more fat, meat, sugar, rice and wheat flour than before [1-4]. This has resulted in a rise in obesity, diabetes, and cardiovascular disease prevalence. There is a need to study the relation between diet and chronic diseases in this population, but there is no customized instrument to do so. The Food Frequency Questionnaire (FFQ) is the most commonly used method to assess diet in relation to chronic disease [5]. Based on a complete search of the literature (using Medline medical subject heading and text words) and personal communication with nutritionists in United Arab Emirates and Kuwait Universities, we decided to develop a SFFQ and accompanying food composition database for UAE and Kuwait.
Subjects and methods
Population
Our sample consisted of 326 apparently healthy persons of Arab origin, between the ages of 18 and 65 years, living in UAE and Kuwait in 2003–2004. Of these 126 provided information using the 24-hour dietary recall, and 200 participated in the testing of the long-FFQ in the SFFQ development.
Development of the semi-quantitative food frequency questionnaire
To develop the SFFQ we went through the following steps: construction of a food list, definition of portion sizes, and assignment of frequency of consumption, pilot test of long-FFQ and assembling the selected food list into SFFQ.
24-hour Dietary Recall (DR)
Qualified nutritionists interviewed the participants. The nutritionists asked the participants what they ate in the previous 24-hours in direct chronological order from the first foods in the morning to the last foods before breakfast on the day of the interview. To standardize data collection, we prepared a manual of procedures for the interviewers. The interviewers used a food atlas modified from "Food portion sizes: A photographic Atlas" [6] containing coloured pictures of 8 different portion sizes of foods commonly eaten in UAE and Kuwait.
We constructed a long food list from information we obtained from the 24-hour dietary recalls, and supplemented it with foods derived from popular cookbooks, and suggestions of experienced local dieticians. We obtained the range of portion sizes from the 24-hour dietary recall and cookbooks. For items such as eggs we considered one of those items as a portion. For fruits such as banana or orange, a medium size was considered to be a "unit" of the fruit. For foods with non-unitary measures, such as grapes, we considered 1/2 cup to be one unit. For other foods one unit of a utensil that was mostly reported by respondents was assumed as one portion size. To get an estimate of the usual portion we used the mode of the portion size distribution for each food reported.
We formatted the SFFQ based on the pattern of the Harvard FFQ. We organized the main foods by the traditional food groups into seven food categories: 1. Milk, milk products and fats (including milk with different amounts of fat, Labnah, etc.), 2. vegetables (fresh or cooked), 3. fruit, 4. meat, eggs and meat products (including meat organs), 5. cereal and cereal product, 6. beverages 7. sweet and baked goods (Faaloodah, baklava, etc.) and nuts like almond, and hamoose.
To distinguish the fibre content of the diet and the quality of carbohydrates, we differentiated between the types of consumed cereal and cereal products (white or wholemeal bread, whole grain). In the last section of the FFQ we asked about type of cooking oils and fats and also, minerals including calcium, iron, zinc and multivitamins.
We used 9 categories to assess frequency of intake varying from "never or less than once a month to 6 or more times per day. For each food item, participants indicated their average frequency of consumption over the past year of a specified serving size by checking 1 of the 9 frequency categories. For foods that contain an extremely high amount of a particular nutrient but are used infrequently, such as liver, we re-categorized the options for frequency of intake. For instance, we used eliminated options of higher intake (once per day) but distinguished between never and less than once a month at the lower end. We will compute the daily intake based on the midpoint of the reported frequency category for each food item; for example we will take a response of "2–4/week" to be 3/7 or 0.43 times/day.
Although most fruits and vegetables are available year round in UAE and Kuwait, their intakes may vary depending upon cost and cultural preferences of foods by season. For this reason we designed specific questions for fruit and vegetable consumption by season. We determined the length of the season from local experts who used their experience.
We pilot tested the long-FFQ among 200 participants from the same populations (but not those who participated in the 24 hr DR). The objectives were to determine the completeness of the food list and to shorten the food list by deleting foods that were not commonly consumed. Based on the analysis of the pilot we completed the food list and created SFFQ.
Food Composition Database
We will use the food composition database to convert intakes of foods into nutrients. We constructed one nutrient database for UAE and Kuwait, as most foods are similar in both countries. We extracted the nutrient contents of the food items from Table SR17 of the USDA food database, which is available online, as the starting point to establish the database . From SR17 we chose those varieties of food items which are not very specific to a region and are more representative, for example; for apple we chose "apples, raw, with skin (NDB No:09003)" or for orange, we chose "oranges, raw – all commercial varieties (NDB No: 09200)". We used Statistical analyses SPSS 10.1 for windows (SPSS Inc, Chicago IL) for all analyses.
Results
There were 326 participants with different occupations in Kuwait and UAE in our study. The populations were similar in UAE and Kuwait with respect to age, sex distribution, and BMI, but Kuwaiti women had higher education levels than those in UAE (Tables 1 and 2). No significant differences were noted between female and male respondents with respect to BMI (P = 0.4, 0.5 for UAE and Kuwait, respectively). However, in UAE, women had a higher mean BMI than men while in Kuwait men were heavier than women.
Table 1 Demographic characteristics of UAE participants
Men (N = 35) Women (N = 91) Overall (N = 126)
Age 43.0 ± 11 34.3 ± 10 37.0 ± 11
BMI (kg/m2) 27.4 ± 4 28.7 ± 7 28.3 ± 7
Education
None 22.7% 10% 13%
Primary school 9.0% 8% 9%
Secondary school 23% 30% 31%
Trade School 32% 3% 2%
University 23% 49% 45%
Income (Dirham)
<5000 12.5% 9% 11%
5001–10000 12.5% 63% 60%
10001–15000 19% 24% 22%
>15000 12.5% 4% 6%
Table 2 Demographic characteristics of Kuwaiti participants
Men (N = 56) Women (N = 145) Overall (N = 201)
Age 45.6 ± 14.0 37.3 ± 12 39.6 ± 13.3
BMI (kg/m2) 26.6 ± 7 25.9 ± 5 26.0 ± 6
Education
None 0% 0% 0%
Primary school 0% 5% 4%
Secondary school 32% 18% 21%
Trade School 5% 4% 4%
University 64% 72% 70%
Income
<500 68% 31% 61%
501–1000 32% 54% 36%
>1000 0% 15% 3%
Daily food intake
The estimated daily intakes of seven major food groups among Kuwaiti and UAE men and women are shown in Tables 3 and 4. On average the participants in UAE reported eating 3.4 servings/d of fruits and 3.1 servings/d of vegetables versus 2.8 servings/d of fruits and 3.2 servings/d of vegetables in Kuwait. Cereals are an important staple in the diet of both countries and the participants reported eating cereals 4.8 times/d in UAE and 5.3 times/d in Kuwait. All participants reported consuming cereals at least once per day. Meat was consumed nearly two times/day in both countries and among the meat group, poultry was consumed more often than red meat or fish. The mean intake of dairy products was 2.2/day in UAE and 3.4/day in Kuwait.
Table 3 Average daily intake of main foods estimated by long-FFQ reported by UAE participants (Men = 24, Women = 76)
Sex Foods Min Max Mean Std. Deviation
Women Fruits 0.2 8.5 3.0 1.7
Vegetables 0.4 7.9 3.0 1.5
Dairy products 0.0 5.2 2.1 1.0
Meat 0.6 4.2 1.7 0.7
Cereals and cereal products 0.7 10.7 4.7 2.2
Beverages 0.0 9.5 3.4 2.1
Baked goods 0.0 3.4 0.5 0.5
Men Fruits 1.8 8.8 4.8 2.0
Vegetables 0.3 6.6 3.7 1.6
Dairy products 0.4 7.0 2.5 1.3
Meat 0.6 4.4 2.3 0.9
Cereals and cereal products 1.5 6.6 5.0 1.2
Beverages 1.3 8.5 5.0 1.9
Baked goods 0.0 2.1 0.8 0.6
Overall Fruits 0.2 8.8 3.4 1.9
Vegetables 0.2 7.9 3.1 1.6
Dairy products 0.2 7.1 2.2 1.1
Meat 0.6 4.4 1.9 0.8
Cereals and cereal products 0.7 10.8 4.8 2.0
Beverages 0.0 9.5 3.8 2.2
Baked goods 0.0 3.4 0.6 0.5
Table 4 Average daily intake of main foods estimated by long-FFQ reported by Kuwaiti participants (Men = 22, Women = 78)
Sex Foods Min Max Mean Std. Deviation
Women Fruits 0.4 8.1 2.8 1.7
Vegetables 0.0 10.5 3.3 2.2
Dairy products 0.0 9.7 3.3 2.3
Meat 0.2 9.9 1.8 1.3
Cereals and cereal products 0.7 20.1 4.9 3.2
Beverages 0.0 11.1 2.9 2.3
Baked goods 0.0 5.0 1.0 1.0
Men Fruits 0.5 7.3 3.1 1.8
Vegetables 0.3 6.5 3.0 1.9
Dairy products 0.4 6.6 3.5 1.7
Meat 0.4 6.6 2.5 1.6
Cereals and cereal products 2.3 12.8 6.5 2.4
Beverages 0.0 9.3 4.0 2.7
Baked goods 0.0 5.7 1.2 1.5
Overall Fruits 0.4 8 2.8 1.7
Vegetables 0.00 10.5 3.2 2.1
Dairy products 0.00 9.7 3.4 2.3
Meat 0.2 9.9 1.9 1.4
Cereals and cereal products 0.7 20.1 5.3 3.1
Beverages 0.0 5.7 1.0 1.1
Baked goods 0.0 11.0 3.1 2.4
Frequency of consumed food
Tables 6 and 7 show the frequency of consumption of some foods in UAE and Kuwait. About 32% of respondents in UAE and 26% of Kuwaiti respondents reported that they had at least one glass of milk daily on average in the past year. Sixty-eight percent of UAE participants and 48% of Kuwaiti participants reported consuming rice at least once per day. 67% and 51% of people (UAE and Kuwaiti respectively) ate an egg at least 2 times/week. Overall in UAE, 86% of participants did not eat chicken with skin while in Kuwait 42% of participants did not eat chicken with skin. Among fruits, apples, oranges and bananas were consumed very frequently.
Nutrient database
To convert local mixed dishes to nutrients, we created a new nutrient database appropriate for local foods (Table 5). Therefore, a local nutritionist collected 2 recipes from each low, middle and high-income family. We supplemented these recipes from the "Food composition: Kuwaiti composite dishes" [7] and other popular cookbooks. The average amount of ingredients from those recipes was used to create a base recipe for the nutrient database. We matched ingredients of the recipes with the appropriate food items in the USDA database to obtain nutrient content, taking cooking method into account. The SFFQ for UAE is in Appendix I and the SFFQ for Kuwait is in Appendix II.
Table 5 Nutrient composition per serving (100 g) of some commonly eaten foods in UAE and Kuwait
Vitamins (mg)
Food Total calories (Kcal) CHO (g) Fat (g) Protein (g) Fiber (g) A (RE,μ) (α) Folate (μ) B1 B6 B12 C E Ca (mg) Phosphorus (mg) Iron (mg)
Mixed dish
Kofta 173 3.1 11.1 15.0 0.6 63.1 14.1 0.09 0.26 1.7 12.6 0.1 23.7 128 1.6
Qouzi 206 15.0 11.2 10.5 0.6 5.1 36.7 0.1 0.1 0.9 2.3 0.3 18.0 90.3 1.4
Marga Laham 95 7.1 4.0 7.5 0.8 19.0 4.6 0.07 0.2 0.7 7.0 0.04 7.1 65.4 0.8
Jereesh 226 29.7 7.0 12.9 5.2 13.9 22.7 0.2 0.2 0.7 3.5 0.4 21.1 252 2.1
Sweets
Balalett 210 35 4.7 6.6 0.1 Trace 10 0.01 0.06 Trace Trace 0.5 28.5 105 1.5
Elba 264 30.6 12.6 11.3 Trace 206 25 0.1 0.1 1.3 1.1 0.6 522 356 2.1
Discussion
In this paper, we have described the development of a semi-quantitative FFQ and food composition database for the Arab population in UAE and Kuwait. The goals of diet assessment in epidemiologic studies are to obtain a measure of usual rather than current diet, and rank people by intake, in contrast to clinical settings where current absolute intake is more important. The FFQ has been developed with these purposes in mind and has become the standard method to collect dietary data in studies of chronic disease all over the world. We opted to use a semi-quantitative FFQ, which estimated food intake in categories rather than the exact frequency, because it has been shown that there is minimal loss of information in estimating nutrient intakes using food intake categories [8]. We also asked the participants about intakes of pre-specified portion sizes rather than asking them to estimate their regular portion size. Correlations for nutrient intake calculated using the FFQ with and without taking portion sizes into account were over 0.9 [5]. The advantage of using categories to estimate food intake and pre-specified portion sizes is that the SFFQ becomes easier to administer, and likely, more reliable. We did not attempt to make a comprehensive list of foods to include in the SFFQ. Rather, we kept items in the SFFQ if they were nutrient rich, consumed frequently and discriminated intakes between individuals. The other criterion we considered together with the nutrient content (including caloric value) was the presence of other substances of interest, for instance, caffeine. Most FFQs have between 100–150 items [9] and our SFFQ has 153 (UAE) and 152 (Kuwait) items. Increasing the number of items in the FFQ has been shown to increase over-reporting [10].
To estimate nutrient intake from SFFQ, there is a need for a food composition table listing the average nutrient content of foods contained in the SFFQ. To obtain nutrient intake we multiplied the average nutrient content of a specified portion of food listed in the food composition table by the average frequency of intake reported in the SFFQ. The food composition table can be a substantial source of variation in the estimation of nutrients using the SFFQ. As no nutritional database has ever been gathered in UAE or Kuwait, we used the US Department of Agriculture nutrient database as our standard to estimate nutrient content. The advantages of this approach are: First, the USDA food composition database is probably the most comprehensive in the world. For example, there are 26 categories of spinach including different types of spinach, raw spinach, and spinach cooked in a variety of ways [11], allowing us to choose the most appropriate one. Second, the nutrient estimation assays have been done in a standardized manner. Third, it has the largest number of nutrients reported. Fourth, the USDA food composition database is continually updated. Last, UAE and Kuwait import foods from all around the world and a mixture of food items from different regions are available in any market. For mixed dishes that were not listed in the USDA database, we calculated nutrient intake by analyzing recipes. Moreover, there are nearly 150 food composition tables in use around the world and their values are primarily based on USDA [12-14], and even European countries include nutrient information from USDA in their food composition tables [15,16]. Finally, similar approaches have been taken by other investigators in Israel, [17] and Costa Rica [18].
A limitation of this study is that the age groups represented in the UAE and Kuwait sample are mostly <50 years for both males and females. Thus, the overall impression in dietary habits is biased towards this younger group. For example, the consumption of rice as well as dates might be underestimated. The way to make it more accurate is of course to repeat it (validate). Another limitation of this study is that most participants from both countries were women and some foods, which men may eat, may be underestimated. However, a nutritionist with experience in those countries reviewed the food lists to ensure their completeness.
Conclusion
The validated questionnaire and food composition database will not only be useful tools for our own study, but they will also be assets that other researchers in the region can use or adapt to suit their needs. We have enclosed two SFFQs in this article so other researchers in the field of public health can use this comprehensive SFFQ. We are currently evaluating SFFQs and the validated SFFQ will be available online for all public health researchers in the region.
List of Abbreviations
SFFQ Semi-Quantitative Food Frequency Questionnaire
24 hr DR 24 hour Dietary Recall
UAE United Arab Emirates
PURE Prospective Urban and Rural Epidemiologic
SPSS Statistical Packages for Social Sciences
Authors' contributions
MD Participated in design of study, coordinated and performed statistical analysis, drafted the manuscript
AM Participated in design of study, performed statistical analysis, helped to draft the manuscript
NH Coordinated study in Kuwait, helped to draft the manuscript
AY Facilitated data collection in UAE, helped to draft the manuscript
FN Coordinated study in UAE
SY Participated in design of study, helped to draft the manuscript
All authors read and approved the final manuscript.
Acknowledgements
The authors acknowledge the contribution of Mrs. Sumathy Rangarajan who supported the fieldwork during the data collection phase and are grateful to the nutritionists who collected the dietary data in Kuwait and UAE and Mrs. Pam Mackie for secretarial support. We are grateful to the participants of the study for their cooperation. We also wish to thank Dr. Yusuf (Director of Population Health Research Institute) for all his support and guidance. We also acknowledge the "Sheikh Hamdan bin Rashid Al Makhtoum Award for Medical Sciences" for their Grant no. MGR-16/2001–2002 for the UAE portion of the study.
==== Refs
Alawadi F Amine EK Overweight and Obesity in Kuwait Journal of the Royal Society of Health 1989 109 175 177 2509705
Musaiger AO Nutrition Situation in the Arabian Gulf Countries Journal of the Royal Society of Health 1985 105 104 106 3925140
Musaiger AO Sungpuag P Composition of Mixed Dishes Commonly Consumed in the Arabian Gulf States Ecology of Food and Nutrition 1985 16 153 160
Musaiger AO Sociocultural and Economic-Factors Affecting Food-Consumption Patterns in the Arab Countries Journal of the Royal Society of Health 1993 113 68 74 8478894
Willett W Willett W Food Frequency Methods Nutritional Epidemiology 1998 5 Second New York, Oxford University Press
M N M A J M A photographic Atlas of Food Portion Sizes 1997
Sawaya food composition: Kuwaiti composite dishes 1997
Willett W Lenart E Willett W Reproducibility and Validity of Food-Frequency Questionnaires Nutritional Epidemiology 1998 6 Second New York, Oxford University Press
W W Future directions in the development of food-frequecny questionnaires Am J Clin Nutr 1994 59 171S 4S 8279418
P P AM H E H Reproducibility and validity of dietary assessment instruments: II. A qualitative food frequency questionnaire Am J Epidemiol 1988 128 667 76 2843041
USDA National Nutrient Database for Standard Reference Release 17 2004
Garcia V Rona RJ Chinn S Effect of the choice of food composition table on nutrient estimates: a comparison between the British and American (Chilean) tables
1 Public Health Nutrition 2004 7 577 583 15153265 10.1079/PHN2003555
WM R AT P SP M JC K Compiling Data for Food Composition Data Bases 1991 United Nation University Press
W W Nutrition Epidemiology 2 AD
Hakala P Knuts LR Vuorinen A Hammar N Becker W Comparison of nutrient intake data calculated on the basis of two different databases. Results and experiences from a Swedish-Finnish study
14 European Journal of Clinical Nutrition 2003 57 1035 1044 12947420 10.1038/sj.ejcn.1601639
Deharveng G Charrondiere UR Slimani N Southgate DAT Riboli E Comparison of nutrients in the food composition tables available in the nine European countries participating in EPIC
1 European Journal of Clinical Nutrition 1999 53 60 79 10048800 10.1038/sj.ejcn.1600677
Shai I Vardi H Shahar DR Azrad AB Fraser D Adaptation of international nutrition databases and data-entry system tools to a specific population Public Health Nutrition 2003 6 401 406 12795829 10.1079/PHN2002445
H C 2004
| 15921524 | PMC1166573 | CC BY | 2021-01-04 16:39:31 | no | Nutr J. 2005 May 27; 4:18 | utf-8 | Nutr J | 2,005 | 10.1186/1475-2891-4-18 | oa_comm |
==== Front
Reprod Biol EndocrinolReproductive biology and endocrinology : RB&E1477-7827BioMed Central London 1477-7827-3-201592707610.1186/1477-7827-3-20ResearchTGF-beta expression during rat pregnancy and activity on decidual cell survival Shooner Carl [email protected] Pierre-Luc [email protected]échette-Frigon Guylaine [email protected] Valérie [email protected]éry Marie-Claude [email protected] Eric [email protected] Département de Chimie-Biologie, Groupe de Recherche en Biopathologies Cellulaires et Moléculaires, Université du Québec à Trois-Rivières, C.P. 500, Trois-Rivières, Québec, G9A 5H7, Canada2005 31 5 2005 3 20 20 27 4 2005 31 5 2005 Copyright © 2005 Shooner et al; licensee BioMed Central Ltd.2005Shooner et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
During early rat pregnancy, trophoblast of the tiny embryo joins with the endometrium and epithelial cells undergo apoptosis. Near the end of pregnancy, regression of the decidua basalis (DB) is also observed (from day 14 to 20). However, little is known about the intra-cellular and molecular mechanisms involved in apoptosis regulation in the uterus during pregnancy. The objective of the present study was to investigate the presence and the developmental expression of transforming growth factor-beta isoforms (TGF-beta well known differentiation factor) in the rat endometrium throughout pregnancy and its action in vitro using cultured endometrial stromal cells.
Methods
In vivo: Rats were killed at different days of pregnancy (days 2–20) and uteri removed to collect endometrial protein extracts or the uteri were fixed, embedded and sectioned for immunohistochemistry (IHC) and in situ cell death analyses using TdT-mediated dUTP nick end labeling (TUNEL). In vitro: Rats were ovariectomized and decidualization was induced using sex steroids. Endometrial stromal decidual cells were then collected and cultured.
Results
An increase of apoptosis in the DB on days 14, 16 and 18 was observed. Cleaved caspase-3 was clearly detected during regression of the DB by Western analysis and immunofluorescence. Western analyses using endometrial protein extracts demonstrated that TGF-beta1, TGF-beta2 and TGF-beta3 were highly expressed at the time of DB regression (day 14). During early pregnancy, TGF-beta1 and -beta2 expressions raised at days 5.5 to 6.5. TGF-beta3 protein was not detected during early pregnancy. IHC analyses revealed that TGF-beta1 and -2 were found surrounding both epithelium (luminal and glandular) in the stroma compartment at the implantation site, and TGF-beta3 was mainly located surrounding endometrial epithelium in the stroma compartment. Smad2 phosphorylation was increased at the time of DB regression. In vitro studies using decidual endometrial stromal cells revealed that TGF-beta1 induced apoptosis and Smad2 phosphorylation. Moreover, TGF-beta1 reduced both Akt (a well known survival factor) phosphorylation and XIAP (X-linked inhibitor of apoptosis protein) expression in decidual endometrial stromal cells in vitro.
Conclusion
Taken together, these results suggest that TGF-beta isoforms are regulated differently during pregnancy and may have an important role in the control of apoptosis and cell survival at specific stages during pregnancy.
==== Body
Background
Apoptosis is a type of programmed cell death and is a natural phenomenon occurring when the cells are subjected to stress such as DNA damage, death signals or lack of growth factor. Apoptotic stimuli allow an intracellular cascade of signals such as the caspases, a family of cysteine proteases implicated in the cleavage of a number of important proteins which results in cell disassembly and cell death, phagocytosis and removal of cell debris by immune cells. Apoptosis plays an important role during embryo implantation in rodents where morphological characteristics of apoptosis are observed in endometrial epithelial cells at the embryo implantation site [1-3]. Moreover, this phenomenon also occurs during late pregnancy, especially during regression of the decidua basalis (DB) in the rat endometrium [4,5]. Two decidual zones are formed during pregnancy: the primary decidual zone on the antimesometrial side of the uterus and the secondary decidual zone (or antimesometrial decidua) which is formed following expansion of the primary decidual zone [5,6]. The secondary decidual zone eventually transforms stromal cells in the mesometrial region to form the DB that regresses following day 14 of pregnancy [7]. Whether the phenomenon of growing size of embryo is a cause or correlation to the increase of apoptosis remains to be elucidated.
The first members of the transforming growth factor-beta (TGF-β) superfamily were identified on the basis of their ability to induce a transformed phenotype of certain cells in culture [8]. They are now known as multifunctional polypeptides involved in the regulation of cell proliferation and differentiation, immunoregulation, angiogenesis and the regulation of extracellular matrix [9,10]. They act via cellular signalling through Smads and Phosphorylated-Smads (P-Smads), the active form of Smads. Those proteins are translocated to the nucleus and activate transcription factors which in turn activate caspases and other regulation proteins [11,12]. Another characteristic of TGF-β is its capacity to induce apoptosis in several cell types [7,13]; in fact, TGF-β was shown to have a pro-apoptotic function mediated by caspases [14-16]. Genes encoding the three isoforms are localized on different chromosomes and the isoforms molecular weights are slightly different: 15, 12.5 and 12 KDa for TGF-β1, β2 and β3 respectively; they share 80 % sequence identity and are produced in latent forms which are activated into a 112-amino acid mature peptide [17]. Multiplicity of TGF-β isoforms and sequence conservation within each form through evolution suggests important specific roles. Moreover, it has been demonstrated that TGF-β1, -β2 and -β3 are differently expressed in the mouse uterus [18] and porcine conceptus-maternal interface [19,20].
The uterus is a hormone-dependent organ and it is subject to an abundant amount of cellular proliferation and cell death. Studies have shown that apoptosis is increased in the rat endometrium during implantation and regression of the decidual basalis in the rat [1,2,21]. The mRNA for TGF-β1 has been shown to be present within the uterus during rat pregnancy and was localized to the luminal and glandular epithelial cells during early and late pregnancy [22]. TGF-β1 and -β2 mRNAs were also found in the mouse uterus during pregnancy [23-25]. Expression of TGF-β2 and TGF-β3 mRNAs were also shown to be expressed in the mouse periimplantation uterus [18]. A study showed that TGF-β1 and -β2 treatments on cultured endometrial rat stromal cells induced apoptosis [7]. These studies suggest that TGF-β isoforms might be involved specifically in the control of apoptosis in the uterus during pregnancy. However, the mechanisms involved in the control of apoptosis in the endometrium during pregnancy are poorly documented. Studies suggesting the importance of TGF-β isoforms at specific time of pregnancy were done at the mRNA level and it is important to determine their presence at the protein level. Thus, the aim of this study was to determine the expression and the developmental expression of TGF-β1, β2 and β3 proteins in the rat uterus throughout pregnancy and to further determine in vitro, the effect of TGF-β in determining decidual cell fate. We found that the three isoforms of TGF-β were expressed and regulated differently in epithelial and stromal endometrial cells during rat pregnancy and showed using primary decidual cell cultures the involvement of TGF-β in the regulation of programmed cell death. Moreover, the present study shows that TGF-β signals through Smad2, which coincide with XIAP and Akt down regulation and induction of apoptosis.
Methods
Reagents
TGF-β1 (sc-146, lot # F262, 200 μg/ml), TGF-β2 (sc-90, lot # B202, 200 μg/ml) and TGF-β3 (sc-82, lot # A222, 200 μg/ml) polyclonal antibodies were purchased from Santa Cruz Biotechnology, Inc (Santa Cruz, CA, USA). CDC47/MCM7 antibody was obtained from Medicorp (Montréal, QC, Canada). Phospho-Akt (Ser 473), Akt, XIAP, Cleaved caspase-3, and Phospho-Smad2 (Ser 465 / 467) antibodies were obtained from Cell Signaling Technology (Beverly, MA, USA). The Keratin 8/18 antibody used to determine cell culture purity was donated by Dr Monique Cadrin (Univ. of Québec at Trois-Rivières, QC, Canada). Anti-Smad2/3 antibody was purchased from Calbiochem (San Diego, CA, USA). Vectastain ABC Kit for rabbit IgG was purchased from Vector Laboratories Inc. (Burlingame, CA, USA). In Situ Cell Death detection kit (TUNEL), POD and DAB substrate was obtained from Roche (Laval, QC, Canada). TGF-β1 recombinant protein was purchased from Biosource (Cat # PHG9104, lot # 16865-01S, 5 μg, diluted at 50 μg/ml, QC, Canada).
Animals
Sprague-Dawley female rats, 200–225 g, were obtained from Charles River Laboratories Canada. Animals were maintained on standard chow and water, which were available ad libitum, in animal facilities illuminated between 6:00 h and 20:00 h. All procedures were performed in accordance with guidelines of the Canadian Council on Animal Care for the handling and training of laboratory animals and the Good Health and Animal Care Committee of the Université du Québec à Trois-Rivières. Male and female mice were mated overnight and confirmation of pregnancy was determined by vaginal smears and/or the presence of a vaginal plug (day 1). Rats were killed on day 2, 4, 5, 6, 8, 10, 12, 14, 16, 18 and 20 of pregnancy at 10:00 h in the morning and at 18:00 h for days 5.5 and 6.5. Six to 8 different rats were used for each time of pregnancy. Uteri were collected and fixed for immunohistochemical staining (IHC) and apoptotic cell death detection by [TdT]-mediated deoxyuridinetriphosphate nick end-labeling (TUNEL) or endometrial protein extracts collected for Western blot analysis.
Rat pretreatments and decidual endometrial stromal cell culture
A total of 10 rats were ovariectomized and then allowed to recover from surgery for a minimum of 10 days. They were pre-treated with physiological doses of estradiol (1,3,5(10)-Estratriene-3,17β-diol, Sigma-aldrich) and progesterone (Laboratoire Mat, PQ) to induce decidualization as described previously [26]: 1) 0.2 ug estradiol injection per day for three days (in the morning, day -2,-1 and 0); 2) On the third day (day 0 of pseudopregnancy), another injection in the afternoon of estradiol (0.2 μg) and progesterone (1 mg) was performed; 3) No treatment for 2 days (day 1 and 2 of pseudopregnancy); 4) Injections of estradiol (0.1 μg) and progesterone (4 mg) for three days (day 3, 4 and 5 of pseudopregnancy); 5) Another injection of estradiol (0.1 μg) in the afternoon on day 7 (day 4 of pseudopregnancy); 6) Rats were killed on day 8 (day 5 of pseudopregnancy). All endometrial stromal cells collected for cultures were recovered from rats treated with the protocol described above.
Uteri were removed and horns taken and immerged in HBSS solution containing HEPES (20 mM), penicillin (100 units/ml), streptomycin (100 μg/ml) and fungizone (1,25 μl/ml) (Invitrogen, ON, Canada). Further manipulations were performed in a sterile environment. The uterine horns were transferred into a sterile petri containing HBSS, slit longitudinally and immersed in trypsin type I solution (0.3%) (Roche Diagnostics, QC, Canada) in HBSS and agitated for 60 minutes at room temperature. Uterine horns were then vortexed at maximum for 5 sec and supernatant containing epithelial cells was discarded. Uterine horns were washed three times with 2.5 ml of HBSS and immersed in a HBSS solution containing trypsin type I (0.03%), DNAse I (0.016%) and collagenase type II (0.064%) for 15 minutes at 37°C in a water bath. Uterine horns were then vortexed at maximum for 5 sec. The supernatant containing stromal cells was transferred into a sterile falcon tube containing 150 μl of FBS D.C (Dextran-Charcoal extracted). Uterine horns were washed two times with 2.5 ml of HBSS and the supernatant was mixed with stromal cells. Uterine horns were discarded and stromal cells were centrifuged at 1000 g for 5 minutes. Cells were washed two times with HBSS and centrifuged. The supernatant was discarded and cells diluted with DMEM-F12 (Ph 7.1) (Invitrogen, ON, Canada) containing 2.438 g/L NaHCO3, 10% FBS D.C. and gentamycine 50 μg/ml. Cells were incubated at 37°C in an atmosphere of 5% CO2. Cells were plated in 6-well plates (Corning plates) at a density of 50% (4 × 105 cells per well). The medium was changed two hours after the first incubation in order to eliminate epithelial cell contamination from stromal cell cultures. The purity of stromal cells was more than 97%: cell culture contamination with epithelial cells was evaluated by cellular morphology and immunofluorescence using a Keratin 8/18 antibody. Three to 5 days after plating (more than 90% of confluency reached), cells were treated for 24 hours in the presence or absence of increasing doses of TGF-β recombinant protein. Total proteins from treated cell cultures were extracted using TRIZOL (Invitrogen, ON, Canada). For Western blot analyses, 15 μg of total protein was used for each analysis.
Immunohistochemical staining
The uterus was fixed in 4% paraformaldehyde solution and embedded in paraffin. Tissue sections 7 μm thick were mounted on polylysine-coated slides, deparaffinized, rehydrated, and then heated in 10 mM citrate buffer (pH 6) containing triton X-100 (Sigma-Aldrich) 0.1% (v/v). After two washes with PBS, slides were then incubated with 0.3 % hydrogen peroxide in methanol for 30 min to quench endogenous peroxidase activity. After washing with PBS, tissues were incubated with blocking serum (Vectastain ABC Kit) at room temperature for 1 h. Then, a primary antibody diluted in blocking serum (TGF-β1, β2 or β3; 1:50 dilution or CDC47/MCM7; 1:100 dilution) was added to the slides and incubated at 4°C overnight in a humidified chamber. After washing 5 min. in PBS, tissue sections were incubated for 30 min. with 3 μg/ml biotinylated antibody (anti-rabbit or anti-mouse). Subsequently, slides were washed with PBS and incubated with avidin-biotin complex reagent containing horseradish peroxidase for 30 min. Slides were washed with PBS for 5 min and color development was achieved using DAB substrate. The tissue sections were counterstained with haematoxylin. Negative controls were performed using the same protocol but substituting the primary antibody with normal rabbit IgG (Vector Laboratories Inc., Burlingame, CA, USA).
Immunofluorescence
Tissues were prepared as described in the immunohistochemical section. Cleaved caspase-3 antibody was diluted 1:100 in blocking serum and slides were incubated at 4°C overnight. After washing twice for 5 min. in PBS, tissue sections were incubated for 30 min. at room temperature with 2 mg/ml Alexa Fluor 488 donkey anti-rabbit (1:50). Subsequently, slides were washed with PBS and mounted. Negative controls were performed using the same protocol but substituting the primary antibody with normal rabbit IgG. Sections were examined using an OlympusBX60 microscope equipped with a Coolsnap-pro CF digital camera (Carsen Group, ON, Canada).
TdT-mediated deoxyuridinetriphosphate nick end-labeling (TUNEL)
Tissue sections were deparaffinized, rehydrated and rinsed with PBS. They were incubated with proteinase K (20 μg/ml) for 30 min. at room temperature. Slides were washed twice with PBS, the endogenous peroxidase was quenched with 0.3 % hydrogen peroxide in methanol for 30 min. The slides were rinsed and incubated with 10 mM citrate solution for two min on ice. Then, tissue sections were rinsed with PBS and incubated with TdT labelling reaction (In Situ Cell Death Detection, POD) for 30 min at 37°C in humidified environment. Slides were washed three times in PBS and tissue sections were blocked with 3% BSA for 20 min. at room temperature. Converter-POD solution was added to the slides and incubated for 30 min. at 37°C in humidified environment. Slides were washed for 5 min. in PBS, colour development was achieved using DAB substrate and counterstained with haematoxylin. Negative controls were performed using the same protocol without TdT enzyme.
Protein extraction and Western analysis
Protein homogenates from pregnant endometrium were isolated according to a protocol previously described [27]. Briefly, uteri from Day 2 to Day 20 pregnant rats were rapidly excisedand placed in ice-cold saline until dissected. Uteri were carefully laid on a glass plate and placed on the stage of a dissecting microscope. In early pregnancy (Day 2 to 5.5), total endometrium was scraped using a microscope glass and collected. Uteri from Day 6 to 10 the placenta and decidua were at an early stage of differentiation and could not be reliably separated. For this reason, DB dissectedfrom animals between these days of pregnancy contain some chorioallantoic cells, but antimesometrial decidua, choriovitelline tissues, fetus, and myometrium were removed. Even though we carefully dissected DB from these tissues, it is a possibility that a contamination with some antimesometrial decidual cells that regress to form the deciduas caspularis (DC) would occur. This is an important fact that we need to take into consideration. In uteri collected from Day 12 to 20 pregnant rats, DB were isolated by gently separating the placenta and myometrial regions with 23-gauge needles. Additionally, the DB began to regress on Day 14 and became too thin to reliablydissect after Day 17. The protocol for DB isolation was described previously by Ogle and George [28].
Endometrial cells from pregnant animals were homogenized using a pipette in RIPA lysis buffer (PBS 1× pH 7.4; 1% Nonidet P-40; 0.5% Sodium deoxycholate; 0.1% SDS; Protease Inhibitor Cocktail Tablets (Roche Diagnostics Canada, PQ)). Homogenates were centrifuged (12,000 × g for 20 min at 4°C) to remove insoluble material. The supernatant was recovered and stored at -20°C pending analysis. Protein content was determined with the Bio-Rad DC Protein Assay. Protein extracts (50 μg) were heated at 94°C for 3 min, resolved by 10% SDS-PAGE and electrotransferred to nitrocellulose membranes using a semidry transfer (Bio-Rad, Mississauga, ON). The membranes were then blocked 2 h at room temperature with PBS containing 5 % milk powder, then incubated with anti TGF-β 1-2-3 1:1000 ; P-Smad2 (Ser 465 / 467) 1:1000 and Smad 2/3 1:1000 and subsequently with horseradish peroxidase-conjugated anti-rabbit or anti-mouse secondary antibody (1:3000; room temperature for 45 min). All membranes were stripped with Restore western blot stripping buffer (Pierce, # 21059, lot # FH71541), reprobed with an antibody specific to β-actin which was used as an internal standard. Peroxidase activity was visualized with the Super signal® West Femto maximum sensitivity substrate (Pierce, Arlington Heights, IL, USA), according to the manufacturer's instructions. Signal was visualized using the Biochemi Imaging System (UVP, CA, USA). Densitometrical analyses were performed (protein of interest and β-actin) using the GelDoc 2000 and the Quantity One software (Bio-Rad, Mississauga, ON, Canada). Results are expressed as a ratio (protein of interest/β-actin) to correct for loading for each endometrial sample.
Hoechst and trypan blue exclusion staining
Following TGF-β treatment, both floating and attached cells were resuspended in PBS containing Hoechst 33258 for 24 hours at 4°C or resuspended in trypan blue solution (0,4%) for 5 minutes. Hoechst nuclear staining was viewed and photographed using a Olympus BX60 fluorescence microscope and a Coolsnap-Pro CF digital Camera (Carsen Group, ON, Canada). Cells with typical apoptotic nuclear morphology (nuclear shrinkage, condensation and fragmentation) were identified and counted using randomly selected fields on numbered photographic slides, of which the "counter" was not aware of the treatment, so as to avoid experimental bias. A minimum of 200 cells per treatment group were counted in each experiment. For trypan blue exclusion test, blue cells were counted under a regular microscope and were counted as non-living cells.
Statistical analysis
Western analyses of pregnant animals were repeated six to eight times (6 to 8 different endometrial extract per day of pregnancy from 6 to 8 different rats). Endometrial extracts from each rat were assessed individually. Western analyses of cultured decidual cells were repeated 5 times for each TGF-β dose (for each culture experiment, decidual cells were recovered from a pool of ten different ovariectomized/treated rats). Results subjected to statistical analyses were expressed as mean ± SEM. Data were subjected to one-way ANOVA (PRISM software version 4.0; GraphPad, San Diego, CA). Differences between experimental groups were determined by the Tukey's test.
Results
Apoptosis expression during pregnancy
In order to confirm the presence of apoptosis in DB, the presence of the activated form of caspase-3 was measured by Western analysis (Fig. 1A) and immunofluorescence (Fig. 1B) using a day 14 pregnant uterine section. TUNEL measurement was also performed using a day 14 pregnant uterine section (Fig. 1C). As demonstrated by Western analysis, Fig. 1A clearly demonstrates that apoptosis was present in the endometrium at day 14: the 17 KDa cleaved caspase-3 fragment was significantly and gradually increased from day 8 and was maximal at day 14. Cleaved caspase-3 fragment was observed in the cytoplasm of apoptotic cells as demonstrated by immunofluorescence (Fig. 1B) and TUNEL positive cells were also found in the in the endometrium at day 14 (Fig. 1C).
Figure 1 Detection of apoptosis in pregnant endometrial tissues as demonstrated by Western and TUNEL analyses. A) Apoptosis as determined by Western analysis of cleaved caspase-3 (one blot presented out of 6). β-actin blots shown were used as controls to correct for loading in each lane. Blots shown are from one representative experiment. Graphics represent Western blot densitometrical analysis of the 17 KDa cleaved fragment. B) Cleaved caspase-3 immunofluorescence at day 14 of pregnancy. Magnification: control: 10× ; inset and Day 14: 40×. C) TUNEL analysis at day 14 of pregnancy. B) and C) One representative section is presented out of 6 experiments. C-: negative control. Magnification: control: 10× ; inset and Day 14: 40×. Arrows indicate positive staining.
Expression of TGF-β1, β2 and β3 in the rat uterus during pregnancy
To document the presence and expression of TGF-β proteins in the uterus throughout pregnancy, IHC and Western analyses were performed on uterine sections and lysate of pregnant rats respectively. It was important to document the presence of TGF-β proteins since the information found in the literature shows principally mRNA expression of different TGF-β isoforms in specific periods of pregnancy rather than in the whole gestation period. Western blot analyses shown in figure 2 demonstrate that TGF-β1 and β2 are both expressed in a similar pattern. Their expression is increased following implantation (days 5.5 to 6.5) and is maximal during regression of the DB (day 14; p < 0.01). However, the localization of the expression of those two isoforms during pregnancy is slightly different (Fig. 3 and 4 respectively): immunohistochemicals analysis confirms that during early pregnancy the signal is found in both epithelial and stromal cells, but during late pregnancy TGF-β1 is expressed mainly in stromal cells while TGF-β2 is located in epithelial cells. It is interesting to see that both TGF-β1 and β2 isoforms are clearly present in the epithelial cells and in stroma at the time of implantation (day 5.5) all around the uterine lumen surrounding the implanting conceptus. On the opposite, TGF-β3 has not been found during early pregnancy (Fig. 2 and 5). However, TGF-β3 was increased and present at the time of DB regression (days 12 to 16; p < 0.001) suggesting that its action might be limited to decidual regression during pregnancy.
Figure 2 TGF-β1, -β2 and -β3 expressions in rat endometrium during rat pregnancy. Total endometrial proteins were collected at different days of pregnancy. β-actin blots shown were used as controls to correct for loading in each lane. Blots shown are from one representative experiment. Graphics represent Western blot densitometrical analysis. Data represent the mean ± SEM of six independent experiments (six different rats). C+: positive control (day 14 endometrial protein extract).
Figure 3 Immunohistochemistry of TGF-β1 in rat endometrium during pregnancy. IHC shown are from one representative experiment and were repeated 6 times using 6 different uterine sections from 6 different rats per day of pregnancy. Representative days of pregnancy are presented (A: day 4; B: day 5.5; C: day 6.5; D: day 10; E: day 14; F: negative control in which primary antibody was absent). le: luminal epithelium; em: embryo; s: stroma. Magnification: 40×.
Figure 4 Immunohistochemistry of TGF-β2 in rat endometrium during pregnancy. IHC shown are from one representative experiment and were repeated 6 times using 6 different uterine sections from 6 different rats per day of pregnancy. Representative days of pregnancy are presented (A: day 4; B: day 5.5; C: day 6.5; D: day 10; E: day 14; F: negative control in which primary antibody was absent). le: luminal epithelium; em: embryo; s: stroma. Magnification: 40×.
Figure 5 Immunohistochemistry of TGF-β3 in rat endometrium during pregnancy. IHC shown are from one representative experiment and were repeated 6 times using 6 different uterine sections from 6 different rats per of day pregnancy. Representative days of pregnancy are presented (A: day 4; B: day 5.5; C: day 6.5; D: day 10; E: day 14; F: negative control in which primary antibody was absent). le: luminal epithelium; em: embryo; s: stroma. Magnification: 40×.
Expression of Smad2 and Phospho-Smad2 during pregnancy
TGF-β signal transduction is mediated intracellularly by Smad proteins, including the R-Smads (receptor regulated Smads including Smad2), the I-Smads (inhibitor Smads), and the Co-Smad (common Smad). The triggering event in Smad activation is the type I receptor-dependent sequential phosphorylation of the two C-terminal serine residues in Smads [29]. Therefore, phosphorylation of the C-terminus of receptor-activated Smads, particularly Smad2, is crucial for initiation of the TGF-β signaling. Western blot analyses of Smad2 and phospho-Smad2 on endometrial cell lysate from pregnant rats were carried out to confirm that TGF-β isoforms present in the endometrium during pregnancy have an activity on those cells. The results demonstrate that Smad2 expression is regulated throughout pregnancy (Figure 6). Its expression is high from day 5 to 10 and is dramatically reduced from day 12 to the end of pregnancy (p < 0.05). However the levels of phospho-Smad2, the activated form, are high on days 12 and 14 and are gradually reduced to the end of pregnancy. The presence of high levels of phospho-Smad2 correlates with the high expression of the three TGF-β isoforms and the presence of apoptosis, with an exception on day 2 of pregnancy (Figure 6). Although high levels of phospho-Smad2 are observed, levels of TGF-β1 and -2 isoforms are higher when compared to days 4 and 5 and caspase-3 cleaved fragment is also present.
Figure 6 Smad2 and phospho-Smad2 (P-Smad2) expressions in rat endometrium during pregnancy. Total endometrial proteins were collected at different days of pregnancy. β-actin blots shown were used as controls to correct for loading in each lane. Blots shown are from one representative experiment. Graphics represent Western blot densitometrical analysis. Data represent the mean ± SEM of six independent experiments (six different rats).
TGF-β action in vitro on decidual endometrial stromal cell fate
As demonstrated previously by Moulton in 1994 [7], TGF-β1 induces DNA cleavage in rat decidual cells. To confirm that TGF-β1 is responsible for the induction of apoptosis, three different techniques were used to measure apoptosis (Figure 7). Hoechst nuclear staining (Figure 7A) and TUNEL analysis (Figure 7C) clearly demonstrated that TGF-β1 induced apoptosis in a dose-dependent manner (p < 0.0001). Apoptosis was increased to 20% at 1 ng/ml of TGF-β1 and up to 30% at 10 ng/ml. Trypan Blue exclusion staining assay was used to test for viability and cell death; even though this test is not an apoptotic specific test, it shows a direct effect of TGF-β1 on cell survival and viability. A dose-dependent increase of cell death was observed in response to TGF-β1 treatment (Figure 7B).
Figure 7 Effect of TGF-β1 (ng/ml) on cell survival in cultured rat endometrial cells as demonstrated by Hoechst staining, TUNEL and trypan blue exclusion analyses. A) Apoptosis as determined by Hoechst nuclear staining. Data represent the mean ± SEM of six independent experiments. All doses are significantly different from control (p < 0.001). B) Cell viability as determined by trypan blue exclusion assay. Data represent the mean ± SEM of six independent experiments. 1, 5 and 10 ng/ml TGF-β1 doses are significantly different from control (p < 0.0001). C) Apoptosis as determined by TUNEL assay. Representative fields are presented out of 6 experiments. Arrows indicate positive staining.
Effect of TFG-β on Akt, P-Akt, CDC-47 and XIAP expression in vitro on decidual endometrial stromal cells
To further determine how TGF-β might act at the intra-cellular level to induce apoptosis in decidual cells, experiments were carried out to determine the possible interaction of TGF-β and the PI3K/Akt survival pathway. Recent studies have suggested and demonstrated that TGF-β directly acts with Smad3 to regulate the sensitivity to TGF-β induced apoptosis [30,31] and another study showed that TGF-β exerts a largely inhibitory effect on basal meningioma proliferation possibly through Smad 2/3 [32]. Since Smad3 is directly involved in TGF-β signaling, a similar mechanism might be involved in the control of decidual cell fate. Another study has shown that Akt activity might in turn be affected by the presence or absence of inhibitor of apoptosis proteins such as XIAP [33,34]. Figure 8 shows that Phospho-Smad2, the activated form, is significantly increased in response to TGF-β1. However, the concentration-response relationship in term of Smad phosphorylation appears to be biphasic, with 1 ng/ml stimulating, while 10 ng/ml having a significant effect compared to control (p < 0.05) but lower than the 1 ng/ml dose. There was no significant difference observed in term of Smad2 protein expression in response to TGF-β1. As demonstrated in Figure 8, the proliferation marker CDC-47 was significantly decreased in response to TGF-β1 treatment. Figure 9 demonstrates that Phospho-Akt, the active form of Akt, was highly expressed in control cells, indicating that this pathway is active and important in cell proliferation and cell survival. However, in the presence of TGF-β1, Phospho-Akt was significantly decreased suggesting an interaction of TGF-β and the PI3K/Akt survival pathway. Total Akt protein expression was not influenced by TGF-β1 treatment. Moreover, XIAP protein expression, a well known inhibitor of apoptosis protein, was significantly reduced in response to increasing doses of TGF-β.
Figure 8 Expression of Smad2, P-Smad2 and CDC47 in cultured rat endometrial cells in vitro as demonstrated by Western blot analyses in response to TGF-β1 (ng/ml). β-actin blots shown were used as controls to correct for loading in each lane. Blots shown are from one representative experiment. Graphics represent Western blot densitometrical analysis and are the mean ± SEM of four independent experiments. *Significantly different from control (p < 0.05).
Figure 9 Expression of Akt, P-Akt and XIAP in cultured rat endometrial cells in vitro as demonstrated by Western blot analyses in response to TGF-β1(νγ/μλ). β-actin blots shown were used as controls to correct for loading in each lane. Blots shown are from one representative experiment. Graphics represent Western blot densitometrical analysis and are the mean ± SEM of four independent experiments. *Significantly different from control (p < 0.05).
Discussion
Transforming growth factor-β isoforms have been known to be expressed and regulated differently in several types of tissues such as ovine uterus [35], human colon carcinoma [36] and at the porcine conceptus-maternal interface [19]. They are also recognized as pro-apoptotic factors in many cell types including fetal rat hepatocytes [14] and human leiomyoma smooth muscle cells [37]. However, little is known about the role of TGF-β isoforms in the rat uterus during pregnancy. The aim of the present study was to investigate the pro-apoptotic functions of TGF-β isoforms in rat uterus during pregnancy and also to determine more precisely the different patterns of expression of those isoforms in pregnant endometrium. The results presented in this study demonstrate that, as observed in other tissues, TGF-β isoforms (β1, β2 and β3) are differently regulated in rat uterus throughout pregnancy.
It is already known that apoptosis is induced during embryo implantation and decidualization in rodents [1,2,7]. Our results confirm that apoptosis is induced in the pregnant rat uterus especially during regression of the decidua basalis. Caspases are well known executioners of apoptosis [15,38]. The highest concentration of cleaved caspase-3 protein, the activated form of caspase-3, was found on day 14 of pregnancy, at the time of DB regression. The presence of active caspase-3 shows that this pathway might be important to induce cleavage of critical survival proteins and to further stimulate apoptosis during the regression of DB. However, caspase-3 activation was weakly observed at the time of implantation and this might be explained by the fact that, although uterine epithelium undergoes degeneration in the presence of embryo [4-6], only some epithelial cells undergo apoptosis during this process at the implantation site. Western blot and IHC analyses might not be sensitive enough techniques to detect the presence of small levels of cleaved caspase-3 in epithelial cells at implantation. It is also a possibility that degeneration of the epithelium may also involve non-apoptotic pathways.
The logical pursuit of this study was to determine the expression of TGF-β isoforms during those critical stages of pregnancy. The present results are consistent with previous work published in regards to TGF-β isoforms in other systems and in mouse uterus [18,22,39], where expression and regulation is different for each isoform. TGF-β1 was already known to induce apoptosis in human [40] and rat [7] endometrial stromal cells. In the present study, TGF-β1 and TGF-β2 were found throughout pregnancy and were particularly strong during apoptotic phases such as regression of the DB. On the other hand, using both IHC and Western analyses, TGF-β3 protein was undetectable in the early stages of gestation, suggesting that TGF-β3 may not be required in the regulation of cell death during embryo implantation and early pregnancy. This result supports a study performed by Das et al. [18] showing that TGF-β3 mRNA was absent during early pregnancy. Nevertheless, the three mammalian forms of TGF-β are strongly expressed during regression of the DB suggesting they could all play an important role during the regulation of programmed cell death to induced regression of DB. Those three isoforms are also expressed differently in distinct cells of the same tissues; similarities have been observed in human normal and malignant prostate epithelial cells [39] as TGF-β2 and TGF-β3 are more expressed in epithelial cells than in stromal cells during late pregnancy. The strong expression of TGF-β1 during rat early pregnancy (day 5.5 to 6.5) may be explained by the fact that this isoform could be necessary to initiate embryo implantation processes during the periimplantation period, a similar situation that is observed during trophoblast invasion at the time of human embryo implantation [41].
The next logical step of the present study was to determine if the TGF-β isoforms present during pregnancy were active. A lot of information can be found in many physiological systems regarding TGF-β and its cellular receptors [8,10] and Smad proteins responsible for its intracellular signal transduction [42-44]. Recent studies have suggested and demonstrated that TGF-β directly acts with Smad3 to regulate the sensitivity to TGF-β induced apoptosis [30,31] and another study showed that TGF-β exerts a largely inhibitory effect on basal meningioma proliferation possibly through Smad 2/3 [32]. Since Smad3 is directly involved in TGF-β signaling, a similar mechanism might be involved in the control of decidual cell fate. Since it is well known that TGF-β signals through Smads proteins, Western blot and IHC analyses were performed on pregnant endometrial cell lysates to measure Smad2 and phospho-Smad2 (the activated form) to test this hypothesis. The results showed that Smad2 protein was increased and stronger at the time of embryo implantation and that Smad2 phosphorylation was gradually increased during regression of the DB, which correlates with the presence of TGF-β isoforms. These results suggest that TGF-β isoforms present during these two critical stages of pregnancy might act through Smads proteins to induce apoptosis or to induce other genes known to be regulated by TGF-βs. Smad2 protein is relatively low during regression of the DB compared to early stages of pregnancy. This result is supported by a recent study showing that increased Smad2 expression is probably caused by the invasion of the trophoblast resulting in the formation of the first decidual zone [45]. However, Smad2 phosphorylation is not as much increased during early pregnancy as compared to late pregnancy. It is again a possibility that, since only epithelial cells undergo apoptosis at the time of embryo implantation, the possible increase of Smad2 phosphorylation induced by TGF-β might only be observed in a small number of cells which was undetectable with the techniques used.
To better understand the effect of TGF-β at the cellular level, decidual cell cultures were used to further investigate the interaction of TGF-β and the PI 3-K/Akt survival pathway. Although a recent study showed the possibility that cells obtained following artificial decidualization might be different from those obtained from pregnant animals [46], this model is an excellent alternative to obtain sufficient material to test the role of TGF-β and to correlates the data with the physiologic situation. It has been demonstrated recently that Akt phosphorylation is directly induced by 17β-estradiol in the ovariectomized rat uterus indicating that sex steroids have an important influence on endometrial cell fate [47]. Very recent studies have shown that TGF-β might directly block Akt activity through Smad activation [30]. Thus, stromal decidual cells were treated with different doses of TGF-β1 to determine if Smad activation might in turn block Akt survival pathway to induce cell death. TGF-β1 induced Smad2 phosphorylation in cultured endometrial stromal cell in vitro and triggered apoptosis in a dose-dependent manner, which was accompanied by a reduction of cell proliferation, confirming TGF-β as an apoptotic factor in rat decidual endometrial stromal cells. In response to TGF-β1, Akt phosphorylation was significantly decreased indicating that Akt activity inhibition might be an important mechanism for TGF-β-induced apoptosis in this model. Other studies have shown that Akt activity might in turn be affected by the presence or absence of inhibitor of apoptosis proteins such as XIAP [33,34] and cIAP-1 [48]. The results support the hypothesis that TGF-β action via Smads not only acts at the transcriptional level to induce production of apoptotic factors in decidual cells but also at the protein level to block activation of survival factors.
Akt phosphorylation was recently shown to be regulated by XIAP, a well known inhibitor of apoptosis protein, in human ovarian epithelial surface cells and in rat granulosa cells [33,34]. The present results show a possible interaction (direct or indirect) between TGF-β1 and XIAP protein expression. TGF-β1 reduced XIAP expression in vitro in a dose dependent manner. Recent studies have demonstrated that XIAP can act as a cofactor in the regulation of gene expression induced by TGF-β and is independent of Smad4 [14,49]. Because TGF-β1 reduced Akt phosphorylation and that XIAP was shown to induce Akt phosphorylation [34], it is possible that TGF-β action in this case might be through Smad2 activation and XIAP gene expression which in turn would act on Akt phosphorylation. Further experiments will be necessary to have a better understanding of the interactions between TGF-β and Akt survival pathway. In particular, how specifically Smads act on XIAP expression and how XIAP acts on the PI 3-K/Akt survival pathway activity. Other factors such as Smac/Diablo, a XIAP intracellular inhibitor, which was demonstrated as being regulated by 17β-estradiol in the rat during estrous cycle [50], might also be a putative candidate for regulation of TGF-β activity in decidual cells.
Conclusion
In conclusion, this study demonstrates that the three isoforms of TGF-β are differently localized and regulated in endometrial cells of pregnant rats, particularly at the time of implantation and regression of the DB. The present study also showed that TGF-β plays an important role in the control of cell survival and cell death and that it may interacts with the PI 3-K/Akt survival pathway through Smad activation to allow apoptosis induction. Further experiments will be necessary to understand more precisely the effect of other Smads and/or co-Smads proteins during TGF-β-induced apoptosis. Other investigations will also be required to better understand the specific roles of TGF-β2 and TGF-β3 at the intracellular and molecular level in vitro to determine how and if these isoforms control cell survival through Smad signal transducers.
Authors' contributions
CS drafted the paper. CS, PLC, GFF, VL and MCD performed the experiments. EA conceived the study, participated in its design and coordination, and wrote final version of the manuscript. All authors read and approved the final manuscript.
Acknowledgements
This work has been supported by a grant from NSERC (238501-01). Eric Asselin is a chercheur-boursier from the Fond de la Recherche en Santé du Québec (FRSQ) and New Investigator of the Canadian Institute of Health Research of Canada (CIHR). Marie-Claude Déry is recipient of a FRSQ and NSERC studentships. We are grateful to Mrs Rollande Caron for the contribution of her precious time and expertise to our projects. We thank also Mrs Sophie Parent and Mrs Daphne Efford for reviewing the manuscript.
==== Refs
Abrahamsohn PA Zorn TM Implantation and decidualization in rodents J Exp Zool 1993 266 603 628 8371101 10.1002/jez.1402660610
Pampfer S Donnay I Apoptosis at the time of embryo implantation in mouse and rat Cell Death Differ 1999 6 533 545 10381643 10.1038/sj.cdd.4400516
Parr EL Tung HN Parr MB Apoptosis as the mode of uterine epithelial cell death during embryo implantation in mice and rats. Biol Reprod 1987 36 211 225 3567276
Welsh AO Enders AC Chorioallantoic placenta formation in the rat. III. Granulated cells invade the uterine luminal epithelium at the time of epithelial cell death. Biol Reprod 1993 49 38 57 8353189
Welsh AO Uterine cell death during implantation and early placentation Microsc Res Tech 1993 25 223 245 8400423 10.1002/jemt.1070250305
Welsh AO Enders AC Light and electron microscopic examination of the mature decidual cells of the rat with emphasis on the antimesometrial decidua and its degeneration Am J Anat 1985 172 1 29 3969928 10.1002/aja.1001720102
Moulton BC Transforming growth factor-beta stimulates endometrial stromal apoptosis in vitro Endocrinology 1994 134 1055 1060 8119142 10.1210/en.134.3.1055
Lutz M Knaus P Integration of the TGF-beta pathway into the cellular signalling network Cell Signal 2002 14 977 988 12359303 10.1016/S0898-6568(02)00058-X
Rich J Borton A Wang X Transforming growth factor-beta signaling in cancer Microsc Res Tech 2001 52 363 373 11170295 10.1002/1097-0029(20010215)52:4<363::AID-JEMT1021>3.0.CO;2-F
Attisano L Wrana JL Lopez-Casillas F Massague J TGF-beta receptors and actions Biochim Biophys Acta 1994 1222 71 80 8186268 10.1016/0167-4889(94)90026-4
Kretzschmar M Doody J Massague J Opposing BMP and EGF signalling pathways converge on the TGF-beta family mediator Smad1 Nature 1997 389 618 622 9335504 10.1038/39348
Imamura T Takase M Nishihara A Oeda E Hanai J Kawabata M Miyazono K Smad6 inhibits signalling by the TGF-beta superfamily Nature 1997 389 622 626 9335505 10.1038/39355
Perlman R Schiemann WP Brooks MW Lodish HF Weinberg RA TGF-beta-induced apoptosis is mediated by the adapter protein Daxx that facilitates JNK activation Nat Cell Biol 2001 3 708 714 11483955 10.1038/35087019
Herrera B Fernandez M Benito M Fabregat I cIAP-1, but not XIAP, is cleaved by caspases during the apoptosis induced by TGF-beta in fetal rat hepatocytes FEBS Lett 2002 520 93 96 12044877 10.1016/S0014-5793(02)02774-6
Inman GJ Allday MJ Apoptosis induced by TGF-beta 1 in Burkitt's lymphoma cells is caspase 8 dependent but is death receptor independent J Immunol 2000 165 2500 2510 10946276
Boone DL Tsang BK Caspase-3 in the rat ovary: localization and possible role in follicular atresia and luteal regression Biol Reprod 1998 58 1533 1539 9623616
Massague J The transforming growth factor-beta family Annu Rev Cell Biol 1990 6 597 641 2177343 10.1146/annurev.cb.06.110190.003121
Das SK Flanders KC Andrews GK Dey SK Expression of transforming growth factor-beta isoforms (beta 2 and beta 3) in the mouse uterus: analysis of the periimplantation period and effects of ovarian steroids Endocrinology 1992 130 3459 3466 1375903 10.1210/en.130.6.3459
Gupta A Dekaney CM Bazer FW Madrigal MM Jaeger LA Beta transforming growth factors (TGFbeta) at the porcine conceptus-maternal interface. Part II: uterine TGFbeta bioactivity and expression of immunoreactive TGFbetas (TGFbeta1, TGFbeta2, and TGFbeta3) and their receptors (type I and type II) Biol Reprod 1998 59 911 917 9746743
Gupta A Ing NH Bazer FW Bustamante LS Jaeger LA Beta transforming growth factors (TGFss) at the porcine conceptus-maternal interface. Part I: expression of TGFbeta1, TGFbeta2, and TGFbeta3 messenger ribonucleic acids Biol Reprod 1998 59 905 910 9746742
Gu Y Jow GM Moulton BC Lee C Sensibar JA Park-Sarge OK Chen TJ Gibori G Apoptosis in decidual tissue regression and reorganization Endocrinology 1994 135 1272 1279 8070373 10.1210/en.135.3.1272
Chen HL Yelavarthi KK Hunt JS Identification of transforming growth factor-beta 1 mRNA in virgin and pregnant rat uteri by in situ hybridization J Reprod Immunol 1993 25 221 233 8207711 10.1016/0165-0378(93)90065-P
Lea RG Flanders KC Harley CB Manuel J Banwatt D Clark DA Release of a transforming growth factor (TGF)-beta 2-related suppressor factor from postimplantation murine decidual tissue can be correlated with the detection of a subpopulation of cells containing RNA for TGF-beta 2 J Immunol 1992 148 778 787 1730871
Manova K Paynton BV Bachvarova RF Expression of activins and TGF beta 1 and beta 2 RNAs in early postimplantation mouse embryos and uterine decidua Mech Dev 1992 36 141 152 1373953 10.1016/0925-4773(92)90065-R
Tamada H McMaster MT Flanders KC Andrews GK Dey SK Cell type-specific expression of transforming growth factor-beta 1 in the mouse uterus during the periimplantation period Mol Endocrinol 1990 4 965 972 2284009
Kennedy TG Ross HE Effect of prostaglandin E2 on rate of decidualization in rats. Prostaglandins 1993 46 243 250 8234832 10.1016/0090-6980(93)90007-T
Dai D Ogle TF Progesterone regulation of epidermal growth factor receptor in rat decidua basalis during pregnancy Biol Reprod 1999 61 326 332 10377066
Ogle TF George P Regulation of the estrogen receptor in the decidua basalis of the pregnant rat Biol Reprod 1995 53 65 77 7669858
Macias-Silva M Abdollah S Hoodless PA Pirone R Attisano L Wrana JL MADR2 is a substrate of the TGFbeta receptor and its phosphorylation is required for nuclear accumulation and signaling Cell 1996 87 1215 1224 8980228 10.1016/S0092-8674(00)81817-6
Conery AR Cao Y Thompson EA Townsend CMJ Ko TC Luo K Akt interacts directly with Smad3 to regulate the sensitivity to TGF-beta induced apoptosis Nat Cell Biol 2004 6 366 372 15104092 10.1038/ncb1117
Remy I Montmarquette A Michnick SW PKB/Akt modulates TGF-beta signalling through a direct interaction with Smad3 Nat Cell Biol 2004 6 358 365 15048128 10.1038/ncb1113
Johnson MD Okediji E Woodard A Transforming growth factor-beta effects on meningioma cell proliferation and signal transduction pathways J Neurooncol 2004 66 9 16 15015765 10.1023/B:NEON.0000013461.35120.8a
Asselin E Wang Y Tsang BK X-linked inhibitor of apoptosis protein activates the phosphatidylinositol 3-kinase/Akt pathway in rat granulosa cells during follicular development Endocrinology 2001 142 2451 2457 11356694 10.1210/en.142.6.2451
Asselin E Mills GB Tsang BK XIAP regulates Akt activity and caspase-3-dependent cleavage during cisplatin-induced apoptosis in human ovarian epithelial cancer cells Cancer Res 2001 61 1862 1868 11280739
Dore JJJ Wilkinson JE Godkin JD Ovine endometrial expression of transforming growth factor beta isoforms during the peri-implantation period Biol Reprod 1996 54 1080 1087 8722629
Bellone G Carbone A Tibaudi D Mauri F Ferrero I Smirne C Suman F Rivetti C Migliaretti G Camandona M Palestro G Emanuelli G Rodeck U Differential expression of transforming growth factors-beta1, -beta2 and -beta3 in human colon carcinoma Eur J Cancer 2001 37 224 233 11166150 10.1016/S0959-8049(00)00391-9
Arici A Sozen I Transforming growth factor-beta3 is expressed at high levels in leiomyoma where it stimulates fibronectin expression and cell proliferation Fertil Steril 2000 73 1006 1011 10785229 10.1016/S0015-0282(00)00418-0
Cohen GM Caspases: the executioners of apoptosis Biochem J 1997 326 1 16 9337844
Perry KT Anthony CT Steiner MS Immunohistochemical localization of TGF beta 1, TGF beta 2, and TGF beta 3 in normal and malignant human prostate Prostate 1997 33 133 140 9316654 10.1002/(SICI)1097-0045(19971001)33:2<133::AID-PROS7>3.0.CO;2-L
Chatzaki E Kouimtzoglou E Margioris AN Gravanis A Transforming growth factor beta1 exerts an autocrine regulatory effect on human endometrial stromal cell apoptosis, involving the FasL and Bcl-2 apoptotic pathways Mol Hum Reprod 2003 9 91 95 12569178 10.1093/molehr/gag011
Slater M Murphy CR Transforming growth factors alpha and beta-1 are co-expressed in the uterine epithelium during early pregnancy Cell Tissue Res 2000 300 315 320 10867826 10.1007/s004419900139
Ingman WV Robertson SA Defining the actions of transforming growth factor beta in reproduction Bioessays 2002 24 904 914 12325123 10.1002/bies.10155
Javelaud D Mauviel A Mammalian transforming growth factor-betas: Smad signaling and physio-pathological roles Int J Biochem Cell Biol 2004 36 1161 1165 15109563 10.1016/S1357-2725(03)00255-3
Akhurst RJ Derynck R TGF-beta signaling in cancer--a double-edged sword Trends Cell Biol 2001 11 S44 S51 11684442
Lin HY Wang HM Li QL Liu DL Zhang X Liu GY Qian D Zhu C Expression of Smad2 and Smad4, transforming growth factor-beta signal transducers in rat endometrium during the estrous cycle, pre-, and peri-implantation Anim Reprod Sci 2004 80 303 316 15036506 10.1016/S0378-4320(03)00171-4
Wang X Matsumoto H Zhao X Das SK Paria BC Embryonic signals direct the formation of tight junctional permeability barrier in the decidualizing stroma during embryo implantation J Cell Sci 2004 117 53 62 14627626 10.1242/jcs.00826
Dery MC Leblanc V Shooner C Asselin E Regulation of Akt expression and phosphorylation by 17beta-estradiol in the rat uterus during estrous cycle Reprod Biol Endocrinol 2003 1 47 12816542 10.1186/1477-7827-1-47
Gagnon V St Germain ME Parent S Asselin E Akt activity in endometrial cancer cells: regulation of cell survival through cIAP-1 Int J Oncol 2003 23 803 810 12888921
Birkey RS Wurthner JU Parks WT Roberts AB Duckett CS X-linked inhibitor of apoptosis protein functions as a cofactor in transforming growth factor-beta signaling J Biol Chem 2001 276 26542 26549 11356828 10.1074/jbc.M100331200
Leblanc V Dery MC Shooner C Asselin E Opposite regulation of XIAP and Smac/DIABLO in the rat endometrium in response to 17beta-estradiol at estrus Reprod Biol Endocrinol 2003 1 59 12967350 10.1186/1477-7827-1-59
| 15927076 | PMC1166574 | CC BY | 2021-01-04 16:37:12 | no | Reprod Biol Endocrinol. 2005 May 31; 3:20 | utf-8 | Reprod Biol Endocrinol | 2,005 | 10.1186/1477-7827-3-20 | oa_comm |
==== Front
RetrovirologyRetrovirology1742-4690BioMed Central London 1742-4690-2-361591890510.1186/1742-4690-2-36ResearchConservation of functional domains and limited heterogeneity of HIV-1 reverse transcriptase gene following vertical transmission Sundaravaradan Vasudha [email protected] Tobias [email protected] Nafees [email protected] Department of Microbiology and Immunology, College of Medicine, The University of Arizona Health Sciences Center, Tucson, Arizona 85724, USA2005 26 5 2005 2 36 36 18 2 2005 26 5 2005 Copyright © 2005 Sundaravaradan et al; licensee BioMed Central Ltd.2005Sundaravaradan et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
The reverse transcriptase (RT) enzyme of human immunodeficiency virus type 1 (HIV-1) plays a crucial role in the life cycle of the virus by converting the single stranded RNA genome into double stranded DNA that integrates into the host chromosome. In addition, RT is also responsible for the generation of mutations throughout the viral genome, including in its own sequences and is thus responsible for the generation of quasi-species in HIV-1-infected individuals. We therefore characterized the molecular properties of RT, including the conservation of functional motifs, degree of genetic diversity, and evolutionary dynamics from five mother-infant pairs following vertical transmission.
Results
The RT open reading frame was maintained with a frequency of 87.2% in five mother-infant pairs' sequences following vertical transmission. There was a low degree of viral heterogeneity and estimates of genetic diversity in mother-infant pairs' sequences. Both mothers and infants RT sequences were under positive selection pressure, as determined by the ratios of non-synonymous to synonymous substitutions. Phylogenetic analysis of 132 mother-infant RT sequences revealed distinct clusters for each mother-infant pair, suggesting that the epidemiologically linked mother-infant pairs were evolutionarily closer to each other as compared with epidemiologically unlinked mother-infant pairs. The functional domains of RT which are responsible for reverse transcription, DNA polymerization and RNase H activity were mostly conserved in the RT sequences analyzed in this study. Specifically, the active sites and domains required for primer binding, template binding, primer and template positioning and nucleotide recruitment were conserved in all mother-infant pairs' sequences.
Conclusion
The maintenance of an intact RT open reading frame, conservation of functional domains for RT activity, preservation of several amino acid motifs in epidemiologically linked mother-infant pairs, and a low degree of genetic variability following vertical transmission is consistent with an indispensable role of RT in HIV-1 replication in infected mother-infant pairs.
==== Body
Background
The vertical transmission of human immunodeficiency virus type 1 (HIV-1) accounts for more than 90% of all HIV-1 infections in children. HIV-1 infected pregnant women can transmit the virus to their infants during all stages of their pregnancy, including prepartum (trans-placental passage), intrapartum (exposure of infants' skin and mucous membranes to contaminated maternal blood and vaginal secretions) and post-partum (via breast milk) at an estimated rate of 30% [1-4]. However, the rate of vertical transmission can be reduced by antiretroviral therapy during pregnancy. The risk of vertical transmission increases with several parameters, including advanced maternal disease status, low maternal CD4 cell count, high maternal viral load, recent infection of the mother, prolonged exposure of infant to ruptured membranes during parturition, and higher viral heterogeneity in the mother [5-8].
Viral heterogeneity is one of the classical means by which HIV-1 evades the host immune system. The heterogeneity of HIV-1 is attributed to the error-prone reverse transcriptase (RT) enzyme, which is responsible for converting the single stranded viral genomic RNA to double-stranded DNA that integrates into the host chromosome. As reverse transcription is the first step of the viral replication cycle [9], errors made at this stage ensures propagation of the erroneously copied genome to form the quasi-species of HIV-1 found in the infected individuals. These quasi-species infect other uninfected target cells and the cycle of error-prone reverse transcription continues. We have previously demonstrated that HIV-1 sequences from transmitting mothers (mothers who transmitted HIV-1 to their infants) were more heterogeneous compared with HIV-1 sequences from non-transmitting mothers (mothers who failed to transmit HIV-1 to their infants) [10]. This finding further suggests that the reverse transcription step that is responsible for generation of viral heterogeneity, may also play an important role in vertical transmission. The RT gene is unique in that it is also exposed to the same mutating effects of the RT enzyme as other part of the HIV-1 genome. Therefore, we sought to examine HIV-1 RT sequences from five infected mother-infant pairs following perinatal transmission.
The HIV-1 RT shows significant sequence and structural similarity to other viral reverse transcriptases as well as viral and bacterial RNA polymerases [11-13]. HIV-1 RT is a heterodimeric protein comprising of two subunits, 66 kDa and 51 kDa. It is encoded as a Gag-Pol precursor, Pr160gag-pol, which is cleaved by viral protease to yield the Gag protein and the viral polymerase which codes for RT [9,14]. The larger subunit (p66) of the heterodimer acts as an RNA-dependant DNA polymerase, a DNA-dependant DNA polymerase and has RNase H activity associated with the C-terminus [15,16], whereas the p51 subunit lacks the C-terminus RNase H activity, is folded differently from the p66 subunit and is thus inactive [17-20]. The p66 is folded to form a structure similar to a right hand with palm, finger and thumb subdomains [21-23] that are connected to the RNase H by the "connexion" subdomain [22,24,25]. Each domain has several secondary structural elements which are critical for primer binding, template binding [14,22,23,26,27] and nucleotide recruitment [28]. More specifically, the aspartate residues at position 110, 185 and 186 are believed to be the active sites of the polymerase and are located in the palm subdomain at the bottom of the DNA binding cleft [14,16,20,28,29]. Mutations in this subdomain and the active site abolish the enzymatic activity of HIV-1 RT [2,19,22,30-32] and alter viral replication, which may also affect HIV-1 mother-to-infant transmission.
In this study, we characterized the HIV-1 RT quasi-species from five mother-infant pairs following vertical transmission, including a mother with infected twin infants. We show that the open reading frame of the RT gene was highly conserved in the sequences from five mother-infant pairs. In addition, there was a low degree of heterogeneity and high conservation of functional domains essential for RT activity. These findings may be helpful in the understanding of the molecular mechanisms of HIV-1 vertical transmission.
Results
Patient population and sample collection
Blood samples were collected from five HIV-1-infected mother-infant pairs following perinatal transmission, including samples from a set of twins (IH1 and IH2) in the case of mother H. The demographic, clinical and laboratory findings on these mother-infant pairs are summarized in Table 1. The Human Subjects Committee of the University of Arizona, and the Institutional Review Board of the Children's Hospital Medical Centre, Cincinnati Ohio, approved this study. Written informed consent was obtained for participation in the study from mothers of infected mother-infant pairs.
Table 1 Demographic, Clinical, and Laboratory Parameters of HIV-1 Infected Mother-Infant Pairs
Patient Age Sex CD4+ cells/mm3 Length of infection a Antiviral drug Clinical Evaluation b
MB 28 yr 509 11 mo None Asymptomatic
IB 4.75 mo M 1942 4.75 mo None Asymptomatic, P1A
MC 23 yr 818 1 yr6 mo None Asymptomatic
IC 14 mo F 772 14 mo ZDV Symptomatic AIDS;P2A,D1,3,F
MD 31 yr 480 2 yr6 mo None Asymptomatic
ID 28 mo M 46 28 mo ddCc Symptomatic AIDS, P2AB,F; failed ZDV therapy
MF 23 yr 692 2 yr10 mo None Asymptomatic
IF 1 wk M 2953 1 wk ZDV Asymptomatic,P1A
MH 33 yr 538 5 mo None Asymptomatic
IHT1 7 mo F 3157 7 mo ACTG152 Hepatosplenomeglay lymphadenopathy
IHT2 7 mo F 2176 7 mo ACTG152 Hepatosplenomegaly lymphadenopathy
M: mother; I: infant. aLength of infection: The closest time of infection that we could document was the first positive HIV-1 serology date or the first visit of the patient to the AIDS treatment Center, where all the HIV-1 positive patients were referred to as soon as an HIV-1 test was positive. Therefore, these dates may not reflect the exact dates of infection.
b Evaluation for infants is based on CDC criteria, cddC, Zalcitibine
Phylogenetic analysis of RT sequences of mother-infant isolates
We first performed multiple independent polymerase chain reaction (PCR) amplifications from peripheral mononuclear cells (PBMC) DNA of five mother-infant pairs and obtained 10 to 14 clones from each patient followed by nucleotide sequencing of these clones. We then performed the phylogenetic analysis by constructing a neighbor-joining tree of the 132 RT sequences from these mother-infant pairs, including the set of twins from mother H and the reference strain NL4-3, as shown in Figure 1. A model of evolution was optimized for the entire nucleotide sequence data set using the approach outlined by Huelsenbeck and Crandall [33]. The model of choice was incorporated into PAUP [34] to estimate a neighbor-joining tree and the tree was bootstrapped 1000 times to ensure fidelity. The phylogenetic tree demonstrated that the RT sequences from five mother-infant pairs were well discriminated in separate clusters and that the mother and infant sequences were generally separated in distinct subclusters. However, there was some intermingling between mother and infant sequences in pair C. Furthermore, the formation of separate subclusters of RT sequences from twins of mother H suggests that the there was probably compartmentalization of HIV-1 in the two fetuses causing independent evolution. We also compared our mother-infant pairs' RT sequences with the RT sequences of several clades present in the HIV databases and found that our RT sequences grouped with clade or subtype B sequences (not shown). The data on phylogenetic analysis indicate that the epidemiologically linked mother-infant sequences are closer to each other than epidemiologically unlinked sequences and that there was no PCR cross contamination. It is important to note that the mother-infant pairs grouped in the same subtree, even when some of the infants' ages were more than 2 to 3 years, suggesting that the epidemiological relationships are maintained in mother-infant pairs no matter how long the infection in the infants has progressed.
Figure 1 Phylogenetic analysis of HIV-1 RT of 132 RT sequences from five mother-infant pairs, including B, C, D, F and H. The neighbor-joining tree is based on the distance calculated between the nucleotide sequences from the five mother-infant pairs. Each terminal node represents one RT gene sequence. The numbers on the branch points indicate the percent occurrence of branches over 1,000 bootstrap resamplings of the data set. The sequences from each mother formed distinct clusters and are well discriminated and in confined subtrees, indicating that the variants from the same mother-infant pair are closer to each other than to other sequences and that there was no PCR cross-contamination. These data were strongly supported by the high bootstrap values indicated on the branch points.
Coding potential of RT gene sequences
The multiple sequence alignments of the deduced amino acid sequences of HIV-1 RT genes from five mother-infant pairs, B, C, D, F, mother H and her twin infants IH1 and IH2 are shown in Figures 2, 3, 4, 5, 6, and 7, respectively. These sequences were aligned with consensus subtype B RT sequence (CON B). We found that 115 of the 132 sequences analyzed contained a complete RT open reading frame (ORF), with an 87.2% frequency of intact RT open reading frames thus indicating that the coding potential of the RT ORF was maintained in most of the sequences in 1680 bp sequenced. Moreover, the infected mothers' sequences showed a frequency of 85.5% of intact RT ORF while infants demonstrated a frequency of 88.5%. Several clones in mother-infant pair B and mother H were found to be defective due to a single nucleotide substitution, insertion or deletion resulting either in frame-shift or stop codons. The RT sequences also displayed patient and pair specific amino acid sequence patterns. Several amino acid motifs changes were observed in majority of the mother-infant pairs' sequences, including a glutamic acid (E) or proline (P) at position 122, an arginine (R) at 277, and a threonine (T) or serine (S) at 376 and 400.
Figure 2 Multiple sequence alignment of deduced amino acids of HIV-1 reverse transcriptase (RT) gene from mother-infant pair B involved in vertical transmission. In the alignment, the top sequence is the consensus RT sequence of subtype or clade B (CON B) to which mother-infant pair-B RT sequences are aligned. In mother-infant pair B sequences, each line refers to a clone identified by a clone number with M referring to mothers and I referring to infants. The structural elements of RT are indicated above the alignment. Dots represent amino acid agreement with CON-B and substitutions are shown by single letter codes for the changed amino acid. Stop codons are shown as x and dashes represent gaps or truncated protein. Relevant amino acid motifs and domains essential for RT activity are shown by spanning arrowheads indicated above the alignment.
Figure 3 Multiple sequence alignment of deduced amino acids of HIV-1 reverse transcriptase (RT) gene from mother-infant pair C in reference to consensus subtype B (CON B) RT sequence. In the alignment, the top sequence is CON B RT sequence and the bottom sequences are mother-infant pair C sequences (M refers to mother sequences and I to sequences). The number of clones sequenced is represented with clone numbers. The structural elements of RT are indicated above the alignment. Dots represent amino acid agreement with CON-B and substitutions are shown by single letter codes for the changed amino acid. Stop codons are shown as x and dashes represent gaps or truncated protein. Spanning arrowheads indicated above the alignment shows relevant amino acid motifs and domains essential for RT function.
Figure 4 Multiple sequence alignment of deduced amino acids of HIV-1 reverse transcriptase (RT) gene from mother-infant pair D. The patient sequences are aligned in reference to consensus RT sequence of HIV-1 subtype or clade B (CON B) at the top. In the mother-infant pair sequences, each line refers to a clone identified by a clone number with M referring to mother and I to infants. The structural elements of RT are indicated above the alignment. Dots represent amino acid agreement with CON-B and substitutions are shown by single letter codes for the changed amino acid. Stop codons are shown as x and dashes represent gaps or truncated protein. Relevant amino acid motifs and domains essential for RT activity are shown by spanning arrowheads indicated above the alignment.
Figure 5 Multiple sequence alignment of deduced amino acids of HIV-1 reverse transcriptase gene from mother-infant pair F. In the alignment, the top sequence (CON B) is the consensus subtype B RT sequence and the bottom sequences are from mother-infant pair F sequences (M stands for mother sequences and I for infant sequences and the number of clones for mother and infant are indicated by clone number). The structural elements of RT are indicated above the alignment. Dots represent amino acid agreement with CON-B and substitutions are shown by single letter codes for the changed amino acid. Stop codons are shown as x and dashes represent gaps or truncated protein. Relevant amino acid motifs and domains essential for RT functions are shown by spanning arrowheads indicated above the alignment.
Figure 6 Multiple sequence alignment of deduced amino acids of HIV-1 reverse transcriptase (RT) gene from mother H, who had given birth to infected twins, H1 and H2 (alignment shown in Figure 7). In the mother H sequences, each line refers to a clone identified by a clone number with M referring to mother. The mother sequences are aligned in reference to consensus RT sequence of HIV-1 subtype or clade B (CON B) shown at the top. The structural elements of RT are indicated above the alignment. Dots represent amino acid agreement with CON-B and substitutions are shown by single letter codes for the changed amino acid. Stop codons are shown as x and dashes represent gaps or truncated protein. Spanning arrowheads indicated above the alignment shows relevant amino acid motifs and domains required for RT activity.
Figure 7 Multiple sequence alignment of deduced amino acids of HIV-1 reverse transcriptase gene (RT) from infected twin infants, H1 and H2 of mother H (alignment shown in Figure 6). In the alignment, the top sequence is the consensus subtype B RT sequence (CON B) and the bottom sequences are of infants H1 and H2 represented by I and clone numbers. Dots represent amino acid agreement with CON-B and substitutions are shown by single letter codes for the changed amino acid. Stop codons are shown as x and dashes represent gaps or truncated protein. Relevant amino acid motifs and domains essential for RT activity are shown by spanning arrowheads indicated above the alignment.
Variability of RT gene sequences in mother-infant isolates
The degree of genetic variability of RT sequences, measured as nucleotide and amino acid distances based on pairwise comparison (as described in Methods), was determined for the five mother-infant pairs' sequences, and is shown in Table 2. The nucleotide sequences of RT within mothers (mothers B, C, D, F and H) differed by 0.80, 1.76, 1.37, 1.21 and 2.90% (median values), respectively, ranging from 0 to 3.46%. The variability in the infant sets (infants B, C, D, F, H1 and H2) was similar to the mother sequences and differed by 0.80, 1.49, 1.37, 1.31, 0.64 and 1.24% (median values), respectively, ranging from 0 to 2.21%. Interestingly, the variability between epidemiologically linked mother and infant sets (pairs B, C, D, F and H) was also on the same order of 1.05, 1.7. 1.74, 1.22 and 1.45 (median values) respectively, ranging from 0 to 4.48%. Moreover, the amino acid sequence variability of RT within mothers (mothers B, C, D, F and H) differed by 1.26, 2.81, 1.98, 1.26 and 2.27% (median values), respectively, ranging from 0 to 5.51%. The variability within infants (infants B, C, D, F, H1 and H2) differed by 1.44, 2.35, 1.80, 1.62, 1.44 and 1.62% (median values), ranging from 0 to 4.57%, and between mother-infant pairs (pairs B, C, D, F and H) by 1.44, 2.90, 2.53, 1.44 and 2.17% (median values), ranging from 0 to 6.47%, respectively. We also determined sequence variability between epidemiologically unlinked individuals and found that the nucleotide distances ranged from 0 to 9.1% (median 5.4%) and amino acid from 0 to 12.4% (median 6.34%). The variability in general was lower between epidemiologically linked mother-infant pairs' sequences than epidemiologically unlinked individuals, suggesting that epidemiologically linked mother-infant pair sequences are closer to each other.
Table 2 Distances in the RT sequences within mother sets, within infant sets, and betweenmother-infant pairs
Nucleotide distances
Within mothers Within infants Between mother and infants
Pair Min Med Max Pair Min Med Max Pair Min Med Max
MB 0.0 0.80 2.10 IB 0.0 0.80 1.30 B 0.0 1.05 2.05
MC 0.0 1.76 3.46 IC 0.0 1.49 2.17 C 0.0 1.70 3.26
MD 0.0 1.37 2.21 ID 0.0 1.37 2.21 D 0.0 1.74 4.48
MF 0.0 1.21 1.54 IF 0.0 1.31 2.93 F 0.0 1.22 2.08
MH 0.0 2.90 2.60 IH1 0.0 0.64 1.34 H 0.0 1.45 3.30
IH2 0.0 1.24 1.75
Total 0.0 1.34 3.46 Total 0.0 1.48 2.21 Total 0.0 1.32 4.48
Amino acid distances
Within mothers Within infants Between mother and infants
Pair Min Med Max Pair Min Med Max Pair Min Med Max
MB 0.0 1.26 4.61 IB 0.0 1.44 2.72 B 0.0 1.44 4.57
MC 0.0 2.81 5.51 IC 0.0 2.35 4.01 C 0.0 2.90 5.51
MD 0.0 1.98 3.83 ID 0.0 1.80 4.57 D 0.0 2.53 6.47
MF 0.0 1.26 2.35 IF 0.0 1.62 3.09 F 0.0 1.44 3.09
MH 0.0 2.27 3.09 IH1 0.0 1.44 2.17 H 0.0 2.17 6.27
IH2 0.0 1.62 2.72
Total 0.0 1.52 5.51 Total 0.0 1.42 4.57 Total 0.0 2.90 6.47
M: mother; I: infant. Min: Minimum; Med: Median; Max: Maximum. Totals were calculated for all pairs together
We also investigated if the low variability of RT sequences seen in our mother-infant pair isolates is due to errors made by LA Taq polymerase used in our study. We did not find any errors made by the LA Taq polymerase when we used a known sequence of HIV-1 NL 4–3 for PCR amplification and DNA sequencing of the RT gene.
Dynamics of HIV-1 RT gene evolution in mother-infant isolates
The maximum likelihood estimates and chi square tests performed by Modeltest 3.06 [35] suggested different models of evolution for each patient sample. The estimates of genetic diversity of RT sequences from the five mother-infant pairs were determined by using the Watterson model, assuming segregating sites and the Coalesce method assuming a constant population size. The estimates of genetic diversity shown as theta values (estimated as nucleotide substitutions per site per generation) are shown in Table 3. The levels of genetic diversity among infected mothers and infants, as estimated by Watterson method, ranged from 0.012 to 0.025 and 0.009 to 0.021, respectively. Similar results were obtained when the mother-infant pair populations were analyzed by the Coelesce method, with the values ranging from 0.020 to 0.058 in mothers and from 0.016 to 0.060 in infants. These data suggest that the mother and infant populations evolved very slowly and at similar rates. The differences observed in the estimates of genetic diversity between and mothers and infants sequences are not statistically significant.
Table 3 Estimates of genetic diversity of HIV-1 RT within mother sets and infant sets
MOTHERS INFANTS
N θw θc θw θc
Mother B 12 0.015 0.038 Infant B 12 0.014 0.033
Mother C 12 0.025 0.058 Infant C 13 0.021 0.060
Mother D 11 0.017 0.042 Infant D 10 0.019 0.040
Mother F 14 0.012 0.029 Infant F 12 0.018 0.053
Mother H 14 0.020 0.020 Infant H1 11 0.009 0.016
Infant H2 11 0.015 0.044
Totals 63 0.018 0.037 69 0.016 0.041
N – number of RT clones sequenced. θw – genetic diversity as calculated by the Watterson method; θc – genetic diversity as calculated by the Coelesce method. Totals were indicated as an average of all values.
Rates of accumulation of nonsynonymous and synonymous substitutions
Selection pressure on the RT gene was estimated as a ratio of accumulation of non-synonymous to non-synonymous substitutions using the Nielsen and Yang model [36] as implemented in codeML [37]. Although there are several models to predict the rate of positive selection, most of these models assume that all sites in a sequence are under the same selection pressure with the same underlying dN/dS ratio [38]. As substitutions of critical regions of a protein can lead to deleterious mutations, it is unrealistic to make assumptions about equal degree of selection throughout the protein. In cases where positive selection is operating on proteins, it has been shown that only a limited number of amino acids may be responsible for adaptive evolution. In such a case, methods that estimate dN/dS ratios over an entire sequence may fail to detect positive selection even when it exists [39]. The codeML method uses the codon as a unit of evolution as opposed to a nucleotide, and thus allows us to estimate the percentage of positions that are being positively selected instead of averaging the rates of positive selection over the entire gene [39]. This method also provides the percentage of mutations that are conserved, neutral or positively selected based on dN/dS values of 0, 1 or > 1, respectively. The dN/dS values as well as the proportions of each site category estimated using the Nielsen and Yang model are shown in Table 4. As described in the methods, a dN/dS value of greater than 1 suggests positive selection. The percentage of the substitutions being positively selected is shown in column p3. Except for viral populations in infants C and F, all isolated populations were associated with dN/dS ratio >1, indicating positive selection. In case of infants C and F, there was no positive selection on the mutations and most of the substitutions were neutral. All mothers generally displayed a higher proportion of positively selected p3 sites as compared to the infants. Although the dN/dS values for infant H1 and H2 seem higher than mother H, closer observation shows that the percentage of sites undergoing positive selection is higher in the mother than in the twin infants. Table 4 shows that in mothers, over half the sites (66.6%) belong to the conserved p1 category, whereas the frequency of neutral and positively selected sites was equally distributed. This is in contrast to the viral population from the infants where the conserved site category (p1) had a frequency of only 36.5% and close to half the sites (55.7%) belongs to the neutral p2 category. Statistical analysis revealed that only the proportion of the neutral p2 category was significantly different between mothers' and infants' sequence viral populations (p < 0.05). This is signified by the case that all the sites in Infant F belonged to the p2 category. Higher proportion of p2 sites in infants have also been shown in the nef gene product in these same mother infant pairs [40]. The variable (positively selected) sites (p3) in the mothers' sequences were associated with dN/dS ratios that ranged from 2.34 to 8.9, with viral sequence populations from three mothers (MD, MF, MH) that displayed a dN/dS ratio of below three. This is in contrast to the infants' viral populations that were either associated with a dN/dS of below 1, indicating no directional selection (IC and IF), a dN/dS ratio between 3 and 4 (IB and ID) or a very high dN/dS ratio as found in the sequences isolated from the twins H1 and H2. This analysis showed that the RT gene in both the mothers and infants is under positive selection pressure.
Table 4 dN/dS values in HIV-1 RT sequences within mother sets and within infant sets.
MOTHER INFANT
N P1 P2 P3 dN/dS N P1 P2 P3 dN/dS
Mother B 12 53 18.8 27 8.9 Infant B 12 41 42 16 3.31
Mother C 12 55.5 43 1.3 6.09 Infant C 13 0 81.2 18.8 0.01
Mother D 11 70.6 5.7 23.6 2.52 Infant D 10 74.8 19.2 5.9 4.44
Mother F 14 81.7 7.8 10.4 2.67 Infant F 12 0 100 0 0.001
Mother H 14 72 0 27 2.34 Infant H1 11 47 50 2.8 14.04
Infant H2 11 56 42 0.6 16.58
Totals 66.5 15.1 18.4 4.50 69 36.5 55.7 7.8 6.39
N – number of RT clones sequenced.; P1 = proportion of conserved codons as a percent; P2 = proportion of neutral codons as a percent; P3 = proportion of positively selected codons as a percent. dN/dS = ratio of synonymous to non-synonymous at P3 sites. Totals were calculates as an average of all values.
Analysis of functional domains of RT in mother-infant pairs
HIV-1 RT is a heterodimeric protein comprising of two subunits, p66 and p51. The larger subunit of the heterodimer acts as an RNA-dependant DNA polymerase, a DNA-dependant DNA polymerase and an RNase H that is associated with the C-terminus [15,16]. The p66 is folded to form a structure similar to the right hand with palm, finger and thumb subdomains [21,23,32] that are connected to the RNase H by the "connexion" subdomain [22,24,25]. Each domain has several secondary structural elements, which are critical for primer binding, template binding [14,22,23,26,27,41] and nucleotide recruitment [28]. The active sites of the polymerase comprise of aspartic acid (D) residues at positions 110, 185 and 186, which are located in the palm subdomain at the bottom of the DNA binding cleft [22,23]. Mutations of these aspartic acid residues abrogates the polymerase activity of RT [22,23,29,32]. These aspartate residues of the RT active site were conserved within the five mother-infant pairs RT sequences. Furthermore, the D185 and D186 that form a part of an essential highly conserved YMDD [32,42,43] motif involved in binding to the 3'OH of the primer strand [14,26], were highly conserved in our mother-infant pairs' RT sequences (Figures 2 to 7). The amino acids at positions 73–90 that constitute the template grip required for positioning and binding the RT template near the active site of the RT [23], were also conserved in most of our RT sequences. The primer grip responsible for primer binding extends from amino acids 227 to 235 [22,23] and these amino acids were also conserved in the mother-infant RT sequences. The K263, K353 and R358 that form salt bridges with the phosphate groups [14,21,22,30,44] of the template and primer were found to be conserved in most of the RT sequences analyzed. The thumb subdomain of RT is comprised of two anti-parallel α helices, αH and αI, which bind to the opposite strand of dsDNA. The αH also directly inserts into the minor groove of the DNA [14,22,41]. Both these helices were generally conserved in our mother-infant RT sequences.
The connexion subdomain that links the RT to the RNase H and forms the floor of the template binding cleft [22,24,25,42], showed some substitutions, including V293I, A376S and A400T in our mother-infant RT sequences. Mutations at positions H361 and Y501 reduces RNase H activity [24]. Examination of the five mother-infant pairs' sequences revealed that these two positions were intact in all RT sequences (Figures 2 to 7). Furthermore, the RNase H active sites contain four acidic amino acid residues, D443, E478, D498 and D549 [22,24,25,41,42], which were highly conserved in our mother-infant pairs sequences. In addition, several substitutions were seen in regions of RT that are not known to have critical function. The relevance of these changes is not known.
Mutations associated with anti-retroviral drug resistance
Several naturally occurring mutations in the pol gene in treatment-naïve patients have been reported [45,46], although most of these mutations are not seen in our RT gene sequences. In addition, these mutations found in treatment-naïve patients were usually seen in non-subtype B infections and our patient population was from subtype B infected individuals. These changes were usually in amino acids where the mutations did not actually confer nucleoside reverse transcriptase inhibitor (NRTI) drug resistance but were accessory mutations [46-48]. Several amino acid changes in RT seen in patients undergoing NRTI therapy are selected primarily with zidovudine (ZDV) treatment. These mutations referred to as thymidine analog mutations (TAMs) include M41L, D67N, K70R, L210N, T215Y/F and K219Q [47,49]. Since most of our infected mothers were treatment naïve but infants were actively on ZDV therapy or on other drugs (Table 1), we examined the RT sequences for ZDV resistant mutations (Figure 2). Several TAMs associated with drug resistance were observed in our infants C and D who were either on prolonged or failed ZDV therapy. These mutations included M41L in three clones from infant C and two clones in infant D, D67N and K70R in five clones from infant C, L210W in one clone from infant D and T215F in seven clones from infant D and K219Q in four clones from infant C and D. In addition, one clone from infant C had all the above mutations, indicating significant resistance to ZDV [46,50]. Although Mother C was not on any antiretroviral therapy two clones had TAMs at M41L and K219Q positions, suggesting that these mutations were naturally occurring. It is interesting to note that the infant of this mother yielded several clones with these two mutations. An R211K mutation known as an accessory mutation associated with NRTI resistance [46] was also observed in all mother-infant pair H clones.
Immunologically relevant mutations in the CTL epitopes of RT
The cytotoxic T lymphocyte (CTL) responses have been shown to exert significant immune pressure during HIV-1 infection. Strong CTL responses are maintained in long-term nonprogressors and these responses correlate with decrease in viral load [51-55]. It has been shown that transmitting mothers have larger numbers of CTL escape variants as compared to non-transmitting mothers [56], emphasizing that CTL escape variants may become a part of circulating virus that influences vertical transmission [56,57]. Several regions in the RT gene have been shown to elicit strong CTL responses during HIV-1 infection. The CTL eptitope, TVLDVGDAY, between amino acid positions 107–115 , is highly conserved among known HIV-1 isolates [57]. This epitope contains the amino acid D110 which is part of the RT active site. This epitope was highly conserved in most of the mother-infant RT clones sequenced (Fig. 2).
Another motif, TAFTIPSI, between amino acid positions 128–135 is an HLA-B51 restricted epitope . This epitope is present in the palm region consisting of positions A129 and I135 as anchor residues [57]. This motif was mostly conserved in the RT sequences of the five mother-infant pairs analyzed. In addition, I135T mutation decreases CTL response but increasing concentration of mutant peptide re-establishes appropriate responses [57]. The I135T mutation was seen in several of our mother-infant pair's D sequences.
The next motif AIFQSSMTK from amino acid positions 158–166, comprising of I159, F160, K166 anchor residues and recognized by several HLA types, is conserved among known HIV-1 isolates and believed to be associated with vertical transmission [56,57]. Our mother-infant pairs' RT sequences showed conservation in this motif. Another CTL epitope YPGIKVRQL from positions 271–279 has been reported to be conserved in transmitting mothers and infants with several natural occurring variants [56], was also found to be conserved in our mother-infant pairs' RT sequences. In addition, a P272H mutation that causes significant loss of CTL response for this epitope [56] was not seen in any of the RT clones analyzed.
Discussion
In this study, we show for the first time that reverse transcriptase open reading frames from five mother-infant pairs following perinatal transmission were maintained with a frequency of 87.2%. The functional domains required for reverse transcriptase activity in HIV-1 replication were highly conserved in most of the mother-infants sequences. We also demonstrate a low degree of sequence variability and estimates of genetic diversity for reverse transcriptase genes after mother-to-infant transmission. However, epidemiologically unlinked individual's sequences were more heterogeneous than epidemiologically linked mother-infant pair's sequences. Several motifs in reverse transcriptase responsible for primer and template binding and positioning and motifs involved in nucleotide recruitment were conserved in all mother-infant pairs' sequences. The data we show here are comparable to those of our previously analyzed conserved genes, including gagP17MA, vif, vpr, tat and nef [58-62]. Our findings suggest that an intact and functional reverse transcriptase open reading frame is essential for HIV-1 replication in mothers and their infants and low degree of viral heterogeneity is maintained following vertical transmission.
The RT open reading frame was maintained in 115 of the 132 sequences (1680 base pairs sequenced), whereas 17 sequences contained stop codons (Figure 2). The frequency of conservation in five mother-infant pairs was found to be 87.2%. The comparison of the RT sequences with those of other conserved genes from HIV-1 infected mother-infant pairs showed comparable frequency of conversation, including gag p17 (86.2%), vif (89.8%), vpr (92.1%), tat (90.9%), nef (86.2%) and vpu (90.12%). There was no significant correlation between the conservation of RT open reading frame and disease progression in mothers and infants [63-65]. Several amino acid motifs were found to be a signature characteristic of each mother-infant pair, even in older infants where infection has progressed for more than 3 years. Phylogenetic analysis of the RT sequences revealed that the five mother-infant pairs were well discriminated, separated and confined within subtrees (Fig. 1), indicating that the epidemiologically linked mother-infant pairs were closer to each other and that there was no PCR product cross-contamination [66,67]. In addition, most of the mother and infant sequences of the same pair formed separate subclusters, with little intermingling between sequences of mother and infant in some pairs. In some mother-infant pairs, minor variants of the mothers seem to be predominating in the infants, which was also seen in our previous V3 region analysis [68]. We also observed intermingling of sequences in mother-H and her infected twins, indicating that different mother's variants were transmitted to the twins. With respect to viral heterogeneity, there was a low degree of genetic variability in the RT sequences from mother-infant pairs estimated by several methods. Similar levels of genetic diversity were seen in other conserved genes of the same mother-infant pairs, including gag, vif, vpr and tat [59-61,69]. The low degree of genetic variability was observed in RT sequences of mothers and maintained in the infants following transmission, suggesting the essential nature of this gene in viral pathogenesis. It is important to note that the mother-infant pairs retained the same epidemiological relationship, even when some of the infant's age was more than 2 to 3 years. We believe this is an important finding that the epidemiological relationships as well as certain signature sequence motifs are maintained in mother-infant pairs or transmitter-recipient partners no matter how long the infection has progressed. This information may be critical in terms of vaccine development.
Examining the motifs of the deduced amino acid sequences of the RT gene from five mother-infant pairs, we found that the essential motifs required for RT activity were mostly conserved in our mother-infant pairs' sequences (Figure 2). The sites essential for primer binding, template binding, positioning of template and primer, which are located in α-Helix H and α-Helix I [22,23], were are all conserved in RT sequences (Figure 2). Specifically, the amino acids involved in recruitment of nucleotides during reverse transcription [28] were mostly conserved. The active sites of the polymerase are located in the palm subdomain at the bottom of the DNA binding cleft comprising of aspartic acid (D) residues at positions 110, 185 and 186 were conserved within the five mother-infant pairs' RT sequences. Furthermore, the D185 and D186 also form a part of an essential YMDD motif, which is highly conserved in known HIV-1 isolates [14,22,23,26,32,43], was also conserved in our mother-infant pairs' RT sequences analyzed.
Some of the amino acids of the connexion subdomain that are critical for RNase H activity and replication [9,24,25] are conserved in our RT sequences with several substitutions of compatible nature, including V293I, K358R, A376S, and A390T. These substitutions were located in the regions of the connexion that forms the base of the binding cleft. It is possible that such mutations in the binding cleft may change the size of the cleft and affect fidelity of the reverse transcriptase without affecting the active site. Further assessment also shows that our RT sequences harbor mutations in the connexion and RNase H subdomains that are not at the critical sites required for RT activity. The implications of these mutations can be studied by performing the biological characterization of these RT clones in the context of HIV-1 replication. It would be interesting to determine whether the degree of genetic variability and conservation of RT functional domains in non-transmitting mothers and compare their sequences with the data presented here. Nonetheless, the data described here suggest that functional domains of the RT enzyme, including reverse transcriptase, DNA polymerase and RNase H, were highly conserved in our five mother-infant pair sequences.
In terms of CTL epitopes in the RT gene, Wilson et al., have shown that the transmitting mothers have larger numbers of CTL escape variants as compared to non-transmitting mothers but the transmitted viruses carrying epitopes are not escape variants [56]. It is possible that the CTL responses studied are tissue specific and a representation of peripheral blood, and the virus and the CTL variants in the placenta, birth canal, and breast milk are different [70]. In addition, there is evidence suggesting that Nef and Pol specific CTLs found in breast milk showed no detectable responses in peripheral blood. Although several previously defined CTL motifs in the RT gene [56,57] were conserved in our RT sequences, other mutations that either abrogated or improved the CTL responses [56,57] were not seen in our sequences. The possibilities exist that the mutants observed in the CTL epitopes in our study may contribute to differential responses in a tissue specific manner and thus influence vertical transmission.
While antiretroviral treatment during pregnancy has reduced the risk of vertical transmission in the United States, HIV-1 infection in children, as a result of perinatal transmission, is still increasing rapidly in developing countries. There is a global need of better preventive strategies of HIV-1 vertical transmission. If we characterize the properties of the transmitted viruses, we can then develop interventions against the properties of the transmitted viruses. We have already shown that the minor genotypes with R5 phenotypes are transmitted from mothers to infants and are initially maintained in the infants with the same properties [71]. Additional data on the properties of HIV-1 from mothers and infants following perinatal transmission presented in this study may aid in a better understanding of the molecular mechanisms of vertical transmission and development of effective strategies for prevention and control of HIV-1 infection in children.
Conclusion
We have demonstrated that an intact and functional RT gene was maintained in infected mother-infant pairs following perinatal transmission. In addition, there was a lower degree of viral heterogeneity and estimates of genetic diversity in epidemiologically linked mother-infant pairs compared with epidemiologically unlinked individuals. Several amino acid motifs were found as a signature sequences in each mother-infant pair. We also found that the functional motifs of RT responsible for reverse transcription, DNA polymerization and RNase H were highly conserved in mother-infant RT sequences. These findings support the notion that RT is essential for HIV-1 replication in mothers and their infected infants.
Methods
PCR amplification, cloning and nucleotide sequencing
Peripheral blood mononuclear cells (PBMCs) were isolated by a single step Ficoll-Hypaque procedure (Pharmacia-LKB) from whole blood samples of HIV-1-infected mother-infant pairs. DNA was isolated as described previously [68]. The HIV-1 RT gene was amplified by a two-step PCR method, first using outer primers RT1 (5 GTACAGTATTAGTAGGACCTACACCTGTC, 2470 to 2498, sense) and RT2 (5'AAAATCACTAGCCATTGCTCTCCAATTAC, 4307 to 4279, antisense) and then with nested primers RT3 (5'TGGAAGAAATCTGTTGACTCAGATTGG, 2507 to 2533, sense) and RT4, (5'TTCTCATGTTCTTGGGCCTTATCT, 4270 to 4244, antisense). Equal amounts of PBMC DNA (approximately 25 to 50 copies from each patient) as determined by end-point dilution was subjected to multiple (5 to 8) independent PCRs to obtain clones that were sequenced and analyzed. PCRs were performed according the modified procedure of Ahmad et al., [68] in a 25 μl reaction mixture containing 2.5 μl of 10X PCR buffer (100 mM Tris-HCL, pH 8.3, 100 mM KCl, 0.02% Tween 20), 2.5 mM MgCl2, 400 μM each of dATP, dCTP, dGTP and dTTP, 0.2 to 1.0 μM of each of outer primers, and 2.5 U of TaKaRa LA Taq polymerase (TaKaRa Biomedicals, Shiga, Japan). The reactions were carried out at 94°C for 30s, 45°C for 45s and 72°C for 3 min for 35 cycles, with the last cycle allowing for seven minutes of additional polymerization. After the first round of PCR, 4μl of the first-PCR product was used for nested PCR, using inner primers and same reagents at 94°C for 30s, 52°C for 45s and 72°C for 3 min for 35 cycles. We used negative control with each PCR amplification and a known HIV-1 DNA, pNL4-3, to assess errors generated by the LA Taq polymerase. To avoid contamination, all samples, reagents and PCR products were stored separately and dispensed in a separate room free of all DNA used in the lab. The PCR products were then visualized on a 1% agarose gel, excised ad extracted by using a QIAquick Gel Extraction kit (Qiagen Inc.). These DNAs were cloned into the TA cloning system (pCR 2.1-TOPO vector, Invitrogen Inc.) and transformed into chemically competent TOP10 cells (Invitrogen Inc.). The white colonies were screened for correct size inserts and 10 to 14 clones from each patient obtained from multiple independent PCRs were initially manually sequenced and then sequenced using University of Arizona Biotechnology Center automated system.
Sequence analysis
The nucleotide sequences of HIV-1 RT gene (approximately 1680 bp) from five mother-infant pairs were analyzed with the Wisconsin package 10.1 version of the Genetics Computer group (GCG) and were translated to corresponding deduced amino acid sequences (560 amino acids). A multiple sequence alignment was performed for the nucleotide and amino acid sequences with a reference HIV-1 consensus clade or subtype B RT sequences with a gap-opening penalty of 10 and a gap extension penalty of 5 using Clustal X. The transitions were not weighted and the amino acids were scored using a BLOSUM matrix. A model of evolution was optimized for the entire nucleotide sequence data set using the approach outlined by Huelsenbeck and Crandall [33]. Likelihood scores for different models of evolution were calculated using PAUP [34] and a chi square test was performed by Modeltest 3.06 [34,35,40,72]. Using the Model test and Akaike Information Criterion [72], all the null hypotheses were rejected except a GTR+G model. The five rate categories were as follows: R (A-C) = 2.962, R (A-G) = 10.5176, R (A-T) 1.3663, R (C-G) = 0.6563, R (C-T) 12.5484, R (G-T) = 1. A gamma distribution with the shape parameter (α) of the distribution estimated from the data matrix via maximum likelihood was used to account for the rate of heterogeneity. This shape parameter α was = 0.7775. The model of choice was incorporated into PAUP [34] to estimate a neighbor-joining tree and the tree was bootstrapped 1000 times to ensure fidelity. Models to represent patterns of evolution of variants of each patient population were identified and were used to estimate corrected pairwise nucleotide distances using PAUP [34]. Amino acid distances were also estimated using the Jukes-Cantor model with the Wisconsin package 10.1 of GCG. The minimum, median and maximum nucleotide and amino acid distances for each patient and linked patient pairs were calculated from these data (Table 2). To analyze the evolutionary processes acting on the RT gene, we estimated the ratio of non-synonymous (dN) to synonymous (dS) substitutions by a maximum likelihood model using codeML, a part of the PAML [37] package. The Nielsen and Yang [36] model considers the codon instead of the nucleotide as the unit of evolution and incorporates three distinct categories of sites. Every mutation is three times more likely to cause a nonsynonymous than a synononymous substitution and codeML accounts for this bias. The first category p1 represents the sites that are conserved and invariable where dN/dS = 0. The second category p2 represents neutral sites where dN/dS = 1 and represents sites at which the dN and the dS are fixed at the same rate. The third category p3 represents sites that are under positive selection where the dN have a higher rate of fixation than dS proportionally and dN/dS >1. The dynamics of HIV-1 evolution was assessed using techniques of population genetics. In population genetics, genetic diversity is defined as θ = 2Neiμ, where Nei is the inbreeding effective population size and μ is the per nucleotide mutation rate per generation. The Watterson model based on segregating sites and the Kuhner model assuming constant population size were used to estimate differences in genetic diversity, using the program Coalesce, which is part of the Lamarc software package. The tree files and the data matrixes from PAUP were used to estimate θ values as a measure of genetic diversity.
Nucleotide sequence accession numbers
The sequences have been submitted to GenBank with accession numbers AY560388 to AY560528.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
VS carried out the PCR, cloning, and sequencing. VS and TH performed the sequence analysis by computer programs. VS and NA participated in the experimental design, data interpretation and writing of the manuscript. All the authors read and approved the final manuscript.
Acknowledgements
This work was supported by grants to NA from the National Institute of Allergy and Infectious Disease (AI 40378, AI 40378-06) and the Arizona Disease Control Research Commission (ADCRC-7002, 8001). We thank Raymond C. Baker, Children's Hospital Medical Center, Cincinnati, Ohio and Ziad M. Shehab Department of Pediatrics, University of Arizona College of Medicine for providing HIV-1-infected mother-infant pairs blood samples. We thank members of Ahmad Lab, including Tiffany Davis and Kamlesh Patel for their help in cloning of the RT genes and Rajesh Ramakrishnan, Roshni Mehta and Brian Wellensiek for critically reading this manuscript and providing helpful suggestions.
==== Refs
Lepage P Van de Perre P Carael M Nsengumuremyi F Nkurunziza J Butzler JP Sprecher S Postnatal transmission of HIV from mother to child Lancet 1987 2 400 2886858 10.1016/S0140-6736(87)92423-8
Lowe DM Parmar V Kemp SD Larder BA Mutational analysis of two conserved sequence motifs in HIV-1 reverse transcriptase FEBS Lett 1991 282 231 234 1709876 10.1016/0014-5793(91)80484-K
Weinbreck PLV Denis F Vidal B Muvnier M DeLumley I Postnatal transmission of HIV infection Lancet 1988 1 482
Ziegler JB Cooper DA Johnson RO Gold J Postnatal transmission of AIDS-associated retrovirus from mother to infant Lancet 1985 1 896 898 2858746 10.1016/S0140-6736(85)91673-3
Ahmad N Molecular mechanisms of human immunodeficiency virus type 1 mother-infant transmission Adv Pharmacol 2000 49 387 416 11013769
Blanche S Rouzioux C Moscato ML Veber F Mayaux MJ Jacomet C Tricoire J Deville A Vial M Firtion G A prospective study of infants born to women seropositive for human immunodeficiency virus type 1. HIV Infection in Newborns French Collaborative Study Group N Engl J Med 1989 320 1643 1648 2657430
Mok JQ Giaquinto C De Rossi A Grosch-Worner I Ades AE Peckham CS Infants born to mothers seropositive for human immunodeficiency virus. Preliminary findings from a multicentre European study Lancet 1987 1 1164 1168 2883489 10.1016/S0140-6736(87)92142-8
Ryder RW Nsa W Hassig SE Behets F Rayfield M Ekungola B Nelson AM Mulenda U Francis H Mwandagalirwa K Perinatal transmission of the human immunodeficiency virus type 1 to infants of seropositive women in Zaire N Engl J Med 1989 320 1637 1642 2786145
Gotte M Li X Wainberg MA HIV-1 reverse transcription: a brief overview focused on structure-function relationships among molecules involved in initiation of the reaction Arch Biochem Biophys 1999 365 199 210 10328813 10.1006/abbi.1999.1209
Matala E Crandall KA Baker RC Ahmad N Limited heterogeneity of HIV type 1 in infected mothers correlates with lack of vertical transmission AIDS Res Hum Retroviruses 2000 16 1481 1489 11054261 10.1089/088922200750006001
Larder BA Kemp SD Darby G Related functional domains in virus DNA polymerases Embo J 1987 6 169 175 3034575
Kamer G Argos P Primary structural comparison of RNA-dependent polymerases from plant, animal and bacterial viruses Nucleic Acids Res 1984 12 7269 7282 6207485
Toh H Hayashida H Miyata T Sequence homology between retroviral reverse transcriptase and putative polymerases of hepatitis B virus and cauliflower mosaic virus Nature 1983 305 827 829 6195530 10.1038/305827a0
Ding J Hughes SH Arnold E Protein-nucleic acid interactions and DNA conformation in a complex of human immunodeficiency virus type 1 reverse transcriptase with a double-stranded DNA template-primer Biopolymers 1997 44 125 138 9354757 10.1002/(SICI)1097-0282(1997)44:2<125::AID-BIP2>3.0.CO;2-X
di Marzo Veronese F Copeland TD DeVico AL Rahman R Oroszlan S Gallo RC Sarngadharan MG Characterization of highly immunogenic p66/p51 as the reverse transcriptase of HTLV-III/LAV Science 1986 231 1289 1291 2418504
Gotte M Maier G Gross HJ Heumann H Localization of the active site of HIV-1 reverse transcriptase-associated RNase H domain on a DNA template using site-specific generated hydroxyl radicals J Biol Chem 1998 273 10139 10146 9553061 10.1074/jbc.273.17.10139
Hizi A McGill C Hughes SH Expression of soluble, enzymatically active, human immunodeficiency virus reverse transcriptase in Escherichia coli and analysis of mutants Proc Natl Acad Sci U S A 1988 85 1218 1222 2448794
Prasad VR Goff SP Linker insertion mutagenesis of the human immunodeficiency virus reverse transcriptase expressed in bacteria: definition of the minimal polymerase domain Proc Natl Acad Sci U S A 1989 86 3104 3108 2470090
Larder BA Purifoy DJ Powell KL Darby G Site-specific mutagenesis of AIDS virus reverse transcriptase Nature 1987 327 716 717 2439916 10.1038/327716a0
Le Grice SF Naas T Wohlgensinger B Schatz O Subunit-selective mutagenesis indicates minimal polymerase activity in heterodimer-associated p51 HIV-1 reverse transcriptase Embo J 1991 10 3905 3911 1718745
Boyer PL Ferris AL Clark P Whitmer J Frank P Tantillo C Arnold E Hughes SH Mutational analysis of the fingers and palm subdomains of human immunodeficiency virus type-1 (HIV-1) reverse transcriptase J Mol Biol 1994 243 472 483 7525967 10.1006/jmbi.1994.1673
Jacobo-Molina A Ding J Nanni RG Clark AD JrLu X Tantillo C Williams RL Kamer G Ferris AL Clark P Crystal structure of human immunodeficiency virus type 1 reverse transcriptase complexed with double-stranded DNA at 3.0 A resolution shows bent DNA Proc Natl Acad Sci U S A 1993 90 6320 6324 7687065
Kohlstaedt LA Wang J Friedman JM Rice PA Steitz TA Crystal structure at 3.5 A resolution of HIV-1 reverse transcriptase complexed with an inhibitor Science 1992 256 1783 1790 1377403
Julias JG McWilliams MJ Sarafianos SG Alvord WG Arnold E Hughes SH Mutation of amino acids in the connection domain of human immunodeficiency virus type 1 reverse transcriptase that contact the template-primer affects RNase H activity J Virol 2003 77 8548 8554 12857924 10.1128/JVI.77.15.8548-8554.2003
Julias JG McWilliams MJ Sarafianos SG Arnold E Hughes SH Mutations in the RNase H domain of HIV-1 reverse transcriptase affect the initiation of DNA synthesis and the specificity of RNase H cleavage in vivo Proc Natl Acad Sci U S A 2002 99 9515 9520 12093908 10.1073/pnas.142123199
Ding J Jacobo-Molina A Tantillo C Lu X Nanni RG Arnold E Buried surface analysis of HIV-1 reverse transcriptase p66/p51 heterodimer and its interaction with dsDNA template/primer J Mol Recognit 1994 7 157 161 7530020 10.1002/jmr.300070212
Gao G Orlova M Georgiadis MM Hendrickson WA Goff SP Conferring RNA polymerase activity to a DNA polymerase: a single residue in reverse transcriptase controls substrate selection Proc Natl Acad Sci U S A 1997 94 407 411 9012795 10.1073/pnas.94.2.407
Harris D Kaushik N Pandey PK Yadav PN Pandey VN Functional analysis of amino acid residues constituting the dNTP binding pocket of HIV-1 reverse transcriptase J Biol Chem 1998 273 33624 33634 9837947 10.1074/jbc.273.50.33624
Harris D Yadav PN Pandey VN Loss of polymerase activity due to Tyr to Phe substitution in the YMDD motif of human immunodeficiency virus type-1 reverse transcriptase is compensated by Met to Val substitution within the same motif Biochemistry 1998 37 9630 9640 9657675 10.1021/bi980549z
Boyer PL Ferris AL Hughes SH Cassette mutagenesis of the reverse transcriptase of human immunodeficiency virus type 1 J Virol 1992 66 1031 1039 1370546
Chao SF Chan VL Juranka P Kaplan AH Swanstrom R Hutchison CA 3rd Mutational sensitivity patterns define critical residues in the palm subdomain of the reverse transcriptase of human immunodeficiency virus type 1 Nucleic Acids Res 1995 23 803 810 7535923
Mulky A Sarafianos SG Arnold E Wu X Kappes JC Subunit-specific analysis of the human immunodeficiency virus type 1 reverse transcriptase in vivo J Virol 2004 78 7089 7096 15194785 10.1128/JVI.78.13.7089-7096.2004
Huelsenbeck JP Crandall KA Phylogeny estimation and hypothesis testing using maximum likelihood Annu Rev Ecol Sys 1997 437 466 10.1146/annurev.ecolsys.28.1.437
Swofford DI PAUP* Phylogenetic analysis using parsimony and other methods 4.0.0b2 1999 Sinauer associated, Sunderland, MA
Posada D Crandall KA MODELTEST: testing the model of DNA substitution Bioinformatics 1998 14 817 818 9918953 10.1093/bioinformatics/14.9.817
Nielsen R Yang Z Likelihood models for detecting positively selected amino acid sites and applications to the HIV-1 envelope gene Genetics 1998 148 929 936 9539414
Yang Z Phylogenetic Analysis of Maximum Likelihood (PAML) 2000 3.0 University College of London: London
Nei M Gojobori T Simple methods for estimating the numbers of synonymous and nonsynonymous nucleotide substitutions Mol Biol Evol 1986 3 418 426 3444411
Zanotto PM Kallas EG de Souza RF Holmes EC Genealogical evidence for positive selection in the nef gene of HIV-1 Genetics 1999 153 1077 1089 10545443
Hahn T Ramakrishnan R Ahmad N Evaluation of genetic diversity of human immunodeficiency virus type 1 NEF gene associated with vertical transmission J Biomed Sci 2003 10 436 450 12824703 10.1159/000071163
Jacobo-Molina A Arnold E HIV reverse transcriptase structure-function relationships Biochemistry 1991 30 6351 6356 1711368 10.1021/bi00240a001
Sarafianos SG Das K Tantillo C Clark AD JrDing J Whitcomb JM Boyer PL Hughes SH Arnold E Crystal structure of HIV-1 reverse transcriptase in complex with a polypurine tract RNA:DNA Embo J 2001 20 1449 1461 11250910 10.1093/emboj/20.6.1449
Huang H Chopra R Verdine GL Harrison SC Structure of a covalently trapped catalytic complex of HIV-1 reverse transcriptase: implications for drug resistance Science 1998 282 1669 1675 9831551 10.1126/science.282.5394.1669
Boyer PL Ding J Arnold E Hughes SH Subunit specificity of mutations that confer resistance to nonnucleoside inhibitors in human immunodeficiency virus type 1 reverse transcriptase Antimicrob Agents Chemother 1994 38 1909 1914 7529011
Cornelissen M van den Burg R Zorgdrager F Lukashov V Goudsmit J pol gene diversity of five human immunodeficiency virus type 1 subtypes: evidence for naturally occurring mutations that contribute to drug resistance, limited recombination patterns, and common ancestry for subtypes B and D J Virol 1997 71 6348 6358 9261352
Vergne L Peeters M Mpoudi-Ngole E Bourgeois A Liegeois F Toure-Kane C Mboup S Mulanga-Kabeya C Saman E Jourdan J Genetic diversity of protease and reverse transcriptase sequences in non-subtype-B human immunodeficiency virus type 1 strains: evidence of many minor drug resistance mutations in treatment-naive patients J Clin Microbiol 2000 38 3919 3925 11060045
Tantillo C Ding J Jacobo-Molina A Nanni RG Boyer PL Hughes SH Pauwels R Andries K Janssen PA Arnold E Locations of anti-AIDS drug binding sites and resistance mutations in the three-dimensional structure of HIV-1 reverse transcriptase. Implications for mechanisms of drug inhibition and resistance J Mol Biol 1994 243 369 387 7525966 10.1006/jmbi.1994.1665
Turner D Brenner B Wainberg MA Relationships among various nucleoside resistance-conferring mutations in the reverse transcriptase of HIV-1 J Antimicrob Chemother 2004 53 53 57 14645322 10.1093/jac/dkh009
Turner D Roldan A Brenner B Moisi D Routy JP Wainberg MA Variability in the PR and RT genes of HIV-1 isolated from recently infected subjects Antivir Chem Chemother 2004 15 255 259 15535047
Shafer RW Hsu P Patick AK Craig C Brendel V Identification of biased amino acid substitution patterns in human immunodeficiency virus type 1 isolates from patients treated with protease inhibitors J Virol 1999 73 6197 6202 10364383
Borrow P Lewicki H Wei X Horwitz MS Peffer N Meyers H Nelson JA Gairin JE Hahn BH Oldstone MB Shaw GM Antiviral pressure exerted by HIV-1-specific cytotoxic T lymphocytes (CTLs) during primary infection demonstrated by rapid selection of CTL escape virus Nat Med 1997 3 205 211 9018240 10.1038/nm0297-205
Harrer T Harrer E Kalams SA Barbosa P Trocha A Johnson RP Elbeik T Feinberg MB Buchbinder SP Walker BD Cytotoxic T lymphocytes in asymptomatic long-term nonprogressing HIV-1 infection. Breadth and specificity of the response and relation to in vivo viral quasispecies in a person with prolonged infection and low viral load J Immunol 1996 156 2616 2623 8786327
Harrer T Harrer E Kalams SA Elbeik T Staprans SI Feinberg MB Cao Y Ho DD Yilma T Caliendo AM Strong cytotoxic T cell and weak neutralizing antibody responses in a subset of persons with stable nonprogressing HIV type 1 infection AIDS Res Hum Retroviruses 1996 12 585 592 8743084
Klein MR van Baalen CA Holwerda AM Kerkhof Garde SR Bende RJ Keet IP Eeftinck-Schattenkerk JK Osterhaus AD Schuitemaker H Miedema F Kinetics of Gag-specific cytotoxic T lymphocyte responses during the clinical course of HIV-1 infection: a longitudinal analysis of rapid progressors and long-term asymptomatics J Exp Med 1995 181 1365 1372 7699324 10.1084/jem.181.4.1365
Rinaldo CR JrBeltz LA Huang XL Gupta P Fan Z Torpey DJ 3rd Anti-HIV type 1 cytotoxic T lymphocyte effector activity and disease progression in the first 8 years of HIV type 1 infection of homosexual men AIDS Res Hum Retroviruses 1995 11 481 489 7632463
Wilson CC Brown RC Korber BT Wilkes BM Ruhl DJ Sakamoto D Kunstman K Luzuriaga K Hanson IC Widmayer SM Wiznia A Clapp S Aman AJ Koup RA Wolinsky SM Walker BD Frequent detection of escape from cytotoxic T-lymphocyte recognition in perinatal human immunodeficiency virus (HIV) type 1 transmission: the ariel project for the prevention of transmission of HIV from mother to infant J Virol 1999 73 3975 3985 10196293
Menendez-Arias L Mas A Domingo E Cytotoxic T-lymphocyte responses to HIV-1 reverse transcriptase (review) Viral Immunol 1998 11 167 181 10189185
Hahn T Ahmad N Genetic characterization of HIV type 1 gag p17 matrix genes in isolates from infected mothers lacking perinatal transmission AIDS Res Hum Retroviruses 2001 17 1673 1680 11779356 10.1089/088922201753342095
Husain M Hahn T Yedavalli VR Ahmad N Characterization of HIV type 1 tat sequences associated with perinatal transmission AIDS Res Hum Retroviruses 2001 17 765 773 11429117 10.1089/088922201750237040
Yedavalli VR Chappey C Ahmad N Maintenance of an intact human immunodeficiency virus type 1 vpr gene following mother-to-infant transmission J Virol 1998 72 6937 6943 9658150
Yedavalli VR Chappey C Matala E Ahmad N Conservation of an intact vif gene of human immunodeficiency virus type 1 during maternal-fetal transmission J Virol 1998 72 1092 1102 9445004
Yedavalli VR Husain M Horodner A Ahmad N Molecular characterization of HIV type 1 vpu genes from mothers and infants after perinatal transmission AIDS Res Hum Retroviruses 2001 17 1089 1098 11485627 10.1089/088922201300343780
Albert J Wahlberg J Leitner T Escanilla D Uhlen M Analysis of a rape case by direct sequencing of the human immunodeficiency virus type 1 pol and gag genes J Virol 1994 68 5918 5924 7520096
Holmes EC Zhang LQ Simmonds P Rogers AS Brown AJ Molecular investigation of human immunodeficiency virus (HIV) infection in a patient of an HIV-infected surgeon J Infect Dis 1993 167 1411 1414 8501332
Huang Y Zhang L Ho DD Characterization of gag and pol sequences from long-term survivors of human immunodeficiency virus type 1 infection Virology 1998 240 36 49 9448687 10.1006/viro.1997.8913
Korber BT Learn G Mullins JI Hahn BH Wolinsky S Protecting HIV databases Nature 1995 378 242 244 7477340 10.1038/378242a0
Wolinsky SM Korber BT Neumann AU Daniels M Kunstman KJ Whetsell AJ Furtado MR Cao Y Ho DD Safrit JT Adaptive evolution of human immunodeficiency virus-type 1 during the natural course of infection Science 1996 272 537 542 8614801
Ahmad N Baroudy BM Baker RC Chappey C Genetic analysis of human immunodeficiency virus type 1 envelope V3 region isolates from mothers and infants after perinatal transmission J Virol 1995 69 1001 1012 7815476
Hahn T Matala E Chappey C Ahmad N Characterization of mother-infant HIV type 1 gag p17 sequences associated with perinatal transmission AIDS Res Hum Retroviruses 1999 15 875 888 10408724 10.1089/088922299310584
Sabbaj S Edwards BH Ghosh MK Semrau K Cheelo S Thea DM Kuhn L Ritter GD Mulligan MJ Goepfert PA Human immunodeficiency virus-specific CD8(+) T cells in human breast milk J Virol 2002 76 7365 7373 12097549 10.1128/JVI.76.15.7365-7373.2002
Matala E Hahn T Yedavalli VR Ahmad N Biological characterization of HIV type 1 envelope V3 regions from mothers and infants associated with perinatal transmission AIDS Res Hum Retroviruses 2001 17 1725 1735 11788024 10.1089/08892220152741423
Akaike H A new look at the statistical model identification IEEE Trans Autom Contr 1974 19 716 723 10.1109/TAC.1974.1100705
| 15918905 | PMC1166575 | CC BY | 2021-01-04 16:36:41 | no | Retrovirology. 2005 May 26; 2:36 | utf-8 | Retrovirology | 2,005 | 10.1186/1742-4690-2-36 | oa_comm |
==== Front
RetrovirologyRetrovirology1742-4690BioMed Central London 1742-4690-2-401596703710.1186/1742-4690-2-40Short ReportTRIM5α selectively binds a restriction-sensitive retroviral capsid Sebastian Sarah [email protected] Jeremy [email protected] Departments of Microbiology and Medicine, Columbia University, College of Physicians and Surgeons, 701 West 168th Street, HHSC 1502, New York, New York 10032, USA2005 20 6 2005 2 40 40 6 6 2005 20 6 2005 Copyright © 2005 Sebastian and Luban; licensee BioMed Central Ltd.2005Sebastian and Luban; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
TRIM5 is a potent retrovirus inhibitor that targets viruses bearing particular capsid (CA) residues. In most primate species, retroviral restriction requires the C-terminal SPRY domain unique to the α-isoform of TRIM5, but the mechanism by which susceptible viruses are recognized and targeted for restriction is unknown. Here we show that TRIM5α binds retroviral CA from detergent-stripped virions in a SPRY-dependent manner with sufficient discrimination to account for the exquisite specificity of restriction.
==== Body
Findings
Two independent screens identified TRIM5 as a potent retrovirus restriction element that targets select viruses after entry into primate cells [1,2]. The biochemical basis for specificity of restriction is only evident in cells of the owl monkey where HIV-1 CA is recognized by the C-terminal cyclophilin domain that is unique to the TRIM5 orthologue found in this genus [2-4]. In all other primates, including humans and macaques, potent CA-specific restriction is conferred by the TRIM5α isoform [1,5-9], which possesses a C-terminal SPRY domain [10]. The mechanism by which TRIM5α selects retroviruses bearing particular CAs for restriction is unknown, though the TRIM5α SPRY domain is required for restriction and variation in SPRY amino acid residues determines the CA-specificity of given TRIM5α orthologues [9,11-13].
Conventional biochemical and two-hybid experiments failed to detect an interaction between TRIM5α and CA (SS and JL, unpublished data). The observation that non-infectious virus-like particles saturate TRIM5α-mediated restriction [14], but only if the particles bear a mature core from a restriction-sensitive virus [15,16] suggests that the TRIM5α SPRY domain recognizes a complex structure unique to the core of susceptible virions. Consistent with this model, expression within target cells of gag, gag-pol, or gag fragments encoding CA, CA-NC, or ubiquitin-CA-NC fusions, failed to block restriction activity (David Sayah and JL, unpublished data).
Retrovirion cores can be liberated from the viral membrane envelope by detergent [17]. HIV-1 virion cores were prepared with several different detergents and mixed with recombinant TRIM5 orthologues. After TRIM5 enrichment by affinity chromatography, CA associated with owl monkey TRIMCypA, as reported with other methods [3,4], but not with the equally potent HIV-1 restriction factor rhesus macaque TRIM5α (SS and JL, unpublished data).
We then selected murine leukemia virus (MLV) for study because, relative to HIV-1, MLV CA remains tightly associated with viral reverse transcription (RT) and preintegration complexes [18,19]. MLV strains bearing an arginine at CA residue 110 (so-called N-MLV) are highly susceptible to restriction by human TRIM5α whereas MLV virions bearing glutamate in this position (B-MLV) are completely resistant to restriction [5-8].
VSV G-pseudotyped N- and B-tropic MLV virions were produced as previously described [20] and, after normalization on non-restrictive Mus dunni cells, N-MLV was roughly 100-fold less infectious than B-MLV on HeLa cells (Figure 1A). Full-length human TRIM5α was then produced as a GST-fusion protein in 293T cells and mixed with purified N-MLV virions. CAp30, the major MLV core protein constituent, associated with TRIM5α (Figure 1B). CAp30 from B-MLV virions did not associate with TRIM5α (Figure 1B) demonstrating that TRIM5α binding was specific for restriction-sensitive CA. CAp30 did not associate with TRIM5 lacking the SPRY domain (Figure 1B), indicating that the SPRY-domain is required for CA-recognition.
Figure 1 Human TRIM5α binds CA from restricted MLV virions. (A) HeLa cells were infected with VSV G-pseudotyped, N- and B-tropic MLV-GFP vectors after normalization for RT activity and infectivity on non-restrictive Mus dunni tail fibroblasts. The percentage of infected (GFP-positive) cells was determined by flow cytometry. (B) 293T cells were transfected with plasmids encoding glutathione S-transferase (GST) fusions with full-length TRIM5α or with TRIM5 lacking the SPRY domain. Cells were lysed (50 mM Tris pH 8.0, 150 mM NaCl, 1% NP-40, 0.1% SDS) and mixed for 2 hrs at 4°C with virions (N-MLV or B-MLV) that had been concentrated by acceleration through 25% sucrose. GST fusions and associated proteins were enriched on glutathione-sepharose beads and immunoblotted with goat anti-MLV CA antibody (CA pull-out), or anti-GST antibody (bottom panel). Unbound CA remaining in the binding reaction was probed with anti-MLV CA antibody (CA input). TRIM5 protein domains fused to GST are indicated schematically on the bottom left: RF, ring finger; BB, B box; CC, coiled-coil.
Retroviral restriction specificity thus seems to be determined by TRIM5α binding to CA in a process that requires the SPRY domain. The fact that TRIM5α recognized retroviral CA presented by detergent-stripped virion cores, but not free CA protein, suggests that the SPRY domain recognizes a complex surface of multimerized CA. Once cores of restriction-sensitive viruses are singled out by the SPRY domain, TRIM5α blocks retroviral RT [1] by a mechanism that awaits elucidation. Our findings bring us one step closer to understanding how the potent antiviral activity of TRIM5α might be harnessed to block HIV-1 infection in people.
List of abbreviations
HIV-1, human immunodeficiency virus; MLV, murine leukemia virus; TRIM, tripartite motif protein; RT, reverse transcriptase; CA, retroviral capsid protein; GST, glutathione S-transferase; RF, ring finger domain; BB, B box domain; CC, coiled-coil domain.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
SS and JL conceived the experiments and wrote the manuscript. SS performed the laboratory work. Both authors read and approved the final manuscript.
Acknowledgements
This work was supported by NIH grant AI 36199 to J.L.
==== Refs
Stremlau M Owens CM Perron MJ Kiessling M Autissier P Sodroski J The cytoplasmic body component TRIM5alpha restricts HIV-1 infection in Old World monkeys Nature 2004 427 848 853 14985764 10.1038/nature02343
Sayah DM Sokolskaja E Berthoux L Luban J Cyclophilin A retrotransposition into TRIM5 explains owl monkey resistance to HIV-1 Nature 2004 430 569 573 15243629 10.1038/nature02777
Nisole S Lynch C Stoye JP Yap MW A Trim5-cyclophilin A fusion protein found in owl monkey kidney cells can restrict HIV-1 Proc Natl Acad Sci U S A 2004 101 13324 13328 15326303 10.1073/pnas.0404640101
Berthoux L Sebastian S Sayah DM Luban J Disruption of human TRIM5alpha antiviral activity by nonhuman primate orthologues J Virol 2005 79 7883 7888 15919943 10.1128/JVI.79.12.7883-7888.2005
Keckesova Z Ylinen LM Towers GJ The human and African green monkey TRIM5alpha genes encode Ref1 and Lv1 retroviral restriction factor activities Proc Natl Acad Sci U S A 2004 101 10780 10785 15249687 10.1073/pnas.0402474101
Hatziioannou T Perez-Caballero D Yang A Cowan S Bieniasz PD Retrovirus resistance factors Ref1 and Lv1 are species-specific variants of TRIM5alpha Proc Natl Acad Sci U S A 2004 101 10774 10779 15249685 10.1073/pnas.0402361101
Yap MW Nisole S Lynch C Stoye JP Trim5alpha protein restricts both HIV-1 and murine leukemia virus Proc Natl Acad Sci U S A 2004 101 10786 10791 15249690 10.1073/pnas.0402876101
Perron MJ Stremlau M Song B Ulm W Mulligan RC Sodroski J TRIM5alpha mediates the postentry block to N-tropic murine leukemia viruses in human cells Proc Natl Acad Sci U S A 2004 101 11827 11832 15280539 10.1073/pnas.0403364101
Song B Javanbakht H Perron M Park do H Stremlau M Sodroski J Retrovirus restriction by TRIM5alpha variants from old world and new world primates J Virol 2005 79 3930 3937 15767395 10.1128/JVI.79.7.3930-3937.2005
Ponting C Schultz J Bork P SPRY domains in ryanodine receptors (Ca(2+)-release channels) Trends Biochem Sci 1997 22 193 194 9204703 10.1016/S0968-0004(97)01049-9
Yap MW Nisole S Stoye JP A single amino acid change in the SPRY domain of human Trim5alpha leads to HIV-1 restriction Curr Biol 2005 15 73 78 15649369 10.1016/j.cub.2004.12.042
Sawyer SL Wu LI Emerman M Malik HS Positive selection of primate TRIM5alpha identifies a critical species-specific retroviral restriction domain Proc Natl Acad Sci U S A 2005 102 2832 2837 15689398 10.1073/pnas.0409853102
Stremlau M Perron M Welikala S Sodroski J Species-Specific Variation in the B30.2(SPRY) Domain of TRIM5{alpha} Determines the Potency of Human Immunodeficiency Virus Restriction J Virol 2005 79 3139 3145 15709033 10.1128/JVI.79.5.3139-3145.2005
Towers G Collins M Takeuchi Y Abrogation of Ref1 retrovirus restriction in human cells J Virol 2002 76 2548 2550 11836433 10.1128/jvi.76.5.2548-2550.2002
Cowan S Hatziioannou T Cunningham T Muesing MA Gottlinger HG Bieniasz PD Cellular inhibitors with Fv1-like activity restrict human and simian immunodeficiency virus tropism Proc Natl Acad Sci U S A 2002 99 11914 11919 12154227 10.1073/pnas.162299499
Towers GJ Hatziioannou T Cowan S Goff SP Luban J Bieniasz PD Cyclophilin A modulates the sensitivity of HIV-1 to host restriction factors Nat Med 2003 9 1138 1143 12897779 10.1038/nm910
Welker R Hohenberg H Tessmer U Huckhagel C Krausslich HG Biochemical and structural analysis of isolated mature cores of human immunodeficiency virus type 1 J Virol 2000 74 1168 1177 10627527 10.1128/JVI.74.3.1168-1177.2000
Bowerman B Brown PO Bishop JM Varmus HE A nucleoprotein complex mediates the integration of retroviral DNA Genes Dev 1989 3 469 478 2721960
Fassati A Goff SP Characterization of intracellular reverse transcription complexes of Moloney murine leukemia virus J Virol 1999 73 8919 8925 10515996
Towers G Bock M Martin S Takeuchi Y Stoye JP Danos O A conserved mechanism of retrovirus restriction in mammals Proc Natl Acad Sci U S A 2000 97 12295 12299 11027299 10.1073/pnas.200286297
| 15967037 | PMC1166576 | CC BY | 2021-01-04 16:36:40 | no | Retrovirology. 2005 Jun 20; 2:40 | utf-8 | Retrovirology | 2,005 | 10.1186/1742-4690-2-40 | oa_comm |
==== Front
Respir ResRespiratory Research1465-99211465-993XBioMed Central London 1465-9921-6-441591670310.1186/1465-9921-6-44ResearchInterleukin-17A mRNA and protein expression within cells from the human bronchoalveolar space after exposure to organic dust Ivanov Stefan [email protected] Lena [email protected] Per [email protected] Kjell [email protected]én Anders [email protected] Lung Pharmacology Group, Department of Respiratory Medicine and Allergy, Institute for Internal Medicine, Göteborg University, Guldhedsgatan 10A, 413 46 Gothenburg, Sweden2 Lung and Allergy Research, the Institute of Environmental Medicine, Karolinska Institute, 171 77 Stockholm, Sweden3 Department of Clinical Chemistry and Pharmacology, Uppsala University, 751 85 Uppsala, Sweden2005 25 5 2005 6 1 44 44 8 11 2004 25 5 2005 Copyright © 2005 Ivanov et al; licensee BioMed Central Ltd.2005Ivanov et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
In mice, the cytokine interleukin (IL)-17A causes a local accumulation of neutrophils within the bronchoalveolar space. IL-17A may thereby also contribute to an increased local proteolytic burden. In the current study, we determined whether mRNA for IL-17A is elevated and protein expression of IL-17A occurs locally in inflammatory cells within the human bronchoalveolar space during severe inflammation caused by organic dust. We also assessed the expression of the elastinolytic protease MMP-9 in this airway compartment.
Methods
Six healthy, non-smoking human volunteers were exposed to organic dust in a swine confinement, a potent stimulus of neutrophil accumulation within the human bronchoalveolar space. Bronchoalveolar lavage (BAL) fluid was harvested 2 weeks before and 24 hours after the exposure and total and differential counts were conducted for inflammatory BAL cells. Messenger RNA for IL-17A was measured using reverse transcript polymerase chain reaction-enzyme linked immunoassay (RT-PCR-ELISA). Intracellular immunoreactivity (IR) for IL-17A and MMP-9, respectively, was determined in BAL cells.
Results
The exposure to organic dust caused more than a forty-fold increase of mRNA for IL-17A in BAL cells. IL-17A immunoreactivity was detected mainly in BAL lymphocytes, and the number of these IL-17A expressing lymphocytes displayed an eight-fold increase, even though not statistically significant. The increase in IL-17A mRNA was associated with a substantial increase of the number of BAL neutrophils expressing MMP-9 immunoreactivity.
Conclusion
Exposure to organic dust increases local IL-17A mRNA and because there is intracellular expression in BAL lymphocytes, this suggests that IL-17A protein can originate from lymphocytes within the human bronchoalveolar space. The fact that the increased IL-17A mRNA is associated with an increased number of MMP-9-expressing neutrophils is compatible with IL-17A increasing the local proteolytic burden through its neutrophil-accumulating effect.
==== Body
Introduction
Several chronic lung diseases are associated with an exaggerated accumulation and activity of neutrophils locally in the human bronchoalveolar space [1]. These lung diseases include acute, severe asthma, chronic bronchitis and chronic obstructive pulmonary disease (COPD) [1]. Neutrophils may play a pathogenic role in these diseases through the release of free oxygen radicals and by producing enzymes that increase the local proteolytic burden. Thus, via these compounds, neutrophils may contribute to pathogenic hallmarks such as non-specific bronchial hyper-responsiveness and hypersecretion, as well as to epithelial damage and tissue remodelling [1].
There is evidence that, among the proteolytic enzymes in the lungs, matrix metalloproteinase (MMP)-9 plays an important pathogenic role and this is most likely due to its capacity to cleave structural proteins such as collagens and elastin [2]. In support of this, local MMP-9 is increased in asthma and in COPD [3-8]. It is believed that neutrophils constitute an important source of MMP-9 in the lungs, even though macrophages, bronchial epithelial cells and fibroblasts may also produce MMP-9 under certain conditions [2].
Recent studies on mice in vivo and on human cells in vitro are compatible with activated T-lymphocytes contributing to the local accumulation of neutrophils in the bronchoalveolar space through the release of the cytokine interleukin (IL)-17A. However it remains unknown whether lymphocytes producing IL-17A actually reside within the bronchoalveolar space of humans [1]. In the bronchoalveolar space of mice and rats, local administration of recombinant IL-17A protein increases the number of neutrophils substantially [1,9]. Systemic pre-treatment with a neutralizing anti-IL-17A antibody attenuates endotoxin-induced neutrophil accumulation in the same compartment of mice [10]. It is likely that IL-17A causes this neutrophil accumulation in part indirectly through the induced production of neutrophil-mobilizing cytokines, such as granulocyte-macrophage colony-stimulating factor (GMC-SF), IL-6 and IL-8, in local cells, including bronchial epithelial cells, fibroblasts and smooth muscle cells [1,10]. In addition, there are now studies on mice and rats indicating that IL-17A may control the local proteolytic burden in the bronchoalveolar space in vivo through its impact on neutrophil accumulation [11,12].
We recently showed that organic dust in a swine confinement, a strong stimulus of neutrophilic inflammation, causes a substantial increase in the concentration of free, soluble IL-17A protein in the human bronchoalveolar space [13]. Interestingly, this increase in local IL-17A protein is associated not only with an accumulation of neutrophils but also with an accumulation of lymphocytes. The current study was undertaken to determine whether these lymphocytes can produce IL-17A in humans. The study was also undertaken to address whether production of IL-17A is associated with an increased local proteolytic burden from neutrophils. Exposure to organic dust in a swine confinement was utilised as a pro-inflammatory stimulus and intracellular expression of MMP-9 was targeted as a sign of proteolytic burden in the bronchoalveolar space of human healthy volunteers.
Methods
Study design
The study protocol was approved by the Ethics Committee at Karolinska Institute (Diary N. KI 95:347). Six healthy, non-smoking volunteers gave their written consent to participate in the study after receiving both written and oral information.
All the participants were non-atopic, non-asthmatic as determined by history and questionnaire. They were exposed to organic dust while weighing pigs in a swine confinement (ie. a barn) during three hours, as previously described [14-16]. The procedure incorporates exposure to aerosolised organic dust, with a concentration of approximately 24 mg dust and 1.2 μg endotoxin per m3, as assessed in a recent study [13]. Normal lung function and normal airway responsiveness were ascertained in all subjects prior to exposure. The subjects underwent bronchoscopy with bronchoalveolar lavage (BAL-see below) 2 weeks before and 24 hours after the exposure.
Lung function
Spirometry was performed in accordance with the criteria of the American Thoracic Society using a low-resistance rolling-seal spirometer (OHIO model 840; Airco, Madison, WI, USA) [17]. Swedish reference values were used [18,19].
Bronchial responsiveness
The methacholine provocation test was conducted prior to exposure to ascertain a normal airway function, as previously described [20]. Briefly, after the inhalation of the diluent (vehicle) alone, doubling concentrations of methacholine were given starting at 0,5 and ending at 32 mg/ml. The test was stopped either at a FEV1 decrease of 20%, compared to the value registered after the inhalation of the diluent, or after inhalation of the highest methacholine provocation (32 mg/ml). The cumulative dose causing a 20% decrease of FEV1 (PD20FEV1) was calculated.
Bronchoalveolar lavage
Bronchoscopy and bronchoalveolar lavage were performed according to standard procedures previously described [13]. In short, after pre-medication with morphine-scopolamine, a flexible fibreoptic bronchoscope (Olympus Type 4B2; Olympus Optical Co. Ltd., Shinjukuku, Tokyo, Japan) was inserted through the nose under local anaesthesia with lidocaine (Xylocain R, Astra, Södertälje, Sweden). The bronchoscope was wedged in a middle lobe bronchus and a total of 250 ml of sterile saline at 37°C was instilled in 5 aliquots of 50 ml. After each instillation, the BAL suspension was gently aspirated and collected in a siliconized plastic bottle kept on ice.
After sterile filtration (70 μm filter), the BAL suspension was centrifuged (Hereus Omnifuge 300 g, 10 min, +4°C). The cell-free supernatant was kept frozen (-80°C) until analysis. The cell pellet was resuspended (phosphate-buffered saline [PBS]: 5 ml). Viability of cells was assessed using trypan blue exclusion and the total cell number (ie. concentration) was determined for each sample in a Bürker chamber. BAL cytospin samples were prepared and stained (May-Grünwald-Giemsa) and differential cell counts were performed using light microscopy (Zeiss Axiopaln 2, Carl Zeiss, Jena, Germany).
Messenger RNA for IL-17A
Remaining cells from the resuspended pellet were centrifuged (see above) and the supernatant was removed. The cell pellet was re-suspended (PBS: 50 μl plus RNAlater from Ambion Inc, Austin, USA: 250 μl per 3 × 106 cells), transferred into microtubes, (3 × 106 cells per tube) and incubated (24 hrs, +4°C). The RNeasy minikit was used according to the manufacturer's protocol with the following modification: The eluted RNA was treated with Dnase I (Rnase-Free Dnase set: 30 min, 37°C). After this, the steps from adjusting binding conditions to eluting RNA were repeated.
The eluted total RNA was measured for quantity and purity using spectrophotometry (SpectraMaxPlus®Molecular Devices Corporation Sunnyvale, CA, USA; absorbance at 260 and 260/280 nm respectively) and then stored frozen (-83°C) until purification of Total RNA.
The RT-PCR ELISA technique was employed to quantify relative changes in the IL-17A mRNA gene transcript. A one-step RT-PCR was utilized with a Gene Amp PCR system 2400 (Perkin Elmer, Wellesley, MA, USA) for amplification. Each RT-PCR of 50 μl was conducted using 100 ng of total cellular RNA and 30 pmol of each primer, 10 U RNase inhibitor (recombinant RNasin, Promega Corporation, Madison, WI, USA), 200 μM PCR DIG Labelling mix (20 μM dATP, dGTP, dCTP each plus 19 μM dTTP plus 1 μM DIG-dUTP), 5 mM DDT, 10 μl RT-PCR reaction buffer (1.5 mM Mg+), 1 μl Titan enzyme mix (AMV reverse transcriptase+Taq DNA polymerase+Pwo DNA polymerase) or 0,5 μl Expand high fidelity PCR system (Taq DNA polymerase+Pwo DNA polymerase) for DNA controls (all reagents from Roche Diagnostics). Reverse transcription was performed (30 min, 50°C). The IL-17A and the house-keeping gene HPRT were subsequently annealed (55°C). IL-17A and HPRT were then amplified (35 and 30 cycles, respectively) and the DIG labelled PCR product was stored frozen (-20°C) before the detection step. RT-PCRs were performed in duplicate. Gene sequences were accessed from NCBI Database and accession number used was for human (h) HPRT V00530 and for hIL-17 U32659. Scandinavian Gene Synthesis AB (Köping, Sweden) provided the oligonucleotides.
The gene primer sequences used for RT-PCR and ELISA detection:
hHPRT
Sense (5') 5'CGT CGT GAT TAG TGA TGA TGA AC3'
Antisense (3') 5'GCA AAG TCT GCA TTG TTT TGC CA3'
Internal probe 5'GAG GCC ATC ACA TTG TAG CCC TCT GTG3'
hIL-17
Sense (5') 5' GTG AAG GCA GGA ATC ACA ATC 3'
Antisense (5') 5' ACC AGG ATC TCT TGC TGG AT 3'
Internal probe 5' CAG AGT TCA TGT GGT AGT CCA CGT TCC CA 3'
The DIG labelled PCR products were denaturated and hybridized with the biotinylated internal probe specifically designed to hybridize with each gene PCR product, and immobilized on streptavidin coated microtiter plates (3 hrs, 42°C), utilising the PCR ELISA DIG-detection kit (Roche). After washing, the bound PCR-products were incubated (30 min, 37°C) with an anti-DIG-horseradish peroxidase conjugated antibody followed by reaction (20 min) with the substrate 2,2'-azino-di(3-ethyl benzthiazoline sulfonate) (ABTS). The absorbance was then measured using spectrophotometry (see above, at 405/492 nm) in an ELISA plate reader (Labsystems Multiscan Multisoft, Vanda, Finland). The expression of transcripts for IL-17 mRNA was normalized to the expression of HPRT transcripts and shown as percent of the house-keeping gene (% HPRT). In parallel with tested samples, control samples for PCR, probe specificity, DNA contamination, hybridisation and sample dilution were run.
Immunocytochemistry (ICC)
General procedure
BAL cells were fixed with formaldehyde (2%, 30 min, on ice) and washed twice in buffer prior to making cytospin preparations. Air-dried samples were stored frozen (-80°C) until further use. After thawing, samples were treated with donkey serum (10%) to avoid unspecific binding. Endogenous biotin was blocked using the Biotin Blocking System (DAKO corporation, Glostrup, Denmark).
IL-17A immunoreactivity (IR)
The intracellular expression of IL-17A protein was assessed utilising cytospin slides incubated with a polyclonal goat anti-human IL-17A antibody (R&D: 1 hr). As secondary antibody, a biotinylated F(ab')2 fragment donkey anti-goat IgG (Jackson ImmunoResearch laboratories Inc) was used, followed by alkaline phosphatase-conjugated streptavidin (DAKO). All the solutions above were supplemented with saponin (Sigma: 0.1 %), to permeabilise cell membrane. Bound antibodies were visualised with Vector Red Alkaline Substrate Kit (Vector Laboratories, Inc. Burlingame, CA, USA). Mayer's Hematoxylin (Sigma) was used for counterstaining.
MMP-9 immunoreactivity
The intracellular expression of MMP-9 protein was assessed utilising cytospin slides incubated with a polyclonal goat anti-human MMP-9 (R&D: 1 hr). The secondary antibody and the detection system were the same as for IL-17A (see above).
Human neutrophilic lipocalin
The concentration of the neutrophil-specific activity marker human neutrophilic lipocalin (HNL) was measured in cell-free BAL fluid using a solid phase, double-ligand radioimmunoassay as described elsewhere [21].
Data analyses
Data are presented as median (range) values unless otherwise stated. The analysis of differences between measurements prior to and after the exposure, were conducted utilizing the sign test, assuming binominal distribution. To avoid falsely positive conclusions, the significance level at each test was set to 0.05/3 (ie. 0.0167), since three key variables (IL-17A mRNA, IL-17 IR and MMP9 IR) were compared in the current material. n refers to number of human subjects.
Results
Clinical characteristics prior to exposure
Four males and 2 females with a median age of 22 (19–24) were included in the study. There were no apparent gender-related differences in pulmonary function of the subjects. FEV1 was 96 (92 – 105) % of predicted value and vital capacity 98 (90–102) % predicted value. All subjects had normal bronchial responsiveness to metacholine (PD20FEV1 for metacholine: 5.3 [1.7–15] mg).
Cells in BAL fluid
The BAL recovery volume was similar before (195 [170–234] ml) and after (196 [190–212] ml) the exposure. The exposure caused more than a two-fold increase in the total BAL cell number, more than a five-fold increase in the number of lymphocytes and more than a ten-fold increase in the number of neutrophils.(Table 1).
Table 1 Concentration of BAL cells. BAL cells before and after exposure to organic dust in a swine confinement. Data are presented as 1 × 106/L median (range).
Cell type Before After
Total cells 71,3 (57,9–80,9) 165,1 (98,2–365,6)
Lymphocytes 4,4 (1,2–10.0) 23,1 (9,8–61,6)
Neutrophils 2,3 (0,8–3,6) 23,1 (6,6–167,3)
Messenger RNA for IL-17A
Before the exposure, 4 out of 6 persons displayed no detectable levels of mRNA for IL-17A, whereas all six subjects displayed detectable and increased levels after the exposure (fig. 1).
Figure 1 Messenger RNA for IL-17A in BAL cells. Messenger RNA for IL-17A in BAL cells (percentage of the house-keeping gene HPRT), measured 2 weeks before and 24 hours after exposure to organic dust in a swine confinement. Data are shown as individual (rhombs) plus median (bold horizontal lines) values. *: p < 0,0167; n = 6
IL-17A immunoreactivity
IL-17A immunoreactivity was mainly detected in BAL lymphocytes (fig. 2). In addition, the percentage of lymphocytes positive for IL-17A immunoreactivity (fig. 3) tended to increase in 5 out of 6 subjects after the exposure. In contrast, a much lower fraction of macrophages expressed a weak signal for IL-17A immunoreactivity and there was no pronounced increase in this signal after the exposure (data not shown). BAL neutrophils did not display IL-17A immunoreactivity (data not shown)
Figure 2 Immunocytochemical detection of IL-17A protein in BAL lymphocytes. BAL lymphocytes expressing IL-17A IR (brown arrows) after exposure to organic dust in a swine confinement, detected using immunocytochemistry.
Figure 3 BAL lymphocytes expressing IL-17A protein. Percentage of BAL lymphocytes expressing IL-17A IR before and after the exposure to organic dust in a swine confinement. Data are shown as individual (rhombs) plus median (bold horizontal lines) values. NS: p > 0,0167; n = 6
MMP-9 immunoreactivity
Neutrophils were the prevailing cell type in BAL fluid expressing MMP-9 immunoreactivity (fig. 4) and this signal was substantially increased after exposure (fig. 5). However, the fraction of neutrophils (% all neutrophils) expressing MMP-9 immunoreactivity was not increased after exposure (data not shown). Very few macrophages expressed MMP-9 immunoreactivity and this signal was consistently weak (data not shown).
Figure 4 Immunocytochemical detection of MMP-9 protein in BAL neutrophils. Abundance of BAL neutrophils positive for MMP-9 IR (purple arrows) after exposure to organic dust in a swine confinement.
Figure 5 BAL neutrophils expressing MMP-9 protein. BAL neutrophils expressing MMP-9 IR (percent of total cells) before and after exposure to organic dust in a swine confinement. Data are shown as individual (rhombs) plus median (bold horizontal lines) values. *: p < 0,0167; n = 5.
HNL
The exposure did not cause any substantial increase in the concentration of free, soluble HNL in the BAL fluid, even though there was a weak average trend in this direction (data not shown). Furthermore, the amount of HNL per neutrophil tended to be decreased after exposure (data not shown).
Discussion
The current study demonstrates that, in previously healthy human volunteers, exposure to organic dust substantially increases the messenger RNA for IL-17A in BAL cells. Our study also demonstrates that lymphocytes constitute the predominant cell type that expresses intracellular IL-17A protein among BAL cells. The demonstrated increase in IL-17A mRNA is associated with an increased absolute number of MMP-9 expressing BAL neutrophils at the same time point.
The aerosolised organic dust in a swine confinement, that was utilised as a pro-inflammatory stimulus in our study, is a more complex stimulus than endotoxin, because of its mixed content of grain dust, ammonia, fungi, Gram-positive and Gram-negative bacteria [15]. It has previously been shown that exposure to this type of organic dust causes severe inflammation in the bronchoalveolar space of humans [13,15,16]. Our current study now adds to these previous studies novel evidence of de novo synthesis of IL-17A by local cells within the bronchoalveolar space of humans [1]. Furthermore, our study forwards lymphocytes as a local source of IL-17A protein in the human bronchoalveolar space, because the intracellular immunoreactivity for this specific protein was found mainly in certain BAL lymphocytes. Noteworthy, even though this immunoreactivity should be regarded as a qualitative assessment primarily, it was increased eight-fold by average after exposure with only one subject lacking a detectable increase. Clearly, this is compatible with lymphocytes accounting for production of IL-17A protein in the bronchoalveolar space of humans. Indeed, our current results are supported by our previous demonstration of an increase in the final consequence of the increased transcription and intracellular loading of protein, namely in free, soluble IL-17A protein in cell-free BAL fluid [13]. It is also noteworthy that in our current study, certain but not all lymphocytes in the human bronchoalveolar space express IL-17A protein after exposure to organic dust. This observation is compatible with previous studies on activated mouse CD4+ and CD8+ lymphocytes from BAL and spleen as well as human CD4+ and CD8+ lymphocytes from blood [1,22-28]. Taken together, these observations warrant new specific cellular targets for additional analysis in future studies on human airways.
We assessed intracellular immunoreactivity for MMP-9 as a marker of proteolytic burden, both before and after exposure to organic dust. Even though some of the BAL macrophages displayed a very weak expression of MMP-9 immunoreactivity, as has previously been reported in a different inflammatory setting [29], we found the most pronounced increase in and expression of MMP-9 immunoreactivity consistently among BAL neutrophils. This observation fully supports that neutrophils can constitute an important source of MMP-9 in the human bronchoalveolar space in vivo, at least after exposure to organic dust. At the same time point after the exposure, the MMP-9 expression in neutrophils was associated with an increase in mRNA for IL-17A, even though the fraction (percentage) of neutrophils expressing MMP-9 was not increased. This is compatible with IL-17A indirectly contributing to the local proteolytic load, mainly through its increasing effect on the number of neutrophils within the human bronchoalveolar space; a type of mechanism supported by previous studies on the bronchoalveolar space of mice in vivo [9,12].
We also measured the concentration of free, soluble HNL protein in BAL fluid, as an assessment of neutrophil-specific activity [30]. However, we detected only a weak average trend towards a modest increase in the HNL concentration after exposure to organic dust and this increase did not even correspond to the substantial increase in neutrophil number; the amount of HNL per neutrophil was actually decreased after the exposure. Furthermore some subjects displayed even a decrease in the total HNL concentration after exposure. Moreover, separate and preliminary assessments of the myeloperoxidase (MPO) concentration in BAL fluid displayed a weak increase not corresponding to the increase in neutrophil number (data not shown). Similar findings on MPO and neutrophils have previously been published [31]. Taken together, all these findings imply that, in terms of MPO and HNL, there is actually no true increase in the average activity of each accumulated neutrophil in the human bronchoalveolar space after exposure to organic dust. Again, from a mechanistical point of view, this finding in the bronchoalveolar space of humans is supported by our recently published findings on the effect of recombinant IL-17A in the bronchoalveolar space of mice in vivo [12]. This IL-17A induces an increase of MMP-9 protein and in corresponding gelatinase activity, that is due to an increased number of neutrophils rather than an increased amount of MMP-9 per neutrophil [12].
In conclusion, supported by our recent study showing a corresponding increase in free, soluble IL-17A protein [13], the current study adds novel evidence for organic dust inducing de novo synthesis of IL-17A protein in a subset of local lymphocytes within the human bronchoalveolar space. Our current study on humans also adds evidence compatible with induced de novo synthesis of IL-17A being associated with an increased proteolytic burden due to a local accumulation of neutrophils rather than an increased activity in each of these inflammatory cells. Interventional studies will be required to determine whether targeting IL-17A is therapeutically beneficial in lung diseases characterised by excessive accumulation of neutrophils.
Authors' contributions
LP, KL, AL – study design and coordination
SI, LP, KL, PV – exposure in swine farm, laboratory work
SI, AL – data analysis and interpretation of results
SI, LP, KL, PV, AL – preparation and revision of the manuscript
Acknowledgements
The present study was financially supported by Göteborg University, the Karolinska Institute, the Swedish Heart-Lung Foundation, the Swedish Medical Research Council (K2002-74X-09048-13A), the Vårdal Foundation and, finally, by Glaxo-Wellcome, Sweden. No support was obtained from the tobacco industry.
The excellent technical support by Carina Malmhäll, B Sci, and Margareta Sjöstrand, PhD, is gratefully acknowledged. The support with statistical analysis by Associate Professor Kerstin Wiklander, Department of Mathematics, the Chalmer's University of Technology in Göteborg is also acknowledged.
==== Refs
Kolls J Lindén A Interleukin-17 family members and inflammation Immunity 2004 21 467 476 15485625 10.1016/j.immuni.2004.08.018
Atkinson JJ Senior RM Matrix Metalloproteinase-9 in lung remodeling Am J Respir Cell Mol Biol 2003 28 12 24 12495928 10.1165/rcmb.2002-0166TR
Cataldo DD Bettiol J Noel A Bartch P Foidart JM Louis R Matrix metalloproteinase-9, but not tissue inhibitor of matrix metalloproteinase-1, increases in the sputum from allergic patients after allergen challenge Chest 2002 122 5 1553 1559 12426252 10.1378/chest.122.5.1553
Mattos W Lim S Russel R Jatakanon A Chung KF Barnes PJ Matrix mettaloproteinase-9 expression in asthma: effect of asthma severity, allergen challenge, and inhaled corticosteroids Chest 2002 122 5 1543 1552 12426251 10.1378/chest.122.5.1543
Lee YC Lee HB Rhee YK Song CH The involvement of matrix metalloproteinase-9 in airway inflammation of patients with acute asthma Clin Exp Allergy 2001 31 1623 1630 11678864 10.1046/j.1365-2222.2001.01211.x
Ohnishi K Takagi M Kurokawa Y Satomi S Konttinen YT Matrix metalloproteinase-mediated extracellular matrix protein degradation in human pulmonary emphysema Lab Invest 1998 78 1077 1087 9759652
Finlay GA Russel KG McMahon KG D'Arcy EM Masterson JB FitzGerald MX O'Connor CM Elevated levels of matrix metalloproteinases in bronchoalveolar lavage fluid of emphysematous patients Thorax 1997 52 502 506 9227714
Segura-Valdez L Pardo A Gaxiola M Uhal BD Becerril C Selman M Upregulation of gelatinases A and B, collagenases 1 and 2, and increased parenchymal cell deth in COPD Chest 2000 117 684 694 10712992 10.1378/chest.117.3.684
Laan M Cui ZH Hoshino H Lötvall J Sjöstrand M Gruenert DC Skoogh BE Lindén A Neutrophil recruitment by human IL-17 via C-X-C chemokines release in airways J Immunol 1999 162 4 2347 52 9973514
Miyamoto M Prause O Laan M Sjöstrand M Lötvall J Lindén A Endogenous IL-17 mediates endotoxin-induced airway neutrophilia in mice in vivo J Immunol 2003 170 4665 72 12707345
Hoshino H Laan M Sjöstrand M Lötvall J Skoogh BE Lindén A Increased elastase and myeloperoxidase activity associated with neutrophil recruitment by IL-17 in airways in vivo J Allergy Clin Immunol 2000 105 143 149 10629464 10.1016/S0091-6749(00)90189-1
Prause O Bozhinovski S Anderson GP Lindén A Increased matrix metalloproteinase-9 concentration and activity after stimulation with Interleukin-17 in mouse airways Thorax 2004 59 4 313 7 15047951 10.1136/thx.2003.008854
Laan M Palmberg L Larsson K Lindén A Free, soluble interleukin-17 protein during severe inflammation in human airways Eur Respir J 2002 19 534 537 11936535 10.1183/09031936.02.00280902
Muller-Suur C Larsson K Malmberg P Larsson PH Increased number of activated lymphocytes in human lung following swine dust inhalation Eur Respir J 1997 10 376 380 9042635 10.1183/09031936.97.10020376
Wang Z Larsson K Palmberg L Malmberg P Larsson P Larsson L Inhalation of swine dust induces cytokine release in the upper and lower airways Eur Respir J 1997 10 381 387 9042636 10.1183/09031936.97.10020381
Larsson BM Palmberg L Malmberg PO Larsson K Effect of exposure to swine dust on levels of IL-8 in airway lavage fluid Thorax 1997 52 638 642 9246137
Statement of the American Thoracic Society Standardization of spirometry – 1987 update Am Rev Respir Dis 1987 136 1285 1298 3674589
Hedenstrom H Malmberg P Agarwal K Reference values for lung function tests in females. Regression equations with smoking variables Bull Eur Physiopathol Respir 1985 21 551 557 4074961
Hedenstrom H Malmberg P Fridriksson HV Reference values for lung function tests in men. Regression equations with smoking variables Ups J Med Sci 1986 91 299 310 3811032
Malmberg P Larsson K Thunberg S Increased lung deposition and biological effect of methacholine by use of a drying device for bronchial provocation tests Eur Respir J 1991 4 890 898 1955011
Xu SY Petersson CG Carlson M Venge P The development of an assay for human neutrophil lipocalin (HNL) – to be used as a specificmarker of neutrophil activity in vivo and vitro J Immunol Methods 1994 171 245 252 8195592 10.1016/0022-1759(94)90044-2
Fossiez F Banchereau J Murray R Van Kooten C Garrone P Lebecque S Interleukin-17 Int Rev Immunol 1998 16 541 551 9646176
Yao Z Painter SL Fanslow WC Human IL-17: a novel cytokine derived from T cells J Immunol 1995 155 5483 5486 7499828
Spriggs MK Interleukin-17 and its receptor J Clin Immunol 1997 17 366 369 9327335 10.1023/A:1027360106635
Shin N Benbernou N Esnault S Guenounou M Expression of IL-17 in human memory CD45RO+ T lymphocytes and its regulation by protein kinase A pathway Cytokine 1999 11 257 266 10328864 10.1006/cyto.1998.0433
Ferretti S Bonneau O Dubois GR Jones CE Trifilieff A IL-17, produced by lymphocytes and neutrophils, is necessary for lipopolysaccharide-induced airway neutrophilia: IL-15 as a possible trigger J Immunol 2003 170 2106 2112 12574382
Happel KI Zheng M Young E Quinton LJ Lockhart E Ramsay AJ Shellito JE Schurr JR Bagby GJ Nelson S Kolls JK Cutting edge: roles of Toll-like receptor 4 and IL-23 in IL-17 expression in response to Klebsiella pneumoniae infection J Immunol 2003 170 4432 4436 12707317
Eijnden SV Goriely S De Wit D Willems F Goldman M IL-23 up-regulates IL-10 and induces IL-17 synthesis by polyclonally activated naive T cells in human Eur J Immunol 2005 35 2 469 75 15682457 10.1002/eji.200425677
Welgus HG Campbell EJ Cury JD Eisen AZ Senior RM Wilhelm SM Goldberg GI Neutral metalloproteinases produced by human mononuclear phagocytes. Enzyme profile, regulation and expression during cellular development J Clin Invest 1990 86 1496 1502 2173721
Sevéus L Amin K Peterson CGB Roomans GM Venge P Human neutrophil lipocain (HNL) is a specific granule constituent of the neutrophil granulocyte. Studies in bronchial and lung parenchimal tissue and peripheral blood Histochem Cell Biol 1997 107 423 432 9208334 10.1007/s004180050129
Larsson K Muller-Suur C Sandström T Sundblad B-M Larsson B-M Palmberg L Sodium cromoglycate attenuates pulmonary inflammation without influencing bronchial responsiveness in healthy subjects exposed to organic dust Clin Exp Allergy 2001 31 1356 1368 11591185 10.1046/j.1365-2222.2001.01193.x
| 15916703 | PMC1166577 | CC BY | 2021-01-04 16:23:26 | no | Respir Res. 2005 May 25; 6(1):44 | utf-8 | Respir Res | 2,005 | 10.1186/1465-9921-6-44 | oa_comm |
==== Front
Theor Biol Med ModelTheoretical Biology & Medical Modelling1742-4682BioMed Central London 1742-4682-2-201592705510.1186/1742-4682-2-20ResearchPromoter addresses: revelations from oligonucleotide profiling applied to the Escherichia coli genome Sivaraman Karthikeyan [email protected] Aswin Sai Narain [email protected] Krishnakumar [email protected] Geetha [email protected] Gautam [email protected] Centre for Biotechnology, Anna University, Chennai, India2 AU-KBC for Research, MIT Campus, Anna University, Chennai, India2005 31 5 2005 2 20 20 19 4 2005 31 5 2005 Copyright © 2005 Sivaraman et al; licensee BioMed Central Ltd.2005Sivaraman et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Transcription is the first step in cellular information processing. It is regulated by cis-acting elements such as promoters and operators in the DNA, and trans-acting elements such as transcription factors and sigma factors. Identification of cis-acting regulatory elements on a genomic scale requires computational analysis.
Results
We have used oligonucleotide profiling to predict regulatory regions in a bacterial genome. The method has been applied to the Escherichia coli K12 genome and the results analyzed. The information content of the putative regulatory oligonucleotides so predicted is validated through intra-genomic analyses, correlations with experimental data and inter-genome comparisons. Based on the results we have proposed a model for the bacterial promoter. The results show that the method is capable of identifying, in the E.coli genome, cis-acting elements such as TATAAT (sigma70 binding site), CCCTAT (1 base relative of sigma32 binding site), CTATNN (LexA binding site), AGGA-containing hexanucleotides (Shine Dalgarno consensus) and CTAG-containing hexanucleotides (core binding sites for Trp and Met repressors).
Conclusion
The method adopted is simple yet effective in predicting upstream regulatory elements in bacteria. It does not need any prior experimental data except the sequence itself. This method should be applicable to most known genomes. Profiling, as applied to the E.coli genome, picks up known cis-acting and regulatory elements. Based on the profile results, we propose a model for the bacterial promoter that is extensible even to eukaryotes. The model is that the core promoter lies within a plateau of bent AT-rich DNA. This bent DNA acts as a homing segment for the sigma factor to recognize the promoter. The model thus suggests an important role for local landscapes in prokaryotic and eukaryotic gene regulation.
==== Body
Introduction
Transcription, the first step of information flow from DNA, is regulated by sequence specific DNA-protein interactions. The regulation depends on the presence of cis-acting elements. The best examples of cis-acting elements are promoters. Other well-known examples in bacteria include the Shine Dalgarno (SD) sequence, sigma 32 binding site, LexA binding site, etc.
In bacteria, promoters recognized by sigma factors initiate transcription. The responses of an organism to various stimuli are mediated by changes in gene expression patterns. These changes are initiated by promoter-sigma factor interactions and regulated by other cis-acting elements. Thus, families of co-regulated genes are under the control of the same promoter. Though core promoters are small words (6–8 bases), certain changes that are permissible in promoter sequences have little or no effect on their activity. This means that a few closely-related sequences, in the right context, can function as promoters. Identifying promoters is a challenging yet rewarding problem; challenging because promoters can differ subtly in sequence and still retain function, and rewarding because it can shed light on an organism's life style. Computational approaches are required since experimental methods for identifying promoters are not applicable on a genome-wide scale.
In most instances, computational identification or prediction of promoters involves model-based searches. The model is, by and large, derived from prior data. Techniques using artificial neural networks [1] or genetic programming methodologies [2] are also used, and require prior experimental data. Using prior data for identifying new candidates is also known as dictionary-based searching. Databases of experimentally verified cis-acting elements are available for promoter prediction [3] through dictionary-based approaches. These approaches are biased towards the best-characterized promoter in the initial dataset, though non-redundant data sets have been used recently [4]. A paucity of experimental data can compromise the efficiency of these methods. The success of dictionary-based methods is directly dependent on the relatedness of the database to the query. It has also been observed that, while using dictionary-based methods, taking into account the local genomic landscape for generating Markov profiles improved the prediction quality in eukaryotes [5]. Another method that has been applied to both simpler and larger genomes is the comparative genome analysis method. It is observed that functional regions, albeit non-coding, are conserved across species and genera. Analyses of this kind have been used for yeast [6,7], higher eukaryotes [8,7] and bacterial regulons [9,7].
In Saccharomyces cerevisiae, the distribution of certain words across the genome is non-random. For example, some words appear to be preferred in regions upstream [10] or downstream [11] of genes. Analyses showed that such words occurring preferentially near the genes represent functional elements. Though non-random usage of k-sized words in bacterial genomes has been documented [12,13] in genomic contigs, studies have not focused on the upstream regions of prokaryotic genes.
We have developed a method that uses preferential occurrence of k-sized words within specific (gene-proximal) regions in a given genome to predict cis-acting elements. This method does not use a dictionary or database for initiating searches. The method can be applied to any genome of which the gene co-ordinates are known. Its advantage is that there is no extrapolation of data. This allows unique families of cis-acting elements for a given genome to be determined. Inter-genome comparison can establish the functionality of conserved words across genera.
The results of oligonucleotide profiling as applied to the genome of E.coli K12 [14] are presented. Comparative analyses of the resultant oligonucleotide profiles show that a subset of preferred hexanucleotides in E.coli-K12 is conserved across two other genomes, those of Salmonella typhi and Yersinia pestis [15,16]. We suggest a function for the ubiquitous hexanucleotides that are preferentially present in -100 regions and are neither single-base relatives of TATAAT or AGGA nor CTAG-containing, and we propose a novel model for bacterial promoters.
Results and Discussion
The results of oligonucleotide profiling, as performed for E.coli K12 genome, are discussed. The word size was restricted to six. For higher word sizes the word occurrence frequency was low. Smaller words were not used since the intra-word Markov dependencies, if any, are statistically invalid [17].
Word occurrences were analyzed in four contiguous sequence sets, F4 through F1 (Fig. 1a),. A threshold of 200% (two-fold increase in occurrence over the genomic average) was set to identify signals for cis-acting elements. The average occurrence of a random hexanucleotide in a sequence set is 4.6% of its genomic total and the standard deviation is 0.573. It can be seen that a two-fold increase (9.2%) is more than six times the standard deviation (σ) above the average. Any hexanucleotide that had at least 9.2% of its overall genomic occurrence within any of the four fragments analyzed was termed "enriched" in that respective region. Such enrichment was more pronounced in the gene-proximal regions (-1 to -100 region) than in the distal regions (-300 to -400). In the three random sequence sets (controls), only once did we find enrichment (a CTAG-containing element). Fig. 1a schematically illustrates this procedure.
Figure 1 (A) A schematic representation of the procedure used for profiling, incorporating the definition of the four fragments F1, F2, F3 and F4 used in this study. (B) Comparison of the occurrence distribution in the random control (series 1), F4 (series 2), F3 (series 3), F2 (series 2) and F1 (series 4). (C) Number of words whose occurrence is greater than μ+Nσ, where N is on the x axis. (D) Distribution of the three classes of oligonucleotides in the four fragments: TATAAT for class 1, AGGAGG for class 2 and AAAAAA for class 3.
The preferential occurrences of hexanucleotides within the controls and the fragments under study are contrasted in Table 1. The distributions of hexanucleotide occurrence in control 1 and fragments (F1-F4) are shown in Fig. 1b, while Fig. 1c shows the number of hexanucleotides with frequencies N × (σ) more than average. The units on the X-axis are N (N times σ) and 200%.
Table 1 Threshold(C)/Region(R) %>μ+2 %>μ+3 %>μ+4 %>200
σ σ σ %
Control1 184 42 18 1
Control2 155 30 9 0
Control3 164 46 16 0
F1 229 66 24 7
F2 341 116 44 0
F3 662 387 236 14
F4 1112 834 634 190
The method retrieved 183 hexanucleotides that were enriched in the -100 region. These included the Pribnow box (TATAAT), SD consensus (AGGA), the LexA binding site (CTATNN), sigma 32 binding site one-base relative (CCCTAT) and CTAG-containing regulatory elements [Supplementary Information 1].
The CTAG-containing elements are known to be core repressor binding regions in the Trp, Met and MalPQ operons and the treA gene [18-20]. They occur at high frequency near the rRNA gene clusters [12]. However, in the rest of the genome, we find their distribution to be roughly uniform (data not shown).
Certain trends are apparent in the usage of enriched oligonucleotides by bacterial genomes. The occurrence of some oligonucleotides increases gradually with proximity to genes (class I oligonucleotides), while others (class II oligonucleotides) peak near the genes. A third class comprises non-specifically preferred oligonucleotides (Class III oligonucleotides).
Class I Oligonucleotide
Bacteria are expected to have limited number of promoter elements and to have them near genes. The Pribnow box in E.coli is a representative promoter. The overall frequency of the Pribnow box is lower than the genomic average (1067 occurrences as against the genomic average of ~1400). Here, we analyze: the occurrence of the Pribnow box and its single base substitution relatives, the distribution of the Pribnow box within the -100 region, and the position-dependency of other bases on the Pribnow box in its vicinity. For this analysis, Pribnow box occurrences in the -100 region alone were taken into account for four strains of E.coli.
Occurrence of Pribnow box
This analysis shows that the occurrence of the Pribnow box increases gradually as one goes closer to genes. Furthermore, seven of its one-base substitution relatives figure in the enriched list [Table 2]. Most of these one-base relatives show a gradual but definite increase in their occurrence as we move nearer the genes [Table 2]. This gives an idea as to how an element that has a function similar to the Pribnow box would behave in other genomes.
Table 2 Occurrence of single base relatives of TATAAT in E.coli genome. F1:-301 to -400; F2:-201 to -300; F3: -101 to -200; F4: -1 to -100. Those elements that are enriched (> = 200%) are marked by an asterisk in the last column.
Hex Total Occ. F4 F3 F2 F1 Occ. % in F1 ENR
TCTAAT 595 29 30 47 46 7.731092
TAGAAT 507 25 23 36 71 14.00394 *
TATAGT 681 19 38 30 87 12.77533 *
TATAAG 879 45 32 67 102 11.6041 *
TACAAT 903 42 56 71 109 12.07087 *
TATAAC 1590 65 80 94 121 7.610063
TATGAT 1539 63 111 94 127 8.252112
TATACT 620 39 40 62 131 21.12903 *
CATAAT 2448 90 106 115 132 5.392157
TATAAT 1036 58 68 78 134 12.93436 *
TGTAAT 1870 74 80 129 140 7.486631
TATCAT 2082 101 96 128 164 7.877041
TATATT 1943 87 130 145 168 8.646423
TATTAT 2280 118 124 155 178 7.807018
GATAAT 3735 125 140 172 201 5.381526
TATAAA 2304 98 144 177 236 10.24306 *
TTTAAT 3671 182 205 219 249 6.782893
TAAAAT 2947 142 159 204 268 9.093994
AATAAT 4132 188 201 287 287 6.945789
Distribution of Pribnow box
Analyses show that the maximal number of strong minimal promoters occur within the -100 region and that the Pribnow box prefers the -30 to -70 position, centering around -40 [Fig. 2a]. The report by Collado-Vides et al. shows that ~80% of the 800 genes analyzed have their promoters in the -100 region. In fact, the highest concentration of promoters that they report is at the -40 region [21], which we corroborate.
Figure 2 Addressed promoter model. (A) Occurrence distribution of TATAAT, AGGAGG and AAAAAA within the -100 region using a 30-base window: -1 to -30, -10 to -40, -20 to -50, ..., -70 to -100. (B) A schematic comparison of the classical and the addressed promoter models. Blue peaks represent the canonical promoter. Red background (where present) represents the address.
Markov dependency analysis of sequences surrounding Pribnow box
Markovian analysis of TATAAT-containing sequences (within the -100 region) was done for E.coli. For analysis, such sequences were taken from all four E.coli genomes (K12, O157:H7, EDL933 and CFT073) to improve statistical significance (TATAAT occurred only 128 times in the -100 region of the K12 genome). The results showed that TTGACA is preferred between positions -32 and -27. Further, it was seen that, with G at -14, the occurrence of TTGACA decreased, (All corresponding data points are highlighted in the Supplementary Information 2 file.) This has been reported by analysis of experimentally characterized promoters [22]. These correlations validate the results of oligonucleotide profiling with respect to the sigma 70 binding site.
Class II Oligonucleotides
AGGA- (SD consensus) and CTAG-containing hexanucleotides belong to this class. Unlike the Class I oligonucleotides, Class II oligonucleotides show a steep increase in occurrence in the -100 region. This is expected in the case of the Shine-Dalgarno sequence (AGGA), since it should lie within 30 base pairs upstream of the ORF start site (owing to geometric constraints imposed by the ribosomal complex).
Another example of this class is the tetranucleotide CTAG, representing all the hexanucleotides that contain it. CTAG kinks DNA when bound by proteins [23], making it a likely candidate for a regulatory site. CTAG also has low genomic frequency, uniform distribution and a preference for the -100 region. This might imply a global regulatory function.
Class III Oligonucleotides
Certain oligonucleotides not only have a more than average genomic frequency but are also more common in the -100 region. Many of these are A/T rich oligonucleotides, which are known to bend DNA when present in stretches [24]. The presence of such A/T repeat elements upstream [25] and downstream [26] of the canonical promoter is necessary. They are evidently not stand-alone signals. We propose that they are facilitator elements that are necessary but not sufficient for promoter recognition and function. The set of such oligonucleotides that were readily distinguished as facilitators is given, along with their distribution, in Supplementary Information 3. They occur preferentially up to -100 and beyond. We find this significant since a recent report shows that DNA of size 90 base pairs can bend upon itself in a sequence-dependent manner [24].
Though all 64 A/T containing hexanucleotides were found to occur more frequently than the genomic average, only 18 of them were enriched in the -100 region. Thus, the increased occurrence of Class III hexanucleotides is not an artifact of increased base frequency. It transpires that the genome increases the bending capacity of the -100 region by preferential usage of certain oligonucleotides.
The occurrence of hexanucleotides representing each of the three classes is shown in Fig. 1d. TATAAT is used to represent class I, AGGA-containing hexanucleotides to represent class II and AAAAAA to represent class III.
Protein Binding Capacity of the -100 region: Evidence from NDB
We analyzed the occurrence of enriched hexanucleotides in a protein-bound state in the NDB database [27]. Of the ~130 hexanucleotides that are neither TATAAT-related (1 base substitution oligonucleotides) nor AGGA- or CTAG-containing, 112 have at least one occurrence in the database, bound to proteins [data not shown]. Most of them occurred more than once in the database in a protein-bound state. These results show the propensity of the genome to increase the protein-interacting capacity of the -100 region and hence increase the activity of this region.
Dependency Analysis
A position-specific probability matrix (PSPM) was created for enriched oligonucleotides that were not TATAAT related or AGGA/CTAG-containing. This matrix was used to determine the tendency of hexanucleotides to assume specific consensus words within the -100 region of the genes. Secondary matrices were derived by anchoring the first base in the PSPM. The consensus words derived from these matrices are given in Supplementary Information 4. For each secondary matrix, two more character states were chosen for anchoring on the basis of their prominence,. The results show a strong preference for tetra-A signals, TATA-containing signals and GGA-containing signals.
Inter-genome comparison of hexanucleotide usage profiles
Conservation of DNA sequence across genomes has been established as a pointer to functionality. This method has been used to identify regulatory regions in Saccharomyces [6] by sequence comparison among different species. We see that the logic extends beyond conservation of sequences and patterns to that of oligonucleotide profiles.
We have compared the profile of enriched hexanucleotides between E.coli, Salmonella enterica and Yersinia pestis to test its validity. The E.coli and Salmonella profiles shared 110 enriched oligonucleotides out of 160 in Salmonella typhi. Yersinia pestis, whose profile had 97 enriched oligonucleotides, shared 66 of them with E.coli. Of those that were conserved across genomes, the AGGA-containing and CTAG-containing hexanucleotides, TATAAT, and the LexA binding site were prominent (Supplementary Information 5).
While conservation of hexanucleotides usage implies functionality, the converse may not be true and might reflect unique regulatory / facilitator elements for each genome.
Role of facilitator elements in promoter identification and the Addressed Promoter Model
Classical promoters in bacteria are sigma factor binding sites. The sequence that is known to bind to sigma factor with maximal affinity in vitro is taken to be the strongest promoter. DNA footprinting experiments do not allow us to assess the importance of the surrounding sequences.
It is clear from the profiles that the strongest promoters have limited occurrence in the genome. Most genes are controlled by sigma 70 in E.coli [28], and only ~12% of the overall strong consensus occur in a region where they are maximally effective [21]. The question to be addressed is how a sigma factor (Sigma 70 in this case) can distinguish the promoter from non-specific promoter-like signals (degenerate -10 and -35 like signals in non-functional places in the genome). The sigma factor could not read every one of the possible signal combinations since this would result in enormous loss of time in bacterial genomes. In larger genomes, given the small size and degeneracy of the promoters, it is possible that the sigma factor would recognize a false signal on most occasions.
To account for the efficiency of promoter recognition in the organism, we propose the addressed promoter model, where the sigma factor binding element is an information-dense peak (specific information) within a plateau of moderate information density (different but related words). The peak and the plateau together constitute the promoter. The plateau is formed by class III oligonucleotides that have the capacity to bend DNA. The facilitators are an integral part of the promoter. The presence of facilitators, which occur in greater frequencies around the core promoter, will serve as addresses for the core promoter. These addresses act as homing segments that allow the transcription factor to recognize the core promoter and bind to it.
This model immediately suggests a way of identifying cis-acting regions in eukaryotes, where greater genome sizes and more degeneracy are seen. The extension of this logic would be to view enhancers and other regulatory regions in large eukaryotic genomes as local landscapes rather than as sequence motifs. While the protein binding sites would still be sequence motifs, their occurrence in a particular landscape may prove to be the determining factor for their activity. This accords with the observation of Huang et. al. [5] that local genomic landscape information affects the prediction quality of promoter elements.
To illustrate this model, we have analyzed the distribution of one representative element from each of the three classes. The distribution was studied in a 30-base sliding window with a 10-base pitch. The representative elements are TATAAT (Class I), AGGAGG (Class II) and AAAAAA (Class III). The distribution is shown in Fig. 2a. It can be seen that AAAAAA forms a plateau around the TATAAT peak. The classical model and the addressed promoter model are contrasted in Fig. 2b.
Conclusion
This method for identifying regulatory regions in DNA is powerful. Its strength is its ability to use the genomic sequence as a control. This obviates the need for data extrapolation from related genomes. The method can identify functional elements that can be experimentally characterized.
Application of this method to the E.coli K12 genome reveals the presence of at least three classes of cis-acting elements. The occurrence, distribution and dependencies of these elements have been analyzed. Most of the profile data correlate with existing experimental evidence. The canonical sigma70 promoter has been analyzed in further detail in four E.coli genomes.
The information derived from E.coli K12 using this method suggests that the functionality of a promoter is determined not only by the sequence of the core promoter element but also by its local milieu. We note that the occurrence of proposed facilitator elements extends just beyond the length known for DNA to bend upon itself (90 bp) and this, together with other reports about AT-rich tracts in the vicinity of the canonical promoter, suggests that the sigma factor recognizes a promoter more efficiently if it is present in the "address" region. This immediately explains why the transcription process is efficient in spite of the degeneracy that the promoter exhibits. We see that the occurrence of facilitators is not an artifact of increased base frequencies.
The occurrence of many of the enriched hexanucleotides as protein-bound DNA complexes in the NDB database is indicative of their protein-interacting ability. This reflects on the protein binding capacity of the gene proximal regions in E.coli K12.
The limitation of this method is its inability to pick up rare regulatory elements. In small genomes the method is known to give false positives, and in degraded genomes it picks up false negatives. In such cases, comparative analysis with related genomes will give valuable information.
Methods
Sequence Extraction
Published genome sequences from the NCBI database (.fna file) were used. The start sites of genes given in the annotation file (.ptt file) were used for extracting upstream sequences of all the genes. Upstream sequences were taken only from their respective strands (+ strand for + genes and vice versa) because of the directionality of promoters. Four such fragments were taken from upstream of each gene, viz. -1 to -100, -101 to -200, -201 to -300 and -301 to -400. The distance between any two genes was not given importance because of the possibility that regulatory and transcriptional start sites may be present in the coding region of the preceding gene.
Profiling
For every gene in the E. coli K12 genome, four contiguous DNA fragments from the corresponding strand were extracted. The length of each fragment was 100 bases. The fragments were named F4 through F1, where F1 is the gene-proximal fragment. There are 4311 genes in E.coli. Four sequence sets, one each for F1, F2, F3 and F4, were created for all the genes. Each of these sequence sets covers approximately 4.6% of the genome.
Occurrence of all hexanucleotides was counted on both strands of the genome and the four upstream-sequence sets. The Compseq program from the EMBOSS [29] suite was used for this purpose. Any word that was non-functional was expected to be distributed equally across the sequence sets. Thus, for a non-functional word in the upstream context, we expected approximately 4.6% of its genomic occurrence in any of the sequence sets.
Since cis-acting elements are gene-proximal, we expected their occurrence to be higher in F1 than elsewhere. We set a threshold (T) of 200% in word frequency to identify signals. Given a standard deviation of 0.56, it is apparent that a 200% increase (9.2% of genomic occurrence) is more than 6σ, which is significant. Words whose frequency in a given sequence set was 9.2% or more were termed "enriched" in the corresponding fragment.
All analyses were carried out using Perl 5.6.1 scripts on a Mandrake Linux 9.1 platform. The complete dataset is available in an in-house MySql -based server.
Markov Dependency Analysis
We analyzed the character-state probabilities of all the words (137 words) for which a function could not be assigned. For this, we created a position-specific probability matrix (PSPM). The PSPM was derived from a position-specific frequency matrix (PSFM), which is defined as follows. For a word size of L, a PSFM is a 4 × L matrix M, where each element Mi,j [i ∈ {A,T,G,C} and j ∈ {1,2, ... L}] is the number of times the character state i occurs at position j. In this case, L = 6.
If S is the sum of all occurrences of words, then the PSPM is related to the PSFM as given below:
PSPM = (1/S) × PSFM
Such a matrix was used to derive consensus words preferred in the -100 region. From the PSPM, four sub-matrices were derived by anchoring the various character states (A, C, G, and T) at the first position. Further dependencies were analyzed by subsequent anchoring of two more positions, based on their prominence in the sub-PSPMs, to their representative character states.
Markov Analysis for TATAAT-dependent Signals
For each occurrence of the Pribnow box within the -100 region, the preceding 50-base region was extracted. The PSPM was created for the sequence set as described above, where the value of L is 50. Different profiles were created by anchoring the base profile at all positions with all four bases. This was used to analyze the dependency of upstream signals on TATAAT. This analysis was done on a sequence set collated from all the four strains of E.coli.
Authors' contributions
KS gave the core idea for oligonucleotide profiling, analysis of occurrence and proposed the model. ASNS worked with KS in profiling and analyzing the statistical significance of results, and KrS worked with KS in analyzing the distribution of words in gene proximal regions. GM was involved in analysis of results and critically analyzing the manuscript. PG is the group leader.
Acknowledgements
The authors would like to thank Ms. Anishetty for discussions, and to acknowledge the financial support given by Council for Scientific and Industrial Research, Government of India and Department of Biotechnology, Government of India through the BTIS programme. We also extend our thanks to the developers of EMBOSS for making it available free of cost. We wish to acknowledge the contribution of the Free Software Foundation, MySQL, PERL community and others for making valuable software available free.
==== Refs
Kalate RN Tambe SS Kulkarni BD Artificial Neural Networks for prediction of Mycobacterial promoter sequence Comp Biol Chem 2003 27 555 564 10.1016/j.compbiolchem.2003.09.004
Howard D Benson K Evolutionary computation method for prediction of cis-acting sites Biosystems 2003 72 19 27 14642656 10.1016/S0303-2647(03)00132-1
Bussemaker HJ Li H Siggia ED Building a Dictionary for genomes: Identification of presumptive regulatory sites by statistical analysis Proc Natl Acad Sci USA 2000 97 10096 10100 10944202 10.1073/pnas.180265397
Lenhard B Sandelin A Mendoza L Engström P Jareborg N Wasserman WW dentification of conserved regulatory elements by comparative genome analysis Journal of Biology 2003 2 1 13 10.1186/1475-4924-2-13
Huang H Kao MJ Zhou X Liu JS Wong WH Determination of local statistical significance of patterns in Markov sequences with application to promoter element identification J Comp Biol 2004 11 1 14 10.1089/106652704773416858
Kellis M Patterson N Endrizzi M Birren B Lander ES Sequencing and comparison of yeast species to identify genes and regulatory elements Nature 2003 423 241 254 12748633 10.1038/nature01644
McGuire MA Church GM Predicting regulons and their cis-regulatory motifs by comparative genomics Nucl Acids Res 2000 28 4523 4530 11071941 10.1093/nar/28.22.4523
Thomas JW Touchman JW Blakesley RW Bouffard GG Beckstrom-Sternberg SM Margulies EH Blanchette M Siepel AC Thomas PJ Mcdowell JC Maskeri B Hansen NF Schwartz MS Weber RJ Kent WJ Karolchik D Bruen TC Bevan R Cutler DJ Schwartz S Elnitski L Idol JR Prasad AB Lee-Lin S-Q Maduro VVB Summers TJ Portnoy ME Dietrich NL Akhter N Ayele K Benjamin B Cariaga K Brinkley CP Brooks SY Granite S Guan X Gupta J Haghighi P Ho S-L Huang MC Karlins E Laric PL Legaspi R Lim MJ Maduro QL Masiello CA Mastrian SD Mccloskey JC Pearson R Stantripop S Tiongson EE Tran JT surgeon CT Vogt JL Walker MA Wetherby KD Wiggins LS Young AC Zhang L-H Osoegawa K Zhu B Zhao B Shu CL DeJong PJ Lawrence CE Smit AF Chakravarti A Haussler D Green P Miller W Green ED Comparative analyses of multi-species sequences from targeted genomic regions Nature 2003 424 788 793 12917688 10.1038/nature01858
Tan K Moreno-Hagelsaib G Collado-Vides J Stormo GD A comparative genomics approach to prediction of new members of regulons Genome Res 2001 11 566 584 11282972 10.1101/gr.149301
van Helden J André B Collado-Vides J Extracting regulatory sites from the upstream region of yeast genes by computational analysis of oligonucleotide frequencies J Mol Biol 1998 281 827 842 9719638 10.1006/jmbi.1998.1947
van Helden J del Olmo M Perez-Ortin JE Statistical Analysis of yeast genomic downstream sequences reveals putative polyadenylation signals Nucl Acids Res 2000 28 1000 1010 10648794 10.1093/nar/28.4.1000
Burge C Campbell AM Karlin S Over-and under representation of short oligonucleotides in DNA sequences Proc Natl Acad Sci USA 1992 89 1358 1362 1741388
Karlin S Mrazek J Campbell AM Compositional Biases of Bacterial Genomes and Evolutionary Implications J Bacteriology 1997 179 3899 3913
Blattner FR Plunkett G IIIBloch CA Perna NT Burland V Riley M Collado-vides J Glasner JD Rode CK Mayhew GF Gregor J Davis NW Kirkpatrick HA Goeden MA Rose DJ Mau B Sao Y The complete genome sequence of Escherichia coli K-12 Science 1997 277 1453 1462 9278503 10.1126/science.277.5331.1453
Parkhill J Dougan G James KD Thomson NR Pickard D Wain J Churcher C Mungall KL Bentley SD Holden MTG Sebaihia M Baker S Basham D Brooks K Chillingworth T Connerton P Cronin A Davis P Davies RM Dowd L White N Farrar J Feltwell T Hamlin N Haque A Hien TT Holroyd S Jagels K Krogh A Larsen TS Leather S Moule S O'Gaora S Parry C Quail M Rutherford K Simmonds M Skelton J Stevens K Whitehead S Barrell BG Complete genome sequence of a multiple drug resistant Salmonella enterica serovar Typhi CT18 Nature 2001 413 848 852 11677608 10.1038/35101607
Parkhill J Wren BW Thomson NR Titball RW Holden MTG Prentice MB Sebaihia M James KD Churcher C Mungall KL Baker S Basham D Bentley SD Brooks K Cerde?O-T?Rraga AM Chillingworth T Cronin A Davies RM Davis P Dougan G Feltwell T Hamlin N Holroyd S Jagels K Karlyshev AV Leather S Moule S Oyston PCF MQuail M Rutherford K Simmonds M Skelton J Stevens K Whitehead S Barrell BG Genome sequence of Yersinia pestis, the causative agent of plague Nature 2001 413 523 527 11586360 10.1038/35097083
Leung MY Marsh GM Speed TP Over- and Underrepresentation of Short DNA Words in Herpesvirus Genomes J Comp Biol 1996 3 345 360
Zhang H Zhao D Revington M Lee W Jia X Arrowsmith C Jardetzky O The solution structures of trp repressor operator DNA complex J Mol Biol 1994 238 592 614 8176748 10.1006/jmbi.1994.1317
Somers WS Phillips SEV Crystal structure of the met repressor-operator complex at 2.8A resolution reveals dna recognition by beta-strands Nature 1992 359 387 393 1406951 10.1038/359387a0
Robison K McGuire AM Church GA Comprehensive library of DNA-binding site matrices for 55 proteins applied to the complete Escherichia coli K-12 genome J Mol Biol 1998 284 241 254 9813115 10.1006/jmbi.1998.2160
Heurta AM Collado-vides J Sigma70 promoters in Escherichia coli: specific transcription in dense regions of overlapping promoter-like signals J Mol Biol 2003 333 261 278 14529615 10.1016/j.jmb.2003.07.017
Burr T Mitchell J Kolb A Minchin S Busby S DNA sequence elements located immediately upstream of the -10 hexamer in Escherichia coli promoters: a systematic study Nucl Acids Res 2000 28 1864 1870 10756184 10.1093/nar/28.9.1864
Tereshko V Urpi L Malinina L Hyunh-Dinh Subirana JA Structure of the B-DNA Oligomers d(CGCTAGCG) and d(CGCTCTAGAGCG) in New Crystal Forms Biochemistry 1996 35 11589 11595 8794738 10.1021/bi961048l
Cloutier TE Widom J Spontaneous sharp bending of double stranded DNA Molecular Cell 2004 14 355 362 15125838 10.1016/S1097-2765(04)00210-2
Ozoline ON Deev AA Arkhipova MV Chasov VV Travers A Proximal transcribed regions of bacterial promoters have a non-random distribution of A/T tracts Nucl Acids Res 1999 27 4768 4774 10572177 10.1093/nar/27.24.4768
Estrem ST Gaal T Ross W Gourse RL Identification of an UP element consensus sequence for bacterial promoters Proc Natl Acad Sci USA 1998 95 9761 9766 9707549 10.1073/pnas.95.17.9761
Berman HM Olson WK Beveridge DL Westbrook J Gelbin A Demeny T Hsieh SH Srinivasan AR Schneider B The Nucleic Acid Database: A Comprehensive Relational Database of Three-Dimensional Structures of Nucleic Acids Biophys J 1992 63 751 759 1384741
Gruber TM Gross CA Multiple Sigma Subunits and the partitioning of the Bacterial transcription space Annu Rev Microbiol 2003 57 441 466 14527287 10.1146/annurev.micro.57.030502.090913
Rice P Longden I Bleasby A EMBOSS: The European Molecular Biology Software Suite Trends in Genetics 2000 16 276 277 10827456 10.1016/S0168-9525(00)02024-2
| 15927055 | PMC1166578 | CC BY | 2021-01-04 16:39:25 | no | Theor Biol Med Model. 2005 May 31; 2:20 | utf-8 | Theor Biol Med Model | 2,005 | 10.1186/1742-4682-2-20 | oa_comm |
==== Front
World J Surg OncolWorld Journal of Surgical Oncology1477-7819BioMed Central London 1477-7819-3-261589007510.1186/1477-7819-3-26ReviewThe immunogenicity of colorectal cancers with high-degree microsatellite instability Banerjea Ayan [email protected] Stephen A [email protected] Sina [email protected] Centre for Academic Surgery, Barts and the London Queen Mary School of Medicine and Dentistry, London, UK2005 12 5 2005 3 26 26 21 1 2005 12 5 2005 Copyright © 2005 Banerjea et al; licensee BioMed Central Ltd.2005Banerjea et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
High-degree microsatellite instability (MSI-H) is a feature of approximately 15% of sporadic colorectal cancers. Patients with MSI-H cancers have been reported to have a better prognosis than those with non-MSI-H cancers. The MSI-H subset is also characterised by a dense infiltrate of intra-epithelial lymphocytes and the hypothesis that the latter represents an efficacious immune response contributing to improved outcome is very attractive.
Methods
Data for this review were identified by searches of MEDLINE, PubMed, and cross references from relevant articles using the search terms 'microsatellite instability', 'colorectal cancer' and 'immunology', 'immune response' or 'immunogenicity'.
Results
A total of 38 articles were identified by the search criteria and a further 95 articles by cross-referencing. The relevance of the articles to be interviewed was established by hand searching. Out of a total of 133 articles identified, 47 articles were rejected due to lack of relevance. A total of 86 articles were included in the review, pertaining to microsatellite instability in colorectal cancer, and immune mechanisms in colorectal cancer.
Conclusion
It is suggested that this distinct group of colorectal cancers may have inherent immunogenic properties and that further elucidation of these may be invaluable to the development of successful immunotherapy.
==== Body
Background
Colorectal cancer remains a leading cause of cancer-related mortality and morbidity in the Western world. In the UK it is the third commonest cancer, after lung and breast, with more than 35,000 new cases diagnosed each year and the second commonest cause of cancer-related mortality with approximately 16,000 deaths per year (CancerStats: Large Bowel – UK, Cancer Research UK 2003, [1]). Complete surgical resection is the cornerstone of curative treatment. Other treatment modalities, such as chemotherapy and radiotherapy, administered before or after surgery, are used to counteract disease progression particularly in Stage III and IV disease [2,3]. Despite continuing technical advances in the use of these techniques the improvement in overall five-year survival rate has been limited (5–6%). This fact, along with the high proportion of patients who present with tumours not amenable to surgery, drives the search for additional modalities of anti-cancer treatment. Immunotherapy, the use of the adoptive immune system to target cancer cells, holds much promise in this regard.
The concept of immune surveillance, whereby the host immune system detects and removes cancerous cells, arose from the observation that immunodeficiency predisposes to the development of malignancies. Furthermore, it has been proposed that rare reports of solid tumour regression are the result of an anti-tumour immune response. Early work suggested that such anti-tumour responses were impotent against colorectal cancer [4-6]. However, evidence that colorectal malignancies may generate tumour specific antigens (TSA's) has encouraged considerable efforts to develop means of harnessing the host immune system to combat colorectal cancer. The use of immunotherapeutic approaches in colorectal cancer has evolved substantially (not reviewed here) and now focuses on the use of tumour specific antigens. This involves either passive immune therapy with antibodies targeted directly to tumour cells or by active immune therapy via vaccination with tumour cells, tumour cell lysates, peptides, carbohydrates, gene constructs encoding proteins, or anti-idiotypic antibodies that mimic TSA's. Despite some successes these techniques are still in their infancy and many hurdles remain, largely because our understanding of the biology of host-tumour interactions in colorectal cancer remains elementary.
In the last ten years a distinct subset of colorectal cancer, with characteristics of widespread microsatellite instability, has emerged as a group in which immune responses may be pronounced. Clearly, if this type of colorectal cancer does indeed have particular immunogenic features, its study should provide vital advances in our understanding of colorectal tumour immunology. Here we review the literature in relation to putative immune responses in colorectal cancers with microsatellite instability.
Microsatellite instability (MSI)
It is now clear that colorectal cancers may arise by a number of distinct molecular pathways. The "classical pathway" characterised by chromosomal instability (CSI) and a series of genetic events that drives the progression from normal colon through adenomatous polyp to invasive cancer accounts for 50–60% of cancers [7]. However, this is but one of many alternate pathways and one of these, involving mismatch repair dysfunction, leads to colorectal cancer characterised by microsatellite instability. High-degree microsatellite instability (MSI-H) is a feature of most colorectal cancers arising as part of the hereditary non-polyposis colorectal cancer (HNPCC) syndrome and also 15–20% of sporadic colorectal cancers [8].
Microsatellites are short segments of repetitive DNA bases found throughout the genome but mainly located in intronic (non-coding) segments. Due to their repetitive nature they are prone to insertion and deletion mutations during DNA replication, which commonly introduces such errors at a rate of 1 in 100,000 base pairs copied. The majority (99%) of these errors are detected and corrected by the inherent proof reading capabilities of DNA polymerase enzymes. A small proportion of mismatches that are missed by this mechanism are normally identified and corrected by a group of proteins collectively termed the mismatch repair (MMR) system [9]. Dysfunction of the MMR system allows the accumulation of replication errors and leads to microsatellite instability [10], defined as "a change of any length due to either insertion or deletion mutations of repeating units in a microsatellite" [11].
Mismatch repair dysfunction
The molecular mechanisms that underlie MMR dysfunction are different in familial and sporadic colorectal cancers. In HNPCC colorectal cancers a germline mutation within an individual mismatch repair gene is inherited and a subsequent "second hit" [Knudson's 'two-hit' hypothesis [12]] in the normal allele leads to mismatch repair deficiency. The commonly affected genes are hMLH1, hMSH2 and to a lesser extent PMS2, and their involvement predicts the development of extensive microsatellite instability [13]. By contrast, cancer cells with isolated mutations in hMSH3 and hMSH6 continue to maintain some mismatch repair function [14-16].
In sporadic MSI colorectal cancers genetic alterations in MMR genes are relatively rare. Instead epigenetic modulation of MMR genes, particularly hMLH1, such as hypermethylation of the promoter region leads to silencing and MMR deficiency [17,18]. Hypermethylation is characteristic of a subset of colorectal cancers designated the CpG island methylator phenotype (CIMP+) that is relatively common in right sided tumours [19]. Sporadic MSI-H colorectal cancer appears to represent a subset of the methylator phenotype in which global hypermethylation silences MMR genes. These cancers have biological properties quite distinct from that of HNPCC tumours, in which MMR dysfunction is the sole abnormality, whereas widespread changes in methylation targets the expression of numerous other genes not involved in the MMR pathway [20].
All colorectal cancers display some degree of microsatellite instability if enough markers are studied [21]. In 1997 an International Collaborative Group laid down guidelines for the identification and assessment of microsatellite instability [22]. They classified tumours into microsatellite stable (MSS) and two groups of microsatellite unstable cancers, discriminated by their degree of instability: high (MSI-H) or low (MSI-L). Two mononucleotide microsatellite markers (BAT-25 and BAT-26) and three dinucleotide markers (D2S123, D5S346 and D17S250) were chosen as a panel to be studied for assignation of MSI status. Tumours displaying instability in two or more markers were designated MSI-H, instability in only one marker was designated MSI-L and if no markers were affected the tumour was designated MSS. There is now a growing consensus that the MSI-H clinico-pathological phenotype is characterised particularly by instability in the mononucleotide markers [21]. Colorectal cancers with MSI-H clearly demonstrate distinct biological behaviour whereas MSI-L cancers are less well characterised and are often grouped with cancers that show no instability (MSS) [23]. The focus of this review is the clinico-pathological phenotype characteristic of sporadic MSI-H colorectal cancer.
MSI-H colorectal cancer
Sporadic MSI cancers do not harbour some of the characteristic features or gene mutations associated with CSI cancers, such as aneuploidy and p53 mutation. A number of human genes implicated in pathways regulating growth control and apoptosis, for example IGF-IIR, TGFβ-RII and BAX, contain microsatellite repeats within the coding regions of their transcribed sequences. More recently the BRAF gene has been noted to be commonly mutated in sporadic MSI-H, as well as in serrated polyps, suggesting that serrated polyps are likely precursors of these cancers [20]. It has been suggested that instability of such sequences plays a role in the progression of disease, presumably by altering gene activity [8,24]. Altered regulation of all or some of these genes may be involved in cancer development but precise mechanisms are yet to be identified.
Colorectal cancers with MSI-H also have distinct clinico-pathological characteristics. Sporadic MSI-H tumours are associated with the right side of the colon and display marked lymphocyte infiltration into tumour epithelium, stroma, peri-tumoral cuffs and Crohn's type reactions [25]. Sporadic MSI-H colorectal cancers have also specifically been associated with medullary-type poor differentiation, high mucin content and reduced lymph node involvement [20,25].
MSI-H and improved survival
Early reports on microsatellite instability noted an association of MSI with improved patient survival [26,27]. Some small studies have failed to reproduce this finding [28-30] but generally the association of MSI-H with improved survival in sporadic cancers has been confirmed in larger studies [31-33]. Many further studies have followed that confirm improved prognosis for patients with sporadic MSI-H colorectal cancer, particularly in lymph node positive cancers, and the link to improved survival has now been confirmed in a systematic review [34].
One explanation offered for the improved survival of MSI-H colorectal cancer patients has been that these cancers may be more sensitive to adjuvant chemotherapy. Indeed early retrospective analyses suggested that cancers with high-degree microsatellite instability had improved response to 5-Fluorouracil (5FU)-based adjuvant chemotherapy [35-37]. However, these data were retrospectively derived from non-randomised groups and the effects of small numbers, younger age of patients receiving chemotherapy, and different responses of right and left-sided tumours might have confounded the findings. In contrast, two studies have reporting retrospective data derived from randomised control trials of chemotherapy conclude that 5-FU regimes confer no benefit in sporadic MSI-H colorectal cancers and may even be detrimental [38,39]. There is clearly a need for robust prospective randomised controlled trials to evaluate the effects of 5-FU, and other agents, on survival with respect to MSI status.
An alternative explanation for the improvement in patient survival is one of enhanced host immune response. An immunohistochemical study noted that the improved survival of patients with MSI-H was associated with the higher frequency of activated tumour infiltrating lymphocytes in these cancers [40]. Consequently, it has been suggested that these lymphocytes may actually represent a host immune response that contributes to improved survival and subsequent work has confirmed a possible link [41]. The hypothesis that colorectal cancers with MSI-H are more immunogenic than microsatellite stable cancers is very attractive, as study of these cancers may provide crucial insights into colorectal cancer immunology. The further elucidation of immune responses to colorectal cancer in vivo is crucial to the continuing development of immunotherapy.
MSI-H and tumour immunogenicity
Current concepts in solid tumour immunology identify certain features that are fundamental to the stimulation of an anti-tumour response [Reviewed in [42]]. Successful immune response requires a cancer to possess antigens that can be recognised as non-self during immune surveillance. In MSI-H colorectal cancer the accumulation of errors in microsatellites, that reside in gene exons, leads to the generation of a large number of abnormal peptides due to frameshift mutations: the so-called "mutator phenotype" [43]. Clearly, such an array of abnormal peptides might represent a pool of TSA's that render MSI-H tumours inherently more detectable by the host immune system.
Studies on abnormal peptides characteristic of MSI-H have demonstrated their potential for immune recognition. A peptide generated by frameshift mutations in TGFβRII, characteristic of the mutator phenotype, has been used to pulse dendritic cells, which in turn induced activated cytotoxic (CD8+) T cells [44]. One cytotoxic T cell clone demonstrated specific anti-tumour activity against a cell line expressing this peptide in in vitro conditions. The same group have also identified MHC class-II restricted epitopes by induction of helper (CD4+) T cells from the peripheral blood mononuclear cells of normal volunteers and MSI-H colorectal cancer patients [45]. They also demonstrated that tumour infiltrating lymphocytes derived from an HNPCC MSI-H cancer recognised this frameshift-mutation-derived peptide but unusually the infiltrate in this tumour was predominantly CD4+ T cells. More recently, another group have identified several other frameshift-mutation-derived peptides as potential tumour specific antigens (TSA's) by using SEREX (serological analysis of recombinant cDNA expression cloning) [46]. They also detected IgG antibodies specific to these peptides only in the MSI-H cancer patients. In an HNPCC patient they demonstrated an antibody specific to a mutated CDX2 peptide that was found in the tumour tissue of the patient and this antibody was not seen in any of the other patients. Interestingly, the antibody disappeared seven years after curative resection. These observations lend significant support to the notion that MSI-H TSA's are effectively recognised by the host immune response and an immune response is induced, but more work is needed to confirm that findings in HNPCC patients are mirrored in sporadic MSI-H cancers.
Tumour specific antigens must be appropriately presented to the host immune system if a specific immune response is to occur. This normally requires the presentation of antigen in conjunction with the appropriate Major Histocompatibility Complex (MHC) molecules that interact with the T cell receptor (TCR): Class I MHC for presentation to cytotoxic (CD8+) T cells and Class II MHC for presentation to helper (CD4+) T cells [47]. It has been argued that MSI-H colorectal cancers are incapable of eliciting cytotoxic responses in vivo due to the truncation of β2-microglobulin that is characteristic of these tumours [48]. The β2-microglobulin protein is an essential co-factor for MHC Class I and its defective function would render effective presentation of antigens impossible. However, whilst this defect negates antigen presentation by the tumour itself there is now considerable evidence that the direct presentation of antigen by a tumour may be relatively unimportant. Instead, the concept of "cross-priming" in which APC's such as dendritic cells, and to a lesser extent macrophages, pick up antigens released by dead tumour cells and subsequently present them to T cells may be more important in vivo [49,50]. Thus, β2-microglobulin mutations may be of relatively little importance. Instead a pool of abnormal peptides generated by the mutator phenotype may be recognised and harvested as TSA's by immature dendritic cells. On acquisition of non-self antigens these dendritic cells mature into professional APC's, with a natural propensity to appropriately present antigen and co-stimulate T lymphocytes [50].
Antigen presenting cells may obviate the need for direct presentation by tumour cells and cross-priming may involve the use of HLA Class II machinery. Immunohistochemical studies have demonstrated that HLA Class II expression is increased in MSI-H colorectal cancer compared to MSS cancers, although this was not associated with improved survival [51]. Additionally, molecular analyses using single subtraction hybridisation [52] and oligonucleotide microarrays [53] have also confirmed increased Class II mRNA levels in MSI-H colorectal cancer. These findings support the in vitro studies of tumour infiltrating lymphocytes in MSI-H colorectal cancer, mentioned earlier, that demonstrated HLA Class II restricted T helper cell activity and the presence of dendritic cells [44,45]. Either of these two populations may provide an alternative pathway by which cytotoxic T cells may be recruited and stimulated indirectly, but more work is needed to ascertain whether cytotoxic populations themselves are capable of recognising TSA's.
It has recently become evident that appropriate co-stimulation is pivotal to effective antigen presentation [54]. Co-stimulation refers to the interaction between surface molecules on the antigen-presenting cell (APC), such as CD80 (B7.1) and CD86 (B7.2), and surface molecules on the T cells (CTLA-4, OX40, CD40-L). If these molecules do not bind each other during antigen-presentation then co-stimulation fails and the T cells become anergic, i.e. ineffective and tolerogenic [54]. A microarray analysis comparing the gene expression profiles of MSI-H colorectal cancers to MSS counterparts demonstrated increased signal intensity of CD80 and CD86 in the former group [53] but further studies to validate these findings are still required. After appropriate antigen-presentation and co-stimulation lymphocytes are activated in a tumour-specific response [49,54]. They may then migrate to the tumour, infiltrate it and release mediators that can induce tumour cell death [47].
MSI-H colorectal cancer and lymphocyte infiltration
For many years the presence of a pronounced infiltrate of lymphocytes in colorectal cancer has been associated with improved prognosis [55,56] but conclusions have been confounded by inconsistencies. Lymphocytes associated with colorectal cancer can be sub-divided into those that invade tumour epithelium (intra-epithelial lymphocytes, IEL's), those confined to the stroma or those aggregated around the tumour (peri-tumoral lymphocytes). Previous studies on the significance of tumour infiltrating lymphocytes have been confusing due to variability in the definition of the subset being studied. More recently it has been shown that the presence of IEL's is positively associated with an improved survival in colorectal cancer in general [57] and specifically MSI-H colorectal cancer [41]. It has been suggested that they IEL's may represent evidence of an immune response to tumour antigens.
In a study specific to MSI-H colorectal cancer, Dolcetti and colleagues demonstrated increased immunostaining for IEL's when compared to MSS cancers [58]. These lymphocytes were shown to be predominantly CD8+ in keeping with a cytotoxic lymphocytic response and these findings have been confirmed by other groups using immunohistochemistry and RT-PCR [41,59]. However, debate continues as to whether these lymphocytes are of the αβT cell receptor lineage that are involved in tumour infiltration from the circulation or whether they are derived from γδ T cells that normally reside in the gastrointestinal tract [60]. The αβT cell phenotype represents lymphocytes that are targeting the tumour after antigen priming in lymphoid tissue, whereas the γδ T cells might represent a proliferation of lymphocytes resident in tumour epithelium. These characteristics of the lymphocyte infiltrates need further clarification.
One immunohistochemical study, involving relatively small numbers and two groups that differed considerably in size (n = 17 v n = 7), has noted the increased presence of CD8+ CD103+ (αEβ7+) lymphocytes in MSI-H colorectal cancer compared to MSS cancers [61]. The presence of CD103+ cells was much higher in tumour tissue than in adjacent colon in both groups and the authors' postulate that this integrin subunit, which binds to E-Cadherin, has a role in migration of lymphocytes from stroma to tumour epithelium. They suggest that the differences in lymphocyte infiltration between the two groups are likely to be due to increased expression of CD103 by local lymphocytes in MSI-H cancer that promotes infiltration into the tumour. They also postulate that local mediators released by the tumour, such as TGFβ-I rather than a systemic immune response, leads to CD103 upregulation, but they provide no evidence to support this. The expression of CD103 may well facilitate lymphocyte infiltration from stroma to tumour, but whether the difference in IEL numbers between MSI-H and MSS is due to tumour-derived mediators or an immune response is unclear from this study [61].
The increased expression of cytolytic mediators by IEL's in MSI-H colorectal cancer suggests that these cytolytic T-cells are indeed activated. Increased expression of perforin, granzyme B and granulysin in MSI-H colorectal cancers [53,59,62] suggests that IEL infiltrates are attempting to induce tumour cell death. This is lent further credence by the finding that the activation marker IL2Rα is also expressed more significantly in these tumours [59]. No single activation marker has been shown to correlate with survival in studies to date but this may well due to the complexities of immune responses.
The process of lymphocyte infiltration and anti-tumour activity is also influenced by the differential activity of helper (CD4+) T lymphocyte subsets and local cytokine profiles. Immune responses are promoted by the Th1 subset of CD4+ lymphocytes and their associated cytokines [Interferon (IFN)-γ, Tumour necrosis factor (TNF)-α, Interleukin (IL)-2 and IL-12). By contrast the Th2 subset of CD4+ lymphocytes and cytokines such as IL-10 promote tolerance to unrecognised antigens and prevent successful antigen-specific responses. A microarray analysis performed in our laboratory has demonstrated the upregulation of several pro-inflammatory cytokines in MSI-H colorectal cancer [53]. As well as the common players this analysis has identified potentially crucial roles for IL-18 and IL-15, both of which are capable of co-ordinating innate and acquired responses [63,64]. Clearly, activity of these interleukins should promote the likelihood of a successful immune response.
This microarray analysis also demonstrated that the heat shock protein family is up-regulated in MSI-H colorectal cancer [53]. This is highly significant in the context of previous work by Srivastava and others that has demonstrated the role of heat shock proteins in innate and antigen-specific immune responses [65,66]. Heat shock proteins act as chaperones that are actively involved in regulating the folding of newly synthesised proteins [67]. Indeed their name derives from the observation that these proteins are over-expressed in response to heat shock, and other stresses, that lead to native protein unfolding. The native fold of a protein is encoded by its amino acid sequence and it is therefore attractive to suggest that cancers with high-degree microsatellite instability, that generate large numbers of abnormal proteins with consequent misfolding, might excite a heat shock protein response. Heat shock proteins are used as natural adjuvants in immunotherapy trials and their up-regulation in MSI-H tumours may reflect a similar function in naturally occurring immune responses [68,69].
Our microarray findings have been validated using quantitative real-time RT-PCR across several genes of interest and demonstrate clear differences in the tumour biology of MSI-H and MSS cancers at the mRNA level.
Tumour escape and counter-attack
To counteract immune surveillance solid cancers may employ mechanisms to evade the immune system. Several possible methods of immune escape have been identified in colorectal cancer, such as the down-regulation of MHC proteins and co-stimulatory molecules [70,71]. The available evidence suggests that MSI-H colorectal cancers demonstrate higher levels of MHC Class II machinery than MSS counterparts, although the inefficacy of HLA Class I molecules in MSI-H tumours has been proposed as a means of tumour escape [48]. The significance of this in light of the potential for immune cross-priming is controversial, as discussed earlier.
Alternative mechanisms of immune escape identified in colorectal cancer include the release of mediators that suppress the function of tumour infiltrating lymphocytes: so-called "tumour counter-attack". In the past in vitro studies of lymphocytes infiltrating colorectal cancer have failed to demonstrate specific anti-tumour activity even though analysis of their receptor usage strongly suggested antigen-specificity [72,73]. These studies did not discriminate tumours according to microsatellite status but one explanation offered for the findings was that the presence of anti-lymphocyte agents, released by the tumour itself, neutralized the activity of tumour infiltrating lymphocytes. The fatty acid synthase (Fas)/Fas-Ligand system has been implicated as a pathway of colorectal cancer counter-attack [74]. Fas-L released by colorectal cancers may bind to Fas receptors on infiltrating lymphocytes and induce their apoptosis. Infiltrating lymphocytes may release Fas-L themselves but colorectal cancers evade the detrimental effects of this by uncoupling their Fas receptors from the intra-cellular machinery that mediates cell death. An immunohistochemical study examining membrane-bound Fas-L expression found that, contrary to expectation, Fas-L expression is not increased in MSS cancers and thus does not explain the less prominent lymphocyte infiltrates seen in these cancers [75]. The authors conclude that some other, as yet unidentified, mechanism of counter-attack must exist in these cancers to account for the reduced infiltrate in MSS colorectal cancer rather than attributing the difference to variable degrees of immunogenicity.
MSI-H colorectal cancer and apoptosis
Dolcetti and colleagues showed that MSI-H colorectal cancers stained significantly more heavily for markers of apoptotic cell death [76]. Subsequent follow-up analysis of the patients from whom the tumours had been removed showed that increased apoptosis counts correlated well with improved survival [40]. However, Michael-Robinson and co-workers also studied apoptosis in these cancers using TUNEL and though they confirmed the presence of more apoptotic cells, they found no co-localisation between these cells and infiltrating lymphocytes [77]. They concluded therefore that increased T cell infiltrates were not likely to be responsible for more marked tumour cell death. However, it may be argued that the release cytokine mediators of target cell death by infiltrating lymphocytes may render the need for direct co-localisation obsolete. In our opinion as MSI-H colorectal cancer does appear to be infiltrated by an activated cytotoxic T cell population and the tumours show high levels of apoptosis the two are likely to be linked but we acknowledge the need for further clarification.
An alternative explanation for the increased apoptosis observed in MSI-H colorectal cancer has been the theory of "effete malignancy". This concept proposes that the mutator phenotype affects peptides or pathways involved in cell processes fundamental to life. Thus, the accumulation of mutations adversely influences the tumour cells' viability and hence, leads to apoptotic cell death [78]. The anti-apoptotic bcl-2 protein has been noted to be under-expressed in MSI-H colorectal cancers [79] but the pro-apoptotic gene BAX also appears to be a common target for mutation in the MSI pathway [80], an event that may promote clonal expansion and tumourigenesis. These observations confirm the complex role of apoptosis in tumour development and progression.
The apoptosis observed in these cancers, whether induced by effete malignancy or an immune response, is of significance for another reason. The death of tumour cells releases intra-cellular proteins into the tumour micro-environment. This would be a vital step in the promotion of TSA release, recognition and presentation to the host T lymphocytes. It might also release heat shock proteins, upregulated in MSI-H colorectal canecr, which may promote both innate and antigen-specific arms of the immune response. The importance of dendritic cells in immune responses has already been mentioned [49] and immunohistochemical analysis of colorectal cancer has demonstrated the presence of dendritic cells at tumour margins [81]. The presence of this population has not been evaluated in MSI-H cancers specifically but the presence of dendritic cell infiltrates has been associated with reduced tumour progression in colorectal cancer [82].
Conclusion
Clearly, the mutator phenotype may influence the function of several cellular processes and these may include those that are designed to nullify the host response. Equally it has been suggested that it is the effect of microsatellite instability on other cellular processes, unrelated to tumour immunology, which leads to the survival benefit observed in MSI-H colorectal cancer. Effete malignancy may, for instance, limit a tumour's ability grow and survive [78]. Alternatively processes critical to tumour metastasis may be adversely affected by the mutator phenotype. The down-regulation of VEGF in MSI-H colorectal cancer is a one example of how these tumours may suffer reduced metastatic potential [83]. Certainly many of the biological characteristics of MSI-H, such as diploidy, wild-type p53 expression, activating β-catenin mutations and the CIMP+ phenotype, have all been associated with improved prognosis [84]. However, the effects of all these factors and that of an immune response may be additive, rather than exclusive and they may all contribute to the improvement in outcome.
There is now an accumulation of evidence that promotes the argument that MSI-H colorectal cancer is subject to a marked, possibly antigen-specific, immune response. We acknowledge that this may not be the sole determinant of improved prognosis although it seems likely to be a major influence. We believe that MSI-H may be a natural paradigm of host-tumour interactions in immunogenic colorectal cancers and as such further studies are required to clarify the nature of immune responses in these tumours. The use of heat shock proteins and abnormal peptides, derived from frameshift mutations in coding microsatellites, already hold promise in advancing the field of immunotherapy [85,86]. Ultimately the demonstration of specific anti-tumour activity in cytotoxic lymphocytes from patients with MSI-H colorectal would provide the best evidence in support of such a response. Such studies should enhance our understanding of the immune responses in MSI-H tumours and the tumour immunology of colorectal cancer in general. This may be crucial to the advance of efforts in the field of immunotherapy.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
AB searched and evaluated the literature and drafted the manuscript.
SAB and SD revised the manuscript.
All authors read and approved the final manuscript.
Acknowledgements
This study was funded by the Bowel and Cancer Research (Registered charity no. 328667, 4th Floor Alexandra Wing, The Royal London Hospital, Whitechapel, London E1 1BB, UK) the funding source had no influence over the content or conclusions of this manuscript.
==== Refs
Cancer Research UK. Cancer stats – Bowel (colorectal) cancer 2004
Andre T de Gramont A An overview of adjuvant systemic chemotherapy for colon cancer Clin Colorectal Cancer 2004 4 S22 S28 15212702
Gibbs P Chao MW Jones IT Yip D Evidence supports adjuvant radiotherapy in selected patients with rectal cancer ANZ Journal of Surgery 2004 74 152 157 14996164 10.1046/j.1445-1433.2003.02919.x
Rosenberg SA The immunotherapy and gene therapy of cancer J Clin Oncol 1992 10 180 199 1732421
Hawkins MJ Atkins MB Dutcher JP A phase II trial of interleukin-2 and lymphokine-activated killer cells in advanced colorectal carcinoma J Immunother 1994 15 74 78 8110733
Greco FA Figlin R York M Phase III randomized study to compare interferon alfa-2a in combination with fluorouracil versus fluorouracil alone in patients with advanced colorectal cancer J Clin Oncol 1996 14 2674 2681 8874326
Fearon ER Vogelstein B A genetic model for colorectal tumorigenesis Cell 1990 61 759 767 2188735 10.1016/0092-8674(90)90186-I
Haydon AM Jass JR Emerging pathways in colorectal-cancer development Lancet Oncol 2002 3 83 88 11905459 10.1016/S1470-2045(02)00649-6
Fishel R Signaling mismatch repair in cancer Nat Med 1999 5 1239 1241 10545986 10.1038/15191
Strand M Prolla TA Liskay RM Petes TD Destabilization of tracts of simple repetitive DNA in yeast by mutations affecting DNA mismatch repair Nature 1993 365 274 276 8371783 10.1038/365274a0
Boland CR Thibodeau SN Hamilton SR Sidransky D Eshleman JR Burt RW Meltzer SJ Rodriguez-Bigas MA Fodde R Ranzani GN A National Cancer Institute Workshop on Microsatellite Instability for cancer detection and familial predisposition: development of international criteria for the determination of microsatellite instability in colorectal cancer Cancer Res 1998 58 5248 5257 9823339
Knudson AG Hereditary cancer, oncogenes, and antioncogenes Cancer Res 1985 45 1437 1443 2983882
Lawes DA SenGupta S Boulos PB The clinical importance and prognostic implications of microsatellite instability in sporadic cancer Eur J Surg Oncol 2003 29 201 212 12657227 10.1053/ejso.2002.1399
Bhattacharyya NP Skandalis A Ganesh A Groden J Meuth M Mutator phenotypes in human colorectal carcinoma cell lines Proc Natl Acad Sci U S A 1994 91 6319 6323 8022779
Marsischky GT Filosi N Kane MF Kolodner R Redundancy of Saccharomyces cerevisiae MSH3 and MSH6 in MSH-2 dependent mismatch repair Genes Dev 1996 10 407 420 8600025
Strand M Earley MC Crouse GF Petes TD Mutations in the MSH3 gene preferentially lead to defects within tracts of simple repetitive DNA in Saccharomyces cerevisiae Proc Natl Acad Sci U S A 1995 92 10418 10421 7479796
Cunningham JM Christensen ER Tester DJ Kim CY Roche PC Burgart LJ Thibodeau SN Hypermethylation of the hMLH1 promoter in colon cancer with microsatellite instability Cancer Res 1998 58 3455 3460 9699680
Herman JG Umar A Polyak K Graff JR Ahuja N Issa JP Markowitz S Willson JK Hamilton SR Kinzler KW Incidence and functional consequences of hMLH1 promoter hypermethylation in colorectal carcinoma Proc Natl Acad Sci U S A 1998 95 6870 6875 9618505 10.1073/pnas.95.12.6870
Toyota M Issa JP CpG island methylator phenotypes in aging and cancer Semin Cancer Biol 1999 9 349 357 10547343 10.1006/scbi.1999.0135
Jass JR HNPCC and sporadic MSI-H colorectal cancer: a review of the morphological similarities and differences Familial Cancer 2004 3 93 100 15340259 10.1023/B:FAME.0000039849.86008.b7
Umar A Boland CR Terdiman J Syngal S de la Chapelle A Ruschhoff J Fishel R Lindor NM Burgart LJ Hamelin R Revised bethesda Guidelines for Hereditary Nonpolyposis Colorectal Cancer (Lynch Syndrome) and Microsatellite Instability J Natl Cancer Inst 2004 96 261 267 14970275
Boland CR Thibodeau SN Hamilton SR Sidransky D Eshleman JR Burt RW Meltzer SJ Rodriguez-Bigas MA Fodde R Ranzani GN A National Cancer Institute Workshop on Microsatellite Instability for cancer detection and familial predisposition: development of international criteria for the determination of microsatellite instability in colorectal cancer Cancer Res 1998 58 5248 5257 9823339
Gonzalez-Garcia I Moreno V Navarro M Marti-Rague J Marcuello E Benasco C Campos O Capella G Peinado MA Standardized approach for microsatellite instability detection in colorectal carcinomas J Natl Cancer Inst 2000 92 544 549 10749909 10.1093/jnci/92.7.544
Duval A Hamelin R Genetic instability in human mismatch repair deficient cancers Ann Genet 2002 45 71 75 12119215
Jass JR Young J Leggett BA Evolution of colorectal cancer: change of pace and change of direction J Gastroenterol Hepatol 2002 17 17 26 11987262 10.1046/j.1440-1746.2002.02635.x
Lothe RA Peltomaki P Meling GI Aaltonen LA Nystrom-Lahti M Pylkkanen L Heimdal K Andersen TI Moller P Rognum TO Genomic instability in colorectal cancer: relationship to clinicopathological variables and family history Cancer Res 1993 53 5849 5852 8261392
Thibodeau SN Bren G Schaid D Microsatellite instability in cancer of the proximal colon Science 1993 260 816 819 8484122
Feeley KM Fullard JF Heneghan MA Smith T Maher M Murphy RP O'Gorman TA Microsatellite instability in sporadic colorectal carcinoma is not an indicator of prognosis J Pathol 1999 188 14 17 10398134 10.1002/(SICI)1096-9896(199905)188:1<14::AID-PATH323>3.0.CO;2-Q
Curran B Lenehan K Mulcahy H Tighe O Bennett MA Kay EW O'Donoghue DP Leader M Croke DT Replication error phenotype, clinicopathological variables, and patient outcome in Dukes' B stage II (T3,N0,M0) colorectal cancer Gut 2000 46 200 204 10644313 10.1136/gut.46.2.200
Salahshor S Kressner U Fischer H Lindmark G Glimelius B Pahlman L Lindblom A Microsatellite instability in sporadic colorectal cancer is not an independent prognostic factor Br J Cancer 1999 81 190 193 10496341 10.1038/sj.bjc.6690676
Wright CM Dent OF Barker M Newland RC Chapuis PH Bokey EL Young JP Leggett BA Jass JR Macdonald GA Prognostic significance of extensive microsatellite instability in sporadic clinicopathological stage C colorectal cancer Br J Surg 2000 87 1197 1202 10971428 10.1046/j.1365-2168.2000.01508.x
Ward R Meagher A Tomlinson I O'Connor T Norrie M Wu R Hawkins N Microsatellite instability and the clinicopathological features of sporadic colorectal cancer Gut 2001 48 821 829 11358903 10.1136/gut.48.6.821
Gryfe R Kim H Hsieh ET Aronson MD Holowaty EJ Bull SB Redston M Gallinger S Tumor microsatellite instability and clinical outcome in young patients with colorectal cancer N Engl J Med 2000 342 69 77 10631274 10.1056/NEJM200001133420201
Popat S Hubner R Houlston RS Systematic Review of Microsatellite Instability and Colorectal Cancer Prognosis J Clin Oncol 2005 23 609 618 15659508 10.1200/JCO.2005.01.086
Elsaleh H Powell B Soontrapornchai P Joseph D Goria F Spry N Iacopetta B p53 gene mutation, microsatellite instability and adjuvant chemotherapy: impact on survival of 388 patients with Dukes' C colon carcinoma Oncology 2000 58 52 59 10644941 10.1159/000012079
Elsaleh H Joseph D Grieu F Zeps N Spry N Iacopetta B Association of tumour site and sex with survival benefit from adjuvant chemotherapy in colorectal cancer Lancet 2000 355 1745 1750 10832824 10.1016/S0140-6736(00)02261-3
Elsaleh H Powell B McCaul K Grieu F Grant R Joseph D Iacopetta B P53 alteration and microsatellite instability have predictive value for survival benefit from chemotherapy in stage III colorectal carcinoma Clin Cancer Res 2001 7 1343 1349 11350904
Carethers JM Smith EJ Behling CA Nguyen L Tajima A Doctolero RT Cabrera BL Goel A Arnold CA Miyai K Use of 5-fluorouracil and survival in patients with microsatellite-unstable colorectal cancer Gastroenterology 2004 126 394 401 14762775 10.1053/j.gastro.2003.12.023
Ribic C Sargent DJ Moore MJ Thibodeau SN French AJ Goldberg RM Hamilton SR Laurent-Puig P Gryfe R Shepherd LE Tumor microsatellite-instability status as a predictor of benefit from fluorouracil-based adjuvant chemotherapy for colon cancer N Engl J Med 2003 349 247 257 12867608 10.1056/NEJMoa022289
Guidoboni M Gafa R Viel A Doglioni C Russo A Santini A Del Tin L Macri E Lanza G Boiocchi M Microsatellite instability and high content of activated cytotoxic lymphocytes identify colon cancer patients with a favorable prognosis Am J Pathol 2001 159 297 304 11438476
Takemoto N Konishi F Yamashita K Kojima M Furukawa T Miyakura Y Shitoh K Nagai H The Correlation of Microsatellite Instability and Tumor-infiltrating Lymphocytes in Hereditary Non-polyposis Colorectal Cancer (HNPCC) and Sporadic Colorectal Cancers: the Significance of Different Types of Lymphocyte Infiltration Jpn J Clin Oncol 2004 34 90 98 15067103 10.1093/jjco/hyh018
Adam JK Odhav B Bhoola KD Immune responses in cancer Pharmacol Ther 2003 99 113 132 12804702 10.1016/S0163-7258(03)00056-1
Bodmer W Bishop T Karran P Genetic steps in colorectal cancer [news] Nat Genet 1994 6 217 219 8012377 10.1038/ng0394-217
Saeterdal I Gjertsen MK Straten P Eriksen JA Gaudernack G A TGF betaRII frameshift-mutation-derived CTL epitope recognised by HLA-A2-restricted CD8+ T cells Cancer Immunol Immunother 2001 50 469 476 11761441 10.1007/s002620100222
Saeterdal I Bjorheim J Lislerud K Gjertsen MK Bukholm IK Olsen OC Nesland JM Eriksen JA Moller M Lindblom A Frameshift-mutation-derived peptides as tumor-specific antigens in inherited and spontaneous colorectal cancer Proc Natl Acad Sci U S A 2001 98 13255 13260 11687624 10.1073/pnas.231326898
Ishikawa T Fujita T Suzuki Y Okabe S Yuasa Y Iwai T Kawakami Y Tumor-specific Immunological Recognition of Frameshift-mutated Peptides in Colon Cancer with Microsatellite Instability Cancer Res 2003 63 5564 5572 14500396
Titu LV Monson JR Greenman J The role of CD8(+) T cells in immune responses to colorectal cancer Cancer Immunol Immunother 2002 51 235 247 12070710 10.1007/s00262-002-0276-4
Bicknell DC Kaklamanis L Hampson R Bodmer WF Karran P Selection for beta 2-microglobulin mutation in mismatch repair-defective colorectal carcinomas Curr Biol 1996 6 1695 1697 8994836 10.1016/S0960-9822(02)70795-1
Banchereau J Steinman RM Dendritic cells and the control of immunity Nature 1998 392 245 252 9521319 10.1038/32588
Banchereau J Briere F Caux C Davoust J Lebecque S Liu YJ Pulendran B Palucka K Immunobiology of dendritic cells Annu Rev Immunol 2000 18 767 811 10837075 10.1146/annurev.immunol.18.1.767
Lovig T Andersen SN Thorstensen L Diep CB Meling GI Lothe RA Rognum TO Strong HLA-DR expression in microsatellite stable carcinomas of the large bowel is associated with good prognosis Br J Cancer 2002 87 756 762 12232760 10.1038/sj.bjc.6600507
Bustin SA Li SR Phillips S Dorudi S Expression of HLA class II in colorectal cancer: evidence for enhanced immunogenicity of microsatellite-instability-positive tumours Tumour Biol 2001 22 294 298 11553859 10.1159/000050630
Banerjea A Ahmed S Hands R Huang F Han X Shaw P Feakins R Bustin S Dorudi S Colorectal cancers with microsatellite instability display mRNA expression signatures characteristic of increased immunogenicity Molecular Cancer 2004 3 21 15298707 10.1186/1476-4598-3-21
Abken H Hombach A Heuser C Kronfeld K Seliger B Tuning tumor-specific T-cell activation: a matter of costimulation? TRENDS in Immunology 2002 23 240 245 12102744 10.1016/S1471-4906(02)02180-4
Jass JR Lymphocytic infiltration and survival in rectal cancer J Clin Pathol 1986 39 585 589 3722412
Watt AG House AK Colonic carcinoma: a quantitative assessment of lymphocyte infiltration at the periphery of colonic tumors related to prognosis Cancer 1978 41 279 282 626936
Naito Y Saito K Shiiba K Ohuchi A Saigenji K Nagura H Ohtani H CD8+ T cells infiltrated within cancer cell nests as a prognostic factor in human colorectal cancer Cancer Res 1998 58 3491 3494 9721846
Dolcetti R Viel A Doglioni C Russo A Guidoboni M Capozzi E Vecchiato N Macri E Fornasarig M Boiocchi M High prevalence of activated intraepithelial cytotoxic T lymphocytes and increased neoplastic cell apoptosis in colorectal carcinomas with microsatellite instability Am J Pathol 1999 154 1805 1813 10362805
Phillips SM Banerjea A Feakins R Li SR Bustin SA Dorudi S Tumour-infiltrating lymphocytes in colorectal cancer with microsatellite instability are activated and cytotoxic Br J Surg 2004 91 469 475 15048750 10.1002/bjs.4472
Hayday A Theodoridis E Ramsburg E Shires J Intraepithelial lymphocytes: exploring the Third Way in immunology nat immunol 2001 2 997 1003 11685222 10.1038/ni1101-997
Quinn E Hawkins N Yip YL Suter C Ward R CD103+ intraepithelial lymphocytes – a unique population in microsatellite unstable sporadic colorectal cancer Eur J Cancer 2003 39 469 475 12751377 10.1016/S0959-8049(02)00633-0
Dolcetti R Viel A Doglioni C Russo A Guidoboni M Capozzi E Vecchiato N Macri E Fornasarig M Boiocchi M High prevalence of activated intraepithelial cytotoxic T lymphocytes and increased neoplastic cell apoptosis in colorectal carcinomas with microsatellite instability Am J Pathol 1999 154 1805 1813 10362805
Pages F Berger A Lebel-Binay S Zinzindohoue F Danel C Piqueras B Carriere O Thiounn N Cugnenc PH Fridman WH Proinflammatory and antitumor properties of interleukin-18 in the gastrointestinal tract Immunol Lett 2000 75 9 14 11163860 10.1016/S0165-2478(00)00285-6
Fehniger TA Caliguiri MA Interleukin 15: biology and relevance to human disease Blood 2001 97 14 25 11133738 10.1182/blood.V97.1.14
Srivastava PK Udono H Heat shock protein-peptide complexes in cancer immunotherapy Curr Opin Immunol 1994 6 728 732 7826528 10.1016/0952-7915(94)90076-0
Todryk SM Melcher AA Dalgleish AG Vile RG Heat shock proteins refine the danger theory Immunology 2000 99 334 337 10712661 10.1046/j.1365-2567.2000.00002.x
Castelli C Rivoltini L Rini F elli F estori A aio M azzaferro V oppa J rivastava PK. armiani G Heat shock proteins: biological functions and clinical application as personalized vaccines for human cancer Cancer Immunol Immunother 2004 53 227 233 14689240 10.1007/s00262-003-0481-9
Todryk SM Melcher AA Hardwick N Linardakis E Bateman A Colombo MP Stoppacciaro A Vile RG Heat Shock Protein 70 Induced During Tumor Cell Killing Induces Th1 Cytokines and Targets Immature Dendritic Cell Precursors to Enhance Antigen Uptake J Immunol 1999 163 1398 1408 10415040
Srivastava PK Purification of heat shock protein-peptide complexes for use in vaccination against cancers and intracellular pathogens Methods 1997 12 165 171 9184380 10.1006/meth.1997.0464
Dalerba P Maccalli C Casati C Castelli C Parmiani G Immunology and immunotherapy of colorectal cancer Crit Rev Oncol Hematol 2003 46 33 57 12672517
McDougall CJ Ngoi SS Goldman IS Godwin T Felix J DeCosse JJ Rigas B Reduced expression of HLA class I and II antigens in colon cancer Cancer Res 1990 50 8023 8027 2123744
Ostenstad B Lea T Schlichting E Harboe M Human colorectal tumour infiltrating lymphocytes express activation markers and the CD45RO molecule, showing a primed population of lymphocytes in the tumour area Gut 1994 35 382 387 8150352
Ostenstad B Sioud M Lea T Schlichting E Harboe M Limited heterogeneity in the T-cell receptor V-gene usage in lymphocytes infiltrating human colorectal tumours Br J Cancer 1994 69 1078 1082 8198973
O'Connell J O'Sullivan GC Collins JK Shanahan F The Fas counterattack: Fas-mediated T cell killing by colon cancer cells expressing Fas ligand J Exp Med 1996 184 1075 1082 9064324 10.1084/jem.184.3.1075
Michael-Robinson JM Pandeya N Cummings MC Walsh MD Young JP Leggett BA Purdie DM Jass JR Radford-Smith GL Fas ligand and tumour counter-attack in colorectal cancer stratified according to microsatellite instability status J Pathol 2003 201 46 54 12950016 10.1002/path.1406
Dolcetti R Viel A Doglioni C Russo A Guidoboni M Capozzi E Vecchiato N Macri E Fornasarig M Boiocchi M High prevalence of activated intraepithelial cytotoxic T lymphocytes and increased neoplastic cell apoptosis in colorectal carcinomas with microsatellite instability Am J Pathol 1999 154 1805 1813 10362805
Michael-Robinson JM Biemer-Huttmann A Purdie DM Walsh MD Simms LA Biden KG Young JP Leggett BA Jass JR Radford-Smith GL Tumour infiltrating lymphocytes and apoptosis are independent features in colorectal cancer stratified according to microsatellite instability status Gut 2001 48 360 366 11171826 10.1136/gut.48.3.360
Shibata D Peinado MA Ionov Y Malkhosyan S Perucho M Genomic instability in repeated sequences is an early somatic event in colorectal tumorigenesis that persists after transformation Nat Genet 1994 6 273 281 8012390 10.1038/ng0394-273
Biden KG Simms LA Cummings M Buttenshaw R Schoch E Searle J Gobe G Jass JR Meltzer SJ Leggett BA Expression of Bcl-2 protein is decreased in colorectal adenocarcinomas with microsatellite instability Oncogene 1999 18 1245 1249 10022131 10.1038/sj.onc.1202413
Rampino N Yamamoto H Ionov Y Li Y Sawai H Reed JC Perucho M Somatic frameshift mutations in the BAX gene in colon cancers of the microsatellite mutator phenotype Science 1997 275 967 969 9020077 10.1126/science.275.5302.967
Suzuki A Masuda A Nagata H Kameoka S Kikawada Y Yamakawa M Kasajima T Mature dendritic cells make clusters with T cells in the invasive margin of colorectal carcinoma J Pathol 2002 196 37 43 11748640 10.1002/path.1018
Schwaab T Weiss JE Schned AR Barth RJ Dendritic cell infiltration in colon cancer J Immunother 2001 24 130 137 10.1097/00002371-200103000-00007
Wynter CVA Simms LA Buttenshaw RL Biden KG Young J Leggett BA Conrad RJ Schoch EM Jass JR Pillay SP Angiogenic factor VEGF is decreased in human colorectal neoplasms showing DNA microsatellite instability J Pathol 1999 189 319 325 10547592 10.1002/(SICI)1096-9896(199911)189:3<319::AID-PATH436>3.0.CO;2-2
Forster S Sattler HP Hack M Romanakis K Rohde V Seitz G Wullich B Microsatellite instability in sporadic carcinomas of the proximal colon: association with diploid DNA content, negative protein expression of p53, and distinct histomorphologic features Surgery 1998 123 13 18 9457218 10.1067/msy.1998.83304
Castelli C Rivoltini L Rini F Belli F Testori A Maio M Mazzaferro V Coppa J Srivastava PK. Parmiani G Heat shock proteins: biological functions and clinical application as personalized vaccines for human cancer Cancer Immunol Immunother 2004 53 227 233 14689240 10.1007/s00262-003-0481-9
Schwitalle Y Linnebacher M Ripberger E Gebert J von Knebel-Doeberitz M Immunogeic peptides generated by frameshift mutations in DNA mismatch repair-deficient cancer cells Cancer Immunity 2004 4 14 15563124
| 15890075 | PMC1166579 | CC BY | 2021-01-04 16:39:03 | no | World J Surg Oncol. 2005 May 12; 3:26 | utf-8 | World J Surg Oncol | 2,005 | 10.1186/1477-7819-3-26 | oa_comm |
==== Front
World J Surg OncolWorld Journal of Surgical Oncology1477-7819BioMed Central London 1477-7819-3-271590719910.1186/1477-7819-3-27ReviewViral hepatitis and hepatocellular carcinoma Michielsen Peter P [email protected] Sven M [email protected] Dongen Jurgen L [email protected] Division of Gastroenterology and Hepatology University Hospital Antwerp, Belgium2005 20 5 2005 3 27 27 29 11 2004 20 5 2005 Copyright © 2005 Michielsen et al; licensee BioMed Central Ltd.2005Michielsen et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world. The incidence of HCC varies considerably with the geographic area because of differences in the major causative factors. Chronic hepatitis B and C, mostly in the cirrhotic stage, are responsible for the great majority of cases of HCC worldwide. The geographic areas at the highest risk are South-East Asia and sub-Saharan Africa, here hepatitis B is highly endemic and is the main cause of HCC. In areas with an intermediate rate of HCC such as Southern Europe and Japan, hepatitis C is the predominant cause, whereas in low rate areas such as Northern Europe and the USA, HCC is often related to other factors as alcoholic liver disease. There is a rising incidence in HCC in developed countries during the last two decades, due to the increasing rate of hepatitis C infection and improvement of the clinical management of cirrhosis.
Methods
This article reviews the literature on hepatitis and hepatocellular carcinoma. The Medline search was carried out using these key words and articles were selected on epidemiology, risk factors, screening, and prevention of hepatocellular carcinoma.
Results
Screening of patients with advanced chronic hepatitis B and C with hepatic ultrasound and determination of serum alfa-fetoprotein may improve the detection of HCC, but further studies are needed whether screening improves clinical outcome.
Hepatitis B and C viruses (HBV/HCV) can be implicated in the development of HCC in an indirect way, through induction of chronic inflammation, or directly by means of viral proteins or, in the case of HBV, by creation of mutations by integration into the genome of the hepatocyte.
Conclusion
The most effective tool to prevent HCC is avoidance of the risk factors such as viral infection. For HBV, a very effective vaccine is available. Preliminary data from Taiwan indicate a protective effect of universal vaccination on the development of HCC. Vaccination against HBV should therefore be a health priority. In patients with chronic hepatitis B or C, interferon-alfa treatment in a noncirrhotic stage is protective for HCC development in responders, probably by prevention of cirrhosis development. When cirrhosis is already present, the protective effect is less clear. For cirrhosis due to hepatitis B, a protective effect was demonstrated in Oriental, but not in European patients. For cirrhosis due to hepatitis C, interferon-alfa treatment showed to be protective in some studies, especially in Japan with a high incidence of HCC in untreated patients. Virological, but also merely biochemical response, seems to be associated with a lower risk of development of HCC. As most studies are not randomized controlled trials, no definitive conclusions on the long-term effects of interferon-alfa in HBV or HCV cirrhosis can be established. Especially in hepatitis C, prospective studies should be performed using the more potent reference treatments for cirrhotics, namely the combination of peginterferon and ribavirin.
==== Body
Epidemiology of hepatocellular carcinoma
Background
Hepatocellular carcinoma (HCC) is one of the most common malignant tumors, representing more than 5% of all cancers. The estimated annual number of cases exceeds 500,000 [1], with a mean annual incidence of around 3–4% [2]. In terms of relative frequencies, HCC ranks as the fifth most common cancer in the world, it is also the fifth among men and eighth among women; it is the second among cancers of the digestive tract after stomach cancer [3].
The incidence of HCC varies considerably with the geographic area because of differences in the major causative factors. The geographic areas at the highest risk are located in Eastern Asia, with age-adjusted incidence rates (AAIR) ranging from 27.6 to 36.6 per 100,000 in men; Middle Africa (AAIR 20.8–31.1/100,000) and some Western African countries (30–48/100,000). The geographic areas at lowest risk are Northern Europe, Australia, New Zealand and the Caucasian populations of North and Latin America (AAIR 1.5–3.0). In Southern Europe, AAIR is around 10 per 100,000 in men [3].
The most powerful risk factor for development of HCC is the existence of liver cirrhosis, regardless of its etiology [4]. Among cirrhotics, viral infection and high alcohol intake are associated with the highest risk [5-8].
Of the primary hepatitis viruses, only hepatitis B and C viruses cause HCC [9]. Hepatitis A and E viruses do not produce long-term pathological sequelae. Although hepatitis D virus (HDV) always occurs as co-infection with hepatitis B virus and leads to severe acute or chronic hepatic disease, there is controversy whether it increases the carcinogenic potential [10,11].
Risk factors for development of HCC
Hepatitis B
Hepatitis B virus (HBV) infection is a major public health problem. It is estimated that two billion people have been infected worldwide and 360 million suffer from chronic HBV infection [12]. Over 520,000 die each year, 50,000 from acute hepatitis B, 470,000 from cirrhosis and liver cancer. In South-East Asia hepatitis B is mostly acquired perinatally from an infected mother. In sub-Saharan Africa, it is mostly acquired in early childhood by horizontal infection, whereas in Northwestern Europe, North America and Australia infection is mainly through sexual contact or needle sharing among injecting drug users, with a peak incidence in the 15–25 age group [12]. Infection acquired perinatally and in early childhood is usually asymptomatic, becoming chronic in 90 and 30% of cases, respectively. In adults, infection resolves in >95% with loss of serum HBsAg and the appearance of anti-HBs. Chronic infection is characterized by the persistence of HBsAg for more than 6 months. Acute hepatitis B usually results in complete recovery with little if any risk of HCC. In cases with persistent HBV infection, HBV is one of the most important risk factors for HCC.
Chronic HBV infection presents as one of three potentially successive phases: immune tolerant, immune active and low- or non-replicative. In the immune tolerant phase, serum HBsAg and HBeAg are detectable, serum HBV DNA levels are high, serum aminotransferases are normal or minimally elevated. In the immune active phase, serum HBV DNA levels decrease and serum aminotransferase levels increase. Flares of aminotransferases may be observed, in some patients these flares are followed by HBeAg-anti-HBe seroconversion. Following this conversion, in the low- or non-replicative phase the HBV replication persists but at a very low level suppressed by the host immune response. HBV DNA in serum is undetectable by conventional, non-PCR based techniques. This phase is also called the 'inactive carrier state'. It may lead to resolution of HBV infection where HBsAg becomes undetectable and anti-HBs is detected, anti-HBc staying positive as sign of contact with the virus. Recently it has been reported that HBV DNA can persist in the serum and liver tissue even after negativation of HBsAg [13]. Recent advances in molecular technology have allowed the isolation of HBV variants that either cannot produce HBeAg or produce it less efficiently, based on precore stop codon mutation and mutations in the core promoter region respectively. In patients with HBV variants, progressive liver damage occurs in parallel with relatively high levels of viremia. In perinatally infected people, the immunotolerant phase lasts till the age of 15–35 years, after which hepatitis flares may occur, leading eventually to viral remission. In patients infected during later childhood or adulthood, there is no immunotolerant phase.
Most studies on the risk of developing HCC in chronic HBV infection have been performed in the Far East. Here, most patients acquired the HBV infection as newborn infants [14]. It has been noted that the probability of acquiring HCC increases with severity of liver disease. The annual risk of HCC is 0.5% for asymptomatic HBsAg carriers and 0.8% for patients with chronic hepatitis B [15]. Patients with HBV-cirrhosis have a 1000 times higher risk of developing HCC compared to a HBsAg negative control group [16]. The incidence of HCC in compensated cirrhosis due to HBV from Asia was 2.7%. In Japan, the mean interval between the time of initial infection with HBV and the occurrence of HCC is 50 years. As most people here are infected at birth, HBV related liver cirrhosis usually develops in patients in their 40's and HCC in their 50's [17].
Few adequate studies have been performed in the West to address the issue of the incidence of HCC in persons who are positive for HBsAg. Most of the studies in Western countries have included small numbers of HBsAg positive patients and/or have not specifically analyzed the group of HBsAg carriers. There is also lack of uniformity in the timing of initiation of follow-up monitoring. In a cohort of 350 Western European patients with compensated cirrhosis followed for a mean period of 6 years, the 5-year cumulative incidence of HCC was 6% [18,19]. The incidence was 2.2% in a series of 179 untreated Caucasian patients [19,20]. In a retrospective analysis of cirrhotic European patients with HBV infection, the 5-year incidence of HCC was 9% irrespective of HBeAg or HBV DNA status at the time of diagnosis of cirrhosis [21].
The hepatitis B replication status seems to play an important role in determining the risk of development of HCC [22-24]. A recent study found that whereas the relative risk of HCC among men with HBsAg alone was 9.6 compared to those without HBsAg, the risk increased to 60.2 when they were positive for both HBsAg and HBeAg [23]. Another analysis showed that the level of HBV DNA is a prognostic marker for HBV-related HCC and that HCC patients with a less favorable course appear to either clear the virus poorly or to have a greater level of virus production [24]. It was recently demonstrated that positivity for anti-HBc alone in absence of HBsAg and anti-HCV is not rare in Japanese patients with HCC, which may indicate that HBV virus might be involved in so-called non-B HCC [25].
The entire nucleotide sequences of HBV genomes have been classified into 8 genotypes (A-H), with predominance of genotypes A and D in Western countries, and B and C in Southeast Asia and the Far East [26-29]. Several studies from the Far East evaluated the association between distinct genotypes and severity of liver disease. Genotype C was shown to be associated with the development of liver cirrhosis and HCC in Taiwan [30], China [31] and Japan [32], whereas genotype B was shown rarely to be associated with the development of HCC in China and Japan. In contrast, in Taiwan genotype B is the predominant type in patients with HCC who are younger than 35 years [30]. Another study from Taiwan showed that patients with genotype C had a greater tumor recurrence rate after curative resection of HCC compared with those with genotype B [33]. It was also shown that the likelihood of presence of T1762/A1764 mutations in the basal core promoter parallels the progression of liver disease, and that this mutation is found more frequent in HBV genotype C than B patients [34]. PreS deletions were shown to be more frequent in patients with HBV genotype C, and associated with more advanced disease such as liver cirrhosis and hepatocellular carcinoma [35].
Hepatitis C
Hepatitis C is also a major public health problem. There are more than 170 million people infected worldwide [36]. Approximately 80% of HCV infected patients develop chronic hepatitis C. About 20% of these patients will develop severe chronic hepatitis C and cirrhosis, which becomes detectable in the second and third decade after infection. The natural history of chronic hepatitis C infection is characterized by a predominantly asymptomatic course and a variable clinical outcome. For these reasons it is difficult to define the rate of progression to cirrhosis and HCC. The risk of cirrhosis in chronic hepatitis C is less than 10% in women infected at a young age and >30% in men infected after the age of 40 over a 20 year period [37,38]. Five prospective studies from Europe and the US have shown that during the first 10–15 years after initial infection, liver cancer is a rare occurrence [39-43]. In patients with hepatitis C, there is an increased risk of HCC coinciding with the establishment of cirrhosis with yearly incidence between 3–8% [6,7,44-47]. In Japan, the mean interval between infection and development of HCC is 30 years [48]. A study from the US shows a long time lag (mean 28 years, range 8–42) between transfusion-associated hepatitis and development of HCC [49].
There is conflicting information on the relationship between HCV genotype and progression to HCC in longitudinal studies. It is suggested by some authors that genotype 1b (most prevalent in Europe and Japan) is associated with a higher incidence of HCC than infection with other genotypes [50,51]. In other studies, however, this was not observed [52,53].
Coinfection of HBV and HCV
Both HBV and HCV are transmitted parenterally and coinfection is not uncommon in intravenous drug users and in countries with a high prevalence of HBV [54]. Coinfection of HBV and HCV seems to result in more severe liver disease than either infection alone [55]. The risk of developing HCC in subjects with both infections has been investigated in a meta-analysis of 32 epidemiological studies between 1993 and 1997 [56]. The odds ratio for development of HCC in HBsAg positive, anti-HCV/HCV RNA negative subjects was 20.4; in HBsAg negative, anti-HCV/HCV RNA positive subjects 23.6; and subjects positive for both markers 135. These data suggest a more than additive but less than multiplicative effect of HBV and HCV coinfection on the relative risk for HCC. The viruses may act through common as well as different pathways in the carcinogenic process.
It has been reported that HBV DNA is still present after seroconversion of HBsAg in patients with hepatitis B. Several reports indicate that prior HBV infection, characterized by presence of anti-HBc, affects the development of HCC in patients infected with HCV [57-59]. Given these data, in patients with chronic HCV infection, serologic markers of past HBV infection should be checked, not just HBsAg. Other authors, however, were not able to document any adverse event of occult HBV infection on the clinicopathologic course of chronic HCV infection [60].
In case of coinfection with HBV (whether active or past), a more aggressive surveillance to detect early HCC could be suggested [61]. However, to date screening and surveillance programs have not demonstrated a significant survival benefit.
In view of the role of HBV as cofactor in the development of HCV related cirrhosis and HCC, vaccination of patients with chronic hepatitis C against HBV has been advocated with the presumption of avoiding additional liver injury [62,63].
Coinfection of HBV and HDV
Verme et al [11] suggested that HBsAg positive patients with HDV superinfection develop cirrhosis and HCC at an earlier stage (mean age 48 year) than HBsAg carriers without HDV infection (mean age 62 years).
Coinfection of HBV and HCV with HIV
Coinfection of HBV and HCV with HIV is common because these diseases share the same routes of transmission. Recently a series of HCC in HIV-HCV coinfected patients was published, indicating an unusually rapid development of HCC in these patients [64]. This is not surprising, as chronic hepatitis C is more aggressive in HIV positive subjects, leading to cirrhosis and end-stage liver disease in a shorter period of time [65].
Coinfection of HCV and S. mansoni
An Egyptian study showed that Schistosoma infection increased the risk of HCC, only in the presence of HCV, whereas isolated S. mansoni infection does not [66].
Role of alcohol consumption in HBV or HCV infection
Reports suggest that HBV and ethanol act synergistically to promote HCC [67,68]. Habitual heavy drinking was reported to be a significant risk factor for HCC in patients with HCV-related liver cirrhosis by multiple logistic regression analysis [57]. A recent study showed synergism between alcohol drinking and HBV or HCV infection, with approximately a twofold increase in the odds ratio for each hepatitis virus infection for drinkers' > 60 g/d, with a more than additive but less than multiplicative risk [69]. Although two case-control studies did not show a relationship of alcohol consumption with the occurrence of HCC [70,71], another case-control study found a positive interaction between HBsAg positivity and HCV RNA positivity and heavy alcohol intake in the development of HCC [72]. Furthermore, Hassan et al. [73] showed synergistic interaction (more than additive) between heavy alcohol consumption ≥ 80 ml/d and chronic HBV or HCV infection (odds ratio 53.9) and insulin or non-insulin dependent diabetes mellitus (odds ratio 9.9).
Incidence of HBV- and HCV-related HCC worldwide
Chronic hepatitis B and C infection are responsible for the great majority of cases of HCC worldwide [9]. They also account for the peculiar geographical distribution of the tumor. The relative frequencies of HBV and/or HCV related HCC in the world is illustrated in Table 1[17,72,74-93]. The worldwide incidence of HCC varies and is predominantly related to the regional prevalence of chronic viral hepatitis and its associated chronic liver disease and cirrhosis. Aflatoxin intake has a role in the genesis of HCC only in patients who have pre-existing chronic hepatitis B [84].
Table 1 Relative frequencies of HBV and HCV related HCC in the world
Author [reference] Country Era Sample size HBsAg + (%) Anti-HCV + (%) HBsAg/anti HCV + (%) Other (%)
Chen, 1990 [74] Taiwan NR 66 35 (53.0) 15 (22.7) 7 (10.6) 9 (13.6)
Chuang, 1991 [75] Taiwan NR 128 87 (68.0) 13 (10.1) 12 (9.4) 16 (12.5)
Lee, 1992 [76] Taiwan NR 326 233 (71.5) 31 (9.5) 10 (3.1) 52 (15.9)
Jeng, 1991 [77] Taiwan NR 129 62 (48.1) 29 (22.5) 19 (14.7) 19 (14.7)
Leung, 1992 [78] Hong Kong 1986–90 424 341 (80.3) 16 (3.8) 15 (4.0) 52 (12.3)
Nishioka, 1990 [79] Japan NR 180 64 (35.6) 80 (44.4) 11 (6.1) 25 (13.9)
Saito, 1990 [80] Japan NR 253 49 (19.4) 136 (53.8) 2 (0.8) 66 (26.1)
Kiyosawa, 1990 [17] Japan 1958–89 83 19 (22.9) 51 (61.4) 10 (12.0) 3 (3.6)
Hassan, 2001 [81] Egypt 1995–96 33 5 (15.2) 25 (75.8) NR NR
Kew, 1990 [82] South Africa NR 380 137 (36.1) 63 (16.6) 47 (12.4) 127 (33.4)
Yu, 1990 [83] USA 1984–89 58 22 (37.9) 36 (62.1) NR NR
Di Bisceglie, 1991 [84] USA 1987–88 99 7 (7) 12 (12) 1 (1) 79 (79)
Hadziyannis, 1995 [85] Greece 1991–92 65 33 (50.8) 5 (7.6) 3 (4.5) 23 (38.3)
Colombo, 1989 [86] Italy 1975–88 132 19 (14.4) 64 (48.5) 22 (16.7) 27 (20.5)
Levrero, 1991 [87] Italy 1980–88 167 38 (22.8) 82 (49.1) 15 (9.0) 32 (19.2)
Simonetti, 1992 [88] Italy 1982–88 212 15 (7.1) 133 (62.7) 18 (8.5) 46 (21.7)
Donato, 1997 [72] Italy 1995–96 172 37 (21.5) 65 (37.8) 4 (2.3) 66 (38.4)
Stroffolini, 1998 [89] Italy 1996–97 1083 125 (11.5) 771 (71.2) 55 (5.1) 132 (12.2)
Bruix, 1989 [90] Spain NR 96 4 (4.2) 67 (69.8) 5 (5.2) 20 (20.8)
Nalpas, 1991 [91] France 1982–89 55 3 (5.5) 28 (50.9) 9 (16.3) 15 (27.3)
Van Roey, 2000 [92] Belgium 90s 154 37 (24.0) 62 (40.0) NR 55 (36.0)
Haydon, 1997 [93] UK 1985–94 80 13 (16.3) 22 (27.5) 2 (2.5) 43 (53.8)
NR: not reported; Bold: predominant cause
In the Far East and sub-Saharan Africa, where HBV is highly endemic, HBV is the main cause of HCC.
In areas with an intermediate rate of liver tumors such as Southern Europe, Egypt and Japan, HCV is the predominant cause of HCC. Here HCC is mostly discovered at an older age in patients with longstanding cirrhosis due to HCV.
In regions with a low incidence of HCC such as Northern Europe and the United States, HCC related to HCV or HBV infection are found in a minority of cases and the tumor is often related to other factors such as alcoholic liver disease. In these low endemic areas, HCC is usually discovered at an older age in patients with longstanding cirrhosis due to alcohol abuse [72]. In France, ethanol is still the leading cause of cirrhosis and was responsible for 60% of all HCC causes during the last decade [8].
Time trends in the incidence of HCC
An important epidemiological fact is the rising incidence of HCC in developed countries during the last two decades [79,89,95,99](Table 2).
Table 2 Time trends on the incidence of HCC in the world
Author [reference] Country Number/100,000 era 1 Number/100,000 era 2
El Serag, 1999 [95] USA 1976–80: 1.4 1991–95: 2.4
El Serag, 2000 [96] USA 1993–95: 2.3 1996–98: 7.0
Benhamiche, 1998 [97] (men) France 1976–79: 7.5 1992–95: 10.2
Stroffolini, 1998 [89] Italy 1969: 4.8 1994: 10.9
Law, 2000 [98] (men) Australia 1983–85: 2.1 1995–96: 4.0
Nishioka, 1991 [79] Japan 1968–77: 9.5 1984–85: 16.0
Yoshizawa, 2002 [99] Japan 1980: ca 10 2000: ca 40
In Japan, the HCC-related mortality rate has sharply increased since 1975 from 10/100,000 to almost 40/100,000 in 2000 [99]. An analysis of the Shinshu University Hospital (Japan) showed a change in etiology of the HCC [100]. Whereas in the 1971–1980 decade, hepatitis B was the predominant cause of HCC, in the 1991–1995 period hepatitis C was largely predominant (Table 3). However, the total numbers of yearly deaths because of HCC in HBsAg carriers' stays constant, approximately 10% in the survey conducted in 1995. The rapid increase of mortality due to HCC in Japan is mainly attributable (ca 80%) to persistent infection with HCV [99]. The hepatitis C epidemic in Japan originated due to intravenous drug use by the young generation after World War II during the late 40s and early 50s. It spread in the general population due to remunerated blood donors. Abrogation of paid blood donation in 1968, exclusion of blood units contaminated with HBV in 1973 and HCV in 1989 decreased the risk of posttransfusion hepatitis from > 50% in the 60s to almost zero at present. The incidence of HCV in Japan is decreasing. As the interval between the time of the initial infection with the hepatitis C virus and the development of HCC is 30 years [79], the growing incidence of HCC in Japan is expected to reach a plateau around the year 2015, and then to decrease [99].
Table 3 Changing causes of HCC in Japan, 1971–95
Author [reference] Era Sample size HBsAg + (%) Anti-HCV + (%) HBsAg/anti HCV + (%) Other (%)
Kiyosawa, 1992 [100] 1971–80 112 60 (54%) 38 (34%) 5 (4%) 9 (8%)
1981–90 267 82 (31%) 159 (59%) 4 (2%) 22 (8%)
1991–95 162 21 (13%) 126 (78%) 5 (3%) 10 (6%)
Bold: predominant cause
Also in Italy the mortality rate of HCC is rising [89] from 4.8/100,000 in 1969 to 10.9/100,000 in 1994, reflecting the large cohort of subjects infected with HCV through iatrogenic route during the 50s and 60s when glass syringes were commonly used for medical treatment. Likewise in Australia, France and the United States of America (US) the HCC mortality is increasing, most probably because people infected with HCV have grown old and reach the cancer-bearing age [95-98]. In the US, an increase of about 80% in the incidence of HCC over the past 20–30 years is described, it is estimated that approximately 15,000 new cases occur each year. Also in France the incidence of HCC is steadily and markedly increased, the estimated number being about 4,000 per year [101].
Although the prevalence of HCV is declining in developed countries because of the decline in incidence in the 90s, the number of persons infected for ≥ 20 years is expected to increase substantially before peaking in 2015 [102].
Analysis of long-term serial HCV samples from the US and Japan suggest that HCV was introduced into the US population around 100 years ago and widely disseminated in the 1960s. In contrast, HCV was introduced in Japan > 100 years ago and widely disseminated in the 1930s and 40s. The HCV genotype 1b population in Japan started to decrease around 1995 whereas HCV genotype 1a in the US is still growing exponentially. It is predicted that an increased HCC prevalence will occur in the US over the next two to three decades [103].
The reasons advocated for explaining the increased incidence of HCC are the increased rate of HCV infection and an improvement of the clinical management of cirrhotic patients. Enhancing the survival of patients with advanced cirrhosis leads to an increased incidence of HCC. In fact, a decade ago, most of the deaths in cirrhotic patients were due to digestive hemorrhage or bacterial infections, two conditions that are now efficiently prevented and cured [104]. Therefore, HCC has become the leading cause of death in patients with cirrhosis.
Screening tests for HCC in patients with chronic viral hepatitis
Despite knowledge of the risk factors for HCC, screening of HCC is controversial, as there have been no randomized controlled studies demonstrating the efficacy of screening for HCC. As HCC mostly occurs in patients with cirrhosis, or at least advanced fibrosis, most studies have been performed in these patients at risk. The most frequently used tests have been serum alfa-fetoprotein (AFP) and hepatic ultrasound (US).
There is one non randomized prospective cohort study suggesting that HCC was detected earlier and was more often resectable in patients who had twice yearly screening with serum AFP and hepatic US than in patients who had usual care [105].
Twenty-four studies, which included patients with chronic hepatitis B or C or both, addressed the sensitivities and specificities of screening tests [106].
Serum AFP for detection of HCC was evaluated in 19 studies. They were relatively consistent in showing that the sensitivity of serum AFP for detecting HCC increases from very low levels to moderately high levels of 60 to 80% as the threshold value decreased from 400 to 10 ng/mL, with corresponding specificity decreasing from 100 to 70–90%. A threshold between 10 and 19 ng/mL seems most appropriate as sensitivity usually is moderately high (45 to 100%), with a specificity of 70 to 90%. It has been shown that AFP is not always specific for HCC and titers can increase with flares of active hepatitis [107].
Seven studies evaluated screening with US, reporting high specificity of 95–100%, but variable sensitivity, varying from 11–99% [94].
A surveillance study combining US and AFP in 1,125 patients with HCV, HBV or both, reported a sensitivity of 100% when using a serum AFP > 10 ng/mL together with US, compared with a sensitivity of 75% using only AFP > 10 ng/mL and a sensitivity of 87% when using US alone [108].
Computed tomography and magnetic resonance imaging have a high sensitivity and specificity in detecting HCC, but are too expensive to be used in surveillance [1].
The surveillance intervals studied varied from 3 to 12 months. In a study of patients with hepatitis B, the most rapidly growing tumor increased from 1 to 3 cm in 5 months [109]. The ideal time for re-screening has not been identified. Some investigators suggest a 4–5 month interval, others have suggested that a 6-month interval may be most appropriate [109,110]. It is suggested that in case of concomitant HBV and HCV infection serum AFP levels should be obtained every 3 months, and that persistent AFP levels should prompt an aggressive imaging search for HCC [61].
It can be concluded that screening patients with advanced chronic hepatitis B or C with AFP and US may improve detection of HCC, but further studies are needed whether screening improves clinical outcomes.
Pathogenesis of hepatitis B and C-induced hepatocellular carcinoma
Introduction
Epidemiologic data indicate that chronic hepatitis B and C are independent risk factors for development of HCC [7,16]. Furthermore, animal models confirm the oncogenic potential of HBV and HCV in the liver: transgenic mice for hepatitis B and C [110,111], and natural models such as the woodchuck infected with the woodchuck hepatitis virus, a hepadnavirus closely related to the HBV [112].
Carcinogenesis is believed to be a multistage process, occurring through a sequence of steps termed initiation, promotion and progression. This process evolves over several or many years. Tumor initiation begins in cells through mutations induced by exposure to carcinogens. DNA changes, maintained during successive cell divisions, activation of oncogenes and inactivation of suppressor genes lead to dysregulation of the cell division and to immortalization [113]. Tumor-initiated cells have a decreased responsiveness to both intercellular and intracellular signals that maintain normal cellular architecture and regulate homeostatic growth. Tumor promotion results in a further selective clonal expansion of initiated cells. During tumor progression, pre-malignant cells continue to develop progressive phenotypic changes and genomic instability (dysplasia), culminating as overt carcinoma [115].
More than 80% of HCC originate in cirrhotic livers. Macronodules (macroregenerative nodules and adenomatous hyperplasia), irregular hepatocyte regeneration, and some hyperplastic foci are considered as precancerous [116-119]. Large cell dysplasia and small cell dysplasia are considered to be risk factors for development of HCC [120-122].
HBV and HCV can be implicated in the development of HCC in an indirect way, through induction of inflammation, necrosis and chronic hepatocellular regeneration, or directly by means of viral proteins or, in the case of HBV, by creating insertional mutations by integration in the genome of the hepatocyte.
Indirect carcinogenicity of HBV and HCV
In most patients with chronic hepatitis B and/or C the occurrence of HCC is preceded by a process of longstanding inflammation. It is probable that malignant transformation is related to continuous or recurring cycles of hepatocyte necrosis and regeneration [123]. The resulting accelerated cell turnover rate may act as a tumor promotor by increasing the probability of spontaneous mutations or damage to DNA by exogenous factors. The accelerated rate of cell division leaves less time for altered DNA to be repaired before the cell divides again, resulting in transmission of altered DNA to the daughter cells. In this way a series of mutations may accumulate in individual cells over time. This process can lead to focal uncontrolled liver cell growth and eventual malignant cell transformation [115,124]. Another mechanism of induction of malignant transformation is the generation of mutagenic reactive oxygen species as a result of the inflammatory process, such as nitric oxide (NO), superoxide anion (O2-), hydroxyl radical (OH•) and hydrogen peroxide (H2O2) [124].
Evidence for a causal role for chronic necro-inflammation is provided by transgenic mice into which HBV preS/S genes have been introduced. These mice overproduce pre S1 protein that accumulates in the endoplasmatic reticulum of hepatocytes, producing severe and prolonged injury to these cells, initiating a response characterized by inflammation, regenerative hyperplasia and transcriptional deregulation that progresses ultimately to neoplasia [125].
Patterns of gene expression in cirrhosis and hepatocellular carcinoma have recently been shown to be of value in predicting prognosis. Kim et al could identify, using the complementary DNA microarray, a 273-gene signature that distinguished high risk types of cirrhosis (hepatitis B, hepatitis C, hereditary hemochromatosis) from low risk types (autoimmune hepatitis, PBC, alcoholic liver diseases) [126]. The same 273-gene signature was present in samples from patients with proven HCC. A subset of 30 genes was most significantly altered in both the high risk types of cirrhosis and the HCC patients. The TACSTD1, a gene associated with HCC development in other studies, is a lead gene in this gene signature. Lee et al could identify a limited number of genes that accurately predicted survival in a series of 91 HCC patients [127]. The genes involved are implicated in cell proliferation and apoptosis, but also in ubiquitination and histone modification. Delpuech et al identified distinct patterns of gene expression according to the viral aetiology [128]. Finally, Hann et al could demonstrate the presence of antibodies to differentially expressed genes in hepatitis B and C, and this appeared to be linked with decreased survival [129]. These discoveries not only increase our insight in hepatocarcinogenesis, but may ultimately lead to the development of clinically valuable preneoplastic and prognostic blood markers.
Direct carcinogenicity of HBV and HCV
Hepatitis B
A significant proportion of HBV-related HCCs arise in an otherwise normal liver, implicating that the virus can also be directly oncogenic [124].
It has been demonstrated that HBV integrates into the DNA of the host cells. This integration may dysregulate the control mechanisms on the cell cycle by chromosomal abnormalities, production of viral proteins or alteration of human genes and proto-oncogenes. It is, however, controversial whether viral integration plays an important role in the process leading to development of HCC. The hepadnaviral integration process appears to involve recombination mechanisms that do not preserve the viral genome sequence. Thus it is impossible for the viral integrant to function as a template for subsequent virus replication. Several studies suggest that DNA integration sites are at random and that integration occurs at random times during the course of a chronic viral infection [130,131]. HBV integration can be present in chronically infected liver tissue without evidence of HCC [132]. Non-neoplastic hepatocytes may have a similar pattern of rearrangement of viral sequences following integration into human DNA.
Chromosomal DNA instability
Several studies have shown that HBV DNA integration enhances chromosomal instability. In many hepatic tumors large inverted duplication insertions, translocations and micro- and macrochromosomal deletions have been associated with HBV insertion [133-136]. These changes can result in loss of important cellular genes, sometimes involving tumor-suppressor genes and other genes involved in the regulation of regeneration and growth processes.
Trans-activation of cellular genes
HBV DNA may induce malignant transformation in another way.
Mammalian hepadnaviruses contain a gene (the HBX gene), of which the protein (HBX protein) can trans-activate several cellular promotors and upregulate their expression of different cellular and viral genes [137,138]. Integrated HBX, even when truncated, frequently encodes functionally active trans-activator proteins [139]. This protein has been shown to transform mouse fetal hepatocytes into a full malignant phenotype [140]. There are studies in transgenic mice with the HBX gene that developed multifocal areas of altered hepatocytes, adenomas and HCCs [110].
In contrast to mammalian hepadnaviruses associated with HCC, avian hepadnaviruses such as the duck hepatitis virus or heron hepatitis virus, lack the HBX gene and are not associated with HCC [123].
A gene that may be affected by the HBX gene is the p53 tumor suppression gene. This gene has been shown to play an important role in hepatocarcinogenesis. It is considered to negatively regulate the cell cycle. The HBX protein has been shown to complex p53 protein and to inhibit its function [141,142]. In a transgenic mouse model it was shown that HCC development correlates with p53 binding to HBX [143].
Oncogenes
It has been proposed that HBV acts as an insertion mutagen by integrating into the host genome and activating the cellular proto-oncogenes c-myc, ras and c-fos [144].
The preS2/S gene is integrated in most HCCs associated with HBV. When 3'-truncated it generates a truncated protein that is oncogenic by trans-activating proto-oncogenes c-myc and c-fos [145].
Growth factors
Growth factors and their receptors function as positive or negative modulators of cell proliferation and differentiation. Insulin-like growth factor-II and transforming growth factor-β expression correlate with HBX protein expression in animal models [146,147], suggesting trans-activation of these growth factors facilitating tumor formation.
Role of PreS mutations
PreS deletion mutants accelerate the storage of large envelope proteins in hepatocyte cytoplasm, which could induce cytotoxic effects toward the development of end-stage liver disease [148]. The accumulation of large envelope protein can activate cellular promoters by inducing endoplasmic reticulum stress [149]. Furthermore, pre-S1 sequences can stimulate the transcription of transforming growth factor α (TGFα). Coexpression of TGFα and HBsAg could accelerate hepatocellular carcinogenesis by stimulation of hepatocyte proliferation [150].
Allelic loss of chromosome 4q
Allelic loss of chromosome 4q is one of the most frequent genetic aberrations found in HCC. It was found to be associated with HBV-related hepatocarcinogenesis, probably by inactivation of a putative tumor suppressor gene included in it [151].
Hepatitis C
In contrast to HBV, HCV is an RNA virus that lacks a reverse-transcriptase enzyme and cannot integrate into the host genome. Thus, insertional mutagenesis can be excluded as a pathogenic mechanism for the development of HCC associated with chronic HCV infection. The molecular pathogenetic mechanisms by which HCV contributes to cell transformation remain unclear.
One possibility is that the development of HCC is simply related to chronic necro-inflammatory liver disease. Overall, 97% of patients with HCV markers and HCC have cirrhosis [152,153], and most of the remainder develop HCC in the presence of chronic hepatitis.
An alternative mechanism of HCV-induced hepatocarcinogenesis may be that HCV has a direct oncogenic action. Viral replication might cause inappropriate expression of two growth factors that may be implicated in hepatic carcinogenesis: transforming growth factor-α and insulin-like growth factor II [154,155].
The non-structural HCV protein NS3 has both protease and helicase activity. HCV may therefore induce genomic instability and favor mutations through its helicase activity [156]. The protein also has an activity similar to protein kinase A, and could disturb cellular homeostasis [157].
The HCV envelope protein E2 and the non-structural protein NS5A inhibit RNA-dependent protein kinase, key mediator of the antiviral, antiproliferative and anti-oncogenic effect of interferon [158-160].
The HCV core protein has characteristics that imply that this protein could function as a gene-regulator [161,162]. The presence of the protein in transgenic mice can induce HCC [111]. After mutation, the HCV core protein can also inhibit tumor suppressor genes such as p53, as has been demonstrated in hepatic oncogenesis [163-165]. It has recently been shown that the HCV core protein induces nuclear factor κB (NF-κB), thereby suppressing TNF-α-induced apoptosis [166]. This anti-apoptosis may be a mechanism by which HCV leads to viral persistence and possibly to hepatocarcinogenesis.
Prevention of hepatocellular carcinoma caused by viral hepatitis
Primary prevention
The most effective tool to prevent HCC is avoidance of the risk factors such as viral infection by HBV or HCV. Any action diminishing the potential transmission of contaminated blood products (uncontrolled blood transfusion, needle sharing, invasive procedures without proper health standards) will decrease the likelihood of viral spread.
The major advance has come from the availability of an effective vaccine that protects against HBV.
In 1969, Taiwan was an hyperendemic area of HBV infection with a high rate of HBsAg positivity, 19% of the population being infected before the fourth decade of life. In 1976, HBsAg prevalence was > 80% in HCC in Taiwan [167]. In 1984 a program to control cirrhosis and HCC began. All neonates born to HBsAg positive mothers were given hepatitis B vaccine in order to counter perinatal infection. In 1986 all neonates were included in the program. As a consequence, there was a decrease in HBsAg positivity in six-year-olds from 10.6% in 1983–1984 to 0.8% in 1993–1994. There was a parallel decline in incidence of childhood HCC (6–14 years old), in the cohort born between 1980 and 1984. The incidence of liver cancer in children between 6 and 14 years old decreased to zero for children born in 1986 and 1987 [168]. The decline of HCC in children after universal vaccination can be considered as an early indicator of the effectiveness of vaccination in reducing the rate of HCC. Since the incidence of HCC in Taiwan peaks in the sixth decade of life, it may take 40 years or longer to see an overall decrease in the rate of HCC as a result of the vaccination program. Vaccination against HBV should become a health priority together with the promotion of adequate health standards.
Unfortunately, there is no vaccine against HCV. Up to now, the only effective method to prevent its transmission is the avoidance of contamination with infective blood products.
Prevention of HCC in patients with previously acquired risk
Introduction
Chronic viral carriage is one of the main risk factors for the development of HCC. Effective antiviral treatments have been developed in recent years and this has changed the management of viral infection.
Interferon-alfa is still considered the reference therapy for HBeAg positive chronic hepatitis B. However, its efficacy is limited, with seroconversion from anti-HBe negative to anti-HBe positive in up to 40%. Only <10% of patients become HBsAg negative [169]. Other possible treatments are antiviral drugs such as lamivudine and adefovir dipivoxil [12].
For the treatment of chronic hepatitis C, interferon-alfa monotherapy yielded only limited response. Combination with ribavirin led to a significant increase in sustained viral response to about 40% in treatment-naïve patients [170,171]. Recently, the combination of peginterferon-alfa and ribavirin improved the sustained viral response rate to nearly 60% in treatment-naïve patients [172,173], and is now considered the reference treatment.
It is under debate whether interferon-alfa-based treatments are effective in declining the incidence of HCC in chronic hepatitis B and C.
Anti-oncogenic effects of interferon-alfa
HCC prevention by interferon-alfa might be the result of several direct or indirect mechanisms. Interferon has an antiproliferative and pro-apoptotic effect [174]. Interferon inhibits the expression of the c-myc oncogene and induces the expression of anti-proliferative factors and tumor suppressor genes [175-177]. In experimental animal models, the anti-neoplastic potential of interferon was demonstrated in already established tumors. In a transgenic mouse model it was demonstrated that early and prolonged administration of interferon diminished the severity of preneoplastic lesions and slowed down the development of HCC [178]. Interferon-alfa also could indirectly reduce the oncogenic risk by inhibition of synthesis of viral proteins which potentially dysregulate the cell cycle, and by enhancing the immune system eliminating not only infected hepatocytes but also initiated or fully malignant cells. Furthermore, interferon-alfa has an antifibrotic and anti-angiogenetic effect, which could also have an influence on tumor development [179].
Interferon and antiviral treatment
Noncirrhotics
In patients with chronic hepatitis B, clearance of the HBeAg after treatment with interferon-alfa is associated with improved clinical outcome in terms of survival and development of complications of cirrhosis [180]. Another study confirmed these results and showed a reduction of incidence of HCC in the responders [181]. As most of these patients were non-cirrhotics at entry of the study, the prophylactic effect of interferon on development of HCC can be explained by prevention of cirrhosis development. In Chinese patients with chronic hepatitis B infection, however, interferon-alfa was of no long-term benefit in inducing HBeAg conversion, or in the prevention of HCC and other cirrhosis-related complications [182].
Cirrhotics
Seven studies investigated the possible effect of interferon treatment on development of HCC in patients with already established cirrhosis [183-189] (Table 4). A meta-analysis was performed on these studies [190]. Interferon seemingly decreased the rate of HCC in all trials, while a significant difference was observed in 2 studies [183,186]. Virologic response was strongly associated with reduced risk for HCC in the studies of Oon [183] and Mazzella [184], suggesting that arrest of viral replication is a critical factor. Subgroup analysis in relation to ethnic origin of patients (European, Oriental) showed no preventive effect of interferon on the development of HCC in the European patients [190].
Table 4 Studies of treatment with interferon-α for prevention of HCC in patients with hepatitis B-related cirrhosis
Author [reference] Country Type of study Interferon regimen (duration in weeks) Follow-up (range) in months Sample size Rate of HCC (n/n) Significance
Oon, 1992 [183] Singapore NRCT, P 10 MU daily, 10 days/month (12) 12 (12–60) T 600
C 180 T: 0/600 (0%)
C: 10/180 (5.6%) Significant
Mazzella, 1996 [184] Italy NRCT, P 10 MU tiw (26) 49 (12–119) T 34
C 28 T: 2/34 (5.9%)
C: 4/28 (14.3%) Not significant
Fattovich, 1997 [185] Europe NRCT, P ≥ 300 MU (12–52) 84 (80–92) T 40
C 50 T: 3/40 (7.5%)
C: 4/50 (8.0%) Not significant
Ikeda, 1998 [186] Japan NRCT, P 12 MU/wk (26) 84 (6–168) T 94
C 219 T: 10/94 (10.6%)
C: 51/219 (23.3%) Significant
IHCSG, 1998 [187] Argentina, Germany, Italy, Saudi Arabia NRCT, P 9–30 MU/wk for 3–30 months (36–250) T 49
C 97 T: 8/49 (16.3%) C: 18/97 (18.6%) Not significant
Benvegnù, 1998 [188] Italy NRCT, P 6–10 MU (20–26) 72 T 10
C 18 T: 0/10 (0%)
C: 4/18 (22.2%) Not significant
Di Marco, 1999 [189] Italy NRCT, P 655 MU 93 (6–180) T 26
C 60 T: 2/26 (7.7%)
C: 6/60 (10%) NR
NRCT: non-randomized controlled trial
P: prospective
T: treated
C: controls
MU: million units
NR: not reported
It should be noted that the studies are very heterogeneous and that none of them were randomized controlled trials, so that the results should be interpreted with caution.
A recent study showed a significant reduction of the risk of HCC in patients with chronic hepatitis B and advanced fibrosis or cirrhosis, treated with lamivudine for a maximum of five years, compared to placebo [191].
Interferon treatment in HCV patients and HCC prevention
Noncirrhotics
Three studies assessed whether interferon treatment prevents the development of HCC in noncirrhotic patients with chronic hepatitis C [192-194] comprising 3,798 noncirrhotic patients treated with interferon-alfa monotherapy. Pooled together, the incidence of HCC was 60/2,532 (2.37%) in sustained virological responders and 76/1,266 (5.29%) in nonresponders. In a study of 291 noncirrhotic patients with chronic hepatitis C who were nonresponders to interferon therapy and followed for 6–117 months after therapy, the incidence of HCC was significantly lower in patients who received > 500 MU of interferon. Patients with a transient response (i.e. relapse after end of treatment) had a significant lower rate of HCC development (4/166 = 2.4%) than nonresponders (12/125 = 9.6%) [195].
This anti-oncogenic benefit can presumably be explained by an arrest or slowing down of the cirrhogenic process.
Cirrhotics
The findings of 13 studies of interferon treatment and development of HCC in HCV-infected patients with compensated cirrhosis are summarized in Table 5[45,184-186,194,196-204]. Only 3 studies were randomized [199,201,202,204], the remainders were observational cohort studies. Statistical combination of data is not possible because of different definitions of response (biochemical, virological), different dose schedules for interferon and different duration of follow-up. All studies showed a lower risk for development of HCC in the interferon-treated patients, suggesting that interferon may prevent HCC in compensated cirrhosis caused by hepatitis C. The overall result was largely influenced by three Japanese studies [194,198,201,202], which had the highest incidence of HCC in untreated patients (5–6% per year). This may be explained by intensiveness of the screening programs, but also by genetic, environmental or viral factors. Four European studies failed to document a significant reduction in risk of developing HCC [45,196,199]. In the studies of Fattovich et al [196] and Bruno et al [45], interferon-alfa treatment showed a decrease in incidence of HCC in univariate analysis. However, this was not present in multivariate analysis. In the study of Fattovich [196], a very low natural incidence of HCC was observed, rendering difficult to show a significant decrease. The prospective randomized controlled trial of Valla et al [199] also failed to show a significant effect of interferon treatment on the development of HCC. However, the number of patients in this study was limited and the follow-up relatively short. Also a recently published randomized controlled study from Italy comprising 51 interferon-treated and 71 untreated patients with compensated hepatitis C-cirrhosis, failed to demonstrate any reduced risk in development of HCC after a mean follow-up of 96.5 months [204].
Table 5 Studies on treatment with interferon-α for prevention of HCC in patients with HCV-related cirrhosis
Author [reference] Country Type of study Interferon regimen (duration in weeks) Follow-up (range) in months Sample size Rate of HCC (n/n) Significance
Mazzella, 1996 [184] Italy NRCT, P 3 MU tiw (52) 32 (12–71) T 193
C 91 T: 5/193 (2.6%)
C: 9/91 (9.9%) Significant
Fattovich, 1997 [196] Europe NRCT, P ≥ 200 MU 60 (1–153) T 193
C 136 T: 7/193 (3.6%)
C: 16/136 (11.8%) Not significant
Bruno, 1997 [45] Italy NRCT, P 6 MU tiw (26) 68 (60–84) T 82
C 81 T: 6/82 (7.3%)
C: 14/81 (17.3%) Not significant
Serfaty, 1998 [197] France NRCT, P 3 MU tiw (48) 40 (6–72) T 59
C 44 T: 2/59 (3.4%)
C: 9/44 (20.1%) Significant
IHCSG, 1998 [187] Argentina, Germany, Italy, Saudi Arabia NRCT, R 9–30 MU/wk (3–30 months) (36–250) T 232
C 259 T: 2/232 (0.9%)
C: 48/259 (18.5%) Significant
Imai, 1998 [198] Japan NRCT, R 480 MU (26) 48 (3–65) T 32
C 20 T: 8/32 (25%)
C: 7/20 (35%) Significant
Benvegnù, 1998 [188] Italy NRCT, P 3–6 MU tiw (26–52) 72 T 75
C 77 T: 4/75 (5.3%)
C: 20/77 (26.0%) Significant
Valla, 1999 [199] France RCT 3 MU TIW (48) 40 (37–53) T 47
C 52 T: 5/47 (10.6%)
C: 9/52 (17.3%) Not significant
Yoshida, 1999 [194] Japan NRCT, R 480 MU (23) 52 T 230
C 107 T: 33/230 (14.3%)
C: 29/107 (27.1%) NR
Okanoue, 1999 [200] Japan NRCT, R 3–10 MU qd or tiw (16–24) 1–7 years T 40
C 55 T: 7/40 (17.5%)
C: 22/55 (40.0%) NR
Nishiguchi, 1995/2001 [201,202] Japan RCT 6 MU tiw (12–24) 104 (31–110) T 45
C 45 T: 12/45 (26.7%)
C: 33/45 (73.3%) Significant
Gramenzi, 2001 [203] Italy RCT, P 741 MU 72 T 72
C 72 T: 6/72 (8.3%)
C: 19/72 (26.4%) Significant
Testino, 2002 [204] Italy RCT 3 MU tiw (52) 96.5 ± 18 T 51
C 71 T: 15.51 (29.4%)
C: 24/71 (33.8%) Not significant
NRCT: non-randomized controlled trial
RCT: randomized controlled trial
P: prospective
R: retrospective
NR: not reported
T: treated
C: controls
MU: million units
In most studies, virological and/or biochemical response are associated with a lower risk of development of HCC, which is less clear in nonresponders. In the study of Imai et al. [198], patients with sustained biochemical response after interferon therapy were at low risk for development of HCC (risk ratio versus controls 0.06; 0.95 in nonresponders). Also in the study of Mazzella [184], a statistically significant effect of interferon treatment was demonstrated when biochemical responders were compared with controls but not when compared with nonresponders. In the study of Benvegnù et al [188], the beneficial effect of interferon treatment on development of HCC was independent of the type of response. In the study of Yoshida et al [194] the risk for HCC was reduced especially among patients with sustained virological but also merely biochemical response that tested positive for HCV RNA. Okanoue et al [200] studied 1,148 patients with chronic hepatitis C treated with interferon-alfa, 40 of them having cirrhosis (fibrosis stage F4). They were followed for 1–7 years after therapy. The cumulative incidence of HCC was significantly decreased in sustained biochemical responders, compared to nonresponders and transient responders, in patients with stage F2 fibrosis, but not in the more advanced stages F3 and F4. In the study of Testino et al [204] HCC did also develop in sustained biochemical responders. Tanaka et al [205], however, demonstrated in 55 patients with HCV-cirrhosis that long-term administration of interferon prevented HCC in those with biochemical and virological response, whereas HCC only appeared in nonresponders.
The mechanisms by which an interferon treatment might reduce the risk of HCC development in cirrhosis caused by HCV independent of virological response remains speculative. Maintenance of serum transaminases at low levels may protect against the development of HCC as hepatocyte necrosis, cell damage and increase in hepatocyte replication result in increased DNA damage, influencing hepatocarcinogenesis. Other possible mechanisms for prevention of HCC are the direct and indirect effects of interferon. It is, however, perplexing that only 6 or 12 months of therapy can produce this benefit without virological response. Because of potential biases in the published trials it is premature to advocate the use of interferon as established therapy in HCV infected patients with cirrhosis to prevent HCC. Prospective randomized controlled trials should reproduce the findings in large numbers of patients before a definitive conclusion on the long term effects of interferon in HCV cirrhosis can be established.
It must also be realized that a sustained virological response to interferon-alfa monotherapy can be obtained only in 0–8% of patients with cirrhosis [206-208]. New treatments are now available for chronic hepatitis C, which are more performant in difficultly to treat cases as patients with cirrhosis. The combination of interferon-alfa and ribavirin results in a sustained virologic response in up to 25% of cirrhotics due to hepatitis C [207]. A sustained virologic response of 32% was reported after peginterferon-alfa-2a monotherapy [207] and of 43% after combination of peginterferon-alfa2a and ribavirin [173]. It should be investigated in prospective trials, taking into account the sustained virological and biochemical responses if these more performant treatment regimens will also influence favorably the incidence of HCC, as no data on the long-term effects of these treatments are available up to now.
Secondary prevention
A few sudies focus on the possible role of intereron in the secondary prevention of HCC recurrence in patients with chronic hepatitis B and C after curative resection or ablation.
Ikeda et al [209] showed that interferon prevented HCC recurrence after complete resection or ablation of the primary tumor depending on the clearance of HCV viremia. Kubo et al [210] reported a decreased recurrence after surgical resection independent of clearance of HCV or normalization of serum ALT. Another study demonstrated prevention of HCC recurrence after medical ablation therapy for primary tumors in hepatitis B but not in hepatitis C patients by the use of interferon-alfa [211].
Conclusions
Chronic hepatitis B and C, mostly in the cirrhotic stage, are
responsible for the majority of the hepatocellular carcinomas worldwide.
The rising incidence in HCC in developed countries during the last two
decades is due to the increasing rate of hepatitis C infection and
improvement of the clinical management of cirrhosis.
Vaccination against hepatitis B seems to protect against the development
of HCC.
In patients with chronic hepatitis B or C, interferon alpha treatment in
a noncirrhotic stage is protective for HCC development in responders,
probably by prevention of cirrhosis development. When cirrhosis is
already present, the protective affect is less clear. Further
prospective long-term studies should be performed on the new treatments
for chronic hepatitis B and C. Some studies also suggested a favourable
effect of interferon alpha in the prevention of HCC recurrence in
patients with chronic hepatitis B and C after curative resection or
ablation.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
PPM participated in the literature search and was responsible for
the redaction of the paper.
SMF participated in the redaction of the manuscript and critical
review of the paper.
JLV participated in the literature search and finalizing of the
lay-out of the paper.
==== Refs
Bruix J Sherman M Llovet JM Beaugrand M Lencioni R Burroughs AK Christensen E Pagliaro L Colombo M Rodes J EASL Panel of Experts on HCC Clinical management of hepatocellular carcinoma. Conclusions of the Barcelona-2000 EASL conference J Hepatol 2001 35 421 430 11592607 10.1016/S0168-8278(01)00130-1
Llovet JM Beaugrand M Hepatocellular carcinoma: present status and future prospects J Hepatol 2003 38 136 149 12547401 10.1016/S0168-8278(02)00432-4
Bosch FX Ribes J Borras J Epidemiology of primary liver cancer Semin Liver Dis 1999 19 271 285 10518307
Zaman SN Melia WM Johnson RD Portmann BC Johnson PJ Williams R Risk factors in development of hepatocellular carcinoma in cirrhosis: prospective study of 613 patients Lancet 1985 1 1357 1360 2861313 10.1016/S0140-6736(85)91785-4
Poynard T Aubert A Lazizi Y Bedossa P Hamelin B Terris B Naveau S Dubreuil P Pillot J Chaput JC Independent risk factors for hepatocellular carcinoma in French drinkers Hepatology 1991 13 896 901 1851493 10.1016/0270-9139(91)90260-3
Colombo M de Franchis R Del Ninno E Sangiovanni A De Fazio C Tommasini M Donato MF Piva A Di Carlo V Dioguardi N Hepatocellular carcinoma in Italian patients with cirrhosis N Engl J Med 1991 325 675 680 1651452
Tsukuma H Hiyama T Tanaka S Nakao M Yabuuchi T Kitamura T Nakanishi K Fujimoto I Inoue A Yamazaki H Kawashima T Risk factors for hepatocellular carcinoma among patients with chronic liver disease N Engl J Med 1993 328 1797 1801 7684822 10.1056/NEJM199306243282501
Chevret S Trinchet JC Mathieu D Rached AA Beaugrand M Chastang C A new prognostic classification for predicting survival in patients with hepatocellular carcinoma J Hepatol 1999 31 133 141 10424293 10.1016/S0168-8278(99)80173-1
International Agency for Research on Cancer Hepatitis Viruses IARC Monographs on the Evaluation of Carcinogenic Risks to Humans 1994 59 Lyon: IARC
Kew MC Dusheiko GM Hadziyannis SJ Paterson A Does Delta infection play a part in the pathogenesis of hepatitis B virus related hepatocellular carcinoma? Br Med J 1984 288 1727 6329398
Verme G Brunetto MR Oliveri F Baldi M Forzani B Piantino P Ponzetto A Bonino F Role of hepatitis delta virus infection in hepatocellular carcinoma Dig Dis Sci 1991 36 1134 1136 1650690 10.1007/BF01297460
EASL Jury EASL International Consensus Conference on Hepatitis B. 13–14 September, 2002: Geneva, Switzerland. Consensus statement (short version) J Hepatol 2003 38 533 540 12663250
Yotsuyanagi H Yasuda K Iino S Moriya K Shintani Y Fujie H Tsutsumi T Kimura S Koike K Persistent viremia after recovery from self-limited acute hepatitis B Hepatology 1998 27 1377 1382 9581694 10.1002/hep.510270526
Okada K Kamiyama I Inomata M Imai M Miyakawa Y e antigen and anti-e in the serum of asymptomatic carrier mothers as indicators of positive and negative transmission of hepatitis B virus to their infants N Engl J Med 1976 294 746 749 943694
Liaw YF Tai DI Chu CM Lin DY Sheen IS Chen TJ Pao CC Early detection of hepatocellular carcinoma in patients with chronic type B hepatitis. A prospective study Gastroenterology 1986 90 263 267 2416625
Beasley RP Hwang LY Lin CC Chien CS Hepatocellular carcinoma and hepatitis B virus. A prospective study of 22707 men in Taiwan Lancet 1981 2 1129 1133 6118576 10.1016/S0140-6736(81)90585-7
Kiyosawa K Sodeyama T Tanaka E Gibo Y Yoshizawa K Nakano Y Furuta S Akahane Y Nishioka K Purcell RH Alter HJ Interrelationship of blood transfusion, non-A, non-B hepatitis and hepatocellular carcinoma: analysis by detection of antibody to hepatitis C virus Hepatology 1990 12 671 675 2170265
Realdi G Fattovich G Hadziyannis S Schalm SW Almasio P Sanchez-Tapias J Christensen E Giustina G Noventa F Survival and prognostic factors in 366 patients with compensated cirrhosis type B: a multicenter study J Hepatol 1994 21 656 666 7814813 10.1016/S0168-8278(94)80115-0
Fattovich G Giustina G Schalm SW Hadziyannis S Sanchez-Tapias J Almasio P Christensen E Krogsgaard K Degos F Carneiro De Moura M Solinas A Noventa F Realdi G Occurrence of hepatocellular carcinoma and decompensation in western European patients with cirrhosis type B Hepatology 1995 21 77 82 7806171 10.1016/0270-9139(95)90411-5
Fattovich G Progression of hepatitis B and C to hepatocellular carcinoma in western countries Hepatogastroenterology 1998 45 1206 1213 9730376
Fattovich G Pantalena M Zagni I Realdi G Schalm SW Christensen E Effect of hepatitis B and C virus infections on the natural history of compensated cirrhosis: a cohort study of 297 patients Am J Gastroenterol 2002 97 2886 2895 12425564 10.1111/j.1572-0241.2002.07057.x
Sakuma K Saitoh N Kasai M Jitsukawa H Yoshino I Yamaguchi M Nobutomo K Yamumi M Tsuda F Komazawa T Relative risks of death due to liver disease among Japanese male adults having various statuses for hepatitis B s and e antigen/antibody in serum: a prospective study Hepatology 1988 8 1642 1646 3192178
Yang HI Lu SN Liaw YF You SL Sun CA Wang LY Hsiao CK Chen PJ Chen DS Chen CJ Taiwan Community-Based Cancer Screening Project Group Hepatitis B e antigen and the risk of hepatocellular carcinoma N Engl J Med 2002 347 168 174 12124405 10.1056/NEJMoa013215
Ohkubo K Kato Y Ichikawa T Kajiya Y Takeda Y Higashi S Hamasaki K Nakao K Nakata K Eguchi K Viral load is a significant prognostic factor for hepatitis B virus-associated hepatocellular carcinoma Cancer 2002 94 2663 2668 12173334 10.1002/cncr.10557
Yano Y Yamashita F Sumie S Ando E Fukumori K Kiyama M Oyama T Kuroki S Kato O Yamamoto H Tanaka M Sata M Clinical features of hepatocellular carcinoma seronegative for both HBsAg and anti-HCV antibody but positive for anti-HBc antibody in Japan Am J Gastroenterol 2002 97 156 161 11808941 10.1111/j.1572-0241.2002.05440.x
Okamoto H Tsuda F Sakugawa H Sastrosoewignjo RI Imai M Miyakawa Y Mayumi M Typing hepatitis B virus by homology in nucleotide sequence: comparison of surface antigen subtypes J Gen Virol 1988 69 2575 2583 3171552
Stuyver L De Gendt S Van Geyt C Zoulim F Fried M Schinazi RF Rossau R A new genotype of hepatitis B virus: complete genome and phylogenetic relatedness J Gen Virol 2000 81 67 74 10640543
Arauz-Ruiz P Norder H Robertson BH Magnius LO Genotype H: a new Amerindian genotype of hepatitis B virus revealed in Central America J Gen Virol 2002 83 2059 2073 12124470
Norder H Courouce AM Magnius LO Complete genomes, phylogenetic relatedness, and structural proteins of six strains of the hepatitis B virus, four of which represent two new genotypes Virology 1994 198 489 503 8291231 10.1006/viro.1994.1060
Kao JH Chen PJ Lai MY Chen DS Hepatitis B genotypes correlate with clinical outcomes in patients with chronic hepatitis B Gastroenterology 2000 118 554 559 10702206
Ding X Mizokami M Yao G Xu B Orito E Ueda R Nakanishi M Hepatitis B virus genotype distribution among chronic hepatitis B virus carriers in Shanghai, China Intervirology 2001 44 43 47 11223719 10.1159/000050029
Orito E Ichida T Sakugawa H Sata M Horiike N Hino K Okita K Okanoue T Iino S Tanaka E Suzuki K Watanabe H Hige S Mizokami M Geographic distribution of hepatitis B virus (HBV) genotype in patients with chronic HBV infection in Japan Hepatology 2001 34 590 594 11526547 10.1053/jhep.2001.27221
Chen JD Liu CJ Lee PH Chen PJ Lai MY Kao JH Chen DS Hepatitis B genotypes correlate with tumor recurrence after curative resection of hepatocellular carcinoma Clin Gastroenterol Hepatol 2004 2 64 71 15017634 10.1016/S1542-3565(03)00293-3
Kao JH Chen PJ Lai MY Chen DS Basal core promoter mutations of hepatitis B virus increase the risk of hepatocellular carcinoma in hepatitis B carriers Gastroenterology 2003 124 327 334 12557138 10.1053/gast.2003.50053
Sugauchi F Ohno T Orito E Sakugawa H Ichida T Komatsu M Kuramitsu T Ueda R Miyakawa Y Mizokami M Influence of hepatitis B virus genotypes on the development of preS deletions and advanced liver disease J Med Virol 2003 70 537 544 12794715 10.1002/jmv.10428
Anon Global surveillance and control of hepatitis C. Report of a WHO Consultation organized in collaboration with the Viral Hepatitis Prevention Board, Antwerp, Belgium J Viral Hepat 1999 6 35 47 10847128 10.1046/j.1365-2893.1999.6120139.x
Crowe J Doyle C Fielding JF Holloway H Keegan M Kelleher D Kelly P Leader M Little M McDonald G McCarthy CF McWeeney J O'Keane C Rajan E Presentation of hepatitis C in a unique uniform cohort 17 years from inoculation [abstract] Gastroenterology 1995 108 1054
Poynard T Bedossa P Opolon P Natural history of liver fibrosis progression in patients with chronic hepatitis C Lancet 1997 349 825 832 9121257 10.1016/S0140-6736(96)07642-8
Hopf U Moller B Kuther D Stemerowicz R Lobeck H Ludtke-Handjery A Walter E Blum HE Roggendorf M Deinhardt F Long-term follow-up of posttransfusion and sporadic chronic hepatitis non-A, non-B and frequency of circulating antibodies to hepatitis C virus (HCV) J Hepatol 1990 10 69 76 2106548 10.1016/0168-8278(90)90075-3
Di Bisceglie AM Goodman ZD Ishak KG Hoofnagle JH Melpolder JJ Alter HJ Long-term clinical and histopathological follow-up of chronic posttransfusion hepatitis Hepatology 1991 14 969 974 1959884 10.1016/0270-9139(91)90113-A
Tremolada F Casarin C Alberti A Drago C Tagger A Ribero ML Realdi G Long-term follow-up of non-A, non-B (type C) post-transfusion hepatitis J Hepatol 1992 6 273 281 1487603 10.1016/S0168-8278(05)80657-9
Koretz RL Abbey H Coleman E Gitnick G Non-A, non-B post-transfusion hepatitis. Looking back in the second decade Ann Intern Med 1993 119 110 115 8512159
Mattsson L Sonnerborg A Weiland O Outcome of acute symptomatic non-A, non-B hepatitis: a 13-year follow-up study of hepatitis C virus markers Liver 1993 13 274 278 7505044
Bolondi L Sofia S Siringo S Gaiani S Casali A Zironi G Piscaglia F Gramantieri L Zanetti M Sherman M Surveillance programme of cirrhotic patients for early diagnosis and treatment of hepatocellular carcinoma: a cost effectiveness analysis Gut 2001 48 251 259 11156649 10.1136/gut.48.2.251
Bruno S Silini E Crosignani A Borzio F Leandro G Bono F Asti M Rossi S Larghi A Cerino A Podda M Mondelli MU Hepatitis C virus genotypes and risk of hepatocellular carcinoma in cirrhosis: a prospective study Hepatology 1997 25 754 758 9049231 10.1002/hep.510250344
Ikeda K Saitoh S Koida I Arase Y Tsubota A Chayama K Kumada H Kawanishi M A multivariate analysis of risk factors for hepatocellular carcinogenesis: a prospective observation of 795 patients with viral and alcoholic cirrhosis Hepatology 1993 18 47 53 7686879 10.1016/0270-9139(93)90505-H
Degos F Christidis C Ganne-Carrie N Farmachidi JP Degott C Guettier C Trinchet JC Beaugrand M Chevret S Hepatitis C virus related cirrhosis: time to occurrence of hepatocellular carcinoma and death Gut 2000 47 131 136 10861275 10.1136/gut.47.1.131
Kiyosawa K Tanaka E Sodeyama T Hepatitis C virus and hepatocellular carcinoma Curr Stud Hematol Blood Transfus 1998 62 161 180 9507810
Tong MJ El Farra NS Reikes AR Co RL Clinical outcomes after transfusion-associated hepatitis C N Engl J Med 1995 332 1463 1466 7739682 10.1056/NEJM199506013322202
Pozzato G Kaneko S Moretti M Croce LS Franzin F Unoura M Bercich L Tiribelli C Crovatto M Santini G Kobayashi S Crovatto M Santini G Kobayashi S Different genotypes of hepatitis C virus are associated with different severity of chronic liver disease J Med Virol 1994 43 291 296 7931191
Bruno S Silini E Crosignani A Borzio F Leandro G Bono F Asti M Rossi S Larghi A Cerino A Podda M Mondelli MU Hepatitis C virus genotypes and risk of hepatocellular carcinoma in cirrhosis: a prospective study Hepatology 1997 25 754 758 9049231 10.1002/hep.510250344
Benvegnu L Pontisso P Cavalletto D Noventa F Chemello L Alberti A Lack of correlation between hepatitis C virus genotypes and clinical course of hepatitis C virus-related cirrhosis Hepatology 1997 25 211 215 8985292
Romeo R Rumi MG Del Ninno E Colombo M Hepatitis C virus genotype 1b and risk of hepatocellular carcinoma Hepatology 1997 26 1077 9328339
Zarski JP Bohn B Bastie A Pawlotsky JM Baud M Bost-Bezeaux F Tran van Nhieu J Seigneurin JM Buffet C Dhumeaux D Characteristics of patients with dual infection by hepatitis B and C viruses J Hepatol 1998 28 27 33 9537860 10.1016/S0168-8278(98)80198-0
Sato S Fujiyama S Tanaka M Yamasaki K Kuramoto I Kawano S Sato T Mizuno K Nonaka S Coinfection of hepatitis C virus in patients with chronic hepatitis B infection J Hepatol 1994 21 159 166 7527435 10.1016/S0168-8278(05)80389-7
Donato F Boffetta P Puoti M A meta-analysis of epidemiological studies on the combined effect of hepatitis B and C virus infections in causing hepatocellular carcinoma Int J Cancer 1998 75 347 354 9455792 10.1002/(SICI)1097-0215(19980130)75:3<347::AID-IJC4>3.0.CO;2-2
Chiba T Matsuzaki Y Abei M Shoda J Tanaka N Osuga T Aikawa T The role of previous hepatitis B virus infection and heavy smoking in hepatitis C virus-related hepatocellular carcinoma Am J Gastroenterol 1996 91 1195 1203 8651170
Kubo S Nishiguchi S Hirohashi K Tanaka H Tsukamoto T Hamba H Shuto T Yamamoto T Ikebe T Kinoshita H Clinical significance of prior hepatitis B virus infection in patients with hepatitis C virus-related hepatocellular carcinoma Cancer 1999 86 793 798 10463977 10.1002/(SICI)1097-0142(19990901)86:5<793::AID-CNCR14>3.0.CO;2-K
Marusawa H Osaki Y Kimura T Ito K Yamashita Y Eguchi T Kudo M Yamamoto Y Kojima H Seno H Moriyasu F Chiba T High prevalence of anti-hepatitis B virus serological markers in patients with hepatitis C virus related chronic liver disease in Japan Gut 1999 45 284 288 10403743
Kao JH Chen PJ Lai MY Chen DS Occult hepatitis B virus infection and clinical outcomes of patients with chronic hepatitis C J Clin Microbiol 2002 40 4068 4071 12409376 10.1128/JCM.40.11.4068-4071.2002
Kurtz RC Hepatocellular carcinoma and coinfection with hepatitis B and C. Making a difficult situation worse Cancer 1999 86 741 743 10463966 10.1002/(SICI)1097-0142(19990901)86:5<741::AID-CNCR3>3.0.CO;2-M
Anon National Institutes of Health Consensus Development Conference Panel Statement: Management of Hepatitis C Hepatology 1997 26 2S 10S 9305656
Chlabicz S Grzeszczuk A Hepatitis B virus vaccine for patients with hepatitis C virus infection Infection 2000 28 341 345 11139151 10.1007/s150100070002
Garcia-Samaniego J Rodriguez M Berenguer J Rodriguez-Rosado R Carbo J Asensi V Soriano V Hepatocellular carcinoma in HIV-infected patients with chronic hepatitis C Am J Gastroenterol 2001 96 179 183 11197250
Telfer P Sabin C Devereux H Scott F Dusheiko G Lee C The progression of HCV-associated liver disease in a cohort of haemophilic patients Br J Haematol 1994 87 555 561 7993796
Hassan MM Zaghloul AS El-Serag HB Soliman O Patt YZ Chappell CL Beasley RP Hwang LY The role of hepatitis C in hepatocellular carcinoma: a case control study among Egyptian patients J Clin Gastroenterol 2001 33 123 126 11468438 10.1097/00004836-200108000-00006
Ohnishi K Iida S Iwama S Goto N Nomura F Takashi M Mishima A Kono K Kimura K Musha H Kotota K Okuda K The effect of chronic habitual alcohol intake on the development of liver cirrhosis and hepatocellular carcinoma: relation to hepatitis B surface antigen carriage Cancer 1982 49 672 677 6275976
Qiao ZK Halliday ML Rankin JG Coates RA Relationship between hepatitis B surface antigen prevalence, per capita alcohol consumption and primary liver cancer death rate in 30 countries J Clin Epidemiol 1988 41 787 792 2843610 10.1016/0895-4356(88)90165-5
Donato F Tagger A Gelatti U Parrinello G Boffetta P Albertini A Decarli A Trevisi P Ribero ML Martelli C Porru S Nardi G Alcohol and hepatocellular carcinoma: the effect of lifetime intake and hepatitis virus infections in men and women Am J Epidemiol 2002 155 323 331 11836196 10.1093/aje/155.4.323
Simonetti RG Camma C Fiorello F Cottone M Rapicetta M Marino L Fiorentino G Craxi A Ciccaglione A Giuseppetti R Stroffolini T Pagliaro L Hepatitis C virus infection as a risk factor for hepatocellular carcinoma in patients with cirrhosis. A case-control study Ann Intern Med 1992 116 97 102 1309286
Trichopoulos D Day NE Kaklamani E Tzonou A Munoz N Zavitsanos X Koumantaki Y Trichopoulou A Hepatitis B virus, tobacco smoking and ethanol consumption in the etiology of hepatocellular carcinoma Int J Cancer 1987 39 45 49 3025110
Donato F Tagger A Chiesa R Ribero ML Tomasoni V Fasola M Gelatti U Portera G Boffetta P Nardi G Hepatitis B and C virus infection, alcohol drinking, and hepatocellular carcinoma: a case-control study in Italy Hepatology 1997 26 579 584 9303486
Hassan MM Hwang LY Hatten CJ Swaim M Li D Abbruzzese JL Beasley P Patt YZ Risk factors for hepatocellular carcinoma: synergism of alcohol with viral hepatitis and diabetes mellitus Hepatology 2002 36 1206 1213 12395331 10.1053/jhep.2002.36780
Chen DS Kuo G Sung JL Lai MY Sheu JC Chen PJ Yang PM Hsu HM Chang MH Chen CJ Hahn LC Choo QL Wang TH Houghton M Hepatitis C virus infection in an area hyperendemic for hepatitis B and chronic liver disease: the Taiwan experience J Infect Dis 1990 162 817 822 2169497
Chuang WL Chang WY Lu SN Su WP Lin ZY Chen SC Hsieh MY Wang LY You SL Chen CJ The role of hepatitis B and C viruses in hepatocellular carcinoma in a hepatitis B endemic area. A case-control study Cancer 1992 69 2052 2054 1311978
Lee SD Lee FY Wu JC Hwang SJ Wang SS Lo KJ The prevalence of anti-hepatitis C virus among Chinese patients with hepatocellular carcinoma Cancer 1992 69 342 345 1309428
Jeng JE Tsai JF Hepatitis C virus antibody in hepatocellular carcinoma in Taiwan J Med Virol 1991 34 74 77 1653308
Leung NW Tam JS Lai JY Leung TW Lau WY Shiu W Li AK Does hepatitis C virus infection contribute to hepatocellular carcinoma in Hong Kong? Cancer 1992 70 40 44 1318777
Nishioka K Watanabe J Furuta S Tanaka E Iino S Suzuki H Tsuji T Yano M Kuo G Choo QL Houghton M Oda T A high prevalence of antibody to the hepatitis C virus in patients with hepatocellular carcinoma in Japan Cancer 1991 67 429 433 1845946
Saito I Miyamura T Ohbayashi A Harada H Katayama T Kikuchi S Watanabe Y Koi S Onji M Ohta Y Choo QL Houghton M Kuo G Hepatitis C virus infection is associated with the development of hepatocellular carcinoma Proc Natl Acad Sci USA 1990 87 6547 6549 2168552
Hassan MM Zaghloul AS El-Serag HB Soliman O Patt YZ Chappell CL Beasley RP Hwang LY The role of hepatitis C in hepatocellular carcinoma: a case control study among Egyptian patients J Clin Gastroenterol 2001 33 123 126 11468438 10.1097/00004836-200108000-00006
Kew MC Houghton M Choo QL Kuo G Hepatitis C virus antibodies in southern African blacks with hepatocellular carcinoma Lancet 1990 335 873 874 1691422 10.1016/0140-6736(90)90474-J
Yu MC Tong MJ Coursaget P Ross RK Govindarajan S Henderson BE Prevalence of hepatitis B and C viral markers in black and white patients with hepatocellular carcinoma in the United States J Natl Cancer Inst 1990 82 1038 1041 2161463
Di Di Bisceglie AM Order SE Klein JL Waggoner JG Sjogren MH Kuo G Houghton M Choo QL Hoofnagle JH The role of chronic viral hepatitis in hepatocellular carcinoma in the United States Am J Gastroenterol 1991 86 335 338 1847790
Hadziyannis S Tabor E Kaklamani E Tzonou A Stuver S Tassopoulos N Mueller N Trichopoulos D A case-control study of hepatitis B and C virus infections in the etiology of hepatocellular carcinoma Int J Cancer 1995 60 627 631 7860136
Colombo M Kuo G Choo QL Donato MF Del Ninno E Tommasini MA Dioguardi N Houghton M Prevalence of antibodies to hepatitis C virus in Italian patients with hepatocellular carcinoma Lancet 1989 2 1006 1008 2572740 10.1016/S0140-6736(89)91016-7
Levrero M Tagger A Balsano C De Marzio E Avantaggiati ML Natoli G Diop D Villa E Diodati G Alberti A Antibodies to hepatitis C virus in patients with hepatocellular carcinoma J Hepatol 1991 12 60 63 1848874
Simonetti RG Camma C Fiorello F Cottone M Rapicetta M Marino L Fiorentino G Craxi A Ciccaglione A Giuseppetti R Stroffolini T Pagliaro L Hepatitis C virus infection as a risk factor for hepatocellular carcinoma in patients with cirrhosis Ann Intern Med 1992 116 97 102 1309286
Stroffolini T Andreone P Andriulli A Ascione A Craxi A Chiaramonte M Galante D Manghisi OG Mazzanti R Medaglia C Pilleri G Rapaccini GL Simonetti RG Taliani G Tosti ME Villa E Gasbarrini G Characteristics of hepatocellular carcinoma in Italy J Hepatol 1998 29 944 952 9875641 10.1016/S0168-8278(98)80122-0
Bruix J Barrera JM Calvet X Ercilla G Costa J Sanchez-Tapias JM Ventura M Vall M Bruguera M Bru C Castillo R Rodes J Prevalence of antibodies to hepatitis C virus in Spanish patients with hepatocellular carcinoma and hepatic cirrhosis Lancet 1989 2 1004 1006 2572739 10.1016/S0140-6736(89)91015-5
Nalpas B Driss F Pol S Hamelin B Housset C Brechot C Berthelot P Association between HCV and HBV infection in hepatocellular carcinoma and alcoholic liver disease J Hepatol 1991 12 70 74 1848875
Van Roey G Fevery J Van Steenbergen W Hepatocellular carcinoma in Belgium: clinical and virological characteristics of 154 consecutive cirrhotic and non-cirrhotic patients Eur J Gastroenterol Hepatol 2000 12 61 66 10656212
Haydon GH Jarvis LM Simmonds P Harrison DJ Garden OJ Hayes PC Association between chronic hepatitis C infection and hepatocellular carcinoma in a Scottish population Gut 1997 40 128 132 9155590
Yeh FS Yu MC Mo CC Luo S Tong MJ Henderson BE Hepatitis B virus, aflatoxins, and hepatocellular carcinoma in southern Guangxi, China Cancer Res 1989 49 2506 2509 2539905
El Serag HB Mason AC Rising incidence of hepatocellular carcinoma in the United States N Engl J Med 1999 340 745 750 10072408 10.1056/NEJM199903113401001
El Serag HB Mason AC Risk factors for the rising rates of primary liver cancer in the United States Arch Intern Med 2000 160 3227 3230 11088082 10.1001/archinte.160.21.3227
Benhamiche AM Faivre C Minello A Clinard F Mitry E Hillon P Faivre J Time trends and age-period-cohort effects on the incidence of primary liver cancer in a well-defined French population: 1976–1995 J Hepatol 1998 29 802 806 9833919 10.1016/S0168-8278(98)80262-6
Law MG Roberts SK Dore GJ Kaldor JM Primary hepatocellular carcinoma in Australia, 1978–1997: increasing incidence and mortality Med J Aust 2000 173 403 405 11090031
Yoshizawa H Hepatocellular carcinoma associated with hepatitis C virus infection in Japan: projection to other countries in the foreseeable future Oncology 2002 62 8 17 11868791 10.1159/000048270
Kiyosawa K Furutu S Clinical aspects and epidemiology of hepatitis B and C viruses in hepatocellular carcinoma in Japan Cancer Chemother Pharmacol 1992 31 150 156 10.1007/BF00687126
Deuffic S Buffat L Poynard T Valleron AJ Modeling the hepatitis C virus epidemic in France Hepatology 1999 29 1596 1601 10216148 10.1002/hep.510290528
Armstrong GL Alter MJ McQuillan GM Margolis HS The past incidence of hepatitis C virus infection: implications for the future burden of chronic liver disease in the United States Hepatology 2000 31 777 782 10706572 10.1002/hep.510310332
Tanaka Y Hanada K Mizokami M Yeo AE Shih JW Gojobori T Alter HJ A comparison of the molecular clock of hepatitis C virus in the United States and Japan predicts that hepatocellular carcinoma incidence in the United States will increase over the next two decades Proc Natl Acad Sci USA 2002 99 15584 15589 12438687 10.1073/pnas.242608099
Garcia-Tsao G Current management of the complications of cirrhosis and portal hypertension: variceal hemorrhage, ascites, and spontaneous bacterial peritonitis Gastroenterology 2001 120 726 748 11179247
Solmi L Primerano AM Gandolfi L Ultrasound follow-up of patients at risk for hepatocellular carcinoma: results of a prospective study on 360 cases Am J Gastroenterol 1996 91 1189 1194 8651169
Gebo KA Chander G Jenckes MW Ghanem KG Herlong HF Torbenson MS El-Kamary SS Bass EB Screening tests for hepatocellular carcinoma in patients with chronic hepatitis C: a systematic review Hepatology 2002 36 84 92 10.1053/jhep.2002.36817
Di Bisceglie AM Hoofnagle JH Elevations in serum alpha-fetoprotein levels in patients with chronic hepatitis B Cancer 1989 64 2117 2120 2478280
Izzo F Cremona F Ruffolo F Palaia R Parisi V Curley SA Outcome of 67 patients with hepatocellular cancer detected during screening of 1125 patients with chronic hepatitis Ann Surg 1998 227 513 518 9563539 10.1097/00000658-199804000-00011
Sheu JC Sung JL Chen DS Yang PM Lai MY Lee CS Hsu HC Chuang CN Yang PC Wang TH Lin JT Lee CZ Growth rate of asymptomatic hepatocellular carcinoma and its clinical implications Gastroenterology 1985 89 259 266 2408960
Collier J Sherman M Screening for hepatocellular carcinoma Hepatology 1998 27 273 278 9425947 10.1002/hep.510270140
Kim CM Koike K Saito I Miyamura T Jay G HBx gene of hepatitis B virus induces liver cancer in transgenic mice Nature 1991 351 317 320 2034275 10.1038/351317a0
Moriya K Fujie H Shintani Y Yotsuyanagi H Tsutsumi T Ishibashi K Matsuura Y Kimura S Miyamura T Koike K The core protein of hepatitis C virus induces hepatocellular carcinoma in transgenic mice Nat Med 1998 4 1065 1067 9734402 10.1038/2053
Summers J Smolec JM Snyder R A virus similar to human hepatitis B virus associated with hepatitis and hepatoma in woodchucks Proc Natl Acad Sci USA 1978 75 4533 4537 212758
Weinberg RA Oncogenes, antioncogenes, and the molecular bases of multistep carcinogenesis Cancer Res 1989 49 3713 3721 2660980
Idilman R De Maria N Colantoni A Van Thiel DH Pathogenesis of hepatitis B and C-induced hepatocellular carcinoma J Viral Hepat 1998 5 285 299 9795912 10.1046/j.1365-2893.1998.00116.x
Nakanuma Y Terada T Ueda K Terasaki S Nonomura A Matsui O Adenomatous hyperplasia of the liver as a precancerous lesion Liver 1993 13 1 9 8384281
Theise ND Macroregenerative (dysplastic) nodules and hepatocarcinogenesis: theoretical and clinical considerations Semin Liver Dis 1995 15 360 371 8578320
Sh Shibata M Morizane T Uchida T Yamagami T Onozuka Y Nakano M Mitamura K Ueno Y Irregular regeneration of hepatocytes and risk of hepatocellular carcinoma in chronic hepatitis and cirrhosis with hepatitis-C-virus infection Lancet 1998 351 1773 1777 9635950 10.1016/S0140-6736(97)08002-1
Sugitani S Sakamoto M Ichida T Genda T Asakura H Hirohashi S Hyperplastic foci reflect the risk of multicentric development of human hepatocellular carcinoma J Hepatol 1998 28 1045 1053 9672182 10.1016/S0168-8278(98)80355-3
Lee RG Tsamandas AC Demetris AJ Large cell change (liver cell dysplasia) and hepatocellular carcinoma in cirrhosis: matched case-control study, pathological analysis, and pathogenetic hypothesis Hepatology 1997 26 1415 1422 9397980
Borzio M Bruno S Roncalli M Mels GC Ramella G Borzio F Leandro G Servida E Podda M Liver cell dysplasia is a major risk factor for hepatocellular carcinoma in cirrhosis: a prospective study Gastroenterology 1995 108 812 817 7875483
Zhao M Zhang NX Laissue JA Zimmermann A Immunohistochemical analysis of p53 protein overexpression in liver cell dysplasia and in hepatocellular carcinoma Virchows Arch 1994 424 613 621 8055155 10.1007/BF01069741
Kew MC Hepatitis B and C viruses and hepatocellular carcinoma Clin Lab Med 1996 16 395 406 8792079
Kew MC Hepatitis viruses and hepatocellular carcinoma Res Virol 1998 149 257 262 9879602 10.1016/S0923-2516(99)89003-7
Chisari FV Klopchin K Moriyama T Pasquinelli C Dunsford HA Sell S Pinkert CA Brinster RL Palmiter RD Molecular pathogenesis of hepatocellular carcinoma in hepatitis B virus transgenic mice Cell 1989 59 1145 1156 2598264 10.1016/0092-8674(89)90770-8
Kim JW Ye Q Forgues M Chen Y Budhu A Sime J Hofseth LJ Kaul R Wang XW Cancer-associated molecular signature in the tissue samples of patients with cirrhosis Hepatology 2004 39 518 527 14768006 10.1002/hep.20053
Lee JS Chu IS Heo J Calvisi DF Sun Z Roskams T Durnez A Demetris AJ Thorgeirsson SS Classification and prediction of survival in hepatocellular carcinoma by gene expression profiling Hepatology 2004 40 667 676 15349906 10.1002/hep.20375
Delpuech O Trabut JB Carnot F Feuillard J Brechot C Kremsdorf D Identification, using cDNA macroarray analysis, of distinct gene expression profiles associated with pathological and virological features of hepatocellular carcinoma Oncogene 2002 21 2926 2937 11973655 10.1038/sj.onc.1205392
Hann HW Lee J Bussard A Liu C Jin YR Guha K Clayton MM Ardlie K Pellini MJ Feitelson MA Preneoplastic markers of hepatitis B-virus associated hepatocellular carcinoma Cancer Res 2004 64 7329 7335 15492253
Chen PJ Chen DS Lai MY Chang MH Huang GT Yang PM Sheu JC Lee SC Hsu HC Sung JL Clonal origin of recurrent hepatocellular carcinomas Gastroenterology 1989 96 527 529 2535996
Lugassy C Bernuau J Thiers V Krosgaard K Degott C Wantzin P Schalm SW Rueff B Benhamou JP Tiollais P Bréchot C Sequences of hepatitis B virus DNA in the serum and liver of patients with acute benign and fulminant hepatitis J Infect Dis 1987 155 64 71 3794404
Koshy R Maupas P Muller R Hofschneider PH Detection of hepatitis B virus-specific DNA in the genomes of human hepatocellular carcinoma and liver cirrhosis tissues J Gen Virol 1981 57 95 102 6275024
Rowley JD Molecular cytogenetics: Rosetta stone for understanding cancer – twenty-ninth G. H. A. Clowes memorial award lecture Cancer Res 1990 50 3816 3825 2191766
Schimke RT The search for early genetic events in tumorigenesis: an amplification paradigm Cancer Cells 1990 2 149 151 2201341
Slagle BL Zhou YZ Butel JS Hepatitis B virus integration event in human chromosome 17p near the p53 gene identifies the region of the chromosome commonly deleted in virus-positive hepatocellular carcinomas Cancer Res 1991 51 49 54 1670994
Robinson WS Molecular events in the pathogenesis of hepadnavirus-associated hepatocellular carcinoma Annu Rev Med 1994 45 297 323 8198385 10.1146/annurev.med.45.1.297
Shirakata Y Kawada M Fujiki Y Sano H Oda M Yaginuma K Kobayashi M Koike K The X gene of hepatitis B virus induced growth stimulation and tumorigenic transformation of mouse NIH3T3 cells Jpn J Cancer Res 1989 80 617 621 2507484
Twu JS Schloemer RH Transcriptional trans-activating function of hepatitis B virus J Virol 1987 61 3448 3453 2822953
Paterlini P Poussin K Kew M Franco D Brechot C Selective accumulation of the X transcript of hepatitis B virus in patients negative for hepatitis B surface antigen with hepatocellular carcinoma Hepatology 1995 21 313 321 7843699 10.1016/0270-9139(95)90086-1
Henkler FF Koshy R Hepatitis B virus transcriptional activators: mechanisms and possible role in oncogenesis J Viral Hepat 1996 3 109 121 8871869
Wang XW Forrester K Yeh H Feitelson MA Gu JR Harris CC Hepatitis B virus X protein inhibits p53 sequence-specific DNA binding, transcriptional activity, and association with transcription factor ERCC3 Proc Natl Acad Sci USA 1994 91 2230 2234 8134379
Truant R Antunovic J Greenblatt J Prives C Cromlish JA Direct interaction of the hepatitis B virus HBx protein with p53 leads to inhibition by HBx of p53 response element-directed transactivation J Virol 1995 69 1851 1859 7853526
Ueda H Ullrich SJ Gangemi JD Kappel CA Ngo L Feitelson MA Jay G Functional inactivation but not structural mutation of p53 causes liver cancer Nat Genet 1995 9 41 47 7704023 10.1038/ng0195-41
Pasquinelli C Bhavani K Chisari FV Multiple oncogenes and tumor suppressor genes are structurally and functionally intact during hepatocarcinogenesis in hepatitis B virus transgenic mice Cancer Res 1992 52 2823 2829 1316229
Kekule AS Lauer U Meyer M Caselmann WH Hofschneider PH Koshy R The preS2/S region of integrated hepatitis B virus DNA encodes a transcriptional transactivator Nature 1990 343 457 461 2153938 10.1038/343457a0
Fu XX Su CY Lee Y Hintz R Biempica L Snyder R Rogler CE Insulinlike growth factor II expression and oval cell proliferation associated with hepatocarcinogenesis in woodchuck hepatitis virus carriers J Virol 1988 62 3422 3430 2457114
Yoo YD Ueda H Park K Flanders KC Lee YI Jay G Kim SJ Regulation of transforming growth factor-beta 1 expression by the hepatitis B virus (HBV) X transactivator. Role in HBV pathogenesis J Clin Invest 1996 97 388 395 8567959
Bock CT Tillmann HL Manns MP Trautwein C The pre-S region determines the intracellular localization and appearance of hepatitis B virus Hepatology 1999 30 517 525 10421662 10.1002/hep.510300206
Xu Z Jensen G Yen TS Activation of hepatitis B virus S promoter by the viral large surface protein via induction of stress in the endoplasmic reticulum J Virol 1997 71 7387 7392 9311817
Jakubczak JL Chisari FV Merlino G Synergy between transforming growth factor alpha and hepatitis B virus surface antigen in hepatocellular proliferation and carcinogenesis Cancer Res 1997 57 3606 3611 9270035
Yeh SH Lin MW Lu SF Wu DC Tsai SF Tsai CY Lai MY Hsu HC Chen DS Chen PJ Allelic loss of chromosome 4q21 approximately 23 associates with hepatitis B virus-related hepatocarcinogenesis and elevated alpha-fetoprotein Hepatology 2004 40 847 854 15382172 10.1002/hep.20409
Yano M Kumada H Kage M Ikeda K Shimamatsu K Inoue O Hashimoto E Lefkowitch JH Ludwig J Okuda K The long-term pathological evolution of chronic hepatitis C Hepatology 1996 23 1334 1340 8675148
Kew MC Hepatitis C virus and hepatocellular carcinoma FEMS Microbiol Rev 1994 14 211 219 8086196 10.1016/0168-6445(94)90035-3
Nardone G Romano M Calabro A Pedone PV de Sio I Persico M Budillon G Bruni CB Riccio A Zarrilli R Activation of fetal promoters of insulinlike growth factors II gene in hepatitis C virus-related chronic hepatitis, cirrhosis, and hepatocellular carcinoma Hepatology 1996 23 1304 1312 8675143
Tanaka S Takenaka K Matsumata T Mori R Sugimachi K Hepatitis C virus replication is associated with expression of transforming growth factor-alpha and insulin-like growth factor-II in cirrhotic livers Dig Dis Sci 1996 41 208 215 8565758
Takamizawa A Mori C Fuke I Manabe S Murakami S Fujita J Onishi E Andoh T Yoshida I Okayama H Structure and organization of the hepatitis C virus genome isolated from human carriers J Virol 1991 65 1105 1113 1847440
Borowski P Oehlmann K Heiland M Laufs R Nonstructural protein 3 of hepatitis C virus blocks the distribution of the free catalytic subunit of cyclic AMP-dependent protein kinase J Virol 1997 71 2838 2843 9060639
Taylor DR Shi ST Romano PR Barber GN Lai MM Inhibition of the interferon-inducible protein kinase PKR by HCV E2 protein Science 1999 285 107 110 10390359 10.1126/science.285.5424.107
Gale M JrKwieciszewski B Dossett M Nakao H Katze MG Antiapoptotic and oncogenic potentials of hepatitis C virus are linked to interferon resistance by viral repression of the PKR protein kinase J Virol 1999 73 6506 6516 10400746
Koromilas AE Roy S Barber GN Katze MG Sonenberg N Malignant transformation by a mutant of the IFN-inducible dsRNA-dependent protein kinase Science 1992 257 1685 1689 1382315
Shih CM Lo SJ Miyamura T Chen SY Lee YH Suppression of hepatitis B virus expression and replication by hepatitis C virus core protein in HuH-7 cells J Virol 1993 67 5823 5832 8396658
Kim DW Suzuki R Harada T Saito I Miyamura T Trans-suppression of gene expression by hepatitis C viral core protein Jpn J Med Sci Biol 1994 47 211 220 7715094
Ray RB Steele R Meyer K Ray R Transcriptional repression of p53 promoter by hepatitis C virus core protein J Biol Chem 1997 272 10983 10986 9110985 10.1074/jbc.272.17.10983
Ray RB Steele R Meyer K Ray R Hepatitis C virus core protein represses p21WAF1/Cip1/Sid1 promoter activity Gene 1998 208 331 336 9524287 10.1016/S0378-1119(98)00030-4
Ruster B Zeuzem S Roth WK Hepatitis C virus sequences encoding truncated core proteins detected in a hepatocellular carcinoma Biochem Biophys Res Commun 1996 219 911 915 8645278 10.1006/bbrc.1996.0340
Tai DI Tsai SL Chen YM Chuang YL Peng CY Sheen IS Yeh CT Chang KS Huang SN Kuo GC Liaw YF Activation of nuclear factor kappa B in hepatitis C virus infection: implications for pathogenesis and hepatocarcinogenesis Hepatology 2000 31 656 664 10706556 10.1002/hep.510310316
Sung JL Chen DS Hepatitis B antigen and antibody in liver disease in Taiwan Proceedings 5th Asian Pacific Congress of Gastroenterology: Singapore 1976 265 269
Chang MH Chen CJ Lai MS Hsu HM Wu TC Kong MS Liang DC Shau WY Chen DS Universal hepatitis B vaccination in Taiwan and the incidence of hepatocellular carcinoma in children N Engl J Med 1997 336 1855 1859 9197213 10.1056/NEJM199706263362602
Wong DK Cheung AM O'Rourke K Naylor CD Detsky AS Heathcote J Effect of alpha-interferon treatment in patients with hepatitis B e antigen-positive chronic hepatitis B. A meta-analysis Ann Intern Med 1993 119 312 323 8328741
McHutchison JG Gordon SC Schiff ER Shiffman ML Lee WM Rustgi VK Goodman ZD Ling MH Cort S Albrecht JK Interferon alfa-2b alone or in combination with ribavirin as initial treatment for chronic hepatitis C N Engl J Med 1998 339 1485 1492 9819446 10.1056/NEJM199811193392101
Poynard T Marcellin P Lee SS Niederau C Minuk GS Ideo G Bain V Heathcote J Zeuzem S Trepo C Albrecht J Randomised trial of interferon alpha2b plus ribavirin for 48 weeks or for 24 weeks versus interferon alpha2b plus placebo for 48 weeks for treatment of chronic infection with hepatitis C virus Lancet 1998 352 1426 1432 9807989 10.1016/S0140-6736(98)07124-4
Manns MP McHutchison JG Gordon SC Rustgi VK Shiffman M Reindollar R Goodman ZD Koury K Ling M Albrecht JK Peginterferon alfa-2b plus ribavirin compared with interferon alfa-2b plus ribavirin for initial treatment of chronic hepatitis C: a randomised trial Lancet 2001 358 958 965 11583749 10.1016/S0140-6736(01)06102-5
Fried MW Shiffman ML Reddy KR Smith C Marinos G Goncales FL JrHaussinger D Diago M Carosi G Dhumeaux D Craxi A Lin A Hoffman J Yu J Peginterferon alfa-2a plus ribavirin for chronic hepatitis C virus infection N Engl J Med 2002 347 975 982 12324553 10.1056/NEJMoa020047
Dianzani F Antonelli G Capobianchi MR The biological basis for clinical use of interferon J Hepatol 1990 11 5 10 2204659
Iwase S Furukawa Y Kikuchi J Nagai M Terui Y Nakamura M Yamada H Modulation of E2F activity is linked to interferon-induced growth suppression of hematopoietic cells J Biol Chem 1997 272 12406 12414 9139687 10.1074/jbc.272.19.12406
Raveh T Hovanessian AG Meurs EF Sonenberg N Kimchi A Double-stranded RNA-dependent protein kinase mediates c-Myc suppression induced by type I interferons J Biol Chem 1996 271 25479 25484 8810318 10.1074/jbc.271.41.25479
Arany I Rady P Tyring SK Interferon treatment enhances the expression of underphosphorylated (biologically-active) retinoblastoma protein in human papilloma virus-infected cells through the inhibitory TGF beta 1/IFN beta cytokine pathway Antiviral Res 1994 23 131 141 7511881 10.1016/0166-3542(94)90040-X
Merle P Chevallier M Levy R Maisonnas M Terradillos O Ahmed SNS Trepo C Buendia MA Vitvitski-Trepo L Preliminary results of interferon-alpha therapy on woodchuck hepatitis virus-induced hepatocarcinogenesis: possible benefit in female transgenic mice J Hepatol 2001 34 562 569 11394656 10.1016/S0168-8278(00)00054-4
Singh RK Gutman M Bucana CD Sanchez R Llansa N Fidler IJ Interferons alpha and beta down-regulate the expression of basic fibroblast growth factor in human carcinomas Proc Natl Acad Sci USA 1995 92 4562 4566 7753843
Niederau C Heintges T Lange S Goldmann G Niederau CM Mohr L Haussinger D Long-term follow-up of HBeAg-positive patients treated with interferon alfa for chronic hepatitis B N Engl J Med 1996 334 1422 1427 8618580 10.1056/NEJM199605303342202
Lin SM Sheen IS Chien RN Chu CM Liaw YF Long-term beneficial effect of interferon therapy in patients with chronic hepatitis B virus infection Hepatology 1999 29 971 975 10051505 10.1002/hep.510290312
Yuen MF Hui CK Cheng CC Wu CH Lai YP Lai CL Long-term follow-up of interferon alfa treatment in Chinese patients with chronic hepatitis B infection: The effect on hepatitis B e antigen seroconversion and the development of cirrhosis-related complications Hepatology 2001 34 139 145 11431745 10.1053/jhep.2001.25273
Oon CJ Long-term survival following treatment of hepatocellular carcinoma in Singapore: evaluation of Wellferon in the prophylaxis of high-risk pre-cancerous conditions Cancer Chemother Pharmacol 1992 31 137 142 10.1007/BF00687123
Mazzella G Accogli E Sottili S Festi D Orsini M Salzetta A Novelli V Cipolla A Fabbri C Pezzoli A Roda E Alpha interferon treatment may prevent hepatocellular carcinoma in HCV-related liver cirrhosis J Hepatol 1996 24 141 147 8907566 10.1016/S0168-8278(96)80022-5
Fattovich G Giustina G Realdi G Corrocher R Schalm SW Long-term outcome of hepatitis B e antigen-positive patients with compensated cirrhosis treated with interferon alfa Hepatology 1997 26 1338 1342 9362381
Ikeda K Saitoh S Suzuki Y Kobayashi M Tsubota A Fukuda M Koida I Arase Y Chayama K Murashima N Kumada H Interferon decreases hepatocellular carcinogenesis in patients with cirrhosis caused by the hepatitis B virus: a pilot study Cancer 1998 82 827 835 9486570 10.1002/(SICI)1097-0142(19980301)82:5<827::AID-CNCR5>3.0.CO;2-G
International Interferon-alpha Hepatocellular Carcinoma Study Group Effect of interferon-alpha on progression of cirrhosis to hepatocellular carcinoma: a retrospective cohort study Lancet 1998 351 1535 1539 10326535 10.1016/S0140-6736(98)07236-5
Benvegnù L Chemello L Noventa F Fattovich G Pontisso P Alberti A Retrospective analysis of the effect of interferon therapy on the clinical outcome of patients with viral cirrhosis Cancer 1998 83 901 909 9731893 10.1002/(SICI)1097-0142(19980901)83:5<901::AID-CNCR15>3.0.CO;2-Z
Di Marco V Lo Iacono O Camma C Vaccaro A Giunta M Martorana G Fuschi P Almasio PL Craxi A The long-term course of chronic hepatitis B Hepatology 1999 30 257 264 10385664 10.1002/hep.510300109
Camma C Giunta M Andreone P Craxi A Interferon and prevention of hepatocellular carcinoma in viral cirrhosis: an evidence-based approach J Hepatol 2001 34 593 602 11394661 10.1016/S0168-8278(01)00005-8
Liaw YF Sung JJ Chow WC Farrell G Lee CZ Yuen H Tanwandee T Tao QM Shue K Keene ON Dixon JS Gray DF Sabbat J Cirrhosis Asian Lamivudine Multicentre Study Group Lamivudine for patients with chronic hepatitis B and advanced liver disease N Engl J Med 2004 351 1521 1531 15470215 10.1056/NEJMoa033364
Kasahara A Hayashi N Mochizuki K Takayanagi M Yoshioka K Kakumu S Iijima A Urushihara A Kiyosawa K Okuda M Hino K Okita K Risk factors for hepatocellular carcinoma and its incidence after interferon treatment in patients with chronic hepatitis C Hepatology 1998 27 1394 1402 9581697 10.1002/hep.510270529
Camma C Di Marco V Lo Iacono O Almasio P Giunta M Fuschi P Vaccaro A Fabiano C Magrin S Di Stefano R Bonura C Pagliaro L Craxi A Long-term course of interferon-treated chronic hepatitis C J Hepatol 1998 28 531 537 9566819 10.1016/S0168-8278(98)80274-2
Yoshida H Shiratori Y Moriyama M Arakawa Y Ide T Sata M Inoue O Yano M Tanaka M Fujiyama S Nishiguchi S Kuroki T Imazeki F Yokosuka O Kinoyama S Yamada G Omata M Interferon therapy reduces the risk for hepatocellular carcinoma: national surveillance program of cirrhotic and noncirrhotic patients with chronic hepatitis C in Japan Ann Intern Med 1999 131 174 181 10428733
Toyoda H Kumada T Nakano S Takeda I Sugiyama K Kiriyama S Sone Y Tanikawa M Hisanaga Y Hayashi K Honda T Effect of the dose and duration of interferon-alpha therapy on the incidence of hepatocellular carcinoma in noncirrhotic patients with a nonsustained response to interferon for chronic hepatitis C Oncology 2001 61 134 142 11528252 10.1159/000055364
Fattovich G Giustina G Degos F Diodati G Tremolada F Nevens F Almasio P Solinas A Brouwer JT Thomas H Realdi G Corrocher R Schalm SW Effectiveness of interferon alfa on incidence of hepatocellular carcinoma and decompensation in cirrhosis type C J Hepatol 1997 27 201 205 9252096 10.1016/S0168-8278(97)80302-9
Serfaty L Aumaitre H Chazouilleres O Bonnand AM Rosmorduc O Poupon RE Poupon R Determinants of outcome of compensated hepatitis C virus-related cirrhosis Hepatology 1998 27 1435 1440 9581703 10.1002/hep.510270535
Imai Y Kawata S Tamura S Yabuuchi I Noda S Inada M Maeda Y Shirai Y Fukuzaki T Kaji I Ishikawa H Matsuda Y Nishikawa M Seki K Matsuzawa Y Relation of interferon therapy and hepatocellular carcinoma in patients with chronic hepatitis C Ann Intern Med 1998 129 94 99 9669992
Valla DC Chevallier M Marcellin P Payen JL Trepo C Fonck M Bourliere M Boucher E Miguet JP Parlier D Lemonnier C Opolon P Treatment of hepatitis C virus-related cirrhosis: a randomized, controlled trial of interferon alfa-2b versus no treatment Hepatology 1999 29 1870 1875 10347132 10.1002/hep.510290616
Okanoue T Itoh Y Minami M Sakamoto S Yasui K Sakamoto M Nishioji K Murakami Y Kashima K Interferon therapy lowers the rate of progression to hepatocellular carcinoma in chronic hepatitis C but not significantly in an advanced stage: a retrospective study in 1148 patients J Hepatol 1999 30 653 659 10207807 10.1016/S0168-8278(99)80196-2
Nishiguchi S Kuroki T Nakatani S Morimoto H Takeda T Nakajima S Shiomi S Seki S Kobayashi K Otani S Randomised trial of effects of interferon-alpha on incidence of hepatocellular carcinoma in chronic active hepatitis C with cirrhosis Lancet 1995 346 1051 1055 7564784 10.1016/S0140-6736(95)91739-X
Nishiguchi S Shiomi S Nakatani S Takeda T Fukuda K Tamori A Habu D Tanaka T Prevention of hepatocellular carcinoma in patients with chronic active hepatitis C and cirrhosis Lancet 2001 357 196 197 11213099 10.1016/S0140-6736(00)03595-9
Gramenzi A Andreone P Fiorino S Camma C Giunta M Magalotti D Cursaro C Calabrese C Arienti V Rossi C Di Febo G Zoli M Craxi A Gasbarrini G Bernardi M Impact of interferon therapy on the natural history of hepatitis C virus related cirrhosis Gut 2001 48 843 848 11358906 10.1136/gut.48.6.843
Testino G Ansaldi F Andorno E Ravetti GL Ferro C De Iaco F Icardi G Valente U Interferon therapy does not prevent hepatocellular carcinoma in HCV compensated cirrhosis Hepatogastroenterology 2002 49 1636 1638 12397752
Tanaka K Sata M Uchimura Y Suzuki H Tanikawa K Long-term evaluation of interferon therapy in hepatitis C virus-associated cirrhosis: does IFN prevent development of hepatocellular carcinoma? Oncol Rep 1998 5 205 208 9458323
Schalm SW Weiland O Hansen BE Milella M Lai MY Hollander A Michielsen PP Bellobuono A Chemello L Pastore G Chen DS Brouwer JT Interferon-ribavirin for chronic hepatitis C with and without cirrhosis: analysis of individual patient data of six controlled trials Gastroenterology 1999 117 408 413 10419923
Heathcote EJ Shiffman ML Cooksley WG Dusheiko GM Lee SS Balart L Reindollar R Reddy RK Wright TL Lin A Hoffman J De Pamphilis J Peginterferon alfa-2a in patients with chronic hepatitis C and cirrhosis N Engl J Med 2000 343 1673 1680 11106716 10.1056/NEJM200012073432302
Pagliaro L Craxi A Camma C Tine F Di Marco V Lo Iacono O Almasio P Interferon-αα for chronic hepatitis C: An analysis of pretreatment clinical predictors of response Hepatology 1994 19 820 828 8138252 10.1016/0270-9139(94)90278-X
Ikeda K Arase Y Saitoh S Kobayashi M Suzuki Y Suzuki F Tsubota A Chayama K Murashima N Kumada H Interferon beta prevents recurrence of hepatocellular carcinoma after complete resection or ablation of the primary tumor-A prospective randomized study of hepatitis C virus-related liver cancer Hepatology 2000 32 228 232 10915728 10.1053/jhep.2000.9409
Kubo S Nishiguchi S Hirohashi K Tanaka H Shuto T Kinoshita H Randomized clinical trial of long-term outcome after resection of hepatitis C virus-related hepatocellular carcinoma by postoperative interferon therapy Br J Surg 2002 89 418 422 11952580 10.1046/j.0007-1323.2001.02054.x
Lin SM Lin CJ Hsu CW Tai DI Sheen IS Lin DY Liaw YF Prospective randomized controlled study of interferon-alpha in preventing hepatocellular carcinoma recurrence after medical ablation therapy for primary tumors Cancer 2004 100 376 382 14716774 10.1002/cncr.20004
| 15907199 | PMC1166580 | CC BY | 2021-01-04 16:39:03 | no | World J Surg Oncol. 2005 May 20; 3:27 | utf-8 | World J Surg Oncol | 2,005 | 10.1186/1477-7819-3-27 | oa_comm |
==== Front
World J Surg OncolWorld Journal of Surgical Oncology1477-7819BioMed Central London 1477-7819-3-271590719910.1186/1477-7819-3-27ReviewViral hepatitis and hepatocellular carcinoma Michielsen Peter P [email protected] Sven M [email protected] Dongen Jurgen L [email protected] Division of Gastroenterology and Hepatology University Hospital Antwerp, Belgium2005 20 5 2005 3 27 27 29 11 2004 20 5 2005 Copyright © 2005 Michielsen et al; licensee BioMed Central Ltd.2005Michielsen et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world. The incidence of HCC varies considerably with the geographic area because of differences in the major causative factors. Chronic hepatitis B and C, mostly in the cirrhotic stage, are responsible for the great majority of cases of HCC worldwide. The geographic areas at the highest risk are South-East Asia and sub-Saharan Africa, here hepatitis B is highly endemic and is the main cause of HCC. In areas with an intermediate rate of HCC such as Southern Europe and Japan, hepatitis C is the predominant cause, whereas in low rate areas such as Northern Europe and the USA, HCC is often related to other factors as alcoholic liver disease. There is a rising incidence in HCC in developed countries during the last two decades, due to the increasing rate of hepatitis C infection and improvement of the clinical management of cirrhosis.
Methods
This article reviews the literature on hepatitis and hepatocellular carcinoma. The Medline search was carried out using these key words and articles were selected on epidemiology, risk factors, screening, and prevention of hepatocellular carcinoma.
Results
Screening of patients with advanced chronic hepatitis B and C with hepatic ultrasound and determination of serum alfa-fetoprotein may improve the detection of HCC, but further studies are needed whether screening improves clinical outcome.
Hepatitis B and C viruses (HBV/HCV) can be implicated in the development of HCC in an indirect way, through induction of chronic inflammation, or directly by means of viral proteins or, in the case of HBV, by creation of mutations by integration into the genome of the hepatocyte.
Conclusion
The most effective tool to prevent HCC is avoidance of the risk factors such as viral infection. For HBV, a very effective vaccine is available. Preliminary data from Taiwan indicate a protective effect of universal vaccination on the development of HCC. Vaccination against HBV should therefore be a health priority. In patients with chronic hepatitis B or C, interferon-alfa treatment in a noncirrhotic stage is protective for HCC development in responders, probably by prevention of cirrhosis development. When cirrhosis is already present, the protective effect is less clear. For cirrhosis due to hepatitis B, a protective effect was demonstrated in Oriental, but not in European patients. For cirrhosis due to hepatitis C, interferon-alfa treatment showed to be protective in some studies, especially in Japan with a high incidence of HCC in untreated patients. Virological, but also merely biochemical response, seems to be associated with a lower risk of development of HCC. As most studies are not randomized controlled trials, no definitive conclusions on the long-term effects of interferon-alfa in HBV or HCV cirrhosis can be established. Especially in hepatitis C, prospective studies should be performed using the more potent reference treatments for cirrhotics, namely the combination of peginterferon and ribavirin.
==== Body
Epidemiology of hepatocellular carcinoma
Background
Hepatocellular carcinoma (HCC) is one of the most common malignant tumors, representing more than 5% of all cancers. The estimated annual number of cases exceeds 500,000 [1], with a mean annual incidence of around 3–4% [2]. In terms of relative frequencies, HCC ranks as the fifth most common cancer in the world, it is also the fifth among men and eighth among women; it is the second among cancers of the digestive tract after stomach cancer [3].
The incidence of HCC varies considerably with the geographic area because of differences in the major causative factors. The geographic areas at the highest risk are located in Eastern Asia, with age-adjusted incidence rates (AAIR) ranging from 27.6 to 36.6 per 100,000 in men; Middle Africa (AAIR 20.8–31.1/100,000) and some Western African countries (30–48/100,000). The geographic areas at lowest risk are Northern Europe, Australia, New Zealand and the Caucasian populations of North and Latin America (AAIR 1.5–3.0). In Southern Europe, AAIR is around 10 per 100,000 in men [3].
The most powerful risk factor for development of HCC is the existence of liver cirrhosis, regardless of its etiology [4]. Among cirrhotics, viral infection and high alcohol intake are associated with the highest risk [5-8].
Of the primary hepatitis viruses, only hepatitis B and C viruses cause HCC [9]. Hepatitis A and E viruses do not produce long-term pathological sequelae. Although hepatitis D virus (HDV) always occurs as co-infection with hepatitis B virus and leads to severe acute or chronic hepatic disease, there is controversy whether it increases the carcinogenic potential [10,11].
Risk factors for development of HCC
Hepatitis B
Hepatitis B virus (HBV) infection is a major public health problem. It is estimated that two billion people have been infected worldwide and 360 million suffer from chronic HBV infection [12]. Over 520,000 die each year, 50,000 from acute hepatitis B, 470,000 from cirrhosis and liver cancer. In South-East Asia hepatitis B is mostly acquired perinatally from an infected mother. In sub-Saharan Africa, it is mostly acquired in early childhood by horizontal infection, whereas in Northwestern Europe, North America and Australia infection is mainly through sexual contact or needle sharing among injecting drug users, with a peak incidence in the 15–25 age group [12]. Infection acquired perinatally and in early childhood is usually asymptomatic, becoming chronic in 90 and 30% of cases, respectively. In adults, infection resolves in >95% with loss of serum HBsAg and the appearance of anti-HBs. Chronic infection is characterized by the persistence of HBsAg for more than 6 months. Acute hepatitis B usually results in complete recovery with little if any risk of HCC. In cases with persistent HBV infection, HBV is one of the most important risk factors for HCC.
Chronic HBV infection presents as one of three potentially successive phases: immune tolerant, immune active and low- or non-replicative. In the immune tolerant phase, serum HBsAg and HBeAg are detectable, serum HBV DNA levels are high, serum aminotransferases are normal or minimally elevated. In the immune active phase, serum HBV DNA levels decrease and serum aminotransferase levels increase. Flares of aminotransferases may be observed, in some patients these flares are followed by HBeAg-anti-HBe seroconversion. Following this conversion, in the low- or non-replicative phase the HBV replication persists but at a very low level suppressed by the host immune response. HBV DNA in serum is undetectable by conventional, non-PCR based techniques. This phase is also called the 'inactive carrier state'. It may lead to resolution of HBV infection where HBsAg becomes undetectable and anti-HBs is detected, anti-HBc staying positive as sign of contact with the virus. Recently it has been reported that HBV DNA can persist in the serum and liver tissue even after negativation of HBsAg [13]. Recent advances in molecular technology have allowed the isolation of HBV variants that either cannot produce HBeAg or produce it less efficiently, based on precore stop codon mutation and mutations in the core promoter region respectively. In patients with HBV variants, progressive liver damage occurs in parallel with relatively high levels of viremia. In perinatally infected people, the immunotolerant phase lasts till the age of 15–35 years, after which hepatitis flares may occur, leading eventually to viral remission. In patients infected during later childhood or adulthood, there is no immunotolerant phase.
Most studies on the risk of developing HCC in chronic HBV infection have been performed in the Far East. Here, most patients acquired the HBV infection as newborn infants [14]. It has been noted that the probability of acquiring HCC increases with severity of liver disease. The annual risk of HCC is 0.5% for asymptomatic HBsAg carriers and 0.8% for patients with chronic hepatitis B [15]. Patients with HBV-cirrhosis have a 1000 times higher risk of developing HCC compared to a HBsAg negative control group [16]. The incidence of HCC in compensated cirrhosis due to HBV from Asia was 2.7%. In Japan, the mean interval between the time of initial infection with HBV and the occurrence of HCC is 50 years. As most people here are infected at birth, HBV related liver cirrhosis usually develops in patients in their 40's and HCC in their 50's [17].
Few adequate studies have been performed in the West to address the issue of the incidence of HCC in persons who are positive for HBsAg. Most of the studies in Western countries have included small numbers of HBsAg positive patients and/or have not specifically analyzed the group of HBsAg carriers. There is also lack of uniformity in the timing of initiation of follow-up monitoring. In a cohort of 350 Western European patients with compensated cirrhosis followed for a mean period of 6 years, the 5-year cumulative incidence of HCC was 6% [18,19]. The incidence was 2.2% in a series of 179 untreated Caucasian patients [19,20]. In a retrospective analysis of cirrhotic European patients with HBV infection, the 5-year incidence of HCC was 9% irrespective of HBeAg or HBV DNA status at the time of diagnosis of cirrhosis [21].
The hepatitis B replication status seems to play an important role in determining the risk of development of HCC [22-24]. A recent study found that whereas the relative risk of HCC among men with HBsAg alone was 9.6 compared to those without HBsAg, the risk increased to 60.2 when they were positive for both HBsAg and HBeAg [23]. Another analysis showed that the level of HBV DNA is a prognostic marker for HBV-related HCC and that HCC patients with a less favorable course appear to either clear the virus poorly or to have a greater level of virus production [24]. It was recently demonstrated that positivity for anti-HBc alone in absence of HBsAg and anti-HCV is not rare in Japanese patients with HCC, which may indicate that HBV virus might be involved in so-called non-B HCC [25].
The entire nucleotide sequences of HBV genomes have been classified into 8 genotypes (A-H), with predominance of genotypes A and D in Western countries, and B and C in Southeast Asia and the Far East [26-29]. Several studies from the Far East evaluated the association between distinct genotypes and severity of liver disease. Genotype C was shown to be associated with the development of liver cirrhosis and HCC in Taiwan [30], China [31] and Japan [32], whereas genotype B was shown rarely to be associated with the development of HCC in China and Japan. In contrast, in Taiwan genotype B is the predominant type in patients with HCC who are younger than 35 years [30]. Another study from Taiwan showed that patients with genotype C had a greater tumor recurrence rate after curative resection of HCC compared with those with genotype B [33]. It was also shown that the likelihood of presence of T1762/A1764 mutations in the basal core promoter parallels the progression of liver disease, and that this mutation is found more frequent in HBV genotype C than B patients [34]. PreS deletions were shown to be more frequent in patients with HBV genotype C, and associated with more advanced disease such as liver cirrhosis and hepatocellular carcinoma [35].
Hepatitis C
Hepatitis C is also a major public health problem. There are more than 170 million people infected worldwide [36]. Approximately 80% of HCV infected patients develop chronic hepatitis C. About 20% of these patients will develop severe chronic hepatitis C and cirrhosis, which becomes detectable in the second and third decade after infection. The natural history of chronic hepatitis C infection is characterized by a predominantly asymptomatic course and a variable clinical outcome. For these reasons it is difficult to define the rate of progression to cirrhosis and HCC. The risk of cirrhosis in chronic hepatitis C is less than 10% in women infected at a young age and >30% in men infected after the age of 40 over a 20 year period [37,38]. Five prospective studies from Europe and the US have shown that during the first 10–15 years after initial infection, liver cancer is a rare occurrence [39-43]. In patients with hepatitis C, there is an increased risk of HCC coinciding with the establishment of cirrhosis with yearly incidence between 3–8% [6,7,44-47]. In Japan, the mean interval between infection and development of HCC is 30 years [48]. A study from the US shows a long time lag (mean 28 years, range 8–42) between transfusion-associated hepatitis and development of HCC [49].
There is conflicting information on the relationship between HCV genotype and progression to HCC in longitudinal studies. It is suggested by some authors that genotype 1b (most prevalent in Europe and Japan) is associated with a higher incidence of HCC than infection with other genotypes [50,51]. In other studies, however, this was not observed [52,53].
Coinfection of HBV and HCV
Both HBV and HCV are transmitted parenterally and coinfection is not uncommon in intravenous drug users and in countries with a high prevalence of HBV [54]. Coinfection of HBV and HCV seems to result in more severe liver disease than either infection alone [55]. The risk of developing HCC in subjects with both infections has been investigated in a meta-analysis of 32 epidemiological studies between 1993 and 1997 [56]. The odds ratio for development of HCC in HBsAg positive, anti-HCV/HCV RNA negative subjects was 20.4; in HBsAg negative, anti-HCV/HCV RNA positive subjects 23.6; and subjects positive for both markers 135. These data suggest a more than additive but less than multiplicative effect of HBV and HCV coinfection on the relative risk for HCC. The viruses may act through common as well as different pathways in the carcinogenic process.
It has been reported that HBV DNA is still present after seroconversion of HBsAg in patients with hepatitis B. Several reports indicate that prior HBV infection, characterized by presence of anti-HBc, affects the development of HCC in patients infected with HCV [57-59]. Given these data, in patients with chronic HCV infection, serologic markers of past HBV infection should be checked, not just HBsAg. Other authors, however, were not able to document any adverse event of occult HBV infection on the clinicopathologic course of chronic HCV infection [60].
In case of coinfection with HBV (whether active or past), a more aggressive surveillance to detect early HCC could be suggested [61]. However, to date screening and surveillance programs have not demonstrated a significant survival benefit.
In view of the role of HBV as cofactor in the development of HCV related cirrhosis and HCC, vaccination of patients with chronic hepatitis C against HBV has been advocated with the presumption of avoiding additional liver injury [62,63].
Coinfection of HBV and HDV
Verme et al [11] suggested that HBsAg positive patients with HDV superinfection develop cirrhosis and HCC at an earlier stage (mean age 48 year) than HBsAg carriers without HDV infection (mean age 62 years).
Coinfection of HBV and HCV with HIV
Coinfection of HBV and HCV with HIV is common because these diseases share the same routes of transmission. Recently a series of HCC in HIV-HCV coinfected patients was published, indicating an unusually rapid development of HCC in these patients [64]. This is not surprising, as chronic hepatitis C is more aggressive in HIV positive subjects, leading to cirrhosis and end-stage liver disease in a shorter period of time [65].
Coinfection of HCV and S. mansoni
An Egyptian study showed that Schistosoma infection increased the risk of HCC, only in the presence of HCV, whereas isolated S. mansoni infection does not [66].
Role of alcohol consumption in HBV or HCV infection
Reports suggest that HBV and ethanol act synergistically to promote HCC [67,68]. Habitual heavy drinking was reported to be a significant risk factor for HCC in patients with HCV-related liver cirrhosis by multiple logistic regression analysis [57]. A recent study showed synergism between alcohol drinking and HBV or HCV infection, with approximately a twofold increase in the odds ratio for each hepatitis virus infection for drinkers' > 60 g/d, with a more than additive but less than multiplicative risk [69]. Although two case-control studies did not show a relationship of alcohol consumption with the occurrence of HCC [70,71], another case-control study found a positive interaction between HBsAg positivity and HCV RNA positivity and heavy alcohol intake in the development of HCC [72]. Furthermore, Hassan et al. [73] showed synergistic interaction (more than additive) between heavy alcohol consumption ≥ 80 ml/d and chronic HBV or HCV infection (odds ratio 53.9) and insulin or non-insulin dependent diabetes mellitus (odds ratio 9.9).
Incidence of HBV- and HCV-related HCC worldwide
Chronic hepatitis B and C infection are responsible for the great majority of cases of HCC worldwide [9]. They also account for the peculiar geographical distribution of the tumor. The relative frequencies of HBV and/or HCV related HCC in the world is illustrated in Table 1[17,72,74-93]. The worldwide incidence of HCC varies and is predominantly related to the regional prevalence of chronic viral hepatitis and its associated chronic liver disease and cirrhosis. Aflatoxin intake has a role in the genesis of HCC only in patients who have pre-existing chronic hepatitis B [84].
Table 1 Relative frequencies of HBV and HCV related HCC in the world
Author [reference] Country Era Sample size HBsAg + (%) Anti-HCV + (%) HBsAg/anti HCV + (%) Other (%)
Chen, 1990 [74] Taiwan NR 66 35 (53.0) 15 (22.7) 7 (10.6) 9 (13.6)
Chuang, 1991 [75] Taiwan NR 128 87 (68.0) 13 (10.1) 12 (9.4) 16 (12.5)
Lee, 1992 [76] Taiwan NR 326 233 (71.5) 31 (9.5) 10 (3.1) 52 (15.9)
Jeng, 1991 [77] Taiwan NR 129 62 (48.1) 29 (22.5) 19 (14.7) 19 (14.7)
Leung, 1992 [78] Hong Kong 1986–90 424 341 (80.3) 16 (3.8) 15 (4.0) 52 (12.3)
Nishioka, 1990 [79] Japan NR 180 64 (35.6) 80 (44.4) 11 (6.1) 25 (13.9)
Saito, 1990 [80] Japan NR 253 49 (19.4) 136 (53.8) 2 (0.8) 66 (26.1)
Kiyosawa, 1990 [17] Japan 1958–89 83 19 (22.9) 51 (61.4) 10 (12.0) 3 (3.6)
Hassan, 2001 [81] Egypt 1995–96 33 5 (15.2) 25 (75.8) NR NR
Kew, 1990 [82] South Africa NR 380 137 (36.1) 63 (16.6) 47 (12.4) 127 (33.4)
Yu, 1990 [83] USA 1984–89 58 22 (37.9) 36 (62.1) NR NR
Di Bisceglie, 1991 [84] USA 1987–88 99 7 (7) 12 (12) 1 (1) 79 (79)
Hadziyannis, 1995 [85] Greece 1991–92 65 33 (50.8) 5 (7.6) 3 (4.5) 23 (38.3)
Colombo, 1989 [86] Italy 1975–88 132 19 (14.4) 64 (48.5) 22 (16.7) 27 (20.5)
Levrero, 1991 [87] Italy 1980–88 167 38 (22.8) 82 (49.1) 15 (9.0) 32 (19.2)
Simonetti, 1992 [88] Italy 1982–88 212 15 (7.1) 133 (62.7) 18 (8.5) 46 (21.7)
Donato, 1997 [72] Italy 1995–96 172 37 (21.5) 65 (37.8) 4 (2.3) 66 (38.4)
Stroffolini, 1998 [89] Italy 1996–97 1083 125 (11.5) 771 (71.2) 55 (5.1) 132 (12.2)
Bruix, 1989 [90] Spain NR 96 4 (4.2) 67 (69.8) 5 (5.2) 20 (20.8)
Nalpas, 1991 [91] France 1982–89 55 3 (5.5) 28 (50.9) 9 (16.3) 15 (27.3)
Van Roey, 2000 [92] Belgium 90s 154 37 (24.0) 62 (40.0) NR 55 (36.0)
Haydon, 1997 [93] UK 1985–94 80 13 (16.3) 22 (27.5) 2 (2.5) 43 (53.8)
NR: not reported; Bold: predominant cause
In the Far East and sub-Saharan Africa, where HBV is highly endemic, HBV is the main cause of HCC.
In areas with an intermediate rate of liver tumors such as Southern Europe, Egypt and Japan, HCV is the predominant cause of HCC. Here HCC is mostly discovered at an older age in patients with longstanding cirrhosis due to HCV.
In regions with a low incidence of HCC such as Northern Europe and the United States, HCC related to HCV or HBV infection are found in a minority of cases and the tumor is often related to other factors such as alcoholic liver disease. In these low endemic areas, HCC is usually discovered at an older age in patients with longstanding cirrhosis due to alcohol abuse [72]. In France, ethanol is still the leading cause of cirrhosis and was responsible for 60% of all HCC causes during the last decade [8].
Time trends in the incidence of HCC
An important epidemiological fact is the rising incidence of HCC in developed countries during the last two decades [79,89,95,99](Table 2).
Table 2 Time trends on the incidence of HCC in the world
Author [reference] Country Number/100,000 era 1 Number/100,000 era 2
El Serag, 1999 [95] USA 1976–80: 1.4 1991–95: 2.4
El Serag, 2000 [96] USA 1993–95: 2.3 1996–98: 7.0
Benhamiche, 1998 [97] (men) France 1976–79: 7.5 1992–95: 10.2
Stroffolini, 1998 [89] Italy 1969: 4.8 1994: 10.9
Law, 2000 [98] (men) Australia 1983–85: 2.1 1995–96: 4.0
Nishioka, 1991 [79] Japan 1968–77: 9.5 1984–85: 16.0
Yoshizawa, 2002 [99] Japan 1980: ca 10 2000: ca 40
In Japan, the HCC-related mortality rate has sharply increased since 1975 from 10/100,000 to almost 40/100,000 in 2000 [99]. An analysis of the Shinshu University Hospital (Japan) showed a change in etiology of the HCC [100]. Whereas in the 1971–1980 decade, hepatitis B was the predominant cause of HCC, in the 1991–1995 period hepatitis C was largely predominant (Table 3). However, the total numbers of yearly deaths because of HCC in HBsAg carriers' stays constant, approximately 10% in the survey conducted in 1995. The rapid increase of mortality due to HCC in Japan is mainly attributable (ca 80%) to persistent infection with HCV [99]. The hepatitis C epidemic in Japan originated due to intravenous drug use by the young generation after World War II during the late 40s and early 50s. It spread in the general population due to remunerated blood donors. Abrogation of paid blood donation in 1968, exclusion of blood units contaminated with HBV in 1973 and HCV in 1989 decreased the risk of posttransfusion hepatitis from > 50% in the 60s to almost zero at present. The incidence of HCV in Japan is decreasing. As the interval between the time of the initial infection with the hepatitis C virus and the development of HCC is 30 years [79], the growing incidence of HCC in Japan is expected to reach a plateau around the year 2015, and then to decrease [99].
Table 3 Changing causes of HCC in Japan, 1971–95
Author [reference] Era Sample size HBsAg + (%) Anti-HCV + (%) HBsAg/anti HCV + (%) Other (%)
Kiyosawa, 1992 [100] 1971–80 112 60 (54%) 38 (34%) 5 (4%) 9 (8%)
1981–90 267 82 (31%) 159 (59%) 4 (2%) 22 (8%)
1991–95 162 21 (13%) 126 (78%) 5 (3%) 10 (6%)
Bold: predominant cause
Also in Italy the mortality rate of HCC is rising [89] from 4.8/100,000 in 1969 to 10.9/100,000 in 1994, reflecting the large cohort of subjects infected with HCV through iatrogenic route during the 50s and 60s when glass syringes were commonly used for medical treatment. Likewise in Australia, France and the United States of America (US) the HCC mortality is increasing, most probably because people infected with HCV have grown old and reach the cancer-bearing age [95-98]. In the US, an increase of about 80% in the incidence of HCC over the past 20–30 years is described, it is estimated that approximately 15,000 new cases occur each year. Also in France the incidence of HCC is steadily and markedly increased, the estimated number being about 4,000 per year [101].
Although the prevalence of HCV is declining in developed countries because of the decline in incidence in the 90s, the number of persons infected for ≥ 20 years is expected to increase substantially before peaking in 2015 [102].
Analysis of long-term serial HCV samples from the US and Japan suggest that HCV was introduced into the US population around 100 years ago and widely disseminated in the 1960s. In contrast, HCV was introduced in Japan > 100 years ago and widely disseminated in the 1930s and 40s. The HCV genotype 1b population in Japan started to decrease around 1995 whereas HCV genotype 1a in the US is still growing exponentially. It is predicted that an increased HCC prevalence will occur in the US over the next two to three decades [103].
The reasons advocated for explaining the increased incidence of HCC are the increased rate of HCV infection and an improvement of the clinical management of cirrhotic patients. Enhancing the survival of patients with advanced cirrhosis leads to an increased incidence of HCC. In fact, a decade ago, most of the deaths in cirrhotic patients were due to digestive hemorrhage or bacterial infections, two conditions that are now efficiently prevented and cured [104]. Therefore, HCC has become the leading cause of death in patients with cirrhosis.
Screening tests for HCC in patients with chronic viral hepatitis
Despite knowledge of the risk factors for HCC, screening of HCC is controversial, as there have been no randomized controlled studies demonstrating the efficacy of screening for HCC. As HCC mostly occurs in patients with cirrhosis, or at least advanced fibrosis, most studies have been performed in these patients at risk. The most frequently used tests have been serum alfa-fetoprotein (AFP) and hepatic ultrasound (US).
There is one non randomized prospective cohort study suggesting that HCC was detected earlier and was more often resectable in patients who had twice yearly screening with serum AFP and hepatic US than in patients who had usual care [105].
Twenty-four studies, which included patients with chronic hepatitis B or C or both, addressed the sensitivities and specificities of screening tests [106].
Serum AFP for detection of HCC was evaluated in 19 studies. They were relatively consistent in showing that the sensitivity of serum AFP for detecting HCC increases from very low levels to moderately high levels of 60 to 80% as the threshold value decreased from 400 to 10 ng/mL, with corresponding specificity decreasing from 100 to 70–90%. A threshold between 10 and 19 ng/mL seems most appropriate as sensitivity usually is moderately high (45 to 100%), with a specificity of 70 to 90%. It has been shown that AFP is not always specific for HCC and titers can increase with flares of active hepatitis [107].
Seven studies evaluated screening with US, reporting high specificity of 95–100%, but variable sensitivity, varying from 11–99% [94].
A surveillance study combining US and AFP in 1,125 patients with HCV, HBV or both, reported a sensitivity of 100% when using a serum AFP > 10 ng/mL together with US, compared with a sensitivity of 75% using only AFP > 10 ng/mL and a sensitivity of 87% when using US alone [108].
Computed tomography and magnetic resonance imaging have a high sensitivity and specificity in detecting HCC, but are too expensive to be used in surveillance [1].
The surveillance intervals studied varied from 3 to 12 months. In a study of patients with hepatitis B, the most rapidly growing tumor increased from 1 to 3 cm in 5 months [109]. The ideal time for re-screening has not been identified. Some investigators suggest a 4–5 month interval, others have suggested that a 6-month interval may be most appropriate [109,110]. It is suggested that in case of concomitant HBV and HCV infection serum AFP levels should be obtained every 3 months, and that persistent AFP levels should prompt an aggressive imaging search for HCC [61].
It can be concluded that screening patients with advanced chronic hepatitis B or C with AFP and US may improve detection of HCC, but further studies are needed whether screening improves clinical outcomes.
Pathogenesis of hepatitis B and C-induced hepatocellular carcinoma
Introduction
Epidemiologic data indicate that chronic hepatitis B and C are independent risk factors for development of HCC [7,16]. Furthermore, animal models confirm the oncogenic potential of HBV and HCV in the liver: transgenic mice for hepatitis B and C [110,111], and natural models such as the woodchuck infected with the woodchuck hepatitis virus, a hepadnavirus closely related to the HBV [112].
Carcinogenesis is believed to be a multistage process, occurring through a sequence of steps termed initiation, promotion and progression. This process evolves over several or many years. Tumor initiation begins in cells through mutations induced by exposure to carcinogens. DNA changes, maintained during successive cell divisions, activation of oncogenes and inactivation of suppressor genes lead to dysregulation of the cell division and to immortalization [113]. Tumor-initiated cells have a decreased responsiveness to both intercellular and intracellular signals that maintain normal cellular architecture and regulate homeostatic growth. Tumor promotion results in a further selective clonal expansion of initiated cells. During tumor progression, pre-malignant cells continue to develop progressive phenotypic changes and genomic instability (dysplasia), culminating as overt carcinoma [115].
More than 80% of HCC originate in cirrhotic livers. Macronodules (macroregenerative nodules and adenomatous hyperplasia), irregular hepatocyte regeneration, and some hyperplastic foci are considered as precancerous [116-119]. Large cell dysplasia and small cell dysplasia are considered to be risk factors for development of HCC [120-122].
HBV and HCV can be implicated in the development of HCC in an indirect way, through induction of inflammation, necrosis and chronic hepatocellular regeneration, or directly by means of viral proteins or, in the case of HBV, by creating insertional mutations by integration in the genome of the hepatocyte.
Indirect carcinogenicity of HBV and HCV
In most patients with chronic hepatitis B and/or C the occurrence of HCC is preceded by a process of longstanding inflammation. It is probable that malignant transformation is related to continuous or recurring cycles of hepatocyte necrosis and regeneration [123]. The resulting accelerated cell turnover rate may act as a tumor promotor by increasing the probability of spontaneous mutations or damage to DNA by exogenous factors. The accelerated rate of cell division leaves less time for altered DNA to be repaired before the cell divides again, resulting in transmission of altered DNA to the daughter cells. In this way a series of mutations may accumulate in individual cells over time. This process can lead to focal uncontrolled liver cell growth and eventual malignant cell transformation [115,124]. Another mechanism of induction of malignant transformation is the generation of mutagenic reactive oxygen species as a result of the inflammatory process, such as nitric oxide (NO), superoxide anion (O2-), hydroxyl radical (OH•) and hydrogen peroxide (H2O2) [124].
Evidence for a causal role for chronic necro-inflammation is provided by transgenic mice into which HBV preS/S genes have been introduced. These mice overproduce pre S1 protein that accumulates in the endoplasmatic reticulum of hepatocytes, producing severe and prolonged injury to these cells, initiating a response characterized by inflammation, regenerative hyperplasia and transcriptional deregulation that progresses ultimately to neoplasia [125].
Patterns of gene expression in cirrhosis and hepatocellular carcinoma have recently been shown to be of value in predicting prognosis. Kim et al could identify, using the complementary DNA microarray, a 273-gene signature that distinguished high risk types of cirrhosis (hepatitis B, hepatitis C, hereditary hemochromatosis) from low risk types (autoimmune hepatitis, PBC, alcoholic liver diseases) [126]. The same 273-gene signature was present in samples from patients with proven HCC. A subset of 30 genes was most significantly altered in both the high risk types of cirrhosis and the HCC patients. The TACSTD1, a gene associated with HCC development in other studies, is a lead gene in this gene signature. Lee et al could identify a limited number of genes that accurately predicted survival in a series of 91 HCC patients [127]. The genes involved are implicated in cell proliferation and apoptosis, but also in ubiquitination and histone modification. Delpuech et al identified distinct patterns of gene expression according to the viral aetiology [128]. Finally, Hann et al could demonstrate the presence of antibodies to differentially expressed genes in hepatitis B and C, and this appeared to be linked with decreased survival [129]. These discoveries not only increase our insight in hepatocarcinogenesis, but may ultimately lead to the development of clinically valuable preneoplastic and prognostic blood markers.
Direct carcinogenicity of HBV and HCV
Hepatitis B
A significant proportion of HBV-related HCCs arise in an otherwise normal liver, implicating that the virus can also be directly oncogenic [124].
It has been demonstrated that HBV integrates into the DNA of the host cells. This integration may dysregulate the control mechanisms on the cell cycle by chromosomal abnormalities, production of viral proteins or alteration of human genes and proto-oncogenes. It is, however, controversial whether viral integration plays an important role in the process leading to development of HCC. The hepadnaviral integration process appears to involve recombination mechanisms that do not preserve the viral genome sequence. Thus it is impossible for the viral integrant to function as a template for subsequent virus replication. Several studies suggest that DNA integration sites are at random and that integration occurs at random times during the course of a chronic viral infection [130,131]. HBV integration can be present in chronically infected liver tissue without evidence of HCC [132]. Non-neoplastic hepatocytes may have a similar pattern of rearrangement of viral sequences following integration into human DNA.
Chromosomal DNA instability
Several studies have shown that HBV DNA integration enhances chromosomal instability. In many hepatic tumors large inverted duplication insertions, translocations and micro- and macrochromosomal deletions have been associated with HBV insertion [133-136]. These changes can result in loss of important cellular genes, sometimes involving tumor-suppressor genes and other genes involved in the regulation of regeneration and growth processes.
Trans-activation of cellular genes
HBV DNA may induce malignant transformation in another way.
Mammalian hepadnaviruses contain a gene (the HBX gene), of which the protein (HBX protein) can trans-activate several cellular promotors and upregulate their expression of different cellular and viral genes [137,138]. Integrated HBX, even when truncated, frequently encodes functionally active trans-activator proteins [139]. This protein has been shown to transform mouse fetal hepatocytes into a full malignant phenotype [140]. There are studies in transgenic mice with the HBX gene that developed multifocal areas of altered hepatocytes, adenomas and HCCs [110].
In contrast to mammalian hepadnaviruses associated with HCC, avian hepadnaviruses such as the duck hepatitis virus or heron hepatitis virus, lack the HBX gene and are not associated with HCC [123].
A gene that may be affected by the HBX gene is the p53 tumor suppression gene. This gene has been shown to play an important role in hepatocarcinogenesis. It is considered to negatively regulate the cell cycle. The HBX protein has been shown to complex p53 protein and to inhibit its function [141,142]. In a transgenic mouse model it was shown that HCC development correlates with p53 binding to HBX [143].
Oncogenes
It has been proposed that HBV acts as an insertion mutagen by integrating into the host genome and activating the cellular proto-oncogenes c-myc, ras and c-fos [144].
The preS2/S gene is integrated in most HCCs associated with HBV. When 3'-truncated it generates a truncated protein that is oncogenic by trans-activating proto-oncogenes c-myc and c-fos [145].
Growth factors
Growth factors and their receptors function as positive or negative modulators of cell proliferation and differentiation. Insulin-like growth factor-II and transforming growth factor-β expression correlate with HBX protein expression in animal models [146,147], suggesting trans-activation of these growth factors facilitating tumor formation.
Role of PreS mutations
PreS deletion mutants accelerate the storage of large envelope proteins in hepatocyte cytoplasm, which could induce cytotoxic effects toward the development of end-stage liver disease [148]. The accumulation of large envelope protein can activate cellular promoters by inducing endoplasmic reticulum stress [149]. Furthermore, pre-S1 sequences can stimulate the transcription of transforming growth factor α (TGFα). Coexpression of TGFα and HBsAg could accelerate hepatocellular carcinogenesis by stimulation of hepatocyte proliferation [150].
Allelic loss of chromosome 4q
Allelic loss of chromosome 4q is one of the most frequent genetic aberrations found in HCC. It was found to be associated with HBV-related hepatocarcinogenesis, probably by inactivation of a putative tumor suppressor gene included in it [151].
Hepatitis C
In contrast to HBV, HCV is an RNA virus that lacks a reverse-transcriptase enzyme and cannot integrate into the host genome. Thus, insertional mutagenesis can be excluded as a pathogenic mechanism for the development of HCC associated with chronic HCV infection. The molecular pathogenetic mechanisms by which HCV contributes to cell transformation remain unclear.
One possibility is that the development of HCC is simply related to chronic necro-inflammatory liver disease. Overall, 97% of patients with HCV markers and HCC have cirrhosis [152,153], and most of the remainder develop HCC in the presence of chronic hepatitis.
An alternative mechanism of HCV-induced hepatocarcinogenesis may be that HCV has a direct oncogenic action. Viral replication might cause inappropriate expression of two growth factors that may be implicated in hepatic carcinogenesis: transforming growth factor-α and insulin-like growth factor II [154,155].
The non-structural HCV protein NS3 has both protease and helicase activity. HCV may therefore induce genomic instability and favor mutations through its helicase activity [156]. The protein also has an activity similar to protein kinase A, and could disturb cellular homeostasis [157].
The HCV envelope protein E2 and the non-structural protein NS5A inhibit RNA-dependent protein kinase, key mediator of the antiviral, antiproliferative and anti-oncogenic effect of interferon [158-160].
The HCV core protein has characteristics that imply that this protein could function as a gene-regulator [161,162]. The presence of the protein in transgenic mice can induce HCC [111]. After mutation, the HCV core protein can also inhibit tumor suppressor genes such as p53, as has been demonstrated in hepatic oncogenesis [163-165]. It has recently been shown that the HCV core protein induces nuclear factor κB (NF-κB), thereby suppressing TNF-α-induced apoptosis [166]. This anti-apoptosis may be a mechanism by which HCV leads to viral persistence and possibly to hepatocarcinogenesis.
Prevention of hepatocellular carcinoma caused by viral hepatitis
Primary prevention
The most effective tool to prevent HCC is avoidance of the risk factors such as viral infection by HBV or HCV. Any action diminishing the potential transmission of contaminated blood products (uncontrolled blood transfusion, needle sharing, invasive procedures without proper health standards) will decrease the likelihood of viral spread.
The major advance has come from the availability of an effective vaccine that protects against HBV.
In 1969, Taiwan was an hyperendemic area of HBV infection with a high rate of HBsAg positivity, 19% of the population being infected before the fourth decade of life. In 1976, HBsAg prevalence was > 80% in HCC in Taiwan [167]. In 1984 a program to control cirrhosis and HCC began. All neonates born to HBsAg positive mothers were given hepatitis B vaccine in order to counter perinatal infection. In 1986 all neonates were included in the program. As a consequence, there was a decrease in HBsAg positivity in six-year-olds from 10.6% in 1983–1984 to 0.8% in 1993–1994. There was a parallel decline in incidence of childhood HCC (6–14 years old), in the cohort born between 1980 and 1984. The incidence of liver cancer in children between 6 and 14 years old decreased to zero for children born in 1986 and 1987 [168]. The decline of HCC in children after universal vaccination can be considered as an early indicator of the effectiveness of vaccination in reducing the rate of HCC. Since the incidence of HCC in Taiwan peaks in the sixth decade of life, it may take 40 years or longer to see an overall decrease in the rate of HCC as a result of the vaccination program. Vaccination against HBV should become a health priority together with the promotion of adequate health standards.
Unfortunately, there is no vaccine against HCV. Up to now, the only effective method to prevent its transmission is the avoidance of contamination with infective blood products.
Prevention of HCC in patients with previously acquired risk
Introduction
Chronic viral carriage is one of the main risk factors for the development of HCC. Effective antiviral treatments have been developed in recent years and this has changed the management of viral infection.
Interferon-alfa is still considered the reference therapy for HBeAg positive chronic hepatitis B. However, its efficacy is limited, with seroconversion from anti-HBe negative to anti-HBe positive in up to 40%. Only <10% of patients become HBsAg negative [169]. Other possible treatments are antiviral drugs such as lamivudine and adefovir dipivoxil [12].
For the treatment of chronic hepatitis C, interferon-alfa monotherapy yielded only limited response. Combination with ribavirin led to a significant increase in sustained viral response to about 40% in treatment-naïve patients [170,171]. Recently, the combination of peginterferon-alfa and ribavirin improved the sustained viral response rate to nearly 60% in treatment-naïve patients [172,173], and is now considered the reference treatment.
It is under debate whether interferon-alfa-based treatments are effective in declining the incidence of HCC in chronic hepatitis B and C.
Anti-oncogenic effects of interferon-alfa
HCC prevention by interferon-alfa might be the result of several direct or indirect mechanisms. Interferon has an antiproliferative and pro-apoptotic effect [174]. Interferon inhibits the expression of the c-myc oncogene and induces the expression of anti-proliferative factors and tumor suppressor genes [175-177]. In experimental animal models, the anti-neoplastic potential of interferon was demonstrated in already established tumors. In a transgenic mouse model it was demonstrated that early and prolonged administration of interferon diminished the severity of preneoplastic lesions and slowed down the development of HCC [178]. Interferon-alfa also could indirectly reduce the oncogenic risk by inhibition of synthesis of viral proteins which potentially dysregulate the cell cycle, and by enhancing the immune system eliminating not only infected hepatocytes but also initiated or fully malignant cells. Furthermore, interferon-alfa has an antifibrotic and anti-angiogenetic effect, which could also have an influence on tumor development [179].
Interferon and antiviral treatment
Noncirrhotics
In patients with chronic hepatitis B, clearance of the HBeAg after treatment with interferon-alfa is associated with improved clinical outcome in terms of survival and development of complications of cirrhosis [180]. Another study confirmed these results and showed a reduction of incidence of HCC in the responders [181]. As most of these patients were non-cirrhotics at entry of the study, the prophylactic effect of interferon on development of HCC can be explained by prevention of cirrhosis development. In Chinese patients with chronic hepatitis B infection, however, interferon-alfa was of no long-term benefit in inducing HBeAg conversion, or in the prevention of HCC and other cirrhosis-related complications [182].
Cirrhotics
Seven studies investigated the possible effect of interferon treatment on development of HCC in patients with already established cirrhosis [183-189] (Table 4). A meta-analysis was performed on these studies [190]. Interferon seemingly decreased the rate of HCC in all trials, while a significant difference was observed in 2 studies [183,186]. Virologic response was strongly associated with reduced risk for HCC in the studies of Oon [183] and Mazzella [184], suggesting that arrest of viral replication is a critical factor. Subgroup analysis in relation to ethnic origin of patients (European, Oriental) showed no preventive effect of interferon on the development of HCC in the European patients [190].
Table 4 Studies of treatment with interferon-α for prevention of HCC in patients with hepatitis B-related cirrhosis
Author [reference] Country Type of study Interferon regimen (duration in weeks) Follow-up (range) in months Sample size Rate of HCC (n/n) Significance
Oon, 1992 [183] Singapore NRCT, P 10 MU daily, 10 days/month (12) 12 (12–60) T 600
C 180 T: 0/600 (0%)
C: 10/180 (5.6%) Significant
Mazzella, 1996 [184] Italy NRCT, P 10 MU tiw (26) 49 (12–119) T 34
C 28 T: 2/34 (5.9%)
C: 4/28 (14.3%) Not significant
Fattovich, 1997 [185] Europe NRCT, P ≥ 300 MU (12–52) 84 (80–92) T 40
C 50 T: 3/40 (7.5%)
C: 4/50 (8.0%) Not significant
Ikeda, 1998 [186] Japan NRCT, P 12 MU/wk (26) 84 (6–168) T 94
C 219 T: 10/94 (10.6%)
C: 51/219 (23.3%) Significant
IHCSG, 1998 [187] Argentina, Germany, Italy, Saudi Arabia NRCT, P 9–30 MU/wk for 3–30 months (36–250) T 49
C 97 T: 8/49 (16.3%) C: 18/97 (18.6%) Not significant
Benvegnù, 1998 [188] Italy NRCT, P 6–10 MU (20–26) 72 T 10
C 18 T: 0/10 (0%)
C: 4/18 (22.2%) Not significant
Di Marco, 1999 [189] Italy NRCT, P 655 MU 93 (6–180) T 26
C 60 T: 2/26 (7.7%)
C: 6/60 (10%) NR
NRCT: non-randomized controlled trial
P: prospective
T: treated
C: controls
MU: million units
NR: not reported
It should be noted that the studies are very heterogeneous and that none of them were randomized controlled trials, so that the results should be interpreted with caution.
A recent study showed a significant reduction of the risk of HCC in patients with chronic hepatitis B and advanced fibrosis or cirrhosis, treated with lamivudine for a maximum of five years, compared to placebo [191].
Interferon treatment in HCV patients and HCC prevention
Noncirrhotics
Three studies assessed whether interferon treatment prevents the development of HCC in noncirrhotic patients with chronic hepatitis C [192-194] comprising 3,798 noncirrhotic patients treated with interferon-alfa monotherapy. Pooled together, the incidence of HCC was 60/2,532 (2.37%) in sustained virological responders and 76/1,266 (5.29%) in nonresponders. In a study of 291 noncirrhotic patients with chronic hepatitis C who were nonresponders to interferon therapy and followed for 6–117 months after therapy, the incidence of HCC was significantly lower in patients who received > 500 MU of interferon. Patients with a transient response (i.e. relapse after end of treatment) had a significant lower rate of HCC development (4/166 = 2.4%) than nonresponders (12/125 = 9.6%) [195].
This anti-oncogenic benefit can presumably be explained by an arrest or slowing down of the cirrhogenic process.
Cirrhotics
The findings of 13 studies of interferon treatment and development of HCC in HCV-infected patients with compensated cirrhosis are summarized in Table 5[45,184-186,194,196-204]. Only 3 studies were randomized [199,201,202,204], the remainders were observational cohort studies. Statistical combination of data is not possible because of different definitions of response (biochemical, virological), different dose schedules for interferon and different duration of follow-up. All studies showed a lower risk for development of HCC in the interferon-treated patients, suggesting that interferon may prevent HCC in compensated cirrhosis caused by hepatitis C. The overall result was largely influenced by three Japanese studies [194,198,201,202], which had the highest incidence of HCC in untreated patients (5–6% per year). This may be explained by intensiveness of the screening programs, but also by genetic, environmental or viral factors. Four European studies failed to document a significant reduction in risk of developing HCC [45,196,199]. In the studies of Fattovich et al [196] and Bruno et al [45], interferon-alfa treatment showed a decrease in incidence of HCC in univariate analysis. However, this was not present in multivariate analysis. In the study of Fattovich [196], a very low natural incidence of HCC was observed, rendering difficult to show a significant decrease. The prospective randomized controlled trial of Valla et al [199] also failed to show a significant effect of interferon treatment on the development of HCC. However, the number of patients in this study was limited and the follow-up relatively short. Also a recently published randomized controlled study from Italy comprising 51 interferon-treated and 71 untreated patients with compensated hepatitis C-cirrhosis, failed to demonstrate any reduced risk in development of HCC after a mean follow-up of 96.5 months [204].
Table 5 Studies on treatment with interferon-α for prevention of HCC in patients with HCV-related cirrhosis
Author [reference] Country Type of study Interferon regimen (duration in weeks) Follow-up (range) in months Sample size Rate of HCC (n/n) Significance
Mazzella, 1996 [184] Italy NRCT, P 3 MU tiw (52) 32 (12–71) T 193
C 91 T: 5/193 (2.6%)
C: 9/91 (9.9%) Significant
Fattovich, 1997 [196] Europe NRCT, P ≥ 200 MU 60 (1–153) T 193
C 136 T: 7/193 (3.6%)
C: 16/136 (11.8%) Not significant
Bruno, 1997 [45] Italy NRCT, P 6 MU tiw (26) 68 (60–84) T 82
C 81 T: 6/82 (7.3%)
C: 14/81 (17.3%) Not significant
Serfaty, 1998 [197] France NRCT, P 3 MU tiw (48) 40 (6–72) T 59
C 44 T: 2/59 (3.4%)
C: 9/44 (20.1%) Significant
IHCSG, 1998 [187] Argentina, Germany, Italy, Saudi Arabia NRCT, R 9–30 MU/wk (3–30 months) (36–250) T 232
C 259 T: 2/232 (0.9%)
C: 48/259 (18.5%) Significant
Imai, 1998 [198] Japan NRCT, R 480 MU (26) 48 (3–65) T 32
C 20 T: 8/32 (25%)
C: 7/20 (35%) Significant
Benvegnù, 1998 [188] Italy NRCT, P 3–6 MU tiw (26–52) 72 T 75
C 77 T: 4/75 (5.3%)
C: 20/77 (26.0%) Significant
Valla, 1999 [199] France RCT 3 MU TIW (48) 40 (37–53) T 47
C 52 T: 5/47 (10.6%)
C: 9/52 (17.3%) Not significant
Yoshida, 1999 [194] Japan NRCT, R 480 MU (23) 52 T 230
C 107 T: 33/230 (14.3%)
C: 29/107 (27.1%) NR
Okanoue, 1999 [200] Japan NRCT, R 3–10 MU qd or tiw (16–24) 1–7 years T 40
C 55 T: 7/40 (17.5%)
C: 22/55 (40.0%) NR
Nishiguchi, 1995/2001 [201,202] Japan RCT 6 MU tiw (12–24) 104 (31–110) T 45
C 45 T: 12/45 (26.7%)
C: 33/45 (73.3%) Significant
Gramenzi, 2001 [203] Italy RCT, P 741 MU 72 T 72
C 72 T: 6/72 (8.3%)
C: 19/72 (26.4%) Significant
Testino, 2002 [204] Italy RCT 3 MU tiw (52) 96.5 ± 18 T 51
C 71 T: 15.51 (29.4%)
C: 24/71 (33.8%) Not significant
NRCT: non-randomized controlled trial
RCT: randomized controlled trial
P: prospective
R: retrospective
NR: not reported
T: treated
C: controls
MU: million units
In most studies, virological and/or biochemical response are associated with a lower risk of development of HCC, which is less clear in nonresponders. In the study of Imai et al. [198], patients with sustained biochemical response after interferon therapy were at low risk for development of HCC (risk ratio versus controls 0.06; 0.95 in nonresponders). Also in the study of Mazzella [184], a statistically significant effect of interferon treatment was demonstrated when biochemical responders were compared with controls but not when compared with nonresponders. In the study of Benvegnù et al [188], the beneficial effect of interferon treatment on development of HCC was independent of the type of response. In the study of Yoshida et al [194] the risk for HCC was reduced especially among patients with sustained virological but also merely biochemical response that tested positive for HCV RNA. Okanoue et al [200] studied 1,148 patients with chronic hepatitis C treated with interferon-alfa, 40 of them having cirrhosis (fibrosis stage F4). They were followed for 1–7 years after therapy. The cumulative incidence of HCC was significantly decreased in sustained biochemical responders, compared to nonresponders and transient responders, in patients with stage F2 fibrosis, but not in the more advanced stages F3 and F4. In the study of Testino et al [204] HCC did also develop in sustained biochemical responders. Tanaka et al [205], however, demonstrated in 55 patients with HCV-cirrhosis that long-term administration of interferon prevented HCC in those with biochemical and virological response, whereas HCC only appeared in nonresponders.
The mechanisms by which an interferon treatment might reduce the risk of HCC development in cirrhosis caused by HCV independent of virological response remains speculative. Maintenance of serum transaminases at low levels may protect against the development of HCC as hepatocyte necrosis, cell damage and increase in hepatocyte replication result in increased DNA damage, influencing hepatocarcinogenesis. Other possible mechanisms for prevention of HCC are the direct and indirect effects of interferon. It is, however, perplexing that only 6 or 12 months of therapy can produce this benefit without virological response. Because of potential biases in the published trials it is premature to advocate the use of interferon as established therapy in HCV infected patients with cirrhosis to prevent HCC. Prospective randomized controlled trials should reproduce the findings in large numbers of patients before a definitive conclusion on the long term effects of interferon in HCV cirrhosis can be established.
It must also be realized that a sustained virological response to interferon-alfa monotherapy can be obtained only in 0–8% of patients with cirrhosis [206-208]. New treatments are now available for chronic hepatitis C, which are more performant in difficultly to treat cases as patients with cirrhosis. The combination of interferon-alfa and ribavirin results in a sustained virologic response in up to 25% of cirrhotics due to hepatitis C [207]. A sustained virologic response of 32% was reported after peginterferon-alfa-2a monotherapy [207] and of 43% after combination of peginterferon-alfa2a and ribavirin [173]. It should be investigated in prospective trials, taking into account the sustained virological and biochemical responses if these more performant treatment regimens will also influence favorably the incidence of HCC, as no data on the long-term effects of these treatments are available up to now.
Secondary prevention
A few sudies focus on the possible role of intereron in the secondary prevention of HCC recurrence in patients with chronic hepatitis B and C after curative resection or ablation.
Ikeda et al [209] showed that interferon prevented HCC recurrence after complete resection or ablation of the primary tumor depending on the clearance of HCV viremia. Kubo et al [210] reported a decreased recurrence after surgical resection independent of clearance of HCV or normalization of serum ALT. Another study demonstrated prevention of HCC recurrence after medical ablation therapy for primary tumors in hepatitis B but not in hepatitis C patients by the use of interferon-alfa [211].
Conclusions
Chronic hepatitis B and C, mostly in the cirrhotic stage, are
responsible for the majority of the hepatocellular carcinomas worldwide.
The rising incidence in HCC in developed countries during the last two
decades is due to the increasing rate of hepatitis C infection and
improvement of the clinical management of cirrhosis.
Vaccination against hepatitis B seems to protect against the development
of HCC.
In patients with chronic hepatitis B or C, interferon alpha treatment in
a noncirrhotic stage is protective for HCC development in responders,
probably by prevention of cirrhosis development. When cirrhosis is
already present, the protective affect is less clear. Further
prospective long-term studies should be performed on the new treatments
for chronic hepatitis B and C. Some studies also suggested a favourable
effect of interferon alpha in the prevention of HCC recurrence in
patients with chronic hepatitis B and C after curative resection or
ablation.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
PPM participated in the literature search and was responsible for
the redaction of the paper.
SMF participated in the redaction of the manuscript and critical
review of the paper.
JLV participated in the literature search and finalizing of the
lay-out of the paper.
==== Refs
Bruix J Sherman M Llovet JM Beaugrand M Lencioni R Burroughs AK Christensen E Pagliaro L Colombo M Rodes J EASL Panel of Experts on HCC Clinical management of hepatocellular carcinoma. Conclusions of the Barcelona-2000 EASL conference J Hepatol 2001 35 421 430 11592607 10.1016/S0168-8278(01)00130-1
Llovet JM Beaugrand M Hepatocellular carcinoma: present status and future prospects J Hepatol 2003 38 136 149 12547401 10.1016/S0168-8278(02)00432-4
Bosch FX Ribes J Borras J Epidemiology of primary liver cancer Semin Liver Dis 1999 19 271 285 10518307
Zaman SN Melia WM Johnson RD Portmann BC Johnson PJ Williams R Risk factors in development of hepatocellular carcinoma in cirrhosis: prospective study of 613 patients Lancet 1985 1 1357 1360 2861313 10.1016/S0140-6736(85)91785-4
Poynard T Aubert A Lazizi Y Bedossa P Hamelin B Terris B Naveau S Dubreuil P Pillot J Chaput JC Independent risk factors for hepatocellular carcinoma in French drinkers Hepatology 1991 13 896 901 1851493 10.1016/0270-9139(91)90260-3
Colombo M de Franchis R Del Ninno E Sangiovanni A De Fazio C Tommasini M Donato MF Piva A Di Carlo V Dioguardi N Hepatocellular carcinoma in Italian patients with cirrhosis N Engl J Med 1991 325 675 680 1651452
Tsukuma H Hiyama T Tanaka S Nakao M Yabuuchi T Kitamura T Nakanishi K Fujimoto I Inoue A Yamazaki H Kawashima T Risk factors for hepatocellular carcinoma among patients with chronic liver disease N Engl J Med 1993 328 1797 1801 7684822 10.1056/NEJM199306243282501
Chevret S Trinchet JC Mathieu D Rached AA Beaugrand M Chastang C A new prognostic classification for predicting survival in patients with hepatocellular carcinoma J Hepatol 1999 31 133 141 10424293 10.1016/S0168-8278(99)80173-1
International Agency for Research on Cancer Hepatitis Viruses IARC Monographs on the Evaluation of Carcinogenic Risks to Humans 1994 59 Lyon: IARC
Kew MC Dusheiko GM Hadziyannis SJ Paterson A Does Delta infection play a part in the pathogenesis of hepatitis B virus related hepatocellular carcinoma? Br Med J 1984 288 1727 6329398
Verme G Brunetto MR Oliveri F Baldi M Forzani B Piantino P Ponzetto A Bonino F Role of hepatitis delta virus infection in hepatocellular carcinoma Dig Dis Sci 1991 36 1134 1136 1650690 10.1007/BF01297460
EASL Jury EASL International Consensus Conference on Hepatitis B. 13–14 September, 2002: Geneva, Switzerland. Consensus statement (short version) J Hepatol 2003 38 533 540 12663250
Yotsuyanagi H Yasuda K Iino S Moriya K Shintani Y Fujie H Tsutsumi T Kimura S Koike K Persistent viremia after recovery from self-limited acute hepatitis B Hepatology 1998 27 1377 1382 9581694 10.1002/hep.510270526
Okada K Kamiyama I Inomata M Imai M Miyakawa Y e antigen and anti-e in the serum of asymptomatic carrier mothers as indicators of positive and negative transmission of hepatitis B virus to their infants N Engl J Med 1976 294 746 749 943694
Liaw YF Tai DI Chu CM Lin DY Sheen IS Chen TJ Pao CC Early detection of hepatocellular carcinoma in patients with chronic type B hepatitis. A prospective study Gastroenterology 1986 90 263 267 2416625
Beasley RP Hwang LY Lin CC Chien CS Hepatocellular carcinoma and hepatitis B virus. A prospective study of 22707 men in Taiwan Lancet 1981 2 1129 1133 6118576 10.1016/S0140-6736(81)90585-7
Kiyosawa K Sodeyama T Tanaka E Gibo Y Yoshizawa K Nakano Y Furuta S Akahane Y Nishioka K Purcell RH Alter HJ Interrelationship of blood transfusion, non-A, non-B hepatitis and hepatocellular carcinoma: analysis by detection of antibody to hepatitis C virus Hepatology 1990 12 671 675 2170265
Realdi G Fattovich G Hadziyannis S Schalm SW Almasio P Sanchez-Tapias J Christensen E Giustina G Noventa F Survival and prognostic factors in 366 patients with compensated cirrhosis type B: a multicenter study J Hepatol 1994 21 656 666 7814813 10.1016/S0168-8278(94)80115-0
Fattovich G Giustina G Schalm SW Hadziyannis S Sanchez-Tapias J Almasio P Christensen E Krogsgaard K Degos F Carneiro De Moura M Solinas A Noventa F Realdi G Occurrence of hepatocellular carcinoma and decompensation in western European patients with cirrhosis type B Hepatology 1995 21 77 82 7806171 10.1016/0270-9139(95)90411-5
Fattovich G Progression of hepatitis B and C to hepatocellular carcinoma in western countries Hepatogastroenterology 1998 45 1206 1213 9730376
Fattovich G Pantalena M Zagni I Realdi G Schalm SW Christensen E Effect of hepatitis B and C virus infections on the natural history of compensated cirrhosis: a cohort study of 297 patients Am J Gastroenterol 2002 97 2886 2895 12425564 10.1111/j.1572-0241.2002.07057.x
Sakuma K Saitoh N Kasai M Jitsukawa H Yoshino I Yamaguchi M Nobutomo K Yamumi M Tsuda F Komazawa T Relative risks of death due to liver disease among Japanese male adults having various statuses for hepatitis B s and e antigen/antibody in serum: a prospective study Hepatology 1988 8 1642 1646 3192178
Yang HI Lu SN Liaw YF You SL Sun CA Wang LY Hsiao CK Chen PJ Chen DS Chen CJ Taiwan Community-Based Cancer Screening Project Group Hepatitis B e antigen and the risk of hepatocellular carcinoma N Engl J Med 2002 347 168 174 12124405 10.1056/NEJMoa013215
Ohkubo K Kato Y Ichikawa T Kajiya Y Takeda Y Higashi S Hamasaki K Nakao K Nakata K Eguchi K Viral load is a significant prognostic factor for hepatitis B virus-associated hepatocellular carcinoma Cancer 2002 94 2663 2668 12173334 10.1002/cncr.10557
Yano Y Yamashita F Sumie S Ando E Fukumori K Kiyama M Oyama T Kuroki S Kato O Yamamoto H Tanaka M Sata M Clinical features of hepatocellular carcinoma seronegative for both HBsAg and anti-HCV antibody but positive for anti-HBc antibody in Japan Am J Gastroenterol 2002 97 156 161 11808941 10.1111/j.1572-0241.2002.05440.x
Okamoto H Tsuda F Sakugawa H Sastrosoewignjo RI Imai M Miyakawa Y Mayumi M Typing hepatitis B virus by homology in nucleotide sequence: comparison of surface antigen subtypes J Gen Virol 1988 69 2575 2583 3171552
Stuyver L De Gendt S Van Geyt C Zoulim F Fried M Schinazi RF Rossau R A new genotype of hepatitis B virus: complete genome and phylogenetic relatedness J Gen Virol 2000 81 67 74 10640543
Arauz-Ruiz P Norder H Robertson BH Magnius LO Genotype H: a new Amerindian genotype of hepatitis B virus revealed in Central America J Gen Virol 2002 83 2059 2073 12124470
Norder H Courouce AM Magnius LO Complete genomes, phylogenetic relatedness, and structural proteins of six strains of the hepatitis B virus, four of which represent two new genotypes Virology 1994 198 489 503 8291231 10.1006/viro.1994.1060
Kao JH Chen PJ Lai MY Chen DS Hepatitis B genotypes correlate with clinical outcomes in patients with chronic hepatitis B Gastroenterology 2000 118 554 559 10702206
Ding X Mizokami M Yao G Xu B Orito E Ueda R Nakanishi M Hepatitis B virus genotype distribution among chronic hepatitis B virus carriers in Shanghai, China Intervirology 2001 44 43 47 11223719 10.1159/000050029
Orito E Ichida T Sakugawa H Sata M Horiike N Hino K Okita K Okanoue T Iino S Tanaka E Suzuki K Watanabe H Hige S Mizokami M Geographic distribution of hepatitis B virus (HBV) genotype in patients with chronic HBV infection in Japan Hepatology 2001 34 590 594 11526547 10.1053/jhep.2001.27221
Chen JD Liu CJ Lee PH Chen PJ Lai MY Kao JH Chen DS Hepatitis B genotypes correlate with tumor recurrence after curative resection of hepatocellular carcinoma Clin Gastroenterol Hepatol 2004 2 64 71 15017634 10.1016/S1542-3565(03)00293-3
Kao JH Chen PJ Lai MY Chen DS Basal core promoter mutations of hepatitis B virus increase the risk of hepatocellular carcinoma in hepatitis B carriers Gastroenterology 2003 124 327 334 12557138 10.1053/gast.2003.50053
Sugauchi F Ohno T Orito E Sakugawa H Ichida T Komatsu M Kuramitsu T Ueda R Miyakawa Y Mizokami M Influence of hepatitis B virus genotypes on the development of preS deletions and advanced liver disease J Med Virol 2003 70 537 544 12794715 10.1002/jmv.10428
Anon Global surveillance and control of hepatitis C. Report of a WHO Consultation organized in collaboration with the Viral Hepatitis Prevention Board, Antwerp, Belgium J Viral Hepat 1999 6 35 47 10847128 10.1046/j.1365-2893.1999.6120139.x
Crowe J Doyle C Fielding JF Holloway H Keegan M Kelleher D Kelly P Leader M Little M McDonald G McCarthy CF McWeeney J O'Keane C Rajan E Presentation of hepatitis C in a unique uniform cohort 17 years from inoculation [abstract] Gastroenterology 1995 108 1054
Poynard T Bedossa P Opolon P Natural history of liver fibrosis progression in patients with chronic hepatitis C Lancet 1997 349 825 832 9121257 10.1016/S0140-6736(96)07642-8
Hopf U Moller B Kuther D Stemerowicz R Lobeck H Ludtke-Handjery A Walter E Blum HE Roggendorf M Deinhardt F Long-term follow-up of posttransfusion and sporadic chronic hepatitis non-A, non-B and frequency of circulating antibodies to hepatitis C virus (HCV) J Hepatol 1990 10 69 76 2106548 10.1016/0168-8278(90)90075-3
Di Bisceglie AM Goodman ZD Ishak KG Hoofnagle JH Melpolder JJ Alter HJ Long-term clinical and histopathological follow-up of chronic posttransfusion hepatitis Hepatology 1991 14 969 974 1959884 10.1016/0270-9139(91)90113-A
Tremolada F Casarin C Alberti A Drago C Tagger A Ribero ML Realdi G Long-term follow-up of non-A, non-B (type C) post-transfusion hepatitis J Hepatol 1992 6 273 281 1487603 10.1016/S0168-8278(05)80657-9
Koretz RL Abbey H Coleman E Gitnick G Non-A, non-B post-transfusion hepatitis. Looking back in the second decade Ann Intern Med 1993 119 110 115 8512159
Mattsson L Sonnerborg A Weiland O Outcome of acute symptomatic non-A, non-B hepatitis: a 13-year follow-up study of hepatitis C virus markers Liver 1993 13 274 278 7505044
Bolondi L Sofia S Siringo S Gaiani S Casali A Zironi G Piscaglia F Gramantieri L Zanetti M Sherman M Surveillance programme of cirrhotic patients for early diagnosis and treatment of hepatocellular carcinoma: a cost effectiveness analysis Gut 2001 48 251 259 11156649 10.1136/gut.48.2.251
Bruno S Silini E Crosignani A Borzio F Leandro G Bono F Asti M Rossi S Larghi A Cerino A Podda M Mondelli MU Hepatitis C virus genotypes and risk of hepatocellular carcinoma in cirrhosis: a prospective study Hepatology 1997 25 754 758 9049231 10.1002/hep.510250344
Ikeda K Saitoh S Koida I Arase Y Tsubota A Chayama K Kumada H Kawanishi M A multivariate analysis of risk factors for hepatocellular carcinogenesis: a prospective observation of 795 patients with viral and alcoholic cirrhosis Hepatology 1993 18 47 53 7686879 10.1016/0270-9139(93)90505-H
Degos F Christidis C Ganne-Carrie N Farmachidi JP Degott C Guettier C Trinchet JC Beaugrand M Chevret S Hepatitis C virus related cirrhosis: time to occurrence of hepatocellular carcinoma and death Gut 2000 47 131 136 10861275 10.1136/gut.47.1.131
Kiyosawa K Tanaka E Sodeyama T Hepatitis C virus and hepatocellular carcinoma Curr Stud Hematol Blood Transfus 1998 62 161 180 9507810
Tong MJ El Farra NS Reikes AR Co RL Clinical outcomes after transfusion-associated hepatitis C N Engl J Med 1995 332 1463 1466 7739682 10.1056/NEJM199506013322202
Pozzato G Kaneko S Moretti M Croce LS Franzin F Unoura M Bercich L Tiribelli C Crovatto M Santini G Kobayashi S Crovatto M Santini G Kobayashi S Different genotypes of hepatitis C virus are associated with different severity of chronic liver disease J Med Virol 1994 43 291 296 7931191
Bruno S Silini E Crosignani A Borzio F Leandro G Bono F Asti M Rossi S Larghi A Cerino A Podda M Mondelli MU Hepatitis C virus genotypes and risk of hepatocellular carcinoma in cirrhosis: a prospective study Hepatology 1997 25 754 758 9049231 10.1002/hep.510250344
Benvegnu L Pontisso P Cavalletto D Noventa F Chemello L Alberti A Lack of correlation between hepatitis C virus genotypes and clinical course of hepatitis C virus-related cirrhosis Hepatology 1997 25 211 215 8985292
Romeo R Rumi MG Del Ninno E Colombo M Hepatitis C virus genotype 1b and risk of hepatocellular carcinoma Hepatology 1997 26 1077 9328339
Zarski JP Bohn B Bastie A Pawlotsky JM Baud M Bost-Bezeaux F Tran van Nhieu J Seigneurin JM Buffet C Dhumeaux D Characteristics of patients with dual infection by hepatitis B and C viruses J Hepatol 1998 28 27 33 9537860 10.1016/S0168-8278(98)80198-0
Sato S Fujiyama S Tanaka M Yamasaki K Kuramoto I Kawano S Sato T Mizuno K Nonaka S Coinfection of hepatitis C virus in patients with chronic hepatitis B infection J Hepatol 1994 21 159 166 7527435 10.1016/S0168-8278(05)80389-7
Donato F Boffetta P Puoti M A meta-analysis of epidemiological studies on the combined effect of hepatitis B and C virus infections in causing hepatocellular carcinoma Int J Cancer 1998 75 347 354 9455792 10.1002/(SICI)1097-0215(19980130)75:3<347::AID-IJC4>3.0.CO;2-2
Chiba T Matsuzaki Y Abei M Shoda J Tanaka N Osuga T Aikawa T The role of previous hepatitis B virus infection and heavy smoking in hepatitis C virus-related hepatocellular carcinoma Am J Gastroenterol 1996 91 1195 1203 8651170
Kubo S Nishiguchi S Hirohashi K Tanaka H Tsukamoto T Hamba H Shuto T Yamamoto T Ikebe T Kinoshita H Clinical significance of prior hepatitis B virus infection in patients with hepatitis C virus-related hepatocellular carcinoma Cancer 1999 86 793 798 10463977 10.1002/(SICI)1097-0142(19990901)86:5<793::AID-CNCR14>3.0.CO;2-K
Marusawa H Osaki Y Kimura T Ito K Yamashita Y Eguchi T Kudo M Yamamoto Y Kojima H Seno H Moriyasu F Chiba T High prevalence of anti-hepatitis B virus serological markers in patients with hepatitis C virus related chronic liver disease in Japan Gut 1999 45 284 288 10403743
Kao JH Chen PJ Lai MY Chen DS Occult hepatitis B virus infection and clinical outcomes of patients with chronic hepatitis C J Clin Microbiol 2002 40 4068 4071 12409376 10.1128/JCM.40.11.4068-4071.2002
Kurtz RC Hepatocellular carcinoma and coinfection with hepatitis B and C. Making a difficult situation worse Cancer 1999 86 741 743 10463966 10.1002/(SICI)1097-0142(19990901)86:5<741::AID-CNCR3>3.0.CO;2-M
Anon National Institutes of Health Consensus Development Conference Panel Statement: Management of Hepatitis C Hepatology 1997 26 2S 10S 9305656
Chlabicz S Grzeszczuk A Hepatitis B virus vaccine for patients with hepatitis C virus infection Infection 2000 28 341 345 11139151 10.1007/s150100070002
Garcia-Samaniego J Rodriguez M Berenguer J Rodriguez-Rosado R Carbo J Asensi V Soriano V Hepatocellular carcinoma in HIV-infected patients with chronic hepatitis C Am J Gastroenterol 2001 96 179 183 11197250
Telfer P Sabin C Devereux H Scott F Dusheiko G Lee C The progression of HCV-associated liver disease in a cohort of haemophilic patients Br J Haematol 1994 87 555 561 7993796
Hassan MM Zaghloul AS El-Serag HB Soliman O Patt YZ Chappell CL Beasley RP Hwang LY The role of hepatitis C in hepatocellular carcinoma: a case control study among Egyptian patients J Clin Gastroenterol 2001 33 123 126 11468438 10.1097/00004836-200108000-00006
Ohnishi K Iida S Iwama S Goto N Nomura F Takashi M Mishima A Kono K Kimura K Musha H Kotota K Okuda K The effect of chronic habitual alcohol intake on the development of liver cirrhosis and hepatocellular carcinoma: relation to hepatitis B surface antigen carriage Cancer 1982 49 672 677 6275976
Qiao ZK Halliday ML Rankin JG Coates RA Relationship between hepatitis B surface antigen prevalence, per capita alcohol consumption and primary liver cancer death rate in 30 countries J Clin Epidemiol 1988 41 787 792 2843610 10.1016/0895-4356(88)90165-5
Donato F Tagger A Gelatti U Parrinello G Boffetta P Albertini A Decarli A Trevisi P Ribero ML Martelli C Porru S Nardi G Alcohol and hepatocellular carcinoma: the effect of lifetime intake and hepatitis virus infections in men and women Am J Epidemiol 2002 155 323 331 11836196 10.1093/aje/155.4.323
Simonetti RG Camma C Fiorello F Cottone M Rapicetta M Marino L Fiorentino G Craxi A Ciccaglione A Giuseppetti R Stroffolini T Pagliaro L Hepatitis C virus infection as a risk factor for hepatocellular carcinoma in patients with cirrhosis. A case-control study Ann Intern Med 1992 116 97 102 1309286
Trichopoulos D Day NE Kaklamani E Tzonou A Munoz N Zavitsanos X Koumantaki Y Trichopoulou A Hepatitis B virus, tobacco smoking and ethanol consumption in the etiology of hepatocellular carcinoma Int J Cancer 1987 39 45 49 3025110
Donato F Tagger A Chiesa R Ribero ML Tomasoni V Fasola M Gelatti U Portera G Boffetta P Nardi G Hepatitis B and C virus infection, alcohol drinking, and hepatocellular carcinoma: a case-control study in Italy Hepatology 1997 26 579 584 9303486
Hassan MM Hwang LY Hatten CJ Swaim M Li D Abbruzzese JL Beasley P Patt YZ Risk factors for hepatocellular carcinoma: synergism of alcohol with viral hepatitis and diabetes mellitus Hepatology 2002 36 1206 1213 12395331 10.1053/jhep.2002.36780
Chen DS Kuo G Sung JL Lai MY Sheu JC Chen PJ Yang PM Hsu HM Chang MH Chen CJ Hahn LC Choo QL Wang TH Houghton M Hepatitis C virus infection in an area hyperendemic for hepatitis B and chronic liver disease: the Taiwan experience J Infect Dis 1990 162 817 822 2169497
Chuang WL Chang WY Lu SN Su WP Lin ZY Chen SC Hsieh MY Wang LY You SL Chen CJ The role of hepatitis B and C viruses in hepatocellular carcinoma in a hepatitis B endemic area. A case-control study Cancer 1992 69 2052 2054 1311978
Lee SD Lee FY Wu JC Hwang SJ Wang SS Lo KJ The prevalence of anti-hepatitis C virus among Chinese patients with hepatocellular carcinoma Cancer 1992 69 342 345 1309428
Jeng JE Tsai JF Hepatitis C virus antibody in hepatocellular carcinoma in Taiwan J Med Virol 1991 34 74 77 1653308
Leung NW Tam JS Lai JY Leung TW Lau WY Shiu W Li AK Does hepatitis C virus infection contribute to hepatocellular carcinoma in Hong Kong? Cancer 1992 70 40 44 1318777
Nishioka K Watanabe J Furuta S Tanaka E Iino S Suzuki H Tsuji T Yano M Kuo G Choo QL Houghton M Oda T A high prevalence of antibody to the hepatitis C virus in patients with hepatocellular carcinoma in Japan Cancer 1991 67 429 433 1845946
Saito I Miyamura T Ohbayashi A Harada H Katayama T Kikuchi S Watanabe Y Koi S Onji M Ohta Y Choo QL Houghton M Kuo G Hepatitis C virus infection is associated with the development of hepatocellular carcinoma Proc Natl Acad Sci USA 1990 87 6547 6549 2168552
Hassan MM Zaghloul AS El-Serag HB Soliman O Patt YZ Chappell CL Beasley RP Hwang LY The role of hepatitis C in hepatocellular carcinoma: a case control study among Egyptian patients J Clin Gastroenterol 2001 33 123 126 11468438 10.1097/00004836-200108000-00006
Kew MC Houghton M Choo QL Kuo G Hepatitis C virus antibodies in southern African blacks with hepatocellular carcinoma Lancet 1990 335 873 874 1691422 10.1016/0140-6736(90)90474-J
Yu MC Tong MJ Coursaget P Ross RK Govindarajan S Henderson BE Prevalence of hepatitis B and C viral markers in black and white patients with hepatocellular carcinoma in the United States J Natl Cancer Inst 1990 82 1038 1041 2161463
Di Di Bisceglie AM Order SE Klein JL Waggoner JG Sjogren MH Kuo G Houghton M Choo QL Hoofnagle JH The role of chronic viral hepatitis in hepatocellular carcinoma in the United States Am J Gastroenterol 1991 86 335 338 1847790
Hadziyannis S Tabor E Kaklamani E Tzonou A Stuver S Tassopoulos N Mueller N Trichopoulos D A case-control study of hepatitis B and C virus infections in the etiology of hepatocellular carcinoma Int J Cancer 1995 60 627 631 7860136
Colombo M Kuo G Choo QL Donato MF Del Ninno E Tommasini MA Dioguardi N Houghton M Prevalence of antibodies to hepatitis C virus in Italian patients with hepatocellular carcinoma Lancet 1989 2 1006 1008 2572740 10.1016/S0140-6736(89)91016-7
Levrero M Tagger A Balsano C De Marzio E Avantaggiati ML Natoli G Diop D Villa E Diodati G Alberti A Antibodies to hepatitis C virus in patients with hepatocellular carcinoma J Hepatol 1991 12 60 63 1848874
Simonetti RG Camma C Fiorello F Cottone M Rapicetta M Marino L Fiorentino G Craxi A Ciccaglione A Giuseppetti R Stroffolini T Pagliaro L Hepatitis C virus infection as a risk factor for hepatocellular carcinoma in patients with cirrhosis Ann Intern Med 1992 116 97 102 1309286
Stroffolini T Andreone P Andriulli A Ascione A Craxi A Chiaramonte M Galante D Manghisi OG Mazzanti R Medaglia C Pilleri G Rapaccini GL Simonetti RG Taliani G Tosti ME Villa E Gasbarrini G Characteristics of hepatocellular carcinoma in Italy J Hepatol 1998 29 944 952 9875641 10.1016/S0168-8278(98)80122-0
Bruix J Barrera JM Calvet X Ercilla G Costa J Sanchez-Tapias JM Ventura M Vall M Bruguera M Bru C Castillo R Rodes J Prevalence of antibodies to hepatitis C virus in Spanish patients with hepatocellular carcinoma and hepatic cirrhosis Lancet 1989 2 1004 1006 2572739 10.1016/S0140-6736(89)91015-5
Nalpas B Driss F Pol S Hamelin B Housset C Brechot C Berthelot P Association between HCV and HBV infection in hepatocellular carcinoma and alcoholic liver disease J Hepatol 1991 12 70 74 1848875
Van Roey G Fevery J Van Steenbergen W Hepatocellular carcinoma in Belgium: clinical and virological characteristics of 154 consecutive cirrhotic and non-cirrhotic patients Eur J Gastroenterol Hepatol 2000 12 61 66 10656212
Haydon GH Jarvis LM Simmonds P Harrison DJ Garden OJ Hayes PC Association between chronic hepatitis C infection and hepatocellular carcinoma in a Scottish population Gut 1997 40 128 132 9155590
Yeh FS Yu MC Mo CC Luo S Tong MJ Henderson BE Hepatitis B virus, aflatoxins, and hepatocellular carcinoma in southern Guangxi, China Cancer Res 1989 49 2506 2509 2539905
El Serag HB Mason AC Rising incidence of hepatocellular carcinoma in the United States N Engl J Med 1999 340 745 750 10072408 10.1056/NEJM199903113401001
El Serag HB Mason AC Risk factors for the rising rates of primary liver cancer in the United States Arch Intern Med 2000 160 3227 3230 11088082 10.1001/archinte.160.21.3227
Benhamiche AM Faivre C Minello A Clinard F Mitry E Hillon P Faivre J Time trends and age-period-cohort effects on the incidence of primary liver cancer in a well-defined French population: 1976–1995 J Hepatol 1998 29 802 806 9833919 10.1016/S0168-8278(98)80262-6
Law MG Roberts SK Dore GJ Kaldor JM Primary hepatocellular carcinoma in Australia, 1978–1997: increasing incidence and mortality Med J Aust 2000 173 403 405 11090031
Yoshizawa H Hepatocellular carcinoma associated with hepatitis C virus infection in Japan: projection to other countries in the foreseeable future Oncology 2002 62 8 17 11868791 10.1159/000048270
Kiyosawa K Furutu S Clinical aspects and epidemiology of hepatitis B and C viruses in hepatocellular carcinoma in Japan Cancer Chemother Pharmacol 1992 31 150 156 10.1007/BF00687126
Deuffic S Buffat L Poynard T Valleron AJ Modeling the hepatitis C virus epidemic in France Hepatology 1999 29 1596 1601 10216148 10.1002/hep.510290528
Armstrong GL Alter MJ McQuillan GM Margolis HS The past incidence of hepatitis C virus infection: implications for the future burden of chronic liver disease in the United States Hepatology 2000 31 777 782 10706572 10.1002/hep.510310332
Tanaka Y Hanada K Mizokami M Yeo AE Shih JW Gojobori T Alter HJ A comparison of the molecular clock of hepatitis C virus in the United States and Japan predicts that hepatocellular carcinoma incidence in the United States will increase over the next two decades Proc Natl Acad Sci USA 2002 99 15584 15589 12438687 10.1073/pnas.242608099
Garcia-Tsao G Current management of the complications of cirrhosis and portal hypertension: variceal hemorrhage, ascites, and spontaneous bacterial peritonitis Gastroenterology 2001 120 726 748 11179247
Solmi L Primerano AM Gandolfi L Ultrasound follow-up of patients at risk for hepatocellular carcinoma: results of a prospective study on 360 cases Am J Gastroenterol 1996 91 1189 1194 8651169
Gebo KA Chander G Jenckes MW Ghanem KG Herlong HF Torbenson MS El-Kamary SS Bass EB Screening tests for hepatocellular carcinoma in patients with chronic hepatitis C: a systematic review Hepatology 2002 36 84 92 10.1053/jhep.2002.36817
Di Bisceglie AM Hoofnagle JH Elevations in serum alpha-fetoprotein levels in patients with chronic hepatitis B Cancer 1989 64 2117 2120 2478280
Izzo F Cremona F Ruffolo F Palaia R Parisi V Curley SA Outcome of 67 patients with hepatocellular cancer detected during screening of 1125 patients with chronic hepatitis Ann Surg 1998 227 513 518 9563539 10.1097/00000658-199804000-00011
Sheu JC Sung JL Chen DS Yang PM Lai MY Lee CS Hsu HC Chuang CN Yang PC Wang TH Lin JT Lee CZ Growth rate of asymptomatic hepatocellular carcinoma and its clinical implications Gastroenterology 1985 89 259 266 2408960
Collier J Sherman M Screening for hepatocellular carcinoma Hepatology 1998 27 273 278 9425947 10.1002/hep.510270140
Kim CM Koike K Saito I Miyamura T Jay G HBx gene of hepatitis B virus induces liver cancer in transgenic mice Nature 1991 351 317 320 2034275 10.1038/351317a0
Moriya K Fujie H Shintani Y Yotsuyanagi H Tsutsumi T Ishibashi K Matsuura Y Kimura S Miyamura T Koike K The core protein of hepatitis C virus induces hepatocellular carcinoma in transgenic mice Nat Med 1998 4 1065 1067 9734402 10.1038/2053
Summers J Smolec JM Snyder R A virus similar to human hepatitis B virus associated with hepatitis and hepatoma in woodchucks Proc Natl Acad Sci USA 1978 75 4533 4537 212758
Weinberg RA Oncogenes, antioncogenes, and the molecular bases of multistep carcinogenesis Cancer Res 1989 49 3713 3721 2660980
Idilman R De Maria N Colantoni A Van Thiel DH Pathogenesis of hepatitis B and C-induced hepatocellular carcinoma J Viral Hepat 1998 5 285 299 9795912 10.1046/j.1365-2893.1998.00116.x
Nakanuma Y Terada T Ueda K Terasaki S Nonomura A Matsui O Adenomatous hyperplasia of the liver as a precancerous lesion Liver 1993 13 1 9 8384281
Theise ND Macroregenerative (dysplastic) nodules and hepatocarcinogenesis: theoretical and clinical considerations Semin Liver Dis 1995 15 360 371 8578320
Sh Shibata M Morizane T Uchida T Yamagami T Onozuka Y Nakano M Mitamura K Ueno Y Irregular regeneration of hepatocytes and risk of hepatocellular carcinoma in chronic hepatitis and cirrhosis with hepatitis-C-virus infection Lancet 1998 351 1773 1777 9635950 10.1016/S0140-6736(97)08002-1
Sugitani S Sakamoto M Ichida T Genda T Asakura H Hirohashi S Hyperplastic foci reflect the risk of multicentric development of human hepatocellular carcinoma J Hepatol 1998 28 1045 1053 9672182 10.1016/S0168-8278(98)80355-3
Lee RG Tsamandas AC Demetris AJ Large cell change (liver cell dysplasia) and hepatocellular carcinoma in cirrhosis: matched case-control study, pathological analysis, and pathogenetic hypothesis Hepatology 1997 26 1415 1422 9397980
Borzio M Bruno S Roncalli M Mels GC Ramella G Borzio F Leandro G Servida E Podda M Liver cell dysplasia is a major risk factor for hepatocellular carcinoma in cirrhosis: a prospective study Gastroenterology 1995 108 812 817 7875483
Zhao M Zhang NX Laissue JA Zimmermann A Immunohistochemical analysis of p53 protein overexpression in liver cell dysplasia and in hepatocellular carcinoma Virchows Arch 1994 424 613 621 8055155 10.1007/BF01069741
Kew MC Hepatitis B and C viruses and hepatocellular carcinoma Clin Lab Med 1996 16 395 406 8792079
Kew MC Hepatitis viruses and hepatocellular carcinoma Res Virol 1998 149 257 262 9879602 10.1016/S0923-2516(99)89003-7
Chisari FV Klopchin K Moriyama T Pasquinelli C Dunsford HA Sell S Pinkert CA Brinster RL Palmiter RD Molecular pathogenesis of hepatocellular carcinoma in hepatitis B virus transgenic mice Cell 1989 59 1145 1156 2598264 10.1016/0092-8674(89)90770-8
Kim JW Ye Q Forgues M Chen Y Budhu A Sime J Hofseth LJ Kaul R Wang XW Cancer-associated molecular signature in the tissue samples of patients with cirrhosis Hepatology 2004 39 518 527 14768006 10.1002/hep.20053
Lee JS Chu IS Heo J Calvisi DF Sun Z Roskams T Durnez A Demetris AJ Thorgeirsson SS Classification and prediction of survival in hepatocellular carcinoma by gene expression profiling Hepatology 2004 40 667 676 15349906 10.1002/hep.20375
Delpuech O Trabut JB Carnot F Feuillard J Brechot C Kremsdorf D Identification, using cDNA macroarray analysis, of distinct gene expression profiles associated with pathological and virological features of hepatocellular carcinoma Oncogene 2002 21 2926 2937 11973655 10.1038/sj.onc.1205392
Hann HW Lee J Bussard A Liu C Jin YR Guha K Clayton MM Ardlie K Pellini MJ Feitelson MA Preneoplastic markers of hepatitis B-virus associated hepatocellular carcinoma Cancer Res 2004 64 7329 7335 15492253
Chen PJ Chen DS Lai MY Chang MH Huang GT Yang PM Sheu JC Lee SC Hsu HC Sung JL Clonal origin of recurrent hepatocellular carcinomas Gastroenterology 1989 96 527 529 2535996
Lugassy C Bernuau J Thiers V Krosgaard K Degott C Wantzin P Schalm SW Rueff B Benhamou JP Tiollais P Bréchot C Sequences of hepatitis B virus DNA in the serum and liver of patients with acute benign and fulminant hepatitis J Infect Dis 1987 155 64 71 3794404
Koshy R Maupas P Muller R Hofschneider PH Detection of hepatitis B virus-specific DNA in the genomes of human hepatocellular carcinoma and liver cirrhosis tissues J Gen Virol 1981 57 95 102 6275024
Rowley JD Molecular cytogenetics: Rosetta stone for understanding cancer – twenty-ninth G. H. A. Clowes memorial award lecture Cancer Res 1990 50 3816 3825 2191766
Schimke RT The search for early genetic events in tumorigenesis: an amplification paradigm Cancer Cells 1990 2 149 151 2201341
Slagle BL Zhou YZ Butel JS Hepatitis B virus integration event in human chromosome 17p near the p53 gene identifies the region of the chromosome commonly deleted in virus-positive hepatocellular carcinomas Cancer Res 1991 51 49 54 1670994
Robinson WS Molecular events in the pathogenesis of hepadnavirus-associated hepatocellular carcinoma Annu Rev Med 1994 45 297 323 8198385 10.1146/annurev.med.45.1.297
Shirakata Y Kawada M Fujiki Y Sano H Oda M Yaginuma K Kobayashi M Koike K The X gene of hepatitis B virus induced growth stimulation and tumorigenic transformation of mouse NIH3T3 cells Jpn J Cancer Res 1989 80 617 621 2507484
Twu JS Schloemer RH Transcriptional trans-activating function of hepatitis B virus J Virol 1987 61 3448 3453 2822953
Paterlini P Poussin K Kew M Franco D Brechot C Selective accumulation of the X transcript of hepatitis B virus in patients negative for hepatitis B surface antigen with hepatocellular carcinoma Hepatology 1995 21 313 321 7843699 10.1016/0270-9139(95)90086-1
Henkler FF Koshy R Hepatitis B virus transcriptional activators: mechanisms and possible role in oncogenesis J Viral Hepat 1996 3 109 121 8871869
Wang XW Forrester K Yeh H Feitelson MA Gu JR Harris CC Hepatitis B virus X protein inhibits p53 sequence-specific DNA binding, transcriptional activity, and association with transcription factor ERCC3 Proc Natl Acad Sci USA 1994 91 2230 2234 8134379
Truant R Antunovic J Greenblatt J Prives C Cromlish JA Direct interaction of the hepatitis B virus HBx protein with p53 leads to inhibition by HBx of p53 response element-directed transactivation J Virol 1995 69 1851 1859 7853526
Ueda H Ullrich SJ Gangemi JD Kappel CA Ngo L Feitelson MA Jay G Functional inactivation but not structural mutation of p53 causes liver cancer Nat Genet 1995 9 41 47 7704023 10.1038/ng0195-41
Pasquinelli C Bhavani K Chisari FV Multiple oncogenes and tumor suppressor genes are structurally and functionally intact during hepatocarcinogenesis in hepatitis B virus transgenic mice Cancer Res 1992 52 2823 2829 1316229
Kekule AS Lauer U Meyer M Caselmann WH Hofschneider PH Koshy R The preS2/S region of integrated hepatitis B virus DNA encodes a transcriptional transactivator Nature 1990 343 457 461 2153938 10.1038/343457a0
Fu XX Su CY Lee Y Hintz R Biempica L Snyder R Rogler CE Insulinlike growth factor II expression and oval cell proliferation associated with hepatocarcinogenesis in woodchuck hepatitis virus carriers J Virol 1988 62 3422 3430 2457114
Yoo YD Ueda H Park K Flanders KC Lee YI Jay G Kim SJ Regulation of transforming growth factor-beta 1 expression by the hepatitis B virus (HBV) X transactivator. Role in HBV pathogenesis J Clin Invest 1996 97 388 395 8567959
Bock CT Tillmann HL Manns MP Trautwein C The pre-S region determines the intracellular localization and appearance of hepatitis B virus Hepatology 1999 30 517 525 10421662 10.1002/hep.510300206
Xu Z Jensen G Yen TS Activation of hepatitis B virus S promoter by the viral large surface protein via induction of stress in the endoplasmic reticulum J Virol 1997 71 7387 7392 9311817
Jakubczak JL Chisari FV Merlino G Synergy between transforming growth factor alpha and hepatitis B virus surface antigen in hepatocellular proliferation and carcinogenesis Cancer Res 1997 57 3606 3611 9270035
Yeh SH Lin MW Lu SF Wu DC Tsai SF Tsai CY Lai MY Hsu HC Chen DS Chen PJ Allelic loss of chromosome 4q21 approximately 23 associates with hepatitis B virus-related hepatocarcinogenesis and elevated alpha-fetoprotein Hepatology 2004 40 847 854 15382172 10.1002/hep.20409
Yano M Kumada H Kage M Ikeda K Shimamatsu K Inoue O Hashimoto E Lefkowitch JH Ludwig J Okuda K The long-term pathological evolution of chronic hepatitis C Hepatology 1996 23 1334 1340 8675148
Kew MC Hepatitis C virus and hepatocellular carcinoma FEMS Microbiol Rev 1994 14 211 219 8086196 10.1016/0168-6445(94)90035-3
Nardone G Romano M Calabro A Pedone PV de Sio I Persico M Budillon G Bruni CB Riccio A Zarrilli R Activation of fetal promoters of insulinlike growth factors II gene in hepatitis C virus-related chronic hepatitis, cirrhosis, and hepatocellular carcinoma Hepatology 1996 23 1304 1312 8675143
Tanaka S Takenaka K Matsumata T Mori R Sugimachi K Hepatitis C virus replication is associated with expression of transforming growth factor-alpha and insulin-like growth factor-II in cirrhotic livers Dig Dis Sci 1996 41 208 215 8565758
Takamizawa A Mori C Fuke I Manabe S Murakami S Fujita J Onishi E Andoh T Yoshida I Okayama H Structure and organization of the hepatitis C virus genome isolated from human carriers J Virol 1991 65 1105 1113 1847440
Borowski P Oehlmann K Heiland M Laufs R Nonstructural protein 3 of hepatitis C virus blocks the distribution of the free catalytic subunit of cyclic AMP-dependent protein kinase J Virol 1997 71 2838 2843 9060639
Taylor DR Shi ST Romano PR Barber GN Lai MM Inhibition of the interferon-inducible protein kinase PKR by HCV E2 protein Science 1999 285 107 110 10390359 10.1126/science.285.5424.107
Gale M JrKwieciszewski B Dossett M Nakao H Katze MG Antiapoptotic and oncogenic potentials of hepatitis C virus are linked to interferon resistance by viral repression of the PKR protein kinase J Virol 1999 73 6506 6516 10400746
Koromilas AE Roy S Barber GN Katze MG Sonenberg N Malignant transformation by a mutant of the IFN-inducible dsRNA-dependent protein kinase Science 1992 257 1685 1689 1382315
Shih CM Lo SJ Miyamura T Chen SY Lee YH Suppression of hepatitis B virus expression and replication by hepatitis C virus core protein in HuH-7 cells J Virol 1993 67 5823 5832 8396658
Kim DW Suzuki R Harada T Saito I Miyamura T Trans-suppression of gene expression by hepatitis C viral core protein Jpn J Med Sci Biol 1994 47 211 220 7715094
Ray RB Steele R Meyer K Ray R Transcriptional repression of p53 promoter by hepatitis C virus core protein J Biol Chem 1997 272 10983 10986 9110985 10.1074/jbc.272.17.10983
Ray RB Steele R Meyer K Ray R Hepatitis C virus core protein represses p21WAF1/Cip1/Sid1 promoter activity Gene 1998 208 331 336 9524287 10.1016/S0378-1119(98)00030-4
Ruster B Zeuzem S Roth WK Hepatitis C virus sequences encoding truncated core proteins detected in a hepatocellular carcinoma Biochem Biophys Res Commun 1996 219 911 915 8645278 10.1006/bbrc.1996.0340
Tai DI Tsai SL Chen YM Chuang YL Peng CY Sheen IS Yeh CT Chang KS Huang SN Kuo GC Liaw YF Activation of nuclear factor kappa B in hepatitis C virus infection: implications for pathogenesis and hepatocarcinogenesis Hepatology 2000 31 656 664 10706556 10.1002/hep.510310316
Sung JL Chen DS Hepatitis B antigen and antibody in liver disease in Taiwan Proceedings 5th Asian Pacific Congress of Gastroenterology: Singapore 1976 265 269
Chang MH Chen CJ Lai MS Hsu HM Wu TC Kong MS Liang DC Shau WY Chen DS Universal hepatitis B vaccination in Taiwan and the incidence of hepatocellular carcinoma in children N Engl J Med 1997 336 1855 1859 9197213 10.1056/NEJM199706263362602
Wong DK Cheung AM O'Rourke K Naylor CD Detsky AS Heathcote J Effect of alpha-interferon treatment in patients with hepatitis B e antigen-positive chronic hepatitis B. A meta-analysis Ann Intern Med 1993 119 312 323 8328741
McHutchison JG Gordon SC Schiff ER Shiffman ML Lee WM Rustgi VK Goodman ZD Ling MH Cort S Albrecht JK Interferon alfa-2b alone or in combination with ribavirin as initial treatment for chronic hepatitis C N Engl J Med 1998 339 1485 1492 9819446 10.1056/NEJM199811193392101
Poynard T Marcellin P Lee SS Niederau C Minuk GS Ideo G Bain V Heathcote J Zeuzem S Trepo C Albrecht J Randomised trial of interferon alpha2b plus ribavirin for 48 weeks or for 24 weeks versus interferon alpha2b plus placebo for 48 weeks for treatment of chronic infection with hepatitis C virus Lancet 1998 352 1426 1432 9807989 10.1016/S0140-6736(98)07124-4
Manns MP McHutchison JG Gordon SC Rustgi VK Shiffman M Reindollar R Goodman ZD Koury K Ling M Albrecht JK Peginterferon alfa-2b plus ribavirin compared with interferon alfa-2b plus ribavirin for initial treatment of chronic hepatitis C: a randomised trial Lancet 2001 358 958 965 11583749 10.1016/S0140-6736(01)06102-5
Fried MW Shiffman ML Reddy KR Smith C Marinos G Goncales FL JrHaussinger D Diago M Carosi G Dhumeaux D Craxi A Lin A Hoffman J Yu J Peginterferon alfa-2a plus ribavirin for chronic hepatitis C virus infection N Engl J Med 2002 347 975 982 12324553 10.1056/NEJMoa020047
Dianzani F Antonelli G Capobianchi MR The biological basis for clinical use of interferon J Hepatol 1990 11 5 10 2204659
Iwase S Furukawa Y Kikuchi J Nagai M Terui Y Nakamura M Yamada H Modulation of E2F activity is linked to interferon-induced growth suppression of hematopoietic cells J Biol Chem 1997 272 12406 12414 9139687 10.1074/jbc.272.19.12406
Raveh T Hovanessian AG Meurs EF Sonenberg N Kimchi A Double-stranded RNA-dependent protein kinase mediates c-Myc suppression induced by type I interferons J Biol Chem 1996 271 25479 25484 8810318 10.1074/jbc.271.41.25479
Arany I Rady P Tyring SK Interferon treatment enhances the expression of underphosphorylated (biologically-active) retinoblastoma protein in human papilloma virus-infected cells through the inhibitory TGF beta 1/IFN beta cytokine pathway Antiviral Res 1994 23 131 141 7511881 10.1016/0166-3542(94)90040-X
Merle P Chevallier M Levy R Maisonnas M Terradillos O Ahmed SNS Trepo C Buendia MA Vitvitski-Trepo L Preliminary results of interferon-alpha therapy on woodchuck hepatitis virus-induced hepatocarcinogenesis: possible benefit in female transgenic mice J Hepatol 2001 34 562 569 11394656 10.1016/S0168-8278(00)00054-4
Singh RK Gutman M Bucana CD Sanchez R Llansa N Fidler IJ Interferons alpha and beta down-regulate the expression of basic fibroblast growth factor in human carcinomas Proc Natl Acad Sci USA 1995 92 4562 4566 7753843
Niederau C Heintges T Lange S Goldmann G Niederau CM Mohr L Haussinger D Long-term follow-up of HBeAg-positive patients treated with interferon alfa for chronic hepatitis B N Engl J Med 1996 334 1422 1427 8618580 10.1056/NEJM199605303342202
Lin SM Sheen IS Chien RN Chu CM Liaw YF Long-term beneficial effect of interferon therapy in patients with chronic hepatitis B virus infection Hepatology 1999 29 971 975 10051505 10.1002/hep.510290312
Yuen MF Hui CK Cheng CC Wu CH Lai YP Lai CL Long-term follow-up of interferon alfa treatment in Chinese patients with chronic hepatitis B infection: The effect on hepatitis B e antigen seroconversion and the development of cirrhosis-related complications Hepatology 2001 34 139 145 11431745 10.1053/jhep.2001.25273
Oon CJ Long-term survival following treatment of hepatocellular carcinoma in Singapore: evaluation of Wellferon in the prophylaxis of high-risk pre-cancerous conditions Cancer Chemother Pharmacol 1992 31 137 142 10.1007/BF00687123
Mazzella G Accogli E Sottili S Festi D Orsini M Salzetta A Novelli V Cipolla A Fabbri C Pezzoli A Roda E Alpha interferon treatment may prevent hepatocellular carcinoma in HCV-related liver cirrhosis J Hepatol 1996 24 141 147 8907566 10.1016/S0168-8278(96)80022-5
Fattovich G Giustina G Realdi G Corrocher R Schalm SW Long-term outcome of hepatitis B e antigen-positive patients with compensated cirrhosis treated with interferon alfa Hepatology 1997 26 1338 1342 9362381
Ikeda K Saitoh S Suzuki Y Kobayashi M Tsubota A Fukuda M Koida I Arase Y Chayama K Murashima N Kumada H Interferon decreases hepatocellular carcinogenesis in patients with cirrhosis caused by the hepatitis B virus: a pilot study Cancer 1998 82 827 835 9486570 10.1002/(SICI)1097-0142(19980301)82:5<827::AID-CNCR5>3.0.CO;2-G
International Interferon-alpha Hepatocellular Carcinoma Study Group Effect of interferon-alpha on progression of cirrhosis to hepatocellular carcinoma: a retrospective cohort study Lancet 1998 351 1535 1539 10326535 10.1016/S0140-6736(98)07236-5
Benvegnù L Chemello L Noventa F Fattovich G Pontisso P Alberti A Retrospective analysis of the effect of interferon therapy on the clinical outcome of patients with viral cirrhosis Cancer 1998 83 901 909 9731893 10.1002/(SICI)1097-0142(19980901)83:5<901::AID-CNCR15>3.0.CO;2-Z
Di Marco V Lo Iacono O Camma C Vaccaro A Giunta M Martorana G Fuschi P Almasio PL Craxi A The long-term course of chronic hepatitis B Hepatology 1999 30 257 264 10385664 10.1002/hep.510300109
Camma C Giunta M Andreone P Craxi A Interferon and prevention of hepatocellular carcinoma in viral cirrhosis: an evidence-based approach J Hepatol 2001 34 593 602 11394661 10.1016/S0168-8278(01)00005-8
Liaw YF Sung JJ Chow WC Farrell G Lee CZ Yuen H Tanwandee T Tao QM Shue K Keene ON Dixon JS Gray DF Sabbat J Cirrhosis Asian Lamivudine Multicentre Study Group Lamivudine for patients with chronic hepatitis B and advanced liver disease N Engl J Med 2004 351 1521 1531 15470215 10.1056/NEJMoa033364
Kasahara A Hayashi N Mochizuki K Takayanagi M Yoshioka K Kakumu S Iijima A Urushihara A Kiyosawa K Okuda M Hino K Okita K Risk factors for hepatocellular carcinoma and its incidence after interferon treatment in patients with chronic hepatitis C Hepatology 1998 27 1394 1402 9581697 10.1002/hep.510270529
Camma C Di Marco V Lo Iacono O Almasio P Giunta M Fuschi P Vaccaro A Fabiano C Magrin S Di Stefano R Bonura C Pagliaro L Craxi A Long-term course of interferon-treated chronic hepatitis C J Hepatol 1998 28 531 537 9566819 10.1016/S0168-8278(98)80274-2
Yoshida H Shiratori Y Moriyama M Arakawa Y Ide T Sata M Inoue O Yano M Tanaka M Fujiyama S Nishiguchi S Kuroki T Imazeki F Yokosuka O Kinoyama S Yamada G Omata M Interferon therapy reduces the risk for hepatocellular carcinoma: national surveillance program of cirrhotic and noncirrhotic patients with chronic hepatitis C in Japan Ann Intern Med 1999 131 174 181 10428733
Toyoda H Kumada T Nakano S Takeda I Sugiyama K Kiriyama S Sone Y Tanikawa M Hisanaga Y Hayashi K Honda T Effect of the dose and duration of interferon-alpha therapy on the incidence of hepatocellular carcinoma in noncirrhotic patients with a nonsustained response to interferon for chronic hepatitis C Oncology 2001 61 134 142 11528252 10.1159/000055364
Fattovich G Giustina G Degos F Diodati G Tremolada F Nevens F Almasio P Solinas A Brouwer JT Thomas H Realdi G Corrocher R Schalm SW Effectiveness of interferon alfa on incidence of hepatocellular carcinoma and decompensation in cirrhosis type C J Hepatol 1997 27 201 205 9252096 10.1016/S0168-8278(97)80302-9
Serfaty L Aumaitre H Chazouilleres O Bonnand AM Rosmorduc O Poupon RE Poupon R Determinants of outcome of compensated hepatitis C virus-related cirrhosis Hepatology 1998 27 1435 1440 9581703 10.1002/hep.510270535
Imai Y Kawata S Tamura S Yabuuchi I Noda S Inada M Maeda Y Shirai Y Fukuzaki T Kaji I Ishikawa H Matsuda Y Nishikawa M Seki K Matsuzawa Y Relation of interferon therapy and hepatocellular carcinoma in patients with chronic hepatitis C Ann Intern Med 1998 129 94 99 9669992
Valla DC Chevallier M Marcellin P Payen JL Trepo C Fonck M Bourliere M Boucher E Miguet JP Parlier D Lemonnier C Opolon P Treatment of hepatitis C virus-related cirrhosis: a randomized, controlled trial of interferon alfa-2b versus no treatment Hepatology 1999 29 1870 1875 10347132 10.1002/hep.510290616
Okanoue T Itoh Y Minami M Sakamoto S Yasui K Sakamoto M Nishioji K Murakami Y Kashima K Interferon therapy lowers the rate of progression to hepatocellular carcinoma in chronic hepatitis C but not significantly in an advanced stage: a retrospective study in 1148 patients J Hepatol 1999 30 653 659 10207807 10.1016/S0168-8278(99)80196-2
Nishiguchi S Kuroki T Nakatani S Morimoto H Takeda T Nakajima S Shiomi S Seki S Kobayashi K Otani S Randomised trial of effects of interferon-alpha on incidence of hepatocellular carcinoma in chronic active hepatitis C with cirrhosis Lancet 1995 346 1051 1055 7564784 10.1016/S0140-6736(95)91739-X
Nishiguchi S Shiomi S Nakatani S Takeda T Fukuda K Tamori A Habu D Tanaka T Prevention of hepatocellular carcinoma in patients with chronic active hepatitis C and cirrhosis Lancet 2001 357 196 197 11213099 10.1016/S0140-6736(00)03595-9
Gramenzi A Andreone P Fiorino S Camma C Giunta M Magalotti D Cursaro C Calabrese C Arienti V Rossi C Di Febo G Zoli M Craxi A Gasbarrini G Bernardi M Impact of interferon therapy on the natural history of hepatitis C virus related cirrhosis Gut 2001 48 843 848 11358906 10.1136/gut.48.6.843
Testino G Ansaldi F Andorno E Ravetti GL Ferro C De Iaco F Icardi G Valente U Interferon therapy does not prevent hepatocellular carcinoma in HCV compensated cirrhosis Hepatogastroenterology 2002 49 1636 1638 12397752
Tanaka K Sata M Uchimura Y Suzuki H Tanikawa K Long-term evaluation of interferon therapy in hepatitis C virus-associated cirrhosis: does IFN prevent development of hepatocellular carcinoma? Oncol Rep 1998 5 205 208 9458323
Schalm SW Weiland O Hansen BE Milella M Lai MY Hollander A Michielsen PP Bellobuono A Chemello L Pastore G Chen DS Brouwer JT Interferon-ribavirin for chronic hepatitis C with and without cirrhosis: analysis of individual patient data of six controlled trials Gastroenterology 1999 117 408 413 10419923
Heathcote EJ Shiffman ML Cooksley WG Dusheiko GM Lee SS Balart L Reindollar R Reddy RK Wright TL Lin A Hoffman J De Pamphilis J Peginterferon alfa-2a in patients with chronic hepatitis C and cirrhosis N Engl J Med 2000 343 1673 1680 11106716 10.1056/NEJM200012073432302
Pagliaro L Craxi A Camma C Tine F Di Marco V Lo Iacono O Almasio P Interferon-αα for chronic hepatitis C: An analysis of pretreatment clinical predictors of response Hepatology 1994 19 820 828 8138252 10.1016/0270-9139(94)90278-X
Ikeda K Arase Y Saitoh S Kobayashi M Suzuki Y Suzuki F Tsubota A Chayama K Murashima N Kumada H Interferon beta prevents recurrence of hepatocellular carcinoma after complete resection or ablation of the primary tumor-A prospective randomized study of hepatitis C virus-related liver cancer Hepatology 2000 32 228 232 10915728 10.1053/jhep.2000.9409
Kubo S Nishiguchi S Hirohashi K Tanaka H Shuto T Kinoshita H Randomized clinical trial of long-term outcome after resection of hepatitis C virus-related hepatocellular carcinoma by postoperative interferon therapy Br J Surg 2002 89 418 422 11952580 10.1046/j.0007-1323.2001.02054.x
Lin SM Lin CJ Hsu CW Tai DI Sheen IS Lin DY Liaw YF Prospective randomized controlled study of interferon-alpha in preventing hepatocellular carcinoma recurrence after medical ablation therapy for primary tumors Cancer 2004 100 376 382 14716774 10.1002/cncr.20004
| 15941478 | PMC1166581 | CC BY | 2021-01-04 16:39:03 | no | World J Surg Oncol. 2005 Jun 7; 3:33 | latin-1 | World J Surg Oncol | 2,005 | 10.1186/1477-7819-3-33 | oa_comm |
==== Front
PLoS MedPLoS MedpmedplosmedPLoS Medicine1549-12771549-1676Public Library of Science San Francisco, USA 1598491010.1371/journal.pmed.0020232Policy ForumInfectious DiseasesOtherEpidemiology/Public HealthHealth PolicyInfectious DiseasesMicrobiologyHealth PolicyPublic HealthEpidemiologyAgricultural Antibiotics and Human Health Policy ForumSmith David L *Dushoff Jonathan Morris J. Glenn JrDavid Smith is a mathematical epidemiologist and infectious disease ecologist at Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America. Jonathan Dushoff is on the research staff in the Department of Ecology and Evolutionary Biology at Princeton University, Princeton, New Jersey, United States of America, and at Fogarty International Center, National Institutes of Health. J. Glenn Morris, Jr., is a physician epidemiologist and specialist in infectious diseases, and chair of the Department of Epidemiology and Preventive Medicine in the School of Medicine, University of Maryland, Baltimore, Maryland, United States of America.
*To whom correspondence should be addressed. E-mail: [email protected]
Competing Interests: DLS and JGM received funding four years ago from Pfizer to conduct a risk assessment for the emergence of streptogramin resistance in Enterococcus faecium. JD declares that he has no competing interests.
8 2005 5 7 2005 2 8 e232Copyright: © 2005 Public Library of Science.2005This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.Smith and colleagues discuss evidence suggesting that antibiotic use in agriculture has contributed to antibiotic resistance in the pathogenic bacteria of humans.
Does antibiotic use in agriculture have a greater impact than hospital use?
==== Body
Like SARS, Ebola, and other emerging infectious diseases, antibiotic resistance in bacteria may have a zoonotic origin [1]. Evidence suggests that antibiotic use in agriculture has contributed to antibiotic resistance in the pathogenic bacteria of humans, but the chain from cause to effect is long and complicated.
Antibiotic use clearly selects for antibiotic resistance, but how far do these effects extend beyond the population where antibiotics are used? Antibiotics and antibiotic-resistant bacteria (ARB) are found in the air and soil around farms, in surface and ground water, in wild animal populations, and on retail meat and poultry [2–9]. ARB are carried into the kitchen on contaminated meat and poultry, where other foods are cross-contaminated because of common unsafe handling practices [10,11]. Following ingestion, bacteria occasionally survive the formidable but imperfect gastric barrier, and colonize the gut [12].
Patterns of colonization (asymptomatic carriage) and infection (symptomatic carriage) in human populations provide additional evidence that ARB occasionally move from animals to humans [13,14]. The strongest evidence comes from the history of the use of antibiotics for growth promotion in Europe. After first Denmark and then the European Union banned the use of antibiotics for growth promotion, prevalence of resistant bacteria declined in farm animals, in retail meat and poultry, and within the general human population [8,15].
Despite the evidence linking bacterial antibiotic resistance on farms to resistance in humans, the impact of agricultural antibiotic use remains controversial [16–19] and poorly quantified. This is partly because of the complex of population-level processes underlying the between-species (“heterospecific”) and within-species, host-to-host (“horizontal”) spread of ARB. To emerge as human pathogens, new strains of ARB must (1) evolve, originating from mutations or gene transfer; (2) spread, usually horizontally among humans or animals, but occasionally heterospecifically; and (3) cause disease.
All three of these steps are complex and imperfectly understood. The emergence of a new type of resistance is a highly random event, which can't be predicted accurately, and may involve multiple steps that preclude perfect understanding even after the fact. Spread is equally complicated and may obscure the origins of resistance. In some cases, emergence of resistance in one bacterial species is a consequence of the emergence and spread in another species, followed by the transfer of resistance genes from one bacterial species to another. Because of the underlying complexity, mathematical models are necessary to develop theory—a qualitative understanding of the underlying epidemiological processes [20–25]. Theory helps researchers organize facts, identify missing information, design surveillance, and analyze data [26].
Horizontal Transmission
Theory clearly shows that the impact of agricultural antibiotic use depends on whether resistant bacteria have high, low, or intermediate horizontal transmission rates in human populations [23,24]. The rate of horizontal transmission among humans is determined by the underlying biology of the pathogen, medical antibiotic use, and hospital infection control, but not by agricultural antibiotic use [22]. On the other hand, a farm where multiple antibiotics are used routinely, universally, and in low quantities for growth promotion is likely to be an excellent environment for the evolution of multiple resistance factors, including some variants that might never have evolved in humans. Thus, even very rare transmission resulting from agricultural antibiotics may have a medical impact by introducing new resistant variants to the human population. The epidemiology of spread in the human population dictates how the impact of agricultural antibiotic use should be assessed.
Zoonotic pathogens, such as Campylobacter and Salmonella, are generally regarded as having low horizontal transmission rates in human populations. While resistance in zoonotic infections should be directly attributable to resistance in the zoonotic reservoir, the impact of agricultural antibiotic use remains controversial [18,27–29]. Zoonotic species could acquire resistance genes from human commensal bacteria during the infection process, but this hypothesis is difficult to test.
For pathogens with high horizontal transmission rates, resistant bacteria will spread rapidly once they have emerged, and prevalence will be maintained at a steady state by horizontal transmission. Thus, the impact of subsequent heterospecific transmission is limited (Figure 1). Nevertheless, one or two heterospecific transmission events could be sufficient to cause the appearance of a highly successful ARB genotype in humans, affecting the timing, nature, and extent of spread within the human population [22]. Not only are such events difficult to trace, but their impact is impossible to measure, since there is no way to know what type of resistance would have appeared and with what temporal pattern, if transfers from animals had been prevented.
Figure 1 The Emergence and Spread of Antibiotic Resistance in Bacteria with High Horizontal Transmission Rates
Emergence and spread begins with a honeymoon period following the approval of a new antibiotic; the honeymoon ends when resistance emerges. Prevalence increases exponentially at first, but it eventually approaches a steady state. The impact of agricultural antibiotic use must be assessed by comparing the observed situation with the counterfactual situation, an imaginary world in which antibiotics were never used in agriculture. The impact of agricultural antibiotic use is, then, the total number of cases of resistance that would not have happened without the use of antibiotics in agriculture. This is approximately the difference between the time of actual emergence and the counterfactual emergence, multiplied by the steady-state prevalence. While we don't know what would have happened in any particular case, we can estimate the likely magnitude of agricultural impacts.
The case where horizontal human transmission rates are intermediate is particularly interesting. If each case in a population generates approximately one new case (a situation we call “quasi-epidemic” transmission), each instance of heterospecific transmission will initiate a long chain of horizontal transmission that eventually burns out. Quasi-epidemic transmission can amplify a relatively low amount of heterospecific transmission and substantially increase prevalence [23–25]. The effect is sustained as long as heterospecific transmission continues. A corollary is that banning agricultural antibiotic use would have maximal benefits if horizontal transmission is quasi-epidemic [24]. Moreover, the effects are most difficult to estimate because both heterospecific and horizontal transmission must be accounted for.
These principles apply to bacteria associated with outpatient antibiotic use and community-acquired infections as well as those that are primarily hospital-acquired. Although quasi-epidemic transmission would seem to be a special case, it may in fact be the rule for many hospital-acquired bacteria because it is the natural endpoint of the interplay between economics and ecology [30]. By spending money on hospital infection control, hospital administrators can reduce nosocomial transmission rates for resistant bacteria. For example, hospitals may screen and isolate patients who are likely to be carriers (i.e., active surveillance) and implement infection-control measures, but this comes at the cost of isolating patients [31]. Total costs are minimized by spending just enough to eliminate (or nearly eliminate) the pathogen; thus, quasi-epidemic transmission is the economic optimum [30].
The Community as a Reservoir for Resistance
Horizontal transmission is further complicated by population structure, such as the movement of humans through hospitals and long-term care facilities. Medical antibiotic use and horizontal transmission rates are high in hospitals, but this is counterbalanced by short hospital stays. An emerging view for hospital-acquired bacterial infections is that persistent asymptomatic carriage plays a key role in the epidemic of resistance. ARB can asymptomatically colonize a person for years: even if the number of other people infected during a single hospital visit is less than one, this number will exceed one when summed over several hospital visits [25,32,33]. Thus, the ecological reservoir of resistance in the community plays an important role in the increasing frequency of resistance in hospital-acquired infections.
Short hospital visits and long persistence times of ARB in people guarantee that some of the costs associated with failed infection control are passed on to other hospitals—new carriers are frequently discharged from one hospital only to be admitted to another hospital later [30]. Thus, the harm done by these ARB is borne by the whole human population, particularly all of the health-care institutions that serve a single catchment population. In economic terms, the damage caused by the carriage of ARB is a kind of pollution.
By comparing the total number of new carriers generated in the community, the impacts of agricultural antibiotic use on hospitals can be compared directly to the impact hospitals have on each other (Figure 2). The rate of heterospecific transmission is intrinsically difficult to measure directly because the risk of exposure and colonization per meal is very small. Nevertheless, agricultural antibiotic use may generate as many carriers as hospitals for the simple reason that the population experiences many more meals than hospital discharges [34]. When agricultural and nosocomial transmission are equally rare in the population, the latter will be much easier to identify and quantify.
Figure 2 How Large Is the Impact of Antibiotic Use in Agriculture?
Comparing the amount of antibiotics used in agriculture with the amount used in medicine means comparing fundamentally different things because they affect the emergence of medically important antibiotic resistance in different ways. For hospital-acquired infections, it is more appropriate to think about ARB carriage in the community as a kind of pollution that flows into hospitals. Thus, the appropriate way to measure impact is by counting how many new carriers are added to the community reservoir from hospital discharges versus from exposure to bacteria that originate on farms. Different formulas describe these processes.
To count ARB carriers among hospital discharges, let x denote the proportion of patients from a hospital (or other institution) that are colonized on discharge. In some discharged patients, resistant bacteria clear quickly, but a fraction, p, become ARB carriers. Some proportion of patients were already carriers at the time of admission, denoted by k. Institutions vary by size, H, and average length of stay (1/s). Thus, the rate that new carriers are discharged from a hospital is given by the formula: sH(px − k). This formula measures the contribution of a hospital to the number of ARB carriers in the community.
For example, a hospital with 400 filled beds (H = 400 people) serves a US population of about 250,000 people. With a five-day average length of stay (the discharge rate is s = 0.2 per patient per day), the hospital discharges about 80 patients each day. If we suppose that 20% of patients acquire resistant bacteria while hospitalized, and one in four of these patients become carriers (px − k = 0.05), a hospital would discharge about four persistently colonized people per day—about 1,460 carriers after one year, or approximately 0.58% of its catchment population.
A different formula characterizes heterospecific transmission, following exposure to ARB on contaminated food. We let g denote the daily per-capita rate that ARB are ingested with a meal. Similarly, we let h denote the proportion of those ARB populations that survive the gastric barrier and persistently colonize. The number of new carriers generated in the community by agricultural antibiotic use in a population of size N is: ghN. For example, if the average person consumes some ARB in 1% of meals (g = 0.03 per person per day), followed by colonization with probability one in 2,000 (h = 0.0005), agricultural antibiotic use would generate about four new carriers per day in a population of 250,000 people, N, approximately the same number as a hospital.
The formulas illustrate a general principle: “A large number of people exposed to a small risk may generate many more cases than a small number exposed to a high risk” [34].
A Natural Experiment: Glycopeptides and Vancomycin-Resistant Enterococci
Is the impact of agricultural antibiotic use on the emergence and spread of ARB in humans large or small relative to medical antibiotic use? Put another way, are farms or hospitals bigger polluters? A large-scale natural experiment was conducted in the United States and several European countries when each adopted different policies on glycopeptide use in animals (avoparcin) and humans (vancomycin) [16,17,35–37]. Many European countries approved avoparcin for animal growth promotion in the 1970s, but the US did not.
In the early 1980s, demand for vancomycin in US hospitals surged because of increasing aminoglycoside resistance among enterococci and methicillin resistance in Staphylococcus aureus. Physicians in US hospitals also used oral vancomycin for some Clostridium difficile infections [37–39]. In the late 1980s and early 1990s, vancomycin-resistant enterococci (VRE) emerged and spread through US health-care systems. In Europe, hospitals used less vancomycin because most enterococci were sensitive to aminoglycosides, and oral vancomycin was seldom used. VRE still emerged and spread through European hospitals, but the problem has been less severe than in the US [40].
A different pattern emerges for community prevalence of VRE. VRE are rarely found outside of hospitals in the US, except for patients who have a prior history of hospitalization. Community prevalence of VRE in the US is typically less than 1%. In contrast, community prevalence of VRE was estimated at 2%–12% in Europe during the late 1990s, including carriage by people with no history of hospitalization [17,41–48]. In other words, the European community reservoir generated by vancomycin use in hospitals and avoparcin use in agriculture was apparently much larger than the US community reservoir generated only by vancomycin use in hospitals.
The prevalence of VRE in the community declined after the EU banned avoparcin [15]. Thus, avoparcin is at least partly responsible for the reservoir of VRE in the European community, but how much of that reservoir came from avoparcin and how much came from hospitals? To weigh the impact, we subtract the community prevalence of VRE in the US (<1%) from the community prevalence of VRE in Europe (>2%). The remainder (>1%) is attributed to avoparcin. This analysis probably underestimates the real impact because vancomycin was used less in European than in US hospitals. Thus, avoparcin use in Europe would appear to be responsible for generating a larger reservoir of VRE in the community than US hospitals. Put another way, the impact of avoparcin use on European hospitals was larger than the impact of US hospitals on one another.
Conclusion
Despite the evidence that avoparcin use has had a large impact on the emergence and spread of VRE by increasing the reservoir of VRE in the EU, some uncertainty continues to surround the clinical significance of VRE strains of animal origin and of the zoonotic origins of resistance in general. Bacterial strains circulating in hospitalized populations may be genetically distinct from those circulating in the general human population [13,17,49]. Thus, bacterial populations are some combination of zoonotic, quasi-epidemic, and epidemic strains. The complexity of bacterial population biology and genetics makes it practically impossible to trace bacteria (or resistance factors) from the farm to the hospital, or to directly attribute some fraction of new infections to agricultural antibiotic use. Asymptomatic carriage of resistance factors by nonfocal commensal bacteria adds to a general risk of resistance, but transfer of resistance among bacterial species is unpredictable and difficult to quantify. Until more evidence is available, it is prudent and reasonable to consider bacteria with resistance genes a general threat [50–52].
Some part of the controversy over agricultural antibiotic use has been a disagreement about how to weigh evidence and make decisions when the underlying biological processes are complex. In this case, the effects of agricultural antibiotic use on human health remain uncertain, despite extensive investigation, and the effects may be unknowable, unprovable, or immeasurable by the empirical standards of experimental biology. What should be done when complexity makes an important public-health effect intrinsically difficult to measure? What is an appropriate “null hypothesis” or its equivalent? Should the same standards of proof be used in science and science-based policy? Where should the burden of proof fall?
Scientific assessments for policy should summarize the best state of the science, recognizing that the burdens and standards of proof are necessarily softer because of the uncertainty that is introduced by biological complexity. The best decisions weigh the evidence in light of the inherent uncertainty. The EU banned the use of antibiotics for growth promotion, based on the precautionary principle. The use of the precautionary principle was criticized by some as unscientific in this context. In fact, the intrinsic problem of knowability, posed by the biological complexity of the problem, makes the use of precautionary decision making particularly suitable in this arena. The assumption that plausible dangers are negligible, even when it is known that such dangers are constitutively very difficult to measure, may be more unscientific than the use of precaution.
Summary Points
The emergence and spread of ARB is complex and intrinsically difficult to study; mathematical models can help with understanding underlying mechanisms and guiding policy responses.
Agricultural antibiotic use may generate novel types of ARB that spread to the human population; models can help estimate how much additional disease has been caused by agricultural antibiotic use.
Transmission of ARB from animal to human populations is particularly difficult to measure, as it is the product of a very high exposure rate to potentially contaminated food, and a very low probability of transmission at any given meal.
Depending on the assumptions used, the model suggests that transmission from agriculture can have a greater impact on human populations than hospital transmission.
A comparison of patterns of colonization of VRE in Europe and the United States, which had different patterns of agricultural and hospital antibiotic use, suggests that agricultural antibiotic use can have important quantitative effects on the spread of resistance in the community.
Citation: Smith DL, Dushoff J, Morris G Jr (2005) Agricultural antibiotics and human health. PLoS Med 2(8): e232.
The views presented in this paper represent the personal views of the authors and do not construe or imply any official position or policy of the Fogarty International Center, National Institutes of Health, Department of Health and Human Services, or the US government.
Abbreviations
ARBantibiotic-resistant bacteria
VREvancomycin-resistant enterococci
==== Refs
References
Taylor LH Latham SM Woolhouse MEJ Risk factors for human disease emergence Philos Trans R Soc Lond B Biol Sci 2001 356 983 989 11516376
Hamscher G Pawelzick HT Sczesny S Nau H Hartung J Antibiotics in dust originating from a pig-fattening farm: A new source of health hazard for farmers? Environ Health Perspect 2003 111 1590 1594 14527837
Zahn JA Evidence for transfer of tylosin and tylosin-resistant bacteria in air from swine production facilities using sub-therapeutic concentrations of Tylan in feed J Anim Sci 2001 79 189
Iversen A Kuhn I Rahman M Franklin A Burman LG Evidence for transmission between humans and the environment of a nosocomial strain of Enterococcus faecium
Environ Microbiol 2004 6 55 59 14686941
Gilliver MA Bennett M Begon M Hazel SM Hart CA Antibiotic resistance found in wild rodents Nature 1999 401 233 234 10499578
Osterblad M Norrdahl K Korpimaki E Huovinen P Antibiotic resistance. How wild are wild mammals? Nature 2001 409 37 38
Chee-Sanford JC Aminov RI Krapac IJ Garrigues-Jeanjean N Mackie RI Occurrence and diversity of tetracycline resistance genes in lagoons and groundwater underlying two swine production facilities Appl Environ Microbiol 2001 67 1494 1502 11282596
Emborg HD Andersen JS Seyfarth AM Andersen SR Boel J Relations between the occurrence of resistance to antimicrobial growth promoters among Enterococcus faecium isolated from broilers and broiler meat Int J Food Microbiol 2003 84 273 284 12810291
Kmmerer K Resistance in the environment J Antimicrob Chemother 2004 54 311 320 15215223
Mattick K Durham K Domingue G Jorgensen F Sen M The survival of foodborne pathogens during domestic washing-up and subsequent transfer onto washing-up sponges, kitchen surfaces and food Int J Food Microbiol 2003 85 213 216 12878380
Gorman R Bloomfield S Adley CC A study of cross-contamination of food-borne pathogens in the domestic kitchen in the Republic of Ireland Int J Food Microbiol 2002 76 143 150 12038571
Sorensen TL Blom M Monnet DL Frimodt-Moller N Poulsen RL Transient intestinal carriage after ingestion of antibiotic-resistant Enterococcus faecium from chicken and pork N Engl J Med 2001 345 1161 1166 11642232
Willems RJ Top J van den Braak N van Belkum A Endtz H Host specificity of vancomycin-resistant Enterococcus faecium
J Infect Dis 2000 182 816 823 10950776
Bruinsma N Willems RJL van den Bogaard AE van Santen-Verheuevel M London N Different levels of genetic homogeneity in vancomycin-resistant and -susceptible Enterococcus faecium isolates from different human and animal sources analyzed by amplified-fragment length polymorphisms Antimicrob Agents Chemother 2002 46 2779 2783 12183228
Aarestrup FM Seyfarth AM Emborg HD Pedersen K Hendriksen RS Effect of abolishment of the use of antimicrobial agents for growth promotion on occurrence of antimicrobial resistance in fecal enterococci from food animals in Denmark Antimicrob Agents Chemother 2001 45 2054 2059 11408222
Wegener HC Aarestrup FM Jensen LB Mammerum AM Bager F Use of antimicrobial growth promoters in food animals and Enterococcus faecium resistance to therapeutic antimicrobial drugs in Europe Emerg Infect Dis 1999 5 329 335 10341169
Bonten MJ Willems R Weinstein RA Vancomycin-resistant enterococci: Why are they here, and where do they come from? Lancet Infect Dis 2001 1 314 325 11871804
Phillips I Casewell M Cox T de Groot B Friis C Does the use of antibiotics in food animals pose a risk to human health? A critical review of published data J Antimicrob Chemother 2004 53 28 52 14657094
Jensen VF Neimann J Hammerum AM Molbak K Wegener HC Does the use of antibiotics in food animals pose a risk to human health? An unbiased review? J Antimicrob Chemother 2004 54 274 275 15140862
Bonten MJ Austin DJ Lipsitch M Understanding the spread of antibiotic resistant pathogens in hospitals: Mathematical models as tools for control Clin Infect Dis 2001 33 1739 1746 11595995
Lipsitch M Singer RS Levin BR Antibiotics in agriculture: When is it time to close the barn door? Proc Natl Acad Sci U S A 2002 99 S572 S574
Smith DL Harris AD Johnson JA Silbergeld EK Morris JG Animal antibiotic use has an early but important impact on the emergence of antibiotic resistance in human commensal bacteria Proc Natl Acad Sci U S A 2002 99 6434 6439 11972035
Smith DL Johnson JA Harris AD Furuno JP Perencevich EN Assessing risks for a pre-emergent pathogen: Virginiamycin use and the emergence of streptogramin resistance in Enterococcus faecium
Lancet Infect Dis 2003 3 241 249 12679267
Kelly L Smith DL Snary EL Johnson JA Harris AD Animal growth promoters: To ban or not to ban? A risk assessment approach Int J Antimicrob Agents 2004 24 205 212 15325422
Smith DL Dushoff J Perencevich EN Harris AD Levin SA Persistent colonization and the spread of antibiotic resistance in nosocomial pathogens: Resistance is a regional problem Proc Natl Acad Sci U S A 2004 101 3709 3714 14985511
Becker NG Analysis of infectious disease data 1989 London Chapman and Hall 224
Wegener HC Aarestrup FM Gerner-Smidt P Bager F Transfer of antibiotic resistant bacteria from animals to man Acta Vet Scand Suppl 1999 92 51 57 10783717
Aarestrup FM Engberg J Antimicrobial resistance of thermophilic Campylobacter
Vet Res 2001 32 311 321 11432422
Luber P Wagner J Hahn H Bartelt E Antimicrobial resistance in Campylobacter jejuni and Campylobacter coli strains isolated in 1991 and 2001–2002 from poultry and humans in Berlin, Germany Antimicrob Agents Chemother 2003 47 3825 3830 14638490
Smith DL Levin SA Laxminarayan R Strategic interactions in multi-institutional epidemics of antibiotic resistance Proc Natl Acad Sci U S A 2005 102 3153 3158 15677330
Perencevich EN Fisman DN Lipsitch M Harris AD Morris JG Projected benefits of active surveillance for vancomycin-resistant enterococci in intensive care units Clin Infect Dis 2004 38 1108 1115 15095215
Bonten MJ Hayden MK Nathan C Rice TW Weinstein RA Stability of vancomycin-resistant enterococcal genotypes isolated from long-term-colonized patients J Infect Dis 1998 177 378 382 9466524
Cooper BS Medley GF Stone SP Kibbler CC Cookson BD Methicillin-resistant Staphylococcus aureus in hospitals and the community: Stealth dynamics and control catastrophes Proc Natl Acad Sci U S A 2004 101 10223 10228 15220470
Rose G The strategy of preventive medicine 1992 Oxford Oxford University Press 160
Martone WJ Spread of vancomycin-resistant enterococci: Why did it happen in the United States? Infect Control Hosp Epidemiol 1998 19 539 545 9758052
Cetinkaya Y Falk P Mayhall CG Vancomycin-resistant enterococci Clin Microbiol Rev 2000 13 686 707 11023964
Rice LB Emergence of vancomycin-resistant enterococci Emerg Infect Dis 2001 7 183 187 11294702
Morris JG Shay DK Hebden JN McCarter RJ Perdue BE Enterococci resistant to multiple antimicrobial agents, including vancomycin. Establishment of endemicity in a university medical center Ann Intern Med 1995 123 250 259 7611590
Kirst HA Thompson DG Nicas TI Historical yearly usage of vancomycin Antimicrob Agents Chemother 1998 42 1303 1304 9593175
Schouten MA Hoogkamp-Korstanje JA Meis JF Voss A European VRE Study Group Prevalence of vancomycin-resistant enterococci in Europe Eur J Clin Microbiol Infect Dis 2000 19 816 822 11152305
van der Auwera P Pensart N Korten V Murray BE Leclercq R Influence of oral glycopeptides on the fecal flora of human volunteers: Selection of highly glycopeptide-resistant enterococci J Infect Dis 1996 173 1129 1136 8627064
Gordts B van Landuyt H Ieven M Vandamme P Goossens H Vancomycin-resistant enterococci colonizing the intestinal tracts of hospitalized patients J Clin Microbiol 1995 33 2842 2846 8576330
Endtz HP van den Braak N van Belkum A Kluytmans JA Koeleman JG Fecal carriage of vancomycin-resistant enterococci in hospitalized patients and those living in the community in The Netherlands J Clin Microbiol 1997 35 3026 3031 9399488
Schouten MA Voss A Hoogkamp-Korstanje JA VRE and meat Lancet 1997 349 1258
van den Braak N Kreft A van Belkum D Verbrugh H Endtz H Vancomycin-resistant enterococci in vegetarians Lancet 1997 350 146 147
van den Bogaard AE Mertens P London NH Stobberingh EE High prevalence of colonization with vancomycin- and pristinamycin-resistant enterococci in healthy humans and pigs in The Netherlands: Is the addition of antibiotics to animal feeds to blame? J Antimicrob Chemother 1997 40 454 456 9338505
van den Braak N van Belkum A van Keulen M Vliegenthart J Verbrugh HA Molecular characterization of vancomycin-resistant enterococci from hospitalized patients and poultry products in The Netherlands J Clin Microbiol 1998 36 1927 1932 9650938
Stobberingh E van den Bogaard A London N Driessen C Top J Enterococci with glycopeptide resistance in turkeys, turkey farmers, turkey slaughterers, and (sub)urban residents in the south of The Netherlands: Evidence for transmission of vancomycin resistance from animals to humans? Antimicrob Agents Chemother 1999 43 2215 2221 10471567
Leavis HL Willems RJ Top J Spalburg E Mascini EM Epidemic and nonepidemic multidrug-resistant Enterococcus faecium
Emerg Infect Dis 2003 9 1108 1115 14519248
Hammerum AM Fussing V Aarestrup FM Wegener HC Characterization of vancomycin-resistant and vancomycin-susceptible Enterococcus faecium isolates from humans, chickens, and pigs by RiboPrinting and pulsed-field gel electrophoresis J Antimicrob Chemother 2000 45 677 680 10797092
Sundsfjord A Simonsen GS Courvalin P Human infections caused by glycopeptide-resistant Enterococcus spp: Are they a zoonosis? Clin Microbiol Infect 2001 7 Suppl 4 16 33
Bogo Jensen L Willems AE van den Bogaard RJ Genetic characterization of glycopeptide-resistant enterococci of human and animal origin from mixed pig and poultry farms APMIS 2003 111 669 772 12969023
| 15984910 | PMC1167557 | CC0 | 2021-01-05 11:13:39 | no | PLoS Med. 2005 Aug 5; 2(8):e232 | utf-8 | PLoS Med | 2,005 | 10.1371/journal.pmed.0020232 | oa_comm |
==== Front
PLoS MedPLoS MedpmedplosmedPLoS Medicine1549-12771549-1676Public Library of Science San Francisco, USA 1600002410.1371/journal.pmed.0020207Policy ForumOtherMedical EducationAcademic MedicineMedical EducationPatientsFive Futures for Academic Medicine Policy ForumAwasthi Shally Beardmore Jil Clark Jocalyn *Hadridge Philip Madani Hardi Marusic Ana Purcell Gretchen Rhoads Margaret Sliwa-Hähnle Karen Smith Richard Edejer Tessa Tan-Torres Tugwell Peter Underwood Tim Robyn Ward on behalf of the International Campaign to Revitalise Academic Medicine Shally Awasthi is Professor, Department of Paediatrics, King George's Medical University, Lucknow, India. Jil Beardmore is Research and Project Coordinator at the Centre for Global Health, University of Ottawa, Ottawa, Ontario, Canada. Jocalyn Clark is Associate Editor of BMJ, London, United Kingdom, and Project Manager of ICRAM, London, United Kingdom. Philip Hadridge is an organisation consultant in Cambridge, England. Hardi Madani is a fourth-year medical student at the Royal Free and UCL Medical Schools in London, United Kingdom, and a part-time pharmacist. Ana Marusic is Professor, Department of Anatomy, Zagreb University School of Medicine, Zagreb, Croatia, and Editor of Croatian Medical Journal, Zagreb, Croatia. Gretchen Purcell is Pediatric Surgery Fellow at Pittsburgh Children's Hospital and Adjunct Assistant Professor of Medicine at the University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America. Margaret Rhoads is a medical student at Imperial College London, London, United Kingdom. Karen Sliwa-Hähnle is Professor, Department of Cardiology, CH Baragwanath Hospital, University of the Witwatersrand, Johannesburg, South Africa. Richard Smith is former Editor of BMJ, co-founder of ICRAM, and Chief Executive of UnitedHealth Europe, London United Kingdom. Tessa Tan-Torres Edejer is Scientist, Department of Health Systems Financing, World Health Organization, Geneva, Switzerland. Peter Tugwell is Professor of Medicine and Head of the Centre for Global Health at the University of Ottawa, Ottawa, Ontario, Canada, and Leader of ICRAM. Tim Underwood is Medical Research Council/Royal College of Surgeons Clinical Research Training Fellow, University of Southampton, Southampton, United Kingdom. Robyn Ward is Professor, Department of Medical Oncology, St Vincent's Hospital, Darlinghurst, New South Wales, Australia, and School of Medicine, University of New South Wales, Darlinghurst, New South Wales, Australia. See Acknowledgments for the members of the working party of the International Campaign to Revitalise Academic Medicine.
Competing Interests: JC is an employee of the BMJ Publishing Group, which benefits from academic medicine. RS is an employee of the UnitedHealth Group, which benefits from the output of academic medicine. It's not easy to see how the company might be affected financially from any of the possible changes in academic medicine. He is also an unpaid governor of St George's, University of London, and an unpaid board member of the Public Library of Science, both of which will be affected by any changes.
*To whom correspondence should be addressed. E-mail: [email protected] 2005 5 7 2005 2 7 e207Copyright: © 2005 Awasthi et al.2005This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.The International Campaign to Revitalise Academic Medicine (ICRAM) considered current global instabilities and future drivers of change, and then created five scenarios of how academic medicine might look in 2025.
The International Campaign to Revitalise Academic Medicine (ICRAM) considered current global instabilities and future drivers of change, and then created five scenarios of how academic medicine might look in 2025
==== Body
Introduction
“Academic medicine” might be defined as the capacity of the health-care system to think, study, research, discover, evaluate, innovate, teach, learn, and improve. As such, little could be more important—particularly as new discoveries in science offer tremendous opportunities and emergent diseases pose huge threats. Yet something is not right with academic medicine. Worse, the diagnosis is not entirely clear, although many august bodies have reported on the issue (Table 1), and the treatment is unknown. Moreover, these previous consultations have been based in the industrialised world, particularly the United Kingdom and the United States, and few have taken a global view.
Table 1 Reports of Major National Academic Medicine Organisations
The International Campaign to Revitalise Academic Medicine (ICRAM) was founded to give young medical academics an opportunity to think about the future of academic medicine (Box 1). It started with only two premises: (1) at the start of the new millennium it was necessary to think globally, and (2) “more of the same” was not the answer. Reinvention was needed.
Box 1. ICRAM
In 2003 the BMJ, Lancet, and 40 other partners launched ICRAM, a global initiative that is committed to fostering a debate about the future of academic medicine (bmj.com/academicmedicine). The campaign arose because of a persistent concern that academic medicine is in crisis around the world. At a time of increasing health burden, poverty, globalisation, and innovation, many have argued that academic medicine is nevertheless failing to realise its potential and global social responsibility.
ICRAM is composed of the following:
A core working party of 20 medical academics representing 14 countries
Stakeholder groups representing the areas of academia, business and industry, government and policy makers, journal editors, patients, professional associations, and students and trainees
Regional groups covering the world
A facilitating committee that helps plan and execute the ICRAM work
Through a series of stakeholder and regional consultations, systematic review of the available evidence, and future scenarios building, ICRAM intends to produce a series of recommendations for reform in global academic medicine, including the following:
Developing a vision and values for academic medicine
Recommending strategies for building capacity in academic medicine, including better career paths
Proposing how academic medicine could improve its relationships with “customers,” including patients, policy makers, practitioners, and others
ICRAM decided to undertake some scenario planning, a technique of thinking about both the future and the present. The technique works by gathering together a team who consider the instabilities in the present and the drivers of the future and who then imagine plausible but different futures. The aim is not to predict the future, which is impossible, but to enable richer conversations through stretching thinking on what the future might bring. Once the scenarios have been created, they can be used to think more deeply about the present and the near future.
The group began by considering current instabilities in academic medicine around the world (Box 2). None of these ideas are new, and most people would probably agree with most of them.
Box 2. Current Instabilities in Academic Medicine
Widespread, even universal, agreement that things are not right but little agreement on the exact nature of the problem
Lack of capacity in “translational research”—that which brings innovations directly to patients
The substantial gap between best, evidence-based practice and what actually happens
The canyon between academics and practitioners
The growing difficulty/impossibility of a single individual being competent in practice, research, and teaching
Use of citation indices in research assessment, which overemphasises the value of basic research and underemphasises the importance of applied research that may bring more immediate benefit to patients
A lack of mutual respect among different categories of researchers—basic, clinical, public health, primary care, applied, etc.
Problems with career progression for academics
Shortages of doctors wanting to enter careers in research
In many, probably most, countries those doctors who enter careers in research, who ideally would be the “best and the brightest,” being likely to earn much less than those who can spend at least some time working in private practice
Research often not being concerned with the biggest health problems (particularly true in a global context)
Systems of accreditation of doctors making life difficult for doctors who want to pursue an academic career
Although no clinicians are openly against research, clinicians being often unimpressed with doctors who concentrate on research
Too much medical research being undertaken by doctors with limited training in research methods—making the research of poor quality
Researchers often setting little store by quality improvement projects, although such projects are one of the ways of ensuring that all patients receive the most up-to-date care
Much of the teaching in medicine being done by people with very little training in medicine
The ratio of teachers to students in many medical schools being so low that the quality of teaching is reduced
In many countries academic medicine lacking a well-resourced institution to speak for it
Academic medicine relating poorly to its stakeholders—patients, policy makers, practitioners, the public, and the media
The great pressures on health services, such that academic medicine is often squeezed and forgotten
Much of what determines the future of academic medicine will lie outside the control of medical academics themselves. The world will change around them, and they will have to follow. But there will also be change that comes from within academic medicine. Box 3 shows some of the drivers of the future considered by the group.
Box 3. Drivers of Change in Academic Medicine
New science and technology, particularly genetics and information technology
The rise of sophisticated consumers
Globalisation
Emergent diseases
Increasing gap between rich and poor
Death of distance
“Big hungry buyers” demanding more from health care
Spread of the internet and digitalisation
Managerialism
Increasing anxieties about security
Expanding gap between what could be done and what can be afforded in health care
Lack of agreement on where “health” begins and ends
Ageing of society
Feminisation of medicine
Increasing accountability of all institutions
Loss of respect for experts
Rise of self care
Rise of ethical issues
24/7 society
Economic and political rise of India and China
Five Scenarios
In building scenarios, the group used a time span of 20 years, but some of the scenarios are more futuristic than others. We decided to write up the scenarios as if they were in the past in order to give some idea of how they might arise. The scenarios are summarised in Table 2, and described more fully in the rest of this article.
Table 2 Summary of Scenarios
Academic Inc.: “Academic medicine flourishes in the private sector”. Slowly but surely the public sector around the world realised that it could not support the costs of academic medicine. Medical students had high earnings during a professional lifetime: why shouldn't they pay for their education? And if researchers were doing something valuable then shouldn't they be able to find a market for their product—accepting that sometimes payment would come from the public sector?
The process of academic medicine moving almost entirely into the private sector began with an increasing number of medical schools becoming private. The most prestigious schools went first. In an increasingly global market these schools could charge high fees, pay their staff well, and improve their facilities. They also invested a great deal in information and communication technology, bringing state-of-the-art learning to their students. This meant too that the schools could run courses for students far away from their geographical base. As these schools developed they expanded internationally, sometimes forming alliances with other prestigious schools but also taking over weaker schools. Soon the best schools were operating on all five continents. In the branches in developing countries, medical student bodies tended to comprise both students from the developed countries along with a quota from the developing countries.
Competition was intense and involved both cost and quality. Schools that managed to improve quality while reducing costs—usually through clever use of technology—flourished, but a great many medical schools disappeared. The numbers of students, however, increased, and the competition for talent was intense, with schools offering generous bursaries to poor but bright students and becoming ever more sophisticated at finding high-quality students in resource-poor populations.
As happens in most intensely competitive markets, medical schools also competed by occupying niches. Schools offered very different kinds of courses, specialising in older students, basic science, rural medicine, surgical skills, training doctors for poor communities (in both the country where the medical school was based and lower and middle income countries), and many other subject areas. Sometimes the students' fees were paid by governments, local communities, or the military in order to produce students who met their needs. Many students attended schools in countries other than their own.
Health research happened almost entirely in the private sector, but in a wide range of organisations: pharmaceutical companies, medical schools, biotechnology companies, small companies offering a huge range of services, and charities. Companies were founded not only by researchers but also by patients, practitioners, and others. Many of the companies founded by academics offered complex and innovative heath services. As in all business, to be successful companies had to be highly responsive to the needs of customers, including patients and governments. Those that were innovative, flexible, responsive, and relentlessly cost-conscious flourished, but many companies “failed”. Little stigma was, however, attached to “failure”. Indeed, as in Silicon Valley at the end of the 20th century, experience of “failure” was seen by many as an important qualification in a leader.
The injection of more competitive pressure and a competitive business model into academic medicine increased not only efficiency but also “effectiveness”: research was much more relevant, and the time lag between the development of new ideas and their introduction into practice was dramatically shortened. Basic science was still well funded because both governments and investors recognised the potentially high returns. Research into the health needs of poor and marginal populations also improved because public sector bodies concentrated their resources into these problems, leaving the problems of the wealthier to the market.
Applying a competitive business model to academic medicine meant that efficiency and effectiveness trumped equity. On the negative side, the scenario “Academic Inc.” resulted in a two-tier system, with the rich finding it easy to create careers in academic medicine and the poor finding it hard to enter the profession—despite the generous bursaries available to some. In addition, much more attention continued to be paid to the health problems of wealthier people and countries, and the brain drain from poor to rich countries accelerated. Innovation also suffered. Private academic medicine enjoyed less lead time and had more direct and immediate accountability to its shareholders than when it was publicly funded.
Reformation: “All teach, learn, research, and improve”. Twenty years ago there was increasing concern about the gap between academic medicine and practice, with important research results not being implemented, too much irrelevant research, bored students, and practitioners who stopped learning. In some medical communities and among their medical leadership, the response was not to try and strengthen academic medicine and make it more responsive but rather to abolish it and instead to bring the processes of teaching, learning, researching, and improving into the main stream of health care, and tailor these to local needs. This innovative—though not initially welcomed—response proved to be highly successful and was copied everywhere. A century of separation of academic medicine from practice was ended. Professors disappeared. The entity “academic medicine” was dead. It was akin to the destruction of the monasteries and so became known as the reformation of academic medicine.
Teaching, learning, researching, and quality improvement all began to take place in the practice setting and were everybody's business. But importantly the fiction that an individual could be competent in practice, teaching, research, and improvement finished. It was teams that had to have all these competencies not individuals, and substantial investment was made in getting teams to work well and to communicate to a degree rarely seen before in health care.
The teams were supported by advanced technology that provided online learning, decision support, answers to questions that arose during practice, and access to research results. Much of the teaching and research was done in collaboration with patients, and all teams included patients as well as practitioners, students, professional researchers, and other health professionals.
Research was built around the questions that arose when doctors (and other health professionals) and patients consulted together. The questions were collected by the National Question Answering Service, which provided evidence-based answers to questions when it could. The service also organised research to answer questions that arose commonly, were unanswered at that time, but could be answered. Teams of different sizes and skills were assembled to conduct research; some of the researchers were permanently in practice but others—particularly basic researchers—were resident in research institutions and joined teams as needed.
Some research was driven by discoveries made in basic science rather than questions that arose during practice; the fact that practitioners and researchers were used to working together in teams facilitated “translational” research.
The teams also switched back and forth from research to quality improvement, ensuring that research developments were fed through into practice. Studies reporting the results of quality improvement projects were published just as frequently as research studies, and highly efficient information systems ensured that relevant information reached practitioners quickly—unlike in the old days when practitioners had been deluged with research results, most of which were irrelevant to them.
Intellectual leadership in health care was provided by specialist societies, which included patients, citizen juries, researchers, health professionals other than doctors, health managers, and policy makers as equal members. In most countries the specialist societies were gathered together into an academy or institute of health care, and there was an international academy that was much more than a talking shop: it had a strong influence on world leaders.
Health students started their training with six months in institutions that taught them how to learn. The learning professionals who staffed these institutions were available to all the practice teams. Students then learnt through attachment to practice teams, starting with a spell in general practice. Some students specialised early, some becoming competent cardiologists within five years. Becoming an independent professional depended not on university degrees or exams but on a demonstration of competencies determined by a national body dominated by patients that used the most up-to-date methods for assessment.
Learning was by doing, and the divisions of undergraduate, specialist, and continuing education disappeared—as did the divisions among teaching, learning, researching, and quality improvement.
One problem with the “Reformation” scenario was that it lacked stability because it required shared values and beliefs, which not all teams held. Plus decision making could be slow, and it was hard for brilliant and charismatic individuals to shine as leaders and thinkers. One result was that such individuals eschewed careers in health care, research, and education. In developing countries, in particular, the lack of an academic medicine structure meant that there were fewer opportunities to influence medical research and training.
In the public eye: “Success comes from delighting patients and the public”. Academic medicine was slow to recognise the rise of global media, “celebrity culture,” and the use of public relations (or spin) to drive the political process, but once it did recognise how the world had changed it responded dramatically. Whereas it had been suspicious of the media and public appeal and rather patronising to patients, academic medicine realised that to succeed it must delight patients and the public and learn to use the media. The most successful academics became those who were very responsive to patients and the public, capturing their imaginations, and appearing regularly on their television screens. Some medical academics became as well known as film and rock stars and were feted by politicians.
All academic institutions became dominated by public citizens and patients, and the public and media relations department became the most important department in any institution. Money—from both public and private sources—followed “interest,” which was often influenced through game and “reality” shows on television. Academic medicine learnt from sport, and large prizes were awarded to those who won academic competitions. Although some academics were horrified by these developments, others remembered how John Harrison had been stimulated to solve the problem of calculating longitude through the promise of a large prize.
Not all decisions on research priorities and resource allocation were made in the glare of television cameras. Although all decisions put the public interest first and were made by the representatives of the public, some were made by more sedate and evidence-driven bodies like citizens' juries, where randomly selected patients and members of the public were presented with detailed evidence by “experts.”
Medical training was also conducted in the public eye, with students receiving much of their training from expert patients. The agenda for training was set predominantly by the public and patients, and responsiveness to patients was the number one characteristic of successful doctors and students.
There was much greater diversity than at the beginning of the millennium in the form and size of academic institutions, with both huge public and private universities and smaller institutions that were often built around one charismatic individual. Competition among the institutions was intense—particularly for “celebrity” teachers and researchers. Only those institutions that could attract and keep public attention could survive.
In developing countries, the academic health community linked itself with strong consumer movements, such as those focused on HIV/AIDS, and the leading nongovernmental organisations established their own medical schools. These ensured a powerful public voice, that training was tailored to local need, and a committed group for field testing new research advances.
On the negative side in the “In the Public Eye” scenario, medical academics felt more anxious about their job security and ability to succeed. Even celebrity academics worried their time in the spotlight was short lived. Advances in science, medicine, and technology were shaped by popular appeal, and thus subject to fads and fashion. Some patients struggled with their new-found status as governors, and there was little regulation of health information.
Global academic partnership: “Academic medicine for global health equity”. In 2005, the world began to find the growing global gap between the rich and poor unacceptable. The concern was driven partly by the media and global travel bringing the plight of the poor in front of the eyes of the rich, but it was also driven by anxieties over global security. Terrorism was recognised to be fuelled by the gap between rich and poor. Global policy makers also understood better—particularly after the report of the Commission on Macroeconomics and Health [2]—that investment in health produced some of the richest returns in not only social but also economic development. Health care was a “must have” not a “nice to have”.
Money flowed into health in the poor world, and governments required that the investment be accompanied by learning, research, planning, and evaluation. The primary concern of much of academic medicine became to improve global health, particularly through concentrating on the health problems of the 90% who had previously received only 10% of health care resources (the 90:10 gap). Academics became excited by this kind of work not only because it was intellectually exciting and highly rewarding in personal terms but also because it was where money and prestige were most likely to be found. The result was that it was impossible for an academic institution to be a world leader without a substantial investment in global health and extensive links around the world.
The view and scope of academic medicine broadened. It was increasingly concerned with human rights, justice, economics, and the environment, recognising that these are the major drivers of health. This broader view meant that academic medicine (usually referred to as “global health innovation” by 2012) became the main institution concerned with the rights of those who will be alive 50 years from now, a group that previously had nobody to speak for them. But at the same time basic science remained important because of the contribution it could make to global problems like finding vaccines and new treatments for malaria, AIDS, and emergent diseases like rapidly spread respiratory virus, which appeared in 2010 and killed millions in a global pandemic.
Academic medicine, in partnership with governments (and where corruption is prevalent, with nongovernmental organisations), became a major driver towards achieving the millennium development goals. The G8 governments had signed an accord that prohibited recruitment of academic health professionals from developing countries. Medical schools and research institutions formed themselves into networks linking with local nongovernmental organisations, joining developed and developing countries and forming links among developing countries. A network was formed whereby the universities in developed countries committed 10% of their faculty members' time to addressing problems of the developing world. Some institutions formed developed country–developing country pairs, some merged, and researchers, teachers, and students moved regularly between both settings. The net flow was to the developing world, with the 90:10 divide beginning to correct itself surprisingly rapidly. Big investments in information and communication technology meant that those in developing countries had the same access to information and modern learning methods as those in developed countries.
The networks of institutions developed a global governance structure with substantial input from politicians, practitioners, policy makers, the public, and patients. Academic medicine moved from being marginal to central in global affairs, and medical academics, particularly those with experience in both the developing and developed world, became global leaders. It was a development that happened naturally because of their broad interests in human rights, justice, and the environment.
The “Global Academic Partnership” scenario for academic medicine, however, was idealistic and sometimes struggled with realising its full potential—despite the best intentions of its architects and practitioners—because it required enormous political will and global cooperation. Too often nations would revert to narrow self interest. Academics as well often longed for the comforts of the developed world and sometimes felt exhausted by extensive travelling and the enormous problems of the developing world.
Fully engaged: “Academic medicine engages energetically with all stakeholders”. Early in the new millennium academic medicine became concerned that its relationships with its stakeholders were mostly poor. The public had little or no understanding of what academic medicine was or why it mattered. Its very name implied irrelevance to many. Patients often felt patronised by academics, and many practitioners—including doctors—were unconvinced of the value of academic medicine. “I wouldn't want a professor of surgery touching me,” was a commonly heard refrain. Although some leading academics did have good relationships with politicians, policy makers found that many academics were not interested in policy problems and that the studies they produced, even if relevant, came too late to be useful. Policy makers recognised that biotechnology might be very important in future wealth creation, but it was difficult to fund because the public profile of academic medicine was both low and clouded.
Most medical academics recognised that they were doing a poor job of relating to stakeholders and that it was thus unsurprising that they were misunderstood, underappreciated, and seen as largely irrelevant. This, they thought, was particularly unfortunate as the ability of the system of health care to discover, think, study, learn, and evaluate had never been more important.
The medical academic community thus decided that it had to do better, and across the globe medical academics organised themselves to engage fully with their stakeholders. In many countries this meant the creation of new organisations. In others it involved the transformation of existing organisations: the gongs and gowns were abandoned, and focus groups began. Fifty prestigious universities in developed countries with medical faculties partnered with universities in developing countries to help stop the “brain drain” and replace it with a “brain gain” through incentive programs that provided resources for training and research, academic recognition, travel funds, and family support. Everywhere medical academics had to learn how to communicate with the public, patients, and practitioners. They had to stop being elitist and patronising and recognise the messiness of public discourse. Crucially, they had to be much cleverer in handling the media, telling them not only about their successes but also sharing their uncertainties and problems.
But communication on its own wasn't enough. Academic medicine had to bring its stakeholders inside its processes. The governance of academies included patients, the public, practitioners, health administrators, and policy makers. Sometimes the president of an academy was not a distinguished researcher but a prominent patient, journalist, or community organisation leader. The medical academics discovered that their arguments were taken much more seriously when advanced clearly by a patient rather than by themselves. Patients, health administrators, and community organisation representatives became involved not only in peer review of grants and studies but also in the prioritising, designing, and conducting of research. Medical students became the main drivers of medical education rather than simply its consumers.
Slowly but surely medical academics became not a group apart but a highly diverse group of people with a broad set of skills and backgrounds. They were at the centre of a vibrant community of patients, members of the public, practitioners of all stripes, policy makers, members of the media, marketing experts, and politicians, all of whom were interested in learning, studying, researching, and thinking about health care.
Some academics, it must be said, found the change uncomfortable and were unconvinced of its value. Critics talked of “dumbing down” and popularisation. They fretted that in abandoning its elitism academic medicine had lost its ability to be truly original and speak independently.
For most, however, academic medicine was so much more fun than it used to be. Applications to medical schools increased. Health services invested more in evaluating what they did and paid more attention to the results. More funds flowed into basic research, and there were improvements in the connections between the many diverse groups involved in research—with the result that intellectual silos were breached.
Lessons from the Scenarios
None of these scenarios will come to exist as we have described them, but the future is likely to contain some elements from each of them. We have tried to identify common features in the scenarios to learn lessons for now. These features are shown in Box 4. Our main hope for these scenarios is that other groups may find them useful in thinking about both the present and the future of academic medicine. The scenarios will need to be adapted to the particular social, economic, and political conditions of different regional and national settings. As such, they are tools that can be used globally, modified as required. We seek not agreement but broader thinking.
Box 4. Common Features Shared By All Five Scenarios
It is likely to be important in all scenarios for academic medicine to put more effort into relating to its stakeholders: the public, patients, practitioners, politicians, and policy makers. This may demand the development of new institutions that involve all these groups.
Academic institutions will need to be more globally minded.
Teaching, researching, improving, leading, and providing service will continue to be important, but expecting individuals to be competent in them all will be increasingly impractical.
Teamwork will become ever more important, but it will also be necessary to allow individuals to shine and flourish.
Competition among academic institutions is likely to increase, and the competition will increasingly be international.
Academic institutions will need to become more “business-like” in all the scenarios. They will also need to be more adept at using the media.
Teaching and learning will be increasingly important—not least because dissatisfied students may go elsewhere. Learning will be lifelong and will depend heavily on information technology.
It will be increasingly important to combine research, both basic and applied, with implementation and improvement. The gap between knowledge and practice will become increasingly intolerable.
The range of types of academic institutions is likely to become increasingly diverse, with medical schools or academic centres just one form.
Academic medicine will need to be ever broader in its thinking and skill set, combining with and learning from other disciplines such as economics, law, ecology, and humanities.
Thinking about the future will become increasingly important for academic institutions but also increasingly difficult.
The members of the working party of the ICRAM are Tahmeed Ahmed (Scientist, Clinical Sciences Division, International Centre for Diarrhoeal Disease Research Bangladesh, Dhaka, Bangladesh), Shally Awasthi (Professor, Department of Paediatrics, King George's Medical University, Lucknow, India), A. Mark Clarfield (Professor, Department of Geriatrics, Soroka Hospital, Ben-Gurion University of the Negev, Beersheva, Israel), Lalit Dandona (Director, Centre for Public Health Research, Administrative Staff College of India, Hyderabad, India), Amanda Howe (Professor of Primary Care, School of Medicine, University of East Anglia, Norfolk, United Kingdom), John P. A. Ioannidis (Chairman, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece), Edwin C. Jesudason (Academy of Medical Sciences National Clinician Scientist, Health Foundation Leadership Fellow, and Lecturer in Paediatric Surgery, School of Reproductive and Developmental Health, University of Liverpool, Liverpool, United Kingdom), Youping Li (Director, Chinese Cochrane Centre, West China Hospital, Sichuan University, Chengdu, China), Juan Manuel Lozano (Professor, Department of Pediatrics and Clinical Epidemiology, Javeriana University School of Medicine, Bogota, Colombia), Ana Marusic (Professor, Department of Anatomy, Zagreb University School of Medicine, and Editor, Croatian Medical Journal, Zagreb, Croatia), Idris Mohammed (Outgoing Provost, College of Medical Sciences, Department of Medicine and Clinical Immunology, University of Maiduguri, Maiduguri, Nigeria), Gretchen Purcell (Pediatric Surgery Fellow, Pittsburgh Children's Hospital, and Adjunct Assistant Professor of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States), Karen Sliwa-Hähnle (Professor, Department of Cardiology, CH Baragwanath Hospital, University of the Witwatersrand, Johannesburg, South Africa), Sharon E. Straus (Associate Professor, Department of Medicine, Toronto General Hospital, University of Toronto, Toronto, Ontario, Canada), Tessa Tan-Torres Edejer (Scientist, Department of Health Systems Financing, World Health Organization, Geneva, Switzerland), Timothy Underwood (Medical Research Council/Royal College of Surgeons Clinical Research Training Fellow, University of Southampton, Southampton, United Kingdom), Robyn Ward (Associate Professor, Department of Medical Oncology, St Vincent's Hospital and School of Medicine, University of New South Wales, Darlinghurst, New South Wales, Australia), Michael S. Wilkes (Vice Dean and Professor of Medicine, School of Medicine, University of California, Davis, California, United States), and David Wilkinson (Deputy Head and Professor of Primary Care, School of Medicine, University of Queensland, Brisbane, Australia).
Note Added in Proof
Reference information for the summary of this article being published in the BMJ: Clark JP, for ICRAM (2005) Five futures for academic medicine: The ICRAM scenarios. BMJ. In press.
Citation: Awasthi S, Beardmore J, Clark J, Hadridge P, Madani H, et al. (2005) Five futures for academic medicine. PLoS Med 2(7): e207.
This article is a shortened version of a report entitled “The Future of Academic Medicine: Five Scenarios to 2025” [1] published by the Milbank Memorial Fund (www.milbank.org). A summary of this article is being published in the BMJ.
Abbreviation
ICRAMInternational Campaign to Revitalise Academic Medicine
==== Refs
References
International Campaign to Revitalise Academic Medicine The future of academic medicine: Five scenarios to 2025 2005 New York Milbank Memorial Fund In press
Commission on Macroeconomics and Health Macroeconomics and health: Investing in health for economic development 2001 Geneva World Health Organization 210
Academy of Medical Sciences Clinical academic medicine in jeopardy: Recommendations for change 2002 June London Academy of Medical Sciences Available: http://www.acmedsci.ac.uk/p_clinacad.pdf . Accessed 18 May 2005
Academy of Medical Sciences Strengthening clinical research 2003 October London Academy of Medical Sciences Available: http://www.acmedsci.ac.uk/p_scr.pdf . Accessed 18 May 2005
Forum on Academic Medicine Clinical academic medicine: The way forward 2004 November London Royal College of Physicians Available: http://www.rcplondon.ac.uk/pubs/books/clinacad/ClinAcadMed.pdf . Accessed 18 May 2005
Association of Academic Health Centers Association of Canadian Medical Colleges the Nuffield Trust The challenge to academic medicine: Leading or following? 2002 September London The Nuffield Trust Available: http://www.nuffieldtrust.org.uk/policy_themes/docs/fifthtrilateralconference-sep02.pdf . Accessed 18 May 2005
Commonwealth Fund Task Force on Academic Heath Centers Envisioning the future of academic health centers 2003 February New York The Commonwealth Fund Available: http://www.cmwf.org/usr_doc/ahc_envisioningfuture_600.pdf . Accessed 18 May 2005
Committee on the Roles of Academic Health Centers in the 21st Century Academic health centers: Leading change in the 21st century 2004 Washington (DC) Institute of Medicine of the National Academies Available: http://www.nap.edu/openbook/0309088933/html/ . Accessed 18 May 2005
American Association of Medical Colleges Ad Hoc Committee of Deans Educating doctors to provide high quality medical care: A vision for medical education in the United States 2004 July Washington (DC) American Association of Medical Colleges Available: http://services.aamc.org/Publications/showfile.cfm?file=version27.pdf&prd_id=115&prv_id=130 . Accessed 18 May 2005
| 16000024 | PMC1168885 | CC BY | 2021-01-05 10:40:26 | no | PLoS Med. 2005 Jul 5; 2(7):e207 | utf-8 | PLoS Med | 2,005 | 10.1371/journal.pmed.0020207 | oa_comm |
==== Front
Aust New Zealand Health PolicyAustralia and New Zealand Health Policy1743-8462BioMed Central London 1743-8462-2-111591891210.1186/1743-8462-2-11ResearchReducing perinatal mortality among Indigenous babies in Queensland: should the first priority be better primary health care or better access to hospital care during confinement? Johnston Trisha [email protected] Michael [email protected] Epidemiology Services Unit, Health Information Branch, Queensland Health GPO Box 48 Brisbane Queensland 4001 Australia2005 27 5 2005 2 11 11 21 3 2005 27 5 2005 Copyright © 2005 Johnston and Coory; licensee BioMed Central Ltd.2005Johnston and Coory; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
The perinatal mortality rate among Indigenous Australians is still double that of the rest of the community. The aim of our study was to estimate the extent to which increased risk of low birthweight and preterm birth among Indigenous babies in Queensland account for their continuing mortality excess. If a large proportion of excess deaths can be explained by the unfavourable birthweight and gestational age distribution of Indigenous babies, then that would suggest that priority should be given to implementing primary health care interventions to reduce the risk of low birthweight and preterm birth (eg, interventions to reduce maternal smoking or genitourinary infections). Conversely, if only a small proportion is explained by birthweight and gestational age, then other strategies might need to be considered such as improving access to high-quality hospital care around the time of confinement.
Methodology
Population-based, descriptive study of perinatal mortality rates among Indigenous and non-Indigenous babies, in Queensland, stratified by birthweight and gestational age.
Results
Indigenous babies are twice as likely to die as their non-Indigenous counterparts (rate ratio1998–2002: 2.01; 95%ci 1.77, 2.28). However, within separate strata of birth weight and gestational age, Indigenous and non-Indigenous rates are similar. The Mantel-Haenszel rate ratio adjusted for birth weight and gestational age was 1.13 (0.99, 1.28). This means that most of the excess mortality in Indigenous babies is largely due to their unfavourable birth weight and gestational-age distributions. If Indigenous babies had the same birth weight and gestational age distribution as their non-Indigenous counterparts, then the relative disparity would be reduced by 87% and 20 fewer Indigenous babies would die in Queensland each year.
Conclusion
Our results suggest that Indigenous mothers at high risk of poor outcome (for example those Indigenous mothers in preterm labour) have good access to high quality medical care around the time of confinement. The main reason Indigenous babies have a high risk of death is because they are born too early and too small. Thus, to reduce the relative excess of deaths among Indigenous babies, priority should be given to primary health care initiatives aimed at reducing the prevalence of low birth weight and preterm birth.
==== Body
Background
From a public-health perspective, the major obstetric and perinatal problem in Australia is the poor health of Indigenous mothers and babies. Although Australia as a whole has one of the lowest perinatal mortality rates (PMR) of any of the established market economies [1], Indigenous Australians have PMRs that are at least twice as high as their non-Indigenous counterparts [2,3].
Moreover, the relative excess of deaths among Indigenous babies has not improved over time. In Queensland in 1987–1989, the PMR was 2.2 times higher among Indigenous compared with non-Indigenous babies and in 2000–2002 the rate was still 2.1 times higher. A similar lack of progress is evident in other states [4-6].
The risk of perinatal death is strongly related to a baby's birthweight and gestational age. For example, the risk of death for a moderately preterm baby (33 to 36 weeks gestation) in Queensland is 8.2 times greater than that of a term baby and for a very preterm baby (27 to 32 weeks) the risk is 41.3 times greater. Similarly, a baby who was born at term but weighed less than 2500 g was 6.3 times more likely to die than a baby who weighed more than 2500 g. In Queensland, Indigenous babies are 1.6 (95%ci: 1.5,1.7) times more likely to be born preterm (<37 weeks gestation) and 2.2 (2.0,2.5) times more likely to be low birthweight at term than non-Indigenous babies [3]. Similar disparities in birthweight and gestational age have been reported from the other states of Australia [2,5,7-10].
The aim of this paper is to estimate the number and proportion of excess deaths among Indigenous babies that can be explained by their higher risk of low birthweight and preterm birth. This analysis strategy assumes that the distribution of birthweight and gestational age among Indigenous babies reflects the prevalence of antenatal risk factors such as smoking, infection, maternal nutrition and psycho-social stress; while any excess of mortality that remains after the excess low-birthweight and preterm risk among Indigenous babies is removed might say something about the quality of medical care at the time of confinement.
Although such reasoning has many proponents [11-13], risk factors such as smoking and infection are likely to also have at least a small effect on mortality that is independent of birthweight and gestational age. That is, adjustment of perinatal mortality rates by birthweight and gestational age is not a perfect way of assessing the quality of medical care at the time of confinement. It is similar to case-mix adjustments used in other settings to allow for differences in risk [14,15]. Such adjustments are not expected to remove all confounding. Instead, the reasoning is that the adjusted rates, although not perfect, provide a useful way of identifying policy issues, setting agendas, and facilitating discussion.
To be more specific, if a large proportion of excess deaths can be explained by the unfavourable birthweight and gestational age distribution of Indigenous babies, then that would suggest that priority should be given to implementing primary health care interventions to reduce the risk of low birthweight and preterm birth (eg, interventions to reduce maternal smoking or genitourinary infections). Conversely, if only a small proportion is explained by birthweight and gestational age, then other strategies might need to be considered such as improving access to high-quality hospital care around the time of confinement.
Methods
Data were obtained from the population-based Queensland Perinatal Data Collection for the five years 1998 to 2002. This was the most recent five-year period for which complete data were available. The database includes information on all livebirths and stillbirths of at least 20 weeks gestation or 400 g birthweight. A perinatal death is defined as a stillbirth or the death of a liveborn baby within 28 days of birth. Our data set comprised 231,039 births and 2,255 deaths to non-Indigenous mothers and 13,920 births and 273 deaths to Indigenous mothers. Indigenous status is based on the self-reported Indigenous status of the mother and the gestational age is based on the best clinical estimate, which might be derived from the date of the last menstrual period, ultrasound in early pregnancy or maturity scoring of the neonate at birth. The method used is not recorded.
In this paper we report the results of a Mantel-Haenszel procedure, which was used to determine the relationship between perinatal mortality and Indigenous status adjusted for the effect of low birthweight and preterm birth. The proportion and number of deaths that could be avoided were estimated by comparison of the crude and adjusted rates.
We also used Poisson-regression models to adjust perinatal mortality rates for birthweight and gestational age. We variously fitted single week or four week categories of gestational age and 250 g and 500 g categories of birth weight. The results were the same as using the Mantel-Haenzel approach with broad categories of gestational age and birthweight, and we included these in preference to the Poisson-regression models for ease of interpretation.
Results
The crude perinatal mortality rate among Indigenous babies was 19.6 per 1000 births, which was 2.01 (95%ci:1.77,2.28) times higher than the rate among non-Indigenous babies. When perinatal mortality rates were compared within each birthweight and gestational age strata, the point estimates suggested that Indigenous babies were only slightly more likely to die than non-Indigenous babies (Figure 1). The test for homogeneity of the rate ratios across strata was not significant (χ2 (3) = 5.78, p = 0.1226) suggesting that the effect of Indigenous status is the same across the birthweight and gestational age strata (except for statistical noise) and that it is appropriate to use the adjusted combined estimate: M-H Adjusted RR = 1.13, 0.99–1.28.
Figure 1 Rate ratiosa comparing Indigenous to non-Indigenous perinatal mortality stratified by preterm and birthweight status, 1998–2002. a) Rate ratios greater than 1.0 indicate higher mortality among Indigenous babies. b) Differences between stratum-specific rate ratios are not statistically significant (χ2 (3) = 5.78, p = 0.1226).
These results suggest that if the population of Indigenous babies had the same birthweight and gestational age distribution as non-Indigenous babies, then the relative disparity would be reduced by 87% and there would be 20 fewer deaths of Indigenous babies per year.
Discussion
Interpretation of results
Perinatal mortality among Indigenous babies has remained twice that of their non-Indigenous counterparts for more than a decade. We found that most of this mortality excess is because Indigenous babies are at greater risk of being born too early and too small. In contrast, the case fatality rates of Indigenous babies who were born preterm or of low birth weight were similar to their non-Indigenous counterparts.
Using a framework advocated by several perinatal epidemiologists [11-13], these results suggests that, broadly speaking, access to high quality care during confinement is adequate for Indigenous mothers and babies. That is, priority should initially be given to primary health care interventions to reduce the proportion of preterm and low birth weight babies.
Policy implications
Risk factors for preterm birth and low birth weight include smoking, gentio-urinary tract infections, poor maternal nutrition and psycho-social stress [16-19]. Several studies have reported a higher prevalence of these risk factors among Indigenous compared with non-Indigenous mothers.
More specifically, the prevalence of smoking among Indigenous women during pregnancy has been reported to be more than 60%, which is at least 3 times the prevalence for non-Indigenous women [9,20,21]. A recent Cochran review found that there are effective primary health care interventions to help and support women to stop smoking that lead to fewer preterm babies and better birthweights [22]. Further, we know that Indigenous women are more than two times as likely to have a urinary tract infection during pregnancy as non-Indigenous women [23]. In overseas studies, primary health care interventions to detect and treat asymptomatic bacteruria have been shown to decrease preterm birth by 40% [24].
In Australia, the best example we have of a primary health care initiative aimed at reducing risk factors among Indigenous mothers is the Strong Women Strong Babies Strong Culture program in the Northern Territory [25]. This program resulted in increased early attendance for antenatal care, reduced numbers of STDs and a reduced proportion of low birthweight babies [26].
Although such results are encouraging, if substantial progress is to be made across the whole of Australia, a properly funded national initiative is needed. Such an initiative would include funding to improve access to culturally appropriate primary health care during the antenatal period, which would deliver, inter alia, interventions for smoking cessation, screening and treatment of genito-urinary tract infections, screening for domestic violence, and programs aimed at reducing alcohol consumption and poor nutrition.
It would not be a case of one strategy fits all. Instead local partnerships with possibly different types of service models would be needed to implement the national initiative. This approach will encourage creativity, innovation and risk taking, which will be essential ingredients to tackling a situation that has proved difficult to improve.
Study limitations
Using vital statistics to set agendas has a long and continuing tradition in public health [27]. The advantages of such statistics are convenience, low cost and total enumeration. The disadvantages are insufficient and inaccurate data, which create uncertainty about the validity of the results [27]. This study used four variables: perinatal death, birthweight, gestational age, and Indigenous status. It is unlikely that an important number of perinatal deaths were missed because they are checked against notifications to the Registrar-General of Births, Deaths and Marriages. It is also unlikely that there are important errors in the measurement of birthweight. Consequently, the main areas of uncertainty are Indigenous status and gestational age.
With regard to Indigenous status, some mothers may be reluctant to identify as Indigenous, others may be non-Indigenous with an Indigenous male partner, or midwives may not ask the mother or make an educated guess [28]. However, of all the types of mortality data, perinatal mortality provides the most accurate estimate of excess Indigenous mortality because the numerator (number of perinatal deaths) and denominator (number of births) for the rate can be obtained from the one data set. This is in contrast to adult death rates where identification of Indigenous people can be different in death registration data (the numerator for mortality rates) and population data (the denominator). This problem of the numerator not being appropriate for the denominator is not unique to comparisons of Indigenous and non-Indigenous Australians; it hinders interpretation of race-specific rates around the world [29,30]. Thus, of all the routinely available mortality data, perinatal data provides the most valid estimate of the mortality excess for Indigenous people and provides robust support for policy discussions.
For several reasons, gestational age is known to be less accurate among Indigenous than non-Indigenous babies [31]. Nevertheless, previous work in Queensland and elsewhere has shown that gestational age in combination with birthweight provides a better statistical adjustment of mortality rates than birthweight alone [32,33]. We therefore considered it better to present birthweight and gestational age adjusted rates, rather than just birthweight-adjusted rates.
Conclusion
Although perinatal mortality rates in Queensland have decreased over the last 16 years, the rates in Indigenous populations remain at least double those in the non-Indigenous population. Our analyses, stratified by birthweight and gestational age, suggest that the priority for reducing the excess mortality among Indigenous babies is primary health care to reduce the prevalence of risk factors during the antenatal period. A primary health care approach encompasses a much-needed component of an overall shift towards empowerment of Indigenous women and increased awareness and ownership of health which has the potential to play an important role in reducing the social inequality that has resulted in outcomes such as those found for perinatal mortality.
Authors' contributions
TJ performed the statistical analysis and participated in drafting the manuscript. MC conceived of the study and its design and participated in drafting the manuscript. Both authors read and approved the final manuscript.
==== Refs
OECD OECD Health Data
ABS AIHW The health and welfare of Australia's Aboriginal and Torres Strait Islander Peoples 2003 Canberra , ABS and AIHW
Johnston T Coory M Trends in perinatal mortality, birthweight and gestational age among Aboriginal, Torres Strait Islander and non-Indigenous babies in Queensland Information Circular No 67 2004 Brisbane , Epidemiology Services Unit, Health Information Branch, Queensland Health
Roder D Chan A Priest K Perinatal mortality trends among South Australian Aboriginal births 1981-92 Journal of Paediatric Child Health 1995 31 446 450
Gee V Green TJ Perinatal Statistics in Western Australia, 2002: Twentieth Annual Report of the Western Australian Midwives' Notification System 2004 Perth , Department of Health
Alessandri LM Chambers HM Blair EM Read AW Perinatal and postneonatal mortality among Indigenous and non-Indigenous infants born in Western Australia, 1980-1998 Medical Journal of Australia 2001 175 185 189 11587276
Riley M King J Births in Victoria 2001-2002 2003 Melbourne , Victorian Perinatal Data Collection Unit, Victorian Government Department of Human Services
NT Perinatal Information Managment Group Northern Territory Midwives Collection: Mothers and Babies 1999 2002 Darwin , Department of Health and Community Services
NSW Department of Health The NSW Aboriginal perinatal health report 2003 Sydney , NSW Department of Health
Westenberg L van der Klis K Chan A Dekker G Keane RJ Aboriginal teenage pregnancies compared with non-Aboriginal in South Australia 1995-1999 Australian and New Zealand Journal of Obstetrics and Gynaecology 2002 42 187 192 12069148 10.1111/j.0004-8666.2002.00187.x
Clarke M Mason ES MacVicar J Clayton DG Evaluating perinatal mortality rates: Effects of referral and case mix British Medical Journal 1993 306 824 827 8490374
Macfarlane A Mugford M Johnson A Garcia J Counting the changes in childbirth: Trends and gaps in national statistics 1996 Oxford , National Perinatal Statistics Unit
Joyce R Peacock J A comparison of methods of adjusting stillbirth and neonatal mortality rates for birthweight in hospital and geographic populations Paediatric Perinatal Epidemiology 2003 17 119 124 10.1046/j.1365-3016.2003.00486.x
Iezzoni L Assessing quality using administrative data Annals of Internal Medicine 1997 127 666 674 9382378
Coory M Youlden D Baker P Interpretation of hospital-specific outcome measures based on routine data Australian Health Review 2002 25 69 72 12404968
Kramer MS The epidemiology of adverse pregnancy outcomes: An overview Journal of Nutrition 2003 133 S1592 S1596
Gulmezoglu AM de Onis M Villar J Effectiveness of interventions to prevent or treat impaired fetal growth Obstetrical and Gynecological Survey 1997 52 139 148 9027913 10.1097/00006254-199702000-00023
Villar J Gulmezoglu AM de Onis M Nutritional and antimicrobial interventions to prevent preterm birth: An overview of randomized controlled trials Obstetrical and Gynecological Survey 1998 53 575 585 9751940 10.1097/00006254-199809000-00025
Goldenberg RL Rouse DJ Prevention of premature birth The New England Journal of Medicine 1998 339 313 320 9682045 10.1056/NEJM199807303390506
Chan A Keane RJ Robinson JS The contribution of maternal smoking to preterm birth, small for gestational age and low birthweight among Aboriginal and non-Aboriginal births in South Australia Medical Journal of Australia 2001 174 389 393 11346081
Gilchrist D Woods B Binns CW Scott JA Gracey M Smith H Aboriginal mothers, breastfeeding and smoking Australian and New Zealand Journal of Public Health 2004 28 225 -228 15707168
Lumley J Oliver SS Chamberlain C Oakley L Interventions for promoting smoking cessation during pregnancy (Review) The Cochrane Library 2005 2005
de Costa C Child A Pregnancy outcomes in urban Aboriginal women Medical Journal of Australia 1996 164 523 526 8649285
Darmstadt GL Bhutta ZA Cousens S Adam T Walker N de Bernis L Evidence-based, cost-effective interventions: how many newborn babies can we save? Lancet 2005 March 3
Herceg A Sansoni J, Tilley L Improving health in Aboriginal and Torres Strait Islander pregnant women, babies and young children: A literature review: 15-16 September 2004; Canberra.
2004 10 The Australian Health Outcomes Collaboration
Mackerras D Birthweight changes in the pilot phase of the Strong Women Strong Babies Strong Culture Program in the Northern Territory Australian and New Zealand Journal of Public Health 2001 25 34 40 11297299
Gould JB Vital records for quality improvements Pediatrics 1999 103 278 290 9917471
Robertson H Lumley J How midwives identify women as Aboriginal or Torres Strait Islanders Australian College of Widwives Journal 1995 26 29
Paradies Y Cunningham J Placing Aboriginal and Torres Strait Islander mortality in an international context Australian and New Zealand Journal of Public Health 2002 26 11 16 11895018
Kaufman J How inconsistencies in racial classification demystify the race construct in public health statistics Epidemiology 1999 10 101 103 10069240
Day P Sullivan EA Lancaster P Indigenous mothers and their babies Perinatal Statistical Series No 8 1999 Sydney , AIHW National Perinatal Statistics Unit
Coory M Does gestational age in combination with birthweight provide a better statistical adjustment of neonatal mortality rates than birthweight alone? Paediatric Perinatal Epidemiology 1997 11 385 391 10.1046/j.1365-3016.1997.d01-23.x
Wilcox AJ On the importance - and the unimportance - of birthweight International Journal of Epidemiology 2001 30 1233 1241 11821313 10.1093/ije/30.6.1233
| 15918912 | PMC1168887 | CC BY | 2021-01-04 16:38:28 | no | Aust New Zealand Health Policy. 2005 May 27; 2:11 | utf-8 | Aust New Zealand Health Policy | 2,005 | 10.1186/1743-8462-2-11 | oa_comm |
==== Front
BMC BioinformaticsBMC Bioinformatics1471-2105BioMed Central London 1471-2105-6-1171589289010.1186/1471-2105-6-117Methodology ArticleRobust detection of periodic time series measured from biological systems Ahdesmäki Miika [email protected]ähdesmäki Harri [email protected] Ron [email protected] Heikki [email protected] Olli [email protected] Institute of Signal Processing, Tampere University of Technology, P.O. Box 553, 33101 Tampere, Finland2 ProSanos Corporation, Harrisburg PA 17101, USA2005 13 5 2005 6 117 117 4 3 2005 13 5 2005 Copyright © 2005 Ahdesmäki et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Periodic phenomena are widespread in biology. The problem of finding periodicity in biological time series can be viewed as a multiple hypothesis testing of the spectral content of a given time series. The exact noise characteristics are unknown in many bioinformatics applications. Furthermore, the observed time series can exhibit other non-idealities, such as outliers, short length and distortion from the original wave form. Hence, the computational methods should preferably be robust against such anomalies in the data.
Results
We propose a general-purpose robust testing procedure for finding periodic sequences in multiple time series data. The proposed method is based on a robust spectral estimator which is incorporated into the hypothesis testing framework using a so-called g-statistic together with correction for multiple testing. This results in a robust testing procedure which is insensitive to heavy contamination of outliers, missing-values, short time series, nonlinear distortions, and is completely insensitive to any monotone nonlinear distortions. The performance of the methods is evaluated by performing extensive simulations. In addition, we compare the proposed method with another recent statistical signal detection estimator that uses Fisher's test, based on the Gaussian noise assumption. The results demonstrate that the proposed robust method provides remarkably better robustness properties. Moreover, the performance of the proposed method is preferable also in the standard Gaussian case. We validate the performance of the proposed method on real data on which the method performs very favorably.
Conclusion
As the time series measured from biological systems are usually short and prone to contain different kinds of non-idealities, we are very optimistic about the multitude of possible applications for our proposed robust statistical periodicity detection method.
Availability
The presented methods have been implemented in Matlab and in R. Codes are available on request. Supplementary material is available at: .
==== Body
Background
Periodic phenomena are widespread in biology, including, among others, membrane potential oscillations, cardiac rhythms, smooth muscle contraction, calcium oscillations, protoplasmic streaming, glycolytic oscillations, cAMP oscillations, oscillations in neuronal signals, insulin secretion (pancreas), gonadotropic hormone secretion, cell cycle, circadian rhythms, and ovarian cycle (see e.g. [1]). Consequently, there are numerous biological applications where periodicities must be detected from experimental biological data. Because the data measured from biological applications are inherently noisy and usually sparsely sampled, efficient algorithms are being developed to extract as much information as possible.
In the past few years there has been an explosion of available microarray gene expression data. Detecting periodicity in gene expression is of great importance because it indicates, e.g., cell-cycle regulation [2] as well as the effect of circadian rhythms [3]. The significance of the detection of cell-cycle regulated processes is further emphasised by the linkage between cell-cycle and cancer (see, e.g., [4] and [5]). To this end, microarrays have been used to study the circadian gene expression in Neurospora Crassa [3] as well as cell-cycle regulated genes, e.g., in budding yeast [6], in fission yeast [7], and in human cells [5].
The task of finding periodicity in time series measured from a biological system can be viewed as a decision problem based on spectral analysis together with multiple hypothesis testing. A formal statistical testing procedure for the detection of periodic expression profiles was recently introduced by Wichert et al. [8]. It relies on the use of a so-called Fisher's g-statistic for which the exact null-distribution can be derived under the Gaussian noise assumption.
Recently, a number of other methods for detecting periodic transcripts have also been proposed [9-13]. A major difference between the method proposed by Wichert et al. [8] and other methods is that Wichert's method is capable of detecting unknown frequencies whereas other methods are designed for detecting fixed frequencies. From a computational point of view, the problem of finding unknown frequencies is even more demanding since no prior knowledge of the frequency to be detected is available. In many biological applications it is more important to search for periodicities having an unknown frequency. However, in some applications, such as large-scale cell cycle studies, the period length is usually known and thus provides additional information for testing. In this paper, our goal is to tackle both of the two problems. That is, we develop two methods, one for the detection of unknown frequencies and the other for testing fixed frequencies.
In many applications, including those arising from bioinformatics, the exact noise characteristics are usually unknown and can be remarkably non-Gaussian. Furthermore, the observed gene expression time series can exhibit other non-idealities, such as outliers, short length and distortion from the original wave form. Therefore, it would be useful to have a robust method for detecting periodic components, i.e., a method that also works well when the original (Gaussian) noise assumption no longer holds.
A robust, rank-based, non-parametric spectral estimator was recently introduced in [14]. In this paper, we extend the approach of [14] to the detection of periodic time series. This results in a robust testing procedure which is insensitive to a heavy contamination of outliers, missing-values, short time series, nonlinear distortions, and is completely insensitive to any monotone nonlinear distortions. We also consider a permutation-based alternative to the method proposed in [8] and show that, when the data is contaminated with the above mentioned non-idealities, this results in a more robust method.
As discussed, e.g., in [15], the performance of a method can be proven using either extensive simulations, analytical proofs or multiple plasmode experiments (to use a term from [15]). Plasmode is a real data structure whose true structure is known. Although very useful, the kinds of benchmarkings proposed in the literature (related to periodically behaving gene expression time series) so far do not belong to any of the above categories. In particular, the proposed benchmarking frameworks cannot be considered as plasmodes since the true structure (periodic genes) is not known but, instead, is based on partial biological knowledge (or other measurements, such as protein-DNA binding). Hence, the performance cannot be assessed solely on real data. Therefore, as the analytical proofs are hard to obtain in this case, we perform extensive simulations to show the superior performance of the proposed methods. However, we also apply the proposed method to real experimental data to show that the methods perform well on real data and that the results are biologically meaningful.
Results
Computational methods
In order to be consistent with the previously published methods, we use similar notation as in [8] and also consider the same model for the periodic time series
yn = β cos(ωn + φ) + εn, (1)
where β ≥ 0, ω ∈ (0, π), n = 1,..., N, φ ∈ (-π, π], and εn is an i.i.d. noise sequence. To test for the periodicity, define the null hypothesis as H0 : β = 0, i.e., time series consists of the noise sequence alone, yn = εn. In the following we develop a method for detecting unknown frequencies and later introduce a modification which can be applied to the detection of known frequencies. We first review the Fisher's test for the detection of periodic transcripts as introduced by Wichert et al. in [8].
Wichert's method
The method proposed by Wichert et al. [8] is based on the periodogram spectral estimator, defined as
where N is the time series length. The periodogram is further evaluated at (harmonic) normalised frequencies
where a = [(N – 1)/2] and [x] denotes the integer part of x. To test for the periodicity formally, some kind of a test statistic must be chosen. The so-called g-statistic for one time series is given by
In plain words, the g-statistic is the maximum periodogram ordinate divided by the sum of all periodogram ordinates for l = 1, ..., a. Large value of g indicates a strong periodic component and leads to the rejection of the null hypothesis.
Wichert et al. [8] resort to a result by Fisher that, under the Gaussian noise assumption, gives the exact distribution of the g-statistic under the null hypothesis (see, e.g., [16,8]). The exact p-value for a realisation of the g-statistic is shown to be
where b is the largest integer less than 1/x and x is the observed value of the g-statistic. Because there are usually thousands of time series that are tested simultaneously, whether they exhibit periodicity or not, there is a possibility that a time series can have a small p-value by chance. To correct the p-values for multiple testing, Wichert et al. [8] use the method of Benjamini and Hochberg (see, e.g., [17]), which controls the False Discovery Rate (FDR). The FDR method controls the expected proportion of false positives (Type I errors) at a given rate q. The threshold of the FDR depends on the evaluated p-values. The FDR procedure for the ordered set of p-values p(1), p(2),...,p(M), where M is the number of time series, is as follows
1. Let iq be the largest i for which
2. Reject the null hypothesis for the time series corresponding to the p-values p(1), p(2),...,
The procedure based on the periodogram spectral estimator for periodicity detection has several well-known and important properties. For example, if the noise sequence ∈n is i.i.d. Gaussian and the true underlying frequencies are among the harmonic frequencies Ω = {ωl : l = 0,..., [(N - 1)/2]}, then the (square root of the) periodogram is the minimum variance unbiased estimator of the frequency content at discrete frequencies Ω (see, e.g., [18]). However, it is also widely recognized that the standard periodogram is an inconsistent spectrum estimator (see, e.g. [19]). Despite this weakness, the periodogram is a standard method that is theoretically well-founded. Under the popular Gaussian working assumption, widely invoked in spectral estimation, the distributional characteristics of the periodogram are known and useful. Indeed, it is this distributional characterisation that forms the basis for Fisher's g-test for whiteness. In other words, Equation (5) provides the exact significance value for a realisation of the g-statistic. This provides a solid theoretical basis for the use of the method proposed in [8].
Concerning the problem of detecting hidden periodicities, some generalisations and improvements over the traditional methods have been proposed. A recent review of the proposed methods can be found in [20]. Many of the improved methods are some type of generalisations of the traditional methods, such as the correlogram or periodogram. Artis et al. [20] report that two particular methods are generally found to have a good performance: so-called mixed spectrum methods by Priestley and Bhansali (see, e.g. [19,20]), and a modified method based on the maximum periodogram ordinate by Chiu [21]. The method by Priestley and Bhansali uses a certain type of windowing of the correlogram for the "smoothing" purposes (i.e., in order to reduce the variance). The method by Chiu in turn modifies the g-statistic by replacing the average spectrum in the denominator with a proper trimmed mean of the ranked periodogram ordinates. As we explain in the Discussion Section, the same modifications/improvements can be used in the proposed robust method (to be introduced shortly) as well. Indeed, the windowing can be utilized much in the same way as it is used in the method by Priestley and Bhansali. Similarly, the modification(s) of Chiu can be directly implemented in the case of the proposed robust estimator.
Fisher's test and the proposed robust method can be considered to be analogous in the sense that neither of them incorporates any modifications for the traditional periodogram/correlogram approach. In Simulations Section we perform an extensive comparison of the unmodified, standard methods since this provides a better insight into the performance differences of the traditional methods and the proposed robust rank-based methodology. Furthermore, from an extensive simulation point of view, comparison of many different modifications together with the robust method would also result in a rather large number of simulations, especially because it is possible to use many different combinations of the modifications. Note, however, that the further modifications, such as the ones proposed by Priestly, Bhansali, and Chiu, can be implemented in both of the frameworks (the traditional and the robust rank-based) to gain further performance improvements. We discuss this issue further in Discussion Section.
In many applications, particularly in bioinformatics, the noise distributions are usually unknown and can remarkably deviate from the Gaussian assumption. The methods based on Gaussian noise assumption may fail, or even produce invalid results, when the model assumptions do not hold. The goal of this paper is to introduce an alternative for the standard methods, aimed at providing a robust estimator.
A robust alternative
As a starting point we should like to remind that the periodogram I(ω) is equal equivalent to the correlogram spectral estimator (see, e.g., [25])
where is the biased estimator of the autocorrelation function
Note that the required values for for m < 0 are obtained by invoking the inherent symmetry of the autocorrelation function: r(-m) = r(m). Consequently, the g-statistic in Equation (4) as well as the corresponding significance value in Equation (5) can also be computed using S(ω) instead of I(ω). It is natural to try to obtain robustness by replacing with a robust alternative.
Before continuing to the robust method, it is important to note that, especially in the case of gene expression time series, the data is often contaminated with missing values. Therefore, the spectral estimation method must take missing samples into account. Let Im be the set of time indices k for which both yk and yk+m are available and Km = |Im|. As long as Km ≠ 0, a missing data-adapted version of the unbiased estimate of the autocorrelation can be obtained as
We cover only the versions adapted to missing data in the following text since they are equal to the standard estimators in case of complete data sets. Note that Km equals N - m for the complete data sets. Next we consider a recently introduced rank-based autocorrelation estimator [14] for the problems of spectrum estimation. This estimator is a moving-window extension of the Spearman rank correlation coefficient, quantifying the association between the sequences {yk} and {yk+m}. The resulting quantity, ρS(m) is actually an alternative estimator of the standard correlation coefficient ρ(m) between these sequences (see e.g. [19])
where [·] denotes the expectation operator and μyi = [yi] is the mean of the sequence. Recall that the sample correlation coefficient between two N length sequences {xi} and {yi} is defined as
where denotes the sample mean of {xi}.
Under the assumption of stationarity, it immediately follows from Equation (9) that the correlation coefficient ρ(m) is related to the autocorrelation function r(m) by , where is the variance of the sequence. Since it is important to remove the mean of the sequence prior to spectrum estimation to avoid low frequency artifacts and since is simply a scale factor, the problem of detecting periodic components in a data sequence may equally well be based on ρ(m) as r(m). Consequently, we consider spectral estimators of the form
where estimates the correlation coefficient between {yk} and {yk+m} and L is the maximum lag for which the correlation coefficient is computed. More specifically, we consider the correlation coefficient between the data ranks Ry(i) and , defined by
where C is a normalisation factor, Ry(i) denotes the rank of yi in the set S = {yj : j ∈ Im} and denotes the rank of yi+m in the set S' = {yj+m : j ∈ Im}. By selecting either C = Km or C = N in Equation (12) yields the unbiased or the biased estimate of the correlation coefficient between the rank sequences, respectively. Because both of these rank sequences assume every value from 1 to Km precisely once, their average is (Km + 1)/2, independent of the data values {yn}, and their sample variance, when scaled by the sequence length Km, can be shown to be ( - 1)/12. More generally, if C = Km, and since ρS(m) is the correlation coefficients between ranks, it is bounded by -1 ≤ ρS(m) ≥ 1 for all m. In the following we shall use L = N - 2 in Equation (11) because N - 2 is the largest lag for which Equation (12) can be computed.
We shall use the biased estimate, i.e., C = N, here because of its connection to the equivalence between I(ω) and S(ω). Moreover, the use of the biased estimate in spectrum estimation (Equations (6) and (7)) can be interpreted as triangular weighting of the autocorrelation function estimate. Windowing is usually applied to reduce the scalloping loss effect which is the reason why some frequencies are inferior to others [25].
As in the case of the standard autocorrelation estimate, the values for ρS(m) for m < 0 are obtained by symmetry: ρS(-m) = ρS(m). This also helps in computing Equation (11) since it reduces to
where (x) denotes the real part of x. As opposed to standard periodogram or the corresponding correlogram, the proposed robust spectral estimator is not guaranteed to be non-negative. We shall hence use the absolute value of in the following.
Significance values
In the same way as Wichert et al. [8] do, we use the g-statistic and evaluate
for each time series spectral estimate. However, we do not have the luxury of resorting to an exact distribution of the g-statistic, e.g., under the Gaussian noise assumption. To obtain the significance values we consider two common ways of computing them: simulation and permutation-based methods. This also opens up a possibility for adjusting some parameters in the proposed robust method that were previously kept fixed. In particular, we vary the number of equidistant frequencies at which the spectral estimate is evaluated and change Equation (14) accordingly by incorporating more terms in the max-operator as well as in the sum in the denominator. Instead of having a fixed set of a + 1 normalised frequencies as in Equation (3), we can evaluate the spectral estimate at [(K - 1)/2] + 1 equidistant frequencies
Although the method is rather insensitive to the selection of K, we found that K = 2N generally provides a good performance. Evaluating at more frequencies can be viewed as a smoothing or interpolation of the original discrete spectral estimate. From the implementation point of view it is worth mentioning that Equation (13) evaluated at frequencies shown in Equation (15) can be computed using the fast Fourier transform (FFT).
As was already discussed in the Background Section, in some cases one might be interested in testing fixed instead of unknown frequencies. The proposed method can naturally be adapted to that case as well. If ω' is the known frequency for which the spectral content is to be tested, then a modified g-statistic, g', can be used
In the following, we mainly concentrate on the use of the standard g-statistic for detecting unknown frequencies. However, the same methods, such as simulation and permutation based significance values, can also be applied to the modified g-statistic. In Experimental results Section we apply both the standard and the modified g-statistics to real microarray data.
When the noise satisfies the i.i.d. assumption, the decision between simulation and permutation test-based significance values is facilitated by the following observation. A statistic T is said to be distribution-free over a collection of distributions if the distribution of T is the same for every joint distribution in . Consider the signal model shown in Equation (1) under the null hypothesis H0: β = 0, i.e., yn = εn, and assume that εn is again i.i.d. and has continuous distribution. It is easy to see from Equation (12) that, for any time series {yn}n = 1,...,N, the g-statistic depends on {yn}n = 1,...,N only through the rank sequence {Ry(i)}i = 1,...,N, where Ry(i) denotes the rank of yi in the original sequence. This implies that the g-statistic is distribution-free over the class of all joint distributions of N i.i.d. continuous univariate random variables (see, e.g., [22]). In other words, for each N and independent of the type of the noise, the g-statistic has exactly the same null distribution as long as the noise term satisfies the continuous i.i.d. assumption. Therefore we can choose to use either the simulated distributions (must be simulated separately for each times series sequence length) or the permutation tests, depending on the circumstances.
Simulation-based significance values
The simulation-based method is simple. Given the model as in Equation (1) together with some distributional assumptions for εn, generate a set of P random time series under the null hypothesis. Evaluate the test statistic shown in Equation (14) on each of the P time series. Use the obtained g-values to compute an estimate of the distribution of the g-statistic under the null hypothesis. The distribution can be estimated, e.g., using kernel density estimation methods. The testing can then be performed as explained above except that the significance values are computed/integrated relative to the estimated distribution. Note that the null distribution must be estimated for each time series length separately but, due to the distribution-free property, the null distribution is independent of the noise characteristics under the i.i.d. assumption.
Permutation-based significance values
A more flexible way of obtaining p-values is to use permutation tests [23]. Although they are a relatively old concept, permutation tests have only recently become interesting in practise because of the intensity of needed computing power. The idea is simple:
1. Choose a test statistic.
2. Evaluate the test statistic on the original data.
3. Randomly permute the data and evaluate the test statistic on every permutation.
4. Estimate the distribution of the test statistic with the help of the sample generated in point 3.
5. Use the estimated distribution to get a p-value for the original test statistic computed in point 2.
A sequence of random variables {Xn}, n = 1, 2,...,N is exchangeable, if the joint distribution of is the same as that of the original sequence X1, X2,..., XN for all permutations π. Under the null hypothesis, the elements of the time series yn are i.i.d. and therefore exchangeable, and hence the permutation test can be applied. Alternatively, as the application of a random permutation destroys any periodic structure that is present in the original sequence, permutation tests can be used to assess how highly structured the given time point values are in the light of the chosen test statistic versus other permutations of the given sample. As the concept of permutation tests is non-parametric, they can be applied without knowing the exact distribution of the data at hand.
Instead of performing all the N! permutations for each time series, we have chosen to permute each of the original time series for P = 5000 times. As our simulations show, this seems to be quite an adequate number of iterations. The selection of P is always a compromise, because too high P makes computations too slow and too low P weakens the accuracy and resolution of the calculated p-values. For example, time series having a very periodic structure can get a p-values of zero due to the low value of P.
While we have mainly applied the permutation tests to the robust estimator, it must be noted that with the help of permutation tests the robustness of the periodogram can also be improved. As we show in Results section that if we add, e.g., some impulsive noise to the simulated data, the results when using the periodogram method as in Equation (5) are not as good as when we use permutation tests to find the p-values.
Correction for multiple testing
In order to facilitate the comparison between the proposed and previous methods, the obtained p-values are corrected exactly in the same way as in the method by [8].
Simulations
We put the presented methods to a test by first going through simulated data, where the ground truth is known, and then by finding periodically behaving genes in real microarray data.
In simulations, we use exactly the same test signal model as in [8] for comparison purposes, namely Equation (1) with β = and φ = -π/4, i.e.,
where n = 1,...,N, ω is uniformly randomly chosen in the interval ω ∈ [0.05π, 0.45π] (we wanted to avoid frequencies near zero and the Nyquist frequency) and εn is an i.i.d. noise sequence. An essential parameter is the amplitude (β = ) which affects the signal-to-noise ratio and which we would like to have the same as in [8]. We chose to consider three types of non-idealities, namely (i) pure standard Gaussian noise (zero mean and unit variance, see Figure 1(a)), (ii) standard Gaussian and impulsive noise (number of impulses equals ten percent of the sequence length, amplitude ± 6 times the standard deviation of the Gaussian noise, see Figure 1(b)), and (iii) standard Gaussian noise and x3 distortion, where all values were raised to the power of three after adding the noise (see Figure 1(c)).
In each example sequence in Figure 1, the normalised frequency of the original sinusoidal is ω = 0.1. Figures 2(a)–(c) show the spectral estimates for the time series in Figures 1(a)–(c), respectively, using both the standard periodogram and the proposed robust method. Note that the spectra have been scaled for viewing purposes.
Figures 2(b)–(c) already illustrate a remarkable difference between the two methods. For more details about the performance of the proposed robust method as a spectrum estimator, see [14]. A detailed comparison of the periodicity detection capabilities is performed next.
Let us first examine the power of the test, i.e., one minus the probability of the type II error (false negative). The power of the test is estimated for the three different test cases as well as for different time series lengths and for different noise parameters using 10000 Monte Carlo runs, see Figure 3. The significance level is set to α = 0.05. In all the three cases, the case-specific noise assumptions are used for both the null hypothesis (β = 0) and the alternative hypothesis (β > 0). In this simulation, we use the signal model shown in Equation (17) to represent a periodic signal (i.e., the alternative hypothesis). In the right column of Figure 3, the length of the time series is set to 40 and the power is shown as the function of varying noise parameters. Figure 3 clearly shows that the power of the proposed robust hypothesis testing method is remarkably better than that of the Fisher's test, especially in the case of outliers and non-linear distortion. More interestingly, however, the proposed method is also more powerful in the case of standard Gaussian noise.
Next we consider another simulation. In the same way as in [8], two thousand time series of length N = 10, 20, 40, 45, 50 and 100 were generated to test the periodicity detection. One thousand and nine hundred of the time series were plain noise and one hundred time series were generated according to Equation (17). We again consider the three aforementioned noise models. As explained in the Computational Methods Subsection, we evaluated the g-statistic and p-value for each time series and then used the FDR rule to determine which of the time series were considered to be cyclic for a certain FDR level. The FDR level, at which the expected rate of false positives is controlled, was chosen similarly as in [8], i.e., q = 0.15, 0.10, 0.05, 0.01 and 0.005. For each N and q the simulation was run for 99 times for the simulation-based cases and 9 times for the permutation-based cases. Median statistics are reported for the number of found periodic components, the number of correctly identified periodic components (shown in parenthesis) and the number of truly periodic time series among the top 100 ranked sequences (Z).
If we take a look at the results in Tables 1 to 9 we can draw some immediate conclusions. First, when the noise is plain Gaussian, Tables 1, 2, 3, 4 show that both methods perform approximately equally well.
There are no significant differences between the two methods in terms of the number of detected genes or in terms of the number of correctly detected genes. However, the numbers of truly periodic genes among the top 100 ranked sequences (Z-scores) show somewhat favorable performance for the robust method, especially for the short time series N = 20 and N = 40. Indeed, this observation agrees with previous findings [14] where the robust method was found to have a good performance as a spectrum estimator for short time series. By comparing Tables 1 and 2 and Tables 3 and 4, it is obvious that the permutation tests do not provide any significant performance gain over the traditional approach where the significance values are computed using the simulation-based method or Equation (5), respectively. In both cases, the Z-scores are about the same, as expected. The only notable difference is seen in the number of found periodic genes for short time series (e.g., N = 40, 45, 50) and small FDR levels (q = 0.005, 0.01, 0.05) where the numbers are slightly higher when permutation tests are used. This suggests that the permutation-based method finds a bit smaller p-values than the simulation-based method.
Tables 1, 2, 3, 4, 5, 6, 7, 8 clearly show the superior robustness of the proposed method over the traditional Gaussian analysis. As can be seen from Tables 1 and 5 and Tables 2 and 6, there is only a minor performance degradation between the Gaussian case and the combined Gaussian and impulsive case. On the other hand, Tables 3 and 7 and Tables 4 and 8 clearly indicate the sensitivity of the periodogram method to fluctuations from the original Gaussian noise assumption.
As discussed above, Tables 5 and 6 show that, in the case of the robust method, permutation-based significance value computation performs approximately equally well as the simulation-based computation. The only notable difference is again seen in the number of found periodic genes for short time series (e.g., N = 40, 45, 50) and small FDR levels (q = 0.005, 0.01, 0.05). Tables 7 and 8 in turn show that, apart from the Z-scores, the permutation-based method mitigates the sensitivity of periodogram method to the fluctuations from the model (Gaussian) distribution.
The robustness of the proposed method is further demonstrated by its response to combined Gaussian noise and nonlinear cubic distortion. As explained in Computational Methods Section, the robust method depends on the observed time series only through the rank sequence. Any monotone distortion preserves the ordering of the samples. Therefore, the rank-based method is completely insensitive to any monotone distortions. Consequently, the results for the third test case are identical to those presented in Tables 1 and 2. The results for the periodogram method are shown in Table 9.
Experimental results
The data sets that are considered here are from the following papers: [6,5,7]. For each time series experiment (13 in total), we apply the proposed robust methods for detecting genes having both fixed and unknown frequency components. For the fixed frequency we use the one that corresponds to the length of the cell cycle. Following the idea presented in [8], a simple method for estimating the cell cycle length/frequency is to compute the average robust spectral estimate. For each time series, we present the number of statistically significant genes that are found to be periodically behaving at a specific level of the FDR (q = 0.05). For the cdc15 experiment by Spellman et al. [6], the sampling time was not equidistant in the beginning and at the end of the data set. Considering the missing time points as missing values would result in a large number of missing values with a regular pattern of occurrence. Although the proposed robust methods can cope with missing values, such a regular pattern of missing values can artificially cause many small significance values and hence result in an unreliably large number of statistically significant periodic genes. This can be avoided e.g. by interpolating the expression values for the systematically missing time points, in which we used simple linear interpolation. Only non-missing expression values are considered in the interpolation. If the expression values of both the previous and the next time instants are missing, then the interpolated sample is defined to be missing as well. This results in a more conservative number of detected genes for the cdc15 experiment. We chose to consider only those genes that have less than 30% missing values and decided to rule out all except the Score3 experiment in the data by Whitfield et al. [5] because of high degree of irregular sampling and short time series length. The obtained results are shown in Table 10. The total number of genes analysed in each data set is denoted as M. The number of found periodic genes having fixed and unknown frequency are denoted as P' and P, respectively. The corresponding figures from [8] are shown in parentheses. For the detection of periodic components having unknown frequency, we used the permutation-based method. As was shown in Simulations Section, both the simulation and permutation based approaches performed approximately equally well. Hence, for the ease of implementation, we used the simulation-based method for the detection of periodic components having a fixed frequency.
If we first take a look at the numbers of detected genes having a periodic component of an unknown frequency (P) shown in Table 10, we can see that generally the numbers of periodically behaving genes are lower than those of the corresponding figures in [8]. In other words, the proposed robust method seems to provide more conservative estimates, although the cdc15 experiments shows an exception. In the case of real data further comparison between the two methods is much more subjective than in simulation experiments since the ground truth is not completely known. Based on the simulation results shown above, one could put more faith on the robust method, especially in the cases where the Gaussian noise assumption is violated. Hence one could argue that the robust method has ignored more non-periodic time series, particularly ones where outliers and other non-idealities have caused artificial variation in the periodogram. The number of detected truly periodic genes can be increased, at the cost of detecting more false positives, by using a higher level of q.
Let us then focus on the numbers of found periodic genes when using a fixed frequency in the robust method (P'). Concerning the numbers of detected periodic genes in the data sets by Spellman et al. [6], the results are in concordance with the previously published ones [24]. On the cdc28 data set, the proposed method finds a slightly higher number of periodic genes. Direct comparison between the numbers P and P' is not meaningful as the number of detected genes depends on the significance level, which may be dependent on the used method. The comparison is better done using the ordered gene lists which we will discuss shortly together with three benchmark gene sets (see below).
We have not yet come across with another study, besides the original paper, that would have examined the periodicity in the data by Rustici et al. [7]. Rustici et al. investigate the global cell cycle control of gene expression in the fission yeast Schizosaccharomyces pombe using DNA microarrays. Thus, the comparison of values in Table 10, related to Rustici et al. data, is not feasible. Table 10 shows that the number of detected periodic genes ranges from 673 up to 3131. In the case of very large number of detected periodic genes, more insight into the data set can be gained by looking at the ordered list of genes.
Table 10 only shows the number of detected genes. Further insight can be gained by looking at the enrichment of the genes assumed to be cell cycle regulated among the top ranked genes. In particular, we resort to the three different benchmark gene sets introduced in [24]. In order to provide a direct comparison with the results shown in [24], we show similar enrichment graphs for the both robust detection methods (fixed and unknown frequency) in Figure 4. Note that some of the benchmark genes are ignored during the analysis since they have more than 30% missing values. There are also a few benchmark genes for which no exact match was found among the genes in the data provided by [6]. Hence the graphs are drawn based on slightly smaller benchmark gene sets, namely, 101–112 (B1), 309–339 (B2), and 465–505 (B3), depending on the experiment.
Figure 4 reveals some interesting results. First, let us compare how well the proposed robust method (with the fixed frequency) finds the benchmark genes when compared to previously published methods (for comparison, see the corresponding graphs in [24]).
The results for the benchmark gene set B1 are shown on the first row in Figure 4. For all the data sets, the performance of the robust method is either between the best methods and the amplitude-independent method by Zhao et al. [9], or close to the method by Zhao et al. [9]. This finding is not surprising. As discussed in [24], this benchmark gene set is biased towards periodic genes which are strongly regulated, i.e., have large amplitudes. In general, because high-amplitude periodic genes are more easily detected from noisy expression data, the gene sets identified from such studies are likely to be biased towards high amplitude genes. An advantage of amplitude-independent methods is, however, that they detect small-amplitude periodic transcripts better, and hence may identify genes which are not yet known to be periodic.
For the benchmark gene set B2, the performance of the proposed robust method is approximately the same as that of the best methods reported in [24], except for the alpha experiments on which the robust method performs slightly worse. Noteworthy is that the benchmark gene set B2 is obtained from a separate Chromatin IP experiment and thus is independent of the previous gene expression studies.
Concerning the benchmark gene set B3, the robust method performs better than the majority of the methods. Notably good performance is seen on the data from the Cdcl5 and the Cdc28 experiments. Interestingly, the benchmark set B3 is also likely to be biased, but towards small amplitude genes [24]. This strengthens the assumption that the potential of the proposed robust method is especially in detecting unknown, small-amplitude, periodic genes.
Yet another interesting observation can be drawn by comparing the solid and dashed curves in Figure 4. As can be expected, the method which detects especially cell cycle frequencies ranks the benchmark genes higher than the method which detects unknown (all) frequencies, i.e., the solid line is above the dashed line. Another expected behavior is that the method which detects unknown frequencies also detected a great number of genes assumed to be related to the cell cycle. However, from another point of view, Figure 4 also indicates that there are some statistically significant periodic patterns which are more significant than some of the cell cycle related ones. Possible sources of those significant periodic patterns may include, among others, systematic artifacts in the array/experiment preparation, unknown periodic biological processes, or simply the considerable amount of experimental noise (false positives).
The top 300 ranked genes for all the data sets analysed, obtained using the proposed robust method, are provided on our companion website.
Discussion
As discussed above, some extensions and improvements over the traditional periodogram/correlogram approach have been proposed in the literature. Two particular modifications, namely utilisation of windowing and a trimmed g-statistic, were reported to provide a good performance in a recent review by Artis et al. [20]. Although we provided an extensive comparison of the unmodified traditional and the (unmodified) proposed rank-based methodologies, the further modifications can be implemented in a straightforward fashion in both of the frameworks. These extensions for the robust rank-based method will be examined in future studies but let us give an overview of the possible modifications.
As discussed previously, the biased version of the robust correlation estimator can be viewed as a type of weighting or windowing. More generally the windowing is typically incorporated into the computation of the spectral estimate (see, e.g., Equations (6) and (11)). Different windows provide different properties for spectral estimators. For example, the shape of the window can be used to control the smearing and leakage effects whereas the length of the window compromises with the spectral resolution and the variance [25]. In general, the used windows can be chosen from a general class of windows, including, among others, Bartlett, Daniel, and Parzen windows (see, e.g. [16,18,19]). Concerning the detection of hidden periodicities, windowing can be applied much in the same way as it is used in the method by Priestley.
Similarly, the modification by Chiu [21], i.e., the use of a proper trimmed mean of the ranked periodogram ordinates in place of the average periodogram, can be applied to the robust rank-based estimator as well. A drawback associated with the use of the trimmed g-statistic in the traditional periodogram setting is that only asymptotic distribution of the test statistic is available. The discrepancy between the true distribution and the asymptotic one can be remarkable in the case of small sample size typical e.g. in gene expression studies. These difficulties can be circumvented by the computer intensive simulation and permutation-based methods explained above.
The proposed method has other possible extensions as well. As a periodically behaving gene may be involved in several different biological processes, its expression pattern may contain several dominant frequencies. In that regard, the testing procedure can be extended to detect several frequency peaks from the spectral estimate. See, e.g., [19,21] for extensions of Fisher's test to that direction.
In cell cycle related studies, a cell population is usually forced to synchrony prior to taking the measurements using an external synchronisation method. The synchronisation is achieved by arresting the cells at a specific phase of the cell cycle after which they are released. However, as time evolves, the cell population gradually loses its synchrony. Such a phenomenon can be viewed as time-varying (low-pass) filtering of the expression values where the time-varying filter kernel corresponds to the distribution of the cell population over the cell cycle. Inverse methods have been developed to correct for the effect of the loss of synchrony [26,27]. Several interesting questions remain to be studied. First, the inverse filtering problem as such is fairly sensitive to noise and is further complicated by the fact that the accuracy level at which the filter kernel (i.e., distribution of the cell population) can be measured is limited. Therefore, the corrected time series may contain even more obscure non-idealities than the uncorrected ones.
Consequently, robust methods are potentially even more important when periodic components are sought from the time series which are corrected for the loss of synchrony. Future studies are also needed to compare the robust periodicity detection method, when applied to both uncorrected and corrected time series, to see whether the inversion of the loss of synchrony brings any additional gain in the case of robust periodicity detection. In addition to the simulation results presented in the Simulations Section, we also performed preliminary simulations where the amplitude of the periodic signal was attenuated to model the loss of synchronisation. We noticed that if the average amplitude of the sinusoidal signal remained the same, the results were similar to those in the tables of the Simulations Section.
Further comparisons must also be made to assess the performance differences between the proposed method (possibly combined with a proper inversion method for the loss of synchrony) and alternative methods in which a model for the loss of synchrony is incorporated into the statistical testing framework [12,11]. Although elegant, such combined approaches have potential difficulties in that they usually result in a computationally intensive optimisation problem [11] and/or include several distributional assumptions [12]. Furthermore, the inversion of the loss of synchrony is performed blindly, i.e., without any additional measurements, which the distribution of the cell population could be estimated with. Future experiments are needed to address these questions.
Conclusion
The presented method yields a robust way of finding periodicity in short time series data. As illustrated in Simulations Section, the proposed robust detection method is remarkably insensitive to different kinds of non-idealities in the data, such as heavy contamination of outliers, missing values, short time series, nonlinear distortions, and is completely insensitive to any monotone nonlinear distortions. The results also show that the proposed method has clearly better performance than the Fisher's test, even in the case of the standard Gaussian noise. Furthermore, the results on real data demonstrate that the proposed method performs well on real data and that the results are biologically meaningful. As illustrated in Figures 2(a)–(c) and more extensively reported in [14], the robust method serves also as a good spectral estimator. As the time series measured from biological systems are usually short and prone to contain different kinds of non-idealities, we believe that the robust detection method presented in this paper will find many important applications in this field.
Authors' contributions
MA carried out an implementation of the methods, performed the computations and co-drafted the manuscript. HL developed the statistical methods, helped in computations and mainly drafted the manuscript. RP helped in developing the statistical methods. OY-H conceived of the study and participated in its design and coordination. HH helped in the implementation of the computational methods. All authors read and approved the final manuscript.
Acknowledgements
The support of Tampere Graduate School in Information Science and Engineering (TISE) and the Academy of Finland are gratefully acknowledged. We are indebted to Dr. Korbinian Strimmer for providing an implementation of their methods, stimulating discussions, and useful suggestions.
Figures and Tables
Figure 1 Examples of time series. An example of a time series composed of a sine and (a) additive standard Gaussian noise, (b) additive standard Gaussian and impulsive noise, and (c) additive standard Gaussian noise and cubic distortion.
Figure 2 Examples of spectral estimates. The spectral estimates for the time series in Figures 1 (a)-(c), respectively, using both the standard periodogram and the proposed robust method.
Figure 3 Power of the test. The power of the tests (y-axis) for the three different test cases as the function of the time series length and varying noise parameters (x-axis). The solid (resp. dashed) line corresponds to the proposed robust method (resp. Fisher's test). Three different types of non-idealities are considered, namely, pure standard Gaussian noise (the first row), standard Gaussian and impulsive noise (the second row), and standard Gaussian noise and x3 distortion (the third row). The left (resp. right) column shows the results for different time series lengths (resp. different values of the noise parameters).
Figure 4 Benchmark results. The fraction of the benchmark set that is identified (y-axis) as the function of the highest ranked genes (x-axis). The solid (resp. dashed) line corresponds the robust detection having fixed (resp. unknown) frequency. The dotted line shows the performance of the random gene selection. The columns from left to right correspond to the Alpha, the Cdcl5 and the Cdc28 experiment by [6]. The rows, from top to bottom, correspond to the three different benchmark gene sets B1, B2 and B3. for more details about the benchmark gene sets, see [24].
Table 1 Number of inferred periodic time series: case 1. The number of inferred periodic time series using the robust method and standard Gaussian noise in the data. p-values were obtained by simulating the distribution of the g-statistic using 10000 time series composed of Gaussian noise.
q\N 10 20 40 45 50 100
0.15 0 2(1) 107(90) 109(96) 117(99) 115(100)
0.10 0 1(1) 96(87) 103(94) 110(98) 109(100)
0.05 0 1(0) 83(79) 95(89) 101(96) 105(100)
0.01 0 1(0) 59(59) 80(79) 90(89) 101(100)
0.005 0 0(0) 32(32) 62(61) 64(64) 100(100)
Z 12 49 89 93 95 100
Table 2 Number of inferred periodic time series: case 2. The number of inferred periodic time series using the robust method and standard Gaussian noise in the data. p-values were obtained by using permutation tests.
q\N 10 20 40 45 50 100
0.15 0 4(3) 108(92) 113(96) 111(98) 119(100)
0.10 0 1(1) 99(90) 106(94) 106(97) 112(100)
0.05 0 1(0) 88(84) 97(89) 101(95) 106(100)
0.01 0 0 65(64) 80(78) 86(86) 101(100)
0.005 0 0 46(46) 61(61) 71(71) 100(100)
Z 15 48 91 92 95 100
Table 3 Number of inferred periodic time series: case 3. The number of inferred periodic time series using the periodogram method and standard Gaussian noise in the data. p-values were obtained by using Equation 5.
q\N 10 20 40 45 50 100
0.15 1(0) 17(11) 111(89) 108(86) 117(97) 122(100)
0.10 0 9(6) 100(85) 98(80) 108(96) 115(100)
0.05 0 2(1) 83(78) 79(71) 99(93) 107(100)
0.01 0 0 56(55) 54(52) 84(83) 101(100)
0.005 0 0 23(23) 20(20) 54(54) 99(99)
Z 13 39 85 83 93 99
Table 4 Number of inferred periodic time series: case 4. The number of inferred periodic time series using the periodogram method and standard Gaussian noise in the data. p-values were obtained by using permutation tests.
q\N 10 20 40 45 50 100
0.15 0 2(0) 109(94) 111(98) 114(98) 117(100)
0.10 0 2(0) 98(91) 103(96) 107(98) 112(100)
0.05 0 2(0) 87(84) 98(95) 103(98) 105(100)
0.01 0 2(0) 68(67) 88(86) 91(80) 102(100)
0.005 0 1(0) 55(55) 70(70) 80(79) 100(100)
Z 14 40 92 94 97 100
Table 5 Number of inferred periodic time series: case 5. The number of inferred periodic time series using the robust method and standard Gaussian plus impulsive noise in the data. p-values were obtained by simulating the distribution of the g-statistic using 10000 time series composed of Gaussian noise.
q\N 10 20 40 45 50 100
0.15 0 1(0) 73(62) 84(73) 101(84) 114(100)
0.10 0 1(0) 60(55) 76(69) 91(81) 109(100)
0.05 0 1(0) 48(46) 58(56) 77(73) 105(100)
0.01 0 0 22(21) 21(21) 49(49) 100(99)
0.005 0 0 13(13) 17(17) 34(34) 95(95)
Z 9 35 73 78 84 99
Table 6 Number of inferred periodic time series: case 6. The number of inferred periodic time series using the robust method and standard Gaussian plus impulsive noise in the data. p-values were obtained by using permutation tests.
q\N 10 20 40 45 50 100
0.15 0 1(0) 70(57) 83(72) 93(82) 117(100)
0.10 0 0 59(51) 71(68) 89(79) 111(100)
0.05 0 0 48(45) 60(58) 77(72) 105(99)
0.01 0 0 24(23) 35(33) 54(53) 99(98)
0.005 0 0 22(21) 27(27) 41(41) 95(95)
Z 9 38 72 78 82 99
Table 7 Number of inferred periodic time series: case 7. The number of inferred periodic time series using the periodogram method and standard Gaussian plus impulsive noise in the data. p-values were obtained by using Equation 5.
q\N 10 20 40 45 50 100
0.15 0 0 16(16) 24(22) 28(28) 77(71)
0.10 0 0 13(12) 20(12) 25(24) 73(69)
0.05 0 0 11(11) 13(13) 17(17) 65(63)
0.01 0 0 3(3) 6(6) 9(9) 52(52)
0.005 0 0 0(0) 1(1) 3(3) 40(40)
Z 11 29 44 46 52 79
Table 8 Number of inferred periodic time series: case 8. The number of inferred periodic time series using the periodogram method and standard Gaussian plus impulsive noise in the data. p-values were obtained by using permutation tests.
q\N 10 20 40 45 50 100
0.15 0 6(5) 38(29) 40(33) 18(16) 82(76)
0.10 0 2(2) 34(26) 36(32) 14(13) 76(72)
0.05 0 1(1) 23(22) 32(29) 10(9) 69(69)
0.01 0 0 16(15) 18(18) 7(6) 61(61)
0.005 0 0 15(14) 17(17) 7(6) 53(53)
Z 11 32 47 49 44 80
Table 9 Number of inferred periodic time series: case 9. The number of inferred periodic time series using the periodogram method and standard Gaussian noise and cubic distortion in the data. p-values were obtained by using permutation tests.
q\N 10 20 40 45 50 100
0.15 0 0 49(44) 79(64) 89(74) 107(93)
0.10 0 0 39(36) 71(62) 80(69) 98(90)
0.05 0 0 25(24) 52(49) 64(59) 90(88)
0.01 0 0 8(8) 28(28) 44(43) 82(82)
0.005 0 0 8(8) 19(19) 37(36) 67(67)
Z 7 15 68 71 79 91
Table 10 Number of inferred periodic genes from real microarray data. Results obtained by using real microarray data are presented here. Permutation tests were used to obtain significance values for the robust spectra. Symbols: N is the length of the time series, M is the number of genes analysed, P (resp. P') is the number of found periodic genes having an unknown frequency (resp. frequency corresponding to the cell cycle length). Notes in the table: aSince the elutriation time course did not show any significant periodic components, we did not perform the test with a fixed frequency. bThe average spectrum showed several major peaks. The one in the vicinity of the assumed cell cycle frequency was chosen manually.
Cell type Experiment N M P' P'/M P P/M Source
S.cerevisiae cdc15 24 5287 981 18.6 946(766) 17.9 [6]
S.cerevisiae cdc28 17 6103 363 6.0 32(105) 0.5
S.cerevisiae alpha 18 6056 346 5.7 139(468) 2.3
S.cerevisiae elutriation 14 6074 _a _a 4(193) 0.07
Human HeLa Score3 48 41508 1285b 3.1b 3580(6043) 9.0 [5]
S.pombe cdc25-1 19 4373 1431 32.7 759 17.4 [7]
S.pombe cdc25-2 36 4422 2605 58.9 2197 49.7
S.pombe cdc25-sep1 20 4700 2624 55.8 2295 48.8
S.pombe elutriation1 20 4229 1948 46.1 551 13.0
S.pombe elutriation2 20 3961 1453 36.7 384 9.7
S.pombe elutriation3 20 4236 673 15.9 355 8.4
S.pombe elutr.-cdc10-br 22 4647 3131 67.4 2431 52.3
S.pombe elutr.-cdc25-br 21 4272 2405 56.3 767 18.0
==== Refs
Tyson JJ Fall C, Marland E, Wagner J, Tyson J Biochemical oscillations Computational Cell Biology: An Introductory Text on Computer Modeling in Molecular and Cell Biology 2002 New York: Springer-Verlag
Breeden LL Periodic transcription: a cycle within a cycle Curr Biol 2003 13 R31 R38 12526763 10.1016/S0960-9822(02)01386-6
Correa A Lewis ZA Greene AV March IJ Gomer RH Bell-Pedersen D Multiple oscillators regulate circadian gene expression in Neurospora Proc Natl Acad Sci USA 2003 100 13597 13602 14597725 10.1073/pnas.2233734100
Sherr CJ Cancer cell cycles Science 1996 274 1672 1677 8939849 10.1126/science.274.5293.1672
Whitfield ML Sherlock G Saldanha AJ Murray JI Ball CA Alexander KE Matese JC Perou CM Hurt MM Brown PO Botstein D Identification of genes periodically expressed in the human cell cycle and their expression in tumors Mol Biol Cell 2002 13 1977 2000 12058064 10.1091/mbc.02-02-0030.
Spellman PT Sherlock G Zhang MQ Iyer VR Anders K Eisen MB Brown PO Botstein D Futcher B Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization Mol Biol Cell 1998 9 3273 3297 9843569
Rustici G Mata J Kivinen K Lió P Penkett CJ Burns G Hayles J Brazma A Nurse P Bähler J Periodic gene expression program of the fission yeast cell cycle Nat Genet 2004 36 809 817 15195092 10.1038/ng1377
Wichert S Fokianos K Strimmer K Identifying periodically expressed transcripts in microarray time series data Bioinformatics 2004 20 5 20 14693803 10.1093/bioinformatics/btg364
Zhao LP Prentice R Breeden L Statistical modeling of large microarray data sets to identify stimulusresponse profiles Proc Natl Acad Sci USA 2001 98 5631 5636 11344303 10.1073/pnas.101013198
Johansson D Lindgren P Berglund A A multivariate approach applied to microarray data for identification of genes with cell cycle-coupled transcription Bioinformatics 2003 19 467 473 12611801 10.1093/bioinformatics/btg017
Liu D Umbach DM Peddada SD Li L Crockett PW Weinberg CR A random-periods model for expression of cell-cycle genes Proc Natl Acad Sci USA 2004 101 7240 7245 15123814 10.1073/pnas.0402285101
Lu X Zhang W Qin ZS Kwast KE Liu JS Statistical resynchronization and Bayesian detection of periodically expressed genes Nucleic Acids Res 2004 32 447 455 14739237 10.1093/nar/gkh205
Luan Y Li H Model-based methods for identifying periodically expressed genes based on time course microarray gene expression data Bioinformatics 2003 20 332 339 10.1093/bioinformatics/btg413
Pearson RK Lähdesmäki H Huttunen H Yli-Harja O Detecting periodicity in nonideal datasets Proceedings of the SIAM International Conference on Data Mining: Cathedral Hill Hotel, San Francisco, CA 1–3 May 2003
Mehta T Tanik M Allison DB Towards sound epistemological foundations of statistical methods for high-dimensional biology Nat Genet 2004 36 943 947 15340433 10.1038/ng1422
Brockwell PJ Davis RA Time Series: Theory and Methods 1991 2 New York: Springer-Verlag
Dudoit S Shaffer JP Boldrick JC Multiple hypothesis testing in microarray experiments Stat Sci 2003 18 71 103 10.1214/ss/1056397487
Kay SM Fundamentals of Statistical Signal Processing: Estimation Theory 1993 Englewood Cliffs, New Jersey: Prentice-Hall
Priestley MB Spectral Analysis and Time Series 1981 1 London: Academic Press
Artis M Hoffmann M Nachane D Toro J The detection of hidden periodicities: a comparison of alternative methods Working Paper No ECO 2004/10 European University Institute
Chiu S-T Detecting periodic components in a white Gaussian time series J Roy Statist Soc B 1989 51 249 259
Randies RH Wolfe DA Introduction to the Theory of Nonparametric Statistics Wiley 1979
Good P Permutation Tests: A Practical Guide to Resampling Methods for Testing Hypothesis 2003 2 New York: Springer
de Lichtenberg U Jensen LJ Fausbøll A Jensen TS Bork P Brunak S Comparison of computational methods for the identification of cell cycle regulated genes Bioinformatics 2005 21 1164 1171 15513999 10.1093/bioinformatics/bti093
Stoica P Moses R Introduction to Spectral Analysis 1997 New Jersey: Prentice Hall
Lähdesmäki H Huttunen H Aho T Linne M-L Niemi J Kesseli J Pearson R Yli-Harja O Estimation and inversion of the effects of cell population asynchrony in gene expression time-series Signal Processing 2003 83 835 858 10.1016/S0165-1684(02)00471-1
Bar-Joseph Z Farkash S Gifford DK Simon I Rosenfeld R Deconvolving cell cycle expression data with complementary information Bioinformatics 2004 20 123 130
| 15892890 | PMC1168888 | CC BY | 2021-01-04 16:02:50 | no | BMC Bioinformatics. 2005 May 13; 6:117 | utf-8 | BMC Bioinformatics | 2,005 | 10.1186/1471-2105-6-117 | oa_comm |
==== Front
BMC BioinformaticsBMC Bioinformatics1471-2105BioMed Central London 1471-2105-6-1181589288710.1186/1471-2105-6-118Methodology ArticleComputing expectation values for RNA motifs using discrete convolutions Lambert André [email protected] Matthieu [email protected] Jean-Fred [email protected] Daniel [email protected] CNRS UMR 6207, Université de la Méditerranée, Luminy Case 907, 13288 Marseille cedex 9, France2 INSERM ERM 206, Université de la Méditerranée, Luminy Case 928, 13288 Marseille Cedex 9, France3 INSERM EMI U 00.18, CHU d'Angers, 49033 Angers, France2005 13 5 2005 6 118 118 8 3 2005 13 5 2005 Copyright © 2005 Lambert et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Computational biologists use Expectation values (E-values) to estimate the number of solutions that can be expected by chance during a database scan. Here we focus on computing Expectation values for RNA motifs defined by single-strand and helix lod-score profiles with variable helix spans. Such E-values cannot be computed assuming a normal score distribution and their estimation previously required lengthy simulations.
Results
We introduce discrete convolutions as an accurate and fast mean to estimate score distributions of lod-score profiles. This method provides excellent score estimations for all single-strand or helical elements tested and also applies to the combination of elements into larger, complex, motifs. Further, the estimated distributions remain accurate even when pseudocounts are introduced into the lod-score profiles. Estimated score distributions are then easily converted into E-values.
Conclusion
A good agreement was observed between computed E-values and simulations for a number of complete RNA motifs. This method is now implemented into the ERPIN software, but it can be applied as well to any search procedure based on ungapped profiles with statistically independent columns.
==== Body
Background
The introduction of the Expectation value (E-value) in the Blast program in 1990 [1] was a major milestone in the development of sequence search algorithms. For any sequence match with a score S obtained in a given database, the E-value is the number of hits of same or higher score that can be expected by chance. E-values tell biologists how likely they are to encounter a specific sequence match in a database search, which is a more useful view of biological significance than a mere similarity score. Except in some special cases, low E-values are commonly accepted as an evidence of sequence homology.
The recent years have seen a growing interest for RNA motif searches, driven by the discovery of important new classes of regulatory RNA genes and motifs in all organisms. Non-coding RNAs are characterized in a large part by long range base pair interactions, whereas linear sequence constraints are not as important as in protein coding genes. As a result, standard sequence alignment programs such as Blast are not suited to RNA motif search. Computational biologists have addressed this problem in several ways, notably through descriptor-based systems in which the topology of base paired regions is user-specified [3,5,4], Stochastic Context Free Grammars (SCFG) which use a complete statistical model of RNA elements [6], and Secondary Structure Profiles, which use position weight matrices describing stems and single strands in the RNA motif, as found in the ERPIN program [8]. Although the last two methods compute alignment scores, the complexity of the underlying models and search algorithms has hampered the estimation of an E-value to date.
When the behavior of the score distribution is known, such as in sequence alignment scores, E-values can be computed either directly, or by empirically fitting a histogram of scores from a sample of random sequences to the assumed distribution function [1,2]. Unfortunately, we will show here that a search algorithm such as the one used in ERPIN does not produce predictable score distributions. A possible workaround for this practical limitation is to run simulations on randomized sequences and use the observed hit count at score S as the E-value for this score. However, since interesting high scoring solutions can be extremely rare (commonly less than one random occurrence per genome) simulations often require days of calculations. Can we then estimate score distributions without having to run such lengthy simulations?
In this article, we show that ERPIN score distributions can be estimated a priori through a discrete convolution analysis of score profiles, based on a random model of nucleotide frequencies. This led us to develop a computational procedure that estimates the score distribution of ERPIN profiles in a very short time, before the actual search begins, so that each solution can be automatically assigned an E-value.
ERPIN profiles
ERPIN is an RNA motif search software using as input a training set of aligned RNA sequences, and a target database in which the motif is to be identified. The training set contains both RNA sequence and their common secondary structure, specified as shown in Figure 1 in the form of single strands and helices. Importantly, gap characters (insertions or deletions) are allowed in single strands but not in helices. Helices are composed of two distinct strands of equal length. A region is defined as a continuous stretch of complete single strands or helical elements. When only one strand of a helix is included in a region, this strand is considered as a single strand. A mask is a subset of a region constituted of single strands and/or complete helices.
ERPIN converts each helix and single strand in the alignment into a lod-score profile. This involves two steps. First, columns in the alignment are converted into frequency profiles, recording the frequencies of bases or base-pairs in column c as:
Here nic is the number of bases or base-pairs of type i in column c, and N is the total base or base-pair count in a column. There is one frequency profile for each single strand or helix in the alignment. In the case of a single strand, i ∈ {A, T, G, C}, whereas for a helix, i ∈ {AA, AT, AG, AC, ..., CC} and each column in a helical profile actually refers to two positions in the initial alignment. Single strand profiles thus have 4 rows while helix profiles have 16 rows. The special case of gap-containing single strands, where a fifth character is added to the profile is discussed later on.
Frequency profiles are then converted into lod-score profiles, where values for column c are defined as:
where bi is the background frequency of base or base-pair i in the target database. Base-pair frequencies are considered as the product of individual base frequencies. The score of a helix or single-strand element is obtained by presenting a target sequence to this element's profile and summing the scores obtained for every profile column. For ungapped elements, the calculation is straightforward. For gap-containing single strands, a dynamic programming matrix of the profile and target sequence is constructed, which provides the best possible alignment score [8]. In a first stage, let us ignore this alignment procedure and focus on ungapped elements.
Exclusions and pseudocounts
We define as an exclusion a profile element for which no base or base pair is observed in the training set, and thus Pic = 0. Exclusions may be due either to an unsufficient size of the training set, or to a true avoidance of this particular base or base-pair at this position in the RNA molecule. In any case, the log-odd ratio formula would produce a value of -∞ for such cases, thus requiring a special treatment. Exclusions are dealt with either by using arbitrary low values (e.g. -30) or by introducing pseudocounts in the frequency matrix that simulate what could have been observed in a larger training set.
Pseudocounts are based on some prior knowledge of "typical" substitution frequencies in RNA molecules, as observed in a model RNA sequence alignment. The pseudocount calculation procedure used in ERPIN is the same spirit as that of Henikoff and Henikoff [9], but we use a different definition of pseudocounts, as explained below. Let us first reformulate the values in any column c of a frequency profile:
Where nij is the number of {i, j} couples in column c, P(i, j) is the joint probability of finding i and j in this column, and . This develops into:
Where P(i|j) is the conditional probability of observing i, knowing that j is observed in the column. This conditional probability amounts to the observed frequency of i → j substitutions. To introduce pseudocounts in ERPIN frequency profiles, P(i|j) is replaced with the average substitution frequencies observed in a model RNA sequence alignment, expressed in the form of a substitution matrix M. Pseudocount-based frequencies can be expressed as:
where M is a square matrix whose columns j are normalized, ∑i Mij = 1, so that . See Methods section for construction of M. The relative ratio of pseudocounts to true counts in the final frequency matrix is then controlled by a user-defined weight parameter α ∈ [0, 1], such that:
Since Mij are generally ≠ 0 in the substitution matrices (either for single strand or helices), most exclusions in the frequency profile are replaced by nonzero values as soon as α ≠ 0. Not only the resulting lod-score profiles are basically devoid of arbitrary low values, but they better reflect "natural" base and base-pair substitution frequencies observed in real RNA alignments. This is especially interesting in helical regions, since the substitution matrix for helices represent natural exchanges between frequent base-pairs such as Watson-Crick, G:U or even G:A, while incurring strong penalties for exchanges involving rare base pairs. This maintains a large fraction of strongly negative values in helix profiles, which is desirable for the sake of search specificity.
Shapes of score distributions: finite and non-finite scores
We define as a "finite" score the score obtained for a sequence that does not contain any match to a profile exclusion. When pseudocounts are used, almost all scores are finite, but when pseudocounts are not in use (α = 0), many scores, especially in helix profiles, are "non-finite", although in practice they are replaced by arbitrary low values.
Let S denote a finite score obtained at a given site in a random sequence. For any x > -∞, the conditional probability formula reads:
P(S > x) = P(S > -∞).P(S > x|S > -∞) (7)
In this decomposition, it is noteworthy that:
• The first factor is independent of x as soon as x is finite,
• The second factor can be computed based on profile elements that contain no exclusion.
Let Sc (c = 1, 2, .., w) denote a score for column c of a profile, and S = S1 + S2 + ... + Sw the score obtained by presenting a given sequence to this profile. If w is large enough (w ≳ 10) and the distributions of random variables Sc are (i) independent and (ii) identically distributed, the sum S follows a normal distribution (central limit theorem [11]).
Due to exclusions arising with different frequencies in different columns, condition (ii) is generally not fulfilled, but, using the decomposition given by formula (7) rewritten for column c, we can write:
P(Sc > x) = Pfs,c.Pf,c(x) (8)
where Pfs is the probability that a score is finite, and Pf(x) is the probability that a finite score is higher than x. This gives, for a complete profile:
In many cases, the probability distributions of finite scores Pf,c are similar enough so that their sum S is normally distributed. If this behavior was always observed, the score distribution could be fully determined by computing the mean value μ and the standard deviation σ that characterize the normal law, which would enable a direct calculation of the E-value [2]:
Figure 2 shows the score distributions obtained using the tRNA region spanning the anticodon and TΨC loop (two helices + three single-strands) at each position of a 100 Mb random sequence database, with pseudocounts switched off (α = 0). As expected, finite scores (Fig 2a) follow a normal distribution, while total scores (Fig 2b) are unevenly distributed.
So called "non-finite" scores may be biologically relevant, since many valid substitutions are potentially absent from the training set. However, non-finite scores are detected only when high enough to fall into the extreme end of the distribution. This part of the distribution is composed mainly of finite scores and should thus behave like that of finite scores. Unfortunately finite scores may also deviate from a Gaussian distribution, for instance when score distributions in successive columns are too different from each other.
Pseudocounts are used to inject missing substitutions into frequency profiles, resulting in most "non-finite" scores becoming "finite". But what is the behavior of finite scores when pseudocounts are in use? Fig 3a–d and 4a–b show finite score distributions for a variety of ungapped RNA motifs (shaded bars), obtained using a typical level of pseudocounts (α = 2.10-4) in frequency profiles. Although some training sets (tRNA, SECIS) have nearly gaussian distributions, others (let-7 miRNA, snoRNA, polyA sites) are more erratic. This is due to the larger number of exclusions in the later sets – only partially compensated for by pseudocounts – and/or their non-uniform distribution over profile columns. If we aim to address true biological problems with such imperfect or sparse training sets, we necessarily have to deal with this type of score distribution that cannot be approached with classical methods. Nonetheless, we will still be using the decomposition formula (7), as it provides an important reduction of the range of values of the random variables involved.
Score distributions of helices and single-strands
Ungapped helices and single strands
How can we estimate score distributions such as those in Fig 3, 4 ? Let us admit that profile columns are independent. After matching the profile to a purely random sequence, the resulting scores for each column would thus behave as independent random variables, say X1 and X2 for columns 1 and 2. Therefore, the final score for two columns would be:
S = X1 + X2
Then, the probability of obtaining a score S = x is:
The last formula defines the discrete convolution product [11] of two distributions. The overall score distribution can be obtained by doing the calculation for every possible values of u and v.
Using the separation formula (7) between "exclusions" and "finite scores", equation (10) can be written:
These operations can easily be extended to N columns by iterating the products on successive columns in the same single-strand or helix profile. At each successive iteration, scores are discretized on a predefined grid so that the number of possible scores increases linearly with the number of columns (see Methods section for algorithm).
We performed such an analysis on a variety of helix and single strand profiles, with grid intervals set at Δx = .05. In Figures 3 and 4, score distributions estimated from discrete convolution (solid lines) are compared to scores obtained through simulation on a random database of variable size (shaded bars). There is a very good agreement between the discrete convolution and simulation.
Gap-containing single strands
The score of a gap-containing single strand in the ERPIN program is computed from the dynamic programming alignment matrix. Therefore, it is the maximum of several values, and could be expected to comply with an extreme value distribution. However, gapped single strands in ERPIN are very diverse entities that may include oddities such as single-nucleotide strands, or strands mostly filled with gaps. This results in very uneven distributions that we were not able to model satisfyingly. Therefore, the score distribution of a gapped single strand in ERPIN is currently estimated based on a short simulation performed on a random sequence (see Methods section for details).
Score distributions of complete regions with gaps
Score of a configuration
When presenting a sequence to a whole region, the presence of gaps in single-strands results in multiple allowed positions for flanking helical elements. A configuration is a specific arrangement of helix elements determined by the number of intervening gaps (Fig 1). There is one score for each allowed configuration, which is the sum of scores for all helices and single strands in this configuration. We therefore need to compose the different score distributions to obtain the distribution of the total score for one configuration. This is again done using a discrete convolution of these distributions, with the same procedure and grid parameter as above. This provides the score distribution of a single configuration. Note that, although a configuration may contain gapped single strands of which score distribution was not produced by a discrete convolution, such distributions can now be treated by this second convolution round applied to whole profiles.
Score of a complete region
The number of gaps in a single strand is bounded by the maximum number of gaps observed for this strand in the training set: mxgaps. For a simple hairpin-loop motif with mxgaps possible gaps in the loop, there are (mxgaps + 1) possible configurations. For a whole region containing N strands with gaps (i = 1, 2, ..., N), the number of configurations is:
Erpin evaluates all possible configurations without any construction rule or strategy. A combinatorial explosion is avoided by implementing multi-stage searches, where search at each stage is limited to a defined mask, or subset of the region under study. The score of a region or mask at in given site is the maximum score obtained for all possible configurations.
Since a motif is identified only after all possible configurations are evaluated at a given site, our estimation of motif scores requires taking into account this additional complexity. Let K denote the number of configurations for a given motif, and Si, the score obtained for the ith configuration. As the ERPIN program does not permit the of addition gaps relative to those present in the training set, K is necessarily bounded but its value can be relatively large. We are now interested in the maximal score obtained for all configurations at each site. This is the extreme value distribution, or the distribution of a random variable M defined as:
If Pfs = P(Si > -∞) and pi(x) = P(Si > x|Si > -∞), and the random variables Si are statistically independent (s.i) and identically distributed (i.d), then:
The most "interesting" scores are expected to be of the same order of magnitude as those obtained by training set sequences. For any realistic training set, these scores should be very high compared to scores obtained on random sequences and, therefore, their probability should be very low. In this case P(M > x), given by formula (17), behaves at the first order approximation as K.Pfs.p(x).
For a database of size Ω, considering that individual sequences in the database are large enough compared to the search motif so that border effects can be ignored, the final E-value, is :
E(x) = P(M > x).Ω (18)
Figure 5 compares these computed E-values (solid lines) to simulations performed on a random database (circles), for complex RNA regions encompassing multiple helices and singles strands (gapped or ungapped). Overall there is a very good agreement between E-value and simulation, consistent with our hypothesis that configuration scores are independent and equally distributed. Importantly, E-values remain accurate for RNA regions containing large gapped single strands, such as snoRNA (Fig 5b), Let-7 miRNA (Fig 5c) and SECIS (Fig 5d), and over a wide range of scores. This last point is also important, since "borderline" solutions with an E-value around 0.1 or 1 are potentially more interesting biologically as low E-value solutions. Moreover, computing times for overall E-value calculations in all our tests motifs remained insignificant relative to database scan times.
In the case where pseudo-counts are switched-off, profiles contain multiple "non-finite scores" which are excluded from the convolution process. This may imply a lack of accuracy in the left-hand side of the estimated score distribution, where scores have low values, but should have little effect in the region of biologically interesting scores. Therefore we do not expect E-values to deteriorate significantly in practise when pseudocounts are switched off.
Conclusion
We have presented a method to estimate the score distributions of RNA helices or single strand profiles and of their combinations into larger motifs. This method is based on discrete convolutions. The computing time of the discrete convolution algorithm increases quadratically with profile size and remains in any case negligible relative to database scan durations. This procedure is implemented in the last release of the ERPIN software (V. 4.2) and provides accurate estimates of E-values for practical applications. Interestingly, the discrete convolution approach can be applied as well to others sequence scoring models -nucleic acids or proteins – based on ungapped profiles with independent columns.
Methods
ERPIN program and utilities
The ERPIN program (sources and executables) is available at . Simulated score distributions of independent helix and single-strand profiles (Fig 2, 3, 4) were obtained using the -hist (histogram) option of ERPIN and utility programs epnstat, convhstat, convsstat and mstat provided in the distribution. For Fig 5, full motif searches were performed using ERPIN Version 4.2.5 with pseudocount weight α = 2.10-4. Graphical outputs for figures 2, 3, 4, 5 were produced using the Matlab [13] package.
Training sets
Training sets for profile statistics and ERPIN runs in Fig 2, 3, 4, 5 are available on the ERPIN web site and were obtained as follows:
• tRNA: 903 type I tRNA sequences (all species) from the 1997 version of M. Sprinzl's nuclear tRNA alignment [17].
• SECIS (Selenocystein Insertion Sequence): 117 metazoan SECIS sequences, from our own compilation [7].
• snoRNA (Small nucleolar RNA): 217 archaean C/D box snoRNA sequences, compiled and aligned by Fabrice Leclerc at CNRS Nancy (Personal communication).
• Let-7 miRNA: 27 animal miRNA precursor sequences from our previous compilation [15].
• PolyA sites: 2327 human polyadenylation sequences from our previous compilation [16].
RNA substitution matrices for pseudocounts
Pseudocount calculation requires substitution matrices obtained from a model RNA sequence alignment or "training set", annoted with secondary structure information (helix or single strand). Klein and Eddy have developed RNA substitution matrices previously [18], but we use a different type here. Training set columns are converted into profiles containing raw nucleotide or base-pair counts. Let Q denote a nucleotide or base-pair count profile of width w, produced by a concatenation of all single strand or helix profiles from the pseudo-count training set. Q is either a 4-line matrix for single strands (h = 4) or a 16-line matrix for helices (h = 16). The substitution matrix M introduced in Section "Exclusions and Pseudocounts" is then a square matrix of size h × h defined as:
The square matrix N is actually a "correlation matrix" of the profile lines since element Nij is the scalar product correlation of lines i and j. Coefficients λj make this matrix normalized, so that:
Probability conservation is verified for P and therefore it is also verified for P':
Finally, it is obvious from formula (6) that P" also verifies verifies probability conservation, hence:
Substitution matrices can be generated from any RNA sequence alignment using the utility program mksum of the ERPIN distribution. Default matrices provided with distribution (SUM.dat file) were obtained using a 16S/18S rRNA training set from R.Gutell ([10]) containing 6310 sequences from all three phylogenetic domains. We used the secondary structure of E-coli 16S rRNA as the consensus structure, resulting in 481 columns of helix profile and 7512 columns of single strand profile.
Option -pcw is used to set pseudo-count weight α in the ERPIN program. Default internal value is 2.10-4, but this has been rescaled for users by a factor of 2.10-3 giving a default user value of 0.1 and a practical maximal value that should not exceed 1. Effects of pseudocounts and of the α parameter on profiles can be visualized using the utility program pview.
Score distribution of gap-containing single-strands
The score distribution of gap-containing single strands is evaluated by repeatedly computing profile scores with a random sequence of same length L as the profile and same composition as the target sequence database. The calculation is repeated C.L2 times, with C a constant, and L <Lmax in order to limit CPU time for unusually large strands. Default values are C = 300 and Lmax = 12.
Histograms and discrete convolution product
Although discrete convolutions can be computed using iterated Fast Fourier Transforms, this approach is subject to numerical approximations in practice. A direct calculation is more accurate and proved fast enough in all cases tested. Time complexity of the discrete convolution algorithm is O(N2) where N is the total number of profile columns. This value remains tractable even for the largest RNA motifs. The convolution algorithm was adapted from those found in the Octave [12] and Matlab [13] packages. The linear sampling interval was set at Δx = .05. CPU time for the complete E-value calculation (including profile construction, convolution of independent profiles and convolution of configurations) for motifs in Fig 5 ranged from 10-4s to 0.8s on a 2.6 GHz Intel Pentium workstation with 1 Gb of RAM.
Extreme value distribution
Formula (17) used for calculating the extreme value distribution is of the type (1 - (1 - x)N). If x.N > 1 the result is obtained with the C library function x xy which lacks precision when x ≪ 1. Otherwise we compute (17) using the binomial formula for (1 - x)N.
Authors' contributions
AL conceived the discrete convolution approach, programmed the software and participated in drafting the manuscript, ML and JFF performed program runs and statistical analyzes of outputs, DG participated in the design and coordination of the study and wrote most of the manuscript. All authors read and approved the final manuscript.
Acknowledgements
We thank the ACI IMPBio program for their support to the development of the ERPIN software and Web server.
Figures and Tables
Figure 1 An example of ERPIN training set containing two double helices (noted 2 and 4), and three single strands (noted 3, 5 and 7). Due to gaps in the alignment, helix 2 spans 9 to 11 nt, and helix 4 spans 6 to 7 nt. Combinations of these allowed ranges give 6 possible configurations for the whole RNA motif.
Figure 2 Distributions of finite and total scores obtained from the motif encompassing the anticodon and TΨC loop of tRNA, at each position of a 100 Mb random sequence database. This region covers three single strand profiles and two helix profiles and spans a gap-containing single- strand profile that is not included in score calculation. ERPIN results were processed by the epnstat utility program. A: finite scores. B: total scores (both finite and non-finite).
Figure 3 Comparision of finite score distributions obtained from discrete convolution of helix profiles (solid lines) and simulation (shaded bars). The various helices in the region under study were combined into a larger 16 × W profile, where W is the total number of base-pairs in the region. Lod-scores were computed based on a uniform nucleotide composition, by the convhstat utility program.
Figure 4 Comparision of finite score distributions obtained from discrete convolution of single-strand profiles (curve) and simulation (shaded bars). The various strands in the region under study were combined into a larger 4 × W profile, where W is the total number of nucleotides in the region. Lod-scores were computed based on a uniform nucleotide composition, by the convsstat utility program.
Figure 5 Comparision of computed E-values (solid lines) and number of solutions obtained from simulation on a random database of uniform nucleotide composition (circles), for different RNA motifs. Numbers following "region" refer to secondary structure elements in the corresponding training set available from . E-values were computed using the mstat utility program. (a) tRNA region covering the anticodon and TΨC stem-loops; (b) C/D box snoRNA region covering the major stem and C+D boxes; (c) Let-7 miRNA region covering the complete precursor hairpin; (d) SECIS element covering the large 14 bp stem and apical stem+loops.
==== Refs
Altschul SF Gish W Miller W Myers EW Lipman DJ Basic local alignment search tool J Mol Biol 1990 215 403 10 2231712 10.1006/jmbi.1990.9999
Karlin S Altschul SF Methods for assessing the statistical significance of molecular sequence features by using general scoring schemes Proc Natl Acad Sci U S A 1990 87 2264 8 2315319
Gautheret D Major F Cedergren R Pattern searching/alignment with RNA primary and secondary structures: an effective descriptor for tRNA Comput Appl Biosci 1990 6 325 31 1701686
Billoud B Kontic M Viari A Palingol: a declarative programming language to describe nucleic acids' secondary structures and to scan sequence database Nucleic Acids Res 1996 24 1395 403 8628670 10.1093/nar/24.8.1395
Macke TJ Ecker DJ Gutell RR Gautheret D Case DA Sampath R RNAMotif, an RNA secondary structure definition and search algorithm Nucleic Acids Res 2001 29 4724 35 11713323 10.1093/nar/29.22.4724
Eddy SR Durbin R RNA sequence analysis using covariance models Nucleic Acids Res 1994 22 2079 88 8029015
Lambert A Lescure A Gautheret D A survey of metazoan selenocysteine insertion sequences Biochimie 2002 84 953 9 12458087 10.1016/S0300-9084(02)01441-4
Gautheret D Lambert A Direct RNA motif definition and identification from multiple sequence alignments using secondary structure profiles J Mol Biol 2001 313 1003 11 11700055 10.1006/jmbi.2001.5102
Henikoff JG Henikoff S Using substitution probabilities to improve position-specific scoring matrices Comput Appl Biosci 1996 12 135 43 8744776
Cannone JJ Subramanian S Schnare MN Collett JR D'Souza LM Du Y Feng B Lin N Madabusi LV Muller KM Pande N Shang Z Yu N Gutell RR The comparative RNA web (CRW) site: an online database of comparative sequence and structure information for ribosomal, intron, and other RNAs BMC Bioinformatics 2002 3 2 11869452 10.1186/1471-2105-3-2
Feller W An Introduction to Probability Theory and its Applications 1968 Third John Wiley & sons -convolution product: Vol.1 chapter XI, Vol.2 chapter V. -central limit theorem: Vol.1 chapter X.
Eaton JW GNU Octave Manual: A high-level interactive langage for numerical computations 1997
Matlab High-Performance Numeric Computation and Visual Software The MathWorks, Inc
Press WH Teukolsky SA Vetterling WT Flannery BP Numerical Recipes in C 1994 Second Cambridge University Press
Legendre M Gautheret D Sequence determinants in human polyadenylation site selection BMC Genomics 2003 4 7 12600277 10.1186/1471-2164-4-7
Legendre M Lambert A Gautheret D Profile-based detection of microRNA precursors in animal genomes Bioinformatics 21 841 5 2005 Apr 1 15509608 10.1093/bioinformatics/bti073
Sprinzl M Dank N Nock S Schon A Compilation of tRNA sequences and sequences of tRNA genes Nucl Acids Res 1991 19 2127 2171 2041802
Klein RJ Eddy SR RSEARCH: Finding homologs of single structured RNA sequences BMC Bioinformatics 2003 4 44 14499004 10.1186/1471-2105-4-44
| 15892887 | PMC1168889 | CC BY | 2021-01-04 16:02:51 | no | BMC Bioinformatics. 2005 May 13; 6:118 | utf-8 | BMC Bioinformatics | 2,005 | 10.1186/1471-2105-6-118 | oa_comm |
==== Front
BMC BiotechnolBMC Biotechnology1472-6750BioMed Central London 1472-6750-5-151591671410.1186/1472-6750-5-15Research ArticleAn inter-platform repeatability study investigating real-time amplification of plasmid DNA Donald Carol E [email protected] Fizza [email protected] Malcolm J [email protected] Marcia J [email protected] Joseph R [email protected] Alison J [email protected] Bio-Molecular Innovation Team, LGC Ltd, Queens Road, Teddington, Middlesex TW11 0LY, UK2 Bioprocess Measurement Group, National Institute of Standards and Technology (NIST), 100 Bureau Drive, Mail Stop 8312, Gaithersburg, MD 20899-8312, USA2005 25 5 2005 5 15 15 6 10 2004 25 5 2005 Copyright © 2005 Donald et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
The wide variety of real-time amplification platforms currently available has determined that standardisation of DNA measurements is a fundamental aspect involved in the comparability of results.
Statistical analysis of the data arising from three different real-time platforms was conducted in order to assess inter-platform repeatability. On three consecutive days two PCR reaction mixes were used on each of the three amplification platforms – the LightCycler®, ABI PRISM® 7700 and Rotor Gene 3000™. Real-time PCR amplification using a fluorogenic 5' exonuclease assay was performed in triplicate on negative controls and DNA plasmid dilutions of 108–102 copies to give a total of 24 reactions per PCR experiment.
Results
The results of the statistical analyses indicated that the platform with the most precise repeatability was the ABI PRISM® 7700 when coupled with the FastStart PCR reaction mix. It was also found that there was no obvious relationship between plasmid copy number and repeatability. An ANOVA approach identified the factors that significantly affected the results, in descending order of magnitude, as: plasmid copy number, platform, PCR reaction mix and day (on which the experiment was performed).
Conclusion
In order to deliver useful, informative genetic tests, standardisation of real-time PCR detection platforms to provide repeatable, reliable results is warranted. In addition, a better understanding of inter-assay and intra-assay repeatability is required.
==== Body
Background
A diverse range of applications that impact on clinical diagnosis and prognosis rely on the real-time detection and quantification of Polymerase Chain Reaction products such as bacterial diagnostics [1,2], viral load [3-6], cancerous cell burden [7,8] and parasite quantification [9]. Each particular assay dictates the requirement for instrument capacity, data reproducibility and run length times. There is an expansive collection of different fluorescent chemistries and instruments available for real-time amplification reactions [10-12]. These platforms represent a technological advance from the traditional thermal cycler and typically offer faster, smaller (reduced volume) and more (high-throughput) reactions. Whilst the number of instruments with different software and fluorescent dyes is considerable, the obvious drawback is that the resultant data may not be repeatable or even directly comparable between instruments or even within instruments on different runs. A statistically appropriate number of samples and runs need to be conducted in order to have confidence in the results or to assign mathematical significance to any of the factors affecting real-time amplification. In addition, there is a shortage of reliable, universal DNA standards at present. Increasing diversity through technological advances in DNA quantitation instruments and software may further challenge the standardisation of results. It should be ensured that proper quality controls under-pin both existing and emerging technologies.
The aim of this study was to evaluate the repeatability of three different real-time PCR platforms including the effect of PCR reaction mix. Previous work carried out has shown that fluorogenic 5' exonuclease ("TaqMan®") probe chemistry was more repeatable than Scorpion probe or SYBR® Green I chemistries for genetically modified soya amplification on the LightCycler® (Roche Diagnostics, Lewes, UK) and the ABI PRISM® 7700 (Applied Biosystems, Warrington, UK) [13]. Hence, for the amplification of a 'model' plasmid dilution series we have selected "TaqMan®" probes to assess inter-platform repeatability of the LightCycler®, the ABI PRISM® 7700 and the Rotor Gene 3000™ (Corbett Research, Cambridge, UK). These three real-time PCR platforms have different temperature control mechanisms, specifically a 96 well heating block (ABI PRISM® 7700), an air fan and/or coil with 32-position carousel (LightCycler®), and ambient air with 72-position rotor (Rotor Gene 3000™) [10].
In addition the performance of two commercially available master-mixes were compared. Statistical analysis was performed on the data to assess the levels of inter-platform repeatability and dynamic range of the instruments with different master-mixes.
Results
Repeatability Estimates
Precision estimates were determined based on each platform with PCR reaction mix combination at every plasmid copy number across the three days using ISO guidelines [14]. Precision estimates were calculated as repeatability standard deviations of the Ct (threshold cycle number) values from the amplification of each plasmid dilution. In addition, the mean value and standard deviations of these repeatability standard deviations were also presented in Table 1 to provide a measure of the variance of these estimates. Percentage coefficients of variance (%CV) were not used to represent precision estimates as a low mean Ct value in this experiment is indicative of good precision and therefore percentage CV would generate misleading results.
Although the assay was not designed to assess biological sensitivity of the system, and the dilution levels did not approach the limit of detection for the system, the 108 plasmid copy number data set had the best overall precision associated with it. The most probable reason for this is the availability of the target analyte in the sample.
The ABI PRISM® 7700 had the lowest mean repeatability estimate of all the platforms in this study when combined with the FastStart reaction mix, as shown in Table 1. However, the means of the repeatability estimates for the two PCR reaction mixes when combined with this platform were different (0.202 for the FastStart mix and 0.362 for the Excite™ mix). With the exception of the 104 plasmid copy number, every repeatability estimate value for the reactions performed on the ABI PRISM® 7700 using FastStart was lower than the corresponding Excite™ reaction mix. Indeed, consistently across the three platforms, the FastStart mix had the lowest average repeatability estimates in this trial. The value of the mean and standard deviations of the repeatability estimates were comparable when the FastStart PCR reaction mix was employed on the ABI PRISM® 7700 and on the LightCycler® (0.202 and 0.219 respectively and 0.047 and 0.082 respectively).
The lowest repeatability estimate calculated in this study was found to be 0.100. This value was generated on the LightCycler® using the FastStart reaction mix and a plasmid copy number of 104. Conversely, the highest repeatability estimate (1.378) was also produced on the LightCycler® but the Excite™ PCR reaction mix was employed with a plasmid copy number of 106.
Unexpectedly, the highest repeatability estimates for each data set are not necessarily associated with the low plasmid copy numbers [15]. The lowest repeatability estimates and the highest repeatability estimates for each platform and PCR reaction mix data set show no discernible trend with respect to plasmid copy number.
The least repeatable system in this trial based upon the data in Table 1 was the combination of the LightCycler® with the Excite™ PCR reaction mix. Comparison with the results of other published studies was not possible, as the statistical methods used were not clearly reported in the literature.
Analysis of Variance
An ANOVA approach using the threshold cycle number was used to identify sources of variability within the data. Table 2 shows the significance levels of the four main factors of day, plasmid copy number, reaction mix, and platform, as well as the significance levels of the interaction terms. The factors and interaction terms were compared to the Error MS (mean square) in order to assess their significance.
All four individual factors were highly significant. From the calculated F-variance ratio the factor of day had the least significant effect of the four factors, followed by PCR reaction mix (approximately 1.5 times the effect of day), then platform (approximately 7 times the effect of day), and then, as expected, plasmid copy number (approximately 45 times the effect of day). Even though the effect of day had a significant effect upon the results, this effect was very small when compared to the effect of platform and plasmid copy number.
The interaction of the four main factors was also investigated, this demonstrated that the majority of interaction terms were significant. However, in general the magnitude of the effect of these interaction terms was very small compared to the effect of the four main factors.
Day Effect
Day had a statistically significant effect upon the Ct value of the raw data (P<0.00001). The average Ct value in the full data set decreased from 19.76 to 18.54 across the 3 days (data not shown).
Plasmid Dilution Effect
As Figure 1 illustrates, the number of plasmid copies was inversely proportional to the average Ct value [6,12] within the instrument dynamic working range and above the LOD (limit of detection). Our results concur with Sanchez et al [5] who reported that cytomegalovirus quantification was linear between 101 and 106 copies, and with Moberg et al who used 102 to 107 DNA copies in their real-time assay [16]. At extremely low or high plasmid copy numbers the linear relationship with Ct value may be affected. At high copy number it may be difficult to set an accurate baseline because threshold values will be reached after only a few amplification cycles. In addition, reactions with very low numbers of target molecules may be disproportionately affected by pipetting errors and by stoichiometric effects. This highlights the need to work within the linear dynamic range of the instrument and the potential inaccuracy introduced by extrapolation of calibration curves.
Fresh plasmid dilutions were utilised to counteract the previously observed progressive loss of intact plasmid DNA, particularly at low plasmid copy number dilutions. This is probably due to physical adhesion of the DNA to the tube walls, although precautions, such as the use of siliconised tubes, were undertaken.
Fresh plasmid dilutions were made each day. Figure 2 illustrates how the average Ct value alters across the three days (which have three different dilution sets) for each plasmid copy number.
PCR Reaction Mix Effect
The results from reactions containing FastStart mix had significantly lower average Ct values than their Excite™ 2x mix reaction counterparts (data not presented) – the difference is approximately 1 cycle per plasmid dilution. The smallest interaction term is that of PCR reaction mix with platform (P = 0.019), indicating good consistency of results when using the reaction mixes across different platforms.
Platform Effect
The platforms have different heating mechanisms and therefore it was expected that their performance characteristics such as repeatability might differ significantly. The largest significant interaction term (F = 150.8) was that of platform with day, indicating that each platform may not be behaving consistently between the three days. Closer inspection of the data shows that the majority of the variation associated with the platform by day interaction is attributed to the Rotor Gene day 2, as illustrated in Figure 3, which appears inconsistent compared to the other two platforms. This interaction effect of platform with day was not significantly different from the factor of day or PCR reaction mix. The interaction of PCR reaction mix and platform (shown in Table 2) was found to be statistically significant at the 5% level.
The full raw data set is available [see Additional file 1].
Discussion
Use of a 'model' system that contained little or no contaminants, coupled with a balanced experimental design enabled accurate assessment of repeatability. Other factors such as extraction methods and complex matrices can potentially increase analytical variability. As demonstrated by the present study, a range of factors can affect performance of each of the instruments. In addition, results are influenced by the threshold value settings applied to the machine by the analyst. To underpin meaningful quantitative PCR measurement, internationally accepted guidelines should be established to standardise the analysis and interpretation of real-time PCR results. PCR reference standards could also be used as indicators of instrument reliability and amplification efficiency [17,18], while internal reaction controls could additionally monitor effects of PCR inhibitors and normalise for any instrument non-uniformity. A recent publication has looked at the plateau phase and the effect of enzyme inhibition during this stage of amplification [19]. With regard to analysis and software compatibility, a study conducted by Kuhne and Oschmann [20] has demonstrated the feasibility of importing standard curves from different LightCycler runs. Historically, standard curves have been the method of choice for determining absolute DNA concentration. However, the quantity of the standards used should be accurately calculated by gravimetry or other primary methods, as absorbance at a wavelength of 260 nm is not sufficient alone. Our present study has shown the potential inaccuracies introduced by importing standard curves, considering the significance of the factor 'day' on the data presented. Even under the controlled conditions used in the present study, significant variability was observed, suggesting that transferring standard curves between runs could be unreliable unless adequate controls are used. Recent research using more sophisticated software approaches has demonstrated the ability to use grand mean calibration curves between runs following compensation for differences in amplification efficiency [21]. Amplification efficiency changes throughout the course of a PCR reaction and is dependent on enzyme kinetics [22,23]. The potential pitfall of assuming that the sample analyte has the exact same kinetics and amplification efficiency of the standards has been highlighted recently [15]. A Galton-Watson branching process has been proposed which involves considering the number of molecules present during PCR cycles and uses Michaelis-Menten enzyme kinetics together with a population growth approach [23]. One other source of uncertainty associated with using amplification curves is the issue of handling outlier data points. In a recent publication Bar et al discussed this subject and presented a new statistical method [24]. This may have applications for clinical samples that have been extracted from complex matrices or any analysis with high levels of variability between results. It is not surprising that difficulties in data comparison arise due to the many different mathematical and software approaches applied to real-time quantitative PCR, despite sharing the same mathematical fundamentals [25-28].
The data generated in this study is not intended to indicate any preference for a particular piece of equipment or PCR reaction mix. The instrument specification, reliability, operator training, servicing and comparability all contribute to overall assay precision. In choosing a real-time platform, we would recommend that users consider the statistical outcomes of our results and perform their own critical assessments to ensure that an instrument is fit for their purpose. Generally any such judgement would involve factors such as the volume of samples for processing, the speed at which results need to be obtained and the reproducibility or repeatability of the results.
In addition to choice of appropriate real-time platform, accurate quantitative measurement is dependent upon rational experimental design, optimisation and careful data interpretation.
Conclusion
We have demonstrated that in this trial the most repeatable system was the ABI PRISM® 7700 with the FastStart PCR reaction mix. However the mean repeatability estimate of the LightCycler® combined with the FastStart mix was comparable. In addition, we have shown that the plasmid copy numbers used in this trial did not display a distinct relationship with instrument repeatability.
An ANOVA established that plasmid copy number, platform, PCR reaction mix and day significantly affected the results in a descending order of magnitude.
Inherent differences in the data handling between instruments still presents a challenge to the normalisation of real-time PCR assays between laboratories and users of different instruments. We have confirmed that standardised real-time PCR detection instruments and data analysis approaches are imperative in order to guarantee the integrity and the repeatability of DNA measurement experiments.
Methods
Plasmid Composition and Dilution
The target DNA was a pPCR-Script Amp SK(+) plasmid (Stratagene, Amsterdam, The Netherlands) with an insert at the Srf I site in the multiple cloning site (supplied by N.I.S.T, Gaithersburg, MD, USA). A portion of the insert sequence follows with the primer binding sites indicated in bold face type and the probe binding site underlined: 5'-CAGACCGCTCGACGATAGGTCAGCACTGTCTCGTTGACAGGCGTGGTCAATCAGCCTGAAATCCTCGATCAGAGTGTGCCGATCTCTGGTCCACGTCCT-3'. From a stock solution of plasmid (3 × 1013 copies) in molecular biology grade water (Sigma, Poole, UK), 1 in 10 serial dilutions were carried out to a copy number of 3 × 105 per mL using the same batch of water. Fresh dilutions were made every day from the same stock and using the same conditions and were kept at 4°C before and between use. At low copy numbers particularly, a reduction in target copies available for amplification was observed on prolonged storage, possibly due to DNA absorption to the walls of the tube (data not shown). Fresh dilutions were prepared each day in order to minimise this source of variation.
Real-time PCR Conditions
A 100-bp region of the insert sequence was amplified using HPLC purified oligonucleotide primers (Sigma-Genosys, Cambridge, UK) and a fluorogenic 5' exonuclease probe (Sigma-Genosys, Cambridge, UK) diluted in molecular biology grade water (Sigma, Poole, UK). The primers and probe used were P1A (forward primer): 5'-ACAGACCGCTCGACGATAGG-3', P1B (reverse primer): 5'-AGGACGTGGACCAGAGATCG-3' and TAQ1 (probe): 5'-{FAM}CAGCACTGTCTCGTTGACAGGCGTG{TAMRA}-3' (FAM – 6-carboxyfluoresceine; TAMRA – 5'-carboxytetramethylrhodamine).
Primer Express® software (Applied Biosystems; Warrington, UK) was used to design the primers and probe. The thermal cycling conditions used were dependent on the PCR reaction mix employed and were optimised protocols based on the manufacturer's guidelines. Amplification conditions for those reactions that contained 'FastStart Master mix' (Roche Diagnostics, Lewes, UK) were a 10 minute hold at 95°C followed by 55 cycles of 95°C for 15 seconds and 60°C for 30 seconds. For reactions with the Excite™ 2x kit (Biogene, Kimbolton, UK) the amplification conditions were a 2 minute hold at 50°C followed by a 10 minute hold at 95°C and then 55 cycles of 95°C for 15 seconds and 60°C for one minute.
Instrumentation & PCR Reaction Mixes
Three platforms compatible with "TaqMan®" probes were assessed – LightCycler® (Roche Diagnostics, Lewes, UK), ABI PRISM® 7700 (Applied Biosystems, Warrington, UK) and Rotor Gene 3000™ (Corbett Research, Cambridge, UK). All of these instruments were found to be compatible with FastStart (Roche Diagnostics, Lewes, UK) and Excite™ 2x (Biogene Kimbolton, UK) mixes following optimisation. The amplification performances of both PCR reaction mixes were investigated on each of the three machines using the plasmid dilution series as target. The probe was added at a final concentration of 200 nM per reaction for all experiments. The Primers P1A and P1B were used at a final concentration of 1500 nM each in the Excite™ mix reactions whereas the FastStart mix reactions contained the primers at a final concentration of 500 nM each. A supplement of magnesium chloride (final concentration of 3 mM) was added to those reactions containing Excite™ mix that were run on the LightCycler®. In addition, magnesium chloride at a final concentration of 3 mM was required for all those reactions containing the FastStart mix except for the equivalent amplification reactions run on the LightCycler®, where a final concentration of 2 mM of magnesium chloride was optimal.
A solution of BSA (BSA 100x; New England Biolabs, Hitchin, UK) at a final concentration of 0.1 mg/mL was added to the Excite mix for reactions run on the LightCycler®. To every reaction except the negative controls, 1 μL of plasmid DNA was added. Additional molecular biology grade water was added to a final volume of 20 μL and 25 μL for the FastStart and Excite™ mixes respectively.
Reactions were set up in 20 μL glass capillaries, 0.1 mL plastic tubes and 96 well optical plates for use on the LightCycler®, Rotor Gene 3000™ and ABI PRISM® 7700 respectively.
Experimental Design
Six experiments (two per platform) were run, and repeated for three consecutive days. Three replicates of each plasmid DNA dilution plus three negative controls (24 reactions in total) were amplified per experiment. One specific analyst prepared the complete master-mixes containing primers, probes, water and other supplements as already outlined, in a pre-PCR 'clean' room using the same pipettes each day. A second specific analyst added the plasmid DNA in a dedicated template addition area and used the same instruments for all template additions. Those amplification reactions containing the Excite™ 2x mix were run at the same time each morning on the Rotor Gene 3000™, ABI PRISM® 7700 and LightCycler® and the reactions containing FastStart mix were run at the same time each afternoon on the Rotor Gene 3000™, ABI PRISM® 7700 and LightCycler®. For each run the same instrument, rotor and carousel (where applicable) were employed to minimise intra-run variability.
Baseline Settings & Data
The Ct (threshold cycle number) was used as the measurand in order to assess the level of product in proportion to the level of starting target. As recommended by the manufacturers' guidelines, the Ct values were calculated from the mid-point of the exponential phase of amplification. However, each real-time platform required some manual intervention to set analysis parameters. In addition specific analysis software was associated with each instrument and inherent differences in data manipulation may introduce further inter-platform variability. As amplification efficiency has been shown to change over the course of the reaction [29], we have based our analysis on the mid-point of the exponential phase to measure threshold cycles irrespective of platform, run or PCR reaction mix.
Statistical Analysis
The results were interpreted and analysed according to the instrument manufacturer protocols. For each platform, graphs of cycle number versus arbitrary fluorescence units were generated and from this raw data, Ct values were automatically calculated by the software provided with each instrument [see Additional file 1]. The statistical package Statistica 6.0 (Statsoft; Tulsa, OK, USA) was used to analyse the data for all the instrument runs by ANOVA (Analysis of Variance) and then repeatability estimates were carried out.
Abbreviations
FAM: 6-carboxyfluoresceine
TAMRA: 5-carboxytetramethylrhodamine
BSA: bovine serum albumin
Ct: threshold cycle number
%CV: Percentage coefficient of variance
MS: Mean square
Authors' contributions
CED carried out the experimental work and drafted the manuscript; FQ carried out the experimental work; MJB participated in the design of the study and performed the statistical analysis; MJH conceived of the study; JRB produced the plasmid material; AJW conceived and designed the study. All authors read and approved the final manuscript.
Supplementary Material
Additional File 1
Raw Data Table. Table 3 consists of the raw data results comparing the effect of day, plasmid copy number, PCR reaction mix and platform on the mean Ct value.
Click here for file
Acknowledgements
The work described in this study was supported under contract with the UK Department of Trade and Industry as part of the national measurement system valid analytical measurement (VAM) program. We would like to thank the Biotech Division at NIST, (USA) for providing us with the plasmid DNA. The authors wish to thank Jacquie Keer for editing and helpful discussion. In addition, David McDowell and Gavin Nixon are thanked for their help with primer and probe design. We would like to thank Corbett Research UK for the loan of the Rotor Gene 3000™ instrument.
Figures and Tables
Figure 1 Average threshold cycle number (Ct) plotted against plasmid copy number. The data have been pooled from each platform, PCR reaction mix and day to give an average Ct value. Linear regression performed on the ploted data values from this graph determined that the gradient was -2.92 and that the amplification efficiency [21] was greater than two. However the amplification efficiency cannot be greater than two since PCR is an exponential reaction where the amount of product doubles at each cycle.
Figure 2 Average threshold cycle number (Ct) plotted against day for each plasmid dilution illustrating the interaction of day and plasmid copies. The data have been pooled from each platform, PCR reaction mix and plasmid dilution.
Figure 3 Average threshold cycle number (Ct) plotted against day for each platform illustrating the interaction of day and platform. The data have been pooled from each PCR reaction mix and plasmid dilution.
Table 1 Comparison of repeatability estimates of the PCR measurements using different reaction mixes and platforms over three days (using standard deviations of the Ct value).
Repeatability Estimates (standard deviations of the Ct value) based on Individual Plasmid Copy Number
Plasmid Copy Number Platform and PCR Reaction Mix
ABI 7700 LightCycler RotorGene
Excite FastStart Excite FastStart Excite FastStart
102 0.543 0.182 0.568 0.233 0.888 0.186
103 0.452 0.204 1.177 0.190 0.184 0.445
104 0.223 0.305 1.123 0.100 0.256 0.592
105 0.243 0.168 0.947 0.224 0.209 0.221
106 0.362 0.183 1.378 0.281 0.772 0.333
107 0.473 0.189 0.919 0.156 0.319 0.247
108 0.236 0.184 0.454 0.352 0.322 0.166
Degrees of Freedom 6–8 6 6–8 5–6 6–8 6
Mean 0.362 0.202 0.938 0.219 0.421 0.313
Standard Deviation 0.130 0.047 0.331 0.082 0.286 0.156
(Note that one replicate is missing for the LC platform coupled with the Fast Start reaction mix – the capillary broke).
Table 2 Variation attributable to day, plasmid copy number, PCR reaction mix and platform following an ANOVA test using threshold cycle number (Ct) as the variable factor.
Univariate Tests of Significance for Ct value. Sigma-restricted parameterisation. Effective hypothesis decomposition.
Effect SS DF MS F P
Day 96.0 2 48.0 221.4 <0.00001
Plasmid Copies 12919.2 6 2153.2 9932.0 <0.00001
PCR Reaction Mix 75.0 1 75.0 346.2 <0.00001
Platform 700.5 2 350.2 1615.5 <0.00001
Day with Plasmid Copies 53.2 12 4.4 20.5 <0.00001
Day with PCR Reaction Mix 1.9 2 0.9 4.3 0.01442
Plasmid Copies with PCR Reaction Mix 8.5 6 1.4 6.5 <0.00001
Day with Platform 130.8 4 32.7 150.8 <0.00001
Plasmid Copies with Platform 51.0 12 4.2 19.6 <0.00001
PCR Reaction Mix with Platform 1.7 2 0.9 4.0 0.01901
Day with Plasmid Copies with PCR Reaction Mix 14.6 12 1.2 5.6 <0.00001
Day with Plasmid copies with Platform 18.3 24 0.8 3.5 <0.00001
Day with PCR Reaction Mix with Platform 49.6 4 12.4 57.1 <0.00001
Plasmid copies with PCR Reaction Mix with Platform 4.5 12 0.4 1.7 0.06337
Day with Plasmid Copies with PCR Reaction Mix with Platform 11.8 24 0.5 2.3 0.00091
Error 54.4 251 0.2
(Where SS = sum of squares; DF = degrees of freedom; MS = Mean Square; F = ratio of variances; p = probability of obtaining a specific result, given by the null hypothesis).
==== Refs
Sharma VK Detection and quantitation of enterohemmorrhagic Escherichia coli O157, O111, and O26 in beef and bovine feces by real-time polymerase chain reaction Journal of Food Protection 2002 65 1371 80 12233845
Lyons SR Griffen AL Leys EJ Quantitative real-time PCR for Porphyromonas gingivalis and total bacteria Journal of Clinical Microbiology 2000 38 2362 5 10835003
Hausler M Scheithauer S Ritter K Kleines M Molecular diagnosis of Epstein-Barr virus Expert Review of Molecular Diagnosis 2003 3 81 92 10.1586/14737159.3.1.81
Monpocho S Coste-Burel M Costa-Mattioli M Besse B Chomel JJ Billaudel S Ferre V Application of a real-time polymerase chain reaction with internal positive control for detection and quantification of enterovirus in cerebrospinal fluid European Journal of Clinical Microbiological Infectious Disease 2002 21 532 6 Epub 10.1007/s10096-002-0766-5
Sanchez JL Storch GA Multiplex, quantitative, real-time PCR assay for cytomegalovirus and human DNA Journal of Clinical Microbiology 2002 40 2381 6 12089251 10.1128/JCM.40.7.2381-2386.2002
Weinberger KM Wiedenmann E Böhm S Jilg W Sensitive and accurate quantitation of hepatitis B virus DNA using a kinetic fluorescence detection system (TaqMan PCR) Journal of Virological Methods 2000 85 75 82 10716340 10.1016/S0166-0934(99)00154-8
Tester AM Sharp JA Dhanesuan N Waltham M Thompson EW Correlation between extent of osteolytic damage and metastatic burden of human breast cancer metastasis in nude mice: real-time PCR quantitation Clinical and Experimental Metastasis 2002 19 377 83 12198765 10.1023/A:1016381416463
Merino ME Navid F Christensen BL Toretsky JA Helman LJ Cheung NK Mackall CL Immunomagnetic purging of Ewing's sarcoma from blood and bone marrow: quantitation by real-time polymerase chain reaction Journal of Clinical Oncology 2001 19 3649 59 11504746
Bell AS Ranford-Cartwright LC Real-time quantitative PCR in parasitology TRENDS in Parasitology 2002 18 337 342 12380021 10.1016/S1471-4922(02)02331-0
Biocompare 9/8/04
Foy CA Parkes HC Emerging Homogeneous DNA-based Technologies in the Clinical Laboratory Clinical Chemistry 2001 47 990 1000 11375283
Van der Velden VHJ Hochhaus A Gazzaniga G Szczepanski T Gabert J van Dongen JJM Detection of minimal residual disease in hematologic malignancies by real-time quantitative PCR: principles, approaches, and laboratory aspects Leukemia 2003 17 1013 1034 12764363 10.1038/sj.leu.2402922
Terry CF Shanahan DJ Ballam LD Harris N McDowell DG Parkes HC Real-Time Detection of Genetically Modified Soya Using LightCycler and ABI 7700 Platforms with TaqMan, Scorpion, and SYBR Green I Chemistries Journal of AOAC International 2002 85 938 944 12180691
ISO regulation 3534-1 'Statistics – Vocabulary and symbols – Part1: Probability and general statistical terms.'
Stenamn J Orpana A Accuracy in Amplification. [Letter] Nature Biotechnology 2001 19 1011 2 10.1038/nbt1101-1011b
Moberg M Gustavsson I Gyllensten U Real-time PCR-based system for simultaneous quantification of human papillomavirus types associated with high risk of cervical cancer Journal of Clinical Microbiology 2003 41 3221 8 12843067 10.1128/JCM.41.7.3221-3228.2003
Najioullah F Thouvenot D Lina B Development of a real-time PCR procedure including an internal control for the measurement of HCMV viral load Journal of Virological Methods 2001 92 55 64 11164918 10.1016/S0166-0934(00)00273-1
Ovstebo R Haug KB Lande K Kierulf P PCR-based calibration curves for studies of quantitative gene expression in human monocytes: development and evaluation Clinical Chemistry 2003 49 425 32 12600954 10.1373/49.3.425
Kainz P The PCR Plateau Phase-towards an understanding of its limitations Biochimica et Biophysica Acta 2000 1494 23 27 11072065
Kuhne BS Oschmann P Quantitative real-time RT-PCR using hybridization probes and imported standard curves for cytokine gene expression analysis Biotechniques 2002 33 1078,1080-2 1084 12449386
Peirson SN Butler JN Foster RG Experimental validation of novel and conventional approaches to quantitative real-time PCR data analysis Nucleic Acids Research 2003 31 e73 12853650 10.1093/nar/gng073
Arezi B Xing W Sorge JA Hogrefe HH Amplification efficiency of thermostable DNA polymerases Analytical Biochemistry 2003 321 226 235 14511688 10.1016/S0003-2697(03)00465-2
Jagers P Klebaner F Random variation and concentration effects in PCR Journal of Theroretical Biology 2003 224 299 304 10.1016/S0022-5193(03)00166-8
Bar T Stahlberg A Muszta A Kubista M Kinetic Outlier Detection (KOD) in real-time PCR Nucleic Acids Research 2003 31 e105 12930979 10.1093/nar/gng106
Peccoud J Jacob C Ferré F Statistical Estimations of PCR Amplification Rates Gene Quantification 1998 Boston: Birkhäuser 111 128
Rutledge RG Cote C Mathematics of quantitative kinetic PCR and the application of standard curves Nucleic Acids Research 2003 31 e93 12907745 10.1093/nar/gng093
Peccoud J Jacob C Theoretical Uncertainty of Measurements Using Quantitative Polymerase Chain Reaction Biophysical Journal 1996 71 101 108 8804593
Nedelman J Heagert P Lawrence C Quantitative PCR with internal controls Comput Appl Biosci 1992 8 65 70 1568128
Liu W Saint DA Validation of a quantitative method for real time PCR kinetics Biochemica Biophysica Research Communication 2002 294 347 53 10.1016/S0006-291X(02)00478-3
| 15916714 | PMC1168890 | CC BY | 2021-01-04 16:02:57 | no | BMC Biotechnol. 2005 May 25; 5:15 | utf-8 | BMC Biotechnol | 2,005 | 10.1186/1472-6750-5-15 | oa_comm |
==== Front
BMC CancerBMC Cancer1471-2407BioMed Central London 1471-2407-5-511591069310.1186/1471-2407-5-51Research ArticleAdenovirus-mediated interleukin-12 gene transfer combined with cytosine deaminase followed by 5-fluorocytosine treatment exerts potent antitumor activity in Renca tumor-bearing mice Hwang Kyung-Sun [email protected] Won-Kyung [email protected] Jinsang [email protected] Hwan-Jung [email protected] Samyong [email protected] Dong-Soo [email protected] Laboratory of Gene Therapy and Virology, Korea Research Institute of Bioscience and Biotechnology, Yusong, Daejeon, Republic of Korea2 Department of Internal Medicine, College of Medicine, Chungnam National University, Daejeon, Republic of Korea2005 24 5 2005 5 51 51 12 11 2004 24 5 2005 Copyright © 2005 Hwang et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Therapeutic gene transfer affords a clinically feasible and safe approach to cancer treatment but a more effective modality is needed to improve clinical outcomes. Combined transfer of therapeutic genes with different modes of actions may be a means to this end. Interleukin-12 (IL-12), a heterodimeric immunoregulatory cytokine composed of covalently linked p35 and p40 subunits, has antitumor activity in animal models. The enzyme/prodrug strategy using cytosine deaminase (CD) and 5-fluorocytosine (5-FC) has been used for cancer gene therapy. We have evaluated the antitumor effect of combining IL-12 with CD gene transfer in mice bearing renal cell carcinoma (Renca) tumors.
Methods
Adenoviral vectors were constructed encoding one or both subunits of murine IL-12 (Ad.p35, Ad.p40 and Ad.IL-12) or cytosine deaminase (Ad.CD). The functionality of the IL-12 or CD gene products expressed from these vectors was validated by splenic interferon (IFN)-γ production or viability assays in cultured cells. Ad.p35 plus Ad.p40, or Ad.IL-12, with or without Ad.CD, were administered (single-dose) intratumorally to Renca tumor-bearing mice. The animals injected with Ad.CD also received 5-FC intraperitoneally. The antitumor effects were then evaluated by measuring tumor regression, mean animal survival time, splenic natural killer (NK) cell activity and IFN-γ production.
Results
The inhibition of tumor growth in mice treated with Ad.p35 plus Ad.p40 and Ad.CD, followed by injection of 5-FC, was significantly greater than that in mice treated with Ad.CD/5-FC, a mixture of Ad.p35 plus Ad.p40, or Ad.GFP (control). The combined gene transfer increased splenic NK cell activity and IFN-γ production by splenocytes. Ad.CD/5-FC treatment significantly increased the antitumor effect of Ad.IL-12 in terms of tumor growth inhibition and mean animal survival time.
Conclusion
The results suggest that adenovirus-mediated IL-12 gene transfer combined with Ad.CD followed by 5-FC treatment may be useful for treating cancers.
==== Body
Background
Gene therapy for treating cancers has been intensively investigated. Therapeutic gene transfer using viral or nonviral vectors has been shown to be clinically feasible and safe. However, the therapeutic outcome appears not to be high as expected, presumably because the in vivo gene delivery efficiency is low. In this sense, a more effective modality is needed to improve the therapeutic benefit. Combined transfer of genes with different mechanisms of action may potentate the therapeutic outcome. Indeed, combination cancer gene therapy using cytokine and suicide genes has been shown to be more effective than single gene transfer in animal models [1-9].
Interleukin (IL)-12 is a heterodimeric cytokine composed of 35- and 40-kDa subunits, which are covalently linked by a disulfide bond [10,11]. IL-12 stimulates interferon-γ (IFN-γ) production by natural killer (NK) cells, enhances the cytolytic activities of NK cells and cytotoxic T lymphocytes (CTLs), stimulates the differentiation of Th1 cells and inhibits angiogenesis [12-14]. These biological activities have provided a rationale for the use of IL-12 in cancer immunotherapy. In fact, recombinant IL-12 (rIL-12) exhibits significant antitumor activity in various animal models [12-14]. Subsequent phase I and II studies on various cancer types using intravenous or subcutaneous administration of human rIL-12 [15,16] showed some beneficial responses, but there were also adverse effects, which interrupted the clinical trials [17,18]. Recently, it has been reported that intratumoral administration of rIL-12 shows dose-limiting toxicity and results in measurable locoregional immunological responses in head and neck squamous cell carcinoma patients [19].
Since intratumoral IL-12 gene transfer could minimize the adverse effects of systemic rIL-12 administration [17], the effectiveness against tumors of cell vaccines expressing IL-12, or viral or nonviral vectors encoding IL-12, has been evaluated in various animal models [18,20-23]. The results indicate that, compared to IL-2, IL-4, interferons, and granulocyte-macrophage colony-stimulating factor, IL-12 is one of the most effective immunomodulators for cancer treatment [13,18,20,21,23]. Pilot clinical trials have been conducted in patients with advanced primary and metastatic liver cancer on the basis of these results [24]. Intratumorally administered adenoviral vectors expressing IL-12 had low efficacy but no cumulative toxicity [24].
Suicide gene therapy deploys genes such as cytosine deaminase (CD), herpes simplex or varicella zoster virus thymidine kinase (TK), or nitroreductase, all of which convert nontoxic prodrugs into cytotoxic agents [25-27]. Systemically administered prodrugs are converted to the active agents only in cells expressing these suicide genes, so the therapeutic effect is maximized while systemic toxicity is reduced. CD, which normally catalyzes the deamination of cytosine to uracil during RNA biosynthesis, is found in many bacteria and fungi but not in mammalian cells [28-30]. It also deaminates 5-fluorocytosine (5-FC) to 5-fluorouracil (5-FU), which is highly toxic to cells. 5-FU has been used clinically since the late 1950s to treat colorectal cancer [31]. A cellular metabolite of 5-FU, 5-fluorouridine triphosphate, is incorporated into RNA in place of UTP and consequently the multiple functions of RNA are impaired. Another metabolite of 5-FU, 5-fluorodeoxyuridine monophosphate, blocks thymidylate synthase activity and thus inhibits DNA synthesis.
No currently available gene delivery system can deliver therapeutic genes including suicide genes to all the target cells in vivo. However, tumor cells expressing a suicide gene can kill neighboring tumor cells that do not express this gene by the by-stander effect, which could partly overcome the gene delivery problem [32-35]. A number of suicide gene therapies have been shown to be effective against various cancer cell lines in culture and in animal models. Subsequent phase I, II or III studies using CD or TK genes were performed in colorectal cancer patients with liver metastases and in brain tumor patients [36-47]. The antitumor activities appeared less than expected [46], but the results showed that suicide gene therapy is safe to apply in the oncology clinic [36-47].
A combination of IL-2 and TK genes exerted a more potent therapeutic outcome in a metastatic carcinoma model, and induced antitumor immunity [1]. Since then, combination gene therapies using various cytokine and suicide genes have been intensively investigated [2-9]. In the present study, we investigated the effectiveness of combined transfer of IL-12 and CD genes against renal cell carcinoma (Renca)-tumors in mice.
Methods
Cells and mice
HeLa, 293, Renca (a cell line spontaneously derived from BALB/c renal cell adenocarcinoma), and NK cell-sensitive YAC-1 cells were cultured in DMEM or RPMI-1640 medium (Gibco-BRL) supplemented with 10% fetal bovine serum (FBS) and penicillin/streptomycin. Cultures were maintained in a 5% CO2 atmosphere at 37°C.
Male or female wild-type BALB/c mice, 7–8 weeks of age, were purchased from the animal breeding laboratory at the Korea Research Institute of Bioscience and Biotechnology. They were kept (five mice per cage) in isolation under specific pathogen-free conditions, exposed to 12-h light/12-h dark cycles, and provided with standard feed and water ad libitum.
Construction of replication-defective adenoviral vectors
cDNAs for Esherichia coli cytosine deaminase, p35 and/or p40 murine IL-12 subunits [48] or green fluorescent protein (GFP) were inserted by a standard cloning procedure into pX.dCMV.pA, an adeno-transfer plasmid harboring the immediate early gene promoter from human cytomegalovirus [49-51]. The shuttle plasmids were cotransfected into 293 cells together with pJM17, which harbors the genomic DNA of adenovirus 5 (Microbix, Canada), by a standard calcium phosphate method. Primary plaques were isolated and screened by PCR to ensure the presence of the inserts. Positive clones were plaque-purified twice and a single plaque was chosen for further amplification in 293 cells. Recombinant adenoviruses were purified by cesium chloride gradient centrifugation as previously described [49-51], dialyzed to remove the cesium chloride and frozen at -70°C.The viral titer was determined by a 293 plaque assay and expressed as plaque-forming units (pfu).
Cell viability assay
HeLa cells were plated on 60-mm dishes at 5 × 105 cells/plate and mock-transduced, or transduced with Ad.CD, for 2 h at a multiplicity of infection (MOI) of 50 in serum-free DMEM. Cultures were continued for a further 12 h. Transduced and non-transduced cells were then mixed in different ratios and incubated in 24-well dishes for 24 h. The culture media were replaced with fresh media containing various concentrations of 5-FC, and incubation was continued for 4 days. Cell viability was assessed by the trypan-blue exclusion assay.
Western blotting
HeLa cells were plated on 60-mm dishes at 5 × 105 cells/dish and transduced with recombinant adenoviruses in serum-free DMEM for 2 h. The culture media from mock- or virus-transduced cells were retained for measurement of released IL-12 at 48 h postinfection, and the cells were harvested in a lysis buffer (10 mM Tris-HCl, pH 7.5, 10 mM NaCl, 1.5 mM MgCl2, 10 mM β-mercaptoethanol). Cell extracts were prepared by three cycles of freezing (-70°C) and thawing and precleared by centrifugation. Fifty micrograms of precleared cell lysates were subjected to SDS-10% polyacrylamide gel electrophoresis (PAGE). The separated proteins were transferred to PVDF membranes, which were blocked with 3% bovine serum albumin (BSA) in phosphate-buffered saline (PBS) and incubated with rat anti-mouse IL-12 antibody (PharMingen), then with horseradish peroxidase-conjugated rabbit anti-rat lgG antibody (Sigma). Proteins were detected according to Amersham's ECL protocol. The culture supernatants were incubated with anti-IL-12 antibody. A suspension of protein G-Sepharose beads (100 μl) was added and the incubation mixtures were further incubated at 4°C for 12 h. The immunoprecipitates were washed three times with 40 mM N-2-hydroxyethylpiperazine-N'-2-ethanesulfonic acid, pH 7.4, 100 mM KCl, 0.1% NP-40, 0.1 mM DTT, and once with PBS, then immunoblotted with the rat anti-mouse IL-12 antibody described above.
Animal model and treatment
Tumors were generated on the flanks of BALB/c mice by subcutaneous (s.c.) injection of 1.5 × 105 of Renca cells in 0.1 ml of PBS. After visible tumors had developed for 7–9 days after inoculation, the mice were injected once intratumorally with recombinant adenoviruses at 1 × 109 pfu in 10 mM Tris-HCl, pH 7.4, 1 mM MgCl2, 10% glycerol. Animals undergoing 5-fluorocytosine therapy received intraperitoneal administration of 5-FC (400 mg/kg) daily for 10 days. Tumors were measured prior to virus injection and subsequently at intervals of 3 days. Linear calipers were used to measure the longest diameter (a), width (b), and depth (c). The tumor size was calculated by the formula: (a × b × c/2).
ELISA for IFN-γ
ELISAs were performed using essentially the reagents and procedures described in the Endogen (USA) product literature. Flat-bottomed 96-well microtiter plates (Nunc Maxisorp) were coated with rat anti-IFN-γ antibodies (1 μg/ml) at 4°C overnight and blocked with 4% BSA in PBS for 2 h at 37°C. Renca cells were treated with mitomycin C at 50 μg/ml for 20 min at 37°C. Splenocytes (2 × 106 cells/ml) obtained from the tumor-bearing mice 21 days after virus treatment were stimulated with the inactivated Renca cells in U-bottomed 96-well plates at an effector-to-stimulator ratio of 10:1. Supernatants (50 μl) from 24 h and 48 h cultures were added to the ELISA plate wells and incubated for 1 h. After several washing steps, rat anti-mouse IFN-γ antibody conjugated with biotin was added. Color was developed using avidin-conjugated horseradish peroxidase and OPD substrate (Sigma). The reaction was terminated by the addition of 2N H2SO4. The absorbance was measured at 490 nm with an ELISA plate reader. The amounts of IFN-γ were quantified by interpolation of a standard curve generated using known amounts of standard mouse rIFN-γ (Endogen). The biological activity of the IL-12 produced from the recombinant adenoviruses was assessed on the basis of its ability to induce IFN-γ secretion from murine splenocytes. Murine splenocytes (1.5 × 106 cells/well) were washed with cold medium and incubated with the culture supernatants. IFN-γ in the incubation media was then determined by an ELISA, as described above.
Cytotoxicity assay of NK cells
The cytolytic activity of NK cells was determined by a standard 4-h 51Cr-release assay. The spleens from dead mice obtained 21 days after tumor inoculation were removed aseptically and single-cell suspensions, prepared by passing the spleens through a metal mesh, were suspended in 5 ml of 0.83% ammonium chloride to lyse the red blood cells. The splenocytes were then used as effector cells to assay NK cell activity. YAC-1 cells (2 × 106) in 0.5 ml of RPMI-1640 with 20% FBS were labeled with 50 μCi of Na51CrO4 (Amersham) for 90 min. The labeled cells were washed three times with serum-free DMEM and mixed (1 × 104 per well) with the effector cells in a U-bottomed 96-well plate for 4 h at 37°C at three different effector-to-target ratios (100:1, 33:1, and 11:1), each in triplicate. The mixtures of target and effector cells were incubated for 4 h at 37°C. The percentage of specific 51Cr release was calculated as [(cpm experimental release - cpm spontaneous release/cpm maximum release - cpm spontaneous release)] × 100. The maximum 51Cr release was determined from the supernatant when labeled cells were lysed by adding 0.1 ml of 3% SDS. Spontaneous release was determined from the supernatants after labeled cells were incubated in 0.1 ml of medium without effector cells. The standard deviations for each triplicate sample and for spontaneous release were less than 10% and 20%, respectively.
Statistics
Statistical analysis was carried out using the Student's t test (unipolar, paired) and the chi-square test (two-tailed). The values were considered statistically significant when the P value was less than 0.05.
Results and discussion
Recombinant adenoviruses encoding the p35 and/or p40 subunits of murine IL-12 express bioactive IL-12
We constructed replication-defective adenoviruses containing the p35 and/or p40 subunits of murine IL-12 under the transcriptional control of the immediate early gene promoter of human cytomegalovirus (Figure 1). Ad.IL-12 contains murine cDNAs of both IL-12 subunits, which are linked by an internal ribosome entry site sequence from encephalomyocarditis virus. To test whether Ad.p40 and Ad.IL-12 express the p40 subunit and the p35-p40 heterodimer respectively, we transduced HeLa cells with the two constructs at the indicated MOI. Replication-defective adenovirus encoding GFP (Ad.GFP) was used as a control. Lysates of cells transduced with Ad.p40 or Ad.GFP were resolved by SDS-PAGE followed by immunoblotting with anti-IL-12 antibody, which reacts specifically with the p40 subunit of mouse IL-12 and with free p40 (Figure 2A, left panel). Ad.p40 was found to express p40. The culture media from cells transduced with Ad.IL-12 or Ad.GFP were immunoprecipitated with anti-IL-12 antibody. The immuno-complexes were resolved by SDS-PAGE under nonreducing conditions and immunoblotted with anti-IL-12 antibody. The two protein bands detected might be a p40 homodimer (p80) and a p35-p40 heterodimer (p70) (Figure 2A, right panel, indicated by arrows). Under nonreducing conditions, Ad.IL-12 produced a doublet of 79/75 kDa that was sensitive to a reducing agent [52]. Ad.p40 produces a band migrating with an apparent molecular mass of approximately 90 kDa, which on a reducing gel reveals a band consistent with the p40 monomer [53]. Thus, our result appeared to be consistent with previous findings. We could not assess p35 expression because no antibody specific for this subunit was available.
We next examined whether cells transduced with adenoviruses encoding the p35 and/or p40 subunits release bioactive IL-12. HeLa cells were mock-transduced, or transduced with a 1:1 (pfu ratio) mixture of Ad.p35 and Ad.p40, Ad.IL-12, or Ad.GFP at the indicated MOI, and the culture supernatants were collected after 24 h incubation. Splenocytes from naïve mice were incubated with equivalent volumes of the culture supernatants, and the IFN-γ contents of the medium were measured using ELISA (Figure 2B and 2C). The culture supernatants from cells transduced with a mixture of Ad.p35 and Ad.p40 or Ad.IL-12 exhibited much higher IFN-γ inducing-activity than the controls. These results suggest that cells transduced with Ad.p35 plus Ad.p40 or Ad.IL-12 release bioactive IL-12.
Recombinant adenovirus encoding cytosine deaminase (Ad.CD) expresses catalytically active cytosine deaminase
We constructed a replication-defective adenovirus encoding cytosine deaminase (Figure 1). To examine whether the Ad.CD virus expresses cytosine deaminase capable of converting 5-FC to cytotoxic 5-FU, we transduced HeLa cells with Ad.CD at an MOI of 50. Naïve HeLa or HeLa/CD cells, or mixtures of the two at the indicated ratios (Figure 3), were incubated in culture media without or with the indicated concentrations of 5-FC for 4 days, and cell viability was assessed by the trypan-blue exclusion assay (Figure 3). In the presence of 5-FC, the viability of the HeLa/CD cells decreased markedly but the naïve HeLa cells were unaffected, suggesting that cytosine deaminase was expressed in the virus-transduced cells and metabolized 5-FC to 5-FU. The viability of the mixtures of naïve and HeLa/CD cells appeared to decrease more than the proportion of naïve cells in the mixtures, particularly with 500 μg/ml 5-FC. Thus, the Ad.CD virus appeared to exert a bystander effect, though not a drastic one. The results suggest that Ad.CD expresses catalytically active cytosine deaminase.
Transfer of the IL-12 and cytosine deaminase genes in combination, followed by 5-FC treatment, exerts potent antitumor activity in Renca-tumor bearing mice
Renca-tumor bearing mice were established as described in the Methods section, randomly divided into 4 groups, and injected once intratumorally with Ad.GFP, Ad.CD/5-FC, Ad.p35 plus Ad.p40, or Ad.p35 plus Ad.p40 plus Ad.CD. Mice receiving Ad.CD were treated with 5-FC. Tumor growth was measured at the indicated times (Figure 4A). Mouse survival until day 42 was recorded (Figure 4B). The treatment outcomes are summarized in Table 1. Inhibition of tumor growth was most marked in mice treated with Ad.p35 plus Ad.p40 plus Ad.CD/5-FC (p < 0.001 for Ad.p35 plus Ad.p40 plus Ad.CD/5-FC vs Ad.GFP and p < 0.0053 for Ad.p35 plus Ad.p40 plus Ad.CD/5-FC vs Ad.CD/5-FC). The mean survival times were for 33.2 ± 10.4 days for Ad.p35 plus Ad.p40 plus Ad.CD/5-FC group and 27.2 ± 10.9 days for Ad.p35 plus Ad.p40 group; the difference is statistically significant (p < 0.0018). Among the 15 mice treated with Ad.p35 plus Ad.p40 plus Ad.CD/5-FC, four became tumor-free and four exhibited partial responses (Table 1). Among the 15 mice treated with Ad.p35 plus Ad.p40, one became tumor-free and two showed partial responses (p < 0.0464 for comparison of the two treatments). Ad.p35 plus Ad.p40 treatment appeared to be more effective than Ad.CD/5-FC, which had a modest antitumor effect compared to the control (Ad.GFP).
IL-12 and cytosine deaminase genes in combination, followed by 5-FC treatment, enhance the cytolytic activity of NK cells and increase IFN-γ production
We examined whether the increased antitumor activity of Ad.p35 plus Ad.p40 plus Ad.CD/5-FC (Figure 4) was associated with the induction of tumor-specific CTLs, activation of NK cells, and induction of Th1 cytokines such as IL-2 and IFN-γ. Effector cells were prepared from the splenocytes of tumor-bearing mice treated with the recombinant adenoviruses. Renca cells labeled with 51Cr were used as target cells. A standard 4-h 51chromium release assay was carried out. However, we did not detect specific lysis of the labeled Renca cells (data not shown). We performed an NK cell assay using the splenocytes as effector cells and YAC-1 cells labeled with 51Cr as target cells (Figure 5A). The effector cells from mice treated with Ad.p35 plus Ad.p40 plus Ad.CD/5-FC lysed the target cells about 10- and 5-fold more effectively than Ad.CD/5-FC and Ad.GFP, respectively, at a 100:1 effector-to-target cell ratio. Although Ad.p35 plus Ad.p40 treatment also increased NK cell activity compared to Ad.CD/5-FC or Ad.GFP, the cytolytic activity of splenic NK cells from mice treated with this mixture was lower than that from mice treated with Ad.p35 plus Ad.p40 plus Ad.CD/5-FC. The effector cells used in the NK cell assay were mainly splenocytes from mice in which the tumors were completely regressed or small. This may account for the increased NK cell activity in the Ad.p35 plus Ad.p40 plus Ad.CD/5-FC treatment group compared to the Ad.p35 plus Ad.p40 treatment group.
We next examined whether the virus treatments induced Th1 cytokines, which may represent innate and/or adaptive immune responses. Splenocytes from tumor-bearing mice treated with the viruses were incubated with inactivated Renca cells. The IL-2 and IFN-γ contents of the culture supernatants were measured by ELISA 24 and 48 h after incubation, respectively. We detected no IL-2 induction in splenocytes from any of the treatment groups (data not shown). However, IFN-γ production was about twice as great in splenocytes from mice treated with Ad.p35 plus Ad.p40 plus Ad.CD/5-FC as in those treated with Ad.CD/5-FC or Ad.GFP (Figure 5B, p < 0.0179 and < 0.0394 for Ad.p35 + Ad.p40 + Ad.CD/5-FC vs Ad.GFP and Ad.CD/5-FC, respectively). Ad.p35 plus Ad.p40 treatment also increased IFN-γ, but its effectiveness was significantly less than that of Ad.p35 plus Ad.p40 plus Ad.CD/5-FC (p < 0.0076). The results suggest that Ad.p35 plus Ad.p40 treatment, but not Ad.CD/5-FC, may enhance NK cell activity and stimulate IFN-γ production. Thus, the enhancement of NK cell activity may be partially responsible for the inhibition of tumor growth by treatment with Ad.p35 plus Ad.p40 plus Ad.CD/5-FC or with Ad.p35 plus Ad.p40.
The rapid tumor cell killing effect induced by suicide gene products induces a strong antitumor immune response, such as induction of tumor-specific CTLs and increased NK cell activity [54-57]. However, we detected neither a tumor-specific T cell immune response nor an enhanced NK cell activity after Ad.CD/5-FC treatment alone. It is possible that the antitumor activity of the Ad.CD constructed here was so weak that the tumor cells were not killed rapidly (Figure 4). However, this is unlikely, because Ad.CD/5-FC treatment increased the antitumor activity of Ad.IL-12 (see Figure 6B and 6C). Alternatively, the bystander effect, which kills neighboring tumor cells not expressing suicide genes, may have exerted a negative effect on the generation of tumor-specific CTL and/or active NK cells. Immune cells or antigen-presenting cells located close to the tumor cells could have taken up, and been killed by, the toxic metabolites generated by the suicide gene products. This may explain why the NK cell activity in Ad.CD-treated mice was significantly lower than in Ad.GFP-treated mice (Figure 5A, p < 0.001).
Transfer of the cytosine deaminase gene followed by 5-FC treatment increases the antitumor effectiveness of IL-12 gene transfer in Renca-tumor bearing mice
Since a mixture of Ad.p35 and Ad.p40 was used in previous experiments (Figure 4), we examined whether Ad.IL-12, containing p35 and p40 in a single adenoviral vector (Figure 1), was more effective against the tumors when combined with Ad.CD/5-FC. Renca-tumor bearing mice were divided randomly into four groups, treated intratumorally with (1) Ad.IL-12 plus Ad.CD/5-FC, (2) Ad.IL-12, (3) Ad.CD/5-FC, or (4) Ad.GFP (control). Tumor sizes were measured at the indicated times (Figure 6A). There was a significant inhibition of tumor growth in mice treated with Ad.IL-12 plus Ad.CD/5-FC compared to Ad.GFP (p < 0.0456). The effectiveness of Ad.IL-12 (5 × 108 pfu) plus Ad.CD/5-FC (5 × 108 pfu) appeared to be similar to that of Ad.IL-12 (1 × 109 pfu) alone. This contrasts with the effectiveness of Ad.p35 plus Ad.p40 plus Ad.CD/5-FC as compared to Ad.p35 plus Ad.p40 (Figure 4). Presumably the in vivo gene delivery of the Ad.p35-Ad.p40 mixture was not so efficient as that of Ad.IL-12.
We further examined whether CD gene transfer followed by 5-FC treatment increased the antitumor effectiveness of IL-12 gene transfer. Sixteen Renca tumor-bearing mice were divided into 2 groups. Since a higher dose than 1 × 109 pfu of adenoviral vector appeared to be toxic to the mice, the total dose given was 1 × 109 pfu. Mice in each group received Ad.IL-12 (5 × 108 pfu) with either Ad.CD (5 × 108 pfu) or Ad.GFP (5 × 108 pfu) as a control. Both groups were treated with 5-FC for 10 days. Tumor sizes were measured at the indicated times (Figure 6B). Combined transfer of the IL-12 and CD/5-FC genes resulted in significant inhibition of tumor growth compared to IL-12 gene transfer alone (p < 0.0301). Six of the 8 mice treated with Ad.IL-12 plus Ad.CD/5-FC, but only 4 of the 8 mice treated with Ad.IL-12 plus Ad.GFP/5-FC, became tumor-free and survived at 88 days. The mean survival times were 80.5 ± 20.8 days for the Ad.IL-12 + Ad.CD/5-FC group and 67.3 ± 28.3 days for the Ad.IL-12 + Ad.GFP/5-FC group; the difference is statistically significant (p < 0.0368).
Conclusion
Among various cancer gene therapies, immunogene therapy is a promising but challenging modality. Recent clinical trials using Ad.IL-12 have shown that intratumoral IL-12 gene transfer is a feasible and well-tolerated procedure but exerts only mild antitumor effects [24]. An increased Ad.IL-12 dose may increase the antitumor efficacy but might entail a systemic, toxic effect that would limit the use of Ad.IL-12 alone. In this study we have attempted to improve the antitumor efficacy in Renca tumor-bearing mice by using adenoviral vectors to transfer the IL-12 gene in combination with cytosine deaminase, followed by 5-FC treatment. The results show a marked inhibition of tumor growth and significant prolongation of survival time, suggesting that IL-12 plus CD gene transfer followed by 5-FC treatment may be an alternative modality for the human cancer treatment.
Abbreviations
Ad: adenovirus; IL-12: interleukin-12; CD: cytosine deaminase; 5-FC: 5-fluorocytosine; DMEM: Dulbecco's Modified Eagle's Medium.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
Cho W-K and Yoo J constructed the adenoviral vectors and analyzed the functionality of the expressed gene products. Hwang K-S, Yun H-J, and Kim S performed the tumor growth studies in the animal model, and the immunological assays with murine splenocytes. Im DS drafted the manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
We are grateful to Yong J. Lee at University of Pittsburgh School of Medicine, Pittsburgh, PA, USA, for providing us with cytosine deaminase. This study was supported by a grant from the KRIBB Initiative Program, a grant from the 21C FrontierFunctional Genome Project from the Ministry of Science and Technology, Republic of Korea, and a grant from Samyang Genex Biotech Research Institute.
Figures and Tables
Figure 1 Schematic illustration of replication-defective adenoviral vectors constructed in this study. The E1 region of adenovirus type 5 (Ad 5) was replaced by the indicated genes under the transcriptional control of the immediate early gene promoter from human cytomegalovirus (pCMV). IRES; internal ribosomal entry sequence.
Figure 2 The recombinant adenoviruses encoding murine p35 and/or p40 subunits express biologically active IL-12. (A) HeLa cells were transduced with Ad.GFP, Ad.p40, or Ad.IL-12 at the indicated MOIs. Cells or culture media were harvested 48 h after transduction. Cleared lysates of cells transduced with Ad.GFP or Ad.p40 were immunoblotted with anti-IL-12 antibody (left panel). The culture media from HeLa cells transduced with Ad.IL-12 or Ad.GFP were immunoprecipitated with anti-IL-12 antibody. The immunoprecipitates were dissolved in SDS sample buffer without reducing agent and subjected to SDS-PAGE, followed by immunoblotting with anti-IL-12 antibody (right panel). Molecular size markers in kilodaltons are shown at the left. The positions of p40, p35–p40 heterodimer (p70) and p40 homodimer (p80) are indicated by arrows. (B and C) HeLa cells were mock-transduced or transduced with either a 1:1 (pfu ratio) mixture of Ad.p35 and Ad.p40, or Ad.IL-12, or Ad.GFP, at the indicated MOI. Splenocytes from naïve mice were incubated with the culture supernatants for 24 h. ELISA was performed to determine the IFN-γ levels after incubation. Data are means ± SD of two independent experiments, each performed in duplicate.
Figure 3 Ad.CD virus expresses functional cytosine deaminase. HeLa cells were transduced with Ad.CD at an MOI of 50 and incubated for 12 h. These cells (HeLa/CD) were then mixed with naïve HeLa cells at the indicated ratios. The HeLa/CD, HeLa, or mixed cells were incubated on 24-well dishes for 24 h, then treated with 5-FC at the indicated concentrations for 4 days. Cell viability was assessed by the trypan-blue exclusion assay. Data are means ± SD of two independent experiments, each performed in duplicate.
Figure 4 The antitumor activity effected by IL-12 gene transfer increases in vivo when combined with cytosine deaminase/5-FC. (A) Renca tumors were established in BALB/c mice by s.c. inoculation of 1.5 × 105 cells. When the tumors reached 5–6 mm diameter, the animals were randomly divided into four treatment groups (n = 15 per group) and injected once intratumorally with (1) Ad.p35 (2.5 × 108 pfu) plus Ad.p40 (2.5 × 108 pfu) plus Ad.CD (5 × 108 pfu), or (2) Ad.p35 (5 × 108 pfu) and Ad.p40 (5 × 108 pfu), or (3) Ad.CD (1 × 109 pfu), or (4) Ad.GFP (1 × 109 pfu). Mice treated with Ad.CD were given 5-FC (400 mg/kg) intraperitoneally daily for 10 days. Graphic representations of mean tumor growth rates are shown. Bars indicate SD. (B) Mouse survival until day 42 was recorded. Mice were sacrificed and considered as death when tumor size exceeded 1.5 cm in long and short axes. The mean survival times (± SD) were 33.2 ± 10.4 days for (1) group, 27.2 ± 10.9 days for (2) group, 21.9 ± 9.1 days for (3) group, and 19.7 ± 7.1 days for (4) group. The difference between (1) and (2) groups was statistically significant (p < 0.0018) by Student's t test. The treatment outcome is summarized in Table 1. One animal in each of the groups treated with Ad.CD and Ad.GFP succumbed to toxicity, and two mice in the group treated with Ad.p35 plus Ad.p40 were excluded owing to peritoneal metastasis.
Figure 5 IL-12 gene transfer combined with Ad.CD/5-FC increases splenic NK cell activity and IFN-γ production. (A) Cytotoxicity of NK cells in Renca tumor-bearing mice treated with various adenoviral vectors (see Figure 4 legend). Mice in which tumor growth was completely or partially inhibited were chosen from the treatment groups on day 21 after tumor cell inoculation. Splenocytes were isolated from the treated mice (n = 3 per group) and used as effector cells. A standard 4-h 51Cr release assay was performed using YAC-1 cells labeled with 51Cr as target cells. The percentage specific lysis was determined. Data are means ± SD. (B) Mouse splenocytes (n = 3 per group) were isolated from the treatment groups on day 21 as described above, and incubated with Renca cells inactivated by pretreatment with 50 μg/ml mitomycin C for 20 min at 37°C. Culture supernatants were obtained from the incubated cells at the indicated times. Amounts of IFN-γ in the supernatants were measured using ELISA. Bars represent mean ± SD.
Figure 6 CD gene transfer followed by 5-FC treatment increases the antitumor effectiveness of IL-12 gene transfer. (A) Mice with tumors were established by subcutaneous inoculation of 1.5 × 105 cells of Renca. The experimental animals in which tumors reached a diameter of about 5 mm were randomly divided into 4 treatment groups (n = 7 per group) and injected once intratumorally (day 0) with Ad.IL-12 (5 × 108 pfu) plus Ad.CD (5 × 108 pfu), or 1 × 109 pfu of Ad.IL-12, or Ad.CD, or Ad.GFP. Mice treated with Ad.CD were given intraperitoneal 5-FC (400 mg/kg) daily for 10 days. Tumor growth was measured at intervals of three days until day 21. Graphic representations of mean tumor growth rates are shown. (B) and (C) Renca tumor-bearing mice were divided into two groups (n = 8 per group), which received single intratumorally injections (day 0) of Ad.IL-12 (5 × 108 pfu) plus Ad.CD (5 × 108 pfu) or Ad.IL-12 (5 × 108 pfu) plus Ad.GFP (5 × 108 pfu). Mice in both groups were given intraperitoneal 5-FC (400 mg/kg) daily for 10 days. Tumor growth was measured at the indicated times until day 25. Graphic representations of mean tumor growth rates are shown (B). Mouse survival until day 88 was recorded (C). The mean survival times (± SD) were 80.5 ± 20.8 days for the Ad.IL-12 plus Ad.CD/5-FC group and 67.3 ± 28.3 days for the Ad.IL-12 plus Ad.GFP/5-FC group. The difference between these mean survival times was statistically significant (p < 0.0368) by Student's t test.
Table 1 Tumor regression following intratumoral injection of Ad.p35 plus Ad.p40, or Ad.CD/5-FC alone, or a combination of both
Treatment Response (%)
N Complete Partial Death or peritoneal metastasis None
Ad.p35 + Ad.p40 + Ad.CD/5-FC 15 4 (27) 4 (27) 0 (0) 7 (46)
Ad.p35 + Ad.p40 15 1 (7) 2 (14) ‡2 (13) 10 (66)
Ad.CD/5-FC 15 1 (7) 0 (0) †1 (7) 13 (86)
Ad.GFP 15 0 (0) 0 (0) †1 (7) 14 (93)
N = number of Renca tumor-bearing mice injected once intratumorally with adenoviral vectors at the doses indicated in Figure 4 legend.
"Complete" refers to animals undergoing total and permanent regression of the injected tumor.
"Partial" refers to animals undergoing partial tumor regression followed by regrowth, or a significant delay in growth
"Death or peritoneal metastasis" refers to animals that died or had peritoneal metastasis during the period of investigation.
None refers to animals whose tumors have continued to grow at a rate comparable to controls.
†Death probably by toxicity.
‡Excluded due to peritoneal metastasis during the experiment.
==== Refs
Chen SH Chen XH Wang Y Kosai K Finegold MJ Rich SS Woo SL Combination gene therapy for liver metastasis of colon carcinoma in vivo Proc Natl Acad Sci U S A 1995 92 2577 2581 7708688
Chen SH Kosai K Xu B Pham-Nguyen K Contant C Finegold MJ Woo SL Combination suicide and cytokine gene therapy for hepatic metastases of colon carcinoma: sustained antitumor immunity prolongs animal survival Cancer Res 1996 56 3758 3762 8706021
Felzmann T Ramsey WJ Blaese RM Characterization of the antitumor immune response generated by treatment of murine tumors with recombinant adenoviruses expressing HSVtk, IL-2, IL-6 or B7-1 Gene Ther 1997 4 1322 1329 9472556 10.1038/sj.gt.3300533
Cao X Ju DW Tao Q Wang J Wan T Wang BM Zhang W Hamada H Adenovirus-mediated GM-CSF gene and cytosine deaminase gene transfer followed by 5-fluorocytosine administration elicit more potent antitumor response in tumor-bearing mice Gene Ther 1998 5 1130 1136 10326037 10.1038/sj.gt.3300727
Ju DW Wang BM Cao X Adenovirus-mediated combined suicide gene and interleukin-2 gene therapy for the treatment of established tumor and induction of antitumor immunity J Cancer Res Clin Oncol 1998 124 683 689 9879829 10.1007/s004320050232
Drozdzik M Qian C Xie X Peng D Bilbao R Mazzolini G Prieto J Combined gene therapy with suicide gene and interleukin-12 is more efficient than therapy with one gene alone in a murine model of hepatocellular carcinoma J Hepatol 2000 32 279 286 10707868 10.1016/S0168-8278(00)80073-2
Toda M Martuza RL Rabkin SD Combination suicide/cytokine gene therapy as adjuvants to a defective herpes simplex virus-based cancer vaccine Gene Ther 2001 8 332 339 11313808 10.1038/sj.gt.3301392
Nakamori M Iwahashi M Ueda K Tsunoda T Terasawa H Hamada H Yamaue H Dose of adenoviral vectors expressing interleukin-2 plays an important role in combined gene therapy with cytosine deaminase/5-fluorocytosine: preclinical consideration Jpn J Cancer Res 2002 93 706 715 12079520
Goto T Nishi T Kobayashi O Tamura T Dev SB Takeshima H Kochi M Kuratsu J Sakata T Ushio Y Combination electro-gene therapy using herpes virus thymidine kinase and interleukin-12 expression plasmids is highly efficient against murine carcinomas in vivo Mol Ther 2004 10 929 37 15509510 10.1016/j.ymthe.2004.07.028
Kobayashi M Fitz L Ryan M Hewick RM Clark SC Chan S Loudon R Sherman F Perussia B Trinchieri G Identification and purification of natural killer cell stimulatory factor (NKSF), a cytokine with multiple biologic effects on human lymphocytes J Exp Med 1989 170 827 845 2504877 10.1084/jem.170.3.827
Wolf SF Temple PA Kobayashi M Young D Dicig M Lowe L Dzialo R Fitz L Ferenz C Hewick RM Cloning of cDNA for natural killer cell stimulatory factor, a heterodimeric cytokine with multiple biologic effects on T and natural killer cells J Immunol 1991 146 3074 3081 1673147
Wolf SF Sieburth D Sypek J Interleukin 12: A key modulator of immune function Stem Cells 1994 12 154 168 7911046
Brunda MJ Role of IL12 as an anti-tumour agent: current status and future directions Res Immunol 1995 146 622 628 8839170 10.1016/0923-2494(96)83040-9
Ma X Trinchieri G Regulation of interleukin-12 production in antigen-presenting cells Adv Immunol 2001 79 55 92 11680011
Atkins MB Robertson MJ Gordon M Lotze MT DeCoste M DuBois JS Ritz J Sandler AB Edington HD Garzone PD Mier JW Canning CM Battiato L Tahara H Sherman ML Phase I evaluation of intravenous recombinant human interleukin 12 in patients with advanced malignancies Clin Cancer Res 1997 3 409 417 9815699
Robertson MJ Cameron C Atkins MB Gordon MS Lotze MT Sherman ML Ritz J Immunological effects of interleukin 12 administered by bolus intravenous injection to patients with cancer Clin Cancer Res 1999 5 9 16 9918197
Leonard JP Sherman ML Fisher GL Buchanan LJ Larsen G Atkins MB Sosman JA Dutcher JP Vogelzang NJ Ryan JL Effects of single-dose interleukin-12 exposure on interleukin-12-associated toxicity and interferon-gamma production Blood 1997 90 2541 2548 9326219
Golab J Zagozdzon R Antitumor effects of interleukin-12 in pre-clinical and early clinical studies Int J Mol Med 1999 3 537 544 10202188
van Herpen CM Looman M Zonneveld M Scharenborg N de Wilde PC van de Locht L Merkx MA Adema GJ de Mulder PH Intratumoral administration of recombinant human interleukin 12 in head and neck squamous cell carcinoma patients elicits a T-helper 1 profile in the locoregional lymph nodes Clin Cancer Res 2004 10 2626 2635 15102664
Burke F Cytokines (IFNs, TNF-alpha, IL-2 and IL-12) and animal models of cancer Cytokines Cell Mol Ther 1999 5 51 61 10390079
Shurin MR Esche C Peron JM Lotze MT Antitumor activities of IL-12 and mechanisms of action Chem Immunol 1997 68 153 174 9329221
Barajas M Mazzolini G Genove G Bilbao R Narvaiza I Schmitz V Sangro B Melero I Qian C Prieto J Gene therapy of orthotopic hepatocellular carcinoma in rats using adenovirus coding for interleukin 12 Hepatology 2001 33 52 61 11124820 10.1053/jhep.2001.20796
Chada S Ramesh R Mhashilkar AM Cytokine- and chemokine-based gene therapy for cancer Curr Opin Mol Ther 2003 5 463 474 14601514
Sangro B Mazzolini G Ruiz J Herraiz M Quiroga J Herrero I Benito A Larrache J Pueyo J Subtil JC Olague C Sola J Sadaba B Lacasa C Melero I Qian C Prieto J Phase I trial of intratumoral injection of an adenovirus encoding interleukin-12 for advanced digestive tumors J Clin Oncol 2004 22 1389 1397 15084613 10.1200/JCO.2004.04.059
Beltinger C Uckert W Debatin KM Suicide gene therapy for pediatric tumors J Mol Med 2001 78 598 612 11269507 10.1007/s001090000175
Yazawa K Fisher WE Brunicardi FC Current progress in suicide gene therapy for cancer World J Surg 2002 26 783 789 11948367 10.1007/s00268-002-4053-5
Moolten FL Tumor chemosensitivity conferred by inserted herpes thymidine kinase genes: paradigm for a prospective cancer control strategy Cancer Res 1986 46 5276 5281 3019523
Austin EA Huber BE A first step in the development of gene therapy for colorectal carcinoma: cloning, sequencing, and expression of Escherichia coli cytosine deaminase Mol Pharmacol 1993 43 380 387 8450832
Kilstrup M Meng LM Neuhard J Nygaard P Genetic evidence for a repressor of synthesis of cytosine deaminase and purine biosynthesis enzymes in Escherichia coli J Bacteriol 1989 171 2124 2127 2539360
Mullen CA Kilstrup M Blaese RM Transfer of the bacterial gene for cytosine deaminase to mammalian cells confers lethal sensitivity to 5-fluorocytosine: a negative selection system Proc Natl Acad Sci U S A 1992 89 33 37 1729703
Schilsky RL Biochemical and clinical pharmacology of 5-fluorouracil Oncology 1998 12 13 18 9830619
Freeman SM Abboud CN Whartenby KA Packman CH Koeplin DS Moolten FL Abraham GN The "bystander effect": tumor regression when a fraction of the tumor mass is genetically modified Cancer Res 1993 53 5274 5283 8221662
Huber BE Austin EA Richards CA Davis ST Good SS Metabolism of 5-fluorocytosine to 5-fluorouracil in human colorectal tumor cells transfectd with the cytosine deaminase gene: significant antitumor effects when only a small percentage of tumor cells express cytosine deaminase Proc Natl Acad Sci U S A 1994 91 8302 8306 8058798
Wygoda MR Wilson MR Davis MA Trosko JE Rehemtulla A Lawrence TS Protection of herpes simplex virus thymidine kinase-transfectd cells from ganciclovir-mediated cytotoxicity by bystander cells: the Good Samaritan effect Cancer Res 1997 57 1699 1703 9135011
Kievit E Nyati MK Ng E Stegman LD Parsels J Ross BD Rehemtulla A Lawrence TS Yeast cytosine deaminase improves radiosensitization and bystander effect by 5-fluorocytosine of human colorectal cancer xenografts Cancer Res 2000 60 6649 6655 11118048
Crystal RG Hirschowitz E Lieberman M Daly J Kazam E Henschke C Yankelevitz D Kemeny N Silverstein R Ohwada A Russi T Mastrangeli A Sanders A Cooke J Harvey BG Phase I study of direct administration of a replication deficient adenovirus vector containing the E. coli cytosine deaminase gene to metastatic colon carcinoma of the liver in association with the oral administration of the pro-drug 5-fluorocytosine Hum Gene Ther 1997 8 985 1001 9195221
Pandha HS Martin LA Rigg A Hurst HC Stamp GW Sikora K Lemoine NR Genetic prodrug activation therapy for breast cancer: A phase I clinical trial of erbB-2-directed suicide gene expression J Clin Oncol 1999 17 2180 2189 10561274
Nemunaitis J Cunningham C Senzer N Kuhn J Cramm J Litz C Cavagnolo R Cahill A Clairmont C Sznol M Pilot trial of genetically modified, attenuated Salmonella expressing the E. coli cytosine deaminase gene in refractory cancer patients Cancer Gene Ther 2003 10 737 744 14502226 10.1038/sj.cgt.7700634
Izquierdo M Martin V de Felipe P Izquierdo JM Perez-Higueras A Cortes ML Paz JF Isla A Blazquez MG Human malignant brain tumor response to herpes simplex thymidine kinase (HSVtk)/ganciclovir gene therapy Gene Ther 1996 3 491 495 8789798
Stockhammer G Brotchi J Leblanc R Bernstein M Schackert G Weber F Ostertag C Mulder NH Mellstedt H Seiler R Yonekawa Y Twerdy K Kostron H De Witte O Lambermont M Velu T Laneuville P Villemure JG Rutka JT Warnke P Laseur M Mooij JJ Boethius J Mariani L Gianella-Borradori A Gene therapy for glioblastoma multiform: in vivo tumor transduction with the herpes simplex thymidine kinase gene followed by ganciclovir J Mol Med 1997 75 300 304 9151217 10.1007/s001090050116
Ram Z Culver KW Oshiro EM Viola JJ DeVroom HL Otto E Long Z Chiang Y McGarrity GJ Muul LM Katz D Blaese RM Oldfield EH Therapy of malignant brain tumors by intratumoral implantation of retroviral vector-producing cells Nat Med 1997 3 1354 1361 9396605 10.1038/nm1297-1354
Klatzmann D Cherin P Bensimon G Boyer O Coutellier A Charlotte F Boccaccio C Salzmann JL Herson S A phase I/II dose-escalation study of herpes simplex virus type 1 thymidine kinase "suicide" gene therapy for metastatic melanoma. Study Group on Gene Therapy of Metastatic Melanoma Hum Gene Ther 1998 9 2585 2594 9853525 10.1089/10430349850019427
Shand N Weber F Mariani L Bernstein M Gianella-Borradori A Long Z Sorensen AG Barbier N A phase 1–2 clinical trial of gene therapy for recurrent glioblastoma multiforme by tumor transduction with the herpes simplex thymidine kinase gene followed by ganciclovir. GLI328 European-Canadian Study Group Hum Gene Ther 1999 10 2325 2335 10515452 10.1089/10430349950016979
Packer RJ Raffel C Villablanca JG Tonn JC Burdach SE Burger K LaFond D McComb JG Cogen PH Vezina G Kapcala LP Treatment of progressive or recurrent pediatric malignant supratentorial brain tumors with herpes simplex virus thymidine kinase gene vector-producer cells followed by intravenous ganciclovir administration Neurosurg 2000 92 249 254
Sandmair AM Loimas S Puranen P Immonen A Kossila M Puranen M Hurskainen H Tyynela K Turunen M Vanninen R Lehtolainen P Paljarvi L Johansson R Vapalahti M Yla-Herttuala S Thymidine kinase gene therapy for human malignant glioma, using replication-deficient retroviruses or adenoviruses Hum Gene Ther 2000 11 2197 2205 11084677 10.1089/104303400750035726
Rainov NG A phase III clinical evaluation of herpes simplex virus type 1 thymidine kinase and ganciclovir gene therapy as an adjuvant to surgical resection and radiation in adults with previously untreated glioblastoma multiforme Human Gene Ther 2000 11 2389 2401 11096443 10.1089/104303400750038499
Smitt PS Driesse M Wolbers J Kros M Avezaat C Treatment of relapsed malignant glioma with an adenoviral vector containing the herpes simplex thymidine kinase gene followed by ganciclovir Mol Ther 2003 7 851 858 12788659 10.1016/S1525-0016(03)00100-X
Park J-H Chang S-H Lee K-M Lee H-K Murine sarcoma cells transfected with interleukin-12 are rejected in vivo inducing protective and curative immune response against the parental cells Mol Cells 1995 5 595 564
Seong YR Choi S Lim JS Lee CH Lee CK Im DS Immunogenicity of the E1E2 proteins of hepatitis C virus expressed by recombinant adenoviruses Vaccine 2001 19 2955 2964 11282207 10.1016/S0264-410X(00)00534-X
Hwang KS Cho WK Yoo J Seong YR Kim BK Kim S Im DS Adenovirus-mediated interleukin-18 mutant in vivo gene transfer inhibits tumor growth through the induction of T cell immunity and activation of natural killer cell cytotoxicity Cancer Gene Ther 2004 11 397 407 15044962 10.1038/sj.cgt.7700711
Cho WK Seong YR Lee YH Kim MJ Hwang K-S Yoo J Choi S Jung CR Im DS Oncolytic effect of adenovirus mutant capable of replicating in hypoxic and normoxic regions of solid tumor Mol Ther 2004 10 938 949 15509511 10.1016/j.ymthe.2004.07.023
Bramson J Hitt M Gallichan WS Rosenthal KL Gauldie J Graham FL Construction of a double recombinant adenovirus vector expressing a heterodimeric cytokine: in vitro and in vivo production of biologically active interleukin-12 Hum Gene Ther 1996 7 333 342 8835220
Chen L Chen D Block E O'Donnell M Kufe DW Clinton SK Eradication of murine bladder carcinoma by intratumor injection of a bicistronic adenoviral vector carrying cDNAs for the IL-12 heterodimer and its inhibition by the IL-12 p40 subunit homodimer J Immunol 1997 159 351 359 9200473
Vile RG Nelson JA Castleden S Chong H Hart IR Systemic gene therapy of murine melanoma using tissue specific expression of the HSVtk gene involves an immune component Cancer Res 1994 54 6228 6234 7954471
Consalvo M Mullen CA Modesti A Musiani P Allione A Cavallo F Giovarelli M Forni G 5-Fluorocytosine-induced eradication of murine adenocarcinomas engineered to express the cytosine deaminase suicide gene requires host immune competence and leaves an efficient memory J Immunol 1995 154 5302 5312 7730633
Pavlovic J Nawrath M Tu R Heinicke T Moelling K Anti-tumor immunity is involved in the thymidine kinase-mediated killing of tumors induced by activated Ki-ras(G12V) Gene Ther 1996 3 635 643 8818652
Freeman SM Ramesh R Marrogi AJ Immune system in suicide-gene therapy Lancet 1997 349 2 3 8988108 10.1016/S0140-6736(97)22001-5
| 15910693 | PMC1168891 | CC BY | 2021-01-04 16:03:03 | no | BMC Cancer. 2005 May 24; 5:51 | utf-8 | BMC Cancer | 2,005 | 10.1186/1471-2407-5-51 | oa_comm |
==== Front
BMC GenomicsBMC Genomics1471-2164BioMed Central London 1471-2164-6-781591891410.1186/1471-2164-6-78Research ArticleA new approach for the analysis of bacterial microarray-based Comparative Genomic Hybridization: insights from an empirical study Taboada Eduardo N [email protected] Rey R [email protected] Christian C [email protected] Wendy A [email protected] John HE [email protected] Pathogen Genomics Group, Institute for Biological Sciences, National Research Council, 100 Sussex Drive, Ottawa, Ontario, K1A 0R6, Canada2005 27 5 2005 6 78 78 16 2 2005 27 5 2005 Copyright © 2005 Taboada et al; licensee BioMed Central Ltd.2005Taboada et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Microarray-based Comparative Genomic Hybridization (M-CGH) has been used to characterize the extensive intraspecies genetic diversity found in bacteria at the whole-genome level. Although conventional microarray analytical procedures have proved adequate in handling M-CGH data, data interpretation using these methods is based on a continuous character model in which gene divergence and gene absence form a spectrum of decreasing gene conservation levels. However, whereas gene divergence may yet be accompanied by retention in gene function, gene absence invariably leads to loss of function. This distinction, if ignored, leads to a loss in the information to be gained from M-CGH data.
We present here results from experiments in which two genome-sequenced strains of C. jejuni were compared against each other using M-CGH. Because the gene content of both strains was known a priori, we were able to closely examine the effects of sequence divergence and gene absence on M-CGH data in order to define analytical parameters for M-CGH data interpretation. This would facilitate the examination of the relative effects of sequence divergence or gene absence in comparative genomics analyses of multiple strains of any species for which genome sequence data and a DNA microarray are available.
Results
As a first step towards improving the analysis of M-CGH data, we estimated the degree of experimental error in a series of experiments in which identical samples were compared against each other by M-CGH. This variance estimate was used to validate a Log Ratio-based methodology for identification of outliers in M-CGH data. We compared two genome strains by M-CGH to examine the effect of probe/target identity on the Log Ratios of signal intensities using prior knowledge of gene divergence and gene absence to establish Log Ratio thresholds for the identification of absent and conserved genes.
Conclusion
The results from this empirical study validate the Log Ratio thresholds that have been used in other studies to establish gene divergence/absence. Moreover, the analytical framework presented here enhances the information content derived from M-CGH data by shifting the focus from divergent/absent gene detection to accurate detection of conserved and absent genes. This approach closely aligns the technical limitations of M-CGH analysis with practical limitations on the biological interpretation of comparative genomics data.
==== Body
Background
Comparison of intraspecies multi-strain bacterial genome sequence data has shown that, even over short evolutionary time scales, genome evolution is dominated by gene insertions/deletions and gene divergence [1-4]. Genome levels of intraspecies genetic diversity must be examined if we are to gain a better understanding of genome evolution [5] and if we are to maximize the practical use of bacterial genome sequence information, for instance for development of technical applications, e.g., vaccine or drug development.
One of the aims of bacterial intraspecies comparative genomics is to determine the overall genetic similarity between strains. Where sequence information is available, this type of analysis relies heavily on sequence homology and centres on the determination of conserved genes, strain-specific (i.e. unique) genes and, where the sequence provides unambiguous evidence, determination of orthologous and paralogous genes [6-9]. Although it has become increasingly apparent that obtaining the sequence of multiple strains per species is highly desirable, currently these types of datasets are limited in number. In their absence, other methods for performing comparative genomics have been developed. Among them, microarray-based comparative genomic hybridization (M-CGH) based on genome-sequenced strains has shown enormous potential [10-12].
Two different microarray-based approaches have been used to study the genetic composition of unknown bacterial strains. In the first approach, a control genome-sequenced strain was used as a reference to generate the probes for a microarray [13-16]. In the second approach, microarray probes were derived from the tester strain, either from a tester-derived shotgun library or a library enriched for tester-specific DNAs [17]. With either approach, control- and tester-derived targets are co-hybridized to the microarray and control- and tester-derived signals are compared, often by computing the Log Ratio (LR) = log2(tester signal/control signal). Whereas genes with similar signal in either channel are expected to have LRs near zero, genes with LRs that deviate significantly from LR = 0 are likely to show copy number changes or sequence divergence between control and tester strains.
The relatively small number of studies on bacterial M-CGH has demonstrated the power of the method in a comparative genomics context despite a lack of consensus in current methods for analyzing M-CGH data. Although potential methods for standardizing and improving analysis have been suggested [15,18] in practice, M-CGH data has routinely been analyzed by categorizing genes into two groups: genes that are likely to be conserved and genes that are likely to be divergent. One notable problem with this approach is that no attempt is made to differentiate between gene divergence and gene absence, despite the significant biological and evolutionary differences implied by these two types of events. A framework for improved analysis would require empirical data on the relationship between Log Ratio (LR) from M-CGH experiments and sequence conservation levels, however, to our knowledge no studies exist that have directly examined this question.
The availability of intraspecies genome data from two strains of Campylobacter jejuni [19,20], has provided us with the opportunity to examine the quantitative relationship between the LR and probe/target identity (PTI) using our C. jejuni microarray. This experimental design allows us to directly match microarray results to the a priori interpretation of gene divergence and gene absence patterns. The goal of this study is to define the analytical parameters for the accurate prediction of gene conservation levels, leading to improved interpretation of M-CGH data. We present here the results of a detailed analysis of M-CGH experiments using the two genome-sequenced strains of C. jejuni.
Results and discussion
Determination of technical variation in M-CGH experiments
In order to examine the Log Ratio (LR) distributions where no differential signals are expected, we performed control experiments in which dual-labelled NCTC 11168 (or RM1221) DNA was tested in a series of self-self M-CGH experiments. Although our microarray is based on strain NCTC 11168 the resulting LRs should remain close to zero because, regardless of the strain used in the self-self experiment, "Control" and "Tester" targets are identical. Thus, any observed deviation from this result is likely due to technical variability in the assay and can be used to determine a threshold for statistically significant differential signals (i.e., outliers). The LR distribution in six replicates follows a normal distribution with a mean LR for six replicates of ~0.01 ± 0.22 (Figure 1) and, as expected, the mean and standard deviation of the various replicates were uniform regardless of the strain used. The variances observed were due to stochastic differences in the competitive hybridization of targets to the probes on the microarray and a good estimate of the technical variation in our experimental platform. Based on this data a LR = ± 1.0, used by many experimenters to identify divergent or deleted genes in similar M-CGH studies, represents a conservative threshold for divergent gene detection, since genes in which tester and control sequences are identical have a probability of less than 3.0 × 10-6 of having a LR greater than 1.0
Figure 1 Log Ratio distribution of self-self experiments. The LR distribution of self-self experiments was used to determine the level of experimental variability in our experimental platform. Standardized samples of genomic DNA from C. jejuni NCTC 11168 (or RM1221) labelled with Cy3 and Cy5 were co-hybridized to our microarray. Results from six replicates had mean LR = 0.01 with an average SD of 0.215. Because samples from the same genomic DNA were used in both channels, LRs were expected to remain close to 0 and any deviations could be attributable to experimental error.
Analysis of the Log Ratio distribution of highly conserved genes
We analyzed data from a set of M-CGH experiments comparing strain NCTC 11168 (Control) with strain RM1221 (Tester). Because the probes in our microarray were PCR-amplified from the Control strain, Control targets should have 100% probe/target identity (PTI) with the probes on the microarray, and the LR values observed should be a function of the PTI between Tester targets and the NCTC 11168-derived microarray probes. The LR distribution of genes with 100% identity between NCTC 11168 and RM1221 (n = 114) would be expected to behave much like that of self-self experiments because in both cases Control and Tester targets are identical and thus have 100% PTI. This was found to be the case although the distribution of genes with 100% PTI had larger standard deviation (σ = 0.28) than that of self-self experiments (σ = 0.21) (Figure 2). Genes for which the RM1221 sequence had less than 100% sequence identity with NCTC 11168 would be expected to yield LRs that deviate from 0 due to the decreased hybridization of targets that are imperfectly matched to probes on the microarray. We examined the behaviour of genes with high levels of PTI in order to determine the level of sequence divergence that would have an observable effect on LRs. We found that whereas genes with greater than 99% PTI had LR distributions that were nearly indistinguishable from those from self-self experiments, genes with as little as 2% sequence divergence (i.e., 98% PTI and below) deviated from the LR distribution of genes with 100% PTI.
Figure 2 Log Ratio distributions of highly conserved genes. LR distributions from a series of M-CGH experiments comparing two genome-sequenced strains of C. jejuni (NCTC 11168 vs. RM1221). Genes were binned according to PTI and the LR distributions of bins with greater than 95% PTI are presented here. Because the microarray was designed based on strain NCTC 11168, LR deviations from 0 would be the result of sequence divergence or gene absence in strain RM1221. The LR distributions of genes with greater than 99% PTI do not deviate significantly from the average distribution of a Self-self experiment whereas increasingly larger deviations are observed in the range from 98 to 95% PTI.
Analysis of the relationship between PTI and Log Ratio
In order to examine the relationship between % PTI and LR in greater detail, we plotted the mean LR of genes according to their % PTI (Figure 3). As shown previously, the LR distribution of genes with greater than 99% PTI were similar. However, in lower PTI ranges a small yet noticeable decrease in average LR was observed. Although the small number of genes with less than 93% identity makes it difficult to obtain meaningful LR trends because of high variance, decreasing PTI still led to increasingly negative LRs. One caveat of these observations is that the LR of individual data points within a given PTI range show sufficient variability to make PTI predictions based on LR values potentially inaccurate across most of the range of PTIs. For example, although the difference in mean LR of genes with 95% PTI and 96% PTI is 0.12, their standard deviations are 0.42 and 0.39, respectively. Thus, although the average LR decreased with decreasing PTI, there is considerable overlap between the distributions.
Figure 3 Relationship between Log Ratio and PTI. We plotted the average LR of genes with varying levels of % PTI from M-CGH experiments comparing two genome-sequenced strains of C. jejuni (NCTC 11168 vs. RM1221). Genes were binned according to PTI and the LR distributions of individual bins are presented here. The number of observations made within each PTI bin is shown in the lower axis. As seen in Figure 2, the average LR of genes with high levels of PTI are very similar, although a noticeable decrease in average LR is observed even at 98% PTI. Although the average LR becomes increasingly negative as PTI levels drop, given the SD observed within each group PTI category, there is considerable overlap between categories.
Analysis of the Log Ratio distribution of absent genes
Genes that are absent in RM1221 (ie. 0% PTI) should have highly negative LRs because they should yield detectable hybridization signal in the Control channel coupled with a lack of signal in the Tester channel. Although the LR distribution of genes with 0% PTI was shifted towards the left (Mean = -2.34 ± 1.35), it also appeared to be bimodal, with a number of genes with higher than expected LR. When these genes were examined more closely, a common feature was a short microarray probe size (< 250 bp). We plotted the LR distribution of genes with probe sizes <250 bp and >250 bp separately, and found a significant difference in their respective LR distributions (Figure 4). Whereas the LR distribution of the former was -0.93 ± 0.82, the LR distribution for longer genes was -2.94 ± 1.04. This "dampening" in LR amplitude appears to be largely the effect of an overall diminished signal for short genes (results not shown), possibly due to a difference in hybridization kinetics or hybrid stability under the hybridization and washing conditions used. The effect of decreased signal is that of decreased dynamic range because a lower signal in the control channel restricts the amplitude of the LR that can be measured.
Figure 4 Log Ratio distribution of genes absent from strain RM1221. We plotted the LR distribution of genes predicted to be absent from strain RM1221 based on BLAST searches of NCTC 11168 against the RM1221 genome. Because of the lack of Tester signal predicted from these genes, LRs should be expected to be highly negative. The LR distribution (A) appeared to be bimodal with a significant number of genes bearing unusually high LRs. Further examination of these genes revealed a potential bias towards genes represented by short probes on the microarray (i.e. less than 250 bp). Separate re-plotting of the LR distributions of long (B) and short (C) probes confirms a higher average LR among genes with short probes.
Determination of thresholds for highly conserved and absent genes
One of our goals for this analysis was to determine whether the observed trends would enable us to predict the PTI in M-CGH experiments based on LR alone. Although the levels of technical variability mask the subtle effect that low levels of sequence divergence have on LR, the LR distributions at the two PTI extremes (>98% and 0%), which correspond to highly conserved and absent genes, show very little overlap. This enabled us to establish thresholds that, with high confidence, can be used to predict absent and highly conserved genes in M-CGH data (Figure 5). After removal of genes with short amplicon-based probes from our analysis, we established that less than 1% of the observed LRs > -0.8 originated from absent genes (31 of n = 7910). Similarly, less than 1% of observed LRs < -3.0 originated from conserved genes (6 of n = 636) with all false-positive observations stemming from the pyrC gene, which has a PTI of only 81.2%. Of 808 observed LR measurements in the range between -3.0 and -0.8, only 221 (27.3%) originated from genes with greater than 90% PTI. Although, based on our empirical data, LR values that fall between these two thresholds are likely to be from either absent or significantly divergent genes and unlikely to be from highly conserved genes, there is significant overlap between LR distributions of absent and divergent genes. At LRs ≅ -1.4, an observation has a nearly equal likelihood of stemming from an absent gene as it does from a present gene and thus the two classes cannot be distinguished in this LR range.
Figure 5 Determination of thresholds for absent and conserved genes. We calculated the proportion of genes belonging to each of four PTI categories at 0.2 LR intervals in order to determine LR thresholds that could be used to predict absent and conserved genes with a high degree of certainty. Below a LR of -3.0, the false positive rate for conserved genes is less than 1%; similarly, the false positive rate for absent genes above LRs of -0.8 is also less than 1%. In the LR interval between -3.0 and -0.8, particularly approaching the -0.8 boundary, there are significant number of genes from more than one PTI category and thus there is significant risk of misclassification.
Conclusion
Microarray analysis, whether in the context of gene expression or M-CGH studies, is based on determining which genes have statistically significant differential hybridization signal between two samples. In M-CGH analysis, these differential signals are the result of sequence divergence or differences in copy number. Two critical issues rise to the forefront in M-CGH analysis: a) does a gene show genuine differential signal (i.e. outside the norms of variability due to experimental error); b) what is the nature of the event that gave rise to the differential signal (i.e. sequence divergence, copy number change)?
Because M-CGH generates hybridization data as a proxy for sequence similarity data, it is important that it be analyzed as such. While some empirical work has been carried out on probe/target identity (PTI) and data analysis using the microarray platform, the focus has largely been on optimization of species detection and/or identification in complex samples [21-23]. In these applications, the primary goal is that of optimizing probe sets and hybridization conditions to maximize the specificity of species-specific probe/target interactions, possibly at the expense of decreased assay sensitivity and thus the majority of microarrays used for species identification are oligonucleotide-based. By contrast, in comparative genomics, the primary goal is that of gene detection for the purpose of characterizing gene content, and thus the focus must shift to detection sensitivity in order to minimize the likelihood of false positive calls on gene absence events. Because oligonucleotide-based arrays can lead to erroneous gene absence calls [24], the majority of M-CGH studies have used amplicon-based microarrays, which are more sensitive albeit at the expense of specificity [25].
A common thread among bacterial M-CGH studies has been the grouping of all outliers into a single category. Currently it is unclear whether divergent and absent genes can be distinguished based on LR data alone. Although the lack of distinction between these types of events does not negate the results from these studies, it can potentially restrict further analysis of the data. For example, in any pair of intraspecies genomes, sequence similarity can be used to define genes absent in one or the other strain as well as genes that are conserved in both strains. Although the "biological interpretation" in the case of gene absence is unambiguous, many possibilities arise when sequences share any level of similarity. For instance, single nucleotide substitutions can lead to truncated or inactive gene products. Additionally, the level of sequence similarity required for full functional homology varies from gene to gene, increasing the complexity of the analysis even when DNA sequences are directly available. The inexact nature of hybridization analysis further compounds the difficulty in interpreting signal from divergent genes by M-CGH, and thus focusing on conserved and divergent genes ignores the increased reliability of gene absence calls.
In previous work, we presented data suggesting that highly negative LR values were consistent with gene deletion events, paving the way for making the distinction between divergent and absent genes based on LR data [16]. When M-CGH data is analyzed such that gene absence events are grouped together with all other gene divergence events (i.e. as a continuous character model), it represents a significant loss of information both from a technical and from a biological point of view. In addition to the greater ambiguity in data interpretation as LRs approach the threshold for gene conservation, the continuous character approach negates the functional distinction that can be made between gene absence and gene divergence events. Because the LR thresholds described here could be used to reliably predict gene absence and gene conservation, it would be advantageous to focus the analysis of M-CGH data on the accurate detection of conserved and absent genes. While the data between the two thresholds should not be altogether discarded, the two thresholds represent boundaries defining regions in which gene absence and gene presence can be predicted with high confidence and thus should be given greater weight in subsequent analytical steps. It is important to note that the exact value of the LR thresholds presented here is specific to our experimental platform. The prediction accuracy achieved was remarkably high because of the uniform levels of variance across the multiple replicates analysed and because of the high correlation coefficients between replicates (the average ρ ≅ 0.92). This dataset was highly idealized because the relatively small number of replicates was carried out in such a way as to minimize technical variation. Nevertheless, a previous study in which we applied the thresholds described here on a large dataset showed that LRs below our "absence threshold" correlated very highly with other potential indicators of gene deletion [16].
Given the many documented sources of technical variability that can influence microarray results (e.g. variation in handling between individual investigators, laboratory conditions, microarray print batches), thresholds for gene presence/absence detection should be calibrated to the differential levels of technical variance found in individual microarray experiments, especially in large datasets. Kim et al [18] have suggested a solution to array-specific variance and normalization bias by determining thresholds specific to each array based on the point at which the LR distribution deviates from its inferred normal distribution. In practice, we have found that this approach can be susceptible to "narrow" LR distributions, leading to relaxed thresholds that yield an increased number of false positives for gene divergence. An alternative approach to deal with unequal variances and normalization biases across a dataset is based on normalizing multiple microarrays using the Z-score transformation [26,27], in which LR values are divided by the standard deviation of the LR data distribution. Z score-based metrics could be used to replace Log Ratio-based metrics, enabling direct comparisons that are more valid because data from each microarray is "variance-calibrated".
Based on the higher than expected Log Ratio values obtained in the case of absent genes, the "relative accuracy" of Log Ratio measurements obtained from short probes is significantly compromised under the standard hybridization conditions we used. It is important to note however, that based on the average standard deviations observed (< 250 bp = 0.68; > 250 bp = 0.85), results obtained from short probes do not lack precision compared to those obtained from longer probes. Nevertheless, our results show that data obtained from short probes yield anomalously high Log Ratio values. It is only because our assay represents a closed system in which all components are known that we were able to determine that short probes can significantly underestimate Log Ratio measurements. These results would not have been readily apparent in a typical experiment since there would be no a priori knowledge on expected Log Ratio values. Although these results were obtained in a series of CGH experiments, the anomalous Log Ratio data from short probes is likely to be encountered under any type of microarray hybridization experiment, including gene expression-profiling experiments. Although longer probes performed better in our assay, this is likely a result of the higher signal intensity obtained with long probes relative to short probes. Optimal hybridization and scanning conditions for long probes would likely be sub-optimal for short probes, leading to decreased signal and a concomitant drop in Log Ratio amplitudes. Thus the problem resides not in probe length per se, but rather in the mixed probe lengths encountered in our microarray. These results have important implications towards microarray probe design because the adverse probe-length effect could be mitigated through standardizing probe length. Failing that, it would be advantageous to incorporate probe length effects into any analytical framework.
The results presented here have been used to examine the relationship between LR and sequence conservation. The variability inherent in hybridization-based approaches makes it unlikely that LR data from M-CGH experiments can be used to accurately predict the level of sequence identity among divergent genes. In view of the considerable ambiguity in interpreting the significance of gene divergence even when sequence information is available, the focus on gene divergence in M-CGH studies must be re-assessed. We have established thresholds for the use of LR values for the accurate detection of highly conserved and absent genes, which should increase the robustness of downstream data interpretation and should extend the range of biological interpretation of M-CGH data. An accurate determination of conserved and absent genes should increase the accuracy of strain genotyping, metabolic pathway prediction, and determination of conserved targets for vaccine or drug development from M-CGH data.
Methods
Bacterial strains and genomic DNA isolation
Strain RM1221 was obtained from Food Safety and Health Research Unit, USDA. Strain NCTC 11168 was obtained from the American Type Culture Collection (Mannassas, VA). Genomic DNA isolation was carried out as previously described [16]
Construction of a C. jejuni NCTC 11168 open reading frame DNA microarray
The DNA microarrays used in this work were previously described in [16]. Additional information can be obtained at [28].
Microarray hybridizations
Genomic DNA was sheared to a mean fragment size of 1.5 Kb by nebulization in 35% glycerol at 15 PSI for 45 seconds as described by [29]. For each sample, 5 μg of sheared DNA were fluorescently labelled using direct chemical coupling with the Label-IT (Mirus Corp., Madison, WI) cyanine dyes Cy3 and Cy5 as recommended by the manufacturer. Probes were purified by sequentially passing samples through SigmaSpin (Sigma, Oakville, ON) and Qiaquick (Qiagen, Mississauga, ON) columns. Labelled DNA sample yields and dye incorporation efficiencies were calculated using a Nanodrop ND-1000 spectrophotometer (Nanodrop, Rockland, DE). Microarray hybridizations were set-up by co-hybridizing 2 ug of differentially labelled genomic DNA samples and were carried out as previously described [16]. NCTC 11168 versus RM1221 hybridizations were carried out in triplicate. A set of dye-swap experiments was also carried out, giving a total of 6 replicate experiments. Self-self hybridization experiments were carried out in which separate NCTC 11168 (or RM1221) genomic DNA samples were labelled with each Cy-dye and co-hybridized to the array.
Data acquisition and analysis
Microarrays were scanned and analyzed as previously described [16]. Briefly, microarrays were scanned using a Chipreader laser scanner (BioRad, Mississauga, ON) according to the manufacturer's recommendations. Spot quantification, signal normalization and data visualization were performed using the program ArrayPro Analyzer (version 4.5; Media Cybernetics, Silver Spring, MD). Net signal intensities were obtained by performing local-ring background subtraction and spots with a signal less than 5-times above background were excluded from the analysis. Signal intensities for replicate spots were averaged and data from each channel were adjusted by sub-array normalization using cross-channel Loess regression. The ratio of tester signal to control signal for each gene was transformed to its base 2 logarithm [30], log2 [Tester Signal / C. jejuni NCTC 11168 Signal], hereafter referred to as "Log Ratio" (LR). LRs from the two "within slide" spot replicates were averaged. To increase the number of observations for statistical purposes, LR data from each microarray replicates were analyzed separately.
Determining level of sequence identity between probes and targets (PTI)
We used the BLAST software package [31] to determine the identity between microarray probes and predicted target sequences. Complete genome sequence information for C. jejuni NCTC 11168 and C. jejuni RM1221 was downloaded from the National Center for Biotechnology Information's Prokaryotic Genomes Database [32], GenBank records AL111168 and CP000025, respectively. We created BLAST databases from the nucleotide sequences of the open reading frames in each C. jejuni genome strain and queried them with the nucleotide sequences of each probe in our microarray using the BLASTN program. The percent identity of the best hit for each subject/query pair was determined.
List of abbreviations
M-CGH: microarray-based comparative genomic hybridization; LR: Log Ratio; PTI: Probe/Target Identity; SD: standard deviation (or σ)
Authors' contributions
ENT designed M-CGH experiments, carried out downstream data analysis, and drafted the manuscript. RRA assisted with downstream data analysis. WAF carried out BLAST analysis of the two sequenced genomes. CCL carried out hybridizations and performed upstream data analysis. JHEN participated in the conception and supervised the design of the study and writing the manuscript. All authors submitted comments on drafts and read and approved the final manuscript.
Acknowledgements
Funding for this work has been provided to ENT, RRA, WAF and JHEN through the National Research Council's Genomics and Health Initiative, and to CCL through Health Canada.
==== Refs
Alm RA Ling LS Moir DT King BL Brown ED Doig PC Smith DR Noonan B Guild BC deJonge BL Carmel G Tummino PJ Caruso A Uria-Nickelsen M Mills DM Ives C Gibson R Merberg D Mills SD Jiang Q Taylor DE Vovis GF Trust TJ Genomic-sequence comparison of two unrelated isolates of the human gastric pathogen Helicobacter pylori Nature 1999 397 176 80 9923682 10.1038/16495
Anjum MF Lucchini S Thompson A Hinton JC Woodward MJ Comparative genomic indexing reveals the phylogenomics of Escherichia coli pathogens Infect Immun 2003 71 4674 83 12874348 10.1128/IAI.71.8.4674-4683.2003
Edwards RA Olsen GJ Maloy SR Comparative genomics of closely related salmonellae Trends Microbiol 2002 10 94 9 11827811 10.1016/S0966-842X(01)02293-4
Fukiya S Mizoguchi H Tobe T Mori H Extensive genomic diversity in pathogenic Escherichia coli and Shigella Strains revealed by comparative genomic hybridization microarray J Bacteriol 2004 186 3911 21 15175305 10.1128/JB.186.12.3911-3921.2004
Lan R Reeves PR Intraspecies variation in bacterial genomes: the need for a species genome concept Trends Microbiol 2000 8 396 401 10989306 10.1016/S0966-842X(00)01791-1
Avison MB Woodford N, Johnson AP Comparative Genomics: Digging for Data Genomics, Proteomics, and Clinical Bacteriology: Methods and Reviews 2004 266 Totowa, NJ USA: Humana Press 47 70
Kuroda M Hiramatsu K Woodford N, Johnson AP Genome Sequencing and Annotation: An Overview Genomics, Proteomics, and Clinical Bacteriology: Methods and Reviews 2004 266 Totowa, NJ USA: Humana Press 29 46
Payne DJ Gwynn MN Holmes DJ Rosenberg M Woodford N, Johnson AP Genomic Approaches to Antibacterial Discovery Genomics, Proteomics, and Clinical Bacteriology: Methods and Reviews 2004 266 Totowa, NJ USA: Humana Press 231 60
Van Ijperen C Saunders NA Woodford N, Johnson AP Microarrays for Bacterial Typing: Realistic Hope or Holy Grail? Genomics, Proteomics, and Clinical Bacteriology: Methods and Reviews 2004 266 Totowa, NJ USA: Humana Press 213 28
Sails AD Swaminathan B Fields PI Utility of multilocus sequence typing as an epidemiological tool for investigation of outbreaks of gastroenteritis caused by Campylobacter jejuni J Clin Microbiol 2003 41 4733 9 14532212 10.1128/JCM.41.10.4733-4739.2003
Schouls LM Reulen S Duim B Wagenaar JA Willems RJ Dingle KE Colles FM Van Embden JD Comparative genotyping of Campylobacter jejuni by amplified fragment length polymorphism, multilocus sequence typing, and short repeat sequencing: strain diversity, host range, and recombination J Clin Microbiol 2003 41 15 26 12517820 10.1128/JCM.41.1.15-26.2003
Yan W Chang N Taylor DE Pulsed-field gel electrophoresis of Campylobacter jejuni and Campylobacter coli genomic DNA and its epidemiologic application J Infect Dis 1991 163 1068 72 2019755
Dorrell N Mangan JA Laing KG Hinds J Linton D Al-Ghusein H Barrell BG Parkhill J Stoker NG Karlyshev AV Butcher PD Wren BW Whole genome comparison of Campylobacter jejuni human isolates using a low-cost microarray reveals extensive genetic diversity Genome Res 2001 11 1706 15 11591647 10.1101/gr.185801
Leonard EE 2ndTakata T Blaser MJ Falkow S Tompkins LS Gaynor EC Use of an open-reading frame-specific Campylobacter jejuni DNA microarray as a new genotyping tool for studying epidemiologically related isolates J Infect Dis 2003 187 691 4 12599089 10.1086/368268
Pearson BM Pin C Wright J I'Anson K Humphrey T Wells JM Comparative genome analysis of Campylobacter jejuni using whole genome DNA microarrays FEBS Lett 2003 554 224 30 14596944 10.1016/S0014-5793(03)01164-5
Taboada EN Acedillo RR Carrillo CD Findlay WA Medeiros DT Mykytczuk OL Roberts MJ Valencia CA Farber JM Nash JH Large-scale comparative genomics meta-analysis of Campylobacter jejuni isolates reveals low level of genome plasticity J Clin Microbiol 2004 42 4566 76 15472310 10.1128/JCM.42.10.4566-4576.2004
Poly F Threadgill D Stintzi A Identification of Campylobacter jejuni ATCC 43431-specific genes by whole microbial genome comparisons J Bacteriol 2004 186 4781 95 15231810 10.1128/JB.186.14.4781-4795.2004
Kim CC Joyce EA Chan K Falkow S Improved analytical methods for microarray-based genome-composition analysis Genome Biol 2002 3 RESEARCH0065 12429064 10.1186/gb-2002-3-11-research0065
Parkhill J Wren BW Mungall K Ketley JM Churcher C Basham D Chillingworth T Davies RM Feltwell T Holroyd S Jagels K Karlyshev AV Moule S Pallen MJ Penn CW Quail MA Rajandream MA Rutherford KM van Vliet AH Whitehead S Barrell BG The genome sequence of the food-borne pathogen Campylobacter jejuni reveals hypervariable sequences Nature 2000 403 665 8 10688204 10.1038/35001088
Fouts DE Mongodin EF Mandrell RE Miller WG Rasko DA Ravel J Brinkac LM Deboy RT Parker CT Daugherty SC Dodson RJ Durkin AS Madupu R Sullivan SA Shetty JU Ayodeji MA Shvartsbeyn A Schatz MC Badger JH Fraser CM Nelson KE Major structural differences and novel potential virulence mechanisms from the genomes of multiple campylobacter species PLoS Biol 2005 3 e15 15660156 10.1371/journal.pbio.0030015
Wu L Thompson DK Li G Hurt RA Tiedje JM Zhou J Development and evaluation of functional gene arrays for detection of selected genes in the environment Appl Environ Microbiol 2001 67 5780 90 11722935 10.1128/AEM.67.12.5780-5790.2001
Tiquia SM Wu L Chong SC Passovets S Xu D Xu Y Zhou J Evaluation of 50-mer oligonucleotide arrays for detecting microbial populations in environmental samples Biotechniques 2004 36 664 70 672, 674-5 15088384
Wilson WJ Strout CL DeSantis TZ Stilwell JL Carrano AV Andersen GL Sequence-specific identification of 18 pathogenic microorganisms using microarray technology Mol Cell Probes 2002 16 119 27 12030762 10.1006/mcpr.2001.0397
Daran-Lapujade P Daran JM Kotter P Petit T Piper MD Pronk JT Comparative genotyping of the Saccharomyces cerevisiae laboratory strains S288C and CEN.PK113-7D using oligonucleotide microarrays FEMS Yeast Res 2003 4 259 69 14654430 10.1016/S1567-1356(03)00156-9
Denef VJ Park J Rodrigues JL Tsoi TV Hashsham SA Tiedje JM Validation of a more sensitive method for using spotted oligonucleotide DNA microarrays for functional genomics studies on bacterial communities Environ Microbiol 2003 5 933 43 14510847 10.1046/j.1462-2920.2003.00490.x
Cheadle C Vawter MP Freed WJ Becker KG Analysis of microarray data using Z score transformation J Mol Diagn 2003 5 73 81 12707371
Colantuoni C Henry G Zeger S Pevsner J SNOMAD (Standardization and NOrmalization of MicroArray Data): web-accessible gene expression data analysis Bioinformatics 2002 18 1540 1 12424128 10.1093/bioinformatics/18.11.1540
Campychip Description
Bodenteich AS Chissoe Y Wang F Roe BA Adams MD, Fields C, Venter C Shotgun cloning as the strategy of choice to generate templates for high throughput dideoxynucleotide sequencing Automated DNA sequencing and analysis techniques 1994 London, UK: Academic Press 42 50
Smyth GK Yang YH Speed T Statistical issues in cDNA microarray data analysis Methods Mol Biol 2003 224 111 36 12710670
Altschul SF Lipman DJ Protein database searches for multiple alignments Proc Natl Acad Sci U S A 1990 87 5509 13 2196570
National Center For Biotechnology Information's Prokaryotic Genomes Database
| 15918914 | PMC1168892 | CC BY | 2021-01-04 16:39:54 | no | BMC Genomics. 2005 May 27; 6:78 | utf-8 | BMC Genomics | 2,005 | 10.1186/1471-2164-6-78 | oa_comm |
==== Front
BMC Health Serv ResBMC Health Services Research1472-6963BioMed Central London 1472-6963-5-381591068910.1186/1472-6963-5-38Research ArticleIntermediate care: for better or worse? Process evaluation of an intermediate care model between a university hospital and a residential home Plochg Thomas [email protected] Diana MJ [email protected] der Kruk Tineke F [email protected] Tonnie ACM [email protected] Niek S [email protected] Department of Social Medicine, Academic Medical Centre / University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands2 Nivel Netherlands Institute for Health Services Research, Drieharingstraat 6, Utrecht, The Netherlands3 Department of Geriatrics, Academic Medical Centre / University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands4 Medical Board, Academic Medical Centre / University of Amsterdam, Meibergdreef 9, Amsterdam The Netherlands2005 24 5 2005 5 38 38 12 11 2004 24 5 2005 Copyright © 2005 Plochg et al; licensee BioMed Central Ltd.2005Plochg et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Intermediate care was developed in order to bridge acute, primary and social care, primarily for elderly persons with complex care needs. Such bridging initiatives are intended to reduce hospital stays and improve continuity of care. Although many models assume positive effects, it is often ambiguous what the benefits are and whether they can be transferred to other settings. This is due to the heterogeneity of intermediate care models and the variety of collaborating partners that set up such models. Quantitative evaluation captures only a limited series of generic structure, process and outcome parameters. More detailed information is needed to assess the dynamics of intermediate care delivery, and to find ways to improve the quality of care. Against this background, the functioning of a low intensity early discharge model of intermediate care set up in a residential home for patients released from an Amsterdam university hospital has been evaluated. The aim of this study was to produce knowledge for management to improve quality of care, and to provide more generalisable insights into the accumulated impact of such a model.
Methods
A process evaluation was carried out using quantitative and qualitative methods. Registration forms and patient questionnaires were used to quantify the patient population in the model. Statistical analysis encompassed T-tests and chi-squared test to assess significance. Semi-structured interviews were conducted with 21 staff members representing all disciplines working with the model. Interviews were transcribed and analysed using both 'open' and 'framework' approaches.
Results
Despite high expectations, there were significant problems. A heterogeneous patient population, a relatively unqualified staff and cultural differences between both collaborating partners impeded implementation and had an impact on the functioning of the model.
Conclusion
We concluded that setting up a low intensity early discharge model of intermediate care between a university hospital and a residential home is less straightforward than was originally perceived by management, and that quality of care needs careful monitoring to ensure the change is for the better.
==== Body
Background
Due to technological developments, better communication facilities and further differentiation and specialisation of professionals, patient care is increasingly provided outside hospitals. Financiers, governments and patients advocate this development, as they consider outpatient care to be more efficient and patient centred [1].
This shift has repercussions for chronically ill and elderly patients with complex care needs. First, it is questionable whether optimal care for these patients can be delivered in an outpatient setting. They need sufficient time to recover and are often in frail health [2]. Early hospital discharge can present dangers for them. Moreover, alternatives are often scarce, as the capacity of long-term care facilities is either limited or too expensive. What is known as 'bed-blocking' occurs when patients whose medical treatment has been completed cannot be discharged because of poor continuation of care outside the hospital [3].
Second, these patients often need care from health professionals in multiple settings. Consequently, patient care journeys encompass multiple transitions from one setting to another [4]. Systems of care often fail to organise these transitions, thus influencing the quality of care [5-7].
Bearing these issues in mind, a plethora of care models have been developed to substitute hospital inpatient care and to improve transitional care [8]. One model can be described by the term 'intermediate care'. This model refers to a range of services intended to bridge acute, primary and social care. It is considered to serve goals like reducing the length of hospital stays, preventing hospital admissions and readmissions, improving transitions from hospital to consecutive settings, and retaining people's independence as long as possible [9].
Still, the benefits and transportability of intermediate care are ambiguous [9-12]. This can be attributed to the blurred definition of the concept and the wide range of services labelled as such. Models differ in focus, setting, case mix, staffing, professionals involved, commissioning and context. Hence, it is quite difficult to define the concept, to identify best practices and to compare different settings. Against this background, it is argued that the 'black-box' of intermediate care (i.e. the processes of care) should be opened [13]. Process evaluations are therefore warranted and promoted [14,15].
This paper provides such a process evaluation of an intermediate care model. The aim was to provide management with information to assess and improve the quality of care. Even so, it should also provide more generalisable insights into the accumulated impact of the model.
In the Dutch health care system, a distinction is made between the financing and organisation of acute and long-term care. Acute care is financed either by social health insurance (covering about 60% of the population) or private health insurance (covering about 40% of the population). Compulsory national health insurance covers the whole population for long-term care. Health care providers organise their services in networks that are covered by either scheme. Cooperation and coordination of care takes place predominately within the acute care sector.
But health care delivery is fragmented in the transition from acute to long-term care. To bridge the gap, various intermediate care models are being set up in hospitals, nursing homes and residential homes [16,17]. However, due in part to the division of the insurance schemes, financing is often ad hoc and available only for the duration of a single project.
The model evaluated in this study eventually became structurally embedded in the local health system of the South-eastern Amsterdam district. The Henriëtte Roland Holst House (HRHH), a residential home, and the Academic Medical Center of the University of Amsterdam (AMC) agreed to establish a low intensity early discharge model of intermediate care encompassing transitional care as well as a transfer unit. This model focuses exclusively on all AMC patients who no longer require hospital treatment but are not healthy enough to be discharged to their home situations. It supplements two more intensive rehabilitation models of intermediate care in nursing homes for stroke and orthopaedic AMC patients. Table 1 describes the model and its local context.
Table 1 Characteristics of the intermediate care model
Focus Starting a 'transfer unit' in a residential home for AMC patients whose medical treatment has been completed, but are unfit to be discharged to their homes. The unit should serve as a substitute hospital ward that relieves the problem of 'bed-blocking' in the AMC and improves transitional care to the home situation.
Admission criteria All AMC patients are eligible for admission to the transfer unit if they meet the following criteria:
- Patient is medically stable and curative treatment has been completed;
- Patient needs care that can be delivered by one nursing assistant;
- Patient is not eligible for other regular care services and cannot go home;
- Patient is insured;
- Patient does not need daily care and/or intensive physical therapy;
- Patient is not a drug addict, terminally ill or comatose, and does not have AIDS;
- Patient does not exhibit disturbing behaviour if he or she is a psychiatric or psychogeriatric patient.
- Patient has an official indication for discharge to a consecutive setting.
Transitional care Three AMC liaison nurses control, plan and coordinate all transitions of AMC inpatients to the transfer unit systematised by agreed discharge procedures. The nursing home physician, occupational therapist, the liaison nurse and the head (an RN) assess whether an AMC patient will be admitted to the transfer ward.
Setting 20 transfer beds located in 10 rooms. The unit was established outside the AMC in a residential home in the South-eastern Amsterdam district. This institution accounts for 110 residential home places, 7 places for day care, 4 community health beds and 218 apartments for assisted living.
Staffing Head of the transfer unit 1.0 FTE; nursing home physician 0.33 FTE, registered nurses 0.89 FTE; liaison nurses 0.5 FTE; occupational therapist 0.5 FTE; licensed practice nurses 11.61 FTE. Two physiotherapists with a practice in the residential care home are directly available for patients of the transfer unit. An AMC geriatric nursing specialist attends multidisciplinary meetings once a week.
Context The AMC and Henriëtte Roland Holst House are located in the South-eastern Amsterdam district. This region accounts for approximately 85,000 residents of whom 7,000 (8%) are older than 65, and 61% belong to an ethnic minority. A number of institutions in the region provide care for the elderly: 1 AMC, 1 nursing home, 4 residential homes, 1 public home-care agency, 1 public health agency, 1 social care agency, 5 primary care centres and 1 institution for psychiatric care.
Commissioning The local public insurer structurally finances the transfer unit. The annual budget is 758,205 euros. Transitional care is financed by the AMC budgets.
Methods
Aim
The intermediate care model was evaluated at the request of the collaborating institutions. During the course of 2000, both partners expressed concerns about how the model was functioning, and needed information to make informed decisions on how to improve the quality of care. This implied that the evaluation should be conducted from a 'managerial evaluation perspective' [18]. The following questions were addressed: 1) Is the patient population admitted to the model in accordance with the ex ante expectations of key players and staff members? 2) How does the model ensure quality of care?
Design
A process evaluation based on quantitative and qualitative methods was considered the most appropriate and feasible way of answering both questions. Registration forms and patient questionnaires were used to quantify the patient population. Semi-structured interviews were conducted to explore the expectations and experiences of the key players and staff members, as well as to describe how the quality of care is ensured. The project proposal was reviewed by the medical ethical committee of the AMC in August 2000 and was considered not in need of formal approval according to the Dutch legislation on experiments with human beings. There were no ethical objections raised against the study.
Patient questionnaires and registration forms (quantitative analyses)
Sample
Initially, all candidates (n = 189) for admission to the transfer unit between 1 October 2000 and 31 October 2001 were in the study. RNs working in the AMC wards selected candidates after consulting the individual patients and their families. Liaison nurses at the AMC collected the submitted applications and sent them to the transfer unit for assessment. Using formalised admission criteria (Table 1), the nursing home physician assessed whether a candidate could be admitted to the transfer unit. 162 out of 189 (85.7%) candidates met the admission criteria and 27 out of 189 (14.3%) did not. As researchers, we did not interfere in this process.
During the assessments, we requested informed consent from patients participating in the study. There were two significant differences between consenting (n = 70) and non-consenting patients (n = 119). The age distribution differed significantly between both groups (chi2 = 12.51; p = .03), and the youngest and oldest patients were less willing to participate. Moreover, consenting patients were less likely to be refused for admission than those who did not consent. Just 2 out of 70 consenting patients (3%) were refused, while this rate was 27 out of 119 (21%) for non-consenting patients. This selective non-response can be explained by health status. Patients who did not meet the admission criteria were more seriously ill and less inclined to participate in the study. Of the 68 positively assessed patients who consented, 54 were actually admitted. During the assessment period 2 patients died and 12 were discharged to another destination. The sample is shown in figure 1.
Figure 1 Flow chart
Data collection
Two registration forms and two patient questionnaires measured process parameters. The first form, filled in before the assessment procedure was started, recorded 'medical diagnosis', 'reason for hospital admission', 'reason for application' (rehabilitation, waiting for admission to a nursing home, waiting for admission to a residential home, oncology, wound therapy, other), and 'name of the submitting AMC ward'. After the assessment procedure 'refusal or admittance to the transfer unit', 'date of hospital admission', 'date of hospital discharge', 'discharge destination' (transfer unit, home, nursing home, residential home, other) were registered.
The second form was filled out at discharge from the transfer unit. In this form 'destination of discharge' (home with or without home care, nursing home, residential home, hospital, other), 'experienced burden of care in relation to the expected burden of care based on the application' (the head of the unit gave his or her assessment), 'whether the patient was in the appropriate place' (the head of the unit gave his or her assessment), and 'care delivery problems experienced' were registered.
During the assessment procedure, the patients filled out two questionnaires, assisted by a researcher if necessary: the 36-item short-form health survey (SF-36) and the Groningen Activity Restriction Scale (GARS). The SF-36 includes one multi-item scale measuring eight health concepts: 1) limitations in physical activities because of health problems; 2) limitations in social activities because of physical or emotional problems; 3) limitations in usual role activities because of physical health problems; 4) bodily pain; 5) general mental health (psychological distress and well-being); 6) limitations in usual role activities because of emotional problems; 7) vitality (energy and fatigue) and 8) general health perceptions [19,20]. The GARS aims at measuring both the ADL and instrumental ADL disability in community-based studies with respect to the aid and services provided by professional home help and district nursing agencies [21,22].
Data analysis
We analysed the quantitative data using SPSS 10.1. We used T-tests and chi-squared test statistics to assess significance.
Semi-structured interviews (qualitative analyses)
Sample
We interviewed 21 key players and staff members selected 'purposively' for their positions, disciplines and institutions. All disciplines involved were represented in the study. In addition, nursing assistants were selected on the basis of gender, age, ethnicity and work experience. It was not feasible to interview them all. This approach resulted in the sample presented in table 2.
Table 2 Interviewed professionals
Respondent Position Institution
Nr 1. General manager HRHH
Nr 2. Director of integrated care AMC
Nr 3. Head of care department HRHH
Nr 4. Chair board of directors HRHH
Nr 5. Chair medical specialist staff AMC
Nr 6. Nursing home physician HRHH
Nr 7. Liaison nurses / head discharge unit AMC
Nr 8. Liaison nurse AMC
Nr 9. Liaison nurse AMC
Nr 10. Geriatric nurse specialist AMC
Nr 11. Liaison nurse / occupational therapist HRHH
Nr 12. Registered nurse internal medicine AMC
Nr 13. Registered nurse / Head of the transfer unit HRHH
Nr 14. Occupational therapist AMC
Nr 15. Physical therapist HRHH
Nr 16. Physical therapist HRHH
Nr 17. Nursing assistant transfer unit HRHH
Nr 18. Nursing assistant transfer unit HRHH
Nr 19. Nursing assistant transfer unit HRHH
Nr 20. Nursing assistant transfer unit HRHH
Nr 21. Nursing assistant transfer unit HRHH
Data collection
We interviewed the respondents at their places of work using an interview guide (see figure 2), which was developed around the research questions. During the interviews, the guide was used in an informal and flexible way in order to prevent the researchers from imposing their own preconceptions. The interviews took approximately one hour each; they were recorded and later transcribed. One researcher coded the transcripts and wrote memos to systematise the analysis. We completed the data collection after finishing 21 interviews – all disciplines working with the model were then represented and no new findings were expected.
Figure 2 Interview guide
Data analysis
We used open and framework approaches to analyse the interviews. Building on respondents' perceptions, we conceptualised the dynamics underlying the admittance of patients to the transfer unit. To interpret quality assurance activities and their implementation, a theoretical framework was explicated. On the basis of a typology of quality systems consisting of five elements (structural assets, allocation of responsibilities, protocols, information transfer and monitoring/feedback cycles) we identified existing quality assurance activities in the model. We contrasted respondents' notions on the implementation of the model with recent knowledge on effective implementation [23,24].
Rigour
To monitor and consider the rigour of the interviewing process, we used several strategies to rule out validity threats [25]. First, due to our sampling strategy we were able to identify respondents who gave socially desirable answers. We noticed that three of them were much too positive about the functioning of the transfer unit and were defensive in their responses. Second, we conducted member checks by asking respondents to validate transcripts and interpretations of their interviews. Respondents had few actual corrections, which we adopted without discussion. Third, we aimed for 'triangulation'. We verified respondents' essential statements by contrasting them with our quantitative data, local documents and/or international and Dutch literature. Finally, we solicited feedback from a variety of senior and other researchers (peer review). The researchers in the team systematically monitored the data collection, analysis and emerging findings. Colleagues at the Department of Social Medicine and the Dutch National Institute of Health Services Research reviewed earlier drafts of the manuscript.
Results
Foreseen versus actual/perceived patient population
The target population was described in the initial intermediate care model [26]. AMC patients whose medical treatment had been completed but who were unfit to be discharged to their homes – the bed-blockers- were eligible for admission to the unit. Admission criteria further specify this target population (table 1). Quantitative as well as qualitative data were used to verify whether members of this target population were actually admitted to the unit.
The quantitative profile of the patient population
During the 13 months of the study, 189 candidates were assessed (table 3). The majority were female, single and older than 65. Apart from this, the profile of these candidates was more heterogeneous. Although the most prevalent diseases were cardiovascular diseases and cancer, candidates suffered from a variety of different diseases. This was also shown by the diversity of the submitting clinical wards and the various reasons for application. A relatively small number of candidates were waiting for placement in a nursing home (n = 33) or residential home (n = 3) and could be identified as bed-blockers.
Table 3 Characteristics of assessed candidates
Process parameter Outcome
Gender Male n = 72 (38.3%)
Female n = 117 (61.7%)
Age distribution < 65 years n = 34 (18.3%)
65–69 years n = 21 (11.3%)
70–74 years n = 19 (10.2%)
75–79 years n = 40 (21.5%)
80–84 years n = 33 (17.7%)
> 85 years n = 39 (21.0%)
missing n = 3
Home situation Living alone n = 160 (84.7%)
Living with a partner n = 29 (15.3%)
Medical diagnoses Cardiovascular diseases n = 44 (23.3%)
Cancer n = 37 (19.4%)
Other n = 108 (57.3%)
Reasons for application Recovery after surgery n = 30 (17.4%)
Rehabilitation n = 65 (37.8%)
Waiting for a nursing home n = 33 (19.2%)
Waiting for a residential care home n = 3 (1.8%)
Oncology therapy n = 10 (5.8%)
Other n = 31 (18.0%)
Missing n = 17
The 'Health-related quality of life' (SF-36) and the 'Activities of daily living' (GARS DL-scale) were filled out by 59 of the 70 participating patients. Their scores were comparable with those of a population in a British geriatric day hospital and a population in a Dutch community GP ward for recuperating elderly people [27,28].
The 70 patients participating in the study had an average length of stay (LoS) in the AMC of 31.8 days (range 3–109; stdv 22.2). The 54 out of the 70 patients participating in the study who were actually admitted to the transfer unit stayed there for an average of 46.5 days (range 0–340). This average lies within the maximum of three months LoS. Looking back on their stays, the head of the transfer unit considered 12 of the 54 patients (22.2%) to have needed more care than had been expected, and 5 patients (9.3%) to have needed less care than had been expected. For 6 of the 12 more serious patients (11.1%) and for 3 of the 5 less serious ones (5.6%), the head also considered the transfer unit to have been inappropriate. The final discharge destination was home (n = 18; 33.3%), home with home care (n = 18; 33.3%), hospital (n = 6; 11.1%) or elsewhere (n = 12; 22.2%).
A more complex patient load than anticipated
Respondents felt that a patient population with a heavier burden of care than anticipated had been admitted to the transfer unit. Respondents experienced a limited inflow of bed-blockers:
The focus of the model was to reduce the problem of bed-blocking in the AMC. Now we notice we admit hardly any bed-blockers to the transfer unit (…). In practice it seems there are no bed-blockers in the AMC. (respondent 10)
This perception was difficult to verify in the quantitative data. Based on the discharge destinations, just 36 out of 189 candidates (19%) could be considered as bed-blockers. This seems to be opposed by the average LoS in the AMC of 31.8 days, which is three times the average LoS of patients in the AMC in 2001 (9.4) [29]. However, the high standard deviation (22.2) and the median of 24 indicate that outliers are increasing the average LoS. Moreover, average LoS is an indicator of bed-blocking, not a valid measure.
To support their perception, respondents put forward two explanations. First, respondents felt the target population envisioned in the design of the intermediate care model either did not exist in the AMC or was smaller than expected. An initial assessment of the size of the target population did not take place. This implies that the relevance of the intermediate care model may have been overestimated from the outset:
You instinctively know the size of this patient group (…). As far as I know, there were no data available [during the planning of the transfer unit]. (respondent 8)
Second, respondents suggested that the assessment procedure took too long. The model is only appropriate during a short period of patients' care episodes because their care needs vary. Therefore, the transition from the AMC to the unit must be flexible and fast, and this was not achieved in practice. The period between application and discharge took on average 8.7 days (range 1–39). Moreover, in the study group, 14 out of 68 patients meeting the admission criteria were not discharged to the transfer unit. In the meantime, patients died (n = 2), went home (n = 5) or were admitted to another institution (n = 7). This implies that 20% of the inflow was cancelled during transitional care processes.
Respondents considered the main reason for delays to be the limited availability of the nursing home physician (only three afternoons a week), whose authorisation was needed for admission. Another reason mentioned for delays was discharge planning in the AMC. Time was sometimes lost waiting for the medical application/referral forms.
Due to the limited inflow of targeted patients, filling transfer beds became problematic. To avoid empty beds, respondents felt that admission criteria had been applied subjectively. In their opinion, restrictive application of inclusion criteria was not in the financial interests of the collaborating institutions:
There is a negative spiral nobody in health care can ignore. (...) On the one hand you must deliver a certain volume of care. On the other hand you have your human resources. When you fail delivering this volume of care you will loose personnel, as you earn not enough money. (...) What happens? You can admit even less patients. So, you must compromise. (respondent 6)
The HRHH maximised production to prevent budget reductions. The AMC optimised the turnover of patients to be in a better position for the annual budget negotiations with insurers. These inverse incentives may have resulted in admitting patients with a heavier burden of care to the transfer unit:
I think the patient population admitted to the transfer unit has a heavier burden of care than was originally expected. (respondent 8)
The medical aspects become more serious. Although the patients' medical treatment has been completed, their health is still frail. (respondent 6)
This perceived pattern was partly supported by quantitative data. According to the official hospital statistics bed-blocking days increased from 2,818 days in 2000 towards 3,315 days in 2001 while bed-occupancy rates decreased from 61.5% in 2000 to 57.5% in 2001 [29]. This may indicate that hospital discharge of bed-blockers is postponed to maximise bed-occupancy rates, which supports the hypothesis of the respondents. However, the severity of the self-reported health status of the patients (SF-36) did not change during the study.
Quality of care
Almost all respondents felt there was insufficient quality of care assurance and questioned the functioning of the model:
It works, but if a few things go wrong it doesn't work anymore – then the quality of care goes down fast. (respondent 11)
It doesn't function like it should, but in the past it was worse. (respondent 17)
Although we cannot verify these quotes, we assume that the intermediate care model functions poorly because it was mentioned by the majority of the respondents. Two key players (respondents 6, 10) gave an overall explanation for the poor functioning of the model. They highlighted contextual differences between the HRHH and the AMC as the main stumbling blocks. Setting up and implementing intermediate care requires a certain level of know-how and expertise. In the AMC, these kinds of requirements could easily be met, while in the HRHH they could not. Initiators took this difference for granted, thereby overestimating the organisational capacity of the HRHH:
I don't think all of the consequences [of setting up a transfer unit] were foreseen...There was no experience available of caring for these patients in another setting. (respondent 6)
This overall explanation is supported by respondents' thoughts on the implementation and on the nursing staff mix. Because the interviews were planned to take place throughout the study period, we noticed during the course of 2001 that all planned working processes and quality assurance activities were put into place. The respondents interviewed early in the study reported fewer activities than those interviewed later. Table 4 presents the processes and activities categorised in the five dimensions of a quality system. Although these activities confirmed the existence of quality of care assurance practices, the rather late implementation suggested otherwise. Respondents said that people don't work enough according to the agreed working processes and quality assurance practices, and concluded the implementation process was flawed:
Table 4 Quality assurance activities in the transfer unit
Structural assets - Description of required staff
- Facilities
Allocation of responsibilities - Job descriptions
- Job assessment interviews
Protocols - Description of the target population
- Admission criteria
- Discharge criteria
- Routing of the patients using a flow chart
- Nursing care plans
Information transfer and record-keeping - Transfer procedures from the AMC to the HRHH
- Patient record
- Handover procedures during shifts
Monitoring and feedback cycles - Steering group meetings
- Weekly multidisciplinary meetings
- Supervision by an AMC geriatric nursing specialist
- Patient satisfaction questionnaire upon discharge from the transfer unit
- Training and education
- Management information system
On the transfer unit, the wheel is reinvented every day. Because people don't work according to the agreements, the implementation has been flawed. (respondent 6)
In the implementation literature, good preparation – involving the relevant people, developing a proposal for change and selecting a set of multifaceted strategies – is emphasised [23,24]. Even so, the necessity of an open culture for change and involved management is underscored. Contrasting these insights with our data revealed shortcomings in the implementation. First, the initial intermediate care model lacked a detailed implementation strategy. Various respondents who had worked in the unit from the start confirmed this. Second, it can be questioned whether all relevant people where involved soon enough. Chief executives confessed they involved the nursing home physician too late. Also, nursing assistants said they were insufficiently prepared. Third, there seemed to be a lack of communication, resulting in a 'closed organisational culture' and resistance to change. Finally, involvement by management was considered insufficient. There was criticism that supervision and control was too lax to bring about the desired change. This lack of management was partly due to discontinuities in leadership. Although four persons headed up the unit from the start, reorganisation of the entire residential home distracted chief executives. All these shortcomings were reflected in the following quotes:
At the start, there was very little idea of what might happen. (respondent 6)
They told us almost nothing about what was going to happen. I had the idea they didn't really know, either. (respondent 18)
A nursing home physician was represented in the project group, but it wasn't the physician who was going to do the job. I didn't think this was very smart.(respondent 2)
Staff members act differently. Different perceptions, different realities can be observed, but they're not tried out on each other or debated. (respondent 11)
Apart from the implementation, respondents were also concerned with the nursing staff mix. In their view, the staff was insufficiently qualified:
At this moment, I do not have a positive image of their expertise. (respondent 8)
Managers and staff at the HRHH attributed the lack of expertise to the shortage of skilled nurses. Local figures showed that in 2000, nursing homes and residential homes in Amsterdam had 56 vacancies per 1,000 nursing staff. This rate is the highest in the Netherlands [30]. The managers of the HRHH said they had enormous problems filling the vacancies. Respondents working in the AMC underscored this, but also questioned the chosen staff mix model of the transfer unit:
I was and still am disappointed in the nursing staff mix. The number of staff is okay, but on a ward where discharged hospital patients are admitted, just one RN supplemented by nursing assistants isn't enough. (respondent 2)
Limitations
The process evaluation has its limitations. The large number of non-consenting patients (119 out of 189) has biased the quantitative results. Most of the non-consenting patients were unable or less inclined to participate in the study. We attribute this in part to a flawed informed consent procedure. Consenting patients had to fill out questionnaires immediately, which made various candidates less willing, especially the sicker ones. Consequently, healthier patients are over-represented in the sample. This explains why we could not verify the perception by respondents that the patient population was more seriously ill.
The validity of the qualitative findings is rather high, although some weaknesses were revealed. Because of our managerial evaluation perspective [18], three respondents seemed to give socially desirable answers. Furthermore, we had the impression that the evaluation became a management intervention in itself (Hawthorne effect). During the study we noticed that our framework of analysis, which was implicitly communicated during the interviews, was translated into management actions. Another weakness is that just one researcher conducted the interviews and analysis. Still, we were able to overcome these sources of bias because of the combination of methods, the purposive sampling procedure undertaken and the comprehensive triangulation achieved. The interviews therefore provide a credible exploration of the functioning of an intermediate care model in its local context.
Overall, the transportability of the findings to other settings is limited. As we conducted a process evaluation, findings only provide a detailed description of the intermediate care model in Amsterdam. Nevertheless, we assume that the accumulated impact of the model is not unique to the Amsterdam model. From this perspective, the findings provide a good starting point for developing and evaluating models elsewhere.
Discussion
In the current climate of health care policy, many stakeholders advocate the development and implementation of intermediate care models. However, the widespread popularity of the concept is insufficiently supported by evidence. Intermediate care is still in need of evaluation, as the benefits and the deficits of the various models are ambiguous [1-4].
Nevertheless, available knowledge provides enough do's and don'ts for initiators who want to set up and implement intermediate care. Basically, initiators should be cautious. As our study shows, the accumulated impact of setting up such models may result in a 'bad practice'. To prevent this, initiators should adequately plan, organise and monitor intermediate care services. The following issues are important.
First, the relevance of an intermediate care model must be clear at the outset and supported by sound information. This was not the case in Amsterdam. The low intensity early discharge model was set up alongside two more intensive intermediate care models for stroke and orthopaedic patients. Consequently, the transfer unit was targeted towards a remnant and heterogeneous patient population within which the number of eligible candidates was smaller than expected. The straightforward conclusion is that one should know the size and profile of the target population. Apart from that, patients may view intermediate care as unacceptable. Little is known about this topic [31], and this is reflected in the call for more user involvement in intermediate care development [32]. Even so, this study indicates that the dynamic health status of candidates requires fast and flexible transition processes. Because the health status of patients can change rapidly, intermediate care services are appropriate for short periods during patient journeys. Moreover, poorly organised transition processes may increase the average LoS in the acute care setting which undermines achieving the goal of early discharging patients. So, detailed knowledge of the care needs, desires and size of the target population is necessary to justify the relevance of an intermediate care model.
Second, policy-makers and managers should pay attention to the dynamics resulting from organisational and financial incentives. These may influence a broadening of admission criteria to maximise bed occupancy rates, as shown in Amsterdam. In the literature, this phenomenon is also known as 'Roemer's law': a bed built is a bed filled [33-35]. Perverse incentives induce improper use of intermediate care beds, which results in another patient profile than initially anticipated. The changed patient profiles reported in various studies support this hypothesis [13,36,37]. Continuous monitoring of the patient profile in relation to bed occupancy rates is necessary to detect and overcome this phenomenon.
Third, intermediate care requires a minimum of nursing staff to guarantee quality of care delivery. Their skills should meet the needs of envisioned patients. This was inadequate in Amsterdam. Nursing assistants gave direct care to patients, while medical and registered nursing staff headed up the unit. This high percentage of direct care given by relatively unqualified staff is also reported in other studies. It is considered one of the main reasons for the absence of improved outcomes of intermediate care [13,36]. Other studies as well indicate that nursing staff does matter: those hospitals and nursing homes with the most highly qualified staff provide better care [38-40]. This underscores the importance of thoroughly considering nursing staff mix in intermediate care. However, it is difficult to determine what nursing staff mix is appropriate. There is no minimum standard available.
Fourth, the implementation of intermediate care needs to be given attention. It requires know-how and expertise. In Amsterdam, the initiators overestimated the ability of the staff of the residential home to develop and operate a transfer unit for early discharged patients. These homes provide minimal care services for elderly people in stable health. These homes are less prepared to deliver care to post-acute care patients. This is reflected in the less advanced stage of development of quality assurance activities in Dutch residential homes [41,42]. Initiators of collaborative intermediate care models should be aware of this pitfall and plan a comprehensive implementation strategy. Such a strategy must contain multiple approaches at different levels, tailored to specific settings and target groups [23,24]. Such a strategy should ensure that all requirements are met for delivering good care.
From a more general perspective, these issues promote a more rational and evidence-based management of intermediate care. It is acknowledged that the uptake of evidence in managerial practice could be better [43,44]. As intermediate care lacks a straightforward evidence base, managers run the risk of being persuaded by political willingness rather than by 'evidence'. Uninformed decision-making is dangerous and may ultimately harm patients; future research should fill the existing knowledge gaps. Steiner [1] identifies three key questions for intermediate care research: 1) Which services are best for which patients at which point? 2) Which professionals should be involved, doing what at which point? 3) What is the bottom line financially?
Our findings indicate that these key questions must be answered simultaneously. One cannot properly answer one of the key questions without knowing the answers to the other two. This implies that research designs should have a broad scope, which as our study illustrates, is at the expense of rigour. However, creative study designs are being promoted that try to balance rigour and validity by combining quantitative and qualitative approaches, purpose-collected and coincidental data, and multidisciplinary research perspectives [45,46]. These evaluative approaches provide a good foundation for developing the evidence base for intermediate care.
Conclusion
We conclude that setting up a low intensive early discharge model of intermediate care between a university hospital and a residential home is less straightforward than was originally perceived by management, and that quality of care needs careful monitoring to ensure the change is for the better.
The AMC and HRHH management have taken on these lessons, and the findings of the process evaluation have been translated into management interventions: consistent use of discharge and admission criteria, increasing patient flows by working with a second general hospital in Amsterdam, increasing nursing and medical expertise on the ward, implementing specific nursing protocols and more systematic monitoring of care.
A combined quantitative and qualitative evaluation approach executed in close collaboration with the actors involved was helpful in revealing the underlying mechanism leading to the shortcomings.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
TP designed the qualitative study, conducted the semi-structured interviews, analysed the qualitative data, analysed all data, and primarily wrote the paper.
DMJD designed the whole study, drafted the main protocol, assisted with the quantitative data analysis, reviewed earlier drafts of the paper, and supervised the daily research activities
TFK collected quantitative data, was responsible for the quantitative data entry, did the quantitative analysis, and critically reviewed earlier drafts of the paper
TJ collected quantitative data, critically reviewed earlier drafts of the paper
NSK was responsible for completing the study and the supervision, designed the whole study, and critically reviewed earlier drafts of the paper
Pre-publication history
The pre-publication history for this paper can be accessed here:
==== Refs
European Observatory on Health Care Systems Hospitals in a changing Europe 2002 Buckingham Philadelphia: Open University Press
Hammerman D Towards an understanding of frailty Ann Int Med 1999 130 945 50 10375351
Black D Pearson M Average length of stay, delayed discharge, and hospital congestion BMJ 2002 325 610 611 12242160 10.1136/bmj.325.7365.610
Murtaugh CM Litke A Transitions through post-acute and long-term care settings. Patterns of use and outcomes for a national cohort of elders Medical Care 2002 40 227 236 11880795 10.1097/00005650-200203000-00006
Coleman EA Berenson RA Lost in transition: challenges and opportunities for improving the quality of transitional care Ann Intern Med 2004 141 533 6 15466770
Coleman EA Boult C Improving the quality of transitional care for persons with complex care needs JAGS 2003 51 556 557 10.1046/j.1532-5415.2003.51186.x
Coleman EA Falling through the cracks: challenges and opportunities for improving transitional care for persons with continuous complex care needs JAGS 2003 51 549 555 10.1046/j.1532-5415.2003.51185.x
Mulley GP Introduction: Alternatives to hospital care for older people Age Ageing 2001 1 30 S3
Steiner A Intermediate care – a good thing? Age Ageing 2002 30-S3 33 39
Pencheon D Intermediate care – appealing and logical, but still in need of evaluation BMJ 2002 324 1347 1348 12052787 10.1136/bmj.324.7350.1347
Carpenter I Gladman JRF Parker SG Potter J Clinical and research challenges of intermediate care Age & Ageing 2002 31 97 100 11937472 10.1093/ageing/31.2.97
Melis RJF Olde Rikkert MGM Parker SG van Eijken MIJ What is intermediate care? An international consensus on what constitutes intermediate care is needed BMJ 2004 329 360 361 15310588 10.1136/bmj.329.7462.360
Walsh B Steiner A Warr J Sheron L Pickering R Nurse-led inpatient care: opening the 'black-box' International Journal of Nursing Studies 2003 40 307 319 12605953 10.1016/S0020-7489(02)00091-3
Clendon JM Nurse-managed clinics: issues in evaluation Journal of Advanced Nursing 2003 44 558 565 14651678 10.1046/j.0309-2402.2003.02845.x
Pearson A Guest editorial: Liberating our conceptualisation of 'evidence' Journal of Advanced Nursing 2003 44 441 442 14651691 10.1046/j.1365-2648.2003.02838.x
Temmink D Francke AL Kerkstra A Huyer Abu-Saad H Dutch transmural nurse clinics for chronic patients: a descriptive study Patient Education and Counseling 2000 39 177 184 11040717 10.1016/S0738-3991(99)00020-8
Linden van der BA Spreeuwenberg C Schrijvers JP Integration of care in the Netherlands: the development of transmural care since 1994 Health Policy 2001 55 111 120 11163650 10.1016/S0168-8510(00)00125-1
Øvretveit J Evaluating Health Interventions 1998 Buckingham Philadelphia: Open University Press
Ware JJ Sherbourne CD The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection Medical Care 1992 30 473 83 1593914
Walters SJ Munro JF Brazier JE Using the SF-36 with older adults: a cross-sectional community-based survey Age Ageing 2001 30 337 343 11509313 10.1093/ageing/30.4.337
Doeglas DM Functional ability, social support and quality of life longitudinal study in patients with early rheumatoid arthritis [thesis] 2000 Groningen: Northern Centre for Health Care Research
Kempen GIJM Doeglas DM Suurmeier TPBM Groningen Activity Restriction Scale [in Dutch] 1993 Groningen: Northern Centre for Health Care Research
Grol R Improving the quality of medical care. Building bridges among professional pride, payer profit and patient satisfaction JAMA 2001 286 2578 2585 11722272 10.1001/jama.286.20.2578
Grol R Grimshaw J From best evidence to best practice: effective implementation of change in patients' care The Lancet 2003 362 1225 1230 14568747 10.1016/S0140-6736(03)14546-1
Maxwell JA Qualitative research design An Interactive Approach Applied Social Research Methods Series 1996 41 Thousand Oaks London New Delhi: Sage Publications
Fluijt H Elaborated project plan for the transfer ward at the Henriëtte Roland Holst House [in Dutch] 1999 Amsterdam: Henriëtte Roland Holsthuis
Fowler RW Congdon P Hamilton S Assessing health status and outcomes in a geriatric day hospital Public Health 2000 114 440 5 11114753 10.1016/S0033-3506(00)00384-X
Moll van Charante EP IJzermans CJ The GP clinic in IJmuiden An explorative investigation [in Dutch] 2001 Ridderkerk: Ridderprint
Academic Medical Center of the University of Amsterdam (AMC) Annual report [in Dutch] 2001 Leiden: Drukkerij Groen BV
SIGRA Facts about the labour market in the metropolitan area of Amsterdam [in Dutch] 2001 Amsterdam: SIGRA
Wiles R Postle K Steiner A Walsh B Nurse-led intermediate care: patients' perceptions International Journal of Nursing Studies 2003 40 61 71 12550151 10.1016/S0020-7489(02)00033-0
Andrews J Manthorpe J Watson R Involving older people in intermediate care Journal of Advanced Nursing 2004 46 303 310 15066111 10.1111/j.1365-2648.2004.02990.x
Roemer MI Bed supply and utilization: a natural experiment Hospitals: J Am Hosp Ass 1961 35 35 42
Noordt van M van der Zee J Groenewegen PP Regional variation in hospital admission rates in the Netherlands, Belgium, northern France, Nordrhein-Westfalen Gesundheitswesen 1992 54 173 8 1600289
Kroneman MW Health care systems and hospital bed use [thesis] 2001 Utrecht: Nivel
Griffiths P Wilson-Barnett J Richardson G Spilsbury K Miller F Harris R The effectiveness of intermediate care in a nursing-led in-patient unit International Journal of Nursing Studies 2000 37 153 161 10684957 10.1016/S0020-7489(99)00061-9
Steiner A Walsh B Pickering RM Wiles R Ward J Brooking JI Therapeutic nursing or unblocking beds? A randomised controlled trial of a post-acute intermediate care unit BMJ 2001 322 453 460 11222419 10.1136/bmj.322.7284.453
Aiken LH Clarke SP Sloane DM Sochalski J Silber JH Hospital nurse staffing and patient mortality, nurse burnout, and job dissatisfaction JAMA 2002 288 1987 1993 12387650 10.1001/jama.288.16.1987
McGillis Hall L Nursing staff mix models and outcomes Journal of Advanced Nursing 2003 44 217 226 14521688 10.1046/j.1365-2648.2003.02786.x
Schnelle JF Simmons SF Harrington C Cadogan M Garcia E Bates-Jensen BM Relationship of nursing home staffing to quality of care HSR 2004 39 225 250 15032952 10.1111/j.1475-6773.2004.00225.x
Casparie AF Sluijs EM Wagner C de Bakker DH Quality systems in Dutch health care institutions Health Policy 1997 42 255 267 10176304 10.1016/S0168-8510(97)00071-7
Sluijs E Wagner C The progress in the implementation of Quality Management in Dutch Health Care: 1995–2000 Int J Qual Health Care 2003 15 223 234 12803350 10.1093/intqhc/mzg033
Kovner AR Elton JJ Billings J Evidence-based management Frontiers of Health Services Management 2000 16 3 46 11183283
Walshe K Rundall TG Evidence-based management: from theory to practice in health care Millbank Quarterly 2001 79 429 457 10.1111/1468-0009.00214
Denis JL Lomas J Convergent evolution: the academic and policy roots of collaborative research J Health Serv Res Policy 2003 8 1 6 14596741 10.1258/135581903322405108
Lomas J Health services research: More lessons from Kaiser Permanente and Veterans' Affairs healthcare system BMJ 2003 327 1301 1302 14656811 10.1136/bmj.327.7427.1301
| 15910689 | PMC1168893 | CC BY | 2021-01-04 16:31:49 | no | BMC Health Serv Res. 2005 May 24; 5:38 | utf-8 | BMC Health Serv Res | 2,005 | 10.1186/1472-6963-5-38 | oa_comm |
==== Front
BMC Health Serv ResBMC Health Services Research1472-6963BioMed Central London 1472-6963-5-391591346010.1186/1472-6963-5-39Research ArticleA centralised public information resource for randomised trials: a scoping study to explore desirability and feasibility Langston Anne L [email protected] Marion K [email protected] Vikki A [email protected] Zoë [email protected] Health Services Research Unit, University of Aberdeen, Aberdeen, UK2005 24 5 2005 5 39 39 20 1 2005 24 5 2005 Copyright © 2005 Langston et al; licensee BioMed Central Ltd.2005Langston et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
There are currently several concerns about the ways in which people are recruited to participate in randomised controlled trials, the low acceptance rates among people invited to participate, and the experiences of trial participants. An information resource about on-going clinical trials designed for potential and current participants could help overcome some of these problems.
Methods
We carried out a scoping exercise to explore the desirability and feasibility of establishing such a resource. We sought the views of a range of people including people who were considering taking part in a trial, current trial participants, people who had been asked but refused to participate in a trial, consumer group representatives and researchers who design and conduct trials.
Results
There was broad-based support for the concept of a centralised information resource for members of the public about on-going and recently completed clinical trials. Such an information resource could be based on a database containing standardised information for each trial relating to the purpose of the trial; the interventions being compared; the implications of participation for participants; and features indicative of scientific quality and ethical probity. The usefulness of the database could be enhanced if its search facility could allow people to enter criteria such as a disease and geographic area and be presented with all the trials relevant to them, and if optional display formats could allow them to view information in varying levels of detail. Access via the Internet was considered desirable, with complementary supported access via health information services. The development of such a resource is technically feasible, but the collation of the required information would take a significant investment of resources.
Conclusion
A centralised participant oriented information resource about clinical trials could serve several purposes. A more detailed investigation of its feasibility and exploration of its potential impacts are required.
==== Body
Background
The rigorous evaluation of health care interventions requires potential users of these interventions to participate in clinical trials to assess their effectiveness. There are currently various concerns about both the small proportion of eligible people who participate in randomised controlled trials (RCTs) and the experiences of participants [1,2]. Inadequate information provision is a contributing factor to several of these concerns. For example, some people who would like to enter RCTs are not invited to do so, and struggle to identify trials for which they would be eligible [3]. Problems have been identified with the quality of information given [4]. Thus some people who are invited to participate in RCTs do not develop an adequate understanding to make a well-informed decision to participate or not [5,6]. People who agree to participate in trials sometimes struggle to make sense of their participation [7], may not know what to do if they identify questions during the course of the trial, and are often disappointed at the lack of information they are given about the progress or results of the trials [8].
An information resource about ongoing clinical trials designed for potential and current participants could help overcome some of these problems. It could serve as a source of additional, semi-independent information for people who have been invited to participate in trials, and it could help people to identify trials in which they might participate. If kept up to date, it could serve as a source of information about the progress and results of particular trials.
A number of trial registers have been established in recent years (for example, metaRegister of Controlled Trials , UKCCCR National Register of Cancer Trials ), and there has been increasing pressure for requirements that all clinical trials be registered in the public domain. [9]. Trial registers are undoubtedly helpful in terms of getting information about planned, ongoing and completed trials into the public domain and reducing the problems associated with underreporting of trials. However, the current registers are not comprehensive [10-12]. They were not designed to be easily accessible or useful to general public audiences and none were designed specifically to meet the information needs of members of the public as potential or current trial participants. It can be difficult to identify which registers are appropriate for particular purposes [12,13], and it is hard to search across registers because they do not organise and present information in a standardised way [3,13].
In this paper we report on a scoping exercise undertaken for Consumers in NHS Research (now known as INVOLVE) to assess the desirable features and feasibility of developing and providing an information resource about ongoing clinical trials for potential and current participants [14].
Methods
We recognised that people who had played different roles in relation to trials would have different perspectives on information needs relating to clinical trials. Reflecting this, we sought information and opinions from a range of people from across the UK that included: people seeking to participate in or considering participating in a trial; current and recent trial participants; representatives of national patient interest/support groups; and researchers involved in the design and conduct of trials. People who were seeking to participate and considering participating in a trial were identified through condition-specific consumer networks, in particular the National Association for the Relief of Paget's Disease (a trial investigating the treatment of Paget's disease was about to start at the time we conducted this scoping exercise). Current and recent trial participants were identified at three meetings of health care consumers and advocates. Representatives of consumer groups were selected from those patient interest/support groups with a known interest in trials (identified primarily by Consumers in NHS Research). Researchers involved in the design and conduct of trials were selected from the UK MRC trial managers network and individuals known to the research team. Several of the consumer advocates and researchers had current or recent personal experience of participating (or declining to participate) in clinical trials. We accepted their contributions from the perspective of trial participants, because the time frame of our scoping exercise did not permit us to obtain ethics committee approval to identify and approach current participants via trial offices.
We used semi-structured interviews, focus groups and e-mail discussion lists to explore the kinds of information that people want and need when considering whether or not to participate in a particular trial, and the ways they might access and use this information. We asked people to discuss the feasibility and appropriateness of 'star rated' information on the quality of particular aspects of ongoing trials, and the provision of generic guidance about how to interpret and appraise information about trials. We also asked researchers and consumer representatives what they thought made for a good quality trial and what issues might arise from an attempt to provide standardised information about ongoing randomised clinical trials in a publicly accessible participant-orientated information resource.
We used topic guides to support semi-structured interviews and focus group discussions. An example of the topic guide used with potential trial participants is included [see Additional file 1]. Most interviews were audio-taped and transcribed in full. If audio-recording was not possible, members of the research team took detailed notes. Analysis of transcripts, discussion notes and e-mails was carried out using a modified 'charting' approach [15]: to facilitate the identification of the range of views about particular issues, the points made by each participant were summarised under key headings that reflected the main areas of questioning.
Over the course of the scoping exercise we formally interviewed 25 individuals on a one-to-one basis including:
• nine potential trial participants;
• six representatives from patient interest /support groups;
• nine researchers (including trial principal investigators, trial managers and a research nurse); and
• one pharmaceutical/medical devices industry representative.
In addition, the views of 24 consumer advocates were elicited in focus groups held at national meetings of consumers and advocates, and nine consumer representatives contributed comments via e-mail. Several of the consumer advocates and researchers had personal experience of participating (or declining to participate) in clinical trials.
Results
Information elements required by potential trial participants
Our informants identified a range of information needs of potential trial participants. We grouped these into the following categories: (a) the interventions being compared; (b) the implications of trial participation for participants; (c) the scientific or methodological quality of a trial; (d) the ethical probity and governance of a trial; and (e) contact details (Figure 1).
Figure 1 The features identified as desirable for a centralised information resource about randomised controlled trials.
Interventions being compared
There was a consensus that potential trial participants need to know about the 'new' intervention being tested, its potential risks, and how it is known to compare with the current "standard" intervention and any other interventions with which it is compared in the trial. Information about the availability of relevant interventions outwith the trial was also mentioned as important.
Implications for participants
Information needs relating to implications for participants included practical issues such as the timescales for the trial interventions and follow-up, and the rationale for, and number of extra visits or investigations associated with the trial. Several informants highlighted the need for information about whether and how people could withdraw from or join the trial at a later date. They also thought that participants should be told whether or how they could gain access to data about their own outcomes and the trial findings, and about whether and how participants would be told if a trial was stopped early for any reason.
Scientific or methodological quality, and ethical probity and governance
There was a consensus that people should be able to be confident about the quality of any trial they might agree to participate in, but it was widely recognised that relatively few people would currently be able to judge the scientific quality or ethical probity of a trial for themselves on the basis of the information they are typically given for recruitment purposes. The provision of information about key features of trial quality (and/or about quality assessment) was thought desirable for a centralised resource.
Contact details
Several respondents from all categories mentioned that potential trial participants might benefit from the option to talk to someone before deciding whether or not to participate in a trial, and possibly also during the trial. The case was regularly made that two-way interaction was key to understanding information, as any misconceptions could be corrected and personal concerns could be addressed. For people who had been invited to participate in a particular trial, the options suggested were:
• having a chance to speak with a member of the trial team (preferably someone who is not related directly to a person's normal care) – someone who can explain things like randomisation;
• having a chance to talk to an independent person (i.e. someone not associated with the trial) e.g. GP, consumer advocate, voluntary health organisations, advice services; and
• having contact details, so know whom to contact if concerned about anything while participating in the trial.
People who were themselves looking for trials in which they might participate would be likely to need:
• contact details for initial enquiries about the specific trial and (possibly subsequently) local recruiting centres/clinicians; and possibly
• an information helpline staffed by people who could offer general information, answer general questions about trials, and help explain information provided about specific trials.
However, the capacity of trialists or trial centres to handle unsolicited enquiries was limited, they might be reluctant to have their contact details 'advertised' in the context of an information resource that promised help to people identify trials in which they might participate.
Aids to information appraisal
As indicated in the methods section, we explored two approaches that might help people evaluate information about trials and assess their quality: (a) a quality or "star" rating scheme in which key features of trials were allocated one- to three- star ratings; and (b) a guide to help people appraise trials for themselves.
Informants registered some strongly felt concerns about the quality ratings option. These included doubts about the feasibility of producing valid and reliable ratings across a diverse range of trials, and fears that particular ratings were likely to be contested by trial sponsors and trialists, which could create a lot of 'hassle' and work for the resource producers.
Despite the limitations of a quality ratings scheme, there was general agreement that it would be useful to indicate that key quality assurance features were in place for particular trials. The most obvious features suggested were that a trial had been through an independent peer review process (a check on scientific quality) and that it had been assessed and approved by an independent ethics committee (a check on ethical probity).
There was widespread support for the provision of a general information section within any centralised resource that could: explain the purpose of clinical trials; highlight key features and indicate points to look out for in clinical trials; provide a glossary of commonly used terms; and identify links to relevant organisations. The inclusion of a 'guide' to help people appraise the quality of a trial for themselves was also thought appropriate. This guide could be based on existing checklists developed for peer reviewers, ethics committees and consumer representatives who appraise trials, but modified for more general public use.
Key design features of a centralised resource
All informants supported the basic concept of a centralised information resource about clinical trials. This could be built using a database structure with a standard set of information elements for each trial reflecting the key areas outlined above. Respondents identified a variety of design features that could potentially enhance the usefulness of the information within the resource, including:
• A sophisticated search facility that would allow people to enter their personal details (e.g. health condition, age, gender, geographical location etc), and retrieve information on trials that fulfilled their search criteria.
• Options to view particular types of information in varying levels of detail.
• The use of a variety of media within or as a complement to the resource (for example, diagrams or video-clips to illustrate and explain trial procedures or the interventions being compared in particular trials
Potential models for providing a centralised information resource
There was widespread support for the provision of this centralised information resource on the Internet, but a clear recognition that some people would not be able to access the information effectively via this route. Opportunities for supported access via outlets in health care settings, public libraries or other community centres would also be useful. Health information services might usefully serve as valuable 'intermediaries', adding value to the resource by helping people to appraise the information and interpret it for their own use.
Discussion
One of the strengths of our study is that we canvassed views from a range of perspectives. We identified a broad-base of support for the concept of a centralised, publicly accessible, participant-oriented information resource about ongoing clinical trials. We also identified several concrete suggestions for the content and design of such a resource. However, time constraints prevented us from exploring the views of a larger sample of people, and from considering the issues we identified in more depth. We acknowledge in particular that further research is needed to explore the opinions of a wider spectrum of the 'general public' as potential users of a centralised resource for information about clinical trials, and to consider the potential implications of presenting particular elements of information and in particular ways. We also acknowledge that the potential trial participants interviewed for this study were mostly people with a chronic condition. Their perspectives may differ from potential trial participants with acute health problems. However, individuals with acute conditions were canvassed for their views as current or recent trial participants. We do not claim to have identified all possible information requirements, but are confident that we have identified the main ones.
In theory, a centralised information resource about clinical trials would have two main audiences in terms of trial participants: those who have been invited to participate in a trial and want to find out more about it, and those who have not been invited to participate in a trial, but would like to identify any ongoing trials for which they might be eligible. If the resource included updated reports on trial progress, it may also be useful to a third group of people who are currently participating in trials who want more information about the trials in which they are participating
It is unclear whether and to what extent a centralised information resource would achieve the desired aims of improving recruitment rates, and people's experiences of information provision relating to trial recruitment and participation, nor whether it would have any unwanted effects. It is not clear to what extent a publicly accessible resource might increase demand for participation in trials, nor what the implications of such demands might be. At the moment, some health care providers are not in a position to offer trial participation to their service users. Increased public awareness of particular trials might place a variety of extra burdens on health care systems, for example if patients start demanding access to particular trials and/or changing health care providers in order to gain access to them.
Other potential disadvantages of making information about trials more easily accessible should be explored. For example, breaches of privacy might become a problem if the knowledge that someone is eligible to participate in a particular trial (which is often readily obtained by third parties who observe markers on medical records or witness the receipt of mailings from a trial team) could quickly lead to the revelation of information about personal health status or health care experiences because trial eligibility criteria would be easily ascertained. Public access to trial progress reports might, depending on the nature of information provided, influence people's self-reporting of outcome status and willingness to continue to participate in a trial. Issues such as these require further consideration and investigation.
While the development of the database framework, search engine and the features identified above as desirable are technologically feasible, there are several potential barriers to the development of a participant-oriented central information resource about clinical trials. Current trial registers do not contain all the information elements that potential participants might find useful. The process of gathering, checking and updating the requisite information would be logistically challenging and time consuming, and would require considerable and sustained investment. Any attempt to include trial progress reports to the database would significantly add to the logistical challenges. However, recent trends towards increasing disclosure of information about trials, including commitments to openness from some pharmaceutical companies, will facilitate the acquisition of relevant information.
Conclusion
A centralised participant-oriented information resource about randomised trials could offer many benefits. The development of such a resource would require considerable investment, but the support for the basic concept that is evident among trial participants, consumer advocates and trialists suggest that it warrants further investigation and evaluation.
Abbreviations
UKCCR United Kingdom Coordinating Committee on Cancer Research
RCT Randomised Controlled Trial
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
All authors contributed equally to the design and execution of the study. MKC was principal investigator. ALL wrote the first draft of the manuscript. All authors contributed to the development of subsequent drafts, and read and approved the final manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Supplementary Material
Additional File 1
2001. Example Topic Guide.
Click here for file
Acknowledgements
Consumers in NHS Research (now known as INVOLVE) funded the scoping study on which this paper is based. We would like to thank the secretarial staff of the Health Services Research Unit for transcription of the interviews. Most of all we would like to extend our many thanks to the people who agreed to be interviewed or submit opinions for this study and gave generously of their time and views. The Health Services Research Unit is funded by the Chief Scientist Office of the Scottish Executive Department of Health. The views expressed are those of the authors and not necessarily those of the funders.
==== Refs
Prescott RJ Counsell CE Gillespie WJ Grant AM Russell IT Kiauka S Colthart IR Ross S Shepherd SM Russell D Factors that limit the quality, number and progress of randomised controlled trials Health Technol Assess 1999 3 20
Edwards SJL Lilford RJ Thorton J Hewison J Informed consent for clinical trials: in search of the 'best' method Soc Sci Med 1998 47 1825 1840 9877351 10.1016/S0277-9536(98)00235-4
Case Notes [Radio programme] British Broadcasting Corporation: Radio 4 28 August 2001
Lees N Dixon-Woods M Young B Heney D Thornton H CaTLET: Evaluation of information leaflets for patients entering cancer trials Psycho Oncol 2001 10 266
Thornton H Information and involvement Health Expect 2001 4 71 74 11286601 10.1046/j.1369-6513.2001.00129.x
Donovan JL Brindle L Mills N Capturing users' experiences of participating in cancer trials Eur J Cancer Care 2002 11 210 214 10.1046/j.1365-2354.2002.00341.x
Featherstone K Donovan JL 'Why don't they just tell me straight? Why allocate it?' The struggle to make sense of participating in a randomised controlled trial Soc Sci Med 2002 55 709 719 12190265 10.1016/S0277-9536(01)00197-6
Madsden S Holm S Riis P Ethical aspects of clinical trials: the attitudes of the public and outpatients J Intern Med 1999 245 571 579 10395186 10.1046/j.1365-2796.1999.00502.x
Steinbrook R Public registration of clinical trials N Engl J Med 2004 351 315 317 15269307 10.1056/NEJMp048191
Till JE Phillips RA Jadad AR Finding Canadian cancer clinical trials on the Internet: an exploratory evaluation of online resources CMAJ 2003 168 1127 1129 12719315
Tonks A A clinical trials register for Europe BMJ 2002 325 1314 1315 12468459 10.1136/bmj.325.7376.1314
Manheimer E Anderson D Survey of public information about ongoing clinical trials funded by industry: evaluation of completeness and accessibility BMJ 2002 325 528 531 12217994 10.1136/bmj.325.7363.528
Meric F Bernstam EV Mirza NQ Hunt KK Ames FC Ross MI Kuerer HM Pollock RE Musen MA Singletary SE Breast cancer on the world wide web: cross sectional survey of quality of information and popularity of websites BMJ 2002 324 577 581 11884322 10.1136/bmj.324.7337.577
Campbell M Entwistle V Langston A Skea Z Scoping Study to explore the most appropriate way to produce and disseminate information on Randomised Control Trials Report to Consumers in NHS Research 2002
Ritchie J Spencer L Bryman A, Burgess R Qualitative data analysis for applied policy research Analysis of Qualitative Data 1994 London: Routledge
| 15913460 | PMC1168894 | CC BY | 2021-01-04 16:31:49 | no | BMC Health Serv Res. 2005 May 24; 5:39 | utf-8 | BMC Health Serv Res | 2,005 | 10.1186/1472-6963-5-39 | oa_comm |
==== Front
BMC Health Serv ResBMC Health Services Research1472-6963BioMed Central London 1472-6963-5-431594147410.1186/1472-6963-5-43Research ArticleWillingness to pay to assess patient preferences for therapy in a Canadian setting Marra Carlo A [email protected] Luciana [email protected] Alan F [email protected] Amy O [email protected] M Lynn [email protected] Ruth E [email protected] Carole A [email protected] Sally [email protected] Barbara M [email protected] Peter J [email protected] Pharmaceutical Sciences Clinical Service Unit, Vancouver Hospital and Health Sciences Centre, Vancouver British Columbia, Canada2 Faculty of Pharmaceutical Sciences, Uniiversity of British Columbia, Vancouver, British Columbia, Canada2005 7 6 2005 5 43 43 29 12 2004 7 6 2005 Copyright © 2005 Marra et al; licensee BioMed Central Ltd.2005Marra et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Adult outpatient parenteral antibiotic therapy (OPAT) programs have been reported in the literature for over 20 years, however there are no published reports quantifying preference for treatment location of patients referred to an OPAT program. The purpose of this study was to elicit treatment location preferences and willingness to pay (WTP) from patients referred to an OPAT program.
Methods
A multidisciplinary, single centre, prospective study at a 1000-bed Canadian adult tertiary care teaching hospital. This study involved a WTP questionnaire that was administered over a 9-month study period. Eligible and consenting patients referred to the OPAT program were asked to state their preference for treatment location and WTP for a hypothetical treatment scenario involving intravenous antibiotic therapy. Multiple linear regression analysis was performed to determine predictors of WTP.
Results
Of 131 eligible patients, 91 completed the WTP questionnaire. The majority of participants were males, married, in their sixth decade of life and had a secondary school education or greater. The majority of participants were retired or they were employed with annual household incomes less than $60,000. Osteomyelitis was the most common type of infection for which parenteral therapy was required. Of those 87 patients who indicated a preference, 77 (89%) patients preferred treatment at home, 10 (11%) patients preferred treatment in hospital. Seventy-one (82%) of these patients provided interpretable WTP responses. Of these 71 patients, 64 preferred treatment at home with a median WTP of $490 CDN (mean $949, range $20 to $6250) and 7 preferred treatment in the hospital with a median WTP of $500 CDN (mean $1123, range $10 to $3000). Tests for differences in means and medians revealed no differences between WTP values between the treatment locations. The total WTP for the seven patients who preferred hospital treatment was $7,859 versus $60,712 for the 64 patients who preferred home treatment. Income and treatment location preference were independent predictors of WTP.
Conclusion
This study reveals that treatment at home is preferred by adult inpatients receiving intravenous antibiotic therapy that are referred to our OPAT program. Income and treatment location appear to be independently associated with their willingness to pay.
willingness to payoutpatientintravenousantibiotics
==== Body
Background
Adult outpatient parenteral antibiotic therapy (OPAT) programs have been reported in the literature for over 20 years [1]. These programs have now become an accepted alternative to inpatient therapy for select patients and infection types [2-4]. OPAT programs have been demonstrated to be a safe, effective and acceptable alternative to hospitalization [5-7]. Cost analysis of OPAT programs in the U.S., Canadian and other settings have been reported [5,8-13].
An adult OPAT program was implemented at our hospital in 1995. A cost analysis performed at our institution from 1995 to 1998 showed significant cost avoidance for both the hospital and the Ministry of Health [14]. Informal patient satisfaction surveys have shown that the program has been well received by patients. However, there are no published reports quantifying preference for treatment location of OPAT program patients. Willingness to pay (WTP) is a method of quantifying preference and this methodology is gaining popularity in health care [15-19]. WTP provides a measure of how much an individual values a particular treatment preference.
The objective of this study was to elicit hypothetical infection treatment location preferences, and the willingness to pay for this preferred treatment option from OPAT program referral patients.
Methods
This was conducted as a multidisciplinary, single centre, prospective study at a 1000-bed Canadian adult tertiary care teaching hospital. Our OPAT program receives about 250 patient referrals and provides approximately 3,000 patient-days of outpatient parenteral therapy per year [20]. General characteristics of patients managed by this service are described elsewhere [14,20]. Adult patients are accepted into the program if they had a proven or suspected infection requiring one or more parenteral antimicrobials for an expected minimum duration of 5 days, are medically stable, have an acceptable venous access, demonstrate a willingness and capability to perform the necessary self-management tasks and live in a suitable home environment with access to a telephone. Once enrolled, the OPAT pharmacist and nurses provide patient teaching, insert the appropriate vascular device, liaise with community nursing personnel, coordinate delivery of drugs and supplies and arranged appropriate patient follow up. These patients are treated in their home environment and return to the hospital periodically for follow-up purposes only. Patients requiring short courses of parenteral antibiotics are typically excluded from the program and are treated as inpatients or managed in a hospital medical daycare setting.
This study was approved by the University Ethics Committee and the Hospital Research Committee.
Patient enrollment
Patients referred to the OPAT program during the 9-month study (September 1999 – June 2000) were considered eligible for the patient preference assessment. For inclusion into the study, the questionnaire had to be administered to the patient prior to assessment by the OPAT clinical staff for possible inclusion into the program. Only consenting patients were administered the WTP questionnaire. This precaution was taken to avoid the possibility of biased responses from the participants in an attempt to obtain the treatment location of their choice.
Willingness to pay
Contingent valuation methodology (CVM) was used to quantitatively measure patient preference (i.e. WTP) for intravenous antibiotic treatment location [15-19]. CVM is a survey-based approach for eliciting a consumer's monetary valuations for program benefits for use in cost-benefit analysis. The specific methodology employed was similar to that adopted by Donaldson et al [21]. The consumer utility being measured was compensating variation and the survey measured WTP in the context of program availability. Since the questionnaires were given to individuals undertaking the valuation who were already consumers of the treatment in question (i.e. were receiving parenteral antimicrobials when enrolled) and thus the primary uncertainty at the time of the questionnaire was the probability of treatment course outcomes, an ex-post perspective was adopted [15,16].
The WTP questionnaire consisted of two hypothetical scenarios that were created based upon OPAT program data collected during the period 1995–1998 (see Additional File 1) [14]. Each hypothetical scenario involved an infection that required a 23-day course of intravenous antibiotics (the average duration of therapy for patients enrolled in the OPAT program). The first scenario described a hospital treatment course, while the second scenario described a similar treatment regimen that was administered in the home setting. Using these historic data, the risks associated with each treatment location were also provided to the patient [14]. Patients were asked to specify their preference for treatment location based upon these scenarios. Utilizing open-ended questions, patients were asked to quantify their preference by stating how much they would be willing to pay to obtain treatment in their preferred location.
The survey was initially designed and tested on ten patients, four clinical nurse specialists and two infectious diseases specialists. We utilized comments from these individuals to modify our survey in order to improved readability and understandability.
Data collection
A single investigator coordinated all patient self-administered WTP questionnaires. Partial completion of the surveys was identified in four of the first eleven patients; thereafter, the investigator examined the questionnaires for completeness at bedside and encouraged patients to provide responses if necessary. If requested by the patient, the questionnaire was read aloud and the investigator recorded the patient's responses. In these cases, the completed questionnaire was subsequently reviewed with the patient to ensure accuracy. Demographic information, socioeconomic data, infection details and WTP for treatment location were collected for all patients.
Data analysis
Means, medians and ranges for WTP by treatment preference location were determined. Differences in means and medians were testing using t-tests and Mann-Whitney U tests, respectively. To estimate an overall monetary valuation, a total WTP was calculated for patients preferring hospital treatment and a total WTP was also calculated for those preferring home treatment.
A positive association between WTP and income was assessed to determine the construct validity of our questionnaire [22]. WTP was examined for normality using histograms to determine if a natural log transformation was necessary to fit the assumptions of linear regression. Using WTP as the dependent variable, multiple linear regression was utilized. Univariate analyses were performed between each of the possible predictor variables (gender, marital status, level of education, employment, annual household income, infection type) and the dependent variable using ordinary least-squares linear regression.
Variables associated with WTP with a p-value < = 0.10 in the univariate analyses were considered in the multiple linear regression models. Adjusted r2 was calculated for the multivariable models to determine the amount of variance in the outcome variable explained by the predictor variables in the final models. Among significant variables, two-way interactions were investigated. No adjustments were made to p-values to account for multiple comparisons. Studentized residuals and Cook's distance were examined to determine if assumptions of multiple linear regression were violated. Two-sided P values are reported for all analyses. A p value of less than 0.05 was considered to be statistically significant. All analyses were conducted by using SPSS, version 10.
Results
During the 9-month study period, 131 patients were considered eligible for enrollment in the contingent valuation analysis. Of these patients, 40 were excluded, as the investigator was unavailable to conduct an interview prior to the assessment by the OPAT team, informed consent could not be obtained due to language barriers, decreased cognitive status was evident or patients simply declined to participate. The remaining 91 patients completed the WTP questionnaire.
Patient demographics and socioeconomic status are reported in Table 1. Participants were typically married males in their sixth decade of life with a secondary school education or greater. The majority of participants were retired or were employed with an annual household income of less than $60,000. Osteomyelitis was the most common type of infection for which parenteral therapy was required.
Table 1 Patient demographics
Parameter Value
No. of Patients 91
Mean age, years (range) 56 (25–81)
Gender
Male (%) 63 (69)
Marital Status (%)
Married 60 (66)
Divorced 11 (12)
Widowed 9 (10)
Single 10 (12)
Highest Level of Education (%)
Elementary School 7 (8)
Secondary School 29 (32)
Trades/Technical College 34 (36)
University Degree 16 (18)
Post-graduate 5 (6)
Employment (%)
Retired 45 (49)
Employed 29 (32)
Unemployed 16 (18)
Unknown 1 (1)
Annual Household Income (%)
< $20,000 22 (24)
$20,000–39,999 20 (23)
$40,000–59,999 22 (24)
$60,000–79,999 9 (10)
$80,000–99,999 3 (3)
$100,000–149,000 7 (8)
> $150,000 4 (4)
Unknown 4 (4)
Type of Infection (%)
Osteomyelitis 39 (43)
Infected pacemaker/wires 9 (10)
Endocarditis 9 (10)
Wound infection 7 (8)
Abscess 6 (7)
Bacteremia 4 (5)
Other1 17 (17)
1Meningitis (3), pneumonia (4), infected graft of lower limb (2), line sepsis (2), septic arthritis (2), cellulites (1), pyelonephritis (1), CMV (1), discitis (1)
Willingness to pay
Of the 91 patients who were enrolled in the study, 87 (96%) indicated a treatment location preference while the remaining four participants had no preference. Of those 87 patients who indicated a preference, 77 (89%) preferred treatment at home while 10 (11%) preferred treatment in hospital. Seventy-one (82%) patients provided an interpretable response regarding WTP for treatment in their preferred location. Of those 16 patients (13 patients with a preference for home therapy vs. 3 patient with a preference for hospital therapy) who did not provide an interpretable response, one registered an astronomically high "protest" WTP far exceeding their ability to pay, while 15 indicated a treatment preference but provided no monetary value.
For those 71 patients who provided an interpretable response, 64 patients preferred treatment at home with a median WTP of $490 CDN (mean $949, range $20 to $6250), and 7 patients preferred treatment in the hospital with a median WTP of $500 CDN (mean $1123, range $10 to $3000). Tests for differences in means and medians revealed no statistically significant differences between WTP values between the treatment locations at the 5% level. The total WTP for the seven patients who preferred hospital treatment was $7,859 versus $60,712 for the 64 patients who preferred home treatment.
The natural logarithm of WTP values approximated a normal distribution, thus satisfying this assumption of linear regression (Figure 1). Only seventy-five patients (71 patients with an interpretable response plus those 4 patients with no treatment location preference) were included in the regression analysis. Multiple linear regression analysis revealed that income and treatment location preference were independent predictors of WTP (Table 2). There was a trend towards respondents with lower incomes being willing to pay slightly less for their preferred treatment location than those with the highest incomes (p = 0.067). In addition, people who stated preferences were willing to pay significantly more for than those who did not state a preference (p < 0.001). In the multiple linear regression model that included interaction terms (adjusted r2 = 0.543), there was also a significant interaction between income and treatment location preference such that patients with the lowest income were willing to pay significantly more for hospital treatment than for home treatment (p < <0.0001). The fact that there was a significant association between WTP and ability to pay (i.e. higher income) validates the theoretical construct of our survey.
Figure 1 Table 2 WTP regression analysis1,2
Parameter β - coefficient p-value 95% Confidence Interval
Lower Upper
Intercept 0.75 0.35 -0.82 2.32
Income, $ CAN 0.067
≤ 20,000 -0.991 0.031 -1.89 -0.093
21,000–79,000 -1.011 0.037 -1.96 -0.060
≥ 80,000 Reference
Location preference <0.001
Home 6.10 <0.001 4.58 7.54
Hospital 6.13 <0.001 4.32 7.94
None Reference
1Dependent variable is the natural logarithm of WTP
2Adjusted r2 = 0.478
Discussion
To our knowledge, this is the first published report quantifying preference for treatment location in an adult OPAT program patients using WTP.
According to our WTP analysis, candidates for the program expressed an overwhelming preference for treatment in the home setting. Our results also demonstrated that the WTP values were similar between those patients who preferred to be treated at home and those who wished to remain in hospital. Accordingly, the total WTP value was greater (in fact, almost 8-fold greater) for those patients preferring treatment at home. This reflects the overall magnitude of societal preference for the management of infectious diseases that require intravenous therapy, but does not require institutionalization.
There were several limitations to this study. We conducted this trial in one adult acute care institution, thus caution must be exercised when attempting to generalize the results to other health care settings involving different patient populations, and other infectious diseases which will require different treatment regimens. We relied on a hypothetical treatment scenario in our attempt to solicit a preference location and willingness to pay for this patient population. As the scenario did not necessarily reflect the treatment that they were about to receive, we must be careful in our extrapolation of the results. Although we acknowledge the potential problems with using such scenarios in CVM, we believe that this effect was minimized by surveying patients who were currently experiencing an infection that initiated a consult from the OPAT team (i.e. the ex-post perspective). We believe that most of these individuals would be able to realistically comprehend the health outcomes described in our scenarios.
We also relied on open-ended technique rather than a bidding-game technique to solicit a WTP value. While the bidding game technique forces an upper and lower limit to the patient response and can be criticized for introducing a starting point bias, the open-ended technique has also been questioned. As described by O'Brien and Viramontes, patient naivety regarding health care costs due to the Canadian universal health insurance environment may lead to an inability to quantify the value of an expected health improvement [16]. The broad range of WTP values provided by our participants may be a reflection of this naivety. In addition, O'Brien and Gafni discuss that open-ended questions often elicit large numbers of non-responses or protest zero responses [21]. Indeed, some patients in our study expressed difficulty in placing a dollar value on their choice of treatment location. In some cases, this appeared to be a protest against the interview question and reflected a concern that their response would be used to determine a future fee for their treatment preference. In other cases, this may have been related to the fact that patients are not typically aware of, nor directly pay for, the costs of health care services in the Canadian health care system. Finally, WTP surveys measure only what a patient claims they are willing to pay for a particular treatment. The magnitude of payment is not necessarily an accurate reflection of what they would actually be willing to pay if they were to encounter the actual scenario.
As expected, ability to pay was associated with WTP and this functioned as a confirmation of construct validity of our questionnaire. Unfortunately, as mentioned by Drummond et al, there is not an actual market for most health programs and, thus, there is no "gold standard" against which one can compare WTP values [22]. It is, therefore, difficult to establish criterion validity in this context.
Conclusion
This study reveals that the majority, but not all, of adult inpatients receiving parenteral antibiotic therapy who are referred to an outpatient parenteral antibiotic therapy program prefer to be treated at home. Income and treatment location appear to independently predict their willingness to pay.
Competing interests
This was an unfunded study. The authors declare that they have no competing interests.
Authors' contributions
CM made substantial contributions to the conception, design, analysis and interpretation of the data; he was involved in the drafting of the article and revising it critically for intellectual content and has given final approval for the current version to be published. LF made substantial contributions to the conception, design, analysis and interpretation of the data; she was involved in the drafting of the article and revising it critically for intellectual content and has given final approval for the current version to be published. AG contributed to the study design, made substantial contributions to data collection, and assisted in the interpretation of the data; he was involved in the drafting of the article, revising it, and has given final approval for the current version to be published. AW contributed to the study conception, design, daily supervision of and participation in data collection, analysis and interpretation of the data; she was involved in the drafting of the article, revising it, and has given final approval for the current version to be published. LC contributed to the study design, data collection and interpretation of the data; she was involved in the drafting of the article and has given final approval for the current version to be published. RN contributed to the study design, data collection and interpretation of the data; she was involved in the drafting of the article and has given final approval for the current version to be published. CL contributed to the study design, data collection and interpretation of the data; she was involved in the drafting of the article and has given final approval for the current version to be published. ST contributed to the study design, data collection and interpretation of the data; she was involved in the drafting the article and has given final approval for the current version to be published. BF contributed to the study design, data collection and interpretation of the data; she was involved in the drafting of the article and has given final approval for the current version to be published. PJ was the coordinating investigator, made substantial contributions to the conception, design, analysis and interpretation of the data; he was involved in the drafting of the article and revising it critically for intellectual content and has given final approval for the current version to be published. All authors take public responsibility for appropriate portions of the content of the manuscript and all authors have read and approved the final manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Supplementary Material
Additional File 1
WTP BMC HSR Version 1 PJJ appendix 1.doc. This file contains the questionnaire used for this study
Click here for file
Acknowledgements
The investigators are (or were) members of the Pharmaceutical Sciences Clinical Service Unit at VHHSC and this work was conducted as part of their professional and academic obligation to the institution, and to the patients we serve. We thank these patients, and our colleagues for their contributions to this effort.
==== Refs
Stiver HG Telford GO Mossey JM Cote DD van Middlesworth EJ Trosky SK McKay NL Mossey WL Intravenous antibiotic therapy at home Ann Intern Med 1978 89 690 3 717941
Kind AC Williams DN Persons G Gibson JA Intravenous antibiotic therapy at home Arch Intern Med 1979 139 413 5 434994 10.1001/archinte.139.4.413
Poretz DM Home intravenous antibiotic therapy Clin Geriatr Med 1991 7 749 63 1760792
Poretz DM Eron LJ Goldenberg RI Gilbert AF Rising J Sparks S Horn CE Intravenous antibiotic therapy in an outpatient setting JAMA 1982 248 336 9 7087128 10.1001/jama.248.3.336
Grayson ML Silvers J Turnidge J Home intravenous antibiotic therapy. A safe and effective alternative to inpatient care Med J Aust 1995 162 249 53 7891605
Tice AD Experience with a physician-directed, clinic-based program for outpatient parenteral antibiotic therapy in the USA Eur J Clin Microbiol Infect Dis 1995 14 655 61 7588860 10.1007/BF01690748
Montalto M Patient's and carers' satisfaction with hospital-in-the-home care Int J Qual Health Care 1996 8 243 51 8885188 10.1016/1353-4505(96)00029-4
Balinsky W Nesbitt S Cost-effectiveness of outpatient parenteral antibiotics: a review of the literature Am J Med 1989 87 301 5 2505615
Williams DN Bosch D Boots J Schneider J Safety, efficacy, and cost savings in an outpatient intravenous antibiotic program Clin Ther 1993 15 169 79 8458046
Chamberlain TM Lehman ME Groh MJ Munroe WP Reinders TP Cost analysis of a home intravenous antibiotic program Am J Hosp Pharm 1988 45 2341 5 3228090
Parker SE Nathwani D O'Reilly D Parkinson S Davey PG Evaluation of the impact of non-inpatient i.v. antibiotic treatment for acute infections on the hospital, primary care services and the patient J Antimicrobiol Chem 1998 42 373 80 10.1093/jac/42.3.373
Thickson ND Economics of home intravenous services Pharmacoeconomics 1993 3 220 7 10146945
Cote D Oruck J Thickson N A review of the Manitoba home i.v. antibiotic program Can J Hosp Pharm 1989 42 137 41 10294299
Stiver G Wai A Chase L Frighetto L Marra C Jewesson P Outpatient intravenous antibiotic therapy: The Vancouver Hospital experience Can J Infect Dis 2000 11 11A 14A
Gafni A Willingness to pay. What's in a name? Pharmacoeconomics 1998 14 465 70 10344912
O'Brien B Viramontes JL Willingness to pay: a valid and reliable measure of health state preference Medical Decision Making 1994 14 289 98 7934716
O'Brien B Gafni A When do the dollars make sense? Toward a conceptual framework for contingent valuation studies in health care Med Decis Making 1996 16 288 99 8818128
Bala MV Mauskopt JA Wood LL Willingness to pay as a measure of health benefits Pharmacoeconomics 1999 15 9 18 10345161
McIntosh E Donaldson C Ryan M Recent advances in the methods of cost-benefit analysis in healthcare Pharmacoeconomics 1999 15 357 367 10537954
Wai AO Frighetto L Marra CA Chan E Jewesson PJ Cost analysis of an adult Outpatient Parenteral Antibiotic Therapy (OPAT) Programme. A Canadian teaching hospital and Ministry of Health perspective Pharmacoecon 2000 18 451 7
Donaldson C Hundley V Mapp T Willingness to pay: A method for measuring preferences for maternity care? Birth 1998 25 32 39 9534503 10.1046/j.1523-536x.1998.00032.x
Drummond MF O'Brien B Stoddart GL Torrance GW eds Methods for the Economic Evaluation of Health Care Programmes 1997 2 Oxford University Press, Oxford
| 15941474 | PMC1168895 | CC BY | 2021-01-04 16:31:49 | no | BMC Health Serv Res. 2005 Jun 7; 5:43 | utf-8 | BMC Health Serv Res | 2,005 | 10.1186/1472-6963-5-43 | oa_comm |
==== Front
BMC Mol BiolBMC Molecular Biology1471-2199BioMed Central London 1471-2199-6-141595816610.1186/1471-2199-6-14Research ArticleComparative 3-D Modeling of tmRNA Burks Jody [email protected] Christian [email protected]üller Florian [email protected] Iwona [email protected] Jacek [email protected] Department of Animal Sciences, Cellular and Molecular Biosciences Program, Auburn University, Auburn, AL 36849 USA2 Department of Molecular Biology, University of Texas Health Science Center at Tyler, 11937 US Hwy 271, Tyler, 75708 TX USA3 Max Planck Institute for Molecular Genetics, Ihnestrasse 73, D-14195, Berlin, Germany2005 15 6 2005 6 14 14 28 1 2005 15 6 2005 Copyright © 2005 Burks et al; licensee BioMed Central Ltd.2005Burks et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Trans-translation releases stalled ribosomes from truncated mRNAs and tags defective proteins for proteolytic degradation using transfer-messenger RNA (tmRNA). This small stable RNA represents a hybrid of tRNA- and mRNA-like domains connected by a variable number of pseudoknots. Comparative sequence analysis of tmRNAs found in bacteria, plastids, and mitochondria provides considerable insights into their secondary structures. Progress toward understanding the molecular mechanism of template switching, which constitutes an essential step in trans-translation, is hampered by our limited knowledge about the three-dimensional folding of tmRNA.
Results
To facilitate experimental testing of the molecular intricacies of trans-translation, which often require appropriately modified tmRNA derivatives, we developed a procedure for building three-dimensional models of tmRNA. Using comparative sequence analysis, phylogenetically-supported 2-D structures were obtained to serve as input for the program ERNA-3D. Motifs containing loops and turns were extracted from the known structures of other RNAs and used to improve the tmRNA models. Biologically feasible 3-D models for the entire tmRNA molecule could be obtained. The models were characterized by a functionally significant close proximity between the tRNA-like domain and the resume codon. Potential conformational changes which might lead to a more open structure of tmRNA upon binding to the ribosome are discussed. The method, described in detail for the tmRNAs of Escherichia coli, Bacillus anthracis, and Caulobacter crescentus, is applicable to every tmRNA.
Conclusion
Improved molecular models of biological significance were obtained. These models will guide in the design of experiments and provide a better understanding of trans-translation. The comparative procedure described here for tmRNA is easily adopted for the modeling the members of other RNA families.
==== Body
Background
Transfer-messenger RNA (tmRNA), also known as 10Sa RNA or ssrA RNA, is a hybrid of a tRNA-like domain (TLD) and a mRNA-like domain (MLD) connected by a variable number of pseudoknots [1]. TmRNA is a stable and essential component of trans-translation, a quality-control process that rescues ribosomes stalled on mRNAs lacking stop codons. During trans-translation, ribosomes switch from a defective mRNA (lacking its translation-termination signal) to the MLD of tmRNA. Because a stop codon is provided by the tmRNA, the ribosomes can dissociate and recycle [2]. As an additional advantage, the tandem translation of the two templates generates a tagged polypeptide which is degraded by housekeeping proteases [3,4].
For tagging, tmRNA has to be charged by aminoacyl-tRNA synthetases [5]. Assisted by protein SmpB, the charged tmRNA is delivered to stalled ribosomes as a quaternary complex with EF-Tu and GTP. Binding of tmRNA to ribosomes is facilitated by ribosomal protein S1, which interacts with the MLD and pseudoknots but not with the TLD [6-9]. Recently, cryo-EM revealed the shape of the tmRNA associated with SmpB and EF-Tu in its ribosome-bound form [10]. Despite this significant progress, high-resolution structures as obtained by NMR and X-ray crystallography are unavailable and expected to be difficult to obtain in the foreseeable future due to the relatively large size and flexibility of the tmRNA.
In the present work we used a stepwise procedure for arriving at high-resolution models for the entire tmRNA molecule. First, 2-D structures were obtained by covariation analysis of a large number of tmRNA sequences. The basepairing information was submitted to the ERNA-3D modeling program [11] to build the helical sections. Structural motifs of the loops and turns were identified in SCOR [12], high-resolution data were extracted from known structures, and these data were incorporated into the models. Overall, significantly improved 3-D models were obtained which will be useful to understand the role of tmRNA in trans-translation. The described approach can be adapted to obtain high-resolution models of the members of other RNA families.
Results
Identification of tmRNA sequences
The tmRNA sequences were identified previously and subjected to comparative sequence analysis (CSA) as described [1,13]. New tmRNA sequences were obtained from the tmRNA website [14], through keyword searches of the literature and GenBank [15], or BLAST [16,17], and various genome sequencing projects. The new sequences were examined iteratively as described in Materials and Methods to confirm tmRNA identity, remove sequence duplications, and create a meaningful alignment.
New potential tmRNA sequences were maintained as a preliminary alignment in BioEdit [18], separate EMBL-formatted sequence files, and a HTML-formatted phylogenetic list. The sequences were ordered phylogenetically using the information in the Ribosomal Database Project (RDP) [19]. If the organism name was not listed in the RDP, the sequence was placed next to its closest relative using the NCBI Taxonomy resource [20].
Selection of tmRNA sequences
The new sequences were confirmed individually as tmRNAs by comparison with the closest relative using the pairwise alignment feature of BioEdit [18]. If there was a lack of obvious similarity, the sequence was inspected for evidence of biological features such as the ability to form a TLD and an open reading frame. Furthermore, the possibility of a two-part tmRNA was considered. A sequence suspected to be a new tmRNA was investigated further by CSA [13] as described in Materials and Methods.
Potential new sequences of the alpha-Proteobacteria and some Cyanobacteria that were encoded in two separate sections of their genes [21], were compared to the two-part tmRNA sequence from a closest relative for effective comparison with the one-part tmRNAs. The 3'- and 5'-ends of each section were determined by pairwise alignment to generate a single sequence. Each of the 20 new two-part tmRNAs (14 sequences from alpha-Proteobacteria and six from Cyanobacteria) was subjected to this rearrangement.
Comparative Sequence Analysis
Sequences were ordered phylogenetically using the RDP [19] as a guide or by alignment with the closest relative. Identical regions were aligned first. Subsequently, similar regions were aligned using invariant positions as signposts. Regions of biological significance, such as the resume and stop codons, were then considered. Finally, common secondary structure features were used to align regions that lacked primary structure similarity or biological features. Supported Watson-Crick basepairs and G-U interactions were indicated in the alignment by uppercase letters. Gaps were introduced to account for differences in sequence length and to avoid the alignment of dissimilar regions.
Secondary structure was determined using covariation analysis as described [13] (see also Materials and Methods). The alignment was examined to identify compensatory base changes (CBCs) and other covariations. The numbers of CBCs and mismatches between the alignment columns were counted. CBCs provided positive evidence for the existence of a basepair; mismatches provided negative evidence. If the number of compensatory base changes was two times or greater than the number of mismatches, the basepair was considered supported. If a basepair was invariant, no evidence for or against its existence could be gained from CSA. A basepair was considered specific to a particular phylogenetic group if it was proven only in that group.
Quality control
To check for the proper assignment of basepairs, the alignment was sent through an automated pipeline of programs from RNAdbTools [22]. The output was inspected visually and corrections were made manually using the BioEdit program [18]. The revised alignment was resubmitted to RNAdbTools, and the review process was repeated until a satisfactory alignment was produced.
TmRNA alignment
The final alignment contained a total of 274 tmRNA sequences in 16 bacterial phylogenetic groups. A complete phylogenetic list is available at the tmRDB [23]. There was a substantial increase in the number of two-part tmRNAs for a total of 27 sequences: 20 from alpha-Proteobacteria (20 tmRNAs), one mitochondrial tmRNA, and six cyanobacterial tmRNAs. The nine organelle sequences included one from a cyanelle, six from chloroplasts, one from a plastid, and one from the Reclinomonas americana mitochondrion. The typical tmRNA was about 350 nucleotides long. The R. americana mitochondrion tmRNA contained only 189 nucleotides and, since it appeared to lack an ORF, may not be functional. Excluding this exception and any partial tmRNAs, the tmRNA of Synechococcus species PCC7009 was the shortest (250 nucleotides), and the longest was from Chlamydophila psittaci (425 nucleotides). The tmRNA alignment is provided as additional files 1: tmRNA-alignment.html, 2: tmRNA-alignment-wide.txt, 3:tmRNA-alignment-92col.txt, and 4: tmRNA-alignment.msf.
Secondary structure of tmRNA
The tmRNA secondary structure features were extracted from the alignment and are listed in phylogenetic order in Table 1. The representative secondary structure of Escherichia coli tmRNA is shown in Figure 1. Secondary structures of Bacillus anthracis and Caulobacter crescentus are presented in as additional file 5: Banthracis2D.pdf and additional file 6: Ccrescentus2D.pdf, respectively.
TLD (helices 1, 2a and 12)
Although a prominent feature of each tmRNA, the TLD was relatively weakly supported by CSA due to a high degree of sequence conservation. However, the structure of this region is well established by experimental evidence [24-26].
Helix 1 contained seven basepairs and was usually continuous with the exception of the Anabaena species tmRNA, which contained an insertion in the 3'-portion of helix 1. The first pair (1G-C359 in E. coli tmRNA) was conserved with one exception in Alcaligenes eutrophus where there was a 1U-C345 mismatch possibly due to a sequencing error. The second (2G-C358,E. coli numbering, Figure 1) and third pair (3G-U357) of helix 1 were invariant and therefore neither supported nor disproved by CSA. The identities of the bases involved in the fourth (4G-C356) and fifth pair varied. The closing pair of helix 1 (7G-C353) was conserved with the exception of a 7U-A388 pair the Trichodesmium erythraeum tmRNA. The single-stranded region between helices 1 and 2a ranged from ten in Dehalococcoides ethenogenes to 13 nucleotides in one Clostridium acetobutylicum sequence. A U-A basepair (U6 in chain A with A88 in chain B) was possible in the R. americana mitochondrion tmRNA.
Helix 2a was equivalent to the anticodon stem of tRNA and contained eight supported basepairs as well as a short variable internal loop in the 5'half of the helix that occurred in a few sequences (e.g. Caulobacter crescentus, see additional file 6: Ccrescentus2D.pdf). The first position in the helix was a conserved cytosine (C21 in E. coli) which formed a weakly-supported basepair with the conserved G333. The partial tmRNA from the chloroplast of Pavlova lutheri contained a uracil in the first position, but no information regarding the 3'portion of helix 2a was available.
The T-loop and helix 12 were highly conserved, although many sequences lacked information about helix 12 due to primer annealing during PCR amplification. Helix 12 contained four strongly supported basepairs and a fifth conserved G-C pair (340G-C348 in E. coli; Figure 1). The Dehalococcoides ethenogenes tmRNA had the potential to form a sixth basepair in helix 12. Helix 12 was almost always continuous, except for the tmRNA of Carboxydothermus hydrogenoformans which possessed four basepairs and a mismatched U333 and C347. A 331-GG-332 preceded U333 in C. hydrogenoformans and followed the conserved 328-GAC-330. Therefore, U333 was unlikely to pair. In the T-loop, the U341 and U342 (E. coli tmRNA) seen in most sequences were replaced by two guanines in the tmRNA from the R. americana mitochondrion (G79 and G80 in chainB) [21]. In the tmRNA from Caulobacter crescentus, the nucleotide corresponding to U342 in E. coli tmRNA was changed to G62 in chainB (see additional file 6: Ccrescentus2D.pdf).
Helical sections 2b, 2c and 2d
Overall, sections 2b, 2c, and 2d were well supported. Sections 2a and 2b were separated by a variable loop ranging from one to seven nucleotides in the 5'portion and from one to nine nucleotides in the 3'portion. Sections 2b and 2c had the potential to form a continuously stacked helix (e.g. in Chlamydophila psittaci tmRNA). Usually, a bulge of two to six nucleotides separated helical sections 2c and 2d (residues 309–311 in E. coli tmRNA, Figure 1). An asymmetrical loop was present in some sequences (for example, residues 40–41 in chainA, and 27–31 in chainB of Caulobacter crescentus tmRNA, see additional file 6: Ccrescentus2D.pdf). Helix 2d was the most conserved of the three helical sections. The G43-U308 basepair (E. coli numbering) in helix 2d was only weakly supported, conserved in most phylogenetic groups, but altered in the Thermatogales, Cyanobacteria, alpha-Proteobacteria, and Gram-positive bacteria. A 46A-U334 pair was possible in the Synechocystis species PCC6803 tmRNA.
Pseudoknot 1 (helices 3 and 4)
Pseudoknot 1 (pk1) was well supported. Of the three connecting regions, the two 5'-regions were very short (no or only one residue) while the third was relatively long (one to 11 residues). All pseudoknots in tmRNA followed the same general design [27]. Most sequences contained helices 3 and 4, with the exception of the tmRNA from Oenococcus oeni and the partial sequence from the chloroplast of Pavlova lutheri, both of which lacked helix 4 and thus did not form a pseudoknot. Helix 3 usually contained five basepairs. However, a sixth pair was possible in some bacteria.
Helix 4 could be split into helicalsections 4a and 4b by a bulge seen in 46 sequences (position57 in B. anthracis tmRNA; see additional file 5: Banthracis2D.pdf) or an internal loop seen in 52 tmRNA sequences. The adenine-rich terminal loop between the downstream halves of helices 3 and 4 ranged in length from twoto13 nucleotides.
The mRNA-like region (MLD)
The MLD consisted of an open reading frame (ORF) preceding helix 5 and varied from 48 (Heliobacillus mobilis) to 126 nucleotides (Odontella sinensis chloroplast). The resume codon usually coded for alanine, but for glycine in 30 sequences (e.g. Bacillus anthracis), aspartic acid in three sequences (e.g. Staphylococcus epidermidis), arginine in two uncultured species (FS1 and LEM2), serine in the uncultured species RCA1, and glutamic acid in Mycoplasma pulmonis.
Although helix 5 was only weakly supported by CBCs, recent site-directed mutagenesis experiments combined with functional studies in vivo and in vitro [28] provide strong evidence for its existence. One to three stop codons were located within the helix 5 loop. A single UAA stop codon was present in 157 sequences. UAG (17 sequences) or UGA (10 sequences) were used less frequently. In 85 sequences there were two in-frame stop codons, where UAA was always the first codon, followed by another UAA (73 sequences), UAG (10 sequences) or UGA (2 sequences). Curiously, two sequences (Bacillus megaterium and Chloroflexus aurantiacu) were found to contain three tandem in-frame stop codons.
Pseudoknot 2 (helices 6 and 7)
Pseudoknot 2 was well supported and similar in overall design to pk1. Helical sections 6b and 6c showed a potential to form a continuous helix in Thermotoga maritima. In beta-Proteobacteria, 6b was replaced by a short hairpin6d [1]. Helix 6d was observed also in three tmRNAs of the gamma-Proteobacteria Acidithiobacillus ferroxidans and Francisella tularensis.
Pseudoknot 3 (helices 8 and 9)
Pseudoknot 3 was well supported but missing in Cyanobacteria and the organelles (Table 1). Helical sections 8a and 8b were likely to be continuously stacked because a single helix was present in some species such as Aquifex aeolicus. The unusual purine-rich internal loop between helical sections 8a and 8b was present in most gamma-Proteobacteria suggesting a special function.
Pseudoknot 4 (helices 10 and 11)
This feature was well supported and was similar in design to the other tmRNA pseudoknots. Helical sections 10a and 10b had the potential to stack because a single helix was present in Prevotella intermedia. In some Cyanobacteria sequences, however, pk4 was replaced with two smaller tandem pseudoknots.
Secondary structure prediction of the MLD
Because CSA was unable to determine secondary structure for a large portion of the MLD, energy calculations were carried out aimed to predict structure for the single-stranded portion of the open reading frame. The region corresponding to residues 79–107 of E. coli tmRNA (Figure 1) was extracted from the alignment. A representative alignment of 197 sequences was submitted to Mfold [29]. Each sequence had the potential to form at least one helix, designated "m" (see Figure 1, additional file 5: Banthracis2D.pdf, and additional file 6: Ccrescentus2D.pdf). Two or more adjacent helices were predicted for 17 sequences. The number of basepairs varied from two in Chloroflexus aurantiacus to ten in Mycoplasma pulmonis.
Secondary structures of three representative tmRNA molecules
Secondary structures were determined for all sequences in the alignment but only three were extracted, diagrammed, and processed for 3-D modeling.
Secondary structure of E. coli tmRNA
The 363-nucleotide tmRNA of the gamma-Proteobacterium Escherichia coli represented the typical tmRNA containing the TLD, the MLD, and four pseudoknots (pk1 to pk4) encompassing the pseudoknot domain (PKD). The 90-GCA-92 resume triplet coded for alanine. Two in-frame UAA stop codons (positions 120–125) were located within the terminal loop of helix 5 (Figure 1). Three basepaired regions (shown boxed) were only weakly supported by CSA. Helixm (residues 87–98) was predicted only by energy calculations. A slightly different helix involving residues 88–100 has been suggested by footprinting of E. coli tmRNA [30]. The evidence for the 112U-A133 basepair was weak, but was included due to the possibility of extending helix 5 (Materials and Methods). Helical section 5a (residues 108–113 and 134–137) was enlarged by the weakly supported 108G-C137, 110U-A135 and 111U-G134. The 109C-G136 pair was disproved. In helix 10ab, the basepair between 256G-C275 was only weakly supported. Helix 10ab (residues 248–256 and 274–283) could be extended by the boxed 257U-G274 pair.
Secondary structure of Bacillus anthracis tmRNA
Overall, the secondary structure of Bacillus anthracis tmRNA (see additional file 5: Banthracis2D.pdf) was similar to that of E. coli. One notabledifference was a bulged uridine (U57) between helical sections 4a and 4b in pk1. A three-basepair helixm was predicted. The resume triplet (residues 89–91) coded for glycine, and the UAA stop codon was located at residues 119–121. Two weakly-supported pairs (108C-G132 and 109U-A131) extended helical section 5a.
Secondary structure of Caulobacter crescentus tmRNA
Caulobacter crescentus tmRNA (additional file 6: Ccrescentus2D.pdf) consisted of two chains, A and B, of 213 and 83 residues, respectively. The resume codon (82-GCG-84 of chainA) coded for alanine and was followed by a UAA stop codon at residues 121–123. Helical sectionsm1 and m2 were predicted by energy calculations. There was weak support for 5a (G109-U135 and 111C-G133 in chainA), and the 106U-A138, 107U-A137, 108C-G136, and 110C-G134 in chainA were disproved. The pseudoknots were relatively small. Helix 11 corresponded to the absent pk4 (residues 1–18 in chain B).
Tertiary structure modeling and visualization of tmRNA
ERNA-3D, a program developed to model RNA in three dimensions [11], was used on an SGI workstation as described in Materials and Methods. E. coli tmRNA was selected because this tmRNA is the subject of extensive research. B. anthracis tmRNA was chosen as an example of a tmRNA from a Gram-positive bacterium, and C. crescentus tmRNA was selected it represents a two-part tmRNA.
In order to create the initial models, the sequence and basepairing information were entered into an ERNA-3D input file to automatically generate A-form RNA for the helices sections and specify the single-stranded regions using ERNA-3D's algorithm [11]. Since ERNA-3D avoided an XYZ coordinate system as reference for the user, the manipulation of the model from the viewer's perspective was simple and intuitive. The coordinates of each model were saved in PDB format [31] for compatibility with other molecular modeling programs. Motifs (listed in Tables 2 to 4) were selected to model the loops and turns of a particular tmRNA. ERNA-3D selection files were generated to define clusters and place the motif in 3-D without disturbance to the rest of the model. The 3-D cursor box was used to manipulate a cluster in three-dimensional space, similar to the manipulation of a section of a physical model.
Numerous high-resolution structures determined by NMR or X-ray crystallography represented a rich source of detailed information for defining biologically meaningful motifs. The SCOR database [12] provided a way to find suitabletemplates. In rare cases when a SCOR search for a motif did not result in an acceptable match (e.g. motif 9, Table 2), the nucleotides were positioned manually in ERNA-3D. Otherwise, the coordinates were obtained from the Protein Data Bank PDB [32], extracted using the program Swiss-PDBViewer [33], and imported into ERNA-3D. The source motif and the region to be modeled were selected as separate clusters and aligned in three dimensions using common features (usually a shared basepair). Once superimposed, the coordinates of the residues in the source motif were copied onto the corresponding residues in the model. The template was then deleted, leaving a biologically meaningful structure. The backbone connections between the motif and the rest of the model were inspected visually and, if needed, manual adjustments were made to correct bond lengths and tetrahedral angles involving the phosphorous atom at the joint between the extracted motif and the helical structures generated by ERNA-3D.
As an example of the motif modeling process, the purine-rich loop in E. coli pk3 (positions 204–206 and 223–225) was constructed using a similar loop in the 30S ribosomal subunit. First, the purine-rich loop was defined as motif 11a (Table 2), and used to search the SCOR database. Positions 780–782 and 800–802 in the structure of the Thermus thermophilus 30S ribosomal subunit [34] were found to conform to the motif. The 30S ribosomal subunit coordinates (1J5E.pdb in this case) were downloaded from the PDB and displayed using Swiss-PDBViewer. The coordinates of the loop and the closing basepairs were extracted and inspected to confirm that the structure was compatible. The clustered regions were aligned with the ends of helical sections 8a and 8b at the basepairs 203U-G226 and 207A-U222 of the E. coli model and 779C-G803 and 783C-G799 of the template. Template positions 780-AAA-782 and 800-GUA-802 were then copied onto 204-GGA-206 and 223-GAA-225 of the model. The template was deleted and the bond lengths and angles involving the atoms of the phosphates of residuesU203, G222, A206, and U222 were adjusted.
In some instances, the tmRNA sequence alignment was reinvestigated using ideas derived from the 3-D model. For example, the alignments of pk1 in Bacillus anthracis tmRNA and relatives was changed from a two nucleotide bulge (56-AU-57) between helical sections 4a and 4b to a more feasible and equally well supported one-nucleotide bulge (U57, see additional file 5: Banthracis2D.pdf). The alignment of helix 10 in pk3 in B. anthracis tmRNA and relatives was altered from a 237C-A269 mismatch and an asymmetrical loop (C239 and 266-GU-267) to a single looped-out C269. The alignment of pk3 of Caulobacter crescentus and relatives was changed from four basepairs and a weakly supported fifth pair in helix 8 (between 174G-C196 of chainA) to the four basepair structure seen in additional file 6: Ccrescentus2D.pdf. Information about spatial neighborhoods as obtained from cross-linking, site-directed mutagenesis, and functional testing of E. coli tmRNA was introduced and is described in detail below. All models were inspected visually for correct bond angles and distances around the phosphorous atoms at the joints between the extracted motifs and the helical regions generated by ERNA-3D. The coordinates are provided as additional file 7: Ecoli-closed.pdb, 8: Ecoli-open.pdb, 9: Banthracis-closed.pdb, and 10: Ccrescentus-closed.pdb.
3-D model of E. coli tmRNA
The model shown as a ribbon diagram in Figure 3 consists of a compacted MLD and PKD with the TLD extending from the body of the molecule due to the near-coaxial stacking of the helix 2 sections. The coordinates for the TLD were taken from a previous model [35] which is based on two cross-linked sites, one formed between nucleotides U9/U10 near the 5' end and nucleotides C346/U347 in the T loop, the other involving residues at positions 25–28 and 326–329 within helix 2a (motif 2 in Table 2). Important features of the TLD include the non-Watson-Crick base pairs formed by 19-GA-20 and 333-GA-334 which have been confirmed by site-directed mutagenesis [36].
A very efficient UV-induced cross-link observed between the stop codon loop of helix 5 and pk2 of E. coli tmRNA (Wower et al., unpublished) introduced a considerable constraint of helices 5, 6, and 7, and, as has been shown recently, is consistent with the cryo-EM structure of ribosome-bound tmRNA of the initial stage of trans-translation [10]. Also considered was the previously-discovered covariation [37] between C44 and C66 (E. coli numbering, Figure 1) which determines the orientation of helix 2 in relation to helix 3 and thus the approximate angle by which the TLD protrudes. The 44/66 covariation is strongly supported (26 covariations versus four mismatches) in an alignment of 143 representative sequences (not shown). Since this is a non-Watson-Crick covariation, it is difficult to propose a precise structure in this region. More extensive studies will be required to better understand the nature of the 44/66 covariation.
Overall, the distance between the 3'end and A231 in pk3 was 180 Å, and 70 Å between the outside edges of pk1 and pk4. Helix 5 and pk2 were positioned in a parallel fashion. The nucleotides in the bulge between helical sections 6a and 6b (motif 9, Table 2) were adjusted manually to allow for a close fit of helix 5 and pk2. This model is supported by the finding that mutations that destroy base pairing in helix 5 substantially decrease tmRNA tagging activity (Wower et al, in press) and abolish the long-distance interaction between helix 5 and pk2 as judged by the absence of a cross-link between the stop codon loop of helix 5 and pk2 (Wower, unpublished data). Evidence for the existence of helix 5 has been provided by the analysis of compensatory mutations which completely restore tagging [28]. Each of the four pseudoknots displayed the previously determined structural properties characterized by extensive helical stacking [27]. The MLD and pseudoknots were arranged in a central loop with the resume codon positioned near the junction between helices 2a and 2b (motif 3a, Table 2). Our model reflects the finding that the pseudoknots are functionally interchangeable [38] and thus are likely to retain a considerable level of structural independence. Furthermore, data derived from cross-linking experiments showing that pk2 and pk3 are in close proximity whereas helix 5 and pk4 are further apart (Wower, unpublished data) agree with the presented model.
3-D model of B. anthracis tmRNA
The 3-D model of the B. anthracis tmRNA (Figure 4) was similar to the E. coli model. A sharper angle was modeled between helix 2 axis and the PKD. The dimensions were 150 Å from the 3'end to the distant edge of pk2, and approximately 80 Å between the outer edges of pk2 and pk4, respectively.
3-D model of C. crescentus two-part tmRNA
Compared to the other two tmRNA models, the two-part tmRNA Caulobacter crescentus model (Figure 5) was slightly more elongated. It measured 195 Å from the 3'-end of chainB to the single-stranded region between pk2 and pk3. The distance between helix 5 and the 3'end of chainA was 55 Å.
Discussion
We have compared a growing number of tmRNA sequences from all groups of bacteria to produce an alignment from which the secondary structure of any tmRNA could be easily extracted. Most basepairs were supported by phylogenetic evidence, whereas only a few helical sections required energy calculations. Uncertainties in assignment of basepairs, such as the pseudoknot region of chloroplasts and one-piece cyanobacterial tmRNAs, may be eliminated in the future when more sequences will become available.
The common layout of the secondary structures indicated a similar function in all bacteria. The number and size of the pseudoknots varied, supporting the idea that the pseudoknots may only enhance the essential functions carried by the TLD and the MLD [28]. Differences in the secondary structure features were usually not random but occurred between groups of related organisms. For example, helix 6d was present only in the beta- and three close relatives of the gamma-Proteobacteria. Whether these group-specific features are responsible for differences in the trans-translation mechanism remains to be determined. However, strategies that exploit these differences, for example for developing new antibiotics targeted at a specific group of bacteria, can now be envisioned.
In principle, tertiary structure models of any tmRNA in the alignment could be built using the described procedures. Here, we have shown how to generate a biologically more meaningful model of E. coli tmRNA which represents a significant progress from a previous model [27]. We also constructed 3-D model of the tmRNAs of B. anthracis and C. crescentus. Overall, the three models were similar in shape and size confirming that all tmRNAs have the potential to function similarly in trans-translation. The TLD mimicked the L-shape of canonical tRNA [39] and may be necessary for proper association tmRNA with the EF-Tu, SmpB, and subsequent binding to the ribosomal A-site. The lack of a D-stem has been suggested to confer flexibility [40], but SmpB may be responsible for stabilizing this region [41,42].
Differences in the shapes of the three tmRNA models (e.g. the angle between helix 2 and the main body of the molecule) may be due to the difficulty in determining the precise arrangement of the pseudoknots. Considering that the pseudoknots are likely to constitute relatively independent structural units, conformational changes might occur around the connecting single strands, as well as in the MLD and the weakly-supported helix m. TmRNA may become less flexible when bound to proteins such as SmpB and ribosomal protein S1. EF-Tu, however, likely binds to the coaxially-stacked helices 1 and 12 [43], and therefore appears to have little effect on the conformation of the TLD. Protein SmpB was found to bind near helix 2a [41,44], has two RNA binding sites [45], and thus could make additional contacts with other regions. Protein S1 is the largest ribosomal protein, has been shown to be close to numerous sites, and to be required for the binding of tmRNA to the ribosome [7]. Since S1 is a flexible, beadlike protein [46] it may not restrict the conformational potential of the tmRNA molecule. Instead, the protein may instill some constraint to the large central loop formed by the PKD and the MLD. Because S1 is known to melt helices in mRNAs [47], it is also possible that it unwinds helix m and exposes the resume codon and the preceding nucleotides U85 and A86 for efficient trans-translation [48,49].
The tmRNA models show the resume codon in close proximity to the internal loop formed between helical sections 2a and 2b. This arrangement would allow the ribosome to "jump" a relatively short distance from the end of the broken mRNA onto the ORF of tmRNA. In a recent cryo-EM study of the initial stage of trans-translation [10], the tRNA-like region, SmpB, EF-Tu, and part of pk4 were located in the A-site of the ribosome. We suggest that this more open arrangement is made possible due to the flexibility of tmRNA, the melting of helix m, and/or a change in conformation induced by the binding of tmRNA to the ribosome (Figure 6). The opening of the central loop seems to be accompanied by a rotation of the TLD around the helix 2 axis (compare Figure 6A and 6B) and thus might properly align the resume codon with the 3'-end of broken mRNA in the ribosomal decoding centre. At the later stages of the transit of tmRNA across the ribosome even more dramatic conformational changes were shown to disrupt helix 5 and the pseudoknotted regions (Wower et al, in press). These downstream alterations are likely mediated not by protein S1 but by the intrinsic helicase activity of the ribosome [50] and are required to maintain the ribosomal subunits in close proximity to the unfolded tmRNA in order to monitor trans-translation.
Conclusion
This study significantly advances our understanding of trans-translation by providing biologically feasible 3-D models for the entire tmRNA molecule. Although the modeling of only three tmRNAs has been described here, 3-D models of every tmRNA can be extracted from the alignment. The models are characterized by a functionally significant features, including biologically relevant structures for the single-stranded regions and the close proximity between the TLD and the resume codon. Conformational changes induced by binding of tmRNA to SmpB, ribosomal protein S1, and the ribosome suggest a transformation of a free compact tmRNA to a more open ribosome-bound structure. The comparative modeling approach described here for tmRNA is easily adapted for other RNA classes.
Methods
Comparative sequence analysis
The tmRNA sequences were arranged in phylogenetic order using information available in the RDP [19]. When the phylogenetic order could not be determined, the sequence was placed next to the closest relative as determined by the ClustalW plug-in of BioEdit [18,51]. The sequences were made available at the tmRDB [52].
Aligning was done manually using BioEdit [18] with details described previously [13]. Briefly, closely related sequences were aligned first. Then, invariant positions were used as guides to align the dissimilar regions. Next, common secondary structure elements were identified by observing covariations and find support for basepairs, tertiary interactions, or other structural features. Compensatory base changes (CBCs) were observed if a change in one residue of a Watson-Crick or G-U pair was compensated by a second change to maintain basepairing. Two residues were mismatched if they did not form a Watson-Crick or G-U pair. CBCs and mismatches were counted to determine positive and negative evidence in order to prove or disprove the existence of a particular pair. A basepair was considered proven if there was at least twice as much positive than negative evidence. Invariant pairs provided neither positive nor negative evidence. If a basepair was proven in one phylogenetic group and disproved in another group, the basepair was considered to be specific to that group.
The alignment and suggested CBCs were checked using RNAdbTools [22] to eliminate incorrectly-paired nucleotides, suggest extensions of helices, and determine the phylogenetic support for each basepair. Weakly supported basepairs adjacent to supported basepairs were considered an extension of the helix and usually included in the secondary structures (Figure 1, additional file 5: Banthracis2D.pdf and 6: Ccrescentus2D.pdf).
3-D model building
The secondary structure information was used as input for ERNA-3D [11] installed on an SGI workstation running IRIX 6.5. ERNA-3D generated A-form RNA for each helix and calculated the conformations of single-stranded regions. The models were examined using CrystalEyes stereovision goggles and an StereoGraphics infrared emitter. Structural motifs were identified using SCOR [12], the coordinates were obtained from the Protein Data Bank (PDB) [32], extracted using Swiss-PDBViewer [33], and superimposed onto the model. Data obtained from site-directed mutagenesis, cross-linking experiments, or the literature were incorporated, and bond lengths and angles were adjusted manually to produce biologically feasible models. The final models were saved in PDB format (additional files 7: Ecoli-closed.pdb, 8: Ecoli-open.pdb, 9: Banthracis-closed.pdb, and 10: Ccrescentus-closed.pdb and viewed in iMol [53] to create the ribbon diagrams shown in Figures 3 to 5.
Authors' contributions
JB identified and aligned a large number of the tmRNA sequences, carried out the 3-D modeling experiments, and drafted portions of the text. CZ conceived the study, participated in all of its aspects, and wrote the final manuscript. FM developed the ERNA-3D program and incorporated new functions to allow comparative modeling of RNA. IW developed assays which allowed to test the biological significance of the Escherichia coli tmRNA model. JW participated in the coordination of the study and provided RNA-RNA cross-link data which were crucial for constraining the models in 3-D. All authors read and approved the final manuscript.
Supplementary Material
Additional File 1
tmRNA alignment. Species names are shown on the left with their tmRDB ID (see ). Supported base pairing are shown with upper case letters and are indicated on the bottom. Secondary structure features are indicated on the top.
Click here for file
Additional File 2
tmRNA alignment. Species names are shown on the left with their tmRDB ID (see ). Supported base pairing are shown with upper case letters and are indicated on the bottom. Secondary structure features are indicated on the top. Each sequence is shown on a single long line suitable for import into other programs.
Click here for file
Additional File 3
tmRNA alignment. Species names are shown on the left with their tmRDB ID (see ). Supported base pairing are shown with upper case letters and are indicated on the bottom. Secondary structure features are indicated on the top. The alignment is shown in sections for easier viewing and printing. This arrangement is not suited for import into other programs.
Click here for file
Additional File 4
tmRNA alignment. tmRNA alignment in msf format suitable for import into editors which support the msf format. Can be used to convert into other sequence formats using, for example the Readseq server at
Click here for file
Additional File 5
Secondary structure of Bacillus anthracis tmRNA. Phylogenetically-supported helices are highlighted in gray and numbered from 1 to 12. The 5' and 3' ends are indicated. Arrows represent connections from 5' to 3'. Residues are numbered in increments of ten. Weakly supported regions and basepairs are show in boxes. The star labels the first nucleotide of the resume codon. The tag peptide sequence is shown below the mRNA-like region. The stop codon is indicated with a solid arrowheads. Three domains are distinguished: The tRNA-like domain (TLD), the mRNA-like domain (MLD), and the pseudoknot domain (PKD).
Click here for file
Additional File 6
Secondary structure of Caulobacter crescentus tmRNA. Phylogenetically-supported helices are highlighted in gray and numbered from 1 to 12. The 5' and 3' ends of both chains are indicated. Arrows represent connections from 5' to 3'. Residues are numbered in increments of ten. Weakly supported regions and basepairs are show in boxes. The star labels the first nucleotide of the resume codon. The tag peptide sequence is shown below the mRNA-like region. The stop codons are indicated with solid arrowheads. Three domains are distinguished: The tRNA-like domain (TLD), the mRNA-like domain (MLD), and the pseudoknot domain (PKD).
Click here for file
Additional File 7
PDB coordinates of the closed form of Escherichia coli tmRNA. 3-D model of the closed form of Escherichia coli tmRNA.
Click here for file
Additional File 8
PDB coordinates of the open form of Escherichia coli tmRNA. 3-D model of the open form of Escherichia coli tmRNA.
Click here for file
Additional File 9
PDB coordinates of the closed form of Bacillus anthracis tmRNA. 3-D model of the open form of Bacillus anthracis tmRNA.
Click here for file
Additional File 10
PDB coordinates of the closed form of Caulobacter crescentus tmRNA. 3-D model of the closed form of Caulobacter crescentus tmRNA.
Click here for file
Acknowledgements
This work was supported by Grant GM58267 to JW from the National Institutes of Health.
Figures and Tables
Figure 1 Secondary structure of E. coli tmRNA. Phylogenetically-supported helices are highlighted in gray and numbered from 1 to 12. The 5' and 3' ends are indicated. Arrows represent connections from 5' to 3'. Residues are numbered in increments of ten. Weakly supported regions and basepairs are shown in boxes. The disproved potential pairing of C109 with G136 is labeled with an open arrowhead. The star labels the first nucleotide of the resume codon. The tag peptide sequence is shown below the mRNA-like region. The stop codons are indicated with solid arrowheads. Three domains are distinguished: the tRNA-like domain (TLD), the mRNA-like domain (MLD), and the pseudoknot domain (PKD).
Figure 2 Motif modeling procedure. Motifs, for example the nonamer-loop shown in the top-left panel, were identified in the known high-resolution structures (top-right) with the help of SCOR [12]. The PDB coordinates were extracted (bottom-right) and compared with the 3-D model generated by ERNA-3D (bottom-left) to deduce relevant models.
Figure 3 3-D model of Escherichia coli tmRNA. The 3-D model of Escherichia coli tmRNA is viewed as a ribbon diagram from the side in panel A, the top in panel B, and in panel C turned by approximately 90° around the y-axis in relation to A. Panel D shows a representation of the corresponding 2-D structure using the identical coloring scheme. Labeled are the 5' and 3' ends, the resume (R) and stop codons (S), and the three domains (TLD, MLD, PKD). The figure was produced with iMol [53] and the PDB coordinates of additional file 7: Ecoli-closed.pdb.
Figure 4 3-D model of Bacillus anthracis tmRNA. The 3-D model of Bacillus anthracis tmRNA is viewed as a ribbon diagram from the side in panel A, the top in panel B, and in panel C turned by approximately 90° around the y-axis in relation to A. Panel D shows a representation of the corresponding 2-D structure using the identical coloring scheme. Labeled are the 5' and 3' ends, the resume (R) and stop codons (S), and the three domains (TLD, MLD, PKD). The figure was produced with iMol [53] and the PDB coordinates of additional file 9: Banthracis-closed.pdb.
Figure 5 3-D model of Caulobacter crescentus tmRNA. The 3-D model of Caulobacter crescentus s tmRNA is viewed as a ribbon diagram from the side in panel A, the top in panel B, and in panel C turned by approximately 90° around the y-axis in relation to A. Panel D shows a representation of the corresponding 2-D structure using the identical coloring scheme. Labeled are the 5' and 3' ends, the resume (R) and stop codons (S), and the three domains (TLD, MLD, PKD). The figure was produced with iMol [53] and the PDB coordinates of additional file 10: Ccrescentus-closed.pdb.
Figure 6 Conformational changes in Escherichia coli tmRNA. Panel A: closed form of the E. coli model as shown in Figure 3. Panel B: open conformation adjusted to more closely resemble the ribosome-bound form as determined by cryo-EM [10] using additional file 8: Ecoli-open.pdb. Panel C: coordinates extracted from the cryo-EM model [10]. The TLD is shown in dark purple, helix 2 in green, pk1 in yellow, helix 5 in pink, pk2 in turquoise, pk3 in red, and pk4 in dark blue. Panel D: Electron density map of the 50S subunit in light blue, the 30S subunit in yellow, and the bound tmRNA (in the absence of ribosomal protein S1) in dark blue (from [10]).
Table 1 Phylogenetic distribution of tmRNA features
Phylogenetic Group TLD MLD pk1 pk2 pk3 pk4 Other
Thermophilic Oxygen Reducers
Thermatogales
Green Non-sulfur & Bacteria elatives
Flexibacter Cytophaga Bacteroides
Green Sulfur Bacteria
Planctomyces & elatives
Cyanobacteria 1 1,2 3
Plastids - -
Mitochondria - - - - -
Fibrobacter/Acidobacter & elatives
Spirochetes & elatives
Proteobacteria, alpha 4 5 3
Proteobacteria, beta 6 3
Proteobacteria, gamma 6
Proteobacteria, delta
Proteobacteria, epsilon
Fusobacteria
Gram Positive Bacteria
The tRNA-like domain (TLD), mRNA-like domain (MLD), and the four pseudoknots pk1 to pk4 are shown on the top. Other features peculiar to a phylogenetic group are in the right column. White fields indicate the presence, dashes the absence of a feature. Numbers suggest the following structural features: (1) certain Cyanobacteria lack these pseudoknots. (2) One-chain cyanobacterial tmRNAs contain two smaller tandem pseudoknots named pk4a and 4b. (3) The tmRNAs of some species in this group consist of two basepaired molecules [14, 21]. (4) The genus Ricketsia and its relatives lack pk2. (5) pk4 of the alpha-Proteobacteria has been reduced to a single helix (named helix 11). (6) Some species in this group contain an additional helix (helix 6d).
Table 2 Structural motifs used for the Escherichia coli tmRNA model
Motif SCOR class tmRNA Res. Source Res. Coordinates Comments
1 1–7, 353–363 1–7, 12–22 1IKD.pdb (chain W) ACCA end and G3-U357 pair
2 8–28, 325–352 8–28, 325–352 tmx-34.pdb from tmRDB
3a internal loop with unpaired stacked bases 29–33, 321–324 1775–1779, 1765–1768 1JJ2.pdb
3b stacked duplex with one non-WC pair C35, A319 ERNA-3D
4 stacked duplex with two non-WC pairs 38–39, 315–316 2874–2875, 2882–2883 1JJ2.pdb
5 309–311 ERNA-3D
6a pseudoknot 49–78 1–33 1RNK.pdb pk1
6b tetraloop 87–98 5–8 1AFX.pdb the only YRRR tetraloop in SCOR
7 nonaloop 118–126 1834–1842 1JJ2.pdb
8 one unpaired and stacked U U131 U30 1B36.pdb
9 171–174 ERNA-3D
10a stacked duplex with two non-WC pairs 149–150, 165–166 288–289, 363–364 1JJ2.pdb
10b pseudoknot 138–196 6a pk2
11a internal loop 204–206, 223–225 780–782, 800–802 1J5E.pdb
11b pseudoknot 197–247 6a pk3
12 stacked duplex with one non-WC pair G258, A273 A-G6, B-A27 420D.pdb
13a stacked duplex with one non-WC pair C266, U296 ERNA-3D
13b pseudoknot 248–299 6a pk4
Shown in columns one to four are the motif numbers in bold, their SCOR classification [12], the residue positions in the tmRNA model and the source structure. column five lists the filenames containing the atomic coordinates that were derived from the PDB [31], the tmRDB [52], or were generated by ERNA-3D [11].
Table 3 Structural motifs used for the Bacillus anthracis tmRNA mode
Motif SCOR class tmRNA Res. Source Res. Coordinates Comments
1 1–11, 12–27, 316–355 1–11, 13–28, 324–363 E. coli 1 ACCA end and G3-U349 pair
2 loop with stacked interdigitated bases 28–33, 312–316 477–482, 451–455 1J5E.pdb
3 300–301 ERNA-3D
4a 43–53, 61–65, 294–299 43–53, 63–67, 302–308 E. coli model helix 2d, helix 3
4b pseudoknot 58–60, 66, 67–73 12–14, 20, 23–29, 1RNK.pdb pk1, helix 4b
4c 54–56, 74–75 54–56, 77–78 E. coli 6a pk1, helix 4a
5 heptaloop 82–88 335–341 1JJ2.pdb
6a one looped out A A112 210 1GID.pdb
6b C114, C127 ERNA-3D
6c octaloop 117–124 1499–1506 1JJ2.pdb
7a 134–138, U163, A164, 165–169, 140–144, A171, A174, 175–179 E. coli 10b helix 6a, looped out U163 and A164.
7b one looped out U U158 U87 1JJ2.pdb
7c 144–147, 148–156, 180–185 259–262, 264–272, 293–298 E. coli 13b helix 6c, helix 7, pk2
8 G133, C170, 171–177, 178–179 C138, G181, 182–188, 190–191 E. coli 10b
9a C190, 191–198, 208–215, 216 G200, 203–210, 219–226, U229 E. coli 11a, 11b purine-rich loop, pk3
9b pseudoknot 202–206, 228–232 9–13, 28–32 1RNK.pdb pk3, helix 9
10a 199–201 154–156 E. coli 6a pk3
10b 217–227 229–239 E. coli 6a pk3
11a one looped out C C269 C6 1BVJ.pdb
11b stacked duplexes with four non-WC pairs 241–245, 260–263 795–798, 815–818 1JJ2.pdb
12 246–259, 275–290 259–277, 284–299 E. coli 6a helix 10c, helix 11ab, pk4
Motif numbers in bold, their SCOR classification [12], residue positions in the tmRNA model and the source structure are shown in columns one to four. Column five lists the filenames containing the atomic coordinates that were derived from the PDB [31], the E. coli model (see Table 2), or were generated by ERNA-3D [11].
Table 4 Structural motifs used for the Caulobacter crescentus tmRNA model
Motif SCOR class tmRNA Res. Source Res. Coordinates Comments
1 A-1-13, A-14-21, B-50-83 1–13, 15–22, 322–355. B. anthracis 1 -
2a one non-Watson Crick pair and one looped-out A A-22, B-48-49 14, 4–5 5MSF.pdb disruption in anticodon stem
2b loop with base triple A-26-31; B-40-44 8–13, 24–28 1FMN.pdb
2c A-C36, B-C35 ERNA-3D
3 A-40-41, B-27-31 ERNA-3D
4 A-47-61, A-62-70 196–210, 224–232 B. anthracis 8a, 8b, 9a, 9c pk1
5 A-87-93 82–88 B. anthracis 5 terminal heptaloop of helix m2
6 one looped out A and one or more non-WC pairs A-78-81, A-99-101 113–116, 205–207 1GID.pdb internal loop between helices m1 and m2
7 B-8-11 284–285, 291–292 1D6K.pdb
8a A-112-114, A-131-132 ERNA-3D
8b A-119-125 82–88 B. anthracis 5
9a U148, C163 ERNA-3D
9b A-156-165, A-146-153, A-167-171 157–166, 149–156, 192–196 E. coli 10b pk2. Single-stranded regions were adjusted to connect helices
10 A-154-156, A-170-171 54–55, 76–77 E. coli 6a Correction of two pairs in pk2 based on E. coli pk1
11 A-211-214, A-177-182, A-184-193, A-177-178, A-192-198, A-194-209 360–363, 207–212, 213–222, 200–201, 228–234, 230–245 E. coli 1 (ACCU tail) and 11b pk3 and ACCU tail of pk3
Motif numbers in bold, their SCOR classification [12], residue positions in the tmRNA model and the source structure are shown in columns one to four. Column five lists the filenames containing the atomic coordinates that were derived from the PDB [31], the E. coli or B. anthracis models (see Tables 2 and 3), or were generated by ERNA-3D [11].
==== Refs
Zwieb C Wower I Wower J Comparative sequence analysis of tmRNA Nucleic Acids Res 1999 27 2063 2071 10219077 10.1093/nar/27.10.2063
Withey J Friedman D Analysis of the role of trans-translation in the requirement of tmRNA for lambdaimmP22 growth in Escherichia coli J Bacteriol 1999 181 2148 2157 10094693
Tu GF Reid GE Zhang JG Moritz RL Simpson RJ C-terminal extension of truncated recombinant proteins in Escherichia coli with a 10Sa RNA decapeptide J Biol Chem 1995 270 9322 9326 7536743 10.1074/jbc.270.16.9322
Keiler KC Waller PR Sauer RT Role of a peptide tagging system in degradation of proteins synthesized from damaged messenger RNA Science 1996 271 990 993 8584937
Himeno H Sato M Tadaki T Fukushima M Ushida C Muto A In vitro trans translation mediated by alanine-charged 10Sa RNA J Mol Biol 1997 268 803 808 9180372 10.1006/jmbi.1997.1011
Karzai AW Roche ED Sauer RT The SsrA-SmpB system for protein tagging, directed degradation and ribosome rescue Nat Struct Biol 2000 7 449 455 10881189 10.1038/75843
Wower IK Zwieb CW Guven SA Wower J Binding and cross-linking of tmRNA to ribosomal protein S1, on and off the Escherichia coli ribosome Embo J 2000 19 6612 6621 11101533 10.1093/emboj/19.23.6612
Barends S Wower J Kraal B Kinetic parameters for tmRNA binding to alanyl-tRNA synthetase and elongation factor Tu from Escherichia coli Biochemistry 2000 39 2652 2658 10704215 10.1021/bi992439d
Karzai AW Sauer RT Protein factors associated with the SsrA.SmpB tagging and ribosome rescue complex Proc Natl Acad Sci U S A 2001 98 3040 3044 11248028 10.1073/pnas.051628298
Valle M Gillet R Kaur S Henne A Ramakrishnan V Frank J Visualizing tmRNA entry into a stalled ribosome Science 2003 300 127 130 12677067 10.1126/science.1081798
Mueller F Doring T Erdemir T Greuer B Junke N Osswald M Rinke-Appel J Stade K Thamm S Brimacombe R Getting closer to an understanding of the three-dimensional structure of ribosomal RNA Biochem Cell Biol 1995 73 767 773 8721993
Klosterman PS Tamura M Holbrook SR Brenner SE SCOR: a Structural Classification of RNA database Nucleic Acids Res 2002 30 392 394 11752346 10.1093/nar/30.1.392
Larsen N Zwieb C SRP-RNA sequence alignment and secondary structure Nucleic Acids Res 1991 19 209 215 1707519
Williams KP The tmRNA Website: invasion by an intron Nucleic Acids Res 2002 30 179 182 11752287 10.1093/nar/30.1.179
Benson DA Karsch-Mizrachi I Lipman DJ Ostell J Wheeler DL GenBank Nucleic Acids Res 2005 33 Database Issue D34 8 15608212
Altschul SF Gish W Miller W Myers EW Lipman DJ Basic local alignment search tool J Mol Biol 1990 215 403 410 2231712 10.1006/jmbi.1990.9999
Altschul SF Madden TL Schaffer AA Zhang J Zhang Z Miller W Lipman DJ Gapped BLAST and PSI-BLAST: a new generation of protein database search programs Nucleic Acids Res 1997 25 3389 3402 9254694 10.1093/nar/25.17.3389
Hall TA BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT Nucl Acids Symp Ser 1999 41 95 98
Cole JR Chai B Marsh TL Farris RJ Wang Q Kulam SA Chandra S McGarrell DM Schmidt TM Garrity GM Tiedje JM The Ribosomal Database Project (RDP-II): previewing a new autoaligner that allows regular updates and the new prokaryotic taxonomy Nucleic Acids Res 2003 31 442 443 12520046 10.1093/nar/gkg039
Wheeler DL Church DM Federhen S Lash AE Madden TL Pontius JU Schuler GD Schriml LM Sequeira E Tatusova TA Wagner L Database resources of the National Center for Biotechnology Nucleic Acids Res 2003 31 28 33 12519941 10.1093/nar/gkg033
Keiler KC Shapiro L Williams KP tmRNAs that encode proteolysis-inducing tags are found in all known bacterial genomes: A two-piece tmRNA functions in Caulobacter Proc Natl Acad Sci U S A 2000 97 7778 7783 10884408 10.1073/pnas.97.14.7778
Gorodkin J Zwieb C Knudsen B Semi-automated update and cleanup of structural RNA alignment databases Bioinformatics 2001 17 642 645 11448882 10.1093/bioinformatics/17.7.642
tmRDB [http://psyche.uthct.edu/dbs/tmRDB/]
Hou YM Schimmel P A simple structural feature is a major determinant of the identity of a transfer RNA Nature 1988 333 140 145 3285220 10.1038/333140a0
Komine Y Kitabatake M Yokogawa T Nishikawa K Inokuchi H A tRNA-like structure is present in 10Sa RNA, a small stable RNA from Escherichia coli Proc Natl Acad Sci U S A 1994 91 9223 9227 7524073
Ushida C Himeno H Watanabe T Muto A tRNA-like structures in 10Sa RNAs of Mycoplasma capricolum and Bacillus subtilis Nucleic Acids Res 1994 22 3392 3396 7521527
Zwieb C Mueller F Wower J Comparative three-dimensional modeling of tmRNA Nucl Acids Symp Ser 1999 41 200 204
Wower IK Zwieb C Wower J Contributions of pseudoknots and protein SmpB to the structure and function of tmRNA in trans-translation J Biol Chem 2004 279 54202 54209 15494393 10.1074/jbc.M410488200
Zuker M Mfold web server for nucleic acid folding and hybridization prediction Nucleic Acids Res 2003 31 3406 3415 12824337 10.1093/nar/gkg595
Felden B Himeno H Muto A McCutcheon JP Atkins JF Gesteland RF Probing the structure of the Escherichia coli 10Sa RNA (tmRNA) Rna 1997 3 89 103 8990402
Sussman JL Abola EE Lin D Jiang J Manning NO Prilusky J The protein data bank. Bridging the gap between the sequence and 3D structure world Genetica 1999 106 149 158 10710721 10.1023/A:1003753517358
Berman HM Westbrook J Feng Z Gilliland G Bhat TN Weissig H Shindyalov IN Bourne PE The Protein Data Bank Nucleic Acids Res 2000 28 235 242 10592235 10.1093/nar/28.1.235
Guex N Peitsch MC SWISS-MODEL and the Swiss-PdbViewer: an environment for comparative protein modeling Electrophoresis 1997 18 2714 2723 9504803 10.1002/elps.1150181505
Wimberly BT Brodersen DE Clemons WMJ Morgan-Warren RJ Carter AP Vonrhein C Hartsch T Ramakrishnan V Structure of the 30S ribosomal subunit Nature 2000 407 327 339 11014182 10.1038/35030006
Zwieb C Guven SA Wower IK Wower J Three-dimensional folding of the tRNA-like domain of Escherichia coli tmRNA Biochemistry 2001 40 9587 9595 11583158 10.1021/bi010443v
Hanawa-Suetsugu K Bordeau V Himeno H Muto A Felden B Importance of the conserved nucleotides around the tRNA-like structure of Escherichia coli transfer-messenger RNA for protein tagging Nucleic Acids Res 2001 29 4663 4673 11713316 10.1093/nar/29.22.4663
Kelley ST Harris JK Pace NR Evaluation and refinement of tmRNA structure using gene sequences from natural microbial communities Rna 2001 7 1310 1316 11565752 10.1017/S1355838201010573
Nameki N Tadaki T Himeno H Muto A Three of four pseudoknots in tmRNA are interchangeable and are substitutable with single-stranded RNAs FEBS Lett 2000 470 345 349 10745094 10.1016/S0014-5793(00)01349-1
Sussman JL Holbrook SR Warrant RW Church GM Kim SH Crystal structure of yeast phenylalanine transfer RNA. I. Crystallographic refinement J Mol Biol 1978 123 607 630 357742 10.1016/0022-2836(78)90209-7
Stagg SM Frazer-Abel AA Hagerman PJ Harvey SC Structural studies of the tRNA domain of tmRNA J Mol Biol 2001 309 727 735 11397092 10.1006/jmbi.2001.4632
Barends S Karzai AW Sauer RT Wower J Kraal B Simultaneous and functional binding of SmpB and EF-Tu-TP to the alanyl acceptor arm of tmRNA J Mol Biol 2001 314 9 21 11724528 10.1006/jmbi.2001.5114
Gutmann S Haebel PW Metzinger L Sutter M Felden B Ban N Crystal structure of the transfer-RNA domain of transfer-messenger RNA in complex with SmpB Nature 2003 424 699 703 12904796 10.1038/nature01831
Nissen P Kjeldgaard M Thirup S Polekhina G Reshetnikova L Clark BF Nyborg J Crystal structure of the ternary complex of Phe-tRNAPhe, EF-Tu, and a GTP analog [see comments] Science 1995 270 1464 1472 7491491
Wower J Zwieb CW Hoffman DW Wower IK SmpB: a protein that binds to double-stranded segments in tmRNA and tRNA Biochemistry 2002 41 8826 8836 12102625 10.1021/bi0201365
Dong G Nowakowski J Hoffman DW Structure of small protein B: the protein component of the tmRNA-SmpB system for ribosome rescue Embo J 2002 21 1845 1854 11927568 10.1093/emboj/21.7.1845
Subramanian AR Structure and functions of ribosomal protein S1 Prog Nucleic Acid Res Mol Biol 1983 28 101 142 6348874
Bear DG Ng R Van Derveer D Johnson NP Thomas G Schleich T Noller HF Alteration of polynucleotide secondary structure by ribosomal protein S1 Proc Natl Acad Sci U S A 1976 73 1824 1828 778845
Williams KP Martindale KA Bartel DP Resuming translation on tmRNA: a unique mode of determining a reading frame Embo J 1999 18 5423 5433 10508174 10.1093/emboj/18.19.5423
Ivanov PV Zvereva MI Shpanchenko OV Dontsova OA Bogdanov AA Aglyamova GV Lim VI Teraoka Y Nierhaus KH How does tmRNA move through the ribosome? FEBS Lett 2002 514 55 59 11904181 10.1016/S0014-5793(02)02310-4
Takyar S Hickerson RP Noller HF mRNA helicase activity of the ribosome Cell 2005 120 49 58 15652481 10.1016/j.cell.2004.11.042
Thompson JD Higgins DG Gibson TJ CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice Nucleic Acids Res 1994 22 4673 4680 7984417
Zwieb C Gorodkin J Knudsen B Burks J Wower J tmRDB (tmRNA database) Nucleic Acids Res 2003 31 446 447 12520048 10.1093/nar/gkg019
iMol [http://www.pirx.com/imol]
Chime [http://www.umass.edu/microbio/chime/]
| 15958166 | PMC1168896 | CC BY | 2021-01-04 16:22:25 | no | BMC Mol Biol. 2005 Jun 15; 6:14 | utf-8 | BMC Mol Biol | 2,005 | 10.1186/1471-2199-6-14 | oa_comm |
==== Front
BMC MedBMC Medicine1741-7015BioMed Central London 1741-7015-3-101597514310.1186/1741-7015-3-10Research ArticleAge-related human small intestine methylation: evidence for stem cell niches Kim Jung Yeon [email protected] Kimberly D [email protected]é Simon [email protected] Darryl [email protected] Departments of Pathology, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA2 Preventive Medicine, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA3 Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA, and Department of Oncology, University of Cambridge, Cambridge, UK2005 23 6 2005 3 10 10 1 11 2004 23 6 2005 Copyright © 2005 Kim et al; licensee BioMed Central Ltd.2005Kim et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
The small intestine is constructed of many crypts and villi, and mouse studies suggest that each crypt contains multiple stem cells. Very little is known about human small intestines because mouse fate mapping strategies are impractical in humans. However, it is theoretically possible that stem cell histories are inherently written within their genomes. Genomes appear to record histories (as exemplified by use of molecular clocks), and therefore it may be possible to reconstruct somatic cell dynamics from somatic cell errors. Recent human colon studies suggest that random somatic epigenetic errors record stem cell histories (ancestry and total numbers of divisions). Potentially age-related methylation also occurs in human small intestines, which would allow characterization of their stem cells and comparisons with the colon.
Methods
Methylation patterns in individual crypts from 13 small intestines (17 to 78 years old) were measured by bisulfite sequencing. The methylation patterns were analyzed by a quantitative model to distinguish between immortal or niche stem cell lineages.
Results
Age-related methylation was observed in the human small intestines. Crypt methylation patterns were more consistent with stem cell niches than immortal stem cell lineages. Human large and small intestine crypt niches appeared to have similar stem cell dynamics, but relatively less methylation accumulated with age in the small intestines. There were no apparent stem cell differences between the duodenum and ileum, and stem cell survival did not appear to decline with aging.
Conclusion
Crypt niches containing multiple stem cells appear to maintain human small intestines. Crypt niches appear similar in the colon and small intestine, and the small intestinal stem cell mitotic rate is the same as or perhaps slower than that of the colon. Although further studies are needed, age-related methylation appears to record somatic cell histories, and a somatic epigenetic molecular clock strategy may potentially be applied to other human tissues to reconstruct otherwise occult stem cell histories.
==== Body
Background
The human small intestine is the longest segment of the gastrointestinal tract, approximately five to six meters long in adults. Although it is three to four times longer than the colon, small intestinal tumors are rare, forming about 1% of all gastrointestinal malignancies [1]. Like the colon, the small intestine is composed of multiple crypts (of Lieberkühn), which also contribute cells to finger-like projections called villi (Figure 1). Stem cells appear to reside near the crypt bases, producing numerous differentiated progeny that die within a week as they migrate upwards [2-4]. Stem cells also produce Paneth cells that migrate downwards, and subsequently survive a few weeks.
Figure 1 Schematic of a crypt of Lieberkühn and villus. Stem cells probably reside within a niche just above the Paneth cells. Differentiated cells migrate out of the niche and up a villus, and die within a week. Illustrated are an isolated crypt and villus fragments. A cross-section illustrates that the villus fragments were essentially hollow tubes of epithelium. The schematic of stem cell lineages illustrates that cell division is always asymmetric (one stem cell and one differentiated daughter) in immortal stem cell lineages, and predominately asymmetric in a stem cell niche. However, niche symmetric divisions occasionally occurs (yellow region) leading to loss of one lineage and the expansion of another, such that total niche stem cell numbers remain unchanged. In this way, niches allow heterogeneous crypts to become homogenous.
Although there are likely to be many stem cells per crypt [2-4], intestinal stem cells have not been directly isolated or identified, and their properties and numbers are uncertain. Stem cell lineages may be immortal if at least one daughter retains stem cell properties after each division. However, mouse studies are more consistent with periodic losses of crypt stem cell lineages. The primary observation is that heterogeneous crypts created through mutagenesis or with chimeras eventually become homogenous [5]. If stem cell lineages were immortal, heterogeneous crypts would not become homogeneous.
Stem cell turnover by a niche mechanism [5,6] can explain how heterogeneous crypts become homogeneous (Figure 1). Niche stem cells divide but total niche stem cell numbers remain unchanged as daughter cells constantly leave the niche and differentiate. Usually a stem cell produces one stem cell and one differentiated daughter (~95% of the time in mice [7]), but sometimes a stem cell lineage may become extinct when both daughter cells leave the niche, balanced by another stem cell lineage that expands when both daughters remain within the niche. Such a niche population-type mechanism (random stem cell loss with replacement) eventually results in the loss of all stem cell lineages except one, allowing heterogeneous crypts to become homogeneous (Figure 1).
Human stem cell studies are difficult because the powerful visible fate-marking strategies of animal models are impractical. Most human crypts are visually homogeneous and therefore consistent with either immortal or niche stem cell mechanisms. A study of human colon crypts after therapeutic radiation was consistent with stem cell niches because the frequencies of mutant heterogeneous crypts progressively declined after radiation [8]. Similar studies have not been performed on human small intestines.
One method that can reconstruct the past without direct serial observations infers ancestry from present day sequences. The past is encoded in sequences because errors may accumulate in a clock-like fashion (the molecular clock hypothesis [9]) and record relationships between cells and times since the most recent common ancestor or bottleneck. Just as the age of the human race may be inferred by comparing contemporary genomes, so the ages of crypt stem cell populations may in theory be inferred from their sequences. With immortal stem cell lineages, adult crypts will have greater sequence diversity compared to crypts maintained by stem cell niches that periodically "bottleneck" whenever all but one current stem cell lineage are lost. Therefore, crypt diversity measurements potentially reveal whether stem cell lineages are immortal (last bottleneck around birth) or turn over by a niche mechanism (more recent bottlenecks).
Mutations are rare in normal cells, but recent studies illustrate that stem cell ancestries may be automatically recorded by random somatic epigenetic errors that frequently accumulate with aging [10]. Methylation increases with age at certain CpG-rich regions in the colon [11,12]. This age-related methylation does not resemble a stereotypic developmental process because different cells within the same intestine may have different methylation patterns (5' to 3' order of methylated sites). Such random somatic errors resemble the drift of genomes during species evolution, and by analogy, such drift can be used to reconstruct somatic cell ancestry because methylation exhibits somatic inheritance [13] and all cells are related. Therefore, somatic methylation patterns potentially encode numbers of divisions since birth, and ancestral relationships among cells within a single crypt or villus. Here we infer from methylation patterns that crypt niches containing multiple stem cells maintain the human small intestine.
Methods
Specimens
Crypts or villi were isolated from 1–2 cm2 patches of fresh small intestines obtained from 13 patients undergoing surgery for non-small intestinal diseases (Table 1), using an EDTA-containing solution as previously performed for colon crypts [10]. The research was approved by our Institutional Review Board and is in compliance with the Helsinki Declaration. Individual crypts or villus fragments were identified under a dissecting microscope (Figure 1) and placed in 0.5 ml microfuge tubes. Villus fragments were essentially hollow tubes of epithelium without stroma. Nine crypts were analyzed from 13 intestines for CSX, eight crypts from six intestines for MYOD, and 4–10 villi (average of seven) were analyzed for CSX from six intestines. The DNA was extracted and bisulfite converted as previously described [10]. DNA was also extracted from microdissected paraffin-embedded small intestinal tissues of an eight month old and a four year old. The bisulfite treated DNA from about half a crypt was amplified by PCR at CpG-rich segments of CSX or MYOD [10]. PCR products were cloned into bacteria and eight clones were sequenced from each crypt or villus.
Table 1 Specimens
Patient Age/Sex Site Surgery Specimen Tags
A 17/F Ileum Constipation Crypt CSX, MYOD
B 27/F Ileum Inflammatory Bowel Crypt, Villi CSX
C 46/F Ileum Ovarian Cancer Crypt, Villi CSX, MYOD
D 51/M Duodenum Whipple Crypt CSX
E 52/M Ileum Colorectal Cancer Crypt, Villi CSX
F 58/F Duodenum Whipple Crypt CSX, MYOD
G 58/F Ileum Colorectal Cancer Crypt,Villi CSX, MYOD
H 63/F Duodenum Whipple Crypt CSX
I 67/F Duodenum Whipple Crypt CSX, MYOD
J 72/M Ileum Colorectal Cancer Crypt CSX
K 75/F Ileum Colorectal Cancer Crypt,Villi CSX
L 76/M Ileum Colorectal Cancer Crypt CSX, MYOD
M 78/M Duodenum Whipple Crypt,Villi CSX
N 0.07/F Ileum Obstruction Paraffin CSX, MYOD
O 4/M Ileum Trauma Paraffin CSX, MYOD
Ileum specimens were proximal portions of total colectomies.
Stem cell dynamics from methylation patterns
Small intestinal methylation patterns were analyzed by the same quantitative approach we applied to colon crypt methylation patterns ([10], and its Supplementary Materials). Human crypts of Lieberkühn containing a total of ~500 cells [14] were simulated on a computer, modeling the processes of stem cell division (symmetrical or asymmetrical), differentiation, death, and random methylation errors. The parameters of the model (Table 2) are numbers of stem cells per crypt, probabilities of symmetric or asymmetric stem cell division, a methylation error rate, and numbers of divisions since birth. These parameters are uncertain for the human small intestines, and the values are just guesses chosen to be consistent with the biology of the intestines, and are similar to the values we estimated for the colon [10]. We emphasize that they are just estimates, and further experiments are needed to define these values better. The model starts with unmethylated sites in the CpG-rich regions of CSX or MYOD, and errors are assumed to accumulate independently between CpG sites with the same rates as simulated in the colon [10]. The output is the methylation patterns of these regions after a given number of divisions. A total of 1000 simulations were performed for each crypt scenario.
Table 2 Model Parameters
Parameter Stem Cell Niche Immortal Lineages
Stem Cells per Crypt 4–256 2
Probability of Asymmetric Stem Cell Division (P1)* 0.98 to 0.89 1.0
Probability of Symmetric Stem Cell Division: zero (P0) or two (P2) stem cell offspring* 0.02 to 0.11 0
Methylation Error Rate 2 × 10-5 per CpG site per division** 2 × 10-5 per CpG site per division**
Stem Cell Division Rate 0.75 per day 0.75 per day
*P0+P1+P2 = 1, with P0 = P2
** Equal probabilities for methylation and demethylation errors
A stem cell hierarchy is simulated with small numbers of stem cells that produce differentiated mitotic cells, which subsequently become differentiated non-mitotic cells. For example, if there are two stem cells per crypt, differentiated mitotic cells divide six more times before becoming non-mitotic. Differentiated non-mitotic cells remain through two more divisions with the oldest cells dying after each division cycle to maintain a constant number of crypt cells. In this scenario, there are 512 cells per crypt – two stem cells, 126 differentiated mitotic cells, and 384 differentiated non-mitotic cells. With greater numbers of stem cells, numbers of differentiated mitotic cells and their divisions are correspondingly reduced to maintain a constant size of the mitotic compartment and 512 cells per crypt.
Immortal stem cell lineages were simulated with strictly asymmetric division producing one stem cell and one differentiated daughter (P1 = 1.0). After a given number of stem cell divisions, eight alleles are randomly sampled from each simulated crypt, as in the experimental approach. Niche and immortal scenarios were identical except niche stem cells also exhibit symmetric divisions (P1 < 1.0). Total niche stem cell numbers remain constant because divisions that produce two differentiated daughters are balanced by divisions that produce two stem cell daughters (P0 = P2). Symmetric divisions tend to reduce crypt diversity because methylation patterns can be lost through lineage extinction.
The Paneth cell compartment was not specifically modeled because its dynamics are uncertain and these cells would be rarely sampled because their relative numbers are small (~2–4 Paneth cells per crypt section [15]). Paneth cell methylation patterns should be similar to those of other differentiated cells because they survive only a few weeks in mice [16], although human Paneth cells may potentially have different lifetimes.
Methylation of CSX or MYOD "tags" can be converted into a 5' to 3' binary code, with "0" representing an unmethylated site and "1" representing a methylated site. For example, an unmethylated CSX tag (eight CpG sites or 256 different possible tags) is "00000000" and a fully methylated MYOD tag (5 CpG sites or 64 different possible tags) is "11111". Tags can be summarized with three statistics that reflect numbers and types of stem cell divisions:
1) Percent Methylation. Numbers of methylated tag sites can be summarized by percent methylation. For example the CSX tag "01010101" is 50% methylated. In general, percent methylation reflects numbers of divisions since birth.
2) Unique Tags per Crypt. Diversity, or numbers of unique tags among the eight tags sampled from a crypt, reflects numbers of stem cells and stem cell lineage survival. Greater numbers of stem cells or longer-lived stem cell lineages would lead to greater crypt tag diversity.
3) Intracrypt Distance. This is the average number of site differences between crypt tags (Hamming distance). For example, the distance between CSX tags 00000011 and 11000000 is four. Intracrypt distance is another measure of crypt diversity.
Results
Crypts of Lieberkühn and villus fragments were isolated from fresh human small intestine (Figure 1) and individual allele methylation patterns were analyzed by bisulfite sequencing. Examples of crypt CSX methylation patterns (5' to 3' order of methylated sites) or "tags" are illustrated in Figure 2. Methylation represents somatic errors because CSX tags, like most CpG-rich sites [13], are initially unmethylated at birth. Although the tag patterns were complex, with differences within crypts and between crypts in the same intestine, the average percent methylation generally increased with age (Figure 3A). Crypt diversity (unique tags per crypt and intracrypt tag distances) also exhibited age-related changes (Figure 3A). Duodenum and ileum tag patterns appeared similar.
Figure 2 Examples of CSX crypt methylation patterns. Each group represents eight CSX tags (5' to 3' horizontal orientation, each of the eight CpG sites is represented by a circle) sampled from a single crypt, with nine crypts per patient. Open circles are unmethylated sites and filled circles are methylated sites. Numbers of unique tags per crypt and crypt percent methylation are summarized below each crypt. The seemingly random methylation patterns collectively encode both numbers of divisions since birth and ancestry.
Figure 3 Methylation tag analysis. A: Summary of CSX methylation tags sampled from crypts of Lieberkühn. Individual crypt values ("X" for duodenal crypts and "+" for ileal crypts) and average values (open circles for the duodenum and filled circles for the ileum) were plotted for 12 small intestines. Black filled circles represent the methylation measured in fixed small intestine from children. Solid green lines represent average values for a stem cell niche simulation best matching the experimental data. Consistent with the scatter of experimental crypt values, niche simulations also produced a variety of different outcomes summarized by dotted green lines representing 95% of simulated outcomes. Gray solid lines represent average simulated values consistent with the colon [10]. Small intestine percent methylation appeared to increase more slowly than the colon with age, consistent with fewer stem cell divisions relative to the colon. B: Summary of MYOD crypt of Lieberkühn methylation tags. C: Summary of CSX villus methylation tags. Average crypt values (black circles) for the same intestine are also plotted for comparison with average villus values (red circles). Unique tags and distances were significantly greater in villi compared to crypts whereas percent methylation was not significantly different.
Different tags within the same intestine are consistent with stochastic errors that accumulate independently in different cells. To extract ancestral information encoded by seemingly random tags within a single intestine, crypts were modeled assuming stochastic methylation errors and either immortal or niche stem cells (see Methods). The primary difference between the models is that the probability of symmetric division (yielding two stem cell (P2) or two differentiated daughters (P0)) is zero with immortal stem cells, whereas the probability of symmetric division is greater than zero with niche stem cells (Table 2). Greater inter-crypt variability is expected with stem cell niches because both methylation errors and stem cell survival are stochastic.
As in the experimental data, the simulated crypts contained tags with different patterns, summarized by averages and intervals including 95% of simulated crypt outcomes (Figure 4A). Average simulated crypt values were consistent with average experimental values for either two immortal stem cells per crypt, or 4 to 256 niche stem cells. However, niche stem cells produced more inter-crypt tag variation, which better matched the variability observed in the small intestines. Inconsistent with immortal stem cell lineages were the observations that unique crypt tag variances were greater than simulated average values for all 12 intestines, and only 4 of the 12 intestines were within 95% simulation intervals for immortal stem cells (Figure 4B). In contrast, experimental variances for 10 of 12 intestines fell within 95% simulation intervals for the niche scenarios. In addition, more than four unique sequences per crypt were often observed, which should occur only rarely with two immortal crypt stem cells (four possible alleles), but may occur more frequently with 4 to 256 niche stem cells (Figure 4A).
Figure 4 Niche versus Immortal Stem Cells. A: Comparisons between niche (green) and immortal (red) stem cell simulations with CSX tags. Niche simulations assume a constant number of stem cell (from 4 to 256 stem cells per niche) and probabilities of asymmetric division (P1) from 0.98 to 0.89 (see Table 3). Outcomes of all niche simulations were similar and therefore one cannot be certain of the exact stem cell niche size. Immortal lineage simulations assume two stem cells per niche. Parameters (see Table 2) were otherwise identical between the simulations. Outcomes were more variable with niche simulations with wider 95% simulation intervals (dotted lines). The differences are most obvious with unique tags per crypt. B: Variances of unique CSX crypt tags per intestine (for example from Figure 2, Patient A had 2, 2, 2, 2, 3, 3, 3, 4, and 5 unique tags per crypt for a variance of 1.1, and Patient M had 2, 2, 2, 3, 3, 3, 4, 4, and 6 unique tags per crypt for a variance of 1.7). Simulations with the immortal lineage scenario (average is a solid red line, 95% intervals are dotted lines) were less consistent with the experimental data (circles) than the niche simulations (green lines).
Tag data from human large [10] and small intestinal crypts were similar, except the percent methylation appeared to increase more slowly with age in the small intestine (Figure 3A). Small intestine percent methylation was generally lower than published [10,17] measurements of human colon crypts, with a trend towards a slower increase with age (Figure 5), but this difference was not significant (p = 0.24, F-test). Potentially methylation error rates are lower in the small intestine, but assuming equivalent error rates (a molecular clock hypothesis [9]), stem cell division rates are either equivalent or lower in the small intestine compared to the colon. For example, simulations with a mitotic rate 75% of the colon (0.75 divisions per day) and a methylation error rate identical to the colon (2 × 10-5 per site per division) better fit the small intestine data (Figure 3A and Figure 5).
Figure 5 Comparisons of large and small intestine age-related CSX methylation rates. Average percent methylation increased more slowly with age in the small intestine (black circles) relative to previously published [10, 17] colon measurements (red triangles). However this trend (black and red dotted lines) was not significant. A lower stem cell division rate was more consistent with the small intestinal data (green line, 0.75 divisions per day), relative to a model [10] postulating one division per day for the colon (grey line).
Crypt methylation patterns encode niche dynamics, but exact niche stem cell numbers and probabilities of symmetric divisions remain uncertain because different combinations yield similar outcomes (Table 3). These niche combinations (4–256 stem cells and P1 from 0.98 to 0.89) are the same in large [10] and small intestines. For example, assuming that 95% of stem cell divisions yield one stem cell daughter, the crypt of Lieberkühn niche size is 64 stem cells. As in the colon [10], loss of all niche stem cell lineages except one or a "bottleneck" would recur on average every 3,000 divisions (with a 95% interquantile range of 1,000–7,000 divisions). Small intestinal crypt diversity (unique tags per crypt) did not change with age (Figure 3A), suggesting that niche dynamics or numbers of niche stem cells do not change with aging.
MYOD tags sampled from six small intestines were also consistent with the same niche parameters inferred with the CSX tags (Figure 3B). For a further test of our model, CSX tags were sampled from villi of six intestines. Villi should exhibit more tag diversity than crypts because they receive contributions from four to ten surrounding crypts [18]. Furthermore, if methylation reflects the lifetime accumulation of stem cell mitotic errors, percent methylation should be similar between villi and crypts because crypt cells are only a few divisions older than villus cells. Consistent with these expectations (Figure 3C), there were significantly more unique tags per villus than per crypt (average 4.8 versus 3.0, p < 0.001, two-tail t-test) whereas methylation differences were not significant (average 21.8% versus 22.9%, p = 0.76). Distances between tags within a villus were also significantly greater than tag intracrypt distances (2.5 versus 1.7, p <0.001). Villus and crypt comparisons illustrate the ability of methylation tags to encode simultaneously both mitotic age (numbers of divisions since birth) and distinctly different ancestries.
Table 3 Stem Cell Niche Parameters
Niche Size P asymmetric (P1)* P symmetric (P0+P2)
4 0.98 0.02
16 0.97 0.03
64 0.95 0.05
256 0.89 0.11
*P0+P1+P2 = 1, with P0 = P2
Discussion
The adult small intestine is physically composed of millions of crypts, and cells that constantly divide and die. Underlying the homeostatic visual appearance of a normal small intestine is an ancestral somatic cell tree that grows with age (Figure 6). Starting with the zygote, millions of related cells create an intestine. Past and present cells are all connected through time by ancestral lineages or branches, which ultimately root in the zygote or first common ancestor. Although stem cell definitions may differ [2-4], a crypt common ancestor is equivalent to a stem cell because all cells in a clonal crypt unit are progeny of this single common stem cell ancestor.
Figure 6 Somatic cell trees. A: A niche somatic cell tree. Starting from the zygote, millions of related cells create an intestine. Within each crypt are multiple stem cells (a niche with four stem cells is illustrated). With age, branches become longer reflecting more divisions since birth. Most niche stem cell lineages are lost (dotted lines) from random stem cell loss with replacement, which continuously creates newer more recent common crypt ancestors (circles). Such common crypt ancestors are stem cells because all current crypt cells are progeny of such cells. Any one of the four current niche stem cells may become a common ancestor, but only one will. In this way, crypts can appear to have both a single stem cell (most recent common crypt ancestor) and multiple potential stem cells. A villus tree (red lines in bottom tree) has essentially the same age as the crypt tree (same number of divisions since birth) but villi should exhibit more diversity than crypts because villus cells have older most recent common ancestors. B: Somatic cell tree with immortal stem cell lineages. Stem cells always divide asymmetrically and their lineages never become extinct. Unlike a niche somatic cell tree, branches are never lost or "pruned".
Both immortal and niche stem cell mechanisms can theoretically produce appropriate numbers of differentiated cells consistent with the morphology of normal small intestine. However, the shape of an intestinal somatic cell tree differs whether stem cell lineages are immortal or maintained by niches (Figure 6). Immortal stem cell lineages result in multiple long crypt branches, with the most recent common crypt ancestor present around birth. In contrast, a niche mechanism constantly creates newer more recent common crypt ancestors as most niche stem cell lineages become extinct.
Methylation tags can distinguish between immortal or niche stem cell lineages because random somatic epigenetic errors will accumulate differently. Specifically, a niche mechanism produces more variability between crypts (wider variation in unique tags per crypt within a single intestine) and less intracrypt diversity (smaller average intracrypt distances) than immortal stem cells (Figure 4). Small intestine and colon crypt methylation patterns [10] were similar and more consistent with stem cell niches. The same stem cell dynamics (Table 3) fit both colon and small intestinal niches. There were no apparent differences between ileal and duodenal crypt niches, and niche stem cell numbers (like the colon [10]) did not appear to change or decline with age.
Niche stem cells defined by ancestry are physically intangible because common ancestors are defined by past events and no longer exist. Stem cells with immortal lineages are more readily identified because their pasts and futures are predictable. However, niche stem cell fates are unpredictable because all may potentially become common ancestors but only one will. The inability to predict niche survival may help explain why some adult stem cells have been so difficult to isolate or characterize. A niche somatic cell tree has few branches because random stem cell turnover eventually "prunes" all niche lineages except one (Figure 6). Such bottlenecks are predicted by our analysis to recur on average after 3,000 divisions.
Other mechanisms may also be consistent with crypt methylation patterns and the assumptions of our model remain unverified [19]. For example, the observed variability in methylation patterns could also be generated if stem cell numbers were different between crypts within an intestine [19]. Although our bisulfite sequencing appears technically adequate (no evidence of nonconversion of C to T and only rare mutations (<1 per 1,000 bases) at non-CpG sites), it is difficult to check the accuracy and reproducibility of the data. Repeat sampling of a crypt typically yields similar but not identical methylation patterns (data not shown), which may reflect crypt heterogeneity or experimental artifact.
One strategy to test empirically a stochastic model that inherently yields scattered results is to examine similar but biologically distinct entities. Both small intestine and colon crypts are thought to be maintained by stem cell niches [5,6] and the successful application of our model to the small and large intestines with methylation patterns from CpG-rich sequences on different chromosomes (CSX and MYOD) is empirical support for its ability to infer stem cell dynamics. In addition, small intestinal villi are physically different from crypts and represent mixtures from multiple adjacent crypts. Villi should be more diverse than crypts, yet villi and crypts should have similar numbers of divisions since birth. As one would expect if methylation records somatic cell histories, villus and crypt tag percent methylation were not significantly different, and villi contained significantly more tag diversity than crypts. Therefore, methylation patterns and our model are consistent with colon and small intestine crypt niches, and small intestine villi. Genetic alterations also appear to modulate stem cell dynamics because certain germline APC mutations are associated with significantly more diverse tags in normal-appearing familial adenomatous polyposis colon crypts, consistent with increased niche stem cell survival [17].
Mouse studies suggest that stem cell division rates are higher in the small intestines than the colon [2,3,20]. However, it is difficult with most assays to distinguish between stem and non-stem cell proliferation, and there are few human small intestine stem cell studies. Of interest, neoplasia, as with Min mice [21], is more frequently observed in the murine small intestines relative to the colon, whereas human small intestinal tumors are a small fraction of colon tumors [1]. In contrast to murine studies, human small intestinal stem cell division rates appeared to be slower or similar to those in the colon because age-related methylation appeared to increase more slowly in the small intestine (Figure 5), although the difference was not significant. Assuming a molecular clock hypothesis [9] or equivalent CSX methylation error rates throughout the lower gastrointestinal tract, the data are more consistent with equivalent or slightly lower small intestinal stem cell division rates relative to the colon.
There is no definitive evidence supporting a somatic cell molecular clock hypothesis, but a priori a slower small intestinal stem cell division rate is more consistent with human intestinal cancer epidemiology [1], because fewer small intestinal errors (genetic or epigenetic) would be expected to accumulate during aging. A slower small intestinal stem cell division rate could also help explain why crypt purification is faster in the murine colon relative to the small intestine [5]. Moreover, an ability to count relative divisions since birth in different human tissues allows distinctions (Figure 7) between mitotic tissue ages (divisions since birth) and chronological ages (years since birth). The colon and small intestines within an individual have equivalent chronological ages but may have different mitotic ages.
Figure 7 An intestinal tree based on mitotic ages or numbers of divisions since birth. Each horizontal branch reflects a single crypt. Although all tissues have the same chronological ages, differences in stem cell division rates allow tissues within the same individual to have different mitotic ages. A small intestine tree has a more crypt branches (greater numbers of crypts) than a colon, but its branches may be shorter, which can possibly help explain why despite the greater physical size of the organ, small intestinal tumors are infrequent relative to colonic ones.
Conclusion
Methylation patterns suggest that niches containing multiple stem cells maintain crypts throughout the lower gastrointestinal tract. Small intestine stem cells appear to divide at equivalent or slower rates relative to the colon, and niche dynamics remain stable during aging. Although methylation tags only indirectly track stem cell dynamics and their exact interpretations are uncertain, they potentially allow for the systematic investigation of any intestine without prior experimental intervention. A somatic cell tree must underlie all human tissues and studies based on the hypothesis that certain somatic methylation errors record somatic cell histories may better define how cells divide and die during normal and abnormal aging.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
JYK performed most of the experiments and helped write the manuscript. KDS and ST helped with the statistical and quantitative analysis. DS analyzed the data and wrote the manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
We thank Mario Campuzano for technical assistance and Dr. Robert W. Beart for providing the specimens and clinical information. This work was supported by a grant from the National Institutes of Health (DK61140). ST is a Royal Society-Wolfson Research Merit Award holder and is supported in part by a grant from Cancer Research UK.
==== Refs
Gore RM Small bowel cancer. Clinical and pathologic features Radiol Clin North Am 1997 35 351 360 9087208
Potten CS Booth C Hargreaves D The small intestine as a model for evaluating adult tissue stem cell drug targets Cell Prolif 2003 36 115 129 12814429 10.1046/j.1365-2184.2003.00264.x
Potten CS Radiation, the ideal cytotoxic agent for studying the cell biology of tissues such as the small intestine Radiat Res 2004 161 123 136 14731078
Potten CS Loeffler M Stem cells: attributes, cycles, spirals, pitfalls and uncertainties. Lessons for and from the crypt Development 1990 110 1001 1020 2100251
Williams ED Lowes AP Williams D Williams GT A stem cell niche theory of intestinal crypt maintenance based on a study of somatic mutation in colonic mucosa Am J Pathol 1992 141 773 776 1415475
Spradling A Drummond-Barbosa D Kai T Stem cells find their niche Nature 2001 414 98 104 11689954 10.1038/35102160
Marshman E Booth C Potten CS The intestinal epithelial stem cell BioEssays 2002 24 91 98 11782954 10.1002/bies.10028
Campbell F Williams GT Appleton MA Dixon MF Harris M Williams ED Post-irradiation somatic mutation and clonal stabilisation time in the human colon Gut 1996 39 569 573 8944567
Blair Hedges S Kumar S Genomic clocks and evolutionary timescales Trends Genet 2003 19 200 206 12683973 10.1016/S0168-9525(03)00053-2
Yatabe Y Tavaré S Shibata D Investigating stem cells in human colon by using methylation patterns Proc Natl Acad Sci USA 2001 98 10839 10844 11517339 10.1073/pnas.191225998
Ahuja N Li Q Mohan AL Baylin SB Issa JP Aging and DNA methylation in colorectal mucosa and cancer Cancer Res 1998 58 5489 5494 9850084
Issa JP CpG-island methylation in aging and cancer Curr Top Microbiol Immunol 2000 249 101 118 10802941
Bird A DNA methylation patterns and epigenetic memory Genes Dev 2002 16 6 21 11782440 10.1101/gad.947102
Potten CS Kellett M Rew DA Roberts SA Proliferation in human gastrointestinal epithelium using bromodeoxyuridine in vivo: data for different sites, proximity to a tumour, and polyposis coli Gut 1992 33 524 529 1316306
Scott H Brandtzaeg P Enumeration of Paneth cells in coeliac disease: comparison of conventional light microscopy and immunofluorescence staining for lysozyme Gut 1981 22 812 816 7028576
Garabedian EM Roberts LJ McNevin MS Gordon JI Examining the role of Paneth cells in the small intestine by lineage ablation in transgenic mice J Biol Chem 1997 272 23729 23740 9295317 10.1074/jbc.272.38.23729
Kim KM Calabrese P Tavaré S Shibata D Enhanced stem cell survival in familial adenomatous Polyposis Am J Pathol 2004 164 1369 1377 15039224
Cocco AE Dohrmann MJ Hendrix TR Reconstruction of normal jejunal biopsies: three-dimensional histology Gastroenterology 1966 51 24 31 5939338
Ro S Rannala B Methylation patterns and mathematical models reveal dynamics of stem cell turnover in the human colon Proc Natl Acad Sci U S A 2001 98 10519 10521 11553798 10.1073/pnas.201405498
Wright NA Alison M The biology of epithelial cell populations 1984 Oxford: Oxford University Press
Su LK Kinzler KW Vogelstein B Preisinger AC Moser AR Luongo C Gould KA Dove WF Multiple intestinal neoplasia caused by a mutation in the murine homolog of the APC gene Science 1992 256 668 670 1350108
| 15975143 | PMC1168897 | CC BY | 2021-01-04 16:27:56 | no | BMC Med. 2005 Jun 23; 3:10 | utf-8 | BMC Med | 2,005 | 10.1186/1741-7015-3-10 | oa_comm |
==== Front
BMC MicrobiolBMC Microbiology1471-2180BioMed Central London 1471-2180-5-291590720410.1186/1471-2180-5-29Research ArticleDetection of a highly prevalent and potentially virulent strain of Pseudomonas aeruginosa from nosocomial infections in a medical center Matar Ghassan M [email protected] Mira H [email protected] George F [email protected] Zaher [email protected] Ghassan [email protected] Usamah [email protected] Departments of Microbiology and Immunology, American University of Beirut, Beirut, Lebanon2 Otolaryngology, Neck and Head Surgery, American University of Beirut, Beirut, Lebanon3 Pathology and Laboratory Medicine, American University of Beirut, Beirut, Lebanon4 Internal Medicine Faculty of Medicine, American University of Beirut, Beirut, Lebanon2005 20 5 2005 5 29 29 26 1 2005 20 5 2005 Copyright © 2005 Matar et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
We correlated genotypes, virulence factors and antimicrobial susceptibility patterns of nosocomially identified Pseudomonas aeruginosa isolates from clinical specimens to those of environmental isolates encountered in the same units of a medical center. Antibiotic susceptibility testing, RAPD analysis and detection of enzymatic activities of extracellular virulence factors, were done on these isolates.
Results
Data showed that most of the clinical and environmental isolates were susceptible to tested antimicrobial agents. RAPD analysis determined the presence of 31 genotypes, with genotype 1 detected in 42% of the clinical isolates and 43% of the environmental isolates. Enzymatic activity testing showed that genotype 1 produced all virulence factors tested for.
Conclusion
In conclusion, our data demonstrated the predominant prevalence of a potentially virulent P. aeruginosa genotype, circulating in a number of units of the medical center and emphasize the need to reinforce infection control measures.
==== Body
Background
Despite the advances in hospital care and the introduction of a wide variety of antimicrobial agents, Pseudomonas aeruginosa continues to be a major nosocomial pathogen particularly in patients who suffer from immunosuppression [1]. P. aeruginosa is a ubiquitous pathogen prevalent in the hospital environments, and can cause severe nosocomial infections [2]. The latter involve a broad spectrum of infections including the respiratory, gastrointestinal, and urinary tracts as well as wound infections, sepsis and others [3]. Various possible sources of P. aeruginosa infection in hospitals have been identified; such as tap water, medical equipment, hospital personnel and other patients [2,4]. P. aeruginosa accounts for 10% of all hospital acquired infections, a site specific prevalence which may vary from one unit to another and from study to study [5]. Among data on site-specific infections, P. aeruginosa appears to be the major cause of ventilator-associated pneumonia with a high rate of attributable mortality [6]. Moreover this organism can contaminate a number of other medical equipment such as respirators, endoscopes, bronchoscopes, transvenous pacemakers, urinary catheters, and dialysis equipment, leading to site-related infections [7,8]. During the last year, the average prevalence of P. aeruginosa nosocomial infections in our medical center was 18%. Such a high rate prompted us to study the P. aeruginosa genotypes circulating in the various units to reveal the clonal relationship between clinical and environmental isolates and to allow elucidating the source and mode of transmission of this important bacterium at this medical center.
Results
Our data have shown that several mechanical devices were associated with P. aeruginosa infection in our patients with 55% due to mechanical ventilation and the remaining 45% due to polysite catheters, Foley catheters and different types of surgery.
RAPD analysis have shown 31 genotypes present among the clinical and the environmental isolates (figure 1). Thirty eight of ninety (42%) of the clinical isolates and 10/23 (43%) of the environmental isolates showed genotype 1 to be distributed among the medical center units. Each of the genotypes 2–30 represented from 1–8% of the strains. Antimicrobial susceptibility testing has shown that susceptibility patterns between clinical and environmental isolates were similar with most drugs showing > 90% susceptibility, with the exception of tobramycin and gentamycin which showed lower susceptibility (83%) in the environmental strains. Data is in concordance with previous reports in this institution [13]. Enzymatic assays determined that genotype 1 in addition to other 10 genotypes, in clinical and environmental isolates, were positive for all virulence factors tested for. All other genotypes were all positive for the production of protease, lecithinase and coagulase and positive in 83–89% of the cases for the production of the other 4 virulence factors (Figure 2). Table 1 shows the relationship between the various genotypes, to source, antibiograms and virulence factors.
Discussion
The strain distribution based on RAPD analysis showed that clinical and environmental isolates distributed in one or more than one unit, included genotypes 1–8 and 9, with predominance of genotype 1 in all investigated units. This may indicate that cross contamination among patients lead to the spread of this genotype among the various units, possibly through transient hand carriage by health care personnel due to contact with contaminated surfaces or by patient contact with contaminated surfaces or medical equipment [4]. Our findings suggest that cross colonization may be an important means of P. aeruginosa spread and infection especially after identification of a potentially virulent clone (genotype 1) of this organism that had been propagated in various units over a period of 9 months. This could indicate that the patients were continuously infected with a strain originating from an exogenous source. The importance of cross colonization of P. aeruginosa in nosocomial infections was previously reported, by Bergmans et al who studied 100 patients admitted to an ICU ward; cross colonization accounted for 50% of all cases of acquired P. aeruginosa colonization, the other 50% of patients were probably colonized from endogenous sources [14].
The remaining genotypes were isolated exclusively from the clinical specimens of patients and were not detected among environmental isolates. Most of these genotypes did not harbor all the virulence factors tested for. Not being encountered in environmental sources may indicate that these strains may have been endogenously acquired. High rate of colonization with P. aeruginosa from endogenous sources occurs mainly in the respiratory and gastrointestinal tracts [2]. Hospitalization may lead to increased rates of carriage, particularly in the lower respiratory tract in patients undergoing mechanical ventilation, upper respiratory tract due to broncho- pulmonary colonization and infection, in the gastrointestinal tract of patients receiving chemotherapy for neoplastic diseases, or at virtually any site in patients treated with antibiotics [3,15,16].
Prevalence of strains with resistance to all antimicrobial agents will constitute a major risk for hospitalized patients. In our study, though, the most prevalent strain of genotype 1 was susceptible to all antimicrobial agents and does not constitute a problem in treatment. However, its potential of producing all virulence factors and being spread by various means in the hospital, unlike other genotypes that harbor all virulence factors, may render genotype 1 a high risk pathogen specially in the immunosuppressed and debilitated patients. The fact that genotype 1 remained susceptible to all antibiotics lead to the conclusion that patients could be continuously infected with a strain originating from an exogenous source.
In addition to mechanical spread by personnel, this genotype may carry a number of adhesins that enhance its colonization in the hospital environment and render it more accessible to patients. Studies are underway in our laboratory to detect by PCR, genes encoding a number of adhesins and determine their transcription levels in genotype 1, in comparison to other encountered genotypes. This will shed light on the possible role of adhesins on the prevalence of this genotype in the hospital environment. The extracellular enzymes or toxins produced, on the other hand, will contribute to the breaking down physical barriers and help the organism to penetrate, impair host defenses, and render its new milieu more conducive to its physical, nutritional and reproductive requirements [17].
In summary, our data have shown the predominant prevalence of a potentially virulent P. aeruginosa genotype 1 in clinical and environmental specimens, circulating in the various hospital units. From a practical point of view, the results of our study emphasize the need to reinforce implementation of infection control measures, and to limit the transmission of P. aeruginosa among patients and from environmental sources to patients. Screening for P. aeruginosa carriage in all patients with nosocomial colonization or infection should also be done in research settings using both rectal and respiratory tract specimens to determine the source of colonization/infection and hence get informed on whether it was acquired endogenously or exogenously.
Conclusion
In conclusion, our data have shown the predominant prevalence of a potentially virulent P. aeruginosa genotype 1 in clinical and environmental specimens, circulating in the various medical center units.
Methods
Consecutive P. aeruginosa (90) isolates were recovered from different patients specimens (one per patient) submitted for bacteriological investigations at the Clinical Microbiology Laboratory at the American University of Beirut Medical Center (AUBMC), between September 2003 and May 2004. Patients acquiring a nosocomial infection due to P. aeruginosa as determined by clinical and laboratory testing and indicated in their medical records, were only considered in this study. Fever, and recovery of P. aeruginosa from the site of infection during stay at the medical center, constituted the most important criteria that defined patient's infection with this organism. Patients' data collected from the medical records, included age (2 to 91 years), sex (Males: 43 and Females: 47), admission date, admission diagnosis, invasive procedures used on the patients, symptoms, and the date of the first positive culture for P. aeruginosa. The drugs used in the treatment of these patients, mainly included: amikacin, azactam, gentamicin, tobramycin, and tazocin. Patients were distributed within ten different units in the medical center, mainly the Respiratory Care Unit (RCU), Intensive Care Unit (ICU), Coronary Care Unit (CCU), the Surgery Unit, as well as other units. Twenty three isolates were also collected from different environmental sources, such as, respirators, respirators' filters, water irrigation, tap water, basins, trays, bed side tables, side rails, and sink sides. Statistical analysis determined the sample size required to estimate the true proportion (percentage of P. aeruginosa infections during a given period of time) to within 0.10, with 95% confidence was calculated. Calculations estimated the minimum number of samples required to be 54 [9].
The presumptive identification of P. aeruginosa on culture based on colonial morphology, Gram stain microscopy, and oxidase test was further confirmed by the API NE Kits and growth at 42°C. Susceptibility of all isolates to a panel of antimicrobial agents (amikacin, aztreonam, ceftazidime, ciprofloxacin, gentamicin, imipenem, piperacillin/tazobactam, tobramycin) was determined according to the guidelines of the National Committee for Clinical Laboratory Standards (NCCLS) [10]. P. aeruginosa ATCC 25321 strain was used as positive control in all tests.
DNA was extracted from P. aeruginosa ATCC strain and from all isolates of P. aeruginosa by the GFX™ Genomic Blood DNA Purification Kit (Amersham PharmaciaBiotech, Uppsala, Sweden) according to the manufacturers' specifications. Random amplified polymorphic DNA (RAPD) analysis of the clinical and environmental isolates using two in-house oligonucleotide primers, Pa1 (5'AGGGGTCTTG 3') and Pa2 (5' CTTCTTCAGCTCGACGCGACG 3') was done. RAPD was carried out according to Matar et al [11] using the PTC-100™ Programmable Thermal Controller (MJ Research, Inc., Watertown, Mass., USA). Briefly, RAPD was carried out on all isolates in 100 μl reaction mixtures containing each: 10 μl of template DNA, 16 μl of dNTPs (0.2 mM), 10 μl of 10X PCR buffer (100 mM TrisHCl [pH 8.3], 500 mM KCl, 4 mM MgCl2), 1 μl of primer 1 (0.5 μM), 1 μl of primer 2 (0.3 μg/ μl), 2.5 U of Taq DNA polymerase and 61.5 μl of nanopure sterile water. The amplification program, included the following steps: denaturation at 94°C for 3s, annealing at 53°C for 1 min and extension at 72°C for 1 min, for 44 cycles. The cycles were followed by a final extension step at 72°C for 10 min. Amplicons were subjected to electrophoresis on 2% agarose gels at 107 volts for 2 hours. Patterns that had the same number of bands and similar fragments size were considered identical.
The enzymatic activities of the isolates of P. aeruginosa were evaluated by spot inoculation containing 106 CFU/ml of the organisms in various media [12]. Media used: Brain heart infusion for the protease activity, 1% elastin (Sigma Chemical Co. St Louis, Mo. USA) for the elastase activity, human fibrinogen type 1 (Sigma Chemical Co. St Louis, Mo. USA) for the fibrinolytic activity, trypticase soy agar (TSA) supplemented with egg yolk (Difco Laboratories, Detroit, Mi., USA) for the lecithinase production, TSA with tween 80 (Sigma Chemical Co. St Louis, Mo. USA) for the lipase activity, DNase test agar with toluidine blue 0, (Difco Laboratories, Detroit Mi., USA) for the DNAase production, and rabbit plasma (Difco Laboratories, Detroit Mi., USA) for the coagulase activity. Positivity of tests was assessed as follows: clearing of opacity around the inoculum spots for the protease, elastase and fibrinolytic activities, white precipitate around or beneath the inoculum spots for the lecithinase activity, a turbid halo around the inoculum spots for the lipase activity, formation of a pink halo around the inoculum spots for the DNase activity, and gelling of rabbit plasma after 48 hours for the coagulase activity.
Authors' contributions
GM supervised the study and wrote the manuscript. MC did the bench work and helped in writing the manuscript. GA provided bacterial isolates. ZS provided help on wards. GJ provided clinical support. UH provided clinical support. All authors read and approved the final manuscript.
Acknowledgements
Thanks are due Miss Marie Risk and Mr. Elias Rahal for technical assistance.
Figures and Tables
Figure 1 (A) Genotypes of P. aeruginosa isolates found in 10 units. Lane 1: 50-bp ladder, lane 2: negative control, lane 3:ATCC25321 strain, lanes 4–18: Genotypes 1,2,3,4,5,6,7,8,9,10,11,12,13,14, and 15. (B) Lane 16: 50-bp ladder, lane 17: negative control, lane 18: ATCC 25321 strain, lanes 19–33: Genotypes 16,17,18,19,20,21,22,23,24,25,26,27,28,29, and 30. (C) Genotypes of P. aeruginosa from environmental sources found in the RCU. Lane 1: 50-bp ladder, lane 2: negative control, lane 3:ATCC 25321 strain, lane 4–11: Genotypes (1,4,17,25,27,28,30,31).
Figure 2 Percentage of clinical and environmental P. aeruginosa isolates producing the virulence factors.
Table 1 Correlation between P. aeruginosa genotypes, source and site of infection, antimicrobial susceptibility and enzymatic activities of virulence factors
Genotypes types of unit Number of clinical isolates Isolation site/ Number of isolates Antibiograms Virulence factors
AN ATM CAZ CIP GM IPM TZ NN Pro Lec Elas Lip Fib Coag
1 RCU 15 DTA1/ 13 blood/ 1 Wound/ 1 S S S S S S S S + + + + + +
ICU 3 DTA/ 2 Wound/ 1 S S S S S S S S + + + + + +
CCU 1 Urine/ 1 S S S S S S S S + + + + + +
PICU 4 DTA/2 Tongue/ 1 Wound/ 1 S S S S S S S S + + + + + +
St Jude 1 Wound/ 1 S S S S S S S S + + + + + +
Surgery 3 Wound/ 3 S S S S S S S S + + + + + +
5 South 6 Abscess/ 1 Sputum/ 2 DTA/ 1 Bronchial washing/ 1 Urine/ 1 S S S S S S S S + + + + + +
4 South 2 Sputum/ 1 Swab/ 1 S S S S S S S S + + + + + +
9 South 3 DTA/ 1 Sputum/ 1 Blood/ 1 S S S S S S S S + + + + + +
2 RCU 1 DTA/ 1 S S S S S S S S + + + + + +
ICU 1 DTA/ 1 S S S S S S S S + + + + + +
Surgery 2 Wound/ 2 S S S S S S S S + + + + + +
Oncology 1 Blood/ 1 S S S S S S S S + + + + + +
5 south 1 Pleural fuild/ 1 S S S S S S S S + + + + + +
3 RCU 2 DTA/ 1 Wound/ 1 S S S S S S S S + + + + + +
5 South 2 Sputum/ 2 S S S S S S S S + + + + + +
Oncology 3 DTA/ 2 Blood/ 1 S S S S S S S S + + + + + +
4 RCU 1 DTA/ 1 S S S S S S S S + + + + + +
St Jude 2 Blood/ 1 Catheter/ 1 S S S S S S S S + + + + + +
5 South 1 Bile/ 1 S S S S S S S S + + + + + +
5 PICU 1 DTA/ 1 S S S S S S S S + + - + + +
4 South 1 DTA/ 1 S S S S S S S S + + - + + +
6 RCU 1 DTA/ 1 S S S S S S S S + + + - + +
ICU 1 Sinus/ 1 S S S S S S S S + + + - + +
7 ICU 2 DTA/ 2 S S S S S S S S + + + - + +
Oncology 1 Blood/ 1 S S S S S S S S + + + - + +
8 ICU 1 DTA/ 1 S S S S S S S S + + + + - +
Oncology 1 Blood/ 1 S S S S S S S S + + + + - +
9 RCU 1 Urine/ 1 S S S S S S S S + + + + + +
Surgery 1 Wound/ 1 S S S S S S S S + + + + + +
10 4 South 2 Wound/ 2 S S S R R R R R + + - + - +
11 Oncology 2 leg ulcer/ 1 Bronchial washing/ 1 S S S S S S S S + + + + + +
12 5 South 2 DTA/ 2 S S S S S S S S + + + - - +
13 9 South 1 Sinus discharge/ 1 S S S R R S S R + + - + - +
14 9 South 1 Wound/ 1 S S S S S S S S + + + + + +
15 ICU 1 DTA/ 1 S S S S S S S S + + + - + +
16 CCU 1 Sternal tissue / 1 S S S S S S S S + + + + + -
17 CCU 1 Urine/ 1 S S S S S S S S + + + - + +
18 CCU 1 DTA/ 1 S I S S S S S S + + - - - +
19 RCU 1 DTA/ 1 S I S S S S S S + + + + + +
20 RCU 1 DTA/ 1 S S S S S R S S + + - + - +
21 RCU 1 DTA/ 1 S S S S R S S R + + - + - +
22 RCU 1 DTA/ 1 S I S S S S S S + + + + + +
23 RCU 1 DTA/ 1 S I S S S S R S + + - + - +
24 RCU 1 Wound/ 1 R S R R R R R R + + - + - +
25 RCU 1 DTA/ 1 S S S S R S S I + + + + + +
26 RCU 1 Sputum/ 1 S R R S S R R S + + - + - +
27 PICU 1 DTA/ 1 S R R S S S R S + + + + + +
28 ICU 1 DTA/ 1 S R R S S I R S + + + + + +
29 4 South 1 DTA/ 1 S I S S R R S S + + + + + -
30 RCU 1 DTA/ 1 S S S S R S S I + + - + - +
NB: Genotype 31 was only found among the environmental isolates
1 DTA: Deep Tracheal Aspirate
AN: Amikacin
CIP: Ciprofloxacin
TZ: Tazocin
ATM: Aztreonam
GM: Gentamicin
NN: Tobramycin
CAZ : Ceftazidime
IPM: Imipenem
Pro: Protease
Lip: Lipase
Lec: Lecithinase
Fib: Fibrinolysin
Elas: Elastase
Coag: Coagulase
==== Refs
Zenone T Souillet G X linked Agammaglobulinemia presenting as Pseudomonas aeruginosa septicemia Scand J Infect Dis 1996 28 417 418 8893410
Morrison AJ Wenzel RP Epidemiology of infections due to Pseudomonas aeruginosa Rev Infect Dis 1984 6 S627 S642 6443765
Pollack M Mandell GL, Bennett JE, Dolin R Pseudomonas aeruginosa Principles and Practice of infectious diseases 1995 New York: Churchill Livingstone 1980 2003
Pittet D Dharan S Touveneau S Sauvan V Perneger TV Bacterial contamination of the hands of hospital staff during routine patient care Arch Intern Med 1999 159 821 826 10219927 10.1001/archinte.159.8.821
Jones RN Croco MA Kugler KC Pfaller MA Beach ML Respiratory tract pathogens isolated from patients hospitalized with suspected pneumonia: frequency of occurrence and susceptibility patterns from the Sentry Antimicrobial Surveillance Program Diagn Microbiol Infect Dis 2000 37 115 125 10863106 10.1016/S0732-8893(00)00115-2
Rello J Rue M Jubert P Survival in patients with nosocomial pneumonia: impact of the severity of illness and the etiologic agent Crit Care Med 1997 25 1862 1867 9366771 10.1097/00003246-199711000-00026
Baker AM Meredith JW Gontijo PP Pneumonia in intubated trauma patients-microbiology and outcomes Am J Respir Crit Care Med 1996 153 343 347 8542141
Morrison AJ Wenzel RP Epidemiology of infections due to Pseudomonas aeruginosa Rev Infect Dis 1984 6 S627 S642 6443765
Kuzma JW Kuzma JW Determination of sample size. Kuzma, JW Basics statistics for the health sciences 1998 California: Mayfield Publishing Company 117 118
National Committee for Clinical Laboratory Standards Performance standards for antimicrobial susceptibility testing; Fourteenth informational supplement NCCLS document M 100- S14 National Committee for Clinical Laboratory Standards, Wayne, Pennsylvania, USA 2004 36 37
Matar GM Harakeh HS Ramlawi F Khneisser I Hadi U Comparative analysis between Pseudomonas aeruginosa genotypes and severity of symptoms in patients with unilateral or bilateral otits externa Curr Microbiol 2001 42 190 193 11270653 10.1007/s002840010202
Matar GM Ramlawi F Harakeh HS Hadi U Comparative Analysis Between Virulence Factors Produced By Various Pseudomonas aeruginosa Genotypes and Severity of Symptoms in Patients with Otitis Externa Br Med J (ME) 2002 9 7 9
Araj G Kanj S Current status and changing trends of antimicrobial resistance in Lebanon J Med Liban 2000 48 221 226 11214193
Bergmans DC Bonten MJ Vantiel FH Gaillard CA Van der Geest S Wilting RM De Leeuw PW Stobberingh EE Cross colonization with Pseudomonas aeruginosa of patients in an intensive care unit Thorax 1998 53 1053 1058 10195078
Berthelot P Grattard F Mahul P Pain P Jospe R Venet C Carricajo A Aubert G Ros A Dumont A Lucht F Zeni F Auboyer C Bertrand J-C Pozzetto B Prospective study of nosocomial colonization and infection due to Pseudomonas aeruginosa in mechanically ventilated patients Int Care Med 2001 27 503 512 10.1007/s001340100870
Correa CMC Tibana A Gontijo Filho PP Vegetables as a source of infection with Pseudomonas aeruginosa Vin a university and oncology hospital of Rio de Janeiro J Hosp Infect 1991 18 301 306 1682368 10.1016/0195-6701(91)90187-D
Amitani R Wilson R Rutman A Effects of human neutrophil elastase and pseudomonas aeruginosa proteinases on human respiratory epithelium Am J Respir Cell Mol Biol 1991 4 26 32 1898852
| 15907204 | PMC1168898 | CC BY | 2021-01-04 16:03:39 | no | BMC Microbiol. 2005 May 20; 5:29 | utf-8 | BMC Microbiol | 2,005 | 10.1186/1471-2180-5-29 | oa_comm |
==== Front
BMC MicrobiolBMC Microbiology1471-2180BioMed Central London 1471-2180-5-381597813310.1186/1471-2180-5-38Research ArticleImmunization of mice with YscF provides protection from Yersinia pestis infections Matson Jyl S [email protected] Kelly A [email protected] David S [email protected] Matthew L [email protected] Department of Microbiology and Immunology, University of North Dakota School of Medicine and Health Sciences, Grand Forks, ND 58202, USA2005 24 6 2005 5 38 38 26 3 2005 24 6 2005 Copyright © 2005 Matson et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Yersinia pestis, the causative agent of plague, is a pathogen with a tremendous ability to cause harm and panic in populations. Due to the severity of plague and its potential for use as a bioweapon, better preventatives and therapeutics for plague are desirable. Subunit vaccines directed against the F1 capsular antigen and the V antigen (also known as LcrV) of Y. pestis are under development. However, these new vaccine formulations have some possible limitations. The F1 antigen is not required for full virulence of Y. pestis and LcrV has a demonstrated immunosuppressive effect. These limitations could damper the ability of F1/LcrV based vaccines to protect against F1-minus Y. pestis strains and could lead to a high rate of undesired side effects in vaccinated populations. For these reasons, the use of other antigens in a plague vaccine formulation may be advantageous.
Results
Desired features in vaccine candidates would be antigens that are conserved, essential for virulence and accessible to circulating antibody. Several of the proteins required for the construction or function of the type III secretion system (TTSS) complex could be ideal contenders to meet the desired features of a vaccine candidate. Accordingly, the TTSS needle complex protein, YscF, was selected to investigate its potential as a protective antigen. In this study we describe the overexpression, purification and use of YscF as a protective antigen. YscF immunization triggers a robust antibody response to YscF and that antibody response is able to afford significant protection to immunized mice following challenge with Y. pestis. Additionally, evidence is presented that suggests antibody to YscF is likely not protective by blocking the activity of the TTSS.
Conclusion
In this study we investigated YscF, a surface-expressed protein of the Yersinia pestis type III secretion complex, as a protective antigen against experimental plague infection. Immunization of mice with YscF resulted in a high anti-YscF titer and provided protection against i.v. challenge with Y. pestis. This is the first report to our knowledge utilizing a conserved protein from the type III secretion complex of a gram-negative pathogen as a candidate for vaccine development.
==== Body
Background
Yersinia pestis, the causative agent of plague, causes rapidly progressing disease in humans with a high mortality rate, especially in the pneumonic form of the disease. Due to the severe nature of plague, its ability for aerosol transmission, and the potential for human to human transmission plague is considered to be a disease of high concern as an agent of biological warfare or biological terrorism [1]. For this reason, an improved vaccine for plague is desirable. Current efforts for vaccine development have focused on two proteins: LcrV (also known as the V antigen) and the capsular F1 antigen [2]. The best results to date have been obtained by using a combination of recombinant LcrV and F1 subunits [3] separately or as a fusion protein [4,5]. These subunit vaccines demonstrate very good protection against both pneumonic and systemic forms of plague [2] in mouse models. One of the potential limitations of these subunit vaccines is that F1 is not required for full virulence of Y. pestis, as F1-negative strains have the same LD50 value as F1-positive strains [6-9]. A second limitation that could result in undesired side-effects in immunized individuals is the demonstrated immunosuppressive effect of LcrV [10-13]. Additionally, serologic diversity of LcrV has been reported, in Yersinia species other than Y. pestis, that could theoretically limit the usefulness of an LcrV based vaccine. While the recombinant subunit vaccines are very effective in experimental animals and offer protection against F1 minus strains of Y. pestis [2], the inclusion of other antigens with the LcrV/F1 subunit vaccine candidates could improve the ability of the resulting vaccine to offer protection against multiple Y. pestis strains, or the new antigens could be developed as separate vaccine candidates.
The type III secretion apparatus encoded on the low-calcium response (LCR) virulence plasmid, pCD1 in strain KIM [14], of Y. pestis is a conserved virulence mechanism that is absolutely required for virulence of Y. pestis [15]. YscF is a surface localized protein that is required both to secrete Yops and to translocate toxins into eukaryotic cells [16-19]. One report speculates that YscF polymerization is required for a YscF needle to puncture eukaryotic cell membranes [18]. Other researchers suggest that YscF and its homologs function to provide a base that a translocon complex is built upon, or that YscF builds a conduit from the bacterium to the eukaryotic membrane [20]. This suggestion seems more likely given that other proteins such as YopB, YopD, and LcrV are also required for translocation into eukaryotic cells [21-28]. Additionally, YscF needle producing Y. enterocolitica deficient in production of the translocators (LcrV, YopB, and YopD) do not translocate Yops into macrophages, demonstrating that the YscF-needle is not sufficient for translocation [19].
Most currently described pathogenesis-related type III secretion systems possess homologs to YscF. In pathogenic Salmonella and Shigella, the YscF homologs (PrgI and MxiH, respectively) have been demonstrated to form a needle structure that protrudes from the surface of bacterial cells [29-31]. The best-characterized homolog of YscF is EscF of enteropathogenic E. coli (EPEC). EscF is required for "attaching and effacing" (A/E) lesion formation on the intestinal mucosa and for type III secretion of effector proteins [32-34]. EscF is thought to be a structural component of the needle complex on the bacterial surface as it binds EspA, the major component of a filamentous surface organelle, and is required for formation of the EspA filaments. [32-34] However, this surface localization has never been visualized directly, as the only EscF antiserum generated was unable to recognize the native protein [33].
Based on the fact that YscF is thought to be a surface-expressed protein in Y. pestis and is required for virulence, we sought to determine if YscF could serve as a protective antigen against experimental plague infection. Immunization of mice with His-tagged YscF resulted in a high anti-YscF titer and significant protection against i.v. challenge with Y. pestis. The findings of this study suggest that YscF may be a potential plague vaccine candidate that could be used in conjunction with other plague antigens, or possibly alone if its efficacy can be improved by alternative delivery methods.
Results and discussion
Expression and purification of HT-YscF
To facilitate the purification of YscF, yscF was cloned into the overexpression plasmid pET24b (Novagen) to yield a hexahistidine-tag on the C-terminus of YscF (HT-YscF). E. coli BL21(DE3) harboring the HT-YscF expression plasmid, pJM119, was grown in one liter of LB broth [35] containing kanamycin at 37°C. Expression of HT-YscF was induced after 2 h of growth with 0.3 mM IPTG and then incubated until the A550 reached ~1.0. Cells were harvested by centrifugation and disintegrated by passage through a French pressure cell at 20,000 lb/in2. Subsequent to disintegration, the extracts were clarified by centrifugation at 3,200 × g for 20 min at 4°C. Affinity purification of HT-YscF was performed using Talon resin (BD Clontech) using standard methods. Purity of the recovered protein (> 95 %) was estimated by SDS-PAGE on a 15% (wt/vol) gel followed by staining with a Coomassie blue stain. The purified HT-YscF ran as multiple bands on the gel, regardless of the presence or absence of a reducing agent, such as dithiothreitol (data not shown). A band that corresponded to the predicted size of HT-YscF was the dominant species and other larger bands could also be visualized (Figure 1A). Based on the sizes of these bands, it is likely that they represent dimers and other multimers of YscF. The presence of YscF multimers is not surprising as YscF and its homologs are known to form multimeric structures [29,36]. Support for the contention that the larger bands are multimers of YscF is seen in Fig. 1B. Purified recombinant HT-YscF was immunoblotted with a Penta-His specific antibody (Qiagen). The results seen in Figure 1 show that the larger bands seen in panel A are also recognized by the penta-His antibody (Fig. 1B) demonstrating that the larger bands are likely recombinant proteins containing a poly-histidine tag and, therefore, contain YscF. Additionally, the purified HT-YscF was immunoblotted and probed with serum from immunized mice (Fig. 1C) to demonstrate that the immunized mice mounted an immune response against the purified HT-YscF. The larger bands seen in the Coomassie stain and visualized on the immunoblots (with both anti-Penta-His antibody and post-immune sera) could also be contaminating E. coli proteins, that cross-react to the penta-His antibody, this possibility cannot be currently discounted. The presence of the higher molecular weight proteins, if they are not YscF multilmers and they are from E. coli, likely had little influence on this study as immunization with HT-YscF induced a specific antibody response to native YscF produced by Y. pestis (discussed below).
Specificity of the antibody response to YscF
To confirm that the recombinant HT-YscF antibody response generated in immunized mice was directed against YscF from Y. pestis, Y. pestis protein extracts from the parental strain KIM8.3002 (pgm-, pla-) and extracts from a isogenic yscF deletion strain (kindly provided by G. Plano, University of Miami, Miami, Fl.) were immunoblotted and probed with pooled antiserum from HT-YscF immunized mice (Figure 2). The results in Figure 2 demonstrate that the pooled mouse antiserum specifically recognizes YscF produced by Y. pestis. As seen in Figure 2, YscF is visualized on the immunoblot as a highly reactive band of the correct predicted size and the YscF band is only seen only in strains containing the yscF gene (Figue 2, lanes 1–4). Importantly, no bands are seen in lanes 5 and 6 that contain proteins derived from the yscF deletion strain. In lanes 1 and 2, calcium regulation of the YscF band is seen as expected for the LCR-regulated yscF gene. Transcomplementaion of the ΔyscF strain with pBAD-YscF (G. Plano, University of Miami) restored YscF reactivity to the HT-YscF serum in the ΔyscF strain (Figure 2, lanes 3 and 4). Demonstrating that the lack of YscF reactivity in the ΔyscF strain was due to the deletion of yscF. The higher molecular weight bands seen in the whole cell fraction (Figure 2, lanes 1–6) represent cross-reactive Y. pestis bands not specific to YscF, as they are present in the ΔyscF samples. The same cross-reactive bands are also present in whole cell samples probed with pre-immune serum (data not shown) suggesting that the reactivity seen is not induced by immunization with HT-YscF. The higher molecular weight band seen in the culture supernatant fractions could represent a multimer of YscF (possibly a trimer) or YscF in complex with another secreted protein. This higher molecular weight species is likely related to YscF as a similar band is not seen with pre-immune sera (data not shown) or in the ΔyscF strain (Figure 2). These results demonstrate that mice immunized with recombinant HT-YscF produce antibodies that specifically recognize YscF produced by Y. pestis.
Active immunization of outbred mice followed by challenge with Y. pestis KIM5
To examine the ability of HT-YscF to protect mice from Y. pestis infection outbred mice were immunized intra peritoneally with purified HT-YscF using complete Freund's adjuvant (CFA) for primary immunization and incomplete Freund's adjuvant (IFA) for booster immunizations or with a phosphate-buffered saline (PBS, [37]) control in CFA or IFA to control for adjuvant effects. For these studies, 6-to 8-week-old female Swiss-Webster mice were immunized i.p. with 40 μg/mouse HT-YscF in PBS or PBS (control mice) alone emulsified 1:1 with CFA. Experimental mice were boosted with 40 μg/mouse HT-YscF in IFA after two weeks and with 20 μg/mouse HT-YscF in IFA at 4 weeks post-immunization. Negative control mice were boosted with PBS emulsified with IFA according to the same schedule. Two weeks following the final booster immunization, sera were collected from the HT-YscF-immunized and the PBS-immunized mice to assay for HT-YscF reactivity. Sera from 22 mice from the HT-YscF-immunized and the PBS-immunized groups were tested for total IgG reactivity. HT-YscF immunized mice had a geometric mean titer of 1:40,000 for IgG specific to HT-YscF while PBS-immunized mice had HT-YscF titers less than the lowest dilution 1:800 (Table 1). After establishing that the HT-YscF immunized mice had developed a strong antibody response to HT-YscF, the mice were challenged with Y. pestis. Two weeks after the final immunization, groups of 10 mice were challenged intra venously via the retro-orbital sinus with 101 to 106 CFU Y. pestis KIM5 (pgm-) in PBS (grown at 26°C). The mice were observed for 19 days after challenge, and the average doses required to kill 50% of the mice (LD50) for the treatment groups were calculated using the extrapolation method of Reed and Muench [38]. Mice that were immunized with HT-YscF demonstrated a 134-fold increase in the calculated LD50 value as compared to PBS-immunized mice (Table 1). These results demonstrate that immunization of mice with HT-YscF was able to provide a degree of protection to the immunized mice from a subsequent challenge with Y. pestis (Table 1). While the protection provided by HT-YscF is not of the same magnitude as that seen with the protective antigens F1 or LcrV, the increased LD50 value clearly shows that immunization with YscF affords a significant level of protection. Thus, HT-YscF becomes the only other reported antigen apart from LcrV or F1 to induce a significant protection in F1-positive Y. pestis. Immunization with YopD has been demonstrated to provide significant protection against a F1-minus mutant of Y. pestis [39]. The protection generated by HT-YscF suggests that YscF could be potentially developed as a novel subunit vaccine for Y. pestis or could serve as an additional antigen in a multivalent Y. pestis vaccine comprised of YscF, F1, and LcrV for example.
Characterization of the antibody response to HT-YscF
Mice immunized with HT-YscF demonstrated a strong antibody response to YscF and provided protection to the vaccinated mice from lethal Y. pestis challenge. Due to the strong antibody response, isotyping analysis was performed to determine the predominant isotypes of antibodies produced by mice in response to vaccination with HT-YscF in CFA/IFA. Anti-YscF antibody titers were determined two weeks following the last immunization, prior to challenge. The YscF-specific antibody titers of PBS-immunized mice were below the ELISA assay baseline of 1:800 (Table 1), as was the pre-immune serum (data not shown). However, the HT-YscF immunized mice reached a GMT (geometric mean titer) of 1:40,000 (Table 1) for total IgG. Isotyping analysis was performed on the pooled sera obtained from the 22 mice selected for total the IgG analysis reported in Table 1. Pooled sera were used to minimize the animal to animal variation expected from using outbred mice. The isotyping analysis demonstrated no significant IgA or IgM production (Table 2) and a very high IgG titer (Table 2) as expected from the data in Table 1. Among the IgG subclasses IgG2b appeared to have the highest levels (Table 2), although IgG1 and IgG2a levels were also very high (Table 2). IgG3 levels were the lowest (Table 2). Generally, immunization with CFA tends to drive a strong Th1 response. Immunization with HT-YscF in CFA induced a strong Th1 response, evident by the high IgG2a response. However, a strong Th2 response is also present as seen by the high IgG1 and IgG2b levels. Immunization with HT-YscF induced a strong IgG1 response in mice and interestingly, Titball et al. have shown that high IgG1 titers to a F1/LcrV recombinant subunit vaccine correlated very well with protection against pneumonic plague in mice [40]. This suggests that YscF, which also induces a strong IgG1 response, could possibly afford some protection against pneumonic challenge as well as against systemic challenge.
Ability of α-YscF to effect Yop translocation
To examine one possible method that anti-YscF could be functioning to provide protection in immunized animals the ability to translocate Yops in the presence of anti-YscF antiserum was examined. Antibody to the surface-localized LcrV has been shown to block the ability of the TTSS in Y. pestis to translocate Yops into cultured macrophages [41,42] but anti-LcrV was unable to block translocation into HeLa cells [21].
However, anti-LcrV was able to block Yops translocation by Y. pseduotuberculosis into HeLa cells [26]. Since YscF is also surface-localized the ability of anti-HT-YscF to block Yop translocation into HeLa cells was tested. Day et al have described an elegant methodology to follow the translocation of Yop effector by fusing them to a Elk reporter [43]. Elk, a eukaryotic transcriptional activator, becomes phosphorylated only after entering the nucleus, providing a reporter for translocation into eukaryotic cells [43,44]. This methodology has the advantage of not requiring cell fractionation and protease protection assays to establish the intracellular localization of translocated proteins. To test the ability of anti-YscF to block translocation Y. pestis KIM8-3002 was transformed with plasmid pYopE129-Elk [43]. HeLa cells were infected at an MOI of 10 and infection was allowed to progress for 4 h. After the 4 h incubation infected HeLa cells were harvested and immunoblotted to analyze YopE, Elk and PO4-Elk production. Y. pestis KIM8-3002 (wt; [24]) and an isogenic translocation defective strain containing a yopD deletion (KIM8-3002.2, ΔyopD; [45]) both containing pYopE129-Elk were used as positive and negative translocation controls, respectively. Immunoblots of HeLa cells infected with the wt and the ΔyopD strains showed that only the wt strain elicited the production of PO4-Elk while the ΔyopD strain had no production of PO4-Elk. The wt and the ΔyopD strains were used to infect HeLa cells in the presence of a 1:10 or a 1:25 dilution of anti-YscF (titer for HT-YscF, 1:100,000) or in the presence of anti-PcrG (a Yersinia non-reactive antibody control, titer for PcrG, 1:20,000). The wt strain was capable of translocating YopE-Elk in presence of both anti-sera, demonstrating that anti-YscF was not capable of blocking Yops translocation and expectedly the ΔyopD strain was still defective for translocation. The experiment likely contained sufficient antibody against YscF to block translocation. In a previous report Pettersson et al used as low as a 1:100 dilution of an anti-LcrV anti-sera with a titer of 1:20,000 for LcrV and in that experiment translocation of Yops into HeLa cells was blocked [26]. These results suggest that antibody to YscF may not exert its protective effect by blocking Yops translocation. The results also suggest that while YscF is surface-exposed in the yersinae, antibody directed against YscF, unlike, anti-LcrV cannot block translocation. This may imply that YscF activity is shielded from neutralization by antibody, unlike LcrV activity that is blocked by antibody in some cases. However, since anti-LcrV was unable to block Yops translocation into by Y. pestis into HeLa cells [21] but could block translocation into cultured macrophages [41,42], the possibility remains that anti-YscF also display this type of differential blockage.
Conclusion
In this study we have determined that immunization of mice with recombinant YscF can protect mice from an i.v. challenge with Y. pestis. This is the first report to our knowledge that has utilized a conserved protein from the type III secretion complex of a gram-negative pathogen as a candidate for vaccine development. This result suggests that type III secretion complexes of other gram negative pathogens could also serve as vaccine targets. YscF and its homologs are obvious targets for use as vaccine candidates as they are surface exposed and are required for virulence in all the systems examined. The protective antibody response elicited by HT-YscF is evidence that YscF is not only expressed during the course of a plague infection, but is also in a location accessible to antibodies at some point in the infectious process. The mechanism of protection by the YscF antibody response is currently under investigation. Essentially three possibilities exist to explain the antibody's protective activity: increased opsonization of the bacteria, enhanced complement binding to the bacterial surface, or direct blocking of Yops translocation into the host cells. Cytotoxicity assays (data not shown) and the ability to translocate Elk-tagged YopE into HeLa cells (Figure 3) have shown that it is unlikely that anti-YscF directly blocks Yops translocation into HeLa cells. Suggesting that a blockage of Yops translocation may not be the mechanism whereby anti-YscF antibodies are protective. The degree of protection observed after immunization with YscF is not as great as that seen for the two known protective antigens, F1 and LcrV. This result suggests that YscF could be best used in combination with the other known antigens to formulate a tri-valent vaccine for Y. pestis. However, further work could lead to the development of YscF as a monovalent vaccine or combined with other antigens that could be efficacious not only against Y. pestis, but also against Y. enterocolitica and Y. pseudotuberculosis.
Methods
Cloning of yscF for overexpression and HT-YscF purification
Plasmid pJM119 was constructed by cloning a BamHI-and XhoI-cleaved PCR product into pET24b (Novagen, Madison, WI). The primers used to amplify yscF were HT-YscF Start (5' CGG GAT CCG ATG AGT AAC TTC TCT GGA TTT 3') and HT-YscF Stop (5' CCG CTC GAG TGG GAA CTT CTG TAG GAT GCC 3'). E. coli BL21(DE3) (Novagen) harboring pJM119 was used for HT-YscF overpexpression according to the manufacturer's suggestions. HT-YscF was purified using Talon resin (BD Clontech, Palo Alto, CA) according the manufacturer's directions.
Immunization of mice and infection with Y. pestis KIM5
For primary immunization 6-to 8-week-old female Swiss-Webster mice were immunized i.p. with 40 μg/mouse His-tagged YscF or phosphate-buffered saline [37] PBS (control mice) emulsified 1:1 with complete Freund's adjuvant (CFA). Booster immunizations were performed the same as the primary immunization with the substitution of Incomplete Freund's Adjuvant for CFA. Mice were challenged with Y. pestis via the retro-orbital sinus using blunt-feeding needles. Y. pestis used to infect mice was grown overnight in HIB broth, sub-cultured to an A620 of 0.2 absorbance units and grown with shaking to an A620 of 1.0 absorbance unit. Y. pestis cells for infection were harvested by centrifugation and resuspended in PBS. Plate counts were performed to verify CFUs for the infectious doses. Infected animals were monitored for death for up to 19 days, after which survivors were euthanized by CO2 inhalation, according to the guidelines of the Panel on Euthanasia of the American Veterinary Medical Association. All animal work for this project was reviewed and approved by UND's IACUC.
Bacterial strains, growth and fractionation
Bacterial strains used were KIM8-3002 [24], ΔyscF an isogenic in-frame deletion of yscF (G. Plano, University of Miami), and KIM8.3002.2 ΔyopD [45]. Y. pestis strains were grown in heart infusion broth or on tryptose blood agar base medium (Difco Laboratories, Detroit, MI) at 26°C for genetic manipulations. For physiological studies, growth of Y. pestis was conducted in a defined medium, TMH, as previously described [46]. Bacterial cells were fractionated as previously described [24]. Briefly, bacterial cells were chilled on ice after growth, harvested by centrifugation, and washed in cold phosphate-buffered saline (PBS; [37]). Bacterial whole cell fractions were prepared by resuspending the washed cells in cold PBS and precipitating total proteins with 10% (vol/vol) trichloroacetic acid (TCA) on ice overnight. Secreted proteins were recovered from the bacterial growth medium by centrifuging the spent medium a second time, transferring the supernatant to a clean tube, and precipitating with 10% (vol/vol) TCA on ice overnight. The TCA-precipitated proteins were pelleted by centrifugation (20,800 × g at 4°C) for 20 min and resuspended in 2X sodium dodecyl sulfate (SDS) sample buffer [37].
Protein electrophoresis, visualization and immunodetection
Proteins were separated by SDS-polyacrylamide gel electrophoresis (SDS-PAGE), using 12.5 % or 15 % (wt/vol) polyacrylamide gels according to the method of Laemmli [47]. Samples were boiled 3–5 min before loading on the gels. Samples were loaded such that lanes containing different culture fractions represented equivalent amounts of the original cultures. Proteins were visualized in gels using GelCode Blue stain (Pierce Chemical, Rockford, IL) according to directions. For immunoblots, proteins resolved by SDS-PAGE were transferred to Immobilon-P membranes (Millipore Corp., Bedford, MA) using carbonate transfer buffer (pH 9.9) [48]. Specific proteins were visualized using mouse or rabbit polyclonal antibodies specific for YopE (rabbit α-YopE; gift from G. Plano, University of Miami, Miami, FL), YscF (mouse α-YscF, this study), Elk (rabbit α-Elk, Cell Signaling Technology, Beverley, MA) and PO4-Elk (rabbit α-PO4-Elk, Cell Signaling Technology). Hexahistidine tagged YscF was visualized using a penta-histidine specific antibody (mouse α-Penta-His, Qiagen, Valencia, CA) Alkaline phosphatase-conjugated secondary antibody (goat anti-rabbit immunoglobulin G or goat anti-mouse immunoglobulin G; Pierce) was used to visualize proteins by development with nitroblue tetrazolium and 5-bromo-4-chloro-3-indolylphosphate (NBT-BCIP; Fisher Scientific, Fair Lawn, NJ).
Antibody characterization and isotyping
Flat-bottom, 96-well Nunc Maxisorp immunoplates (Fisher Scientific, Pittsburgh, PA) were coated with 100 μl of HT-YscF solution (4 μg/ml in Binding solution (0.1 M NaH2PO4, ph 9.0) at room temperature for 2 h (or overnight at 4°C). The wells were blocked with 200 μl/well blocking buffer (1% bovine serum albumin in TTBS (tris-buffered saline [37] + 0.5% Tween 20) and washed with TTBS. Test sera were serially diluted in blocking buffer and 100 μl of each dilution was added to duplicate wells that were incubated for 2 h at RT (or overnight at 4°C). The plates were washed and incubated for 2 h at RT with alkaline-phosphatase-conjugated anti-mouse secondary antibody. For quantitation of YscF-specific immunoglobulin isotypes and subclasses the plates were coated with alkaline-phosphatase-labeled anti-mouse isotype-specific antibody (1:400 in blocking buffer; Southern Biotech, Birmingham, AL). The wells were washed and 75 μl 3 mM para-nitro phenyl phosphate (p-NPP) was added to each well. The plates were incubated for 15 min at RT and the reaction was stopped by the addition of 50 μl of 1.5 M NaOH to each well. A405 was measured to monitor the cleavage of p-NPP. Antibody titers were determined as reciprocal numbers of the highest serum dilution that displayed values for optical density twofold higher than the value of the control serum.
Infection assays
Infection of eukaryotic cells was performed as described previously [24]. Prior to infection, eukaryotic cells were subcultured into 35-mm-diameter six-well tissue culture plates in RPMI-FBS and incubated at 37°C under 5% CO2 for 48 to 72 h to a density of 5 × 105 to 8 × 105 cells per well. Cells were washed twice with warm L15 lacking FBS immediately prior to infection. Bacteria were cultivated at 26°C in HIB and used at an OD620 of ~1.0 for tissue culture infections. Bacteria were added (at a multiplicity of infection (MOI) of 5 to 10) directly to prewarmed medium in the wells of the six-well plates. Plates were then centrifuged at 200 × g at RT for 5 min to achieve contact between the bacteria and the target cells and incubated at 37°C for 4 h.
Translocation of YopE
Detection of Elk-tagged YopE from pYopE129-Elk was performed as described [43]. Y. pestis strains carrying plasmid pYopE129-Elk were used to infect HeLa cells. After 4 h, the culture supernatants were removed, and the infected adherent cells were lysed by the addition of 100 μl of 2X SDS-PAGE lysis buffer containing Pefabloc (Roche Molecular Biochemicals, Indianapoli, IN) and phosphatase inhibitor (P-2850) cocktail (Sigma, St. Louis, MO). Samples were boiled for 5 min and loaded onto 12.5 % SDS-PAGE gels, immunoblotted to PVDF membranes and probed with Elk-1 (#9182) or phosphospecific Elk-1 (#9181) antibody preparations (Cell Signaling Technology). Anti-sera specific for HT-YscF (titer of 1:100,000, this study) or the Pseudomonas aeruginosa LcrG homolog, PcrG (titer of 1:20,000, Matson and Nilles, unpublished), were used at dilutions of 1:10 or 1:25 in the infection medium to assess the ability of α-YscF to effect YopE translocation.
Authors' contributions
J .S. M. cloned yscF for overexpression, purified HT-YscF, characterized the reactivity of antiserum to YscF, assisted with immunization and infection of mice, assisted with the LD50 calculation, and wrote the draft of the manuscript. K. A. D performed immunizations and infections of the mice and performed the antibody isotyping. D. S. B. helped to design the immunization protocol and edited the manuscript. M. L N. conceived of the study, supervised the work, calculated the LD50 and edited the manuscript.
Acknowledgements
The author's would like to thank Deanna O'Bryant and Jennifer Lamoureux for assistance with mouse experiments, Jennifer Miller for help with antibody ELISAs and Gregory Plano (University of Miami, Miami, FL) for YopE antiserum and the ΔyscF strain of Y. pestis. This work was supported by the UND Faculty Research Seed Money program. J. S. M was supported by a pre-doctoral fellowship from ND-EPSCoR. Work in M. L. N.'s laboratory is supported by NIAID grants R01-AI051520 and U01-AI54815.
Figures and Tables
Figure 1 Purified HT-YscF was run on SDS-PAGE gels (12.5% for Panels A and B, 15% Panel C) to analyze purity of the recovered protein. Panel A, separated proteins were stained with GelCode Blue stain (Pierce Chemical). Panel B, purified HT-YscF was immunoblotted to PVDF and probed with antibody specific for penta-histidine to identify which bands contained the His-tag. Panel C, purified HT-YscF was immunoblotted to PVDF and probed with post-immune serum from immunized mice.
Figure 2 Derivatives of Yersinia pestis KIM8-3002 (KIM5 pPCP1-minus, Smr) were grown in a chemically defined medium at 26°C for 2 h in the presence (lanes 1, 3, and 5) or absence of calcium (lanes 2, 4, and 6). Lanes 1 and 2 contain Y. pestis KIM8-3002. Lanes 3 and 4 contain Y. pestis KIM8-3002 ΔyscF expressing YscF from pBAD18-YscF. Lanes 5 and 6 contain Y. pestis KIM8-3002 ΔyscF gene. After the 2 h growth, the culture was shifted to 37°C to induce expression of the Ysc type III secretion system and the Low Calcium Response. Following 4 h of growth at 37°C cultures, were centrifuged to obtain whole cell fractions and cell-free culture supernatant fractions. Total proteins from each fraction were precipitated with 10% trichloro acetic acid. Dried proteins were resuspended in SDS-PAGE sample buffer and electrophoresed in a 15% SDS-PAGE gel. Proteins were then transferred to a PVDF membrane and immuno-blotted with pooled mouse serum used at a 1:20,000 dilution. Mouse serum was obtained by bleeding mice subsequent to immunization with HT-YscF, serum from several mice was pooled to control for animal specific variation. The position and sizes for the molecular weight markers are indicated and the position of YscF is shown.
Figure 3 Y. pestis strain KIM8-3002 (wt) (lane 1 and lanes 3–6) and KIM8-3002.2 (ΔyopD) (lane 2 and lanes 7–10) both containing plasmid pYopE129-Elk were used to infect HeLa cells at an MOI of 10. 4 h following infection the culture supernatant containing non-adherent bacteria were removed the remaining adherent HeLa cells were solubilized in 2X SDS-PAGE buffer. Following solubilization proteins were separated and immunoblotted to triplicate PVDF membranes. The triplicate blots were probed with α-YopE, α-Elk, or α-PO4-Elk, followed by incubation with an alkaline phosphatase conjugated secondary antibody and developed using NBT/BCIP. To some samples anti-sera specific for HT-YscF (lanes 3–4 and lanes 7–8) or the Pseudomonas protein, PcrG (lanes 5–6 and lanes 9–10), were added at dilutions of 1:10 (lanes 3, 5, 7, and 9) or 1:25 (lanes 4, 6, 8, and 10).
Table 1 IgG response to HT-YscF vaccination and LD50 determination.
Immunogen anti-YscF GMT* LD50 Fold increase in survival
PBS < 1:400 159 -
HT-YscF 1:40,000 21,344 134
*Geometric mean titer for total IgG, determined from 22 HT-YscF immunized mice.
Table 2 Antibody isotype titers from mice* immunized with HT-YscF.
Antibody isotype Titer
Total Ig 1:100,000
IgM < 1:800
IgG1 1:100,000
IgG2a 1:100,000
IgG2b > 1:100,000
IgG3 1:20,000
IgA < 1:800
*Sera from 22 mice were pooled for this analysis.
==== Refs
Inglesby TV Dennis DT Henderson DA Bartlett JG Ascher MS Eitzen E Fine AD Friedlander AM Hauer J Koerner JF Layton M McDade J Osterholm MT O'Toole T Parker G Perl TM Russell PK Schoch-Spana M Tonat K Plague as a biological weapon: medical and public health management. Working Group on Civilian Biodefense Jama 2000 283 2281 2290 10807389 10.1001/jama.283.17.2281
Titball RW Williamson ED Yersinia pestis (plague) vaccines Expert Opin Biol Ther 2004 4 965 973 15174978 10.1517/14712598.4.6.965
Titball RW Williamson ED Vaccination against bubonic and pneumonic plague Vaccine 2001 19 4175 4184 11457543 10.1016/S0264-410X(01)00163-3
Anderson GWJ Heath DG Bolt CR Welkos SL Friedlander AM Short- and long-term efficacy of single-dose subunit vaccines against Yersinia pestis in mice Am J Trop Med Hyg 1998 58 793 799 9660466
Heath DG Anderson GWJ Mauro JM Welkos SL Andrews GP Adamovicz J Friedlander AM Protection against experimental bubonic and pneumonic plague by a recombinant capsular F1-V antigen fusion protein vaccine Vaccine 1998 16 1131 1137 9682370 10.1016/S0264-410X(98)80110-2
Davis KJ Fritz DL Pitt ML Welkos SL Worsham PL Friedlander AM Pathology of experimental pneumonic plague produced by fraction 1-positive and fraction 1-negative Yersinia pestis in African green monkeys (Cercopithecus aethiops) Arch Pathol Lab Med 1996 120 156 163 8712895
Drozdov IG Anisimov AP Samoilova SV Yezhov IN Yeremin SA Karlyshev AV Krasilnikova VM Kravchenko VI Virulent non-capsulate Yersinia pestis variants constructed by insertion mutagenesis J Med Microbiol 1995 42 264 268 7707334
Du Y Galyov E Forsberg A Genetic analysis of virulence determinants unique to Yersinia pestis Contrib Microbiol Immunol 1995 13 321 324 8833863
Welkos SL Davis KM Pitt LM Worsham PL Freidlander AM Studies on the contribution of the F1 capsule-associated plasmid pFra to the virulence of Yersinia pestis Contrib Microbiol Immunol 1995 13 299 305 8833858
Nakajima R Brubaker RR Association between virulence of Yersinia pestis and suppression of gamma interferon and tumor necrosis factor alpha. Infection and Immunity 1993 61 23 31 8418045
Nakajima R Motin VL Brubaker RR Suppression of cytokines in mice by protein A-V antigen fusion peptide and restoration of synthesis by active immunization. Infection and Immunity 1995 63 3021 3029 7622225
Nedialkov YA Motin VL Brubaker RR Resistance to lipopolysaccharide mediated by the Yersinia pestis V antigen-polyhistidine fusion peptide: amplification of interleukin-10. Infection and Immunity 1997 65 1196 1203 9119451
Sing A Rost D Tvardovskaia N Roggenkamp A Wiedemann A Kirschning CJ Aepfelbacher M Heesemann J Yersinia V-antigen exploits toll-like receptor 2 and CD14 for interleukin 10-mediated immunosuppression J Exp Med 2002 196 1017 1024 12391013 10.1084/jem.20020908
Perry RD Straley SC Fetherston JD Rose DJ Gregor J Blattner FR DNA sequencing and analysis of the low-Ca2+-response plasmid pCD1 of Yersinia pestis KIM5. Infection and Immunity 1998 66 4611 4623 9746557
Perry RD Fetherson JD Yersinia pestis — etiologic agent of plague. Clinical Microbiology Reviews 1997 10 35 66 8993858
Allaoui A Schulte R Cornelis GR Mutational analysis of the Yersinia enterocolitica virC operon: characterization of yscE, F, G, I, J, K required for Yop secretion and yscH encoding YopR Mol Microbiol 1995 18 343 355 8709853 10.1111/j.1365-2958.1995.mmi_18020343.x
Haddix PL Straley SC Structure and regulation of the Yersinia pestis yscBCDEF operon J Bacteriol 1992 174 4820 4828 1624469
Hoiczyk E Blobel G Polymerization of a single protein of the pathogen Yersinia enterocolitica into needles punctures eukaryotic cells Proc Natl Acad Sci U S A 2001 98 4669 4674 11287645 10.1073/pnas.071065798
Marenne MN Journet L Mota LJ Cornelis GR Genetic analysis of the formation of the Ysc-Yop translocation pore in macrophages by Yersinia enterocolitica: role of LcrV, YscF and YopN Microb Pathog 2003 35 243 258 14580388 10.1016/S0882-4010(03)00154-2
Cornelis GR The Yersinia Ysc-Yop 'type III' weaponry Nat Rev Mol Cell Biol 2002 3 742 752 12360191 10.1038/nrm932
Fields KA Nilles ML Cowan C Straley SC Virulence role of V antigen of Yersinia pestis at the bacterial surface Infection and Immunity 1999 67 5395 5408 10496922
Holmström A Olsson J Cherepanov P Maier E Nordfelth R Pettersson J Benz R Wolf-Watz H Forsberg AA LcrV is a channel size-determining component of the Yop effector translocon of Yersinia Mol Microbiol 2001 39 620 632 11169103 10.1046/j.1365-2958.2001.02259.x
Håkansson S Schesser K Persson C Galyov EE Rosqvist R Homblé F Wolf-Watz H The YopB protein of Yersinia pseudotuberculosis is essential for the translocation of Yop effector proteins across the target cell plasma membrane and displays a contact-dependent membrane disrupting activity. EMBO Journal 1996 15 5812 5823 8918459
Nilles ML Fields KA Straley SC The V antigen of Yersinia pestis regulates Yop vectorial targeting as well as Yop secretion through effects on YopB and LcrG. Journal of Bacteriology 1998 180 3410 3420 9642196
Nordfelth R Wolf-Watz H YopB of Yersinia enterocolitica Is Essential for YopE Translocation Infect Immun 2001 69 3516 3518 11292787 10.1128/IAI.69.5.3516-3518.2001
Pettersson J Holmström A Hill J Leary S Frithz-Lindsten E von Euler-Matell A Carlsson E Titball R Forsberg Wolf-Watz H The V-antigen of Yersinia is surface-exposed before targent cell contact and involved in virulence protein translocation. Molecular Microbiology 1999 32 961 976 10361299 10.1046/j.1365-2958.1999.01408.x
Sory MP Cornelis GR Translocation of a hybrid YopE-adenylate cyclase from Yersinia enterocolitica into HeLa cells. Molecular Microbiology 1994 14 583 594 7885236
Tardy F Homblé F Neyt C Wattiez R Cornelis GR Ruysschaert JM Cabiaux V Yersinia enterocolitica type III secretion-translocation system: channel formation by secreted Yops. EMBO Journal 1999 18 6793 6799 10581252 10.1093/emboj/18.23.6793
Blocker A Jouihri N Larquet E Gounon P Ebel F Parsot C Sansonetti P Allaoui A Structure and composition of the Shigella flexneri "needle complex", a part of its type III secreton Mol Microbiol 2001 39 652 663 11169106 10.1046/j.1365-2958.2001.02200.x
Kubori T Sukhan A Aizawa SI Galan JE Molecular characterization and assembly of the needle complex of the Salmonella typhimurium type III protein secretion system Proc Natl Acad Sci U S A 2000 97 10225 10230 10944190 10.1073/pnas.170128997
Kubori T Matsushima Y Nakamura D Uralil J Lara-Tejero M Sukhan A Galan JE Aizawa SI Supramolecular structure of the Salmonella typhimurium type III protein secretion system. Science 1998 280 602 605 9554854 10.1126/science.280.5363.602
Sekiya K Ohishi M Ogino T Tamano K Sasakawa C Abe A Supermolecular structure of the enteropathogenic Escherichia coli type III secretion system and its direct interaction with the EspA-sheath-like structure Proc Natl Acad Sci U S A 2001 98 11638 11643 11562461 10.1073/pnas.191378598
Wilson RK Shaw RK Daniell S Knutton S Frankel G Role of EscF, a putative needle complex protein, in the type III protein translocation system of enteropathogenic Escherichia coli Cell Microbiol 2001 3 753 762 11696035 10.1046/j.1462-5822.2001.00159.x
Daniell SJ Takahashi N Wilson R Friedberg D Rosenshine I Booy FP Shaw RK Knutton S Frankel G Aizawa S The filamentous type III secretion translocon of enteropathogenic Escherichia coli Cell Microbiol 2001 3 865 871 11736997 10.1046/j.1462-5822.2001.00168.x
Ausubel FM Brent R Kingston RE Moore DD Seidman JG Smith JA Struhl K Current Protocols in Molecular Biology 1998 New York , John Wiley & Sons
Cordes FS Komoriya K Larquet E Yang S Egelman EH Blocker A Lea SM Helical structure of the needle of the type III secretion system of Shigella flexneri J Biol Chem 2003 278 17103 17107 12571230 10.1074/jbc.M300091200
Coligan JE Dunn BM Speicher DW Wingfield PT Current protocols in protein science. 1998 New York , John Wiley & Sons
Welkos S O'Brien A Determination of median lethal and infectious doses in animal model systems Methods Enzymol 1994 235 29 39 8057901
Andrews GP Strachan ST Benner GE Sample AK Anderson GWJ Adamovicz JJ Welkos SL Pullen JK Friedlander AM Protective efficacy of recombinant Yersinia outer proteins against bubonic plague caused by encapsulated and nonencapsulated Yersinia pestis Infect Immun 1999 67 1533 1537 10024607
Williamson ED Vesey PM Gillhespy KJ Eley SM Green M Titball RW An IgG1 titre to the F1 and V antigens correlates with protection against plague in the mouse model Clin Exp Immunol 1999 116 107 114 10209513 10.1046/j.1365-2249.1999.00859.x
Philipovskiy AV Cowan C Wulff-Strobel CR Burnett SH Kerschen EJ Cohen DA Kaplan AM Straley SC Antibody against V antigen prevents Yop-dependent growth of Yersinia pestis Infect Immun 2005 73 1532 1542 15731051 10.1128/IAI.73.3.1532-1542.2005
Weeks S Hill J Friedlander A Welkos S Anti-V antigen antibody protects macrophages from Yersinia pestis -induced cell death and promotes phagocytosis Microb Pathog 2002 32 227 237 12071679 10.1006/mpat.2002.0498
Day JB Ferracci F Plano GV Translocation of YopE and YopN into eukaryotic cells by Yersinia pestis yopN, tyeA, sycN, yscB and lcrG deletion mutants measured using a phosphorylatable peptide tag and phosphospecific antibodies Mol Microbiol 2003 47 807 823 12535078 10.1046/j.1365-2958.2003.03343.x
Day JB Lee CA Secretion of the orgC gene product by Salmonella enterica serovar Typhimurium Infect Immun 2003 71 6680 6685 14573697 10.1128/IAI.71.11.6680-6685.2003
Williams AW Straley SC YopD of Yersinia pestis plays a role in the negative regulation of the low-calcium response in addition to its role in the translocation of Yops. Journal of Bacteriology 1998 180 350 358 9440524
Straley SC Bowmer WS Virulence genes regulated at the transcriptional level by Ca2+ in Yersinia pestis include structural genes for outer membrane proteins. Infection and Immunity 1986 51 445 454 3002984
Laemmli UK Cleavage of structural proteins during the assembly of the head of bacteriophage T4. Nature 1970 227 680 685 5432063
Skrzypek E Straley SC LcrG, a secreted protein involved in negative regulation of the low-calcium response in Yersinia pestis. Journal of Bacteriology 1993 175 3520 3528 8501055
| 15978133 | PMC1168899 | CC BY | 2021-01-04 16:03:41 | no | BMC Microbiol. 2005 Jun 24; 5:38 | utf-8 | BMC Microbiol | 2,005 | 10.1186/1471-2180-5-38 | oa_comm |
==== Front
BMC Med Inform Decis MakBMC Medical Informatics and Decision Making1472-6947BioMed Central London 1472-6947-5-161596323810.1186/1472-6947-5-16Research ArticleEvidence-based patient choice: a prostate cancer decision aid in plain language Holmes-Rovner Margaret [email protected] Sue [email protected] Angela [email protected] John T [email protected] Rodney L [email protected] Janet [email protected] Karen [email protected] David R [email protected] Department of Medicine, C214 East Fee, Michigan State University, East Lansing, MI, USA2 The Clear Language Group, Biddeford, ME, USA3 Department of Urology, University of Michigan, Ann Arbor, MI, USA4 VA HSR&D Centre for Practice Management and Outcomes Research and Department of Internal Medicine, Veterans Affairs Hospital, Ann Arbor, MI, USA2005 20 6 2005 5 16 16 24 9 2004 20 6 2005 Copyright © 2005 Holmes-Rovner et al; licensee BioMed Central Ltd.2005Holmes-Rovner et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Decision aids (DA) to assist patients in evaluating treatment options and sharing in decision making have proliferated in recent years. Most require high literacy and do not use plain language principles. We describe one of the first attempts to design a decision aid using principles from reading research and document design. The plain language DA prototype addressed treatment decisions for localized prostate cancer. Evaluation assessed impact on knowledge, decisions, and discussions with doctors in men newly diagnosed with prostate cancer.
Methods
Document development steps included preparing an evidence-based DA in standard medical parlance, iteratively translating it to emphasize shared decision making and plain language in three formats (booklet, Internet, and audio-tape). Scientific review of medical content was integrated with expert health literacy review of document structure and design. Formative evaluation methods included focus groups (n = 4) and survey of a new sample of men newly diagnosed with prostate cancer (n = 60), compared with historical controls (n = 184).
Results
A transparent description of the development process and design elements is reported. Formative evaluation among newly diagnosed prostate cancer patients found the DA to be clear and useful in reaching a decision. Newly diagnosed patients reported more discussions with doctors about treatment options, and showed increases in knowledge of side effects of radiation therapy.
Conclusion
The plain language DA presenting medical evidence in text and numerical formats appears acceptable and useful in decision-making about localized prostate cancer treatment. Further testing should evaluate the impact of all three media on decisions made and quality of life in the survivorship period, especially among very low literacy men.
==== Body
Background
Patients are increasingly urged to become involved in treatment choices, including watchful waiting (surveillance but no active treatment), by working through medical evidence to decide on a course of action with their physicians. Guidelines and evidence summaries are commonly available to physicians and frequently include a "summary for patients", as do some major clinical journals. Decision aids have proliferated in recent years yet most require high levels of literacy to access them and have not been designed according to the principles of plain language. This paper describes one of the first attempts to make a decision aid accessible to consumers with lower levels of literacy and education using principles from reading research and document design. To develop a prototype plain language decision aid, and to describe the design process, we designed a decision aid for treatment decision making in localized prostate cancer. Three standard therapies, surgery, radiation therapy, and watchful waiting, are available to patients and paid for by most insurers in the US. The 10-year mortality rate for each of the standard treatments is equivalent, but the side effects and the processes are quite different. This conundrum is made even more difficult because specialty physicians tend to recommend treatments performed by their own specialty [1,2]. Even inter-disciplinary case conferences can expose patients to evidence and professional opinions that appear to conflict.
The aim of the research reported here was to develop a plain language decision aid for localized prostate cancer initial management following a positive biopsy. Three decision aids (booklet, Internet, and audio-tape formats) were designed to contain equivalent information. Formative evaluation was designed to test acceptability to men with both highly functional and limited literacy skills. We wanted to make sure that the DAs were not perceived as "dumbed down" either in tone or content. A further aim was to identify missing information, and information that might not adequately represent the cancer experience, The aim was to include the perspective of community dwelling men in the appropriate age group and men who had had treatment for their prostate cancer.
Evidence-based patient choice
"Evidence-based patient choice" is a term coined by Hope in 1996 and elaborated in a book by the same title [3] to articulate the addition of the patient perspective to the evidence based paradigm laid out by Sackett [4]. Adding "patient choice" to evidence-based medicine is an effort to locate the need for evidence squarely in a patient-centred approach to patient-provider encounters. The theoretical roots are in economics, ethics, psychology and medicine. There are also political influences, including the consumer choice movement and struggles over resource allocation and health care organization. The synthesis of ethical approaches to shared decision making, and rational choice models provoke both theoretical and political concerns, and is far from a perfect resolution. The practical task of supporting patients' access to information they can use led us to develop this new prototype. We also desired to have the information available in real time to reach the most satisfying resolution of treatment dilemmas. By making our assumptions transparent, and testing the results with patients and scholars we hoped to improve both theory and practice.
Approaches to evidence tools for patients
Decision aids exist in modest numbers, specific to particular clinical conditions. A recent meta-analysis identified 131 different decision aids across a variety of clinical problems. Sixty-five of these fit the Cochrane criteria and were evaluated in a randomized trial [5]. Decision aids have expanded the scope of traditional patient education materials and draw on several perspectives. These may be classified conceptually as 1) traditional medical, 2) technology assessment (TA), and 3) patient-centred. Traditional patient education materials mirror the medical model didactic elements. They include descriptions of: a) the disease, b) its epidemiology, c) the morbidity and mortality outcomes of the disease in the population, and d) screening and treatment recommendations for either public information campaigns or clinical encounters. This model has been criticized for its emphasis on diseases, rather than on patients and their concerns, and for being paternalistic [6]. Decision aids have addressed the limitations of the traditional medical approach by integrating evidence-based medicine with patient choice and by encouraging shared decision making. It has largely accomplished this with a technology assessment (TA) approach. TA focuses on the quality of the medical evidence, levels of rigor of evidence and providing symmetry in describing risks and benefits of all patient options. The most widely available examples of TA-based decision aids use the Ottawa Decision Support Framework and BMJ Best Treatments approach. The Ottawa Framework asks the decision-maker to choose among treatment or screening choices demonstrated to be effective [7]. It emphasizes clarifying values for outcomes and emphasizes weighing the pros and cons of alternatives in the choice process to arrive at a tentative choice that the patient discusses with the physician. Consistent with evidenced-based health care, it grades the medical evidence for each alternative according to its quality. The Best Treatments approach likewise grades the evidence, teaches patients about uncertainty in data, but does not consistently provide numerical data for side effects [8]. The TA approach is a major step forward in providing patients with accurate evidence for making comparisons among alternatives, but it may suffer from speaking to the professional health care community better than it speaks to patients. To develop a plain language prototype, we accepted most of the premises of the TA approach, but redesigned the presentation of results, using plain language and document design strategies.
Translation of evidence into plain language
The rationale for "re-constructing" decision aids in plain language is that it works for patients with a wide range of literacy abilities. Plain language includes three major elements: 1) The use of everyday language and other clear writing strategies, 2) well-structured, logically sequenced, and focused information, 3) effective design and layout. It uses medical evidence as a base and attempts to lead readers through the relevant elements to provide an opportunity for synthesis and drawing conclusions about which therapy best suits the values, fears and expectations of the patient. A plain language approach incorporates social marketing principles and is often used by pharmaceutical companies, patient advocacy groups, and others to deliver compelling messages. The materials these groups produce, however, sometimes minimize or eliminate numbers in the interest of being non-threatening and engaging and accommodating limited quantitative literacy skills[9,10].
Plain language approaches have also been used to communicate public health messages to patients. They frequently attempt to persuade them to undertake an action (e.g., engaging in cancer screening) rather than engage in shared decision making. Highlighted by the recent Institute of Medicine report [11], many groups have published plain language document design guidelines [12-17].
As stated by Hibbard and Peters [18], the challenge is "how to present\ldotsinformation so that it is actually used in decision making." They note that three information presentation strategies assist consumers, all of which are reflected in a plain language approach: lowering the cognitive effort required to use information; linking information to real-life situations to increase the emotional connection; and presenting numbers in frequencies (e.g. 10 in 100). We addressed each of these in developing the prostate cancer DA. To address the immediate world of patients in the midst of being told of a disease and making a decision, it is important to describe the relevant risks and benefits of treatments without losing the precision and realistic risk communication capacity of numbers. Unpacking technical jargon actually adds substantial detail about what will happen to the patient in non-technical, everyday terms. It also explains laboratory tests and other medical information that doctors will use in making recommendations. The purpose is to provide patients with tools and encouragement to engage with the doctor in discussing technical aspects of the information doctors use to make a decision. Along with risk and benefit data, a decision aid should also explain the treatment process to the patient, in order that she or he can anticipate the personal experience of undergoing treatment. This approach does not abandon or delete technical language. Rather it defines it and provides examples, and phonetic pronunciations of medical technical terms in order to improve communication between patients and health professionals.
In the prototype, we introduce the idea that there is variability among patients in their values for potential outcomes. Unlike some decision aids that provide a rational recommendation based on formal utility assessment [19], this approach does not make a recommendation. The resolution of the values dilemma is left to patients, their families and friends, and health care providers.
Needs assessment
Prior to developing a new decision aid, we performed a two-part needs assessment. In the first part, we searched the literature for surveys providing information about knowledge levels of newly diagnosed patients following biopsy and discussion with their doctors but before treatment. In the second part, we evaluated existing patient education materials for localized prostate cancer. Since we found no surveys of men actually facing the localized prostate cancer treatment decision, we interviewed 184 men newly diagnosed with localized prostate cancer from both community and tertiary care urology practices in Michigan [20]. This sample served as the historical controls for this paper. The survey included demographics, patient knowledge about their prostate cancer, treatment options, side effects and satisfaction with care. Bivariate and multivariable analyses were performed to adjust for potential confounding and to determine if sociodemographic factors affected understanding of key issues. Average age of the men was 64 years and 19% were African American. Seventy-one percent completed some college and 51% of patients were currently employed. White men reported higher rates of knowing their PSA, stage and grade (92%, 93% and 99% respectively) than African American men (69%, 88% and 85%). Ninety-three percent of all respondents stated that they had discussed treatment options with a physician. Only 62% knew that radical prostatectomy, external beam radiation therapy, brachytherapy and watchful waiting were standard options for localized prostate cancer. Significant associations between sociodemographic factors and a patient's understanding of prostate cancer treatment issues were identified. Despite objective gaps in knowledge, men showed high satisfaction with information received from their physicians.
Prostate cancer has been the subject of several decision aids [21,22] Considerable research has identified patient and health professional concerns about treatment. In part 2 of the needs assessment, we used our previously developed generic evidence template to provide evaluation guidelines, but made it specific to prostate cancer [23]. We used the template to comprehensively survey patient education materials publicly available from US government agencies, charities, drug companies and others for inclusion or absence of the evidence elements. The full report found key evidence to be missing from most patient education materials (PEMs) [24]. We found that standard treatment options were almost never explicitly compared to one other. PEMs frequently did not describe the chances of dying from prostate cancer or of experiencing other side effects of each treatment. We found most did not reflect consideration of the user in the way materials were written, structured or designed. Finally, most did not encourage patients to formulate a treatment preference to discuss with their doctors.
Based on the needs assessment, we developed the decision aid, described in this report, in three formats (booklet, audio tape, and Internet) with particular attention to plain language and to potential concerns of African American men. Three major challenges lay at the heart of the plain language translation: 1) introducing the social and emotional context, 2) translating the outcome and side effect rates into plain language, and 3) encouraging shared decision making. The three formats used the same words and content organization to facilitate evaluation of the impact of print, audio and Internet media on patient knowledge and patients' assessment of the usefulness of the different media in preparing to talk with the doctor.
Methods
The decision aid prototype: design method and assumptions
Based upon our earlier analysis of good and bad aspects of the prostate cancer PEMs and an extensive search of the clinical literature, a draft of the decision aid was prepared in what might be called the standard medical parlance. This material was iteratively modified to emphasize shared decision making and incorporate the principles of plain language. The research team who designed the project was strongly guided at this point by two health literacy/plain language experts. Similarly, document design and web design were strongly guided by graphics experts. The prototype was presented to the Michigan Prostate Cancer Action Committee (PCAC), a sub-committee of the Michigan Cancer Consortium (MCC), a consortium of hospitals, universities and cancer centrss in the State of Michigan. Final edits were made based on the formative evaluation by patients, clinicians, and the development collaborators and the final document produced.
The prototype booklet and Internet version that resulted from the evaluation process can be viewed at the Michigan Cancer Consortium (MCC) website [25]. Table 1 lists the design decisions made for the prostate cancer prototype.
Table 1 Information and Information Architecture Issues and Solutions
Concern Solution
Complex information • Organize and structure document for ease of understanding and use, including use of summary tables
• Create affective appeal using individual vignettes
• Describe all elements of treatment process patients experience
Engage the reader in the social context • Use pictures captioned with comments from men of varying ethnicities
• Suggest connection with trusted others and other patients
• Recognize and address feelings of fear
No mandatory autonomy • Suggest that decisions may be made by the patient or delegated to the doctor, or trusted individual.
• Suggest shared decision making is compatible with keeping or delegating
Anticipate cultural issues • African Americans are likely to be sensitive to potential to withhold treatment in the name of watchful waiting.
• African Americans frequently are diagnosed with more severe disease relative to whites.
• Sources of authoritative advice vary among ethnic groups. These can be acknowledged subtly in text
Translate medical words, but do not eliminate technical information • Define words and include a glossary
Creating/choosing appropriate pictures • Simplify anatomical drawings to include only necessary visual information
• Include realistic picture of torso, with head included to provide conceptual context
• Include photographs of men who look serious, but not devastated
Graphic Design and Layout: Use evidence-based document design principles • Spacing to emphasize different points and topic changes
• Wide margins to make text less dense
• Adequate page size to keep information on a topic on one page
• Graphic design that draws the reader through the booklet
• Text design that keeps related information in close proximity
Plain language • Use conversational words and sentence structure, even if not standard grammar
• Keep the writing tight. Eliminate unnecessary words.
• Keep the tone friendly and personal, speaking directly to the reader.
• Explain technical language even though it adds words. Assumptions behind technical words must be included
• Make scientific references available on the website, but do not include in the text
Connecting to patients' social and emotional world
To connect with the concerns of men and their families and friends about prostate cancer treatment, the decision aids embed a number of emotional "hooks", showing photographs of middle-aged men of varying races. Quotes from different men state varying preferences for their preferred degree of autonomy: making the decision themselves, delegating it to family or the doctor, sharing it with clergy, friends, or health professionals. These statements are designed to legitimize a range of appropriate alternatives for the problem of "who decides". They are meant to avoid a "mandatory autonomy" position, allowing the patient to hand off the decision to the physician if he does not want to decide himself [26]. The central message promotes active patient participation, followed by making, sharing, or delegating the decision. Further, an attempt is made to imbed in the text items that speak to culture-specific issues. For example, the statement is made that watchful waiting does not mean that the doctor "just does not want to treat me." This statement anticipates the common belief, particularly among African American patients, that doctors may withhold treatment for cost or other reasons.
The emotional context of the booklet is also invoked by explicitly noting in the text that cancer is scary, and that treatment side effects may have heavy emotional impact. The emotional "threat" level of how the disease is discussed is planned to be at a moderate level. The decision aid acknowledges inevitable fear, supplies concrete understanding of disease and treatment, and encourages a sense that patients are competent to make the decision.
Presenting quantitative evidence
The goal of an evidence-based decision aid is to make the information easy to read, remember, and use. The prostate cancer prototypes use specific textual, organizational, and design elements enhanced by appropriate message framing. They do not assume the reader knows either the technical meaning of words or the background context in which they are used. This filling in of the "why" and "what for" of laboratory tests, treatment regimens, and other medical information is essential for the millions of adults with limited literacy skills and limited experience with navigating the medical system. It is also preferred by most people when learning new information, especially in a highly charged emotional context. Specific guidelines for the prostate cancer decision aids were: 1) aim for low to average reading level (grade 7 level), 2) present quantitative risk information as simply as possible, both positively and negatively framed [27], and 3) use a minimum of technical medical terms, and provide a glossary, called "explanation of medical terms". The objective is to invite all patients to grapple with the decisions they face with as little intervening struggle with technical medical language as possible. The result, ideally, is sophisticated ideas in plain language.
To invite the patient into the content requires attention to "information architecture" and the layout of information on pages to guide the reader through the text. Thus, the density of information on a page, the choice of a booklet or an electronic tool, and the length and "feel" of the information tool become important. The organizing principle was to describe each treatment option in a complete synopsis on its own on two facing pages of the booklet, or on sequential web pages under one button. The audiotape is organized in "chapters", like a "book on tape". For each treatment, the text describes, "What happens", "How this treatment can help", and "How this treatment may cause problems." Each of the individual synopses tells the whole story about a specific treatment. The treatment options are followed by two comparison tables, one narrative and one quantitative. The summary tables explicitly compare results across treatments. Very brief directions guide the reader in how to use the tables. Additional information, not related explicitly to the choice (stage and grade of cancer, and PSA tests), is described in the same amount of detail as a single treatment option (two facing booklet pages). The objective is to demystify what will happen, show how doctors decide what is best, describe the degree of uncertainty about test outcomes, and indicate the medical information on which decisions are based.
Side effects and mortality are presented as mean values, not including the ranges. This is a pragmatic solution to the simplification task, and should be tested further. Explaining that diagnostic test results are imperfect information, and that treatments have only a probability of success is a new idea to most patients. The design task was to present uncertainty, but keep it simple. Another quantitative principle that is critical to informed consent is presentation of absolute, rather than relative risks in terms of specifying a number out of 100 rather than a percentage. Absolute rates have been demonstrated to provide patients with improved estimates of their own chances of experiencing a particular outcome [28].
Shared decision making
A third challenge was to encourage shared decision making without specifying the form of the clinician-patient conversation or the values discussion. The message on the cover of the DA first introduces the concept of choice, that "there is no right answer" to this treatment problem. The general statement, "Your treatment decision is a shared one between you and your doctor" is later stated directly. A "things to think about" section at the end of the booklet asks a patient to identify his most important goal for treatment, such as curing cancer, ameliorating symptoms, having the best possible sexual performance, or good bowel and bladder control. Patients are also asked to write down the best and worst thing for them about each treatment option. These sections are designed to facilitate an open discussion with the physician without directing it.
The booklet was provided to each person with a request to provide written or verbal feedback. The booklet form of the decision aid was finished first, and provided the text and order of presentation that were duplicated in the audiotape and Internet versions. Qualitative methods were used to evaluate and revise the booklet before survey testing was performed with a new sample of men newly diagnosed with prostate cancer.
Results
Formative evaluation
Evaluation was performed in two phases. Phase 1 was a focus group evaluation of the draft language. Phase 2 was a survey follow-up of 60 men newly diagnosed with prostate cancer, using the DA in real-time decision making. The Michigan State University and University of Michigan human subjects IRBs approved all study materials and procedures. Verbal and written consent for participation was obtained at the beginning of interviews and patient encounters.
Phase 1: focus groups
Design and procedure
Focus group methods were used to identify unacceptable or confusing language and to identify missing information or information needed to fully represent the important issues for decision making. This information was obtained from the perspective of men who had not experienced prostate cancer, and also those who had. The analytic techniques used were similar to ethnographic techniques, although cross-sectional rather than longitudinal qualitative reports were used [29].
Homogeneous groups by race were formed to encourage participants to feel comfortable and to express concerns about bias. A moderator's guide addressed the acceptability of content and language, perceived understandability, and usability of the format. We inquired specifically about text passages that described risk numbers, results of a randomized clinical trial, the meaning of laboratory tests and their implications for mortality and treatment. Open-ended questions asked men their perception of the DA main message.
Four focus groups were conducted. Each session lasted between 1.5 and 2 hours and was facilitated by a physician. Booklets were mailed to participants two weeks prior to the focus group and participants were encouraged to review the booklet in detail to provide feedback during the focus group session. Confidentiality ground rules were established and agreed upon by participants. After the session, a twenty-five dollar honorarium was provided to compensate participants for time and travel. Immediately following participants' departure, a debriefing session was held between the facilitator and assistant to develop and amend observation notes and record suggestions for subsequent focus groups. All focus groups were tape-recorded.
Sample
Post-treatment men who had undergone surgery or radiation therapy for prostate cancer were recruited from a tertiary care prostate cancer clinic. Community men at risk for prostate cancer due to age were recruited from a study of decision making in benign prostatic hyperplasia. Actual patients at the point of decision making were not included in the focus group, due to their potential vulnerability to inaccurate, misleading, or offensive content. Twenty-five men participated in four focus groups. Mean age was 64.5 years (range 49–80). Twenty-four had health insurance; approximately half were not college educated.
Focus group results
The men found the prototype booklet "encouraging" and "comforting." The general consensus was that prostate cancer appeared to be something "that can be dealt with." The DA was described as "professional," the "right size" (8 1/2 × 11), and containing the right balance between the size of white space and of print. The summary table of treatments and risks and the comparison table were viewed as especially helpful and men stated that these clarified individual treatment descriptions. The level of detail was described as being "just right", with the exception that the decision aid did not include detailed description of non-standard treatments (cryosurgery and nerve-sparing surgery). These were added, as was a recommended diagram showing cancer spreading to the surrounding lymph nodes and nerves.
Positive and negative framing of statistical information
The booklet stated each side effect as both a number out of 100 chance of occurrence and that number subtracted from 100 as the chance of avoiding occurrence. However, the obvious redundancy was interpreted by some readers as talking down to them and insulting their intelligence. To make it less repetitive, the wording was changed to vary the outcome named and acknowledge that this was another way of stating the outcome. Table 2 shows major changes made based on feedback.
Table 2 Booklet Improvements based on formative evaluation
Information item identified in focus groups and approved by investigators Draft 1 Draft 2
Emotional impact None Hearing that you have prostate cancer may shock or frighten you, your family, and your friends. These feelings are natural. They may change over time, as you learn about your diagnosis, make treatment decisions, deal with symptoms, and go on with your life. Men are often afraid to share their feelings or get help from a counselor if needed. If strong feelings are hurting you or your family, ask your doctor to suggest help.
Positive and negative framing "If 45 men out of 100 experience impotence, this means that 55 do not." "...about 45 men out of 100 have permanent impotence. This means that 55 men out of 100 will have their original level of sexual activity."
African American differences None "African American men are often diagnosed at a younger age than white men and with more advanced prostate cancer. However, treatment may be equally successful for both groups if given the same care."
Specific drug name, "like Viagra" "medicine that helps with erections"
Treatment detail No mention of cryosurgery or nerve-sparing surgery Included under "newer treatments".
Drawing Three inset pictures Only two
Watchful Waiting description Few disadvantages listed Added disadvantages regarding potential progression of disease
Perspectives of African American men vs. White men
While all found the booklet professional and a good source of information, there were differences in what issues the groups discussed. For African American men, the multicultural photos were important in that they illustrated that prostate cancer affects men of any race. The participants did suggest inclusion of more specific mortality information by race. (See Table 2).
African American men discussed several aspects of fear, including fear about acknowledging health problems, and the absence of fear in the faces of the men in the photos. They characterized the overall message of the booklet as not to be afraid. They also cited fear and distrust as major obstacles preventing their acknowledging a health problem. African American men did not feel the text talked down to them and felt the words were manageable – "there are no big words in this booklet." One commented that, "I didn't feel like you were treating me like a 3rd grader." Lastly, the African American men read the overall message of the booklet as one of "don't be afraid," whereas the White men read the message as one of "informed decision making". Several men across groups commented that they rarely read health related materials, but that they read every word before coming to the focus group. "I normally only read sports. But I read this straight through".
Post-treatment men vs. community men
Men who had been treated for their prostate cancer appeared to find discussing the DA more difficult than did the men of the same age who did not have prostate cancer. While they appreciated the information, some indicated that they were not convinced that they really had a choice when deciding on actual therapy, either because of the doctor's presentation or their own concerns about cancer. They also indicated that the consequences of the treatment decision were more emotionally difficult than they anticipated. These men appeared to struggle with the emotional and psychological consequences of their own treatment decisions. Post-treatment White men suggested that the emotional impact of treatment be more strongly addressed as illustrated by the following comments:
"But this doesn't deal with... your first issue is to stay alive and the second issue is the quality of your life afterwards and that may be whether you are incontinent or maybe whether you don't have erections.....But to the fact that, uh, you need to talk to your surgeon about the psychological consequences of the expected outcome of this surgery. Maybe you only think about living first, but looking at it in retrospect, I was like.... Whoa, why didn't you tell me that ahead of time? Not that I would have made a different decision. I just want to be well informed. I didn't get that".
Some post-treatment men felt that the booklet was biased toward watchful waiting as a treatment choice. This was addressed by adding specific negative aspects to watchful waiting in the summary.
For example:
"But this book, uh, had in mind a definite cast toward watchful waiting as opposed to more active interventions and I agree that, uh, that in fact for many of us that was not a very viable option I mean intellectually or emotionally or whatever" and "But as I said before, I thought there was a subliminal message there that said that watchful waiting was probably a preferred choice."
Phase 2: survey
To test the usefulness of the revised decision aid to men at the point of decision, a new convenience sample of 60 men newly diagnosed with prostate cancer on the basis of biopsy was recruited to test the usefulness and influence of the DA in real-time decision making. Participants were recruited and provided a decision aid after receiving their prostate cancer diagnosis at a post-biopsy visit to their urologists. The urologist introduced a research assistant to patients at the end of the visit in which he was told of his cancer diagnosis. The patient was asked if they would like to be in a research study evaluating the effectiveness of the three different decision tool formats. Patients were recruited sequentially until 20 had been accrued to use the booklet. After the Internet and audiotapes were developed, 40 additional patients were recruited to evaluate these formats. Due to the necessity for computer access for use of the Internet version, these men were offered a choice of the audiotape or Internet decision aid until 20 men were recruited for Internet and 20 for audio-tape use. A telephone survey lasting approximately 20 minutes was conducted by trained survey researchers from the Institute for Public Policy and Social Research of Michigan State University.
The survey included knowledge items taken from the previous needs assessment. DA evaluation questions assessing balance, clarity, and length of the DA were modeled after those of Barry et. al. [30]. Demographic (age, race, income, education and geography) and disease (prostate specific antigen (PSA), cancer stage, and grade) characteristics were ascertained during the interview. Knowledge questions included knowing one's own test results (PSA, stage, grade), treatment options and side effects.
Sample
The sample of 60 men recently diagnosed with prostate cancer had an average age of 62 years (SD = 7.9). Ninety percent reported their race as White (8% as African American), 5% had not graduated from high school, 20% had a high school dipoloma or GED, 32% had some college training, 19% had received a bachelors degree and 24% had received training post-baccalaureate. Sixty percent were employed, 33% were retired, and 5% were unable to work. Twenty-two percent had an income of less than $25,000 and 77% reported Internet access.
Survey results
The responses of men using the three different media (internet, audio, booklet) were virtually identical across all survey items with the exception that those receiving the audio version were less likely to share it with family and friends (data not shown). Table 3 shows that the sample of men utilizing the DA and historical controls had similar knowledge of their own pathology results, with the exception that the DA sample were less likely to be informed of the stage of their cancer (Fisher's Exact Test P-value = 0.003). Knowledge of treatment options was not significantly different between the two groups. However, 12% more men believed watchful waiting to be a standard treatment in the DA group (87% vs 75% in controls, p = 0.073). In addition, 6% fewer men believed external beam radiation to be a standard treatment in the DA group (88% vs 94% in controls, p = 0.159).
Table 3 Knowledge: DA sample vs. historical controls
DA sample (N = 60) Historical controls (No./Total) Fisher's Exact Test P-value
Knowledge of personal pathology results
Knew PSA 56 (93%) 160/181 (88%) 0.34
Informed of stage of cancer 53 (88%) 178/181 (98%) 0.00
Knew grade of cancer 57 (95%) 178/184 (97%) 0.69
Knowledge of treatment options
Knew all of age, grade, stage, health, and PSA are at least somewhat important for treatment decision. 52 (87%) 142/184 (77%) 0.14
Believed watchful waiting to be a standard treatment 52 (87%) 138/184 (75%) 0.07
Believed external radiation to be a standard treatment 53 (88%) 173/184 (94%) 0.16
Believed brachytherapy to be a standard treatment 47 (78%) 143/184 (78%) >0.99
Believed surgery to be a standard treatment 57 (95%) 177/184 (96%) 0.71
Discussed watchful waiting with physician 28 (47%) 72/184 (39%) 0.36
Discussed external radiation with physician 53 (88%) 166/184 (90%) 0.63
Discussed brachytherapy with physician 38 (63%) 121/184 (66%) 0.76
Discussed surgery with physician 59 (98%) 163/184 (89%) 0.02
Knowledge of side effects
Knew surgery associated with incontinence 59 (98%) 172/184 (93%) 0.20
Knew surgery associated with impotence 58 (97%) 172/184 (93%) 0.53
Knew surgery associated with painful bowel movements 33 (55%) 82/184 (45%) 0.18
Knew radiation associated with incontinence 48 (80%) 113/184 (61%) 0.01
Knew radiation associated with impotence 56 (93%) 145/183 (79%) 0.01
Knew radiation associated with painful bowel movements 46 (77%) 118/184 (64%) 0.08
Discussion of treatment options with the physician showed a significant increase in surgery discussions (98% in DA group, 89% in controls, p = 0.019). Discussions of watchful waiting increased by 6% to 47% in the DA group, and discussions of radiation decreased by 2% (external beam) and 3% (brachytherapy). While not significant, and very small, these changes are consistent with the increase in knowledge of options and side effects.
Table 4 shows that the DA was universally found to be clear and helpful. A substantial percentage of men reported that the DA influenced their decision making.
Table 4 Clarity and usefulness of DA (n = 60)
Amount of information Much less than needed 5% A little less than needed 14% About right 77% A little more than needed 4% DK or refused 7%
Length Much too short 0% A little too short 11% About right 84% A little too long 5% DK or refused 5%
Clarity of words All clear 44% Mostly clear 51% Some clear/ not 5% Most unclear 0% All unclear 0% DK or refused 2%
Difficulty of numbers Very easy 64% Somewhat Easy 24% Somewhat difficult 12% Very difficult 0% DK or refused 3%
Treatment description balance Complete balance 80% Slanted to surgery 9% Slanted to radiation 4% Slanted to WW 7% DK or refused 8%
Recommend DA to a friend? Definitely would 78% Probably would 20% Unsure 0% Probably would not 0% Definitely Would not 2% DK or refused 2%
DA improved understanding Definitely did 49% Probably did 42% Unsure 2% Probably did not 2% Definitely did not 5% DK or refused 2%
Numbers influenced my decision Definitely did 12% Probably did 41% Unsure 2% Probably did not 22% Definitely did not 22% DK or refused 3%
DA helped decision making A lot 14% Quite a bit 30% Moderate 32% A little 16% Not at all 9% DK or refused 5%
DK = Don't know
Eight-six percent of men reported that they shared the DA with a spouse or partner; 22% shared it with other family members; 14% shared the DA with friends. Seventy-two percent reported that they were more likely to take an active role in their treatment decision.
Discussion
This attempt to marry evidence-based shared decision making and plain language appears to have been informative and helpful in decision making among a diverse set of men. The design process we used was found to translate medical language while retaining quantitative information. The resulting DA was almost universally found to be helpful in decision making. Men in the DA group were more likely to discuss surgery with their physicians and to know that radiation therapy has side effects. Men reported sharing the DA with family and reported that the DA increased the likelihood of taking an active role in decision-making with the physician. The comparisons reported are limited by the use of historical controls and by the unavailability of data about actual decisions made. However, the two cohorts were surveyed using exactly the same questions. Both cohorts were very well informed about their own test results and about side effects of surgery. Side effects of radiation where less well known and somewhat responsive to the decision aid.
In qualitative analyses, patients identified several principles of the plain language approach as particularly important to them. Those included "translations" of medical language, the emotional difficulties of choices, and the use of what they called attractive layout and illustrations. Some men objected to numbers shown both as a percentage and 100 minus that percentage to rigorously frame each in both positive and negative. However, the provision of numbers to show frequency of side effects of treatments was considered essential. We did not find that patients perceived plain language as "talking down".
It is important to ask what is gained and what is lost in translating evidence-based TA approaches to plain language. Decision aids have been demonstrated to improve knowledge and assist patients in coming to stable decisions earlier in the treatment process [31,32]. In the face of that success, what improvements in decision aid effectiveness may be expected with the plain language integration and what may be lost? The major deletion we have made from the TA approach is the grading of the medical evidence studies used as source material. We presented rates of outcomes but did not indicate whether they came from randomized clinical trials or descriptive studies. Our reasoning is that grading actually distracts from the simple presentation of rates of mortality and side effects of treatments, and that absorbing what the rates mean is the core of what is needed to make an informed choice. References were made available separately.
Health literacy research shows that even highly educated patients who are worried and stressed by a difficult health decision prefer simple, every-day language that is easy to read quickly. No patients asked for references. The credibility of the DA may have been enhanced by their physician's offering it to them and by the endorsement of the Michigan Cancer Consortium (MCC). MCC represents major research universities, the State health department, and 75 other major Michigan medical organizations.
Conclusion
The plain language DA presenting medical evidence in text and numerical formats appears acceptable and useful in decision-making about localized prostate cancer treatment. The gains lie in the potential to improve on earlier gains in patient knowledge. If the actual content is not diluted, but the language, organization and design are more useful for patients, it is possible that mean knowledge scores may improve and that the median and the mean will converge. Parker et al [9] argue that health literacy is central to multiple health system priorities, including quality, cost containment, safety, and patients' involvement in health care decisions. They suggest that without attention to literacy, the move toward increased patient participation in health care decisions will exacerbate disparities in access and outcomes. This could mean that people with poor health literacy cannot function successfully in an environment designed for active, informed consumers. It should be noted that among our historical controls, there were large and significant deficits in knowledge among African Americans compared with White patients. We did not have sufficient numbers of African Americans in the intervention sample to test the ability of the DA to improve this deficit or to gauge the effect the DA had on willingness to discuss treatment options with physicians. Further testing should evaluate the DA among men with historically low levels or information, as well as among very low literacy men and non-readers. Testing of this DA in a trial against usual care is needed, as is development of the plain language approach in other conditions.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
All authors collaborated on conception and design of the study. MHR was responsible for drafting the article, the design of the decision aid evaluation and drafting the template. DRR provided the original expert draft of the DA. MHR, JTW, and AF contributed early changes. SS and JOF drafted the plain language translation. AF and JTW designed, drafted and performed the survey. KKB analyzed focus group data. RLD performed the statistical analyses. All contributed to editing and revising and approved the final manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
The authors are indebted to Dr. W. Underwood, and M. Velade for their assistance in conducting focus groups. The University of Michigan Comprehensive Cancer Centre, Health Media Research Laboratory (HMRL) performed design and execution of the booklet.
Supported in part by the Michigan Public Health Institute, the Michigan Department of Community Health, and the Agency for Healthcare Research and Quality with funding from the Centres for Disease Control and Prevention. The contents of the booklet described in this report do not necessarily represent the official views of the Centres for Disease Control and Prevention.
==== Refs
Chapple A Ziebland S Herxheimer A McPherson A Shepperd S Miller R Is 'watchful waiting' a real choice for men with prostate cancer? A qualitative study BJU Int 2002 90 257 264 12133062 10.1046/j.1464-410X.2002.02846.x
Fowler FJ JrMcNaughton CM Albertsen PC Zietman A Elliott DB Barry MJ Comparison of recommendations by urologists and radiation oncologists for treatment of clinically localized prostate cancer JAMA 2000 283 3217 3222 10866869 10.1001/jama.283.24.3217
Edwards A Elwyn G Evidence-based Patient Choice: inevitable or impossible? 2001 Oxford OX26DP, UK: Oxford University Press
Sackett DL Rosenberg WM Gray JA Haynes RB Richardson WS Evidence based medicine: what it is and what it isn't BMJ 1996 312 71 72 8555924
O'Connor AM Stacey D Entwistle V Llewellyn-Thomas H Rovner D Holmes-Rovner M Tait V Tetroe J Fiset V Barry M Decision aids for people facing health treatment or screening decisions Cochrane Database Syst Rev 2003 CD001431 12804407
Coulter A Paternalism or partnership? Patients have grown up-and there's no going back [editorial; comment] BMJ 1999 319 719 720 10487980
O'Connor A Decision Support Framework
Dralle H Scheumann GF Nashan B Brabant G Review: recent developments in adrenal surgery Acta Chir Belg 1994 94 137 140 7915074
Parker RM Ratzan SC Lurie N Health literacy: a policy challenge for advancing high-quality health care Health Aff (Millwood) 2003 22 147 153 12889762 10.1377/hlthaff.22.4.147
Schillinger D Piette J Grumbach K Wang F Wilson C Daher C Leong-Grotz K Castro C Bindman AB Closing the loop: physician communication with diabetic patients who have low health literacy Arch Intern Med 2003 163 83 90 12523921 10.1001/archinte.163.1.83
IOM Health Literacy: A Prescription to End Confusion. 2004 2004 Washington, DC, National Academies Press. Washington, DC Ref Type: Report
Davis TC Holcombe RF Berkel HJ Pramanik S Divers SG Informed consent for clinical trials: a comparative study of standard versus simplified forms J Natl Cancer Inst 1998 90 668 674 9586663 10.1093/jnci/90.9.668
Doak CC Doak LG Friedell GH Meade CD Improving comprehension for cancer patients with low literacy skills: strategies for clinicians CA Cancer J Clin 1998 48 151 162 9594918
Jacobson TA Thomas DM Morton FJ Offutt G Shevlin J Ray S Use of a low-literacy patient education tool to enhance pneumococcal vaccination rates. A randomized controlled trial JAMA 1999 282 646 650 10517717 10.1001/jama.282.7.646
Parikh NS Parker RM Nurse JR Baker DW Williams MV Shame and Health liberacy: the Unspoken Connection Patient Education & Counseling 1996 27 33 39 8788747 10.1016/0738-3991(95)00787-3
Root J Stableford S Easy-to-read consumer communications: a missing link in Medicaid managed care J Health Polit Policy Law 1999 24 1 26 10342253
Plain Language
Hibbard JH Peters E SUPPORTING INFORMED CONSUMER HEALTH CARE DECISIONS: Data Presentation Approaches that Facilitate the use of Information in Choice Annu Rev Public Health 2003 24 413 433 12428034 10.1146/annurev.publhealth.24.100901.141005
Dowie J The role of patients' meta-preferences in the design and evaluation of decision support systems Health Expect 2002 5 16 27 11915844 10.1046/j.1369-6513.2002.00160.x
Wei JT Dunn R Sanda M Hembroff L Taub D Demers R Tiwari A Survey of men newly diagnosed with localized prostate cancer: implications for patient education J Urol 2003 169 14
Rees CE Ford JE Sheard CE Patient information leaflets for prostate cancer: which leaflets should healthcare professionals recommend? Patient Educ Couns 2003 49 263 272 12642198 10.1016/S0738-3991(02)00188-X
Feldman-Stewart D Brundage MD Nickel JC Mackillop WJ The information required by patients with early-stage prostate cancer in choosing their treatment BJU Int 2001 87 218 223 11167645 10.1046/j.1464-410x.2001.02046.x
Holmes-Rovner M Llewellyn-Thomas H Entwistle V Coulter A O'Connor A Rovner DR Patient choice modules for summaries of clinical effectiveness: a proposal BMJ 2001 322 664 667 11250855 10.1136/bmj.322.7287.664
Fagerlin A Rovner D Stableford S Jentoft C Wei JT Holmes-Rovner M Patient education materials about the treatment of early-stage prostate cancer: a critical review Ann Intern Med 2004 140 721 728 15126256
Schneider C The Practice of Autonomy: Patients, Doctors, and Medical Decisions 1998 Oxford, UK: Oxford University Press
Tversky A Kahneman D The framing of decisions and the psychology of choice Science 1981 211 453 458 7455683
O'Connor AM Fiset V DeGrasse C Graham ID Evans W Stacey D Laupacis A Tugwell P Decision aids for patients considering options affecting cancer outcomes: evidence of efficacy and policy implications J Natl Cancer Inst Monogr 1999 67 80 10854460
Kreuger RA Focus Groups 1995 2 Thousand Oaks: Sage Publications, Thousand Oaks, CA
Barry MJ J Fowler FJ J Mulley AG J Henderson JV Wennberg JE Patient reactions to a program designed to facilitate patient participation in treatment decisions for benign prostatic hyperplasia Med Care 1995 33 771 782 7543639
O'Connor AM Rostom A Fiset V Tetroe J Entwistle V Llewellyn-Thomas H Holmes-Rovner M Barry M Jones J Decision aids for patients facing health treatment or screening decisions: systematic review BMJ 1999 319 731 734 10487995
Murray E Davis H Tai SS Coulter A Gray A Haines A Randomised controlled trial of an interactive multimedia decision aid on hormone replacement therapy in primary care BMJ 2001 323 490 493 11532844 10.1136/bmj.323.7311.490
| 15963238 | PMC1168900 | CC BY | 2021-01-04 23:52:11 | no | BMC Med Inform Decis Mak. 2005 Jun 20; 5:16 | utf-8 | BMC Med Inform Decis Mak | 2,005 | 10.1186/1472-6947-5-16 | oa_comm |
==== Front
BMC Musculoskelet DisordBMC Musculoskeletal Disorders1471-2474BioMed Central London 1471-2474-6-261592151010.1186/1471-2474-6-26Research ArticlePre-competition habits and injuries in Taekwondo athletes Kazemi Mohsen [email protected] Heather [email protected] Choung Young [email protected] Clinical education, Canadian Memorial Chiropractic College, Toronto, Ontario, Canada2 Clinical Sciences Resident, Canadian Memorial Chiropractic College, Toronto, Ontario, Canada3 former Canadian Taekwondo Team Head Coach, current Ontario Taekwondo Association President, Toronto, Ontario, Canada2005 27 5 2005 6 26 26 10 12 2004 27 5 2005 Copyright © 2005 Kazemi et al; licensee BioMed Central Ltd.2005Kazemi et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Over the past decade, there has been heightened interest in injury rates sustained by martial arts athletes, and more specifically, Taekwondo athletes. Despite this interest, there is a paucity of research on pre-competition habits and training of these athletes. The purpose of this pilot study was to assess training characteristics, competition preparation habits, and injury profiles of Taekwondo athletes.
Methods
A retrospective survey of Canadian male and female Taekwondo athletes competing in a national tournament was conducted. Competitors at a Canadian national level tournament were given a comprehensive survey prior to competition. Items on training characteristics, diet, and injuries sustained during training and competition were included. Questionnaires were distributed to 60 athletes.
Results
A response rate of 46.7% was achieved. Of those that responded, 54% dieted prior to competition, and 36% dieted and exercised pre-competition. Sixty-four percent of the athletes practised between 4–6 times per week, with 54% practicing 2 hours per session. Lower limb injuries were the most common (46.5%), followed by upper extremity (18%), back (10%), and head (3.6%). The majority of injuries consisted of sprains/strains (45%), followed by contusions, fractures, and concussions. More injuries occurred during training, including 59% of first injuries.
Conclusion
More research needs to be conducted to further illustrate the need for appropriate regulations on weight cycling and injury prevention.
==== Body
Background
The martial arts have their beginnings in the Orient but more specifically the common styles seen in Western society are from Japan, China, and Korea. Taekwondo, which originated in Korea more than 1000 years ago, is more sport than self-defense oriented [1]. In 2000, Taekwondo became recognized as an official sport at the Sydney Olympics. Taekwondo is a full contact free-sparring sport which awards points for head contact. As such, there has been increased interest in injury rates in the sport, especially relating to head injuries [2-5]. Although much of the research focuses on injury rates, very little examination into pre-competition habits and training has been conducted. The current authors felt that certain key areas needed to be addressed. These included training habits, injuries, dietary practices, and social support.
Training habits and injury
Most martial arts athletes practice between two to four times per week [1]. However, like in any sport, the frequency and hours of martial arts training can vary widely depending on athletic and competitive level of the individual. Training may be defined as a routine or process undertaken by athletes to further enhance their skill. Specific training may vary among each athlete, but there is usually a general format which is followed. Training classes often begin with a brief warm-up or stretching routine. This may then be followed by kicking drills, self-defense drills, training in patterns (forms) and sparring [1]. Taekwondo athletes have a wide variety of protective equipment available, although its use varies greatly, and concerns have been raised that the equipment often protects the attacker more than the defender [2]. Besides the regular training routine, students also participate in full-contact tournaments.
At the time of data collection at the tournament in question, one point was awarded for any strike from the waist upward. The World Taekwondo Federation (WTF) rules and regulations for Olympic competition were used for this tournament [7]. For the purpose of this study, an athlete was considered injured if the following occurred: 1) any circumstance which forced the athlete to leave the competition or training session; 2) any circumstance for which the referee or athlete had to stop the competition; or 3) any circumstance for which the athlete requested medical attention [6]. Injuries occur in both training and competition, and trauma to the lower extremity and head are the most common sites reported [6]. A distinction can be made between overuse and traumatic forms of injury; although in reality they could be considered as points along one continuum. Overuse injuries may occur following continued or accumulated microtrauma to a structure or body area [8]. Traumatic injuries are the result of physical trauma or external force to a certain region leading to a diminished functional ability [8]. In the current pilot study no distinction was made between these forms of injury although it would be an interesting feature to examine in future research. The majority of research about Taekwondo injuries has examined injuries sustained during competition. Even so, it has been noted that up to 60% of injuries are not reported [2]. There are a variety of explanations for this, including poor recall, lack of importance placed on the injury, and unwillingness to disappoint trainers.
Weight cycling
Weight cycling is a term used to describe rapid weight loss following self-induced food limitation and/or dehydration. Both gradual (seasonal) and rapid (weekly) weight reduction cycles are used by athletes, and have been investigated for potential effects on nutrition and performance [9]. These cycles are used in various sports such as judo, rowing, wrestling, and boxing in order to make a weight category. Like many of these sports, Taekwondo consists of repeated-effort, high intensity physical demands. In addition to this, Taekwondo competition is structured in a similar fashion to boxing and rowing in that athletes are required to meet weight requirements in order to compete. Although there is no known reported research about weight cycling in Taekwondo, it is the primary author's experience (holding a fifth degree black belt in WTF Taekwondo and practicing Taekwondo for more than twenty-five years) that it is widely practiced in the sport. The WTF has various weight classes depending on competition level [7]. Table 1 illustrates the four WTF weight classes per gender for Olympic competition, which were also the categories used at the tournament for the present study. Although the World Taekwondo Federation has eight distinct weight classes per gender for all competitions and championships except for the Olympic Games, no rulings have been implemented to address weight cycling in the sport.
Table 1 World Taekwondo Federation Olympic Weight Classes for Men and Women
Males Females
Less than 58 kg Less than 49 kg
Between 58 to 68 kg Between 49 to 57 kg
Between 68 to 80 kg Between 57 to 67 kg
Over 80 kg Over 67 kg
To date there has been no research investigating the perceived benefit of weight cycling among Taekwondo athletes and this is an area in which much work should be undertaken. Due to the similarities between boxing and Taekwondo, with respect to competition weigh-ins, it may be possible to infer that Taekwondo athlete's perceptions of this technique may be similar. One study examining weight cycling among boxers reported that all the subjects felt it necessary to lose weight prior to competition and that it improved their performance [10]. Athletes using this weight control technique may be mistaken in thinking that an advantage will be gained over the opponent competing at his/her natural weight. To this point the research findings into the effect of food and fluid restriction has been equivocal [10]. There is also a belief that nutrients and strength can be restored by eating and drinking in the period between the weigh-in and the competition. Several authors have reported various techniques for rapid weight loss. A few strategies include dieting, restricting food and fluid intake, diuretic use, long runs, skipping, cycling, saunas, and exercising in rubber/plastic suits [10-12].
Psychological state / support
Despite athletes' perceptions of the benefits of weight cycling, there are both physiological and psychological side effects. Using the Profile of Mood States-A (POMS-A), anger, confusion, depression, fatigue, tension, and vigor were measured among weight cycling amateur boxers [10]. The study reported that rapid weight loss was associated with significantly higher scores on anger, fatigue, and tension, with decreased vigor. The authors concluded that weight cycling resulted in negative mood and debilitated performance among their respondents. It is important for parents, coaches, and significant others to recognize these signs and address them appropriately.
The idea of participating in competitive situations can be daunting for some individuals. Intense pressure, anxiety, and somatic manifestations may result. For those in athletic competition, it is vital to recognize and address these sources of stress in order to produce more successful outcomes.
To date there is a lack of research in the areas of weight cycling and its perceived benefits among Taekwondo athletes. There is also limited research in the areas of social support and injury profiles in Taekwondo athletes outside of competition. This pilot study is an initial step towards increasing our knowledge in these areas. The purpose of the present study was to assess training characteristics, competition preparation habits and injury profiles of Taekwondo athletes.
Methods
Subjects
Sixty Canadian male and female respondents were recruited for the study. Participants were Taekwondo athletes competing at a national-level tournament. A total of 28 respondents with an age range of 16 to 29 years returned the distributed questionnaire. Four females and 18 males completed the questionnaire. An additional six participants did not indicate their gender on the returned questionnaires. The mean age of the competitors was just over 22 years, with a mean height and weight of 68.6 inches and 148 pounds, respectively.
Instrumentation
A twenty-one-item questionnaire (See Additional file: 1 was used to obtain a general profile of the athletes. Areas of focus included: amount of Taekwondo practice; training satisfaction; protective gear used; pre-competition eating habits; competition preparedness; social support for the sport; and injury profiles. The questionnaire was modelled after one that had been developed for Dragon Boat racers. Neither questionnaire has been tested for validity or reliability.
Procedure
The first author was working at the national carding tournament as a member of the health care team. As they entered the facility, potential participants were invited to fill out the survey by the current author and his assistants. Only card-carrying athletes competing in the tournament were given questionnaires. Prior to participation, informed consent was obtained by the participants or their guardians. At that time, any questions regarding the study or survey were addressed. Sixty questionnaires were distributed. When participants were given the questionnaire, they were asked to complete it immediately and then return it to the current author or assistants.
Statistics
The Statistica Release 6 statistical package was used for all analysis. Descriptive statistics and Pearson's chi-square test were used. When inputting data, it was noted that certain variables had missing responses. In these instances, the number of participants who completed the questions was used to calculate the results.
Results
Training Habits
Training time, measured by number of practices per week, and number of hours per training session, is outlined in Tables 2 and 3. Specific activities during training were also examined. The frequency of sparring was reported. Twenty-five percent (n = 7) of the competitors reported sparring one to two times per week. Over 53% (n = 15) of respondents sparred three to four times per week, and over 21% (n = 6) sparred five or more times per week. Pre- and post-training stretching was also reported. Over 40% (n = 11) of respondents reported only stretching prior to their training sessions, and close to 60% (n = 16) of respondents stretched both before and after training. When examining the use of warm-up and cool-down exercises, over 57% (n = 16) of participants noted always warming up prior to training, while almost 43% (n = 12) reported only warming up occasionally. Only six of 28 respondents (21%) reported they always engaged in post-training cool-down exercises, other than stretching. Over sixty-four and fourteen percent (n = 22) of respondents reported occasionally and never using cool down exercises, respectively.
Table 2 Training Time – Number of practices per week (n = 28)
Practices Per Week
Number of Practices Percent
2 7.1
3 14.3
4 25
5–6 39.3
7 or more 14.3
Table 3 Training Time – Number of hours per practice (n = 28)
Hours Per Practice
Number of Hours Percent
1 17.9
2 53.6
3 17.9
4 7.1
5 or more 3.6
The use of protective gear was also examined. Over 60 percent (n = 17) of respondents reported always using protective gear, while 39.3% (n = 11) only used it occasionally. Table 4 lists the type of gear and its percentage use by the respondents. When examining the frequency of missed practices, five respondents reported never having missed a practice even though they were injured. More athletes missed one to two practices when injured, although there were a few respondents who missed a substantial number of practices regardless of the injury frequency. Less time and practices were missed as injury number increased. Eight respondents reported that they had not experienced any injuries. Four cases had incomplete data and were subsequently not used in the calculation of missed practices.
Table 4 Type and frequency of protective gear used by Taekwondo athletes (n = 28)
Gear Used Elbow Pads Shoes Shin Pads Gloves Head Gear Instep Pads Chest Protector Mouth Guard
% of Use 57.1 35.7 92.9 3.6 57.1 10.7 78.6 14.3
Table 5 reports the number of missed practices for the first to fifth injuries.
Table 5 Number of missed practices affected by injury frequency (n = 16)
# of Missed Practices 1st Injury (n) 2nd Injury (n) 3rd Injury (n) 4th Injury (n) 5th Injury (n)
None 3 0 1 0 1
1 to 2 5 1 0 1 0
3 1 0 0 0 0
5 to 9 1 1 0 0 0
10 to 14 1 2 0 0 0
20 to 24 2 0 0 0 0
25 to 29 0 0 1 1 0
30 to 39 1 0 0 0 0
40 to 49 1 1 0 0 0
50 to 99 1 0 0 0 0
150+ 0 1 0 0 0
Injury profile
At this level of competition, 75% (n = 21) had six or more years of Taekwondo experience, with over 57% (n = 16) of individuals having eight or more years experience. Of the 28 participants, only 6 (21%) reported never having experienced an injury. At a value of 46.5% (n = 13), the lower limb was reported as being the region most injured in first-time injuries. The upper limb and back had an injury rate of 18% (n = 5) and 10.8% (n = 3), respectively. Over 3% (n = 1) of participants reported experiencing head injuries. Data for participants suffering injuries are reported in Table 6. Seventy nine percent (n = 22) of athletes reported they had an injury. Of those, 47 percent (n = 13) had a lower limb injury, 18 percent (n = 5) had an upper limb injury, and 11 percent (n = 3) had a back injury. Thirteen athletes (46%) reported they had experienced a second injury. Of those, 29 percent (n = 8) had a lower limb injury, 11 percent (n = 3) had an upper limb injury, and seven percent (n = 2) had a back injury. Injury rates decreased substantially for those who reported experiencing a third injury. Only fourteen percent (n = 4) of the athletes reported suffering from a third injury. Of those, seven percent (n = 2) had a lower limb injury, while upper limb (n = 1) and back injuries (n = 1) each accounted for four percent of the injuries. Four athletes (14%) reported experiencing a fourth injury while 2 athletes (7%) reported they had a fifth injury. Of those, only lower limb injuries were reported.
Table 6 Injury rates and location of injuries in Taekwondo athletes (n = 24)
Number of Injury Lower Limb Injury (%) Upper Limb Injury (%) Back Injury (%) Other Injury (%)
1st 13 (46.5) 5 (17.9) 3 (10.8) 1 (3.6)
2nd 8 (28.5) 3 (10.8) 2 (7.2) 0
3rd 2 (7.2) 1 (3.6) 1 (3.6) 0
4th 4 (14.4) 0 0 0
5th 2 (7.2) 0 0 0
The frequency of injuries in training versus competition was also examined. Out of a total 22 responses, 13 respondents reported experiencing their first injury during training, while nine respondents experienced their first injury in competition. Training was most frequently reported as the time of injury, with eight out of thirteen respondents reporting second injuries occurring during training, versus five out of thirteen during competition. No competition injuries were reported for the third to fifth injuries.
In order to better understand the injury data, injury rates were calculated using the basic rate formula: (#injuries / # athlete-exposures) × 1000 = # injuries per 1000 athlete-exposures (A-E). Due to problematic data, only 24 of the 28 respondent's data were used. The overall rate of injuries was 520/1000 A-E. The injury rate was 354.2/1000 A-E for training, and 166.7/1000 A-E for competition. The injury rate for training per hour was 32.5/1000 A-E/ hour.
A variety of care was sought by the athletes following injury. Of those respondents completing the survey, 25% (n = 7) did not seek any form of treatment. Another 10.7% (n = 3) of the athletes were treated by medical doctors, 10.7% (n = 3) were treated by physiotherapist, 10.7% (n = 3) were treated by chiropractors, and 3.6% (n = 1) received acupuncture. A variety of treatment combinations were also reported by 14.4% (n = 4) of the athletes. These combinations included chiropractic care as well as various sources of therapy listed above.
Weight cycling
Pre-competition habits are an important factor to examine in all sports. Due to weight classifications in Taekwondo, the athletes are very conscious of their weight. Certain trends were reported by participants in order to achieve the desired weight. Over 53% (n = 15) of participants reported fasting prior to the competition. Of these individuals, 33.3% (n = 4) neither ate nor drank, 50% (n = 6) only drank, and 17% (n = 2) ate but did not drink. Aerobic exercise was another method used by competitors in order to reach the desired weight category. In addition to dieting, 83%, or 10 of the 15 fasting participants reported doing aerobic activity prior to competition.
Social support
Support is often key to athletes at higher levels of competition. The current author examined athlete support for the sport by significant others. Seventy-eight percent (n = 22) of athletes reported they had parental support, while 14% (n = 4) reported no parental support was given, and 7% (n = 2) of respondents responded that this support did not apply. Spousal or partner support was reported by 32% (n = 9) of the athletes, while 18% (n = 5) did not receive this support, and 50% (n = 14) of respondents noted that the category did not apply to them. Because the survey was completed prior to competing, participants were asked to record if they felt prepared for the upcoming event. Fifty percent (n = 14) of respondents responded that they were prepared, 39% (n = 11) felt prepared but nervous, and 11% (n = 3) did not feel adequately prepared for the competition.
Several comparison analyses were performed using Pearson's chi-square test. None of the values were of statistical significance, and thus not reported. The rationale for only reporting frequencies is due to the small sample size of the study, making the use of other analyses like Pearson's or Fisher's Exact Test erroneous.
Discussion
The objective of this retrospective investigation was to assess training characteristics, competition preparation habits, and injury profiles of taekwondo athletes. By having the athletes complete a survey, several areas of concern regarding competition preparation and injuries were highlighted.
Training and injuries
When examining the training habits of taekwondo athletes, the current study reviewed several components of performance. Respondents had significant experience in the sport, with over 75% having six or more years of involvement. Training time, measured by number of practices per week and number of hours per practice, was also high. Over 53% of practices were two hours, with over 45% of athletes practicing between two to four times per week. Of importance is the relationship of how training time and competition is affected by injury. Unfortunately, our sample size was too small to have meaningful comparisons.
Other authors have reviewed this relationship. In a study by Feehan and Waller [2], competitive performance affected by previous injury was examined. On the day of the competition, 35% of respondents had a current injury affecting performance. Some of these required strapping or support in order to perform. Seventeen percent reported continuing to train/compete against medical advice. Even with these injury rates, the authors noted that fight outcome was not significantly associated with current or previous injuries. One conclusion which might be drawn is that the injuries reported were not severe enough to negatively impact the athletes' performance. It can also be assumed that many of those with severe injuries would have chosen to withdraw from or not enter the competition until an appropriate level of health was reached.
Practice activities among the respondents varied. A large proportion of respondents warmed up prior to kicking drills, while less than 25% cooled down. One possible explanation for warm-up participation may be that it is encompassed within the class. On the other hand, cool downs may be left to the discretion of the athlete once training is finished. In the current study, stretching was considered a separate activity from warm-ups and cool-downs. Over 60% of respondents stretched both before and after training, while just over 40% stretched prior to training only. In future studies, it would be interesting to note if stretching occurred after warm-up, which is a newer trend of thinking in the prevention of muscle injury [13]. Within the questionnaire, it was specified that cool down exercises did not include stretching. By doing this, the authors intended to eliminate the overlap between the stretching and cool down items. Future studies should allow subject to specify the various types of cool down activities used, such as light jogging or light-paced jumping jacks. Future studies should also examine the relationship between injury rates and the use of stretching, warm-ups, and cool downs. Due to a limited sample size the current study was not able to make these comparisons. The final training activity examined in the current study was sparring. This was an integral part of taekwondo training, with over 50% of respondents sparring three to four times per week. The current study attempted to examine the relationship between frequencies of sparring when injured, but there were no statistically significant differences. Birrer [14] reported that most injuries occur during sparring, thus it is an area of training which deserves specific focus. Future studies should focus on both injury type and frequency occurring during sparring, as well as limitations in sparring due to injury.
In the current study, training was most frequently reported as the time of injury and relatively few injuries occurred during competition. Even so, the overall reported injury rate was quite high, at 520/1000 A-E. The injury rates calculated for both training and competition are likely to be skewed. Firstly, respondents were asked to simply report if they had been injured during competition or training. A more accurate representation may have occurred if athletes were asked to report how many competitions they had participated in during the previous year and if they had suffered injuries during any of these. Training injury rates may have also been affected by athletes returning to play prior to complete resolution of their problem. This could make athletes more susceptible to subsequent injuries.
When reviewing injury location reported in the current study, it was not surprising, that the lower extremity received the most injuries. This was also true for all subsequent injuries reported (up to five per athlete). These results are consistent with those of several other studies [2,5]. The upper limb was the second most frequently injured region, with the head being the least frequently injured. Sprains and strains were the most common injuries, followed by contusions, which is similar to other research [2]. Other reports have listed contusions and concussions as the most common forms of taekwondo-related injuries [3,6]. Zemper et al. [5] reported that contusions were the predominant type of injury in his study of injury rates recorded during the 1988 US Olympic team trials for taekwondo.
In general, the number of practices missed decreased with subsequent injuries. Also, there were relatively few athletes who missed a large number of practices. This is perhaps attributable to injury severity. One explanation for fewer missed practices could be that once an athlete experienced one injury, s/he was more likely to increase the use of protective gear, thus avoiding or decreasing future injury severity. Future studies should examine if there is a relationship between increased uses of protective gear following an injury.
Recently, there has been increased concern regarding head injuries in taekwondo. Koh and Watkinson [4] reported that when compared to other contact sports, competition Taekwondo had the highest incidence rate of concussions. This might be explained by the fact that athletes are awarded points for head contact. Disturbingly, it was also found that over 30% of concussed athletes suffered more than one significant head blow in the same match. Also, among 99% of the head blows, no evasive manoeuvres were attempted. This would suggest that athletes are poorly trained in blocking skills. Pieter and Zemper [3] also reported that contusions and cerebral concussions were the leading injury types among young male and female Taekwondo athletes. Again, unblocked attacks were a frequent occurrence in these injuries. Widespread safety education on head injuries, and more specifically concussions, is needed among Taekwondo athletes, trainers, and referees. Improved blocking skills and headgear are a priority in order to help avoid serious injury.
Following injury, a variety of care was sought by the current study's athletes. Interestingly, one quarter of the athletes chose not to seek any form of treatment. This could perhaps be accounted for by the athlete's perception of the injury being relatively minor, or being able to manage it without medical advice. Several health professional were consulted by the injured athletes. These included medical doctors, physiotherapist, chiropractors, acupuncturists, and massage therapists. In addition, several athletes consulted multiple therapists. Athletes are generally anxious to return to their pre-injury status, and often become impatient with long-term therapy. This may explain why multiple health professionals were consulted. Also, some health professionals realize the benefit to a multidisciplinary approach, and use a network of referral sources when necessary.
Weight cycling
Not surprisingly, more than half of the competitors in the current study dieted prior to competition in order to make their weight class. Although the questionnaire did not specifically define fasting, the subsequent question provided several categories of fasting, such as "did not eat and drink", "did not drink but eat", and so on. Even with the lack of a clear definition for fasting, fifty percent of the participants reported having completely restricted food intake, while 33% fully restricted food and liquids. Because of the nature of this tournament setting, it was not feasible to weigh athletes prior to their competition. As such, the authors were not able to report actual weight loss occurrence among the athletes. Future studies should focus on intended and actual weight loss among Taekwondo athletes in order to better capture the occurrence of weight cycling in the sport.
Rapid weight loss is a common practice among athletes in weight class sports. Hall and Lane [10] reported that their boxing subjects lost an average of 5.16% of their body weight within one week. Along with the weight loss, subjects reported higher anger, fatigue, and tension, as well as reduced vigour. Participants were able to maintain their baseline performance of circuit training when at the reduced weight, although the scores were significantly lower than the athletes expected. It can be postulated that athletes have a misplaced sense of improved strength and performance capabilities when weight cycling for competition. Unfortunately, these views may be reinforced if a weight cycling athlete wins a competition, thus increasing the likelihood of using the strategies in the future. In a study by Alderman et al. [11] examining the prevalence of and weight loss techniques used by high school wrestlers, more successful wrestlers engaged in rapid weight loss (RWL) versus less successful wrestlers. This further reinforces the use of RWL among young competitors.
What is particularly striking are the methods used to induce rapid weight loss. Among high school wrestlers, excessive running was used by almost 92% of individuals practicing RWL. Exercising in rubber/plastic suits and using saunas are prohibited in American high school wrestling, but they continued to be used by 40–60% of wrestlers to achieve RWL [11]. Thirty-six percent of respondents in the current study did aerobic exercise in addition to dieting to make their weight, but specific activities were not asked for in the survey.
Many short term and long term side effects have been reported with rapid weight loss. Alderman et al. [11] reported multiple symptoms experienced by collegiate weight cycling wrestlers. Over 46% of participants experienced headaches, while over 44% and 42% experienced dizziness and nausea, respectively. Other symptoms included hot flashes, nosebleeds, feverish sensations, disorientation, and increased heart rate. Wenos and Amato [15] reported that college-level wrestlers also experienced an increased perception of effort as muscle strength and endurance decreased with rapid weight loss.
Fogelholm et al. [9] studied the effects of gradual versus rapid weight loss in national wrestlers and judo athletes on nutrient intake, micronutrient status, and physical performance (sprint, jump height, and anaerobic performance). A 5% to 6% reduction in body weight was reported in the gradual and rapid loss groups. Nutrient intake was significantly decreased in both groups in B1, B2, K, Ca, Mg, Fe, and Zn values, compared to baseline measures. Speed, vertical jump, and anaerobic performance were not impaired by either rapid or gradual weight loss. Other studies have also reported that despite nutrient depletion, performance of Olympic level amateur boxers during rapid weight loss was not significantly different versus times of normal dietary behavior. These authors concluded that despite reduced carbohydrate intake, there were other sufficient energy sources to meet performance demands [16]. In contrast, Filare et al. [12] reported that all mean micronutrient intakes were below recommended values, while triglyceride levels and free fatty acids were increased in weight cycling judo athletes. Left hand grip values and 30-second jump test output were decreased after seven days of food restriction.
By reviewing the literature, some might argue that the evidence of health risks from weight cycling is equivocal. Even so, there are several possibilities that may help explain the lack of supporting data. One possibility is that there may be no effect. Another proposed by Waslen, McCargar, and Taunton [17], is that the duration, frequency, and severity of food restriction among the judo athletes in their study may not have been sufficient to have an effect. Even with a lack of strong support to illustrate the ill effects of weight cycling, monitoring dietary habits of athletes in weight class sports is recommended. It is more prudent to assume that larger weight losses and more frequent dieting could potentially result in negative physiological and performance consequences. Widespread regulations need to be implemented to control weight cycling practices among weight class sports. Athletes need to be educated regarding the negative effects of the practice on both their health and performance.
Psychological state/support
Support is often key to athletes at higher levels of competition. The current authors examined athlete support by significant others. The majority of athletes reported receiving support from either their parents, or spouse/partner. Unfortunately, the questionnaire used in this study did not delve into the various aspects of psychological state or support. In this pilot study, respondents were simply asked "Are your parents supportive of your involvement in Taekwondo?" and "Is your spouse or significant other supportive of your involvement in Taekwondo?" It is obvious that neither of these questions addresses the various components involved in support. Future studies need to be more specific in questioning the types and level of support provided to athletes, whether it be emotional, financial, or other various forms of support. As such, these results are of little contributive value. It should be noted that although a large percentage of the athletes felt prepared for the competition, they also reported being nervous. The significance of anxiety and other personality traits in competitive sport has long been studied. It has been reported that winning Taekwondo athletes had lower cognitive and somatic anxiety and higher self-confidence then their losing counterparts [18]. Others found no support for the relationship between competition trait anxiety and Taekwondo performance [19]. Even so, for ultimate personal success, athletes often require a strong support base. This encompasses a sense of understanding, trust, and support from the trainer, and significant others.
In weight class sports, the potential effects of weight cycling must also be kept in mind. As noted above, several studies have reported deleterious effects associated with rapid weight loss. These effects may involve one's mental status. Filaire et al. [12] reported that confusion, anger, fatigue, and tension were significantly higher after weight loss. Vigor was also significantly lower after food restriction. Thus, when considering the psychological preparedness of an athlete, multiple factors must be measured.
There are a few limitations in the present study which need to be addressed. The most obvious methodological issue in this study is that the questionnaire has not been validated. There is very little reported research regarding precompetition habits among Taekwondo athletes. As such, the authors felt it necessary to develop the questionnaire, knowing that there would be issues with its validity. Because this is a pilot study, the results from this study should be used with caution and as a means to enhance future studies in this area. In addition, the small sample size significantly affected statistical analysis. No correlations were significant and thus specific conclusions regarding associations between training behaviors and injuries could not be made. The response rate was low, likely due to the fact the participants were asked to complete the surveys upon entering the tournament building. Athletes may have neglected to complete or return the surveys because of lack of time or feeling that it was not a priority prior to their match. Also, a self-report retrospective survey may be affected by poor recall and perception bias. For example, the recall of more severe and painful injuries would likely be better than that of minor injuries/trauma. The survey was also completed at a competition, thus those who were injured and not participating were already selected out. With respect to the information gained regarding weight cycling, actual weights were not taken. It would have been more informative to weigh the athletes at the mat just prior to their match and compare the result with that of their tournament weigh-in. As mentioned previously, the questionnaire used in this pilot study was vague regarding several concepts. Key definitions were not provided on the questionnaire. Future studies should ensure that all concepts are clearly defined in order to reduce subject confusion and hopefully avoid missing responses or poor response rates.
Conclusion
The results of this pilot study are primarily descriptive. Even so, they highlight specific training habits and injuries among Taekwondo athletes. Although this pilot study examined a variety of pre-competition habits, it is evident that there are several specific areas which require more in-depth investigation. In order for safety recommendations to be implemented, it is likely that clear relationships will need to be demonstrated. Specifically, the physical effects of weight cycling on performance and improved training to avoid injury need to be examined. Athlete's perceptions and belief systems surrounding weight cycling, social support, and injury reporting are all topics in need of further investigation. As such, follow-up research on the relationship of pre-competition habits and injuries in Taekwondo athletes is necessary.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
MK analyzed the data, wrote the abstract and various components of the manuscript. HS wrote various components of the manuscript, as well as helped to edit it. YSC helped to develop, distribute and collect the questionnaire, and edit the manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Supplementary Material
Additional File 1
There is also an additional file attached titled, "Figure 1. Questionnaire". This is the exact Questionnaire which was distributed to the athletes.
Click here for file
Acknowledgements
We would like to thank Dr. Judith Waalen for reviewing the manuscript and Dr. Cameron McDermaid for his help with the statistical analysis. We would also like to thank the Canadian Memorial Chiropractic College for its support.
==== Refs
Buschbacher RM Shay T Martial arts Physical Medicine and Rehabilitative Clinics of North America 1999 10 35 47
Feehan M Waller AE Precompetition injury and subsequent tournament performance in full-contact taekwondo British Journal of Sports Medicine 1995 29 258 62 8808541
Pieter W Zemper ED Head and neck injuries in young taekwondo athletes Journal of sports medicine and physical fitness 1999 39 147 53 10399424
Koh JO Watkinson EJ Possible concussions following head blows in the 2001 Canadian national taekwondo championships Boundaries 2002 1 79 93
Zemper ED Pieter W Injury rates during the 1988 US Olympic team trials for taekwondo British Journal of Sports Medicine 1989 23 161 4 2620229
Kazemi M Pieter W Injuries at a Canadian national taekwondo championship: a prospective study BMC Musculoskeletal Disorder 2004 5 22 10.1186/1471-2474-5-22
Website title
Stedman's Medical Dictionary for the Health Professions and Nursing 2005 5 Baltimore (MD): Lippincott Williams & Wilkins
Fogelholm GM Koskinen R Laakso J Rankinen T Ruokonen I Gradual and rapid weight loss: Effects on nutrition and performance in male athletes Medicine and Science in Sports and Exercise 1993 25 371 7 8455453
Hall CJ Lane AM Effects of rapid weight loss on mood and performance among amateur boxers British Journal of Sports Medicine 2001 35 390 5 11726472 10.1136/bjsm.35.6.390
Alderman BL Landers DM Carlson J Scott JR Factors related to rapid weight loss practices among international-style wrestlers Medicine & Science in Sports & Exercise 2004 36 249 52 14767247
Filare E Maso F Degoutte F Jouanel P Lac G Food restriction, performance, psychological state and lipid values in judo athletes International Journal of Sports Medicine 2001 22 454 59 11531040 10.1055/s-2001-16244
Worrell TW Factors associated with hamstring injuries: An approach to treatment and preventative measures Sports Medicine 1994 17 338 45 8052770
Birrer RB Trauma epidemiology in the martial arts: The results of an eighteen-year international survey American Journal of Sports Medicine 1996 24 S72 9 8947435
Wenos DL Amato HK Weight cycling alters muscular strength and endurance ratings of perceived exertion and total body water in college wrestlers Perceptual and Motor Skills 1998 87 975 8 9885067
Smith M Dyson R Hale T Hamilton M Kelly J Wellington P The effects of restricted energy and fluid intake on simulated amateur boxing performance International Journal of Sport Nutrition and Exercise Metabolism 2001 11 238 47 11426438
Waslen PE McCargar LJ Taunton JE Weight cycling in competitive judokas Clinical Journal of Sports Medicine 1993 3 235 41
Chapman C Lane AM Brierly JH Terry PC Anxiety, self-confidence and performance in tae kwon-do Perceptual and Motor Skills 1997 85 1275 8 9450282
Finkenberg ME DiNucci JM McCune ED McCune SL Analysis of the effect of competitive trait anxiety on performance in taekwondo competition Perceptual and Motor Skills 1992 75 239 43 1528673
| 15921510 | PMC1168901 | CC BY | 2021-01-04 16:32:03 | no | BMC Musculoskelet Disord. 2005 May 27; 6:26 | utf-8 | BMC Musculoskelet Disord | 2,005 | 10.1186/1471-2474-6-26 | oa_comm |
==== Front
BMC Pregnancy ChildbirthBMC Pregnancy and Childbirth1471-2393BioMed Central London 1471-2393-5-101590721010.1186/1471-2393-5-10Research ArticlePregnancy-induced hypertension and infant growth at 28 and 42 days postpartum Baulon Emmanuelle [email protected] William D [email protected] Bruno [email protected] Pierre [email protected] Xu [email protected] Department of Obstetrics and Gynecology, CHU Strasbourg, France2 Department of Obstetrics and Gynecology, University of Montreal, Quebec, Canada3 Department of Pediatrics, Laval University, Quebec, Canada4 Department of Epidemiology, Tulane University, New Orleans, LA, USA2005 20 5 2005 5 10 10 8 3 2005 20 5 2005 Copyright © 2005 Baulon et al; licensee BioMed Central Ltd.2005Baulon et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
No previous studies have examined the effect of pregnancy-induced hypertension (PIH) on early infant growth. The objective was to study infant growth patterns of babies born to mothers with PIH at 28 and 42 days postpartum.
Methods: Design
We conducted a population-based retrospective cohort study of 16,936 pregnancies delivered between January 1, 1989 through December 31, 1990 in Suzhou, China. PIH was classified as gestational hypertension, preeclampsia and severe preeclampsia. Infant Growth Percentage (IGP) was calculated as the weight gain from birth to infant weight at 28 or 42 days postpartum divided by the birth weight. Univariate analysis and multivariate linear regression were performed to compare the infant weight as well as IGP at 28 and 42 days postpartum between various types of PIH and the normotensive group.
Results
Infant weights at 28 and 42 days postpartum were significantly lower in severe preeclampsia (e.g., 4679.9 g at 42 days) and preeclampsia (e.g., 4763.8 g at 42 days) groups than in the normotensive group (e.g., 4869.1 g at 42 days, p < 0.01). However, there were no differences in IGP between groups. After stratifying by intrauterine growth restriction (IUGR) status, if babies were not intrauterine growth restricted, none of the PIH types showed a significantly lower weight at 28 and 42 days postpartum and their IGPs were similar to those of the reference group. When babies were growth restricted, all PIH groups showed significantly lower weights but higher IGP at 28 and 42 days postpartum as compared to the normotensive group.
Conclusion
Infants born to mothers with PIH but without IUGR have normal early infant growth. IUGR secondary to PIH is associated with significant catch-up growth at 28 and 42 days postpartum.
==== Body
Background
Pregnancy-induced hypertension (PIH), especially preeclampsia, is a major cause of maternal and perinatal morbidity and mortality worldwide [1,2]. The impact of PIH on birth outcomes has been extensively studied. However, the potential long-term effect of PIH on infants born to PIH mothers has been less studied. PIH has been confirmed to increase significantly the risk of low birth weight by both increasing preterm birth as well as reducing fetal growth. On the other hand, PIH has been found to be associated with an increased rate of high birth weight and large-for-gestational age babies [3,4]. These findings suggest that PIH, more specifically preeclampsia, is a heterogeneous syndrome and that preeclampsia may appear in two forms: restricted fetal growth preeclampsia and normal fetal growth preeclampsia [4-7]. PIH may have different short and long term effects on infant growth between these possible two types of preeclampsia by intrauterine growth restriction (IUGR) [5,6]. Low birth weight or IUGR babies have been associated with the occurrence of several chronic diseases such as cardiovascular diseases in later life [8-10]. However, the hypothesis of the fetal origins of adult disease is still the subject of debate [11,12]. One argument is that maternal risk factors in pregnancy (such as PIH) and environmental risk factors in the postpartum period can contribute to this life-long development of the chronic disorders. A change in infant growth of the IUGR baby itself (e.g. catch-up growth) such as in the critical early infant period may also have long-term effects on health later in life, and this change of postpartum growth may be influenced by PIH. Therefore, it is important to study postpartum infant growth patterns of babies born to mothers with PIH, and to determine if there are differences in infant growth between babies with and those without IUGR. However, to date, there have been few studies on the effects of PIH on infant growth. The objective of this study was to examine the effects of the various types of PIH on infant weight gain at 28 and 42 days postpartum.
Methods
Database
We conducted a retrospective cohort study based on a population-based perinatal database from Suzhou, China. The database was previously described by Xiong et al [3,13]. In brief, data used in this analysis were population-based, collected in all 10 hospitals in the city, including16,936 pregnant women from January 1, 1989 through December 31, 1990. We excluded patients with multiple pregnancies (212 cases), chronic cardiovascular disease (36 cases), chronic renal disease or a history of renal disease (303 cases), chronic hypertension or history of hypertension (59 cases), and abnormal blood pressure (diastolic pressure ≥ 90 mmHg or systolic pressure ≥ 130 mmHg) at the first prenatal visit before 21 weeks (850 cases) and abnormal blood pressure after 42 postpartum days (988 cases). There were 2,567 women with no or missing information on infant weight at 28 days or 42 days postpartum, including 105 women who had stillbirths, 138 women who had infant deaths up to 28 days postpartum and 2,324 women who were lost to follow-up. After exclusions, a total of 11,921 pregnancies were retained for the analysis.
Definition of pregnancy-induced hypertension
PIH was classified as gestational hypertension, preeclampsia, severe preeclampsia or eclampsia. According to the Chinese criteria [14], gestational hypertension was defined as a blood pressure equal to or greater than 130/90 mmHg on more than two occasions greater than six hours apart without proteinuria after 21 weeks of gestation. Preeclampsia was diagnosed as hypertension of equal or greater than 130/90 mmHg but less than 160/110 mmHg with proteinuria of 1+ or 2+ on dipstick in two samples 6 hours apart or greater than 0.3 grams in a 24-hour urine collection. Severe preeclampsia was diagnosed when preeclampsia was complicated by a systolic pressure of ≥ 160 mmHg or diastolic pressure ≥ 110 mmHg and/or if proteinuria was greater than 2+ on dipstick or 5 grams in 24-hour urine collection. Eclampsia was defined as seizure occurred in patients with preeclampsia. Patients with eclampsia were grouped with the severe preeclampsia group for analysis. We restricted our focus to PIH, therefore, pregnancies complicated by chronic hypertension and preeclampsia superimposed on chronic hypertension were not studied.
Definition of outcomes and confounding variables
Birth weight was measured in grams at birth. Infant weight was measured at 28 and 42 days postpartum. Gestational age was determined by the obstetricians on the basis of the information on menstrual history, physical examination or early ultrasound examination. IUGR was defined as birth weight below the tenth percentile of expected weight for gestational age [15]. Infant weight at 28 days was measured as the standardised medical procedures during the third postpartum home visit by personnel from the community clinic near the newborn's home. Infant weight at 42 days postpartum was measured in hospital during the last day of perinatal care examination while registering for the beginning of the infant care. We developed an index of Infant Growth Percentage (IGP) to measure the infant growth rate. IGP at 28 days is defined as [(infant weight 28 days - birth weight) / birth weight] × 100% and so is the IGP at 42 days by [(infant weight 42 days - birth weight) / birth weight] × 100%. Infant complications were defined as at least one of respiratory distress, newborn fever, birth injury, jaundice, sclerema, cord infection and intra-cranial bleeding. Other potential confounding variables include maternal age, body mass index [weight (kg)/height(m)2], infant's sex, pre-pregnancy or gestational diabetes mellitus and maternal anemia.
Statistical analysis
Mean birth weight and infant weights at 28 and 42 days postpartum were compared by a variance of analysis between different PIH groups. First, the three groups with PIH disorders were compared to the normotensive referent group. Then each PIH group was further divided into two subgroups according to the existence of IUGR and the same analysis performed using normotensive pregnancies without IUGR as the referent group. Post hoc pair-wise multiple comparisons, which test which specific means differ significantly from others, were performed by Tukey and Bonferroni procedures [16]. In order to assess the independent effect of PIH on infant weight at 28 and 42 days postpartum respectively, multiple linear regression analysis was performed to adjust for confounding variables [16,17]. Infant weight at 28 days and 42 days were the dependent variables. Dummy variables of severe preeclampsia with and without IUGR, preeclampsia with and without IUGR, gestational hypertension with and without IUGR, normotensive status with and without IUGR, and other confounding variables were independent variables. The regression coefficients (β) are estimated by the method of least squares [16]. The statistical significance (p-value) of β was also tested. All statistical analyses were performed with SPSS 10.0 for Windows (SPSS Inc., Chicago, IL).
Results
Table 1 summarizes the demographic and reproductive characteristics of the women classified in each of the categories of the three PIH groups. Among the11,921 pregnant women, PIH occurred in 1,252 women (10.5 %). Mean maternal age at delivery was 25.8 years, 95.3 % of women were nulliparous. Almost all women gave birth at hospital (99.8 %). Mean (± SD) gestational age at delivery was 39.30 weeks (± 1.55 weeks), with a shorter gestational age for severe preeclampsia. The incidences of preterm birth (<37 weeks of gestation) and low birth weight (<2,500 g) were significantly higher among babies born to mothers with preeclampsia and severe preeclampsia than normotensive women. Infant complications occurred in 7 % of babies and were more frequent in preeclampsia and severe preeclampsia groups.
Table 1 Demographic and reproductive characteristics of study population by pregnancy-induced hypertension, Suzhou, China, 1989–1990
Subjects
Characteristics* No. % Normotensive
(N=10,669) % Gestational hypertension
(N=782) % Preeclampsia
(N=365) % Severe preeclampsia
(N=105) % Statistical significance
(χ2test)
Maternal age
≤30 11,230 94.2 94.6 90.3 91.5 94.3 0.000
> 30 691 5.8 5.4 9.7 8.5 5.7
Parity
Nulliparous 11,365 95.3 95.3 94.9 97.8 97.1 0.100
Multiparous 556 4.7 4.7 5.1 2.2 2.9
Sex
Male 6,026 50.5 50.8 48.6 47.4 55.2 0.290
Female 5,895 49.5 49.2 51.4 52.6 44.8
Preterm birth (<37 weeks)
No 11,527 96.7 96.6 98.2 96.7 93.3 0.023
Yes 394 3.3 3.4 1.8 3.3 6.7
Low birth weight (<2,500 g)
No 11,620 97.5 97.6 97.3 95.1 92.4 0.000
Yes 301 2.5 2.4 2.7 4.9 7.6
Mean gestational age (Weeks) 39.30 39.29 39.44 39.30 38.69 0.000 (Analysis of variance)
Place of delivery
Hospital 11,900 99.8 99.8 99.7 100 100 0.981
Home 11 0.1 0.1 0.1 0 0
BMI
< 24 11,012 92.8 93.1 90.0 89.6 93.3 0.005
24–28 426 3.6 3.4 5.3 5.8 4.8
> 28 432 3.6 3.5 4.7 4.6 1.9
Infant complications No Yes
No 10,989 93.1 93.1 90.9 87.0 88.5 0.000
Yes 810 6.9 6.4 9.1 13.0 11.5
* Excluding cases with missing information.
Table 2 presents the overall effects of PIH on infant growth at 28 and 42 days postpartum. The infant weights were statistically significantly lower in infants born to mothers with both preeclampsia and severe preeclampsia than infants born to normotensive mothers. However, IGPs were not different between groups. For example, at 42 days postpartum, weights were significantly lower for the preeclampsia and severe preeclampsia groups than for normotensive group (mean weight = 4,763 g and 4,679 g vs. 4,869 g, p < 0.001), but no evidence of catch-up growth in infants born to mothers with preeclampsia and severe preeclampsia (IGP = 47.7% and 48.3% vs. 49.7%, p = 0.618).
Table 2 Pregnancy-induced hypertension and infant weight at 28 and 42 days postpartum, univariate analysis
Infant growth 28 days postpartum Infant growth 42 days postpartum
Mean birth weight (g) SD† Infant weight (g) SD Infant growth percent 1 (%) Infant weight (g) SD Infant growth percent 2 (%)
Normotensive (N=10,669) 3252.4 (Referent) 416,1 4088.8 (Referent) 496.2 25.7 4869.1 (Referent) 609.9 49.7
GH# (N=782) 3288.8 448.9 4084.1 540.4 24.2 4878.6 696.2 48.3
PE¶ (N=365) 3224.9 465.8 4018.6* 513.7 24.6 4763.8** 631.8 47.7
Severe PE (N=105) 3170.9 502.9 3941.9* 564.9 24.3 4679.9** 727.3 47.6
Total (N=11,921) 3253.2 420.9 4085.0 500.7 25.6 4864.8 618.2 49.5
* p < 0.05, ** p < 0.01
1 [(Infant weight 28 days - birth weight) / birth weight] × 100 %, 2 [(Infant weight 42 days - birth weight) / birth weight] × 100 %
† SD: standard deviation, #GH: gestational hypertension, ¶PE: preeclampsia.
Table 3 presents the effect of PIH on growth at 28 and 42 days postpartum, stratified for the presence or absence of intrauterine growth restriction (IUGR). Infant weights were not different between infants born to mothers with any types of PIH without IUGR and normotensive babies without IUGR, and IGPs were not different between any types of PIH and non-IUGR normotensive control. Conversely, infant weights were markedly lower in all infants with IUGR than normotensive controls without IUGR. Infant weight gains and IGPs were higher in any types of PIH and normotensive control with IUGR than in their counterpart groups without IUGR. For example, at 42 days postpartum, in the absence of IUGR, there were no differences in infant weight between any of the types of PIH (ranging from 4,801 g to 4,929 g) and non-IUGR normotensive group (4,905 g). The IGPs were not different between any types of PIH (ranging from 46.2 % to 47.0 %) and non-IUGR normotensive control (48.6%). However, in the presence of IUGR, infant weights were markedly lower in the three types of PIH (ranging from 3,882 g to 4,231 g) and in normotensive (4,255 g) groups than in non-IUGR normotensive control group (4,905 g), p < 0.001. The IGPs were significantly higher (ranging from 59.8% to 71.3%) as compared to the reference group (48.8%), suggesting a significant catch-up growth.
Table 3 Pregnancy-induced hypertension and infant weight at 28 and 42 days postpartum by newborn IUGR status, univariate analysis
Infant growth 28 days postpartum Infant growth 42 days postpartum
Mean birth weight (SD†) (g) Infant weight (SD) (g) Weight gain (g) Infant growth percent 1 (%) Infant weight (SD) (g) Weight gain (g) Infant growth percent 2 (%)
Normotensive / non-IUGR‡ (N=10,067) 3296.6 (382.0) (Referent) 4126.9 (471.3) (Referent) 830.3 25.2 (Referent) 4905.8 (592.9) (Referent) 1609.2 48.8 (Referent)
Normotensive / IUGR (N=602) 2513.2 (219.9)** 3451.1 (466.9) ** 937.9 37.3** 4255.8 (563.3)** 1742.6 69.3**
GH# / non-IUGR (N=725) 3353.1 (395.4)** 4143.6 (500.4) 790.5 23.6 4929.4 (665.8) 1576.3 47.0
GH / IUGR (N=57) 2469.8 (230.9)** 3327.4 (454.8)** 857.5 34.7** 4231.6 (754.3)** 1761.8 71.3**
PE¶/ non-IUGR (N=326) 3314.9 (401.8) 4091.3 (463.8) 776.4 23.4 4853.1 (572.9) 1537.2 46.4
PE / IUGR (N=39) 2472.1 (215.6)** 3410.4 (512.9)** 938.3 37.9** 4025.4 (624.2)** 1553.3 62.8**
Severe PE / non-IUGR (N=91) 3285.2 (434.8) 4037.4 (518.9) 752.2 22.9 4801.8 (682.8) 1516.6 46.2
Severe PE / IUGR (N=14) 2428.6 (171.8) ** 3321.4 (459.0) ** 892.8 36.8** 3882.1 (463.5)** 1453.6 59.8
Total (N=11,921) 3253.2 (420.9) 4085.0 (500.7) 831.8 25.6 4864.8 (618.2) 1611.6 49.5
* p < 0.05, ** p < 0.01
1 [(Infant weight 28 days - birth weight) / birth weight] × 100 %, 2 [(Infant weight 42 days - birth weight) / birth weight] × 100 %
#GH: gestational hypertension, ¶PE: preeclampsia, ‡ IUGR: intrauterine growth restriction.
† SD: standard deviation
Table 4 presents mean birth weight differences, infant weight differences at 28 days and 42 days postpartum between various types of PIH with and without IUGR and the normotensive control group without IUGR, as well as the corresponding regression coefficients (i.e., the weight differences after adjustment for confounders). The results of multivariate linear regression were consistent with those of univariate analysis (Table 3). After adjustment for confounding variables, IUGR babies born to any of the PIH groups had significantly lower infant weights at 28 and 42 days postpartum. For example, there was a 903 g (1,023 g before the adjustment for confounders) reduction in infant weight at 42 days postpartum in IUGR babies born to severe preeclamptic mothers relative to non-IUGR babies born to mothers with normal blood pressure, although the IGP was higher in the IUGR babies.
Table 4 Pregnancy-induced hypertension and infant weight at 28 and 42 days postpartum, multivariate analysis
Mean birth Infant weight 28 days postpartum Infant weight 42 days postpartum
Mean birth weight difference (g) β (SE)§ Infant weight difference (g) β (SE) Infant weight difference (g) β (SE)
Normotensive / non-IUGR‡ (N=10,067) Ref. Ref. Ref. Ref. Ref. Ref.
Normotensive / IUGR (N=602) 783.4** 776.2 (15.4)** 675.8** 640.0 (19.4)** 650.0** 619.4 (25.2)**
GH# / non-IUGR (N=725) -56.6** -34.0 (14.0) -16.7 -4.4 (18.6) -23.7 -12.8 (22.8)
GH / IUGR (N=57) 826.7** 825.4 (49.0)** 799.5** 815.1 (61.8)** 674.2** 678.9 (80.1)**
PE¶/ non-IUGR (N=326) -18. 4 -6.97 (20.5) 35.6 38.0 (25.8) 53.6 55.4 (33.5)
PE / IUGR (N=39) 824.5** 795.9 (60.3)** 716.5** 654.1 (76.0)** 880.4** 835.2 (98.7)**
Severe PE / non-IUGR (N=91) 11.4 -20.0 (38.8) 89.5 39.4 (48.9) 104.0 69.9 (63.5)
Severe PE / IUGR (N=14) 868.0** 796.8 (92.4)** 805.5 674.7 (116.5)** 1023.6** 903.0 (151.2)**
* p < 0.05; ** p < 0.01
§β, coefficient, SE, standard error; adjusted for maternal age, body mass index, diabetes, infant's sex, maternal anemia, gestational age
#GH: gestational hypertension, ¶PE: preeclampsia, ‡ IUGR: intrauterine growth restriction
Discussion
To our knowledge, there is no previous study that has examined the effect of PIH on infant growth in the early infant period. Our study found that when babies were born with IUGR, all PIH groups had lower infant weight and significant 'catch-up' growth at 28 and 42 days postpartum. However, if babies were not born with IUGR, any type of PIH did not have detrimental effect on infant growth at 28 and 42 days postpartum. Our study suggests that PIH per se does not affect early infant growth.
The finding of different effects of PIH on early infant growth according to the presence of IUGR further supports the hypothesis that preeclampsia is a heterogeneous disorder and present at least two subtypes: IUGR vs. normal fetal growth preeclampsia [4-6]. These two subtypes of preeclampsia may have different pathogeneses, clinical manifestations and short and long term effects on both infants and mothers [4-7]. Patients with preeclampsia who have IUGR babies may have placental dysfunction such as reduced utero-placental perfusion as the common pathogeneses. The present study shows this group of infants has sustained lower weight in the early infant period. In contrast, patients with preeclampsia who have babies with normal fetal growth may not have the significant placental dysfunction, thus have normal intrauterine as well as early infant growth.
Newborns with poor intrauterine growth often demonstrate postnatal catch-up growth [18,19]. Our study suggests such a catch-up growth is initiated soon after birth. The impact of catch-up growth on infant's long-term health remains unclear. There is a dilemma as to whether this catch-up growth, either inherent to IUGR babies or through growth promotion programs as promoted in many developing countries, is good or bad. In short term, such a catch-up growth enables infants to accelerate growth in order to reach their normal growth curve, resulting in reduced infant morbidity and mortality [19]. However, it has been suggested that catch-up growth could have a detrimental influence, leading to the onset of certain chronic diseases in later life [20-23]. The crucial time for the development of long-term consequences is the early postnatal period when catch-up growth occurs in around 80 % of IUGR babies [18,22]. Some studies [8,12,20,22] found that hypertension, cardiovascular diseases and mellitus diabetes in adult life were correlated with the existence of a low birth weight and a catch-up growth in the early postnatal period. The hypothesis of the fetal origins of adult disease [10,24,25] may be redefined to consider the impact of the early infant period on the risk of adult diseases [22,23]. Our study indicates that for the infants born to mothers with various types of PIH, only those babies with IUGR showed a catch-up growth. Future long-term follow up studies are needed to examine if IUGR babies born to PIH mothers are at higher risk to develop certain adult diseases later in life than those non-IUGR babies born to PIH mothers.
Several limitations of this study have to be addressed. First, our database does not have information on important factors such as maternal smoking and breastfeeding. The prevalence of smoking is high for men in China, however, reported smoking is rare among women (<0.5%) [26]. Therefore, our results are not likely to be biased by not controlling for smoking. To our knowledge, almost all women breast-fed their infants at that time. However, it is possible that the presence of PIH or IUGR affected breastfeeding and thereby early infant growth. Second, the database has many cases with missing information on weight at 28 days and/or 42 days postpartum. We compared these missing cases with those pregnant women remained for analysis. The rate of preterm birth and low birth weight were higher in missing cases than in the remained study population. This is partly due to women who had perinatal deaths up to 28 days postpartum (most of those babies were preterm, IUGR, or low birth weight) and thus had no information on infant weight at 28 and 42 days postpartum were classified into missing cases. This is the reason why the study population has fewer preterm birth, low birth weight and intrauterine restriction infants. However, there were no significant differences in demographic and reproductive characteristics such as pregnancy-induced hypertension, maternal age, parity, number of prenatal visits, infant's sex and gestational age. Third, weight can be a good growth indicator but, ideally, should be correlated to height and head circumference [27], in order to differentiate between symmetrical and non-symmetrical IUGR. We only considered weight as a measure of growth pattern because it was the only available variable.
Conclusion
The effect of PIH on early infant growth is dependent on whether or not a baby is intrauterine growth restricted. IUGR secondary to PIH is associated with significant catch-up growth in early infant period. Therefore, we speculate that IUGR babies born to mothers with PIH may be at higher risk to develop certain chronic diseases in their later life. More studies in North American or European populations are needed to confirm these results.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
Each author has contributed to the concept, the design and the analysis on the study and to the writing of the draft. All authors read and approved the final version.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
We thank Dr. Zirong Guo, Department of Epidemiology of Suzhou University Medical College (China) for data preparation.
==== Refs
Report of the National High Blood Pressure Education Program Report of the National High Blood Pressure Education Program Working Group on High Blood Pressure in Pregnancy Am J Obstet Gynecol 2000 183 S1 S22. 10.1067/mob.2000.107928
Zhang J Zeisler J Hatch MC Berkowitz G Epidemiology of pregnancy-induced hypertension Epidemiol Rev 1997 19 218 232 9494784
Xiong X Mayes D Demianczuk N Olson DM Davidge ST Newburn-Cook C Saunders LD Impact of pregnancy-induced hypertension on fetal growth Am J Obstet Gynecol 1999 180 207 213 9914605
Xiong X Demianczuk NN Buekens P Saunders LD Association of preeclampsia with high birth weight for age Am J Obstet Gynecol 2000 183 148 155 10920323 10.1067/mob.2000.105735
Xiong X Fraser WD Reply: Association of preeclampsia with high birth weight for gestational age (Letter to the Editors) Am J Obstet Gynecol 2002 186 1105 1106 12015546
Xiong X Demianczuk NN Saunders LD Wang FL Fraser WD Impact of preeclampsia and gestational hypertension on birth weight by gestational age Am J Epidemiol 2002 155 203 209 11821244 10.1093/aje/155.3.203
Rasmussen S Irgens LM Fetal growth and body proportion in preeclampsia Obstet Gynecol 2003 101 575 583 12636965 10.1016/S0029-7844(02)03071-5
Law CM Barker DJ Bull AR Osmond C Maternal and fetal influences on blood pressure Arch Dis Child 1991 66 1291 1295 1755640
Barker DJ Intrauterine programming of adult disease Mol Med Today 1995 1 418 423 9415190 10.1016/S1357-4310(95)90793-9
Barker DJ Maternal nutrition, fetal nutrition, and disease in later life Nutrition 1997 13 807 813 9290095 10.1016/S0899-9007(97)00193-7
Kramer MS Joseph KS Enigma of fetal/infant-origins hypothesis Lancet 1996 348 1254 1255 8909372 10.1016/S0140-6736(05)65750-9
Joseph KS Kramer MS Review of the evidence on fetal and early childhood antecedents of adult chronic disease Epidemiol Rev 1996 18 158 174 9021310
Xiong X Fraser WD Impact of pregnancy-induced hypertension on birthweight by gestational week Paediatrc Perinatal Epidemiol 2004 18 186 191 10.1111/j.1365-3016.2004.00553.x
National epidemiological investigation group on pregnancy-induced hypertension National epidemiological investigation of pregnancy-induced hypertension Chinese J Obstet Gynecol 1991 6 67 70
Chan SG Zhou JR Birth weight distribution in Shanghai Chinese J Obstet Gynecol 1980 15 198 201
Kahn HA Sempos CT Statistical methods in epidemiology 1989 New York: NY, Oxford University Press 137 148
Kleinbaum DG Kupper LL Morgenstern H Epidemiologic research: Principal and quantitative methods 1982 New York, Van Nostrand Reinhold 181 280
Karlberg J Albertsson-Wikland K Growth in full-term small-for-gestational-age infants: from birth to final height Pediatr Res 1995 38 733 739 8552442
Victora CG Barros FC Horta BL Martorell R Short-term benefits of catch-up growth for small-for-gestational-age infants Int J Epidemiol 2001 30 1325 1330 11821340 10.1093/ije/30.6.1325
Huxley RR Shiell AW Law CM The role of size at birth and postnatal catch-up growth in determining systolic blood pressure: a systematic review of the literature J Hypertens 2000 18 815 831 10930178 10.1097/00004872-200018070-00002
Falkner B Hulman S Kushner H Birth weight versus childhood growth as determinants of adult blood pressure Hypertension 1998 31 145 150 9449406
Cianfarani S Germani D Branca F Low birthweight and adult insulin resistance: the "catch-up growth" hypothesis Arch Dis Child Fetal Neonatal Ed 1999 81 F71 3 10375369
Singhal A Fewtrell M Cole TJ Lucas A Low nutrient intake and early growth for later insulin resistance in adolescents born preterm Lancet 2003 361 1089 1097 12672313 10.1016/S0140-6736(03)12895-4
Barker DJ In utero programming of chronic disease Clin Sci (Lond) 1998 95 115 128 9680492
Barker DJ Eriksson JG Forsen T Osmond C Fetal origins of adult disease: strength of effects and biological basis Int J Epidemiol 2002 31 1235 1239 12540728 10.1093/ije/31.6.1235
Yu JJ Mattson ME Boyd GM al. A comparison of smoking patterns in the People's Republic of China with the United States: an impending health catastrophe in the middle kingdom JAMA 1990 264 1575 1579 2395200 10.1001/jama.264.12.1575
Gibson AT Carney S Cavazzoni E Wales JK Neonatal and post-natal growth Horm Res 2000 53 Suppl 1 42 49 10895042 10.1159/000053204
| 15907210 | PMC1168902 | CC BY | 2021-01-04 16:32:05 | no | BMC Pregnancy Childbirth. 2005 May 20; 5:10 | utf-8 | BMC Pregnancy Childbirth | 2,005 | 10.1186/1471-2393-5-10 | oa_comm |
==== Front
BMC Public HealthBMC Public Health1471-2458BioMed Central London 1471-2458-5-481590451310.1186/1471-2458-5-48Research ArticleScreening for asthma in Cantonese-speaking immigrant children Greenfield Robyn O [email protected] Angela C [email protected] Roland [email protected] Doug [email protected] Department of Public Health and Family Medicine, Tufts University School of Medicine; Boston, USA2 University College of Citizenship and Public Service, Tufts University, Medford, USA3 Department of Pediatrics, South Cove Community Health Center, Boston, USA4 Department of Public Health and Family Medicine, Tufts University School of Medicine, Boston, USA2005 17 5 2005 5 48 48 16 11 2004 17 5 2005 Copyright © 2005 Greenfield et al; licensee BioMed Central Ltd.2005Greenfield et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Asthma prevalence among Chinese immigrant children is poorly understood and attempts to screen these children have produced varied outcomes. We sought to learn how to improve screening for asthma in Chinese immigrant children.
Methods
Children (n = 152) were administered the Brief Pediatric Asthma Screen in either Cantonese or English, they then viewed and reacted to a video showing people wheezing and subsequently took a pulmonary function test.
Results
The diagnosed asthma prevalence for our study population was 27.0%, with another 5.3% having possible undiagnosed asthma. Very few children had spirometry findings below normal. In multivariate analysis, being native born (p = 0.002) and having a family history of asthma (p = 0.003) were statistically associated with diagnosis of asthma. After viewing the video, 35.6% of respondents indicated that the images differed from their conception of wheezing. Of four translations of the word "wheeze" no single word was chosen by a majority.
Conclusion
Our findings suggest that asthma diagnoses are higher for Chinese children who were born in the US suggesting that desegregation of data might reveal at risk subpopulations. Care needs to be taken when diagnosing asthma for Cantonese speakers because of the centrality of the word wheeze and the challenges of translation.
==== Body
Background
Asthma continues to be a key challenge in the field of pediatric health. With nine million children diagnosed with asthma in the United States, it is the leading cause of school absences, emergency room visits and hospitalizations among American youth [1,2]. Studies of asthma prevalence however, have tended to neglect the Asian-American population, leaving the burden of asthma faced by this population largely unknown [3,4].
Epidemiological studies of asthma have tended to utilize written questionnaires in English or Spanish, focusing on symptoms [1,5]. In the few studies that have included Asian-American children, lower prevalence of diagnosed asthma than in comparable populations has usually been found [1,3,4]. When included as part of "other races" in the Center for Disease Control report, Asian-American children, were found to have an asthma prevalence of 11.4% [1]. Such results come into conflict with results obtained using other, non-written methods. For example a study published in 2002 found 47.1% of Asian-American third-graders in New Jersey to have abnormal spirometry [6].
Recent studies suggest that lack of general asthma knowledge as well as a misunderstanding of the word "wheeze" may affect detection of asthma in Asian children [3,7]. A study of parents of asthmatic children in Nanjing, China found 54.7% of parents had "poor" knowledge of the disease. Parents were unfamiliar with the triggers of asthmatic attacks, the pathology of wheezing and proper management of the disease in general [7]. In a large international study comparing written questionnaire responses and reaction to a video demonstrating wheezing [5], Cantonese speakers showed less correlation between the written and video questionnaire then did English or Spanish speaking subjects, with the inclusion of the video increasing the number of positive responses for Cantonese speakers.
The "gold standard" in asthma diagnosis consists of history, physical examination and spirometry. As the history portion relies heavily on questions utilizing the word "wheeze" and other symptoms of asthma, language could interfere with proper diagnosis.
The word "wheeze" has multiple Cantonese translations, each conveying a slightly different meaning. To our knowledge, previous studies of asthma among Chinese speakers have not reported which translation(s) they used. The translations that we have encountered are: 1) which means a sound from the throat, 2) () which means a sound from difficulty breathing, 3) which means a special sound from asthma and is the more professional expression which is used in medical books, and 4) which literally means a gasping sound made after crying.
A five-question instrument, the Brief Pediatric Asthma Screen (BPAS) has been validated as an additional means of screening for asthma. The BPAS also relies heavily on the use of the word "wheeze," thereby being subject to the same limitation [8]. Two previous studies have used Chinese translations of the BPAS in attempts to determine the prevalence of asthma in Asian-American immigrant children, yielding conflicting results [3,4]. Both studies offered the survey in English and Chinese. In the first study [4], conducted in 2002, parents of kindergarten through fifth grade students completed a self-administered written version of the BPAS. Using, , the professional term for wheezing, this study found the prevalence of diagnosed and possibly undiagnosed asthma to be 16% and 3%, respectively.
In the second study, the survey was administered orally, with surveyors physically demonstrating what they believed to be wheezing [3]. It should be noted that the demonstration more resembled labored breathing and therefore was not specific for asthma. As such, the prevalence of diagnosed asthma in the second study remained statistically the same at 15%, however the prevalence of possible undiagnosed asthma increased over six-fold to 18.6%.
This study seeks to improve the methodology for asthma screening in Chinese-American immigrant children. By use of the BPAS, a video demonstration of wheezing, and spirometry; the study compares the use of current methods to detect asthma in this population. As there were approximately one-half million hospitalizations for asthma in the US in 1995, effective detection of asthma is critical in patient care [9].
Methods
Sample
A convenience sample of 152 children ages 5–18, was recruited in the waiting room of the pediatrics department at South Cove Community Health Center in Boston, Massachusetts between June 16-July 23, 2004. Children with cough or fever, who were outside the specified age range, who did not speak either English or Cantonese or who had previously taken the screen were excluded from the study.
Procedures
The Tufts-New England Medical Center Institutional Review Board as well as the South Cove Community Health Center Board of Directors approved the study protocol. Consent was given orally at time of entry into the study from parents/grandparents/guardians of children less than 11 years of age and the child him/herself for years thereafter. Collected data was anonymous and de-identified. Families were provided with a written description of the study in their choice of English or Cantonese. The protocol was expanded mid-way through the study to include additional data collection. Data from both the "basic" and "expanded" protocol were analyzed and are presented in this paper.
Questionnaire
A written questionnaire was administered to all participants in the study as our primary tool for assessing asthma status. It was administered to the parent/grandparent/guardian if the child was younger than 11 years of age. Children ages 11–18, were asked to complete the questionnaire him/herself. The survey was written in English and translated into Chinese by one translator using traditional characters. A second translator then translated it back into English in order to check for accuracy. Respondents had the option of taking the survey in their choice of English or Cantonese. A bilingual English/Cantonese speaker (author ACL) orally administered the questionnaire and answered questions when prompted by the participant. The questionnaire consisted of 19 questions.
The majority of questions were demographic in nature. Questions were asked regarding the child's age, sex, place of birth, and length of residence in the United States. Preferred language was inferred from choice of Chinese or English surveys. For children under 11, this meant that it was the parent's preferred language, whereas for children over 11, it was the child's preferred language.
Information was collected on risk factors for asthma, including family smoking habits, highest level of education for parents (as a measure of socioeconomic status), allergies, asthma medication use and family history of asthma. The expanded questionnaire included questions relating to other medical conditions and non-asthma medication use. The remaining five questions in both the basic and expanded questionnaire were from the Brief Pediatric Asthma Screen (BPAS) [8] and were as follows:
1. Have you/your child ever been diagnosed by a doctor as having asthma?
2. Have you/your child ever had episodes of wheezing (whistling in the chest) in the last 12 months?
3. In the last 12 months, have you had/heard your child wheeze or cough during or after active play?
4. Other than a cold, in the last 12 months, have you/your child had a dry cough at night?
5. In the last 12 months, have you/your child been to a doctor, an emergency room or a hospital for wheezing?
This study used the translation for wheeze. Though this version literally means a gasping sound made after crying, it was chosen by a bilingual speaker with extensive experience in the Boston Chinatown community to represent wheezing when used in the context of asthma.
Categorization of asthmatic status
All completed questionnaires were categorized for asthmatic status as described in Wolf et al [8]. An affirmative answer to the first question was automatically categorized as "diagnosed asthma". An affirmative answer to the last question or two or more of questions 2–4, was categorized as "possible undiagnosed asthma." All other responses were considered "probably not asthmatic." For analysis of association between asthma and demographic factors, persons categorized as "possible undiagnosed asthma" were grouped with "probably not asthmatic" to create the non-asthmatic group. The BPAS was administered prior to the respondent's viewing of the video and thus, children were categorized based on the respondent's prior understanding of the word "wheeze."
Video
We asked all parents/grandparents/guardians or children to watch the "international" version (AVQ 3.0) of the International Studies of Asthma and Allergies in Childhood (ISAAC) Phase One study [5]. Our goal was to provide participants with a visual representation of wheezing on the assumption that they might not understand the concept of wheezing. This brief, one minute, video consists of the following five sequences:
1. "A young person seated with clearly audible wheezing, but without breathlessness and no evidence of airway obstruction
2. Exercise-induced wheezing
3. Waking at night with wheezing
4. Nocturnal coughing
5. Severe attack of asthma"
Respondents were asked if their previous understanding of wheezing on the BPAS corresponded to what they had viewed in the video. An answer of "yes" or "no" was recorded, as were any qualitative responses in regards to the concept of wheezing. Patients screened with the expanded protocol were then asked to re-answer questions 2–5 of the BPAS, basing their answers on the depiction of wheezing in the video. These patients were than categorized again based on their second set of answers to the BPAS. Detailed analyses of the second BPAS scoring are not presented. Cantonese speaking participants taking the expanded protocol were then asked which of the four Cantonese translations best matched the video's depiction of wheezing.
Spirometry
Pulmonary function testing was performed on all participants willing to attempt it using the ndd Model 2000 EasyOne™ Frontline Spirometer (ndd Medical Technologies, Andover, MA), an instrument whose performance correlates well with office-based spirometry [10]. We sought to use spirometry as an objective measure of asthma status. Standard, calibrated scales and stadiometers were used to determine height and weight. Each child was then categorized as underweight (<5th percentile), healthy weight (5–85th percentile), at risk for overweight (85th-95th percentile) or overweight (>95th percentile) using the CDC BMI growth charts for boys and girls ages 2–20. Categorization was performed twice, to ensure accuracy.
Spirometry was performed using standard procedures by trained technicians. The children's noses were sealed manually or by use of pediatric size spirometry nose clips. For analysis, we used only spirometry reported by the EasyOne™ software as having at least 2 acceptable maneuvers and FEV1 readings within 150 ml and FVC within 150 ml (score of "A" or "B"; EasyOne™, manual, undated). The parameters recorded were: percent predicted forced expiratory volume during the first second (FEV1), forced vital capacity (FVC), and FEV1 to FVC ratio (FEV1/FVC). Percent predicted values are based upon the results of the NHANES III study as described in Hankinson et. al. without adjusting for ethnicity [11].
Criteria for diagnosis of obstructive lung disease were:
FEV1 < 80% predicted and FVC < 80% predicted
FEV1/FVC < 75%
Numerical values correspond to those recommended by the National Asthma Education and Prevention Program of the National Institutes of Health: National Heart, Lung and Blood Institute [12]. Results of the spirometry were given to the patient and his/her physician so that they could be incorporated into his/her pediatric appointment.
Data management & analysis
Data was double entered into SPSS version 11.5 and crosschecked for errors by reference to the original hard copies of the surveys and data forms. Chi Square tests were used to generate odds ratios (OR), to demonstrate the likelihood of being diagnosed as asthmatic versus being non-asthmatic for the following variables: birthplace, preferred language of respondent, paternal education, maternal education, smoking in the home, overweight status, allergies and family history of asthma. Due to small numbers of values below 80%, Fisher's exact test was used to examine the relationship of being diagnosed with asthma versus being non-asthmatic with FEV1 and FVC values. We then performed a forward step-wise binomial logistic regression to create a model predicting the likelihood of being diagnosed with asthma based on the following independent variables: preferred language of respondent, foreign born, paternal and maternal education, sex, age, country of origin, smoking in the home, allergy, family history of asthma and overweight as possible predictors of diagnosis of asthma. We again used Chi Square tests to elicit odds ratios for having an understanding of wheezing consistent with the video's representation versus inconsistent for the following independent variables: Birthplace, preferred language of respondent, asthmatic status, paternal and maternal education. We performed a forward step-wise binary regression to create a model predictive of consistent or inconsistent understanding of the word wheeze with that portrayed in the video using the following variables: preferred language of respondent, sex, age, overweight, country of origin, foreign born, smoking in the home, allergy, family history of asthma and diagnosis of asthma. For those participants of the expanded protocol we used Mc Nemar's test to examine pre-video BPAS scores with post-video BPAS scores. Statistical significance was set at the p = 0.05 level and borderline significance was set at p ≤ 0.10 for all tests.
Results
Participant demographics
Table 1 presents the demographic characteristics of the full study population (n = 152) as well as three subsets, those children completing the basic protocol (n = 63), those completing the expanded protocol (n = 89) and those with acceptable spirometry results (n = 67). Based on BPAS scores, diagnosed asthma prevalence for the full sample was 27.0% with another 5.3% having possible undiagnosed asthma. Children completing the basic and expanded protocols were similar in most ways, however the expanded protocol subset had statistically higher prevalence of family history of asthma (23.9% vs. 11.1%) and lower prevalence of paternal (50.0% vs. 77.1%) and maternal (52.1% vs. 74.5%) education at high school level or above. The subset of children that completed acceptable spirometry did not differ from the total study population demographically.
Table 1 Demographic characteristics of the study population and subsets of the population used in the analyses in this study.
Basic Protocol (n = 63) Expanded Protocol (n = 89) Total (n = 152) Spirometry (n= 67)
Age
Less than 11 39.7% (25) 37.1% (33) 38.2% (58) 40.3% (27)
11 and older 60.3% (38) 62.9% (56) 61.8% (94) 59.7% (40)
Sex
Female 50.8% (32) 50.6% (45) 50.7% (77) 58.2% (39)
Male 49.2% (31) 49.4% (44) 49.3% (75) 41.8% (28)
Birthplace
Native-born 57.1% (36) 50.6% (45) 53.3% (81) 59.7% (40)
Foreign-born 42.9% (27) 49.4% (44) 46.7% (71) 40.3% (27)
Preferred Language
Cantonese 61.9% (39) 53.9% (48) 57.2% (87) 55.2% (37)
English 38.1% (24) 46.1% (41) 42.8% (65) 44.8% (30)
Smoking
Smoker in the home 38.1% (24) 35.2% (31) 36.4% (55) 33.3% (22)
Smoke-free home 61.9% (39) 64.8% (57) 63.6% (96) 66.7% (44)
Allergies
Yes 37.1% (23) 37.5% (33) 37.3% (56) 37.9% (25)
No 61.9% (39) 62.5% (55) 62.7% (94) 62.1% (41)
Family Asthma
Yes 11.1% (7)* 23.9% (21)* 18.5% (28) 19.4% (13)
No 88.9% (56) 76.1% (67) 81.5% (123) 80.6% (54)
Paternal Education
Did not complete high school. 22.9% (11)* 50.0% (34)* 38.8% (45) 39.0% (23)
Completed high school or above 77.1% (37) 50.0% (34) 61.2% (71) 61.0% (36)
Maternal Education
Did not complete high school 25.5% (13)* 47.8% (33)* 38.3% (46) 41.4% (24)
Completed high school or above 74.5% (38) 52.1% (36) 61.7% (74) 58.6% (34)
BPAS Score
Diagnosed asthma 22.2% (14) 30.3% (27) 27.0% (41) 26.9% (18)
Possible undiagnosed asthma 7.9% (5) 3.4% (3) 5.3% (8) 3.0% (2)
Probably not asthmatic 69.8% (44) 66.3% (59) 67.8% (103) 70.1% (47)
* p <.05
Descriptive analysis
Table 2 lists frequencies, ORs and p-values for associations between key characteristics of the study population along with prevalence of diagnosis of asthma. Being foreign born as compared to native born was associated statistically with a lower prevalence of diagnosed asthma (11.3% vs. 40.7%, p = 0.001). Reporting a family history of asthma was associated with a higher prevalence of asthma (53.6% vs. 20.3%, p = 0.001). Borderline statistical associations with diagnosis of asthma were found for lower maternal education, which was associated with lower asthma prevalence (17.4% vs. 31.1%, p = 0.09) and the presence of allergies in the child, which was associated with higher prevalence of asthma (35.7% vs. 21.3%, p = 0.05). There was no statistical association for preferred language of respondent (a variable that combines the parent/grandparent/guardian for children less than 11 and the child him/herself for those over 11 years of age), paternal education, smoking in the home, body mass index, or both FEV1 and FVC below 80% of predicted. We could not test associations between asthma diagnosis and abnormal FEV1/FVC ratio because there were only 3 FEV1/FVC ratios below 75%. Associations between FEV1 and sex, foreign born, preferred language of respondent, smoking in the home, allergies, family history of asthma, BPAS score and paternal and maternal education were not statistically significant (not shown).
Table 2 Comparison of prevalence of diagnosed asthmatics and non-asthmatics for the total sample (n = 152) by demographic categories.
Diagnosed Asthmatics (n = 41) Non-asthmatics (n = 111) OR & 95% CI P value
Birthplace
Native-born 40.7% (33) 59.3% (48) 5.41 (2.29 – 12.80) <0.001
Foreign-born 11.3% (8) 88.7% (63)
Preferred Language
Cantonese 24.1% (21) 75.9% (66) 0.72 (0.35 – 1.47) 0.36
English 30.8% (20) 69.2% (45)
Paternal Education
Completed high school or above 25.4% (18) 74.6% (53) 0.75 (0.33 – 1.72) 0.66
Did not complete high school. 31.1% (14) 68.9% (31)
Maternal Education
Completed high school or above 31.1% (23) 68.9% (51) 2.14 (0.86 – 5.31) 0.09
Did not complete high school 17.4% (8) 82.6% (38)
Smoking
Smoker in the home 27.3% (15) 72.7% (40) 1.01 (0.48 – 2.13) 0.98
Smoke-free home 27.1% (26) 72.9% (70)
Body Mass Index (BMI)
≥ 85 percentile 34.1% (15) 65.9% (29) 1.61 (0.75 – 3.51) 0.22
<85 percentile 24.2% (24) 75.8% (75)
Allergies
Allergic 35.7% (20) 64.3% (36) 2.06 (0.98 – 4.29) 0.05
Non-allergic 21.3% (20) 78.7% (74)
Family Asthma
Asthma 53.6% (15) 46.4% (13) 4.52 (1.91 – 10.72) <0.001
No asthma 20.3% (25) 79.7% (98)
FEV1 and FVC
>80% 25.8% (16) 74.2% (46) 0.89 (0.27 – 2.95) 1.00**
≤80% 40.0% (2) 60.0% (3)
* Odds ratios were computed using Chi-Square tests and are reflective of the likelihood of being diagnosed with asthma for each of the stated demographic variables.
**Fisher's exact test.
Multivariate analysis
We considered preferred language of respondent, foreign born, paternal and maternal education, sex, age, country of origin, smoking in the home, allergy, family history of asthma and overweight as possible predictors of diagnosis of asthma in a forward stepwise binary logistic regression. Only being native born and having a family history of asthma were statistically significant in the model (p = 0.002 and p = 0.003 respectively), both being associated with higher prevalence of asthma. Because of substantial missing data on parental and maternal education, we also ran the regression leaving these variables out of the analysis. Doing so did not qualitatively change the result (not shown).
Video screening
Participants were asked to indicate whether or not the video portrayal of wheezing was different from their prior understanding (Table 3). About thirty-six percent (35.6%) indicated that the video was different from their conception of wheeze. Cantonese speakers were more likely to report an inconsistency than were English speakers (47.6% vs. 20.0%, p = 0.001). In a forward stepwise binary logistic regression that included preferred language of respondent, sex, age, overweight, country of origin, foreign born, smoking in the home, allergy, family history of asthma and diagnosis of asthma, Cantonese speakers and overweight children were more likely to say that the video portrayal of wheezing was different from their prior understanding (p < 0.001 and p = 0.045 respectively). For those completing the expanded protocol, post-video BPAS scores were compared to pre-video BPAS scores using Mc Nemar's test, the results were not statistically significant.
Table 3 Consistency of understanding wheezing between the video and questionnaire for the total sample (n = 149; 3 missing).
Consistent Inconsistent OR & 95% CI* P value
Total 64.4% (96) 35.6% (53)
Birthplace
Native-born 68.4% (54) 31.6% (25) 1.44 (0.73 – 2.82) 0.288
Foreign-born 60.0% (42) 40.0% (28)
Preferred Language
Cantonese 52.4% (44) 47.6% (40) 0.28 (0.13 – 0.58) <0.001
English 80.0% (52) 20.0% (13)
Asthma Diagnosis
Asthmatic 60.0% (24) 40.0% (16) 0.77 (0.37 – 1.63) 0.494
Non-asthmatic 66.1% (72) 33.9% (37)
Paternal Education
Did not complete high school. 58.1% (25) 41.9% (18) 1.33 (0.61 – 2.88) 0.756
Completed high school or above 64.8% (46) 35.2% (25)
Maternal Education
Did not complete high school 54.5% (24) 45.5% (20) 1.54 (0.72 – 3.30) 0.130
Completed high school or above 64.9% (48) 35.1% (26)
*Odds ratios were computed using Chi-Square tests and are reflective of the likelihood of having an understanding of the word wheeze consistent or inconsistent with the video's depiction for each of the stated variables.
Translation of "wheeze"
The forty-seven (47) Cantonese-speaking respondents completing the expanded protocol rated four choices of Cantonese translations of the English word "wheeze" (Figure 1). "Sound from the throat" was preferred by 46.8%, "sound from difficulty breathing" was preferred by 25.5%, the "professional term for asthma" was preferred by 10.6% and "gasping sound made after crying" was preferred by 17% of respondents.
Figure 1 Preferred translation of "wheeze" for respondents in the expanded protocol (n = 47).
Discussion
Limitations
There are several limitations to our study. We did not ask about smoking by the children themselves, but limited tests of exhaled CO (not shown) suggested that at least a couple smoked. Our measure for socio-economic status (SES) was imperfect, as we had a high non-response rate for the questions of paternal and maternal education level. In most instances this was due to inability of children to recall their parents' education level, but interpretation of educational level may also be limited by the fact that educational systems vary between the US and China. Our classification of preferred language by the parent's choice rather than the child's for children under 11 did not necessarily reflect the preferred language of the child.
Our choice of Cantonese wording for "wheeze" turned out to be one of the less popular options, despite our having introduced it during the BPAS screenings. It is possible that if we had used the most popular choice that it would have improved our BPAS screening. In addition, qualitative reaction of respondents was that the asthma events depicted in the video were more extreme than what the respondents thought of as wheeze. We would suggest that the video might be best described as depictions of "asthma attacks" rather than solely wheezing. Inclusion of spirometry was not an effective tool for assessing asthma status. Possibly the addition of a bronchodilator would have improved its utility.
Our results are not necessarily generalizable because we had a convenience sample from a health clinic waiting room and screened only families that spoke English or Cantonese.
Interpretation
The population of Chinese-American children that we enrolled in the study reported high prevalence of diagnosed asthma, but appeared to be clinically stable at the time of the screening. By screening out children who were coughing on the day of the screening, we may have underestimated overall asthma prevalence and prevalence of active asthma at screening. Few of their spirometry results were below 75% for FEV1/FVC and few were below 80% for FEV1 and FVC. It is worth noting that abnormal spirometry is relatively uncommon, even among children diagnosed with asthma [13].
Only 41.5% of the children reported to have diagnosed with asthma would have been categorized as asthmatic by the other four questions in the BPAS screening. We cannot distinguish between the possibilities that there could be misdiagnosis of asthma as compared to prevalent mild or well-controlled asthma. For those children with diagnosed asthma, who would have been picked up by the BPAS, only 7.3% reported use of asthma medication on the day of their screening. Because we did not distinguish intermittent from persistent asthma and we asked only about medication use on the day of screening, we cannot state with certainty what percentage are not receiving optimal care.
We found that asthmatic children were more likely to have allergies and more likely to have a family history of asthma. Both associations are well supported in the literature [14] suggesting that our study population was similar in this way to other populations.
Our strongest finding was that being born in the US was highly predictive of having diagnosed asthma, which suggests that with the Asian-American immigrant population there may be a more vulnerable subpopulation visible only when data is disaggregated. We were unable to determine whether this is a function of true asthma prevalence or differential diagnosis. The BPAS screen showed only 5.3% "possible undiagnosed asthma" cases, suggesting that there is little undiagnosed asthma consistent with the study of Lee et al. [4]. However, difficulty in translating of the word "wheeze" into Cantonese and its centrality in the BPAS leaves ample room for uncertainty about the true prevalence of undiagnosed asthma.
When screening Cantonese-speaking children for asthma we first would suggest using the translation of wheeze that literally means "a sound from the throat". However, we would urge caregivers to also try other translations, as there was not a single clear choice among our study population. Second, and related to the first, we would suggest that the concept of wheezing is not well-understood or popularized among Cantonese-speakers. This, combined with a low level of knowledge about asthma in general, [7] means that the provider needs to be careful when taking a medical history and rely less on the obvious symptom, wheezing. Even for providers treating diagnosed asthmatic children from Cantonese speaking families, we would suggest extensive follow-up to ensure proper understanding and compliance.
Future studies
There is a need to conduct asthma studies in the Chinese-American population that are free of the limitations of our data collection. This would include asking about children's smoking behavior, use of a better surrogate for socio-economic status (possibly parental occupation, which might be more easily recalled by children than education level), use of the more popular term for wheeze ("sound from the throat") in written or oral screening, and use of a video demonstration with less severe depictions of wheezing.
Additionally, studies are needed to confirm and explain the dramatically different prevalence of asthma between foreign and US born Chinese-Americans that we found. Potential hypotheses for the difference include: differential diagnosis due to language and cultural differences and differences in environmental exposures. Interestingly, exposure to Hepatitis A, a virus more common in China, has been suggested to be protective against the future development of asthma via interaction with the TIM1 gene [15]. If this turns out to be the case, it would suggest a biological cause could explain at least part of the difference in asthma prevalence.
Conclusion
We hope that this paper raises interest in and prompts examination of asthma among Chinese-American populations. There is a prevailing assumption that asthma is not a problem in this population. If nothing else, our study should bring the validity of such an assumption under scrutiny and raise awareness of the lack of general asthma knowledge in this community. In future studies examining prevalence among Chinese-Americans it is important to consider that prevalence among US born Chinese-Americans appears to be significantly higher than prevalence among foreign-born Chinese-Americans. Failure to desegregate data along these lines may mask the high prevalence of asthma within the sub-group. For both research and clinical practice purposes, the emphasis of cultural understanding needs to be explored. Because of asthma's commonplace stature within American culture at this time, it is easy to take one's level of understanding for granted, thereby missing a potentially life-threatening condition. While we raise this concern with respect to the Chinese-American population, it worth considering that it may hold true for other population groups as well.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
ROG participated in the design of the study, helped supervise the fieldwork, conducted data management, conducted the statistical analysis and took the lead in writing the manuscript and assisted in editing it. ACL conducted the field data collection, participated in data management, participated in the analysis and assisted with writing of the manuscript. RT assisted with design of the study, helped supervise the fieldwork, contributed to interpretation of findings and assisted with writing and editing the manuscript. DB provided overall direction to the study, supervised data collection, management and analysis, and participated in writing and editing the manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
The authors wish to thank South Cove Community Health Center, Eugene Welch and the doctors, nurses and staff including: Sherrie Zhang, MD., Vivian Tsuei, MD., Ingrid Henar, MD., MPH, Chia-Mei Lu, Irene Chin, Yanty Leung, Chung He, Qi-Long Fun, Shu Lin, and Wendy Wong. We are indebted to the parents and children who participated in the surveys. We thank Weibo Lu for her expertise in translating our questionnaires and Karen Lee for providing oral translations. We thank Lois Doerr, PNP, of Boston Medical Center for instructing the research team in spirometry coaching techniques. We would also like to thank Cato Hiu for his assistance. William Rand, Ph.D., of Tufts University School of Medicine provided helpful advice on analytical approach. Suzanne Steinbach of Boston Medical Center made useful comments on an early draft of the manuscript. This project was funded by Tufts University College of Citizenship and Public Service and Tufts University School of Medicine, Department of Family Medicine and Community Health.
==== Refs
Dev AN Schiller JS Tai DA Summary health statistics for U.S. children: National Health Interview Survey, 2002. National Center for Health Statistics Vital and Health Stat 2004 10
New England Asthma Regional Council Asthma in New England Dorchester, MA 2004
Chen C Brugge D Leung A Finkelman A Lu W Rand W Acculturation and asthma among Asian Americans 2004 aapi Nexus
Lee T Brugge D Francis C Fisher O Asthma prevalence among inner-city Asian American schoolchildren Public Health Reports 2003 118 215 20 12766216
Crane J Mallol J Beasley R Stewart A Asher MI ISAAC Agreement between written and video questions for comparing asthma symptoms in ISAAC Eur Respir J 2003 21 455 61 12662001
Freeman NCG Schneider D McGarvey P School-based screening for asthma in third-grade urban children: The Passaic asthma reduction effort survey Am J Public Health 2002 92 45 6 11772757
Zhao X Furber S Bauman A Asthma knowledge and medication compliance among parents of asthmatic children in Nanjing, China J of Asthma 2002 39 743 7 12507195 10.1081/JAS-120015798
Wolf RL Berry CA O'Connor T Coover L Validation of the Brief Pediatric Asthma Screen Chest 1999 116 224S 8S 10532498 10.1378/chest.116.suppl_2.224S
Mannino DM Homa DM Akinbami LJ Moorman JE Gwynn C Redd SC Surveillance for Asthma – United States, 1980–1999 MMWR Surveillance Summaries March 29, 2002 / 51(SS01) 1 13
Mortimer KM Fallot A Balmes JR Tager IB Evaluating the use of a portable spirometer in a study of pediatric asthma Chest 2003 123 1899 907 12796166 10.1378/chest.123.6.1899
Hankinson JL Odencrantz JR Fedan KB Spirometric reference values from a sample of the general U.S. population Am J Respir Crit Care Med 1999 159 179 87 9872837
Murphy S Practical Guide for the Diagnosis and Management of Asthma National Institutes of Health: National Heart, Lung, and Blood Institute 1997
Spahn JD Cherniack R Paull K Gelfand EW Is forced expiratory volume in one second the best measure of severity in childhood asthma? Am J Respir Crit Care Med 2004 169 784 786 14754761 10.1164/rccm.200309-1234OE
Corren J Allergic rhinitis and asthma: how important is the link? Journal of Allergy & Clinical Immunology 1997 99 S781 6 9042071
Kuchroo VK Umetsu DT DeKruyff RH Freeman GJ The TIM gene family: Emerging roles in immunity and disease Nature Reviews: Immunology 2003 3 454 462 12776205 10.1038/nri1111
| 15904513 | PMC1168903 | CC BY | 2021-01-04 16:28:56 | no | BMC Public Health. 2005 May 17; 5:48 | utf-8 | BMC Public Health | 2,005 | 10.1186/1471-2458-5-48 | oa_comm |
==== Front
Environ HealthEnvironmental Health1476-069XBioMed Central London 1476-069X-4-81591890710.1186/1476-069X-4-8ResearchPredictors of serum dioxin levels among adolescent boys in Chapaevsk, Russia: A cross-sectional pilot study Hauser Russ [email protected] Paige [email protected] Larisa [email protected] Susan [email protected] Lynne [email protected] Donald G [email protected] Wayman E [email protected] Mary M [email protected] Boris [email protected] Oleg [email protected] Occupational Health Program, Department of Environmental Health, Harvard School of Public Health, 665 Huntington Avenue, I-1405, Boston, MA 02115, USA2 Department of Biostatistics, Harvard School of Public Health, 665 Huntington Avenue, I-415, Boston, MA 02115, USA3 Occupational Health Program, Department of Environmental Health, Harvard School of Public Health, 665 Huntington Avenue, I-B26, Boston, MA 02115, USA4 Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Channing Laboratory 336, 11 Longwood Avenue, Boston, MA 02115, USA5 Center for Disease Control and Prevention, Toxicology Branch Mailstop F-17, TOX/EHLS/NCEH/CDC, 4770 Buford Hwy NE, Atlanta, GA 30341, USA6 Pediatric Endocrine Division, Department of Pediatrics, University of Massachusetts Medical School, 55 Lake Avenue North, Worcester, MA 01532, USA7 Center for Demography and Human Ecology of Institute for Forecasting, Russian Academy of Sciences, RAS. 47 Nahimowski Avenue, Moscow 117418, Russia8 Chapaevsk Medical Association, Lenina Str., 54B, Chapaevsk, Samara reg. 446100, Russia2005 26 5 2005 4 8 8 2 12 2004 26 5 2005 Copyright © 2005 Hauser et al; licensee BioMed Central Ltd.2005Hauser et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Toxicological studies and limited human studies have demonstrated associations between exposure to polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs) and polychlorinated biphenyls (PCBs) and adverse developmental and reproductive health effects. Given that children may be particularly susceptible to reproductive and developmental effects of organochlorines, and the paucity of information available regarding childhood exposures to dioxins in particular, we undertook a pilot study to describe the distribution of, and identify potential predictors of exposure to, dioxin-like compounds and dioxins among adolescent boys in Chapaevsk, Russia. The pilot study was also designed to guide the development of a large prospective cohort study on the relationship of exposure to PCDDs, PCDFs, and PCBs with growth and pubertal development in peri-pubertal Chapaevsk boys.
Methods
221 boys age 14 to 17 participated in the pilot study. Each of the boys, with his mother, was asked to complete a nurse-administered detailed questionnaire on medical history, diet, and lifestyle. The diet questions were used to measure the current and lifetime consumption of locally grown or raised foods. Blood samples from 30 of these boys were sent to the Centers for Disease Control and Prevention (CDC) for analysis of dioxins, furans and PCBs.
Results
The median (25th, 75th percentile) concentrations for total PCDDs, PCDFs and coplanar PCBs were 95.8 pg/g lipids (40.9, 144), 33.9 pg/g lipids (20.4, 61.8), and 120 pg/g lipids (77.6, 157), respectively. For WHO-TEQs, the median (25th, 75th percentile) for total PCDDs, PCDFs, and coplanar PCBs were 0.29 (0.1, 9.14), 7.98 (5.27, 12.3), and 7.39 (4.51, 11.9), respectively. Although TCDD was largely non-detectable, two boys had high TCDD levels (17.9 and 21.7 pg/g lipid). Higher serum levels of sum of dioxin-like compounds and sum of dioxin TEQs were positively associated with increased age, consumption of fish, local meats other than chicken, PCB 118, and inversely with weeks of gestation.
Conclusion
The total TEQs among Chapaevsk adolescents were higher than most values previously reported in non-occupationally exposed populations of comparable or even older ages. Dietary consumption of local foods, as well as age and weeks of gestation, predicted dioxin exposure in this population.
==== Body
Background
Polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), and polychlorinated biphenyls (PCBs) are persistent, lipophilic, halogenated aromatic chemicals that are developmental and male reproductive toxicants in laboratory animals [1-3]. These persistent chlorinated compounds are worldwide environmental pollutants that have been detected in areas as remote as the Arctic [4]. They are biologically concentrated and stored in human adipose tissue with prolonged half-lives. Current estimates of the half-life for 2,3,7,8-tetrachlorodibenzo-p-dioxin (2,3,7,8 TCDD) range from 3 to 10 years depending on age, gender, and serum concentration, with faster elimination in men, younger individuals, and those with higher peak exposures [5]. The general population is primarily exposed to these compounds through ingestion of contaminated food (fish, meat, milk, and their by-products), as well as through water sources, dermal contact with soil and house dust, and inhalation [6].
Human studies on the relationship of in utero and childhood (peri-pubertal) exposure to dioxin-like compounds (furans and PCBs) with growth and sexual development in boys are limited. A cross-sectional study of Belgian teenagers (15.8–19.6-year-olds) living in polluted and non-polluted communities demonstrated earlier male pubertal development (assessed by Tanner pubic hair and genital staging) in association with both living in polluted areas and higher serum PCBs as compared to boys living in clean areas and/or with lower PCB levels [7]. Lower testicular volume was associated with living in a polluted area but not with serum PCBs. Dioxin exposure assessed with a bioassay (CALUX) was not associated with male pubertal development in this study.
Several additional epidemiologic studies have been conducted to investigate growth and development in relation to halogenated aromatic compounds. For example, higher prenatal exposure to DDE has been associated with greater male height and weight adjusted for height at puberty and increased weight for height in peri-pubertal girls [8]. In Taiwan, boys exposed in utero to PCBs and PCDFs from maternal ingestion of contaminated rice oil had a shorter penile length than unexposed children [9].
Chapaevsk, Russia, is a town of approximately 83,000 residents, located in central Russia (1200 kilometers south-east of Moscow) on the bank of the Chapaevsk river, a tributary to the Volga. The town occupies an area of 187 km2, half of which is occupied by industries that are mostly of the military-industrial complex. In 1989, these industries were responsible for the production of the vast majority of the manufactured products from Chapaevsk, and almost half of the city's work force was employed there.
One of the largest chemical factories in Chapaevsk is the Khimprom Chemical Plant (Middle Volga chemical plant), which before 1949 produced chemical warfare agents (such as lewisite and mustard gas). After 1949, there was a transition to the production of industrial and agricultural chemicals, such as gamma-hexachlorocyclohexane (lindane), and other chlorine-containing products such as liquid chlorine, dichloropropionic acid, methyl chloroform, vinyl chloride, and pentachlorophenol [10]. These processes produced PCDDs and PCDFs as industrial contaminants, which subsequently polluted the air, soil, water and food supply in the city [10-12]. Revich and coworkers [10] have found elevated levels of dioxin-like compounds in soil less than two kilometers from the Khimprom Chemical Plant (141 ng TEQ/kg).
The plant has reduced production of these chemicals since 1991; however, since PCDDs and PCDFs persist in the environment, continued human exposure from contaminated air, soil, drinking water, as well as consumption of locally grown vegetables and locally raised animals remains a concern [10-12]. Moreover, a large proportion of the population lives in close proximity to the Khimprom complex.
Given that children may be particularly susceptible to reproductive and developmental effects of organochlorines, and the paucity of information available regarding childhood exposures to dioxins in particular, we undertook a pilot study to describe the distribution of, and identify potential predictors of exposure to, dioxin-like compounds and dioxins among adolescent boys in Chapaevsk, Russia. The pilot study was also designed to guide the development of a large prospective cohort study on the relationship of exposure to PCDDs, PCDFs, and PCBs with growth and pubertal development in peri-pubertal Chapaevsk boys.
Methods
Informed Consent
The study was approved by the Human Studies Institutional Review Boards of the Chapaevsk Medical Association, Harvard School of Public Health, University of Massachusetts Medical School, Brigham and Women's Hospital, and Centers for Disease Control and Prevention (CDC). All subjects signed informed consent prior to blood draw and study participation.
Study Population
From 2579 boys, aged 10–16 years in 1999, enrolled in an earlier pilot study to generate growth and maturation curves for boys in Chapaevsk [13], a subset of 246 older boys (14.0 to 16.9 years) were identified for a sub-study in which blood samples and questionnaire information were obtained. Older boys were chosen for study because blood samples were required and participation rates were expected to be higher than among younger children. Of the 246 boys, 221 had blood samples collected, and of these samples, 30 bloods were initially sent to the CDC for chemical analysis of dioxins, furans and PCBs. By design, of the 30 blood samples, 15 were from children with cryptorchidism or hypospadias, and 15 were from children with neither condition (controls). The selection of the 15 cases and 15 controls was done blindly in relation to factors that may predict dioxin levels.
Each of the 30 boys, with his mother, was asked to complete a nurse-administered detailed questionnaire on medical history, diet, and lifestyle. The diet questions were used to measure the current and lifetime consumption of locally grown or raised foods. The question was worded, "Does your child eat any of the following foods from local sources (i.e. your own garden or farms or lakes in the Chapaevsk area)? Yes/No". There were separate questions for current intake and lifetime intake of each food item. The distances the boys lived from the Khimprom factory at the time of the study and during pregnancy were assessed by questionnaire based on maternal self-report as <2, 2–6, or >6 kilometers, and the distance at the time of the study was also estimated using ArcView GIS 3.0 mapping of addresses.
Dioxin, furan and PCB chemical analysis
After blood collection and serum separation, the serum samples were stored at -20°C until shipment on dry ice to the US. The chemical analysis was performed by the laboratory at the National Center for Environmental Health, Centers for Disease Control and Prevention (NCEH, CDC), Atlanta, GA. Target analytes included polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), non-ortho substituted (coplanar) polychlorinated biphenyls (co-PCBs), mono-ortho substituted PCBs and other PCBs (nondioxin-like PCBs). Serum samples were spiked with a mixture of 13C12- labeled PCDDs/PCDFs and coplanar PCBs as internal standards and the analytes were isolated from serum by a C18 solid phase extraction (SPE) followed by a multi-column automated cleanup and enrichment procedure [14]. Samples were processed in batches of 10, which included a method blank and two quality control samples that were aliquots from pooled bovine sera spiked with PCDDs, PCDFs and co-PCBs.
The analytes were separated on a DB-5 MS capillary column and quantified using selected-ion-monitoring (SIM) high resolution (10,000 resolving power) mass spectrometry (HRGC-ID/HRMS) by the method described by Patterson et al. [15].
Quantification was by isotope dilution mass spectrometry using calibration standards containing 13C labeled, and unlabeled analytes. For specific PCDDs, PCDFs, and co-PCBs that lack their own labeled standard, a labeled congener with the same degree of substitution and a similar retention time was used. Mono-ortho and nondioxin-like PCBs were extracted from an aliquot (1 gram) of sample by SPE extraction [14]. Total Lipids were determined for each serum sample using a "summation" enzymatic method, which is based on the individual measurements of the four lipid groups (free or non-esterified cholesterol, cholesterol esters, triglycerides and phospholipids) [16].
The limits of detection (LODs) were calculated based on long-term standard deviations that were estimated from multiple measurements of low-level standards [17]. For an analyte with a positive blank, the average blank observed during the study was subtracted from individual calculated results [18]. The lipid adjusted detection limits (DLs) were based on observed LODs and corrected for individual sample weight and recovery.
Since values below the DL are expected to have greater variability and uncertainty than values above the DL, some have recommended censoring such data. In the case of our serum analyses, a substantial proportion of our results would be censored at the DL. However, when analyzing group data (as opposed to individual data points), censoring data below the detection limit may lead to the loss of useful information [19]. Where comparisons between uncensored and censored datasets have been performed, the use of DL cut-offs compromised the statistical power of analyses and led to biased exposure estimates [20]. This bias was a greater limitation than any increased variability of low values [18,21]. Thus, in the present study, we retained measurable values below the DL and assigned a value of zero only to samples in which the analyte was not detectable or was at or below the level of contamination in procedural blanks.
The concentrations of PCDDs, PCDFs and co-PCBs were reported on a lipid-adjusted basis as picograms of analyte per gram of lipids (ppt). The concentrations of mono-ortho and nondioxin-like PCBs were reported as nanogram of analyte per gram of lipids (ppb). Toxic equivalents (TEQs) were also reported for PCDDs, PCDFs, co-PCBs and other 'dioxin-like' PCBs based on Toxic Equivalency Factors (TEFs) for individual congeners as specified in the 1998 World Health Organization (WHO) system [22].
Statistical Analysis
Wilcoxon ranksum tests were used to compare dioxin and PCB levels between controls and boys with cryptorchidism or hypospadias. Generalized linear models were used to identify predictors of the log (base 10) of the sum of dioxin concentrations (PCDDs + PCDFs + co-PCBs) and log sum of dioxin TEQs (PCDDs + PCDFs + Co-PCBs) for the 30 boys. Predictors of dioxin concentrations were first modeled univariately and then adjusted for age. Univariate predictors with p-values below 0.15 were considered for inclusion in the multivariate models. Multivariate model selection was based on adjusted R-square values, Mallows C(p) criterion, and forward and backwards selection procedures; final models used a significance level of 0.05 for inclusion of predictors. Two final models were selected: one which considered all potential covariates, and a second model which considered only those covariates collected on all pilot study participants (i.e., excluding PCB measurements), in order to predict dioxin levels in the larger pilot study cohort.
Dietary exposures were coded as "Yes" or "No" for lifetime consumption of food from local sources (own garden or livestock, friend's garden or livestock, or grown/obtained in Chapaevsk) within the following categories: (1) fruits and vegetables; (2) chicken; (3) non-chicken meats which included goats, cows, pigs, and other non-chicken meat; (4) milk and dairy products, including eggs; and (5) fish. Exploratory models included factors considered a priori to have a potential relationship with serum dioxin levels such as the child's age, body mass index (weight in kg/height in m2), and local food consumption habits; reproductive factors (gestational age at birth of the index son, maternal parity [number of live births prior to the index son], gravidity [number of prior pregnancies], and breastfeeding history [cumulative number of weeks of breastfeeding previous children]), residential information (duration in years that the index boy resided in Chapaevsk and distance that mother lived from the factory during pregnancy with the index son and at the time of the study), and socio-demographic factors including parental education, parental occupation, and monthly household income (1 = 300–1000 rubles [$10–$35 U.S.], 2 = 1000–1500 rubles [$35–$50 U.S.], 3 = >1500 rubles [>$50 U.S.]).
Results
Per our selection criteria, of the 30 boys with serum samples analyzed for dioxin-like compounds, fifteen boys had congenital abnormalities (six hypospadias and nine cryptorchidism). No boy had both malformations. The 15 control boys did not have either hypospadias or cryptorchidism. The distances the boys lived from the Khimprom factory at the time of the study, along with other demographic characteristics, are presented in Table 1. The mean (sd) distance the boys lived from the Khimprom factories was 4.45 (1.76) km. During the pregnancy with her son, of the 29 mothers, 8 (27%) lived less than 2 km, 8 (27%) lived 2–6 km, and14 (45%) lived greater than 6 km from the Khimpron factory. One subject was missing questionnaire data, including distance from Khimprom, medical history, and local food consumption. Only three of the boys' fathers worked at the Khimprom factory during the year prior to the child's birth. While pregnant, two of the boys' mothers reported alcohol intake and one smoked.
Table 1 Demographic characteristics of adolescent boys from Chapaevsk, Russia (N = 30)
Mean SD N %
Age (years) 16.1 0.81
Body Mass Index (kg/m2) 19.9 3.09
Weeks of Gestationa 39.2 2.37
Breastfeeding duration of index son (weeks)b 36.9 25.2
Prior maternal breastfeeding (weeks)b 18.1 38.3
Birth weight (gm)c 3433 439
Current residential distance to Khimprom factory (km) 4.45 1.76
Time boy resided in Chapaevsk(yrs) 14.0 3.70
Gravidityd
0 14 48
1 8 28
2–3 7 24
Parityd
0 17 59
1 10 34
2–3 2 7
Monthly family income level
300–1000 rubles ($10–$35 U.S.) 8 28
1000–1500 rubles ($35–$50 U.S.) 7 24
>1500 rubles (> $50 U.S.) 14 48
Maximum parental education level
8–11thgrade 2 7
Junior College 17 59
University 8 28
aOne subject was missing data on weeks of gestation of the index son.
bOne subject was missing data on breastfeeding. Prior maternal breastfeeding is the cumulative number of weeks of breastfeeding children born prior to the index son.
cTwo subjects were missing data on birth weight of the index son.
d Maternal gravidity is the number of pregnancies prior to the index son and parity is the number of live births prior to the index son.
Since the PCDD, PCDF and PCB distributions were skewed, percentile distributions for serum concentrations and WHO-TEQs for 7 PCDD congeners, 9 PCDF congeners, 3 non-ortho (coplanar) PCBs and 6 mono-ortho PCBs are shown in Table 2. The median (25th, 75th percentile) concentrations for total PCDDs, PCDFs and coplanar PCBs were 95.8 pg/g lipids (40.9, 144), 33.9 pg/g lipids (20.4, 61.8), and 120 pg/g lipids (77.6, 157), respectively. The median (25th, 75th percentile) concentration for total mono-ortho PCBs was 47.7 ng/g lipids (39.2, 78.4); as expected more than two orders of magnitude larger than for the other compounds. For WHO-TEQs, the median (25th, 75th percentile) for total PCDDs, PCDFs, and coplanar PCBs were 0.29 (0.1, 9.14), 7.98 (5.27, 12.3), and 7.39 (4.51, 11.9), respectively. For total mono-ortho PCBs, the median (25th, 75th percentile) WHO-TEQ was 8.80 (7.16, 15.5). The total WHO-TEQ for dioxins, furans and PCBs had a median (25th, 75th percentile) of 30.9 (18.4, 46.8).
Table 2 Distribution of concentrations and WHO-TEQs of PCDD/Fs and PCBs in adolescent boys from Chapaevsk, Russia
Congener Average DL # of samples above DLa Concentrations WHO-TEF WHO-TEQ (pg TEQ/g lipid)
Percentiles Percentiles
25-th Median 75-th 25-th Median 75-th
PCDDs (pg/g lipid)
2,3,7,8-TCDD 4.1 2/29 0.00 0.00 0.00 1.000 0.00 0.00 0.00
1,2,3,7,8-PeCDD 4.8 12/30 0.00 0.00 8.30 1.000 0.00 0.00 8.30
1,2,3,6,7,8-HxCDD 7.1 1/30 0.00 0.00 0.00 0.100 0.00 0.00 0.00
1,2,3,7,8,9-HxCDD 6.9 3/30 0.00 0.00 0.00 0.100 0.00 0.00 0.00
1,2,3,4,6,7,8-HpCDD 14.6 15/30 9.40 14.9 25.1 0.010 0.09 0.15 0.25
1,2,3,4,6,7,9-HpCDD 9.0 0/30 0.00 0.20 1.70 0.0000 0.00 0.00 0.00
OCDD 73.1 15/29 32.9 75.0 100 0.0001 0.00 0.01 0.01
PCDFs (pg/g lipid)
2,3,7,8-TCDF 3.9 0/30 0.00 0.00 0.00 0.1000 0.00 0.00 0.00
1,2,3,7,8-PeCDF 4.7 1/30 0.00 0.00 0.00 0.050 0.00 0.00 0.00
2,3,4,7,8-PeCDF 4.5 29/30 8.50 12.6 17.4 0.500 4.25 6.30 8.75
1,2,3,4,7,8-HxCDF 4.2 27/30 5.50 9.15 20.1 0.100 0.55 0.92 2.01
1,2,3,6,7,8-HxCDF 4.5 21/30 0.00 5.70 8.70 0.100 0.00 0.57 0.87
1,2,3,7,8,9-HxCDF 4.2 0/30 0.00 0.00 0.00 0.100 0.00 0.00 0.00
2,3,4,6,7,8-HxCDF 4.5 1/30 0.00 0.00 1.80 0.100 0.00 0.00 0.18
1,2,3,4,6,7,8-HpCDF 16.8 0/30 3.00 5.30 10.5 0.010 0.03 0.05 0.11
1,2,3,4,7,8,9-HpCDF 6.0 0/30 0.00 0.00 0.00 0.010 0.00 0.00 0.00
Coplanar PCBs (pg/g lipid)
3,4,4',5-TCB 81 11.0 2/30 0.00 0.00 1.60 0.0001 0.00 0.00 0.00
3,3',4,4',5-PeCB 126 25.3 30/30 43.3 68.4 116 0.1000 4.33 6.84 11.6
3,3',4,4',5,5'-HxCB 169 7.7 28/30 27.3 44.2 54.3 0.0100 0.27 0.44 0.54
Mono-ortho PCBs (ng/g lipid)
2,3,3',4,4'-PeCB (105) 11.0 9/27 5.6 7.1 11.8 0.0001 0.56 0.71 1.18
2,3',4,4',5-PeCB (118) 11.0 27/27 20.7 28.0 51.6 0.0001 2.07 2.80 5.16
2,3,3',4,4',5-HxCB (156) 11.0 10/27 7.5 9.1 15.9 0.0005 3.75 4.55 7.95
2,3,3',4,4',5'-HxCB (157) 11.0 0/27 2.3 2.6 4.3 0.0005 1.15 1.30 2.15
2,3',4,4',5,5'-HxCB (167) 11.0 0/27 1.6 2.0 3.7 0.00001 0.02 0.03 0.04
2,3,3',4,4',5,5'-HpCB (189) 10.9 0/25 0.4 0.6 0.8 0.0001 0.04 0.06 0.08
Total PCDDs (pg/g lipid) 40.9 95.8 144 0.10 0.29 9.14
Total PCDFs (pg/g lipid) 20.4 33.9 61.8 5.27 7.98 12.3
Total coplanar PCBs (pg/g lipid) 77.6 120 157 4.51 7.39 11.9
Total PCDD/F/coplanar PCBs (pg/g lipid) 154 273 397 12.1 17.1 38.1
Total Mono-ortho PCBs (ng/g lipid) 39.2 47.7 78.4 7.16 8.80 15.5
Total TEQs 30.9 46.8
Abbreviations: DL, detection limit.
Note: 1,2,3,4,7,8-HxCDD, OCDF, and 3,3',4,4'-TCB 77 were not reported in the present study due to interferences in method blanks.
aResults for some samples could not be reported because one or more of the analytical QA/QC criteria were not met. Therefore, the denominator may be less than 30.
Although means and standard deviations do not appropriately describe skewed distributions, to allow for comparisons with other studies we briefly present them. The mean (sd) of total PCDDs, PCDFs, and coplanar PCBs were 104 pg/g lipids (78.0), 63.8 pg/g lipid (89.9) and 123 pg/g lipid (53.1), respectively. The mean of the TEQs for PCDDs, PCDFs, and coplanar PCBs were 5.51, 13.9 and 8.35 pg TEQ/g lipid, respectively.
PCDDs, PCDFs, and coplanar PCBs accounted for a mean percent of total serum dioxin concentrations of 34.3% (range 8.4 to 80.1%), 18.0% (range 4.4 to 57.5%), and 47.7% (range 15.5 to 73.9%), respectively. The relatively high concentrations of mono-ortho PCBs contributed significantly to TEQs and were therefore also included in the total TEQs. PCDDs, PCDFs, coplanar PCBs, and mono-ortho PCBs accounted for a mean percent of total TEQs of 11.9% (range 0.14 to 59.0%), 30.4% (range 3.9 to 71.3%), 25% (range 8.1 to 43.0%), and 32.8% (range 0 to 60.1%), respectively.
Figure 1 displays the percent contribution of each PCDD, PCDF and PCB congener to the total TEQ/g lipid for the thirty boys. Based on serum concentrations, the predominant dibenzo-p-dioxin congeners were OCDD and 1,2,3,4,6,7,8-HpCDD (mean percents of 73.8% and 22.2%, respectively), while 1,2,3,7,8-PeCDD and 1,2,3,4,6,7,8-HpCDD were the predominant congeners based on mean TEQs (mean percents of 56.2% and 37.0%, respectively). For PCDFs, 2,3,4,7,8-PeCDF and 1,2,3,4,7,8-HxCDF accounted for the majority of the total PCDF concentrations (means of 35.5% and 32.4%, respectively), and these same two congeners accounted for the majority of the total PCDF TEQs (75.2% and 16.7%, respectively). For coplanar PCBs, 3,3',4,4',5-PeCB (#126) and 3,3',4,4',5,5'-HxCB (#169) accounted for the majority of the total coplanar PCB concentrations (means of 63.4 and 35.3%, respectively), and 3,3',4,4',5-PeCB (#126) accounted for 94.1% of the total coplanar PCB TEQs. For mono-ortho PCBs, 2,3',4,4',5-PeCB (#118) and 2,3,3',4,4',5-HxCB (#156) accounted for the majority of the total mono-ortho PCB concentrations (means of 56.0% and 19.7%, respectively), while 2,3,3',4,4',5-HxCB (#156) accounted for 48.3% of the total mono-ortho PCB TEQs and 2,3',4,4',5-PeCB (#118) for 30.3%. The concentrations of six prevalent PCB congeners, or so-called indicator PCBs [23], are presented in Table 3. Here the largest contributors to the sum of the 6 congeners were PCB 153 (34.6%) and PCB138 (20.4%).
Figure 1 Percent contribution of PCDDFs and PCBs to TEQs (pg TEQ/g lipid) among boys from Chapaevsk.
Table 3 Concentrations (ng/g lipid) of six PCB congenersa in blood of adolescent boys from Chapaevsk, Russia
PCB congener (IUPAC #) Average DL # of Samples above the DLb Median Concentration (ng/g lipid) Mean (SD) Concentration (ng/g lipid)
PCB 28 20.0 1/24 10.6 11.9 (6.33)
PCB 74 11.0 14/27 10.8 14.8 (10.8)
PCB 99 11.0 27/27 27.7 34.1 (22.5)
PCB 138 18.0 21/27 29.6 39.4 (22.2)
PCB 153 19.8 27/27 51.2 64.5 (30.7)
PCB 180 11.0 23/27 17.7 22.8 (14.9)
Sum of 6 congeners 136 168 (99.3)
Abbreviations: DL, detection limit
aPCB congeners include 6 prevalent or indicator congeners (DIN 51 527, 1987)
bResults for some samples could not be reported because one or more of the analytical QA/QC criteria were not met. Therefore, the denominator may be less than 30.
Only two of the 30 boys had levels of 2,3,7,8-TCDD greater than the detection limits; levels for these two boys were 17.9 and 21.7 pg/g lipid. Because all samples had different weights (4.1 to 12.1 g), different percent lipids, and percent recoveries, the DLs for TCDD in our study samples ranged from 1.5 to 16.5 pg/g lipid. We were unable to identify unique characteristics of the two boys with detectable levels of 2,3,7,8-TCDD. There were no differences in sum of PCDDs, PCDFS, and PCBs between the group of boys with cryptorchidism or hypospadias and the comparison boys. The smallest difference we could detect however, in the sum of dioxin concentrations given the small size of this study is 175 pg/g lipid (with 80% power) or 200 pg/g lipid (with 90% power). In other words, we can only detect differences that are larger than the observed standard deviation in sum of dioxin-like compounds.
Of the 29 boys with lifetime food consumption data, 86% (n = 25) had consumed local meat products (in particular, 83% had consumed non-chicken meat and 52% had consumed local chicken), 83% (n = 24) had consumed local fish, 93% (n = 27) had consumed locally produced dairy products or eggs, and 97% (n = 28) had consumed locally grown fruits and/or vegetables.
Using regression models adjusting for age, associations were found between the log sum of dioxin concentrations and several characteristics of the thirty boys (Table 4). Increasing age, local non-chicken meat and fish consumption, and log of lipid-adjusted PCB congener 118 were associated with increases in the sum of the dioxin concentrations. For instance, a one- year increase in age increased the mean sum of dioxin-like compounds (291 pg/g lipids) by 30% and consumption of local non-chicken meat increased dioxin-like compounds by 75%. Gestational age in weeks was inversely associated with the sum of the dioxin concentrations, multiplicative factor of 0.92. Although the coefficient for the relationship between log sum of dioxin-like compounds and current residential distance from the Khimprom factory was less than 1.0 (which would support a decrease in dioxin levels with increasing distance from the factory), it was not statistically significant. We also explored the relationship between the sum of dioxin-like compounds and categories of GIS distances from Khimprom plants (<2 km, 2–6 km, >6 km) and found an inverse association, though it too was not statistically significant. Duration of breast-feeding, distance from Khimprom during pregnancy, maternal parity, and parental occupation were unrelated to sum of dioxin-like compounds or sum of dioxin TEQs.
Table 4 Individual predictors of log sum of dioxin-like compoundsa, adjusted for age in years
Predictor Estimate p-value Multiplicative factor on dioxin (95% CI) R-Square Value
Age of index son (years) 0.26 0.057 1.30 (1.00–1.72) 0.13
BMI of index son (kg/m2) 0.03 0.40 1.03 (0.95–1.13) 0.15
Consumption of local non-chicken meat (y/n) 0.56 0.042 1.75 (1.05–2.92) 0.26
Consumption of local chicken (y/n) 0.13 0.54 1.14 (0.75–1.72) 0.14
Consumption of local fish (y/n) 0.48 0.079 1.62 (0.97–2.71) 0.23
Consumption of local eggs (y/n) 0.20 0.36 1.23 (0.80–1.88) 0.16
Consumption of local dairy (y/n) -0.19 0.65 0.82 (0.36–1.89) 0.13
Consumption of local fruits/vegetables (y/n) -0.12 0.84 0.89 (0.28–2.77) 0.13
Current residential distance from Khimprom (km) -0.06 0.37 0.94 (0.82–1.07) 0.15
Years resided in Chapaevsk 0.009 0.75 1.01 (0.95–1.07) 0.13
Monthly family income levelb -0.09 0.50 0.92 (0.71–1.18) 0.14
Maximum parental educationb 0.21 0.26 1.23 (0.86–1.76) 0.17
Log (PCB 118) (ng/g lipid) 0.64 <0.001 1.90 (1.37–2.63) 0.46
Congenital abnormality of index son -0.015 0.95 0.99 (0.64–1.51) 0.13
Parityb,c -0.011 0.94 0.99 (0.74–1.32) 0.13
Weeks of gestation -0.08 0.072 0.92 (0.84–1.00) 0.23
Weeks of breast-feeding index son (per 12 weeks) -0.004 0.94 1.00 (0.90–1.10) 0.13
Prior breastfeeding durationd (years) 0.09 0.53 1.10 (0.82–1.47) 0.14
Abbreviations: Log, logarithm base 10; BMI, body mass index; PCB 118, polychlorinated biphenyl 118
aSum of dioxin-like compounds includes PCDDs, PCDFs, and coplanar PCBs.
bEach variable was modeled using three ordinal levels.
cParity refers to the number of live births prior to the index son.
dPrior maternal breastfeeding refers to the cumulative number of weeks of breastfeeding children born prior to the index son.
N = 30 for age, BMI, and distance from Khimprom at time of blood draw; N = 29 for all food consumption and medical history predictors; N = 27 for model with PCB118.
Models predicting the log of the sum of dioxin TEQ's (Table 5) were generally similar in magnitude and direction for the predictors shown in Table 4, but suggested weaker effects of age (multiplicative factor = 1.30, p = 0.14) and local fish consumption (multiplicative factor = 1.43, p = 0.32), and a stronger effect of maximal parental education (multiplicative factor = 1.50, p = 0.086) and log of PCB 118 TEQ (multiplicative factor = 2.61, p < 0.001).
Table 5 Predictors of log dioxin TEQsa among boys in Chapaevsk, Russia (adjusted for age).
Predictor Estimate p-value Multiplicative factor on dioxin (95% CI) R-Square Value
Age (years) 0.26 0.14 1.30 (0.93–1.81) 0.08
BMI (kg/m2) 0.04 0.41 1.04 (0.95–1.13) 0.10
Consumption of local non-chicken meat (y/n) 0.68 0.059 1.97 (1.01–3.87) 0.20
Consumption of local chicken (y/n) 0.06 0.82 1.07 (0.62–1.83) 0.08
Consumption of local Fish (y/n) 0.36 0.32 1.43 (0.71–2.88) 0.11
Consumption of local Eggs (y/n) 0.12 0.68 1.13 (0.64–1.98) 0.09
Consumption of local Dairy (y/n) -0.43 0.44 0.65 (0.22–1.89) 0.10
Consumption of local Fruits/Vegetables (y/n) 0.35 0.65 1.41 (0.32–6.17) 0.09
Current residential distance from Khimprom (km) -0.09 0.32 0.91 (0.77–1.09) 0.12
Years resided in Chapaevsk -0.014 0.71 0.99 (0.92–1.06) 0.09
Monthly family income levelb -0.14 0.41 0.87 (0.63–1.21) 0.10
Maximum parental educationb 0.41 0.086 1.50 (0.96–2.36) 0.18
log (PCB118 TEQ) 0.96 <0.001 2.61 (1.81–3.75) 0.57
Sexual delay/congenital abnormality 0.21 0.46 1.23 (0.71–2.13) 0.10
Parityb,c 0.06 0.77 1.06 (0.73–1.54) 0.09
Weeks of gestation -0.11 0.078 0.90 (0.80–1.01) 0.19
Breast-feeding duration of index son (per 12 weeks) -0.002 0.97 1.00 (0.87–1.14) 0.08
Prior breastfeeding durationd (years) 0.07 0.72 1.07 (0.73–1.57) 0.08
Abbreviations: Log, logarithm base 10; BMI, body mass index; TEQ, toxic equivalents
aSum of dioxin TEQs include TEQs for PCDDs, PCDFs, coplanar PCBs and other 'dioxin-like' PCBs
bEach variable was modeled using three ordinal levels.
cParity refers to the number of live births prior to the index son.
dPrior maternal breastfeeding refers to the cumulative number of weeks of breastfeeding children born prior to the index son.
N = 30 for age, BMI, and distance from Khimprom at time of blood draw; N = 29 for all food consumption and medical history predictors; N = 27 for model with PCB118.
The best fitting multivariate models for predicting the sum of dioxin concentrations are summarized in Table 6. Even after accounting for the strong relationship between PCB 118 concentration and the sum of dioxin concentrations on the log scale, consumption of local non-chicken meat showed a significant association with increased dioxin levels. Similarly, the best fitting multivariate model for predicting the sum of dioxin TEQs also included PCB 118 and consumption of local non-chicken meat (R-square = 0.63). The best-fitting model for sum of dioxin concentrations, excluding log PCB 118, included age, weeks of gestation, income level, and consumption of local non-chicken meat and local dairy products, with an R-square of 0.56. The best fitting multivariate model for predicting the sum of dioxin TEQs, excluding log PCB 118 TEQ, included the same five predictors as those shown in Table 6 with similar magnitudes and significance of effects (R-square = 0.56).
Table 6 Multivariate models for predicting log sum of dioxina concentrations among adolescent boys in Chapaevsk, Russia
Model # Predictor Estimate p-value R-square value Adjusted R-square value
1 Consumption of local non-chicken eat (y/n) 0.59 0.017 0.56 0.52
log (PCB 118) (ng/g lipid) 0.63 <0.001
2 Age (years) 0.40 <0.001 0.56 0.46
Weeks of gestation -0.11 0.005
Consumption of local dairy (y/n) -0.76 0.037
Consumption of local non-chicken meat (y/n) 0.90 <0.001
Monthly family income level (ordinal, low, med, high) -0.27 0.020
Abbreviations: Log, logarithm base 10
aSum of dioxin-like compounds includes PCDDs, PCDFs, and coplanar PCBs
N = 26 for model 1; N = 29 for model 2. Missing data for 3 boys on lipid-adjusted PCB 118, and one boy on questionnaire items (medical history, diet).
Model 1: best fit multivariate model including PCB 118 data.
Model 2: best fit multivariate model (forward and backward selection) not including PCB 118.
Discussion
Among adolescent boys in Chapaevsk, Russia, higher serum levels of sum of dioxin-like compounds and sum of dioxin TEQs were positively associated with increased age, consumption of fish, local meats other than chicken, and inversely with weeks of gestation. The age association was found despite a narrow age range of slightly over two years in our study. Although not statistically significant, the distance the boy lived from the Khimprom factory at the time of blood draw was inversely associated with serum levels of sum of dioxin-like compounds and sum of dioxin TEQs. As expected, serum PCBs, specifically PCB 118, were strongly associated with both sum of dioxin-like compounds and sum of dioxin TEQs.
There was no association between the distance of the residence from the Khimprom plant during the pregnancy and subsequent serum dioxin levels. One potential explanation for the lack of association may include misclassification of distance since the mother was asked to recall a time period more than 14 years prior to the study. However, we would expect that the mother would be able to recall residential history at the time of the birth of their son. Mother's self-reported estimates of current residential distance from Khimprom was generally accurate; twenty-one of twenty-nine mothers correctly categorized their current residential distance from the Khimprom plants based on cross-referencing using GIS mapping. Other explanations include that prenatal exposure 14 or more years prior to the current serum sample is not as strong a predictor as are exposures resulting from present residential location. Although there was no association of case status (cryptorchidism or hypospadias) with dioxin levels, we did not have sufficient power to definitively assess this relationship.
Perinatal history (e.g. weeks of breastfeeding) was generally not associated with exposure measures in this population; this may be a function of older age of the children. However, there are limited data on the relationship of perinatal factors with organochlorine exposures in this age group so a null finding is of interest given reports that differences in organochlorine levels among breastfed and non-breastfed are generally no longer discernable by early school age [24,25] and, furthermore, that dietary intake after this age contributes significantly to total dioxin intake [26]. In prior studies, substantial emphasis has been placed on pre- and early postnatal (via breastfeeding) exposures because of particular vulnerability during fetal and early infant development. The exposure risk factors during peri-adolescence, another period of potential developmental vulnerability, has not been studied in-detail, therefore, the identification of exposure risk factors specific to this period will enhance our understanding of this critical period.
Although data on levels of PCDD/PCDFs in children is limited, our results suggest that the mean total TEQs among Chapaevsk adolescents were higher than most values previously reported in non-occupationally exposed populations of comparable or even older ages. Figure 2 shows a comparison of the mean PCDD/PCDFs TEQ levels in Chapaevsk boys with other populations (TEQ from dioxin-like PCBs was not included, since some of these studies did not report them). The mean TEQs of pooled blood samples from 10 year-old German boys in rural and urban settings was 8.2 pg TEQ/g lipid for an urban industrial area, 9.0 pg TEQ/g lipid for an industrial area within a rural setting, and 10.1 pg TEQ/g lipid for a rural area [27]. In comparison, the mean TEQ in the Chapevsk boys was 19.3 pg TEQ/g lipid. With the exception of children described by Wuthe et al. [27], subjects in the other studies in Figure 2 were significantly older than the Chapaevsk boys. Despite age differences, the mean TEQ in Chapaevsk boys was comparable to or even higher than the mean TEQ in older populations from other countries. For example, they were higher than mean TEQs of 18.4 pg TEQ/g lipid in adults (40.6 years old average) from South Germany [27] or 16.4 pg TEQ/g lipid from 20 year old Japanese women [28] or pooled samples from randomly selected males and females 18–69 years of age from the Spanish city of Mataro [29], which were 12.5 and 14.7 pg TEQ/g lipid respectively. The mean levels in adult female (mean age 41 years) non-factory workers in the Russian city of Shelekhovo were also lower at 14.5 pg TEQ/g lipid [30]. Mean TEQs for the general population (mean age 44.2 years) in Germany, collected in 1997–98 [31], and median TEQs for long-term workers of pulp and paper mill and non-workers in the U.S. in 1996 [32] were similar to levels found in the Chapaevsk boys. The mean levels in the study in Germany were 20.71 pg TEQ/g lipid and in the U.S. the median levels were 19.1 pg TEQ/g lipid for community residents and 21.2 pg TEQ/g lipid for low exposure workers.
Figure 2 Mean PCDD/PCDFs TEQ levels in Chapaevsk boys in comparison with other populations.
Although TCDD was largely below the detection limits in this small pilot sample, the two boys with detectable values had high TCDD levels (17.9 and 21.7 pg/g lipid), suggesting that exposure for at least some portion of this population is substantially higher than typical of this age group. In comparison, in a cohort of adult (mean age of 58 years) fishermen from a polluted region of Finland, the mean TCDD concentration was 19 pg/g lipid [33]. In adult (mean age of 53 years) residents from Calcasieu Parish, Louisiana, which is near a chemical industrial complex, the mean TCDD level was 7.6 pg/g lipid [34]. Not only were the dioxin levels in these two children higher than those found in these studies, but the adults in the previous studies were several decades older and therefore would be expected to have higher dioxin body burdens than younger children [35]. Potential explanations for the large number of non-detectable samples for TCDD include the small sample volume and young age of the subjects. In our future studies in this population, we will collect larger volumes of serum for dioxin analysis.
In one of the few studies on dioxin-like compounds in which children were included, Eskenazi and coworkers [36] evaluated the relationship between serum TCDD concentrations and age at exposure of female residents of Seveso, Italy. Residents near the ICMESA chemical plant in Seveso were exposed to some of the highest known residential levels of 2,3,7,8-TCDD as a result of an explosion at the plant. Archived serum collected near the time of the accident was used to measure exposures. Residents closest to the plant had a median 2,3,7,8-TCDD level of 272 ppt (IQR 92 – 883 ppt). Residential proximity to the plant and younger age (up to 13 years old) were the strongest predictors of an individual's serum 2,3,7,8-TCDD level. Other predictors included being outdoors at the time of explosion and consumption of homegrown food. The higher levels found in children were most likely a result of increased exposure as a result of activity patterns and a greater proportionate consumption of food, water and air than adults [37].
Although the exposure scenario (an acute high exposure event) is different than the chronic low/moderate exposure occurring in Chapaevsk, the results from Seveso suggest that children may be at increased risk for high dioxin exposure from environmental contamination. In our study, although distance from the Khimprom plants was a weak predictor of serum dioxin-like compounds, consumption of local foods (specifically meat and fish), as in the Seveso study, was a strong predictor of sum of dioxin-like compounds and dioxin TEQs. This finding is notable given concerns regarding environmental dioxin contamination in the community and suggests that food may be one of the more, if not most, important routes of environmental contaminant exposure for residents in this setting. In other settings, contaminated food generally contributes much more substantially to human organochlorine burden than air or soil (which may be related to residential proximity to pollutant sources) [6]. We will investigate this issue in more detail in our ongoing study.
Conclusion
Recently, data were published on dioxin levels among adult residents of Chapaevsk, Russia [38]. Twenty-four self-selected volunteers (12 men and 12 women) provided blood samples in 1998 for analysis of dioxin-like compounds. These serum samples were analyzed by the same laboratory at the CDC, which analyzed the serum samples for our study. None of the adult subjects worked at the Khimprom plant in Chapaevsk. The mean age of subjects was 44 years for men and 45 years for women. Among all subjects, the mean TEQ of total dioxins was 61.2 pg TEQ/g lipid (range 16.4 to 168.1 pg TEQ/g lipid). The adults had the same congeners as major contributors to TEQ of dioxin, furan and co-planar PCBs as the boys in our study. We could not compare the levels of mono-ortho-PCBs in the children to levels in the adult Chapevsk residents since they were not reported. In the adults in Chapaevsk, there were positive relationships of TEQs with age and BMI and an inverse relationship of TEQs with residential distance from the plant [38]. In both this adult and our pediatric Chapaevsk population, PCB congeners contributed significantly to TEQs and therefore it is important to assess these congeners vis-à-vis toxicological implications mediated through dioxin-like mechanisms.
We have recently begun recruiting eight- and nine-year old boys and their families in Chapaevsk into a prospective cohort study on the relationship between dioxin exposure and somatic growth and pubertal development. Results of this exposure assessment study demonstrate relatively high TEQ exposures among Chapaevsk children compared to similar aged populations elsewhere and, as evidenced by the importance of local food consumption in determining this exposure, corroborate our hypothesis that local environmental contamination likely contributes to exposure risk in this setting. Our planned additional studies of the potential health consequences of Chapaevsk children's exposure is an important sequel to having characterized organochlorine exposure and exposure risk among this potentially vulnerable age group.
List of Abbreviations
IUPAC International Union of Pure and Applied Chemistry
mono-ortho PCBs Includes PCB congener numbers 105, 114, 118, 123, 156, 157, 167, 189
non-ortho PCBs Includes PCB congener numbers 77, 81, 126, 169
OCDD Octachlorodibenzo-p-dioxin
OCDF Octachlorodibenzo-furan
PCBs Polychlorinated biphenyls
PCDDs Polychlorinated dibenzo-p-dioxins
PCDFs Polychlorinated dibenzofurans
pg/g Picogram per gram, 10-12 g.
TEF Toxic equivalency factors
TEQ Toxic Equivalents (WHO98)
I-TEQ International Toxic Equivalents (NATO-CCMS, 1988)
WHO World Health Organization
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
RH conceived the design of the study and took primary responsibility for drafting the manuscript. PW performed the statistical analysis, participated in the design of the study and the drafting of the manuscript. LA participated in the drafting of the manuscript and the interpretation of the dioxin results. SK participated in the design of the study and the drafting of the manuscript. LP participated in the statistical analysis. DGP carried out the dioxin analyses. WET carried out the dioxin analyses. MML participated in the design of the study and the drafting of the manuscript. BR participated in the design of the study. OS oversaw subject recruitment and data collection, participated in the design of the study and the drafting of the manuscript. All authors read and approved the final manuscript.
Acknowledgements
This work was funded by the US EPA, Grant number R-82943701-0 and NIEHS, Grant Number ES00002.
==== Refs
Bjerke DL Peterson RE Reproductive toxicity of 2,3,7,8-tetrachlorodibenzo-p-dioxin in male rats: Different effects of in utero verses lactational exposure Toxicol Appl Pharmacol 1994 127 241 249 8048067
Brouwer A Longnecker MP Birnbaum LS Cogliano J Kostyniak P Moore J Schantz S Winneke G Characterization of potential endocrine-related health effects at low-dose levels of exposure to PCBs Environ Health Perspect 1999 107 639 649 10421775
Mably T Moore RW Goy RW Peterson RE In utero and lactational exposure of male rats to 2,3,7,8-tetrachlorodibenzo-p-dioxin. 3. Effects on spermatogenesis and reproductive capability Toxicol Appl Pharmacol 1992 114 118 126 1585364
Schecter A Papke O Pavuk M Tobey RE Exposure Assessment: Measurement of Dioxins and Related Chemicals in Human Tissues Dioxins and Health 2003 John Wiley and Sons Inc, Hoboken NJ 629 678
Aylward LL Brunet RC Carrier G Hays SM Cushing CA Needham LL Patterson DG Gerthoux PM Brambilla P Mocarelli P Concentration-dependent TCDD elimination kinetics in humans: toxicokinetic modeling for moderately to highly exposed adults from Seveso, Italy, and Vienna, Austria, and impact on dose estimates for the NIOSH cohort J Expo Anal Environ Epidemiol 2005 15 51 65 15083163
Institute of Medicine, National Academies of Science Dioxins and dioxin-like compounds in the food supply Strategies to decrease exposure 2004 Washington, DC: National Academies Press
Den Hond E Roels HA Hoppenbrouwers K Nawrot T Thijs L Vandermeulen C Winneke G Vanderschueren D Staessen JA Sexual maturation in relation to polychlorinated aromatic hydrocarbons:Sharpe and Skakkebaek's hypothesis revisited Environ Health Perspect 2002 110 771 776 12153757
Gladen BC Ragan NB Rogan WJ Pubertal growth and development and prenatal and lactational exposure to polychlorinated biphenyls and dichlorodiphenyl dichlorethene J Pediatrics 2000 136 490 496
Guo YL Lai Tj Ju SH Chen YC Hsu CC Sexual developments and biological findings in Yucheng children Thirteenth International Symposium on Chlorinated Dioxins and Related Compounds: Vienna, Austria 24–28 September 1993
Revich B Aksel E Dvoirin V Kolbeneva L Pervunina R Dioxin in the environment of Chapaevsk (Russia), health of its population Organohalogen Compounds 1996 30 350 353
Revich B Brodsky E Sotskov Y Dioxin in environmental, blood, breast milk, cow milk in Chapaevsk town Organohalogen Compounds 1999 44 229 232
Revich B Aksel E Ushakova T Ivanova I Zhuchenko N Kluev N Brodsky B Sotskov Y Dioxin exposure and public health in Chapaevsk, Russia Chemosphere 2001 43 951 966 11372889
Lee MM Sergeyev O Williams P Korrick S Zeilert V Revich B Hauser R Physical growth and sexual maturation of male adolescents in Chapaevsk, Russia J Ped Endo Metabol 2003 16 169 178
Turner W DiPietro E Lapeza C Green V Gill J Patterson DG Jr A Fast Universal Automated Cleanup System for the Isotope-Dilution High-Resolution Mass Spectrometric Analysis of PCDDs, PCDFs, Coplanar PCBs, PCB Congeners, and Persistent Pesticides from the Same Serum Sample Organohalogen Compounds 1997 31 26 31
Patterson DG JrHampton L Lapeza CR JrBelser WT Green V Alexander L Needham LL High-Resolution Gas Chromatographic/High-Resolution Mass Spectroscopic Analysis of Human Serum on a Whole-weight and Lipid Basis for 2,3,7,8-tetrachlorodibenzo-p-dioxin Anal Chem 1987 59 2000 2005 3631519
Akins JR Waldrep K Bernert JT Jr The Estimation of Total Serum Lipids by a Completely Enzymatic 'Summation' Method Clin Chim Acta 1989 184 219 226 2611996
Taylor JK Quality Assurance of Chemical Measurements 1987 Chelsea, Michigan: Lewis Publishers
Keith LH Report Results Right! – Part II CHEMTECH 1991 486 489
Berthouex PM A study of the precision of lead measurements at concentrations near the method detection limit Water Environ Res 1993 65 620 629
Kim R Aro A Rotnitzky A Amarasiriwardena C Hu H K x-ray fluorescence measurements of bone lead concentration: the analysis of low-level data Phys Med Biol 1995 40 1475 1485 8532760
Keith LH Throwaway data Environ Sci Technol 1994 28 389A 390A
Van den Berg M Birnbaum L Bosveld AT Brunstrom B Cook P Feeley M Giesy JP Hanberg A Hasegawa R Kennedy SW Kubiak T Larsen JC van Leeuwen FX Liem AK Nolt C Peterson RE Poellinger L Safe S Schrenk D Tillitt D Tysklind M Younes M Waern F Zacharewski T Toxic equivalency factors (TEFs) for PCBs, PCDDs, PCDFs for humans and wildlife Environ Health Perspect 1998 106 775 792 9831538
Deutsches Institut für Normung EV DIN 51 527. Part 1 Determination of the concentration of polychlorinated biphenyls in mineral oil 1987 Prüfung von Mineralölerzeugnissen, Bestimmung des Gehaltes an polychlorierten Biphenylen (PCB)
Kreuzer PE Csanady GA Baur C Kessler W Papke O Greim H Filser JG 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and congeners in infants. A toxicokinetic model of human lifetime body burden by TCDD with special emphasis on its uptake by nutrition Arch Toxicol 1997 71 383 400 9195020
Patandin S Weisglas-Kuperus N de Ridder MAJ Koopman-Esseboom C van Staveren WA van der Paauw CG Sauer PJ Plasma polychlorinated biphenyl levels in Dutch preschool children either breast-fed or formula-fed during infancy Am J Public Health 1997 87 1711 1714 9357362
Patandin S Dagnelie PC Mulder PGH de Coul EO van der Veen JE Weisglass-Kuperus N Sauer PJ Dietary exposure to polychlorinated biphenyls and dioxins from infancy until adulthood: a comparison between breast-feeding, toddler, and long-term exposure Environ Health Perspect 1999 107 45 51 9872716
Wuthe J Piechotowski I Päpke O Zier B Gabrio T Krämer D Kouros B Schwenk M Pfaff G First data on background levels of non-ortho and mono-ortho PCBs in blood of residents from Southern Germany Chemosphere 1996 32 567 574 8907234
Lida T Hirakawa H Matsueda T Shigeyuki T Nagayama J Polychlorinated dibenzo-p-dioxins and related compounds: the blood levels of young Japanese women Chemosphere 1999 38 3497 3502 10365432
Gonzalez CA Kogevinas M Huici A Gadea E Ladona M Bosch A Bleda MJ Blood levels of polychlorinated dibenzodioxins, polychlorinated dibenzofurans and polychlorinated biphenyls in the general population of a Spanish Mediterranean city Chemosphere 1998 36 419 426 9451808
Mamontova EA Tarasova EN Mamontov AA Papke O PCDDs, PCDFs and PCBs Levels in Blood of the Schelekhovo Population, the Irkutsk Region, Russia Organohalogen Compounds 2002 58 281 284
Wittsiepe J Schrey P Ewers U Selenka F Wilhelm M Decrease of PCDD/F levels in human blood from Germany over the past ten years (1989–1998) Chemosphere 2000 40 1103 1109 10739052
Tepper A Burt S Piacitelli L Patterson DG Jr Serum levels of polychlorinated dibenzo-p-dioxins and dibenzofurans in pulp and paper mill workers Chemosphere 1997 34 1587 1603 9134690
Kiviranta H Vartiainen T Tuomisto J Polychlorinated dibenzo-p-dioxins, dibenofurans, biphenyls in fisherman in Finland Environ Health Perspect 2002 110 355 361 11940453
Orloff KG Hewitt D Metcalf S Kathman S Lewin M Turner W Dioxin exposure in a residential community J Exposure Anal Environ Epid 2001 11 352 358
Patterson DG JrCanady R Wong L-Y Lee R Turner W Caudill S Grassman J Needham LL Henderson A Age specific dioxin TEQ reference range Organhalogen Compounds 2004 66 2878 2883
Eskenazi B Mocarelli P Warner M Needham L Patterson DG Samuels S Turner W Gerthoux PM Brambilla P Relationship of serum TCDD concentrations and age at exposure of female residents of Seveso, Italy Environ Health Perspect 2004 112 22 27 14698926
National Research Council Committee on Pesticides in the Diets of Infants and Children Pesticides in the Diets of Infants and Children 1993 Washington, DC: National Academy Press
Akhmedkhanov A Revich B Adibi JJ Zeilert V Masten SA Patterson DG JrNeedham LL Toniolo P Characterization of dioxin exposure in residents of Chapaevsk, Russia J Expo Anal Environ Epidemiol 2002 12 409 417 12415489
Kumagai S Koda S Miyakita T Ueno M Polychlorinated dibenzo-p-dioxin and dibenzofuran concentrations in serum samples of workers at intermittently burning municipal waste incinerators in Japan Occup and Environ Med 2002 41 362 368 12040109
Schuhmacher M Domingo JL Llobet JM Lindström Wingfors H Dioxins and dibenzofuran concentrations in blood of a general population from Tarragona, Spain Chemosphere 1999 38 1123 1133 10028661
The state of dioxin accumulation in the human body, blood, wildlife, and food: Findings of the fiscal 1998 survey
Schecter A Kassis I Papke O Partitioning of dioxins, dibenzofurans, and coplanar PCBs in blood, milk, adipose tissue, placenta and cord blood from five American women Chemosphere 1998 37 1817 1823 9828310
| 15918907 | PMC1168904 | CC BY | 2021-01-04 16:36:33 | no | Environ Health. 2005 May 26; 4:8 | utf-8 | Environ Health | 2,005 | 10.1186/1476-069X-4-8 | oa_comm |
==== Front
Lipids Health DisLipids in Health and Disease1476-511XBioMed Central London 1476-511X-4-121591670910.1186/1476-511X-4-12ResearchThe effect of Irvingia gabonensis seeds on body weight and blood lipids of obese subjects in Cameroon Ngondi Judith L [email protected] Julius E [email protected] Samuel R [email protected] Nutrition, HIV and Health Research Unit, Department of Biochemistry, P.O Box 812, Faculty of Science, University of Yaounde I, Cameroon2005 25 5 2005 4 12 12 26 2 2005 25 5 2005 Copyright © 2005 Ngondi et al; licensee BioMed Central Ltd.2005Ngondi et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Dietary fibres are frequently used for the treatment of obesity. The aim of this study was to evaluate the efficacy of Irvingia gabonensis seeds in the management of obesity. This was carried out as a double blind randomised study involving 40 subjects (mean age 42.4 years). Twenty-eight subjects received Irvingia gabonensis (IG) (1.05 g three time a day for one month) while 12 were on placebo (P) and the same schedule. During the one-month study period all subjects were on a normocaloric diet evaluated every week by a dietetic record book. At the end, the mean body weight of the IG group was decreased by 5.26 ± 2.37% (p < 0.0001) and that of the placebo group by 1.32 ± 0.41% (p < 0.02). The difference observed between the IG and the placebo groups was significant (p < 0.01). The obese patients under Irvingia gabonensis treatment also had a significant decrease of total cholesterol, LDL-cholesterol, triglycerides, and an increase of HDL-cholesterol. On the other hand, the placebo group did not manifest any changes in blood lipid components. Irvingia gabonensis seed may find application in weight lose.
==== Body
Introduction
Obesity is of major primary care concern and is targeted as an international health objective in Healthy 2000, which seeks to reduce the prevalence of obesity to less than 20%. In the last 10 years, the number of overweight people has increased from 26 to 34% [1]. Conventional dietary and behavioral treatment have failed in long-term management. Dietary strategies used to manage obesity include the use of high fibre, low carbohydrates and fats diet [2,3]. Beneficial effect of dietary fibre in the management of obesity is not well established, since their mechanism of action is not known. The discovery of new medicinal plants has led to the creation of potential drugs that modify feeding behavior and metabolism and may therefore have application in weight management. The aim of the present study is to investigate the effect of Irvingia gabonensis extract on body weight.
Subjects and methods
A total of 40 obese subjects aged between 19 and 55 years were selected from a group responding to a radio advertisement. After physical examination and laboratory screening tests, diabetics, pregnant and lactating women were excluded. None of these subjects took any weight reducing medication and none was following any specific diet. The purpose, nature and potential risks of the study were explained to all patients and a written informed consent was obtained before their participation. The local research ethics committee approved the experimental protocol.
Study design
The study was as a randomised, double blind placebo-controlled crossover design, and consisted of a 4-week treatment period. Subjects were given two different types of capsules containing 350 mg of Irvingia gabonensis seed extract (active formulation) or oat bran (placebo). Three capsules were taken three times daily, one-half hour before meals (a total daily amount of 3.15 g of Irvingia gabonensis seed extract) with a glass of warm water. Capsules were identical in shape, colour and appearance, with neither patients nor researchers knowing what capsule they received. During the experimental period, subjects were examined weekly, with their body weight, body fat, waist and hip circumferences recorded each time. Subjective findings such as increased or decreased appetite, feeling of lightness and gastrointestinal pains were individually noted. Side effects of the active extract, if any were also solicited and noted during each visit. The subjects were also interviewed about their physical activity and food intake during the trial, and were instructed to eat a low fat diet (1800 Kcal) as well as keep a record for seven consecutive days (using household measurements).
Anthropometric measurements
Anthropometric measurements were done at each visit, with body weight and body fat (impedance measurement using a TANITA™ monitor Scale) measurements on fasted (12 hour) subjects wearing light clothing. Waist and hip circumferences were measured by soft non-stretchable plastic tape on the narrowest and the widest parts of the trunk.
Laboratory methods
Blood samples were collected after a 12 h overnight fast into heparinized tubes at the beginning of the study, after two weeks and at the end (4 weeks) of treatment. The concentrations of total cholesterol, triacylglycerol, HDL-cholesterol, and glucose, in plasma were measured using a commercial diagnostic kit (Cholesterol infinity, triglycerides Int, EZ HDL™ cholesterol, EZ LDL™ cholesterol, Glucose Trinder, respectively) from SIGMA Diagnostics
Statistical Analysis
Results are expressed as mean ± SEM except for anthropometric measurements. Paired Student's t-test was carried out on the start and end values of placebo and Irvingia gabonensis capsules and also on the differences between the placebo and Irvingia gabonensis crude extract.
Results
Effect on body composition
Irvingia gabonensis induced a decrease in weight of 2.91 ± 1.48% (p < 0.0001) after two weeks and 5.6 ± 2.7% (p < 0,0001) after one month. Although the percentage of body fat was not significantly reduced with both placebo and IG, the waist circumference (5.07 ± 3.18%; p < 0.0001) and hip circumference (3.42 ± 2.12%; p < 0,0001) were significantly reduced by IG. A reduction of 1.32 ± 0.41% (p < 0.02) and 2.23 ± 1.05% (p < 0.05) was observed with the placebo after two and four weeks respectively of treatment.
Effect on blood pressure
From the second week of experimentation, the systolic blood pressure was significantly reduced by the active extract (Table 2).
Table 2 Effect Irvingia gabonensis on systolic (SBP) and diastolic (DBP) blood pressure
Treatment period (weeks)
0 2 4
SBP (mmHg) Active 136.41 ± 19.57 132.66 ± 18.48* 132.83 ± 17.97*
Placebo 134 ± 5.05 121.5 ± 5.89 123.83 ± 2.92
DBP (mmHg) Active 98.5 ± 19.52 97.5 ± 22.80 94.08 ± 11.07
placebo 93.50 ± 10.31 93.83 ± 7.41 91.5 ± 6.53
Values are means ± sem. Significant differences were at *P < 0.001 by comparison to the placebo group.
Effect on blood lipids components
The plasma total cholesterol cencentration was reduced by 39.21%, triglyerides by 44.9% (p < 0,05) and LDL by 45.58%. This was accompanied by a significant increase in HDL-cholesterol of 46.852%. The CT/HDL ratio (p < 0.05) and the blood glucose level were also reduced (32.36%; p < 0.05). No significant change was observed in the placebo group.
Discussion
The soluble fibre of the seed of Irvingia gabonensis like other forms of water-soluble dietary fibres, are "bulk-forming" laxatives. Irvingia gabonensis seeds delay stomach emptying, leading to a more gradual absorption of dietary sugar. This effect can reduce the elevation of blood sugar levels that is typical after a meal [4]. Controlled studies have found that after-meal blood sugar levels are lower in people with diabetes given glucomannan in their food [5] and overall diabetic control is improved with soluble fibre-enriched diets according to preliminary [6] and controlled [7,8] trials. One double-blind study reported that glucomannan (8–13 grams per day) stabilized blood sugar levels in people with the insulin resistance syndrome [9]. Like other soluble fibers, Irvingia gabonensis seed fibre can bind to bile acids in the gut and carry them out of the body in the faeces, which requires the body to convert more cholesterol into bile acids [10]. This can result in the lowering of blood cholesterol as well as other blood lipids. Controlled double-blind [11,12] studies have shown that supplementation with several grams per day of soluble fibre significantly reduced total blood cholesterol, LDL cholesterol, and triglycerides and in some cases raised HDL cholesterol, these being comparable with effects noticed with Irvingia gabonensis.
Considering the wide use of Irvingia gabonensis in the preparation of various dishes in Cameroon, its use should be further encouraged for the purposes of control of dietary lipids as well as for weight reduction.
Table 1 Effect of Irvingia gabonensis crude extract on body weight, body fat, waist and hip circumferences
Treatment period (weeks)
0 2 4
Weight (kg Active 105.10 ± 16.98 102.3 ± 17.06 101.01 ± 16.63
Placebo 79.43 ± 9.83 79.43 ± 9.83 79.33 ± 10.63
Active 46.11 ± 4.4848 46.5 ± 3.68 45.34 ± 3.52
Body fat (%) Placebo 40.58 ± 3.49 40.58 ± 3.9 40.3 ± 3.8
Active 112.76 ± 20.5 109.7 ± 20.4 106.6 ± 20.79
Waist (cm) Placebo 81.1 ± 7.1 81,91 ± 7,91 81.25 ± 7.52
Active 125.69 ± 11.34 122.92 ± 10.67 121.15 ± 10.39
Hip (cm) Placebo 122.2 ± 10.7 122.2 ± 10.7 121.5 ± 10.9
Table 3 The effect of Irvingia gabonensis on blood total cholesterol (TC), triglyceride (TRI), high density lipoprotein cholesterol (HDL-c), low density lipoprotein cholesterol (LDL-c) and glucose.
T-cholesterol TRI HDL-c LDL-c LDL/HDL T-cho/HDL GLUCOSE
Active Initial 215 ± 55.12 162 ± 33.15 61.23 ± 20.36 121.37 ± 36.3 1.98 ± 1.78 3.51 ± 2.70 3.8 ± 1.92
Final 130.68 ± 39.5 89.22 ± 55.63 89.9 ± 28.44 66.08 ± 34.27 0.735 ± 1.20 1.45 ± 1.38 2.57 ± 1.03
Placebo Initial 163.70 ± 25.32 130.65 ± 37.82 31.38 ± 25.21 105.06 ± 11.86 5.05 ± 3.94 6.44 ± 3.37 3.6 ± 0.41
Final 158.36 ± 30.46 100.52 ± 32.55 41.20 ± 19.53 98.55 ± 27.99 3.19 ± 1.85 4.51 ± 2.07 3.9 ± 0.74
==== Refs
Bray GA Complications of obesity Ann Int Med 1985 103 1052 1062 4062125
Harris MI Epidemiological correlates of NIDDM in Hispanics, whites, and blacks in the U.S. population Diabetes Care 1991 14 639 648 1914813
Weintraub M Long-term weight control study: conclusions Clinic Pharmacol Ther 1992 581 Passaretti S, Franzoni M, Comin U, et al. Action of glucomannans on complaints in patients affected with chronic constipation: a multicentric clinical evaluation. Ital J Gastroenterol 1991;23:421-5
Vuksan V Jenkins DJ Spadafora P Konjac-mannan (glucomannan) improves glycemia and other associated risk factors for coronary heart disease in type 2 diabetes. A randomized controlled metabolic trial Diabetes Care 1999 22 913 9 10372241
Cesa F Mariani S Fava A The use of vegetable fibers in the treatment of pregnancy diabetes and/or excessive weight gain during pregnancy Minerva Ginecol 1990 42 271 4 [in Italian] 2166254
Vorster HH Lotter AP Odendaal I Benefits from supplementation of the current recommended diabetic diet with gel fibre Int Clin Nutr Rev 1988 8 140 6
Hopman WP Houben PG Speth PA Lamers CB Glucomannan prevents postprandial hypoglycaemia in patients with previous gastric surgery Gut 1988 29 930 4 2840365
Doi K Effect of konjac fibre (glucomannan) on glucose and lipids Eur J Clin Nutr 1995 49 S190 7 [review] 8549522
Wu J Peng SS Comparison of hypolipidemic effect of refined konjac meal with several common dietary fibers and their mechanisms of action Biomed Environ Sci 1997 10 27 37 9099424
Arvill A Bodin L Effect of short-term ingestion of konjac glucomannan on serum cholesterol in healthy men Am J Clin Nutr 1995 61 585 9 7872224
Walsh DE Yaghoubian V Behforooz A Effect of glucomannan on obese patients: a clinical study Int J Obes 1984 8 289 93 6096282
Vido L Facchin P Antonello I Childhood obesity treatment: double blinded trial on dietary fibres (glucomannan) versus placebo Padiatr Padol 1993 28 133 6 8247594
| 15916709 | PMC1168905 | CC BY | 2021-01-04 16:39:19 | no | Lipids Health Dis. 2005 May 25; 4:12 | utf-8 | Lipids Health Dis | 2,005 | 10.1186/1476-511X-4-12 | oa_comm |
==== Front
Respir ResRespiratory Research1465-99211465-993XBioMed Central London 1465-9921-6-621597210810.1186/1465-9921-6-62ReviewSerum biomarkers in Acute Respiratory Distress Syndrome an ailing prognosticator Tzouvelekis Argyris [email protected] Ioannis [email protected] Demosthenes [email protected] Interstitial Lung Disease Unit, Royal Brompton Hospital, Imperial College, Faculty of Medicine London, UK2 Department of Pneumonology, Medical School, Democritus University of Thrace, Greece2005 22 6 2005 6 1 62 62 1 4 2005 22 6 2005 Copyright © 2005 Tzouvelekis et al; licensee BioMed Central Ltd.2005Tzouvelekis et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The use of biomarkers in medicine lies in their ability to detect disease and support diagnostic and therapeutic decisions. New research and novel understanding of the molecular basis of the disease reveals an abundance of exciting new biomarkers who present a promise for use in the everyday clinical practice. The past fifteen years have seen the emergence of numerous clinical applications of several new molecules as biologic markers in the research field relevant to acute respiratory distress syndrome (translational research). The scope of this review is to summarize the current state of knowledge about serum biomarkers in acute lung injury and acute respiratory distress syndrome and their potential value as prognostic tools and present some of the future perspectives and challenges.
Serum biomarkersacute respiratory distress syndromeacute lung injurycytokinesKL-6surfactant proteinsadhesion molecules.
==== Body
Introduction
The use of biomarkers in medicine lies in their ability to detect disease and support diagnostic and therapeutic decisions. New research and novel understanding of the molecular basis of the disease reveals an abundance of exciting new biomarkers who present a promise for use in the everyday clinical practice.
The initial evaluation of a serum biomarker concerns its expression in patients with the disease and in normal individuals in order to define sensitivity and specificity. The sensitivity of a test is defined as the proportion of patients with disease having a positive test whereas the specificity is the proportion of patients without the disease who have a negative or normal test. Consequently the serum level of an ideal marker should: 1) increase pathologically in the presence of the disease (high sensitivity), 2) not increase in the absence of the disease (high specificity), 3) relate to the disease burden and extent, 4) change in accordance with the clinical evolution, reflecting the current status of disease, or better 5) anticipate clinical changes, i.e. indicating the presence of relapse before it becomes obvious at a clinical level and finally 6) possess constant serum levels (no major fluctuation) [1].
Additionally, a clinically suitable biomarker should fulfil the following requirements [2]:
1. add independent information about the risk or prognosis
2. account for a large proportion of the risk associated with a given disease or condition
3. be reproducible (as determined by the low coefficient of variation)
4. be sensitive, specific and should present with a high predictive value
5. be of easy and cheap determination
Very few markers present a threshold at which the risk suddenly rises. The interplay between sensitivity and specificity and the nature of the disease under prediction assigns suitable cut-off points. Sensitivity and specificity calculated at various cut-off points give rise to a receiver-operating-characteristic (ROC) curve [2]. A clinically useful biomarker will be one with the largest area under the ROC curve. A number of novel blood biomarkers of lung disease including cytokines, enzymes, adhesion molecules, collagen relevant products and products of type II epithelial cells, have been studied for their clinical applicability.
The scope of this review is based on the fact that although there are numerous published papers investigating the utility of biomarkers in the clinical research field the number of review articles summarizing the current state of knowledge about the clinical applications of these molecules as diagnostic and prognostic tools in the research field relevant to acute respiratory distress syndrome (ARDS) and acute lung injury (ALI) still remains inadequately small.
Serum biomarkers in Acute Respiratory Distress syndrome
ARDS is a clinical and pathophysiologic entity characterized by severe acute injury, directly or indirectly via the blood, to the endothelial and epithelial surfaces of the lung leading to respiratory failure. The main characteristics of the syndrome are diffuse inflammation and increased microvascular permeability that cause diffused interstitial and alveolar oedema and persistent refractory hypoxemia [3]. Although a variety of insults may lead to ARDS, a common pathway may probably result in the lung damage [4,5]. A complex series of inflammatory events have been recognized during the development of ARDS but the exact sequence of the events remains elusive. Immunological studies investigating bronchoalveolar lavage fluid (BALF) have shed further light into the pathogenetic mechanisms of ARDS [6] and formed the basis of concepts of its immunopathogenesis. A large variety of inflammatory mediators (Table 1) have been found to be elevated in the early phase of ARDS, including lung-specific proteins, endotoxin binding proteins, tumor necrosis-alpha (TNFa), interleukins – (ILs) – 1, 2, 6, 8, 15, chemokines, ferritin, markers of endothelium activation (adhesive molecules and von-Willebrand factor antigen-VWF) as well as markers of neutrophil activation such as matrix metalloproteinases (MMPs) and their inhibitors and leukotrienes [5-7]. The majority of these molecules have features to recommend them as biologic markers in ARDS. Biomarkers have attracted a lot of attention in both ALI and ARDS since they can shed further light into the pathogenesis and pathophysiology of lung injury. Additionally, from a practical point of view, a clinical useful biomarker for ARDS must add information regarding the development of syndrome in at-risk patients that is not apparent from routine examination and investigation. The latter, could help the intensivist to monitor the disease and evaluate or modulate treatments before they have failed. Driven by this perspective idea, many studies have estimated their usefulness as early predictors of ARDS and accurate markers of lung injury before clinical changes can be detected.
Table 1 List of studied serum biomarkers in ARDS
Lung epithelium-specific proteins Surfactant-associated proteins
• SP-A
• SP-B
• SP-D
Mucin-associated antigens
• KL-6/MUC1
Cytokines • IL-1
• IL-2
• IL-6
• IL-8
• IL-10
• IL-15
• TNFa
Other serological parameters Markers of endothelium activation
• Adhesion molecules (E, L-selectin, I-CAM-1, V-CAM-1)
• VWF
Markers of neutrophil activation
• MMP-9
• LTB4
Ferritin
Abbreviations: ARDS: Acute Respiratory Distress Syndrome, CC16: Clara-cell protein 16, IL: Interleukin, KL-6: Krebs von den Lungen-6, LTB4: Leukotriene B4 MMP-9: Metalloproteinase-9 MUC: Mucin, I-CAM-1: Intercellular Adhesion Molecule-1, sIL-2R: soluble interleukin-2 receptor, V-CAM-1: Vascular Adhesion Molecule-1, VWF: von Willebrand factor antigen
Cytokines (Tables 2 and 3)
Table 2 Studies measuring cytokines in patients with or at risk for ARDS
Investigator Patients Controls Biomarker / Summary ROC curve analysis Cut-off values Specificity – Sensitivity PPV – NPV Limitations
Pinsky et al. 13 52 at risk Relation of IL-6 and TNF plasma levels to multiple-system organ failure and mortality No Not estimated Small number of patients
No ROC curve analysis / cut-off levels
No serial measurement
Takala et al. 14 20 at risk
56 controls IL-6 and IL-8 plasma levels predict organ failure in community-acquired septic shock No Not estimated Small number of patients
No ROC curve analysis / cut-off levels
Poor discriminative value of serum biomarkers per se
Calandra et al. 15 70 at risk IL-6 plasma levels do not predict the outcome in at risk patients for ARDS No Not reported Small number of patients
No ROC curve analysis
Kiehl et al. 16 19 at risk TNFa, IL-6, IL-8 plasma levels fail to associate with severity and course of ARDS in leukocytopenic patients No Not estimated Small number of patients
No ROC curve analysis / cut-off levels
Leukocytopenic patients
Meduri et al. 18 27 ARDS TNFa, IL-1β, IL-2, IL-4, IL-6, IL-8
Superiority of IL-1β and IL-6 plasma levels in monitoring disease activity over commonly applied clinicophysiologic parameters. Yes
TNFa: 400 pg/ml
IL-1β: 400 pg/ml
IL-2: 200 pg/ml
IL-4: 200 pg/ml
IL-6: 400 pg/ml
IL-8: 400 pg/ml TNFa: 89-50-85-57%
IL-1β: 78-83-83-78%
IL-2: 89-83-90-80%
IL-4: 89-50-85-57%
IL-6: 77-75-81-70%
IL-8: 66-50-66-50% Small number of patients
Perspective study
Overlap of cytokine levels between survivors and non-survivors
Heterogeneity of studied population
Definition criteria of ARDS
Agouridakis et al. 19 8 ARDSa
26 at risk Association between increased levels of IL-2 and IL-15 and outcome in patients with early ARDS Yes
IL-2: 173 pg/ml
IL-15: 250 pg/ml IL-2: 100-100-100-100% IL-15: 100-100-100-100% Small number of patients
Limited number of studied molecules
Abbreviations: ARDS: Acute Respiratory Distress Syndrome, BALF: Bronchoalveolar lavage Fluid, IL: Interleukin, NPV: Negative Predictive Value, PPV: Positive Predictive Value, ROC: Receiver Operating Characteristic, sIL-2R: soluble interleukin-2 receptor, TNFa: Tumor Necrosis Factor-alpha
a: Use the American European Consensus Conference definitions
Table 3 Studies measuring cytokines in patients with or at risk for ARDS
Investigator Patients Controls Biomarker / Summary ROC curve analysis Cut-off values Specificity – Sensitivity PPV – NPV Limitations
Lesur et al. 20 19 ARDSa
14 at risk
20 controls Association of early low serum
IL-2 levels with the patients' survival No Not estimated Small number of patients
No ROC curve analysis / cut-off levels
No serial measurement
Discrepancies in serum and BALF IL-2 levels
Limited number of studied molecules
Parsons et al. 23 77 at risk Association of serum IL-1ra, IL-10 levels with the disease outcome No Not estimated No ROC curve analysis / cut-off levels
Poor predictive value for ARDS development
Limited number of studied molecules
Takala et al. 24 52 at risk
9 ARDSa
45 controls IL-8, IL-6, sIL-2R, E-selectin, procalcitonin
Persistent elevation of inflammatory markers in patients with ALI precedes its clinical diagnosis No Not estimated Small number of non-survivors
No ROC curve analysis / cut-off levels
Poor predictive value for ARDS development
Bouros et al. 25 32 ARDSa
27 at risk IL-4, IL-6, IL-6r, IL-8, IL-10
High prognostic value of all the inflammatory markers in assessing the outcome in patients with or at risk for ARDS Yes
IL-4: 84 pg/ml
IL-6: 160 pg/ml
IL-6r: 18 pg/ml
IL-8: 2340 pg/ml
IL-10: 98 pg/ml IL-4: 78-100-81-100%
IL-6: 59-96-69-94%
IL-6r: 78-76-76-78%
IL-8: 93-96-92-96%
IL-10: 96-92-96-93% Small sample size
No serial measurement
Grouping and definition criteria
Schutte et al. 26 30 ARDSa
44 at risk
17 controls IL-6, IL-8, TNFa
Serum levels of IL-6 and IL-8 in
ARDS and/or severe pneumonia, differentiate these entities from cardiogenic pulmonary oedema No Not estimated Small number of patients
Weak correlations with clinical variables
No definitive predictive value for outcome
Overlap of cytokine levels between survivors and non-survivors
No ROC curve analysis / cut-off levels
Bauer et al. 27 46 ARDSa
20 at risk
10 controls IL-6, IL-1b, TNFa serum levels associate better with the degree of lung injury rather than clarify its specific aetiology No Not estimated Corticosteroid treatment
Inconclusive prognostic value
No serial measurement
Limited number of studied molecules
Abbreviations: ARDS: Acute Respiratory Distress Syndrome, BALF: Bronchoalveolar lavage Fluid, IL-1ra: Interleukin-receptor antagonist, NPV: Negative Predictive Value, PPV: Positive Predictive Value, ROC: Receiver Operating Characteristic, sIL-2R: soluble interleukin-2 receptor, TNFa: Tumor Necrosis Factor-alpha
a: Use the American European Consensus Conference definitions
Cytokines are widely recognized as mediators of an inflammatory response. Their discovery has stimulated multidisciplinary investigation to elucidate the role of these mediators in the injury and repair processes of human disease. In the lung, they are produced either by local resident cells such as alveolar macrophages, pneumocytes, endothelial cells and fibroblasts or by cells such as neutrophils, lymphocytes and platelets arriving to the lung in response to local or systemic injury [8,9]. Cytokines are involved both in the early (TNFa, IL-1, 2, 6, 8, 15) and late phase (IL-4) of inflammation and have been shown unequivocally to be of crucial importance in the pathophysiology of septic shock, a condition frequently culminating to ARDS [10,11].
Studies have demonstrated that in ARDS patients detectable cytokine serum levels are closely related to the disease severity and mortality [11,12], suggesting a potential role in reflecting the severity of the lung injury. Moreover, humoral (IL-6, IL-8) and cellular markers (CD 11b) of systemic inflammation have been delineated to identify patients with septic shock at risk for organ failure, culminating to a fatal outcome [13,14]. However, their monitoring and prognostic value in septic-shock patients still remains controversial. Calandra et al. [15] stated that serum cytokines could not be used as a routine laboratory test to predict the outcome in septic-shock patients. In addition, Kiehl et al. [16] failed to prove usefulness of plasma cytokines measurement for the evaluation of severity and course of ARDS in a small cohort of leukocytopenic septic-shock patients. In the same study, estimation of BALF levels appeared to differentiate between responders and non-responders to treatment before clinical differences become apparent. Nonetheless, it should be noted that the small sample size, the contradictive results, the lack of standardization techniques and uniform definitions for ARDS and at risk patients, together with the heterogeneity of the syndrome and the patients studied generate major concerns regarding the reproducibility and the reliability of the data presented. Consequently, there is a need for further large scale investigations in the context of appropriate clinical trials for any meaningful conclusions to be reached.
Evidence from preceding studies [11-13,16] give credence to the view that the inability of the lung to repair after ALI is the result of a persistent inflammatory stimulus that ultimately leads to an unfavorable outcome [17]. Fueled by this prospect, Meduri and coworkers [18] indicated a consistent, efficient and independent predictive value for IL-1β and IL-6 serological concentrations over time in a small cohort of patients with severe ARDS. They generated ROC curve analysis and demonstrated a clear superiority of inflammatory cytokines in monitoring disease activity over commonly applied clinicophysiologic parameters. However, this study exhibited substantial weaknesses including the retrospective analysis, the small sample size and the overlapping results between survivors and non-survivors. These observations coupled with the heterogeneity of the disease and the evidence that elevated serum cytokines may reflect the increased production or decreased clearance and not the disease activity pose major limitations to the aforementioned findings.
In another study, Agouridakis et al. [19] evaluated both the prognostic and predictive significance of IL-2 and IL-15 for the development and outcome of patients at risk who developed ARDS or patients at risk who never developed ARDS, respectively. They applied ROC curve analysis and showed an excellent predictive value of cytokine plasma levels in terms of specificity and sensitivity compared to those observed in BALF. The most remarkable ascertainment of this study was the emergence of the discriminative usefulness of elevated IL-2 and IL-15 serological concentrations in patients with ARDS or at risk for ARDS. Nevertheless, the small number of patients enrolled combined with the lack of serial measurements throughout the clinical course of the disease and the causal diversity of the syndrome render major uncertainty to these findings.
On the contrary with other analyses [16,18], Lesur et al [20] found lower blood IL-2 levels in patients with ARDS compared to those that never developed the syndrome. In addition, evidence of this study regarding the strong association of early low serum IL-2 levels with the patients' survival corroborated earlier findings [16]. Potential criticism of this study include the small number of patients recruited, the absence of multiple time-point evaluation of the cytokine plasma concentrations and more importantly opposite and disproportional fluctuations of IL-2 content in serum and BALF in patients with or without ARDS.
The role of several inflammatory cytokines in monitoring the disease activity and predicting the survival in patients with ARDS has aroused increasing attention the past decade. One of the most intriguing aspects of the application of these biomarkers in the daily clinical practice is the early detection of patients admitted to the intensive care unit (ICU) that will develop ARDS. This approach will allow anti-inflammatory and other supportive treatments to be evaluated or eventually modified before they have failed. Predictive levels of inflammatory cytokines (IL-1, IL-2, IL-6, IL-8) for ARDS development in at risk patients have been extensively reported with controversial results [16,17,21,22]. The importance of considering inflammatory constituents of serum in patients at risk for ARDS was initially raised by Parsons et al [23]. Authors conducted a large prospective analysis and demonstrated that although immunological parameters (IL-1ra and IL-10) were elevated in patients at risk for ARDS and exhibited a remarkable association with the disease outcome, none of these could predict the development of the syndrome.
These observations were extended by the results of Takala et al. [24] who showed that serum levels of inflammatory mediators albeit their persistent elevation in patients with unresolving ALI, preceding its clinical diagnosis, were of poor discriminative value in patients with ALI that did or did not develop ARDS. Nevertheless, these findings provided us with useful knowledge about the inflammation marker profile on the days preceding diagnosis of ARDS, indicating a potential relation of sustained inflammatory response with a poor outcome.
With this aim in mind, Bouros et al. [25] measured prospectively a slew of cytokines in the serum and BALF in ICU patients to identify predictive factors for the course and outcome of ARDS. The most remarkable result of this analysis was that almost all serum molecules studied showed a high prognostic value in assessing the outcome in patients with or at risk for ARDS. However, laboratory parameters failed to prove a positive correlation with the prediction of ARDS development evidence consistent with earlier studies [23,24]. Moreover, major caveats that should be taken under consideration include the limited number of patients, the lack of sufficient follow-up serum data and the marked causal heterogeneity of the syndrome that could be a reason for the contradictive results reported in previous studies [20,23-25]. Further prospective studies with sufficient statistical power are required to validate these results and ameliorate the predictive role of circulating inflammatory mediators in patients at risk for ARDS.
Although the role of cytokines in the pathogenesis of ARDS has been extensively investigated, their importance in the differential diagnosis has not been clearly defined. It is widely accepted that numerous insults may lead to ARDS following a common pathway. Furthermore, a variety of conditions including severe pneumonia imitate clinical and radiological manifestations of ARDS and thereby it is often difficult to differentiate them. However, this would be a fruitful application because the treatment of these conditions differs considerably. Many groups of investigators have attempted to produce a discriminative systematic inflammatory profile and although much good work has been done towards this direction, the results still remain controversial.
Schutte and co-workers [26] provided us with a really well done and heavily informative paper concerning the systemic cytokine profile in patients with ARDS, severe pneumonia and cardiogenic pulmonary oedema. Authors found remarkably and consistently elevated serum levels of IL-6 and IL-8 in ARDS and/or severe pneumonia, differentiating these entities from cardiogenic pulmonary oedema. Nevertheless, they were unable to separate the various entities of ARDS and states of severe pneumonia based solely on alterations in the immunomodulatory pattern.
To streamline these observations, Bauer et al. [27] tested the potential of inflammatory markers (TNFa, IL-1β, IL-6) to differentiate between these two diseases. Results in harmony with the previous study [26] demonstrated higher TNFa serological concentrations in patients with ARDS from the remaining populations. However, they revealed the ability of immunological parameters to associate better with the degree of lung injury rather than clarify its specific aetiology. No clear relationship between serological data and patients' survival was observed. In addition, this data exhibits major limitations, including the absence of uniform methodology (use of corticosteroid treatment in some of the patients), serial measurements and the lack of knowledge regarding serum alterations in other components of the inflammatory network (Tables 2 and 3).
Other serological parameters
Markers of endothelium activation (Tables 4 and 5)
Table 4 Studies measuring markers of endothelium activation in patients with or at risk for ARDS
Investigator Patients Controls Biomarker / Summary ROC curve analysis Cut-off values Specificity – Sensitivity PPV-NPV Limitations
Donnelly et al. 39 82 at risk
14 ARDSa
62 controls E-selectin levels were not correlated with ARDS development and patients' mortality. L-selectin levels exhibited a significant prognostic value No Not estimated Heterogeneity of studied population (trauma-sepsis)
No ROC curve analysis / cut-off levels No serial measurement
Boldt et al. 40 50 at risk Constantly lower E-selectin, ICAM-1 and VCAM-1 levels in survivors experiencing polytrauma than in nonsurvivors No Not estimated Small sample size
Causal diversity of patient group
No definitive association with patients' mortality
No ROC curve analysis / cut-off levels
Cowley et al. 41 40 SIRS
85 controls Superiority of E-selectin plasma levels in predicting organ dysfunction and death patients with SIRS comparing to ICAM-1 No Not estimated Small number of patients
Causal diversity of patients studied
No ROC curve analysis / cut-off levels
Sessler et al. 43 25 at risk
12 controls Association of elevated ICAM-1
Sequential plasma levels with the severity of shock Yes
ICAM-1: 715 ng/ml (predicting survival) Not reported Small sample size
Heterogeneity of studied population
Inconclusive association with disease Severity
Kayal et al. 44 32 at risk
9 controls Cut off values of E-selectin, ICAM-1 and VWF serum levels predicted survival outcome Yes
E-selectin: 128 ng/ml
ICAM-1: 715 ng/ml
VWF: 717% E-selectin: 73-80-67-85%
ICAM-1: 80-90-75-92%
VWF: 87-8080-87% Small number of patients
Most of the patients developed secondary ALI
Agouridakis et al. 45 23 ARDSa
42 at risk TNFa, IL-1, ICAM-1, VCAM-1
ICAM-1 and VCAM-1 showed a high NPV for ARDS development
Correlation with the disease outcome
None of the studied markers was an independent factor for ARDS development Yes
TNFa: 325 pg/ml
IL-1: 225 pg/ml
ICAM-1: 300 pg/ml
VCAM-1: 260 pg/ml For ARDS development
TNFa: 62-75-38-89%
IL-1: 58-88-39-94%
ICAM-1: 69-75-42-90%
VCAM-1: 73-88-50-95% Small sample size
No serial measurement
None of the studied markers was an independent factor for ARDS development
Abbreviations: ALI: Acute Lung Injury, ARDS: Acute Respiratory Distress Syndrome, ICAM-1: Intercellular Cell Adhesion Molecule-1, IL: Interleukin, ROC: Receiver Operating Characteristic, SIRS: Systematic Inflammatory Response Syndrome, TNFa: Tumor Necrosis Factor-alpha, VCAM-1: Vascular Cell Adhesion Molecule-1, VWF: von Willebrand factor antigen, a: Use the American European Consensus Conference definitions
Table 5 Studies measuring markers of endothelium activation in patients with or at risk for ARDS
Investigator Patients Controls Biomarker / Summary ROC curve analysis Cut-off values Specificity – Sensitivity PPV-NPV Limitations
Rubin et al. 47 45 at risk Elevated plasma VWF is an early predictor of ALI in nonpulmonary sepsis syndrome Yes
VWF: 450% 77-87-80% Small sample size 25% of patients had already lung injury at the time sepsis was diagnosed
Exclusion of patients who developed
ALI from a primary pulmonary source VWF levels measured by an old assay
Ware et al. 48 51 ALI/ ARDSa
4 controls VWF is an independent predictor of hospital mortality in patients with ALI No
VWF:450% 91-44-83-62% Inadequate sample volume
Heterogeneity of studied population
No ROC curve analysis
Ware et al. 49 559
ALI/ ARDSa Significant correlation of elevated VWF plasma levels with mortality, duration of unassisted ventilation and organ failures. No differences of VWF levels between septic and non septic patients No Not estimated Not definitive association with patients' mortality
Lack of knowledge regarding the cellular source and the mechanisms of elevated VWF serum levels
No ROC curve analysis / cut-off values
Moalli et al. 50 35 at risk
10 ARDS
9 controls VWF levels were higher in ARDS compared with at risk
VWF levels are not helpful in predicting ARDS development No Not reported Limited number of patients
No ROC curve analysis / cut-off values
Moss et al. 51 96 at risk VWF is not predictive of development of ARDS Yes
VWF:273%
VWF:399% 47-70%
52-64% Causal diversity of patients studied
No definitive relation with disease severity
Sabharwal et al. 52 22 ARDS
21 at risk No significant association of VWF blood levels with patients' mortality No Not estimated Small sample size
Retrospective study
No ROC curve analysis / cut-off values
Bajaj et al. 53 18 ARDS
15 at risk
27 controls Serum VWF levels were non-useful markers for predicting ARDS in at risk patients Yes
VWF: 300% 71-62-34% Limited number of patients
No serial measurement
Coexisting multisystem organ failure
Heterogeneity of studied population
Moss et al. 54 55 at risk
14 ARDS
11 controls ICAM-1, E-selectin, VWF
Degree of endothelial activation varied in patients at risk for ARDS from different etiologic factors No Not estimated Small sample size
Heterogeneity of studied population
Abbreviations: ALI: Acute Lung Injury, ARDS: Acute Respiratory Distress Syndrome, ICAM-1: Intercellular Cell Adhesion Molecule-1, NPV: Negative Predictive Value, PPV: Positive Predictive Value, ROC: Receiver Operating Characteristic, VCAM-1: Vascular Cell Adhesion Molecule-1, VWF: von Willebrand factor antigen
a: Use the American European Consensus Conference definitions
The pathophysiologic sequence characterizing ALI involves apart from cytokine, free radical, proteases and aracidonic acid metabolites release, the endothelial and neutrophil activation which initiate a cascade of leukocyte-endothelium interactions and adhesions. This is followed by transendothelial migration of neutrophils and release of their cytotoxic products, ultimately resulting to microvascular and tissue injury [28].
Adhesion of neutrophils to the endothelium is regulated by at least three adhesion molecule families including selectins (E, L and P), integrins and the immunoglobulin superfamily (intercellular adhesion molecule- ICAM-1 and vascular cell adhesion molecule-VCAM-1) and by chemotactic signals [29,30]. Initial interactions of leukocytes and the endothelium are mediated by members of the selectin family inducing (loose) contact with the endothelium also known as rolling, followed by firm adhesion requiring members of the integrin (β2) and immunoglobulin family (ICAM-1) [31,32].
In recent years, soluble isoforms of some of these molecules {soluble-(s)-E-selectin, sICAM-1, sVCAM-1} have been detected in the circulating blood under various inflammatory conditions [33-35]. Mechanisms that could potentially explain an increase in circulating adhesion molecules include cytokine-induced (IL-1, TNFa) overexpression by the endothelial cells, increased proteolytic cleavage of endothelial-bound adhesion molecules secondary to endothelial damage or both [33,35]. One attractive feature of these molecules and mostly E-selectin is that since their expression is almost restricted to stimulated endothelial cells [32] their presence in serum should potentially reflect the state of endothelium in disease and subsequently the disease severity in ALI.
Other potential markers of endothelial cell injury that were delineated to shed further light into the pathophysiologic process of ALI include von-Willebrand factor antigen (VWF), a macromolecular antigen that is produced predominantly by endothelial cells and to a lesser extent by platelets and megakaryocytes [36]. Endothelial perturbation (as in at risk state) or injury (as in ARDS) results to the release of VWF from preformed stores into the circulation [37,38]. Therefore, it appears that circulating VWF concentrations may serve as a suitable predictive marker for development of ARDS in patients at risk.
So far, the potential usefulness of adhesion molecules and other markers of endothelial cell damage in reflecting the severity of endothelial damage and predicting the development or the final outcome of the disease is a subject of ongoing controversy. One of the first and most informative studies addressing this important issue was conducted by Donnelly et al [39]. Authors demonstrated in a large cohort of patients at risk for ARDS, that mean circulating levels of sE-selectin were not correlated with subsequent ARDS development and patients' mortality. However, low values of sL-selectin exhibited a significant prognostic value. In contrast, Boldt et al. [40] studying the behaviour over 5 d of adhesion molecules (sE-selectin, sICAM-1 and sVCAM-1) in subjects experiencing polytrauma found constantly higher levels in nonsurvivors. In accordance to these findings, Cowley and colleagues [41] showed a superiority of sE-selectin plasma levels in predicting organ dysfunction and death in a group of patients with systemic inflammatory response (SIRS) comparing to sICAM-1 peripheral concentrations. This indicated that measurement of adhesion molecules could serve to advantage in the management of patients with sepsis. Nonetheless, the heterogeneity of patients studied (septic shock and polytraumatic) may justify these controversial results, since E-selectin expression has been found much greater in septic than in traumatic shock in experimental models [42].
Moreover, the relationship between the consequences of sepsis (organ failure, mortality) and blood levels of potential markers of endothelial-cell activation was strengthened by Sessler and co-workers [43]. Results from this study focusing on sICAM-1 sequential plasma levels, were suggestive of a strong association between the severity of shock (as determined by the presence of hypotension and the requirement of vasoactive drugs) and the circulating concentrations of the marker. The aforementioned observations were further confirmed by the study of Kayal et al [44]. Cut off values for three markers of endothelial activation were determined prospectively by ROC curve analysis and clearly predicted survival outcome with high sensitivity and specificity in a limited number of at-risk patients with secondary ALI.
Despite that the role of soluble adhesion molecules in other inflammatory conditions strongly associated with ARDS [40-44] is well known, their value as markers of the disease progression and mortality has not been extensively studied in ARDS patients. To streamline these observations, Agouridakis et al. [45] scrutinized the role of two adhesion molecules (ICAM-1, VCAM-1) in parallel with proinflammatory cytokines in predicting the ARDS development and relating to the disease outcome. None of the studied mediators was found to be an independent factor for ARDS development, whereas both groups of molecules exhibited a considerable negative predictive value for ARDS development both in serum and BALF. Additionally, ROC curve analysis showed a clear superiority of plasma parameters in correlating with the disease outcome compared with BALF molecules. Further studies with serial BALF and serum measurements should be designed to elucidate the exact role of these markers over time in reflecting the disease behaviour and predicting the likelihood of progression.
Elevated circulating concentrations of VWF in patients with ALI/ARDS were first reported in 1982 [46]. Their potential significance in predicting ARDS development was first demonstrated by Rubin and colleagues [47] who found that increased plasma levels of this marker exhibited a high predictive value both for the development of ARDS and for identifying patients with nonpulmonary sepsis who were unlikely to survive. However, authors did not use the uniform criteria for the definition of ARDS and risk state [3], evidence that poses major limitations to the results of the study.
Furthermore, in an aforementioned study, Kayal et al. [44] in parallel with other findings reported a marked and independent association of circulating VWF with the disease severity as assessed by other commonly applied clinical variables. These findings were further supported by a single-center study from Ware et al [48]. They conducted the first comparative study of VWF concentrations in both plasma and edema fluids of patients with early ALI from a variety of causes and reported that serum VWF levels were an independent predictor of hospital mortality and were associated with longer duration of mechanical ventilation. Potential criticisms of this study was the implementation of high tidal volume ventilation that possibly increased systemic endothelial activation, the small sample size, the lack of sequential measurement and the fact that the studied biomarker appeared not to be endothelial-specific since it is produced in small amounts by platelets [36].
To streamline these observations and ameliorate potential hardships the same group of authors {Ware et al. [49]} carried out a multicenter study of 559 patients with ALI and ARDS which was recently published. In accordance with earlier studies [48], a significant correlation of elevated VWF plasma levels with adverse outcomes, including mortality, duration of unassisted ventilation and organ failures was pointed out. Intriguingly, authors demonstrated for the first time a negative association between markers of endothelial activation and presence or absence of sepsis, supporting the hypothesis that ALI might be an independent cause of systemic endothelial activation and injury. Finally, in the same study no modulation of plasma VWF concentrations by protective mechanical ventilation was observed. Despite the remarkable power of the presented findings, there are substantial weaknesses that deserve further investigations including the inconclusive analysis of the plasma VWF levels associated with patients' mortality, the lack of definite knowledge regarding the source of VWF production, and the mechanisms leading to increased peripheral concentrations since the latter also could reflect decreased clearance from the circulation.
Subsequent data derived from other studies [50-54] was rather contradictive and controversial. Even though, Moalli et al. [50] found a poor predictive value of serum VWF levels for the development of ARDS in a group of at risk patients, the biomarker concentrations were correlated with the disease severity,. Similarly, Moss et al. [51] plotted ROC curves and concluded that in patients at risk for ALI/ARDS from multiple causes, serum VWF levels failed to reliably discriminate which patients would develop ARDS. The evidence was further validated by Sabharwal et al [52]. Authors conducted the first study comparing plasma levels between survivors and nonsurvivors in a group of patients both at risk for and with established ARDS and observed no significant association of VWF blood levels with patients' mortality ;predictive value of the marker was not reported. In agreement with the previous study, a study from the same group of scientists {Bajaj et al. [53]} using standard criteria for the definition of ARDS and at risk state [3] demonstrated the inability of three endothelial-specific proteins including VWF to predict the progression of ARDS in at risk patients. Nonetheless, major caveats that should be addressed include the fact that many at-risk patients had already some degree of ALI, the lack of serial measurement that could potentially show a trend towards prediction of ARDS development and the causal diversity of patients examined that could possibly affect the results of the study. The latter limitation was addressed by Moss et al. [54] who established that the degree of endothelial activation as determined by the plasma levels of VWF (higher in subjects with sepsis than patients with trauma) is not uniform in all patients at risk for developing ARDS.
Accumulated evidence from the preceding studies suggest that the etiologic diversity of patients enrolled renders major uncertainty to the reliability of the results and highlights the necessity for further prospective studies using standard criteria for the definition of ARDS and analyzing well defined and uniform group of at risk patients in order to produce knowledge of high scientific rigidity. Direct comparison of the different studies is difficult and in a way meaningless because of the use of varying definitions for ARDS and at-risk patients as well as the inclusion of different patient populations, in which of them some degree of ALI was probably already present (Tables 3a and 3b).
Markers of neutrophil activation (Table 6)
Table 6 Studies measuring markers of neutrophil activation and ferritin in patients with or at risk for ARDS
Investigator Patients Controls Biomarker / Summary ROC curve analysis Cut-off values Specificity – Sensitivity PPV – NPV Limitations
Pugin et al. 60 31 at risk
23 ARDSa IL-8, MMP-2, MMP-9
Plasma levels of inflammatory activity are not useful markers in differentiating permeability from hydrostatic pulmonary edema No Not estimated Measurement of circulating proinflammatory cytokines without the appreciation of their inhibitors or receptor antagonists is misleading mainly due to a possible neutralization
Small number of patients
No ROC curve analysis / cut-off values
Amat et al. 64 21 ARDSa
14 at risk Strong association of LTB4 and IL-8 serum levels with the patients' survival. Yes
LTB4: 14 pmol/ml
IL-8: 150 pmol/ml LTB4 + IL-8: 88-70-85-75% (markers of mortality rate)
LTB4 : 85-72-20-98% (marker of ARDS development) Small sample size
Lack of adjustment with the disease severity
Inability of LTB4 plasma levels to be an independent predictive marker
Connelly et al. 66 75 at risk
8 ARDSa Serum ferritin is a sensitive and specific predictor of ARDS development Yes
Ferritin (male):270 ng/ml
Ferritin (female): 680 ng/ml 71-83-86-67%
90-60-82-75% Limited number of ARDS patients
Heterogeneity of studied population
Sharkey et al. 67 42 at risk
16 ARDSa Correlation of ferritin plasma levels with the development of ARDS, multiple organ failure and severity of lung injury Yes
Ferritin (male):270 ng/ml
Ferritin (female): 680 ng/ml 64-73-75-62%
92-60-95-75% Inadequate sample volume
Not specific cut-off values
Elevated serum levels may reflect a systemic response to a risk factor
Abbreviations: ARDS: Acute Respiratory Distress Syndrome, IL: Interleukin, LTB4: Leukotriene B4, MMP-Metalloproteinase, NPV: Negative Predictive Value, PPV: Positive Predictive Value, ROC: Receiver Operating Characteristic, a: Use the American European Consensus Conference definitions
Generally, it is strongly believed that ARDS arises as a result of tissue injury secondary to sequestration of inflammatory cells, tissue invasion, and secretion of cytotoxic products. Neutrophils have received much attention as key part of this process. Although ARDS has been described in neutropenic patients [16,55] there is increased evidence implicating neutrophils in most cases of ARDS. They have been reported by several studies [56,57] to exert an important role in the early phase of ALI characterized by architecture remodeling, surfactant and epithelial toxicity. They use a wide array of enzymes during the process of transmigration through biological membranes such as alveolar-capillary barrier [58]. These enzymes include, metalloproteinases (MMPs) such as MMP-9 also called gelatinase B which is secreted from preformed neutrophil granules in response to a variety of stimuli including proinflammatory cytokines (IL-8, TNFa). MMP-9 is secreted as a zymogen, and then activated by a variety of other proteases such as elastase, and plays a crucial role in digesting basement membranes [58,59]. Therefore, it has been speculated that metalloproteinases probing aspects of the inflammatory response could be utilized as markers of neutrophil activation and subsequently to reflect disease activity and severity, shedding further light into the pathogenesis of ARDS.
Fueled by this prospect, Pugin et al. [60] compared the concentrations of proinflammatory cytokines and collagenases in serum and pulmonary oedema fluids in a small group of patients with ARDS and hydrostatic oedema from congestive heart failure. Authors concluded that elevated pulmonary oedema levels of these mediators could differentiate between these conditions, whereas plasma levels of proinflammatory and metalloproteinase activity proved to be of poor discriminative value. The latter observation mirrors the hypothesis that the inflammatory response characterizing ARDS patients is well compartmentalized, with little spillover into the circulation and that the measurement of circulating proinflammatory cytokines without the appreciation of their inhibitors or receptor antagonists is misleading mainly due to a possible neutralization.
To gain a more comprehensive understanding on the role that neutrophils exhibit during the inflammatory cascade resulting to ALI, investigators scrutinized the utility of other chemotactic agents including leukotrienes (LTs). LTs (B4, C4, D4, E4) exert a synergistic role with IL-8 in the neutrophil influx and activation leading to a massive recruitment of neutrophils and to a catastrophic inflammatory response. Their BALF levels have been found elevated in patients with ARDS and their involvement in the alterations of microvascular permeability correlated with the accumulation of pulmonary oedema has been suggested [61-63].
Moreover, Amat et al [64] utilizing ROC curve analysis demonstrated that LTB4 plasma levels could serve as a valuable predictive marker of ARDS in terms of specificity and sensitivity. In the same study, authors performed serial measurement and reported a strong association of both LTB4 and IL-8 peripheral concentrations with the patients' survival. However, the small number of patients enrolled, the lack of adjustment with the disease severity and the inability of LTB4 plasma levels to be an independent predictive marker arise major concerns whether they could monitor disease behaviour and predict ARDS development in at risk patients (Table 6).
Ferritin (Table 6)
Ferritin is a 480-kDa iron-storage protein that sequesters iron in the ferric (Fe3+) state. It has been speculated that ferritin may serve as a crucial antioxidant mediator because free iron enhances the formation of highly toxic hydroxyl radicals from superoxide anion and hydrogen peroxide. On the other hand, oxidative stress is a condition commonly seen in disorders at risk for ARDS development such as sepsis. Hence, ferritin-derived iron may aggravate oxidative damage in critically ill patients, contributing to the pathologic abnormalities encountered in ARDS. Furthermore, proinflammatory cytokines such as IL-8, IL-6 and TNFa which are increased and presumably participating in the pathogenetic derangements of ARDS have been suggested to promote ferritin synthesis [39,65]. Thereby, it can be concluded that elevated ferritin levels could result from oxidative stress, proinflammatory cytokines and the degree of lung injury, all conditions characterizing the pathogenesis of ARDS and subsequently can be used as prognostic and monitoring tool reflecting the likelihood of ARDS development and the disease severity.
The first study attempted to prove such correlation was conducted by Connelly et al [66]. They plotted ROC curves to estimate the utility of ferritin levels as prognostic factors and produced clinically useful cut-off points which could predict the development of ARDS with high sensitivity, specificity, negative and positive predictive value, both in male and female predominantly septic subjects. However, the heterogeneity of the etiologic factors resulting to ARDS development in at risk patients renders major uncertainty to the rigidity and reliability of the results.
To ameliorate this hardship, the same group of authors {Sharkey et al. [67]} generalized and extended the latter results in a homogeneous group of at-risk patients with multiple trauma demonstrating a strong correlation of initial ferritin plasma levels with the development of ARDS and multiple organ failure. In addition, an association of serum ferritin levels with the severity of lung injury as well as other markers of endothelial activation was also noted supporting the premise that elevated levels could reflect the inflammatory status encountering in ALI. Nonetheless, authors failed to detect specific predictive cut-off values suggesting that circulating concentrations of this biomarker are unable to predict per se the progression to ARDS. A possible explanation could arise from the hypothesis that elevated levels of this marker must reflect a systemic response to a risk factor, which may prove to reduce its specificity (Table 6).
Lung epithelium-specific proteins (Table 7)
Table 7 Studies measuring lung-specific proteins in patients with or at risk for ARDS
Investigator Patients Controls Biomarker / Summary ROC curve analysis Cut-off values Specificity – Sensitivity Diagnostic accuracy Limitations
Doyle et al. 81 15 ARDSa
10 at risk
10 controls SP-A is an acute indicator of lung function and alveolocapillary membrane injury No Not estimated Small number of patients
No ROC curve analysis / cut-off values
No definitive relation with disease severity
Doyle et al. 82 22 ARDSa
10 at risk
33 controls Superiority of SP-B compared to SP-A plasma levels as a marker of lung function and alveolocapillary membrane injury No Not estimated Only 3 case-control studies
Inadequate sample size
Lack of adjustment with disease behaviour
No ROC curve analysis / cut-off values
Greene et al. 83 41 ARDSa
22 at risk
35 controls SP-A, SP-B, SP-D
Serum changes found to be neither sensitive nor specific in predicting the onset of ARDS and discriminating survivors from non-survivors. Yes
Not reported Poor predictive value
Low specificity/sensitivity Limited number of patients
Serial measurements for a short period of time/ Lack of serial measurement for the most severe forms
Heterogeneity of studied population
Poor predictive value for serum levels
Cheng et al. 84 36 ARDSa
2 ALI SP-A levels were associated with severity of clinical lung injury and with disease outcome No Not estimated Small sample size
Causal diversity of studied population
No serial measurement
Greene et al. 85 51 at risk
26 ARDSa
16 controls SP-A levels are predictive for at risk patients who developed ARDS from sepsis and aspiration but not trauma No Not estimated Small sample size
No ROC curve analysis / cut-off levels
Bersten et al. 86 54 at risk
9 controls SP-B but not SP-A cut-off plasma levels predict ARDS development, particularly in at-risk patients suffering a direct lung injury Yes
SP-B: 4.994 ng/ml 78-85-85-78% Small number of patients
Limited follow-up serum data
Most of patients had already lung injury
Exclusion of milder at risk patients
Eisner et al. 87 565
ALI/ ARDSa SP-A, SP-D
Attenuation of SP-D plasma levels by lower volume ventilation strategies No Not estimated Only 2 serial measurements
Heterogeneity of studied population Potential selection bias
No ROC curve analysis / cut-off levels
Ishizaka et al. 95 35 at risk
27 ARDSa
21 controls Association of optimal cut-off values of KL-6 serum levels with patients' mortality Yes
KL-6: 253 U/ml 100-87% Inadequate sample volume
Heterogeneity of studied population
Sato et al. 96 28 ARDSa
10 controls Association of KL-6 serum levels with variables of lung injury severity and with mortality rates
No correlation with ventilation strategies No Not estimated Small sample size
Heterogeneity of studied group
No serial measurement
No ROC curve analysis / cut-off levels
Diversity of ventilatory treatment
Abbreviations: ALI: Acute Lung Injury, ARDS: Acute Respiratory Distress Syndrome, BAL: Bronchoalveolar Lavage, KL-6: Krebs von den Lungen-6, ROC: Receiver Operating Characteristic, SP: Surfactant Protein, a: Use the American European Consensus Conference definitions
Beyond other important functions, the lung epithelium produces complex secretions, including mucus blanket, surfactant proteins, as well as several proteins important for host defense [68].
Sampling the epithelial lining fluid by bronchoalveolar lavage (BAL) represents the common means of studying the proteins secreted by the lung epithelium and investigating their alterations in lung disorders [69]. However, the past fifteen years pioneering studies [70] showed the presence of these proteins in the bloodstream as well, even though in small amounts. Because these proteins are mainly, if not exclusively secreted within the respiratory tract, their occurrence in the vascular compartment can be explained by several hypothetical mechanisms including, leakage from the lung into the bloodstream, increased production by the alveolar type II cells or diminished clearance rates from the circulation [68].
Surfactant-associated Proteins
Pulmonary surfactant is a complex and highly surface active material covering the alveolar space of the lung. Biochemically, surfactant is a molecular mixture composed mainly of structurally heterogeneous phospholipids. A major function of pulmonary surfactant is to reduce the surface tension at the air-liquid interface of the alveolus, thereby preventing alveolar collapse on expiration. It has also been demonstrated that the surfactant contains specific proteins [71]. Four surfactant-specific proteins with different structural and functional properties have so far been identified. They were named surfactant protein-(SP)-A, SP-B, SP-C and SP-D according to the chronologic order of their discovery [72] and have been divided in two distinctive groups, the low-molecular-weight hydrophobic SP-B and SP-C and the high-molecular-weight-hydrophilic SP-A and SP-D. The latter belong to the collectin subgroup of the C-type lectin superfamily and are produced by two types of non-ciliated epithelial cells in the peripheral airway, Clara cells and alveolar type II cells. Studies have demonstrated that SP-B and SP-C seem to play an essential role for the adsorption of phospholipids to the air-water interface resulting to a stable phospholipids film and for the dynamic surface-tension-lowering properties [73]. Additional functions of the alveolar surfactant system include prevention of alveolar edema [74] and a pronounced influence, especially of the collectins SP-A and SP-D in the innate immune system of the lung [75,76] and have been used as useful markers for confirming the diagnosis and evaluation of disease activity of various ILDs since they reflect the epithelial damage and turnover [77]. Thus, it has been speculated that alterations of SPs in biological fluids could serve as valuable markers of the severity of the lung injury or clinical outcome in ARDS patients.
Most of our knowledge regarding changes in SP concentrations that occur in patients with or at risk for ARDS and their value in reflecting the disease severity or the likelihood of ARDS development comes from BAL studies. Several reports in the literature have demonstrated the occurrence of low SP-A levels in BALF of patients with ARDS following trauma [78,79] coupled with a strong relation of this biological marker to the severity of endothelial damage [80]. Moreover, a potential value of SP-A plasma levels in discriminating patients with ALI of various etiologic factors has also been shown [79]. On the other hand, little is known about changes in peripheral concentrations of surfactant-associated proteins in patients with ALI and whether these alterations can serve as markers of injury to the epithelial and endothelial barriers in the lungs.
Doyle et al. [81] documented elevated circulating concentrations of SP-A in patients with ARDS and in those with acute cardiogenic pulmonary edema possibly resulting from increased alveolocapillary permeability due to excessively high pulmonary capillary pressures. In the same study, blood SP-A levels were inversely associated with blood oxygenation and static respiratory system compliance. These results were fully confirmed by the same group of authors {Doyle et al. [82]} who also illustrated a clear superiority of SP-B compared to SP-A plasma levels as a marker of lung function and alveolocapillary membrane injury.
Another study by Greene et al. [83], evaluated the differences that occur in SPs in BALF and serum of a relatively small cohort of patients at risk for ARDS and during the course of the syndrome. Authors demonstrated that only SP-A and SP-D BALF levels were strongly related to outcome and likelihood of disease progression whereas serum changes found to be neither sensitive nor specific in predicting the onset of ARDS and discriminating survivors from non-survivors.
These data were further confirmed by a small cohort observational study by Cheng et al [84]. Even though authors reported an association of elevated SP-A plasma levels with a high degree of lung injury, they failed to extend this correlation with the disease mortality. Moreover, serum SP-D levels exhibited weak relation to the disease severity. It should also be noted that the aforementioned results present low statistical power due to the limited number of patients, the causal heterogeneity of the studied group and the absence of serial measurement and therefore no meaningful outcome can be excluded.
In harmony with the latter results, Greene et al. [85] found that plasma SP-A was weakly predictive for ARDS development in septic patients and were unable to detect at risk trauma patients that developed the syndrome. Additionally, authors raised the crucial issue whether circulating SPs can reflect pathophysiologic differences between direct and indirect causes of ARDS and subsequently detect biologic changes early after an insult. From a pragmatic clinical perspective the most important question to be answered is which ICU patients requiring ventilatory assistance will develop ARDS.
To do so Bersten et al. [86] generated ROC curve analysis and identified practical thresholds for SP-B plasma levels that could be clinically useful in predicting ARDS development, particularly in at-risk patients suffering a direct lung injury. In consistency with earlier studies [83-85] SP-A blood levels added no significant information on the disease prognosis. Further, an increase of circulating SP-B concentrations was documented on study entry, before changes in commonly applied clinical variables for the assessment of lung injury become apparent. These findings emphasize the usefulness of surfactant-associated proteins for the early detection of ARDS pathophysiologic alterations preceding changes in clinical parameters such as respiratory dysfunction. Arguments that can be made include the small sample size, the limited sequential measurements and the exclusion from the study recruitment of at risk patients with milder pulmonary dysfunction. These caveats coupled with the evidence that a considerable number of patients studied had already lung injury, pose major limitations to the predictive capacity of SP-B plasma levels and raise the necessity for larger prospective studies.
The only so far large multicenter randomized controlled trial was performed by Eisner et al. [87] who estimated the prognostic value of SP-A and SP-D levels in an overall of 565 patients with early ALI/ARDS. Authors conducted the first study with adequate statistical power to examine the impact of SPs on mortality and other clinical variables and clearly demonstrated a strong linkage of elevated SP-D levels with worse clinical outcomes such as greater risk of death, fewer ventilator- free and organ failure-free days. One of the most remarkable ascertainments of this study was the attenuation of SP-D plasma levels by the lower volume ventilation strategies which reduces patients' mortality postulating for the first time a significant association of biological parameters with therapeutic approaches and subsequently emphasizing the role of this mediator as a marker of the disease severity and prognosis. However, this study exhibited substantial weaknesses including the lack of sufficient serial measurements, a potential selection bias of patients recruited and the diversity of predisposing factors for ARDS development. These observations are not to diminish their value as prognostic and monitoring tools but to highlight the need for further confirmation studies using independent and well-defined populations of ALI/ARDS patients.
Mucin-associated Antigens
Mucins are major components of the mucus layer covering the airway epithelium. They consist of high-molecular-weight glycoproteins belonging to a broad family of mucin peptides [68]. Mucins are either associated with membranes or secreted at the surface of the respiratory tract [68]. Krebs von den Lungen-(KL)-6 is mainly associated with cellular membranes. It was initially described by Kohno et al. [70] as a high-molecular-weight glycoprotein and was classified as human MUC1 mucin. Immunohistochemistry has mainly detected KL-6 in alveolar type II and epithelial cells of the respiratory bronchioles. KL-6 is predominantly expressed by airway cells; however, is not entirely lung specific, since it is also present on other somatic cells, such as pancreatic cells, eosophageal cells and fundic cells of the stomach [88]. Additionally, KL-6 is a sensitive indicator of damage to alveolar type II cells, which strongly express this mucin at their surface [70]. Type II pneumonocytes are regenerated over the alveolar basement membrane after the death of type I pneumonocytes over the first stage of lung injury. Therefore, its raise would theoretically represent the destruction of the normal lung parenchyma and architecture, the increased permeability of the air-blood barrier as long as the regenerating process as expressed by type II pneumonocytes' activity.
Towards this direction, the presence of KL-6 has been extensively used with great promises to monitor the severity of disease in idiopathic pulmonary fibrosis [89-91] and other interstitial lung diseases [92-94]. Since damage to, and disruption of, the alveolar epithelial lining coupled with loss of integrity of the air-blood barrier represent key features in the pathophysiology of ARDS, KL-6 serum levels could potentially serve as valuable indicators of the disease severity directly assessing the degree of epithelial damage and predicting the progression to ARDS. Nevertheless, only few studies so far, have evaluated their monitoring and prognostic efficacy in patients with or at risk for ARDS development.
One of the first studies to do so was recently carried out by Ishizaka and co-workers [95]. Authors generated ROC curve analysis and documented a highly sensitive and specific association of optimal cut-off values of KL-6 serum levels with patients' mortality. The latter, further supports the premise that disruption of the alveolar barrier represents a major determinant of prognosis of ALI and that serial measurements of KL-6 plasma levels might be helpful markers of the disease progression. Limitations that should be addressed include the limited number of patients, the retrospective analysis of the results and the diversity of the etiologic factors of ALI generate major concerns about the reproducibility and the reliability of the data.
Recently, Sato et al. [96] sought to determine potential correlations of KL-6 circulating concentrations with disease severity, patients' survival and different predisposing factors of ARDS. The most remarkable ascertainments of this study include strong associations of KL-6 peripheral levels with variables of lung injury severity and with the rates of mortality indicating possible relationship between the degree of epithelial damage and poor outcome in ARDS. Even though, authors attempted to show a modulation of KL-6 serum levels by ventilatory strategies, this relationship failed to reach a statistical significance. Despite substantial weaknesses exhibited such as the lack of serial measurement, the small sample size and the diversity of the applied treatment data derived from this study is highly informative and provides important knowledge regarding the biological impact of mechanical support strategies in this syndrome indicating the monitoring value of the epithelial damage markers. Further and sizeable prospective studies are required to validate the aforementioned hypothesis (Table 7).
Future challenges and limitations
The ARDS represents an overwhelming inflammatory reaction to numerous insults within the pulmonary parenchyma resulting in life-threatening derangements in pulmonary vasomotion, alveolar ventilation and gas exchange. ARDS is a frequent disease with a devastating incidence between 13.5 and 75 per 100,000, thus affecting about 16–18% of all patients ventilated in the ICU [76,97]. Hence, ALI/ARDS is a major public health problem encountered frequently by all physicians who care for critically ill patients. Despite the fact that research efforts over the past several years have provided a more comprehensive knowledge of the potential mechanisms comprising the immunopathogenesis of ALI/ARDS and led to the development of innumerable causative or symptomatic treatment approaches, the mortality rate of these patients remains unacceptably high at 30–40% [97]. Currently, the only therapy that has been proven to be effective at reducing mortality is a protective ventilatory strategy [98]. However, new therapies are still needed. One of the most fruitful applications is monitoring the disease activity and consequently the early identification of at risk patients with increased likelihood of non-response to treatment and progression to ARDS. Nevertheless, there are problems with the sensitivity, effort-dependability and ease of repetition of the current modalities being used for this purpose, including radiological and BAL techniques as well as clinical and physiological indices of pulmonary injury (Murray score), systemic illness (Acute Physiology and Chronic Health Evaluation- APACHE-II score and Simplified Acute Physiological Score -SAPS), ARDS severity (respiratory system compliance and PaO2/FiO2 ratio) and multiorgan system failure (Multi-Organ Dysfunction Score-MODS). Most of these clinical parameters have failed to be independent predictors of mortality in studies of adults with ALI/ARDS [99,100]. Development of a prognostic index that combines clinical and biological determinants may be useful to ameliorate these hardships.
On the basis of this conception, a large body of serum markers either cytokines and lung-specific proteins or markers of endothelium and neutrophil activation as well as other serological parameters probing different facets of the immunopathogenesis of ALI/ARDS has been delineated. The applications of these markers in the clinical setting created major expectations in terms of defining categories of patients for different therapies or prognosis for the purpose of counseling families and patients and/or possibly identifying novel therapeutic targets. The determination of a reliable serologic marker reflecting the disease behaviour and adding independent information regarding the development of the syndrome before it becomes obvious in clinical level, easily reproducible and feasible to be measured serially represents a major challenge. The early serial measurement of this biomarker may serve as an independent non-invasive prognosticator of the disease outcome even at the onset of the syndrome and therefore lead to an early detection of at risk patients with increased likelihood of progression to ARDS. The latter, if sufficiently accurate, could prove extremely useful in identifying and counseling families of patients at low or high risk for adverse outcomes and further, will allow ventilatory or other types of treatment to be evaluated or eventually modulated before they have failed in the high risk group. The presented data give credence to the view that multiple biomarkers can be used to measure the lung and systemic response to a protective ventilatory strategy and potentially to discriminate patients who are ineffectively treated and might be candidates for rescue therapies [49,87].
More importantly, use of one or more of these biologic markers to select a group of patients at higher risk of adverse clinical outcome could be used to restrict or stratify enrollment in future clinical trials applying novel ventilator treatments such as high-frequency oscillatory ventilation leading to a better patient care. Thereby, a combination of clinical factors and biologic marker measurements could be crucial for the selection of more homogeneous groups of patients with ALI/ARDS for further studies producing evidence of high scientific rigidity [101]. Finally, understanding the relative roles of markers of systemic and pulmonary endothelial injury and other inflammatory mediators to the pathogenetic process of the syndrome is likely to lead to valuable insights into the final pathway resulting in diffuse alveolar damage and significant lung dysfunction, highlighting therapeutic targets for novel interventions. The aforementioned components can potentially compile a clinician's "wish list".
However, the feeling of excitement arising from the expected clinical utility comes in contrast with important deficiencies exhibited by the new methodologies including non-standardization techniques, lack of knowledge of reproducibility and link to disease behaviour. Furthermore, most of the studies enrolled a limited number of patients, insufficient to extract any meaningful or statistically significant outcome. In addition, the heterogeneity of the studied population resulting from the causal diversity of the syndrome and the use of non-uniform criteria for the definitions of ARDS and at-risk patients (Tables 2, 3, 4, 5) render major uncertainty to the reproducibility and the scientific rigidity of these findings and may explain potential discrepancies between various studies investigating different groups of at risk patients.
Moreover, many of the caveats arising from this data are generated by the origin disadvantages of the investigated serological parameters to serve as specific markers of the disease activity and severity. In particular, it is well known that assays of circulating cytokine concentration may be misleading, because they do not detect receptor or cellular bound cytokines, or they may fail to detect cytokines when inhibitors or receptor antagonists are present. Thus, measured cytokine concentrations may not reflect the disease activity or the state of inflammation but the increased production or decreased clearance from the circulation. In consistency with these limitations, it should be underlined that cytokines are part of an inflammatory cascade and biological effects are difficult even impossible to interpret without the appreciation of the entire network of the inflammatory response. Hence, data in most of the studies was inconclusive and incomplete since none of them analyzed serum alterations of a considerable number of inflammatory components.
Additionally, it is of high importance to note that unfortunately only few studied molecules (VWF, IL-1β, IL-6, ICAM-1, VCAM-1) exhibited independent discriminatory power [18,44,48,49] and associated with the mortality of patients with high sensitivity and specificity [45]. Finally, only the minority of the studies [18,19,25-27,43,45,47,51,53,64,66,67,83,86,95] clarified the effectiveness and the diagnostic accuracy of the biomarkers by applying ROC curve analysis which is essential to estimate the sensitivity and specificity of a marker and to introduce clinically practical cut-off levels for the prediction of ARDS development in at risk individuals.
Collectively, these findings highlight the necessity for further investigations in the context of large prospective studies analyzing homogeneous and well defined group of ARDS or at risk patients and the assessment of novel molecules to serve as diagnostic and prognostic tools, as well as markers of the disease activity and severity.
Conclusion
Currently, the application status in routine clinical practice for most of these biologic markers is still in its infancy and remains exploratory. Unfortunately, they do not yield independent indications for therapy or mark the end of the inflammatory process and their prognostic value still needs to be established. Although the majority of them have not yet lived up to the "great hype" that was generated, markers of endothelium activation and mostly VWF and adhesion molecules (ICAM-1, VCAM-1, E-selectin) show the greatest promise in ARDS and ALI. On the contrary the majority of serum cytokines and ferritin appear to be not ready for routine monitoring since they may reflect an inflammatory response to a risk factor rather than lung injury and disease severity. Additionally, lung specific proteins have proven to be neither specific nor sensitive for the prediction of ARDS development and the disease outcome and moreover they have failed to associate with alterations in the ventilatory strategies in large clinical trials. Further prospective investigations, technical improvements and introduction of novel markers are warranted in order to elevate the association of serum biomarkers with the pathogenesis of ARDS in the same status as for tumour markers with lung cancer. Nevertheless, crossing the boundary from research to clinical application requires validation in multiple settings, experimental evidence supporting a pathophysiologic role, and ideally intervention trials showing that modification improves the outcome. The emergence of pioneering technologies including DNA microarrays which have already been applied with great success in the respiratory research field [102] can help scientists to circumvent this problem and bridge this boundary. In the interim, these markers can be quite useful to supplement the clinical, radiological and physiological monitoring of the disease and identify high-risk patients who would benefit from aggressive management of established risk factors.
List of Abbreviations
Acute Lung Injury (ALI)
Acute Physiology and Chronic Health Evaluation (APACHE)
Acute Respiratory Distress Syndrome (ARDS)
Bronchoalveolar lavage fluid (BALF)
ICU: Intensive Care Unit
ICAM-1: Intercellular Cell Adhesion Molecule-1
ILs: Interleukins
ILDs: Interstitial Lung Diseases
Krebs von den Lungen-(KL)-6
LTs: Leukotrienes
MMPs (Metalloproteinases)
MODS: Multi-Organ Dysfunction Score
Receiver-operating-characteristic (ROC)
Simplified Acute Physiological Score (SAPS)
SIRS: Systemic Inflammatory Response Syndrome
Soluble-E-selectin: s-E-selectin
Soluble IL-2 receptor (sIL-2R)
Surfactant protein-(SP)
TNFa: Tumor Necrosis Factor-alpha
VWF: von Willebrand factor
VCAM-1: Vascular Cell Adhesion Molecule-1
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
AT, IP and DB were involved with the study conception. AT and IP performed the data acquisition and interpretation. DB was involved in revising the article for important intellectual content. All authors read and approved the final manuscript.
Acknowledgements
The authors are grateful to Stavros Anevlavis (M.D) for his valuable assistance in collecting the data and revising the article.
==== Refs
Ferrigno D Buccheri G Biggi A Serum tumour markers in lung cancer: history, biology and clinical applications Eur Respir J 1994 7 186 97 8143820 10.1183/09031936.94.07010186
Manolio T Novel risk markers and clinical practice N Engl J Med 2003 23 349 1587 9 14573728 10.1056/NEJMp038136
Bernard GR Artigas A Brigham KL Carlet J Falke K Hudson L Lamy M Legall JR Morris A Spragg R The American-European Consensus Conference on ARDS. Definitions, mechanisms, relevant outcomes, and clinical trial coordination Am J Respir Crit Care Med 1994 149 818 24 7509706
Fowler AA Hamman RF Good JT Benson KN Baird M Eberle DJ Petty TL Hyers TM Adult respiratory distress syndrome: risk with common predispositions Ann Intern Med 1983 98 593 7 6846973
Rinaldo JE Christman JW Mechanisms and mediators of the adult respiratory distress syndrome Clin Chest Med 1990 11 621 32 2268993
Pugin J Ricou B Steinberg KP Suter PM Martin TR Proinflammatory activity in bronchoalveolar lavage fluids from patients with ARDS, a prominent role for interleukin-1 Am J Respir Crit Care Med 1996 153 1850 6 8665045
Torii K Iida K Miyazaki Y Saga S Kondoh Y Taniguchi H Taki F Takagi K Matsuyama M Suzuki R Higher concentrations of matrix metalloproteinases in bronchoalveolar lavage fluid of patients with adult respiratory distress syndrome Am J Respir Crit Care Med 1997 155 43 6 9001287
Meduri GU Kanangat S Stefan J Tolley E Schaberg D Cytokines IL-1beta, IL-6, and TNF-alpha enhance in vitro growth of bacteria Am J Respir Crit Care Med 1999 160 961 7 10471625
Park WY Goodman RB Steinberg KP Ruzinski JT Radella F 2ndPark DR Pugin J Skerrett SJ Hudson LD Martin TR Cytokine balance in the lungs of patients with acute respiratory distress syndrome Am J Respir Crit Care Med 2001 164 1896 903 11734443
Tracey KJ Beutler B Lowry SF Merryweather J Wolpe S Milsark IW Hariri RJ Fahey TJ 3rdZentella A Albert JD Shock and tissue injury induced by recombinant human cachectin Science 1986 234 470 4 3764421
Marks JD Marks CB Luce JM Montgomery AB Turner J Metz CA Murray JF Plasma tumor necrosis factor in patients with septic shock. Mortality rate, incidence of adult respiratory distress syndrome, and effects of methylprednisolone administration Am Rev Respir Dis 1990 141 94 7 2297191
Damas P Reuter A Gysen P Demonty J Lamy M Franchimont P Tumornecrosis factor and interleukin-1 serum levels during severe sepsis in humans Crit Care Med 1989 17 975 8 2791581
Pinsky MR Vincent JL Deviere J Alegre M Kahn RJ Dupont E Serum cytokine levels in human septic shock. Relation to multiple-system organ failure and mortality Chest 1993 103 565 75 8432155
Takala A Jousela I Jansson SE Olkkola KT Takkunen O Orpana A Karonen SL Repo H Markers of systemic inflammation predicting organ failure in community-acquired septic shock Clin Sci (Lond) 1999 97 529 38 10545303
Calandra T Gerain J Heumann D Baumgartner JD Glauser MP High circulating levels of interleukin-6 in patients with septic shock: evolution during sepsis, prognostic value, and interplay with other cytokines. The Swiss-Dutch J5 Immunoglobulin Study Group Am J Med 1991 91 23 9 1907101 10.1016/0002-9343(91)90069-A
Kiehl MG Ostermann H Thomas M Muller C Cassens U Kienast J Inflammatory mediators in bronchoalveolar lavage fluid and plasma in leukocytopenic patients with septic shock-induced acute respiratory distress syndrome Crit Care Med 1998 26 1194 9 9671368 10.1097/00003246-199807000-00019
Meduri GU Kohler G Headley S Tolley E Stentz F Postlethwaite A Inflammatory cytokines in the BAL of patients with ARDS. Persistent elevation over time predicts poor outcome Chest 1995 108 1303 14 7587434
Meduri GU Headley S Kohler G Stentz F Tolley E Umberger R Leeper K Persistent elevation of inflammatory cytokines predicts a poor outcome in ARDS. Plasma IL-1 beta and IL-6 levels are consistent and efficient predictors of outcome over time Chest 1995 107 1062 73 7705118
Agouridakis P Kyriakou D Alexandrakis MG Perisinakis K Karkavitsas N Bouros D Association between increased levels of IL-2 and IL-15 and outcome in patients with early acute respiratory distress syndrome Eur J Clin Invest 2002 32 862 7 12423329 10.1046/j.1365-2362.2002.01081.x
Lesur O Kokis A Hermans C Fulop T Bernard A Lane D Interleukin-2 involvement in early acute respiratory distress syndrome: relationship with polymorphonuclear neutrophil apoptosis and patient survival Crit Care Med 2000 28 3814 22 11153619 10.1097/00003246-200012000-00010
Headley AS Tolley E Meduri GU Infections and the inflammatory response in acute respiratory distress syndrome Chest 1997 111 1306 21 9149588
Goodman RB Strieter RM Martin DP Steinberg KP Milberg JA Maunder RJ Kunkel SL Walz A Hudson LD Martin TR Inflammatory cytokines in patients with persistence of the acute respiratory distress syndrome Am J Respir Crit Care Med 1996 154 602 11 8810593
Parsons PE Moss M Vannice JL Moore EE Moore FA Repine JE Circulating IL-1ra and IL-10 levels are increased but do not predict the development of acute respiratory distress syndrome in at-risk patients Am J Respir Crit Care Med 1997 155 1469 73 9105096
Takala A Jousela I Takkunen O Kautiainen H Jansson SE Orpana A Karonen SL Repo H A prospective study of inflammation markers in patients at risk of indirect acute lung injury Shock 2002 17 252 7 11954822 10.1097/00024382-200204000-00002
Bouros D Alexandrakis MG Antoniou KM Agouridakis P Pneumatikos I Anevlavis S Pataka A Patlakas G Karkavitsas N Kyriakou D The clinical significance of serum and bronchoalveolar lavage inflammatory cytokines in patients at risk for Acute Respiratory Distress Syndrome BMC Pulm Med 2004 4 6 15315713 10.1186/1471-2466-4-6
Schutte H Lohmeyer J Rosseau S Ziegler S Siebert C Kielisch H Pralle H Grimminger F Morr H Seeger W Bronchoalveolar and systemic cytokine profiles in patients with ARDS, severe pneumonia and cardiogenic pulmonary oedema Eur Respir J 1996 9 1858 67 8880103 10.1183/09031936.96.09091858
Bauer TT Monton C Torres A Cabello H Fillela X Maldonado A Nicolas JM Zavala E Comparison of systemic cytokine levels in patients with acute respiratory distress syndrome, severe pneumonia, and controls Thorax 2000 55 46 52 10607801 10.1136/thorax.55.1.46
Parrillo JE Pathogenetic mechanisms of septic shock N Engl J Med 1993 328 1471 7 8479467 10.1056/NEJM199305203282008
Osborn L Leukocyte adhesion to endothelium in inflammation Cell 1990 62 3 6 2194672 10.1016/0092-8674(90)90230-C
Springer TA Traffic signals for lymphocyte recirculation and leukocyte emigration: the multistep paradigm Cell 1994 76 301 14 7507411 10.1016/0092-8674(94)90337-9
Springer TA Adhesion receptors of the immune system Nature 1990 346 425 34 1974032 10.1038/346425a0
Stoolman LM Adhesion molecules involved in leukocyte recruitment and lymphocyte recirculation Chest 1993 103 79S 86S 8428546
Gearing AJ Newman W Circulating adhesion molecules in disease Immunol Today 1993 14 506 12 7506035 10.1016/0167-5699(93)90267-O
Newman W Beall LD Carson CW Hunder GG Graben N Randhawa ZI Gopal TV Wiener-Kronish J Matthay MA Soluble E-selectin is found in supernatants of activated endothelial cells and is elevated in the serum of patients with septic shock J Immunol 1993 150 644 54 7678280
Rothlein R Mainolfi EA Czajkowski M Marlin SD A form of circulating ICAM-1 in human serum J Immunol 1991 147 3788 93 1682385
Rossi EC Green D Rosen JS Spies SM Jao JS Sequential changes in factor VIII and platelets preceding deep vein thrombosis in patients with spinal cord injury Br J Haematol 1980 45 143 51 6769466
Ribes JA Francis CW Wagner DD Fibrin induces release of von Willebrand factor from endothelial cells J Clin Invest 1987 79 117 23 3491837
Hamilton KK Sims PJ Changes in cytosolic Ca2+ associated with von Willebrand factor release in human endothelial cells exposed to histamine. Study of microcarrier cell monolayers using the fluorescent probe indo-1 J Clin Invest 1987 79 600 8 3492515
Donnelly SC Haslett C Dransfield I Robertson CE Carter DC Ross JA Grant IS Tedder TF Role of selectins in development of adult respiratory distress syndrome Lancet 1994 23 344 215 9 7518025 10.1016/S0140-6736(94)92995-5
Boldt J Wollbruck M Kuhn D Linke LC Hempelmann G Do plasma levels of circulating soluble adhesion molecules differ between surviving and nonsurviving critically ill patients? Chest 1995 107 787 92 7874954
Cowley HC Heney D Gearing AJ Hemingway I Webster NR Increased circulating adhesion molecule concentrations in patients with the systemic inflammatory response syndrome: a prospective cohort study Crit Care Med 1994 22 651 7 7511496
Redl H Dinges HP Buurman WA van der Linden CJ Pober JS Cotran RS Schlag G Expression of endothelial leukocyte adhesion molecule-1 in septic but not traumatic/hypovolemic shock in the baboon Am J Pathol 1991 139 461 6 1714243
Sessler CN Windsor AC Schwartz M Watson L Fisher BJ Sugerman HJ Fowler AA 3rd Circulating ICAM-1 is increased in septic shock Am J Respir Crit Care Med 1995 151 1420 7 7735595
Kayal S Jais JP Aguini N Chaudiere J Labrousse J Elevated circulating E-selectin, intercellular adhesion molecule 1, and von Willebrand factor in patients with severe infection Am J Respir Crit Care Med 1998 157 776 84 9517590
Agouridakis P Kyriakou D Alexandrakis MG Prekates A Perisinakis K Karkavitsas N Bouros D The predictive role of serum and bronchoalveolar lavage cytokines and adhesion molecules for acute respiratory distress syndrome development and outcome Respir Res 2002 3 25 12537603 10.1186/rr193
Carvalho AC Bellman SM Saullo VJ Quinn D Zapol WM Altered factor VIII in acute respiratory failure N Engl J Med 1982 307 1113 9 6214713
Rubin DB Wiener-Kronish JP Murray JF Green DR Turner J Luce JM Montgomery AB Marks JD Matthay MA Elevated von Willebrand factor antigen is an early plasma predictor of acute lung injury in nonpulmonary sepsis syndrome J Clin Invest 1990 86 474 80 2384595
Ware LB Conner ER Matthay MA von Willebrand factor antigen is an independent marker of poor outcome in patients with early acute lung injury Crit Care Med 2001 29 2325 31 11801836 10.1097/00003246-200112000-00016
Ware LB Eisner MD Thompson BT Parsons PE Matthay MA Significance of von Willebrand factor in septic and nonseptic patients with acute lung injury Am J Respir Crit Care Med 2004 170 766 72 15201135 10.1164/rccm.200310-1434OC
Moalli R Doyle JM Tahhan HR Hasan FM Braman SS Saldeen T Fibrinolysis in critically ill patients Am Rev Respir Dis 1989 140 287 93 2504087
Moss M Ackerson L Gillespie MK Moore FA Moore EE Parsons PE von Willebrand factor antigen levels are not predictive for the adult respiratory distress syndrome Am J Respir Crit Care Med 1995 151 15 20 7812545
Sabharwal AK Bajaj SP Ameri A Tricomi SM Hyers TM Dahms TE Taylor FB JrBajaj MS Tissue factor pathway inhibitor and von Willebrand factor antigen levels in adult respiratory distress syndrome and in a primate model of sepsis Am J Respir Crit Care Med 1995 151 758 67 7881667
Bajaj MS Tricomi SM Plasma levels of the three endothelial-specific proteins von Willebrand factor, tissue factor pathway inhibitor, and thrombomodulin do not predict the development of acute respiratory distress syndrome Intensive Care Med 1999 25 1259 66 10654210
Moss M Gillespie MK Ackerson L Moore FA Moore EE Parsons PE Endothelial cell activity varies in patients at risk for the adult respiratory distress syndrome Crit Care Med 1996 24 1782 6 8917025 10.1097/00003246-199611000-00004
Ognibene FP Martin SE Parker MM Schlesinger T Roach P Burch C Shelhamer JH Parrillo JE Adult respiratory distress syndrome in patients with severe neutropenia N Engl J Med 1986 315 547 51 3736638
Martin TR Pistorese BP Hudson LD Maunder RJ The function of lung and blood neutrophils in patients with the adult respiratory distress syndrome. Implications for the pathogenesis of lung infections Am Rev Respir Dis 1991 144 254 62 1650151
Shapiro SD Elastolytic metalloproteinases produced by human mononuclear phagocytes. Potential roles in destructive lung disease Am J Respir Crit Care Med 1994 150 S160 4 7952653
Delclaux C Delacourt C D'Ortho MP Boyer V Lafuma C Harf A Role of gelatinase B and elastase in human polymorphonuclear neutrophil migration across basement membrane Am J Respir Cell Mol Biol 1996 14 288 95 8845180
Sengelov H Follin P Kjeldsen L Lollike K Dahlgren C Borregaard N Mobilization of granules and secretory vesicles during in vivo exudation of human neutrophils J Immunol 1995 154 4157 65 7535822
Pugin J Verghese G Widmer MC Matthay MA The alveolar space is the site of intense inflammatory and profibrotic reactions in the early phase f acute respiratory distress syndrome Crit Care Med 1999 27 304 12 10075054 10.1097/00003246-199902000-00036
Stephenson AH Lonigro AJ Hyers TM Webster RO Fowler AA Increased concentrations of leukotrienes in bronchoalveolar lavage fluid of patients with ARDS or at risk for ARDS Am Rev Respir Dis 1988 138 714 9 2849342
Ratnoff WD Matthay MA Wong MY Ito Y Vu KH Wiener-Kronish J Goetzl EJ Sulfidopeptide-leukotriene peptidases in pulmonary edema fluid frompatients with the adult respiratory distress syndrome J Clin Immunol 1988 8 250 8 2842367 10.1007/BF00916553
Antonelli M Raponi G Lenti L Severi L Capelli O Riccioni L De Blasi RA Conti G Mancini C Leukotrienes and alpha tumor necrosis factor levels in the bronchoalveolar lavage fluid of patient at risk for the adult respiratory distress syndrome Minerva Anestesiol 1994 60 419 26 7808646
Amat M Barcons M Mancebo J Mateo J Oliver A Mayoral JF Fontcuberta J Vila L Evolution of leukotriene B4, peptide leukotrienes, and interleukin-8 plasma concentrations in patients at risk of acute respiratory distress syndrome and with acute respiratory distress syndrome: mortality prognostic study Crit Care Med 2000 28 57 62 10667499 10.1097/00003246-200001000-00009
Hirayama M Kohgo Y Kondo H Shintani N Fujikawa K Sasaki K Kato J Niitsu Y Regulation of iron metabolism in HepG2 cells: a possible role for cytokines in the hepatic deposition of iron Hepatology 1993 18 874 80 8406363
Connelly KG Moss M Parsons PE Moore EE Moore FA Giclas PC Seligman PA Repine JE Serum ferritin as a predictor of the acute respiratory distress syndrome Am J Respir Crit Care Med 1997 155 21 5 9001283
Sharkey RA Donnelly SC Connelly KG Robertson CE Haslett C Repine JE Initial serum ferritin levels in patients with multiple trauma and the subsequent development of acute respiratory distress syndrome Am J Respir Crit Care Med 1999 159 1506 9 10228118
Hermans C Bernard A Lung epithelium-specific proteins: characteristics and potential applications as markers Am J Respir Crit Care Med 1999 159 646 78 9927386
Reynolds HY Newball HH Analysis of proteins and respiratory cells obtained from human lungs by bronchial lavage J Lab Clin Med 1974 84 559 73 4412011
Kohno N Kyoizumi S Awaya Y Fukuhara H Yamakido M Akiyama M New serum indicator of interstitial pneumonitis activity. Sialylated carbohydrate antigen KL-6 Chest 1989 96 68 73 2661160
King RJ Klass DJ Gikas EG Clements JA Isolation of apoproteins from canine surface active material Am J Physiol 1973 224 788 95 4633419
Possmayer F A proposed nomenclature for pulmonary surfactant-associated proteins Am Rev Respir Dis 1988 138 990 8 3059887
Creuwels LA van Golde LM Haagsman HP The pulmonary surfactant system: biochemical and clinical aspects Lung 1997 175 1 39 8959671
Nieman GF Bredenberg CE High surface tension pulmonary edema induced by detergent aerosol J Appl Physiol 1985 58 29 36
Griese M Pulmonary surfactant in health and human lung diseases: state of the art Eur Respir J 1999 13 1455 76 10445627
Gunther A Ruppert C Schmidt R Markart P Grimminger F Walmrath D Seeger W Surfactant alteration and replacement in acute respiratory distress syndrome Respir Res 2001 2 353 64 11737935 10.1186/rr86
Griese M Pulmonary surfactant in health and human lung diseases: state of the art Eur Respir J 1999 13 1455 76 10445627
Gregory TJ Longmore WJ Moxley MA Whitsett JA Reed CR Fowler AA 3rdHudson LD Maunder RJ Crim C Hyers TM Surfactant chemical composition and biophysical activity in acute respiratory distress syndrome J Clin Invest 1991 88 1976 81 1752956
Gunther A Siebert C Schmidt R Ziegler S Grimminger F Yabut M Temmesfeld B Walmrath D Morr H Seeger W Surfactant alterations in severe pneumonia, acute respiratory distress syndrome, and cardiogenic lung edema Am J Respir Crit Care Med 1996 153 176 84 8542113
Pison U Obertacke U Seeger W Hawgood S Surfactant protein A (SP-A) is decreased in acute parenchymal lung injury associated with polytrauma Eur J Clin Invest 1992 22 712 8 1478239
Doyle IR Nicholas TE Bersten AD Serum surfactant protein-A levels in patients with acute cardiogenic pulmonary edema and adult respiratory distress syndrome Am J Respir Crit Care Med 1995 152 307 17 7599839
Doyle IR Bersten AD Nicholas TE Surfactant proteins-A and -B are elevated in plasma of patients with acute respiratory failure Am J Respir Crit Care Med 1997 156 1217 29 9351625
Greene KE Wright JR Steinberg KP Ruzinski JT Caldwell E Wong WB Hull W Whitsett JA Akino T Kuroki Y Nagae H Hudson LD Martin TR Serial changes in surfactant-associated proteins in lung and serum before and after onset of ARDS Am J Respir Crit Care Med 1999 160 1843 50 10588595
Cheng IW Ware LB Greene KE Nuckton TJ Eisner MD Matthay MA Prognostic value of surfactant proteins A and D in patients with acute lung injury Crit Care Med 2003 31 20 7 12544988 10.1097/00003246-200301000-00003
Greene KE Ye S Mason RJ Parsons PE Serum surfactant protein-A levels predict development of ARDS in at-risk patients Chest 1999 116 90S 91S 10424610 10.1378/chest.116.suppl_1.90S
Bersten AD Hunt T Nicholas TE Doyle IR Elevated plasma surfactant protein-B predicts development of acute respiratory distress syndrome in patients with acute respiratory failure Am J Respir Crit Care Med 2001 164 648 52 11520731
Eisner MD Parsons P Matthay MA Ware L Greene K Acute Respiratory Distress Syndrome Network. Plasma surfactant protein levels and clinical outcomes in patients with acute lung injury Thorax 2003 58 983 8 14586055 10.1136/thorax.58.11.983
Kohno N Akiyama M Kyoizumi S Hakoda M Kobuke K Yamakido M Detection of soluble tumor-associated antigens in sera and effusions using novel monoclonal antibodies, KL-3 and KL-6, against lung adenocarcinoma Jpn J Clin Oncol 1988 18 203 16 3411786
Yanaba K Hasegawa M Hamaguchi Y Fujimoto M Takehara K Sato S Longitudinal analysis of serum KL-6 levels in patients with systemic sclerosis: association with the activity of pulmonary fibrosis Clin Exp Rheumatol 2003 21 429 36 12942693
Yanaba K Hasegawa M Takehara K Sato S Comparative study of serum surfactant protein-D and KL-6 concentrations in patients with systemic sclerosis as markers for monitoring the activity of pulmonary fibrosis J Rheumatol 2004 31 1112 20 15170923
Ishii H Mukae H Kadota J Kaida H Nagata T Abe K Matsukura S Kohno S High serum concentrations of surfactant protein A in usual interstitial pneumonia compared with non-specific interstitial pneumonia Thorax 2003 58 52 7 12511721 10.1136/thorax.58.1.52
Ohnishi H Yokoyama a Yasuhara Y Watanabe A Naka T Hamada H Abe M Nishimura K Higaki J Ikezoe J Kohno N Circulating KL-6 levels in patients with drug induced pneumonitis Thorax 2003 58 872 5 14514942 10.1136/thorax.58.10.872
Kohno N Hamada H Fujioka S Hiwada K Yamakido M Akiyama M Circulating antigen KL-6 and lactate dehydrogenase for monitoring irradiated patients with lung cancer Chest 1992 102 117 22 1320562
Goto K Kodama T Sekine I Kakinuma R Kubota K Hojo F Matsumoto T Ohmatsu H Ikeda H Ando M Nishiwaki Y Serum levels of KL-6 are useful biomarkers for severe radiation pneumonitis Lung Cancer 2001 34 141 8 11557124 10.1016/S0169-5002(01)00215-X
Ishizaka A Matsuda T Albertine KH Koh H Tasaka S Hasegawa N Kohno N Kotani T Morisaki H Takeda J Nakamura M Fang X Martin TR Matthay MA Hashimoto S Elevation of KL-6, a lung epithelial cell marker, in plasma and epithelial lining fluid in acute respiratory distress syndrome Am J Physiol Lung Cell Mol Physiol 2004 286 L1088 94 12959931 10.1152/ajplung.00420.2002
Sato H Callister ME Mumby S Quinlan GJ Welsh KI duBois RM Evans TW KL-6 levels are elevated in plasma from patients with acute respiratory distress syndrome Eur Respir J 2004 23 142 5 14738246 10.1183/09031936.03.00070303
Reynolds HN McCunn M Borg U Habashi N Cottingham C Bar-Lavi Y Acute respiratory distress syndrome: estimated incidence and mortality rate in a 5 million-person population base Crit Care 1998 2 29 34 11056707 10.1186/cc121
The Acute Respiratory Distress Syndrome Network Ventilation with lower tidal volumes as compared with traditional tidal volumes for acute lung injury and the acute respiratory distress syndrome N Engl J Med 2000 342 1301 8 10793162 10.1056/NEJM200005043421801
Zilberberg MD Epstein SK Acute lung injury in the medical ICU: comorbid conditions, age, etiology, and hospital outcome Am J Respir Crit Care Med 1998 157 1159 64 9563734
Monchi M Bellenfant F Cariou A Joly LM Thebert D Laurent I Dhainaut JF Brunet F Early predictive factors of survival in the acute respiratory distress syndrome. A multivariate analysis Am J Respir Crit Care Med 1998 158 1076 81 9769263
Ware LB Prognostic determinants of acute respiratory distress syndrome in adults: impact on clinical trial design Crit Care Med 2005 33 S217 22 15753731 10.1097/01.CCM.0000155788.39101.7E
Tzouvelekis A Patlakas G Bouros D Application of microarray technology in pulmonary diseases Respir Res 2004 5 26 15585067 10.1186/1465-9921-5-26
| 15972108 | PMC1168906 | CC BY | 2021-01-04 16:23:26 | no | Respir Res. 2005 Jun 22; 6(1):62 | utf-8 | Respir Res | 2,005 | 10.1186/1465-9921-6-62 | oa_comm |
==== Front
Respir ResRespiratory Research1465-99211465-993XBioMed Central London 1465-9921-6-631597514910.1186/1465-9921-6-63ResearchCD14 C-159T and early infection with Pseudomonas aeruginosa in children with cystic fibrosis Martin AC [email protected] IA [email protected] G [email protected] S [email protected] K [email protected] PD [email protected] SM [email protected] J [email protected] PN [email protected] School of Paediatrics and Child Health, University of Western Australia, Perth, Western Australia 60012 Division of Clinical Science, Telethon Institute for Child Health Research, Perth, Western Australia 60083 Department of Respiratory Medicine, Princess Margaret Hospital for Children, Perth, Western Australia 60082005 23 6 2005 6 1 63 63 23 12 2004 23 6 2005 Copyright © 2005 Martin et al; licensee BioMed Central Ltd.2005Martin et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Early acquisition of Pseudomonas aeruginosa is associated with a poorer prognosis in patients with cystic fibrosis. We investigated whether polymorphisms in CD14, the lipopolysaccharide receptor, increase the risk of early infection. Forty-five children with cystic fibrosis were investigated with annual bronchoalveolar lavage (BAL) and plasma sCD14 levels. Plasma sCD14 levels were significantly lower in children from whom P.aeruginosa was subsequently isolated (492.75 μg/ml vs. 1339.43 μg/ml, p = 0.018). Those with the CD14 -159CC genotype had a significantly increased risk of early infection with P.aeruginosa suggesting that CD14 C-159T plays a role in determining the risk of early infection with P.aeruginosa.
cystic fibrosisCD14Pseudomonas aeruginosa
==== Body
Introduction
Cystic fibrosis (CF) is the most common serious, monogenic, autosomal recessive disease in Caucasians and results from mutations in the gene encoding the cystic fibrosis transmembrane conductance regulator (CFTR). CF is characterised by variable phenotypic expression, which is not entirely explained by the allelic heterogeneity of the pathogenic CFTR mutations, and there is accumulating evidence that much of this phenotypic diversity is due to the effect of modifier genes [1]. Pseudomonas aeruginosa, an environmental organism, is the most important pathogen in patients with CF as chronic infection results in a more rapid decline in lung function and reduced survival [2].
CD14, a key gene of the innate immune system, functions as a receptor for lipopolysaccharide (LPS), a constitutive element of the P.aeruginosa cell wall, and is a potential modifier of severity in patients with CF. CD14 is expressed in both a membrane-bound form on macrophages, monocytes and neutrophils (mCD14) and soluble form in serum (sCD14). A polymorphism in the CD14 gene promoter (C-159T) has an allele frequency of approximately 50% in Europeans [3]. The -159C allele is associated with lower circulating levels of sCD14 in healthy children. Higher constitutive levels of mCD14 and sCD14 have been shown to increase the magnitude of airway neutrophil response to LPS [4], whereas CD14 receptor blockade results in a reduction in the deleterious systemic responses that occur in sepsis, due to a reduction in pro-inflammatory cytokines but at the expense of an increased bacterial load [5]. Hence, CD14 may play a pivotal role in determining the balance of infection and inflammation in CF. Increased expression of CD14 may be associated with more inflammation but a reduced bacterial load, whereas reduced expression may result in less inflammation but a greater bacterial load.
We hypothesised that P.aeruginosa infection would be acquired earlier in children with the -159CC genotype.
Methods
A prospective, population-based, cohort of children with CF was recruited from the only tertiary paediatric hospital in Western Australia, which cares for all children with CF in the state. Annual bronchoscopy, performed through a laryngeal mask to minimise the risk of upper airway contamination, was done routinely from diagnosis until 7 years of age in all children with CF. Children diagnosed after the neonatal period, whose first BAL was positive for P.aeruginosa were excluded from this analysis, as in this situation it could not be determined when they had initially acquired this pathogen.
All children with a positive BAL culture for P.aeruginosa, which was defined as >10,000 CFU/ml, were admitted to hospital for further treatment. Blood was collected for genetic studies and subjects were genotyped for the CD14 promoter polymorphism as previously described [3]. Plasma samples taken at the time of the earliest BAL, when the children were not infected with P.aeruginosa, was available for measurement of sCD14 levels in 31 children. Plasma sCD14 levels were determined using a commercially available enzyme-linked immunosorbent assay (ELISA) kit (R&D Systems, Minneapolis, USA).
The Kaplan-Meier survival method was used to explore the difference in the P.aeruginosa free survival rates between CD14 genotype groups. As children in the study were not the same age, data was censored for individual children who were known to have not isolated P.aeruginosa at the time of their last BAL and this information was incorporated into the analysis. Breslow test (Breslow Generalized Wilcoxon Test) was employed to compare the difference in the survival curves of acquisition of P. aeruginosa in the three CD14 genotype groups. Multivariate Cox regression was used to estimate the relative risks after adjustment for potential confounding factors including age, sex, CFTR mutation and nutritional status. Plasma sCD14 levels were analysed by ANOVA and all the statistical analyses were performed using SPSS for Windows (Version 11).
Parents of all participants gave informed consent and the Ethics Committee of King Edward Memorial and Princess Margaret Hospitals, Western Australia, approved the study.
Results
Forty-five children (22 male), aged 0.6–6.6 years (mean 3.25 years) were studied, of whom 25/45 (55%) were DF508 homozygous and 20/45 DF508 heterozygous. CF was diagnosed at a mean age of 0.23 yrs (95%CI 0.06–0.4 yrs), with 73% diagnosed in the newborn period. There was no significant difference between CFTR mutation (p = 0.74), gender (p = 0.38), nutritional status (weight for height z scores) (p = 0.39) or socio-economic status (p = 0.29) in those who did and did not isolate P.aeruginosa. CD14 genotype frequencies at position -159 were: CC 12/45 (27%), CT 20/45 (44%), TT 13/45 (29%). P.aeruginosa was isolated from thirteen children (29%) and the mean age of acquisition was 2.26 years (95% CI 1.29–3.25). Subjects with CD14 -159CC appeared to isolate P.aeruginosa at a younger age (mean = 1.1 years, 95%CI = 0.2–1.9 years) than -159CT (mean = 2.8 years, 95%CI = 1.3–4.2 years) and TT subjects (mean = 3.3 years), although this difference was not statistically significant (p = 0.19).
Figure 1 shows the P.aeruginosa free survival curves of the three CD14 genotype groups. The probability of children remaining free of P.aeruginosa with -159CC is consistently below that of children who are CT or TT and the curve for children with CT is below that of children with TT. For example, at 2 years of age, the % children remaining uninfected with P.aeruginosa is 55% vs. 82% vs. 100% for CC, CT and TT respectively.
Figure 1 Kaplan-Meier estimates of proportion of children free from P.aeruginosa by CD14 C-159T. 1Breslow Test (Breslow Generalized Wilcoxon Test) 2"Censored" represents the censored observations that arise when the duration of a study is limited.
Compared with -159TT, children with the CC genotype had a 10-fold (95%CI = 1.09–92.30, p = 0.042) higher relative risk and children with the CT genotype had an intermediate 5.5 fold (95%CI = 0.69–44.63, p = 0.108) higher relative risk of being infected with P.aeruginosa. After adjustment for CFTR mutation and nutritional status, the estimated relative risk in children with CC or CT increased further (RR = 13.32, 95%CI = 1.37–129.13, p = 0.025 and RR = 6.0, 95%CI = 0.71–51.03, p = 0.101 respectively). This suggested that independent of CFTR mutation and nutritional status, those with the C allele had a significantly increased risk of being infected with P.aeruginosa. In addition, there was a significant linear trend across the three genotype groups, between increasing numbers of C alleles and increasing likelihood of being infected with P.aeruginosa (p = 0.015).
Compared to children who subsequently isolated P.aeruginosa, those who remained free of P.aeruginosa had significantly higher plasma sCD14 levels: 1339.43 μg/ml (95%CI 1096.63–1635.98 μg/ml) vs. 492.75 μg/ml (95%CI 55.7–4359.01 μg/ml), p = 0.018. We found no significant association between plasma sCD14 levels and CD14 C-159T (p = 0.38).
Discussion
This study showed an association between CD14 -159CC and early acquisition of P. aeruginosa in children with CF. Many CF centres promote aggressive treatment regimes to eradicate first isolates of P.aeruginosa, and, thus, prospectively identifying a "high risk" group of infants with CF could have substantial clinical benefit.
CD14 receptor activation results in a strong Th1 cytokine response, directed through IL-12, in an attempt to eradicate pathogens. The finding of lower plasma sCD14 levels in children who subsequently isolate P.aeruginosa suggests that an inadequate pro-inflammatory response to LPS may place these individuals with CF at greater risk of early P.aeruginosa acquisition. The lack of association between CD14 C-159T and plasma sCD14 levels may merely reflect the small number of subjects in this population, but may also indicate that in CF there are factors more critical than CD14 C-159T genotype that determine plasma sCD14 levels.
Although children with higher sCD14 levels may be relatively protected from earlier acquisition of P.aeruginosa, when they become colonised they may paradoxically have a worse outcome, as a result of an over-aggressive and ineffectual inflammatory response. These latter patients might potentially benefit from aggressive anti-inflammatory treatment. Thus, the timing of anti-inflammatory therapy would need to be carefully considered, as inflammation might be beneficial in early life by delaying colonisation with P.aeruginosa, but harmful once infection is established, due to the over-exuberant inflammatory response. Therapy that modulates the inflammatory response might promote the acquisition of pathogens such as P. aeruginosa in young children with different genetic susceptibilities.
The results of this study are based on a limited number of subjects due to the stringent inclusion criteria and the prospective longitudinal design. In addition, the potential role of other single nucleotide polymorphisms in genes involved in innate immunity such as Toll-like receptor 4 Asp299Gly [6], Toll-like receptor 2 Arg753Gln [6] and mannose binding lectin [7], may influence the acquisition of P.aeruginosa in children with CF and more detailed investigation of these pathways in CF is indicated. This study identified the potential association between a common genetic variant and the early isolation of P.aeruginosa. The CD14 promoter polymorphism may have a central function in determining the age of first isolation of P.aeruginosa, with the CC genotype conferring a higher risk of early isolation and the TT genotype being relatively protective, emphasising the importance of understanding the delicate balance between inflammation and infection that exists in CF.
Acknowledgements
We would like to thank the children and families who participated in this study and acknowledge the technical assistance of Elizabeth Balding and Samantha Gard. This study was supported by The National Health and Medical Research Council and the Australian Cystic Fibrosis Research Trust.
==== Refs
Accurso FJ Sontag MK Seeking modifier genes in cystic fibrosis Am J Respir Crit Care Med 2003 167 289 290 12554616 10.1164/rccm.2210006
Emerson J Rosenfeld M McNamara S Pseudomonas aeruginosa and other predictors of mortality and morbidity in young children with cystic fibrosis Pediatric Pulmonology 2002 34 91 100 12112774 10.1002/ppul.10127
Baldini M Lohman IC Halonen M A polymorphism in the 5' flanking region of the CD14 gene is associated with circulating soluble CD14 levels and with total serum immunoglobulin E Am J Respir Cell Mol Biol 1999 20 976 83 10226067
Alexis N Eldridge M Reed W CD14-dependent airway neutrophil response to inhaled LPS: role of atopy J Allergy Clin Immunol 2001 107 31 35 11149987 10.1067/mai.2001.111594
Frevert CW Matute-Bello G Skerrett SJ Effect of CD14 blockade in rabbits with Escherichia coli pneumonia and sepsis Journal of Immunology 2000 164 10 5439 45
Schroder NW Schumann RR Single nucleotide polymorphisms of Toll-like receptors and susceptibility to infectious disease Lancet Infect Dis 2005 3 156 64 15766650
Eisen DP Minchinton RM Impact of mannose-binding lectin on susceptibility to infectious disease Clin Infect Dis 2003 37 1496 1505 14614673 10.1086/379324
| 15975149 | PMC1168907 | CC BY | 2021-01-04 16:23:26 | no | Respir Res. 2005 Jun 23; 6(1):63 | utf-8 | Respir Res | 2,005 | 10.1186/1465-9921-6-63 | oa_comm |
==== Front
Respir ResRespiratory Research1465-99211465-993XBioMed Central London 1465-9921-6-651598517110.1186/1465-9921-6-65ResearchEstimation of airway obstruction using oximeter plethysmograph waveform data Arnold Donald H [email protected] David M [email protected] Renee' A [email protected] James S [email protected] Departments of Emergency Medicine and Pediatrics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA2 Department of Pediatrics, Section of Emergency Medicine, Yale University School of Medicine, New Haven, Connecticut, USA3 Department of Medicine, The University of Alabama at Birmingham School of Medicine, Birmingham, Alabama, USA4 Department of Pediatrics, Division of Pulmonary Medicine, The University of Alabama at Birmingham School of Medicine, Birmingham, Alabama, USA2005 28 6 2005 6 1 65 65 18 4 2005 28 6 2005 Copyright © 2005 Arnold et al; licensee BioMed Central Ltd.2005Arnold et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Validated measures to assess the severity of airway obstruction in patients with obstructive airway disease are limited. Changes in the pulse oximeter plethysmograph waveform represent fluctuations in arterial flow. Analysis of these fluctuations might be useful clinically if they represent physiologic perturbations resulting from airway obstruction. We tested the hypothesis that the severity of airway obstruction could be estimated using plethysmograph waveform data.
Methods
Using a closed airway circuit with adjustable inspiratory and expiratory pressure relief valves, airway obstruction was induced in a prospective convenience sample of 31 healthy adult subjects. Maximal change in airway pressure at the mouthpiece was used as a surrogate measure of the degree of obstruction applied. Plethysmograph waveform data and mouthpiece airway pressure were acquired for 60 seconds at increasing levels of inspiratory and expiratory obstruction. At each level of applied obstruction, mean values for maximal change in waveform area under the curve and height as well as maximal change in mouth pressure were calculated for sequential 7.5 second intervals. Correlations of these waveform variables with mouth pressure values were then performed to determine if the magnitude of changes in these variables indicates the severity of airway obstruction.
Results
There were significant relationships between maximal change in area under the curve (P < .0001) or height (P < 0.0001) and mouth pressure.
Conclusion
The findings suggest that mathematic interpretation of plethysmograph waveform data may estimate the severity of airway obstruction and be of clinical utility in objective assessment of patients with obstructive airway diseases.
==== Body
Background
Obstructive airway diseases, including asthma, bronchiolitis, obstructive sleep apnea, and chronic obstructive pulmonary disease (COPD), are common in children and adults [1-7]. Early recognition and accurate assessment of the severity of airway obstruction and the response to therapy are fundamental to the improvement of health for patients with these disorders. However, objective measures of airway obstruction currently available in the Emergency Department (ED) and other acute care settings have significant limitations. Spirometry is frequently not available in acute clinical settings, including the ED. Peak expiratory flow rate (PEFR) has been demonstrated to progressively underestimate airway obstruction with increasing air trapping, making it less reliable as airway obstruction worsens [8]. As well, the ability of a patient with moderate to severe airway obstruction to generate an erroneously normal PEFR and the inability to measure PEFR in young children render this test less useful in the setting of an acute asthma exacerbation [8]. Further, both spirometry and PEFR require patient coordination and cooperation. Validated, objective measures to determine severity of airway obstruction in bronchiolitis are nonexistent [9].
The pulse oximeter plethysmograph waveform reflects dynamic net changes in arteriolar inflow and venous outflow of tissue bed capillaries interrogated by the oximeter light emitting diodes [10-12]. Indeed, the oxygen saturation output of the device (Sp02) depends upon isolation of the oxygenated, arterialized light signal from those light signals representing tissue, venous blood and other chromophobes [13]. At levels of arterial oxygen saturation (Sa02) approaching 100%, the waveform is derived almost entirely from the infrared (940 nm) signal determined by oxyhemoglobin concentration and arterialized flow. Because oxyhemoglobin concentration is constant, dynamic changes in the waveform are a result of arterialized flow change [13]. Under these conditions the waveform represents a plethysmograph, a device measuring change in volume, in this case change in volume of arterialized blood [11,12,14]. As such, the plethysmograph waveform has been demonstrated to correlate with radial artery Doppler waveforms [12].
Changes in the plethysmograph waveform might be useful clinically to estimate the severity of perturbations in physiologic events influencing arterial flow [10]. Certain pathologic conditions, most notably airway obstruction, influence these physiologic events and result in the phenomenon known as pulsus paradoxus [15]. Although pulsus paradoxus cannot be readily measured directly from the plethysmograph waveform, changes in plethysmograph waveform variables might nonetheless correlate with the physiologic perturbations characteristic of pulsus paradoxus and be useful in assessing the severity of physiologic alterations resulting from airway obstruction.
Changes in waveform curve or baseline height, one-dimensional parameters, have been used to estimate pulsus paradoxus [16-18]. Pulsus paradoxus represents change in left ventricular stroke volume, a three-dimensional parameter. As a two-dimensional parameter, area under the curve may more accurately reflect the physiologic events resulting in pulsus paradoxus. Additionally, the contribution of diastolic blood pressure changes to pulsus paradoxus have been noted, and AUC measurement might more completely and accurately incorporate these events [17,19]. Finally, a general principle of signal analysis maintains that the signal-to-noise ratio improves at a rate proportionate to the square root of the number of data points obtained [20]. Area under the curve data may therefore be less prone to noise artifact than height data, and might provide a more optimal signal to noise ratio. With this in mind, changes in area under the waveform curve might represent a more accurate measure of waveform variability than changes in waveform height. Indeed, Hartert and colleagues have suggested evaluation of area under the waveform baseline during the respiratory cycle, rather than baseline height change, as a more accurate measurement of waveform variation[18].
There are limited data on the levels of intrapleural pressure generated in the presence of most obstructive airway diseases. However, levels of intrapleural pressure generated in adults in severe status asthmaticus have been demonstrated to be (-)24.4 ± 6.5 cmH20 on inspiration and (+)7.6 ± 6.0 cmH20 on expiration [15]. Mouth pressure reflects intrapleural pressure within 4 cmH20 [21].
In this study our primary objective was to determine whether maximal change in area under the pulse oximeter plethysmograph waveform curve correlates with the degree of experimentally applied airway obstruction across a range of mouth pressures up to these levels of obstruction. A secondary objective was to determine whether maximal changes in height of the plethysmograph waveform curve similarly correlate with the degree of airway obstruction.
Methods
Study Setting and Population
The study was approved by the University of Alabama at Birmingham Institutional Review Board as an expedited study. Informed written consent was obtained from each subject prior to enrollment. This study was conducted in the Pulmonary Function Laboratory of an urban children's hospital.
A prospective convenience sample of healthy young adult subjects, twenty years of age and above, were recruited. Subjects with doctor-diagnosed asthma, a history consistent with asthma, or either FEV1 or FEV1/FVC less than 80% predicted, were excluded from this study. The subjects underwent spirometry, performed by certified pulmonary function technicians according to American Thoracic Society protocol [22,23].
Study Design and Protocol
We utilized a closed airway circuit to generate airway obstruction, consisting of a Hans Rudolph 2600 two-way non-rebreather valve assembly with adjustable spring-loaded inspiratory and expiratory pressure relief valves and a mouthpiece pressure transducer port (Hans Rudolph, Kansas City, MO).
Our experimental method was to allow each subject to experience increasing levels of inspiratory and expiratory airway obstruction corresponding to the levels of mouth pressure and to the estimated levels of intrapleural pressure noted previously [15,21]. The pressure relief valves were adjusted accordingly at a minimum of five intervals and a maximum of ten intervals, to provide progressively increasing levels of mouth pressure from approximately (-)15 to (-)26 cmH20 on inspiration and (+)2 to (+)9 cmH20 on expiration. Each subject was allowed to rest for a minimum of one minute before testing at the subsequent, increased level of applied resistance in order to allow the plethysmograph waveform to return to baseline. Pulse oximeter plethysmograph waveform data was acquired for 60 seconds at each level of applied obstruction.
Plethysmographic waveforms were acquired with a BioPac MP150 data acquisition system using a TSD123A transducer and an OXY100C pulse oximeter module (BioPac Systems, Santa Barbara, CA). This apparatus utilizes optical transmission at red (660 nm) and infrared (940 nm) wavelengths and employs Novametrix Medical Systems, Inc. artifact rejection and averaging algorithms that use an eight second pulse history signal to output Sp02. The algorithm averages signal only for Sp02 calculation [24]. Plethysmograph waveform signal was acquired, processed and analyzed without averaging, smoothing or filtering. Mouth pressure waveforms were acquired with a BioPac TSD160C transducer. Transducers were calibrated according to manufacturer protocol. Waveform data were analyzed with BioPac Acknowledge software (version 3.7.2). The software algorithm calculates area under the curve (AUC) as the area encompassed by a waveform from the point of deflection from baseline to the point of return to baseline, and calculates height (HT) as height from the point of deflection from baseline to the waveform peak.
Each subject was studied in the sitting position. A nose clip was applied, and the subject was instructed to exclusively mouth breathe through the airway circuit at a respiratory rate of approximately 10–16/min and at normal to slightly increased inspiratory and expiratory effort. Data were acquired at progressively increasing levels of applied inspiratory and expiratory obstruction for approximately 60 seconds at each level.
Data collection and processing
Physiologic perturbations occurring during the respiratory cycle, such as airway obstruction, result in alterations of arterial flow and the phenomenon known as pulsus paradoxus [15]. It is these dynamic changes in arterial flow that we hypothesize might allow estimation of airway obstruction from oximeter plethysmograph waveform changes. Timing the measurement of these changes with the respiratory cycle is difficult in the clinical environment because patients with these disorders often have rapid respiratory rates. For this reason we chose to analyze data during specified time intervals. In order that at least one complete respiratory cycle and the corresponding maximum and minimum mouth pressure be included in each interval, the interval so chosen was 7.5 seconds.
Data extracted for each 7.5 second interval consisted of maximum and minimum waveform area under the curve, maximum and minimum waveform height, and maximum and minimum mouth pressure. Maximum change in area under the curve and height were calculated as the difference between the maximum and minimum values of each parameter divided by the maximum value of the respective parameter during the specified 7.5 second interval. Maximum change in mouth pressure was calculated for the corresponding interval as the absolute difference between the maximum and minimum mouth pressure in cmH20. These data were acquired using the Acknowledge software and entered into a spreadsheet program (Excel, Microsoft, Redmond, WA). Using the Excel formula function, mean values for maximal change in area under the curve, height, and mouth pressure for each level of applied obstruction were calculated from the multiple sequential 7.5-second intervals at the corresponding level of obstruction. This data was then entered into a statistical analysis program (SAS® v9.0, Cary, NC.) for analysis [25].
Outcome Measures
The primary outcome measure was the correlation of mean maximum change in area under the plethysmograph waveform curve with mean maximum change in mouth pressure at each successive level of applied obstruction. The secondary outcome measure was the corresponding correlation using mean maximum change in height.
Data Analysis
Subjects in this study contributed multiple observations to the dataset. Because of this the fundamental assumption of independence across observations was violated. Performing a separate analysis for each subject would reduce the number of observations in each analysis and increase the potential for Type II errors. On the other hand, if all of the observations were analyzed as independent, ignoring the inherent clustering within subjects, then the potential for Type 1 errors would increase. We utilized a repeated measures model that takes into account the clustering and correlation between subjects. In this analysis, the PROC MIXED procedure in SAS® was used to model the relationship between maximum change in area under the curve and maximum change in mouth pressure as well as the relationship between maximum change in height and maximum change in mouth pressure. Each subject contributed a single data point for each level of applied obstruction, representing the average of the 7.5-second intervals for that level of applied obstruction. Akaike's Information Criteria was used to compare the fit of the area under the curve vs. height models for mouth pressure [25]. An alpha level of p < .05 was considered statistically significant. A total sample size of 30 subjects would allow us to construct a 95% CI for correlation and achieve a power of 0.8 and a two-tailed alpha of 0.05.
Results
Forty-eight subjects were enrolled in the study; no subject experienced any known adverse event during or as a result of this study. Two subjects were found after enrollment to have asthma and were excluded from data analysis. Eight subjects experienced an uncomfortable sensation of dyspnea and could not use the closed airway circuit in accordance with study protocol. Data from these subjects was excluded from analysis. Seven subjects had recurrent electrical interference of the waveform baseline, the source of which could not be determined after consultation with software and hardware engineers (BioPac Systems, Santa Barbara, CA). Data from these seven subjects was excluded from analysis. Overall thirty-one subjects met inclusion criteria and had data included for analysis.
Of these thirty-one subjects, eleven were male and twenty were female. The mean age was 29.9 years with a median of 28 years and range of 23 to 48 years. One subject had a prior history of cigarette smoking. No subject had heart or lung disease. One subject performed breathing maneuvers at five levels of applied obstruction, one subject at eight levels, six subjects at nine levels, and twenty-three subjects at ten levels. A total of 297 data points were available for analysis. Plethysmograph waveforms were noted to return to baseline during the period of rest (at least 1 minute) between sequentially increasing levels of applied resistance.
Subjects were noted to generate plethysmograph waveforms visually significant for periodic changes with the respiratory cycle, similar to changes characteristic of pulsus paradoxus, when utilizing this apparatus (Figure 1). There was a significant relationship between plethysmograph waveform maximum change in area under the curve and maximum change in mouth pressure (P < 0.0001) (Figure 2). The prediction equation for each cmH20 maximum change in mouth pressure was 12.01 + 37.21 × (maximum change in area under the curve), 95% CI for coefficient = 30.56 to 43.87. Similarly, there was a significant relationship between maximum change in height and maximum change in mouth pressure (P <0.0001). The prediction equation for each cmH20 maximum change in mouth pressure was 16.10 + 35.94 × (maximum change in height), 95% CI for coefficient = 27.57 to 43.30. A comparison of Akaike's Information Criteria (AIC) between the models showed that the AIC statistic was smaller for the area under the curve model than the height model, indicating a better model fit for the area under the curve model.
Figure 1 Oximeter plethysmographic waveform (Pleth) generated with inspiratory and expiratory pressure relief valve apparatus. Corresponding mouth pressure indicates pressure at airway circuit mouthpiece.
Figure 2 Relationship between maximum changes in mouth pressure and area under the plethysmograph waveform curve.
Discussion
Pulse oximetry is widely available and applied in acute care settings. The device outputs a continuous plethysmographic waveform corresponding to flow of arterialized blood in the tissue bed to which the transducer is applied [10,12-14]. It is plausible that, in the setting of airway obstruction, such changes in arteriolar flow might reflect alterations in left ventricular stroke volume resulting from the same physiologic perturbations that abnormally increase pulsus paradoxus. It is thus of interest whether the severity of airway obstruction might be estimated from changes in mathematic plethysmograph waveform variables. The study results indicate a correlation between maximum changes in area under the curve or in height of the plethysmograph waveform and the severity of airway obstruction.
Analysis of both direct arterial waveform and oximeter plethysmograph waveform data for calculation of arterial flow have previously been explored in the laboratory setting. Cerutti and colleagues provide compelling data from conscious, freely moving Sprague-Dawley rats [26]. These investigators compared different models of central arterial line waveform analysis with simultaneously recorded cardiac output. A model using different waveform parameters identified by multiple linear regression analysis provided a reliable and precise estimation of cardiac output. Although these investigators did not use oximeter plethysmograph waveforms, their findings nonetheless support the principal of waveform analysis. Steele and colleagues performed an unblinded study on one healthy adult, breathing through a valve to which airway resistance was applied to artificially induce pulsus paradoxus. For this subject, the percent decrease in plethysmograph waveform height during the respiratory cycle correlated modestly with pulsus paradoxus calculated similarly from intra-arterial waveform (r = 0.59, 95% CI 0.32 to 0.78). This study was limited by the small subject size (n = 1) and did not measure the degree of airway obstruction generated by the resistance valves in use. The technique relied upon determination of phases of the respiratory cycle and capture of waveform indices in accordance with estimated peak inspiration and expiration [16].
In the clinical setting, variation of the oximeter plethysmograph waveform baseline has been noted to occur during the respiratory cycle and to represent fluctuations in local venous pressure [14,18]. Hartert and colleagues hypothesized that this respiratory waveform variation might occur in response to pleural pressure changes and thus reflect changes in left ventricular stroke volume and pulsus paradoxus. This was studied in adult patients admitted to an ICU with obstructive airway disease, 46% of whom were receiving mechanical ventilation. Respiratory waveform variation was significantly correlated with manually measured pulsus paradoxus (R2 = 0.88) as well as with auto-PEEP (R2 = 0.96) [18]. Frey and Butt compared simultaneous 1 minute paper recordings of intra-arterial pressure and plethysmograph waveforms in 62 non-intubated children with and without respiratory disease. Correlation was noted (r = 0.85) between changes in plethysmograph waveform height and pulsus paradoxus determined from intra-arterial waveform height change [17]. Our study demonstrates that maximal change in height and in area under the plethysmograph waveform curve might provide a non-invasive, clinically relevant estimate of the severity of airway obstruction.
A possible limitation to our study was the method of artificially inducing airway obstruction. The dynamic biomechanical changes occurring during an asthma exacerbation are not ideally simulated by externally applied resistance [27]. Also, in lieu of invasive, intra-arterial waveform analysis as the dependent variable and reference standard, the study protocol utilized change in mouth pressure as a surrogate measure of obstruction induced. The levels of progressive obstruction were not standardized, except insofar as the mouth pressure generated reflects intrapleural pressure [21]. As well, subjects were exposed to both inspiratory and expiratory obstruction during the test period. It is of interest whether correlations of waveform parameters may differ during isolated inspiratory or expiratory obstruction. Other variables that may influence the plethysmograph waveform, including hydration status, hyperinflation, and tidal volume, were likewise not controlled for in this study.
Our method of using time intervals to measure changes in plethysmograph waveform AUC, HT and mouth pressure is unique. Pulsus paradoxus has traditionally been determined by noting the difference between the systolic pressure at which heart sounds are heard only during expiration and the point at which they are heard continuously [28-30]. However, in the tachypneic patient it is often difficult to correlate auscultation of heart sounds with the corresponding phase of the respiratory cycle. With this in mind, we chose to analyze data during specified time intervals that would encompass at least one respiratory cycle. The chosen interval, 7.5 seconds, was based upon the expected duration of the respiratory cycle in our subjects.
We additionally chose to utilize the average values of data extracted from sequential intervals at each level of applied obstruction. Frey and Freezer demonstrated significant intrasubject variation of breath-to-breath measurement of pulsus paradoxus utilizing arterial waveform tracings, and averaging of pulsus paradoxus determined from multiple consecutive respiratory cycles was reported to be more accurate [19]. Pulse oximeters have incorporated an analogous technology for calculation of Sp02, running weighted signal averaging, to minimize the effect of signal artifact and to thus enhance the reliability and validity of the calculated Sp02 [13]. Oxygen saturation is calculated 30 times per second with values averaged over a minimum of several seconds. Each instantaneous value is first compared with this moving average and assigned a weighted value based upon variation from the moving average. This weighted value then contributes to the moving average that in turn is displayed as the Sp02 value [13]. Our analysis may minimize the influence of individual waveform and respiratory cycle artifact and thus enhance the internal validity of the estimated airway obstruction. With these elements of waveform analysis in mind, our method of measuring waveform parameters may represent a strength of study design rather than a limitation.
Conclusion
There is accumulating evidence that the plethysmograph waveform might provide clinically useful information. Our results suggest that analysis of oximeter plethysmograph waveform data may be feasible for real-time estimation of airway obstruction. To our knowledge this is the first investigation of area under the curve as a waveform parameter of potential value, and our results indicate that this parameter may achieve better correlation with airway obstruction than analyses based on waveform height. A non-invasive, real-time method to estimate the severity of airway obstruction, as well as other disorders involving pulsus paradoxus physiology, might enhance the ability of clinicians to identify and quantify the severity of such disorders [31]. An essential step in the development of such technology is to validate the physiologic relevance of estimating the severity of these pathophysiologic events from the oximeter plethysmograph waveform. Future study of patients with obstructive airway disease in the clinical environment, using a quantifiable, objective criterion standard such as FEV1 will enable further assessment of oximeter plethysmograph waveform parameters to predict severity of airway obstruction. Should the accuracy and feasibility of such a tool be demonstrated in the clinical environment, development of this technology for routine clinical practice may be justified.
Competing interests
Don Arnold has applied for patent protection for methods of waveform analysis discussed in this manuscript.
Authors' contributions
DA was the principal investigator and participated in study concept and design, acquisition of the data, drafting of the manuscript and obtained institutional funding for this study to be conducted.
DS was a co-investigator and participated in study concept and design, acquisition of the data, drafting of the manuscript and critical revision of the manuscript for important intellectual content.
RD assisted in the statistical design and analysis and interpretation of the data, and provided critical revision of the manuscript for important intellectual content.
JH participated in study concept and design, acquisition of the data, drafting of the manuscript, critical revision of the manuscript for important intellectual content, and supervised the study.
Grants
This study was funded by a grant from The Research Institute at The Children's Hospital of Alabama.
Acknowledgements
The authors are gratified for the assistance of Sheila S. Gibson, R.R.T., R.P.F.T. Johanna Kimbrough, R.P.T., and Bettye Mitchell, R.P.T. in the conduct of this study.
==== Refs
Mannino DM Homa DM Akinbami LJ Moorman JE Gwynn C Redd SC Surveillance for asthma--United States, 1980-1999 MMWR Surveill Summ 2002 51 1 13
Asthma prevalence and control characteristics by race/ethnicity---United States, 2002 MMWR Morb Mortal Wkly Rep 2004 53 145 148 14985651
Akinbami LJ Schoendorf KC Trends in childhood asthma: prevalence, health care utilization, and mortality Pediatrics 2002 110 315 322 12165584 10.1542/peds.110.2.315
Asthma mortality and hospitalization among children and young adults--United States, 1980-1993 MMWR Morb Mortal Wkly Rep 1996 45 350 353 8604212
Denny FW Clyde WAJ Acute lower respiratory tract infections in nonhospitalized children J Pediatr 1986 108 635 646 3009769
Shay DK Holman RC Newman RD Liu LL Stout JW Anderson LJ Bronchiolitis-associated hospitalizations among US children, 1980-1996 JAMA 1999 282 1440 1446 10535434 10.1001/jama.282.15.1440
Pauwels RA Buist AS Calverley PM Jenkins CR Hurd SS Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease. NHLBI/WHO Global Initiative for Chronic Obstructive Lung Disease (GOLD) Workshop summary Am J Respir Crit Care Med 2001 163 1256 1276 11316667
Eid N Yandell B Howell L Eddy M Sheikh S Can peak expiratory flow predict airflow obstruction in children with asthma? Pediatrics 2000 105 354 358 10654955 10.1542/peds.105.2.354
Mallory MD Shay DK Garrett J Bordley WC Bronchiolitis Management Preferences and the Influence of Pulse Oximetry and Respiratory Rate on the Decision to Admit Pediatrics 2003 111 e45 e51 12509594 10.1542/peds.111.1.e45
Cook LB Extracting arterial flow waveforms from pulse oximeter waveforms apparatus Anaesthesia 2001 56 551 555 11412161 10.1046/j.1365-2044.2001.01986.x
Kim JM Arakawa K Benson KT Fox DK Pulse oximetry and circulatory kinetics associated with pulse volume amplitude measured by photoelectric plethysmography Anesth Analg 1986 65 1333 1339 3777465
Wisely NA Cook LB Arterial flow waveforms from pulse oximetry compared with measured Doppler flow waveforms apparatus Anaesthesia 2001 56 556 561 11412162 10.1046/j.1365-2044.2001.01987.x
Wukitsch MW Petterson MT Tobler DR Pologe JA Pulse oximetry: analysis of theory, technology, and practice J Clin Monit 1988 4 290 301 3057122 10.1007/BF01617328
Murray WB Foster PA The peripheral pulse wave: information overlooked J Clin Monit 1996 12 365 377 8934343
Jardin F Farcot JC Boisante L Prost JF Gueret P Bourdarias JP Mechanism of paradoxic pulse in bronchial asthma Circulation 1982 66 887 894 7116605
Steele DW Wright RO Lee CM Jay GD Continuous noninvasive determination of pulsus paradoxus: a pilot study Acad Emerg Med 1995 2 894 900 8542490
Frey B Butt W Pulse oximetry for assessment of pulsus paradoxus: a clinical study in children Intensive Care Med 1998 24 242 246 9565806 10.1007/s001340050557
Hartert TV Wheeler AP Sheller JR Use of pulse oximetry to recognize severity of airflow obstruction in obstructive airway disease: correlation with pulsus paradoxus Chest 1999 115 475 481 10027449 10.1378/chest.115.2.475
Frey B Freezer N Diagnostic value and pathophysiologic basis of pulsus paradoxus in infants and children with respiratory disease Pediatr Pulmonol 2001 31 138 143 11180690 10.1002/1099-0496(200102)31:2<138::AID-PPUL1022>3.0.CO;2-R
Sijbers J Scheunders P Bonnet N Van Dyck D Raman E Quantification and improvement of the signal-to-noise ratio in a magnetic resonance image acquisition procedure Magn Reson Imaging 1996 14 1157 1163 9065906 10.1016/S0730-725X(96)00219-6
Karam M Wise RA Natarajan TK Permutt S Wagner HN Mechanism of decreased left ventricular stroke volume during inspiration in man Circulation 1984 69 866 873 6705161
Lung function testing: selection of reference values and interpretative strategies. American Thoracic Society Am Rev Respir Dis 1991 144 1202 1218 1952453
Standardization of Spirometry, 1994 Update. American Thoracic Society Am J Respir Crit Care Med 1995 152 1107 1136 7663792
Biopac Systems I Research catalog for the life sciences 2003 Santa Barbara, CA, Biopac Systems, Inc.
Littell RC Milliken GASWW Wolfinger RD SAS System for Mixed Models 2004 North Carolina, SAS Institute, Inc
Cerutti C Gustin MP Molino P Paultre CZ Beat-to-beat stroke volume estimation from aortic pressure waveform in conscious rats: comparison of models Am J Physiol Heart Circ Physiol 2001 281 H1148 H1155 11514281
Kelsen SG Prestel TF Cherniack NS Chester EH Deal ECJ Comparison of the respiratory responses to external resistive loading and bronchoconstriction J Clin Invest 1981 67 1761 1768 6787083
HM S Blood vessels examination and findings Mosby's guide to physical examination 2003 14 5 St. Louis, Mosby 481
LS B and PG S The cardiovascular system Bates' guide to physical examination and history taking 2003 Philadelphia, Lippincott Williams & Wilkins 285
e B JK P e B, PZ Z and P L Physical examination of the heart and circulation. Heart Disease, A textbook of Cardiovascular Medicine 2001 4 6 Philadelphia, WB Saunders 45 81
Tamburro RF Ring JC Womback K Detection of pulsus paradoxus associated with large pericardial effusions in pediatric patients by analysis of the pulse-oximetry waveform Pediatrics 2002 109 673 677 11927714 10.1542/peds.109.4.673
| 15985171 | PMC1168908 | CC BY | 2021-01-04 16:23:26 | no | Respir Res. 2005 Jun 28; 6(1):65 | utf-8 | Respir Res | 2,005 | 10.1186/1465-9921-6-65 | oa_comm |
==== Front
World J Surg OncolWorld Journal of Surgical Oncology1477-7819BioMed Central London 1477-7819-3-371596974610.1186/1477-7819-3-37ResearchMorbidity and mortality after esophagectomy for esophageal carcinoma: A risk analysis Gockel Ines [email protected] Christoph [email protected] Theodor [email protected] Department of General and Abdominal Surgery, Johannes Gutenberg University of Mainz, Germany2005 21 6 2005 3 37 37 1 6 2005 21 6 2005 Copyright © 2005 Gockel et al; licensee BioMed Central Ltd.2005Gockel et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
The study was aimed to identify pre- and intraoperative risk factors that potentially influence morbidity and mortality after esophagectomy for esophageal carcinoma with particular emphasis on the predominant tumor types.
Patients and methods
Between September 1985 and March 2004, 424 patients underwent esophagectomy for esophageal carcinoma. Of these, 186 (43.9%) patients had a transhiatal, and 231 (54.5%) patients underwent a transthoracic procedure with two-field lymphadenectomy. Pre-, intraoperative risk factors and tumor characteristics were included in the risk analysis to assess their influence on postoperative morbidity and mortality.
Results
Multivariate analysis (logistic regression model) identified the surgical procedure as the most important risk factor for postoperative morbidity and mortality with the transthoracic technique associated with a significant higher risk. The comparison of the risk profile between the different histological tumor types, a significantly higher nutritional risk, poorer preoperative lung function and a higher prevalence of hepatopathy was observed in patients with squamous cell carcinoma (n = 229) compared to adenocarcinoma (n = 150) (p < 0.05). Although there was no significant difference in surgical complications between the two groups, the rate of general complications, length of postoperative intensive care unit-stay and mortality rate was significantly higher in patients with squamous cell carcinoma (p < 0.05).
Conclusion
The present risk analysis shows that the selection and the type of the surgical procedure are crucial factors for both the incidence of postoperative complications and the mortality rate. The higher risk of the transthoracic procedure is justified with a view to a better long term prognosis.
==== Body
Background
Despite the standardization of the operative technique, improvement of preoperative risk assessment, and postoperative intensive care management, surgical therapy for esophageal carcinoma continues to be associated with a high incidence of operative complications, and a high mortality rate. Risk stratification in the selection of patients for surgery, and the choice of the surgical procedure are therefore important considerations.
The present study was aimed to identify preoperative and intraoperative factors that could potentially influence morbidity and mortality after esophagectomy for esophageal carcinoma.
Patients and methods
Between September 1985 and March 2004, a total of 424 patients underwent esophagectomy for esophageal carcinoma in the Department of General and Abdominal Surgery of the Johannes Gutenberg-University Hospital Mainz. Of these, 186 (43.9%) patients had transhiatal esophagectomy, 231 (54.5%) patients underwent abdominothoracic esophagectomy with two-field lymphadenectomy (abdominal and mediastinal) and 7 patients had a proximal esophageal resection with a free jejunal graft. Reconstruction was accomplished by gastric tube pull-up in 384 (93.0%) patients, by colon interposition in 21 (5.1%), and small intestine interposition in 7 (1.7%) patients; the anatomic prevertebral esophageal bed was used for the majority of these procedures. Extra-anatomic reconstruction by the retrosternal route with cervical anastomosis after pull-up was carried out in patients with a high risk for loco-regional recurrence only (n = 42; 10.2%).
Abdominothoracic esophagectomy was routinely performed for squamous cell carcinoma (n = 229). A transhiatal procedure was selected for tumors with a distal location, for malignancies without esophageal wall penetration, or in the presence of a high general risk. Transhiatal esophagectomy with abdominal and posterior mediastinal lymphadenectomy was carried out for the majority of adenocarcinomas (n = 150), the two-field procedure was performed in the presence of advanced tumor growth or extended lymph node involvement. Long-term results of this choice of the operative procedure adjusted to the histological tumor type had shown a significant prognostic advantage in patients undergoing transthoracic compared to transhiatal resection in squamous cell carcinoma whereas there was no survival benefit in patients with adenocarcinoma of the esophagus [Junginger T, et al.; Gockel I et al.; unpublished data].
Data were collected prospectively in a specially established database. Preoperative and intraoperative variables as well as postoperative morbidity and mortality were documented, in addition to routine demographic data.
The following preoperative risk factors were recorded: ASA-classification (I-IV) according to the preoperative anesthesiology evaluation, BMI (Body Mass Index) based on body weight and height in kg/m2, and the nutritional status on a scale from 0 (= no alcohol or tobacco consumption), 1 (= tobacco alone), 2 (alcohol alone) to 3 (= combined nutritional risk with tobacco and alcohol use). Among the preoperative diseases, cardiovascular risk factors were defined as a history of coronary heart disease, or myocardial infarction, arterial hypertension, valvular disease (>II°), arrhythmia requiring therapy (>III° according to the Lown-classification), congestive heart failure NYHA (New York Heart Association) > Grade II, and peripheral occlusive arterial disease (>IIb according to Fontaine). A history of chronic obstructive pulmonary disease (COPD), regular tobacco consumption and/or the use of bronchodilators were subsumed under pulmonary diseases. The preoperative assessment of the vital capacity (VC) and forced expiratory volume (FEV1 = Tiffeneau-test) served to ensure a more accurate assessment. Prior cirrhosis of the liver (>/= CHILD-Pugh A) was defined as hepatic disease, and determined on the basis of the assessment of serum albumin (g/dl), serum bilirubin (mg/dl), Quick-value (%), and the presence of ascites or encephalopathy. The evaluation of additional risk factors included the prevalence of diabetes mellitus (insulin-dependent or requiring oral antidiabetic therapy), and the history of a secondary carcinoma.
Intraoperative variables included in the risk analysis were tumor location, the operative procedure, and the transfusion requirement of packed erythrocytes. The group of tumor characteristics comprised tumor size, R-classification, TNM-stage, and the number of dissected lymph nodes.
Postoperative variables were not part of this risk analysis. Morbidity, surgical (anastomotic leakage, graft necrosis, mediastinitis, recurrent laryngeal nerve paralysis, chylothorax, tracheal fistula, bleeding requiring reoperation) and general complications (pneumonia, atelectasis, ARDS i.e. adult respiratory distress syndrome, myocardial infarction, cardiac failure, pulmonary embolism, renal insufficiency, pancreatitis, deep vein thrombosis), length of intensive care unit stay, 30-day mortality, and the mortality rate served as factors for assessment.
Statistical analysis
The SSPS 10.0 software package was used for statistical data analysis (SSPS, Chicago, IL, USA: 1999). Data are expressed as median with ranges (minimum – maximum), or as percentages (%).
Factors with a possible influence on perioperative morbidity and mortality were calculated using the logistic regression model (univariate and multivariate). The χ2 test with Pearson's correction and Fisher's exact test were used for comparison of the parameters for squamous cell carcinoma and adenocarcinoma. The Mann-Whitney U test served as the non-parametric method. A p -value of <0.05 was considered statistically significant for all procedures.
Results
Preoperative and intraoperative parameters, tumor characteristics
Median patient age at the time of surgery was 58 (28–84) years; the proportion of males was 83.0%. The median BMI (Body Mass Index) was 24.4 (13.8–39.3) kg/m2. A total of 36.9% patients were classified as ASA grade II, 58.2% as ASA grade III, and 4.9% as ASA grade IV. A combined nutritional risk (alcohol and tobacco use) was determined in 41.5% of patients. Tobacco use alone was found in 59.1%, and habitual alcohol consumption in 58.2% of patients. Preexisting cardiovascular diseases were noted in 28.2%, pulmonary disease in 13.5%, hepatopathy in 4.9%, and diabetes mellitus in 5.9% of patients undergoing surgery for esophageal carcinoma. The history of 9.8% of all patients showed the presence of secondary carcinoma. Median preoperative vital capacity (VC) ranged at 3.8 (1–7.2) l, FEV1 (Tiffeneau-test) was 2.9 (0.5–9.0) l/sec.
Out of all tumors, 56.3% were located in the lower, 34.6% in the middle, and 9.1% in the upper third of the esophagus. Squamous cell carcinoma was identified in 55.3%, adenocarcinoma in 35.9%, and an undifferentiated carcinoma in 7.6% of patients (1.2% with other malignant esophageal tumors, e.g. melanoma) who underwent esophagectomy.
Operative time ranged at 300 (160–560) minutes. The median number of packed erythrocyte units used was 1 (0–38) (54.6% of all patients did not require packed erythrocyte transfusion). Median length of intensive care therapy was 10 (0–176) days, at a total postoperative hospital stay of 22 (0–189) days. Median tumor size was 4 (0.3–20) cm. A R0 resection was accomplished in 81.0% of all patients (R1 resection: 16.0%, R2 resection: 3.0%). Based on results of the pathological examination, the majority of tumors were assigned to the T3 category (57.5%), while 34.6% of all tumors were allocated to the T1 or T2, and 7.9% to the T4-category. Distribution for the N category was as follows: N0: 34.0%, N1: 66.0%. A M1-situation (M1-lymph node or M1-organ) was identified in 26.5% of all patients, which was treated with curative intent in the course of the same surgical procedure.
Morbidity and mortality: Prevalence and influence factors
There was a 35.5% prevalence of surgical complications in the total population of 424 patients undergoing esophagectomy for esophageal carcinoma. General complications were observed in 36.0% of all patients. The 30-day mortality rate was 6.7%, at a mortality rate for the entire observation period of 11.5%.
Anastomotic leakage was the most common surgical complication (18.2%), followed by recurrent laryngeal nerve paresis (15.7%). There was a similar incidence of graft necrosis (3.2%) and postoperative hemorrhage (2.9%) requiring surgical revision, while 1.3% of all patients developed a chylothorax.
Univariate analysis showed tumor location (p = 0.0194) and the surgical procedure (p = 0.0116) to be significantly related to the incidence of surgical complications; none of the other pre- and intraoperative factors, including tumor characteristics, were of relevance in this model (Table 1). Multivariate analysis identified the transthoracic surgical procedure (p = 0.0004), tumor location (upper third) (p = 0.02), and the transfusion of packed erythrocytes (p = 0.04) as factors significantly related to the incidence of surgical complications (Table 2).
Table 1 Factors with a potential influence on surgical and general complications, as well as on the perioperative mortality rate after esophagectomy for esophageal carcinoma: univariate analysis (p values).
Surgical complications General Complications Perioperative Mortality
Preoperative factors:
- Age 0.8996 0.0073* 0.1349
- Sex 0.7367 0.3396 0.5658
- BMI 0.3710 0.1200 0.0719
- ASA 0.3992 0.0076* 0.0274*
- Nutritional status 0.5093 0.1897 0.2223
- Cardiovascular PD 0.7803 0.0171* 0.0172*
- Pulmonary PD 0.2910 0.0405* 0.0059*
- Hepatopathy 0.1696 0.0282* 0.0165*
- Diabetes mellitus 0.8218 0.0635 0.9430
Intraoperative factors:
- Tumor location 0.0194* 0.0156* 0.0391*
- Surgical procedure 0.0116* 0.0001* 0.0057*
- Packed erythrocyte transfusion 0.1045 0.0006* 0.0022*
Tumor characteristics:
- Tumor size 0.5041 0.1595 0.1502
- R-classification 0.5573 0.3372 0.0439*
- T-category 0.2017 0.0072* 0.0036*
- N-category 0.6805 0.9928 0.0584
- M-category 0.0621 0.8128 0.4359
*statistically significant
Table 2 Significant factors with a potential influence on surgical and general complications, as well as on the perioperative mortality rate after esophagectomy for esophageal carcinoma: multivariate analysis (p value).
Surgical complications General complications Perioperative Mortality
Surgical procedure (p = 0.0004) Surgical procedure (p = 0.0001) Surgical procedure (p = 0.0068)
Tumor location (p = 0.0204) Packed erythrocyte transfusion (p = 0.0009) Pulmonary PD (p = 0.0096)
Packed erythrocyte transfusion (p = 0.0493) Patient age (p = 0.0039) Packed erythrocyte transfusion (p = 0.0099)
Nutritional status (p = 0.0284)
ASA-classification (p = 0.0486)
Pulmonary complications were most common among the general complications (32.9%). Adult respiratory distress syndrome (ARDS) occurred in 6.5% of patients. Postoperatively, 3.7% of patients developed renal failure requiring dialysis, and myocardial infarction or pulmonary embolism occurred in 1.2%, respectively, of all patients. Postoperative pancreatitis was found in 0.5% of patients. Univariate analysis determined patient age (p = 0.0073), ASA-classification (p = 0.0076), preexisting cardiovascular (p = 0.0171), pulmonary (p = 0.0405), and hepatic (p = 0.0282) disease as significant preoperative variables in relation to postoperative general complications. Similarly significant among the intraoperative factors were tumor location (p = 0.0156), the surgical procedure (p = 0.0001), transfusion of packed erythrocytes, as well as the T-category in the group of tumor characteristics (Table 1). On multivariate analysis, independent parameters with a significant influence on postoperative general complications were in decreasing order: the surgical procedure (p = 0.0001), transfusion of packed erythrocytes (p = 0.0009), patient age (p = 0.0039), nutritional status (p = 0.0284), and ASA-classification (p = 0.0486) (Table 2).
The cause of postoperative mortality (11.5%; n = 49 patients) in 19 patients was sepsis (accounted for by anastomotic insufficiency in 8, and in 3 patients by graft necrosis). Twelve patients died from pulmonary failure, and 5 patients died after myocardial infarction. Fulminant pulmonary embolism was the cause of death in 3 patients (one out of these occurred in a patient with suture dehiscence). Two patients developed hemorrhagic shock, and another 2 patients died in hospital from rapid progression of the malignant disease. Further causes of hospital death in 6 additional patients after esophagectomy were; hepatorenal syndrome, syncopal attack with cardiovascular failure, right ventricular heard failure, medial cerebral infarction, intraoperative cardiac arrest, and tracheogastric fistula.
Preoperative variables as predictors of a fatal postoperative course found on univariate analysis comprised ASA-classification (p = 0.0274), preexisting cardiovascular (p = 0.0172) and pulmonary disease (p = 0.0059), and hepatopathy (p = 0.0165). Further factors exerting an influence on mortality were: tumor location (p = 0.0391), the surgical procedure (p = 0.0057), packed erythrocyte transfusion (p = 0.0022), R-classification (p = 0.0439), and T-category (p = 0.0036) (Table 1). Multivariate analysis identified the surgical procedure (p = 0.0068), preexisting pulmonary disease (p = 0.0096), and the transfusion of packed erythrocytes (p = 0.0099) as the most significant predictors of mortality (Table 2).
Risk profile: comparison between squamous cell carcinoma and adenocarcinoma
From among the group of preoperative factors, patients with adenocarcinoma were characterized by significantly more advanced age and a higher BMI (p < 0.0001) compared to those with squamous cell carcinoma. Differences in gender distribution and ASA-classification were not significant. There was a significantly higher nutritional risk (alcohol and tobacco use) in patients with squamous cell carcinoma than in the comparison group of patients with adenocarcinoma undergoing esophagectomy (p < 0.001). The incidence of cardiovascular and pulmonary disease, as well as preexisting diabetes mellitus, or secondary carcinoma in the patient history was similar in both groups. However, patients with squamous cell carcinoma had significantly poorer preoperative lung function (p = 0.0078), and a higher prevalence of hepatopathy (p < 0.0001) (Table 3).
Table 3 Comparison of the preoperative risk profile between patients with squamous cell carcinoma and adenocarcinoma of the esophagus.
Parameter Squamous cell carcinoma (n = 229) Adenocarcinoma (n = 150) p-value
- Age (years) 56.0 (29–84) 61.0 (28–78) 0.0001*
- Sex (% males) 79.8 87.4 0.071
- BMI (kg/m2) 23.2 (13.9–34.9) 25.8 (15.8–39.3) 0.0001*
- ASA-classification (%)
-II 33.2 43.2
-III 62.4 52.1 0.072
-IV 4.4 4.8
- Nutritional risk (%)
-No nutritional risk (%) 16.2 43.2 0.0001*
-Alcohol use (%) 69.5 42.9 0.0001*
-Tobacco use (%) 73.5 38.1 0.0001*
-Combined risk (%) 83.8 56.9 0.0001*
- Cardiovascular PD (%) 30.4 24.7 0.240
- Pulmonary PD (%) 14.7 14.4 0.593
-VC (l) 3.7 (1.0–6.6) 3.8 (1.9–6.1) 0.3063
-FEV 1 (l/sec) 2.8 (0.5–5.2) 3.1 (1.3–5.9) 0.0078*
- Hepatopathy (%) 8.1 1.4 0.0001*
- Diabetes mellitus (%) 4.9 7.5 0.369
- Secondary carcinoma (%) 11.2 8.2 0.382
*statistically significant
The surgical procedure used was different with respect to the significantly more frequent performance of transhiatal esophagectomy in patients with adenocarcinoma (p < 0.0001). In the presence of this histological subtype, the gastric tube (p = 0.027) brought up in the existing esophageal bed (p = 0.001) was used more often as the interposed organ. The number of dissected abdominal lymph nodes was significantly higher (p = 0.0146) for adenocarcinoma, while a significantly higher number of thoracic lymph nodes (p = 0.0011) was removed in patients with squamous cell carcinoma. The operative time was significantly shorter (p < 0.0001) at a lower packed erythrocyte transfusion requirement for adenocarcinoma (p = 0.0495) compared to squamous cell carcinoma (Table 4). There was no significant difference between the two groups with regard to UICC stages and tumor characteristics (p > 0.05).
Table 4 Intraoperative Factors: Comparison between squamous cell carcinoma and adenocarcinoma of the esophagus.
parameter Squamous cell carcinoma (n = 229) Adenocarcinoma (n = 150) p-value
- Surgical procedure (% transhiatal) 30.6 68.7 0.0001*
- Esophageal substitute (% gastric tube) 90.8 97.3 0.027*
- Repositioning (% esophageal bed) 83.7 95.3 0.001*
- Number of removed abdominal LN (n) 11 (0–55) 13 (0–51) 0.0146*
- Number of removed thoracic LN (n) 11 (0–47) 6 (0–83) 0.0011*
- Operative time (min) 305 (115–560) 270 (160–540) 0.0001*
- Intraoperative blood loss (ml) 1000 (200–5000) 800 (0–7500) 0.2224
- Units of transfused packed erythrocytes (n) 1.5 (0–38) 0 (0–14) 0.0495*
*statistically significant
Although there was no significant difference in surgical complications between the two groups, the rate of general complications (p = 0.012), and thus the total complication rate, (p = 0.039) was significantly higher in patients with squamous cell carcinoma. Comparable to the morbidity rate, the duration of postoperative intensive care therapy was significantly longer (p < 0.0001) for this type of tumor than for adenocarcinoma.
The 30-day mortality rate was identical for both groups, while the mortality rate in patients with squamous cell carcinoma was significantly higher (p < 0.0001) (Table 5).
Table 5 Postoperative morbidity and mortality for squamous cell carcinoma compared with adenocarcinoma of the esophagus.
parameter Squamous cell carcinoma (n = 229) Adenocarcinoma (n = 150) p-value
- Surgical complications (%)
- General complications (%) 37.9 33.7 0.447
-Total complications (%) 40.7 28.0 0.012*
- Length of ICU – stay (d) 68.1 57.6 0.039*
- 30-day-moratlity (%)
- Mortality (%) 11 (2–176) 8 (1–107) 0.0001*
6.1 6.1 0.8569
15.1 6.6 0.0001*
*statistically significant
Discussion
Although the morbidity rate after esophagectomy for esophageal carcinoma has been markedly reduced in recent years as a result of improvements in patient selection, surgical technique, and advances in perioperative management, the morbidity rate remains high [1-7]. Pulmonary function disturbances are the major contributing factor here [8-10]. Risk factors for the development of impaired pulmonary function include smoking, patient age (>70 years), obesity, and preexisting COPD [11]. Parameters with an influence on perioperative mortality defined by Bartels et al , are in decreasing order: reduced general status of the patient, impaired cardiac and hepatic function, and respiratory function [12]. The evaluation of the preoperative function of the described organ systems using a scoring system developed by the authors enables the classification of risk groups, and leads to a decrease in the operative risk as a result of adequate patient selection [12].
The aim of our analysis of data collected prospectively in 424 patients undergoing surgery for esophageal carcinoma was to answer the question as to what extent the selection of the surgical procedure, i.e. the transthoracic or the transhiatal approach, and the operative course assessed on the basis of intraoperative blood loss, in addition to patient and tumor related factors, exert an influence on the postoperative course.
The data were collected in 424 consecutive patients undergoing surgery for esophageal carcinoma over the period from 1985 to 2004. Surgical complications occurred in 35.5% and general complications in 36.0% of patients. The 30-day mortality rate ranged at 6.7%, at a mortality rate of 11.5%. Univariate analysis identified the selection of the surgical procedure as the main risk factor affecting the mortality rate. Transthoracic esophagectomy was associated with a higher complication and mortality rate than transhiatal dissection. Various authors have investigated the question as to the effectiveness of an extended radical procedure with an associated increased operative risk after the transthoracic technique. Results of two randomized studies did not demonstrate a difference between these procedures, although the meaningfulness of these findings is limited due to the small number of patients enrolled and the lack of information on the oncological radicality, especially the extent of lymph node dissection [13,14]. In addition, only patients with early tumor stages [14] or with a distal location of the carcinoma [13] were taken into consideration, respectively.
A higher pulmonary complication rate after the transthoracic compared to the transhiatal procedure for adenocarcinoma was found by a prospective randomized study [15]. Postoperative ventilation time, intensive care unit and postoperative in-hospital stay, reflecting perioperative morbidity, were significantly longer after transthoracic in contrast to transhiatal esophagectomy in this trial. However, the authors did not determine any differences in the long-term course [15]. This prospective study confirmed the outcome of a meta analysis revealing significantly higher early (pulmonary) morbidity and mortality after the transthoracic procedure published previously by the same author with 5-year survival rates of approximately 20% after both kinds of resection [16]. In our patient population, the long-term prognosis for patients with squamous cell carcinoma undergoing transthoracic surgery – though exhibiting a higher perioperative morbidity and mortality – was significantly better than that for patients after transhiatal resection [Junginger T, et al.; unpublished data]. Patients with adenocarcinoma did not differ in survival undergoing transhiatal or transthoracic esophagectomy [Gockel I, et al; unpublished data]. In concert with other authors, we therefore favor the transhiatal technique with posterior mediastinal and upper abdominal lymph node dissection for adenocarcinoma of the esophagus, and the transthoracic procedure with abdominal and mediastinal lymphadenectomy for squamous cell carcinoma. Thus – long term results regarding the surgical technique of our own patient population have to be viewed critically, especially for adenocarcinoma, as the two groups differed significantly in UICC-stage and R-classification in contrast to patients with squamous cell carcinoma with a rather equal distribution [1,2].
Independent of the operative procedure, surgical blood loss had a significant influence on the postoperative morbidity and mortality rates. This is in accordance with experiences reported by Whooley et al [8], and indicates that the selection of a limited resection technique can be crucial for the development of the postoperative course. Patient-associated parameters (age, nutritional status, ASA-classification) were of relevance only with respect to the occurrence of general complications.
Preexisting pulmonary disease was an independent predictor of postoperative mortality. This confirms the findings of Chan et al , who identified impaired pulmonary function as a preoperative variable predictive of postoperative mortality [17]. The implementation of an appropriate preoperative therapy, discontinuation of smoking, more frequent use of epidural analgesia, and early bronchoscopy in the presence of the suspicion of postoperative pulmonary secretion impairment are essential factors for risk reduction [8].
In contrast to results of risk analyses by Law et al [18] and Lund et al [19], tumor characteristics as, e.g. TNM classification, were of no influence on the postoperative course in the patient population of this study.
A different operative risk was determined for the two histological tumor types of the esophagus: while there were similar surgical complications in both groups, overall morbidity and mortality rates were significantly higher in patients with squamous cell carcinoma than in the group with adenocarcinoma. In accordance with reports in the literature [20-22], this reflects, on the one hand, the different preoperative risk profile of both entities, consisting of an increased nutritional risk, higher prevalence of hepatopathy, and poorer lung function in patients with squamous cell carcinoma. Additionally, in this study there was a significantly higher incidence of transthoracic esophagectomy with a higher complication rate in patients with squamous cell carcinoma than in those with adenocarcinoma (69.4 vs. 31.3%).
Conclusion
The present analysis shows that the selection and the type of the surgical procedure are crucial factors for both the incidence of postoperative complications and the mortality rate. The transhiatal procedure is associated with a significantly lower morbidity and mortality rate and thus represents – as long term survival does not favor the transthoracic approach – the surgical technique of choice for adenocarcinoma of the esophagus. In contrast, our previous long-term experience and results obtained by this study advocate the performance of the transthoracic procedure for squamous cell carcinoma. The higher operative risk is justified with a view to a better long-term prognosis. Independent of the choice of the operative approach, a less-invasive surgical procedure and the implementation of measures designed to minimize the risk of pulmonary complications are essential to achieve a reduction in the morbidity rate of esophageal carcinoma.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
IG: study design, collection of data, statistical analysis, sequence alignment, draft of manuscript
ChE: collection of data, statistical analysis
ThJ: conceived of the study, design and coordination of the study, draft and revision of the manuscript
==== Refs
Daly JM Esophageal cancer: results of an American College of Surgeons Patient Care Evaluation Study J Am Coll Surg 2001 190 562 572 10801023 10.1016/S1072-7515(00)00238-6
Ferguson MK Martin TR Reeder LB Olak J Mortality after esophagectomy: Risk factor analysis World J Surg 1997 21 599 604 9230656 10.1007/s002689900279
Tachimori Y Kato H Diagnosis and surgery of esophageal cancer Crit Rev Oncol Hematol 1998 28 57 71 9715770
Isono K Ochiai T Okuyama K Onoda S The treatment of lymph node metastases from esophageal cancer by extensive lymphadenectomy Jpn J Surg 1990 20 151 157 2342235
Isono K Sato H Nakyama K Results of a nationwide study on the three-field lymph node dissection of esophageal cancer Oncology 1991 48 411 420 1745490
Kato H Watanabe H Tachimori Y Iizuka T Evaluation of neck lymph node dissection for thoracic esophageal carcinoma Ann Thorac Surg 1991 51 931 935 2039322
Fujita H Kakegawa T Yamana H Shimada I Toh Y Tomita Y Fujii T Yamasaki K Higaki K Noake T Mortality and morbidity rates, postoperative course, quality of life, and prognosis after extended radical lymphadenectomy for esophageal cancer. Comparison of three-field lymphadenectomy with two-field lymphadenectomy Ann Surg 1995 222 654 662 7487213
Whooley BP Law S Murthy SC Alexandrou A Wong J Analysis of reduced death and complication rates after esophageal resection Ann Surg 2001 233 338 344 11224620 10.1097/00000658-200103000-00006
Olsén MF Wennberg E Johnsson E Josefson K Lönroth H Lundell L Randomized clinical study of the prevention of pulmonary complications after thoracoabdominal resection by two different breathing techniques Br J Surg 2002 89 1228 1234 12296888 10.1046/j.1365-2168.2002.02207.x
Fan ST Lau WY Yip WC Poon GP Yeung C Lam WK Wong KK Prediction of postoperative pulmonary complications in oesophagogastric cancer surgery Br J Surg 1987 74 408 410 3594139
Smetana GW Preoperative pulmonary evaluation N Engl J Med 1999 340 937 944 10089188 10.1056/NEJM199903253401207
Bartels H Stein HJ Siewert JR Preoperative risk analysis and postoperative mortality of oesophagectomy for resectable oesophageal cancer Br J Surg 1998 85 840 844 9667720 10.1046/j.1365-2168.1998.00663.x
Chu KM Law SYK Fok M Wong J A prospective randomized comparison of transhiatal and transthoracic resection of lower-third esophageal carcinoma Am J Surg 1997 174 320 324 9324146 10.1016/S0002-9610(97)00105-0
Goldminc M Maddern G Le Prise E Meunier B Campion JP Launois B Oesophagectomy by a transhiatal approach or thoracotomy: a prospective randomized trial Br J Surg 1993 80 367 370 8472154
Hulscher JB van Sandick JW de Boer AG Wijnhoven BP Tijssen JG Fockens P Stalmeier PF ten Kate FJ van Dekken H Obertop H Tilanus HW van Lanschott JJ Extended transthoracic resection compared with limited transhiatal resection for adenocarcinoma of the esophagus N Engl J Med 2002 347 1662 1669 12444180 10.1056/NEJMoa022343
Hulscher JB Tijssen JG Obertop H van Lanschot JJ Transthoracic versus transhiatal resection for carcinoma of the esophagus: a meta-analysis Ann Thorac Surg 2001 72 306 313 11465217 10.1016/S0003-4975(00)02570-4
Chan KH Wong J Mortality after esophagectomy: an analysis of risk factors Dis Esophagus 1990 3 49 56
Law SYK Fok M Wong J Risk analysis in resection of squamous cell carcinoma of the esophagus World J Surg 1994 18 339 346 8091773 10.1007/BF00316812
Lund O Kimose HH Aagaard MT Hasenkam JM Erlandsen M Risk stratification and long-term results after surgical treatment of carcinomas of the thoracic esophagus and cardia J Thorac Cardiovasc Surg 1990 99 200 209 2299857
Bollschweiler E Schroder W Holscher AH Siewert JR Preoperative risk analysis in patients with adenocarcinoma or squamous cell carcinoma of the esophagus Br J Surg 2000 87 1106 1110 10931059 10.1046/j.1365-2168.2000.01474.x
Law SYK Fok M Cheng SWK Wong J A comparison of outcome after resection for squamous cell carcinomas and adenocarcinomas of the esophagus Surg Gynecol Obstet 1992 175 107 112 1636132
Vaughan TL Davies S Kristal A Thomas DB Obesity, alcohol, and tobacco as risk factors for cancer of the esophagus and gastric cardia: Adenocarcinoma versus squamous cell carcinoma Cancer Epidemiol Biomarkers Prev 1995 4 85 91 7742727
| 15969746 | PMC1168909 | CC BY | 2021-01-04 16:39:03 | no | World J Surg Oncol. 2005 Jun 21; 3:37 | utf-8 | World J Surg Oncol | 2,005 | 10.1186/1477-7819-3-37 | oa_comm |
==== Front
Behav Brain FunctBehavioral and brain functions : BBF1744-9081BioMed Central London 1744-9081-1-61595338410.1186/1744-9081-1-6Short PaperDopamine, uncertainty and TD learning Niv Yael [email protected] Michael O [email protected] Peter [email protected] Interdisciplinary Center for Neural Computation, Hebrew University, Jerusalem, Israel2 Gatsby Computational Neuroscience Unit, University College London, London, UK2005 4 5 2005 1 6 6 12 2 2005 4 5 2005 Copyright © 2005 Niv et al; licensee BioMed Central Ltd.2005Niv et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Substantial evidence suggests that the phasic activities of dopaminergic neurons in the primate midbrain represent a temporal difference (TD) error in predictions of future reward, with increases above and decreases below baseline consequent on positive and negative prediction errors, respectively. However, dopamine cells have very low baseline activity, which implies that the representation of these two sorts of error is asymmetric. We explore the implications of this seemingly innocuous asymmetry for the interpretation of dopaminergic firing patterns in experiments with probabilistic rewards which bring about persistent prediction errors. In particular, we show that when averaging the non-stationary prediction errors across trials, a ramping in the activity of the dopamine neurons should be apparent, whose magnitude is dependent on the learning rate. This exact phenomenon was observed in a recent experiment, though being interpreted there in antipodal terms as a within-trial encoding of uncertainty.
==== Body
Introduction
There is an impressively large body of physiological, imaging, and psychopharmacological data regarding the phasic activity of dopaminergic (DA) cells in the midbrains of monkeys, rats and humans in classical and instrumental conditioning tasks involving predictions of future rewards [1-5]. These data have been taken to suggest [6,7] that the activity of DA neurons represents temporal difference (TD) errors in the predictions of future reward [8,9]. This TD theory of dopamine provides a precise computational foundation for understanding a host of behavioural and neural data. Furthermore, it suggests that DA provides a signal that is theoretically appropriate for controlling learning of both predictions and reward-optimising actions.
Some of the most compelling evidence in favour of the TD theory comes from studies investigating the phasic activation of dopamine cells in response to arbitrary stimuli (such as fractal patterns on a monitor) that predict the proximate availability of rewards (such as drops of juice). In many variants, these have shown that with training, phasic DA signals transfer from the time of the initially unpredictable reward, to the time of the earliest cue predicting a reward. This is exactly the expected outcome for a temporal-difference based prediction error (eg. [1,2,10-13]). The basic finding [7] is that when a reward is unexpected (which is inevitable in early trials), dopamine cells respond strongly to it. When a reward is predicted, however, the cells respond to the predictor, and not to the now-expected reward.
If a predicted reward is unexpectedly omitted, then the cells are phasically inhibited at the normal time of the reward, an inhibition which reveals the precise timing of the reward prediction [10], and whose temporal metrics are currently under a forensic spotlight [14]. The shift in activity from the time of reward to the time of the predictor resembles the shift of the animal's appetitive behavioural reaction from the time of the reward (the unconditioned stimulus) to that of the conditioned stimulus in classical conditioning experiments [7,10].
In a most interesting recent study, Fiorillo et al. [15] examined the case of partial reinforcement, in which there is persistent, ineluctable, prediction error on every single trial. A straightforward interpretation of the TD prediction error hypothesis would suggest that in this case (a) dopamine activity at the time of the predictive stimuli would scale with the probability of reward, and (b) on average over trials, the dopaminergic response after the stimulus and all the way to the time of the reward, should be zero. Although the first hypothesis was confirmed in the experiments, the second was not. The between-trial averaged responses showed a clear ramping of activity during the delay between stimulus onset and reward that seemed inconsistent with the TD account. Fiorillo et al. hypothesised that this activity represents the uncertainty in reward delivery, rather than a prediction error.
In this paper, we visit the issue of persistent prediction error. We show that a crucial asymmetry in the coding of positive and negative prediction errors leads one to expect the ramping in the between-trial average dopamine signal, and also accounts well for two further features of the DA signal – apparent persistent activity at the time of the (potential) reward, and disappearance (or at least weakening) of the ramping signal, but not the signal at the time of reward, in the face of trace rather than delay conditioning. Both of these phenomena have also been observed in the related instrumental conditioning experiments of Morris et al. [16]. Finally, we interpret the ramping signal as the best evidence available at present for the nature of the learning mechanism by which the shift in dopamine activity to the time of the predictive stimuli occurs.
Uncertainty in reward occurrence: DA ramping
Fiorillo et al. [15] associated the presentation of five different visual stimuli to macaques with the delayed, probabilistic (pr = 0, 0.25, 0.5, 0.75, 1) delivery of juice rewards. They used a delay conditioning paradigm, in which the stimulus persists for a fixed interval of 2s, with reward being delivered when the stimulus disappears. After training, the monkeys' anticipatory licking behavior indicated that they were aware of the different reward probabilities associated with each stimulus.
Figure 1a shows population histograms of extracellularly-recorded DA cell activity, for each pr. TD theory predicts that the phasic activation of the DA cells at the time of the visual stimuli should correspond to the average expected reward, and so should increase with pr. Figure 1a shows exactly this – indeed, across the population, the increase is quite linear. Morris et al. [16] report a similar result in an instrumental (trace) conditioning task also involving probabilistic reinforcement.
Figure 1 Averaged prediction errors in a probabilistic reward task (a) DA response in trials with different reward probabilities. Population peri-stimulus time histograms (PSTHs) show the summed spiking activity of several DA neurons over many trials, for each pr, pooled over rewarded and unrewarded trials at intermediate probabilities. (b) TD prediction error with asymmetric scaling. In the simulated task, in each trial one of five stimuli was randomly chosen and displayed at time t = 5. The stimulus was turned off at t = 25, at which time a reward was given with a probability of pr specified by the stimulus. We used a tapped delay-line representation of the stimuli (see text), with each stimulus represented by a different set of units ('neurons'). The TD error was δ(t) = r(t) + w(t - 1)·x(t) - w(t - 1)·x(t - 1), with r(t) the reward at time t, and x(t) and w(t) the state and weight vectors for the unit. A standard online TD learning rule was used with a fixed learning rate α, w(t) = w(t - 1) + αδ(t)x(t - 1), so each weight represented an expected future reward value. Similar to Fiorillo et al., we depict the prediction error δ(t) averaged over many trials, after the task has been learned. The representational asymmetry arises as negative values of δ(t) have been scaled by d = 1/6 prior to summation of the simulated PSTH, although learning proceeds according to unscaled errors. Finally, to account for the small positive responses at the time of the stimulus for pr = 0 and at the time of the (predicted) reward for pr = 1 seen in (a), we assumed a small (8%) chance that a predictive stimulus is misidentified. (c) DA response in pr = 0.5 trials, separated into rewarded (left) and unrewarded (right) trials. (d) TD Model of (c). (a,c) Reprinted with permission from [15]©2003 AAAS. Permission from AAAS is required for all other uses.
By contrast, at the time of potential reward delivery, TD theory predicts that on average there should be no activity, as, on average, there is no prediction error at that time. Of course, in the probabilistic reinforcement design (at least for pr ≠ 0, 1) there is in fact a prediction error at the time of delivery or non-delivery of reward on every single trial. On trials in which a reward is delivered, the prediction error should be positive (as the reward obtained is larger than the average reward expected). Conversely, on trials with no reward it should be negative (see Figure 1c). Crucially, under TD, the average of these differences, weighted by their probabilities of occurring, should be zero. If it is not zero, then this prediction error should act as a plasticity signal, changing the predictions until there is no prediction error. At variance with this expectation, the data in Figure 1a which is averaged over both rewarded and unrewarded trials, show that there is in fact positive mean activity at this time. This is also evident in the data of Morris et al. [16] (see Figure 3c). The positive DA responses show no signs of disappearing even with substantial training (over the course of months).
Worse than this for the TD model, and indeed the focus of Fiorillo et al. [15], is the apparent ramping of DA activity towards the expected time of the reward. As the magnitude of the ramp is greatest for pr = 0.5, Fiorillo et al. suggested that it reports the uncertainty in reward delivery, rather than a prediction error, and speculated that this signal could explain the apparently appetitive properties of uncertainty (as seen in gambling).
Both the ramping activity and the activity at the expected time of reward pose critical challenges to the TD theory. TD learning operates by arranging for DA activity at one time in a trial to be predicted away by cues available earlier in that trial. Thus, it is not clear how any seemingly predictable activity, be it that at the time of the reward or in the ramp before, can persist without being predicted away by the onset of the visual stimulus. After all, the pr-dependent activity in response to the stimulus confirms its status as a valid predictor. Furthermore, a key aspect of TD [17], is that it couples prediction to action choice by using the value of a state as an indication of the future rewards available from that state, and therefore its attractiveness as a target for action. From this perspective, since the ramping activity is explicitly not predicted by the earlier cue, it cannot influence early actions, such as the decision to gamble. For instance, consider a competition between two actions: one eventually leading to a state with a deterministic reward and therefore no ramp, and the other leading to a state followed by a probabilistic reward with the same mean, and a ramp. Since the ramp does not affect the activity at the time of the conditioned stimulus, it cannot be used to evaluate or favour the second action (gambling) over the first, despite the extra uncertainty.
We suggest the alternative hypothesis that both these anomalous firing patterns result directly from the constraints implied by the low baseline rate of activity of DA neurons (2–4 Hz) on the coding of the signed prediction error. As noted by Fiorillo et al. [15], positive prediction errors are represented by firing rates of ~270% above baseline, while negative errors are represented by a decrease of only ~55% below baseline (see also [14,18]). This asymmetry is a straightforward consequence of the coding of a signed quantity by firing which has a low baseline, though, obviously, can only be positive. Firing rates above baseline can encode positive prediction errors by using a large dynamic range, however, below baseline firing rates can only go down to zero, imposing a restriction on coding of negative prediction errors.
Consequently, one has to be careful interpreting the sums (or averages) of peri-stimulus-time-histograms (PSTHs) of activity over different trials, as was done in Figure 1a. The asymmetrically coded positive and negative error signals at the time of the receipt or non-receipt of reward should indeed not sum up to zero, even if they represent correct TD prediction errors. When summed, the low firing representing the negative errors in the unrewarded trials will not "cancel out" the rapid firing encoding positive errors in the rewarded trials, and, overall, the average will show a positive response. In the brain, of course, as responses are not averaged over (rewarded and unrewarded) trials, but over neurons within a trial, this need not pose a problem.
This explains the persistent positive activity (on average) at the time of delivery or non-delivery of the reward. But what about the ramp prior to this time? At least in certain neural representations of the time between stimulus and reward, when trials are averaged, this same asymmetry leads TD to result exactly in a ramping of activity toward the time of the reward. The TD learning mechanism has the effect of propagating, on a trial-by-trial basis, prediction errors that arise at one time in a trial (such as at the time of the reward) towards potential predictors (such as the CS) that arise at earlier times within each trial. Under the asymmetric representation of positive and negative prediction errors that we have just discussed, averaging these propagating errors over multiple trials (as in Figure 1a) will lead to positive means for epochs within a trial before a reward. The precise shape of the resulting ramp of activity depends on the way stimuli are represented over time, as well as on the speed of learning, as will be discussed below.
Figure 2 illustrates this view of the provenance of the ramping activity. Here, a tapped delay-line representation of time since the stimulus is used. For this, each unit ('neuron') becomes active (i.e., assumes the value 1) at a certain lag after the stimulus has been presented, so that every timestep after the stimulus onset is consistently represented by the firing of one unit. Learning is based on the (dopaminergically-reported) TD error, formalized as δ(t) = r(t) + V(t) - V(t - 1), with V(t) the weighted input from the active unit at time t, and r(t) the reward obtained at time t. Updating the weights of the units according to the standard TD update rule with a fixed learning rate, allows V(t) to, on average, represent the expected future rewards (see Figure 1 caption). As each subsequent timestep is separately represented, TD prediction errors can arise at any time within the trial. Figure 2a shows these errors in six consecutive simulated trials in which pr = 0.5. In every trial, a new positive or negative error arises at the time of the reward, consequent on receipt or non-receipt of the reward, and step-by-step the errors from previous trials propagate back to the time of the stimulus, through the constant updating of the weights (eg. the error highlighted in red). When averaging (or, as in PSTHs, summing) over trials, these errors cancel each other on average, resulting in an overall flat histogram in the interval after the stimulus onset, and leading up to the time of the reward (black line in Figure 2b, summed over the 10 trials shown in thin blue). However, when summed after asymmetric scaling of the negative errors by a factor of d = 1/6 (which simulates the asymmetric coding of positive and negative prediction errors by DA neurons), a positive ramp of activity ensues, as illustrated by the black line in Figure 2c. Note that this rescaling is only a representational issue, resulting from the constraints of encoding a negative value about a low baseline firing rate, and should not affect the learning of the weights, so as not to learn wrong values (see discussion). However, as PSTHs are directly sums of neuronal spikes, this representational issue bears on the resulting histogram.
Figure 2 Backpropagation of prediction errors explains ramping activity. (a) The TD prediction error across each of six consecutive trials (top to bottom) from the simulation in Figure 1b, with pr = 0.5. Highlighted in red is the error at the time of the reward in the first of the trials, and its gradual back-propagation towards the time of the stimulus in subsequent trials. Block letters indicate the outcome of each specific trial (R = rewarded; N = not rewarded). The sequence of rewards preceding these trials is given on the top right. (b) The TD error from these six trials, and four more following them, superimposed. The red and green lines illustrate the envelope of the errors in these trials. Summing over these trials results in no above-baseline activity on average (black line), as positive and negative errors occur at random 50% of the time, and so cancel each other. (c) However, when the prediction errors are asymmetrically represented above and below the baseline firing rate (here negative errors were asymmetrically scaled by d = 1/6 to simulate the asymmetric encoding of prediction errors by DA neurons), an average ramping of activity emerges when averaging over trials, as is illustrated by the black line. All simulation parameters are the same as in Figure 1b,d.
Figures 1b,d show the ramp arising from this combination of asymmetric coding and inter-trial averaging, for comparison with the experimental data. Figure 1b shows the PSTH computed from our simulated data by averaging over the asymmetrically-represented δ(t) signal in ~50 trials for each stimulus type. Figure 1d shows the results for the pr = 0.5 case, divided into rewarded and unrewarded trials for comparison with Figure 1c. The simulated results resemble the experimental data closely in that they replicate the net positive response to the uncertain rewards, as well as the ramping effect, which is highest in the pr = 0.5 case.
It is simple to derive the average response at the time of the reward (t = N) in trial T, i.e., the average TD error δT(N), from the TD learning rule with the simplified tapped delay-line time representation and a fixed learning rate α. The value at the next to last timestep in a trial, as a function of trial number (with initial values taken to be zero), is
where r(t) is the reward at the end of trial t. The error signal at the last timestep of trial T is simply the difference between the obtained reward r(T), and the value predicting that reward VT - 1 (N - 1). This error is positive with probability pr, and negative with probability (1 - pr). Scaling the negative errors by a factor of d ∈ (0, 1], we thus get
For symmetric coding of positive and negative errors (d = 1), the average response is 0. For asymmetric coding (0 <d < 1), the average response is indeed proportional to the variance of the rewards, and thus maximal at pr = 0.5. However, δT is positive, and concomitantly, the ramps are positive, and in this particular setting, are related to uncertainty, because of, rather than instead of, the coding of δ(t).
Indeed, there is a key difference between the uncertainty and TD accounts of the ramping activity. According to the former, the ramping is a within-trial phenomena, coding uncertainty in reward; by contrast, the latter suggests that ramps arise only through averaging across multiple trials. Within a trial, when averaging over simultaneously recorded neurons rather than trials, the traces should not show a smooth ramp, but intermittent positive and negative activity corresponding to back-propagating prediction errors from the immediately previous trials (as in Figure 2a).
Trace conditioning: a test case
An important test case for our interpretation arises in a variant of Fiorillo et al.'s [15] task, as well as in the analogous instrumental task of Morris et al. [16], both involving trace conditioning. In contrast to delay conditioning (Figure 3a) in which the reward coincides with the offset of the predictive stimulus, here there is a substantial gap between the offset of the predictive stimulus and the delivery of the reward (Figure 3b). Clearly, in this case, uncertainty about the reward could only get larger, owing to noise in timing the interval between stimulus and reward [19], so under the uncertainty account, there should be comparable or even larger ramps. However, the experimental results show the ramping activity to be smaller, or even negligible (Figure 3c;d). Note, though, that the magnitude of the trial-average activity at the expected time of reward is maintained, pointing to a dissociation between the height of the ramp and the amount of positive activity at the expected time of reward.
Figure 3 Trace conditioning with probabilistic rewards. (a) An illustration of one trial of the delay conditioning task of Fiorillo et al. [15]. A trial consists of a 2-second visual stimulus, the offset of which coincides with the delivery of the juice reward, if such a reward is programmed according to the probability associated with the visual cue. In unrewarded trials the stimulus terminated without a reward. In both cases an inter-trial interval of 9 seconds on average separates trials. (b) An illustration of one trial of the trace conditioning task of Morris et al. [16]. The crucial difference is that there is now a substantial temporal delay between the offset of the stimulus and the onset of the reward (the "trace" period), and no external stimulus indicates the expected time of reward. This confers additional uncertainty as precise timing of the predicted reward must be internally resolved, especially in unrewarded trials. In this task, as in [15], one of several visual stimuli (not shown) was presented in each trial, and each stimulus was associated with a probability of reward. Here, also, the monkey was requested to perform an instrumental response (pressing the key corresponding to the side in which the stimulus was presented), the failure of which terminated the trial without a reward. Trials were separated by variable inter-trial intervals. (c,d) DA firing rate (smoothed) relative to baseline, around the expected time of the reward, in rewarded trials (c) and in unrewarded trials (d). (c,d) Reprinted from [16] ©2004 with permission from Elsevier. The traces imply an overall positive response at the expected time of the reward, but with a very small, or no ramp preceding this. Similar results were obtained in a classical conditioning task briefly described in [15], which employed a trace conditioning procedure, confirming that the trace period, and not the instrumental nature of the task depicted in (b) was the crucial difference from (a).
The TD model of DA readily explains these puzzling data. As shown in Figure 4, the shape of the ramp, though not the height of its peak, is affected by the learning rate. The size of the back-propagating prediction errors is determined, in part, by the learning rate, as these errors arise as part of the online learning of new predictions. Indeed, there is a continuous updating of predictions such that after a rewarded trial, there is a higher expectation of reward (and thus the next reward incurs a smaller prediction error), and conversely after a non-rewarded trial [18] (see Figure 2a). This updating of predictions is directly related to the learning rate – the higher the learning rate, the larger the update of predictions according to the current prediction error, and the larger the fraction of the prediction error which is propagated back. In this way, with higher learning rates, the difference in expectations after a rewarded versus an unrewarded trial will be larger, and thus the prediction errors when the next reward is or is not available will be larger – hence the larger and more gradual ramp.
Figure 4 Dependence of the ramp on learning rate. The shape of the ramp, but not the height of its peak, is dependent on the learning rate. The graph shows simulated activity for the case of pr = 0.5 near the time of the expected reward, for different learning rates, averaged over both rewarded and unrewarded trials. According to TD learning with persistent asymmetrically coded prediction errors, averaging over activity in rewarded and unrewarded trials results in a ramp up to the time of reward. The height of the peak of the ramp is determined by the ratio of rewarded and unrewarded trials, however, the breadth of the ramp is determined by the rate of back-propagation of these error signals from the time of the (expected) reward to the time of the predictive stimulus. A higher learning rate results in a larger fraction of the error propagating back, and thus a higher ramp. With lower learning rates, the ramp becomes negligible, although the positive activity (on average) at the time of reward is still maintained. Note that although the learning rate used in the simulations depicted in Figure 1b,d was 0.8, this should not be taken as the literal synaptic learning rate of the neural substrate, given our schematic representation of the stimulus. In a more realistic representation in which a population of neurons is active at every timestep, a much lower learning rate would produce similar results.
Indeed, compared to delay conditioning, trace conditioning is notoriously slow, suggesting that the learning rate is low, and thus that there should be a lower ramp, in accord with the experimental results. A direct examination of the learning rate in the data of Morris et al. [16], whose task required excessive training as it was not only a trace conditioning one but also involved an instrumental action, confirmed it indeed to be very low (Genela Morris – personal communication, 2004).
Discussion
The differential coding of positive and negative values by DA neurons is evident in all the studies of the phasic DA signal, and can be regarded as an inevitable consequence of the low baseline activity of these neurons. Indeed, the latter has directly inspired suggestions that an opponent neurotransmitter, putatively serotonin, be involved in representing and therefore learning the negative prediction errors [20], so that they also have full quarter. Here, however, we have confined ourselves to consideration of the effects of asymmetry on the trial-average analysis of the dopamine activity, and have shown that ramping DA activity, as well as an average positive response at the time of reward, result directly from the asymmetric coding of prediction errors.
Apart from a clearer view of the error signal, the most important consequence of the new interpretation is that the ramps can be seen as a signature of a TD phenomenon that has hitherto been extremely elusive. This is the progressive back-propagation of the error signal represented by DA activity, from the time of reward to the time of the predictor (Figure 2a). Most previous studies of dopaminergic activity have used pr = 1, so making this back-propagation at best a transitory phenomenon apparent only at the beginning of training (when, typically, recordings have not yet begun), and potentially hard to discern in slow-firing DA neurons. Further, as mentioned, the back-propagation depends on the way that the time between the predictive stimulus and the reward is represented – it is present for a tapped delay-line representation as in [6], but not for representations which span the entire delay, such as in [21]. Note that the shape of the ramp also depends on the use of eligibility traces and the so-called TD(λ) learning rule (simulation not shown), which provide an additional mechanism for bridging time between events during learning. Unfortunately, as the forms of the ramps in the data are rather variable (figure 1) and noisy, they can not provide strong constraints on the precise TD mechanism used by the brain.
More recent studies involving persistent prediction errors also show activity suggestive of back-propagation, notably Figure 4 of [13]. In this study, prediction errors resulted from periodic changes in the task, and DA recordings were made from the onset of training, thus back-propagation-like activity is directly apparent, although this activity was not quantified.
We expect the ramps to persist throughout training only if the learning rate does not decrease to zero as learning progresses. Pearce & Hall's [22] theory of the control of learning by uncertainty suggests exactly this persistence of learning – and there is evidence from partial reinforcement schedules that the learning rate may be higher when there is more uncertainty associated with the reward. Indeed, from a 'rational' statistical point of view, learning should persist when there is substantial uncertainty about the relationship between predictors and outcomes, as can arise from the ever-present possibility of a change in the predictive relationships. This form of persistent uncertainty, together with uncertainty due to initial ignorance regarding the task, have been used to formalize Pearce & Hall's theory of the way that uncertainty drives learning [23]. Thus, our claim that uncertainty may not be directly represented by the ramps, should certainly not be taken to mean that its representation and manipulation is not important. To the contrary, we have suggested that uncertainty influences cortical inference and learning through other neuromodulatory systems [24], and that it also may determine aspects of the selection of actions [25].
Various other features of the asymmetry should be noted. Most critical is the effect of the asymmetry on DA-dependent learning [26], if the below baseline DA activity is responsible by itself for decreasing predictions which are too high. In order to ensure that the learned predictions remain correct, we would have to assume that the asymmetric representation does not affect learning, i.e., that a mechanism such as different scaling for potentiation and depression of the synaptic strengths compensates for the asymmetric error signal. Of course, this would be rendered moot if an opponent neurotransmitter is involved in learning from negative prediction errors. This issue is complicated by the suggestion of Bayer [14] that DA firing rates are actually similar for all prediction errors below some negative threshold, perhaps due to the floor effect of the low firing rate. Such lossy encoding does not affect the qualitative picture of the effects of inter-trial averaging on the emergence of ramps, but does reinforce the need for an opponent signal for the necessarily symmetric learning.
Finally, the most direct test of our interpretation would be a comparison of intra- and inter-trial averaging of the DA signal. It would be important to do this in a temporally sophisticated manner, to avoid problems of averaging non-stationary signals. In order to overcome the noise in the neural firing, and determine whether indeed there was a gradual ramp within a trial, or, as we would predict – intermittent positive and negative prediction errors, it would be necessary to average over many neurons recorded simultaneously within one trial, and furthermore neurons associated with similar learning rates. Alternatively, single neuron traces could be regressed against the backpropagation response predicted by their preceding trials and TD learning. A comparison of the amount of variability explained by such a model, compared to that from a regression against a monotonic ramp of activity, could point to the most fitting model. A less straightforward, but more testable prediction is that the shape of the ramp should depend on the learning rate. Learning rates can be assessed from the response to the probabilistic rewards, independent of the shape of the ramp (Nakahara et al. [18] showed in such a way, that in their partial reinforcement trace conditioning task, the learning rate was 0.3), and potentially manipulated by varying the amount of training or the frequency with which task contingencies are changed and relearned. Indeed, quantifying the existence and shape of a ramp in Nakahara et al.'s recorded DA activity, could well shed light on the current proposal.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
YN, MD and PD jointly conceived and executed this study, and helped draft the manuscript. All authors read and approved the final manuscript.
Acknowledgements
We are very grateful to H. Bergman, C. Fiorillo, N. Daw, D. Joel, P. Tobler, P. Shizgal and W. Schultz for discussions and comment, in some cases despite varying interpretation of the data. We are particularly grateful to Genela Morris for analyzing her own published and unpublished data in relation to ramping. This work was funded by the EC Thematic Network (YN), the Gatsby Charitable Foundation and the EU BIBA project.
==== Refs
Ljungberg T Apicella P Schultz W Responses of monkey dopamine neurons during learning of behavioral reactions Journal Neurophysiol 1992 67 145 163
Schultz W Predictive reward signal of dopamine neurons Journal of Neurophysiology 1998 80 1 27 9658025
O'Doherty J Dayan P Friston K Critchley H Dolan R Temporal difference models and reward-related learning in the human brain. Neuron 2003 38 329 337 12718865 10.1016/S0896-6273(03)00169-7
Seymour B O'Doherty J Dayan P Koltzenburg M Jones A Dolan R Friston K Frackowiak R Temporal difference models describe higher order learning in humans Nature 2004 429 664 667 15190354 10.1038/nature02581
Montague PR Hyman SE Cohan JD Computational roles for dopamine in behavioural control Nature 2004 431 760 767 15483596 10.1038/nature03015
Montague PR Dayan P Sejnowski TJ A framework for mesencephalic dopamine systems based on predictive Hebbian learning The Journal of Neuroscience 1996 16 1936 1947 8774460
Schultz W Dayan P Montague PR A neural substrate of prediction and reward Science 1997 275 1593 1599 9054347 10.1126/science.275.5306.1593
Sutton RS Learning to predict by the method of temporal difference Machine Learning 1988 3 9 44
Sutton RS Barto AG Reinforcement learning: An introduction 1998 MIT Press
Hollerman J Schultz W Dopamine neurons report an error in the temporal prediction of reward during learning Nature Neuroscience 1998 1 304 309 10195164 10.1038/1124
Schultz W Apicella P Ljungberg T Responses of monkey dopamine neurons to reward and conditioned stimuli during succesive steps of learning a delayed response task The Journal of Neuroscience 1993 13 900 913 8441015
Tobler P Dickinson A Schultz W Coding of Predicted Reward Omission by Dopamine Neurons in a Conditioned Inhibition Paradigm Journal of Neuroscience 2003 23 10402 10410 14614099
Takikawa Y Kawagoe R Hikosaka O A possible role of midbrain dopamine neurons in short- and long-term adaptation of saccades to position-reward mapping Journal of Neurophysiology 2004 92 2520 2529 15163669 10.1152/jn.00238.2004
Bayer H A role for the substantia nigra in learning and motor control PhD thesis, New York University 2004
Fiorillo C Tobler P Schultz W Discrete Coding of Reward Probability and Uncertainty by Dopamine Neurons Science 2003 299 1898 1902 12649484 10.1126/science.1077349
Morris G Arkadir D Nevet A Vaadia E Bergman H Coincident but distinct messages of midbrain dopamine and striatal tonically active neurons Neuron 2004 43 133 143 15233923 10.1016/j.neuron.2004.06.012
Barto A Sutton R Watkins C Gabriel M, Moore J Learning and sequntial decision making Learning and Computational Neuroscience: Foundations of Adaptive Networks 1990 Cambridge, MA: MIT Press 539 602
Nakahara H Itoh H Kawagoe R Takikawa Y Hikosaka O Dopamine neurons can represent context-dependent prediction error Neuron 2004 41 269 280 14741107 10.1016/S0896-6273(03)00869-9
Gallistel CR Gibbon J Time, rate and conditioning Psychological Review 2000 107 289 344 10789198 10.1037//0033-295X.107.2.289
Daw ND Kakade S Dayan P Opponent interactions between serotonin and dopamine Neural Networks 2002 15 603 616 12371515 10.1016/S0893-6080(02)00052-7
Suri RE Schultz W A neural network model with dopamine-like reinforcement signal that learns a spatial delayed response task Neuroscience 1999 91 871 890 10391468 10.1016/S0306-4522(98)00697-6
Pearce JM Hall G A model for Pavlovian learning: Variations in the effectiveness of conditioned but not of unconditioned stimuli Psychological Review 1980 87 532 552 7443916 10.1037//0033-295X.87.6.532
Dayan P Kakade S Montague PR Learning and selective attention Nature Neuroscience 2000 3 1218 1223 11127841 10.1038/81504
Dayan P Yu A Dietterich T, Becker S, Ghahramani Z Expected and unexpected uncertainty: Ach and NE in the neocortex Advances in Neural Information Processing Sysytems 2002 14 Cambridge, MA: MIT Press 189 196
Daw N Niv Y Dayan P Bezard E Actions, Policies, Values, and the Basal Ganglia Recent Breakthroughs in Basal Ganglia Research New York, USA: Nova Science Publishers, Inc
Wickens J Kötter R Houk JC, Davis JL, Beiser DG Cellular models of reinforcememnt Models of Information Processing in the Basal Ganglia 1995 MIT Press 187 214
| 15953384 | PMC1171969 | CC BY | 2021-01-04 16:39:20 | no | Behav Brain Funct. 2005 May 4; 1:6 | utf-8 | Behav Brain Funct | 2,005 | 10.1186/1744-9081-1-6 | oa_comm |
==== Front
Aust New Zealand Health PolicyAustralia and New Zealand Health Policy1743-8462BioMed Central London 1743-8462-2-101590453610.1186/1743-8462-2-10CommentaryRe-interpreting the data on the cost and effectiveness of population screening for colorectal cancer in Australia Graves Nicholas [email protected] Loretta [email protected] Barbara [email protected] Beth [email protected] School of Public Health, Queensland University of Technology, Victoria Park Road, Kelvin Grove QLD, 4059, Australia2 Queensland Institute for Medical Research, 300 Herston Road, Herston, QLD 4006, Australia2005 18 5 2005 2 10 10 5 1 2005 18 5 2005 Copyright © 2005 Graves et al; licensee BioMed Central Ltd.2005Graves et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Three studies report estimates of the cost and effectiveness of alternate strategies for screening the average-risk Australian population for colorectal cancer. The options considered are faecal occult blood testing, double contrast barium enema, sigmoidoscopy and colonoscopy. At present, there is no consensus over which screening method is optimal by the economic criterion. Also, the existing studies report a mixture of average and incremental cost-effectiveness ratios derived from data collected between 1994 and 2002. We suggest average cost-effectiveness ratios are not useful for decision-making and illustrate how they differ from the preferred incremental cost-effectiveness ratio. We then update the cost data reported in the three studies to 2002 prices and calculate incremental cost-effectiveness ratios where not previously available. Our re-analysis of one study contradicts the conclusions drawn by the authors, who had only calculated average cost-effectiveness ratios. In particular, we find their recommendation of population screening with colonoscopy would cause, annually, between 33 and 1,322 years of life to be lost and between $M17 and $M87 to be wasted. Based on updated cost data and the incremental analysis, our findings indicate that population screening using biennial faecal occult blood testing ($39,459 per life-year gained), annual faecal occult blood testing ($30,556 per life-year gained) and colonoscopy ($26,587 per life-year gained) are cost-effective. Hence, the decision over which method of screening is optimal remains ambiguous across the three studies. We recommend policy-makers choose the study they believe produces the most accurate estimates of cost and health effect, identify their willingness to pay for health benefits and consider other issues relevant to the decision.
==== Body
Introduction
In 1996, Salkeld et al. [1] found that screening the average-risk Australian population for colorectal cancer using a faecal occult blood test (FOBT), compared to existing practice, would cost $24,660 per life-year gained (LYG). Due to uncertainty regarding the effectiveness of FOBT screening, they report a range of values, between $12,695 and $67,848 per LYG. Randomised controlled trials of population screening with FOBT conducted in the UK [2] and Denmark [3], but published after Salkeld et al.'s study, have reduced this uncertainty. The cost-effectiveness analyses based on the UK trial data [4] suggest a cost per life-year gained between £1,371–£5,685 (approximately $AU3,370–13,974) and the analysis of the Danish trial data [5] suggest a cost per life-year gained between 17,000–42,000DKK (approximately $AU3,916–9,672).
Three years before publication of Salkeld's study Bolin [6] discussed the advantages of using colonoscopy for population screening, and in 1996, he suggested colonoscopy was cost-effective [7]. In 1997, he asked whether the time had come to use colonoscopy for population screening in Australia [8]. Kermond [9] responded suggesting double contrast barium enema (DCBE) should not be overlooked arguing colonoscopy is 10 times more expensive, false negatives still occur and complication rates are higher. Bolin argued, in the same issue of the MJA, that the sensitivity of colonoscopy exceeds DCBE, the complication rate is only 0.1% and cost differentials are actually less than those suggested by Kermond [9].
Bolin also claimed that FOBT at one and three years and colonoscopy at 10 years, assuming a 10-year period during which time the cancer is detectable and curable (known as the dwell time), are cost-effective modes of CRC screening, probably referring to data subsequently published in 1999 [10]. For this research, the authors substituted Australian values for cost parameters into a US model of the cost-effectiveness of CRC screening [11] and generalised the results to the Australian population. They reported change in cost and change in life-years gained, as compared to existing practice, for competing screening strategies that encompass FOBT, colonoscopy, flexible sigmoidoscopy and DCBE [10]. By assuming that society is willing to pay up to $US40,000 (approximately $AU65,449 in 2002 prices) per LYG, Bolin proposed that annual FOBT, triennial FOBT, triennial DCBE, five-yearly DCBE, five-yearly colonoscopy and ten-yearly colonoscopy are all cost-effective and concluded that physicians have the option of offering individuals a range of screening alternatives, including colonoscopy [10]. Since publishing the research Bolin has argued, on four separate occasions that population screening with colonoscopy is cost-effective [12-15]. The last of these, in 2002 [14], provoked Macrae and Hebbard [16] to criticise Bolin's interpretation of epidemiological data.
In 2004, O'Leary et al. [17] also addressed the economic questions around population screening in Australia. They estimated the cost-effectiveness, compared to existing practice, of FOBT, flexible sigmoidoscopy and colonoscopy, and found flexible sigmoidoscopy and colonoscopy were cost-effective but FOBT was not.
There are important differences in the way that Salkeld et al. [1], Bolin et al. [10] and O'Leary et al. [17] report the Australian cost and effectiveness data. Salkeld et al. reports an incremental cost-effectiveness ratio, O'Leary et al. reports both average and incremental cost-effectiveness ratios, however they draw their conclusions from an average analysis. Bolin only calculates average cost-effectiveness ratios. The correct ratio for decision-making is an incremental cost-effectiveness ratio: McMahon [18] argues the use of average ratios is not meaningful; Drummond [19] and Gold [20] both discuss why incremental rather than average cost-effectiveness ratios are relevant for decision making; and, both Torgerson [21] and Neuhauser & Lewicki [22] provide examples of how average analyses muddy the waters. In their much-cited 1975 paper, Neuhauser & Lewicki [22] reviewed data on screening for CRC. They illustrated that repeatedly testing a stool sample up to six times, when a previous test result was negative, would capture all cases of CRC, at an average cost per case of $2451. They also did an incremental analysis, with the same data, and showed the incremental cost per case detected, from the fifth to sixth round of testing was $47 million. This illustrates that average analyses can be grossly misleading.
We have four objectives in this paper: first, to demonstrate why incremental, not average, cost-effectiveness ratios should be used for decision-making; second, to update the cost data reported by Salkeld et al. [1], Bolin et al. [10] and O'Leary et al. [17] to 2002 Australian dollar prices; third, to calculate incremental cost-effectiveness ratios from the Bolin data; and fourth, to discuss the results of our re-analysis, comparing the outcomes from the three previous studies. This will provide readers with an up-to-date and appropriate assessment of the existing cost-effectiveness data for population-based CRC screening programmes in Australia.
Defining average & incremental cost-effectiveness ratios
Average cost-effectiveness ratios for health care interventions are the amounts by which costs change from a baseline comparator (ΔC) divided by the amount by which health benefits change from a baseline comparator (ΔE). The baseline comparator is often existing practice. We illustrate this method with hypothetical data in Table 1 by presenting the change in costs and health effects that arise from four competing health care alternatives. If we remain with Existing Practice, there is no change in cost or health effect. However, if we are committed to generating health effects and we wish to be efficient, then we should choose the cheapest option that improves health outcomes. The data in Table 1 show that Intervention 4 generates the best ratio of (ΔC) and (ΔE) when compared to Existing Practice. Cost changes by $145,000 and health effects change by 150 and the cost per LYG is $967.
Table 1 An illustration of average cost-effectiveness ratios for four competing hypothetical health care interventions
Change in cost ($) Change in health effect (Life-years Gained) Average cost-effectiveness ($)
(ΔC) (ΔE) (ΔC) divided by (ΔE)
Existing Practice 0 0
Intervention 1 200,000 12 16,667
Intervention 2 75,000 15 5,000
Intervention 3 300,000 250 1,200
Intervention 4 145,000 150 967
We reject Interventions 1 and 2. The reasons lie in Figure 1 (which is a graph of the data in Table 1). Intervention 1 generates less health benefit and higher costs than Intervention 4, a situation described as 'simple dominance'. For this comparison, Intervention 4 is preferred on both costs and outcomes. Intervention 2 also generates less health effect but differs from Intervention 1 in that it's cheaper than Intervention 4; however, the cost per LYG from Intervention 2 is greater than the cost per LYG from Intervention 4. This situation is known as 'extended dominance' and is only relevant if the cost of Intervention 4 ($145,000) exceeds the total amount of money available to the decision-maker. Rather than choosing Intervention 2 over Intervention 4, it would be better (more productively efficient) to choose some blend of existing practice and Intervention 4. This implies that some proportion of the population would receive Intervention 4 and the remainder would receive existing practice. This raises questions of equity of access and so poses another set of problems for decision-makers. If the available budget exceeds $145,000, there is a further question to consider. Do we invest in the more costly but more effective Intervention 3? Some care is required when making this decision. The average cost-effectiveness ratio for Intervention 3 ($1,200 per LYG), represented by the dashed line on Figure 1, is misleading. It's calculated by comparing Intervention 3 to existing practice; yet, the relevant decision is whether we should invest in Intervention 3 given that we have established Intervention 4 as the most cost-effective option. We must consider the incremental changes in cost and health effects compared to the next best alternative, Intervention 4. The incremental cost-effectiveness ratios for Interventions 4 and 3 are marked with solid lines on Figure 1. When a more effective alternative also costs more, then the decision-maker must compare the increased cost with the increased effects [19]. The only way to achieve this is to conduct an incremental analysis, which we illustrate in Table 2. Investing in Intervention 3, as compared to 4, changes total costs by $155,000 and LYG by 100, yielding an incremental cost-effectiveness ratio of $1,550 per LYG not the $1,200 per LYG as previously estimated using average cost-effectiveness ratios and illustrated in Table 1.
Table 2 An illustration of average and incremental cost-effectiveness ratios for the two remaining hypothetical health care interventions
Intervention Cost ($) Incremental changes in cost ($) Effectiveness (LYG) Incremental changes in effectiveness (LYG) Average cost-effectiveness ratio ($) Incremental cost-effectiveness ratio ($)
(a) (b) (c) (d) (a)/(c) (b)/(d)
Existing Practice 0 0
Intervention 4 145,000 145,000 150 150 967 967
Intervention 3 300,000 155,000 250 100 1,200 1,550
Note: Interventions 1 and 2 have been rejected on the grounds of 'simple' and 'extended' dominance, see text for a discussion
Figure 1 Change in cost and change in effect from four hypothetical health care interventions.
Imagine you have decided to take a holiday in a beach resort. You face a decision between a standard apartment for $1,000 and a Penthouse apartment for $1,300. Because you have decided to take the holiday (and so one of the apartments), it is the difference in cost ($300) that you compare to the difference in benefit (penthouse vs. standard apartment). If you don't perceive the additional benefit to be worth the extra $300, then you reject the penthouse. This simple example illustrates the importance of thinking about decisions in terms of incremental changes. An average analysis with both options compared to 'no holiday' may lead to a bad decision.
Methods for re-analysis and the results
We converted Bolin's $US dollar estimates to Australian dollars with the exchange rate reported in the original article [10] and adjusted the estimates reported by Bolin, Salkeld and O'Leary to 2002 prices using a health price index [23]. As Salkeld and O'Leary reported incremental cost-effectiveness ratios, we only need to calculate incremental cost-effectiveness ratios from the Bolin data. We achieved this by inputting the reported estimates of (ΔC) and (ΔE) into decision analysis software [24]. Assuming a 5-year dwell time (the period during which cancer can be detected and cured), we include 13 screening strategies and the existing practice comparator. For a 10-year dwell time, estimates of (ΔC) and (ΔE)were reported for different, additional, frequencies of FOBT, flexible sigmoidoscopy and DCBE screening, resulting in 27 strategies and the existing practice comparator. We ranked all strategies by increasing cost, estimated incremental cost and effectiveness, and excluded all strategies for which other options prevailed on the basis of 'simple' or 'extended' dominance. Finally, we reported the strategies not excluded due to either 'simple' or 'extended' dominance and present the relevant incremental cost-effectiveness ratios.
In Table 3, we describe all strategies evaluated by the authors of the three studies.
Table 3 Descriptions of the screening strategies included in the re-analysis
Screening strategy Description of screening strategy Salkeld [1] Bolin [10] (5-year dwell time) Bolin [10] (10-year dwell time) O'Leary [17]
Existing practice Existing screening practices X X X
COL10 10-yearly colonoscopy X X X
COL5 5-yearly colonoscopy X X
COL one off screening colonoscopy at age 50 X X
DCBE one off double contrast barium enema X
DCBE10 10-yearly double contrast barium enema X
DCBE15 15-yearly double contrast barium enema X
DCBE20 20-yearly double contrast barium enema X
DCBE3 3-yearly double contrast barium enema X X
DCBE5 5-yearly double contrast barium enema X X
FOBT10 10-yearly faecal occult blood test X
FOBT15 15-yearly faecal occult blood test X
FOBT2 2-yearly faecal occult blood test X X
FOBT20 20-yearly faecal occult blood test X
FOBT5 5-yearly faecal occult blood test X
FOBT one off faecal occult blood test X
FOBT1 annual faecal occult blood test X X X X
FOBT1+DCBE3 annual faecal occult blood test and 3-yearly double contrast barium enema X X
FOBT1+DCBE5 annual faecal occult blood test and 5-yearly double contrast barium enema X X
FOBT1+FSIG3 annual faecal occult blood test and 3-yearly flexible sigmoidoscopy X X
FOBT1+FSIG5 annual faecal occult blood test and 5-yearly flexible sigmoidoscopy X X
FOBT3 3-yearly faecal occult blood test X X
FSIG flexible sigmoidoscopy once only X
FSIG10 10-yearly flexible sigmoidoscopy X X
FSIG15 15-yearly flexible sigmoidoscopy X
FSIG20 20-yearly flexible sigmoidoscopy X
FSIG3 3-yearly flexible sigmoidoscopy X X
FSIG5 5-yearly flexible sigmoidoscopy X X
In Figure 2, we illustrate the costs and effects of all strategies reported by Bolin, assuming a 5-year dwell time. The strategies to the left and above the cost-effective frontier, defined by the solid line, are excluded by either 'simple' or 'extended' dominance. The three remaining (un-dominated) strategies, that define the cost-effective frontier, are EXISTING PRACTICE, DCBE3 and FOBT1+DBCE3. In Table 4, we report all corresponding costs, health benefits and cost-effectiveness ratios, and indicate the options that are 'simply' dominated. In Table 5, we report the incremental cost-effectiveness ratios for the options that survive the tests of 'simple' or 'extended' dominance; these options define the cost-effective frontier.
Figure 2 Updated costs and effects for Bolin et al's 13 tested strategies, assuming a five-year dwell time.
Table 4 Estimates of costs in 2002 prices, health benefits and cost-effectiveness from Bolin et al. [10], assuming a five-year dwell time
Strategy Cost ($) Incremental changes in cost ($) Effectiveness (LYG) Incremental changes in effectiveness (LYG) Average cost-effectiveness ratio ($) Incremental cost-effectiveness ratio ($)
(a) (b) (c) (d) (a)/(c) (b)/(d)
EXISTING PRACTICE 0 0 (Undefined)
FOBT3 109,167,314 109,167,314 2,010 2,010 54,312 54,312
COL 195,987,062 86,819,748 1,166 -844 168,085 (Simply Dominated)
FSIG5 205,570,434 96,403,120 3,365 1,355 61,091 71,146
FOBT1 230,156,355 24,585,921 4,447 1,082 51,755 22,723
DCBE5 253,881,621 23,725,266 5,050 603 50,274 39,345
FSIG3 271,052,169 17,170,548 3,909 -1,141 69,341 (Simply Dominated)
COL10 278,701,522 24,819,901 3,718 -1,332 74,960 (Simply Dominated)
DCBE3 307,911,416 54,029,795 6,184 1,134 49,792 47,645
COL5 360,264,079 52,352,663 6,181 -3 58,286 (Simply Dominated)
FOBT1+FSIG5 364,595,167 56,683,751 5,849 -335 62,335 (Simply Dominated)
FOBT1+DCBE5 373,803,843 65,892,427 6,573 389 56,870 169,389
FOBT1+FSIG3 420,786,416 46,982,573 6,032 -541 69,759 (Simply Dominated)
FOBT1+DBCE3 424,911,339 51,107,496 7,020 447 60,529 114,334
Table 5 Incremental cost-effectiveness ratios in 2002 prices for the preferred (not dominated) strategies from Bolin et al. [10], assuming a five-year dwell time
Strategy Cost ($) Incremental changes in cost ($) Effectiveness (LYG) Incremental changes in effectiveness (LYG) Average cost-effectiveness ratio ($) Incremental cost-effectiveness ratio ($)
(a) (b) (c) (d) (a)/(c) (b)/(d)
EXISTING PRACTICE 0 0 (Undefined)
DCBE3 307,911,416 307,911,416 6,184 6,184 49,792 49,792
FOBT1+DBCE3 424,911,339 116,999,923 7,020 836 60,529 139,952
Note: Other options rejected on the grounds of 'simple' and 'extended' dominance, see text for a discussion.
In Figure 3, we illustrate the costs and effects for all strategies reported by Bolin, assuming a 10-year dwell time. In this case EXISTING PRACTICE, FOBT2, DCBE5, DCBE3, FOBT1+DCBE5 and FOBT1+DCBE3 define the cost-effective frontier. In Table 6, we report all corresponding costs, health benefits and cost-effectiveness ratios, and indicate the options that are 'simply' dominated. In Table 7, we report the incremental cost-effectiveness ratios for the options that survive the tests of 'simple' or 'extended' dominance; again, these options define the cost-effective frontier.
Table 6 Estimates of costs in 2002 prices, health benefits and cost-effectiveness from Bolin et al. [10], assuming a 10-year dwell time
Strategy Cost ($) Incremental changes in cost ($) Effectiveness (LYG) Incremental changes in effectiveness (LYG) Average cost-effectiveness ratio ($) Incremental cost-effectiveness ratio ($)
(a) (b) (c) (d) (a)/(c) (b)/(d)
EXISTING PRACTICE 0 0 (Undefined)
FOBT 24,429,089 24,429,089 352 352 69,401 69,401
FOBT20 31,633,953 7,204,864 558 206 56,692 34,975
FOBT15 37,620,230 5,986,277 681 123 55,243 48,669
FOBT10 47,472,852 9,852,622 951 270 49,919 36,491
FOBT5 75,561,379 28,088,527 1,674 723 45,138 38,850
FSIG 102,900,905 27,339,526 1,222 -452 84,207 (Simply Dominated)
FOBT3 105,521,804 29,960,425 2,605 931 40,507 32,181
FSIG20 120,362,301 14,840,497 1,892 -713 63,616 (Simply Dominated)
FSIG15 131,780,307 26,258,503 2,294 -311 57,446 (Simply Dominated)
DCBE 134,697,657 29,175,853 1,896 -709 71,043 (Simply Dominated)
FOBT2 140,117,791 34,595,987 3,551 946 39,459 36,571
FSIG10 148,850,170 8,732,379 3,127 -424 47,602 (Simply Dominated)
DCBE20 158,390,199 18,272,408 2,939 -612 53,893 (Simply Dominated)
DCBE15 173,448,383 33,330,592 3,566 15 48,639 2,222,039
COL 190,862,405 17,414,022 2,368 -1,198 80,601 (Simply Dominated)
DCBE10 194,089,298 20,640,915 4,778 1,212 40,621 17,030
FSIG5 204,328,539 10,239,241 3,583 -1,195 57,027 (Simply Dominated)
FOBT1 224,367,390 30,278,092 5,271 493 42,566 61,416
DCBE5 248,112,291 23,744,901 6,023 752 41,194 31,576
COL10 265,297,565 17,185,274 5,970 -53 44,438 (Simply Dominated)
FSIG3 270,484,399 22,372,108 3,993 -2,030 67,740 (Simply Dominated)
DCBE3 304,301,903 56,189,612 6,720 697 45,283 80,616
COL5 357,822,831 53,520,928 6,583 -137 54,356 (Simply Dominated)
FOBT1+FSIG5 361,026,560 56,724,657 6,344 -376 56,908 (Simply Dominated)
FOBT1+DCBE5 370,181,240 65,879,337 7,076 356 52,315 185,054
FOBT1+FSIG3 417,677,588 47,496,348 6,457 -619 64,686 (Simply Dominated)
FOBT1+DCBE3 422,777,702 52,596,462 7,299 223 57,923 235,859
Table 7 Incremental cost-effectiveness ratios in 2002 prices for the preferred (not dominated) strategies from Bolin et al. [10], assuming a 10-year dwell time
Strategy Cost ($) Incremental changes in cost ($) Effectiveness (LYG) Incremental changes in effectiveness (LYG) Average cost-effectiveness ratio ($) Incremental cost-effectiveness ratio ($)
(a) (b) (c) (d) (a)/(c) (b)/(d)
EXISTING PRACTICE 0 0 (Undefined)
FOBT2 140,117,791 140,117,791 3,551 3,551 39,459 39,459
DCBE5 248,112,291 107,994,500 6,023 2,472 41,194 43,687
DCBE3 304,301,903 56,189,612 6,720 697 45,283 80,616
FOBT1+DCBE5 370,181,240 65,879,337 7,076 356 52,315 185,054
FOBT1+DCBE3 422,777,702 52,596,462 7,299 223 57,923 235,859
Note: Other options rejected on the grounds of 'simple' and 'extended' dominance, see text for a discussion
Figure 3 Updated costs and effects for Bolin et al's 27 tested strategies, assuming a ten-year dwell time.
The incremental cost-effectiveness ratio derived from the Salkeld data, in 2002 prices, for FOBT, is $30,556 per LYG, and the 2002 incremental cost-effectiveness ratios from the O'Leary data are $17,356 per LYG for FSIG and $26,587 per LYG for COL.
These results define the screening options that are preferred (ie, not dominated), by the measure of cost-effectiveness, for population-based CRC screening in Australia. However, the decision over which to choose depends on additional factors that we discuss next.
Discussion
We defined average and incremental cost-effectiveness ratios and emphasise the latter are relevant for decision-making. We calculated incremental cost-effectiveness ratios, in 2002 prices, for a number of population screening strategies, for which Bolin had previously reported average cost-effectiveness ratios. For Bolin's estimates of (ΔC) and (ΔE), for a 5-year dwell time, we found only DCBE3 ($49,792 per LYG) and FOBT1+DCBE3 ($139,952 per LYG) were preferred (not dominated). For a 10-year dwell time, FOBT2 ($39,459 per LYG), DCBE5 ($43,687 per LYG), DCBE3 ($80,616 per LYG), FOBT1+DCBE5 ($185,054 per LYG) and FOBT1+DCBE3 ($235,859 per LYG) were preferred (not dominated).
Incremental cost-effectiveness ratios are useful for decision-making when a ceiling value for a LYG is specified. Bolin argued in 1996 [7] that $US40,000 per LYG was the relevant cut-off (approximately $AU65,449 in 2002 prices). We prefer a decision rule described by Garber & Phelps [25] that states a LYG is worth approximately twice the median annual per capita income. They derived this value from a model of optimal lifetime spending for medical care and explored its relationship to the cost-effectiveness criterion. They evaluated the model in terms of maximizing utility for individuals, with utility a function of income and health. Their rule implies, for Australia, a rational cut-off for one LYG is approximately $AU39,000 [26].
If we apply this rule to our interpretation of Bolin's data, we wouldn't recommend any additional population screening activities for the 5-year dwell time, and for a 10-year dwell time, we would only recommend FOBT2. Based on the O'Leary and Salkeld data we recommend COL and FOBT1, respectively. The results in Tables 4 and 6 illustrate the colonoscopy strategies, championed by Bolin, would cause between 33 and 1,322 years of life to be lost and between $M17 and $M87 to be wasted. We showed that all colonoscopy options were dominated by more cost-effective alternatives.
Despite our re-analysis, the decision over which model of CRC screening is optimal for the Australian, average-risk population remains ambiguous. While the incremental cost-effectiveness ratios from two studies support annual FOBT [1] or biennial FOBT [10], the most recent study supports colonoscopy [17]. At least we now have incremental cost-effectiveness ratios in 2002 prices. While two of the studies agree that FOBT screening is preferred, we have not investigated why the O'Leary [17] analysis leads to a different conclusion. The answer may be sought in a careful assessment of model structures, the particular perspectives adopted for each analysis and the values used for the parameters, which is beyond the scope of this commentary. In addition, we haven't attempted to model the effect of uncertainty on the conclusions. This would require access to the models, data and software used in each of the previous three studies. Policy-makers should review the three papers and make a judgement over which they believe produces the best estimates of change in cost and health benefit, identify their willingness to pay for the proposed health benefits and make their decision in the context of other logistic, social and political issues.
Competing interests
The author(s) declare that they have no competing interests.
==== Refs
Salkeld G Young G Irwig L Haas M Glasziou P Cost-effectiveness analysis of screening by faecal occult blood testing for colorectal cancer in Australia Australian-and-New-Zealand-journal-of-public-health 1996 20 138 143 8799087
Hardcastle JD Chamberlain JO Robinson MH Moss SM Amar SS Balfour TW James PD CM M Randomised controlled trial of faecal-occult-blood screening for colorectal cancer Lancet 1996 348 1472 7 8942775 10.1016/S0140-6736(96)03386-7
Kronborg O Fenger C Olsen J Jorgensen OD S O Randomised study of screening for colorectal cancer with faecal-occult-blood test Lancet 1996 348 1467 71 8942774 10.1016/S0140-6736(96)03430-7
Whynes D Neilson A Walker A Hardcastle J Faecal Occult Blood Screening for Colorectal Cancer: Is it cost effective? Health-Econ 1998 7 21 29 9541081 10.1002/(SICI)1099-1050(199802)7:1<21::AID-HEC306>3.0.CO;2-9
Gyrd-Hansen D Sogaard J K O Colorectal cancer screening: efficiency and effectiveness Health-Econ 1998 7 9 20 9541080 10.1002/(SICI)1099-1050(199802)7:1<9::AID-HEC304>3.0.CO;2-H
Bolin TD Screening for Colorectal Cancer Lancet 1993 341 1279 8098416 10.1016/0140-6736(93)91181-K
Bolin TD Cost benefit of early diagnosis of colorectal cancer Scand-J-Gastroenterol-Suppl 1996 220 142 6 8898453
Bolin TD Korman MG How can we reduce the incidence and mortality of colorectal cancer? Med-J-Aust 1997 166 175 6 9066543
Kermond AJ How can we reduce the incidence and mortality of colorectal cancer? Med-J-Aust 1997 167 227 9293271
Bolin TD Korman MG Stanton R Talley N Newstead GL Donnelly N Hall W Ho MT Lapsley H Positive cost effectiveness of early diagnosis of colorectal cancer Colorectal-Dis 1999 1 113 122 10.1046/j.1463-1318.1999.00028.x
US Congress Office of Technology Assessment, Cost-effectiveness of colorectal cancer screening in average-risk individuals. Special report. OTA Publication number BP-H-146 1995 Washington: US Government Printing Office
Bolin TD Cowen AE Korman MG Letter Med-J-Aust 1999 170 283 4 10212655
Bolin TD Screening for colorectal cancer: FOBT is being superseded Med-J-Aust 2000 173 334 11061410
Bolin TD Korman MG Cowen A Colorectal cancer prevention Med-J-Aust 2002 176 145 146 11913910
Bolin TD Lapsley HM Korman MG Screening for colorectal cancer – what is the most cost effective approach? Med-J-Aust 2001 174 298 301 11297120
Macrae FA Hebbard GS Colorectal Cancer Prevention Med-J-Aust 2002 177 527 8 12405903
O'Leary BA Olynyk JK Neville AM Platell CF Cost-Effectiveness of Colorectal Cancer Screening: Comparison of Community-Based Flexible Sigmoidoscopy with Fecal Occult Blood Testing and Colonoscopy J-Gastroenterol-Hepatol 2004 19 38 47 14675241 10.1111/j.1440-1746.2004.03177.x
McMahon PM Bosch JL Gleason S Halpern EF Lester JS Gazelle GS Cost-Effectiveness of Colorectal Cancer Screening Radiology 2001 219 44 50 11274533
Drummond MF Stoddart GL Torrance GW Methods for the Economic Evaluation of Health Care Programmes 1997 second Oxford: Oxford University Press
Gold MR Siegel JE Russell LN Weinstein MC Cost-effectiveness in Health and Medicine 1996 New York: Oxford University Press
Torgerson DJ Spencer A Marginal costs and benefits BMJ 1996 312 35 36 8555859
Neuhauser D Lewicki A What do we gain from the sixth stool guaiac? N-Engl-J-Med 1975 293 226 28 1143302
Australian Institute of Health & Welfare, Health Expenditure Australia 2001–02 2003 Canberra: Australian Institute of Health and Welfare
TreeAge Software Inc Data Pro Williamstown 2003
Garber AM Phelps CE Economic foundations of cost-effectiveness analysis Journal-of-health-economics 1997 16 1 31 10167341 10.1016/S0167-6296(96)00506-1
Australian Bureau of Statistics, Selected Social and Housing Characteristics for Australia 2001 2002 Canberra: Australian Bureau of Statistics Vol. TABLE 3, CAT NOS 2015.0.
| 15904536 | PMC1173078 | CC BY | 2021-01-04 16:38:28 | no | Aust New Zealand Health Policy. 2005 May 18; 2:10 | utf-8 | Aust New Zealand Health Policy | 2,005 | 10.1186/1743-8462-2-10 | oa_comm |
==== Front
Aust New Zealand Health PolicyAustralia and New Zealand Health Policy1743-8462BioMed Central London 1743-8462-2-121597813910.1186/1743-8462-2-12ResearchPatient-initiated switching between private and public inpatient hospitalisation in Western Australia 1980 – 2001: An analysis using linked data Moorin Rachael E [email protected] C D'Arcy J [email protected] Australian Centre for Economic Research on Health (UWA Campus), School of Population Health, The University of Western Australia, Australia2 Centre for Health Services Research, School of Population Health, The University of Western Australia, Australia2005 27 6 2005 2 12 12 14 3 2005 27 6 2005 Copyright © 2005 Moorin and Holman; licensee BioMed Central Ltd.2005Moorin and Holman; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
The aim of the study was to identify any distinct behavioural patterns in switching between public and privately insured payment classifications between successive episodes of inpatient care within Western Australia between 1980 and 2001 using a novel 'couplet' method of analysing longitudinal data.
Methods
The WA Data Linkage System was used to extract all hospital morbidity records from 1980 to 2001. For each individual, episodes of hospitalisation were paired into couplets, which were classified according to the sequential combination of public and privately insured episodes. Behavioural patterns were analysed using the mean intra-couplet interval and proportion of discordant couplets in each year.
Results
Discordant couplets were consistently associated with the longest intra-couplet intervals (ratio to the average annual mean interval being 1.35), while the shortest intra-couplet intervals were associated with public concordant couplets (0.5). Overall, privately insured patients were more likely to switch payment classification at their next admission compared with public patients (the average rate of loss across all age groups being 0.55% and 2.16% respectively). The rate of loss from the privately insured payment classification was inversely associated with time between episodes (2.49% for intervals of 0 to 13 years and 0.83% for intervals of 14 to 21 years). In all age groups, the average rate of loss from the privately insured payment classification was greater between 1981 and 1990 compared with that between 1991 and 2001 (3.45% and 3.10% per year respectively).
Conclusion
A small but statistically significant reduction in rate of switching away from PHI over the latter period of observation indicated that health care policies encouraging uptake of PHI implemented in the 1990s by the federal government had some of their intended impact on behaviour.
Data linkageHealth PolicyHealth InsuranceAustralia.
==== Body
Background
Coexistence of public and private health insurance, such as in Australia, has been the subject of intense debate among health economists and policy makers [1]. The main issue surrounding this debate has been how the mix of public and private health care financing influences the demand for private health insurance (PHI) and whether PHI takes pressure off the public system [2].
Falling PHI membership, observed since the introduction of Medicare in 1984, was thought to have increased the demand on the public system [3], prompting the federal government to implement policies aimed at encouraging possession of PHI to take the pressure off public hospitals and restore balance to the health care system [3-5]. Since 1995 three major policy reforms have been introduced in Australia [6]. Firstly, in 1995 selective contracting was introduced. The then federal Labor government passed legislation allowing private health plans to contract selectively with hospitals and doctors so as to improve competition on price and quality. Secondly, government subsidisation of PHI was introduced in 1997 by the Conservative coalition federal government as a means-tested rebate, capped at a flat amount irrespective of the cost of PHI, combined with an income tax surcharge for high income earners without PHI. The rebate part of the policy was subsequently replaced in 1999 by a non-means-tested 30% rebate for PHI available to everyone. Finally, in 2000, lifetime community rating was introduced. This policy relaxed the previous stringent community rating system by allowing the price of PHI to be varied according to the age at which a member joined [6].
The Australian Healthcare Agreement 1998–2003 committed the Commonwealth and states to review the relationship between PHI cover and the use of hospital services by private patients. The investigation of this relationship is becoming a priority as there is disagreement among commentators as to the financial efficiency of the 30% rebate [5,7-10]. To date, analyses of the effects of policies aimed at supporting PHI in Australia have primarily centred on changes in the proportion of the population covered by PHI [3,6,11,12]. However, changing the proportion of the population covered may not directly translate to increased utilisation and, therefore, reduce pressure on the public system. The relationship between PHI cover and type of hospital use is complex because the universality of Medicare in Australia means that anyone can be treated in a public hospital at no charge regardless of their insurance status.
The right of individuals to choose between public and private insurance, regardless of the status (public or privately insured) of previous hospitalisations or the possession of PHI is protected by the principles of Medicare as set out in the Health Insurance Act of 1973. Thus switches between use of the public and PHI system are initiated solely by patients based on choice rather than being mandated by government, notwithstanding that this 'choice' may be constrained in some instances by socioeconomic and locational access factors. We propose that since possession and utilisation of PHI are not equivalent, analysing the effectiveness of the recent government strategies in relieving the pressure on the public system cannot be accomplished by evaluations of changes in possession of PHI alone. Rather, changes in choice, as reflected by patient-initiated switching between the public and private insurance systems must be analysed.
The aim of this study was to identify and measure changes in the behavioural patterns of switching between public and privately insured status for hospitalisation by the population of Western Australia using our novel couplet methodology for analysing longitudinal data.
Method
Hospital morbidity data extraction and case selection
The WA Data Linkage System [13] was used to extract all hospital morbidity data system (HMDS) records from 1st January 1980 to 31st December 2001, containing encrypted patient identification and episode numbers, age, gender, date of admission, date of separation, payment classification (public, insured private, or "other"), and hospital type. The "other" payment category, which included the private uninsured (2.2% of the total episodes), workers compensation (1.8%), motor vehicle (0.7%), defence force personnel (0.3%) and Veteran Affairs (1.7%) classifications was removed from the data set, leaving only the categories of public and private insured. This was done because the study was concerned with elective shifts between PHI and public categories; not enforced payment classifications due to mandatory funding arrangements, or private episodes for which the patients paid the full cost.
Data coverage
This research has made use of records from the HMDS which is the inpatient information system for WA acute care hospitals. The data collected by the HMDS are patient identification, socio-demographic, services, administration and clinical diagnosis information. Every WA hospital defined as an acute care facility has to provide data via the Health Act or for private hospitals as part of their license and every free-standing day surgery unit must also provide data. The HMDS includes patient information for all acute A class hospitals, day surgery units, geriatric and psychiatric inpatient facilities in general hospitals and, as of July 1993, healthy newborn infants born in hospital. It does not include patients of stand-alone geriatric and psychiatric institutions, geriatric hostels or rehabilitation units; however, most metropolitan hospitals have geriatric and psychiatric units attached for which data are provided for the HMDS. Over the lifetime of this study there were no significant changes in the HMDS coverage.
Formation of episodes of care and assignment of payment classification
For each individual in the data set all eligible hospital records were grouped into episodes of care, using the separation and admission dates to define temporally contiguous periods of health care service utilisation. Thus one episode of care could have contained one or more inter hospital transfers. Each episode of care was assigned to one of the two eligible payment classifications (public or privately insured) on the basis of the initial payment classification at admission, where inter-hospital transfers were involved. Allocation of public or PHI status was based solely on payment classification and not on hospital type. This was done because the focus of this paper (consistent with the focus of public policy making in Australia) was on use of PHI rather than hospital type.
Stratification by age group
Stratification was based on age at admission of the first episode in each couplet. Each episode of care was assigned to one of four broad age categories (0–16 years, 17–39 years, 40–69 years and 70+ years) chosen to represent PHI market segmentation (children, young adults, middle age and old age) following consultation with a local private health insurer.
Formation and classification of hospital couplets
For each individual in the data set, eligible episodes of care were grouped incrementally, starting with the index (first episode of care) to form hospital couplets such that episodes 1 and 2 formed hospital couplet 1, episodes 2 and 3 formed hospital couplet 2 and so on (see figure 1). Hospital couplets were categorised depending upon the sequential combination of payment classifications of their two contributing episodes of care as follows:
Figure 1 The formation of hospital couplets.
(i) Concordant public couplets containing only public episodes of care.
(ii) Concordant private couplets containing only privately insured episodes of care.
(iii) Discordant (mixed) public to private couplets had the first episode of care as public and the second as privately insured.
(iv) Discordant (mixed) private to public couplets had the first episode of care as privately insured and the second as public.
Analysis of the mean intra-couplet interval
The intra-couplet interval was defined as the time in days between the final separation from the first episode of care and admission to the second episode of care. The mean intra-couplet interval was calculated for each couplet classification by the year of admission of the second episode of care (a term we subsequently refer to as the couplet year) and expressed as a ratio of the sum of the mean intra-couplet interval of all couplets in that year, regardless of classification. We subsequently refer to this measure as the grand mean. Thus a ratio greater than one for a particular couplet classification was indicative of an intra-couplet interval longer than the grand mean for that couplet year. The couplet year indicates the year the switch (choice) was made.
Analysis of behavioural patterns in switching of payment classification
The proportion of each type of discordant couplet relative to the total number of couplets having a first episode of care in the baseline payment classification was determined independently for all intra-couplet intervals (in whole years) in the data set.
This analysis was performed separately for each age group for the whole observation period and two predefined time periods (1981 to 1989 and 1990 to 2001) chosen to represent the two main eras of health care policy in Australia. The first related to the removal and re-introduction of free public hospital care, while the second related to changes in federal health policies aimed at supporting PHI [5,12,14,15]. Hospital couplets were partitioned into the two time periods using the year of admission of second episodes of care. The values obtained were plotted as segmented trend lines and the average rates of loss from each payment classification per year of intra-couplet interval were calculated using least squares fit.
Results
Characteristics of the hospital couplets in the HMDS data file
The HMDS data file contained data pertaining to 1,979,946 individuals of which 1,185,014 (60%) had at least one valid couplet. The 7,561,486 episodes of care recorded for these individuals formed 6,376,472 distinct hospital couplets (see table 1). Of these, approximately one half (51%) had an intra-couplet interval of one year or greater. Details of the distribution of the hospital couplets by intra-couplet interval are shown in table 2. Significant differences were observed in the characteristics of couplets having intra-couplet intervals of less than 1 year compared with those of one year or over. The largest differences were observed in relation to hospital type and couplet category.
Table 1 Characteristics of individuals, hospital episodes and hospital couplets
Characteristic Individuals Episodes Couplets (2nd Episode)
Number % of Dataset Number % of Dataset Number % of Dataset
Sex Male 522167 44.1 3156438 41.7 2634271 41.3
Female 662841 55.9 4405035 58.3 3742194 58.7
Indeterminate 4 0.0 13 0.0 7 0.0
TOTAL 1185014 100 7561486 100 6376472 100
Age Group 0–16 Years 313244 26.4 1045092 13.9 731848 11.5
17–39 Years 443602 37.4 2495039 33.1 2051437 32.3
40–69 Years 326974 27.6 2708572 35.9 2381598 37.5
70+ Years 100870 8.5 1292462 17.1 1191592 18.7
TOTAL 1184690 1001 7541165 1002 6356475 1003
Hospital Teaching 367964 31.1 2852257 37.7 2484293 39.0
Type Public Metropolitan 198456 16.7 902286 11.9 703830 11.0
Private Metropolitan 313563 26.5 1838354 24.3 1524791 23.9
Public Country 279315 23.6 1745527 23.1 1466212 23.0
Private Country 25097 2.1 208883 2.8 183786 2.9
TOTAL 1184395 1004 7547307 1005 6362912 1006
1 324 missing
2 20321 missing
3 19997 missing
4 619 missing
5 14179 missing
6 13560 missing
Missing records were caused by missing data in the relevant fields of the individual records and do not reflect deficiencies in the linkage process.
Table 2 Distribution of hospital couplets by characteristics and intra-couplet interval
Characteristic Intra-Couplet Interval (I-CI)
Less than 1 Year 1 Year or greater
Number % in Dataset % Across I-CI Number % in Dataset % Across I-CI
Sex
Male 1397957 44.6 53.1* 1236314 38.2 46.9
Female 1739643 55.4 46.5* 2002551 61.8 53.5
Indeterminate 5 0.0 71.4 2 0.0 28.6
TOTAL 3137605 100 49.2* 3238867 100 50.8
Age Group
0–16 Years 318255 10.2 43.5* 413593 12.8 56.5
17–39 Years 871234 27.9 42.5* 1180203 36.5 57.5
40–69 Years 1271495 40.7 53.4* 1110103 34.4 46.6
70+ Years 664439 21.3 55.8* 527153 16.3 44.2
TOTAL 3125423 1001 49.2* 3231052 1002 50.8
Hospital Type
Teaching 1554708 49.6 62.6* 929585 28.7 37.4
Public Metropolitan 249979 8.0 35.5* 453851 14.0 64.5
Private Metropolitan 573729 18.3 37.6* 951062 29.4 62.4
Public Country 672844 21.4 45.9* 793368 24.5 54.1
Private Country 77205 2.5 42.0* 106581 3.3 58.0
Other 9140 0.3 67.4* 4420 0.1 32.6
TOTAL 3137605 100 49.2* 3238867 100 50.8
Couplet Category
Concordant Public 2104333 67.1 56.7* 1605368 49.6 43.3
Private 887622 28.3 43.0* 1176629 36.3 57.0
Discordant Public – Private 74132 2.4 31.5* 161140 5.0 68.5
Private – Public 71518 2.3 19.4* 296730 9.1 80.6
TOTAL 3137605 100 49.2* 3238867 100 50.8
* Statistically significantly different (at the 0.05% level) to the proportion of couplets with an intra-couplet interval 1 year or greater.
1 12182 missing
2 7815 missing
The distribution of first couplet episodes in each year of observation was more uniform in couplets with less than a one year intra-couplet interval compared with couplets longer intra-couplet interval or all couplets in the data file as shown in figure 2(A). The reduction of first couplet episodes in couplets with intervals = one year was directly proportional to the number of years remaining in which a second episode (thus completing a couplet) could be observed. The lack of first episodes observed in 1980 was the result of a reduced volume of data in the original HMDS file for that year, most likely caused by an extraction error.
Figure 2 Distribution of the proportion of first and second episodes in couplets by year.
Figure 2(B) shows the distribution of second episodes in couplets over the observation period. The proportion of second episodes increased over the observation period regardless of the duration of the intra-couplet interval. This was a function of the increased number of individuals eligible to complete a couplet with a second episode as time progressed.
Mean intra-couplet interval
The ratio of the mean intra-couplet interval observed for each couplet category relative to the grand mean by age group and couplet year is shown in figure 3. Discordant couplets had the longest intra-couplet intervals, having on average a ratio relative to the annual grand mean intra couplet interval of 1.35, while concordant couplets types had the shortest intra-couplet intervals, their ratio being 0.65. The overall pattern indicated that the longer the time between the first and second episode of a couplet, the more likelihood there was of a change in payment classification, especially where the first payment classification was private. The trends also indicated that, within each age group, individuals with public concordant couplets, on average, had shorter intervals between episodes (ratio 0.5) than individuals with private concordant couplets (ratio 0.8).
Figure 3 Ratio of the mean intra-couplet interval to the grand mean for each couplet category by age group and couplet year.
The removal / re-introduction of free public hospital care (1980 – 1984) has previously been shown to have had a significant effect on use of in-patient insurance classifications [16]. In this study no significant difference was observed with regard to when the first episode of a couplet occurred (pre or post Medicare); however, the point in time of the second episode did correspond with behavioural change as can be seen in figure 3.
Differences in trend were observed across the four age groups. The 0–16 years age group trended towards a reduction in the intra-couplet interval associated with discordant private to public couplets after 1985. This was not observed during the late 1980s and early 1990s in the other three age groups. The 40–69 years age group showed a trend pattern similar to the 17–39 years age group until 2000, when the average intra-couplet interval associated with discordant private to public couplets reduced sharply. In addition there was a sharp increase in the average intra-couplet interval associated with discordant public to private couplets (also observed in the 0 to 16 years age group) observed at that time. In the oldest age group (70+ years) the average difference in intra-couplet interval between public and private concordant couplets was much smaller than observed in any of the other three age groups.
Over all age groups the trend in concordant couplets was that of a slowly reducing average intra-couplet interval, excluding the 1983 – 1984 period, where the average intra-couplet interval for private concordant couplets increased in all age groups.
Behavioural patterns in switching of payment classification
Differences were observed in the rate of loss from the public and privately insured payment classifications across age groups as shown in table 3. Across all age groups the largest losses, at all intra-couplet intervals, occurred from the privately insured payment classification. The largest differences in the rates of loss were observed in the 70+ years and the 17–39 years age groups, where an additional 2.39 and 1.78 percent of privately insured episodes, respectively, were lost for every year of intra-couplet interval. The rates of loss from the privately insured payment classification over shorter intra-couplet intervals (defined as 0 to 13 years) were greater than the rates of loss over longer intra-couplet intervals (defined as greater than 14 years) in all age groups with the largest difference being observed in the 40–69 years age group and the smallest in the 70+ years age group. The definition of short and long intra-couplet interval was based on an observed substantial change of slope (inflection) in the segmented trend lines.
Table 3 Loss from each payment classification as a function of age and intra-couplet interval
Rate of Loss (percent per intra-couplet year) Difference in Rate (percent per intra-couplet year)
Public Private Insured Public vs. Private Private Insured
Age group* All intervals* All intervals* 0 to 13 yrs 14 to 21 yrs All Intervals* 0 to 13 vs. 14 to 21 yrs
0–16 Years$ 0.63 1.77 2.37 0.40 1.14 1.97
17–39 Years 0.49 2.27 2.39 0.55 1.78 1.84
40–69 Years 0.81 1.94 2.56 0.46 1.13 2.10
70+ Years 0.25 2.64 2.67 1.91 2.39 0.76
* Averaged over all intra-couplet intervals in years.
$Maximum intra-couplet interval 16 years as age determined at second episode.
Figure 4 shows the degree of switching from private to public episodes over the two designated eras in health care policy. In all age groups the average rate of switching away from the private sector in 1991–2001 (era 2) was lower than that observed in 1981–1990 (era 1). The decrease in rate was small (average across all age groups -0.35% per intra-couplet year) but statistically significant. In addition, significance testing of the difference between each pair of proportions (era 1 versus era 2) indicated a significant difference for the majority as indicated in figure 4.
Figure 4 The proportionate discordance among hospital couplets with a private first episode by decade of the second couplet episode. # Significant difference (p < 0.01) between the percentage of discordant second episodes occurring in 1981–1990 versus 1991–2000.
We also found that as the intra-couplet interval increased, the difference between the proportions of discordant couplets having a private first episode versus a public first episode increased from 4.2% at one year to 34.3% at 18 years (data not shown). This indicated that overall, regardless of age, there was greater switching away from PHI than away from the public classification.
Discussion
As expected, due to their greater capacity to move between respective payment classifications, private patients were found to be more likely to switch payment classifications in their next admission than public patients, irrespective of the length of time between the two episodes. There are a number of possible explanations for this including putative structural and cognitive reasons for the observed behaviour. Structurally, the average patient who begins with a public classification is likely to be of lesser socioeconomic means than the average patient who begins with a private insured classification. The option of the former patient to use PHI at the next hospitalisation will be dependant upon them taking out, or at the very least maintaining (if they had private cover at the initial episode but did not use it) private cover in the meantime. The same pre-requisite does not exist for an initially privately insured patient accessing a public classification on the next occasion. Also patients with private insurance experiencing trauma or an acute disease event may, in some circumstances, be admitted in an emergency as a public patient, thus to some extent disallowing the patient from exerting their preference. Cognitive explanations include the possibility that PHI may not be as entrenched culturally as Medicare (the public system) in this population and, as a consequence, use of PHI may be more dependant upon marketed value propositions than use of Medicare. In other words, PHI may be perceived by the populace as a market good, whereas the public system (Medicare) may be perceived as a fundamental right.
We also found that the degree of switching from PHI towards the public system was inversly proportional to the length of time between episodes. Possibly, healthier individuals were more likely to switch to the public system than sicker individuals, assuming that a relatively short duration of intra-couplet interval can be taken as an indicator of increased morbidity. This phenomenon is consistent with reports that the decline in the proportion of the eligible population holding PHI since the introduction of Medicare in 1984 has been largely attributed to younger and healthier individuals dropping out [11,12]. This finding indicated the presence of a substantial cross-subsidisation between low risk and high risk individuals further exacerbating the adverse selection price 'death spiral' of PHI [11]. Improving the risk profile of PHI holders has been a major focus of recent federal government policy, with the introduction of a lifetime community rating in 2000 in an effort to encourage younger, healthier individuals to take out and remain in PHI funds. Our finding that in all age groups the overall rate of switching away from PHI was slightly higher in the period 1981 – 1990 compared with the rate in the period 1991 – 2001, suggests that these policies have had an effect on behaviour consistent with the government's intention.
An alternative, but less likely explanation for our findings, may be systematic differences in the cognitive decision making process between long intra-couplet intervals compared with between shorter intra-couplet intervals. For example, individual historical preferences may play a role in short interval switching but may not be important over longer intervals, where decisions may be made in isolation. While it is important to consider this alternative, we feel that if the changes observed in switches away from PHI were largely due to differences in cognitive decision making, one would expect to see a similar phenomenon in switching away from a public classification. Such a phenomena was not observed in our data.
In all age groups, our analysis indicated that the overall rate of switching from the private payment classification was slightly higher in the period 1981 – 1990 compared with the rate in the period 1991 – 2001, suggesting that the policies had an effect on behaviour consistent with the government's intention.
Assumptions and limitations of the approach
This study made use of the WA Data Linkage Project which is unique in Australia and is one of only a small number of population-based record linkage systems in the world. The use of administrative data has strengths and weaknesses. For example data can be inaccurate due to recording or coding errors [17] or linkage errors. For this study individual patient records were linked by probabilistic matching, using an automated computer algorithm based on the probability of two records being from different people having the same identifier and two records from the same person having different identifiers. The probabilities were then aggregated into a score and checked against a threshold to determine if a match was made. This technique typically has been found to have a true positive predictive value of 95–99% and a negative predictive value of 98–99% [18]. Extensive validation of the quality of the performance of matching has been undertaken on the WA Record Linkage Project using sampling techniques and the proportions of mismatches and missed matches found were in the order of approximately 0.11% [18].
Linked data have the advantage of supporting a large and diverse research programme at relatively low cost, once the infrastructure is in place. They have the capacity to provide a population-based view of events experienced longitudinally by individuals across all institutions [17]. Given the objectives of this study, the latter point makes the use of linked data particularly appropriate.
The approach we have taken in order to analyse the use of PHI and Medicare by the population of Western Australia is unique in at least two respects. Firstly the study was conducted at the population level, due to the use of hospital morbidity data. Therefore, the "reference population" was not merely an abstract concept as in conventional quantitative research, but an operationalised descriptor of the study sample. Secondly, our 'couplet methodology' has not been reported previously in the literature and represents a new method of analysing longitudinal data on use of health insurance. The couplet methodology has enabled patterns to be measured based the behaviour of individuals rather than average shifts in private – public mix generated from unlinked episodes of care. However, we recognise that since the analysis was based on episodes of care, patient initiated switching as part of a hospital transfer could not be analysed. This limitation may have affected our conclusions about intra-couplet intervals.
This paper is dedicated to explaining the couplet technique for the first time and applying it to address an initial set of relatively descriptive questions (ie teasing out what is happening). The next stage of investigation is a more analytic analysis which recognises that a wide range of potential explanatory variables might predict the couplet-based phenomenon of switching (the why). For example hospitalisation rates in set periods before and after a couplet, stratified by different lengths of stay and/or different DRG weights. In addition, the admission types (emergency/elective) of the members of the couplet may also be important predictors. We feel that the couplet methodology described in this paper will enable significant inroads to be made into the investigation of such explanatory variables.
Conclusion
Our study found that the population of Western Australia exhibited distinct behavioural patterns in the switching of payment classifications for inpatient hospitalisation between 1980 and 2001. Private patients were more likely to switch payment classification than public patients with shorter intervals between episodes corresponding to a greater probability of private-to-public switching. However, the average rate of switching from a privately insured classification was greater between 1981 and 1990 than between 1991 and 2001, indicating that recent health care policy reforms implemented by the federal government to promote uptake of PHI have had an impact on behaviour.
Competing interests
Professor D'Arcy Holman is an independent director of HBF Health Funds inc which is the largest provider of private health insurance in Western Australia.
Authors' contributions
The manuscript has been read and approved by all authors and the requirements for authorship have been met as outlined below. REM was responsible for the conception and design of the study; analysis and interpretation of the data; and drafting and revising the paper. CDJH was responsible for conception and design of the study; interpretation of the data; and revising the paper.
Acknowledgements
The initial construction of the Data Linkage System was funded by the Western Australian Lotteries Commission. We would like to thank the WA Department of Health for on-going support of the Data Linkage Unit.
==== Refs
Costa J Garcia J Demand for Private Health Insurance: How Important is the Quality Gap? Health Economics 2003 12 587 599 12825210 10.1002/hec.756
Cromwell D The Lore about Private Health Insurance and Pressure on Public Hospitals Australian Health Review 2002 25 72 74 12536865
Deeble J The Private Health Insurance Rebate: Report to State and Territory Health Ministers 2003 National Centre for Epidemiology and Population Health The Australian National University
McAuley IA Stress on Public Hospitals – Why Private Insurance Has Made it Worse 2004 University of Canberra: Discussion Paper: Australian Consumers' Association and the Australian Healthcare Association
Duckett SJ Jackson TJ The New health Insurance Rebate: An Inefficient Way of Assisting Public Hospitals Medical Journal of Australia 2000 172 439 442 10870538
Willcox S Promoting Private Health Insurance in Australia Health Affairs 2001 20 152 161 11585162 10.1377/hlthaff.20.3.152
Access Economics Striking a Balance: Choice, Access and Affordability in Australian Health Care APHA 2002
Harper I Preserving Choice: A Defence of Public Support for Private Health Care Funding in Australia Medibank Private 2003
Econotech Pty Ltd, Harper Associates Hagan P Easing the Pressure: The Intergenerational Report and Private Health Insurance Medibank Private 2004
Gross P The Value Proposition for Private Health Insurance and the Private Health Sector in Australia: A Framework for Public Debate about Choices 2004 St Christophe en Brionnais, Saone et Loire, France: Health Group Strategies Pty Limited & Institute of Health Economics and Technology Assessment
Butler J Policy Change and Private Health Insurance: Did the Cheapest Policy do the Trick? Australian Health Review 2002 25 33 41 12536860
Cormack M Private Health Insurance: The Problem Child Faces Adulthood Australian Health Review 2002 25 38 51 12046153
Holman CDJ Bass AJ Rouse IL Hobbs MST Western Australia: Development of a Health Services Research Linked Database Aust NZ J Public Health 1999 23 453 459
Blewett N The Politics of Health Australian Health Review 2000 23 10 19 11010563
Duckett SJ The Australian Health Care System 2004 2 Oxford: Oxford University Press
Moorin R Holman CDJ A longitudinal study of in-patient insurance classification in Western Australia using linked hospital morbidity data 2004 Perth: The University of Western Australia
Armstrong BK Kricker A Editorial: Record Linkage – A Vision Renewed Australian and New Zealand Journal of Public Health 1999 23 451 452 10575762
Holman CDJ The Analysis of Linked Health Data: Principles and Hands-On Applications 2002 Dec 2002 School of Population Health, University of Western Australia
| 15978139 | PMC1173079 | CC BY | 2021-01-04 16:38:27 | no | Aust New Zealand Health Policy. 2005 Jun 27; 2:12 | utf-8 | Aust New Zealand Health Policy | 2,005 | 10.1186/1743-8462-2-12 | oa_comm |
==== Front
BMC BiochemBMC Biochemistry1471-2091BioMed Central London 1471-2091-6-91590448610.1186/1471-2091-6-9Research ArticlePattern similarity study of functional sites in protein sequences: lysozymes and cystatins Nakai Shuryo [email protected] Eunice CY [email protected] Jinglie [email protected] Food, Nutrition and Health, The University of British Columbia, 6650 Marine Drive, Vancouver, B.C., Canada2005 18 5 2005 6 9 9 8 7 2004 18 5 2005 Copyright © 2005 Nakai et al; licensee BioMed Central Ltd.2005Nakai et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Although it is generally agreed that topography is more conserved than sequences, proteins sharing the same fold can have different functions, while there are protein families with low sequence similarity. An alternative method for profile analysis of characteristic conserved positions of the motifs within the 3D structures may be needed for functional annotation of protein sequences. Using the approach of quantitative structure-activity relationships (QSAR), we have proposed a new algorithm for postulating functional mechanisms on the basis of pattern similarity and average of property values of side-chains in segments within sequences. This approach was used to search for functional sites of proteins belonging to the lysozyme and cystatin families.
Results
Hydrophobicity and β-turn propensity of reference segments with 3–7 residues were used for the homology similarity search (HSS) for active sites. Hydrogen bonding was used as the side-chain property for searching the binding sites of lysozymes. The profiles of similarity constants and average values of these parameters as functions of their positions in the sequences could identify both active and substrate binding sites of the lysozyme of Streptomyces coelicolor, which has been reported as a new fold enzyme (Cellosyl). The same approach was successfully applied to cystatins, especially for postulating the mechanisms of amyloidosis of human cystatin C as well as human lysozyme.
Conclusion
Pattern similarity and average index values of structure-related properties of side chains in short segments of three residues or longer were, for the first time, successfully applied for predicting functional sites in sequences. This new approach may be applicable to studying functional sites in un-annotated proteins, for which complete 3D structures are not yet available.
==== Body
Background
In their recent review of protein sequence analysis in silico, Michalovich et al. [1] described the methodology for transferring functional annotation of known proteins to a novel protein. Computer-assisted technology is used to search for and assign the similarity from databases of well-maintained and previously annotated sources. Sequence-based and profile-based searches are conducted using BLAST and PSI-BLAST, respectively. Meanwhile, the Hidden Markov model is more efficient in searching for a distant family. Furthermore, structure-based annotation conducted by using a combination of PSI-BLAST and GenThreader (matching of substitution energy in evolution) may facilitate rapid functional annotation from structure [1]. However, proteins sharing the same fold can have different functions, and structure determination and analysis will not always mean that function can be derived [2]. There are examples of protein families, such as the four-helical cytokine and cytochrome super families, whose sequence similarities are either very low or not detectable [3]. Instead, their topography is more conserved than their sequences. This is rational, since protein functions are classified based on function per se, regardless of whether their sequences or 3D structures are similar or different. An example is the classification of a protein as possessing the function of lysozyme activity, as long as the protein possesses the ability of hydrolyzing peptidoglycans.
Another direct approach for peptide QSAR has been simultaneously investigated in peptide sequence analysis [4]. A critical difference between those two approaches, namely bioinformatics and QSAR, is the prerequisite of 3D structure information on the basis of evolutionary conservation in the case of former; on the other hand, the 3D information is helpful but not always indispensable in the case of latter, by substituting with simpler steric parameters to account for the functional mechanism [5]. For example, Hellberg et al. [4] used altogether 29 properties of side chains of bioactive peptides. After dimension reduction using principal components analysis (PCA) the resultant three main PC scores, i.e., z1, z2 and z3, representing hydrophobicity, molecular size and electronic parameter, respectively, were used as independent variables in regression analysis on the dependent variable of functionality [4].
Meanwhile, by using the homology similarity analysis (HSA), we have found the importance of functional segments within 15-residue sequences of lactoferricin derivatives to correlate with the minimum inhibitory concentration (MIC) [6]. Pattern similarity constant (a correlation coefficient) of the pattern of segments within a test derivative, in comparison to the reference pattern of the corresponding segment and the average of property values of the amino acid side-chains in the most potent derivative, was computed and correlated with MIC of the derivatives. In order to obtain the best (lowest) MIC, the pattern similarity should be close to 1.0 and the average property value should be close to that of the reference potent peptide (template). In the case of the above lactoferricin derivatives, higher correlation coefficients were obtained for log MIC predicted by HSA vs. measured log MIC computed as the output variables of regression ANN (artificial neural networks) than by sequence analysis based on the Hellberg approach [4]. More recently, a different approach, namely "additive QSAR" obtained by substituting with other amino acid residues at different positions in the same sequences, was reported to correlate well with peptide functions [7].
Lejon et al. [8] reported that in PCA analysis of peptide sequences, information of the positions of side chains in the sequence should be included for improving R2X value compared to the results obtained by computing without side chain position data (0.99 vs. 0.60, respectively). Our HSA approach, by segregating segments with and without α-helix propensity, was in good agreement with theirs (R2X of 0.90–0.94 compared to corresponding value of 0.60 but with a much larger number of derivatives). We have further extended this approach to infer the mechanism of emulsifying capacity of peptides with 10–32 residues as a function of hydrophobic periodicity [9]. For the study of emulsification function, a new homology similarity search (HSS) was introduced to plot similarity constants and average property values of segments (3–7 residues) by shifting the segment stepwise from N-terminus towards C-terminus of the sequences; the reference segment used was ELE, i.e., alternate cycle of charged (E), hydrophobic (L) and charged (E) residues. However, emulsification ability is a rather general function of peptides that is not dependent on specific active sites within the sequences; overall, the emulsification ability of peptides was highly correlated with hydrophobic periodicity of their entire sequences.
There are cases of "peptides" which do not have definitive functional sites but requiring specific segments, or "functions" which do require neither specific sites nor segments. The lactoferricin derivatives described in the above study [4] are an example of the former since all of the mutants were prepared as derivatives of the corresponding wild-type lactoferricin 15-residue sequence, which has distinct helical and cationic segments. In contrast, the peptide emulsions [9] are an example of the latter. Typical examples of proteins with definitive functional sites are enzymes, for which the positions of active sites are critical to elucidate the functional mechanisms. Defective protein folding leading to amyloid fibril formation has been associated with various human diseases, such as Alzheimer's and Creutzfelds-Jacob diseases. In 1993, hereditary non-neuropathic systemic amyloidosis was reported to be caused by naturally occurring variants of human lysozyme that aggregated in the liver [10]. Similarly, cystatin C mutation in an elderly man was reported to be the cause of amyloid angiopathy and intracerebral hemorrhage [11].
The recent discovery of a new-fold enzyme named Cellosyl [12] led us to select the lysozyme family in this study as an important one to use for validating the HSS approach to search for functional sites [13]. Meanwhile, loss of papain inhibitory activity in recombinant human cystatin C was reported to be due to insolubilization [14]. Assuming that this loss was induced by an amyloidosis, changes of helix-to-strand in the inhibitory sites as well as the binding sites with papain could also be used for a rational example of application of the HSS approach in this study.
The objective of this paper was to extend application of this new HSS approach to search for functional sites, such as active and substrate binding sites in lysozyme and amyloidosis of cystatin families, to verify the reliability of our new method. The intention was to validate the hypothesis that the evaluation of pattern similarity of short segments with 3–7 residues or even slightly longer in protein sequences is useful in predicting functionality, assuming that they are within allowable topographical units. Accordingly, it is not our intention to replace the 3D approach by the new peptide QSAR proposed in this study; rather, it is anticipated to be supplemental.
Results
Lysozyme families
PCS classification
Figure 1 shows a scattergram derived from principal components similarity (PCS) analysis of 25 lysozyme sequences using the hydrophobicity index of side chains and hen lysozyme as a reference. A scattergram similar to this figure was also obtained when a charge index was used (instead of the hydrophobicity index) for classification. CH-type lysozymes used herein were from a fungus and Streptomyces globisporus. The v-type lysozymes were T4 and PA2 phage lysozymes, while g-type lysozymes were from goose, black swan, cassowary, ostrich and chicken G. Sixteen lysozymes (chicken C, human, horse, dog, rat, mouse, red deer, rainbow trout, pigeon, turkey, duck, California quail, Japanese quail, common bobwhite, fruit fly Drosophila, and tobacco hornworm) belong to the c-type family. The large deviations in slope (about 2) of CH-type lysozymes as seen in Figure 1 are suggestive of explicit difference in their molecular structures from those of other lysozyme types.
Figure 1 PCS scattergram of lysozyme families (C-, G-, V-, and CH-types) when hydrophobicity was used as property index. Hen lysozyme was used as the reference with [coefficient of determination] = 1.0 and [slope] = 1.0.
Segment pattern similarity search for active sites
The HSS computer program was applied to the sequence alignment patterns shown in Figure 2 using the active sites of hen lysozyme at positions 54–57(F34ESN) and 80–83(T51DYG) as the references. The position numbers in parenthesis are the positions in un-gapped sequences of individual lysozymes, while the immediately preceding numbers outside of parenthesis are the position numbers of the multiple sequence alignment (gapped) in Figure 2. Since the peptidoglycan-lysing activity is associated with glutamic 55(E35) and aspartic 81(D52) side-chains in the hen lysozyme [13], the segments flanking these residues in the sequences were the focus of pattern similarity search using the HSS.
Figure 2 Multiple sequence alignment of five lysozymes belonging to four families.
The search patterns illustrated in Figure 3A (charge) and 3B (turn propensity) are a trial run to validate the HSS approach, applied to human lysozyme vs. hen lysozyme, employing the five residues flanking E35 (K33FESN of hen) as a search unit. The rules herein for selecting active segments are that the greater the similarity approaching to 1.0 and the nearer the average value to that of the reference, the more likely to be active sites in the test sequence. In Figure 3A, in addition to E35 and D53, three residues of E7, S80 and D120 show about the same similarity constants (upper pattern) as well as similar average charge values (shown by arrows on the lower pattern). However, none of the above latter three positions are acceptable as the active site, as N44, I59, C65, Q86, and Q126 in Figure 3B for β-turn search do not have matching peaks in Figure 2A for charge search. Therefore, only E35 and D53 are qualified as the active positions of human lysozyme. The same result was obtained when five residues flanking D52 (S50TDYG) of hen lysozyme were used as an alternative reference segment. The two regions around E35 and D53 determined for human lysozyme are in good agreement with those being reported for the active site in the literature [13]. Despite the fact that the charge is of prime importance in defining active sites of lysozymes, the turn propensity values of the segment rather than its pattern similarity appear to play an important role in the enzyme, as exemplified in a low similarity value of 0.30 for D53 compared to 0.98 for E35, whereas similar average turn values of 1.2 and 1.1, respectively, were computed (Fig. 3B). All these results may imply that the exposure of active sites to react with the substrate binding sites is essential.
Figure 3 HSS search patterns for active sites of human lysozyme. Segment 53–57 of hen lysozyme was used as the reference. A: HSS search pattern based on charge. B: HSS search pattern based on turn propensity.
The same search was conducted for goose and T4 lysozymes as well as the new fold CH-lysozyme [12], with the assumption that it is an un-annotated sequence, to confirm validation of the HSS approach (Table 1). Two positions of 79(E73) and 103(D97) were determined as the active sites of the goose lysozyme sequence. D97 may not be essential for the catalytic activity of the goose lysozyme [15]. In comparison, 11(E11) and 20(D20) were noted for T4 lysozyme, which are in good agreement with those reported in the literature [13]. As shown in Figure 4, in the case of the sequence of Cellosyl (CH-type), 14(D9), 104(D98) and 106(E100) were identified as candidates to be the active positions of catalysis, which are in good agreement with Rau et al. [12]. These results would support the reliability of the HSS approach.
Table 1 Determination of active sites in sequences of lysozymes in different families
Family Active sites Position Charge 1 Charge 2 Turn 1 Turn 2
Hen 1 55(35)E 1.0/5.0 .98/5.0 1.0/1.12
2 81(52)D .98/5.2 1.0/5.2 1.0/1.21
Hman 1 55(35)E 1.0/5.9 .98/5.0 .98/1.17
2 81(53)D .98/5.2 1.0/5.2 1.01/1.22
Goose 1 79(73)E .67/6.9 .78/6.9 .06/1.03
2 103(97)D .83/7.3 .83/7.3 .67/,92
T4 1 11(11)E .61/4.5 .55/4.5 .76/1.16
2 20(20)D .55/5.4 .55/5.4 .53/1.07
CH 1 14(9)D .98/5.2 1.0/5.2 .95/.95
2 104(98)D .74/4.5 .65/4.5 .81/.92
3 106(100)E .95/5.6 .86/5.6 .87/.97
Position: the first number is the multiple sequence alignment position shown in Figure 2. Number in bracket is that in the sequence of each lysozyme. Charge 1 and 2 and Turn 1 and 2: Sites 54–57 and 80–83 (alignment position numbers in Fig. 2) were used as references. These position numbers correspond to 34–37 and 50–54, respectively in the sequence of hen lysozyme. The first and second digits n each cell of Charge and Turn are similarity constant and average of property value.
Figure 4 HSS search patterns for active sites in Strep. coelicolor lysozyme. Segment 79–83 (STDYG) of hen lysozyme was used as the reference based on charge.
HSS search for substrate binding sites
Compared to the active sites that are explicitly negative in charge at single positions, the substrate binding sites of lysozymes are rather loosely defined, mainly due to the greater complexity of determining the 3D structure of enzyme-substrate complexes than that of enzyme alone. It is generally agreed that the substrates locate inside the cleft formed between the helix lobe and the strand lobe of most lysozyme molecules, except for Cellosyl, the bacterial muramidase from Streptomyces coelicolor, which can be attributed to structural difference in the catalytic crevice [12]. The six-residue segment at alignment positions 84–89 (I55LQINS) of hen lysozyme was employed as the reference segment [16] using the hydrogen bonding scale (Table 2). Based on the high pattern similarity constants and the average hydrogen bonding index values, eight potential sites were identified for hen and human lysozymes. The same rule as that for selecting active site was used herein for selecting of binding sites. Position 77(D48) and 188(W111) shown in "Hen 1" of Table 2 with lower similarity constant and hydrogen bonding value, respectively, may not be the potent substrate binding sites in the hen lysozyme. In the 3D structure [17], those two positions are far away from the catalytic cleft where the substrates snugly fit in. In the human lysozyme, 188(W112) is more likely to be the binding site than 102(A73), with higher pattern similarity and strength of hydrogen bonding of 0.89/0.45 than 0.80/0.32, respectively. Not only strong hydrogen bonding, but also high pattern similarity of a segment may be required to be qualified for substrate binding sites.
Table 2 Determination of substrate binding sites in amino acid sequences of lysozyme families
Potential sites
Hen 1 55(35)E 70(42)A 77(48)D 84(55)I 90(61)R 102(72)S 117(83)L 118(111)W
.81/.71 .79/.53 .34/.65 1.0/.41 .56/.58 .78/.56 .61/.42 .66/.35
Hen 2 36S 45R 49G 56L 62W 73R 90A 100S 112R
.82/.71 .86/.44 .79/.47 1.0/.39 .59/.58 .91/.47 .98/.41 .55/.46 .76/.29
Human 1 54(34)W 70(42)A 77(49)D 84(56)I 90(62)R 102(73)A 116(83)A 118(112)W
.48/.52 .42/.51 .34/.65 .91/.47 .50/.61 .80/.32 .61/.46 .89/.45
Human 2 27N 43T 50R 57F 63Y 74V 84L 101R 117Q
.56/.39 .56/.51 .61/.47 1.0/.45 .55/.61 .72/.33 .48/.47 .58/.29 .79/.45
Goose 43(73)I 99(93)L 119(113)I 143(133)S 181(143)G 201(163)G
.85/.31 .76/.34 .67/.46 .81/.55 .82/.36 .81/.58
T4 6(6)M 16(16)K 53(49)A 66(57)V 75(66)L 94(85)K 123(112)A 186(136)S 207(153)F
.74/.34 .99/.38 .78/.30 1.0/.42 .52/.54 .67/.38 .73/.45 .58/.51 .78/.36
CH 40(35)T 47(42)D 55(50)T 80(74)A 92(86)W 124(118)T 153(147)C 186(180)T
1.0/.58 .63/.52 .80/.51 .51/.44 .73/.49 .83/.59 .51/.56 .56/.54
The first/second digits are similarity constants and average hydrogen bond index values of binding site with segments of sox residues beginning with the positions shown. Bold digits show more likely binding sites than non-bold digits.
Hen 1 and Human 1: from the alignment shown in Figure 2; Hen 2 and Human 2; from the alignment of the lysozyme C family exclusively.
For the goose lysozyme, six potential binding positions were detected (Table 2); I113 and G163appear more likely to be the binding sites than other positions considering the location of the cleft in the molecule. Similarly, nine sites were found to be potential sites of T4 lysozyme, especially three positions, i.e. M6, L66 and S136 (Table 2). In the case of Cellosyl, eight positions were identified as the potential binding sites (Table 2). Probably due to the considerable 3D-structure difference of this lysozyme from those of other lysozyme families [12], the alignment positions 40–45 (T34EGTNY) instead of hen's 84–89 (I55LQINS) were used as a reference segment for obtaining more rational search results. Instead of hydrogen-bonding motivated interactions, less polar van der Waals interaction with the aromatic side chains in CH-lysozyme may be regarded as the second important stereochemical forces in the substrate binding [16].
In the literature, the most frequently cited substrate-binding sites in c-type lysozymes family have been W62 and D101 of hen lysozyme [13]. Since Figure 2 includes the distant family of CH-type, the segment similarity search was repeated within the c-type lysozymes alone to restrict the search within similar fold. The results are shown as "hen 2" and "human 2" in Table 2. Those results almost perfectly match to the substrate binding mechanism based on X-ray crystallographic analysis, e.g. D101, N103, N104, A107, V109, E35, N46, V110, E52, N59, and W63 [15]. Almost all of these side-chains are very close or adjacent to the segments listed in "Hen 1" and "Hen 2" of Table 2.
Substrate binding sites reported by site-directed mutagenesis
Among three mutants obtained by replacing W62 with Y, F or H, the W62H mutant, and especially the double mutant W62H/D101G, reduced substrate binding drastically [15]. This change can be explained by a decrease in the hydrogen bond average value from 0.58 to 0.54 and from 0.46 to 0.29 in V62H and D101G, respectively, when the index values employed in this study were used in computation. The double mutant changed substrate-binding mode while maintaining the overall protein structure almost identical to that of the wild type [18]. An extensive cluster of hydrophobic structure is involved in distinct regions of the sequence, but is all disrupted by a single point mutation of W62G located at the interface of the two major structural domains in the native lysozyme [19]. Similar effects were observed in mutants Y63L and D102E of human lysozyme [20]. The double mutants R41N/R101S and V74R/Q126R of human lysozyme were better catalysts for lysis of Micrococcus lysodeikticus [18]. The average hydrogen bond value of both R41N and R102S was shown to increase in our HSS search, but similar effects could not be observed for V74R/Q126R. An interesting finding is that these two mutations have both resulted in the side chains being identical to those of hen lysozyme. R41 and V74 are near A42 and A73, respectively. Importance of R115 in substrate binding of human lysozyme was reported [21], which is in good agreement of W112 within the same subsite F (Table 2).
Cystatins
PCS classification
The PCS scattergram of the 17 cystatins using human cystatin C (HCC) as a reference and hydrophobicity as side-chain property index is shown in Figure 5; alteration of the index to α-helix and β-strand propensities did not appreciably change the grouping results. The three groups include human cystatins C, D, S, SA, SN and hen cystatin (Group I), human cystatins E, F and M (Group II), and human cystatins A and B (Group III) which are the stefin group cystatins that are smaller in molecular size and have slightly lower papain inhibitory activity than HCC [22].
Figure 5 PCS scattergram of cystatins when hydrophobicity was used as property index. Human cystatin C (HuC) was used as the reference. Human cystatins M, E, S, SA, SN, D, F, A and B are labelled as 1, 2, 7, 8, 9, 10, 15, 16 and 17. Labels 3, 4, 6, and 11–14 are for cystatins from mouse C, rat C, bovine, hen, rainbow trout, chum salmon and carp, respectively.
Active sites
The HSS patterns using hydrophobicity to search for active sites of the four cystatins (HCC, EWC, HCA and HCB), when L9VGG of HCC has been employed as the reference, are shown in Figure 6. The active sites shown with arrows are at about the same location in all cystatins sequences used in this study. Similar results were obtained when bulkiness was used as side-chain index. In these cases, the similarity peaks are the major clue for identifying active sites. However, when similarity peaks appear in the neighbourhood, the average index values would become more reliable for identifying active sites as shown in Figure 6B; hen cystatin has two probable active positions side by side with the same similarity constants. The active sites, therefore, should be near the N-terminus with Prosite-type patterns of [L,I,M]-x(4)-G- [G,A]; the active sites are L9VGG and L7LGA in human cystatin C and hen cystatin, respectively. The similarity constants and the average hydrophobicity of the active sites are shown in Table 3. Stefin B (HCB) shows much lower similarity constant and average hydrophobicity than those of other cystatins. This result is in good agreement with ki difference reported by Abrahamson [23].
Table 3 Active and substrate binding sites of cystatins
HCC EWC HCA HCB
Active site
Segment L9VGG L7LGA I2PGG M2SGA
SimConst/Av.Hydroph* 1.00/1.35 0.87/1.80 0.97/1.00 0.55/-0.01
Binding site 1
Segment Q55IVAG Q53LVSG Q46VVAG Q46VVAG
SimConst/Av.Hydroph 1.00/0.90 0.70/0.92 0.90/0.95 0.90/0.95
Binding site 2
Segment V104PWQG I102PWLN L73PGQN L73PHEN
SimConst/Av.Hydroph 1.00/1.01 0.35/1.95 0.30/0.98 -0.16/0.42
SimConst/Av.Turn** 1.00/1.05 0.90/0.96 0.56/1.22 0.99/1.06
* Pattern similarity constant / average hydrophobicity
** Pattern similarity constant / average turn propensity
Similar to the corresponding tables for lysozymes (Tables 1 and 2), Sim/Const is 1.0 for reference HCC, and the greater the Av.Property the greater the property strength.
Figure 6 HSS search patterns for active sites of cystatins against human cystatin C based on hydrophobicity. A: HCC (reference), B: EWC (egg white cystatin), C: HCA and D: HCB.
Substrate binding sites
A HSA study similar to our previous paper [6] was conducted at the active and two binding sites of cystatins, yielding results (Table 3) which are in good agreement with Turk et al. [22]. Substrate-binding site 1 had the pattern Q-x(3)-V- [S,A]-G, while substrate-binding site 2 had the pattern [L,I,V]-P-x(3)-x(3)- [N,G]. Similarity constants of binding loop 2 of egg white cystatin (EWC) and HCA are lower than that of HCC, whereas not only similarity but also average hydrophobicity are lower in HCB. Similarity constants at the active site (against 1.0 for HCC) using hydrophobicity index were >0.8 for cystatins A, D, F and hen, ~0.5 for E and M, and 0.1–0.2 for cystatins B, S, SA and AN. Similarity constants at binding loop 2, when strand propensity was used for PCS computation, were lower for stefins A and B with values of 0.8 and 0.6, respectively, than >0.9 for other cystatins. On the other hand, similarity constants for strand at binding site 1 were not much different among different cystatins, with values >0.9 (not included in Table 3).
It is interesting to note that stefins A and B do not have the PW pair which is in the binding site 2 of HCC and EWC; instead they have PG and PH pairs, respectively (Table 3). The W → G replacement increased strand propensity, while W → H replacement did so moderately. The values shown in Table 3 were almost inversely proportional to the equilibrium inhibition constant ki except for human cystatin S that was weak in the inhibitory activity, which might have been due to the difference in phosphorylation of serine at N-terminal region [23]. Although stefins A and B are classified differently from other groups on PCS scattergram (Fig. 5), the weak binding at the binding site 2 may not have considerable effects on the ki values.
Turk et al. [22] have stated that the differences in the binding constants between cystatins and various cysteine proteases arise primarily from differences in the structure of enzyme active site clefts. The inhibition of endopeptidases, i.e. papain and cathepsins S and L, by cystatins is extremely tight and rapid, whereas the inhibition of exopeptidases, i.e. cathepsins B and H, is considerably weaker. The active site cleft of known endopeptidases is free to accommodate inhibitors, while in the case of exopeptidases, the active site cleft contains extra residues in it. In the N-terminal region of cystatins, it was observed that the affinity for target proteases decreased with both size and charge of substituting residues [22]. These observations are in good agreement with the results when bulkiness of side chains was used for the HSS computation for the binding site 1, "SimConst /Av.bulk" values were 1.00/12.3, 0.92/14.2, 0.98/11.4 and 0.91/11.34 for HCC, EWC, HCA and HCB, respectively. As expected, stefins A and B were less bulky. Furthermore, HCC and EWC include longer chains at the N-terminal sides with bulkier residues than those of stefins. These findings are in good agreement with the effect of bulkiness of G4 in the stefin A sequence, implying that the bulkier the residue at position 4, the weaker the papain inhibitory activity [24].
Amyloidosis
Lysozymes
Similarity constants and average propensities of α-helix and β-strand were computed for G54IL and G54ILQIN of hen lysozyme (G55IF and G55IFQIN in the case of human lysozyme) as shown in Table 4. The amyloidogenic mutant I55T showed increased strand propensity from 0.82 to 0.85, without a substantial change in the similarity constants. With regard to the helix structure, the similarity constant decreased from 1.00 to 0.93 while the average value increased from 1.08 to 1.14, thereby implicating a decrease in helix, since the helix index used herein is inversely related to the content of helix structure. These changes are favourable for amyloidosis. The fact that position 56 in human lysozyme is near its active position at D53 may explain its dramatic effect on the enzymatic activity, more effective than other positions in the sequence. The six-residue computation did not show as clear a difference as was found in the three-residue computation. Nine double-site mutations in addition to I55T at other positions selected at random in the sequences of the amyloidogenic mutant I55T by using the RCG program did not restore the activity of wild-type lysozyme (unpublished). These results infer that the amyloid, once formed by detrimental mutation at the active site, cannot be restored by mutation at other locations in the sequence.
Table 4 HSA computation for I55T lysozyme
Hen Human I55T (Hen)
Helix
G54IL(F)QINS
SimConst* 1.000 0.917 0.952
Average 0.960 0.993 0.985
G54IL(F)
SimConst 1.000 1.000 0.927
Average 1.082 1.082 1.141
Strand
G54IL(F)QINS
SimConst 1.000 0.978 0.997
Average 0.788 0.762 0.797
G54IL(F)
SimConst 1.000 1.000 0.998
Average 0.822 0.822 0.845
L56 for hen and F57 for human. * Similarity constant.
Cystatins
Heat treatment of HCC induced its dimer formation at an early stage of separation, resulting in a complete loss of its activity [25]. Based on a dramatic decrease in the monomer form as shown by its CD spectrum, polymerization such as amyloidosis could be a cause of the loss of papain inhibitory activity of mutated HCC [14]. Of 35 residues (positions 1–35) of the helix domain of HCC, 17 residues were mutated in the 22 single-site mutants using the RCG program [14 (Table 1)]. When 33 mutants obtained by adding one extra residue each in both side of the original 17 residues after eliminating duplication were used for PCS computation, the resultant PCS demonstrated that helix propensity and bulkiness were playing important roles in thermostability (data not shown). Employment of three residues flanking the mutated residue was important in pattern similarity computation. This conclusion is in good agreement with Hall et al. [26] who did an exhaustive study showing that mutations at positions 8–10 enhanced thermostability of cystatin. With regard to the papain inhibitory activity, the importance of hydrophobicity and bulkiness was demonstrated (the PCS scattergrams, similar to Fig. 7, are not shown here).
Figure 7 Effects of mutating the strand domain of human cystatin C (mutated 21 residues). A: Strand index, B: Helix index. The numbers show multiples of activity increases from wild-type. 1 shows no increase of inhibitory activity. 5* is the reference mutant 12W86V with the highest inhibitory activity.
Of 86 residues in the strand domain (positions 36–121) of HCC, 21 residues (positions 36–120) were mutated in the 23 double-site mutants using the RCG program [14]. Thirty-seven residues were used for the PCS computation of single-site mutations as described above. Hydrophobicity appeared to be playing an important role in thermostability, while strand propensity was important for inhibitory activity (data not shown). Strand and helix propensities in the strand domain were influential to the papain inhibitory activity of HCC (Fig. 7). The figures show 12 data points only by eliminating data from single site mutation in the helix domain, which did not show distinct trends with broader scatter in these figures. The second mutations in addition to the above single mutations were conducted at the strand domain of the enzyme [14]. Coefficient of determination of 1.0 and slope of 1 indicate perfect match with the reference sample (5*) that is mutant G12W/H86V with the lowest strand propensity along with highest helix propensity in the strand domain among 23 double mutants. It is worth noting that the PCS is a classification program comparing pattern similarity without demonstrating quantitative relationships with functions but providing the information of the extent of involvement of side chain properties in the functions of interest.
For mutant G12W/H86V that gained the greatest activity increase of 4.98 ± 0.09 times (mean ± SD at n = 3) that of recombinant wild-type [14], the strand propensity decreased from 0.78 to 0.69 (H86V) with a slight increase in the helix propensity (corresponding to decrease in the index values). The same was true for mutant D15P/H86I with 2.65 ± 0.30 times activity increase. A similar result was observed in mutant G4L/D40I with 2.11 ± 0.29 times activity increase, due to strand decrease along with almost no change in helix (D40I). However, mutant V10S/R93G with 4.50 ± 0.07 times activity increase behaved differently with increased strand and simultaneous decrease in helix. It is worth noting that the single mutation of V10S alone increased the activity 2.96 ± 0.06 times, therefore, changes in the helix domain may have a more predominant effect on the inhibitory activity than mutations in the strand domain. The activity change due to mutation helix → strand in the strand domain in the sequence may be slight in this case.
It is well known that a single-point mutation of human lysozyme, namely I56T, has been identified as the origin of hereditary systemic amyloidosis [27]. The amyloidogenic nature of the lysozyme variants arises from a decrease in the stability of the native fold relative to partially folded intermediates. Accordingly, in a low population of soluble, partially folded species, the protein can aggregate in a slow and controlled manner to form amyloid fibrils. Similarly, sporadic amyloid angiopathy and intracerebral hemorrhage was reported in an elderly man due to cystatin C mutation [11]. In the case of human cystatin C, the decrease in strand along with an increase in helix might have prevented amyloidosis, despite the fact that helix change was not always as evident as in the case of lysozyme. Some inconsistency in the amyloidosis as a cause of inhibitory activity of human cystatin C in our mutation optimization [14] may be due to lack of the data of single-site mutation in the strand domain of the cystatin sequence. Unfortunately, the objective of that study [14] was for mutation optimization and not for investigation of the mechanism of amyloidosis. It has been reported that stefin B (HCB) readily formed amyloid [28], which may imply declined importance of the role being played by the binding site 2 in amyloidosis of HCC.
Discussion
In a review on the quest to deduce protein function from sequences [29], the author stated that the searching of pattern databases would be more sensitive and selective than searching of sequence database. It was predicted that the sequence pattern databases, especially by comparing the pattern similarity, would play an increasingly important role, as the post-genome quest to assign functional information to raw sequence data gains pace [29]. Pattern similarity computation requires at least three residues in segments to represent a nonlinear curve, which is unlikely to be due to the effect of a single point mutation per se.
With regard to an apparent effect of the single residue mutations of hen lysozyme on substrate binding, the structural analysis by NMR of the position-62 mutant of hen lysozyme [18,30] found major changes in the chemical shift of back bone protons, especially in a loop region (positions 61–78), which contains W62 influencing the local folding. Similarly, Muraki et al. [20] reported that compared to the wild-type human lysozyme, the N-acetylglucosamine residue at subsite B of the L63 mutant markedly moved away from the 63rd residue, with substantial loss of hydrogen-bonding interaction. In Figure 5 of Ref 17, involvement of not only Y63 but also W64 is evident. These results are supportive of the importance of pattern similarity of ≥ 3 residues, which are affected by single-residue mutation.
The predictability of the active and binding sites solely on the basis of protein sequences [31] may be useful for investigating the underlying mechanisms of unknown functions of human genes after translation to protein sequences. Usually, two or three essential residues are directly involved in the bond making and breaking steps leading to formation of enzyme catalysis; however, the removal of an essential group often does not abolish activity, but can significantly alter the catalytic mechanism [32]. T4 lysozyme was cited by Peracchi [32] as an example of the alteration of catalytic mechanisms; the lytic activity of lysozyme changed to that of a transglucosidase.
An approach utilizing the property of side chains in a sequence for identifying functional motifs has already been utilized in the computer-assisted selection of antigenic peptide sequences [33]. The authors stated that an antibody produced in response to a simple linear peptide with 7–9 residues in a protein would most likely recognize a linear epitope. Furthermore, this epitope must be solvent-exposed to be accessible to the antibody. In a large scale data mining study, Binkowski et al. [34] described the importance of local sequence and spatial surface patterns in inferring functional relationships of proteins. The general feature of protein structure that would correspond to these criteria could be turns or loop structures, which are generally found on the molecular surface connecting to other elements of secondary structure, and the area of high hydrophobicity, especially for those containing charged residues.
Successful identification of active sites of new-fold of CH-lysozyme using the HSS approach in this study suggests that this approach could be applied to query proteins translated from unknown RNA segments of the human genes against templates with known functions, when their 3D structure information is still unavailable. It has been shown that the inhibition of the papain family by cystatin is due to a tripartite wedge-shaped structure with a good supplement to the active site clefts of the enzyme [35]. Todd [36] stated that despite highly homologous relationship as seen in Figure 8, lysozyme functions as an O-glycosyl hydrolase, while α-lactalbumin lacks this activity and instead regulates the substrate specificity of galactosyltransferase. The active site of peptidoglycan lysis is disrupted in α-lactalbumin. The ESS computation showed that although a pattern equivalent to hen's D53 exists in the form of TEYG/YDYG, there is no residue equivalent to hen's E35 around corresponding positions as in the form of HTSG/WESG. Two side-chain carboxyl radicals are required for the lysozyme activity within the crevice between the helix and strand domains of the molecule belonging to C-type family [16]. According to Alvarez-Fernandez et al. [35], the three parts of the cystatin polypeptide chain included in the enzyme-binding domain are the N-terminal segment, a central loop-forming segment with motif QXVXG and second C-terminal loop typically containing a PW pair [31,37,38].
Figure 8 An example of enzyme vs. non-enzyme. Adopted from Figure 10.3b [36]. Fig. 8A: 1IWT human α-lactalbumin, Fig. 8B: 1B9O human lysozyme C using Swiss-PdbViewer (spdbv). Blast 2 sequences [1] showed that the identities and the positives between the two proteins were 35% and 55% respectively.
For multiple sequence alignment of an uncharacterized protein or peptide, many Web alignment servers are available for use [1], such as Blast and NPSA, as was done in this study. For classification of uncharacterized sequences, the PCS scatterplots are also useful as shown in Figures 1, 5 and 7. The PCA demonstrated the classifying capacity superior to that of distance-based cluster analysis [39]. The PCS is more flexible than cluster analysis as different pattern similarity patterns can be drawn by rotating the reference segment for searching. It implies that similarity is not always [1 – dissimilarity]. This difference resulted in the possibility of selecting outliers, which is critical in deriving true classes or ranking [40]. Most of the currently available peptide QSAR, such as the method of Hellberg et al. [4], intends to be based on whole sequence data. The new HSS approach reported in this study could be just the beginning of more detailed, reliable peptide QSAR to be developed in the future. Analysis of a variety of bioactive proteins contributing to human health is a potential future application of the HSS software package as well as multifunctional PCS. Considering the multifunctional nature of human diseases, the functionality of food proteins also can be manipulated based on combinations of bioactive segments in different or even single natural protein sequences. Therefore, for an uncharacterized protein or peptide, a new plan is proposed: (1) A reference sequence is chosen from multiple sequence alignment (MSA) as discussed above; PCS scattergrams would assist this selection in addition to BLAST search. (2) Based on segments with high similarity in MSA, segments to be used for search are selected within the reference sequence. Then, (3) HSS search is conducted to identify functional segments in the uncharacterized sequence. (4) From the above PCS computation, important PC scores are screened (PCA is a subroutine subprogram of PCS). (5) Regression neural networks are conducted using selected PC scores as input variables as exemplified in our lactoferricin derivative study [6]. (6) RCG would be useful for confirming the HSS data and also to find the best segment or sequence as exemplified in our HCC mutation [14].
One of the original purposes of our new approach in unsupervised data mining was to verify the hypothesis that there might be adaptability of different human cystatins to better inhibit different human cathepsins [41]. This hypothesis has not been fully pursued in the past, probably because of costly separation of pure cystatins and cathepsins. An advantage of our approach is to derive potential hypothesis for enzyme/substrate interactions exclusively from their sequence data. Although the verification of those hypotheses may need to await future 3D-structure study, it is important that most of the useful QSAR data could become available, which would promote the functional mechanism study based on 3D structure. However, we admit that more examples of application should be performed in the future to more thoroughly verify and establish this method for predicting functions based on sequences. This work is underway in our laboratory.
Conclusion
Although the importance of pattern similarities of motifs with 20–30 residues as a whole has been reported for peptide QSAR in the past, the importance of a search for segments with three or more residues as functional sites of protein sequences has not been investigated. Lysozymes and cystatins were used as examples of proteins to demonstrate the capacity of segment pattern similarity analysis to predict functions, such as active and binding sites, amyloidosis and thermostability as a tool for quantitative functional sequence analysis.
Methods
Amino acid sequences of proteins
Multiple sequence alignments of lysozymes were conducted using the Network Protein Sequence Analysis of Pôle Bio-Informatique Lyonnais [42] based on Clustal W. Similarly, multiple sequence alignments were obtained for human cystatins A (HCA), B (HCB) and C (HCC) and hen egg white cystatin (EWC) as well as for papain as host proteases of cysteine protease inhibitors, i.e. cystatins. For PCS analysis, a total of 17 cystatins were used: human A, B, C, D, E, F, M, S, SA, SN, hen (EWC), bovine, ratC, mouseC, Chum salmon, Rainbow trout and carp.
Principal components similarity analysis of protein sequences
The method described in the previous papers [9,39] was followed. Principal components analysis (PCA) was modified to principal components similarity (PCS) by incorporating linear regression of PC scores to be able to account for more than three PC scores on a 2D scatter plot. The PCS was then modified to apply to peptide sequences.
Homology similarity search
Homology similarity search (HSS) was conducted as reported previously [9]. The similarity constant used in this study is eventually a correlation coefficient [43]. A preliminary study was carried out by changing the size of segment (normally 3–7) flanking the potential functional position to determine the most appropriate size of segment in differentiating the functional site from other segments within the sequence of lysozymes and cystains. The property indices used for amino acid side chains were hydrophobicity, charge, propensities of α-helix, β-strand and β-turn, hydrogen bonding, and bulkiness as reported previously [14,44]. Segments with pattern similarity close to 1.0 and average values similar to that of the reference segment were sought within each gapped sequence.
All software used in this study along with the instructions on how to use the computer programs are available in the form of ftp files on the Web [45] to download to PC computers.
List of abbreviations
EWC Egg white cystatin or hen cystatin.
HCC Human cystatin C.
HCA Human cystatin A or stefin A.
HCB Human cystatin B or stefin B.
HSA Homology similarity analysis: the PCS software was modified to compute pattern similarity constants and average side-chain property index values of segments in sequences [6].
HSS Homology similarity search: A step-wise search program initiated from N-terminus of query sequences by shifting the search unit (reference segment) towards C-terminus based on similar segments in terms of pattern similarity constant and average property values compared to those of template sequences [9].
MIC Minimum inhibitory concentration.
PCA Principal components analysis.
PCS Principal components similarity: PCA modified for multi-functional variables using linear regression of deviation of PC scores on the reference PC scores. Scatter plot is drawn as slope vs. coefficient of determination (r2) [44].
RCG Random-centroid optimization of site directed mutagenesis.
QSAR Quantitative structure-activity relationships.
Authors' contributions
EL participated in laboratory investigation to verify the hypothesis set in this study, while JD was taking care of the computer programming. SN was responsible mainly for the creation and application of software used in this study. All authors read and approved the final manuscript.
Acknowledgements
This work was financially supported by a Multidisciplinary Network Grant entitled "Structure-function of food biopolymers" (Dr. Rickey Y. Yada of University of Guelph as the principal investigator) from the Natural Sciences and Engineering Research Council of Canada. The authors acknowledge the collaboration of all co-authors listed in our past publications as shown in the following references. Especially, the drawing of 3D structures to compare lysozyme and α-lactalbumin by Dr. Yasumi Horimoto is highly appreciated.
==== Refs
Michalovich D Overington J Fagam R Protein sequence analysis in silico : application of structure-based bioinformatics to genomic initiatives Cur Opinion Pharmacol 2002 2 574 580 10.1016/S1471-4892(02)00202-3
Norin M Sundsröm M Structural proteomics: developments in structure-to-function predictions Trends Biotechnol 2002 20 79 84 11814598 10.1016/S0167-7799(01)01884-4
Hill EE Morea VM Chothia C Sequence conservation in families whose members have little or no sequence similarity: the four-helical cytokines and cytochromes J Mol Biol 2002 322 205 233 12215425 10.1016/S0022-2836(02)00653-8
Hellberg S Sjöström M Skagerberg B Wold S Peptide quantitative structure-activity relationships, a multivariate approach J Med Chem 1987 30 1126 1135 3599020 10.1021/jm00390a003
Giliani A Benigni R Zbilut JP Webber CL JrSirabella P Colosimo A Nonlinear signal analysis methods in the elucidation of protein sequence-structure relationships Chem Rev 2002 102 1471 1491 11996541 10.1021/cr0101499
Nakai S Chan JCK Li-Chan EC Dou J Ogawa M Homology similarity analysis of sequences of lactoferricin and its derivatives J Agric Food Chem 2003 51 1215 1223 12590458 10.1021/jf0206062
Doytchinova IA Walshe VA Jones NA Closter SE Borrow P Flower DR Coupling in silico and in vitro analysis of peptide-MHC binding: A bioinformatics approach enabling prediction of superbinding peptides and anchorless epitopes J Immunol 2004 172 7495 7502 15187128
Lejon T Ström MB Svendsen JS Is information about peptide sequence necessary in multivariate analysis? Chemom Intell Lab Syst 2001 57 93 95 10.1016/S0169-7439(01)00126-5
Nakai S Alizadeh-Pasdar N Dou J Buttimor R Rousseau D Paulson A Pattern similarity analysis of amino acid sequences for peptide emulsification J Agric Food Chem 2004 52 927 934 14969552 10.1021/jf034744i
Pepys MB Hawkins PN Booth DR Virgushin DM Tennent GA Soutar AK Totty N Nuguyen O Blake CCF Feest TG Zalin AM Hsuan JJ Human lysozyme gene mutations cause hereditary systemic amyloidosis Nature 1993 362 553 557 8464497 10.1038/362553a0
Graffagnino C Herbstreith MH Schmechel DE Levy E Roses AD Alberts MJ Cystatin C mutation in an elderly man with sporadic amyloid angiopathy and intracerebral hemorrhage Stroke 1995 26 2190 2193 7482672
Rau A Hogg R Marquardt R Hulgenfeld R A new lysozyme fold: crystal structure of the muramidase from Streptomyces coelicolor at 1.65 Å J Biol Chem 2001 276 31994 31999 11427528 10.1074/jbc.M102591200
Frastrez J Höltje J-V Jollés P Phage lysozyme, Bacterial lysozymes Lysozymes: Model Enzymes in Biochemistry and Biology 1996 Berlin: Birkhäuser Verlag 35 74
Ogawa M Nakamura S Scaman CH Jing H Kitts DD Dou J Nakai S Enhancement of proteinase inhibitory activity of recombinant human cystatin C using random-centroid optimization Biochim Biophys Acta 2002 1599 115 124 12479412
Strynadka NCJ James MNG Jollès P Lysozyme: a model enzyme in protein crystallography Lysozyme: Model Enzymes in Biochemistry and Biology 1996 Berlin: Birkhäuzer Velag 185 221
Imoto T Jollés P Engineering of lysozyme Lysozymes: Model Enzymes in Biochemistry and Biology 1996 Berlin: Birkhäuser Verlag 163 181
Song HW Inaka K Maenaka K Matsushima M Structure-change of active site cleft and different saccharide binding modes in human lysozyme co- crystallized with hexa-N-acetyl-chitohexaose at pH 4.0 J Mol Biol 1994 244 522 540 7990138 10.1006/jmbi.1994.1750
Maenaka K Matsushima M Kawai G Kidera A Watanabe K Kuroki R Kumagai I Structural and functional effect of Trp-62 → Gly and Asp-101 → Gly substitutions on substrate-binding modes of mutant hen egg-white lysozyme Biochem J 1998 333 71 76 9639564
Klein-Seetharaman J Oikawa M Grimshaw SB Wirmer J Duchardt E Ueda T Imoto T Smith LJ Dobson CM Schwalbe H Long-range interactions within a nonnative protein Science 2002 295 1719 1722 11872841 10.1126/science.1067680
Muraki M Harada K Sugita N Sato K Protein-carbohydrate interaction in human lysozyme probed by combining site-directed mutagenesis and affinity labelling Biochemistry 2000 39 292 299 10630988 10.1021/bi991402q
Muraki M Morikawa M Jigami Y Tanaka H Engineering of human lysozyme as a polyelectolyte by the alteration of molecular surface charge Protein Eng 1988 2 49 54 3075758
Turk B Turk V Turk D Structural and functional aspects of papain-like cysteine proteinases and their protein inhibitors J Biol Chem 1997 378 141 150
Abrahamson M Cystatins Methods Enzym 1994 244 685 700
Shibuya K Kaji H Ohyama Y Tate S Kainosho M Inagaki R Samejima T Significance of the highly conserved Gly-4 residue in human cystatin A J Biochem 1995 118 635 642 8690729
Ekiel I Abramhamson M Folding-related dimerization of human cystatin C J Biol Chem 1996 271 1314 1321 8576118 10.1074/jbc.271.3.1314
Hall A Håkannsson K Mason RW Crubb A Abrahamson M Structural basis for the biological specificity of cystatin C J Biol Chem 1995 270 5115 5121 7890620 10.1074/jbc.270.10.5115
Canet D Sunde M Last AM Miranker A Spencer A Robinson CV Dobson M Mechanistic studies of the folding of human lysozyme and the origin of amyloidogenic behavior in its disease-related variants Biochemistry 1999 38 6419 6427 10350460 10.1021/bi983037t
Žeronik E Pompe-Novak M Škarabot M Ravnikar M Muševič I Turk V Human stefin B readily forms amyloid fibrils in vitro Biochim Biophys Acta 2002 1594 1 5 11825603
Attwood TK The quest to deduce protein function from sequence: the role of pattern databases Int J Biochem Cell Biol 2000 32 139 155 10687950 10.1016/S1357-2725(99)00106-5
Kumagai I Maenaka K Sunada F Takeda S Miura K Effect of subsite alterations on substrate-binding mode in the active site of hen egg-white lysozyme Eur J Biochem 1993 212 151 156 8444153 10.1111/j.1432-1033.1993.tb17645.x
Karplus K Barrett C Cline M Diekhans M Grate L Hughey R Predicting protein structure using only sequence information Proteins 1999 121 125 10526360 10.1002/(SICI)1097-0134(1999)37:3+<121::AID-PROT16>3.0.CO;2-Q
Peracchi A Enzyme catalysis: removing chemically 'essential' residues by site-directed mutagenesis Trends Biochem Sci 2001 26 497 503 11504626 10.1016/S0968-0004(01)01911-9
Grant GA Ausubel EM Synthetic peptides for production of antibodies that recognize intact proteins Current Protocols in Molecular Biology 2002 2 New York: Wiley Interscience 11.16.1 11.16.9
Binkowski TA Adamian L Liang J Inferring functional relationships of proteins from local sequence and special surface patterns J Mol Biol 2003 332 505 526 12948498 10.1016/S0022-2836(03)00882-9
Alvarez-Fernandez M Barrett AJ Gerhartz B Dando PM Ni J Abrahamson M Inhibition of mammalian legumain by some cystatins is due to a novel second reactive site J Biol Chem 1999 274 19195 19203 10383426 10.1074/jbc.274.27.19195
Todd AE Oreng C, Jones D, Thornton J From protein structure to function Bioinformatics: Genes, Proteins and Computers 2003 Oxford: BIOS Scientific Publisher 151 174
Stubbs MT Laber B Bode W Huber R Jerala R Lenarcid B Turk V The refined 2.4Å X-ray crystal structure of recombinant human stefin B in complex with the cysteine protease papain: a novel type of proteinase inhibitor interaction EMBO J 1990 9 1939 1947 2347312
Abrahamson M Titonja A Brown MA Crubb A Machleidt W Barrett AJ Identification of the probable inhibitory reactive site of the cysteine proteinase inhibitors human cystatin C and chicken cystatin J Biol Chem 1987 262 9688 9694 3496337
Nakai S Amantea G Nakai H Ogawa M Kanagawa S Definition of outliers using unsupervised principal component similarity analysis for sensory evaluation of foods Int J Food Prop 2002 5 289 306 10.1081/JFP-120005786
Nakai S Dou J Richards JF New multivariate strategy for panel evaluation using principal component similarity Int J Food Prop 2000 3 149 164
Bromme D Kaleta J Thiol-dependent cathepsins: pathophysiological implications and recent advances in inhibitor design Current Pharm Design 2002 8 1639 1658 10.2174/1381612023394179
Network Protein Sequence Analysis of Pôle Bio-Informatique Lyonnais
Krzanowski WJ Principles of Multivariate Analysis 1988 Oxford: Oxford Science Publications 26
Nakai S Ogawa M Nakamura S Dou J Funane K A computer-aided strategy for structure-function study of food proteins using unsupervised data mining Int J Food Prop 2003 6 25 47 10.1081/JFP-120016622
Nakai S Computer software used in this study 2003
| 15904486 | PMC1173080 | CC BY | 2021-01-04 16:36:49 | no | BMC Biochem. 2005 May 18; 6:9 | utf-8 | BMC Biochem | 2,005 | 10.1186/1471-2091-6-9 | oa_comm |
==== Front
BMC BioinformaticsBMC Bioinformatics1471-2105BioMed Central London 1471-2105-6-1211590448910.1186/1471-2105-6-121Research ArticleA multistep bioinformatic approach detects putative regulatory elements in gene promoters Bortoluzzi Stefania [email protected] Alessandro [email protected] Andrea [email protected] Cinzia [email protected] Gian Antonio [email protected] Department of Biology, University of Padova – Via Bassi 58/B, 35131, Padova, Italy2 Department of Information Engineering, University of Padova – Via Gradenigo 6/B, 35131, Padova, Italy2005 18 5 2005 6 121 121 12 11 2004 18 5 2005 Copyright © 2005 Bortoluzzi et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Searching for approximate patterns in large promoter sequences frequently produces an exceedingly high numbers of results. Our aim was to exploit biological knowledge for definition of a sheltered search space and of appropriate search parameters, in order to develop a method for identification of a tractable number of sequence motifs.
Results
Novel software (COOP) was developed for extraction of sequence motifs, based on clustering of exact or approximate patterns according to the frequency of their overlapping occurrences. Genomic sequences of 1 Kb upstream of 91 genes differentially expressed and/or encoding proteins with relevant function in adult human retina were analyzed. Methodology and results were tested by analysing 1,000 groups of putatively unrelated sequences, randomly selected among 17,156 human gene promoters. When applied to a sample of human promoters, the method identified 279 putative motifs frequently occurring in retina promoters sequences. Most of them are localized in the proximal portion of promoters, less variable in central region than in lateral regions and similar to known regulatory sequences. COOP software and reference manual are freely available upon request to the Authors.
Conclusion
The approach described in this paper seems effective for identifying a tractable number of sequence motifs with putative regulatory role.
==== Body
Background
Discovery of regulatory elements in human gene promoters is one of current bioinformatics challenges. Although transcriptional control mechanisms have been investigated in various organisms for at least three decades, it is still almost impossible to predict tissue-specific or developmental-stage-specific expression of a given gene by simply analyzing its promoter sequence [1].
The 5' segment immediately adjacent to the TSS includes the core promoter and the proximal promoter, which usually extends about 200–300 nucleotides. This region is involved in the modulation of transcription. The distal part of a promoter is variable with respect to composition and length, which may encompass from 100 nucleotides to over 2 kb. There is no clear-cut defined 5'-boundary for promoters [2].
Regulatory elements binding the same transcription factor can be found in different promoters as short DNA sequences, differing among them to some extent; they are, in general, from 5 to 25 nucleotides long [3,4], often separated by un-conserved sequences. Control regions are modular in nature and expression of a given gene depends on specific combination of its regulatory elements and sometimes from their order and orientation [5].
Searching by computational methods for promoters and for regulatory elements in DNA sequences spanning several Kb, produces a large number of false-positive results. A possible solution to this problem is to identify a "sheltered environment" in which specificity of pattern discovery might be enhanced. Unknown binding sites for transcription factors might be detected by searching for common elements in upstream regulatory regions of genes with common biological function and/or expression. In fact, genes with similar expression are frequently co-regulated and genes with related function are often similarly expressed [6].
In this study, we attempted to detect putative regulatory elements in promoters of genes expressed in an adult human tissue (retina), by a multi-step approach involving computational analysis of large-scale expression data, selection of a subset of putatively co-expressed genes, retrieval of the upstream portion of their complete genomic sequence and application of pattern discovery on promoter regions.
Results
Analysis of known regulatory sequence elements binding transcription factors
Before applying COOP software on a selected group of promoters, we attempted to exploit information on known regulatory sequences available in TRANSFAC [10], to establish some "rules" which could facilitate the discovery of novel regulatory elements. In particular, TRANSFAC matrix data were analysed in order to describe number, percent and localization of fixed and variable positions in consensus sequences.
We first considered 385 matrices including information on mammalian regulatory elements. Average length of consensus sequences was 13.0 and mode 12; motifs of even length were more represented (even lengths two times more represented than odd lengths among consensus sequences of length ranging from 8 to 17). Less than 5% of the motifs showed only invariant positions (average and mode of length of completely invariant motifs were 10.3 and 9, respectively). About 33% of motifs showed more than 75% fixed positions (average length 11.5, mode 10), whereas about 73% showed more than 50% fixed positions (average length 12.3, mode 8). In general, the shortest the motif, the less variable appeared its consensus sequence.
By separately considering three regions of consensus sequences (left, center and right), we observed that lateral positions are variable in 37% of sequences, whereas central positions are variable only in 20% of them.
Most regulatory elements included in TRANSFAC seem to be symmetrical, being equally variable in their left and right sides.
We obtained very similar conclusions from the analysis of the group of 610 eukaryotic matrices. Results of this analysis suggested that pattern discovery on mammalian promoter sequences might focus on patterns 10, 12 or 14 nucleotides long, showing from 0% to 25% variable positions, and possibly, less variable in the central region.
COOP : Clustering Overlapping Occurrences of approximate Patterns
Since sequence signals with biological significance are frequently subtle, stringency of pattern discovery analyses in biological sequences cannot be set too high. This implies that results are often too numerous. A novel tool for Clustering Overlapping Occurrences of approximate Patterns (COOP) was implemented in Python (Figure 1). This software allows identification of tractable numbers of possibly interesting motifs, starting from large numbers of exact or approximate patterns.
Selection of genes and retrieval of putative promoter regions
Among 1,814 genes expressed in retina, statistical analysis of differential expression, by Audic and Claverie test [11], picked out 80 genes significantly more expressed in retina than in all other tissues. We selected as well a group of 59 known genes whose mutation is known to cause retinal diseases, recorded in OMIM and/or in RetNet databases, and/or encoding proteins for which a specific function in retina has been described. In total, 129 were selected. For each of these genes, the Reference Sequence or the longest sequence of the mRNA with complete CDS was compared by BLAT [12] to human genome sequence, for annotation of the intron/exon structure and for prediction of the most probable TSS (Transcription Start Site). We predicted with good confidence TSS of 90 genes (45 overexpressed UniGene clusters, 28 retinal disease genes, 7 both overexpressed and retinal disease-genes and 10 genes encoding proteins with a retinal function)[13]. Sequences from 90 selected genes, each corresponding to 1 Kb upstream the predicted TSS, were retrieved for further analyses. For one gene, USH3A (LL 7401) two alternative promoters (USH3A-A and USH3A-B) controlling transcription of messenger RNA encoding retinal products were found. Therefore, 91 gene promoters pertaining to 90 different retinal genes were considered for the study.
Search for approximate patterns
Retinal datasets
We considered datasets including sequences corresponding to the 500 bp upstream the predicted TSS of the selected genes (unmasked sequences, 500U91; partially masked, 500PM91; masked, 500M91) and the group of 91 fully masked sequences corresponding to 1 Kb upstream the predicted TSS (1000M91 dataset). Fully masking of sequences in datasets 500M91 and 1000M91 produced, on average, 435 and 788 unmasked nucleotides, respectively.
In each group of sequences, approximate patterns of length ranging from 10 to 14 nucleotides, with at most two variable positions (10-2, 12-2, 14-2 patterns), were searched by SPEXS (Tables 3 and 4). For each dataset, patterns were ranked in different classes, according to the number of sequences in which they were represented (Tables 3 and 4, Figure 2).
In the 500 bp datasets the number of sequences in which most represented patterns were found as relatively low, reaching a maximum of 44 (48%) for 10-2 patterns in unmasked sequences (500U91) and only 5 (5.5%) for 14-2 patterns in masked sequences (500M91). When considering sequences of length 1,000, the number of sequences with occurrences of most represented patterns slightly increased. For instance, most represented 10-2 patterns were found in 32 sequences in 500M91 and in 40 sequences in 1000M91.
Negative control datasets
Random groups of human promoter sequences were established as negative control. One thousand groups of 91 promoter sequences randomly selected among 17,156 (1 Kb long) human gene promoters were generated (RAN1000M91i, with i ranging from 1 to 1,000). Each of these 1,000 groups included the same number of sequences of the 1000M91 set of retinal gene promoters and sequences fully masked and of the same length of retinal gene promoters. Moreover, TSS predictions were done by Promoser [14,15] according to identical criteria adopted for TSS prediction of retina genes.
Results of pattern discovery in the 91 retina gene promoters group (1000M91) and in the dataset of 1,000 groups of 91 human gene promoters randomly selected among 17,156 (RAN1000M91i) are shown in Tables 3 and 4 and in Figure 2. The number of patterns with different quorum in the retinal datasets and in the negative control groups of promoter sequences are reported. In the last two rows of Table 4 the comparison of pattern discovery results in the 1000M52 retinal gene promoters group and in the dataset of 1,000 groups of 52 sequences (RAN1000M52i) randomly selected among 17,156 human gene promoters is shown.
The number of patterns found in at least 10 and in at least 20 out of 91 retinal promoter sequences is higher than the average of number of patterns found in at least 10 and in at least 20 out of 91 randomly selected promoter sequences, calculated over 1,000 different samples. Statistical significance (P-value) of number of patterns found in each number of sequences of the retina datasets was calculated as the proportion of negative control random datasets in which the number of patterns found was higher or equal to those found in retinal promoters. When this number was below 0.05, the difference was considered statistically significant. Over 1,000 random samples, 351.3 10-2 patterns were found in average in at least 20 promoter sequences, while 719 patterns were found in at least 20 retinal promoters (P-value = 0.017). Similarly, 714 12-2 patterns were found in 7 or more retinal promoter sequences, whereas 410.2 were found in average in random samples (P-value = 0.060). Statistical significance of this observed difference resulted just above 0.05. This effect could be due to possible heterogeneity of the class of 91 gene promoters. When considering the group of 52 promoters corresponding to genes significantly more expressed in retina than in all other considered tissues (1000M52) and the corresponding negative control dataset (RAN1000M52i), the difference between retinal and random datasets is more evident. For instance, 114 12-2 patterns were found in 7 or more retinal promoter sequences, whereas 33.7 in average were found in 1,000 random samples (P-value = 0.027).
In Figure 2A, the cumulative number of patterns is plotted against the number of sequences in which they were found, among sequences of dataset 1000M52 and RAN1000M52i. In Figure 2B the comparison between the 1000M91 and the RAN1000M91i is shown. For negative control (random groups of promoters), the average value of 1,000 sets of sequences is given, with an interval of two standard deviations centred to the mean (e.g. 4,895 patterns were found in at least five sequences out of 91 in the retina dataset, whereas the average number of patterns found in at least five sequences out of 91 was 3,057 in the negative control dataset). It should be noticed that in both comparisons the number of patterns found in the retinal dataset is always considerably higher than average in the negative control dataset.
Putative novel regulatory elements in retina gene promoters identified by COOP
We considered the group of 716, 12-2 patterns detected by SPEXS in at least 7 out of 91 promoter sequences of genes expressed in human retina (dataset 1000M91). We clustered the 6,611 occurrences of 716 selected patterns by using different sets of parameters, in order to identify combinations maximizing the biological meaning of resulting motifs. Distance parameters ranging from 2 to 5 nucleotides were used, each associated with o values of 0.6 or 0.7. The number of clusters decreases when d increases and increases with o. For instance, when o is set to 0.6, the increase of d from 2 to 5 changes the total number of clusters from 211 to 183, changing the number of clusters containing only the occurrences of one SPEXS pattern ("single clusters") from 136 to 116, with maximum number of patterns per cluster increasing from 119 to 180. We kept o high, in order to cluster patterns according to their "very frequent" overlapping occurrences. The change of o from 0.6 to 0.7 changes the number of clusters obtained with d = 3 from 195 to 279, while the number of "single clusters" changes from 123 to 183. The number of clusters containing the occurrences of different SPEXS patterns is quite stable in respect to variation of o (72 and 97, respectively), whereas the number of "single clusters" increases considerably with o. In all cases, the number of extracted motifs, ranging in these experiments from 169 (d = 5, o = 0.6) to 300 (d = 2, o = 0.7), is considerably lower than the number of patterns considered.
Starting from 6,611 occurrences of 716 selected patterns found in at least 7 sequences with d set to 3 and o to 0.7 COOP produced 279 clusters with an average number of occurrences per cluster of 13.9 (median 9 and mode 7, maximum 150). Clusters are associated to 279 sequence alignments, 89 of which (31.9%) are longer than 12 nucleotides, and to position-specific scoring matrices. In average, 13.9 occurrences per motif were observed. These 279 motifs occurred in 87 sequences out of 91. The mean number of motifs per sequence is 26.7, whereas the mean number of motif occurrences per sequence is 42.6. Subgroups of these motifs could be similar or overlapping.
Motifs occurrences were ranked into four classes according to their position in promoter sequences (bp distance from the predicted TSS). The observed distribution significantly deviated from expectation under assumption of randomness (1,558 motif occurrences from -1 to -250; 1,002 in -251/-500; 626 in -501/-750 and 690 in -751/-1000; chi squared test: P = 3.03*10–121). There is a positive correlation between density of motif occurrences and proximity to TSS. In fact, over 40% of total motifs occurrences are concentrated in 250 nucleotides close to the predicted TSS and the two thirds of the total number of occurrences fall within 500 nucleotides adjacent to the first exon. Regions of promoters sequences corresponding to the 500 bp proximal to TSS were in average less masked than the upstream regions. When normalizing the number of motifs occurrences to the percentage of unmasked nucleotides in the different regions, a strong difference remains, with significant deviation from a random distribution. P value of chi squared test for the comparison among two groups (from -1 to -500 and from -501 to -1000) is 3.3*10–48.
From each sequence alignment pertaining to a cluster, a consensus sequence representing the motif was built. Different sets of parameters were used to this purpose. The choice of different stringency of parameters for building consensus sequences influences the length of obtained motifs and the fraction of variable positions included in them. Threshold i ranged from 0.1 to 0.5 and fl and fc ranged from 0.6 and 0.8 (data not shown). If fl and fcare sufficiently stringent, a low value for i could be used, in order to maximize information extracted. When a i = 0.1 is applied for construction of consensus sequences, the average length of motifs remains almost unchanged (12.4), with 89 motifs of length over 12. Part of the information about each motif is lost when a matrix is built from the alignment of pattern occurrences and when frequency data are converted into a consensus sequence. We used moderately stringent thresholds for the minimum frequency of a single nucleotide determining "fixed" positions. In particular, fl was set to 0.5, whereas fc, referring to the core regions of consensus sequences, was set to 0.7. Out of 279 motifs, only 62 "most informative" motifs were selected, which showed a completely conserved consensus or a consensus showing variable positions only in the side regions (Table 5). The average length of this group of sequence motifs was 13.0, with about 55% of them longer than 12 nucleotides. Two pairs of motifs were represented by the same consensus sequence. The resulting group of 60 motif consensus sequences, representing putative functional elements in retinal promoters, were compared with TRANSFAC data, by TESS program [16]. In particular, we used the "Filtered String-based Search Query" tool [17] for comparison only with known regulatory sites of mammals, with no mismatches allowed and by using the entire length of known sites instead of their core positions. Out of 60 motifs, 53 (88%) exactly matched at least one sequence known to bind a mammalian transcription factor. Sequences corresponding to common or general transcription factors (Sp1, Sp3, MAZ, GCF, CUP or Yi) were matched by 47 out of 60 consensus sequences (78%), 22 of which matches also additional factors (AP-1, AP-2, WT1, Krox-20, GR, PPUR or ER). In total, 26 consensus sequences resulted similar to sequences recognized by AP-1, AP-2, WT1, Krox-20, GR, PPUR or ER.
Analysis of positive control datasets
To the purpose of both analysing COOP efficiency with selected conditions and of indirectly comparing the performances of the method with those of different software, we analysed by COOP a group of 26 human positive control datasets prepared by Tompa and colleagues for the assessment of computational tools for the discovery of transcription factor binding sites [18,19]. This benchmark included 26 groups of promoters, for which it is known which regulatory signals should be detected.
The number and the length of promoter sequences and of known signals per dataset are reported in Table 6, along with the adopted quorum [see Additional file 1]. The number of signals per group of promoters which are shorter than the length of approximated patterns taken as input by COOP (12 nucleotides) and which were, in principle, very difficult to find by adopted settings, is also reported. For each experiment, among different motifs predicted we selected only the one corresponding to the motif represented in the highest number of sequences. For each dataset the nucleotide-level and site-level [18] overlap between pattern occurrences belonging to the cluster (i.e. the selected motif) and known signals, evaluated by different measures (see Methods), are included in Table 6 [see Additional file 1].
Moreover, the "combined" statistics summarizing COOP performance over the collection of human datasets, was compared with the same statistics calculated for the 14 different programs tested by Tompa and colleagues on the same datasets [18]. Results are presented in Figure 3 and in Table 7 [see Additional file 2].
The comparison showed that the performances of COOP on the "very difficult" human dataset are in line with those of the top rated tools. In comparison with other software, COOP resulted to be in the best 20% of evaluated tools according to four measures (nSn, nPC, sSn, sASP) and in the best one third according to six measures (nSn, nPC, nCC, sSn, sPPV, sASP).
Discussion
Pattern discovery in sequences of putative and sometimes incomplete promoters is a considerably complex problem [20-25]. It may be reasonably assumed that some regulatory regions of a group of co-regulated genes share similar sequence elements. In yeast, pairs of genes showing over 0.84 Pearson correlation between their expression profiles, have over 50% probability of sharing at least one common transcription factor binder [26].
Since patterns with biological significance could be subtle [27], a main difficulty in pattern discovery approaches is a priori establishing a "quorum" and defining search parameters (e.g. pattern length, number of allowed wildcards or distance of occurrences from the model). By increasing the distance and/or decreasing the quorum, the number of false positives becomes excessively large. A possible solution to the problem of output explosion is to use biological knowledge both before and after application of automated pattern discovery.
We analysed TRANSFAC data to obtain information about frequent properties of regulatory elements. It should be noticed that although not all TRANSFAC matrices are based on high-quality data and on large samples of sequences, this database represents the largest existing collection of known regulatory elements in different organisms.
In this study we developed a novel tool, called COOP, for analysing promoter sequences of putatively co-regulated genes, aiming at extraction of sequence motifs with possible regulatory function. The motif extraction method is based on Clustering of Overlapping Occurrences of approximate Patterns, which allows identification of tractable numbers of possibly interesting motifs, starting from large numbers of exact or approximate patterns.
Our method is somehow related to two approaches proposed by van Helden [28] and by Caselle [29], although these studies considered yeast promoter sequences and dealt with exact patterns. The originality of our approach, mainly resides principally in adopting a new similarity measure between patterns, based on the frequency of pattern co-occurrences, and in designing a flexible procedure, with seven parameters which could be varied in order to modulate stringency of different analysis steps.
Motifs reconstruction was designed to maximize information included in each extracted sequence motif avoiding generation of spurious elements, given that clustering parameters (d and o) are appropriately set. Each obtained motif is represented by a consensus sequence, derived from the alignment of strings grouped in a specific cluster by adjustable criteria. In particular, the i threshold affects the length of the consensus sequence, whereas the l, fc and fl determine the number and the distribution of variable positions in the consensus sequence.
In order to evaluate the performance of the method, we analysed positive control datasets, such as all the human benchmark groups of promoter sequences, containing known signals at known positions, proposed by Tompa for a systematic assessment of motif discovery tools. COOP analyses were carried out with the same settings used for analysing retina gene promoter. The quorum was established by using an unique criterion for different datasets, based on the total number of sequences in the sample. In the first analysis phase, approximated patterns of 12 nucleotides, with at most 2 variable positions, were searched. Benchmark datasets were 26 groups of different number of promoters sequences. Each set of sequences contained a group of known signals. Lengths of signals ranged from 4 nucleotides to 71 nucleotides. Thus, several datasets contained a number of very short signals, which were very hard to find by a motif discovery approach designed to find motifs of length equal or higher than 12 nucleotides. We predicted a motif for all but two human datasets, which included only two sequences. COOP performed comparably well than the tools which were top rated in the Tompa assessment. It should be noticed that some of the other tools gave no predictions for a number of datasets, thus being advantaged from the averaging nPPV, sPPV and nCC scores when calculating combined statistics over all the human datasets [18].
The method we developed was applied, in a case study, to a collection of human promoter sequences pertaining to a group of 91 putatively co-regulated genes expressed in the retina.
One Kb long promoter sequences were identified by predicting the most probable TSS according to the consensus of information about cDNA and ESTs alignments with the genome sequence. Even neglecting the possible presence of alternative promoters, definition of exact(s) TSS it is a still open problem, because of low sensitivity of promoter prediction programs and of incomplete cDNA coverage of 5' exons. However, cDNA coverage of the majority of genes selected for this study is almost complete, since genes considered are well known and/or highly expressed. The adequacy of our method for selecting gene promoter sequences is supported by results obtained by Trinklein and colleagues [30]: over 90% 152 human 600 bp promoter sequences, randomly selected among 10,276 TSS predictions (based only on alignment with full-length cDNA clones from Mammalian Gene Collection) resulted active in at least two cell lines. Although the size of 1 Kb upstream the TSS might be insufficient to cover all possible regulatory regions for all genes, it could reasonably include both core and proximal promoters and at least part of the distal promoter.
A very high number of approximate patterns of length from 10 to 14 with at most 20% variable positions was found in retina promoter sequences. This is partially due to the fact that they include similar sequences or sequences shifted only by few positions. By using COOP for clustering approximate patterns, on the basis of their frequent overlapping occurrences, we identified a number of interesting sequence motifs, often longer than the original patterns.
In order to test the significance of the group of sequence patterns frequently found in retinal promoters and used as input for COOP, we generated and studied different negative control datasets corresponding to a thousand groups of sequences, randomly selected among a very large group of human promoters. The average pairwise level of pattern sharing in these groups of promoters was expected to reflect the general level of pattern sharing between human gene promoters. We observed that the selected group of retinal promoters (pertaining to a sample of genes putatively co-expressed, co-regulated and/or with similar function) is enriched in common patterns as compared to random groups.
Sequence motifs produced by COOP resulted more frequently in the regions close to the TSS. Moreover, the group motifs consensus sequences selected according to very low variability in their central region was compared with sequences which are known to bind mammalian transcription factors under stringent criteria. Signals similar to those for general and widespread transcription factors, such as Sp1 or MAZ, are the most represented. Moreover, a number of selected motifs resulted to be similar to signals recognised by transcription factors expressed in tissues of ectodermal origin and relevant to development and function of retina (AP-1, AP-2, WT1, Krox-20, GR, PPUR or ER). For instance, AP-1 elements were found in a number of retinal gene promoters including cGMP-phosphodiesterase beta subunit [31] and hydroxyindole-O-methyltransferase [32] whereas the WT1 zinc finger factor is essential for normal development of retina and specifically involved in regulation of retinal genes [33].
Conclusion
We developed a method to detect sequence motifs corresponding to putative regulatory elements in gene promoters, starting from lists of approximate patterns with occurrences in promoter sequences. This method could be profitably applied to different datasets, including promoter sequences of different groups of genes in humans or in other Eukaryotes, for which co-regulation could be demonstrated or inferred. The method could be used to investigate on different kinds of regulatory sequences, such as intronic enhancers, or other sequence motifs with non-regulatory function.
Availability and requirements
COOP can be downloaded free-of-charge from the web page . COOP was developed in Python. The software works under Linux and requires Python 2.3 or higher, BioPhyton 1.40b and ClustalW. COOP is provided 'as is' with no guarantee or warranty of any kind and it is freely available for all.
Methods
COOP : Clustering Overlapping Occurrences of approximate Patterns
COOP takes as input a FASTA file of nucleotide sequences and a list of patterns with their number of occurrences in sequences or in their reverse complement. We used the SPEXS program [7] for producing the list of approximate patterns frequently represented in selected groups of promoter sequences. SPEXS code is freely available and it provides a number of advantages in terms of execution time and flexibility of parameters determining search conditions and output appearance.
Seven COOP parameters can be varied in order to select stringency at different stages of the analysis (Table 1).
In the first step, patterns represented in more than q promoters are searched by COOP in promoter sequences. In particular, both direct and reverse complement sequences of each pattern are compared against promoter sequences in order to collect pattern occurrences. Then, pattern occurrences (strings) are clustered according to a similarity measure based on frequency of their co-occurrences and by a joining algorithm derived from the so called "quick-find" algorithm [8]. In order to be included in the same cluster, two different strings must occur in promoter sequences much more frequently together than separately. Given the physical distance between pattern occurrences, measured as nucleotide distance between the 5'-ends of two corresponding sequences, the threshold d defines the maximum value for the distance between two pattern occurrences to be considered overlapping. Threshold o indicates the minimum ratio between observed overlapping occurrences of two strings and their average number of occurrences, allowing their inclusion in a unique cluster. The total number of clusters obtained in this way is influenced by the number of pattern occurrences to be clustered, depending on the q parameter, and depends as well on values selected for the minimum distance between patterns and for threshold o.
Once clusters are obtained, all sequence elements corresponding to pattern occurrences belonging to each given cluster are multi-aligned by ClustalW [9], with Gap Opening Penalty set to 100. Each alignment is then analysed in order to build up a matrix describing nucleotide counts in alignment positions. The cell xA1 of the matrix contains the number of times the A nucleotide has been observed in the first alignment position. Later, consensus sequences are built from matrices (Table 2). The maximal number of adjacent matrix positions fulfilling the established threshold for i (minimum ratio between number of nucleotides per alignment position and total number of lines in the alignment) is further analysed to determine the m nucleotides long motif consensus sequence.
Once the extension of lateral regions (l, ranging from 0 to m/2) is fixed, motif positions are considered invariable if the frequency of a single nucleotide exceed selected thresholds (fl for lateral regions and fc for the core region of the motif). Once the length of motif and of lateral regions is known, the extension of the core region is fixed.
Moreover, an additional procedure is available, which uses IUB/IUPAC nucleic acid single letter, double-degenerate codes (M = [A|C], K = [G|T], S = [G|C], W = [A|T], R = [G|A], Y = [T|C]) and four-degenerate code (N = [A|G|;C|T]) and follows IUPAC rules for string consensus reconstruction: i. A single nucleotide is shown if its frequency is greater than 50% and at least twice as high as the second most frequent nucleotide; ii. A double-degenerate code indicates that the corresponding two nucleotides occur in more than 75% of the underlying sequences (but the criteria for a single nucleotide assignment are not met); iii. All other frequency distributions are represented by the letter "N".
The output of the program is a collection of sequence clusters, each one representing a sequence motifs. Each cluster is associated to an alignment, to a matrix describing nucleotide counts in alignment positions and, ultimately, to a consensus sequence. Moreover, information about promoter sequences and nucleotide positions in which each cluster string occurs is given.
Selection of genes and of putative promoter regions
Analysis of genomic expression data
For the study, genes significantly more expressed in retina than in all other tissues were identified by analysis of genomic expression profiles of several human tissues. Genomic expression profiles were reconstructed in silico by using 41 unbiased (un-subtracted and/or un-normalized) UniGene cDNA libraries pertaining to 11 adult human normal tissues (retina, bone, hyppocampus, liver, lung, marrow, melanocyte, muscle, pancreas, prostate and testis) for which at least 6,000 ESTs per tissue were available [34]. The whole dataset included 270,871 ESTs, corresponding to 27,924 UniGene "clusters". The expression profiles were merged in an expression data matrix, which was then analysed by the Audic and Claverie test of differential expression in order to identify genes significantly more expressed in retina than in all other tissues considered. Significance threshold was set to a = 0.05.
Disease genes and genes encoding proteins with a specific function in the retina
By searching in OMIM [35], Retinal Information Network [36], LocusLink [37] and GeneCards [38,39] we selected a group of known genes whose mutation causes retinal diseases and genes encoding proteins which play specific functions in retina.
Retrieval of putative promoter regions
Reference Sequences of selected genes (RefSeq) [37] were extracted from corresponding LocusLink entries. When RefSeq for a gene was unavailable, the longest mRNA sequence with complete CDS was used. Sequences were then searched by BLAT [40] against release 15 of human genome sequence, for prediction of Transcription Start Site (TSS), obtained by analysis of mRNA/genomic DNA alignment, 5' ESTs placement and Acembly gene boundaries [41] annotation. Genomic sequences of 1 Kb upstream the predicted TSS were retrieved. These sequences were masked by RepeatMasker [42], in order to remove repetitive DNA.
Negative controls
Negative control groups of promoter sequences were established as 1,000 sets of promoter sequences, sampled at random among 17,156 human gene promoters.
Reference sequences of 27,427 human mRNA were obtained from GenBank. A group of 20,315 reference sequences was obtained, after exclusion of all sequences referring to unknown genes (chromosome open reading frames, hypothetical or predicted proteins) or to genes including in their sequence record words referring to vision, eye or retina.
Retrieval of promoter sequences corresponding to 1 Kb upstream the predicted TSS of genes was done by PromoSer [14,15]. TSS prediction options were set in order to retrieve for each gene 1 Kb upstream the most 5' TSS, with the same criteria used for retrieval of retinal gene promoters. In addition, exclusion options of PromoSer were set to extract at most one promoter per gene and to avoid retrieval of overlapping sequences. By this way, 17,156 promoters were localized and retrieved.
A Python script was developed for iterative random extraction of groups of m sequences from a list of N sequences, with N > m, without repetition.
Analysis of known regulatory sequence elements binding transcription factors
We used the TRANSFAC version available through BIOBASE. TRANSFAC [43] is a database of eukaryotic cis-acting regulatory DNA elements and trans-acting factors containing information on transcription factors, regulated genes, regulatory sites and nucleotide distribution matrices for binding sites of transcription factors. By using Perl scripts developed to the purpose, flat files pertaining to matrices data were parsed in order to extract information about consensus sequences length and about number, percent and localization of fixed and variable positions.
Analysis of positive control datasets
We analysed by COOP groups of promoters for which it is known which regulatory signals should be detected. Analyses were done of the complete set of groups of human sequences included in public benchmarks prepared by Tompa and colleagues [18], including three different types of sequences: 9 groups of real genomic promoter sequences containing known transcription factors binding sites, 9 groups of randomly chosen human genomic promoter sequences in which the binding sites were planted and 8 groups of sequences randomly generated according to a Markov chain of order 3 (that was constructed from human promoter sequences) in which the binding sites were planted.
We analysed such datasets by using the same methodology applied for the identification of putative novel regulatory elements in retinal gene promoters, including searching for 12-2 patterns by SPEXS and motifs reconstruction by using COOP (clustering parameters: d = 3 and o = 0.7). The quorum (q) was set to the highest integer equal or less than one third of the total number of sequences in the dataset. When with the selected quorum no results were obtained, q was set to the highest integer giving results. When analysing datasets composed of from 3 to 6 sequences, q was set to 2. We made no motif predictions for the two datasets of two sequences each.
For each group of promoters, among different clusters obtained, we selected only the one corresponding to the motif represented in the highest number of sequences. For each dataset out of the 26 considered, we checked the overlap between pattern occurrences belonging to the cluster (i.e. the motif) and known signals. The efficiency of COOP was evaluated according to different measures, defined as follows. At nucleotide-level nTP (number of nucleotide positions in both known sites and predicted sites), nFN (number of nucleotide positions in known sites but not in predicted sites), nFP (number of nucleotide positions not in known sites but in predicted sites) and nTN (number of nucleotide positions in neither known sites nor predicted sites). A predicted site overlaps a known site if they overlap by at least one-quarter the length of the known site. Thus, at site-level we calculated: sTP (number of known sites overlapped by predicted sites), sFN (number of known sites not overlapped by predicted sites) and sFP (number of predicted sites not overlapped by known sites). We then calculated the following measures of accuracy. At either the nucleotide (x = n) or site (x = s) level: Sensitivity, xSn = xTP/(xTP + xFN); Positive Predictive Value, xPPV = xTP/(xTP + xFP). At the nucleotide-level: Specificity, nSP = nTN/(nTN + nFP); Performance Coefficient, nPC = nTP/(nTP + nFN+ nFP); Correlation Coefficient, ; Average Site Performance, sASP = (sSn + sPPV)/2 [18].
In addition, the statistics (nSn, nPPV, nSp, nPC, nCC, sSn, sPPV, sASP) summarizing COOP performance (with selected settings) over the collection of human datasets, were computed with the "combined" method [18] and compared with the same statistics calculated for the 14 different programs tested by Tompa and colleagues on human datasets.
Authors' contributions
SB and GAD conceived the study. SB and AC carried out pattern discovery analyses, developed and tested COOP software and drafted the manuscript. AB and CP participated to the early phases of the work, contributing to gene promoter selection and to the development of the COOP algorithm, respectively. GAD revised the manuscript. All authors read and approved the final manuscript.
Supplementary Material
Additional File 1
Table 6. Results of the analysis of 26 human positive control datasets with COOP.
Click here for file
Additional File 2
Table 7. Comparative evaluation of COOP performance on 26 human positive control datasets.
Click here for file
Acknowledgements
Financial support of the Italian Ministry for Technological and Scientific Research and of Padova University to G.A.D and of Italian Association for Cancer Research (AIRC) to S.B is gratefully acknowledged.
Figures and Tables
Figure 1 Flow-chart of COOP program. Input, output and main steps are shown.
Figure 2 Comparison of patterns discovery results in retinal gene promoter sequences and in 1,000 negative control datasets. Plots of number of patterns (12 bp long, with at most two variable positions) vs number of sequences in which they were found, in retinal gene promoter sequences (open squares) and in 1,000 negative control datasets (filled diamonds). For negative control datasets, the average value of 1,000 sets of sequences is given, with a two standard deviations interval. Statistically significant differences (0.05 threshold) are marked by stars. (A) Comparison between the 1000M52 dataset (52 promoter sequences of genes overexpressed in the retina) and the RAN1000M52i dataset (1,000 groups of 52 randomly chosen human promoters); (B) Comparison between the 1000M91 dataset (91 retinal gene promoter sequences) and the RAN1000M91i (1,000 groups of 91 randomly chosen human promoters).
Figure 3 Statistics comparing the accuracy of COOP and of 14 different motif discovery tools on 26 human positive control datasets. Combined measures of correctness over all 26 human datasets, as defined in Methods. The number of datasets (out of 26) for which no motif was predicted by each tool is reported in brackets, following the name of the tool.
Table 1 Description of COOP parameters.
Step Parameter Description Range Example
Search for pattern occurrences q Quorum (minimum number out of N input sequences in which a given pattern must be represented) 1 - N ≥ 20 out of 100 sequences
Clustering d Physical distance between 5'-ends of occurrences of patterns of length p 0 - |p| ≤ 2 nucleotides
o Ratio between observed overlapping occurrences of two patterns and their average number of occurrences 0 – 1 ≥ 0.8
Consensus building i Ratio between the number of nucleotides per alignment position and the total number of lines in the alignment. The maximal number of adjacent positions exceeding the threshold i (m) is further analysed for determining the consensus sequence of the motif 0 – 1 ≥ 0.5
l Nucleotide length of the lateral region of the motif 0 - m/2 3 bp (out of 10)
f
l
Frequency of a single nucleotide in each position of the lateral region to be considered specified 0 – 1 ≥ 0.6
f
c
Frequency of a single nucleotide in each position of the core region to be considered specified 0 – 1 ≥ 0.8
Table 2 Procedure for building a consensus sequence starting from a matrix of nucleotide counts, according to selected parameters. Rows from two to five represent the matrix of nucleotide counts in different positions of an alignment associated to a cluster of pattern occurrences. The sixth row contains, for each alignment position, the ratio between number of sequences in the position and the total number of lines in the alignment. Out of 11 positions of the matrix, positions from one to ten (shaded in grey) fulfil the minimum i (0.5) and are considered for building the consensus. If the lateral region length is set to 3 nucleotides, a 3-4-3 motif is obtained. The fl (0.6) threshold is applied to the positions in the lateral regions, whereas the fc (0.8) is applied to positions in the core region. Cells containing values fulfilling the condition reported on the left are in bold. In the last row, the derived consensus sequence is shown.
1 2 3 4 5 6 7 8 9 10 11
A 0 0 0 4 0 0 0 0 0 0 0
C 0 0 5 0 5 2 0 0 0 0 2
G 0 4 0 0 0 3 5 5 0 4 0
T 3 0 0 1 0 0 0 0 5 0 0
i (0.5) 0.6 0.8 1 1 1 1 1 1 1 0.8 0.4
fl (0.6) 1 1 1 1 1 1
fc(0.8) 0.8 1 0.6 1
Consensus sequence T G C A C N G G T G -
Table 3 Number of sequences in which most represented patterns were found in different retinal datasets.
Pattern 500U91 500PM91 500M91 1000M91
10-2 44 42 32 40
12-2 19 19 10 12
14-2 11 11 5 7
Table 4 Statistics about patterns found in different groups of retina gene promoter sequences and in the corresponding negative control random datasets.
Quorum
Pattern Obs. Exp. P-value
10-2 719 351.3 0.017
20 12-2 0 - -
14-2 0 - -
1000M91 (91 promoters of retinal genes vs RAN1000M91i) 10-2 18683 12846.4 0.016
10 12-2 41 35.4 0.324
14-2 0 - -
7 12-2 714 410.2 0.060
1000M52 (52 promoters of retinal genes vs RAN1000M52i) 5 12-2 1537 429.4 0.001
Table 5 List of 60 consensus sequences corresponding to selected motifs showing most conserved central regions. For each motif, consensus sequence, length and total number of occurrences in the 1000M dataset are reported, along with LocusLink symbols of corresponding genes. In the last column, for each consensus, the list of mammalian transcription factors recognising similar DNA sequences is reported.
Consensus sequence Length Total occ. Genes in which promoter the motif was found Transcription factors
AAAAAAAAAAAAAA 14 151 EFEMP1, CCNI, CNGB3, KCNV2, IMPDH2, SLC24A1, DHRS3, G2AN, RTP801, MGC15WIF11, USH3A, CRX, 18, HMGA1, SLC24A2, RDS, TULP1, DC-TM4F2, OPN1SW, RP1, MGAT4B, GAPD, ELOVL4, RRAD, ARR3
NGGCCCCGCCCCCN 14 114 EEF1G, HMGA1, EFEMP1, CYBA, KRT18, OPA1, DPYSL4, RAX, FLJ1415, MGC15WIF11, FLJ1415, ALMS1, EIF3S8, G2AN, ALMS1, DC-TM4F2, MSH6, RCV1, KRT19, DHRS3, PITPNC1, RRAD, HPCAL1, MGAT4B, SLC38A3, IMPDH2, CNGB1, RDH5, EFEMP1, CRABP1, C7orf20, CCNI, GNB1, CRX, GAPD, ARF4L, AIPL1, DKFZP564K0822 AP-1, GCF, Sp1, Sp3, TFIID
GCACCCCCAGCCCCN 15 101 RHO, G2AN, EFEMP1, SLCO4A1, CYBA, HPCAL1, KIFC3, RCV1, NK4, KRT18, CRX, ARR3, PPP1R3F, MGAT4B, NRL, RRAD, CCNI, SAG, ALMS1, MGC15WIF11, DKFZP564K0822, VMD2, DPYSL4, GNAT1, GAPD, OPN1SW, RAX, DHRS3, COPEB, SLC38A3, TMEM16B, SLC24A1 Sp1
NGAGGGCAGGGGCNN 15 94 GNB1, KRT19, ELOVL4, VMD2, MSH6, HMGA1, RHO, NK4, SLC38A3, LRRCGUCA1B, CYBA, RCV1, RRAD, GUCY2D, MGC15WIF11, AIPL1, MGAT4B, KIFC3, CRX, CRABP1, G2AN, ALMS1, RTP801, EEF1G, COPEB, OPA1, EFEMP1, KCNV2, PDE6A, AOC2, RLBP1, FLJ1415, RAX, DPYSL4, WIF1, DC-TM4F2 Sp1
CCTCCCTCCCTCCC 14 76 ARF4L, COPEB, RHO, SLC38A3, FLJ1415, WDR17, ELOVL4, DHRS3, KCNV2, OPA1, CCNI, GUCA1B, RDH5, RAX, ALMS1, DKFZP564K0822, NK4, RGS19IP1, RRAD, KIFC3, KRT19, SLCO4A1, HPCAL1, DPYSL4, TNFRSF6, CNGB1, DC-TM4F2 MAZ
NCTCCCCCTCCCCC 14 43 CNGB1, GAPD, RPE65, ALMS1, COPEB, MSH6, RRAD, CRABP1, TNFRSF6, CRX, WIF1, FLJ1415, DKFZP564K0822, PDE6A, RDH5, SLC38A3, CYBA, GNB1, MERTK, WDR17 Sp1, AP-2, MAZ
GNNTGGGGGAGGGGN 15 41 CYBA, RLBP1, KCNV2, CNGB1, COPEB, KIFC3, RDH5, CCNI, FLJ1415, MGC15WIF11, AIPL1, NK4, HPCAL1, CNGB1, GUCA1A, ALMS1 MAZ, Sp1
CNCCCCCACCCCCACC 16 40 RCV1, SLC38A3, HPCAL1, KIFC3, RLBP1, RPE65, DHRS3, RTP801, CYBA, DPYSL4, RDH5, RRAD, COPEB AP-2alphaB, Sp1, WT1
CTCCCCCTCCCCNNC 15 26 CNGB1, CRX, GAPD, RHO, CNGB1, COPEB, CYBA, AIPL1, RAX AP-2, MAZ, Sp1
CCCCAGCCCCNCA 13 23 CCNI, EFEMP1, SLCO4A1, MGC15WIF11, ARR3, CYBA, HPCAL1, KIFC3, RAX, RLBP1, MGAT4B, AIPL1, RGS19IP1, ALMS1 Sp1
NNGGCCCCTGCCCN 14 23 HMGA1, NK4, LRRCGUCA1B, FLJ1415, GNB1, KRT19, AIPL1, GUCA1A, DHRS3 Sp1
NCCCCCTCCACCN 13 22 ARR3, HMGA1, KRT19, VMD2, DHRS3, ARF4L, RAX, CCNI, SIRT3, GUCA1B, DC-TM4F2 Sp1
NCNGGGCTGGGGN 13 22 CYBA, HPCAL1, RRAD, GAPD, GUCA1A, RHO, G2AN, EFEMP1 Sp1
NNTCCCCCTCCCNN 14 22 TNFRSF6, CNGB1, CRX, EEF1G, GAPD, RPE65, ALMS1, DKFZP564K0822, COPEB, AIPL1 AP-2alphaB, MAZ, Sp1, WT1 -KTS
NNCCCAGCCCCCAN 14 20 RDH5, SLC38A3, EFEMP1, ARR3, CYBA, GAPD, HPCAL1, NK4, PPP1R3F Sp1
NTGGGGGAGGGGNA 14 20 COPEB, CYBA, RLBP1, PITPNC1, CNGB1, CRX, GAPD, MERTK, CCNI MAZ, Sp1, Sp3
CCNGCCCTGGCCT 13 18 GUCA1A, GUCY2D, RCV1, VMD2, EFEMP1, LRRCGUCA1B, C7orf20, 4, RRAD, UNC119, MERTK Sp1
GCNGCCCCTGCCN 13 18 CRX, CYBA, GNB1, HMGA1, RHO, SLC38A3, MGAT4B, FLJ1415, KRT18
NCNGGGGGCGGGG 13 18 CYBA, RRAD, FLJ1415, HMGA1, RDH5, RGS19IP1, G2AN, RTP801, DC-TM4F2 AP-1, ER, Sp1
CTNCCCCTCCCC 12 17 RLBP1, AIPL1, PITPNC1, CNGB1, GAPD, RHO, CNGB1, EFEMP1, COPEB, CYBA, GNB1, PDE6A AP-2alphaB, MAZ, Sp1
GGGGTGGGGNTG 12 17 GUCY2D, FLJ1415, AIPL1, RDH5, CRABP1, HPCAL1, KIFC3, DHRS3, RTP801, CYBA, RLBP1 AP-2alphaB, Sp1, Sp3
CCCGCCCCTGNCC 13 16 GNB1, HPCAL1, KRT19, MGAT4B, G2AN, Sp1
NGGGGGTGGGGGN 13 16 HPCAL1, RRAD, DHRS3, FLJ1415, CYBA, GNB1, DPYSL4 Sp1
NNCCCCCGCCCCNN 14 16 GNB1, RGS19IP1, LRRCGUCA1B, ALMS1, DC-TM4F2, KRT18, SAG AP-1, AP-2alphaB, ER, Krox-20, Sp1, WT1, WT1 I, WT1 I -KTS
AGNGGGAGGGGCN 13 14 CYBA, EFEMP1, RAX, MGC15WIF11, ARF4L, CRX, SLCO4A1 MAZ, Sp1, Sp3
CCCTGTCCCTGGAN 14 14 ARR3, HPCAL1, FLJ1415, DC-TM4F2, KRT19, LRRCGUCA1B, TMEM16B GR
CGGGGCCGCCNCN 13 14 FLJ1415, DC-TM4F2, MGC15WIF11, COPEB, MGAT4B, SLCO4A1, RAX CUP, Sp1
CTCTCTCTCCNTN 13 14 GAPD, GUCA1A, NRL, RRAD, FLJ1415, GNAT2, KCNV2
NANCTCTGCACCC 13 14 LRAT, TNFRSF6, CYBA, KIFC3, DPYSL4, G2AN, RTP801
NCCGCCCCCGCCN 13 14 GNB1, IMPDH2, SLC38A3, COPEB, CYBA, KRT18, SLCO4A1 AP-1, ER, Kxox-20, Sp1, WT1 I -KTS, WT1-del2
NGGCCTCTGGNCN 13 14 CYBA, GAPD, KRT19, RDH5, DPYSL4, HPCAL1, MGAT4B
NGGGAGGGGGAAG 13 14 GAPD, AIPL1, FLJ1415, EEF1G, RPE65, ALMS1, WDR17 AP-2alphaB, MAZ, Sp1, WT1 I -KTS
NGNCCCCAGCCCC 13 14 GAPD, GUCA1A, RHO, ARR3, CYBA, NK4, PPP1R3F AP-2, Sp1
NNCCCAGCCCAGNN 14 14 GAPD, RHO, ARR3, CRABP1, CYBA, RRAD, MGAT4B Sp1
TGGGGGTGGGGGN 13 14 HPCAL1, RLBP1, DHRS3, CYBA, HMGA1, RRAD, DPYSL4 Sp1
NGGCGGGGGCGGGG 14 13 EFEMP1, KRT18, RRAD, SLCO4A1, IMPDH2, EFEMP1, COPEB AP-1, Krox-20, Sp1, WT1 I -KTS, WT1-del2
GGNAGGGGCGGG 12 11 ELOVL4, REA, G2AN, GNB1, MSH6, GUCY2D, RGS19IP1, LRRC21, SLCO4A1, PITPNC1 MAZ, Sp1
CCCGCCCGCCCC 12 9 GNB1, RGS19IP1, WIF1, PITPNC1, DC-TM4F2, HMGA1, DPYSL4, KRT18, RAX Sp1
GGGCGGGGCNGG 12 9 CYBA, DPYSL4, MGAT4B, MSH6, RCV1, ALMS1, FLJ1415 ER, GCF, Sp1
GGGCTGGGGGTG 12 9 CYBA, HPCAL1, KIFC3, RCV1, RHO, G2AN, DKFZP564K0822 Sp1
GGGGAAGGGNGG 12 9 TULP1, CRX, MSH6, KRT19, CNGB1, SLC38A3, AIPL1, HMGA1, FLJ1415
GGGGCGGGCNNG 12 9 EEF1G, KRT19, DC-TM4F2, GUCY2D, RGS19IP1, PITPNC1, C7orf20, RTP801 ER, Sp1
GGNGCGGGCGGG 12 9 HMGA1, KRT19, DPYSL4, DC-TM4F2, RGS19IP1, WIF1, PITPNC1, FLJ1415 AP-2, ETF, Krox-20, Sp1, WT1 I -KTS
GNNGGGGCTGGG 12 9 GAPD, HPCAL1, KIFC3, RCV1, RAX, COPEB, RDH5 WT1 -KTS
CAGGGGGCGGGG 12 8 CYBA, EFEMP1, HPCAL1, FLJ1415, GAPD, HMGA1, G2AN, DC-TM4F2 AP-1, ER, Sp1, Yi
CNCCCCCACCCC 12 8 CYBA, HMGA1, RCV1, SLC38A3, HPCAL1, RLBP1, DHRS3 AP-2alphaB, CACCC-binding, factor, Sp1, WT1
GAGTGGGGGAGG 12 8 DHRS3, KCNV2, COPEB, CYBA, HMGA1, WIF1, FLJ1415, MGC15WIF11
GCCTGGGGGAGG 12 8 CYBA, SIRT3, KIFC3, CCNI, DKFZP564K0822, DC-TM4F2, MGC15WIF11 AP-2
GGGCAGGGGCNG 12 8 CYBA, GNB1, HPCAL1, HMGA1, RHO, SLC38A3, MGAT4B, G2AN Sp1
GGGCGGGGCTGG 12 8 CYBA, HPCAL1, RAX, MSH6, RCV1, ALMS1, DC-TM4F2 ER, GCF, Sp1
CCCTGTCCCTGG 12 7 CNGB1, GNB1, FLJ1415, KRT19, ELOVL4, TMEM16B, FLJ1415 GR
CCTTCCCCCNGC 12 7 GNB1, SLC38A3, AIPL1, SLCO4A1, RDH5, TULP1, NK4 MAZ
CNCCTCCTGCNC 12 7 CRABP1, GUCA1A, PDE6A, RGR, DPYSL4, WIF1, HPCAL1 PPUR, Sp1
CNGCCCCCAGNC 12 7 RHO, EFEMP1, DC-TM4F2, CNGB1, CYBA, NK4, MERTK Sp1
GCNCCCCTCCCC 12 7 COPEB, CRX, HPCAL1, RGR, CNGB1, MERTK, RAX MAZ, Sp1
GGGCAGGGGCGG 12 7 ELOVL4, HMGA1, HPCAL1, RHO, SLC38A3, MGAT4B, G2AN Sp1
GGGGCTGGGGNC 12 7 ARR3, CYBA, HPCAL1, NK4, RAX, PPP1R3F, RLBP1 AP-2alphaB, Sp1
GNAGGGGGCAGG 12 7 GAPD, NK4, GUCA1B, SLC38A3, WIF1, G2AN, EFEMP1 Sp1
TGGGGGAGGNNA 12 7 KCNV2, COPEB, HMGA1, KIFC3, RDH5, CCNI, FLJ1415 MAZ, Sp1
TTTTTTTTTNTA 12 7 IMPDH2, G2AN, SLC24A2, RTP801, KCNV2, USH3A-PROMB, CCNI TBP
==== Refs
Bucher P Regulatory elements and expression profiles Curr Opin Struct Biol 1999 9 400 407 10361093 10.1016/S0959-440X(99)80054-2
Werner T Models for prediction and recognition of eukaryotic promoters Mamm Genome 1999 10 168 75 9922398 10.1007/s003359900963
Brazma A Jonassen I Vilo J Ukkonen E Predicting gene regulatory elements in silico on a genomic scale Genome Res 1998 8 1202 1215 9847082
Werner T Finding and decrypting of promoters contributes to the elucidation of gene function In Silico Biol 2002 2 249 255 12542410
Bussemaker HJ Li H Saggia ED Regulatory element detection using correlation with expression Nat Genet 2001 27 167 171 11175784 10.1038/84792
Ge H Liu Z Church GM Vidal M Correlation between transcriptome and interactome mapping data from Saccharomyces cerevisiae Nat Genet 2001 29 482 486 11694880 10.1038/ng776
Vilo J Kapushesky M Kemmeren P Sarkans U Brazma A Parmigiani G, Garrett ES, Irizarry R, Zeger SL Expression Profiler The Analysis of Gene Expression Data: Methods and Software 2003 Springer Verlag, New York, NY
Sedgewick R "Algorithms in C" 1998 Third Addison-Wesley editor, Reading, MA
Higgins D Thompson J Gibson T Thompson JD Higgins DG Gibson TJ CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice Nucleic Acids Res 1994 22 4673 4680 7984417
Wingender E Dietze P Karas H Knuppel R TRANSFAC: a database on transcription factors and their DNA binding sites Nucleic Acids Res 1996 24 238 241 8594589 10.1093/nar/24.1.238
Audic S Claverie JM The significance of digital gene expression profiles Genome Res 1997 7 986 995 9331369
Kent WJ BLAT – the BLAST-like alignment tool Genome Res 2002 12 656 664 11932250 10.1101/gr.229202. Article published online before March 2002
Supplementary material
Halees AS Leyfer D Weng Z PromoSer: A large-scale mammalian promoter and transcription start site identification service Nucleic Acids Res 2003 31 3554 3559 12824364 10.1093/nar/gkg549
PromoSer
Petsko G Baxevanis AD Modeling Structure from Sequence Current Protocols in Bioinformatics 2002 John Wiley & Sons Inc
TESS
Tompa M Li N Bailey TL Church GM De Moor B Eskin E Favorov AV Frith MC Fu Y Kent WJ Makeev VJ Mironov AA Noble WS Pavesi G Pesole G Regnier M Simonis N Sinha S Thijs G van Helden J Vandenbogaert M Weng Z Workman C Ye C Zhu Z Assessing computational tools for the discovery of transcription factor binding sites Nat Biotechnol 2005 23 137 144 15637633 10.1038/nbt1053
Assessment of Computational Motif Discovery Tools
Marsan L Sagot MF Algorithms for extracting structured motifs using a suffix tree with an application to promoter and regulatory site consensus identification J Comput Biol 2000 7 345 362 11108467 10.1089/106652700750050826
Pevzner PA Sze SH Combinatorial approaches to finding subtle signals in DNA sequences Proc Int Conf Intell Syst Mol Biol 2000 8 269 278 10977088
Pavesi G Mauri G Pesole G Methods for pattern discovery in unaligned biological sequences Briefings in Bioinformatics 2001 2 417 430
Buhler J Tompa M Finding motifs using random projections J Comput Biol 2002 9 225 242 12015879 10.1089/10665270252935430
Eskin E Pevzner PA Finding composite regulatory patterns in DNA sequences Bioinformatics 2002 18 S354 363 12169566
Apostolico A Bock ME Lonardi S Monotony of surprise and large-scale quest for unusual words J Comput Biol 2003 10 283 311 12935329 10.1089/10665270360688020
Allocco J Kohane IS Butte AJ Quantifying the relationship between co-expression, co-regulation and gene function BMC Bioinformatics 2004 5 18 28 15053845 10.1186/1471-2105-5-18
Keich U Pevzner PA Subtle motifs: defining the limits of motif finding algorithms Bioinformatics 2002 18 1382 1390 12376383 10.1093/bioinformatics/18.10.1382
van Helden J Andre B Collado-Vides J Extracting regulatory sites from the upstream region of yeast genes by computational analysis of oligonucleotide frequencies J Mol Biol 1998 281 827 842 9719638 10.1006/jmbi.1998.1947
Caselle M Di Cunto F Provero P Correlating overrepresented upstream motifs to gene expression: a computational approach to regulatory element discovery in eukaryotes BMC Bioinformatics 2002 3 7 11876822 10.1186/1471-2105-3-7
Trinklein ND Aldred SJ Saldanha AJ Myers RM Identification and functional analysis of human transcriptional promoters Genome Res 2003 13 308 312 12566409 10.1101/gr.794803
Di Polo A Lerner LE Farber DB Transcriptional activation of the human rod cGMP-phosphodiesterase beta-subunit gene is mediated by an upstream AP-1 element Nucleic Acids Res 1997 25 3863 3867 9380509 10.1093/nar/25.19.3863
Rodriguez IR Mazuruk K Schoen TJ Chader GJ Structural analysis of the human hydroxyindole-O-methyltransferase gene. Presence of two distinct promoters J Biol Chem 1994 269 31969 31977 7989373
KD Wagner N Vidal VP Schley G Wilhelm D Schedl A Englert C Scholz H The Wilms' tumor gene Wt1 is required for normal development of the retina EMBO J 2002 21 1398 1405 11889045 10.1093/emboj/21.6.1398
HGXP
OMIM
RetNet
Pruitt KD Maglott DR RefSeq and LocusLink: NCBI gene-centered resources Nucleic Acids Res 2001 29 137 140 11125071 10.1093/nar/29.1.137
Safran M Solomonm I Shmueli O Lapidot M Shen-Orr S Adato A Ben-Dor U Esterman N Rosen N Peter I Olender T Chalifa-Caspi V Lancet D GeneCards 2002: towards a complete, object-oriented, human gene compendium Bioinformatics 2002 18 1542 1543 12424129 10.1093/bioinformatics/18.11.1542
GeneCards
BLAT
Acembly
RepeatMasker
Biobase
| 15904489 | PMC1173081 | CC BY | 2021-01-04 16:02:48 | no | BMC Bioinformatics. 2005 May 18; 6:121 | utf-8 | BMC Bioinformatics | 2,005 | 10.1186/1471-2105-6-121 | oa_comm |
==== Front
BMC BioinformaticsBMC Bioinformatics1471-2105BioMed Central London 1471-2105-6-1221594388410.1186/1471-2105-6-122DatabaseSuperLigands – a database of ligand structures derived from the Protein Data Bank Michalsky Elke [email protected] Mathias [email protected] Andrean [email protected] Robert [email protected] BCB (Berlin Center for Genome Based Bioinformatics) at Institute of Biochemistry, Charité (University Medicine Berlin), Monbijoustr. 2, 10117 Berlin, Germany2005 19 5 2005 6 122 122 3 2 2005 19 5 2005 Copyright © 2005 Michalsky et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Currently, the PDB contains approximately 29,000 protein structures comprising over 70,000 experimentally determined three-dimensional structures of over 5,000 different low molecular weight compounds. Information about these PDB ligands can be very helpful in the field of molecular modelling and prediction, particularly for the prediction of protein binding sites and function.
Description
Here we present an Internet accessible database delivering PDB ligands in the MDL Mol file format which, in contrast to the PDB format, includes information about bond types. Structural similarity of the compounds can be detected by calculation of Tanimoto coefficients and by three-dimensional superposition. Topological similarity of PDB ligands to known drugs can be assessed via Tanimoto coefficients.
Conclusion
SuperLigands supplements the set of existing resources of information about small molecules bound to PDB structures. Allowing for three-dimensional comparison of the compounds as a novel feature, this database represents a valuable means of analysis and prediction in the field of biological and medical research.
==== Body
Background
Protein modelling and structure prediction as well as binding and interaction prediction have become very valuable instruments for researchers in biology and medicine. In order to build reasonable and useful models, as much information as possible has to be incorporated into the protein modelling process. To refine protein models, chemical as well as spatial information about ligand structures can be considered, specifically to optimise side-chain conformations around binding-sites [1].
Several databases delivering structures and different additional information about ligand molecules from the Protein Data Bank (PDB) [2], [21] have been provided on the Internet. Ligand Depot [3], [22] comprises chemical and structural information for small molecules found in the PDB and also provides a graphical interface for performing chemical substructure searches. Idealized three-dimensional structures and additional information about PDB ligands can be retrieved via the search interface of the E-MSD macromolecular structure relational database [4], [23]. Besides many other features, Relibase [5], [24] allows for two-dimensional similarity and substructure search among the ligands as well as for sequence similarity search among the corresponding proteins. LigBase [6], [25] is a database of ligand binding sites aligned with related protein structures and sequences. Various information about ligands bound to macromolecules deposited in the PDB can be retrieved from many further sources like HIC-Up [7], [26], PDBsum [8], [27] and the IMB Jena Image Library of Biological Macromolecules [9], [28]. The latter can be searched after geometrical properties of the ligand binding sites.
Information contained in these databases can help identifying ligands which are likely to bind to a given protein structure. The opposite question, namely to find target proteins for a certain ligand, was addressed in [10], where a collection of protein active sites was extracted from the PDB and scanned with aid of a docking algorithm. Further data collections emphasize the link between binding affinities and structures of the protein-ligand complexes and, inter alia, provide experimentally measured binding data, e.g. PLD [11], [29] LPDB [12], [30], PDBbind [13], [31].
For modelling and simulation purposes, chemical and spatial information about protein ligands is vitally important. Addressing this fact, SuperLigands is a collection of small molecule structures contained in the PDB, facilitating comparison of the molecules regarding their two-dimensional similarity. As spatial comparison of compounds can deliver valuable information in addition to this, SuperLigands also allows for three-dimensional superpositions. Spatial coordinates of the compounds can be retrieved as MDL Mol files, which include information about multiple bonds.
Construction and content
Native conformations of small molecules contained in the PDB and additional information were collected from the PDB [2], [21], Ligand Depot [3], [22] and MSD [4], [23] and deposited in the database SuperLigands. The database has been designed as a MySQL relational database and supplemented with a user-friendly web interface. Database queries are performed and HTML pages are generated via PHP scripts. The freely available MDL® Chime plug-in is used to display molecules and allows the user some manipulations of the view and to store the displayed molecule in the MDL Mol file format.
In order to enable fast two-dimensional searches, 960 bit binary fingerprints (MDL MACCS Keys [14]) were calculated and stored in the database for all ligands. Tanimoto coefficients are calculated via a PHP script. Here, all 960 MDL keys are included and equally weighted. The Tanimoto coefficient for two structures a and b is defined as follows: T(a,b)=Nab/(Na+Nb-Nab), where Na and Nb are the numbers of bits set in the fingerprint of structure a and b, respectively, and Nab is the number of bits which are common to both fingerprints.
Three-dimensional superposition of two different PDB ligands is performed in the following way: each conformation of one molecule occurring in the PDB is superposed with each conformation of the second molecule. Those two instances matching best are displayed. The best match is defined by maximizing the score defined by
where RMSD is the Root Mean Square Deviation of the superposed atoms. For completion, PDB codes, chain identifiers and positions in the PDB files of the matched conformations as well as the atom numbers of both ligands, the number of superposed atoms, the number of superposed atoms of the same type and the RMSD of the superposition are returned. For detailed information regarding the superposition algorithm see [15].
Utility
SuperLigands can be searched by hetero-ID (i.e. the three-letter PDB code for hetero-compounds), name, molecular formula or PDB identifier. In the results table, hetero-ID and names of the compounds are given. Moreover, the molecular structure is displayed in one cell of the table where it can be rotated by the user and different displaying options can be chosen. More information like molecular formula, atom numbers and occurrence in the PDB can be retrieved additionally.
The database SuperLigands contains compounds defined by 'HETATM' records in PDB files. Some of these molecules may be bound to pseudopeptides but can also be separate ligands. Coming across such a molecule, the user is given a hint and is provided with a list of pseudopeptides in which this molecule is bound.
The user can search the database for molecules that have a significant two-dimensional similarity to a given ligand or assess the three-dimensional similarity of two compounds by superposing them with each other. Such similarity queries can be performed starting from the search results tables or directly using separate forms. Using such a form, the Tanimoto coefficient of two given structures can also be retrieved.
A typical example for a query to SuperLigands is a search for tobramycin, known as antiinfective and antibacterial drug, starting in the main form. Searching the database for similar compounds in the next step supplies the drug kanamycin as PDB ligand with the highest Tanimoto similarity (98.6%). Now, a three-dimensional superposition of all instances of tobramycin (32 atoms, two instances) and kanamycin (33 atoms, four instances) occurring in the PDB can be performed. The best fitting structures are superposed and then displayed. In this case, best fitting are the instances of tobramycin in PDB entry 1m4d and kanamycin in 1m4i with an RMSD of 0.14Å (32 atoms superposed). Navigating through the website, the topological and spatial similarities of PDB ligands can be obtained easily. For example, tobramycin and ribostamycin (31 atoms, four instances) have a Tanimoto coefficient of 96.5%, the RMSD of their best superposition is only 0.95Å (25 atoms superposed). In turn, geneticin (34 atoms, five instances) delivers a Tanimoto coefficient of only 81.1% and a much better RMSD (0.16Å, 30 atoms superposed).
As an additional feature of SuperLigands, similarity of PDB ligands to known drugs can be assessed in a comfortable manner. Starting with a ligand, a two-dimensional similarity search as described above can be initiated, not only among the PDB ligands but also in a database containing the structures of known drugs (SuperDrug Database [16], [32]). The drug structures found can be superposed spatially (for an example, see Figure 1).
Discussion
Statistics: comparison of PDB ligands with drugs
Recently, a database containing 2396 drug molecules and having the same design as SuperLigands has been created (SuperDrug Database [16], [32]). To answer the question, how many drugs or drug-like molecules are bound to PDB structures, Tanimoto coefficients have been calculated for all pairwise combinations of molecules from SuperLigands and the SuperDrug Database. A set of 5,040 PDB ligands has been incorporated into these calculations. Considering two molecules having a Tanimoto coefficient of 100% (or greater than 95% ; 90%) identical or very similar, this analysis reveals that 413 (771 ; 1,457) of 5,040 PDB ligands are drugs or drug-like compounds.
Furthermore, some chemical properties of PDB ligands and drugs have been compared (see Figure 2). The distributions of numbers of hydrogen bond donors for PDB ligands and drugs differ most significantly. A bigger percentage of the drugs (26%) have no hydrogen bond donor, the largest fraction of the PDB ligands (19%) have two of them. About half of the drugs have no or only one hydrogen bond donor, which applies for only a quarter of the PDB ligands. About one third of the drugs have three or four hydrogen bond acceptors, the fractions of drugs with nine or more hydrogen bond acceptors drop below 3%. For the PDB ligands, the distribution is more flat: only 22% of them have three or four hydrogen bond acceptors, still over 3% of them have 11 hydrogen bond acceptors. Most drugs have a logP value around 3, and the logP values of the PDB ligands accumulate around the negative value -1. Approximately the same fraction of PDB ligands and drugs are "drug-like" according to the Lipinski "Rule of five" [17]: 92 and 91%, respectively, have a logP value less than 5, although altogether the logP values of the drugs are closer to this critical value. A majority of the PDB ligands have very low molecular weights in comparison to the drugs, which supposedly is be caused by the fact that in proteins often very small solvent molecules are bound. Nevertheless, slightly more (5%) drugs than PDB ligands fulfil the Lipinski "Rule of five" regarding the molecular weight. The same applies for the numbers of hydrogen bond donors (and acceptors): 7% (5%) more drugs fulfil the Lipinski "Rule of five".
Compounds violating more than one of the Lipinski Rules are assumed to have problems with bioavailability and are therefore presumably not suitable as drugs. Table 1 shows the percentages of PDB ligands and drugs violating the Lipinski Rules. From this table can be seen that a total of approximately 19% of the PDB ligands and 10% of the drugs, respectively, violate more than one of the Lipinski Rules. This analysis reveals that there are only marginal differences between PDB ligands and drugs regarding single chemical properties. But, not surprisingly, from a general point of view, PDB ligands are significantly less drug-like than drugs.
Discussion
SuperLigands is a collection of PDB ligands freely accessible via a user-friendly web site. Molecular coordinates can be retrieved as MDL Mol files, supplementing the connectivity records contained in PDB files with bond types, which are necessary for modelling and simulation purposes. The database can be searched for compounds similar to a given ligand by comparison of Tanimoto coefficients. As stated in [15] and shown in the example in the section Utility, spatial comparison of small molecules can reveal more similarities, and thus similar kinds of interaction, than a pure two-dimensional topology comparison. With aid of SuperLigands, such three-dimensional comparisons can be performed easily. Moreover, the topological similarity of PDB ligand structures to known drugs can be assessed by calculation of Tanimoto coefficients.
Conclusion
The database presented here supplements the set of existing resources of information about small molecules bound to PDB structures. As novel features, three-dimensional comparison of molecules as well as topology comparison of PDB ligands with known drugs are made possible. Thus, SuperLigands represents a valuable means of analysis and prediction in the field of biological and medical research.
Availability and requirements
The database is publicly accessible at . For visualisation, the free browser plug-in MDL® Chime is required. Chime runs on Windows systems with Microsoft Internet Explorer (6.0 or 5.5 SP2) or Netscape 4.75, 4.79 or on Mac OS 9.0 or 8.6 with Netscape 4.75 (please see for detailed information).
Authors' contributions
EM designed the database and the web site and finished its functionality, was responsible for data acquisition and processing and drafted the manuscript. MD delivered the basic part of the website functionality and contributed to database conception and data processing. AG provided the tool for three-dimensional superposition and helped to draft the manuscript. RP conceived of the project, and participated in its design and coordination and helped to draft the manuscript. All authors read and approved the final manuscript.
Acknowledgements
This work was supported by the BMBF (German Federal Ministry of Education and Research).
Figures and Tables
Figure 1 Usage of the web interface of SuperLigands. From the main menu, the form Compound search can be reached. Here, a PDB ligand can be searched after hetero-ID, name, molecular formula or PDB identifier. In the first column of the results table, two buttons can be found to retrieve more information. The FULL info button delivers detailed information about the selected PDB ligand like molecular formula, atom numbers and occurrence in the PDB. After clicking the DRUGS button, a two-dimensional similarity search among the drugs in the SuperDrug database [16] is performed. The best hits are displayed in a new window. From here, they can be spatially superposed. In the figure, this procedure was carried out for celecoxib, a COX-2 inhibitor which was recently categorised as problematic (see the "Pfizer Statement on New Information Regarding Cardiovascular Safety of Celebrex" [18]). The two-dimensional similarity search in the SuperDrug database delivers only hits below 72% Tanimoto similarity. A following spatial superposition of the best hits reveals a further COX-2 inhibitor, namely valdecoxib, (RMSD 0.26Å and 21 of 22 atoms superposed) as very similar to celecoxib. The Tanimoto similarity of celecoxib and valdecoxib is only 65% and there are two drugs more similar to celecoxib: Sulfaphenazole (71% Tanimoto similarity, spatial superposition with 0.65Å RMSD and 15 of 22 atoms superposed) and Sulfamazone (67% Tanimoto similarity, spatial superposition with 0.32Å RMSD and 17 of 26 atoms superposed). Nevertheless, the three-dimensional comparison here proves to be very important to reveal molecular similarities in addition to topological comparison (as also shown in the example in the section Utility), which is confirmed by the fact that valdecoxib was categorised as toxic [19] and sales of this drug were suspended recently [20].
Figure 2 Statistics: comparison of PDB ligands with drugs. Chemical properties of 5040 PDB ligands and 2396 drug molecules are compared: histograms for numbers of hydrogen bond donors and acceptors, logP value and molecular weight are shown. Molecular weight within [100,200) means that the molecular weight is greater than or equal to 100 and less than 200. Those areas for which the Lipinski "Rule of 5" is fulfilled, are highlighted in grey.
Table 1 Percentage of PDB ligands and drugs violating certain numbers of Lipinski Rules
Number of violated Lipinski Rules PDB ligands Drugs
0 64.4 75.7
1 16.9 14.0
2 10.3 5.7
3 8.3 4.7
4 0.1 0.0
==== Refs
Evers A Gohlke H Klebe G Ligand-supported Homology Modelling of Protein Binding-sites using Knowledge-based Potentials J Mol Biol 2003 334 327 345 14607122 10.1016/j.jmb.2003.09.032
Berman HM Westbrook J Feng Z Gilliland G Bhat TN Weissig H Shindyalov IN Bourne PE The Protein Data Bank Nucleic Acids Res 2000 28 235 242 10592235 10.1093/nar/28.1.235
Feng Z Chen L Maddula H Akcan O Oughtred R Berman HM Westbrook J Ligand Depot: a data warehouse for ligands bound to macromolecules Bioinformatics 2004 20 2153 2155 15059838 10.1093/bioinformatics/bth214
Boutselakis H Dimitropoulos D Fillon J Golovin A Henrick K Hussain A Ionides J John M Keller PA Krissinel E McNeil P Naim A Newman R Oldfield T Pineda J Rachedi A Copeland J Sitnov A Sobhany S Suarez-Uruena A Swaminathan J Tagari M Tate J Tromm S Velankar S Vranken W E-MSD: the European Bioinformatics Institute Macromolecular Structure Database Nucleic Acids Res 2003 31 458 462 12520052 10.1093/nar/gkg065
Hendlich M Bergner A Gunther J Klebe G Relibase: design and development of a database for comprehensive analysis of protein-ligand interactions J Mol Biol 2003 326 607 620 12559926 10.1016/S0022-2836(02)01408-0
Stuart AC Ilyin VA Sali A LigBase: a database of families of aligned ligand binding sites in known protein sequences and structures Bioinformatics 2002 18 200 201 11836232 10.1093/bioinformatics/18.1.200
Kleywegt GJ Jones TA Databases in protein crystallography Acta Cryst D Biol Cryst 1998 54 1119 1131 10.1107/S0907444998007100
Laskowski RA PDBsum: summaries and analyses of PDB structures Nucleic Acids Res 2001 29 221 222 11125097 10.1093/nar/29.1.221
Reichert J Sühnel J The IMB Jena Image Library of Biological Macromolecules: 2002 update Nucleic Acids Res 2002 30 253 254 11752308 10.1093/nar/30.1.253
Paul N Kellenberger E Bret G Müller P Rognan D Recovering the True Targets of Specific Ligands by Virtual Screening of the Protein Data Bank Proteins 2004 54 671 680 14997563 10.1002/prot.10625
Puvanendrampillai D Mitchell JBO Protein Ligand Database (PLD): additional understanding of the nature and specificity of protein-ligand complexes Bioinformatics 2003 19 1856 1857 14512362 10.1093/bioinformatics/btg243
Roche O Kiyama R Brooks CL Ligand-protein database: linking protein-ligand complex structures to binding data J Med Chem 2001 44 3592 3598 11606123 10.1021/jm000467k
Wang R Fang X Lu Y Wang S The PDBbind Database: Collection of Binding Affinities for Protein-Ligand Complexes with Known Three-Dimensional Structures J Med Chem 2004 47 2977 2980 15163179 10.1021/jm030580l
Durant JL Leland BA Henry DR Nourse JG Reoptimization of MDL keys for use in drug discovery J Chem Inf Comput Sci 2002 42 1273 1280 12444722 10.1021/ci010132r
Thimm M Goede A Hougardy S Preissner R Comparison of 2D Similarity and 3D Superposition. Application to Searching a Conformational Drug Database J Chem Inf Comput Sci 2004 44 1816 1822 15446841 10.1021/ci049920h
Goede A Dunkel M Mester N Frommel C Preissner R SuperDrug: a conformational drug database Bioinformatics Advance Access published February 2, 2005, PMID: 15691861.
Lipinski CA Lombardo F Dominy BW Feeney PJ Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings Adv Drug Deliv Rev 2001 46 3 26 11259830 10.1016/S0169-409X(00)00129-0
Pfizer Statement on New Information Regarding Cardiovascular Safety of Celebrex
Ray WA Griffin MR Stein CM Cardiovascular toxicity of valdecoxib N Engl J Med 2004 351 2767 15608086 10.1056/NEJMc045711
Pfizer Statement on Status of Bextra
The Protein Data Bank
Ligand Depot
The Macromolecular Structure Database
Relibase
LigBase
HIC-Up, the Hetero-compound Information Centre - Uppsala
PDBsum
The IMB Jena Image Library of Biological Macromolecules
PLD
Ligand-protein database
The PDBbind Database
SuperDrug Database
| 15943884 | PMC1173082 | CC BY | 2021-01-04 16:02:50 | no | BMC Bioinformatics. 2005 May 19; 6:122 | utf-8 | BMC Bioinformatics | 2,005 | 10.1186/1471-2105-6-122 | oa_comm |
==== Front
BMC BioinformaticsBMC Bioinformatics1471-2105BioMed Central London 1471-2105-6-1241591068110.1186/1471-2105-6-124SoftwarearrayCGHbase: an analysis platform for comparative genomic hybridization microarrays Menten Björn [email protected] Filip [email protected] Preter Katleen [email protected] Piet [email protected] Evi [email protected] Karen [email protected] Geert [email protected] Paepe Anne [email protected] Vooren Steven [email protected] Joris [email protected] Yves [email protected] Moor Bart [email protected] Stefan [email protected] Frank [email protected] Jo [email protected] Center for Medical Genetics, Ghent University Hospital, De Pintelaan 185, B-9000 Ghent, Belgium2 Department of Electrotechnical Engineering, Faculty of Applied Sciences, Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, B-3001 Heverlee, Belgium3 Center for Human Genetics, Leuven University Hospital, Herestraat 49, B-3000 Leuven, Belgium4 Hogeschool Gent, Vesalius Department of Health Care, Keramiekstraat 80, B-9000 Ghent, Belgium2005 23 5 2005 6 124 124 27 12 2004 23 5 2005 Copyright © 2005 Menten et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
The availability of the human genome sequence as well as the large number of physically accessible oligonucleotides, cDNA, and BAC clones across the entire genome has triggered and accelerated the use of several platforms for analysis of DNA copy number changes, amongst others microarray comparative genomic hybridization (arrayCGH). One of the challenges inherent to this new technology is the management and analysis of large numbers of data points generated in each individual experiment.
Results
We have developed arrayCGHbase, a comprehensive analysis platform for arrayCGH experiments consisting of a MIAME (Minimal Information About a Microarray Experiment) supportive database using MySQL underlying a data mining web tool, to store, analyze, interpret, compare, and visualize arrayCGH results in a uniform and user-friendly format. Following its flexible design, arrayCGHbase is compatible with all existing and forthcoming arrayCGH platforms. Data can be exported in a multitude of formats, including BED files to map copy number information on the genome using the Ensembl or UCSC genome browser.
Conclusion
ArrayCGHbase is a web based and platform independent arrayCGH data analysis tool, that allows users to access the analysis suite through the internet or a local intranet after installation on a private server. ArrayCGHbase is available at .
==== Body
Background
The introduction of a microarray based comparative genomic hybridization method (arrayCGH) in 1997 paved the way for higher resolution detection of DNA copy number aberrations [1]. ArrayCGH is founded on the same principles as metaphase CGH, but uses mapped reporters instead of whole chromosomes. One of the major challenges in arrayCGH studies remains the accessibility, management, and interpretation of the vast amount of data generated in single experiments, and parallel comparison of multiple experiments. Typically, these arrays contain 3,000 to 30,000 reporters, each of which has multiple biological annotations (chromosomal position, sequence information, gene name, biological and molecular function,...) as well as physical (grid layout) and quality control (sequence verification, FISH mapping information,...) annotations. In addition, the description of the DNA samples under investigation and the applied lab protocols should be easily accessible. For classical CGH, several commercial software packages are available to analyze and interpret the data of a CGH experiment. Also for arrayCGH there are a number of separate software systems that individually address some of the needs, such as databases for data storage (BASE [2]), applications for clustering and visualization of microarray data (seeGH [3], M-CGH [4], CGHAnalyzer [5], aCGH-smooth [6] and CGH-Miner [7]), public genome databases that contain reporter information, commercially available Laboratory Information Management Systems (LIMS), and various storage methods for recording biomaterial annotations. However, none of these software packages or databases combine all these features (see Supplemental Table). In this paper, we present the development of a web based open source arrayCGH analysis platform, arrayCGHbase, that combines all these features and on top provides additional unique aspects making the analysis and sharing of arrayCGH data easily implementable for both research and routine purposes.
Implementation
MIAME compliant database
arrayCGHbase runs in Windows, Linux, Macintosh, and Unix environments. Particular attention was paid to the use of open source software for the development of arrayCGHbase. The software was developed in the PHP scripting language, with all data being stored in a relational, MIAME [8] (Minimal Information About a Microarray Experiment) supportive, MySQL database and communicated to the user through an Apache Web server (Figure 1). After installation on a private server, experiments can be shared by different users over the internet or a local intranet. ArrayCGHbase integrates DNA sample information, lab protocols, extracted data, and contains a plug-in architecture for data transformation, analysis, and graphical display, allowing users to develop their own modules. Reporters can be directly linked to the Ensembl [9] or UCSC [10] genome browsers, providing additional up-to-date information on each reporter. Reporters can also be manually imported into the MySQL database with the ability to update all linked experiments. The structure of arrayCGHbase was designed to follow the laboratory workflow and is compatible with all types of arrayCGH experiments and data formats (dual colour genomic clone, cDNA [11], or oligonucleotide [12] arrays spotted on any substrate, physical layout, type of array, as well as single channel hybridizations such as the Affymetrix SNP chips [13]). With a personal account and administrated access levels, a user can enter new DNA samples, annotate these, and append all relevant sample information such as quantity, quality, and applied lab protocols at each step. Each user can group experiments together into projects and, in a uniform and streamlined fashion, apply filters and transformations and run analyses. Data is exportable in several formats for offline analysis using other (dedicated) software tools, for publication or for sharing data with the research community. For advanced users, an SQL query window allows interrogation of the underlying MySQL database.
Data processing and visualization routines
A first and important step in data analysis of arrayCGH experiments is the processing of large, possibly noisy data sets to identify the specific reporters that are differentially hybridized and hence show an aberrant copy number. Data processing is performed in a streamlined four-step manner: (1) the local noise or background associated with the experiments is removed, (2) the quality of the experiment is assessed and poor quality features are removed, (3) ratios are calculated, transformed to log2 scaled ratios, and normalized, and finally (4) reporters that show altered ratios are identified and hence, reporters with aberrant copy number are identified. In the past, this normally required the sequential processing of data by different, often incompatible programs. Using established and widely used microarray (CGH) data processing procedures, arrayCGHbase will automatically correct the signal intensities, filter out unwanted poor quality features (based on signal to noise ratio, image processing software related flags, or other user defined filters), normalize the fluorescence intensity ratios, score levels of differential hybridization, combine the results of replicate experiments and assess the quality of individual and replicate experiments. All these steps are user adjustable.
Input data and local background correction
The experimental input data for arrayCGHbase consists of export files generated by image analysis software. Currently, the program recognizes files from GenePix Pro versions 2.0–4.0, Scanalyze version 2.0, UCSF SPOT version 2.0, Imagene versions 4.0 – 5.5 and the Affymetrix Chromosome Copy Number Tool. The program can easily be updated for the recognition of other data input formats upon request. Moreover, arrayCGHbase has an interactive import wizard, which makes it possible to import data at your own desire. The processing steps may be changed by altering the parameters at the input stage. By default, the results for each feature are defined as the median foreground minus background intensities for each dye (as determined by the image processing software). The ratio of each feature is determined as the relative background corrected signal between the two dyes or in the case of single color experiments as the corrected signal intensity.
Poor quality flagging
Nearly every experiment contains features of poor quality, comprising features that have unusual morphology (e.g. doughnut patterns), exhibit uneven hybridization, or have saturated signal intensity. After background corrections, arrayCGHbase can automatically flag features of inferior quality using different criterions (e.g., the standard deviation between replicates), by a manually set signal or signal-to-noise threshold, or using image processing generated flag annotations.
Normalization
Following calculation of the corrected signal intensities and filtering for good quality features, the relative contributions of the fluorescence intensities are compared. To go from a multiplicative space to an additive space, ratios are log2 transformed. Ideally, the signals of the two dyes should be equal for nucleic acid reporters that have equal amounts in the test and reference samples (i.e., the log2 transformed ratios of the two corrected signals should approach zero for reporters hybridizing to an equal degree in both fluorescence channels). However, in practice the ratio of the corrected signal intensities deviates from the expected ratio due to the different molecular and physical characteristics of the dyes, the different amounts of DNA used for labeling with the different dyes, the spatial heterogeneity in the hybridization conditions across the slide, and many other factors. Normalization compensates these effects by applying a data transformation such that ratios of reporters with unchanged copy-number are close to zero. In the normalization step, an appropriate term is added or subtracted from the log2 transformed ratio for each feature. The program allows normalization in several ways, either by global normalization or subgrid (or pin) normalization, or by a combination of different normalization procedures.
A major issue in microarray normalization is the definition of the set of constant probes to which the data are normalized. The most widely accepted method employs the 'constant majority' method, which assumes that the majority of reporters do not change in ratio. This method, which is implemented in arrayCGHbase, is generally applicable to most experiments as it is valid even in cases where up to 50% of reporters have altered ratios, it does not require prior knowledge of which features remain constant, and allows for intensity and spatial variation. Hence, this method calculates a scaling term from the median of all ratios, excluding all outliers. In this way the distribution of all ratios is transformed so that it centers around zero.
Quality control
Percentage of good quality spots
This first quality assessment is a basic calculation of the number of reporters (or features) that are not flagged based on quality measures (user defined parameters and thresholds, see above).
Intra- and inter-array hybridization quality
Three other major quality parameters can be determined with arrayCGHbase for each experiment. The first assesses the variation between reporters present in replicates on the array (typically duplicates or triplicates). An increased variation typically reflects lower quality hybridizations resulting in less reliable ratios. A second quality parameter is the standard variation between the different reporters on the array that show a normal (unaltered) copy number. This quality measure is only applicable in experiments with few reporters with aberrant copy number. The third quality measure is the average ratio for reporters with aberrant copy number. This ratio should significantly differ from zero to allow identification of differentially hybridized reporters. This last quality measure is only applicable in experiments where DNA copy number aberrations are known or validated. These parameters provide an objective quality measure and can also be helpful to compare different experiments.
In addition to these parameters, different graphical displays, such as ratio-intensity plots (usually referred to as MA plots), dual channel intensity scatter plots, and ratio histograms give an idea of the quality of an individual experiment or series of experiments (Figure 2). In all these visualizations, thresholds for gains and losses are displayed and can be adjusted. The slide viewer generates a virtual spatial view of all features on the array using the ratio, or signal and background intensities; this viewer allows the identification of problematic regions or artifacts on the slide surface. Clicking on an individual feature shows specific data associated with this feature (e.g., reporter name, signal intensities, and data quality flags).
Scoring chromosomal regions with aberrant copy number
The final step in arrayCGH data processing is the identification of reporters that exhibit differential hybridization, corresponding to chromosomal regions that have altered copy number. The major issue is to identify those reporters whose relative ratios stand out from the experimental noise with sufficient statistical significance. arrayCGHbase currently incorporates two scoring methods. The most widely used approach is to define a ratio threshold and identify the probes that exhibit ratios greater or smaller than this threshold. Another, statistically more sound approach, is to use a floating threshold based on the standard deviation of all reporters in a given experiment. Reporters that exhibit ratios greater than this threshold will be defined as differential [14]. Both methods are implemented in arrayCGHbase and can be applied on each individual feature, or on the mean value of replicates. Besides the aberrant feature scoring methods, two other algorithms are available: a universal data smoothing algorithm, as well as a breakpoint-identification algorithm, which both consist of a moving window along the chromosomes and hence make use of the spatial "along the chromosome" distribution of the reporters. With these algorithms, chromosomal breakpoints can be easily identified in more noisy datasets. By writing custom plug-ins (in PHP or R), sophisticated algorithms that use segmentation methods (e.g. Cluster Along Chromosomes, CLAC [7]) or others, can be implemented by any user in a straightforward way.
Chromosome visualization
A wide variety of result viewers are available. The results can be mapped upon standard ISCN (International Standard on Cytogenetic Nomenclature) ideograms in an electronic karyotype, or visualized per chromosome or zoomed in on a region of interest (Figure 3). Moreover, various CGH profile views provide the user with a tool to compare different experiments and to identify regions with relevant copy number alterations. Views are returned to the user either as PNG (Portable Network Graphic) or as SVG (Scalable Vector Graphic) files, with the ability to scale images according to screen width.
Data export
Processed data can be exported as MIAME compliant text files and figures; these include the original feature signal and background intensities, the normalized ratio value, a list of reporters that are differentially hybridized, and the data quality parameters. Additionally, a file can be generated for submission of arrayCGH results directly into Progenetix [15], a comprehensive collection of published cytogenetic abnormalities in human neoplasms. Lastly, BED files can be created to map results and visualize the experiment from within the Ensembl or UCSC genome browser.
ArrayCGHbase at work
In several publications from our research group, arrayCGHbase has been successfully used to analyse arrayCGH data to identify and delineate copy number aberrations [16-19]).
At the demo site, users can explore the data published in Hellemans et al. [16], a small ~5 Mb deletion in chromosome 12q identified using SNP chips), the results of a case report of the identification of an unbalanced X-autosome translocation by arrayCGH in a boy with a syndromic form of chondrodysplasia punctata brachytelephalangic type [17], a distal 9p trisomy and distal Xp nullisomy caused by an unbalanced X;9 translocation: 46, Y, der(X)t(X;9)(p22.32;p23) detected with a 1 Mb BAC array), and the copy number profile of a cancer cell line NGP.1A.TR [18]). It is possible to look at the raw data of these hybridizations and more importantly, test the performance of the program using different settings.
Conclusion
We present arrayCGHbase, a versatile web based, platform independent data storage and analysis tool for processing microarray CGH data. Routines were implemented for feature flagging, data normalization, data quality assessment and the identification of chromosomal regions with aberrant copy number. A zoomable graphical interface allows immediate identification of altered genomic regions and the underlying gene content by several database links. A multitude of export functions allow the user to further process the results. The easy plug-in architecture makes it possible for each user to add custom algorithms for data analysis and visualization and share these with the user community. This webtool and database will enable investigators to interpret single experiments and compare large data sets efficiently throughout different array platforms and provides all of the essential features and links for further investigation of the genomic regions of interest.
Future developments
arrayCGHbase will continually be updated to incorporate new processing methods that will be developed both within and outside our laboratory. Immediate plans include the addition of export and import functions to R [20] or Bioconductor [21] to be able to apply several available mathematical algorithms such as two-dimensional LOWESS normalization [22]. Immediate export functions to the DECIPHER web site [23] to link phenotypical data to actual experiments will also be included. The arrayCGHbase source code is freely available under a Creative Commons License, to encourage others to develop new analysis methods and utilities that will further improve its capabilities.
Availability and requirements
An arrayCGHbase demo site is available at . At this site, all quality control features and other features can be tested for several experiments with BAC arrays as well as SNP chips (see 'arrayCGHbase at work'). At the same site, the complete package can be freely downloaded for local installation on a private hosted web server. For local use, additional software is required such as the MySQL database [24], a web server (e.g. Apache [25]), and PHP hypertext preprocessor [26]. These software packages are freely available and are key parts of LAMP (Linux, Apache, MySQL, PHP), an open source web platform. Enquiries for arrayCGHbase should be made to [email protected].
Glossary
Reporter: any DNA fragment (BAC, PAC, cosmid, fosmid, cDNA clone, oligonucleotide, genomic PCR product) used for hybridization
Feature: physical reporter spotted, printed, or otherwise linked to a substrate at a specific location
PHP: Hypertext PreProcessor (server-side scripting language)
MIAME: Minimal Information About a Microarray Experiment
MySQL: My Structured Query Language
ISCN: International System for human Cytogenetic Nomenclature
BED: Browser Extendable Data
Authors' contributions
BM was the principle programmer of arrayCGHbase. FP, KDP, PR and SVV contributed ideas for different features and display requirements. JV oversaw the project; all other authors have reviewed the manuscript and FS and JV were the final editors of the manuscript.
Supplementary Material
Additional File 1
Comparison between different already available arrayCGH software programs and arrayCGHbase for the analysis and visualization of arrayCGH data.
Click here for file
Acknowledgements
Jo Vandesompele and Katleen De Preter are supported by a grant from the Flemish Institute for the Promotion of Innovation by Science and Technology in Flanders (IWT). Filip Pattyn is a Research Assistant of the Research Foundation – Flanders (FWO – Vlaanderen). This study is supported by GOA-grant 12051203, FWO-grant G.0185.04, G.0200.03 and G.0106.05 and VEO project 011V1302, research grant of Kinderkankerfonds vzw (a non-profit childhood cancer foundation under Belgian law).
This text presents research results of the Belgian program of Interuniversity Poles of attraction initiated by the Belgian State, Prime Minister's Office, Science Policy Programming (IUAP).
Figures and Tables
Figure 1 arrayCGHbase scheme. The data is stored in a MIAME supportive MySQL database (red) and reporter info is updated using the NCBI, Ensembl and UCSC genome database. Data and results are presented to the user through a web browser via the PHP scripting language. Data-normalization and other analysis or result visualization methods can be integrated using the plug-in architecture. Further data processing using the R statistical scripting language will be implemented in the near future. Results can be exported to a Progenetix or MIAME compatible format, or visualized on the genome using the Ensemble or UCSC genome browser.
Figure 2 Quality control graphs. Graphical displays to assess the quality of an experiment, such as a dual channel intensity scatter plot, ratio histogram, ratio-intensity plot and a virtual slide view.
Figure 3 Selected result viewers. Graphical displays of arrayCGH results of neuroblastoma cell line NGP.1A.TR1: line view (all reporters ordered by chromosome and chromosomal position on one line), karyo view (al reporters mapped on their chromosomal position on a standard ISCN ideogram), chromosome view (zoom on one chromosome or chromosomal region) with breakpoint identification algorithm, and genome browser view (neuroblastoma cell line IMR32), with all reporters and their copy number status displayed in the UCSC genome browser.
==== Refs
Solinas-Toldo S Lampel S Stilgenbauer S Nickolenko J Benner A Dohner H Cremer T Lichter P Matrix-based comparative genomic hybridization: biochips to screen for genomic imbalances Genes Chromosomes Cancer 1997 20 399 407 9408757 10.1002/(SICI)1098-2264(199712)20:4<399::AID-GCC12>3.0.CO;2-I
Saal LH Troein C Vallon-Christersson J Gruvberger S Borg A Peterson C BioArray Software Environment (BASE): a platform for comprehensive management and analysis of microarray data Genome Biol 2002 3 SOFTWARE0003 12186655 10.1186/gb-2002-3-8-software0003
Chi B DeLeeuw RJ Coe BP MacAulay C Lam WL SeeGH--a software tool for visualization of whole genome array comparative genomic hybridization data BMC Bioinformatics 2004 5 13 15040819 10.1186/1471-2105-5-13
Wang J Meza-Zepeda LA Kresse SH Myklebost O M-CGH: analysing microarray-based CGH experiments BMC Bioinformatics 2004 5 74 15189572 10.1186/1471-2105-5-74
Greshock J Naylor TL Margolin A Diskin S Cleaver SH Futreal PA deJong PJ Zhao S Liebman M Weber BL 1-Mb resolution array-based comparative genomic hybridization using a BAC clone set optimized for cancer gene analysis Genome Res 2004 14 179 187 14672980 10.1101/gr.1847304
Jong K Marchiori E Meijer G Van Der Vaart A Ylstra B Breakpoint identification and smoothing of array comparative genomic hybridization data Bioinformatics 2004
Wang P Kim Y Pollack J Narasimhan B Tibshirani R A method for calling gains and losses in array CGH data Biostatistics 2005 6 45 58 15618527 10.1093/biostatistics/kxh017
Brazma A Hingamp P Quackenbush J Sherlock G Spellman P Stoeckert C Aach J Ansorge W Ball CA Causton HC Gaasterland T Glenisson P Holstege FC Kim IF Markowitz V Matese JC Parkinson H Robinson A Sarkans U Schulze-Kremer S Stewart J Taylor R Vilo J Vingron M Minimum information about a microarray experiment (MIAME)-toward standards for microarray data Nat Genet 2001 29 365 371 11726920 10.1038/ng1201-365
Butler D Ensembl gets a Wellcome boost Nature 2000 406 333 10935602 10.1038/35019198
Karolchik D Baertsch R Diekhans M Furey TS Hinrichs A Lu YT Roskin KM Schwartz M Sugnet CW Thomas DJ Weber RJ Haussler D Kent WJ The UCSC Genome Browser Database Nucleic Acids Res 2003 31 51 54 12519945 10.1093/nar/gkg129
Pollack JR Perou CM Alizadeh AA Eisen MB Pergamenschikov A Williams CF Jeffrey SS Botstein D Brown PO Genome-wide analysis of DNA copy-number changes using cDNA microarrays Nat Genet 1999 23 41 46 10471496 10.1038/14385
Lucito R Healy J Alexander J Reiner A Esposito D Chi M Rodgers L Brady A Sebat J Troge J West JA Rostan S Nguyen KC Powers S Ye KQ Olshen A Venkatraman E Norton L Wigler M Representational oligonucleotide microarray analysis: a high-resolution method to detect genome copy number variation Genome Res 2003 13 2291 2305 12975311 10.1101/gr.1349003
Kennedy GC Matsuzaki H Dong S Liu WM Huang J Liu G Su X Cao M Chen W Zhang J Liu W Yang G Di X Ryder T He Z Surti U Phillips MS Boyce-Jacino MT Fodor SP Jones KW Large-scale genotyping of complex DNA Nat Biotechnol 2003 21 1233 1237 12960966 10.1038/nbt869
Vermeesch JR Melotte C Froyen G Van Vooren S Dutta B Maas N Vermeulen S Menten B Speleman F De Moor B Van Hummelen P Marynen P Fryns JP Devriendt K Molecular karyotyping: array CGH quality criteria for constitutional genetic diagnosis J Histochem Cytochem 2005 53 413 22 15750031 10.1369/jhc.4A6436.2005
Baudis M Cleary ML Progenetix.net: an online repository for molecular cytogenetic aberration data Bioinformatics 2001 17 1228 1229 11751233 10.1093/bioinformatics/17.12.1228
Hellemans J Preobrazhenska O Willaert A Debeer P Verdonk PC Costa T Janssens K Menten B Van Roy N Vermeulen SJ Savarirayan R Van Hul W Vanhoenacker F Huylebroeck D De Paepe A Naeyaert JM Vandesompele J Speleman F Verschueren K Coucke PJ Mortier GR Loss-of-function mutations in LEMD3 result in osteopoikilosis, Buschke-Ollendorff syndrome and melorheostosis Nat Genet 2004 36 1213 1218 15489854 10.1038/ng1453
Menten B Buysse K Vandesompele J De Smet E De Paepe A Speleman F Mortier G Identification of an unbalanced X-autosome translocation by array-CGH in a boy with a syndromic form of chondrodysplasia punctata brachytelephalangic type European Journal of Medical Genetics
De Preter K Vandesompele J Menten B Fiegler H Edsjo A Carter N Yigit N Waelput W Van Roy N Bader S Pahlman S Speleman F Positional and functional mapping of a neuroblastoma differentiation gene on chromosome 11 submitted
Van Roy N Vandesompele J Menten B Nilsson H De Smet E Rocchi M De Paepe A Påhlman S Speleman F Translocation-excision-deletion-amplification mechanism leading to non-syntenic co-amplification of MYC and ATBF1 submitted
The R Project for Statistical Computing [http://www.r-project.org/]
Gentleman RC Carey VJ Bates DM Bolstad B Dettling M Dudoit S Ellis B Gautier L Ge Y Gentry J Hornik K Hothorn T Huber W Iacus S Irizarry R Leisch F Li C Maechler M Rossini AJ Sawitzki G Smith C Smyth G Tierney L Yang JY Zhang J Bioconductor: open software development for computational biology and bioinformatics Genome Biol 2004 5 R80 15461798 10.1186/gb-2004-5-10-r80
Cleveland WS Devlin SJ Locally-Weighted Regression: An Approach to Regression Analysis by Local Fitting. Journal of the American Statistical Association 1988 83 596 610
Decipher [http://www.sanger.ac.uk/PostGenomics/decipher/]
MySQL [http://www.mysql.com/]
Apache HTTP Server Project
PHP Hypertext Preprocessor
| 15910681 | PMC1173083 | CC BY | 2021-01-04 16:02:51 | no | BMC Bioinformatics. 2005 May 23; 6:124 | utf-8 | BMC Bioinformatics | 2,005 | 10.1186/1471-2105-6-124 | oa_comm |
==== Front
BMC BioinformaticsBMC Bioinformatics1471-2105BioMed Central London 1471-2105-6-1261591890610.1186/1471-2105-6-126Research ArticleComparative analysis of chromatin landscape in regulatory regions of human housekeeping and tissue specific genes Ganapathi Mythily [email protected] Pragya [email protected] Sushanta Kumar Das [email protected] Kaushal [email protected] Dipayan [email protected] Singh Gajinder [email protected] Vani [email protected] Samir K [email protected] Dr. B. R. Ambedkar Centre for Biomedical Research, University of Delhi, Delhi-110007, India2 Institute of Genomics and Integrative Biology (CSIR), Mall Road, Delhi -110007, India2005 26 5 2005 6 126 126 17 11 2004 26 5 2005 Copyright © 2005 Ganapathi et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Global regulatory mechanisms involving chromatin assembly and remodelling in the promoter regions of genes is implicated in eukaryotic transcription control especially for genes subjected to spatial and temporal regulation. The potential to utilise global regulatory mechanisms for controlling gene expression might depend upon the architecture of the chromatin in and around the gene. In-silico analysis can yield important insights into this aspect, facilitating comparison of two or more classes of genes comprising of a large number of genes within each group.
Results
In the present study, we carried out a comparative analysis of chromatin characteristics in terms of the scaffold/matrix attachment regions, nucleosome formation potential and the occurrence of repetitive sequences, in the upstream regulatory regions of housekeeping and tissue specific genes. Our data show that putative scaffold/matrix attachment regions are more abundant and nucleosome formation potential is higher in the 5' regions of tissue specific genes as compared to the housekeeping genes.
Conclusion
The differences in the chromatin features between the two groups of genes indicate the involvement of chromatin organisation in the control of gene expression. The presence of global regulatory mechanisms mediated through chromatin organisation can decrease the burden of invoking gene specific regulators for maintenance of the active/silenced state of gene expression. This could partially explain the lower number of genes estimated in the human genome.
==== Body
Background
Eukaryotic gene transcription is largely known to be orchestrated by protein factors like activators, co-activators and co-repressors [1]. However, nucleosomal organisation, non-passive structural scaffolds and global structure of chromatin are increasingly being recognised as major players in the regulation of gene expression. The ability of sequences to position nucleosomes and to be anchored to the nuclear matrix to provide a spatial context for regulation of expression are measurable parameters that may influence the interactions with transcription machinery [2,3]. This level of regulation may be distinctly different for genes whose expression is constitutive in comparison to genes that exhibit tissue specific expression. The latter would demand an open chromatin configuration in certain tissues and repressive organisation in others. In this study, we examined whether the potential to utilise global regulatory mechanisms to control gene expression through chromatin organisation varies between housekeeping and tissue specific genes (Hkg and Tsg respectively) by virtue of their organisation. An in-silico comparison of chromatin related organisational differences in the 5' and 3' regulatory regions of housekeeping and tissue specific genes was carried out to shed light in this direction.
Results and discussion
Chromatin landscape of a region plays a major role in determining and modulating the expression status of its neighbouring genes [4]. The role played by chromatin in the 5' regulatory regions of genes in transcriptional regulation has been extensively studied [5,6]. In the present study, we have taken 2 distinct sets of genes differing predominantly in their spatial expression aspect, namely, housekeeping and tissue specific, to understand the various attributes of the regulatory role played by chromatin organisation in the 5' region.
Analysis of scaffold/matrix associated sequences
Scaffold/matrix attachment regions (S/MARs) are defined as sequences, which can attach themselves to the nuclear matrix and hence help in the formation of independent chromatin loops [7]. Transcriptional regulation of gene expression is known to involve formation of dynamic chromatin loops mediated by S/MAR attachment to the nuclear matrix [3]. The attachment of a DNA sequence to the matrix will place the neighbouring genes in proximity of the transcription factors. The abundance of S/MARs in the 5' cis-regulatory regions of genes further demonstrates their role in transcriptional regulation [8]. We have analysed the predicted S/MAR sites in the 5' and 3' flanking regions of human Hkg and Tsg (Table 1). We used MAR Finder (new version) and ChrClass programs for predicting S/MAR binding sites in the sequences (Table 1). Glazko et al have classified 5' flanking regions up to 1500 bp of human tissue specific genes as an out-group, assuming that these regions have no significant association with S/MAR binding [7]. On the contrary, our study reveals that S/MAR binding sequences are enriched in 5' regulatory regions of Tsg in comparison to the Hkg. The common predictions of both the programs were taken for the analysis. This data indicates a significant enrichment of S/MAR binding sequences in the 5' flanking regions of Tsg and depletion of S/MARs in the 3' Hkg regions as compared to Tsg. Chi-square test was applied for both 5' and 3' region S/MAR predictions of Hkg and Tsg, to ascertain whether the distributions are significantly different. The chi-square value of 11.37 (df = 1) and P-value ≤ 0.001 obtained for the distribution of S/MARs in 5' regions of Hkg and Tsg indicate a significant difference in the distribution of S/MAR elements between the two sets. Similarly, for the distribution of S/MARs in 3' regions of Hkg and Tsg the chi-square value of 5.033 (df = 1) and P-value of ≤ 0.025 show that the Hkg 3' regions are significantly depleted of S/MARs as compared to Tsg.
The observation that the 5' regulatory regions of Hkg are less enriched in S/MARs in comparison with Tsg might be related to the distribution of housekeeping genes in the genome. Housekeeping genes cluster in chromosomes and therefore, they often would be present in distinct chromatin domains along with housekeeping genes that have a co-ordinated expression [9,10]. The data showing preferential absence of S/MARs in the 3' regions in Hkg further lend support to this hypothesis. On the other hand, tissue specific genes are known to be dispersed in gene dense as well as heterochromatic regions [9,11]. It may be necessary for them to shield themselves against the effects of positive and negative cis-acting elements of adjacent regions in order to maintain tissue specific expression profile. In this context, the boundary elements or the insulator model has been proposed earlier [11]. S/MARs function as boundary elements and their co-localisation with insulators such as the Drosophila gypsy element is also reported [12,13]. They also function as boundary elements in in vitro systems by shielding away the position effect [14]. Some earlier reports have suggested a role for S/MARs in maintaining tissue specific gene expression [15]. More recently, the 5'-HS4 chicken-globin insulator is known to have a CTCF protein binding dependent matrix association [16]. Hence, the over representation of S/MARs seen in Tsg set might possibly be associated with a boundary element function.
Our results on the prediction performance of the programs have been quite different from the previous reports [7]. We find that MAR Finder (an under predictor) predicts more number of S/MAR regions in our dataset in comparison to ChrClass program (an over predictor) [7]. This may be attributed to the use of the advanced version of MAR Finder in our study wherein, new parameters/features have been added in the form of the "New MAR Rules" option.
Analysis of nucleosomal organisation
The primary template for local and global changes in the chromatin structure of a chromosome is the nucleosomal unit [4]. Chromatin structure and nucleosomal organisation over the promoter regions play a major role in regulation of expression of downstream gene(s) [6,17]. The nucleosome distribution would depend upon the occurrence of nucleosome destabilising elements as well as nucleosome forming sequences. We have analysed both these parameters in our study.
Nucleosome destabilising elements
Nucleosome destabilising/excluding elements such as poly (dA.dT) and (CCGNN)n in promoter regions have been implicated in maintaining constitutive gene expression [18-21]. At the functional level, it is known that poly (dA.dT) elements increase the accessibility of promoters of HIS3, URA3 and Ilv1 in yeast to the cognate transcription factor [18]. With the increasing length of poly (dA.dT) repeat, the availability of the sequences to transcription factors improves and similarly, with increasing lengths, the propensity to exclude nucleosomes increases for (CCGNN)n sequence motif as demonstrated in yeast and mammalian systems [19-21]. It has been demonstrated that (CCGNN)n sequences promote meiotic recombination and activated HIS4 expression by generating open chromatin [22].
We hypothesised that the differential distribution of nucleosome exclusion elements might be one of the mechanisms involved in maintaining distinct nucleosomal organisation of the housekeeping and tissue specific genes. The frequency of pure poly (dA.dT) stretches >10 bp and (CCGNN)2–5 in the 2000 bp 5' cis-regulatory regions of human Hkg and Tsg(s) were analysed. A significant enrichment of poly (dA.dT) elements in the upstream regions of Hkg is seen in comparison to Tsg (Table 2). The t-test for the difference in distribution of poly (dA.dT) stretches (>10 bp) between Hkg and Tsg show significant P-values in the different lengths of the stretches examined.
In Hkg, 670 repeats of (CCGNN)2–5 were detected as against 430 in Tsg. (CCGNN)2 was the most prevalent repeat unit and uninterrupted repeat units (>5 mers) were not found in the sequence sets. Although shorter repeat units (2–5 mers) have not been studied for nucleosome exclusion, they might play a role in destabilising the histone octamer [20]. Further, many of them form a part of longer interrupted stretches. The t-test for difference in distribution of (CCGNN)2–5 between Hkg and Tsg shows a significant P-value of 1.71E-06.
Nucleosome formation potential scores and expression level of genes
Using Recon, Levitsky et al (2001) have examined the nucleosome formation potential of 3 classes of human genes namely, Hkg, Tsg and widely expressed genes that differ in their spatial expression status [2]. Their report, based on a small sample size of around 200 genes shows the difference in the nucleosome formation potential between these 3 classes of genes in the upstream 50 bp from the transcription start site. In this study, we examined the nucleosome formation potential values in upstream 2000 bp of 5' regions of Hkg and Tsg and their correlation with gene expression levels with the complete set of 1083 genes.
The Tsg and Hkg sequences show a considerable difference in their nucleosome formation potential scores over an extended upstream region of 2000 bp (Figures 1 and 2). The Tsg region is enriched in nucleosome formation potential scores (peak at 1) in all upstream positions analysed (till 2000 bp). For Hkg, the distribution seems to be shifted towards the negative scores at 400 bp region and this shift diminishes gradually as we move further upstream to finally peak at 1 in 2000 bp upstream region (Figure 1). t-test was applied to ascertain the difference in distribution of Recon scores between Hkg and Tsg (Table 3). The resultant P-values in various intervals of relevance (0.8 to 1, 1 to 1.2, -0.8 to -1 and -1 to -1.2) reflect that the scores in the upstream 400 bp from the gene start site show the maximum difference in all the intervals and at 2000 bp, the difference gradually fades away in intervals 0.8 to 1 and 1 to 1.2 (Table 3).
A correlation analysis between nucleosome formation potential and expression levels was carried out considering the Recon scores at upstream 400bp region, where the P-values reflect the largest difference and the log10 values of expression levels were taken as inputs ["see Additional file 1"]. Initially, we analysed the gross dependence of total expression levels on nucleosome potential in the upstream regions of the two sets of genes (Table 4). In all the four intervals, no correlation is seen, indicating that chromatin plays an insignificant role in global modulation of levels of expression in these two sets of genes. These results are similar to that observed in case of Saccharomyces cerevisae whole genome analysis (unpublished results).
Further, we refined the analysis to examine the correlation, if any, between nucleosome formation potential in upstream regions and extreme expression levels of genes. The Hkg and Tsg groups were further categorised separately into high and low expression level groups as described under "Methods" section and their correlation with the nucleosome formation potential was analysed (Table 5). The high and low expression genes of Hkg show a low negative correlation with scores in intervals 0.8 to 1.0 and 1 to 1.2 and a low positive correlation with scores in intervals -1.2 to -1 and -1.0 to -0.8. In Tsg, except in one interval, there was no valid correlation seen. This solitary value was not considered since the correlation coefficients in other intervals didn't reflect this trend.
Our data restates that chromatin in 5' region plays a major role in determining the ubiquitous or restricted tissue expression of a gene as shown by Levitsky et al (2001) [2]. The abundance of nucleosome exclusion elements in Hkg 5' regions and the low Recon scores reflect their poor preference for nucleosome assembly. The expression analysis suggests that although chromatin plays a role in bringing about extreme variations of gene expression levels in certain classes of genes such as the housekeeping genes, the relation is not linearly correlated with the total, wider range of expression levels. It is possible that nucleosomes might be involved in fine-tuning of expression levels that may escape our attention, since the difference in the range of expression considered is fairly large. The difference detected in nucleosome formation potential between the two sets might reflect the accessibility to basal transcription factors for Hkg and gene/tissue specific transcription factors for Tsg, considering the difference in spatial and temporal expression patterns of the two groups.
Analysis of repetitive sequences
Repetitive sequences are implicated in chromatin organisation and heterochromatinisation [23-25]. They are differentially enriched in various functional categories of genes and are predicted to play an important role in gene regulation [24,26]. We analysed the distribution of various repeat classes in the 5' regions of Hkg and Tsg using RepeatMasker software. The total repeat content in Hkg regions is seen to be more than in Tsg regions. As reported earlier, our data shows enrichment of SINES (Alu) in comparison to other classes of repetitive sequences in both the sets [24]. Further, the 5' sequences of Hkg are more enriched in Alu sequences in comparison to those of Tsg regions (Table 6). The difference in the distribution of Alu repeats in the two classes of sequences was determined by applying t-test for the number of repeats and the repeat content in terms of length in base pairs in each sequence set (Table 7). The low total repeat content seen in Tsg upstream regions lends support to the hypothesis that condensed chromatin disfavours transposable element insertions in comparison to open chromatin (Hkg promoters)[27].
Genes with high expression levels are clustered in genomic regions known as ridges. These gene rich regions also have high (G+C) content, SINES and genes with short introns [9]. Eisenberg and Levanon [28] have reported the presence of significantly shorter introns and an overall compact gene structure in Hkg as compared to non-Hkg [28]. We have used the gene list provided by Eisenberg and Levanon [28] for our analysis. The enrichment of SINES in the 5' regions of Hkg suggests that Hkg might be localised in the ridge regions of the genome. More recently, it has been suggested that the contrasting attributes of gene compactness, GC content and the length of the intronic and intergenic sequences in Hkg and Tsg might be involved in chromatin mediated regulation for maintaining distinct expression patterns in the gene sets [29]. Recently, Alu elements have been shown to house transcription factor binding sites and the presence of such regulatory elements might influence the chromatin structure and gene expression [30].
The paradigm for regulation of gene expression in human tissues has shifted the focus from involvement of a battery of transcription regulators to global regulatory mechanisms [31]. These mechanisms have also gained significance in the context of the low estimates of gene numbers in the human genome [32]. It is in this framework that we have analysed the chromatin characteristics of two groups of genes, one that needs almost a continuous and ubiquitous expression and another demanding tissue specific regulation. It had been predicted that the nucleosomal density in a chromatin domain and the buffering of supercoiling waves by repetitive DNA will play a major role in establishing coordinated gene regulation in a domain in the context of the relevance of maintenance of repetitive sequences during evolution [[25,33], and [34]]. A recent report also infers the role of chromatin-mediated mechanisms in the differential gene expression patterns seen in housekeeping and tissue specific genes [29]. Our data and analyses lend support to these hypotheses (Figure 3). Another recent report, which addresses the chromatin architecture of the human genome, provides experimental evidence that open chromatin correlates with high gene density regions but not with gene expression [35]. This data further supports our in-silico observations and strengthens the domain concept for concerted expression of clustered genes. The role of nucleosome formation potential is apparent from the present analysis in both the housekeeping genes as well as tissue specific genes but with an opposing correlation. Housekeeping genes apparently discourage nucleosome formation to match their expression profile in space and time by ensuring accessibility to transcription machinery. In addition, they also show a significant enrichment in poly (dA.dT) stretches, which are known to destabilise nucleosomes. On the other hand, the tissue specific genes show higher scores for nucleosome formation potential through which they perhaps provide selective accessibility to the transcriptional machinery. Further, our analysis suggests that tissue specific genes resort to additional global regulatory features such as matrix association, which would facilitate maintenance of functionally distinct domains to insulate themselves from both silencing and activating regulatory influence of adjacent domains. The differential distribution of repetitive sequences in housekeeping and tissue specific genes might also play an important role in maintaining distinct chromatin landscape over these regions.
Conclusion
We have demonstrated that the regulatory regions of housekeeping and tissue specific genes have differential chromatin architecture with respect to S/MAR binding, nucleosome positioning potential and repetitive sequences. This has potential implications for regulation of gene expression in eukaryotic genomes.
Methods
In this study, the 5' and 3' flanking regions of genes were analysed for various attributes of chromatin organisation. The list of human housekeeping genes (Hkg) was retrieved from [28,36]. 532 genes have been categorised as housekeeping because of their ubiquitous and high expression levels in 47 tissues. The list and expression levels of the human tissue specific genes were obtained from Eli Eisenberg (personal communication). 566 genes expressed in only a single tissue were taken as tissue specific genes (Tsg) and analysed. We could unambiguously retrieve sequences of 525 Hkg and 558 Tsg from human genome build 33 (NCBI). Approximately, 2000 bp of the 5' and 3' regions from each of these genes were taken for analysis.
Scaffold/matrix associated regions (S/MAR) analysis
MAR Finder was used for prediction of S/MAR regions [37,38]. All the default options and the "New MAR Rules" were selected for predicting S/MARs. ChrClass program was used for S/MAR prediction [39,40].
Nucleosome organisation and gene expression correlation analysis
The upstream regions (2000 bp) were scanned for nucleosome exclusion elements [18,20] – poly (dA.dT) pure stretches of >10 bp length and [5' (CCGNN) 3']2–5 using in-house programs. Recon was used for evaluating nucleosome formation potential in the sequences [2,41]. The score outputs of the 5' regions were categorised in frequency intervals of 0.2 with a range from -3.2 to +3.2. The Recon scores around +1 and -1 imply strong nucleosome formation and exclusion potentials respectively. The scores in the four intervals of relevance (0.8 to 1, 1 to 1.2, -0.8 to -1 and -1 to -1.2) were taken for all the analyses. Since the promoter region information was not retrieved for these genes, the 2000 bp upstream region from the gene start site was split into 400, 800, 1200 & 1600 bp and analysed.
The Recon scores at 400 bp were used to draw correlation between the nucleosome formation potential and expression levels in the two sets of genes. In each sequence set, genes with expression levels <500 and >5000 affymetrix expression units were classified as low and high expression genes respectively. We considered a minimum ten fold difference in the expression levels of genes as a relevant criterion for classifying them as high and low expression genes. In Hkg, this criterion yielded 33 low expression and 35 high expression genes. In Tsg, we categorised 416 low expression genes and 24 high expression genes.
Repetitive sequence analysis
RepeatMasker version: 20040306-web was used to calculate the repeat content in 2000 bp upstream sequences of the two groups of genes [42].
List of abbreviations
S/MAR: scaffold/matrix attachment regions
Hkg: housekeeping genes
Tsg: tissue specific genes
df: degree of freedom
Authors' contributions
MG, VB and SKB contributed to the study design, analyses and in drafting the manuscript. MG, PS, SKDS, DD, KK and GP were involved in the data retrieval and analyses. All authors read and approved the final manuscript.
Supplementary Material
Additional File 1
gene list and expression levels of housekeeping genes, gene list and expression levels of tissue specific genes. 'supplementaryfile1.xls' contains the list of housekeeping and tissue specific genes and their expression levels used for the analysis.
Click here for file
Acknowledgements
MG acknowledges the financial support provided by Council for Scientific and Industrial Research (CSIR), India. SKB thanks Council for Scientific and Industrial Research, India and VB thanks Indian Council for Medical Research (ICMR), for financial assistance through a grant. The authors wish to acknowledge Dr. Beena Pillai, Dr. Rakesh Sharma, Dr. Neeraj Pandey and Dr. Mitali Mukerji for their valuable discussions and suggestions. We would also like to acknowledge Samira for careful checking and helping with the manuscript.
Figures and Tables
Figure 1 Nucleosome formation potential score distributions for 5' regions of housekeeping and tissue specific genes. The 5' sequences of human housekeeping and tissue specific genes were analysed by Recon for distribution of nucleosome formation potential scores. Frequency distribution histograms were plotted for scores in various intervals (range -3.2 to +3.2). (A) and (B) show the distribution of nucleosome formation potential scores at 400 and 2000 bp upstream from the gene start site respectively. Nucleosomal density is significantly lower for housekeeping genes as compared to tissue specific ones, in regions close to the gene start site.
Figure 2 Nucleosome formation potential score distributions for 5' regions at different positions from the gene start site in housekeeping and tissue specific genes. The 5' regions of 800, 1200 and 1600 bp from the gene start site of housekeeping and tissue specific genes were taken for the analysis. Frequency distribution histograms were plotted for Recon scores in various intervals (range -3.2 to +3.2). (A), (B) and (C) show the distribution of nucleosome formation potential scores at 800, 1200 and 1600 bp upstream from the gene start site respectively. As we move upstream from the gene start site, the difference in the nucleosome formation potentials between housekeeping and tissue specific genes gradually fades away.
Figure 3 A model for chromatin landscape in 5' regions of tissue specific and housekeeping genes. (A) depicts the repressive role of chromatin in maintaining tissue specific gene expression profiles in a chromosome. The chromatin organisation in the 5' regions of Tsg1 and Tsg2, two different tissue specific genes dispersed in the chromosome is shown. Nucleosome formation potentials and S/MARs – the boundary elements, are enriched in their upstream regions and might play a major role in facilitating tissue specific expression. This is likely to be a local effect since neighbouring genes might have a different expression pattern. (B) depicts the chromatin organisation in the 5' regions of Hkg1, Hkg2 and Hkg3, three housekeeping genes clustered in the chromosome. The presence of low nucleosome formation potential regions and enrichment of nucleosome destabilising elements ensure an open chromatin configuration in this domain. As Hkg generally cluster together, they are depleted in S/MARs relative to tissue specific genes as shown in the present analysis by the significant absence of predicted S/MARs in both 5' and 3' regions of housekeeping genes as compared to tissue specific genes.
Table 1 Distribution of putative S/MARs in housekeeping and tissue specific genes.
Putative S/MARs in 5' regions (%)* Putative S/MARs in 3' regions (%)*
Prediction scheme Hkg# Tsg§ Hkg# Tsg§
presence of S/MAR 26.1 34.1 19.1 20.6
absence of S/MAR 26.1 19.2 34.5 25.1
#Housekeeping genes, §Tissue specific genes,
* ChrClass and MAR Finder programs were used for prediction of S/MARs in housekeeping and tissue specific genes regulatory regions (5' & 3' regions – 2000 bp each). The common predictions of both the programs were used for the analysis. The data is represented as percentage of genes with predicted S/MARs in 5' and 3' regions of 525 housekeeping and 532 tissue specific genes.
Table 2 Distribution of poly (dA.dT) repeats of various lengths in the 5' upstream regions of housekeeping and tissue specific genes.
Poly (dA.dT) stretch (bp) No. of repeat stretches in the two classes No. of genes with repeats in 5' region (%)
Hkg# Tsg* Hkg# Tsg* §P-value
>10 443 345 268 (51.0) 240 (43.0) 1.31E-04
>11 381 297 243 (46.3) 214 (38.4) 3.25E-04
>12 339 248 226 (43.1) 184 (33.0) 6.10E-05
>13 295 207 209 (39.8) 156 (28.0) 4.29E-05
>14 251 168 188 (35.8) 128 (22.9) 2.77E-05
>15 209 140 164 (31.2) 111 (19.9) 8.83E-05
>16 180 116 146 (27.8) 99 (17.7) 7.58E-05
>17 155 103 134 (25.5) 88 (15.8) 2.42E-04
>18 138 79 120 (22.9) 71 (12.7) 2.23E-05
>19 112 66 101 (19.2) 59 (10.6) 2.61E-04
>20 100 58 92 (17.5) 53 (9.5) 5.32E-04
#Housekeeping genes, *Tissue specific genes. A total of 525 housekeeping and 558 tissue specific genes were analysed. The numbers in parentheses (4th & 5th columns) represent the percentage of genes containing the repeat stretch.
§Difference in the distribution of poly (dA.dT) stretches in Hkg and Tsg analysed by applying t-test (for normalizing the difference in sample size). The repeat lengths from >12 to >18 bp are showing very significantly different distributions between Hkg and Tsg. The distributions were examined in 2000 bp upstream region from the gene start site.
Table 3 t-test P-values for the difference in the distribution of nucleosome formation potential scores between housekeeping and tissue specific genes.
Length (bp)* P-value in intervals of scores
-1.2 to -1 -1 to -0.8 0.8 to 1 1 to 1.2
400 3.53E-13 8.73E-17 1.28E-17 4.45E-23
800 1.16E-24 6.27E-24 6.64E-12 6.65E-22
1200 6.91E-26 1.44E-24 2.10E-09 1.64E-18
1600 1.72E-24 6.99E-24 2.72E-07 5.63E-15
2000 2.55E-25 1.84E-25 3.22E-05 6.71E-13
*denotes the length of 5' upstream region from the gene start site taken for the analysis. The scores were compared in the four Recon score intervals of relevance -1.2 to -1, -1 to -0.8, 0.8 to 1 and 1 to 1.2.
Table 4 Correlation coefficients of total expression levels (log10) with nucleosome formation potential scores in housekeeping (Hkg) and tissue specific genes (Tsg).
Category Correlation coefficient
-1.2 to -1 -1 to -0.8 0.8 to 1 1 to 1.2
Hkg# 0.10 0.14 0.04 -0.01
Tsg* -0.10 -0.12 0.15 0.17
#Housekeeping genes, *Tissue specific genes.
The correlation was drawn in the four Recon score intervals of relevance -1.2 to -1, -1 to -0.8, 0.8 to 1 and 1 to 1.2.
Table 5 Comparison of the level of correlation between nucleosome formation potential scores and contrasting expression levels of genes.
*Category Correlation coefficient
-1.2 to -1# -1 to -0.8# 0.8 to 1# 1 to 1.2#
Hkg ↑↑ 0.17 0.30 -0.10 -0.26
Hkg ↓↓ 0.36 0.35 -0.28 -0.39
Tsg ↑↑ 0.03 0.02 0.26 0.11
Tsg ↓↓ -0.12 -0.14 0.15 0.16
*High and low expression level genes were categorised in Hkg (housekeeping genes) and Tsg (tissue specific genes) groups separately. # Recon score intervals. The genes classified as high and low expression genes in both Hkg and Tsg had atleast a 10-fold difference in their expression levels. The up (↑↑) and down (↓↓) arrows denote high expression and low expression respectively.
Table 6 The distribution of Alu repeats in 5' upstream regions of housekeeping (Hkg) and tissue specific genes (Tsg) is represented in terms of the number of copies and basepairs covered by Alu repeats.
Repeat category No. of copies % of the total sequences covered by the repeat
Hkg# Tsg* Hkg# Tsg*
Alu 866 575 20.1 12.3
#Housekeeping genes, *Tissue specific genes.
Table 7 t-test P-values for the difference in the distribution of Alu repeats in 5' upstream regions of housekeeping and tissue specific genes.
Repeat Category P-value
No. of repeats Repeat content (bp)
Alu 3.02E-08 7.63E-11
==== Refs
Lemon B Tjian R Orchestrated response: a symphony of transcription factors for gene control Genes Dev 2000 14 2551 2569 11040209 10.1101/gad.831000
Levitsky VG Podkolodnaya OA Kolchanov NA Podkolodny NL Nucleosome formation potential of eukaryotic DNA: calculation and promoters analysis Bioinformatics 2001 17 998 1010 11724728 10.1093/bioinformatics/17.11.998
Bode J Benham C Knopp A Mielke C Transcriptional augmentation: modulation of gene expression by scaffold/matrix-attached regions (S/MAR elements) Crit Rev Eukaryot Gene Expr 2000 10 73 90 10813396
Grewal SI Moazed D Heterochromatin and epigenetic control of gene expression Science 2003 301 798 802 12907790 10.1126/science.1086887
Boeger H Griesenbeck J Strattan JS Kornberg RD Nucleosomes unfold completely at a transcriptionally active promoter Mol Cell 2003 11 1587 1598 12820971 10.1016/S1097-2765(03)00231-4
Wolffe AP Transcriptional activation. Switched-on chromatin Curr Biol 1994 4 525 528 7922373 10.1016/S0960-9822(00)00114-7
Glazko GV Rogozin IB Glazkov MV Comparative study and prediction of DNA fragments associated with various elements of the nuclear matrix Biochim Biophys Acta 2001 1517 351 364 11342213
Glazko GV Koonin EV Rogozin IB Shabalina SA A significant fraction of conserved noncoding DNA in human and mouse consists of predicted matrix attachment regions Trends Genet 2003 19 119 124 12615002 10.1016/S0168-9525(03)00016-7
Versteeg R van Schaik BD van Batenburg MF Roos M Monajemi R Caron H Bussemaker HJ van Kampen AH The human transcriptome map reveals extremes in gene density, intron length, GC content, and repeat pattern for domains of highly and weakly expressed genes Genome Res 2003 13 1998 2004 12915492 10.1101/gr.1649303
Lercher MJ Urrutia AO Hurst LD Clustering of housekeeping genes provides a unified model of gene order in the human genome Nat Genet 2002 31 180 183 11992122 10.1038/ng887
de Laat W Grosveld F Spatial organisation of gene expression: the active chromatin hub Chromosome Res 2003 11 447 459 12971721 10.1023/A:1024922626726
Byrd K Corces VG Visualization of chromatin domains created by the gypsy insulator of Drosophila J Cell Biol 2003 162 565 574 12925706 10.1083/jcb.200305013
Nabirochkin S Ossokina M Heidmann T A nuclear matrix/scaffold attachment region co-localizes with the gypsy retrotransposon insulator sequence J Biol Chem 1998 273 2473 2479 9442099 10.1074/jbc.273.4.2473
Kim JM Kim JS Park DH Kang HS Yoon J Baek K Yoon Y Improved recombinant gene expression in CHO cells using matrix attachment regions J Biotechnol 2004 107 95 105 14711493 10.1016/j.jbiotec.2003.09.015
Bonifer C Yannoutsos N Kruger G Grosveld F Sippel AE Dissection of the locus control function located on the chicken lysozyme gene domain in transgenic mice Nucleic Acids Res 1994 22 4202 4210 7937146
Yusufzai TM Felsenfeld G The 5'-HS4 chicken beta-globin insulator is a CTCF-dependent nuclear matrix-associated element Proc Natl Acad Sci U S A 2004 101 8620 8624 15169959 10.1073/pnas.0402938101
Khorasanizadeh S The nucleosome: from genomic organisation to genomic regulation Cell 2004 116 259 272 14744436 10.1016/S0092-8674(04)00044-3
Suter B Schnappauf G Thoma F Poly(dA.dT) sequences exist as rigid DNA structures in nucleosome-free yeast promoters in vivo Nucleic Acids Res 2000 28 4083 4089 11058103 10.1093/nar/28.21.4083
Koch KA Thiele DJ Functional analysis of a homopolymeric (dA-dT) element that provides nucleosomal access to yeast and mammalian transcription factors J Biol Chem 1999 274 23752 23760 10446135 10.1074/jbc.274.34.23752
Wang YH Griffith JD The [(G/C)3NN]n motif: a common DNA repeat that excludes nucleosomes Proc Natl Acad Sci U S A 1996 93 8863 8867 8799118 10.1073/pnas.93.17.8863
Iyer V Struhl K Poly(dA:dT), a ubiquitous promoter element that stimulates transcription via its intrinsic DNA structure Embo J 1995 14 2570 2579 7781610
Kirkpatrick DT Wang YH Dominska M Griffith JD Petes TD Control of meiotic recombination and gene expression in yeast by a simple repetitive DNA sequence that excludes nucleosomes Mol Cell Biol 1999 19 7661 7671 10523654
Grover D Mukerji M Bhatnagar P Kannan K Brahmachari SK Alu repeat analysis in the complete human genome: trends and variations with respect to genomic composition Bioinformatics 2004 20 813 817 14751968 10.1093/bioinformatics/bth005
Jordan IK Rogozin IB Glazko GV Koonin EV Origin of a substantial fraction of human regulatory sequences from transposable elements Trends Genet 2003 19 68 72 12547512 10.1016/S0168-9525(02)00006-9
Brahmachari SK Meera G Sarkar PS Balagurumoorthy P Tripathi J Raghavan S Shaligram U Pataskar S Simple repetitive sequences in the genome: structure and functional significance Electrophoresis 1995 16 1705 1714 8582360 10.1002/elps.11501601283
Grover D Majumder PP Rao CB Brahmachari SK Mukerji M Nonrandom distribution of alu elements in genes of various functional categories: insight from analysis of human chromosomes 21 and 22 Mol Biol Evol 2003 20 1420 1424 12832639 10.1093/molbev/msg153
Vijaya S Steffen DL Robinson HL Acceptor sites for retroviral integrations map near DNase I-hypersensitive sites in chromatin J Virol 1986 60 683 692 3490582
Eisenberg E Levanon EY Human housekeeping genes are compact Trends Genet 2003 19 362 365 12850439 10.1016/S0168-9525(03)00140-9
Vinogradov AE Compactness of human housekeeping genes: selection for economy or genomic design? Trends Genet 2004 20 248 253 15109779 10.1016/j.tig.2004.03.006
Oei SL Babich VS Kazakov VI Usmanova NM Kropotov AV Tomilin NV Clusters of regulatory signals for RNA polymerase II transcription associated with Alu family repeats and CpG islands in human promoters Genomics 2004 83 873 882 15081116 10.1016/j.ygeno.2003.11.001
Nemeth A Langst G Chromatin higher order structure: opening up chromatin for transcription Brief Funct Genomic Proteomic 2004 2 334 343 15163368
Pennisi E Human genome. A low number wins the GeneSweep Pool Science 2003 300 1484 12791949 10.1126/science.300.5625.1484b
Brahmachari SK Ramesh N Shouche YS Mishra RK Bagga R Meera G Sarma RH, Sarma MH Unusual DNA Structures: Sequence Requirements and Role in Transcriptional Control Structure and Methods 1990 2 New York: Adenine Press 33 49
Conrad M Brahmachari SK Sasisekharan V DNA structural variability as a factor in gene expression and evolution Biosystems 1986 19 123 126 3730535 10.1016/0303-2647(86)90024-9
Gilbert N Boyle S Fiegler H Woodfine K Carter NP Bickmore WA Chromatin architecture of the human genome: gene-rich domains are enriched in open chromatin fibers Cell 2004 118 555 566 15339661 10.1016/j.cell.2004.08.011
List of housekeeping genes
Singh GB Kramer JA Krawetz SA Mathematical model to predict regions of chromatin attachment to the nuclear matrix Nucleic Acids Res 1997 25 1419 1425 9060438 10.1093/nar/25.7.1419
MAR Finder
Rogozin IB Glazko GV Glazkov MV Computer prediction of sites associated with various elements of the nuclear matrix Brief Bioinform 2000 1 33 44 11466972
ChrClass
Recon
RepeatMasker
| 15918906 | PMC1173084 | CC BY | 2021-01-04 16:02:50 | no | BMC Bioinformatics. 2005 May 26; 6:126 | utf-8 | BMC Bioinformatics | 2,005 | 10.1186/1471-2105-6-126 | oa_comm |
==== Front
BMC BioinformaticsBMC Bioinformatics1471-2105BioMed Central London 1471-2105-6-1281592150710.1186/1471-2105-6-128Research ArticleIntegrative analysis of multiple gene expression profiles with quality-adjusted effect size models Hu Pingzhao [email protected] Celia MT [email protected] Joseph [email protected] The Hospital for Sick Children Research Institute, 555 University Ave., Toronto, ON, M5G 1X8, Canada2 Department of Public Health Sciences, University of Toronto, 1 King's College Circle, Toronto, ON, M5S 1A8, Canada2005 27 5 2005 6 128 128 24 1 2005 27 5 2005 Copyright © 2005 Hu et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
With the explosion of microarray studies, an enormous amount of data is being produced. Systematic integration of gene expression data from different sources increases statistical power of detecting differentially expressed genes and allows assessment of heterogeneity. The challenge, however, is in designing and implementing efficient analytic methodologies for combination of data generated by different research groups.
Results
We extended traditional effect size models to combine information from different microarray datasets by incorporating a quality measure for each gene in each study into the effect size estimation. We illustrated our method by integrating two datasets generated using different Affymetrix oligonucleotide types. Our results indicate that the proposed quality-adjusted weighting strategy for modelling inter-study variation of gene expression profiles not only increases consistency and decreases heterogeneous results between these two datasets, but also identifies many more differentially expressed genes than methods proposed previously.
Conclusion
Data integration and synthesis is becoming increasingly important. We live in a high-throughput era where technologies constantly change leaving behind a trail of data with different forms, shapes and sizes. Statistical and computational methodologies are therefore critical for extracting the most out of these related but not identical sources of data.
==== Body
Background
The introduction of DNA microarray technology has enabled investigators to screen thousands of genes simultaneously. One of the main goals of these studies is to identify differentially expressed genes between two biological conditions. For example, many studies [1-4] have been performed in prostate cancer research to find candidate markers. Since laboratory protocols, microarray platforms and analysis techniques used in these studies were not identical, it is difficult to make a comparison among the results obtained from them. However, systematic integration of gene expression data from different sources increases statistical power of detecting differentially expressed genes and allows assessment of heterogeneity. Meta-analysis is a classical statistical methodology for combining results from different studies addressing the same scientific questions, and it is becoming particularly popular in the area of medical and epidemiological research [5]. Meta-analysis methods have recently been applied to the analysis of microarray data [6-11].
Rhodes et al. [6] focused on combining p-values for each gene from the individual studies to estimate an overall p-value for each gene across all studies. Their method has been applied to four prostate cancer microarray datasets, two of which are cDNA microarray data and the remainder Affymetrix microarray data. Samples in each data set were taken from prostate cancer cases, but were analyzed with different platforms. Differential expression was assessed independently for each gene in each dataset. Since the method chosen to combine results across studies was based on the statistical confidence measure, the p-value, not on the expression level, this strategy avoids direct comparisons of data sets and related cross-platform normalization issues. Choi et al. [7] focused on integrating effect size estimates to obtain an overall estimate of the average effect size. Effect size is used to measure the magnitude of treatment effect in a given study. Using the same datasets as those used by Rhodes et al. [6], they demonstrated that their method can lead to the discovery of small but consistent expression changes with increased sensitivity and reliability.
Parmigiani et al. [9] developed a correlation-based method for assessing reproducibility of gene expression studies with application to lung cancer. They demonstrated that their method can improve correlation across the various studies. Jiang et al. [10] used a distribution transformation method to integrate two lung cancer studies and proposed a gene shaving-based classification approach to identify a small list of differentially expressed genes between lung cancer and normal patients. They noted that many of the selected genes have been experimentally validated.
Although some of the above studies (for example Rhodes et al. [6], Choi et al. [7], Parmigiani et al. [9]) demonstrated the utility of integrating cDNA and Affymetrix microarray data, other investigators argued against this approach. Kuo et al. [12] compared Affymetrix and spotted cDNA gene expression measurements based on 60 cell lines from the National Cancer Institute. They found low correlation between the actual gene measurements from the two technologies, and concluded that "data from spotted cDNA microarrays could not be directly combined with data from synthesized oligonucleotide arrays." Moreover, they concluded that it was unlikely that the two types of data could be transformed or normalized into a common standardized index. Jarvinen et al. [13] determined the level of concordance between microarray platforms by analyzing breast cancer cell lines with in situ synthesized oligonucleotide arrays, commercial cDNA microarrays and custom-made cDNA microarrays. Their results demonstrated that data from different microarray platforms are variable to the extent that direct integration of data from different platforms may be complicated and unreliable.
In classical meta-analysis, quality measures have often been used when combining results across studies. It has been argued that studies of a higher quality will give more accurate estimates of the true parameter of interest, and therefore studies of high quality should receive a higher weight in the analysis summarizing across studies [14]. The Affymetrix microarray technology has been used worldwide. Its success has been demonstrated by numerous publications in scientific journals. However, it is well-known that only part (approximately 40–50%) of the whole genome is expressed in any specific tissue type, so there are many genes showing low expression and random variability across samples. Furthermore, some genes will be measured less precisely by some technologies, or studies, than others.
Therefore, our ability to develop powerful statistical methods for efficiently integrating and weighting information from related genomic experiments will be critical in the success of the massive investment made on genomic studies. The focus of this paper is to design and implement a quality measure appropriate for Affymetrix microarray data. Using our quality measure, we weighted the importance of each gene in each experiment and incorporated our quality measure into the effect size model proposed by Choi et al. [7] to model inter-study variation of gene expression profiles. We believe that applying this approach can lead to a more accurate description of expression patterns than Choi et al's method [7].
Results
We used two data sets consisting of gene expression profiles in lung cancer and normal subjects. These datasets were collected using different chip types of the Affymetrix oligonucleotide microarrays and were conducted by two research groups, one from Harvard and the other from Michigan (see Methods section for details). A list of 6124 common probe sets found in the two datasets was used for data analysis in this study [10]. We developed a quality weight for each gene in each study by modeling the log of the detection p-values with an exponential distribution, and then summarizing across arrays and groups within each study (see Methods). In order to visualize the effect of the proposed quality weighting, we calculated the mean expression value of each probe set across all normal samples, where the expression variation presumably is less heterogeneous than among the cancer samples. The mean expression value of a probe set in a study is the estimated average of the probe set's intensity values across all normal samples in the study. Figure 1 shows the scatter plot of the average expression values of the probe sets in the Harvard dataset plotted against that of the Michigan dataset: (a) weighted by the quality score (see Methods section for our definition of the quality score), and (b) un-weighted. This plot is intended to be illustrative only – our algorithm weights the test statistics, rather than the gene expression measures. In Figure 1(a), it can be seen, as expected, that many of the genes with low levels of expression are associated with low quality weights.
We show examples of quality scores for selected probe sets in Table 1. The two datasets may have very different detection p-value distributions, which are reflected in the quality scores. Figure 2 shows a box plot of the detection p-values for one probe set from Table 1. When the two datasets give small p-values (e.g., last line in Table 1), the minimum p-value may be much smaller in one dataset than another. Both, however, will give high quality scores with an appropriate choice of the sensitivity parameter s that adjusts how the quality measure interprets the detection p-values.
Figure 3 shows the adjusted and unadjusted quantile – quantile (Q-Q) plots of the observed vs. expected Q values. Q is the test statistic we used for assessing heterogeneity, and is described in detail later in the Methods section. In the adjusted Q-Q plot, the quality score was used as a weight in the computation of Q while it was not considered in the unadjusted Q-Q plot. From these graphs, we can see that the quantiles of the observed Q values are far from the expected quantiles of a distribution, suggesting that these two datasets generated heterogeneous results beyond random sampling errors. Therefore, we applied the random effect model in this study. The quantiles of the Q statistic were closer to the quantiles of the expected chi-square distribution when quality-adjustment was considered (Figure 3(a)) than when it is was not (Figure 3(b)). The variance for the unadjusted Q values was 9.45, but it was reduced to 3.31 when quality adjustment was used. This result suggests that the incorporation of the adjusted quality measure into effect size estimation can increase consistency and decrease heterogeneity between these two datasets.
To identify a list of potentially "significant" genes, we adapted the false discovery rate (FDR) algorithm implemented in [30]. We first calculated the adjusted z statistics for all genes based on random-effects model (REM). Genes were then ranked by the magnitude of their z statistic values. A permutation-based approach was used to obtain the corresponding expected ordered z statistic. The potentially "significant" genes are genes with a distance between the ordered z statistic from the observed data and that of the permuted data exceeding a given threshold (delta). Figure 4 shows the relationship between the number of significantly differentially expressed genes and different delta levels. As we see in this figure, the quality-adjusted REM can identify many more significant genes than the quality-unadjusted REM model at any fixed level of delta.
We calculated the estimated FDR for each given delta. As expected, the number of genes called significant increased as the value of delta decreased, but at the cost of an increasing FDR. The estimated FDR was zero down to a delta of 0.6, where 228 genes were called significant in the quality-adjusted model and 153 genes in the quality-unadjusted model. In order to get a manageable gene list, we arbitrarily set delta at 1.1. At this delta level, we selected 29 differentially expressed genes (representing 32 probe sets) at a FDR of 0% when the quality weight was incorporated into the estimation of the effect size. However, when the quality measure was not used (Choi et al's method [7]), we only selected 20 differentially expressed genes (representing 21 probe sets) at a FDR of 0%. All the 20 genes were also in the top of the list of the 29 genes identified with the quality-weights. Tables 2 and 3 show the selected differentially expressed genes between normal and lung adenocarcinoma patient samples using the quality-adjusted and quality-unadjusted models, respectively, with genes ordered based on their z statistic values [see Additional files 1 and 2]. As can be seen in Tables 2 and 3, 4 of the 9 genes that were selected by our method, but not by Choi et al's method, have also been identified by several other groups including Jiang et al. [10], Beer et al. [15] and Bhattacharjee et al. [16]. In particular, some of these 4 genes, such as TEK and TGFBR2, have been experimentally validated (shown in Table 3 of Jiang et al.[10]). For a cutoff of an adjusted z value of 1.96 (corresponding to a 5% level of significance), the quality-adjusted model identified 9 significantly expressed genes while the quality-unadjusted model identified only 2 of the 9 significantly differentially expressed genes. All these results suggest that our proposed method may have increased sensitivity to detect more differentially expressed and biologically relevant genes than Choi et al's method [7].
We compared genes identified with our method with genes identified by Jiang et al. [10], Beer et al. [15] and Bhattacharjee et al. [16], sixteen of the 29 genes identified by our proposed model were also detected in at least one of these studies. In particular, we observed that 6 of the 29 genes were consistently identified in the other three studies. There were 13 of the 29 genes that were uniquely identified in our study. Some of these are plausible candidates for lung adenocarcinoma. For example, Walker et al. [17] found that G protein-coupled receptor kinase 5 (GRK5) is a key gene regulating airway response, that may have implications in obstructive airway diseases.
Discussion
In this study we proposed a measure to quantify Affymetrix gene chip data quality for each gene in each study. The quality index measures the performance of each probe set to detect its intended target. Furthermore, we extended a traditional effect size model by using the quality index as a weight for combining information from different chip types of Affymetrix microarrays, and incorporating this weight into a random-effects meta-analysis model. We illustrated the advantages of our proposed methods using the Harvard and Michigan gene expression datasets used in [18]. This approach of using the detection p-values to weight the gene expression estimates can be applied in a more general context and to other microarray meta-analysis methods, such as that of Rhodes et al [6].
The assumption of a group-specific exponential distribution for the negative log detection p-values is a very rough approximation. The true distribution is probably closer to the two-parameter log-beta distribution. However, due to the fact that there are only 16–20 probe pairs per probe set used in the Wilcoxon test statistic for the detection p-values, the p-values follow a somewhat discrete distribution. In particular for highly-expressed genes, the p-values for all samples in a group may have the same near-zero value. Estimation of two-parameters is therefore impossible. It would be worth investigating the sensitivity of the performance of this quality-weighting approach to the distributional assumption.
The performance of the weighting also depends on the sensitivity parameter s. In this study, a high s was needed since a lower cutoff gave almost all genes extremely low quality scores. This is a consequence of the observed detection p-value distributions. These data were created in 2001, and since that time the quality of the oligonucleotide array technology has improved with more specific probe selections and optimized experimental conditions. For expression data obtained today, smaller values of s would be more appropriate. For example, in an analysis of a dataset generated more recently using improved oligonucleotide technology (not shown), using s = 0.05 gave good performance.
The discrepancy between the calculated and expected values for the Q test of heterogeneity was smaller when our quality measure was incorporated than when it was not, as suggested by the quantile-quantile plots, but overall there still remains some variability that has not been fully captured by the weight function, emphasizing the need for a more elaborate weighting strategy and sensitivity analyses.
From a biological point of view, lung adenocarcinoma may be heterogeneous originating from different causes [19] and methods like cluster analysis in which subtypes of relatively homogeneous groups of disorders can be identified might be useful. The focus of our paper was to introduce a methodology that can be used to integrate data, and as such the grouping of the samples as "diseased" versus "normal" was primarily used to identify genes that discriminate the two groups in a broader sense than at a higher resolution in which sub types could be identified.
Choi et al. [7] have also provided a brief Bayesian interpretation of their effect size model to integrate information from multiple microarray studies. They argued that a Bayesian approach could offer a more flexible and robust modeling strategy. We did not consider this issue in this study. It will be interesting to investigate how our proposed quality measure could be incorporated into their Bayesian framework in the future.
Methods
Data source and preprocessing
We selected two Affymetrix microarray data sets from the 4 lung cancer data sets provided by the organizers of the Critical Assessment of Microarray Data Analysis (CAMDA) conference [18]. These datasets were collected using different versions of the Affymetrix oligonucleotide microarrays and were conducted by two research groups, one from Harvard and the other from Michigan. The Michigan study [15] used the HuGeneFL Affymetrix chip, containing 7,129 probe sets, each with 20 probe pairs. This study included 86 lung adenocarcinoma patient samples and 10 normal samples. The Harvard study [16] used the HG_U95Av2 chip with 12,625 probe sets, each with 16 probe pairs. This study included 17 normal and 127 lung adenocarcinoma patient samples. We use the word "sample" interchangeably with "array". The main objectives addressed in these two studies were to identify differentially expressed genes related to lung adenocarcinoma, and genes whose expression was related to patient survival. Our interest is in the former. We developed a new method for identifying genes that are differentially expressed between the cancer and normal samples, by modelling the effect size and integrating information from the Harvard and Michigan studies.
We converted the probe level data to a single expression measure for each probe set using the robust multi-array average (RMA) algorithm [20], which provides higher specificity and sensitivity in detecting differentially expressed genes. We used 6124 common probe sets in these two studies for the data analysis in our study. These probe sets were selected based on a sequence-based probe matching method, which is believed to produce more consistent results when comparing similar biological data sets obtained by different microarray platforms [10,21]. The detailed procedure used to select these probe sets can be found in the Data processing Section of [10].
Quality measure for Affymetrix Genechip data
Affymetrix genechip microarrays are used to monitor gene expression for thousands of transcripts. Each transcript is represented as a probe set, and a probe set is made up of probe pairs comprised of Perfect Match (PM) and Mismatch (MM) probe cells. The level of expression of a gene product is estimated using the intensities of each probe pair in a probe set. Therefore, the probe-specific variability in a probe set can be used as a measure of the performance of that probe set. The detection algorithm proposed by [22] generates a detection p-value, which represents the probability that the probe set (gene) expression is above zero (i.e., turned on), and measured reliably and consistently. A lower p-value is considered as a useful indicator that the measured gene expression is valid and reliable [22]. Specifically, the p-value is based on testing whether the probe-specific differences (PM-MM) are almost always positive. We used the detection p-values to define quality measures for probe sets, summarizing across the arrays and experiments. We realize that some genes may be truly "off" under some experimental conditions and hence a large detection p-value may be providing useful information. However, if a gene is "off" under all experimental conditions, we argue that analysis of this gene contributes little to understanding of the experiment.
For any gene, let pvalue denote its detection p-value and xlg denote - log(pvaluelg) for sample l in group g. We assume that each study compares G groups, where there are ng samples in group g, and g = 1, 2, ..., G. For example, in the lung cancer data, G = 2, since adenocarcinoma samples are compared to controls. It is well known that p-values follow a uniform distribution when there is no signal, and therefore, we expect xlg to follow an exponential distribution with mean λ = 1 if the gene is not expressed. In order to develop a single quality measure for each gene across all samples in one study, we use this relationship with the exponential distribution to motivate a quality measure. We assumed that the detection p-value for a single gene of sample l in group g follows the distribution
xlg = - log (pvaluelg) ~ Exponential (λg),
where different distributions of expression can be expected in each group g. It should be noted that we are modeling the p-value of one gene, across the samples in a group. This is different from the approaches of Allison et al. [23] and Pounds et al. [24] who modeled the distribution of p-values across genes. Although the true distribution of the xlg may not be exponential, this assumption leads to a simple model where the one parameter can be estimated by a closed-form expression. Hence, the parameter λg for each gene, study and group g can be estimated by:
where is the usual sample mean. This is a maximum likelihood estimator (MLE) with well-known asymptotic optimality properties [25].
To combine across the groups, we assumed a sensitivity parameter s. It is defined as the probability that a representative probe set in a particular treatment group shows a detectable signal, assuming that the relevant distribution (exponential or beta) holds. It can be thought of as the equivalent to a detection p-value defined for a whole group rather than for one array, and an appropriate value for s should be chosen with this interpretation in mind. For example, the default settings by Affymetrix software for the detection calls are p = 0.06 for a "Marginal" call, and p = 0.04 for a "Present" call, although these can be altered by the user. In practice, the appropriate choice of s may depend on the signal-detection capability of particular technologies. We recommend plotting the distribution of quality scores for different choices of s, and choosing a value that clearly distinguishes genes of low quality (scores near zero) from high quality genes (scores near 1).
The sensitivity parameter s is a chosen cutoff, so that genes that are "off" or poorly measured across all experimental conditions will have pvalue ≥ s, or in other words, . Therefore, we can define a quality measure across the groups, for each gene and each study as:
The choice of the maximum gives more weight to genes measured with high quality in at least one group, thereby allowing a gene that is "off" in one condition and "on" under another condition to provide useful information in the analysis. We treat this quality score as a weight for each gene in the subsequent analysis.
Modelling effect size with quality-adjusted weights
In order to simplify the discussion, we consider two groups, treatment (t) and control (c) groups, in study i = 1,2,...,k. Let nit and nic denote the number of treatment and control samples in study i, respectively. For each gene, let μ denote its overall mean effect size, a measure of the average differential expression for that gene, and let yi denote the observed effect size for study i. We modeled effect size using the hierarchical model:
Where τ2 is the between-study variability and is the within-study variance, measuring the sampling error for the ith study. Choi et al. [7] used the standardized mean difference as a measure of the observed treatment difference yi. This well-known estimator of treatment difference found in Hedges and Olkin's [26] work is
where and are the average gene expression values in the treatment and control groups of study i, respectively, and is the pooled standard deviation.
For a study with n samples, an approximately unbiased estimator of is given by [26]. The estimated variance of the unbiased effect size is given by [27]
In a fixed-effects model (FEM), the error of the observed effect sizes is fully assigned to sampling error only, ignoring the between study variance, so τ2 = 0 and yi ~ N (μ, ). On the other hand, a random-effects model (REM) considers that each study estimates a different treatment effect θi. These parameters are drawn from a normal distributionθi ~ N(μ, τ2).
To assess whether FEM or REM is most appropriate, we tested the hypothesis τ = 0 using the following test statistic, which is a modification of Cochran's test statistic [28] that incorporates our quality measure for each study
where and
is the weighted least squares estimator that ignores between study variations. Under the null hypothesis of τ = 0, this statistic follows a distribution. We followed Choi's approach [7] to draw quantile-quantile plots of Q to assess whether a FEM or REM model is appropriate. If the null hypothesis of τ = 0 is rejected, we estimate τ based on the method developed by DerSimonian and Laird [29]
Therefore, we can estimate μ that corresponds to a random effects model by
where . Under the REM,
The z statistics to test for treatment effect under REM is
However, when there are only a small number of arrays in each group, the estimates of standard error s for each gene can be very variable. Some genes might by chance have very small standard errors, and therefore appear highly significant. To address this problem, different approaches have been developed for "smoothing" the variance estimates by borrowing information from the ensemble of genes. This can assist in inference about each gene individually. For example, Tusher et al. [30], Efron et al. [31] and Broberg [32] used t-statistics where an offset was added to standard deviation while Smyth [33] proposed a t-statistic with a Bayesian adjustment to the denominator. We took the offset s0 as the quantile of the gene-wise standard errors that minimizes the coefficient of variation of the z statistics [30]. Therefore, we can calculate the adjusted z statistics (used in this study) to test for treatment effect under REM as
The adjusted z statistics for FEM is the same as that for REM except that τ2 = 0. Note that all these expressions refer to a single gene. The adjustment for computing z statistic was also used by Garrett-Mayer et al. [34].
Assessment of differentially expressed genes
We performed a multiple testing procedure, as described by Dudoit et al. [35], to evaluate statistical significance for differentially expressed genes in the combined studies. The false discovery rate (FDR) [36] has become a popular error measure for this purpose. Tusher et al. [30] developed a permutation-based method to calculate FDR for evaluating differentially expressed genes. We adapt their approach to our meta-analytic framework as follows:
1. For each gene j, j = 1,2,..., J, in the original data, compute the adjusted z statistic Z1,...,ZJ based on the meta-analysis procedure described in the previous section
2. Order these z statistic values to obtain Z(1) ≤,..., ≤ Z(J)
3. Create B random permutations within both studies. For each permutation b = 1,2,... B, produce the adjusted z statistic Z1,b,..., ZJ,b for gene j = 1,2,..., J
4. Compute expected order z statistics:
5. The potentially "significant" genes are those that have a distance between Z(j) and , greater than a given threshold delta (Δ). Therefore, we can find the smallest positive Z(j) such that , say t1. Similarly, we can find the largest negative Z(j), say t2
6. The estimated FDR for the selected significant genes at the given delta (Δ) is given by:
Authors' contributions
JB initiated, designed and managed the study. CG proposed the quality measure method and participated in designing and managing the study. PH conducted data analysis and drafted the manuscript. JB and CG revised the manuscript. All authors read and approved the final manuscript.
Supplementary Material
Additional File 1
Selected differentially expressed genes between normal and lung adenocarcinoma patient samples (Genes selected based on quality-adjusted model with delta = 1.1)
Click here for file
Additional File 2
Selected differentially expressed genes between normal and lung adenocarcinoma patient samples (Genes selected based on quality-unadjusted model with delta = 1.1)
Click here for file
Acknowledgements
We would like to thank Dr. Hongying Jiang who provided us with the list of common probe set IDs for the two data sets used in our study. We also acknowledge helpful suggestions from two anonymous reviewers that greatly improved the quality of the manuscript.
Figures and Tables
Figure 1 Scatter plots of (a) quality-weighted and (b) quality-unweighted mean expression values for the 6124 common probe sets in the Harvard and Michigan datasets based on normal (healthy) samples.
Figure 2 Detection p-values for a sample probe set (38249_at). H1 and H2 denote the detection p-values in normal and lung cancer groups, respectively, for the Harvard study; whereas M1 and M2 denote the detection p-values in normal and lung cancer groups, respectively, for the Michigan study.
Figure 3 Quantile – Quantile plots of the observed versus the expected Q statistic: (a) with quality adjustment, and (b) without quality adjustment.
Figure 4 Relationship between number of significantly expressed genes and different delta levels, obtained from fitting the random effects model.
Table 1 Quality scores for selected probe sets at a sensitivity parameter s = 0.2
Quality Score
Probe Set Harvard Study Michigan Study Harvard Study Michigan Study
38249_at 0.663 0.001 0.255 4.050
32180_s_at 0.263 0.732 0.829 0.194
37174_at 0.001 0.495 4.050 0.437
32318_s_at 0.795 0.795 0.142 0.142
==== Refs
Welsh JB Sapinoso LM Su AI Kern SG Wang-odriguez J Moskaluk CA Frierson HF Hampton GM Analysis of gene expression identifies candidate markers and pharmacological targets in prostate cancer Cancer Research 2001 61 5974 5978 11507037
Dhanasekaran SM Barrette TR Ghosh D Shah R Varambally S Kurachi K Pienta KJ Rubin MA Chinnaiyan AM Delineation of prognostic biomarkers in prostate cancer Nature 2001 412 822 826 11518967 10.1038/35090585
Luo J Duggan DJ Chen Y Sauvageot J Ewing CM Bittner ML Trent JM Issacs WB Human prostate cancer and benign prostatic hyperplasia: molecular dissection by gene expression profiling Cancer Research 2001 61 4683 4688 11406537
Magee JA Araki T Patil S Ehrig T True L Humphrey PA Catalona WJ Watson MA Milbrandt J Expression profiling reveals hepsin overexpression in prostate cancer Cancer Research 2001 61 5692 5696 11479199
Olkin I Meta-Analysis: methods for combining independent studies. Editor's introduction Statistical Science 1992 7 226
Rhodes DR Barrette TR Rubin MA Ghosh D Chinnaiyan AM Meta-analysis of microarrays: inter-study validation of gene expression profiles reveals pathway dysregulation in prostate cancer Cancer Research 2002 62 4427 4433 12154050
Choi JK Yu U Kim S Yoo OJ Combining multiple microarray studies and modeling inter-study variation Bioinformatics 2003 i84 i90 12855442 10.1093/bioinformatics/btg1010
Ghosh D Barette TR Rhodes D Chinnaiyan AM Statistical issues and methods for meta-analysis of microarray data: a case study in prostate cancer Functional & Integrative Genomics 2003 3 180 188 12884057 10.1007/s10142-003-0087-5
Parmigiani G Garrett-Mayer ES Anbazhagan R Gabrielson E A cross-study comparison of gene expression studies for the molecular classification of lung cancer Clinical Cancer Research 2004 10 2922 2927 15131026
Jiang H Deng Y Chen H Tao L Sha Q Chen J Tsai C Zhang S Joint analysis of two microarray gene-expression data sets to select lung adenocarcinoma marker genes BMC Bioinformatics 2004 5 81 15217521 10.1186/1471-2105-5-81
Shen R Ghosh D Chinnaiyan AM Prognostic meta-signature of breast cancer developed by two-stage mixture modeling of microarray data BMC Genomics 2004 5 94 15598354 10.1186/1471-2164-5-94
Kuo WP Jenssen TK Butte AJ Ohno-Machado L Kohane IS Analysis of matched mRNA measurements from two different microarray technologies Bioinformatics 2002 18 405 412 11934739 10.1093/bioinformatics/18.3.405
Jarvinen AK Hautaniemi S Edgren H Auvinen P Saarela J Kallioniemi OP Monni O Are data from different gene expression microarray platforms comparable? Genomics 2004 83 1164 1168 15177569 10.1016/j.ygeno.2004.01.004
Tritchler D Modelling study quality in meta-analysis Statistics in Medicine 1999 18 2135 2145 10441769 10.1002/(SICI)1097-0258(19990830)18:16<2135::AID-SIM183>3.3.CO;2-X
Beer DG Kardia SL Huang CC Giordano TJ Levin AM Misek DE Lin L Chen G Gharib TG Thomas DG Lizyness ML Kuick R Hayasaka S Taylor JM Iannettoni MD Orringer MB Hanash S Gene-expression profiles predict survival of patients with lung adenocarcinoma Nature Medicine 2002 9 816 824
Bhattacharjee A Richards WG Staunton J Li C Monti S Vasa P Ladd C Beheshti J Bueno R Gillette M Loda M Weber G Mark EJ Lander ES Wong W Johnson BE Golub TR Sugarbaker DJ Meyerson M Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses Proceedings of the National Academy of Sciences USA 2001 98 13790 13795 10.1073/pnas.191502998
Walker JKL Gainetdinov RR Feldman DS McFawn PK Caron MG Lefkowitz RJ Premount RT Fisher JT G protein-coupled receptor kinase 5 regulates airway response induced by muscarinic receptor activation American Journal of Physiology – Lung Cell Molecular Physiology 2004 286 L312 L319 10.1152/ajplung.00255.2003
CAMDA 2003
Shigematsu H Lin L Takahashi T Nomura M Suzuki M Wistuba II Fong KM Lee H Toyooka S Shimizu N Fujisawa T Feng Z Roth JA Herz J Minna JD Gazdar AF Clinical and biological features associated with epidermal growth factor receptor gene mutations in lung cancers Journal of National Cancer Institute 2005 97 339 346
Irizarry RA Bolstad BM Collin F Cope LM Hobbs B Speed TP Summaries of Affymetrix GeneChip probe level data Nucleic Acids Research 2003 31 e15 12582260 10.1093/nar/gng015
Brigham HM Gregory TK Jeffrey S Meena A David B Peter B Daniel ZW Thomas JM Isaac SK Zoltan S Sequence-matched probes produce increased cross-platform consistency and more reproducible biological results in microarray-based gene expression measurements Nucleic Acids Research 2004 32 e74 15161944 10.1093/nar/gkg933
Affymetrix Microarray Suite User Guide, version 5 2001
Allison DB Gadbury GL Heo M Fernandez JR Lee CK Prolla TA Weindruch R A mixture model approach for the analysis of microarray gene expression data Computational Statistics & Data Analysis 2002 39 1 20 10.1016/S0167-9473(01)00046-9
Pounds S Morris SW Estimating the occurrence of false positives and false negatives in microarray studies by approximating and partitioning the empirical distribution of p-values Bioinformatics 2003 19 1236 1242 12835267 10.1093/bioinformatics/btg148
Knight K Mathematical statistics 2000 Chapman & Hall/CRC Press
Hedges LV Olkin I Statistical methods for meta-analysis 1995 Orlando, FL: Academic Press 81
Cooper H Hedges LV The handbook of research synthesis 1994 New York: Russell Sage 268
Cochran BG The combination of estimates from different experiments Biometrics 1954 10 101 129
DerSimonian R Laird NM Meta-analysis in clinical trials Controlled Clinical Trials 1986 7 177 188 3802833 10.1016/0197-2456(86)90046-2
Tusher VG Tibshirani R Chu G Significance analysis of microarrays applied to the ionizing radiation response Proceedings of the National Academy of Sciences USA 2001 98 5116 5121 10.1073/pnas.091062498
Efron B Tibshirani R Tusher V Empirical Bayes analysis of a microarray experiment Journal of the American Statistical Association 2001 96 1151 1160 10.1198/016214501753382129
Broberg P Statistical methods for ranking differentially expressed genes Genome Biology 2003 4 R41 12801415 10.1186/gb-2003-4-6-r41
Smyth GK Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments Statistical Applications in Genetics and Molecular Biology 2004 3 Article 3
Garrett-Mayer E Parmigiani G Zhong X Cope L Gabrielson E Cross-study Validation and Combined Analysis of Gene Expression Microarray Data Technical Report, Johns Hopkins University, Department of Biostatistics 2004
Dudoit S Shaffer JP Boldrick JC Multiple hypothesis testing in microarray experiments Statistical Science 2003 18 71 103 10.1214/ss/1056397487
Benjamini Y Hochberg Y Controlling the false discovery rate: a practical and powerful approach to multiple testing Journal of the Royal Statistical Society: Series B 1995 85 289 300
| 15921507 | PMC1173085 | CC BY | 2021-01-04 16:02:51 | no | BMC Bioinformatics. 2005 May 27; 6:128 | utf-8 | BMC Bioinformatics | 2,005 | 10.1186/1471-2105-6-128 | oa_comm |
==== Front
BMC BioinformaticsBMC Bioinformatics1471-2105BioMed Central London 1471-2105-6-1291592153410.1186/1471-2105-6-129CorrespondenceConsiderations when using the significance analysis of microarrays (SAM) algorithm Larsson Ola [email protected] Claes [email protected] James A [email protected] Center for Genomics and Bioinformatics, Karolinska Institutet, Berzelius Väg. 35. 171 77 Stockholm, Sweden2005 29 5 2005 6 129 129 2 5 2005 29 5 2005 Copyright © 2005 Larsson et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Users of microarray technology typically strive to use universally acceptable data analysis strategies to determine significant expression changes in their experiments. One of the most frequently utilised methods for gene expression data analysis is SAM (significance analysis of microarrays). The impact of selection thresholds, on the output from SAM, may critically alter the conclusion of a study, yet this consideration has not been systematically evaluated in any publication.
Results
We have examined the effect of discrete data selection criteria (qualification criteria for inclusion) and response thresholds (out-put filtering) on the number of significant genes reported by SAM. The use of a reduced data set by applying arbitrary restrictions vis-à-vis abundance calls (e.g. from D-chip) or application of the fold change (FC) option within SAM (named the FC hurdle hereafter), can substantially alter the significant gene list when running SAM in Microsoft Excel. We determined that for a given final FC criteria (e.g. 1.5 fold change) the FC hurdle applied within Microsoft Excel SAM alters the number of reported genes above the final FC criteria. The reason is that the FC hurdle changes the composition of the control data set, such that a different significance level (q-value) is obtained for any given gene. This effect can be so large that it changes subsequent post hoc analysis interpretation, such as ontology overrepresentation analysis.
Conclusion
Our results argue for caution when using SAM. All data sets analysed with SAM could be reanalysed taking into account the potential impact of the use of arbitrary thresholds to trim data sets before significance testing.
==== Body
Background
Response thresholds and exclusion criteria are applied when presenting a summary of a microarray study; otherwise the data set can be unmanageable. The precise effect of such criteria is, however, rarely discussed or investigated. We believe that many researchers are typically not aware of the effect that their chosen thresholds or 'qualification' criteria have had on their final set of "significant genes". A common example would be data exclusion. In studies using the Affymetrix platform the selection criteria typically uses the absent, moderate or present 'call' system, calculated with algorithms implemented in MAS5 (microarray suite 5 from Affymetrix) or D-chip [1]. The decision of whether the detection threshold is set to 10% or 20% (for example) will change the number of significant genes when the analysis is followed by the use of a parametric test with multiple testing corrections (for example). How predictable the imposition of such thresholds, on the composition of the output, is not clear.
A recent method to identify significant genes is "Significance Analysis of Microarrays" (SAM)[2]. An ISI search indicates that SAM is the most popular method employed for microarray analysis (635 citations of the original publication as of October 2004). In SAM, the relative difference (d(i)) is compared to the distribution of d(i) following random permutation of the sample categories. For each d(i), a certain proportion of all genes in the permutation set (control set) will be found to be 'significant' by chance and this parameter is then used to calculate a "False Discovery Rate" (FDR). This is presented as a q value for each gene in the final list of significant genes. The q-values are influenced by the variability in the data set. This implies that changes in the entire data set composition will affect the d(i) distribution in the permuted control set and thus the q-value assigned to a given gene. To what extent this alters the final output when using SAM or subsequent post-hoc analysis has so far not been discussed. As SAM is arguably the most widely utilized method in the microarray analysis field, we felt it was critical to evaluate these considerations.
The number of reported significant genes is influenced by the FC setting within SAM and the use of "Present/Absent" calls for data inclusion
The first point to emphasise is that we are examining the effect of a variable FC setting, implemented in the Excel SAM, on a final gene list with a fixed 1.5 FC criteria. Our principle findings can be extended to any relevant final FC criteria but in the example we provide we have focused on a 1.5 FC criteria, for simplicity. When using the FC setting, implemented in the Excel addin, the researcher selects a proportion of the all genes on the chip, and this selection is also utilised for the permutated control data set, however the settings from the full data set SAM analysis are maintained (s_0, and pi_0). The FC hurdle setting can therefore change the resulting q-values as genes that pass a certain FC when the original sample categories are used, are less likely to generate high d(i) when the categories are permutated. To test the extent of this effect, we performed SAM at several different FC hurdles within Excel and scored the number of genes reported at the final 1.5 FC criteria. A difference in the number of genes reported as significant above the final FC would indicate that by using the Excel SAM FC restriction setting, during SAM, we change the outcome by altering the d(i) distribution of the permutation data set.
We used three different biological data sets to assess how wide-spread any effects were. The first data set was a paired data set from a human skeletal muscle study which examined subjects before and after endurance training using the U95A-E platform (Affymetrix) [3]. The data was RMA normalized [4-6] and SAM was performed using different biological sample subgroups (groups were formed on the basis of a variety of physiological parameters) and chipset identity (A, B or D). Changing the FC setting in SAM (Excel) altered the final list of significant genes at the 1.5 FC criteria (Figure 1A–D). Importantly, the effect was not uniform across all conditions. For some samples a sequential increase in the FC hurdle in SAM correlated with an increased number of reported genes (Figure 1A–B) while under other conditions a very small change in FC had an apparently random impact on the composition of the significant gene list (e.g. Figure 1C–D). (The number of genes that passed each fold change criteria can be found in [Additional file 1]).
The second data set was derived from an in-vitro mouse senescence study performed on U74Av2 chips [7] and normalized using RMA [4-6]. When comparing two of the time points during the induction of senescence we were unable to observe any effect of FC selection within SAM on the yield of significant genes (Figure 2). We believe this reflected the very low q-values obtained when originally using SAM, which in turn most likely reflects the low experimental variation that one can achieve using in-vitro models.
The third data set is derived from a study of the aging human brain, containing 21 samples split into two categories, young and old (unpaired data) [8], and normalised using D-chip [1]. When varying the FC hurdle within SAM we again saw a large impact on the number of genes reported as being significant, above the 1.5 FC criteria (a q-value threshold of 1% was considered statistically significant similarly to the original report) (Figure 3A–B). The 'significant' gene list increased from 283 genes when using no FC hurdle (during SAM in Excel) to a maximum of 465 significant genes (67% more) when using a 1.51 FC hurdle within Excel SAM (Figure 3A).
A similar effect was observed when we examined the methods utilised by the original authors (20% "Present" call by D-chip). No FC hurdle generates 314 significant genes and a 1.51 FC generates 538 genes (Figure 3B). This is a 71% increase in "significant" genes associated with aging in human brain, despite the fact that the FC hurdle utilised in SAM was actually greater than the final FC of 1.5! Similar effects arise when other final FC criterions are used during SAM. For example if we only consider the significant genes that pass a final FC >2 criteria in the aging brain study, then 5% more >2 FC genes can be found if the FC hurdle within SAM is set to 2.0 compared to 1.5. Clearly, genes that are modulated to a large extent may be of high biological interest and thus our observation is important. Also, there are 73 more significant genes at the FC hurdle of 1.51 if the reduced data set is used compared the full data set (less genes in the data set gave more significant genes). This indicates that Present/Absent filtering also influences the outcome of the analysis, in this case increasing the number of genes defined as being modulated.
Changing the FC setting in SAM changes the reported q-value
The analysis presented above demonstrates that the q-value obtained for a specific gene depends on the FC hurdle applied during SAM in Excel. To monitor the q-values generated, for individual genes, we obtained the q-values during all SAM calculation using various FC hurdles for all genes that were reported as significant at the 1.51 FC setting (538 genes) in the brain aging study (Figure 4A). The highest q-value for a subset of the genes that passed the final fold change criteria was 3.6% when SAM was performed with a 1.0 FC hurdle. The same genes appear as being significant when the "optimal" (in the sense that these setting produced the largest significant gene list) Excel SAM FC hurdle setting 1.51 is used while the highest q-value reported was now only 0.97%.
Running SAM using different FC settings can change data interpretation
Often the main reason for carrying out a microarray experiment is to gain greater insight into the molecular processes that contribute to a complex biological phenotype. One standard method for carrying out such analysis is the use of gene-grouping, such as Gene ontology classification [9]. To address whether the biological interpretation may be influenced, we compared overrepresentation of classifications using EASE [10]. We selected the 314 genes and the 538 genes obtained in the brain aging study using the 1.0 and a 1.51 FC hurdles (described above) and calculated the overrepresented classifications. There was a considerable difference in the number of significantly over-represented classifications identified by EASE (figure 4B). 35 classifications were overrepresented in both gene lists, 8 were found in the GO analysis of the 1.0 FC list and 29 were unique to the 1.51 FC list. We feel it is unlikely that greater inclusion of randomly determined genes (i.e. false positives) would give rise to a significant increase in statistically enriched functional groups. This indicates that both the number of genes and the interpretation may be substantially altered by arbitrary data filtering, as exemplified by the use of the FC hurdle during the operation of Excel SAM or through the application of present-absent calls using e.g. D-chip.
Conclusion
The average researcher is highly dependent on the use of 'standard procedures' for their microarray analysis. An arbitrary filtering option in the Microsoft Excel Addin (we have called this the FC hurdle to distinguish from FC criteria – which is the final FC value selected by the researcher, to define a functionally significant change in gene expression) or data exclusion (e.g. present or absent call thresholds) can impact on a study, in a less than predictable manner. A clear problem also arises when SAM is utilised on different software platforms. In the R package Siggenes, no FC hurdle criteria can be made unless an additional programming function is implemented by the individual researcher. This is in contrast to the more widely used Microsoft Excel SAM Addin where the researcher can introduce a FC hurdle prior to the q-value calculations (while the SAM algorithm maintains the initial parameters from the analysis of the full data set). It is often unclear in the literature if SAM was performed in Excel or R; and if an FC hurdle was applied within SAM or if the fold change criteria was introduced after completing the operation of SAM, in EXCEL.
Indeed, one might question how robust the SAM methodology is, if it is heavily dependent on both pre SAM data selection and within SAM (Excel) data filtering. However, one of the appreciated strengths of SAM is that the real data set is used to estimate experimental variation. One could also question whether it is valid to reduce the data set prior to using SAM. It would seem intuitive that much of the data being removed using a FC hurdle during SAM operation would be below an acceptable response level to be considered as being biologically relevant. However, the FC hurdle may also remove data that is essential for an accurate estimation of the experimental variation. The challenge would then be to remove 'genuine' noise from non-expressing genes without removing genes that are genuinely expressed and necessary to approximate the data set variation. The effects will be pronounced in data sets demonstrating a large range of gene expression FC's or where significant inter experimental variation exists. It is clear, that investigators must be made aware that the impact of 'qualification criteria for inclusion' and 'out-put filtering' is less than predictable, when using SAM.
Methods
Data sets
Three data sets were used. The first is a human skeletal muscle study, comparing eight subjects across the U95A-E Affymetrix chips before and after endurance training [3]. A subset of this data set can be derived by creating a low responder group based on their improvement upon training. This subset is referred to as the low responder group in figure 1. The data can be obtained from the authors (JAT). The second data set is a part of an mouse in-vitro senescence study performed on U74Av2 (Affymetrix) [7]. Two conditions were selected for comparison: EpiA1-ts58 cells at the basal condition and EpiA1-ts58 cells after 72 hours of senescence induction. This data set can be downloaded from the journal web site in a MAS5 (Affymetrix microarray suite 5) normalised format or will be distributed in RMA normalised format by the authors (OL). The third data set is a brain aging study performed on the U95A chip (Affymetrix) and normalised using D-chip [8]. The authors separated their data set into two groups: young (<43 years old) and old (>72 years old) and we used the same grouping in our analysis. The authors further used a data discrimination based on "present" calls given by D-chip (20% present in all samples). We used both the full data set and the 20% data set which is referred to as the reduced data set. The data set can be access at GEO, accession number GSE1572.
SAM analysis
SAM analysis was performed using the Microsoft Excel addin v1.21. The analysis was performed using different settings of the "Fold change". We also performed SAM analysis using the R (R-project.org) package "siggenes" as a comparison to the Excel addin without using the fold change setting with consistent results.
Classification analysis
To look for overrepresented classifications we used EASE [10]. We used all possible classifications and considered a classification as positively overrepresented if the EASE score was lower then 0.05.
Abbreviations
SAM – significance analysis of microarrays
FDR – false discovery rate
FC – fold change
EF – extraction factor
MAS5 – microarray suite 5
RMA – robust multi array average
GEO – gene expression omnibus
Authors' contributions
OL – Hypothesis generation, practical work with all data sets and drafting of the manuscript
CW – Study design and revising the manuscript.
JAT – Hypothesis generation, practical work on the human muscle data section and drafting of the manuscript
Supplementary Material
Additional File 1
Genes that pass various FCs The additional file describes how many genes that passed various FCs from all three data sets
Click here for file
Figures and Tables
Figure 1 FC effects on the endurance training data set: SAM analysis was used at various fold changes studying the exercise data set while scoring genes with a q-value of <0.05 and FC>1.5. This was done to asses the effect of the fold change option in the SAM Excel addin on genes reported as significant at a higher fold change. The figure shows the number of scored genes using 4 different chip and sample combinations: (A) All eight subjects before and after training (totally 16 arrays) were compared in a paired analysis using the U95A chips. (B) All eight subjects before and after training (totally 16 arrays) were compared in a paired analysis using the U95B chips. (C) The reduced group consisting of low four low responders (totally 8 arrays) were compared in a paired analysis using the U95B chips. (D) The reduced group consisting of low four low responders (totally 8 arrays) were compared in a paired analysis using the U95D chips.
Figure 2 FC effects on the senescence data set: SAM analysis was used at various fold changes using the senescence data set while scoring genes with a q-value of <0.01 and FC>1.5. A comparison between non-senescent cells and senescent cells was used (two replicates of the senescent cells and four replicates of the non-senescent cells).
Figure 3 FC effects on the brain aging data set: SAM analysis at various fold changes using the brain aging data set (11 old samples and 10 young samples) while scoring genes with a q-value of <0.01 and FC>1.5. We used both the full data set and the reduced data set suggested by the authors. (A) The full data set. (B) The reduced data set (20% "present" calls by D-chip").
Figure 4 FC effects individual q-values: q-values of all genes scored as significant in the brain aging study (reduced data set) at FC 1.51 at other FC settings. Genes only acquires discrete q-values and all 538 genes are shown, but overlap. (B) Running SAM with different FC settings changes the biological interpretation: Venn diagram comparing the number of significantly overrepresented classifications (EASE score <0.05) using the reduced brain aging data set analysed either with a 1.0 FC setting (314 genes) or a 1.5 FC setting (538 genes).
==== Refs
Li C Hung Wong W Model-based analysis of oligonucleotide arrays: model validation, design issues and standard error application Genome Biol 2001 2 RESEARCH0032 11532216
Tusher VG Tibshirani R Chu G Significance analysis of microarrays applied to the ionizing radiation response Proc Natl Acad Sci U S A 2001 98 5116 5121 11309499 10.1073/pnas.091062498
Timmons JA Larsson O Jansson E Fischer H Gustafsson T Greenhaff PL Ridden J Rachman J Peyrard-Janvid M Wahlestedt C Sundberg CJ Human muscle gene expression responses to endurance training provide a novel perspective on Duchenne muscular dystrophy Faseb J 2005 19 750 760 15857889 10.1096/fj.04-1980com
Irizarry RA Bolstad BM Collin F Cope LM Hobbs B Speed TP Summaries of Affymetrix GeneChip probe level data Nucleic Acids Res 2003 31 e15 12582260 10.1093/nar/gng015
Bolstad BM Irizarry RA Astrand M Speed TP A comparison of normalization methods for high density oligonucleotide array data based on variance and bias Bioinformatics 2003 19 185 193 12538238 10.1093/bioinformatics/19.2.185
Irizarry RA Hobbs B Collin F Beazer-Barclay YD Antonellis KJ Scherf U Speed TP Exploration, normalization, and summaries of high density oligonucleotide array probe level data Biostatistics 2003 4 249 264 12925520 10.1093/biostatistics/4.2.249
Larsson O Scheele C Liang Z Moll J Karlsson C Wahlestedt C Kinetics of senescence-associated changes of gene expression in an epithelial, temperature-sensitive SV40 large T antigen model Cancer Res 2004 64 482 489 14744760
Lu T Pan Y Kao SY Li C Kohane I Chan J Yankner BA Gene regulation and DNA damage in the ageing human brain Nature 2004 429 883 891 15190254 10.1038/nature02661
Harris MA Clark J Ireland A Lomax J Ashburner M Foulger R Eilbeck K Lewis S Marshall B Mungall C Richter J Rubin GM Blake JA Bult C Dolan M Drabkin H Eppig JT Hill DP Ni L Ringwald M Balakrishnan R Cherry JM Christie KR Costanzo MC Dwight SS Engel S Fisk DG Hirschman JE Hong EL Nash RS Sethuraman A Theesfeld CL Botstein D Dolinski K Feierbach B Berardini T Mundodi S Rhee SY Apweiler R Barrell D Camon E Dimmer E Lee V Chisholm R Gaudet P Kibbe W Kishore R Schwarz EM Sternberg P Gwinn M Hannick L Wortman J Berriman M Wood V de la Cruz N Tonellato P Jaiswal P Seigfried T White R The Gene Ontology (GO) database and informatics resource Nucleic Acids Res 2004 32 D258 61 14681407 10.1093/nar/gkh066
Hosack DA Dennis GJ Sherman BT Lane HC Lempicki RA Identifying biological themes within lists of genes with EASE Genome Biol 2003 4 R70 14519205 10.1186/gb-2003-4-10-r70
| 15921534 | PMC1173086 | CC BY | 2021-01-04 16:02:49 | no | BMC Bioinformatics. 2005 May 29; 6:129 | utf-8 | BMC Bioinformatics | 2,005 | 10.1186/1471-2105-6-129 | oa_comm |
==== Front
BMC BioinformaticsBMC Bioinformatics1471-2105BioMed Central London 1471-2105-6-1321592707010.1186/1471-2105-6-132SoftwareGenerating quantitative models describing the sequence specificity of biological processes with the stabilized matrix method Peters Bjoern [email protected] Alessandro [email protected] La Jolla Institute for Allergy and Immunology, 3030 Bunker Hill Street, Suite 326, San Diego, CA 92109, USA2005 31 5 2005 6 132 132 21 1 2005 31 5 2005 Copyright © 2005 Peters and Sette; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Many processes in molecular biology involve the recognition of short sequences of nucleic-or amino acids, such as the binding of immunogenic peptides to major histocompatibility complex (MHC) molecules. From experimental data, a model of the sequence specificity of these processes can be constructed, such as a sequence motif, a scoring matrix or an artificial neural network. The purpose of these models is two-fold. First, they can provide a summary of experimental results, allowing for a deeper understanding of the mechanisms involved in sequence recognition. Second, such models can be used to predict the experimental outcome for yet untested sequences. In the past we reported the development of a method to generate such models called the Stabilized Matrix Method (SMM). This method has been successfully applied to predicting peptide binding to MHC molecules, peptide transport by the transporter associated with antigen presentation (TAP) and proteasomal cleavage of protein sequences.
Results
Herein we report the implementation of the SMM algorithm as a publicly available software package. Specific features determining the type of problems the method is most appropriate for are discussed. Advantageous features of the package are: (1) the output generated is easy to interpret, (2) input and output are both quantitative, (3) specific computational strategies to handle experimental noise are built in, (4) the algorithm is designed to effectively handle bounded experimental data, (5) experimental data from randomized peptide libraries and conventional peptides can easily be combined, and (6) it is possible to incorporate pair interactions between positions of a sequence.
Conclusion
Making the SMM method publicly available enables bioinformaticians and experimental biologists to easily access it, to compare its performance to other prediction methods, and to extend it to other applications.
==== Body
Background
Whenever experimental data is gathered to examine a process, researchers will try – implicitly or explicitly – to define a model describing the process. The purpose of building a model is to generalize the experimental data, allowing the prediction of new experimental outcomes, or to gain insights into the experimental process. In the biological sciences, models are often implicitly built and verbally formulated, such as "the proteasome preferably cleaves after hydrophobic amino acids". Such a model is easy to understand and often reflects all the knowledge that can be gathered from a few, difficult experiments. However, with the advent of high-throughput experiments to the biosciences, it has become feasible to generate more quantitative, mathematical models, based on large volumes of data. For the purpose of building a model, conducting experiments can be formally described as collecting pairs of experimental parameters x and experimental outcomes (measurements: ymeas). Building a model is then equivalent to finding a function f(x) = ypred ≈ ymeas. Herein, we call the model function f a prediction tool, and the experimental observations used to generate it its training set T = (x, ymeas).
Developing a prediction tool is a two step process. First, a general prediction method capable of generating specific tools has to be chosen, such as a certain type of neural network, classification tree, hidden markov model or regression function. This choice is to some degree determined by the experimental data available. However, only a few prediction methods are clearly unsuited for a certain type or amount of data, leaving several potentially appropriate methods to choose from. In practice, the personal experience of a scientist often determines which prediction method he applies, as learning to apply a new method is often more costly than the benefits of a slightly better model.
After a method is chosen, it is applied to the experimental data to generate a specific prediction tool. Several different terms are commonly used for this second step, such as 'supervised learning', 'fitting the model' or 'regression'. Each method has its own formalism describing how this is done, but essentially a method is capable of generating a certain class of functions, of which one is chosen, that minimizes the difference between measured and predicted experimental outcomes for the training set T.
Here we describe a computer program implementing the SMM prediction method, which can be applied to model the sequence specificity of quantifiable biological processes. In such experiments, the input parameter × corresponds to a sequences of amino-or nucleic acids, and the experimental outcome ymeas is a real numbers measuring the process efficiency. The method utilizes training sets in which the examined sequences all have the same length.
The SMM method was previously applied successfully to predictions of MHC binding [1], TAP transport [2] and proteasomal cleavage [3]. However, its software implementation was not made publicly available, because it relied on a commercial library with restrictive licensing terms. Also, applying the method to a new problem required manual changes in the source code, which is impracticable for an external user. Both of these issues are addressed in the software implementation made available here. In addition, this manuscript describes two specific features that we have found to be effective in generating high quality models and which can easily be utilized in other prediction methods, namely handling of bounded data and combinatorial peptide libraries.
The SMM software is not meant for 'classical' sequence analysis, which can be roughly defined as aligning related sequences in order to identify conserved residues or in order to generate classifiers which can identify additional related sequences. Rather, the typical application is the characterization of a sequence recognition event, such as the sequence specific cleavage efficiency of a protease. This characterization does not assume any evolutionary relationship between different recognized sequences. In terms of scientific fields, that makes the SMM software aimed at applications in biochemistry or molecular biology.
Implementation
Code
The SMM algorithm is implemented in C++ code. Only standard libraries or freely available external libraries were used. The two external libraries are Tinyxml [4] to handle the XML input and output and the Gnu Scientific Library [5] for efficient vector and matrix operations. The source code has been compiled and tested using Visual C++ on a windows system and using g++ (1.5 or above) on a Debian and Suse Linux system. A windows executable is also available. The source code, documentation and examples are available as additional files 1 and 2 of this manuscript, and on the project homepage at .
On a standard 2.6 GHz Pentium 4 PC running windows XP, the creation of a prediction tool from a typical set of training data containing 300 8-mer peptides takes about 10 minutes.
Input and output
The program expects an XML document as its standard input. A more sophisticated (graphical) user interface is not likely to be of great interest for the projected user community, most of which will probably call the executable file from a script or integrate the code into an existing program. The XML input document contains either training data to generate a new tool (Figure 1) or sequences for which a prediction should be made with a previously generated tool. The output of the program is again in XML format. For all types of input and output, XML schemas defining their exact structure are supplied. The schemas contain annotation for each input element, documenting their intended use. A simplified alternative input format exists for the most common application, namely the generation of a scoring matrix from a set of standard amino acid sequences. Several example input files are supplied with the program, which should make it easy for users to create similar input files with their own data.
Core algorithm
An amino acid can be encoded as a binary vector of length 20, with zeros at all positions except the one coding for the specific amino acid. Extending this notation, a peptide of length N can be encoded as an N*20 binary vector. The same conversion can be made for nucleic residues, resulting in N*4 length vectors. Any fixed length sequence can be converted into a fixed length binary vector following similar rules. The SMM algorithm expects such a vector as the experimental input parameter 'x'.
For a set of experiments, the vectors tx (where tx indicates the transposed vector x) can be stacked up resulting in a matrix H. An example for a set of nucleic sequences is shown in Figure 2. The matrix H is multiplied by a vector w which assigns a weight to each possible residue at each position in the sequence. This generates a vector of predictions ypred
H w = ypred (1)
From a given training set of sequences encoded in H with measured values ymeas, the 'correct' values for w can be found by minimizing the difference between the predicted values ypred and the measured values ymeas according to a norm || ||. To suppress the effect of noise in the experimental data, a second term is added to the minimization:
||H w - ymeas|| + tw Λ w → minimum, (2)
in which Λ is a positive scalar or a diagonal matrix with positive entries. To better understand the effect of the Λ term, consider first minimizing (2) with Λ set to zero. In this case, the optimal entries for the weight vector w minimize the difference between predicted (ypred) and measured (ymeas) values. Minimizing (2) with a non-zero value for Λ results in a shift of the optimal entries in w towards values closer to zero, especially for entries in w that do not significantly decrease the distance between predicted and measured values. This technique, generally called regularization, suppresses the effect of noise in the measured data ymeas on the entries in the weight vector w. Refer to [6] or [7] for a general introduction to regularization. If the || || norm is simply the sum squared error (or L2 norm), equation (2) can be solved analytically for any given value of Λ to:
w = (tHH + Λ)-1 tH ymeas (3)
The optimal value for Λ can then be determined by cross validation: The experimental data points corresponding to rows of (H, ymeas) are randomly separated into training sets Ti = (H, ymeas)train i and blind sets (H, ymeas)blind i. For a given Λ, equation (3) is used to calculate wi for each training set Ti. These wi can then be used to make predictions for their corresponding blind sets. Summing the distances for all blind predictions gives the cross validated distance Φ:
Φ(Λ) = Σi || Hblind i wi(Λ) -yblind i || (4)
Minimizing Φ as a function of Λ therefore corresponds to minimizing the cross validated distance by 'damping' the influence of coefficients in w which are susceptible to noise.
As the resulting optimal value for Λ and the corresponding wi are somewhat influenced by the split into training and blind sets, the same procedure is repeated several times with different splits, which is called bagging [8]. The final w is generated by averaging over all optimal wi generated in the cross validation and bagging repeats.
Results and discussion
The following sections describe specific properties of the SMM method, and are meant to serve as a guideline when and how to apply it. Additional data validating the SMM algorithm and comparing it with other prediction methods can be found in previous publications [1-3].
Linear model
If no pair coefficients are incorporated, the output vector w of the SMM method is a standard 'scoring matrix', which quantifies the contribution of each residue at each position in the input sequence to the prediction. Such a matrix is easy to interpret and analyze without requiring any additional software or expert knowledge of how the matrix was generated, which is especially important when communicating results to experimentalists. Several methods predicting peptide binding to MHC molecules take this approach, e.g. [9-12], and a comparative study showed that simple statistical methods to generate matrices can perform better than more complex artificial neural networks if the amount of data is limited [13].
Using such a linear model implicitly assumes that the influence of residues at each position in the sequence on the measured value can be considered independent and additive. This has to be a reasonable first approximation in order to successfully apply the SMM method, even if pair coefficients are incorporated. This is the main difference to general learning algorithms such as neural networks, which can in principle model any functional relationship between sequences and measurements.
Quantitative data
The experimental measurements that serve as input to the SMM method and the predicted output are quantitative, not binary. For example, in the case of peptide binding to MHC molecules, IC50 values quantifying binding affinities are used, and not a classification into binding and non-binding peptides.
If different representations of the quantitative data are possible, such as either IC50 or log(IC50) values, a representation should be chosen in which the ymeas values approximately follow a normal distribution. Otherwise the SMM predictions, which are sums of independent contributions and therefore roughly normally distributed themselves, will not be able to fit the experimental data well. In the case of binding affinities, this means log(IC50) values should be used, as IC50 values themselves are usually log normal distributed.
Noisy data
Experimental measurements inevitably contain noise. This will cause problems when building models that take the measured values to be exact. Accordingly, the SMM method incorporates a regularization parameter Λ (equation 2), which corresponds to preferring a simpler solution with 'smooth' values for w to one that exactly reproduces observations. In the first SMM applications [1,2], Λ was a scalar, in which case this approach is called Ridge regression or zero-order regularization. Choosing a scalar value implicitly assumes that the level of signal to noise is roughly the same at each position in the input sequence. In the current version, Λ can also be chosen as sequence position dependent, which is sometimes called local Ridge regression. As shown for an example in Figure 3, this makes Λ into a diagonal matrix in which all Λi values belonging to residues at the same sequence position are set to the same value. For a sequence of length N, there are N different Λi values. For a number of training sets containing peptide binding data to MHC molecules, we compared the prediction performance achieved using a position specific matrix Λi to a scalar Λ. The position specific regularization nearly always resulted in better predictions. The difference was especially large if the influence of different sequence positions varied greatly (data not shown).
Bounded data
Any experimental technique generates measured values contained within a finite range. For example, in many biological experiments a "zero" measurement usually means that the actual value is below the experimental resolution, not that the actual value is 0. Similarly, very large values beyond the expected sensitivity limit are no longer quantitatively accurate. These data points at the upper or lower boundaries of the sensitivity range do not convey the same information as quantified values, but they still do contain information. In the case of MHC binding data available to us, approximately 20% of peptides fall in this category.
The SMM method is, to the best of our knowledge, the only method designed to extract information from such boundary values. This is done by means of the novel L2<> norm, illustrated in Table 1. For example, if an experimental measurement corresponds to an upper boundary ymeas > z, and the predicted value is greater than z, then the distance between ymeas and ypred is zero. This norm has the useful property that any analytical solution according to the L2 norm can be converted into a solution according to the L2<> norm through an iterative process: First, all measurements including boundary values are treated as normal values, and the solution using the L2 norm is found. In a second step, for each ypred, ymeas value pair for which the L2<> norm would be zero, the ymeas value is set to its corresponding ypred value. For these ymeas* values, the distance L2(ypred, ymeas*) = L2<> (ypred, ymeas). These ymeas* values are then used to solve again according to the L2 norm. This process is repeated until the ymeas* values no longer change, as illustrated in Figure 4.
Randomized peptide library data
As stated before, the experimental data used as input for the SMM method consists of same length amino-or nucleic acid sequences associated with a quantitative measurement. When designing an experiment, the selection of sequences to test can introduce bias into the training data, for example by over-or under-representing residues at specific sequence positions. One way to avoid this is the use of randomized peptide libraries, also known as positional scanning combinatorial peptide libraries, which are mixtures of peptides of the same length. In a given library, all peptides have one residue in common at a fixed position and a random mixture of amino acids at all other positions. For example, the library XAXXXXXX contains 8-mer peptides with a common Alanine at position 2. Such libraries can be used to directly measure the influence of their common residue, by comparing their measured process efficiency to that of the completely randomized library XXXXXXXX. In the case of 8-mer peptides, 160 library experiments are sufficient to characterize the influence of each residue at each position. The results of such a complete scan can be summarized in a scoring matrix. This approach has been used successfully in many different experimental systems [14-17]
A novel feature of the SMM method is that it can combine data from these two sources. When the SMM algorithm is given experimental data from individual peptides and from a randomized library summarized in a scoring matrix matlib, it simply subtracts the values predicted by matlib from each individual peptide measurement. These y'meas = ymeas - ypred,lib values are then used to generate a second scoring matrix mat'. The final SMM scoring matrix is simply the sum of the two: matcombined = mat' + matlib. Figure 5 compares the performance of this combined approach to that of a prediction based on peptide or library experiments alone. If enough peptide data is present (roughly the same number as matrix parameters), the combined prediction is better than that of the library matrix alone. At all data points, the combined prediction is better than that using the peptides alone. Importantly, this simple strategy of subtracting library predictions can be used in combination with any prediction method, and is likely to generate similar results, as it effectively increases the training set size. To visualize the prediction quality associated with the distances reported in Figure 5, Figure 6 depicts a scatter plot of the predicted and measured binding affinity for individual peptides corresponding to the data point with the lowest distance in Figure 5.
Introducing pair coefficients
Pair coefficients quantify the contribution of a pair of residues to the measured value that deviates from the sum of their individual contributions. The form of equation (1) remains unchanged if pair coefficients are introduced in the same binary notations as the individual coefficients. Figure 2 gives an example how a set of nucleic sequences is transformed into a matrix H, if two such pair coefficients are taken into account. Note that the number of possible pair coefficients is very large. For a sequence of three nucleic acids, there are already (3*4) * (2*4) / 2 = 48 pair coefficients. For a 9-mer peptide, (9*20) * (8 * 20) / 2 = 14400 pair coefficients exist. To the best of our knowledge, only the SMM method and the additive method [18] explicitly quantify the influence of pair coefficients.
Since most training sets contain only a few hundred measurements, determination of the exact values of all pair coefficients is not feasible. To overcome this difficulty, the SMM algorithm limits the number of pair coefficients to be determined. First, only coefficients for which sufficient training data exists are taken into account. As a rule of thumb, 5 sequences containing the same pair of residues at the same positions have to be present in the training set for a pair coefficient to be considered. In a second filtering step, only pair coefficients for which the information in the training set is reasonably consistent are retained. In the previous SMM version, this used to be determined by multiple fitting of pair coefficients and discarding those for which a sign change was observed. In the current version, a much faster approach is used. First, a scoring matrix is calculated for the training set without any pair coefficients. Then, for each pair coefficient the predicted and measured values for the sequences containing it are compared. Only if a large enough majority (>60%) of measured values are above or below the matrix based predictions is the pair coefficient retained. The remaining pair coefficients are determined in complete analogy to the scoring matrix itself, but with a scalar Λ value.
We tested the effect of incorporating pair coefficients on prediction quality compared to using a scoring matrix alone for a number of training sets containing peptide to MHC binding data. The pair coefficients showed a consistent positive contribution for large training sets, which comprise more measurements than 1.5 times the number of scoring matrix coefficients. However, the improvement is rather small, as reported before in [1]. This makes it reasonable to ignore pair coefficients if the simplicity of a scoring matrix is more valuable than a small improvement in prediction quality.
If higher order sequence interactions such as those described by pair coefficients are expected to be the dominant influence on experimental outcomes, other prediction methods may be better suited than the SMM method. For example, by choosing a different sequence representation than the binary vectors, the information in the training set can be generalized, thereby effectively reducing the degrees of freedom in the input parameters [19]. This allows applying general higher order learning algorithms such as artificial neural networks even with limited input data.
Conclusion
The SMM method generates quantitative models of the sequence specificity of biological processes, which in turn can be used to understand and predict these processes. It has previously been shown to perform very well compared to other prediction methods and tools for three specific types of experimental data [1-3]. However, it is difficult to generalize a comparison between different methods, due to two main problems. First, the training data sets utilized in different studies are often not available, so that when comparing tools generated by different methods it is often unclear when good performance is due to a superior method or a better (larger) set of training data. Second, generating tools from the same training set can be difficult, because publications that make the tools available, often only describe the basic principle of the method used.
To overcome this second obstacle, we herein presented a computer program implementing the SMM method. Significant effort was devoted to ensuring that the program is robust, documented, cross platform compatible and generates reasonable output without requiring additional parameters. Also, any commercial libraries previously utilized were removed to allow free distribution of the code. This will permit any interested user to apply the SMM method with reasonable effort, allowing for the most important validation: application to scientific practice.
Finally, we believe that two strategies demonstrated in this manuscript will be valuable in combination with other prediction methods as well. First, our strategy for the inclusion of experimental data gathered with randomized peptide libraries can be directly transferred to any prediction method. When other experimental data is limited and data from a combinatorial library is available, this should always have a positive effect on prediction quality. Secondly, the L2<> norm can be applied as an error function for other prediction methods. This will increase the amount of training data effectively available to prediction methods requiring quantitative input, by enabling them to handle experimental boundary values.
Availability and requirements
Project name: smm
Project home page:
Operating system(s): Platform independent
Programming language: C++
Other requirements: The Gnu Scientific Library (GSL) has to be installed
License: None for the smm code, but GSL requires the GNU GPL license
Any restrictions to use by non-academics: None
Authors' contributions
BP conceived of this study and implemented the software, AS participated in the design of the software and helped to draft the manuscript. All authors read and approved the final manuscript.
Supplementary Material
Additional File 1
A .zip file containing the SMM source code, documentation and examples for windows systems.
Click here for file
Additional File 2
A .tar.gz file containing the SMM source code, documentation and examples for linux systems.
Click here for file
Acknowledgements
The authors want to acknowledge the help of Emrah Kostem in adopting the source code to g++ and John Sidney for critically reading the manuscript. This work was supported by the National Institutes of Health Contract HHSN26620040006C
Figures and Tables
Figure 1 Input training data. The <TrainingData> element consists of a series of <DataPoints> (2). Each contains a sequence and a measurement value. The characters allowed in <Sequence> are specified in <Alphabet> (1), and the number of characters has to correspond to <SequenceLength> (1). In this example, <Alphabet> and <SequenceLength> specify 8-mer peptides in single letter amino acid code. Each measurement can optionally be associated with a threshold (3) that can either be <Greater> or <Lesser>, signaling that the measurement corresponds to an upper or lower boundary of measurable values.
Figure 2 Converting sequences into matrices. Input sequences of three nucleic acids each are converted to rows of a matrix H. The first column of each row is set to 1, which serves as a constant offset added to each prediction. Columns A1 to T1 contain a binary representation of the first residue in the sequence, in which all columns are set to zero except the one corresponding to the residue. The same is repeated for the second and third residue in the sequence in columns A2 to T2 and A3 to T3. The two last columns G1A3 and A2A3 contain pair coefficients explained at the end of the results section. They are set to one if the two specified residues are present in the input sequence at the two specified positions and zero otherwise. Multiplying matrix H with the weight vector w results in a vector ypred of predicted values for the sequences. Rows A1 to T3 of vector w are commonly written as a 'scoring matrix' which quantifies the contribution of each possible residue at each position to the prediction. Rows G1A3 and A2A3 of vector w quantify the impact of the pair coefficients.
Figure 3 Sequence position dependent regularization. Example for the regularization term tw Λ w in equation (2). The weight vector w corresponds to a scoring matrix for three nucleic acids as in Figure 2, but without pair coefficients. The diagonal matrix Λ has three different values Λ1, Λ2 and Λ3 effecting values in vector w corresponding to sequence positions 1, 2 and 3. There is no regularization penalty on the 'Offset' value.
Figure 4 Iterative model fitting using the L2<> norm. In this example, the model is a linear function which is fitted to a set of paired values (x, ymeas). For two of the x values (x = 3 and x = 5), the measured values are thresholds (Greater 3). Fitting a linear function to paired values according to the L2 norm corresponds to the standard linear regression. A depicts the model fit (straight line) to the measured values (black boxes), ignoring any thresholds. For x = 5, the model value ypred taken from the regression curve is 3.4, above the measured threshold value 3. Therefore, in the next iteration the ymeas* value is set to the model value 3.4. B shows the new linear regression with the adjusted ymeas* values. This procedure is repeated until the ymeas* values no longer change (8 iterations, panel C).
Figure 5 Combining peptide and library data improves prediction quality. A set of 449 9-mer peptides with measured affinities for TAP taken from [20] was split into 5 blind sets. For each of these blind sets, predictions where made from different size subsets of the remaining peptides. The x-axis depicts the number of peptides in these subsets used for generating predictions using either the peptides alone (circles) or in combination with data from a combinatorial peptide library (squares). The dashed line displays the prediction of the library alone, which was taken from [15]. The y-axis depicts the L2<> distance of the predictions for the combined 5 blind sets.
Figure 6 Visualization of prediction quality. Scatter plot of predicted vs. measured affinity for peptide binding to TAP. The depicted prediction corresponds to the data point in figure 5 with the lowest cross-validated distance, in which 350 peptides and the peptide library were used for training.
Table 1 The L2<> norm
Measurement L2<> distance
ypred > ymeas ypred < ymeas
Quantitative (no threshold) (ypred-ymeas)2 (ypred-ymeas)2
Upper boundary (threshold: greater) 0 (ypred-ymeas)2
Lower boundary (threshold: lesser) (ypred-ymeas)2 0
==== Refs
Peters B Tong W Sidney J Sette A Weng Z Examining the independent binding assumption for binding of peptide epitopes to MHC-I molecules Bioinformatics 2003 19 1765 1772 14512347 10.1093/bioinformatics/btg247
Peters B Bulik S Tampe R Van Endert PM Holzhutter HG Identifying MHC class I epitopes by predicting the TAP transport efficiency of epitope precursors J Immunol 2003 171 1741 1749 12902473
Tenzer S Peters B Bulik S Schoor O Lemmel C Schatz MM Kloetzel PM Rammensee HG Schild H Holzhutter HG Modeling the MHC class I pathway by combining predictions of proteasomal cleavage,TAP transport and MHC class I binding Cell Mol Life Sci 2005 62 1025 1037 15868101 10.1007/s00018-005-4528-2
Thomason L TinyXml
Gnu Scientific Library (GSL)
Orr MJL Introduction to Radial Basis Function Networks
Press WH Teukolsky SA Vetterling WT Flannery BP Numerical Recipes in C 1992 2 , Cambridge University Press
Breiman L Bagging Predictors Machine Learning 1996 24 123 140
Parker KC Bednarek MA Coligan JE Scheme for ranking potential HLA-A2 binding peptides based on independent binding of individual peptide side-chains J Immunol 1994 152 163 175 8254189
Rammensee H Bachmann J Emmerich NP Bachor OA Stevanovic S SYFPEITHI: database for MHC ligands and peptide motifs Immunogenetics 1999 50 213 219 10602881 10.1007/s002510050595
Sidney J Dzuris JL Newman MJ Johnson RP Kaur A Amitinder K Walker CM Appella E Mothe B Watkins DI Sette A Definition of the Mamu A*01 peptide binding specificity: application to the identification of wild-type and optimized ligands from simian immunodeficiency virus regulatory proteins J Immunol 2000 165 6387 6399 11086077
Lauemoller SL Holm A Hilden J Brunak S Holst Nissen M Stryhn A Ostergaard Pedersen L Buus S Quantitative predictions of peptide binding to MHC class I molecules using specificity matrices and anchor-stratified calibrations Tissue Antigens 2001 57 405 414 11556965 10.1034/j.1399-0039.2001.057005405.x
Yu K Petrovsky N Schonbach C Koh JY Brusic V Methods for prediction of peptide binding to MHC molecules: a comparative study Mol Med 2002 8 137 148 12142545
Pinilla C Martin R Gran B Appel JR Boggiano C Wilson DB Houghten RA Exploring immunological specificity using synthetic peptide combinatorial libraries Curr Opin Immunol 1999 11 193 202 10322159 10.1016/S0952-7915(99)80033-8
Uebel S Kraas W Kienle S Wiesmuller KH Jung G Tampe R Recognition principle of the TAP transporter disclosed by combinatorial peptide libraries Proc Natl Acad Sci U S A 1997 94 8976 8981 9256420 10.1073/pnas.94.17.8976
Udaka K Wiesmuller KH Kienle S Jung G Tamamura H Yamagishi H Okumura K Walden P Suto T Kawasaki T An automated prediction of MHC class I-binding peptides based on positional scanning with peptide libraries Immunogenetics 2000 51 816 828 10970096 10.1007/s002510000217
Nazif T Bogyo M Global analysis of proteasomal substrate specificity using positional-scanning libraries of covalent inhibitors Proc Natl Acad Sci U S A 2001 98 2967 2972 11248015 10.1073/pnas.061028898
Doytchinova IA Blythe MJ Flower DR Additive Method for the Prediction of Protein-Peptide Binding Affinity. Application to the MHC Class I Molecule HLA-A*0201 Journal of Proteome Research 2002 1 263 272 12645903 10.1021/pr015513z
Nielsen M Lundegaard C Worning P Lauemoller SL Lamberth K Buus S Brunak S Lund O Reliable prediction of T-cell epitopes using neural networks with novel sequence representations Protein Sci 2003 12 1007 1017 12717023 10.1110/ps.0239403
Daniel S Brusic V Caillat-Zucman S Petrovsky N Harrison L Riganelli D Sinigaglia F Gallazzi F Hammer J van Endert PM Relationship between peptide selectivities of human transporters associated with antigen processing and HLA class I molecules J Immunol 1998 161 617 624 9670935
| 15927070 | PMC1173087 | CC BY | 2021-01-04 16:02:47 | no | BMC Bioinformatics. 2005 May 31; 6:132 | utf-8 | BMC Bioinformatics | 2,005 | 10.1186/1471-2105-6-132 | oa_comm |
==== Front
BMC BioinformaticsBMC Bioinformatics1471-2105BioMed Central London 1471-2105-6-1341592708110.1186/1471-2105-6-134Research ArticleEmpirical codon substitution matrix Schneider Adrian [email protected] Gina M [email protected] Gaston H [email protected] Institute of Computational Science, Swiss Federal Institute of Technology, Zurich, Switzerland2005 1 6 2005 6 134 134 20 1 2005 1 6 2005 Copyright © 2005 Schneider et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Codon substitution probabilities are used in many types of molecular evolution studies such as determining Ka/Ks ratios, creating ancestral DNA sequences or aligning coding DNA. Until the recent dramatic increase in genomic data enabled construction of empirical matrices, researchers relied on parameterized models of codon evolution. Here we present the first empirical codon substitution matrix entirely built from alignments of coding sequences from vertebrate DNA and thus provide an alternative to parameterized models of codon evolution.
Results
A set of 17,502 alignments of orthologous sequences from five vertebrate genomes yielded 8.3 million aligned codons from which the number of substitutions between codons were counted. From this data, both a probability matrix and a matrix of similarity scores were computed. They are 64 × 64 matrices describing the substitutions between all codons. Substitutions from sense codons to stop codons are not considered, resulting in block diagonal matrices consisting of 61 × 61 entries for the sense codons and 3 × 3 entries for the stop codons.
Conclusion
The amount of genomic data currently available allowed for the construction of an empirical codon substitution matrix. However, more sequence data is still needed to construct matrices from different subsets of DNA, specific to kingdoms, evolutionary distance or different amount of synonymous change. Codon mutation matrices have advantages for alignments up to medium evolutionary distances and for usages that require DNA such as ancestral reconstruction of DNA sequences and the calculation of Ka/Ks ratios.
==== Body
Background
Models for codon substitutions are used in computational biology for a wide range of applications such as reconstructing ancestral DNA sequences, determining Ka/Ks ratios to identify periods of adaptive evolution and aligning coding DNA.
Methods for estimating mutation matrices from observed substitutions in sequence alignments of proteins were established by Dayhoff [1]. These matrices contain the probabilities of amino acid mutations for a given period of evolution and have long been used for scoring protein sequence alignments, evolutionary studies and homology searches.
More than a decade ago, when large-scale protein databases became established, several amino acid substitution matrices based on observed mutation counts in protein alignments were constructed [2-4], replacing the original Dayhoff matrices that were based on relatively few alignments.
However, to describe substitutions at the codon level, parameterized models have been developed [5,6] and are widely used in the study of molecular evolution.
In the same way that the growth of protein databases allowed refined construction of amino acid substitution matrices, the recent increase of nucleotide sequence data made it possible to apply these methods at the codon level. The matrices presented here were constructed using the approach of Gonnet [4]. This implies that pairwise alignments using full dynamic programming [7,8] were used in order to count the observed transitions between codons. The sequence data was taken from the complete vertebrate genome databases of ENSEMBL [9].
Results
The additional files contain the 64 × 64 matrices presented here. Various aspects of the matrices will be discussed in this section. We present the matrix with the exact counts of the observed substitutions (Additional file 1), the matrix containing the substitution probabilities derived therefrom (Additional file 2) and a matrix containing similarity scores for all possible substitutions (Additional file 3).
Substitution counts
The 17,502 alignments that have been used to construct the matrix presented here contained 8.3 million aligned codon pairs. From each of these aligned pairs, the number of each of the 3730 (61 × 61 + 3 × 3) possible substitutions were counted. The difference between the numbers of frequent and rare substitution is high with the most frequent substitution (the GAG identity) being observed 153,040 times, and the rarest substitution, between TGG and GAG, being counted only 45 times, about 3400 times less often.
To estimate the precision of the count of the rarest substitution, a binomial distribution of the counts can be assumed. The substitution with minimal count cmin occurs with probability p = 45/(8.3·106) = 5.4·10-6. The variance of a binomial distribution is σ2 = N(1 - p)p and thus for very small p, the variance of cmin is almost equal to cmin = 45 and the standard deviation σ is 6.7.
This means that although a very large amount of data is used to construct the matrix, it is just enough to produce codon counts that are of a tolerable accuracy for rare transitions. Only a further increase of high-quality genomic data will allow the clustering of the data into specific subsets. These possibilities will be discussed below.
Substitution probabilities
The mutation matrix M constructed from the counts contains the substitution probabilities for the individual codons. Entry Mi,j gives the probability that codon j mutates to codon i. (As a consequence, each column of M sums to 1).
A convenient measure to express the amount of mutations in a matrix is the percentage identity
with fi being the natural frequencies of the codons. For the matrix reported here, p is .35, meaning that in the alignments used, 65% of the codons have undergone substitution (to any other codon, thereby involving up to three nucleotide changes).
It is also possible to calculate the percentage of identical amino acids resulting from this matrix:
In the second sum, i goes over all codons that code for the same amino acid as j does. The result for pAA is .69, therefore 31% of the amino acids are expected to mutate. This allows the determination of the relationship between the codon substitution matrices and amino acid substitution matrices, because the amino acid PAM distance can be derived from the percentage of amino acid identity.
Analogously to the definition of 1 PAM, 1 Codon-PAM can be defined as the distance at which 1% of the codons undergo substitution. Again, a codon substitution can involve up to three nucleotide base changes. The substitution matrix for any distance d is approximated by raising the 1 CodonPAM matrix to the power of d.
The relationship between CodonPAM, PAM and f2 is shown in Figure 2. It shows that amino acid PAM increases almost linearly with CodonPAM. The curve is slightly steeper for the low distances and flattens with increasing distance. The amount of synonymous substitution decays from 1 to .51 (f2 being a measure of synonymous mutation described in the Methods section).
Mutation scores
Since the substitution probabilities are influenced by the codon frequencies, it is not possible to see directly which substitutions occur more than expected and which occur less. This issue is corrected in the scoring matrix D, where entry Di,j expresses how much more likely it is that codons i and j were derived from a common ancestral codon compared to a random pairing of them. A higher score for a transition means that this transition is indeed more likely than one with a lower score. The scoring matrix is symmetric, i.e. the transition from codon i to j has the same score as the transition from j to i.
Table 1 displays average scores for different categories of substitutions. It confirms the fact that synonymous substitution scores are generally higher than non-synonymous scores. But it can also be seen that as more nucleotides change, the scores become lower. Synonymous substitutions in which all three bases change, have lower scores than non-synonymous substitutions with only one base change.
Discussion
Synonymous mutations
It has been observed that different genes have different Ka/Ks ratios and therefore the fraction of synonymous substitutions will differ between different gene pairs having a certain PAM distance. This is because there are no strong selective constraints on synonymous substitutions and therefore the number of these substitutions accumulates in a clock-like manner [10] while the number of nonsynonymous substitutions is governed by functional constraints.
Increasing amounts of genomic data would allow the construction and comparison of matrices from alignments with differing amounts of synonymous and non-synonymous substitutions, representing a two-dimensional array of matrices, where one dimension is the evolutionary distance and the other corresponds to the amount of synonymous change. Unfortunately, the current size of the nucleotide databases does not yet allow such a clustering of the available data. Instead, the alignments selected to construct the matrices were filtered to fall within a window of synonymous mutations, thereby excluding the most extreme values. (see the Methods section for details). Figure 1 shows the distribution of the alignments' f2 values.
Range of applicability
One possible application of scoring matrices is protein and coding DNA alignment. In order to compare alignments based on amino acid substitution matrices and the codon matrices presented here, the likelihood scores are compared. Since these scores express the probability ratios of the two sequences having evolved from a common ancestor to them being aligned by random chance, they serve as a confidence measure of an alignment. The higher the score, the higher the likelihood that the alignment is by reasons of ancestry than by random chance.
As the likelihood scores serve as an indicator of alignment quality, orthologous sequences for species pairs of various distance and classes were used to determine when codon matrix based alignments produced higher scores than amino-acid PAM matrices.
Table 2 displays for several pairs of species, the number of orthologs used to perform the alignment analysis, the average PAM distance between these orthologs (found by selecting the highest-scoring PAM matrix) and the average ratio of codon based scores to amino acid based scores. A number greater than 1 means that on an average, the codon based scores were higher.
The result is that for closely related species, the codon based scores are always higher, but the more distant two species are, the better the performance of the amino acid based alignments. An interesting point is that although codon mutations in different sets of species were found to be significantly different (χ2 tests, data not shown here), the above finding holds not only for the vertebrates, from which the matrices were constructed, but also for the invertebrates, yeasts and even bacteria.
From the results in Table 2, a PAM distance smaller than 50 would favor the use of codon substitution matrices instead of amino acid based matrices.
Conclusion
Because codon substitution matrices are substantially bigger than amino acid matrices and also because some of the substitutions are extremely rare compared to the most frequent ones, large amounts of genomic data are necessary to model the transitions accurately. The 17,502 alignments used here produce enough aligned codons to fulfill this criterium, but do not allow further clustering of the data set in order to create more specific matrices.
The codon substitution matrix presented here is to our knowledge the first based entirely on empirical data and can serve in many fields of computational biology. We have found that at long distances, when the synonymous mutations have reached saturation, amino acid matrices are better suited for alignments and long-distance homology searching. Codon mutation matrices have advantages for alignment up to medium evolutionary distances and for usages that require DNA such as ancestral reconstruction of DNA sequences and the calculation of Ka/Ks ratios.
Methods
The basic methods to create scoring matrices are well established. The construction of codon substitution matrices is analogous to that of amino acid transition matrices. The main difference lies in the fact that codon matrices are much larger (4096 elements (64 × 64) instead of 400 elements (20 × 20)). In addition, the stop codons need special consideration. Substitutions between stop codons and sense codons are assumed to be very rare because the effect of such substitutions on the function of the protein would probably be very serious thus the chance of acceptance is very small and usually limited to the 3' end of the nucleotide sequence. This makes it almost impossible to observe such events. Therefore, these substitutions are not included in the matrices presented here. Substitutions between stop codons, however, are counted and thus also contained in the matrices. This means that the 64 × 64 matrices are block diagonal composed of a 61 × 61 matrix for the coding codons and a 3 × 3 matrix describing substitutions between stop codons.
Using orthologs
The matrices are constructed from pairwise alignments of orthologous sequences from five vertebrates – human (Homo sapiens), mouse (Mus musculus), chicken (Gallus gallus), frog (Xenopus tropicalis) and zebrafish (Brachydanio rerio). The complete genome databases from ENSEMBL [9] were used for this purpose. Using only orthologs has the advantage that no gene is overrepresented in the data set. This is because a particular gene can have many paralogous genes in a genome, but we allowed at most one ortholog per other genome.
Circular tours
When counting the substitutions in alignments from all pairs of species, substitutions that occurred early in the tree are counted more often than those that happened later, because paths between two species include the branches near the root more often than those near the leaves. This bias can be prevented by using only species pairs along a circular tour. This way every branch of the tree (and therefore every substitution that ever happened in the history of the genes) examined, is counted at most twice. Concretely, this means that only the orthologs between human and mouse (3107 pairs), mouse and chicken (3691 pairs), chicken and frog (3671 pairs), frog and fish (3441 pairs) and fish and human (3592 pairs) are counted, resulting in 17,502 alignments.
Counting substitutions
These alignments must fulfill several criteria: 1) they should all be of similar evolutionary distance because substitution probability depends on evolutionary distance. A trade-off exists for the acceptable range of distances as including a broad range of distances, increases the amount of data but at the same time blurs the distance specific information. 2) The alignments must be of a distance that is high enough to allow the observation of rarer substitutions. 3) There must be enough alignments to have statistically significant data for the rare substitutions. After some observations performed on a subset of the data, a distance range of 25 to 60 PAM (57% to 78% identity) of the protein alignments was found to best satisfy these criteria.
Another selection criterium was based on the amount of synonymous substitutions between the sequences to eliminate saturation effects from the observed synonymous substitutions. One way to estimate the amount of synonymous substitution is f2, the percentage of conserved synonymous codons at two-fold redundant amino acid sites. Two identical sequences have an f2 value of 1 and it will decay to a value near .5 for increasing amounts of substitutions. An f2 range between .50 and .95 was found to exclude the most extreme cases of synonymous substitutions while leaving enough alignments to fill the matrices.
Figure 1 shows the distribution of f2 values for all alignments within the PAM range of 25 to 60. The sequence pairs with f2 values between .50 and .95 are shown in green and were used to construct the matrices, while the alignments corresponding to the red bins were discarded.
Full dynamic programming [4,7,8] was employed in order to construct the alignments. The DNA alignment was obtained by mapping the coding DNA to the aligned proteins. Directly aligning the DNA was not yet possible, because no a priori knowledge about codon similarities was assumed. However, in the refinement steps (see further below), the DNA itself was aligned using the codon substitution matrices from the previous refinement round.
Once the sequences were aligned, the actual substitution matrices could be computed. This included counting the observed codon substitutions in the collected alignments and storing them in a 64 × 64 count matrix C. Since the direction of a substitution is not known, for each observed substitution between codons i and j, Ci,j as well as Cj,i is increased by 1/2. Insertion or deletion sites were ignored since they provide no information about actual substitutions. From the count matrix, the mutation matrix was derived according to equation 3:
Calculating similarity scores
The transition scores for a given substitution matrix express the relative probabilities of two codons originating from a common ancestor compared to the probability of them being paired by random chance. The logarithm is taken to make the scores additive, thereby speeding up the computation of alignment scores. D is calculated as
where fi is the frequency of codon i in the observed data set. The factor 10 is used for purely historical reasons.
In an iterative process, the sequence pairs were aligned again with dynamic programming [7,8] but this time directly on the codon sequences using the substitution matrices obtained before. Exponentiation of the mutation matrix was used to approximate matrices for different evolutionary distances [12], allowing a maximum-likelihood estimation of the best-fitting matrix to align the sequences. From these new alignments new mutation matrices and finally scoring matrices were constructed in the way described above, until after six iterations a sufficient convergence of the matrix was reached.
Authors' contributions
GMC initiated and guided this project and contributed to the programming. AS did the majority of the programming and analysis. Some of the work was based on previous research by GHG. All work was supervised by GHG. AS and GMC drafted the manuscript which was approved by GHG.
Supplementary Material
Additional File 1
The 64 × 64 matrix containing the observed substitution counts as described in the results section.
Click here for file
Additional File 2
The 64 × 64 matrix containing the substitution probabilities.
Click here for file
Additional File 3
The 64 × 64 matrix of the transition scores.
Click here for file
Acknowledgements
GMC wishes to acknowledge Michael T. Hallett, Jan Norberg, and Xianghong Zhou for starting this project. The authors wish to thank Peter von Rohr, Markus Friberg, Daniel Margadant, Christophe Dessimoz and the anonymous reviewers for careful reading and helpful suggestions.
Figures and Tables
Figure 1 f2 histogram. Histogram of the f2 values from the 17,502 alignments used to construct the matrix.
Figure 2 CodonPAM vs PAM and f2
Table 1 Analysis of the scores. Average scores for different categories of substitutions. The stop codons are excluded from this analysis.
n Substitutions Avg. Score
Identity 61 12.9
Synonymous: all 87 8.7
Synonymous: 1 base change 67 10.0
Synonymous: 2 base changes 14 6.6
Synonymous: 3 base changes 6 -1.7
Non-syn.: all 1743 -7.3
Non-syn.: 1 base change 196 -1.3
Non-syn.: 2 base changes 770 -5.9
Non-syn.: 3 base changes 777 -10.3
All Substitutions 1891 -5.9
Table 2 Range of applicability. Ratios of likelihood scores for amino acid and codon based alignments for orthologs between several species pairs, where N is the number of orthologs used.
N Avg. PAM Scores ratio
Homo sapiens
vs. Mus musculus 14655 17.4 1.150
vs. Gallus gallus 9272 29.3 1.060
vs. X. tropicalis 9953 39.1 1.026
vs. B. rerio 7507 43.7 1.013
Drosophila melanogaster
vs. A. gambiae 5059 57.3 .995
vs. H. sapiens 3371 77.5 .959
vs. C. elegans 2156 88.8 .945
Saccharomyces cerevisiae
vs. C. glabrata 3467 52.7 1.002
vs. A. gossypii 2909 61.4 .978
vs. H. sapiens 1187 94.1 .931
Escherichia coli
vs. E. coli strain O6 3156 2.0 1.323
vs. Salmonella typhi 2557 14.2 1.067
vs. P. aeruginosa 1234 71.6 .980
vs. B. japonicum 765 90.2 .959
==== Refs
Dayhoff MO Schwartz RM Orcutt BC Dayhoff MO A model for evolutionary change in proteins Atlas of Protein Sequence and Structure 1978 5 National Biomedical Research Foundation 345 352
Henikoff S Henikoff JG Amino acid substitution matrices from protein blocks Proc Natl Acad Sci USA 1992 89 10915 19 1438297
Jones DT Taylor WR Thornton JM The Rapid Generation of Mutation Data Matrices from Protein Sequences Comput Applic Biosci 1992 8 275 282
Gonnet GH Cohen MA Benner SA Exhaustive matching of the entire protein sequence database Science 1992 256 1443 1445 1604319
Goldman N Yang Z A Codon-based Model of Nucleotide Substitution for Protein-coding DNA Sequences Mol Biol Evol 1994 11 725 736 7968486
Yang Z Nielsen R Goldman N Pedersen AMK Codon-Substitution Models for Heterogeneous Selection Pressure at Amino Acid Sites Genetics 2000 155 432 449
Needleman SB Wunsch CD A general method applicable to the search for similarities in the amino acid sequence of two proteins J Mol Biol 1970 48 443 453 5420325 10.1016/0022-2836(70)90057-4
Gotoh O improved algorithm for matching biological sequences J Mol Biol 1982 162 705 708 7166760 10.1016/0022-2836(82)90398-9
Hubbard T Andrews D Caccamo M Cameron G Chen Y Clamp M Clarke L Coates G Cox T Cunningham F Curwen V Cutts T Down T Durbin R Fernandez-Suarez XM Gilbert J Hammond M Herrero J Hotz H Howe K Iyer V Jekosch K Kahari A Kasprzyk A Keefe D Keenan S Kokocinsci F London D Longden I McVicker G Melsopp C Meidl P Potter S Proctor G Rae M Rios D Schuster M Searle S Severin J Slater G Smedley D Smith J Spooner W Stabenau A Stalker J Storey R Trevanion S Ureta-Vidal A Vogel J White S Woodwark C Birney E Ensembl 2005 Nucl Acids Res 2005 33 D447 453 15608235
Miyata T Yasunaga T Nishida T Nucleotide Sequence Divergence and Functional Constraint in mRNA Evolution Proc Natl Acad Sci USA 1980 77 7328 32 6938980
Kumar S Subramanian S Mutation Rates in Mammalian Genomes Proc Natl Acad Sci USA 2002 999 803 808 10.1073/pnas.022629899
Cox D Miller H The Theory of Stochastic Processes 1965 Chapman and Hall, London
| 15927081 | PMC1173088 | CC BY | 2021-01-04 16:02:48 | no | BMC Bioinformatics. 2005 Jun 1; 6:134 | utf-8 | BMC Bioinformatics | 2,005 | 10.1186/1471-2105-6-134 | oa_comm |
==== Front
BMC BioinformaticsBMC Bioinformatics1471-2105BioMed Central London 1471-2105-6-1421594147710.1186/1471-2105-6-142CommentaryWhich gene did you mean? Mons Barend [email protected] Biosemantics Group Rotterdam, Department of Medical Informatics, Erasmus MC – University Medical Center Rotterdam, P.O. Box 1738, NL-3000 DR Rotterdam, the Netherlands2 MGC – Human and Clinical Genetics, Leiden University Medical Center, Wassenaarseweg 72, 2333AL LEIDEN, the Netherlands2005 7 6 2005 6 142 142 26 5 2005 7 6 2005 Copyright © 2005 Mons; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Computational Biology needs computer-readable information records. Increasingly, meta-analysed and pre-digested information is being used in the follow up of high throughput experiments and other investigations that yield massive data sets. Semantic enrichment of plain text is crucial for computer aided analysis. In general people will think about semantic tagging as just another form of text mining, and that term has quite a negative connotation in the minds of some biologists who have been disappointed by classical approaches of text mining. Efforts so far have tried to develop tools and technologies that retrospectively extract the correct information from text, which is usually full of ambiguities. Although remarkable results have been obtained in experimental circumstances, the wide spread use of information mining tools is lagging behind earlier expectations. This commentary proposes to make semantic tagging an integral process to electronic publishing.
==== Body
Text mining? ...................Why bury it first and then mine it again?
Recently, Sir Tim Berners-Lee, the inventor of the Web, said: 'Life sciences are particularly suitable for pioneering the Semantic Web. For example, within drug discovery, many databases and information systems used by drug researchers are already in, or are ready to be transformed to, machine-readable formats' [1].
Well, we need our breed of optimists to drive things, and he is obviously one of us.
Too much to read
Bioinformatics increasingly consists of computer-aided meta-analysis of dispersed articles and database records to assist researchers in the interpretation of massive datasets. Epidemiological studies and high throughput technologies such as microarrays nowadays often lead to sets of potentially relevant papers being identified that surpass human capability for reading, interpretation and synthesis. Aggregating information from many records, followed by logical association of the concepts represented in the full dataset is what I generally refer to here as meta-analysis. Unfortunately, most of the information in the current information sources is not easily accessible, nor, due to ambiguity of the description of concepts in textual format, is it easily readable by computer programs.
Semantics: a crucial addition to text
If all words had only one possible meaning, computers would be perfectly able to analyse texts. In reality however, words, terms and phrases in text are highly ambiguous. Knowledgeable people have few problems with these ambiguities when they read, because they use context to disambiguate 'on the fly'. Even when fed a lot of semantically sound background information, however, computers currently lag far behind humans in their ability to interpret natural language. Therefore, proper semantic tagging of concepts in texts is crucial to make Computational Biology truly viable. Electronic Publishing has so far only scratched the surface of what is needed.
Open Access publication shows great potential, andis essential for effective information mining, but it will not achieve its full potential if information continues to be buried in plain text. Having true semantic mark up combined with open access for mining is an urgent need to make possible a computational approach to life sciences.
Databases and pathway tools are not enough
Of course, we have our curated databases, increasingly equipped with fancy analysis and visualisation tools. These databases hold established knowledge on molecules, their interactions and pathways. These databases are definitely useful tools to rapidly get a rough view on 'what may be switched on or involved'. However, the inherent restrictions and downsides of such databases include the great efforts that are needed to keep the error level acceptably low and to keep them up-to-date. Furthermore, biological complexity is more than a composition of multiple, man-imagined pathways. Thus free text continues to be a crucial source of cutting edge information for scientists
A further reason for the continued value of free text is that pre-digested information in databases only contains explicit knowledge and will therefore at best cough up 'what somebody already knew', although I as an individual may not be aware of it. Real serendipitous finding of new things and the association between concepts beyond direct co-occurrence is not supported by most existing tools.
However, text is a nightmare for computers
Unfortunately, free text records are a nightmare of ambiguity. Synonyms and homonyms riddle the records and, in particular, gene and protein names/symbols appear to be impossible to resolve with complete accuracy, based on their textual expression. In an ideal world, scientists would mention formal identifiers from recognized data bases such as EntrezGene or SwissProt in the text, rather than their favourite synonym of the molecule.
With traditional search-based text retrieval tools, this problem was little more than a recurrent nuisance, and current traditional search engine providers probably couldn't care less, as their users are satisfied when they 'find what they want on page one'. But now that computational meta-analysis of textual records is increasingly needed, and the underlying datasets may often consist of tens of thousands of papers, it becomes impossible to manually weed out problems relating to synonyms and homonyms.
So, like it or not, we have to face the challenge of semantic enrichment
Before any meta-analysis algorithm can be meaningfully applied, semantic analysis and tagging of the underlying texts with unique identifiers for individual concepts is needed. Ideally, this process should be a one-off effort. In a perfect scenario, communication between scientists would take place entirely at the unique concept level. However, this is not reality. What was clear and straightforward in the mind of the researcher after completing the experiments gets lost in a variety of ambiguous expressions during the writing process and ambiguities are produced every minute. Therefore scientific writing can somewhat cynically be called information burying. Authors are actually inclined and stimulated to use variable expressions and synonyms, aphorisms and the like to make their article 'readable'. This will not change in the foreseeable future and this means we have to face the challenge of semantic tagging of these texts. To keep the challenge manageable, I will restrain this argument to term identification and not include full analysis of the language structure of sentences as attempted by Natural Language Processing approaches.
Will authors do it for us?
Scientific text is dry enough as it stands. Should we therefore even contemplate attempts to force authors to make it semantically correct and uniform, according to strict nomenclature or worse, using structured data entry?
I would argue that not only would this approach be completely unfeasible, given the creative and individualistic minds of the producers of scientific knowledge, but in addition, the result of hypothetical success would lead to a totally dull form of scientific literature. In the end, no matter what computational aids we offer, researchers will always keep reading for final evidence. So, we need to make things computer-digestible in the background.
Will computers do it for us?
With the emerging, improved named entity tagging and semantic tagging technologies, a far more elegant and practical solution is available or just around the corner. Correct (computer) recognition of the concepts denoted by words and phrases in free-text, and the semantic enrichment that comes with it, greatly facilitates direct meta-analysis of subsets of the literature. This pre-processing step also facilitates much more accurate cross-linking of information between articles and databases.
If yes, why not?
It is surprising that publishers have so far taken almost no steps in this direction, even though it holds almost limitless potential, and it is clear that adding value to plain text is the only perspective publishers may have to charge for textual records in the future. Simple, technically feasible additions to current ontology-based semantic tagging software would allow the development of 'tag as you type' tools that normalise and map ambiguous terms in text to the unique concept they denote and to the corresponding ontologies.
The semantic tagging of new and existing text, notably the well over 14 million papers represented in Medline, seems a daunting perspective at first glance. Researchers are neither educated nor encouraged to take a semantic network approach when publishing their data. As a consequence, even decades after electronic publishing became commonplace, most papers are still ending up as dead, non-interactive pages rusting silently away in electronic archives until a search engine happens to be fed with the correct combination of keywords to retrieve them.
Or...will computers and authors do it together?
In my opinion, author-interactive publication tools should not force the writing scientist to use specific terms from pre-structured lists and nomenclatures. Trying to do exactly that, is what made most efforts of nomenclature standardization ineffective. In contrast, the very valuable efforts of the HGNC's, Entrezgenes and SwissProts of this world should be used to disambiguate terms on the fly and only ask the author for assistance in the rare cases the ontology driven system can not make an informed decision about the meaning of a term, for example in case a homonym is used without sufficiently distinguishing context surrounding it. If a title such as: 'Epidemiological considerations of BSE' is typed, the system is unlikely to be able to decide whether the author meant Breast Self Examination or Bovine Spongiform Encephalopathy. If no further context follows, the author could be prompted to resolve the ambiguity. However, if someone decides that he likes EBV more than Human Herpesvirus 4, or she prefers CD154 over TNFSF5, the author should not be forced to change that in the text, as long as the semantic tag added to that term in the background is linked to the unique concept identifier of the virus or the gene in the leading ontologies and nomenclature data bases (see figure 1). Obviously, some extra work will be asked from the author, but not anywhere near as much as most critics of the semantic web idea seem to expect.
In general, the expectation would be that the vast majority of relevant concepts in biomedical text could be correctly tagged on the fly and in the background without bothering the author at all, other than to resolve the occasional ambiguity, and to review the overall markup once complete.
Yes, but..
Obviously, the critics of the Semantic Web approach will bring in their arguments about the difficulties with tagging the legacy documents and the issue of the rapidly developing knowledge, reflecting in ontology changes. Obviously they have a potential point: If only recently published documents are being tagged, computational tools that rely on the tagging will be very restricted in their resources. The technological approach proposed here will enable us to tag existing texts on the fly with high accuracy, by taking care of the 'easy tagging' and interact with the author or the reader only to resolve the few remaining ambiguities. Moreover, as the tagging is not necessarily static, updated ontologies will lead to (optional) updated proposed tags each time the text is retrieved. Tagging would thus effectively be limited to texts that are still used. If an article is never retrieved by anyone it is probably of limited urgency to tag it.
So, let's do it!
Given the enormous impact a collective semantic enrichment effort would make, particularly on many aspects of bioinformatics research and computational biology, this process should have started many years ago. The Open Access publishers, but BMC Bioinformatics in particular, should take the lead and promote the use of semantic tagging, probably starting at one of the time points at which stubborn scientists like me are most likely to accept any guidance, and that is when they submit a manuscript.
Figures and Tables
Figure 1 The part of text of this editorial that was marked in italics was fed to an existing semantic tagging tool and it can be seen in the figure how different expressions are mapped to the same concept number.
==== Refs
| 15941477 | PMC1173089 | CC BY | 2021-01-04 16:02:48 | no | BMC Bioinformatics. 2005 Jun 7; 6:142 | utf-8 | BMC Bioinformatics | 2,005 | 10.1186/1471-2105-6-142 | oa_comm |
==== Front
BMC BiolBMC Biology1741-7007BioMed Central London 1741-7007-3-131588820910.1186/1741-7007-3-13Research ArticleThe TyrA family of aromatic-pathway dehydrogenases in phylogenetic context Song Jian [email protected] Carol A [email protected] Murray [email protected] Roy A [email protected] Los Alamos National Laboratory, Los Alamos, New Mexico, 87545, USA2 Emerson Hall, University of Florida, P.O. Box 14425, Gainesville, Florida, 32604-2425, USA2005 12 5 2005 3 13 13 19 2 2005 12 5 2005 Copyright © 2005 Song et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
The TyrA protein family includes members that catalyze two dehydrogenase reactions in distinct pathways leading to L-tyrosine and a third reaction that is not part of tyrosine biosynthesis. Family members share a catalytic core region of about 30 kDa, where inhibitors operate competitively by acting as substrate mimics. This protein family typifies many that are challenging for bioinformatic analysis because of relatively modest sequence conservation and small size.
Results
Phylogenetic relationships of TyrA domains were evaluated in the context of combinatorial patterns of specificity for the two substrates, as well as the presence or absence of a variety of fusions. An interactive tool is provided for prediction of substrate specificity. Interactive alignments for a suite of catalytic-core TyrA domains of differing specificity are also provided to facilitate phylogenetic analysis. tyrA membership in apparent operons (or supraoperons) was examined, and patterns of conserved synteny in relationship to organismal positions on the 16S rRNA tree were ascertained for members of the domain Bacteria. A number of aromatic-pathway genes (hisHb, aroF, aroQ) have fused with tyrA, and it must be more than coincidental that the free-standing counterparts of all of the latter fused genes exhibit a distinct trace of syntenic association.
Conclusion
We propose that the ancestral TyrA dehydrogenase had broad specificity for both the cyclohexadienyl and pyridine nucleotide substrates. Indeed, TyrA proteins of this type persist today, but it is also common to find instances of narrowed substrate specificities, as well as of acquisition via gene fusion of additional catalytic domains or regulatory domains. In some clades a qualitative change associated with either narrowed substrate specificity or gene fusion has produced an evolutionary "jump" in the vertical genealogy of TyrA homologs. The evolutionary history of gene organizations that include tyrA can be deduced in genome assemblages of sufficiently close relatives, the most fruitful opportunities currently being in the Proteobacteria. The evolution of TyrA proteins within the broader context of how their regulation evolved and to what extent TyrA co-evolved with other genes as common members of aromatic-pathway regulons is now feasible as an emerging topic of ongoing inquiry.
==== Body
Background
Dehydrogenases dedicated to L-tyrosine (TYR) biosynthesis comprise a family of TyrA homologs that have different specificities for the cyclohexadienyl substrate: ones specific for L-arogenate (AGN), ones specific for prephenate (PPA), and those that are able to use both [1,2]. Figure 1 illustrates the biochemical relationship of these specificities to divergent transformations beginning with chorismate (CHA) utilization and converging on TYR formation. Compounding this complexity, a given TyrA enzyme having any of the aforementioned cyclohexadienyl specificities may be specific for NAD+ or NADP+, or may use both. This is consistent with a growing appreciation [3,4] that different substrate specificities are often accommodated across a given protein family that nevertheless maintains a common scaffold of fundamental reaction chemistry. Even within the single category of broad TyrA specificity, there is a continuum ranging from examples where alternative substrates are accepted equally well to other cases where one substrate may be preferred by an order of magnitude or more. Table 1 provides a key to the nomenclature used to identify the various possible substrate-utilization combinations (both cyclohexadienyl and pyridine nucleotide) exhibited by TyrA proteins.
The TyrA family is typical of many protein families in that its members have a relatively small core domain that is not highly conserved. As such, substantial challenges for bioinformatic analysis are posed. Here we have not only carried out a labor-intensive manual analysis, but we have also developed tools intended to facilitate and refine follow-on studies of this protein family in the genome era. The approaches implemented in this study with the TYR segment of aromatic biosynthesis hopefully can serve as a template for forthcoming integrant analyses of other pathway segments of aromatic biosynthesis, and indeed for metabolic subsystems in general.
This manuscript contains three broad sections. First, the biochemical and enzymological complexity of the TyrA protein family is presented in terms of the diversity that exists in nature with respect to substrate specificity and the association of the core domain with other catalytic or regulatory domains. Secondly, the genomic colinear organization of tyrA genes with other genes is evaluated, i.e., tyrA is considered in its syntenic context. Thirdly, tyrA is evaluated in its context of regulation. These three sections are tied together in a framework of evolutionary perspective.
Results and discussion
Background of TyrA diversity
Our evolutionary analysis is limited by the amount of information that can be managed in a single study, with the focus fixed upon the domain Bacteria (due to the relative density of genome representation for Bacteria in the public databases). However, in order to show where future expansion of the analysis might lead, the selection of TyrA proteins in Fig. 2 are from all three domains of life, i.e., Bacteria, Archaea, and Eukarya (lower eukaryotes and higher plants). For practicality of presentation, numerous orphan (i.e., without close relatives) TyrA sequences are not shown, and not all members of a given group are necessarily included. The main purposes of the radial tree shown in Fig. 2 are: (i) to illustrate that TyrA proteins of major phylogenetic groupings are generally congruent with 16S rRNA groupings and (ii) to convey a snapshot visualization of the overall complexity of the TyrA protein family from the vantage point of its varied substrate specificities as well as its multiple fusion partners.
As an illustration of the detailed information that follows, note that the TyrA sequences from the beta Proteobacteria at five o'clock in Fig. 2 form a cohesive cluster (termed a 'congruency group'). In this clade there exists a proposed ancestral background of broad specificity where either AGN or PPA in combination with either NAD+ or NADP+ could be used. This profile of broad substrate use (which can be denoted as NAD(P)TyrAc; see Table 1) generally persists in the beta Proteobacteria. From this background, narrowed specificities for the AGN/NADP+ couple emerged once in the lineage represented by Nitrosomonas europaea (Fig. 2; dark blue line), narrowed specificity for NAD+ emerged once in species of Neisseria (orange line), and fusion of tyrAc with aroF (which encodes enolpyruvylshikimate-3-P synthase, the sixth enzyme in the common pathway of aromatic biosynthesis; see [5,6] for nomenclature used) occurred recently within the Burkholderia lineage. These character-state transformations appear to occur with relative ease, and independent emergence of the same character states can be seen elsewhere in the tree.
Phylogenetically congruent TyrA groupings
Multiple alignments of catalytic-core domains
A phylogenetic tree is only as good as the input alignment. An optimal multiple alignment of TyrA homologs requires a trimmed set of sequences that corresponds to the catalytic-core domain. Alignment of sequences with non-homologous N-terminal fusions (such as with chorismate mutase• (AroQ•), HisHb•, or plant transit peptides•; note the convention of using a bullet to indicate the fusion point of one domain with another domain) will make them appear to be more closely related than they actually are because residues in the non-homologous N-terminal regions find matches at random. Likewise, those TyrA sequences with C-terminal fusions (such as with •AroF, •ACT, or •REG) will appear to be anomalously close to one another. Even enzyme proteins that have much greater sequence conservation and amino-acid lengths than TyrA proteins cannot reasonably be expected to yield a protein tree that would be congruent over an extensive phylogenetic range with the overall 16S rRNA tree. However, if genome representation is sufficiently dense within a range of closely related organisms, 16S rRNA congruency with a given protein can be expected within that range of organisms provided that (i) the particular functional role has been retained and (ii) lateral gene transfer has not occurred to obscure the relationship. This expectation follows from the outcome of a detailed analysis of tryptophan-pathway proteins in Bacteria [7,8].
Congruency within major clades
TyrA sequences from higher-plant and yeast Eukarya form cohesive clusters. Genome representation among Archaea is still relatively limited. (Fig. 2 does reveal, however, that genes encoding TyrA proteins in Archaea have experienced various catalytic- and regulatory-domain fusions at least as frequently as those in Bacteria). Eventual expansion of both the tryptophan-pathway and tyrosine-pathway analyses to Archaea should be quite interesting.
The great majority of TyrA sequences available are from Bacteria, and one can see (by inspection of the major clades supported by high bootstrap values in Fig. 2) a qualitatively apparent congruence of TyrA-tree sub-sections with 16S rRNA expectations of vertical genealogy. Thus, all cyanobacteria possess a NADPTyrAa type of TyrA enzyme, and this is a very cohesive grouping. A few of the larger cyanobacterial genomes have a co-existing second enzyme of the TyrAc_Δ type (discussed in detail later). The low-GC gram-positive bacteria (Bacillus/Staphylococcus/Enterococcus/Listeria) exhibit the NADTyrAp pattern of specificity and also possess a C-terminal domain (ACT) of allosteric regulation. It is interesting that the TyrAp•ACT proteins of the Streptococcus lineage (at eight o'clock in Fig. 2) differ from the main low-GC clade in possessing broad specificity for pyridine nucleotides (as indicated with black line color). The most parsimonious evolutionary conclusion would be that in the low-GC gram-positive grouping, acquisition of the ACT domain and narrowed specificity for prephenate preceded narrowed specificity for NAD+. Thus, the latter event occurred after divergence of the Streptococcus lineage from the remainder of the low-GC clade. Members of the subclass taxon Actinobacteridae (mostly actinomycetes) possess AGN-specific TyrA enzymes (light blue fill color in Fig. 2), but they separate into two distinct groups that correlate either with broad specificity for pyridine nucleotides (Actinobacteridae_1) or a NAD+-specific pattern (Actinobacteridae_2). The Proteobacteria are discussed immediately below.
Proteobacteria
By far the greatest genomic density available is for Proteobacteria, the group of Bacteria that includes purple bacteria and their relatives. The various divisions of Proteobacteria, as currently named, lack hierarchical equivalence. For example, the epsilon and delta divisions branch from much deeper positions on the phylogenetic tree than do the alpha Proteobacteria. As genome representation expands for epsilon and delta Proteobacteria, it is probable that these will subdivide to newly named groupings of approximate hierarchical equivalence with alpha Proteobacteria. The most recently diverged Proteobacteria are the beta and gamma divisions. From the combination of our previous analysis of tryptophan biosynthesis [7,8], TYR biosynthesis (this paper), and other segments of aromatic biosynthesis (unpublished data), we find it useful to separate "upper-gamma" Proteobacteria from "lower-gamma" Proteobacteria (an "enteric lineage" with Shewanella oneidensis as approximately the most divergent member). This separation is because the beta Proteobacteria and the upper-gamma Proteobacteria exhibit a smooth continuity of relatively few evolutionary events with respect to aromatic biosynthesis, in striking contrast to extraordinarily dynamic evolutionary events in the lower-gamma Proteobacteria. As a consequence, the lower-gamma Proteobacteria are much more distinct (in terms of aromatic biosynthesis) from the upper-gamma Proteobacteria than the upper-gamma are from the beta Proteobacteria.
Figure 2 shows that alpha, beta and epsilon divisions of Proteobacteria form phylogenetically coherent clusters with respect to their TyrA proteins. Although delta Proteobacteria fall into two well-separated groupings denoted as Delta_1 and Delta_2, this should not be surprising since these groupings diverge at a deep level on the 16S rRNA tree where genome representation is poor. In addition, the Myxococcus xanthus TyrA sequence, currently an orphan (three o'clock in Fig. 2), represents a third divergent lineage in delta Proetobacteria. In contrast to delta Proteobacteria, genomic representation for the gamma Proteobacteria is relatively good. Nevertheless their TyrA sequences separate into several well-spaced groupings, albeit for entirely different reasons. In this case, the split seen between two clades of these fairly close relatives (upper-gamma and lower-gamma) is attributed to particularly dynamic evolutionary events compressed into a relatively short time span in the lower-gamma Proteobacteria. (We refer to such a dynamic divergence as an evolutionary jump; see the next section.) Note that the allocation of upper-gamma and lower-gamma Proteobacteria to separate TyrA congruency groups is not the same as being incongruent. It is quite possible that as new genomes come on line, new and intermediate TyrA sequences may result in the merging of the foregoing two congruency groups (currently tyrosine congruency group 1 (TyrCG-1) and tyrosine congruency group 2 (TyrCG-2)).
Comparison of tryptophan and tyrosine congruency groups
Although the true extent of lateral gene transfer (LGT) at present must be described as intensely controversial, there is little doubt that any given organism is mosaic with respect to some unknown fraction of its gene repertoire. Our "accounting" system for keeping track of proteins that are faithful to the vertical genealogy is to formulate congruency groupings that are defined by congruence of given protein-tree clusters to a section of the 16S rRNA tree. Ultimately this information will reveal which organisms are "pure" with respect to the vertical inheritance of a given pathway or pathway segment. Our congruency groups are intended to be fluid, in that with the continued availability of new sequences, a previous orphan sequence may very well become the seed for a new congruency group. On the other hand, previously separate congruency groups have the potential to merge. (See Methods for more information.) The present tyrosine congruency groups are listed on the AroPath website [9].
Seven tryptophan congruency groups in Bacteria were previously formulated [8] based upon the correspondence of cohesive clusters in trees of Trp-protein concatenates with sections of 16S rRNA trees. The information input for formulation of tryptophan congruency groups is of greater quality than for tyrosine congruency groups because seven-protein concatenates could be used for the former. On the other hand, the broad information input supporting tyrosine congruency groups in this study is more comprehensive because of greater genome availability. Tryptophan congruency group 1 (TrpCG-1) corresponds perfectly with the organisms represented in TyrCG-1, these being the lower-gamma Proteobacteria (enteric lineage). The upper-gamma Proteobacteria (TyrCG-2) and the beta Proteobacteria (tyrosine congruency group 3; TyrCG-3) are represented by different tyrosine congruency groups. In contrast, the membership of tryptophan congruency group 2 (TrpCG-2) includes both the upper-gamma Proteobacteria and the beta Proteobacteria. The latter merging probably reflects the advantage conferred by the greater information content of the concatenated sequences used to define tryptophan congruency groups.
Species of Xylella and Xanthomonas are usually referred to as gamma Proteobacteria. They probably represent an outlying deeply branching lineage, although trees based on concatenated strings of proteins [10] or 16S rRNA [11] position them with beta Proteobacteria. In any event, Trp-protein concatenate trees placed Xylella and Xanthomonas within TrpCG-2, which contains both upper-gamma and beta Proteobacteria. In contrast, the TyrA domains from Xylella and Xanthomonas were well separated (at about two o'clock in Fig. 2) from those of any other organism. This might simply be due to the limited resolving power of a single protein in combination with too few close relatives. (Note that single Trp-protein trees sometimes failed to achieve the congruency-group placements that were resolved by seven-protein Trp concatenates [8]). An additional clue may be relevant. The TyrA proteins from the Xylella/Xanthomonas genera possess an ACT domain, which has not been observed in any other proteobacterial TyrA proteins thus far. In view of this, origin by LGT seems to be a distinct possibility, but with the important caveat that no likely genome donors are yet obvious on the criterion of sequence similarity. Perhaps more likely is the following possible explanation that postulates a basis for accelerated divergence. The TyrA domains of Xanthomonas/Xylella proteins have an indel structuring (insertions and/or deletions) that places them within the TyrAc_Δ specificity subclass (see below). We suggest (see below) that such indel structuring reflects interaction of the core TyrA domain with an extra-domain extension. Thus, selection for amino acid changes accomplishing a new domain-domain interaction could account for accelerated divergence of the Xanthomonas/Xylella sequences on the TyrA tree (Fig. 2).
Cohesive tryptophan congruency groups of the alpha Proteobacteria (tryptophan congruency group 3; TrpCG-3) and the cyanobacteria (tryptophan congruency group 4; TrpCG-4) match up well with the corresponding tyrosine congruency groups (tyrosine congruency group 4 (TyrCG-4) and tyrosine congruency group 8 (TyrCG-8), respectively). The TyrA proteins of epsilon Proteobacteria define a cohesive tyrosine congruency group (tyrosine congruency group 5; TyrCG-5), whereas the Trp-protein concatenates of epsilon Proteobacteria did not exhibit a coherent congruency group, due at least in part to LGT [8]. The delta Proteobacteria separate into two distinct tyrosine congruency groups: Delta_1 (tyrosine congruency group 6; TyrCG-6) and Delta_2 (tyrosine congruency group 7; TyrCG-7), as shown in Fig. 2. It is likely that corresponding tryptophan congruency groups exist (work in progress), but at the time of the Xie et al. study [8] only Trp-pathway protein concatenates for Desulfovibrio vulgaris (Delta_2) and Geobacter sulfurreducens (Delta_1) were available, and they were provisionally listed as "orphans". In the present work TyrA sequences from Deinococcus radiodurans and Thermus thermophilus are the sole members of tyrosine congruency group 12 (TyrCG-12). At the time of the Trp-pathway work, the genome of Thermus was unavailable and the Deinococcus concatenate was listed as an orphan. It is expected that the Deinococcus and Thermus concatenates will now seed a new tryptophan congruency group.
Whereas tryptophan congruency group 5 (TrpCG-5) is defined by cohesive concatenates from actinomycete bacteria, the TyrA proteins from the same organisms separated into two distinct congruency groups. It is intriguing that this partitioning into two congruency groups correlates with narrowed specificity for NAD+ (indicating an evolutionary jump) in one of the groups. The latter group (tyrosine congruency group 11; TyrCG-11) is denoted Actinobacteridae_2 in Fig. 2, whereas tyrosine congruency group 10 (TyrCG-10) is displayed as Actinobacteridae_1. The opposite scenario whereby a single tyrosine congruency group corresponds to split tryptophan congruency groups applies in the case of low-GC gram-positive bacteria. Whereas TyrA proteins form a single congruency group in these organisms (tyrosine congruency group 9; TyrCG-9), a small cluster of Trp-pathway concatenates from Bacillus subtilis, B. stearothermophilus, and B. halodurans (tryptophan congruency group 6; TrpCG-6) separate distinctly from the remaining organisms (tryptophan congruency group 7; TrpCG-7). The latter evolutionary jump reflects a dynamic scenario of tryptophan-pathway evolutionary events that include loss of one gene from the trp operon, insertion of the trp operon into a 6-gene aro operon to produce a supraoperon, and acquisition of the TRAP (tryptophan-activated RNA-binding protein) mechanism of regulation by an RNA-binding protein [7].
Tyrosine congruency groups and tryptophan congruency groups are maintained and updated at the AroPath website [12].
Distribution in nature of TyrA specificity subclasses for the cyclohexadienyl substrate
Four qualitative classes of specificity for the cyclohexadienyl substrate populate the TyrA superfamily of homologs (Fig. 1). These include PPA-specific (TyrAp), AGN-specific (TyrAa), the broad-specificity cyclohexadienyl (TyrAc) dehydrogenases and a fourth class represented by an enzyme of antibiotic biosynthesis (PapC) that converts 4-amino-4-deoxy-prephenate to 4-amino-phenylpyruvate [13]. Representatives of each specificity class have been studied at molecular and genetic levels. TyrA family members sharing a given substrate specificity do not necessarily cluster tightly together, and assignment of substrate specificity to experimentally uncharacterized TyrA homologs is uncertain unless they exhibit very high amino acid identities with experimentally characterized TyrA proteins. In some cases we do not accept older literature reports without more recent verification. For example, the yeast Saccharomyces cerevisiae TyrAx was characterized as a TyrAp protein [14] long before it was recognized [15] that PPA preparations were often contaminated with AGN (an unknown compound at that time).
Our collection of curated TyrA sequences at AroPath (see Table 3) contains trimmed sequences that comprise catalytic-core domains. This collection was divided into two groups based on whether the sequences contained the relatively short N-terminal pyridine-nucleotide discriminator segment or the longer C-terminal cyclohexadienyl-substrate core segment. The sequences in the latter group were assembled into subgroups representing established substrate specificities (TyrAa, TyrAp and TyrAc) and were aligned separately to obtain overall consensus sequences for cyclohexadienyl-substrate core segments. The TyrAc group members from the lower-gamma assemblage of Proteobacteria (as well as from a few other lineages) were so distinctive that a fourth group (TyrAc_Δ) was defined. This latter group is, in fact, the most divergent of the four. Figure 3 shows a comparison of the four consensus sequences, with invariant anchor residues shaded yellow and residues conserved across all groups shaded in gray. Residues within each group that are >50% conserved are shown in capital letters. In pairwise BLAST (Basic Local Alignment Tool) [16]comparisons, TyrAa and TyrAc consensus sequences are most similar (47% identity), followed by the TyrAc/TyrAp pair (40% identity), with TyrAa and TyrAp exhibiting 34% identity. TyrAc_Δ is quite distinct from the other three groupings, exhibiting only 27% identity with TyrAc, 23% identity with TyrAc, and 18% identity with TyrAp.
Cyclohexadienyl dehydrogenases
Many TyrA proteins (at least in the domain Bacteria) are of the TyrAc subclass. The cyclohexadienyl dehydrogenases commonly accept PPA or AGN about equally well, but various degrees of preference for one of the alternative substrates are also observed. Detailed molecular and genetic studies of TyrAc proteins from Pseudomonas aeruginosa, [17], P. stutzeri [1], and Zymomonas mobilis [18] have been carried out. The distinct variety of TyrAc mentioned above, which has been denoted TyrAc_Δ exhibits a number of indels (mostly deletions) within the catalytic-core region when its consensus sequence is aligned with those of the other TyrA classes (Fig. 3). It is intriguing that the indel structuring of TyrAc_Δ correlates with the presence of an extra-core extension. This extension is often AroQ, but not always. For example, in the genera Nostoc and Anabaena it appears to be a degraded, catalytically inactive AroQ, whereas in Xanthomonas or Xylella it is an ACT domain. Since the one large clade of TyrAc_Δ proteins that has so far been studied prefers PPA over AGN by well over an order of magnitude, an evolutionary relationship of indel insertions to the narrowing of substrate preference for PPA might exist. If so, however, this cannot be the only molecular change to accomplish favored utilization of PPA over AGN since a number of TyrAc proteins, (e.g., TyrAc from Neisseria gonorrhoeae), also exhibits an overwhelming preference for PPA, even though this class lacks the indel structuring.
Arogenate dehydrogenases
The TyrAa class of specificity is currently represented by higher plants and at least three widely spaced bacterial lineages: cyanobacteria, actinomycetes and Nitrosomonas europaea. This discontinuity of phylogenetic spacing is consistent with a fundamental evolutionary scenario [19] whereby the ancestral dehydrogenase was a broad-specificity TyrAc that evolved narrowed substrate specificity (to yield either TyrAp or TyrAa) independently on multiple occasions in modern lineages. The ubiquitous presence of TyrAa in cyanobacteria has been heavily documented [20]. Nitrosomonas europaea currently (as of March, 2005) has no sufficiently close genome relatives that have been sequenced. The first BLAST hit returned from a NADPTyrAa query from N. europaea (March,2005) is the protein from Ralstonia solanacearum (48% identity), which is known to possess broad specificity for both of its substrates (i.e., NAD(P)TyrAc) [21,22].
The TyrA sequences of Actinobacteria separate into two distinct groupings on the protein tree (Fig. 2). Coryneform bacteria in one sub-cluster have been rigorously characterized as the NAD(P)TyrAa substrate specificity type. On the other hand, a variety of Streptomyces species have been shown [23,24] to possess NADTyrAa, and TyrA proteins of these organisms populate the second Actinobacteria sub-cluster of Fig. 2. Figure 4 shows sequence alignments of the N-terminal pyridine-nucleotide discriminator regions of currently available actinomycetes. The conserved 'D' residue (highlighted in yellow) in the upper group is a reliable indicator of NAD+ specificity, in part because NADP+ is repelled by the negative charge at this position. The asparagine residue (highlighted in blue) in the corresponding position in members of the lower group indicates NAD(P)+ specificity as discussed by Bonner et al. [25]. Rubrobacter xylanophilus is the most distant representative of the Actinobacteria, being the sole member of the subclass taxon Rubrobacteridae, and its protein (denoted Rxyl) appears as an orphan in Fig. 2.
A similar relationship of phylogenetic separation associated with narrowed specificity for pyridine-nucleotide substrate exists for the low-GC gram-positive bacteria (eight o'clock in Fig. 2). Here the major clade is NAD+-specific, whereas species of Streptococcus have retained the ancestral breadth of specificity for NAD+/NADP+. Alignments of the pyridine-nucleotide discriminator regions of these latter two groups match up extremely well with the upper alignment of Fig. 4 where residue 32 of the Wierenga fingerprint [26] is 'D' and with the lower alignment where residue 32 is 'N' (data not shown).
Recently, a plant tyrAa from Arabidopsis thaliana has been reported to consist of two near-identical domains that are fused [27]. The gene encoding this 68-kDa protein co-exists in the genome with a single-domain paralog [28] that encodes a predicted 37-kDa protein, somewhat larger than the catalytic-core domain of TyrAa from Synechocystis. TyrAa (known to be located in higher-plant chloroplasts [2]) may have originated from cyanobacteria via endosymbiosis. If so, however, the plant TyrAa sequences have diverged sufficiently that they no longer share a specific phylogenetic grouping with the cyanobacterial TyrA sequences. This is in marked contrast with the phylogenetic coherence of the tryptophan synthase subunit proteins (TrpEa and TrpEb_1) from cyanobacteria and higher plants [29].
Prephenate dehydrogenases
TyrAp is conspicuously represented by a large clade of low-GC gram-positive organisms, of which Bacillus subtilis TyrAp is the best studied [30]. Thus far, all TyrAp proteins are fused to a C-terminal ACT domain, and therefore no "minimal" TyrAp proteins that consist only of a catalytic core are available as yet. At the level of physiological function, it should be added that those cyclohexadienyl dehydrogenases that exhibit a very substantial preference for prephenate are for all practical purposes prephenate dehydrogenases, even though they carry a formal designation of TyrAc or TyrAc_Δ. These include most, if not all, of the AroQ•TyrAc_Δ enzymes of the enteric lineage (lower-gamma in Fig. 2). The TyrAc protein from Neisseria gonorrhoeae (and by inference, the closely related N. meningitides) is also a well-studied example of overwhelming preference for prephenate [21].
PapC dehydrogenases
PapC participates in the formation of p-aminophenylalanine as a step in the synthesis of at least two antibiotics (see Fig. 1). It is so far represented by only a few sequences. The PapC specificity is strongly indicated by absence of the otherwise invariant residue H197 (E. coli numbering) that is associated with recognition of a 4-hydroxy moiety in the cyclohexadienyl substrates of the aforementioned dehydrogenases. This moiety, of course, differs in being a 4-amino substituent in the substrate used by the PapC dehydrogenase (Fig. 1). See Bonner et al. [25] for a more detailed overview.
The "redundant" trp/aro supraoperon of Nostoc/Anabaena
All cyanobacteria possess a highly conserved tyrAa gene, as well as a complete suite of tryptophan-pathway genes that are dispersed (unlinked) in the genome. The large-genome cyanobacterial lineage consisting of the Nostoc and Anabaena genera possess in addition a unique and seemingly redundant trp/aro supraoperon consisting of most of the aforementioned genes [31]. These include a second tyrA gene (curated as tyrAc_Δ), six trp-pathway genes (all except trpC), and genes encoding the first two common-pathway steps of aromatic amino acid biosynthesis. All of these supraoperonic genes appear to be redundant in that they are represented by homologs (paralogs or xenologs) elsewhere in the Nostoc and Anabaena genomes at scattered loci. The closest BLAST hits for the Nostoc/Anabaena TyrAc_Δ proteins are not the co-existing TyrAa homologs present in their own genomes (and universally present in cyanobacteria). Rather the closest BLAST hits are to the TyrAc_Δ domains of the AroQ•TyrAc_Δ fusions in the enteric lineage. Since the enteric proteins are NAD+-specific and strongly prefer prephenate, it is likely that the "extra" cyanobacterial proteins are also NADTyrAc_Δ proteins. Indeed, this would be consistent with enzymological evidence provided in the literature for both Nostoc and Anabaena [20].
Concerning the evolutionary origin of the redundant block of linked genes found in the Nostoc and Anabaena genomes, at least two possibilities await further illumination. (i) These genes might have been acquired by a common ancestor of Nostoc and Anabaena via lateral gene transfer. This is consistent with the observation that biosynthetic-pathway operons are generally absent in the cyanobacteria, and all of the linked genes could have been recruited in a single event. However, at present no candidate donor genomes are known that possess this supraoperon combination of genes. If the TyrAc_Δ proteins of Nostoc/Anabaena and the enteric lineage are possibly related by LGT, it is of interest that the N-terminal extension of TyrAc_Δ from Nostoc/Anabaena resembles a degraded AroQ domain of AroQ•TyrAc_Δ from enterics. In both cases the N-terminal residues may compensate for indel deletions within the catalytic core region of TyrAc_Δ. Subsequently, AroQ function may have evolved in one lineage (or have been lost in the other). This possibility of domain-domain interaction is consistent with the established interdependence of the AroQ• and •TyrAc_Δ domains from E. coli [32]. Alternatively, tyrAa and tyrAc_Δ (and the duplicated trp and aro genes present in the supraoperon) might be ancient paralogs within the cyanobacterial lineage. If so, at a time following divergence of heterocystous cyanobacteria from the unicellular cyanobacteria, the latter may have lost the clustered block of aromatic-pathway genes in a single event of reductive evolution. The supraoperonic genes might be related to a specialized function associated with "developmental" physiological processes that typify the filamentous, heterocyst-forming cyanobacteria. This might be reminiscent of the nature of the phenazine-pigment operon of Pseudomonas aeruginosa. Here unique phenazine-pathway genes are combined with a redundant gene of common-pathway aromatic biosynthesis and two redundant (and fused) genes of tryptophan biosynthesis. This accomplishes the linkage of specific phenazine biosynthesis with a supply of 2-amino-2-deoxy-isochorismate, the branchpoint of divergence toward phenazine and tryptophan [33,34]. This complexity in which multiple paralogs are differentially deployed is consistent with the large genome sizes of Anabaena (7.2 MB) and Nostoc (9.2 MB), compared with the much smaller unicellular genomes of Prochlorococcus marinus (1.7 MB), Synechococcus sp. WH8102 (2.4 MB), and Synechocystis sp. PCC6803 (3.6 MB).
Profile hidden Markov models (HMMs) to distinguish specificity subfamilies for cyclohexadienyl substrate
The limited information thus far available about specific molecular roles of particular TyrA amino acid residues has been summarized recently [25]. The catalytic-core domains of known TyrAa, TyrAp, TyrAc, and TyrAc_Δ proteins were selected from our files of TyrA catalytic-core domains [35], and a new subset of sequences was prepared that lacked the pyridine nucleotide discriminator segment, a glycine-rich βαβ region at the N terminus. Although the glycine-rich βαβ region is not the only segment that contacts pyridine nucleotide substrate, it is the sole region that discriminates between NAD+ and NADP+. The resulting trimmed sequence is defined as the "cyclohexadienyl-substrate core segment". No distinctive motifs were found that, in isolation, would be a clear predictive indicator of specificity for cyclohexadienyl substrate. Similar substrate specificity profiles probably can be dictated by alternative patterns of interplay between different residue combinations.
Because of the rapid accumulation of incorrectly annotated TyrA entries in GenBank and other databases, partly due to the complications of misnaming that are associated with gene fusions and partly to a failure to assimilate published substrate specificities, the use of BLAST does not return reliable annotations with respect to substrate specificity. Even the HMMs used in Pfam [36] and Interpro [37] were not helpful in this case because the HMM deployed in those databases was broadly but incorrectly defined as 'prephenate dehydrogenase (NADP+) activity' for all TyrA dehydrogenases (accession number PF02153 in Pfam and entry IPR003099 in Interpro). However, Profile HMM is known to be well suited for modeling a particular sequence family of interest and for finding additional remote homologs [38]. It is reputed to outperform methods that rely only upon pair-wise alignment of homologous residues in predicting protein function [39]. Therefore, profile HMMs were constructed using our multiple sequence alignments of each curated TyrA specificity subfamily, using the HMMER package [38].
The profile HMMs obtained are only tentatively reliable for prediction of substrate specificity. To facilitate ongoing and future functional annotations, we have made our profile HMMs available as a working resource for "specificity prediction" at AroPath [40]. Users can match query sequences against the four profile HMMs to predict the subfamily to which a query sequence belongs. It is anticipated that future experimental data relevant to substrate specificity will facilitate refinement of the prediction program. For example, at present the program predicts that the TyrA sequences from organisms such as Helicobacter pylori and Saccharomyces cerevisiae belong to the TyrAa grouping, and it will be interesting to see whether this holds up to experimental confirmation. It is additionally fascinating that (i) the dehydrogenase from Archaeoglobus fulgidus is predicted to belong to the indel-containing TyrAc_Δ grouping and (ii) that it possesses a possible cooperatively interacting extra-core domain extension (an AroQ fusion), just as occurs for the large clade of enteric bacteria. If this is relevant, it is even more fascinating that the Archaeoglobus aroQ is fused at the C-terminal side of tyrAc_Δ, rather than at the N terminus as is the case with enteric bacteria.
Users at AroPath [41] can enter query sequences into interactive multiple sequence alignments with any of the four sets of "cyclohexadienyl-substrate core segments" sequences that were used to train the profile HMMs. An ongoing effort is in process to extend the predictor capability to include the pyridine nucleotide substrate as well. One can also align query sequences of interest with either an assemblage of the complete set of curator-approved TyrA catalytic-core TyrA sequences or with any desired subset of seed sequences.
The catalytic-core domain of TyrA proteins
The simplest set of fully functional TyrA proteins consists only of the catalytic-core domain (about 180 amino acids) [1] and includes the well-characterized TyrAc enzymes from Neisseria gonorrhoeae [21] and Zymomonas mobilis [18], as well as TyrAa from a cyanobacterium [25]. In addition the catalytic-core domain from Pseudomonas stutzeri has been engineered for study from a tyrAc•aroF fusion [1]. These model core proteins are roughly as divergent from one another on the TyrA protein tree as are the organisms that contain them (Fig. 2). In view of the possibility raised in this paper about inter-domain interactions, the single-domain TyrA proteins are undoubtedly the simplest sources for study of the fundamental properties of the catalytic-core domain.
Xie et al. [1] suggested that in the set of catalytic-core TyrA proteins, inhibitors bind at the catalytic site and exhibit classical competitive inhibition with respect to the particular cyclohexadienyl substrates that can be accepted by a given organism. This model predicts that the specificity for the sidechains of substrates used would parallel the specificity for inhibitor sidechains. The information summarized in Table 4 supports this expectation. Thus, the TyrAc proteins of P. stutzeri and P. aeruginosa will accept either a pyruvyl (as with PPA) or an alanyl (as with AGN) sidechain in the alternative substrates used, and this is paralleled by recognition of either a pyruvyl (4-hydroxyphenylpyruvate) or an alanyl (TYR) sidechain in the competent inhibitor structures. In another case, the N. gonorrhoeae TyrAc exhibits an overwhelming substrate preference for PPA, and consistent with the foregoing, is subject to inhibition by 4-hydroxyphenylpyruvate but not by TYR. A variety of analog inhibitor structures were used by Xie et al. [1] to show that the minimal structure for binding at the substrate-binding site of P. stutzeri TyrAc is a six-membered ring with a 4-hydroxy substituent.
In contrast to the TyrAc proteins just described, the Z. mobilis TyrAc is totally insensitive to inhibition by either 4-hydroxyphenylpyruvate or TYR. Since both of these compounds lack a 1-carboxy moiety, it is reasonable to assume that the 1-carboxy substituent present in the two substrates accepted may be required for binding at the catalytic center. Thus, although TyrAc from Z. mobilis will accept the same two substrates as does the TyrAc from P. stutzeri, the greatly different inhibition results suggest that Z. mobilis obeys more stringent rules for binding at the catalytic site (i.e., a ring carboxylate must be present).
Synechocystis sp. and Arabidopsis thaliana TyrAa proteins accept as a substrate only AGN, which has an alanyl sidechain. The ring-carboxylate moiety is evidently not absolutely required for binding since these TyrAa proteins can recognize TYR (alanyl sidechain) as a competitive inhibitor. In contrast, since N. europaea TyrAa is not inhibited by TYR, it resembles the Z. mobilis TyrAc in the putative requirement for a 1-carboxy substituent to secure successful binding at the catalytic site.
In summary, some TyrA proteins probably exercise greater discrimination in their requirement for a 1-carboxy moiety for binding at the catalytic site, and these are insensitive to competitive inhibition by the aromatic reaction products (which lack the 1-carboxy substituent). Other TyrA proteins that require the 1-carboxy moiety for the fundamental catalytic process, but presumably do not require it for binding, will recognize product inhibitors that have the same sidechain as any substrate recognized.
Specificity for the pyridine nucleotide co-substrate within the TyrA superfamily
NAD+ differs from NADP+ only in that NADP+ has a phosphate group esterified at the 2'-position of adenosine ribose. Therefore, the ability of a dehydrogenase to discriminate between those two lies in the particular enzyme region that contacts the ribose moiety. The glycine-rich region known to constitute the ADP-binding βαβ fold is well known to be this point of contact [26]. This Rossmann β α β fold is inevitably positioned at the extreme N terminus of TyrA proteins, and the typical GXGXXG motif is almost always observed, as illustrated in Fig. 4. This region is helpful for assessment of probable specificities for pyridine nucleotide. One can be fairly sure that TyrA proteins possessing D-32 (E. coli numbering, reference [26]) are NAD+-specific. A negatively charged residue (D or E) at position 32 is critical for hydrogen binding to the diol group of the ribose near the adenine moiety in NAD+-specific enzymes. NADP+-specific dehydrogenases cannot tolerate a negatively charged residue at position 32. TyrA proteins that possess an asparagine residue in the corresponding position appear to be broadly specific for both NAD+ and NADP+ as discussed above. No clearcut motif has been identified for NADP+-specific TyrA proteins, although at least one positively charged residue is expected in the region just beyond residue 32. By elimination, those sequences lacking D-32 or N-32 are strong candidates for NADP+ specificity. As with the cyclohexadienyl co-substrate, narrowed specificity for NAD+ (or NADP+) also seems to have occurred independently on many occasions (some examples given earlier).
The absolute specificity of TyrAp proteins for PPA tends to be accompanied by absolute specificity for NAD+, as illustrated by the large Bacillus/Staphylococcus/Listeria/Enterococcus clade at eight o'clock in Fig. 2. However, it is interesting that species of Streptococcus have retained the presumed ancestral breadth of specificity for the pyridine nucleotide substrate. The opposite relationship, whereby absolute specificity for AGN tends to be accompanied by absolute specificity for NADP+, is also observed. Here three of the four TyrAa lineages described earlier exhibit this pattern. Exceptions, though, are the aforementioned TyrAa proteins of Actinobacteridae_1 which accept either NAD+ or NADP+, as well as the TyrAa proteins of the sister Actinobacteridae_2 which are specialized for NAD+ [42,43].
The TyrAc proteins of most complete-genome organisms thus far have happened to be NAD+-specific, and this has been the property of the most rigorously characterized ones (from Z. mobilis, P. stutzeri, and P. aeruginosa). However, it is clear from extensive enzymological surveys [22] that TyrAc proteins having broad specificity for NAD+/NADP+ are common, examples including species of Ralstonia and Burkholderia. The spectrum of variation that can exist, even within a clade of organisms that are of fairly close relationship, is illustrated by one striking example. In the pseudomonad clade marked by a common tyrA•aroF fusion, the Acinetobacter sp. TyrAc is NADP+-specific [44], whereas the sister subclade Pseudomonas/Azotobacter exhibits NAD+ specificity (Fig. 2). Here the entire clade marked by a common ancestral fusion shares approximately the same profile of cyclohexadienyl substrate preference, but cofactor specificity has been narrowed in opposite directions.
We had previously suggested that there might be a general structural relationship of substrate pairing that tends to favor interaction between PPA and NAD+, on the one hand, and, on the other hand, between the greater positive charge of AGN and the greater negative charge of NADP+. These relationships may indeed be favored, but it increasingly appears that any combination can occur.
Beyond the catalytic core: allosteric domains
Various lineages have acquired an amino acid binding domain known as the ACT domain (pfam01842), which is known to bind a variety of amino acids, thus functioning as an allosteric domain for many proteins including phosphoglycerate dehydrogenase, aspartokinase, acetolactate synthase, phenylalanine hydroxylase, prephenate dehydratase and formyltetrahydrofolate deformylase. Recruitment of this domain by fusion with tyrAp appears to have occurred in a common ancestor of the large Bacillus/Staphylococcus/Listeria/Enterococcus/Streptococcus assemblage (Fig. 2). It is interesting that B. subtilis also possesses a gene encoding a free-standing ACT domain in its genome (incorrectly annotated as pheB). An additional fusion of genes encoding an ACT domain and tyrA (that arose independently, judging from the widely spaced tree positions) occurred in the common ancestor of Xanthomonas and Xylella. Actinobacteria usually possess a C-terminal extension that probably functions as an allosteric domain. The extension possessed by the Actinobacteridae_2 assemblage, which includes Streptomyces coelicolor and its relatives, appears to be an ACT domain. On the other hand, it is not all all clear that the C-terminal extension of the Actinobacteridae_2 assemblage is an ACT domain. This difference, in addition to the differing specificities for pyridine nucleotide substrate, may have contributed to the overall TyrAa divergence observed between the two Actinobacteridae groups. There is no correlation between presence of the ACT domain and specificity for cyclohexadienyl substrate since TyrAp from the Bacillus clade is PPA-specific, Xanthomonas/Xylella TyrAc is broadly specific, and Streptomyces TyrAa is AGN-specific.
B. subtilis, which belongs to the large clade having an ACT domain as a carboxy extension, has been extensively characterized [30]. 4-Hydroxyphenylpyruvate is an effective competitive inhibitor, as would be consistent with our proposed effects at the catalytic core for a PPA-specific enzyme. However, TYR, phenylalanine (PHE) and tryptophan were also inhibitors. The violation of the rule that the latter three amino acid inhibitors would not be expected to bind the catalytic core region (because they have alanyl sidechains even though the substrate-binding site only recognizes the pyruvyl sidechain of prephenate) and the finding that some of these were not competitive inhibitors can now be accounted for by the presence of the allosteric ACT domain. A carboxy extension shared by a number of Archaea (denoted 'REG' in Fig. 2) is presumably a regulatory domain as well. This is consistent with the recent result of Porat et al. [45] that not only 4-hydroxyphenylpyruvate, but also TYR, inhibited prephenate dehydrogenase activity of Methanococcus maripaludis.
The tyrA gene is a popular fusion partner
Fusion with aroQ
tyrA may be fused with a number of other catalytic domains, each of them relevant to aromatic biosynthesis (Fig. 2). aroQ (encoding chorismate mutase) is frequently fused with a number of other aromatic-pathway genes [46]. The lower-gamma Proteobacteria (enteric lineage) located at twelve o'clock in Fig. 2 possess an aroQ•tyrAc_Δ fusion. The fusion physically links chorismate mutase (which forms PPA) with TyrAc_Δ (which utilizes PPA). The two protein domains of AroQ•TyrAc_Δ may have co-evolved to produce cooperative protein-protein interactions since physical separation of the domains evoked relatively low activities of both activities in E. coli [32]. Substantial comparative work shows that the aroQ•tyrAc_Δ fusion has been stably maintained throughout the entire enteric lineage [47]. Exceptions in some genomes lacking this fusion altogether can be attributed to reductive evolutionary loss in pathogens (e.g., Haemophilus ducreyi) or endosymbionts (e.g., Buchnera aphidicola). An independent aroQ•tyrA fusion was generated in the common ancestor of Sulfolobus solfataricus and S. tokodaii (Fig. 2). Since the TyrA domain of Sulfolobus species lacks the indel structure of the TyrAc_Δ class, it would be interesting to see whether physical separation of the two domains would yield evidence of independent function, in contrast to the results mentioned just above for E. coli.
Fusion with aroF
Secondly, tyrAc has been fused with aroF on at least two separate occasions in Bacteria. (The aroF gene encodes enolpyruvylshikimate-3-P synthase, the sixth enzyme in the common pathway of aromatic biosynthesis; see [5,6] for nomenclature used.) One clade includes members of the upper-gamma Proteobacteria: P. aeruginosa, P. syringae, P. putida, P. stutzeri, P. fluorescens and Azotobacter vinelandii. It is interesting that P. syringae has experienced a deletion of about 200 residues at the N-terminal region of the AroF domain. This has been coupled with the acquisition of a stand-alone aroF gene that is absent in other members of the clade. Interestingly, the latter AroF shows high identity only with AroF from Agrobacterium tumefaciens, an alpha proteobacterium. The A. tumefaciens aroF, in turn, is unique compared to its α-subdivision relatives, both in having divergent sequence and in being unlinked to cmk and rpsA. Thus, it seems likely that the incongruence of AroF belonging to both P. syringae and A. tumefaciens reflects acquisition via LGT from some as yet unknown source. The disruption of the fused aroF domain in P. syringae is an unusual instance where the catalytic function of one fusion domain has become discarded while the function of the second domain has been retained. It is interesting to consider the possibility that the truncated remnant of the aroF fusion domain might be exploitable for use as an innovative source of a new regulatory domain. An additional fusion of tyrA with aroF has occurred independently within the beta Proteobacteria in the common ancestor of Burkholderia pseudomallei and B. mallei. This has been very recent since the closely related B. fungorum and B. cepacia organisms lack the fusion.
It has been suggested that presence of a given fusion may be useful for sorting out clades that diverged from a common ancestor, independent of other methods [48]. Different fusions offer the power of discriminating clades at various hierarchical levels, i.e., nested clades discriminated by nested gene fusions. The tyrA•aroF fusion occurred in the common ancestor of the clade that includes the upper-gamma Proteobacteria shown in Fig. 2. One can reasonably assume that relatively close upper-gamma organisms lacking the tyrA•aroF fusion diverged from the common ancestor of the fusion clade prior to the fusion event. Such would appear to be the case, for example, with Acidithiobacillus ferrooxidans, an outlying member of the upper-gamma Proteobacteria that lacks the fusion. It is reasonable to conclude that the fusion event must have pre-dated the differential specialization for the pyridine nucleotide cosubstrate that distinguishes Acinetobacter sp. (NADP+-specific) from the large grouping of pseudomonads that are NAD+-specific.
Fusion with hisHb
Thirdly, a single organism, Rhodobacter sphaeroides, possesses a hisHb•tyrA fusion that must have occurred very recently. hisHb encodes an aromatic aminotransferase that is closely related to (or sometimes even synonymous with) imidazole acetol phosphate aminotransferase [49]. The hisHb/tyrA/aroF linkage group is part of a supraoperon in some gram-negative bacteria in which a relatively conserved, yet frequently shuffled gene order is observed [5,6]. Hence, it is reasonable to assume that at the time just prior to fusion, hisHb, tyrA and aroF were adjacent. Note that among the fusions currently known, hisHb and aroF are fused to the N-terminal and C-terminal ends of tyrA, respectively. It would be interesting to know the substrate specificity of the R. sphaeroides TyrA domain. If it is AGN-specific the significance of hisHb presumably would be to transaminate PPA to form AGN, the substrate used by TyrAa (see Fig. 1). On the other hand, if the dehydrogenase is PPA-specific, the significance of the HisHb domain would be to transaminate the product of the TyrAp reaction. If the enzyme is a TyrAc enzyme (as is probable), then HisHb likely is competent to catalyze either of the foregoing reactions.
Fusion with ACT
The widespread ACT regulatory domain appears to have been acquired by independent fusions at least three separate times judging from the widely separated lineages that possess a TyrA•ACT fusion (Fig. 2). Xie et al. [5] initially noted homologous domains positioned at the N terminus of mammalian phenylalanine hydroxylase and at the C terminus of most microbial prephenate dehydratases. This domain is responsible for phenylalanine-mediated activation and phenylalanine-mediated inhibition of the hydroxylase and dehydratase enzymes, respectively. This domain was later named the ACT domain [50] and shown to be a widely distributed domain family that shares a conserved overall fold. Members of the ACT-domain family possess a wide variety of different ligand-binding capabilities. For example, the ACT domain of 3-phosphoglycerate dehydrogenase binds L-serine as a allosteric inhibitor.
Fusion with REG
Another putative regulatory domain fused to tyrA (denoted tyrA•REG) is thus far restricted to some of the Archaea. This domain is a predicted regulatory domain, as described in COG4937.
A novel 4-domain fusion
Archaeoglobus fulgidus exhibits a striking four-domain fusion consisting of three catalytic domains and a regulatory ACT domain (TyrA•AroQ•PheA•ACT). The TyrA domain is predicted to belong to the TyrAc_Δ class when used as a query input into the AroPath Specificity Predictor Tool [40]. We speculated earlier that the •AroQ fusion domain of Archaeoglobus may exercise cooperative interactions with TyrAc_Δ, as appears to occur between the AroQ•TyrAc_Δ domains of E. coli and its relatives.
tyrA in its syntenic context
Although the genes of prokaryotes have clearly been subject to frequent scrambling, some gene-gene associations persist more tenaciously than others. Xie et al. [5,6] asserted that one such ancestral gene string that has resisted scrambling forces is hisHb > tyrA > aroF. As suggested above, contemporary gene fusions can serve as frozen-in-time indicators of ancient gene organizations that were later obscured by gene-scrambling events. Another gene string that is often within the syntenic region of hisHb, tyrA, and aroF is cmk > rpsA. Gene synteny in prokaryotes has not been easily recognized because substantial manual scrutiny in combination with a sufficient density of genomic representation on a given portion of the phylogenetic tree is necessary to detect patterns of synteny that are camouflaged by frequent scrambling events (inversion, deletion and transposition).
The domain Bacteria is now represented by a collection of sequenced genomes that is progressively approaching the genomic densities needed for meaningful analysis. Figure 5 provides a visual sense of the frequency with which tyrA is closely positioned with other genes of aromatic biosynthesis, as well as the underlying patterns of overall synteny. These patterns are unstable, and yet persistent traces of synteny can be seen where genomic representation is sufficiently dense. The four genes of particular emphasis in this paper are color coded. Other genes that are engaged in aromatic biosynthesis are colored grey, and any other genes are white. At a very deep level of phylogenetic branching, Thermotoga exhibits a tyrA gene flanked by seven genes encoding all of the common steps of aromatic biosynthesis (two of them being fused). Since closely related genomes are not yet available here, we cannot judge whether these genes came together recently or whether an ancient pattern of synteny has been retained. Although tyrA is not linked to any functionally relevant genes in Aquifex, representing another point of deep phylogenetic branching, this does not necessarily mean that tyrA was not already generally associated with other aromatic-pathway genes at an early time. For reasons that are totally mysterious, certain scattered lineages exhibit a total lack of operon organization for aromatic-pathway genes (and indeed for most other biosynthetic pathways, such as that for histidine biosynthesis). These lineages (Fig. 5) include, besides Aquifex, those of Deinococcus, the actinomycetes, the cyanobacteria, and Chlorobium. Except for the actinomycetes, this phenomenon of total gene dispersal also applies to genes of tryptophan biosynthesis [7,8].
When the various examples of hisHb > tyrA > aroF linkage are mapped on a 16S rRNA tree, they first appear in gram-positive bacteria. In Bacillus and related organisms (such as Listeria), the hisHb > tyrA > aroF unit is associated with a large ancestral operon consisting of aroG > aroB > aroH > hisHb > tyrAp> aroF. Bacillus additionally possesses the cmk > rpsA unit, albeit in a separate location. Interestingly, in one narrow subclade (B. subtilis, B. halodurans and B. stearothermophilus) the trp operon has been inserted between aroH and hisHb to yield a supraoperon that has been fully characterized as a complex functional unit [51]. See Xie et al. [7] for a full presentation of evolutionary interpretation relevant to the latter. Though highly scrambled, a pattern of association of pheA with hisHb > tyrA >aroF is suggested by linkage patterns seen at the hierarchical level of Cytophaga and Bacteroides (Fig. 5). aroQ became associated with pheA through gene fusion as early as the divergence of the Spirochaetes to yield an aroQ•pheA>tyrA>aroF>cmk>rpsA linkage unit (Leptospira interrogans in Fig. 5). The aroQ•pheA gene associated with tyrA and aroF in Clostridium difficile appears to have arisen from a distinctly different fusion event than that present in delta, epsilon, beta and upper-gamma Proteobacteria or from that present in lower-gamma Proteobacteria (based upon analysis of inter-domain linker regions; unpublished data).
Consensus ancestral gene organizations for the most densely represented divisions of Proteobacteria have been deduced as shown at the bottom of Fig. 5. Detailed information that supports a deduced consensus for ancestral gene organizations with respect to beta Proteobacteria, upper-gamma Proteobacteria, and lower-gamma Proteobacteria are shown later (Figs. 6, 7). We suggest that the last common ancestor of all Proteobacteria possessed the gene organization aroQ•pheA>hisHb>tyrA>aroF>cmk>rpsA. This is similar to the synteny that has been retained in general by the beta Proteobacteria and the upper-gamma Proteobacteria. The aroQ•pheA>hisHb>tyrA portion likely specified all the catalytic requirements for conversion of chorismate to PHE and conversion of chorismate to TYR. Chorismate mutase activity specified by the aroQ domain could supply PPA for both PHE and TYR biosynthesis. Likewise, HisHb, widely utilized as an aromatic aminotransferase [49], could also function for both PHE and TYR biosynthesis. Though currently available members of delta and epsilon Proteobacteria exhibit substantial gene scrambling, the various fragmentary linkage patterns seen provide support for the ancestor proposed. Geobacter (and other Delta_1 members) has the aroQ•pheA > tyrA > aroF > cmk > rpsA linkage group (with lytB inserted between cmk and rpsA). Desulfovibrio vulgaris, another delta Proteobacterium (Delta_2) that is highly divergent from Geobacter, has a very interesting pattern of conservation and scrambling. aroQ•pheA > aroF > tyrA has been attached to a complete 7-gene trp operon. hisHb > cmk (not shown in Fig. 5) is completely separated from rpsA. The supraoperonic gene organization shown for D. vulgaris begins with two recently discovered genes, herein denoted aroA' and aroB', that encode enzymes specifying an alternative biochemical route to dehydroquinate [52]. The epsilon Proteobacteria all display significant gene scrambling, but piecemeal evidence for the unscrambled ancestor proposed is present. For example, Campylobacter jejuni possesses an aroQ•pheA > hisHb unit, as well as aroF > lytB > rpsA (Fig. 5). Wollinella succinogenes and Helicobacter hepaticus both possesses an aroF > lytB > rpsA unit.
The ancestor of alpha Proteobacteria has lost the aroQ•pheA fusion, and a stand-alone pheA is consistently observed. Members of this group are quite uniform in the stable possession of hisHb > tyrA and aroF > cmk > rpsA as two separated linkage groups. The beta Proteobacteria are represented by members that have the gene organization: serC > aroQ•pheA > hisHb > tyrA > aroF > cmk > rpsA. This is also seen in the members of the upper-gamma Proteobacteria.
Figure 5 includes organisms that illustrate the traces of synteny that can be detected in Bacteria where overall genome representation is just barely adequate. The following two figures illustrate how syntenic patterns of more resolution and refinement become evident with denser genome representation.
Zooming in on syntenic contexts of proteobacteria
Beta proteobacteria and upper-gamma proteobacteria
The beta Proteobacteria exhibit a dynamic but still interpretable pattern of altered synteny (Fig. 6 and Table 5). Species of Ralstonia have retained the proposed ancestral synteny that is marked with yellow highlighting in Fig. 6. This syntenic organization is such that the aromatic-gene unit aroQ•pheA > hisHb > tyrA > aroF is nested between gyrA > serC at the leftward flank and cmk > rpsA > himD at the rightward flank. Species of Burkholderia (the next closest lineage) are almost identical, but exhibit individual evolutionary events (marked by circled numbers on the left, which correspond to a description of the proposed evolutionary events given in companion Table 5). These events include gene insertion, loss of hisHb, translocation of genes away from the ancestral supraoperon, and fusion of tyrA and aroF (in the common ancestor of B. mallei and B. pseudomallei). At a deeper level in the beta Proteobacteria section of the tree, Nitrosomonas europaea exhibits a separation of the ancestral supraoperon between tyrA and aroF. Either a very large insertion was made between tyrA and aroF, or one of the two gene clusters shown was transposed as part of a sufficiently large segment to include all of the conserved flanking genes. In Chromobacterium violaceum tyrA has become completely isolated from other gene members of the ancestral supraoperon, and aroF has assumed an inverted orientation with respect to cmk. Species of Neisseria exhibit no remnants of supraoperon synteny at all, and wholesale dispersal of all the supraoperon genes has occurred. (It is interesting that among the beta Proteobacteria, Neisseria species are also unique in that all of the trp-pathway genes are dispersed [7]).
The gamma Proteobacteria have separated into two distinctly different synteny patterns. The lower-gamma Proteobacteria have undergone marked syntenic change (see below). The assemblage portrayed between Acidithiobacillus and Microbulbifer in the lower part of Fig. 6 (termed the upper-gamma Proteobacteria) exhibit a strong overall syntenic resemblance of supraoperon genes to that of the beta Proteobacteria. Acidithiobacillus possesses a near-intact ancestral supraoperon, differing only in having two insertions: one gene encoding 3-deoxy-D-arabino-heptulosonate 7-phosphate (DAHP) synthase between hisHb and tyrA, and the other being the insertion of serA between serC and aroQ•pheA. Pseudomonas aeruginosa and P. stutzeri have also retained nearly intact ancestral supraoperons, differing only in the fusion of tyrA and aroF. The serC > aroQ•pheA > hisHb > tyrA•aroF > cmk > rpsA supraoperon has been studied in P. stutzeri [5,6]. The tyrA•aroF fusion occurred in the common ancestor of the clade shown between Azotobacter and Microbulbifer in Fig. 6. The supraoperons of P. syringae, P. fluorescens and P. putida lack hisHb. P. syringae exhibits a recent C-terminal truncation of the aroF domain, coupled with acquisition elsewhere in the genome of a free-standing •aroF that is not phylogenetically congruent (probably of LGT origin). Acinetobacter sp. and Microbulbifer degradans possess an aroQ•pheA > tyrA•aroF unit that has become dissociated from serC at one end and from cmk on the other end. In Xylella and Xanthomonas, hisHb has been deleted from the genome and tyrA has been transposed away from serC > aroQ•pheA > aroF. The latter unit has been transposed away from gyrA, the ancestral flanking gene. On the other hand, cmk > rpsA has remained next to himD, the gene usually flanking rpsA.
The enteric lineage
The lower-gamma Proteobacteria differ sharply from upper-gamma Proteobacteria in their possession of the tyrAc_Δ class of tyrA and its fusion with aroQ. In Fig. 2 this clade of AroQ•TyrAc_Δ fusions was presented as one exhibiting absolute specificity for NAD+, combined with an overwhelming but not complete specificity for PPA. In Fig. 7 the gene synteny associated with tyrAc_Δ is profiled against the 16S rRNA phylogenetic trees of the lower-gamma Proteobacteria possessing these genes, and the proposed evolutionary events are summarized in the companion Table 6. Figure 5 has indicated a synteny consensus for the common ancestor at this hierarchical level whereby gyrA > serC > hisHb > aroF > cmk > rpsA parallels the ancestral synteny of β-Proteobacteria, but without aroQ•pheA or tyrA in the middle of the linkage group. Many dynamic evolutionary events of altered aromatic biosynthesis have occurred within the lower-gamma Proteobacteria since their divergence from the upper-gamma Proteobacteria. This includes the emergence of three allosterically distinct DAHP synthases, one of which now comprises the two-gene, three-domain tyr operon (aroAIα_Y > aroQ•tyrAc_Δ). The upper-gamma Proteobacteria characteristically possess the aroAIα paralogs encoding AroAIα_H (TRP-inhibited DAHP synthase) and AroAIα_Y (TYR-inhibited DAHP synthase). It has been asserted that AroAIα_F (PHE-inhibited DAHP synthase) was the most recent paralog, acquired just after divergence of the lower-gamma Proteobacteria [53]. It is bizarre that Shewanella oneidensis possesses a pseudogene of aroAIβ fused to the C terminus of aroQ•pheA. The aroAIβ subclass of Family-I DAHP synthases is not usually observed in gram-negative bacteria [54].
The dissociation of tyrAc_Δ from the serC/rpsA linkage group correlates with the fusion of aroQ with tyrAc_Δ. The aroQ•pheA fusion has also escaped from the serC/rpsA linkage grouping and has become linked with the newly emerged tyr operon. Some sort of duplication and recombinational event between aroQ•pheA and tyrAc_Δ may have led to the creation of aroQ•tyrAc_Δ since the AroQ•PheA proteins of lower-gamma Proteobacteria are distinct from AroQ•PheA proteins of other Proteobacteria with respect to the inter-domain linker length and the indel content (data not shown).
Although it usually is absent from the lower-gamma Proteobacteria, HisHb has persisted as the broad-specificity aromatic aminotransferase in the Pasteurella/Haemophilus grouping where two hisH paralogs are generally present, one of narrow specificity (denoted hisHn) being within the histidine operon. The aspC gene next to aroF in Shewanella is a paralog that probably functions as an aromatic aminotransferase, suggestive of the situation in the E. coli grouping where tyrB is a close paralog relative of aspC, tyrB having become specialized for aromatic biosynthesis [49]. Gene reduction associated with both endosymbiotic and pathogenic lifestyles are evident. Thus, Buchnera lacks tyrA, cmk, hisH, tyrB, and possesses only a single aroAIα species (aroAIα_H). Haemophilus ducreyi also lacks tyrA, as well as aroAIα_H and the entire trp operon [5].
TyrA in its context of regulation
TyrR regulon
Knowledge of the gene regulation impacting TyrA in prokaryotes is sparse, being limited to the lower-gamma Proteobacteria. Here, extensive information gathered from E. coli has revealed that aroQ•tyrAc_Δ belongs to a large regulon controlled by the TyrR repressor. The limited phylogenetic distribution of TyrR, being present only in the lower-gamma Proteobacteria (Fig. 8), indicates that it is a recent evolutionary acquisition. In E. coli the regulon members that are under the control of tyrR are the aroAIα_Y > tyrA operon, the aroLM operon, tyrP, tyrB, aroP, mtr, aroAIα_F and tyrR itself [55]. Thus, tyrR not only regulates the tyrosine branch of the pathway, but heavily impacts the common pathway and the transport of all three aromatic amino acids as well.
Although outside the scope of this study, a logical expansion of it would be to examine the individual evolutionary histories of all the members of the contemporary E. coli TyrR regulon, i.e., asking when and in what order did these genes come under the influence of tyrR? Clearly, the recruitment of structural genes by tyrR has been recent, quite dynamic and even now, exhibits evidence of further ongoing change. For example, tyrosine phenol-lyase (a catabolic enzyme that is only sparsely present in gamma Proteobacteria) has been recruited to the TyrR regulons of Erwinia herbicola [56] and Citrobacter freundii [57]. In these cases, not only does TyrR perform as a transcriptional activator, but it requires cyclic AMP receptor protein and integration host factor to do so.
As exemplified by E. coli, TyrR is generally a repressor. However, the transcriptional expression of mtr is activated by TyrR in the presence of TYR, and tyrP is activated in the presence of PHE (although it is repressed in the presence of TYR). The N-terminal domain of TyrR has been associated with the ability of TyrR to activate transcription in the case of mtr and tyrP [55]. Members of the Haemophilus/Pasteurella lineage have all lost the N-terminal domain and presumably all lack the ability to accomplish transcriptional activation, as has been demonstrated experimentally with H. influenzae TyrR [58].
In view of the interesting complexity that two operons (mtr and aroLM) in E. coli are regulated by both tyrR and trpR [55], it may be more than coincidental that tyrR and trpR seem to have emerged at about the same evolutionary time, i.e., coincident with the divergence of the upper-gamma Proteobacteria from the lower-gamma Proteobacteria (Fig. 7). A possible interaction between the TyrR and TrpR proteins has been noted [55].
PhhR in relationship to aromatic catabolism
Arias-Barrau et al. [59] have recently characterized a central catabolic pathway (Hmg) that degrades homogentisate in three steps to fumarate and acetoacetate as a source of carbon and energy. One of several peripheral pathways feeding into the central pathway begins with PHE and produces homogentisate via the reactions of phenylalanine hydroxylase (Phh), aromatic aminotransferase, and 4-hydroxyphenylpyruvate dioxygenase (Hpd). In the absence of Phh, a shorter version of the peripheral pathway is one that can use TYR, but not PHE, as a source of carbon and energy. In Fig. 8 the presence of Phh, Hpd, and Hmg segments of catabolism are mapped on a 16S rRNA tree. (The aromatic aminotransferase distribution is not shown since a multiplicity of aromatic aminotransferases having overlapping substrate specificities makes it particularly challenging to identify the functional role [49].) The cyanobacteria are unique among Bacteria in the use of Hpd for a completely different metabolic role unrelated to aromatic catabolism, i.e., the synthesis of vitamin E derivatives [60].
PhhR is a homolog of TyrR that has been shown in P. aeruginosa to be a divergently transcribed activator of a 3-gene operon needed for PHE and TYR catabolism [61]. The structural genes encode phenylalanine hydroxylase (phhA), carbinolamine dehydratase (phhB) and 4-hydroxyphenylpyruvate aminotransferase (phhC), and are powered by a σ54 promoter [61,62]. PhhR evolved relatively recently since it is only present in some gamma Proteobacteria (Fig. 8). The ancestral regulatory gene for the Phh peripheral pathway may have been a member of the leucine-responsive regulatory protein/asparagine synthase C (Lrp/AsnC) family judging from the adjacent and divergently oriented position of asnC genes to phhA in organisms such as Xanthomonas axonopodis and Mesorhizobium loti. A recent overview of the many different regulator families involved in the control of aromatic catabolism conveys an emerging sense of the variety and dynamic evolutionary processes that underlie aromatic catabolism [63]. Occasional distant homologs of phhR that appear in erratic fashion (see Fig. 9) may have some other regulatory function. For example, Clostridium tetani may use its PhhR homolog as a transcriptional activator of the gene encoding tyrosine phenol-lyase, as occurs in species of Erwinia [56] and Citrobacter [57].
Relationship of TyrR and PhhR
What might be of origin of TyrR? TyrR is an anomalous member of the large prokaryote family of σ54 enhancer-binding proteins that activate promoters dependent upon σ54. TyrR is unique within its homology grouping in that it targets σ70 promoters for regulation, usually (but not always) being a repressor. Its closest homolog relative is PhhR, a canonical member of σ54 enhancer-binding proteins. σ54-dependent enhancer proteins possess a highly conserved σ54-contact motif, GAFTGA, that is intimately involved in formation of the ternary complex of enhancer and σ54-RNA polymerase holoenzyme [64]. This is perfectly or nearly perfectly retained in the upper clades shown in Fig. 9, but is disrupted or completely absent in the clades between Shewanella oneidensis and Pasteurella multocida. The deeper phylogenetic distribution of PhhR (Fig. 8) suggests that TyrR evolved as a variant of PhhR. If correct, a regulatory gene that is oriented to catabolism (phhR), and itself of relatively recent origin, was conscripted even more recently for a completely new role in the regulation of primary biosynthesis (tyrR).
Consistent with the latter supposition, the gain of TyrR generally correlates with the loss of competence for aromatic catabolism (Fig. 8). In contrast to the Citrobacter/Salmonella/Escherichia/Shigella and the Pasteurella/Haemophilus clades (whose TyrR homologs completely lack the GAFTGA motif), the remaining enteric clades have retained some residues in this region. These residues appear to be more than random remnants. It would be interesting to know if these residues have any functional significance. Indeed, the Photobacterium/Vibrio clade has retained the ancestral catabolic capabilities (Fig. 8) that would appear to demand retention of regulation via PhhR; yet the parallelism of the overall features of biosynthesis that are shared with other lower-gamma Proteobacteria would seem, on the other hand, to demand TyrR-mediated regulation. Perhaps this "TyrR" species participates in the regulation of both catabolic and biosynthetic genes. In this connection, it is interesting that Chaney et al. [64] found that a change in the GAFTGA motif of NifA could be partially "suppressed" by mutational changes in the N-terminal region of σ54.
Even more striking as a possible evolutionary intermediate is the most outlying member of the lower- gamma Proteobacteria, Shewanella oneidensis. The position of its TyrR on the protein tree parallels expectations based on the 16S rRNA tree. This, plus the conservation of the TyrR regulon features and the overall gene synteny suggest E. coli-like function as TyrR, i.e. acting as a general repressor of regulon-member σ70 promoters engaged in aromatic biosynthesis. However, the location of "tyrR" in S. oneidensis between phhA and phhB on one side, and hmgB and hmgC on the other side, strongly implies some kind of regulatory relationship with the catabolic genes. It would be quite interesting to determine experimentally whether "TyrR" in S. oneidensis (and maybe Vibrio, as well) can function as a repressor of the usual suite of σ70 promoters, as well as an activator of σ54 promoters for phhA/phhB and/or hmgB/hmgC.
We suggest that TyrR evolved as a modified version of PhhR as follows. In view of the distribution of genes encoding PhhR and TyrR, as well as the aforementioned catabolic enzymes, the most parsimonious evolutionary scenario may be that central and peripheral catabolic pathways depicted in Fig. 8 are quite ancient, but acquisition of PhhR as a σ54-dependent activator of phenylalanine hydroxylase was quite recent, originating about the time of divergence of gamma Proteobacteria. The clade defined by Shewanella/Vibrio/Photobacterium retained the catabolic pathway, whereas the other enteric lineages discarded the catabolic pathway, but retained PhhR, which was then recruited as a σ70-dependent regulator of aromatic biosynthesis (TyrR).
Regulation by attenuation
A widespread mechanism of regulation is via an attenuation mechanism whereby transcripts initiated at given promoters can be terminated prior to reaching the structural genes of an operon. Whether termination occurs usually depends on the balance (dictated by a variety of mechanisms) between mutually exclusive terminator and anti-terminator structures [65].
Merino has developed a website [66] to provide a database of putative attenuators ahead of various operons in Bacteria. We screened this database for likely attenuators relevant to the regulation of tyrA. Table 7 shows intriguing results that point to significant experimental work that would be desirable. tyrA is frequently a member of apparent supraoperons, as alluded to elsewhere in this paper, and some of these appear to be large gene clusters controlled by attenuation. Substantial work is needed to establish the depth of clades possessing a given attenuator. For example, the hisHb > tyrA operon is reliably present throughout all alpha Proteobacteria. Since Agrobacterium tumefaciens has been found to possess an attenuator ahead of the hisHb > tyrA operon, one might reasonably expect that most of the alpha Proteobacteria would possess the attenuator as well. If not, this attenuator would have been a very recent evolutionary innovation. Likewise, since the aroAIα_Y > tyrA operon is widely present throughout the lower-gamma Proteobacteria, it would be interesting to confirm whether only the several species of Vibrio identified on the Merino website have an attenuator ahead of this operon (or whether other attenuators present are too weak to exceed the threshold imposed for preliminary detection).
Some of the supraoperons that appear to be controlled by attenuation are interesting in that they contain the majority of genes needed for both PHE and TYR biosynthesis, e.g., the supraoperons in Enterococcus faecalis and Streptococcus pneumoniae. The latter organism displays two attenuator units. The supraoperon of Desulfovibrio vulgaris is novel in that it begins with two relatively rare genes encoding alternative enzyme steps for aromatic biosynthesis [52], denoted here as aroA' and aroB'. The leading five genes are adjacent to the seven-gene trp operon.
Conclusion
Protein divergence within a vertical genealogy is not necessarily smooth and progressive. Qualitative biochemical innovations can result in a barrage of new selective pressures that result in evolutionary jumps. The consequent incongruence might easily be mistaken for LGT. The basis for evolutionary jumps will usually only be recognized by detailed and comprehensive analyses of any given subsystem. Examples in this study are as follows. (i) The tyrAc_Δ gene of the lower-gamma Proteobacteria has diverged markedly from tyrAc of the upper-gamma Proteobacteria. Here the milestone event was fusion of aroQ to a putative tyrAc in the ancestor of lower-gamma Proteobacteria to produce aroQ•tyrAc_Δ. Indels within the •tyrAc_Δ domain presumably reflect a multiplicity of selections for functional interactions known to exist between the two fused domains as discussed earlier. (ii) Members of the subclass taxon Actinobacteridae possess TyrAa proteins that separate into two distinct groupings. The presumed ancestral NAD(p)TyrAa that is still present in the Actinobacteridae_1 clade very likely spawned the divergent NAD+-specific variety of TyrAa to yield the contemporary Actinobacteridae_2 clade.
The previous evolutionary analysis of trp-pathway genes [7,8] can be viewed as a model for comparable studies with other gene systems. Expansion to the greater aromatic pathway is a logical extension. The dynamics of evolutionary change for tyrA can be matched to the dynamics exhibited by the trp system. For example, the lower-gamma Proteobacteria separate as a distinct phylogenetic unit from beta Proteobacteria and upper-gamma Proteobacteria on criteria defined by milestone evolutionary events that altered many character states of both tryptophan and tyrosine biosynthesis in the lower-gamma Proteobacteria. In the future one can anticipate that comprehensive and systematic phylogenetic analysis of each protein member of the TYR, PHE and TRP branches, the common aromatic-pathway trunk, and minor vitamin-like branches (such as the 4-aminobenzoate/folate branch) will accommodate a progressively integrated picture of the entire aromatic network, including catabolic pathways and many other specialized pathways.
Methods
TyrA sequences
Most TyrA sequences were obtained from the National Center for Biotechnology Information (NCBI) [16]. TyrA sequences from incomplete genomes were retrieved from the PEDANT database [67]. Several sequences in our curated TyrA collection have been corrected for incorrect translation start sites. Various curated TyrA sequence files can be downloaded from our website. These files include complete sequences, trimmed catalytic-core domains, and amino-acid sequence segments that are relevant to specificity for pyridine nucleotide or to specificity for the cyclohexadienyl substrate. The sequence files are summarized in Table 3.
Congruency groupings
TyrA proteins that cluster together on the TyrA protein tree in congruence with the 16S rRNA tree are called congruency groups. Exact correspondence of branching orders is not necessarily observed. So far, congruency groupings have been assembled for tryptophan-protein concatenates [8] and for TyrA proteins. Completion of equivalent work with the remaining aromatic-pathway segments will identify the repertoire of bacterial organisms in possession of a "pure" vertical genealogy with respect to aromatic biosynthesis. Congruency groups for TyrA can be accessed at our AroPath website [9], where a listing of the membership of congruency groups is maintained and updated. Any members of congruency-group clusters, whose position there is incongruent with 16S rRNA expectations, probably (but not necessarily) originated by LGT. The donor lineage may not be obvious, but as more genomes come on line, many cases where donor identities are currently unknown may become revealed. A listing of "orphan" TyrA proteins that belong to no current congruency group is given. Such orphans reflect the lack of sufficient genome representation in particular phylogenetic regions and undoubtedly will become the nucleus for additional congruency groups in due course.
Alignments
Multiple alignments were obtained by use of the ClustalW or ClustalX programs (Version 1.83) [68]. Manual adjustments were needed in the region of the GxGxxG motif for binding of pyridine nucleotide cofactor in the N-terminal region of TyrA proteins. Guidance for alignment was assisted by maximizing conformation with the Wierenga fingerprint, making allowance for a variable loop of 2–5 residues [26]. This was done with the assistance of the BioEdit multiple alignment tool of Hall (5.0.9 Edition) [69]. The refined multiple alignment was used as input for generation of a phylogenetic tree using the phylogeny inference package (Version 3.2), PHYLIP [70]. The neighbor-joining program was used to obtain a distance-based tree. The distance matrix was obtained by use of Protdist with a Dayhoff Pam matrix. The Seqboot and Consense programs were then applied to assess the statistical support of the tree using bootstrap resampling (1,000 replications). We also used the ANCESCON package [71], which produced similar results as shown in Fig. 2 (albeit with even wider separation of many groups). The presence of regulatory domains (ACT and REG) was accepted when indicated by the Domain Architecture Retrieval Tool (DART) on the BLAST menu at NCBI [16].
Profile HMMs
Profile hidden Markov models for each of the four TyrA subfamilies, TyrAa, TyrAc, TyrAp and tyrAc_Δ, were built using Sean Eddy's HMMER package [72]. The HMMs were generated from our file of curated cyclohexadienyl-substrate core segments (see Table 3). The seed sequences for each subfamily were first aligned using ClustalW [68]. The resulting multiple sequence alignments were then manually edited to produce more accurate alignment of the seed sequences. Finally, the edited multiple sequence alignments were used to generate the profile HMMs for each TyrA subfamily.
Appraisal of gene fusions as one-time or multiple events
Whether any given contemporary gene fusions tracked back to a fusion event in a common ancestor or whether they occurred independently was evaluated by phylogenetic analysis of the individual protein domains and by inspection of the inter-domain linker region. Linker regions were determined by multiple alignments of fusion sequences with corresponding free-standing domains present in the closest relatives to organisms that lack the gene fusions.
Authors' contributions
JS and MW integrated this specific effort with the broader and ongoing objective of implementing a dynamic and progressively updateable website (AroPath). JS also made substantial contributions to the bioinformatic work. CB did all of the art work and a majority of the bioinformatic analyses. RJ provided initial guiding concepts, a general organizational overview, and assembled the initial manuscript draft. CB, RJ, and JS contributed to the formulation of conclusions made, and all of the authors read and approved the final version of the manuscript.
Supplementary Material
Additional File 1
Table S1, entitled "Key to organism acronyms and sequence identifiers", is provided as supplementary material in an html document. This table contains the full collection of sequence data and annotations contained in this paper, and gene identification (gi) numbers are included and hyperlinked to facilitate access to the corresponding GenBank records. For future reference to a progressively updated table, refer to the AroPath website [73].
Click here for file
Acknowledgements
R. Jensen thanks the National Library of Medicine (Grant G13 LM008297) for partial support. This research is partially supported by the U. S. Army Research Institute of Infectious Diseases (USAMRIID). This analysis would not have been possible were it not for the yeoman efforts in comparative enzymology carried out over a period of more than 25 years by many students and postdoctoral fellows, most notably Graham S. Byng, Robert Whitaker, Alan X. Berry and Suhail Ahmad. This has produced an invaluable resource of comprehensive data, some of it unpublished. This paper is dedicated to our colleague and collaborator, John E. Gander, on the occasion of his 80th birthday.
Figures and Tables
Figure 1 Composite of alternative biochemical routes from chorismate (CHA) to L-tyrosine (TYR) in nature. An antibiotic synthesis branch from CHA is also shown (dimmed). Here the intermediates shown to intervene between chorismate and pristinamycin or chloramphenicol are p-aminochorismate (ADC), p-aminoprephenate (ADP), p-aminophenylpyruvate (APP), and p-aminophenylalanine (APA). PPA may be transaminated by prephenate aminotransferase (PAT) to yield L-arogenate (AGN). The four TyrA homologs and the reactions they catalyze are colored differently. Arogenate dehydrogenase (TyrAa) converts AGN to TYR. Alternatively, prephenate dehydrogenase (TyrAp) converts PPA to 4-hydroxyphenylpyruvate (HPP) which is then transaminated to TYR via an homolog of TyrB, AspC, HisH, or Tat [49]. A broad-specificity cyclohexadienyl dehydrogenase (TyrAc) is competent to catalyze either the TyrAa or the TyrAp reaction. PapC converts the 4-amino analog of PPA to the 4-amino analog of HPP. AroQ, AroH, and AroR are distinct homologs known to exist in nature for performance of the chorismate mutase reaction. Other abbreviations: AA, amino acid donor, KA, keto-acid accepter.
Figure 2 Phylogenetic tree for trimmed core domains of selected members of the TyrA Superfamily. Acronyms used for the various organisms are given in alphabetical order in Table 2. (A more extensive listing that includes organisms not shown in Fig. 2 and which also is hyperlinked to all of the individual GenBank records is given in Table S1. A similar table that also includes compilation of known and predicted substrate specificities is maintained at AroPath [73]. Lineages possessing experimentally established TyrAa, TyrAp, TyrAc or TyrAc_Δ proteins are indicated by fill colors specified in the legend. Three specificity patterns for the pyridine nucleotide substrate are shown by line colors (see figure box). Although the cyanobacteria are depicted as having NADP+-specific TyrA proteins, some of them can also accept NAD, albeit to a lesser degree. All proteins having an aspartate residue homologous to D-32 of the E. coli NADTyrAc_Δ domain are presumed specific for NAD+. Fusion of TyrA domains with other catalytic domains is indicated within grey boxes (AroQ•TyrA, TyrA•AroF, HisHb•TyrA, and TyrA•AroQ•PheA•ACT) using the convention of a bullet to represent the interdomain area. The boxes overlap any relevant lineages. TyrA proteins having carboxy-terminal fusions with regulatory domains (TyrA•ACT and TyrA•REG) are also shown. The distance scale bar at the bottom left represents substitutions per site.
Figure 3 Multiple alignment of the HMM consensus sequences obtained for different substrate-specificity groupings within cyclohexadienyl-substrate core segments (see Table 3). Invariant anchor residues are highlighted in yellow, conserved residues in grey. These consensus sequences will change continuously as corrections and refinements are made. The version shown was current as of April, 2005.
Figure 4 Alignment of the N-terminal glycine-rich P-loop of TyrA•ACT proteins from the Class Actinobacteria. These are specific for L-arogenate as substrate, but fall into two groups with respect to the pyridine nucleotide co-substrate. The top NAD+-specific group possesses an aspartate (D) at position 32 (E. coli numbering), whereas the bottom NAD+/NADP+ group possesses an asparagine at the homologous position. Residue numbers are shown at the left. The species in the middle are color coded to match the hierarchical taxon positions obtained from NCBI. The variable loop of the Wierenga fingerprint [26], which in E. coli contains five residues (22–26), contains the minimal two residues in all of the Actinobacteria shown. The organisms on the right are color coded according to the taxonomic position indicated on the left (NCBI). The Rubrobacter xylanophilus TyrAa sequence is an orphan in the tree displayed in Fig. 2, as consistent with its outlying position in the taxonomy scheme.
Figure 5 Context of gene organization for tyrA, profiled against the 16S rRNA tree of the domain Bacteria. pheA, hisHb, tyrA, and aroF are color coded. Lineages typified by complete dispersal of aromatic-pathway genes are indicated by "GENE DISPERSAL". Gmet refers to Geobacter metallireducens; Dace refers to Desulfuromonas acetoxidans; and Ddes refers to Desulfovibrio desulfuricans. Consensus gene organizations are shown for the alpha and beta divisions of the Proteobacteria. The gamma division is subdivided to yield consensus gene organizations for the upper- and lower-gamma (enteric lineage) organisms. Genes that are adjacent and share a common transcriptional direction appear to reside in operons (or supraoperons). Any white spacing indicates substantial separation of the gene clusters shown in the genome. Genes of special interest are color coded, other genes of aromatic biosynthesis are shown in gray and all other genes are shown in white.
Figure 6 Zoom-in from Fig. 5 showing tyrA synteny for the beta Proteobacteria and the upper-gamma Proteobacteria. The tree shown, based upon 16S rRNA sequences of the indicated organisms, indicates correct branching orders, but (to facilitate presentation) is not strictly correct in proportion. Circled numbers (in violet) indicate deduced evolutionary events for the beta Proteobacteria (see top of Table 5), whereas circled numbers (in pink; see bottom of Table 5) correspond to deduced evolutionary events for the upper-gamma Proteobacteria. Gene organizations of organisms indicated are shown on the right. The dotted outlining of some gene boxes in Coxiella burnetii and in P. syringae indicates pseudogene status.
Figure 7 Zoom-in from Fig. 5 showing tyrA synteny for the lower-gamma Proteobacteria (enteric lineage). Deduced phylogenetic events numbered on the left are described in Table 6. The branching position for Buchnera is as suggested in ref. [7]. Dotted horizontal lines near the top of the tree indicate branch lengths that were shortened for convenience of presentation. Dotted outlining of boxes around some genes indicates their pseudogene status. It is unknown if the various open reading frame (ORF) insertions are functional.
Figure 8 Distribution of modules of aromatic catabolism mapped on a 16S rRNA tree. In this figure, only presence or absence (not gene order) is indicated. The Phh module (orange) consists of phenylalanine hydroxylase (PhhA), carbinolamine dehydratase (PhhB), and tyrosine aminotransferase (not shown, see Text), and accomplishes the overall conversion of PHE to 4-hydroxyphenylpyruvate. The Hpd module (yellow) is 4-hydroxyphenylpyruvate dioxygenase, which converts 4-hydroxyphenylpyruvate to homogentisate. The Hmg module (blue) catalyzes the 3-step conversion of homogentisate to acetoacetate and fumarate. The distribution of PhhR and TyrR is shown in boxes. In some cases the HmgC member is shaded light blue to indicate that the gene encoding this isomerase could not be found and is probably encoded by an as yet unknown analog. Some long branches are drawn with gaps that represent 25% of the length of the scale bar.
Figure 9 Protein tree of TyrR homologs. Nodes supported by bootstrap values of 998 or more are marked with solid circles, and the bootstrap values for nodes internal to these are shown. Generic names relevant to the organism abbreviations can be viewed in Fig. 8. A conserved region containing the σ54 contact motif GAFTGA is highlighted as an orange band. "Imperfect" residues in this region are shown in lower-case fonts. Residue numbers are shown at the right. TyrR and PhhR are regulators of σ70 and σ54 promoters, respectively. Four σ54 proteins of unknown function have very long branches, and to facilitate the visual presentation, the gaps in branch continuity shown represent a scale-bar distance of 0.1. Clades possessing σ54 regulators are indicated with blue stripes, and σ70 regulators are indicated with green stripes.
Table 1 Abbreviations used to designate substrate specificities of tyrA/TyrA homologs
Abbreviationa
Gene Gene Product Description of specificityb
tyrAx TyrAx Specificity for cyclohexadienyl substrate is unknown
tyrAc TyrAc Broad-specificity cyclohexadienyl dehydrogenase (CDH)
tyrAp TyrAp Narrow-specificity prephenate dehydrogenase (PDH)
TyrAc_Δ TyrAc_Δ Broad-specificity cyclohexadienyl dehydrogenase having catalytic-core indels in correlation with an extra-core extension
tyrAa TyrAa Narrow-specificity arogenate dehydrogenase (ADH)
NAD
tyrAa NADTyrAa TyrA homolog is AGN-specific and NAD+-specific
NADP
tyrAa NADPTyrAa TyrA homolog is AGN-specific and NADP+-specific
NAD(P)tyrA
a
NAD(P)TyrAa TyrA homolog is AGN-specific but utilizes either NAD+ or NADP+
xtyrAx xTyrAx Specificity for both the cyclohexadienyl and pyridine nucleotide substrates is unknown
aAbbreviations in the upper-table (upper 5 rows) indicate the specificities for the cyclohexadienyl substrate. Abbreviations in the lower-table (lower 4 rows) indicate specificities for both cyclohexadienyl (right subscripts) and pyridine nucleotide substrates (left subscripts). Combinations not shown can be deduced from the examples given, e.g., a TyrA homolog specific for prephenate and NAD+ would be designated NADTyrAp.
bThe abbreviations CDH, PDH, and ADH (shown parenthetically) have been used frequently in the literature.
Table 2 Key to organism acronyms
Organism Abbreviation
in Paper Abbreviation
on websiteb
Acidithiobacillus ferrooxidans ATCC 23270 Aferr
Acinetobacter sp. ADP1 ACIN
Actinobacillus actinomycetemcomitans HK1651 Aact
Actinomyces naeslundii MG1 Anae
Actinoplanes teichomyceticus Atei
Agrobacterium tumefaciens strain C58 Atum
Amycolatopsis balhimycina Abal
Amycolatopsis orientalis Aori
Anabaena sp. PCC 7120 ANAB
Arabidopsis thaliana Atha
Archaeoglobus fulgidus DSM 4304 Aful Aful_1
Azotobacter vinelandii Avin Avin_1
Bacillis anthracis str. A2012 Bant
Bacillus cereus ATCC 14579 Bcer
Bacillus halodurans C-125 Bhal Bhal_2
Bacillus stearothermophilus Bste
Bacillis subtilis Bsub
Bacillus thuringiensis israelensis Bthu
Bifidobacterium longum NCC2705 Blon Blon_1
Blochmannia floridanus Bflo
Bordetella bronchisepticus Bbro
Burkholderia cepacia J2315 Bcep
Burkholderia fungorum LB400 Bfun
Burkholderia mallei ATCC 23344 Bmal
Burkholderia pseudomallei K96243 Bpse Bpse_6
Campylobacter jejuni Cjej
Chromobacterium violaceum ATCC 12472 Cvio
Corynebacterium diphtheriae NCTC 13129 Cdip
Corynebacterium efficiens YS-314 Ceff
Corynebacterium glutamicum ATCC 13032 Cglu Cglu_1
Desulfovibrio desulfuricans G20 Ddes
Desulfovibrio vulgaris subsp. vulgaris strain Hildenborough Dvul
Desulfuromonas acetoxidans Dace Dace_5
Enterococcus faecalis V583 Efae_2
Enterococcus faecium Efae_1 Efae_1
Erwinia carotovoa subsp.atroseptica SCRI1043 Ecar
Escherichia coli K12 Ecol
Geobacter metallireducens GS-15 Gmet
Geobacter sulfurreducens PCA Gsul
Gloeobacter violaceus PCC 7421 Gvio
Haemophilus influenzae Rd KW20 Hinf
Helicobacter hepaticus ATCC 51449 Hhep
Helicobacter pylori 26695 Hpyl
Klebsiella pneumoniae subsp. pneumoniae MGH 78578 Kpne
Leifsonia xyli subsp. Xyli strain CTCB07 Lxyl
Listeria innocua Clip 11262 Linn
Listeria monocytogenes EGD-e Lmon
Lotus corniculatus var. japonicus Lcor Lcor_3
Lycopersicon esculentum Lesc
Methanococcus jannaschii Mjan
Methanopyrus kandleri AV19 Mkan Mkan_1
Methanosarcina barkeri strain Fusaro Mbar
Methanothermobacter thermoautotrophicus strain Delta H Mthe Mthe_7
Microbulbifer degradans 2–40 Mdeg
Mycobacterium avium subsp. paratuberculosis strain k10 Mavi
Mycobacterium bovis TrEMBL Mbov Mbov_2
Mycobacterium leprae TN Mlep
Mycobacterium tuberculosis CDC1551 Mtub
Myxococcus xanthus DK 1622 Mxan
Neisseria gonorrhoeae FA 1090 Ngon
Nitrosomonas europaea ATCC 19718 Neur
Nocardia farcinica IFM 10152 Nfar
Nonomuraea sp. NONO
Nostoc punctiforme PCC73102 Npun Npun_1
Novosphingomonas aromaticivorans DSM 12444 Naro
Oceanobacillus iheyensis THE831 Oihe
Oryza sativa ssp. japonica Osat
Pantoea agglomerans Pagg
Pasteurella multocida subsp. multocida strain Pm70 Pmul
Photorhabdus luminescens subsp. laumondii TT01 Plum
Prochlorococcus marinus subsp. pastoris strain CCMP1378 Pmar_1 Pmar_3
Prochlorococcus marinus MIT9313 Pmar_2 Pmar_10
Propionibacterium acnes KPA171202 Pacn
Pseudomonas aeruginosa PAO1 Paer Paer_1
Pseudomonas fluorescens PfO-1 Pflu
Pseudomonas putida KT2440 Pput
Pseudomonas stutzeri Pstu
Ralstonia eutropha JMP134 Reut
Ralstonia solanacearum GMI1000 Rsol
Rhodobacter capsulatus Rcap
Rhodobacter sphaeroides 2.4.1 Rsph
Rhodopseudomonas palustris CGA009 Rpal
Rhodospirillum rubrum Rrub Rrub_1
Rubrobacter xylanophilus DSM 9941 Rxyl
Saccharomyces cerevisiae Scer
Salmonella typhimurium LT2 Styp Styp_1
Schizosaccharomyces pombe Spom
Shewanella oneidensis MR-1 Sone
Shewanella putrifacians Spu
Staphylococcus aureus subsp. Aureus MW2 Saur Saur_2
Streptococcus gordonii str. Challis Sgor
Streptococcus pneumoniae R6 Spne
Streptomyces avermitilis MA-4680 Save
Streptomyces caeruleus Scae Scae_2
Streptomyces coelicolor A3(2) Scoe Scoe_1
Streptomyces lavendulae Slav
Streptomyces pristinaespiralis Spri
Streptomyces roseochromogenes subsp. Oscitans Sros Sros_1
Streptomyces toyocaensis strain 7 Stoy
Sulfolobus solfataricus P2 Ssol
Sulfolobus tokodaii strain 7 Stok
Synechococcus sp. WH8102 SYNE_1 SYNE_1
Synechococcus sp. PCC7002 SYNE_2
Synechocystis sp. PCC6803 SYNE_3 SYNE_3
Thermobifida fusca Tfus
Thermosynechococcus elongates BP-1 Telo
Trichodesmium erythraeum IMS101 Tery
Tropheryma whipplei TW08/27 Twhi
Vibrio cholerae O1 biovar eltor strain N16961 Vcho
Vibrio parahaemolyticus RIMD 2210633 Vpar
Wolinella succinogenes DSM 1740 Wsu
Xanthomonas campestris pv. campestris strain ATCC 33913 Xcam
Xylella fastidiosa 9a5c Xfas
Yersinia enterocolitica (type 0:8) Yent
Zymomonas mobilis subsp. mobilis ZM4 Zmob
aThe system of acronym usage is: the first letter (capital) is the first letter of the genus followed by the first three letters (lower-case) of the species. If there is no species designation the first four letters of the genus are used (all in capitals). Redundant 4-letter acronyms are distinguished by unique following numbers. See [74] for a comprehensive listing with hyperlinks to the Taxonomy database records and the GenBank records at NCBI.
Table 3 Curated TyrA amino-acid sequence files at AroPath [35]
Complete TyrA sequences
Catalytic-core domainsa
Pyridine-nucleotide discriminator segmentsb
NAD+-specific
NADP+-specific
Broad specificity
Cyclohexadienyl-substrate core segments
Arogenate-specific (TyrAa)
Prephenate-specific (TyrAp)
Broad specificity
TyrAc
TyrAc_Δ
Pseudogene TyrA sequences
aTrimmed free of N-terminal or C-terminal extensions, including any fusions with regulatory domains or other catalytic domains.
bHigh-glycine βαβ Rossmann fold at the N-terminus.
Table 4 Cyclohexadienyl substrates and inhibitors of TyrA proteins possess identical sidechains
Organism Co-substrate Substrate(s) Inhibitor(s)a Reference
Synechocystis sp. NADP+ AGN TYR [25]
Arabidopsis thaliana NADP+ AGN TYR [27, 28]
Nitrosomonas europaea NADP+ AGN None [21]
Corynebacterium glutamicum NAD(P)+ AGN None [42, 43]
Neisseria gonorrhoeae NAD+ PPAb HPP [21]
Pseudomonas stutzeri NAD+ PPA/AGN HPP/TYR [1]
Pseudomonas aeruginosa NAD+ PPA/AGN HPP/TYR [17]
Zymomonas mobilis NAD+ PPA/AGN None [18]
aAbbreviation: HPP, 4-hydroxyphenylpyruvate. bThis TyrAc enzyme has an overwhelming preference for PPA, but will use AGN poorly.
Table 5 Key to evolutionary events asserted in Figure 6
Group Evolutionary event(s) proposed
Beta 1 Dispersal of aroQ•pheA > hisHb > tyrA away from one another and away from gyrA > serC and from cmk > rspA > himD; inversion of aroF with respect to cmk.
2 Complete dispersal of all nine genes originally in the gyrA/himD linkage group.
3 Insertion of serA after serCa; separation of tyrA and aroF to yield the separated 6-gene unit and 4-gene unit shown.
4 Expulsion of hisHbfrom the genome; insertion of 'ORF' after serC.
5 Fusion of tyrA with aroF.
6 Loss of hisHb from genome.
Upper-Gamma 1 Insertion of serA after serCa; insertion of aroAIα after hisHb.
2 Translocation of hisHb and tyrA to other regions, leaving two separated 3-gene units.
3 Fusion of tyrA with aroF.
4 Loss of hisHb.
5 N-terminal deletion of •aroF domain, and acquisition of new aroF gene (probable LGT).
6 Separation of cmk > rpsA > himD from aroQ•pheA > tyrA•aroF.
7 Insertion of 4 unknown genes between gyrA and serC in opposite orientation and separation of gyrA > ORF > ORF > ORF > serC from aroQ•pheA > tyrA•aroF.
8 Loss of himD; translocation of serC away from gyrA and aroQ•pheA.
aSince both Nitrosomonas (beta Proteobacteria) and Acidothiobacillus (upper-gamma Proteobacteria) emerge at deep positions in the tree of Fig. 5, an almost equally parsimonius possibility is that the ancestral serA was retained in this syntenic position in these two genera, but was transposed elsewhere shortly after early divergence.
Table 6 Key to evolutionary events asserted in Figure 7
Number Evolutionary events proposed
1 Escape of aroQ•pheA and tyrA from the ancestral gyrA > serC > aroQ•pheA > hisHb> tyrA > aroF > cmk > rpsA > himD supraoperon. Origin of an aroQ•tyrA fusion. Origin of the aroAIα_Y > aroQ•tyrA operon. Addition of tyrR. Addition of third aroAIα species: aroAIα_F.
2 Fusion of aroQ•pheA with aroAIβ pseudogene of unknown origin. Replacement of hisHb by aspC duplicate linked with three ORFs.
3 Dissociation of gyrA and serC.
4 Removal of all genes intervening between aroQ•pheA and aroQ•tyrA.
5 Dissociation of aroF from both serC and cmk > rpsA > himD. Insertion of trpR within the intervening region between aroQ•pheA and aroQ•tyrA.
6 Dissociation of serC > hisHb > aroF from cmk > rpsA > himD.
7 Loss of aroAIα_Y from tyr operon.
8 aroF becomes dissociated from hisHb, and aroAIα_Y is removed from the tyrA operon.
9 ORF > gyrA is inserted after aroF.
10 aroQ•tyrA becomes a pseudogene.
11 hisHb is lost.
12 himD is lost.
13 cmk, himD and aroAIα_Y > aroQ•tyrA are lost.
14 aroF, himD, aroQ•pheA, and aroAIα_Y > aroQ•tyrA are lost.
15 All intervening genes between aroQ•pheA and aroQ•tyrA are eliminated.
16 pheA domain of aroQ•pheA becomes a pseudogene.
17 Insertion of ycaL between aroF and cmk.
18 Insertion of ORF between aroF and ycaL.
19 Insertion of ORF between aroQ•pheA and aroQ•tyrA.
Table 7 Putative attenuatorsa associated with tyrA
Organism Gene organizationb Figc
Agrobacterium tumefaciens ¬hisHb > tyrA 4d
Bacillus anthracis ¬aroG > hisHb > tyrA > aroF (11)
Bacillus cereus ¬aroG > hisHb > tyrA > aroF (11)
Bacillus halodurans ¬tyrA > aroF (11)
Bacteroides thetaiotaomicron ¬pheA > hisHb > aroAIβ•aroQ > tyrA 4
Bordetella parapertussis ¬gyrA > serC > aroQ•pheA > tyrA > aroF > cm k> rpsA > himD 5
Desulfovibrio vulgaris ¬aroA' > aroB' > aroQ•pheA > aroF > tyrA > [trp operon] 4
Enterococcus faecalis ¬aroD > aroAIβ > aroB > aroG > tyrA > aroF > aroE > pheA 4
Lactococcus lactis ¬ysaA > blrG > kinG > tyrA > aroF > aroE > pheA 4
Lactobacillus plantarum ¬ORF > aroG > ORF > aroF > tyrA > aroE
Listeria innocua ¬aroG > aroB > aroH > hisH b > tyrA > aroF 4,(11)
Streptococcus pneumoniae ¬ORF>aroCI>aroD>aroB>aroG>tyrA > ¬ORF>aroF>aroE>pheA 4
Thermoanaerobacter tencongensis ¬pheA > aroAIβ > tyrA > aroF > ORF > ORF
Thermus thermophilus ¬aroAIβ > tyrA
Vibrio parahaemolyticus ¬aroAIα_Y > tyrA 6
Vibrio vulnificus ¬aroAIα_Y > tyrA 6
aAttenuators were extracted from the website of Merino [66]. Links are provided for viewing the complete data, including a visualization of the putative attenuator structures.
bThe symbol ¬ is used for attenuators. Genes encoding the alternative biochemical steps that were recently reported for formation of dehydroquinate from aspartate semialdehyde and ketohexose 1-phosphate [52] are designated aroA' and aroB'.
cRefers to figures within this manuscript or, if enclosed within parentheses, to the figure in ref. [7].
dSee the consensus gene organization for α Proteobacteria.
==== Refs
Xie G Bonner CA Jensen RA Cyclohexadienyl dehydrogenase from Pseudomonas stutzeri exemplifies a widespread type of tyrosine-pathway dehydrogenase in the TyrA protein family Comp Biochem Physiol C Toxicol Pharmacol 2000 125 65 83 11790331
Jensen RA Tyrosine and phenylalanine biosynthesis: relationship between alternative pathways, regulation and subcellular location Rec Adv Phytochem 1986 20 57 82
Todd AE Orengo CA Thornton JM Evolution of function in protein superfamilies, from a structural perspective J Mol Biol 2001 307 1113 1143 11286560 10.1006/jmbi.2001.4513
Teichmann SA Rison SCG Thornton JM Riley M Gough J Clothia C The evolution and structural anatomy of the small molecule metabolic pathways in Escherichia coli J Mol Biol 2001 311 693 708 11518524 10.1006/jmbi.2001.4912
Xie G Brettin T Bonner CA Jensen RA Mixed-function supraoperons that exhibit overall conservation, albeit shuffled gene organization, across wide intergenomic distances within eubacteria Microb Comp Genomics 1999 4 5 28 10518299
Xie G Bonner CA Jensen RA A probable mixed-function supraoperon in Pseudomonas exhibits gene organization features of both intergenomic conservation and gene shuffling J Mol Evol 1999 49 108 121 10368439
Xie G Keyhani N Bonner CA Jensen RA Ancient origin of the tryptophan operon and the dynamics of evolutionary change Microbiol Mol Biol Rev 2003 67 303 342 12966138 10.1128/MMBR.67.3.303-342.2003
Xie G Bonner CA Song J Keyhani NO Jensen RA Inter-genomic displacement via lateral gene transfer of bacterial trp operons in an overall context of vertical genealogy BMC Biology 2004 2 15 15214963 10.1186/1741-7007-2-15
AroPath
Gil R Silva FJ Zientz E Delmotte F Gonzalez-Candelas F Latorre A Rausell C Kamerbeek J Gadau J Holldobler B The genome sequence of Blochmannia floridanus : comparative analysis of reduced genomes Proc Natl Acad Sci USA 2003 100 9388 9393 12886019 10.1073/pnas.1533499100
Gevers D Vandepoole K Simillion C Van de Pere Y Gene duplication and biased functional retention of paralogs in bacterial genomes Trends Microbiol 2004 12 148 154 15116722 10.1016/j.tim.2004.02.007
AroPath
Blanc V Gil P Bamasjacques N Lorenzon S Zagorec M Schleuniger J Identification and analysis of genes from Streptomyces pristinaespiralis encoding enzymes involved in the biosynthesis of the 4-dimethylamino-L-phenylalanine precursor of pristinamycin I Mol Microbiol 1997 23 191 202 9044253 10.1046/j.1365-2958.1997.2031574.x
Lingens F Göbel W Üsseler H Regulation der biosynthesis der aromatischen aminosauren in Saccharomyces cerevisiae, I. Hemmung der Enzymaktivitaten (Feedback-Wirkung) Biochem Z 1966 346 357 67
Zamir LO Jung E Jensen RA Co-accumulation of prephenate L-arogenate and spiro-arogenate in a mutant of Neurospora 1983 258 6492 6496 6222045
National Center for Biotechnology Information
Xia T Jensen RA A single cyclohexadienyl dehydrogenase specifies the prephenate dehydrogenase and arogenate dehydrogenase components of the dual pathways to L-tyrosine in Pseudomonas aeruginosa J Biol Chem 1990 265 20033 20036 2123197
Zhao G Xia T Ingram L Jensen RA An allosterically insensitive class of cyclohexadienyl dehydrogenase from Zymomonas mobilis Eur J Biochem 1993 212 157 165 7916685 10.1111/j.1432-1033.1993.tb17646.x
Jensen RA Enzyme recruitment in evolution of new function Annu Rev Microbiol 1976 30 409 425 791073 10.1146/annurev.mi.30.100176.002205
Hall GC Flick MB Gherna RL Jensen RA Biochemical diversity for biosynthesis of aromatic amino acids among the cyanobacteria J Bacteriol 1982 149 65 78 6119309
Subramaniam P Bhatnagar R Hooper A Jensen RA The dynamic progression of evolved character states for aromatic amino acid biosynthesis in gram-negative bacteria Microbiology 1994 140 3431 3440 7533594
Byng GS Whitaker RJ Gherna RL Jensen RA Variable enzymological patterning in tyrosine biosynthesis as a means of determining natural relatedness among the Pseudomonadaceae J Bacteriol 1980 144 247 257 7419490
Keller B Keller E Gorisch H Lingens F Biosynthesis of phenylalanine and tyrosine in Streptomycetes Hoppe Seylers Z Physiol Chem 1983 364 455 459 6862385
Keller B Keller E Lingens F Arogenate dehydrogenase from Streptomyces phaeochromogenes. Purification and properties Biol Chem Hoppe Seyler 1985 366 1063 1066 4074498
Bonner CA Jensen RA Gander JE Kehani NO A core catalytic domain of the TyrA protein family: arogenate dehydrogenase from Synechocystis Biochem J 2004 382 279 291 15171683 10.1042/BJ20031809
Wierenga RK Terpstra P Hol WGJ Prediction of the occurrence of the ADP-binding β α β-fold in proteins, using an amino-acid sequence fingerprint J Mol Biol 1986 187 101 107 3959077 10.1016/0022-2836(86)90409-2
Rippert P Matringe M Molecular and biochemical characterization of an Arabidopsis thaliana arogenate dehydrogenase with two highly similar and active protein domains Plant Mol Biol 2002 48 361 368 11905963 10.1023/A:1014018926676
Rippert P Matringe M Purification and kinetic analysis of the two recombinant arogenate dehydrogenase isoforms of Arabidopsis thaliana Eur J Biochem 2002 269 4753 4761 12354106 10.1046/j.1432-1033.2002.03172.x
Xie G Forst C Bonner CA Jensen RA Significance of two distinct types of tryptophan synthase beta chain in Bacteria, Archaea and higher plants Genome Biol 2002 3 Research0004.1 0004.13 11806827 10.1186/gb-2001-3-1-research0004
Champney WS Jensen RA The enzymology of prephenate dehydrogenase in Bacillus subtilis J Biol Chem 1970 245 3763 3770 4321765
Xie G Bonner CA Brettin T Gottardo R Keyhani NO Jensen RA Lateral gene transfer and ancient paralogy of operons containing redundant copies of tryptophan-pathway genes in Xylella species and heterocystous cyanobacteria Genome Biol 2003 4 R14 12620124 10.1186/gb-2003-4-2-r14
Chen S Vincent S Wilson DB Ganem B Mapping of chorismate mutase and prephenate dehydrogenase domains in the Escherichia coli T-protein Eur J Biochem 2003 270 757 763 12581215 10.1046/j.1432-1033.2003.03438.x
Mavrodi DV Ksenzenko VM Bonsall RF Cook RJ Boronin AM Thomashow LS A seven-gene locus for synthesis of phenazine-1-carboxylic acid by Pseudomonas fluorescens 2–79 J Bacteriol 1998 180 2541 2548 9573209
Pierson LS Gaffney T Lamb S Gong F Molecular analysis of genes encoding phenazine biosynthesis in the biological control bacterium. Pseudomonas aureofaciens 30–84 FEMS Lett 1995 134 299 307 8586283 10.1016/0378-1097(95)00423-X
AroPath
Pfam
Interpro
Eddy SR Profile-hidden Markov models Bioinformatics 1998 14 755 763 9918945 10.1093/bioinformatics/14.9.755
Park J Kaplus K Barrett C Hughey R Haussler D Hubbard T Chothia C Sequence comparisons using multiple sequences detect three times as many remote homologues as pairwise methods J Mol Biol 1998 284 1201 1210 9837738 10.1006/jmbi.1998.2221
AroPath
AroPath
Fazel A Jensen R Obligatory biosynthesis of L-tyrosine via the pretyrosine branchlet in coryneform bacteria J Bacteriol 1979 138 805 815 457594
Fazel AM Bowen JR Jensen RA Arogenate (pretyrosine) is an obligatory intermediate of L-tyrosine biosynthesis: confirmation in a microbial mutant Proc Natl Acad Sci USA 1980 77 1270 1273 6929482
Byng GS Berry A Jensen RA Evolutionary implications of features of aromatic amino acid biosynthesis in the genus Acinetobacter Arch Microbiol 1985 143 122 129 4074072 10.1007/BF00411034
Porat I Waters BW Teng Q Whitman WB Two biosynthetic pathways for aromatic amino acids in the archaeon Methanococcus maripaludis J Bacteriol 2004 186 4940 4950 15262931 10.1128/JB.186.15.4940-4950.2004
Calhoun DH Bonner CA Gu W Xie G Jensen RA The emerging periplasm-localized subclass of AroQ chorismate mutases, exemplified by those from Salmonella typhimurium and Pseudomonas aeruginosa Genome Biol 2001 2research0030.1 0030.16
Ahmad S Jensen RA The stable evolutionary fixation of a bifunctional tyrosine-pathway protein in enteric bacteria Microbiol Lett 1988 52 109 116 10.1016/0378-1097(88)90309-6
Jensen RA Ahmad S Nested gene fusions as markers of phylogenetic branchpoints in prokaryotes Trends Ecol Evol 1990 5 219 224 10.1016/0169-5347(90)90135-Z
Jensen RA Gu W Evolutionary recruitment of biochemically specialized subdivisions of Family I within the protein superfamily of aminotransferases J Bacteriol 1996 178 2161 2171 8636014
Aravind L Koonin EV Gleaning non-trivial structural, functional and evolutionary information about proteins by iterative database searches J Mol Biol 1999 287 1023 1040 10222208 10.1006/jmbi.1999.2653
Henner D Yanofsky C Sonenshein AL, Hoch J, Losick R Bacillus subtilis and other gram-positive bacteria Biochemistry, physiology, and molecular genetics 1993 Washington, DC: ASM Press
White RH L-Aspartate semialdehyde and a 6-deoxy-5-ketohexose 1-phosphate are the precursors to the aromatic amino acids in Methanocaldococcus jannashii Biochemistry 2004 43 7618 7627 15182204 10.1021/bi0495127
Ahmad S Johnson JL Jensen RA The recent evolutionary origin of the phenylalanine-sensitive isozyme of 3-deoxy-D-arabino-heptulosonate 7-phosphate synthase in the enteric lineage of bacteria J Mol Evol 1987 25 159 167 2888901
Jensen RA Xie G Calhoun DH Bonner CA The correct phylogenetic relationship of KdsA (3-deoxy-D-manno-octulosonate 8-phosphate synthase) with one of two independently evolved classes of AroA (3-deoxy-D-arabino-heptulosonate 7-phosphate synthase) J Mol Evol 2002 54 416 423 11847568
Pittard AJ Camakaris H Yang J The TyrR regulon Mol Microbiol 2005 55 16 26 15612913 10.1111/j.1365-2958.2004.04385.x
Katayama T Suzuki H Koyanagi T Kumagai H Cloning and random mutagenesis of the Erwinia herbicola tyrR gene for high-level expression of tyrosine phenol-lyase Appl Envir Microbiol 2000 66 4764 4771 10.1128/AEM.66.11.4764-4771.2000
Bai Q Somerville R Integration host factor and cyclic AMP receptor proein are required for TyrR-mediated activation of tpl in Citrobacter freundii J Bacteriol 1998 180 6173 6186 9829925
Zhao S Somerville RL Isolated operator binding and ligand response domains of the TyrR protein of Haemophilus influenzae associate to reconstitute functional repressor J Biol Chem 1999 274 1842 1847 9880568 10.1074/jbc.274.3.1842
Arias-Barrau E Olivera E Luengo J Fernandez C Galan B Garcia J Diaz E Miñambres B The homogentisate pathway: a central catabolic pathway involved in the degradation of L-phenylalanine, L-tyrosine, and 3-hydroxyphenylacetate in Pseudomonas putida J Bacteriol 2004 186 5062 5077 15262943 10.1128/JB.186.15.5062-5077.2004
Dähnhardt D Falk J Appel J van der Kooij A Schulz-Friedrich R Krupinska K The hydroxyphenylpyruvate dioxygenase from Synechocystis sp. PCC 6803 is not required for plastoquinone biosynthesis FEBS Lett 2002 523 177 181 12123828 10.1016/S0014-5793(02)02978-2
Song J Jensen RA PhhR, a divergently transcribed activator of the phenylalanine hydroxylase gene cluster of Pseudomonas aeruginosa Mol Microbiol 1996 22 497 507 8939433 10.1046/j.1365-2958.1996.00131.x
Zhao G Xia T Song J Jensen R Pseudomonas aeruginosa possesses homologues of mammalian phenylalanine hydroxylase and 4a-carbinolamine dehydratase/DCoH as part of a three-component gene cluster Proc Natl Acad Sci USA 1994 91 1366 1370 8108417
Tropel D van der Meer J Bacterial transcriptional regulators for degradation pathways of aromatic compounds Microbiol Mol Biol Rev 2004 68 474 500 15353566 10.1128/MMBR.68.3.474-500.2004
Chaney M Grande R Wigneshweraraj S Cannon W Casaz P Gallegos M-T Binding of transcriptional activators to sigma 54 in the presence of the transition state analog ADP-aluminum fluoride: insights into activator mechanochemical action Genes Dev 2001 15 2282 2294 11544185 10.1101/gad.205501
Yanofsky C The different roles of tryptophan transfer RNA in regulating trp operon expression in E. coli versus B. subtilis Trends Genet 2004 20 367 374 15262409 10.1016/j.tig.2004.06.007
Predicted attenuators in bacteria
Riley ML Schmidt T Wagner c Mewes H-W Frishman D The PEDANT genome database in 2005 Nuc Ac Res 2005 33 D308 D310 10.1093/nar/gki019
Chenna R Sugawara H Koike T Lopez R Gibson T Higgins D Thompson J Multiple sequence alignment with the Clustal series of programs Nucl Ac Res 2003 31 3497 3500 10.1093/nar/gkg500
BioEdit
Felsenstein J PHYLIP-Phylogeny Inference Package (version 3.2) Cladistics 1989 5 164 166
Cai W Pei J Grishin NV Reconstruction of ancestral protein sequences and its applications BMC Evol Biol 2004 4 33 15377393 10.1186/1471-2148-4-33
Eddy S HMMER package 1995
AroPath
AroPath
| 15888209 | PMC1173090 | CC BY | 2021-01-04 16:02:56 | no | BMC Biol. 2005 May 12; 3:13 | utf-8 | BMC Biol | 2,005 | 10.1186/1741-7007-3-13 | oa_comm |
==== Front
BMC BiolBMC Biology1741-7007BioMed Central London 1741-7007-3-141590453210.1186/1741-7007-3-14Research ArticlePCI proteins eIF3e and eIF3m define distinct translation initiation factor 3 complexes Zhou Chunshui [email protected] Fatih [email protected] Susan [email protected] Srinivasan [email protected] Alexander R [email protected] Anna [email protected] Janet [email protected] Dieter A [email protected] Department of Genetics and Complex Diseases, Harvard School of Public Health, 665 Huntington Avenue, Boston, Massachusetts, 02115, USA2 Applied Biosystems Inc., Framingham, Massachusetts, USA3 Harvard NIEHS Center Proteomics Facility, Harvard School of Public Health, Boston, Massachusetts, USA4 Department of Molecular Genetics and Microbiology, State University of New York, Stony Brook, New York, USA5 Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA2005 17 5 2005 3 14 14 11 3 2005 17 5 2005 Copyright © 2005 Zhou et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
PCI/MPN domain protein complexes comprise the 19S proteasome lid, the COP9 signalosome (CSN), and eukaryotic translation initiation factor 3 (eIF3). The eIF3 complex is thought to be composed of essential core subunits required for global protein synthesis and non-essential subunits that may modulate mRNA specificity. Interactions of unclear significance were reported between eIF3 subunits and PCI proteins contained in the CSN.
Results
Here, we report the unexpected finding that fission yeast has two distinct eIF3 complexes sharing common core subunits, but distinguished by the PCI proteins eIF3e and the novel eIF3m, which was previously annotated as a putative CSN subunit. Whereas neither eIF3e nor eIF3m contribute to the non-essential activities of CSN in cullin-RING ubiquitin ligase control, eif3m, unlike eif3e, is an essential gene required for global cellular protein synthesis and polysome formation. Using a ribonomic approach, this phenotypic distinction was correlated with a different set of mRNAs associated with the eIF3e and eIF3m complexes. Whereas the eIF3m complex appears to associate with the bulk of cellular mRNAs, the eIF3e complex associates with a far more restricted set. The microarray findings were independently corroborated for a random set of 14 mRNAs by RT-PCR analysis.
Conclusion
We propose that the PCI proteins eIF3e and eIF3m define distinct eIF3 complexes that may assist in the translation of different sets of mRNAs.
==== Body
Background
Three protein complexes that are conserved from yeast to humans, the 19S proteasome lid, the CSN, and eIF3, contain subunits characterized by two protein motifs: the MPN (Mpr1/ Pad1 N-terminal) and the PCI (proteasome/CSN/eIF3) domains [1]. The proteasome 20S catalytic particle and the 19S regulatory subunit cooperate in degrading polyubiquitylated proteins (reviewed in [2]). The 19S proteasome can be separated into the base complex, which binds and unfolds substrates [3], and the eight subunit lid complex, which cleaves ubiquitin from substrates, thus apparently facilitating the entry of substrates into the catalytic proteasome barrel [4,5].
In higher eukaryotes, the subunits of the 19S lid show pair-wise similarity to the eight subunits of the CSN [6-9]. In vivo, CSN promotes the activity of cullin-RING ubiquitin ligases [10-16], multiprotein complexes containing cullins, the RING protein RBX1, and one of several hundred substrate-specific adaptors [17-22]. The MPN domain containing CSN subunit 5 harbors a protease motif [23] that cleaves the ubiquitin-related peptide NEDD8 from cullins [24,25]. This activity, acting in concert with the CSN-associated deubiquitylation enzyme Ubp12, was proposed to promote cullin function by facilitating the recruitment of labile substrate adaptors [11,16,26,27].
The third PCI/MPN complex, eIF3, is more distantly related to CSN and the 19S lid (reviewed in [28]). Whereas human eIF3 consists of up to 13 subunits, consecutively named eIF3a – l and GA17 [29,30], budding yeast contains only six to eight subunits (depending on purification conditions). Five of these subunits are orthologs of human eIF3a, b, c, g, and eIF3i [31,32] and appear to constitute a conserved core complex [31,33]. Fission yeast contains the same five core subunits, in addition to the non-core subunits eIF3d/Moe1p, eIF3e/Int6p, and eIF3h [34-36]. A putative eIF3f ortholog was also identified, but biochemical evidence confirming it as an authentic eIF3 subunit functioning in protein synthesis is still outstanding [34,35,37,38].
eIF3 is the most complex translation initiation factor and plays at least two important roles in protein synthesis. First, eIF3 binds to the 40S ribosome and facilitates loading of the Met-tRNA/eIF2· GTP ternary complex to form the 43S preinitiation complex. Subsequently, eIF3 apparently assists eIF4 in recruiting mRNAs to the 43S complex. A critical in vivo function of eIF3 core subunits in these processes was indicated by the lethality of the respective budding yeast deletion strains [31]. In contrast, in fission yeast, the non-core subunits eIF3d and eIF3e are not essential for viability or global protein synthesis [34,36,38,39]. It was therefore proposed that distinct subclasses of eIF3 complexes, containing different combinations of core and non-core subunits, may regulate specific subsets of mRNAs in fission yeast [34,36,38,39]. Our study provides the first experimental evidence substantiating this hypothesis by demonstrating that biochemically distinct eIF3 complexes defined by the PCI domain proteins eIF3e and eIF3m (a novel eIF3 protein) associate with different sets of mRNAs.
Results
Both csn6 and csn7b are essential genes
CSN complexes of higher eukaryotes typically contain eight distinct subunits (two MPN and six PCI proteins). However, in fission yeast only six subunits are known (Csn1p, 2p, 3p, 4p, 5p, 7Ap; Ref. [13]), none of which are essential for viability [40-42]. We noticed two genes in the Schizosaccharomyces pombe genome database, originally annotated as csn6 (SPBC4C3.07) and csn7b (SPAC1751.03), which encode MPN and PCI domain containing proteins with considerable similarity to metazoan CSN6 and CSN7B, respectively (data not shown). In order to determine whether these genes might function in the known biochemical pathways regulated by CSN, cullin deneddylation and Ubp12p-mediated deubiquitylation [24,26], we deleted csn6 and csn7b in wild-type diploid cells. Upon sporulation and tetrad analysis, only two viable spores could be recovered in each case, both of which were uracil auxotroph (Fig. 1A, and data not shown). Thus, unlike the genes encoding the six known subunits of the fission yeast CSN [41,42], csn6 and csn7b are essential.
Csn6p and Csn7Bp associate with eIF3 components
To elucidate the essential functions of Csn6p and Csn7Bp, we sought to identify their interacting proteins. To this end, we attempted to modify csn6 and csn7b at their endogenous genomic loci with five consecutive protein A epitope tags (proA). The C-terminal tag also contained a cleavage site for Tobacco Etch Virus (TEV) protease upstream of the protein A moieties. Diploid analysis indicated that C-terminal tagging destroyed the essential function of csn6 (data not shown). In contrast, a csn7b-proA haploid strain was viable and did not display any obvious phenotypes (data not shown). This indicated that the tagged allele was functional. Total protein lysate from the csn7b-proA haploid strain was absorbed to Immunoglobulin G (IgG) resin and specifically retained proteins were eluted with sodium dodecyl sulfate (SDS) or by cleavage with TEV protease. The two eluates were resolved by gel electrophoresis and Csn7Bp-proA interacting proteins were identified by peptide mass fingerprinting using matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) mass spectrometry.
Both eluates contained an identical set of proteins. In addition to Csn6p, the Csn7Bp complex contained the eIF3 core subunits eIF3a, b, c, and i, as well as the non-core subunit eIF3h (Fig. 1B, Table 1). The eIF3g core subunit was not detected using MALDI-TOF in this purification, but was detected in an independent purification of the Csn7Bp complex using the more sensitive method of nano-liquid chromatography and tandem mass spectrometry (LC-MS/MS, see Fig. 5A). However, eIF3e and eIF3d, two previously described components of S. pombe eIF3 [34,36,38,39] were consistently absent from the Csn7Bp complex when analyzed either by MALDI-TOF or by LC-MS/MS (Fig. 1B and 5A).
Notably, no authentic CSN subunits were found in the Csn7Bp complex, consistent with the previous demonstration that S. pombe CSN contains only six non-essential subunits [13]. Structural analysis indicated that Csn6p is not only related to human CSN6, but shows a slightly greater overall similarity to human eIF3f (data not shown). Based on the functional characterization described below (Fig. 2), fission yeast Csn6p therefore appears to be the ortholog of human eIF3f.
A Csn7Bp ortholog is not known in the human eIF3, although the recently identified subunit GA17 [30] shows considerable similarity to Csn7Bp (K. Hofmann, personal communication). In addition, interactions of metazoan CSN7 with eIF3 subunits have previously been observed [43,44]. With regards to the unified nomenclature of eIF3 subunits [29], we propose eIF3m as a more appropriate name for the novel fission yeast eIF3 subunit encoded by csn7b (see Table 1). Throughout this manuscript, we will use the proposed new names for the eif3f and eif3m genes and their products. The original annotations have recently been revised by the curator of the S. pombe genome database, in order to reflect the findings presented here.
The eIF3f and eIF3m proteins are primarily cytoplasmic
The evidence presented above suggested that eIF3f and eIF3m are essential subunits of S. pombe eIF3. To substantiate this possibility, we determined the subcellular localization of eIF3f and eIF3m. If these proteins were authentic eIF3 subunits involved in protein synthesis, they should assume a subcellular localization similar to known eIF3 subunits. We therefore prepared three strains with green fluorescent protein (GFP) tagged alleles of eIF3b, eIF3e, and eIF3m integrated into their respective genomic loci. In addition, since C-terminal GFP-tagging destroyed the essential function of the small eIF3f protein, we prepared a strain mildly overexpressing N-terminally GFP-tagged eIF3f from a pREP81 plasmid. Fluorescence microscopy of live cells revealed that all four proteins were primarily localized in the cytoplasm (Fig. 2A), which would be consistent with a function in protein translation. In contrast, CSN subunits are largely nuclear in fission yeast ([41], and our own unpublished observation).
eIF3f and eIF3m are required for global protein synthesis
To directly assess the potential role of eIF3f and eIF3m in protein synthesis, we prepared haploid eif3f and eif3m deletion strains maintained viable by plasmids driving the regulated expression of eif3f and eif3m, respectively. Expression from these plasmids could be turned off by the addition of thiamin to the growth media, resulting in a strong reduction in protein levels within 20 to 32 hours (Fig. 2B). Coincident with shut-off of eIF3f and eIF3m expression, global cellular protein synthesis was diminished by ~80%, as determined by metabolic labeling with 35S-methionine (Fig. 2C).
Further biochemical analysis by sucrose gradient velocity centrifugation revealed a strong reduction in the formation of polysomes in eif3f and eif3m mutants following promoter shut-off (Fig. 2D). In contrast, as described previously [34,36,38,39], eif3e mutants showed only a minor reduction in total protein synthesis (data not shown) and essentially normal polysomes (Fig. 2D).
The conserved cullin deneddylation function of CSN was not impaired either in eif3f and eif3m mutants or in eif3e mutants, since cullin 1 (Cul1p) did not accumulate exclusively in the neddylated form as it does in csn5 deletion strains (Fig. 2E). Similarly, unlike in csn5 mutants (Fig. 2E; [26]), CSN/Ubp12p-mediated inhibition of Cul1p in vitro ubiquitin ligase activity was not impaired upon shut-off of either eif3f or eif3m expression. Cul1p neddylation and activity were also unaffected in eif3e mutants (Fig. 2E). These data suggested that eIF3f and eIF3m are bona fide subunits of fission yeast eIF3 but not CSN, performing essential functions in protein synthesis similar to eIF3 core subunits.
The eIF3m and eIF3e proteins define distinct eIF3 complexes
Although the purification of the eIF3m complex robustly retrieved roughly stoichiometric amounts of known eIF3 subunits, two subunits, eIF3d and eIF3e, were conspicuously absent (Fig. 1B, Table 1). To exclude the possibility that we had overlooked these subunits because they were obscured by the IgG bands, we affinity-purified eIF3e-associated proteins from an eif3e-proA strain. The retrieved proteins were identified using MALDI-TOF mass spectrometry as before.
Like the eIF3m complex, the eIF3e complex contained roughly stoichiometric amounts of the eIF3 core subunits a, b, c, g, and i (Fig. 3A, Table 1). In addition, eIF3f was present while, unexpectedly, eIF3m and eIF3h were missing. We did not detect the proteasome lid subunit Rpn5p, which previously had been shown to associate with eIF3e and eIF3d [45]. This observation indicated that the described eIF3d/eIF3e/Rpn5p interaction is either unstable under our purification conditions or contains only a minor fraction of the total eIF3e engaged in protein interactions.
These results raised the intriguing possibility that fission yeast contains two distinct eIF3 complexes that comprise an overlapping set of core subunits, but are distinguished by the presence of either the essential PCI protein eIF3m and the MPN domain protein eIF3h or the non-essential PCI protein eIF3e and its binding partner eIF3d. To exclude the possibility that our mass spectrometry analysis missed substoichiometric amounts of eIF3d in the eIF3m complex, we analyzed eIF3m complexes by immunoblotting with eIF3d antisera. Whereas eIF3d was readily detectable in the eIF3e complex, it was undetectable in the eIF3m complex (Fig. 3B). In the reciprocal experiment, eIF3d antibodies co-immunoprecipitated eIF3e-13Myc, but not eIF3m-13Myc or Csn5p-13Myc (Fig. 3C).
To exclude the possibility that our cell lysis or affinity purification conditions led to uncontrolled release of eIF3 subunits, thus mimicking the existence of distinct subcomplexes, we performed a purification using the protein A-tagged eIF3b core subunit as bait. As determined by LC-MS/MS performed on excised bands detected in the complex upon PAGE separation, the eIF3b complex contained all known eIF3 core components as well as eIF3f and eIF3m (Fig. 3D). The eIF3e and eIF3d proteins were also present, albeit in clearly substoichiometric amounts. These findings indicate that purification of eIF3b resulted in the copurification of the distinct eIF3m- and eIF3e-containing complexes. Taken together, these data strongly suggested the existence of two distinct eIF3 complexes defined by the PCI proteins eIF3m and eIF3e.
The eIF3m and eIF3e proteins associate with distinct sets of mRNAs
The finding that eif3m is essential, whereas eif3e is dispensable, suggested the possibility that the different eIF3 complexes they define regulate different subsets of mRNAs. To approach this, we sought to identify mRNAs specifically associated with the eIF3m and eIF3e complexes. The complexes were affinity-purified as described above in the presence of RNAse inhibitors, and the associated RNA was extracted, amplified, and converted to Cy3-labeled cDNA as described in the Methods section. The Cy3-labeled cDNA was hybridized competitively with Cy5-labeled cDNA prepared from total RNA onto microarrays representing all 4988 predicted S. pombe open reading frames (ORFs) and RNAs. Based on the background subtracted hybridization signals, eIF3-associated mRNAs were ranked according to their factor of enrichment in the eIF3m and eIF3e complexes over a mock purified sample ([see additional file 1]).
The microarray analysis suggested a global role for eIF3m and a more restricted function of eIF3e in translation. Using an arbitrary cut-off value of three-fold enrichment over mock, eIF3m associated with 2464 different mRNAs, whereas eIF3e associated with only 520 distinct species (Fig. 4A). We observed 414 mRNAs enriched more than three-fold in both samples. (Fig. 4A). In addition, our analysis revealed 106 mRNAs uniquely enriched in the eIF3e complex, whereas 2050 transcripts were uniquely enriched in the eIF3m complex (Fig. 4A,C).
A ranked list of all 106 mRNAs that were uniquely enriched more than three-fold in the eIF3e complex was assembled ([see additional file 2]). Approximately 75% of these mRNAs fell into one of three categories: mRNAs encoding proteins involved in intermediary metabolism (25.5%), those encoding proteins involved in protein metabolism (14.2%), and those encoding proteins with unknown functions (35.8%; Fig. 4B). The remainder was distributed roughly equally among four categories: mRNAs encoding proteins involved in nucleic acid metabolism, those encoding proteins involved in transcription, those encoding transporter proteins, and those encoding unclassified proteins.
A corresponding list of the 106 most highly enriched mRNAs exclusively present in the eIF3m complex (out of a total of 2050 enriched by a factor greater than three) revealed that ~58% also fell into three categories: mRNAs encoding proteins involved in nucleic acid metabolism (9.4%), those encoding transporter proteins (18.9%), and those encoding proteins of unknown function (20.8%). The remainder was roughly equally distributed among four categories: mRNAs encoding proteins involved in intermediary metabolism, those mRNAs encoding proteins involved in protein metabolism, those encoding proteins involved in transcription, and those encoding unclassified proteins (Fig. 4B, [see additional file 2]).
To exclude the possibility that our affinity purification protocol unspecifically enriched highly expressed mRNAs, we averaged the data from the three competively hybridized samples of total S. pombe cDNA to determine the relative expression rank of each mRNA (rank 1 = most abundant mRNA, rank 5407 = least abundant mRNA; see legend to Fig. 4C for detail). A plot of expression rank vs. factor of enrichment of the 106 mRNAs most enriched in the eIF3e and eIF3m complexes revealed that the eIF3m complex contained mRNAs that were distributed equally over the entire range of expression levels. In contrast, the eIF3e complex was enriched for rare mRNAs (~65 % of eIF3e-associated mRNAs had an expression rank > 4000; see Fig. 4C). The lack of a linear correlation between mRNA expression level and enrichment in the eIF3e and eIF3m complexes argues against unspecific copurification of abundant mRNAs.
Specific association of mRNAs with eIF3m and eIF3e complexes
To validate the results from the microarray hybridizations, we chose several mRNAs at random from each list of 106 and used RT-PCR to confirm their interactions with the respective eIF3 complexes. eIF3e-proA- and eIF3m-proA-associated complexes were affinity-purified as before and separated by PAGE. Both complexes showed the same differential subunit composition as described above (Fig. 5A). The associated RNA was purified, split into equal portions, and employed in RT-PCR reactions with gene-specific primer pairs.
The RT-PCR analysis of a total of fourteen mRNAs included eight mRNAs identified in the eIF3e complex, five mRNAs identified in the eIF3m complex, and one mRNA found to be associated with both complexes with similar enrichment factors. These mRNAs varied widely in their factors of enrichment and their enrichment ranks as indicated in Fig. 5B. Without exception, all eight mRNAs found to be enriched in the eIF3e complex by microarray analysis were also found preferentially associated with this complex by RT-PCR (Fig. 5B). Based on this result, we calculate a false positive rate of less than 0.11 with a 95% confidence interval of 0.00 – 0.31. Whereas mRNAs with a high enrichment factor (>10, [see additional file 2]) appeared to be exclusively associated with eIF3e-proA (within the limit of detection), those with a lower enrichment factor (<10) also displayed a low amount of association with the eIF3m complex (Fig. 5B). Conversely, all five mRNAs highly enriched in the eIF3m complex as determined by microarray analysis ([see additional file 2]) were almost exclusively bound to this complex when analyzed by RT-PCR (Fig. 5B).
Notably, the mRNA encoding the proteasome subunit Rpn5p, which was found in both complexes by microarray analysis with similar enrichment factors (eIF3e = 5.1; eIF3m = 8.1) was also confirmed as being associated with both eIF3 complexes by RT-PCR (Fig. 5B). These results strongly suggest that the eIF3m and eIF3e complexes specifically associate with distinct sets of mRNAs.
Discussion
PCI proteins define distinct eIF3 complexes
Our results show that Csn6p and Csn7Bp are subunits of fission yeast eIF3. Csn6p was shown to be the eIF3f subunit conserved in all eukaryotes except budding yeast. Consistent with this finding, eIF3f has previously been found to be associated with eIF3g, although the role of eIF3f in protein synthesis had not been examined [34]. Our study further identified two distinct eIF3 complexes defined by the PCI proteins eIF3e and eIF3m (Fig. 3A). No direct equivalent of eIF3m is apparent in eIF3 preparations from other eukaryotes. Considering the essential function of eIF3m in protein synthesis in fission yeast, it is possible that other PCI proteins substitute for eIF3m in other organisms.
Consistent with this idea is the finding that the PCI domain containing GA17, a recently identified protein copurifying with human eIF3 [30], shows more similarity to eIF3m than to any other PCI protein (K. Hofmann, personal communication). In addition, the PCI domain containing CSN subunits 1, 3, 7, and 8 were found to interact with eIF3 subunits in Arabidopsis thaliana and in human cells [43,44,46]. In addition, Pci8p/Csn11p, a non-essential PCI subunit of the budding yeast CSN [47,48], copurifies with essential eIF3 core subunits [49]. Although the functional significance of these interactions is still unclear, our findings raise the intriguing possibility that they define multiple subclasses of distinct eIF3 complexes. Whereas fission yeast appears to rely on an essential eIF3 complex classified by eIF3m and a non-essential complex specified by eIF3e, higher eukaryotes may divide the task of mRNA translation among a multitude of eIF3 complexes. Since the individual PCI proteins defining these subcomplexes are expected to be present in substoichiometric amounts relative to core components, as is eIF3e in the S. pombe core complex, they may have escaped detection in bulk eIF3 preparations from higher eukaryotes.
Distinct eIF3 complexes and translational specificity
Although our finding of distinct eIF3 complexes that associate with different sets of mRNAs was surprising, circumstantial evidence pointing to their existence was provided in previous studies. For example, fission yeast eIF3e copurifies with eIF3 core subunits, and yet, unlike core subunits, eIF3e is not required for global protein synthesis or viability. Two competing models were proposed to explain the pleiotropic phenotype of eif3e deletion mutants, which includes slow growth in minimal media and meiotic defects [34,36,38,39,50,51]. In the first model, eIF3e regulates the translation of all transcripts, but rare mRNAs may be more affected by a fractional reduction in translation efficiency and thus give rise to distinct phenotypes. In the second model, eIF3e regulates the translation of a specific subset of mRNAs encoding proteins whose depletion leads to distinct phenotypes but not lethality. The findings presented here strongly favor the second model.
Our microarray analysis revealed 106 mRNAs uniquely enriched in the eIF3e complex, many being rare, whereas 2050 transcripts were uniquely enriched in the eIF3m complex. The latter finding is consistent with the severe protein synthesis defect and lethality of eif3m deletion mutants. Whereas these mRNA lists were based on an arbitrary cut-off value of three-fold enrichment over mock, this criterion proved stringent enough to confirm specific association with their respective eIF3 complexes of all 14 mRNAs retested by RT-PCR. Thus, since we calculate the false positive rate to be less than 0.11 with 95% confidence interval 0.00 – 0.31, the maximum number of mRNAs listed potentially false positively as enriched in the eIF3e complex would be 33 out of 106 (with 95% confidence).
However, we consider it unlikely that all mRNAs found enriched in the eIF3e complex are exclusive translational targets of this complex, because the cellular phenotypes of eif3e mutants are rather discrete. Although many of the eIF3e-associated mRNAs encode essential proteins, viability, global protein synthesis, and polysome formation are not affected in these mutants when they are grown in rich media (Fig. 2D, and data not shown). It is therefore likely that eIF3m or other PCI domain proteins can deputize for eIF3e in many cases. In fact, our microarray study revealed that a substantial portion of eIF3e-associated mRNAs was also recovered in the eIF3m complex (Fig. 4A). Nonetheless, we strongly suspect that inefficient translation of a limited set of eIF3e-associated mRNAs contributes to distinct cellular phenotypes found in eif3e mutants (see below).
The eIF3e protein and translational control during stress response
The eif3e mutants display marked sensitivity to a wide variety of cellular stresses, such as osmotic stress, nutrient starvation, and low temperature [34,38,39,50,52] In addition, eif3e mutants show synthetic lethality with proteasome mutants, which are presumed to accumulate a large load of misfolded proteins [45]. Conversely, overexpression of eif3e confers resistance to a broad spectrum of unrelated drugs, whose only commonality appears to be that they induce cellular stress [38]. Overexpression of eIF3e also activates genes involved in stress defense, such as thioredoxin [38]. Interestingly, the mRNA encoding thioredoxin was also identified as a putative translational target of eIF3e ([see additional file 2]). Finally, eIF3e undergoes relocalization into cytoplasmic foci in response to heat and osmotic stress, thus implicating it in stress regulation [35].
Global protein synthesis is actively switched off in response to cellular stress and nutrient deprivation (reviewed in Refs. [53,54]). This shut-off protects cells from proteotoxicity by relieving chaperones of their load of unfolded client proteins, conserving amino acids for other essential functions, and attenuating the metabolic consequences of protein synthesis. However, long-term adaptation to stress conditions, repair and recovery require synthesis of new stress-induced proteins. During the stress response, some mRNAs must be translated in the presence of a repressed general translation machinery, suggesting that select eIFs can escape the global repression. Our studies raise the intriguing possibility that the eIF3e complex has such a specialized function during stress response. Lack of eif3e may prevent stress-induced synthesis of its critical translational targets, thus leading to the known stress sensitivity of the mutant. Substantial additional work will be required to address this possibility.
Potential mechanisms underlying mRNA discrimination by eIF3 complexes
Several lines of evidence have begun to implicate other general translation factors, including eIF2 and eIF4, in translational specificity [55]. Importantly, these factors are downstream of important signaling cascades, including the nutrient-sensing TOR pathway and a variety of stress-induced kinases (reviewed in Refs. [55,56]). Although the details of these regulatory mechanisms are beginning to emerge, it is still unclear exactly how eIF2 and eIF4 contribute to mRNA specificity.
Since eIF3 cooperates with the cap-binding eIF4 complex in directing the 5' end of mRNAs to the 40S ribosome, and several eIF3 subunits contain RNA binding motifs, our data is consistent with a model in which eIF3 complexes defined by distinct PCI proteins recognize determining features of mRNAs presented to the 40S subunit in concert with eIF4. In agreement with this idea is the recent finding that the human PCI protein eIF3a specifically facilitates the translation of the mRNA encoding ribonucleotide reductase M2 [57]. In addition, A. thaliana eIF3h, a non-core subunit, was recently shown to be specifically required for efficient translation of the transcription factor ATB2 [46].
While we have so far been unsuccessful in identifying common sequence elements within the upstream regions of mRNAs enriched in the eIF3e complex (data not shown), this analysis was severely hampered by the fact that 5'UTRs are poorly defined in S. pombe. It is therefore still possible that critical features, including secondary structure determinants, lie within the 5'UTR or other regions of eIF3e-associated mRNAs. Substantial additional work will be required to delineate the exact mechanism of how eIF3e may contribute to the translation of specific mRNAs and the potential impact of this mechanism on human cancers defective in INT6/eIF3e [58,59].
Conclusion
We provide biochemical evidence for the existence of two distinct eIF3 complexes in fission yeast. These complexes contain an overlapping set of subunits, but are distinguished by the PCI proteins eIF3e and eIF3m. Based on the finding that the distinct eIF3 complexes associate with different mRNAs, we propose that they have different translational specificities.
Methods
Fission yeast techniques
Preparation of fission yeast cultures, cDNA cloning, yeast transformation, PCR-based genomic epitope tagging and gene deletion, mating, and tetrad analysis were carried out using standard methods as described [26]. The strains used in this study are listed in Table 2.
Affinity purification and mass spectrometry
Epitope-tagged strains (eif3m-proA and eif3e-proA strains) were grown in 12 L yeast extract and supplements (YES) medium to 1.5 optical density (OD) at 595nm wavelength and harvested by centrifugation. Cell lysates were prepared by bead lysis in a lysis buffer containing 50 mM Tris-HCl pH 8.0, 150 mM NaCl, 0.5% Triton X-100, 1 mM dithiothreitol, supplemented with protease inhibitors (10 ug/ml leupeptin, 10 ug/ml pepstatin, 5 ug/ml aprotinin and 1mM phenylmethylsulfonylfluoride). Upon centrifugation at 17,000 rpm for 50 min at 4°C, 300 mg total protein in a volume of 50 ml was absorbed to 100 ul Dyna beads (Dynal Biotech, Oslo, Norway) coupled to whole rabbit IgG (Jackson Immunochemicals, West Grove, Pennsylvania, USA). Mock purifications were performed in parallel by absorbing lysate from cells lacking any tagged proteins to IgG beads. Beads were collected by a magnetic device and washed five times in 5 ml lysis buffer. TEV protease (Invitrogen, Carlsbad, California, USA) cleavage or elution in 5% SDS solution were used to collect bound proteins. Eluted proteins were separated on trycine gels or by conventional SDS-polyacrylamide gel electrophoresis (SDS-PAGE), and visualized by Coomassie G250 staining. Protein bands were excised from gels, digested with trypsin (Promega Corporation, Madison, Wisconsin, USA), and subjected to mass spectrometry. The eIF3 complexes were analyzed by MALDI-TOF, and by LC-MS/MS at the Harvard NIEHS Center Proteomics Facility, according to standard procedures.
Protein synthesis and polysome analysis
The eif3f and eif3m conditional shut-off strains were inoculated in 10 ml Edinburgh Minimal Media (EMM) with or without thiamin and cultured at 30°C for 30 hrs. 100 uCi 35S-methionine were added to the cells, which were labeled for 30 min and then harvested by centrifugation. Cell lysates were prepared by bead disruption and equal amounts of the lysates were analyzed by SDS-PAGE. 35S-methionine incorporation was determined by autoradiography and quantified by PhosphorImager analysis (Bio-Rad, Hercules, California, USA).
Polysome analysis was performed exactly as described in Ref. [60]. Briefly, cells were grown in EMM with or without thiamin for 30 hrs. Cycloheximide (100 ug/ml) was added to each culture for 20 min. Cells were harvested and lysed in breaking buffer (20 mM Tris/HCl pH 7.4, 50 mM NaCl, 30 mM MgCl2, 1 mM DTT, 50 ug/ml cycloheximide, 0.2 mg/heparin, 50 U/ml SuperRNasein, and protease inhibitors), followed by centrifugation at 13,000 × g for 5 min. 20 A260 nm units of each supernatant in a volume of 500 ul were fractionated on 5-45 % sucrose gradients for 3 hrs at 30,000 rpm using a SW40-Ti rotor in a Beckman L70 centrifuge. Polysome profiles were obtained by monitoring the absorbance at 254 nm along the gradient using a Bio-Rad fractionator, and the output was recorded using a Bio-Rad UV detector.
RT-PCR
RNAs associated with the eIF3e and eIF3m complexes were purified as described above. Primer design and RT-PCR conditions were according to the manual supplied with the Platinum Quantitative RT-PCR Thermoscript kit (Invitrogen). Primers used for RT-PCR are listed in Table 3. The primer concentration for actin amplification was 0.25 uM. Other primers were used at 1 uM. Total RNA was obtained as described [19].
Immunological techniques
Immunoprecipitation, immunoblotting, and in vitro ubiquitination assays were carried out exactly as described previously [26]. Antibodies against protein A and ubiquitin were purchased from Sigma and Genzyme (Cambridge, Massachusetts, USA), respectively. Anti-eIF3d/Moe1p polyclonal antibody was provided by E. Chang (Baylor College of Medicine, Houston, Texas, USA)
Microarray analysis
The eIF3 complexes were affinity-purified as described above, except that 50 U/ml SuperRNasein (Ambion, Austin, Texas, USA) and 5 mM ribonucleoside vanadyl complex (New England Biolab, Beverly, Massachusetts, USA) were added to the lysis buffer. A mock purification was performed under identical conditions with lysate from cells lacking any tagged proteins. The methods for extraction of RNA, cDNA synthesis, RNA amplification, and aminoallyl labeling were adopted from previous publications [61,62]. Briefly, after binding and washing, beads were treated with 3 U/ul DNase I, followed by elution with 5 % SDS, extraction with phenol/chloroform and then ethanol precipitation. The associated RNA was reversely transcribed using Superscript II reverse transcriptase (Gibco-BRL Division of Invitrogen) with 1 uM oligo-dT(15)-T7 primer (5'-AAA CGA CGG CCA GTG AAT TGT AAT ACG ACT CAC TAT AGG CGC-3') and 1 uM template switch primer (5'-AAG CAG TGG TAT CAA CGC AGA GTA CGC GGG-3'). Full-length double stranded (ds)-cDNA was synthesized using Advantage Polymerase (Clontech, BD Biosciences, Mountain View, California, USA). Newly synthesized ds-cDNA was passed through Bio-6 columns (Bio-Rad) and dried. RNA amplification was performed with the T7 megascript kit (Ambion). Amplified RNA was purified using the RNeasy kit (Qiagen, Hilden, Germany) and reversely transcribed with Superscript II reverse transcriptase in the presence of aminoallyl-dUTP in reactions primed with oligo-dT (Invitrogen). After RNAse H digestion and purification on QIAquick columns (Qiagen), the aminoallyl-cDNA was labeled with Cy3, and purified on QIAquick columns. Control Cy5-labeled aminoallyl-cDNA was made by oligo dT primed reverse transcription of total S. pombe RNA.
Labeled cDNAs were hybridized onto glass slide microarrays. Microarrays were made by spotting purified ds-PCR products 500 to 1200 bp in length onto glass slides coated with aminopropylsilane (Erie Scientific, Portsmouth, New Hampshire, USA). The PCR products used represented 4988 predicted ORFs and transcripts as annotated by the Sanger Centre [63] and are located at the 3' end of predicted genes to maximize sensitivity in detecting oligo-dT primed reverse transcription products. Descriptions of primer pairs and the features on the microarrays are available at the Longhorn Array Database [64].
Median pixel intensities for each spot obtained from hybridizations of eIF3-associated RNA ([see additional file 1, sheet 1]) were corrected by local background subtraction and divided by the corresponding values obtained from a mock purification. This resulted in the factor of enrichment of mRNAs bound to eIF3 complexes over mock. The mRNAs were ranked according to their factor of enrichment ([see additional file 1, sheet 2]). An enrichment factor of three was chosen as an arbitrary threshold. We found 2464 mRNAs were enriched greater than three-fold over mock in the eIF3m complex, while we observed 520 mRNAs enriched in the eIF3e complex ([see additional file 1, sheet 3]). Comparison of the data sets revealed 414 mRNAs that occurred in both complexes, 2050 mRNAs uniquely enriched in the eIF3m complex and 106 mRNAs that were exclusively enriched in the eIF3e complex ([see additional file 1, sheet 4; additional file 2]). A corresponding list of the 106 mRNAs most highly and uniquely enriched in the eIF3m complex was assembled ([see additional file 2]) and used to select specific mRNAs for RT-PCR analysis.
The competitive Cy5-labeled total cDNA provided clear microarray feature identification and a guide to relative sequence abundance in the pre-purification sample from which the relative expression rank of each mRNA was determined ([see additional file 1, sheet 2]). In this study, data were not adjusted by ratio normalization to total RNA signals or local area normalization functions. The microarray data were deposited with the public ArrayExpress (E-MEXP-208) [65] and GEO [66] databases.
List of abbreviations
CSN COP9 signalosome
Cul Cullin
eIF Eukaryotic initiation factor
EMM Edinburgh Minimal Media
GFP Green fluorescent protein
IgG Immunoglobulin G
LC MS/MS Liquid chromatography tandem mass spectrometry
MALDI-TOF Matrix-assisted laser desorption ionization time-of-flight
MPN Mpr1/Pad1 N-terminal
OD Optical density
PAGE Polyacrylamide gel electrophoresis
PCI Proteasome, COP9 Signalosome, eIF3
ProA Protein A
RT-PCR Reverse transcription-polymerase chain reaction
TEV Tobacco etch virus
YES Yeast extract and supplements (growth media)
Authors' contributions
CZ performed the bulk of the experiments shown in this study. FA and SW prepared various strains used in this study. SK and ARI performed mass spectrometry. AO performed the microarray hybridizations, and JL participated in the design of the microarray studies and in data analysis. DAW contributed to study design and drafting of the manuscript.
Supplementary Material
Additional File 1
This article is accompanied by a Microsoft Excel file (.xls) containing microarray data (see Methods for description).
Click here for file
Additional File 2
A Microsoft Excel file (.xls) is included containing the lists of the 106 mRNAs most highly and uniquely enriched in the eIF3e and eIF3m complexes.
Click here for file
Acknowledgements
We thank E. Chang for eIF3d/Moe1p antisera, V. Leautaud, G. Dittmar, F. Bachand, and P. Silver for help with polysome analyses, and M. Schmidt and A. Houseman for assistance with microarray data analysis. This study was funded by National Institute of Health (NIH) grant GM59780 to DAW, NIH grant P40 RR16320 to JL, by the NIEHS Center Grant ES-00002, and the NIEHS Training Grant ES07155.
Figures and Tables
Figure 1 Analysis of csn6 and csn7b genes and proteins. (A) The csn6 and csn7b genes were disrupted in diploid S. pombe cells by inserting the ura4 marker. Diploids were sporulated and spore viability was examined by tetrad analysis. Only two spores were viable, indicating that csn6 and csn7b are essential. (B) Cell lysate from a strain carrying csn7b modified with five C-terminal pro-A tags and a TEV cleavage site at the endogenous genomic locus was absorbed to IgG resin, followed by elution of bound proteins with TEV protease (left panel) or SDS (right panel). Gels were stained with Coomassie Brilliant Blue, and proteins were identified by MALDI-TOF mass spectrometry. The asterisks denote degradation products of elF3c.
Figure 2 Roles of eif3e and eif3min protein synthesis. (A) Subcellular localization. Live cells expressing GFP-tagged alleles of eif3b, eif3e, and eif3m at the endogenous genomic loci were examined by fluorescence microscopy. N-terminally GFP-tagged eif3f was expressed at low levels from the pREP81 plasmid. (B) Shut-off strains. Diploid heterozygous eif3f and eif3m deletion strains were transformed with pREP81 plasmids driving the thiamin-repressible expression of Myc-tagged eIF3f and eIF3m, respectively. Diploids were sporulated and homozygous disruptants carrying the eif3f and eif3m plasmids were selected. Cells were grown in liquid medium to an OD595 of 0.3 in the absence of thiamin, followed by promoter shut-off by the addition of thiamin. Samples were taken at the indicated time points after promoter shut-off and analyzed for the expression of plasmid borne eIF3f and eIF3m by immunoblotting with anti-Myc antibodies. (C) Effect on total protein synthesis. The eif3f and eif3m shut-off strains were maintained in the absence or presence of thiamin as indicated. Strains transformed with empty pREP81 plasmid were included as control. Cells were metabolically labeled with 35S-methionine, and aliquots of total cellular proteins were separated by SDS-PAGE and analyzed by autoradiography. The Coomassie Blue stained gel is shown to document equal protein loading. Data were quantified by PhosphorImager analysis and results are displayed in a bar graph. (D) Effect on polysomes. Polysome profiles were determined for the indicated strains as described in the Methods section. An eif3e deletion strain is shown for reference. (E) Effect on CSN-mediated regulation of cullin-RING ubiquitin ligases. Cul1p complexes were immunopurified from the indicated strains and employed in substrate-independent in vitro ubiquitylation reactions with purified E1, the E2 Cdc34p, ubiquitin, and ATP [26]. Polyubiquitin chains formed in the reaction are indicated (top panel). In contrast to csn5 mutants, derepression of Cul1p activity is not observed in cells lacking eif3f, eif3m, or eif3e. The neddylation state of Cul1p was determined by immunoblotting (middle panel). Hyperneddylated Cul1p only accumulates in csn5 mutants. Shut-off of eif3f and eif3m expression was verified by immunoblotting with anti-Myc antibodies (lower panel).
Figure 3 Distinct eIF3 complexes. (A) eIF3 complexes associated with eIF3e and eIF3m were affinity-purified by absorption of the respective pro-A-tagged proteins to IgG beads. Bound proteins were eluted by cleavage with SDS (eIF3e) or TEV protease (eIF3m). (B) The eluates described in (A) were analyzed by immunoblotting with eIF3d antibodies. The asterisk refers to cross-reactivity of the secondary antibody with Ig light chains. (C) Lysates from cells expressing Myc-tagged Csn5p, eIF3e, and eIF3m from their endogenous genomic loci were immunoprecipitated with anti-eIF3d antisera. Coprecipitated proteins were identified by immunoblotting as indicated. Total cell lysates are shown to document expression levels of the endogenously tagged proteins. (D) Protein lysate from cells expressing protein A-tagged eIF3b from the endogenous promoter was absorbed to IgG beads, and specifically retained proteins were identified by LC-MS/MS.
Figure 4 Association of mRNAs with eIF3 complexes. (A) Messenger RNAs associated with eIF3e and eIF3m complexes were identified by microarray hybridization as described in the Methods section. The graph indicates the numbers of mRNAs enriched more than three-fold over mock in both complexes. (B) Classification into functional groups of the 106 mRNAs most highly and uniquely enriched in complexes with eIF3e or eIF3m. (C) The relative expression ranks of the 106 most highly and uniquely enriched mRNAs in the eIF3e and eIF3m complexeswere determined using the relative hybridization signals obtained with total S. pombe cDNA ([see additional file 1]). The expression ranks were blotted against the factor of enrichment of each mRNA in the eIF3 complexes. No correlation between expression rank and enrichment is apparent, indicating that highly expressed mRNAs were not unspecifically enriched in eIF3 complexes. The 5407 individual features on the microarray slides represent the 4988 ORFs and transcripts predicted in the Sanger Centre S. pombe genome database and various controls. To simplify the analysis, expression ranks were also assigned to these control spots, thus resulting in expression ranks for some ORFs higher than the theoretically possible number of 4988.
Figure 5 Specific association of mRNAs with the eIF3e and eIF3m complexes. (A) The eIF3 complexes shown were affinity-purified as described in the Methods section, and separated by SDS-PAGE followed by staining with Coomassie Brilliant Blue. The labeled bands were identified by LC-MS/MS. eIF3f* refers to a band in the eIF3m complex that was not identified by mass spectrometry in this experiment, and is therefore assigned based on its comigration with eIF3f identified in the eIF3e complex (right lane). eIF3f was positively identified by MALDI-TOF mass spectrometry as a subunit of the eIF3m complex in Fig. 1B. (B) The indicated eIF3e- and eIF3m-associated mRNAs were extracted from the purified complexes and employed in RT-PCR reactions using primers specific for each mRNA (see Table 3). PCR products obtained with total S. pombe RNA are shown for reference in the left panel. The factor of enrichment of each mRNA in the respective eIF3 complex and the enrichment rank (out of all 106 mRNAs enriched in either complex) are indicated below the gels.
Table 1 Summary of eIF3 subunits in various eukaryotes
Unified Nomenclature
Domain
Human
S. cerevisiae (Core subunits)
S. pombe Csn7Bp complex
S. pombe Int6p complex
S. pombe eIF3b complex
eIF3a PCI p170 Tif32p p107 p107 p107
eIF3b RRM p116 Prt1p p84 p84 p84
eIF3c PCI p110 Nip1p p104 p104 p104
eIF3d - p66 - - Moe1p Moe1p
eIF3e PCI p48 - - Int6p Int6p
eIF3f MPN p47 - Csn6p Csn6p Csn6p
eIF3g RRM/Zn finger p44 Tif35p Tif35p Tif35p Tif35p
eIF3h MPN p40 - p40 - p40
eIF3i WD repeat p36 Tif34p Sum1p Sum1p Sum1p
eIF3j - p35 - - - -
eIF3k PCI p28 - - - -
eIF3l PCI p67 - - - -
eIF3m PCI GA17 (?) - Csn7Bp - Csn7Bp
Table 2 Strains used in this study
Name Genotype Source
DS448/1 leu1-32 ura4-d18 ade6-704 h+ Lab stock
DS448/2 leu1-32 ura4-d18 ade6-704 h- Lab stock
C399/3 leu1-32 ura4-d18 ade6-704 csn5.13myc kan h- Lab stock
C485/3 leu1-32 ura4-d18 ade6-704 eif3m.13myc kan h- Lab stock
C617/1 leu1-32 ura4-d18 ade6-704 eif3m.CBP.tev.5proA kan h- Lab stock
C642/1 leu1-32 ura4-d18 diploid, eif3f/eif3f::ura4 This study
C642/2 leu1-32 ura4-d18 diploid, eif3f/eif3f::ura4 This study
C648 leu1-32 ura4-d18 ade6-704 eif3e.cbp.tev.5proA kan h+ This study
C650/1 leu1-32 ura4-d18 ade6-704 eif3f::ura4 pRep81.6xhis.myc.eif3f h- This study
C650/2 leu1-32 ura4-d18 ade6-704 eif3m::ura4 pRep81.6xhis.myc.eif3m h- This study
C652/1 leu1-32 ura4-d18 ade6-704 eif3e::ura4 h+ This study
C663/1 leu1-32 ura4-d18 ade6-704 eif3m.gfp kan h- This study
C663/2 leu1-32 ura4-d18 ade6-704 eif3e.gfp kan h- This study
C665 leu1-32 ura4-d18 ade6-704 eif3e.13myc kan h- This study
C701 leu1-32 ura4-d18 ade6-704 eif3b.gfp kan, h- This study
C702 leu1-32 ura4-d18 ade6-704 eif3b.cbp.tev.5proA kan h- This study
Table 3 RT-PCR primers
Gene Name Sequence Product Size (bp)
actinF GAGCTTCCTGATGGTCAAGT 200
actinR GGATACATAGTGGTACCACC
cdc16F AAGTTAGCGCCCAAATCACC 150
cdc16R TTTTGAATGCCCCCCCACGG
gar2F GGTGCCATTGAGAAACCTTC 150
gar2R CCGAACCTTCAAAGAAATCA
pof6F TCTGATCGGCCTAAGCTGTC 150
pof6R CAATCTTGCAAATTCAACTC
rpn5F TGAGAAGCAAGTTCGTCAGG 160
rpn5R TGAAACAATCGATGACAAGT
rps8-1F AAGCGTATTCACGAGGTCCG 150
rps8-1R CAACTCGTTGTTAGAAGGGT
scd1F TCAGAGTTGGCTGCTTTCTT 150
scd1R ATCCATTGTGTGCCCTGTTC
SPAC1348.05F CTTAGTGAACAGTTTGGAAG 150
SPAC1348.05R TGATAAACCAACGGATCCGA
SPAC21E11.04F GAGACATCACCTGCTCCAGA 150
SPAC21E11.04R TTTGCTCCGGTGACTAGGTG
SPBC12C2.06F TCTGTTCCCAAACCTCAAGC 150
SPBC12C2.06R ATCGATTTTTGCACCTTTAG
SPBC1683.01F GGCCGTAAATTTGTCTACGG 150
SPBC1683.01R ACCACCAATACCAACACCAA
SPBC36B7.03F CTCTCAATTAAATTTCACCC 150
SPBC36B7.03R AGGAGTACCGTATAAAGCAT
SPCC70.05cF GTACCTGGAAATAACTCTCC 150
SPCC70.05cR CATAGCCTTTTCTAAGAGAT
tf2-12F AAGCATGTACCAGAGATAGG 150
tf2-12R TGAATCACCTAGAAGAATTA
ung1F ACTTTGGAGAGTTCTTGGTT 150
ung1R TGGAGTATGATGTGACCATG
F = Forward; R = Reverse
==== Refs
Hofmann K Bucher P The PCI domain: a common theme in three multiprotein complexes Trends Biochem Sci 1998 23 204 205 9644972 10.1016/S0968-0004(98)01217-1
Glickman MH Ciechanover A The ubiquitin-proteasome proteolytic pathway: destruction for the sake of construction Physiol Rev 2002 82 373 428 11917093
Lam YA Lawson TG Velayutham M Zweier JL Pickart CM A proteasomal ATPase subunit recognizes the polyubiquitin degradation signal Nature 2002 416 763 767 11961560 10.1038/416763a
Verma R Aravind L Oania R McDonald WH Yates JR 3rdKoonin EV Deshaies RJ Role of Rpn11 metalloprotease in deubiquitination and degradation by the 26S proteasome Science 2002 298 611 615 12183636 10.1126/science.1075898
Yao T Cohen RE A cryptic protease couples deubiquitination and degradation by the proteasome Nature 2002 419 403 407 12353037 10.1038/nature01071
Glickman MH Rubin DM Coux O Wefes I Pfeifer G Cjeka Z Baumeister W Fried VA Finley D A subcomplex of the proteasome regulatory particle required for ubiquitin-conjugate degradation and related to the COP9-signalosome and eIF3 Cell 1998 94 615 623 9741626 10.1016/S0092-8674(00)81603-7
Wei N Deng XW Characterization and purification of the mammalian COP9 complex, a conserved nuclear regulator initially identified as a repressor of photomorphogenesis in higher plants Photochem Photobiol 1998 68 237 241 9723217 10.1562/0031-8655(1998)068<0237:CAPOTM>2.3.CO;2
Seeger M Kraft R Ferrell K Bech-Otschir D Dumdey R Schade R Gordon C Naumann M Dubiel W A novel protein complex involved in signal transduction possessing similarities to 26S proteasome subunits Faseb J 1998 12 469 478 9535219
Henke W Ferrell K Bech-Otschir D Seeger M Schade R Jungblut P Naumann M Dubiel W Comparison of human COP9 signalsome and 26S proteasome lid Mol Biol Rep 1999 26 29 34 10363643 10.1023/A:1006991419464
Schwechheimer C Serino G Callis J Crosby WL Lyapina S Deshaies RJ Gray WM Estelle M Deng XW Interactions of the COP9 signalosome with the E3 ubiquitin ligase SCFTIRI in mediating auxin response Science 2001 292 1379 1382 11337587 10.1126/science.1059776
Cope GA Deshaies RJ COP9 signalosome: a multifunctional regulator of SCF and other cullin-based ubiquitin ligases Cell 2003 114 663 671 14505567 10.1016/S0092-8674(03)00722-0
Doronkin S Djagaeva I Beckendorf SK The COP9 signalosome promotes degradation of Cyclin E during early Drosophila oogenesis Dev Cell 2003 4 699 710 12737805 10.1016/S1534-5807(03)00121-7
Liu C Powell KA Mundt K Wu L Carr AM Caspari T Cop9/signalosome subunits and Pcu4 regulate ribonucleotide reductase by both checkpoint-dependent and -independent mechanisms Genes Dev 2003 17 1130 1140 12695334 10.1101/gad.1090803
Wang X Feng S Nakayama N Crosby WL Irish V Deng XW Wei N The COP9 Signalosome Interacts with SCF(UFO) and Participates in Arabidopsis Flower Development Plant Cell 2003 15 1071 1082 12724534 10.1105/tpc.009936
Feng S Ma L Wang X Xie D Dinesh-Kumar SP Wei N Deng XW The COP9 signalosome interacts physically with SCF COI1 and modulates jasmonate responses Plant Cell 2003 15 1083 1094 12724535 10.1105/tpc.010207
Wee S Geyer RK Toda T Wolf DA CSN facilitates Cullin-RING ubiquitin ligase function by counteracting autocatalytic adapter instability Nat Cell Biol 2005 7 387 391 15793566 10.1038/ncb1241
Feldman RM Correll CC Kaplan KB Deshaies RJ A complex of Cdc4p, Skp1p, and Cdc53p/cullin catalyzes ubiquitination of the phosphorylated CDK inhibitor Sic1p Cell 1997 91 221 230 9346239 10.1016/S0092-8674(00)80404-3
Skowyra D Craig KL Tyers M Elledge SJ Harper JW F-box proteins are receptors that recruit phosphorylated substrates to the SCF ubiquitin-ligase complex Cell 1997 91 209 219 9346238 10.1016/S0092-8674(00)80403-1
Geyer R Wee S Anderson S Yates JRI Wolf DA BTB/POZ domain proteins are putative substrate adaptors for cullin 3 ubiquitin ligases Mol Cell 2003 12 783 790 14527422 10.1016/S1097-2765(03)00341-1
Xu L Wei Y Reboul J Vaglio P Shin TH Vidal M Elledge SJ Harper JW BTB proteins are substrate-specific adaptors in an SCF-like modular ubiquitin ligase containing CUL-3 Nature 2003 425 316 321 13679922 10.1038/nature01985
Pintard L Willis JH Willems A Johnson JL Srayko M Kurz T Glaser S Mains PE Tyers M Bowerman B Peter M The BTB protein MEL-26 is a substrate-specific adaptor of the CUL-3 ubiquitin-ligase Nature 2003 425 311 316 13679921 10.1038/nature01959
Furukawa M He YJ Borchers C Xiong Y Targeting of protein ubiquitination by BTB-Cullin 3-Roc1 ubiquitin ligases Nat Cell Biol 2003 5 1001 1007 14528312 10.1038/ncb1056
Ambroggio XI Rees DC Deshaies RJ JAMM: A Metalloprotease-Like Zinc Site in the Proteasome and Signalosome PLoS Biol 2004 2 0113 0119 10.1371/journal.pbio.0020002
Lyapina S Cope G Shevchenko A Serino G Tsuge T Zhou C Wolf DA Wei N Shevchenko A Deshaies RJ Promotion of NEDD8-CUL1 conjugate cleavage by COP9 signalosome Science 2001 292 1382 1385 11337588 10.1126/science.1059780
Cope G Suh GSB Aravind L Schwarz SE Zipursky SL Koonin EV Deshaies RJ Role of Predicted Metalloprotease Motif of Jab1/Csn5 in Cleavage of NEDD8 from CUL1 Science 2002 298 608 611 12183637 10.1126/science.1075901
Zhou C Wee S Rhee E Naumann M Dubiel W Wolf DA Fission Yeast COP9/Signalosome Suppresses Cullin Activity through Recruitment of the Deubiquitylating Enzyme Ubp12p Mol Cell 2003 11 927 938 12718879 10.1016/S1097-2765(03)00136-9
Wolf DA Zhou C Wee S The COP9 signalosome: an assembly and maintenance platform for cullin ubiquitin ligases? Nat Cell Biol 2003 5 1029 1033 14647295 10.1038/ncb1203-1029
Kim T Hofmann K von Arnim AG Chamovitz DA PCI complexes: pretty complex interactions in diverse signaling pathways Trends Plant Sci 2001 6 379 386 11495792 10.1016/S1360-1385(01)02015-5
Browning KS Gallie DR Hershey JW Hinnebusch AG Maitra U Merrick WC Norbury C Unified nomenclature for the subunits of eukaryotic initiation factor 3 Trends Biochem Sci 2001 26 284 11426420 10.1016/S0968-0004(01)01825-4
Unbehaun A Borukhov SI Hellen CU Pestova TV Release of initiation factors from 48S complexes during ribosomal subunit joining and the link between establishment of codon-anticodon base-pairing and hydrolysis of eIF2-bound GTP Genes Dev 2004 18 3078 3093 15601822 10.1101/gad.1255704
Phan L Zhang X Asano K Anderson J Vornlocher HP Greenberg JR Qin J Hinnebusch AG Identification of a translation initiation factor 3 (eIF3) core complex, conserved in yeast and mammals, that interacts with eIF5 Mol Cell Biol 1998 18 4935 4946 9671501
Naranda T MacMillan SE Hershey JW Purified yeast translational initiation factor eIF-3 is an RNA-binding protein complex that contains the PRT1 protein J Biol Chem 1994 269 32286 32292 7798228
Asano K Vornlocher HP Richter-Cook NJ Merrick WC Hinnebusch AG Hershey JW Structure of cDNAs encoding human eukaryotic initiation factor 3 subunits. Possible roles in RNA binding and macromolecular assembly J Biol Chem 1997 272 27042 27052 9341143 10.1074/jbc.272.43.27042
Akiyoshi Y Clayton J Phan L Yamamoto M Hinnebusch AG Watanabe Y Asano K Fission yeast homolog of murine Int-6 protein, encoded by mouse mammary tumor virus integration site, is associated with the conserved core subunits of eukaryotic translation initiation factor 3 J Biol Chem 2001 276 10056 10062 11134033 10.1074/jbc.M010188200
Dunand-Sauthier I Walker C Wilkinson C Gordon C Crane R Norbury C Humphrey T Sum1, a component of the fission yeast eIF3 translation initiation complex, is rapidly relocalized during environmental stress and interacts with components of the 26S proteasome Mol Biol Cell 2002 13 1626 1640 12006658 10.1091/mbc.01-06-0301
Bandyopadhyay A Lakshmanan V Matsumoto T Chang EC Maitra U Moe1 and spInt6, the fission yeast homologues of mammalian translation initiation factor 3 subunits p66 (eIF3d) and p48 (eIF3e), respectively, are required for stable association of eIF3 subunits J Biol Chem 2002 277 2360 2367 11705997 10.1074/jbc.M107790200
Burks EA Bezerra PP Le H Gallie DR Browning KS Plant initiation factor 3 subunit composition resembles mammalian initiation factor 3 and has a novel subunit J Biol Chem 2001 276 2122 2131 11042177
Crane R Craig R Murray R Dunand-Sauthier I Humphrey T Norbury C A fission yeast homolog of Int-6, the mammalian oncoprotein and eIF3 subunit, induces drug resistance when overexpressed Mol Biol Cell 2000 11 3993 4003 11071922
Bandyopadhyay A Matsumoto T Maitra U Fission yeast Int6 is not essential for global translation initiation, but deletion of int6(+) causes hypersensitivity to caffeine and affects spore formation Mol Biol Cell 2000 11 4005 4018 11071923
Mundt KE Porte J Murray JM Brikos C Christensen PU Caspari T Hagan IM Millar JB Simanis V Hofmann K Carr AM The COP9/signalosome complex is conserved in fission yeast and has a role in S phase Curr Biol 1999 9 1427 1430 10607571 10.1016/S0960-9822(00)80091-3
Mundt KE Liu C Carr AM Deletion mutants in COP9/signalosome subunits in fission yeast Schizosaccharomyces pombe display distinct phenotypes Mol Biol Cell 2002 13 493 502 11854407 10.1091/mbc.01-10-0521
Zhou C Seibert V Geyer R Rhee E Lyapina S Cope G Deshaies RJ Wolf DA The fission yeast COP9/signalosome is involved in cullin modification by ubiquitin-related Ned8p BMC Biochemistry 2001 2 7 11504566 10.1186/1472-2091-2-7
Yahalom A Kim TH Winter E Karniol B von Arnim AG Chamovitz DA Arabidopsis eIF3e (INT-6) associates with both eIF3c and the COP9 signalosome subunit CSN7 J Biol Chem 2001 276 334 340 11029466 10.1074/jbc.M006721200
Hoareau Alves K Bochard V Rety S Jalinot P Association of the mammalian proto-oncoprotein Int-6 with the three protein complexes eIF3, COP9 signalosome and 26S proteasome FEBS Lett 2002 527 15 21 12220626 10.1016/S0014-5793(02)03147-2
Yen HC Gordon C Chang EC Schizosaccharomyces pombe Int6 and Ras homologs regulate cell division and mitotic fidelity via the proteasome Cell 2003 112 207 217 12553909 10.1016/S0092-8674(03)00043-6
Kim TH Kim BH Yahalom A Chamovitz DA von Arnim AG Translational regulation via 5' mRNA leader sequences revealed by mutational analysis of the Arabidopsis translation initiation factor subunit eIF3h Plant Cell 2004 16 3341 3356 15548739 10.1105/tpc.104.026880
Wee S Hetfeld B Dubiel W Wolf DA Conservation of the COP9/signalosome in budding yeast BMC Genet 2002 3 15 12186635 10.1186/1471-2156-3-15
Maytal-Kivity V Piran R Pick E Hofmann K Glickman MH COP9 signalosome components play a role in the mating pheromone response of S. cerevisiae EMBO Rep 2002 3 1215 1221 12446563 10.1093/embo-reports/kvf235
Shalev A Valasek L Pise-Masison CA Radonovich M Phan L Clayton J He H Brady JN Hinnebusch AG Asano K Saccharomyces cerevisiae protein Pci8p and human protein eIF3e/Int-6 interact with the eIF3 core complex by binding to cognate eIF3b subunits J Biol Chem 2001 276 34948 34957 11457827 10.1074/jbc.M102161200
Yen HC Chang EC Yin6, a fission yeast Int6 homolog, complexes with Moe1 and plays a role in chromosome segregation Proc Natl Acad Sci U S A 2000 97 14370 14375 11121040 10.1073/pnas.97.26.14370
Chen CR Li YC Chen J Hou MC Papadaki P Chang EC Moe1, a conserved protein in Schizosaccharomyces pombe, interacts with a Ras effector, Scd1, to affect proper spindle formation Proc Natl Acad Sci U S A 1999 96 517 522 9892665 10.1073/pnas.96.2.517
Ptushkina M Malys N McCarthy JE eIF4E isoform 2 in Schizosaccharomyces pombe is a novel stress-response factor EMBO Rep 2004 5 311 316 14968130 10.1038/sj.embor.7400088
Ron D Translational control in the endoplasmic reticulum stress response J Clin Invest 2002 110 1383 1388 12438433 10.1172/JCI200216784
Kaufman RJ Orchestrating the unfolded protein response in health and disease J Clin Invest 2002 110 1389 1398 12438434 10.1172/JCI200216886
Dever TE Gene-specific regulation by general translation factors Cell 2002 108 545 556 11909525 10.1016/S0092-8674(02)00642-6
Clemens MJ Targets and mechanisms for the regulation of translation in malignant transformation Oncogene 2004 23 3180 3188 15094767 10.1038/sj.onc.1207544
Dong Z Liu LH Han B Pincheira R Zhang JT Role of eIF3 p170 in controlling synthesis of ribonucleotide reductase M2 and cell growth Oncogene 2004 23 3790 3801 15094776 10.1038/sj.onc.1207465
Marchetti A Buttitta F Pellegrini S Bertacca G Callahan R Reduced expression of INT-6/eIF3-p48 in human tumors Int J Oncol 2001 18 175 179 11115556
Miyazaki S Imatani A Ballard L Marchetti A Buttitta F Albertsen H Nevanlinna HA Gallahan D Callahan R The chromosome location of the human homolog of the mouse mammary tumor-associated gene INT6 and its status in human breast carcinomas Genomics 1997 46 155 158 9403073 10.1006/geno.1997.4996
Bachand F Silver PA PRMT3 is a ribosomal protein methyltransferase that affects the cellular levels of ribosomal subunits Embo J 2004 23 2641 2650 15175657 10.1038/sj.emboj.7600265
Wang E Miller LD Ohnmacht GA Liu ET Marincola FM High-fidelity mRNA amplification for gene profiling Nature Biotechnology 2000 18 457 459 10748532 10.1038/74546
Hieronymus H Silver PA Genome-wide analysis of RNA-protein interactions illustrates specificity of the mRNA export machinery Nat Genet 2003 33 155 161 12524544 10.1038/ng1080
The Wellcome Trust Sanger Institute
Longhorn Array Database
EMBL - EBI Arrayexpress Database
National Center for Biotechnology Information Gene Expression Omnibus Database
| 15904532 | PMC1173091 | CC BY | 2021-01-04 16:02:56 | no | BMC Biol. 2005 May 17; 3:14 | utf-8 | BMC Biol | 2,005 | 10.1186/1741-7007-3-14 | oa_comm |
==== Front
BMC CancerBMC Cancer1471-2407BioMed Central London 1471-2407-5-451589288510.1186/1471-2407-5-45Research ArticleDifferences in gene expression in prostate cancer, normal appearing prostate tissue adjacent to cancer and prostate tissue from cancer free organ donors Chandran Uma R [email protected] Rajiv [email protected] Changqing [email protected] George [email protected] Michael [email protected] John [email protected] From the Department of Pathology, University of Pittsburgh, Pittsburgh, PA 15232, USA2005 13 5 2005 5 45 45 8 11 2004 13 5 2005 Copyright © 2005 Chandran et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Typical high throughput microarrays experiments compare gene expression across two specimen classes – an experimental class and baseline (or comparison) class. The choice of specimen classes is a major factor in the differential gene expression patterns revealed by these experiments. In most studies of prostate cancer, histologically malignant tissue is chosen as the experimental class while normal appearing prostate tissue adjacent to the tumor (adjacent normal) is chosen as the baseline against which comparison is made. However, normal appearing prostate tissue from tumor free organ donors represents an alterative source of baseline tissue for differential expression studies.
Methods
To examine the effect of using donor normal tissue as opposed to adjacent normal tissue as a baseline for prostate cancer expression studies, we compared, using oligonucleotide microarrays, the expression profiles of primary prostate cancer (tumor), adjacent normal tissue and normal tissue from tumor free donors.
Results
Statistical analysis using Significance Analysis of Microarrays (SAM) demonstrates the presence of unique gene expression profiles for each of these specimen classes. The tumor v donor expression profile was more extensive that the tumor v adjacent normal profile. The differentially expressed gene lists from tumor v donor, tumor v adjacent normal and adjacent normal v donor comparisons were examined to identify regulated genes. When donors were used as the baseline, similar genes are highly regulated in both tumor and adjacent normal tissue. Significantly, both tumor and adjacent normal tissue exhibit significant up regulation of proliferation related genes including transcription factors, signal transducers and growth regulators compared to donor tissue. These genes were not picked up in a direct comparison of tumor and adjacent normal tissues.
Conclusions
The up-regulation of these gene types in both tissue types is an unexpected finding and suggests that normal appearing prostate tissue can undergo genetic changes in response to or in expectation of morphologic cancer. A possible field effect surrounding prostate cancers and the implications of these findings for characterizing gene expression changes in prostate tumors are discussed.
==== Body
Background
Prostate cancer is the most common cancer in men resulting in over 30,000 deaths annually [1]. Early detection and treatment has the potential to markedly reduce the morbidity and mortality associated with the disease. While elevated Prostate Specific Antigen (PSA) [2] is the best available indicator of men with cancer [3], its diagnostic utility is limited due to elevated PSA levels in other non-malignant prostate conditions, varying levels in advanced disease and poor correlation between PSA levels and extent of disease. Furthermore, the variable course of prostate cancer – many patients will not die of the disease – means that radical therapy for all early cases would result in over treatment of significant number of patients. High throughput genomic technologies, by simultaneously interrogating the expression levels of thousands of genes, offers the potential to identify new biomarkers for early detection, prognosis, targets for therapy and for reclassification of prostate tumors. Using expression microarrays, a number of studies have characterized expression profiles for prostate cancer and other tumors. In some cases, correlations between tumor expression signatures, clinical parameters and outcome [4-12] have been identified. While potentially powerful, such studies can be significantly impacted by the choice of baseline or "normal" tissue used to detect tumor related expression changes. Most prostate expression studies to date have utilized normal appearing tissue adjacent to tumor as the tissue for comparison. However, a variety of methods such as chromosomal analysis [13], SAGE [14] and ploidy analysis [15,16] have shown molecular abnormalities in normal appearing prostate adjacent to tumor. Even the term "normal appearing" prostate tissue adjacent to tumor may be misleading, as morphologic researchers using quantitative imaging analysis [17-19], have identified morphologic changes in the epithelial nuclei and blood vessels architecture in prostate tissue adjacent to tumor that are not routinely commented upon by pathologists. This suggests that, in some cases, tissues adjacent to cancer, although appearing morphologically normal by traditional microscopic examination, may contain genetic changes associated with the genesis of or reaction to cancer. Therefore, the use of adjacent normal as the baseline tissue for comparative gene expression studies may mask tumor related molecular changes preceding the appearance of histological tumor. More recently, a microarray study from our institution [12], using adjacent normal and tumor samples, describes a potential field effect around prostate cancers and regulation of selected genes in both adjacent normals and tumors. Using the same microarray data set for our analysis, we have compared the gene expression profiles of prostate cancer, normal appearing prostate tissue adjacent to tumor, and normal appearing prostate tissue from cancer free tissue donors with the aim of identifying the optimal baseline tissue for expression studies and the gene expression changes between the three specimen types.
Methods
Clinical profile of cases
The 60 tumor samples used in this study consisted of 2, 13, 27, 6 and 12 cases of primary prostatic adenocarcinoma of Gleason grade 5, 6, 7, 8 and 9 respectively. There were 4, 20, 23 and 13 cases spanning the age groups 40–49, 50–59, 60–69 and 70–79 respectively. Of the cases, 36 were stage T3 or higher with 2, 22, 23, 11 and 2 cases of stage T2a, T2b, T3a, T3b and 4 respectively.
The 63 adjacent normal samples consisted of 2, 11, 29, 8, and 13 cases of Gleason grade 5, 6, 7, 8 and 9 respectively. There were 4, 21, 25 and 12 cases spanning the age groups 40–49, 50–59, 60–69 and 70–79 respectively. There were 2, 21, 26, 12 and 2 cases of Stage T2a, T2b, T3a, T3b and T4 respectively.
Of the donors, 11 are under and 7 are over the age of 40.
Samples and sample procurement
The tumor and adjacent normal tissue samples were acquired from the University of Pittsburgh Medical Center under stringent Institutional Review Board guidelines with appropriate informed consent. Specimens were received directly from the operating room. Samples (>500 mg) were excised and snap frozen in liquid nitrogen within 30 min of excision and stored at -80°C in the University of Pittsburgh Pathology Tissue Bank until extraction of RNA. All samples were submitted for pathology evaluation. In every case, the tissue was excised from the junction between the ejaculatory duct and the prostatic urethra in the transition zone of the prostate. In particular, adjacent normal tissue was excised away from the cancer lesion macroscopically, and their histological diagnosis was confirmed microscopically.
Donor tissue specimens were received through a collaborative arrangement with the Center for Organ Recovery and Education (CORE), the local organ procurement agency. The arrangement allows the University of Pittsburgh Pathology Tissue Bank to acquire normal prostates and associated serum/plasma specimens from healthy individuals who have donated their organs for transplant. There is extensive collaborative support from CORE. The donor prostatectomies harvested from brain dead, perfused donors and are bathed in Ringer's Lactate solution and transported on wet ice. These donor prostates are transported and handled with the harvested "transplant" organs. This significantly reduces transit time and minimizes the degradation of RNA. The processing methodologies used consist of snap freezing tissues in bulk, freezing in OCT and processing the tissues for routine histology (paraffin embedded tissues. For microarray analysis, the donor samples were excised from the same zone as the tumor and adjacent normal samples.
cRNA preparation and Affymetrix chip hybridization
cRNA was prepared and hybridized to Affymetrix oligonucleotide arrays as previously described [12]
Statistical analysis
We analyzed prostate tissue samples from 18 donors and 63 prostate cancer patients. From the prostate cancer patients we took samples from the histologic tumor as well as normal appearing tissue adjacent to the tumor. High quality RNA and chip data were obtained from 60 cancer and 63 adjacent to tumor samples. In total 141 samples were run against the Affymetrix U95A chip and analyzed. The raw scanned array images were first processed through the Affymetrix Microarray Analysis Suite 5.0 (Affymetrix Corporation, Santa Clara, Ca) to generate probe cel intensity (*.cel) files. The *.cel files were then analyzed using both MAS 5.0 and dChip software from Harvard University [20], to generate gene expression signal values for each probe set. Data normalization to remove variation in overall chip intensities was perfumed by global scaling to a chip mean target intensity of 200 (MAS 5.0) or by the rank-invariant method (dCHIP). The MAS 5.0 with global scaling data and dChip with rank-invariant normalization data gave similar results in the subsequent analysis. Therefore, in the interests of clarity, we will focus on the MAS 5.0 results in the remainder this paper.
In the next phase of analysis, the donors, adjacent normals and tumors were compared for differences in gene expression by using signal values for all 12625 probe sets for each sample. For statistical analysis, we used the Significance Analysis of Microarray (SAM) software package from Stanford University [21]. This method was chosen over conventional statistical tests because of its acceptance in the microarray community, its general simplicity and its ability to provide an estimate of the false discovery rate (the ratio of false positives to total positives). The false discovery rate is particularly important when comparing the expression of thousands of genes simultaneously. For example, when using the Student's t test at a P value of 0.05 to examine a population of 10,000 genes, one would expect 500 false positives. If there were in fact 100 true positives, the false positive rate would be an unacceptably high 0.83 (500/600).
Briefly, SAM calculates a value for each probe set on the array. This value represents the observed difference in mean expression levels between the specimen classes being compared (i.e. tumor and donor) divided by the variance in the data and a fudge factor (see the original paper for details [21]. The resulting value is called the "observed d value". To determine the significance of this value, SAM estimates the "expected" d value if there were no difference between the specimen classes. This is done by permutating (randomly changing) the class labels without changing the data and recalculating the SAM value for each probe set. After thousands of permutations, the result estimates the value that would be obtained if the difference in gene expression were due to chance alone. This is the "expected d value".
The significance of the observed differential gene expression can be estimated by comparing the observed and expected d values. A user defined threshold or "delta" (observed d value – expected d value) can be adjusted to select only those genes observed d value exceeds (for up regulated genes) or is lower (for down regulated genes) than delta. The greater the "delta", the greater the stringency of the result and lower the false discovery rate. For each delta value, the SAM output consists of a gene (probe set) list and an associated false discovery rate. The false discovery rate is estimated from the distribution of expected and observed d values. Probe sets are ordered on the basis of observed d value metric, probe sets with high (or low) values represent genes with relatively high differential expression. The "SAM Plots" are also very useful in visualizing differences in overall differential gene expression between specimen classes.
Results
Expression analysis of tumor, adjacent normal and donor tissue
The prostate tumors analyzed in this study consisted of Gleason grades 5, 6, 7, 8, 9 and patients spanned the ages of 40 through 79. The goal of our research was to examine the differential gene expression patterns observed when comparing our three specimen classes: tumor versus adjacent normal, tumor versus donor and adjacent normal versus donor. The comparison was made at three points in the analytical process: 1) after normalization to remove variation in overall chip intensity 2) after statistical analysis of the data and, 3) after examining the differentially expressed gene lists.
To examine differences in normalized gene expression between tumors, adjacent normals and donors the mean MAS 5.0 and dChip generated signal of each probe set for each specimen class (60 tumors, 63 adjacent normals and 19 donors), was calculated and plotted on a series of scatter plots (Fig 1).
Figure 1 shows the scatter plots and Pearson correlations of the normalized expression data analyzed using both MAS 5.0 and dChip as described above (vide supra, Methods). Data scatter is maximum in the tumor versus donor comparison, intermediate in adjacent normal versus donor and minimal in tumor versus adjacent normal. These findings are suggestive of more differential gene expression in tumor versus donor than tumor versus adjacent normal. In other words, donor normal tissue and adjacent normal tissue do not show the same degree of differential gene expression when paired with tumor tissue. Another striking result apparent in Figure 1 is the close correlation and limited scatter of the tumor versus adjacent plot, even at low levels of signal.
Tumor and adjacent normal specimens came from the same population of patients while donor specimens were received from a different set of individuals. To examine potential patient specific expression effects, the 60 tumors and 63 adjacent normal cases were randomly segmented into two groups, one group provided just tumor data and the other just adjacent normal data and a scatter plot of expression was generated. Since the segmentation of 63 cases can be performed in many different ways (permutations), the scatter analysis was performed 1000 times and the correlation between the sample groups determined by obtaining the mean correlation coefficient of the 1000 permutations. (Figure 2). In this analysis, the close correlation in expression between tumor and adjacent normal specimens persisted even when tumor and adjacent normal samples were taken from different patients.
To determine the statistical significance of the observed differential expression between the three specimen groups, SAM analysis was performed. From each comparison (tumor v adjacent normal, tumor v donor and adjacent normal v donor), a SAM plot was generated and the plots for the three comparisons were overlaid (Fig 3). The diagonal line in Figure 3 represents no differential expression (identical observed and expected d values, for further details see Materials and Methods) with points displaced from the diagonal representing differential expression. Figure 3 shows that each of the comparisons yields a distinct expression profile with donor v tumor exhibiting more differential expression than adjacent normal v tumor or donor v adjacent normal.
To further characterize the expression profiles from these comparisons, differentially expressed gene lists were created from each comparison by selecting genes whose d values (for details, see Materials and Methods) exceed a given threshold. False discovery rates (false positives/ total number of genes in gene list) is no greater than 2.5% at the deltas chosen for this analysis (Table 1).
At a delta of 2.0, when tumor expression is compared to donor expression (Table 1), 474 differentially regulated genes can be detected. At the same delta, when tumor expression is compared to adjacent normals, only 92 genes are differentially regulated between these two tissues. Furthermore, at this delta, comparison of tumor expression with adjacent normals does not yield any genes up-regulated in tumors whereas the comparison with donors demonstrates up-regulation of 121 genes. Similarly at other deltas, approximately three times more differentially regulated genes can be detected when tumors are compared to donors than to adjacent normals.
As was discussed above, tumors and adjacent normal tissues are obtained from the same patients and donor tissues from a different sample population. Therefore the larger gene expression differences between tumors and donors may represent underlying patient specific (genetic, demographic or handling) differences in patient (tumor and adjacent normal) and donor prostates rather than intrinsic differences between tumor, adjacent normal and donor normal tissues. It is significant however, that SAM analysis indicates that adjacent normals exhibit far less differential regulation than tumors when both are compared to donors. At all deltas (Table 1), tumors v donors exhibit greater differential expression than adjacent normals v donor implying that tumors and adjacent normals are not identical in gene expression. Therefore, tumor specific, and not patient specific, expression changes can indeed by detected by comparing tumors to donor prostates. Significantly, these results establish the presence of unique gene expression profiles for prostate tissue from donors, adjacent normals and tumors (see Fig 3) with tumors differing more from donors than from adjacent normals.
A potential limitation of our data is that donors span the ages of 5 to 60 and all tumor patients are older than 40. Therefore, the differential gene expression between donors and patients may be due to age specific differences in their prostates. To examine this, we segmented the donors into different age groups and compared only the 40 to 60 year old donors with tumors of the same age group. Although the number of cases in the study were small, the expression pattern observed in this age matched analysis is identical (data not shown) to that when all donors are included suggesting that potential age related differences in donor prostates do not contribute to the results of the donor v tumor analysis.
GO annotation of differential gene expression
We examined the gene lists produced by SAM analysis of tumor, adjacent normal and donor tissue with two objectives: 1) to identify and functionally annotate some of the genes that contribute to the unique expression signatures of these tissues and 2) to determine whether adjacent normals or donors are the more appropriate baseline tissue for detecting differentially expressed genes in tumors. Functional annotation and comparison of the gene lists was performed using Gene Ontology terms [22], for biological processes and Affymetrix's Gene Ontology Mining Tool .
When donors are used as the baseline for comparison, tumors exhibit up-regulation of proliferation related genes including transcription factors, signal transducers and growth regulators (see additional file 1). This list includes putative oncogenes, signal transducers and growth regulators. Some of the most up-regulated genes are v-fos, jun B, jun D, c-src tyrosine kinase, FGF receptor activating protein, immediate early protein and early growth response 1. The most down-regulated genes in tumors include those involved in immune response and signal transduction. Some of the genes in this list are the interferon induced transmembrane proteins, Duffy blood group antigen and tumor necrosis factor. In contrast, when adjacent normal tissue is used as the baseline for comparison, tumor tissue exhibits far fewer differentially expressed genes and the genes themselves are less compelling. The list up regulated genes is dominated by ribosomal proteins and metabolic enzymes, while the down-regulated list includes muscle related genes such as tropomysin, actin and actinin.
When expression in adjacent normal is compared to donors, an up-regulation pattern remarkably similar to tumors is seen (additional file 1). Adjacent normals also exhibit up-regulation of putative oncogenes, signal transducers and growth regulators with an almost 70% overlap of the 50 and 100 most up-regulated genes in tumors and adjacent normals, respectively. Similarly there is almost 60% overlap between the most down-regulated genes in tumors and adjacent normals that includes genes involved in immune response.
The biological processes regulated in tumors and adjacent normals were also studied using Affymetrix's Gene Ontology Mining tool. The up regulated gene lists obtained at a SAM delta of 2.0 (Table 1) were uploaded to the tool and the resulting annotations examined. Comparison of tumor gene expression to donor expression reveals up-regulation of genes involved in a number of biological processes (Figure 4a). Amongst these are genes involved in apoptosis, cell cycle, cell proliferation, immune response, protein phosphorylation, protein biosynthesis and transcription. A subset of these including genes involved in immune response and transcription are also up-regulated in adjacent normals (Figure 4b). In contrast when tumor expression is compared to adjacent normals, up-regulation of majority of these processes, except protein metabolism, is not detected (Figure 4c).
Two important conclusions can be derived from the gene annotations, 1) though there are large number of genes regulated in tumors, there is a relatively small subset of genes including oncogenes and signal transducers that are highly regulated in both adjacent normal and tumor tissues and 2) regulation of a number of potentially important biological processes in tumors can be detected from using donors as the baseline tissues. The common regulation of oncogenes, signal transducers and immune response genes in adjacent normals is a striking result in that it suggests that adjacent normal tissue although appearing morphologically normal, undergo gene expression changes that may be important in tumorigenesis or as a reaction to tumor. Since these genes are regulated in both tumor and adjacent normal, they are not picked up on a direct comparison of the two tissues. While it is possible that donors are different from both adjacent normals and tumors due to processing artifacts – the tumor and adjacent tissues were taken at surgery and donors at harvesting – it is unlikely that the large differences seen in donor v tumor are all due to processing differences. This issue is examined further in the discussion section.
The up regulation of proliferation markers in both adjacent normals and tumors coupled with the result that more differential regulation is detected when tumors are compared to donors than to adjacent normals suggests that donor prostates may be the more appropriate tissue for expression studies. Regulation of critical of biological processes and pathways may remain undetected if tissue adjacent to tumors is used for comparison.
Discussion
There is a growing interest in the use of high throughput microarray analysis for the molecular reclassification of diseases. This interest appears to be well founded, as many groups have reported consistent patterns of gene expression associated with pathologic phenotypes, clinical behaviors and outcomes [4-11]. In the area of prostate cancer numerous groups [23-29] have all reported significant differential gene expression between histologic tumor specimens and normal appearing prostate tissue from patients with tumor present elsewhere in the prostate. Recently, a group from our institution reported a 70 gene signature that may predict aggressiveness of prostate cancer [12]. Comparison of the gene lists from published data sets with the results of our tumor versus adjacent normal analysis is complicated by the heterogeneity in samples, analysis platforms and analysis methods. Nevertheless, our study is qualitatively similar to other studies in the expression profile of tumors compared to adjacent normal tissue. A number of genes including hepsin, myc, fatty acid synthase SPARC1 and EBNA-2 coactivator show similar expression patterns across multiple prostate cancer studies [30], and are also regulated in our study.
Our donors did not have prostate cancer or prostatic intraepithelial neoplasia (PIN) identified in their prostate and as such are good candidates for "true normals". Differential expression was much greater between tumor and donor tissue than between tumor and adjacent normal. The fact that tumor and adjacent specimens come from the same patients could possibly explain this difference but this was ruled out by our analysis. Another possibility is that tissue handing and processing differences could account for some or all of the differential expression seen when donor tissue is use as a baseline. In fact, data in the literature does suggest that tissue processing could effect the expression of genes such as fos, jun and egr in prostate tissue [29]. However, the same literature indicates that the effect warm ischemic time is limited to specific genes and in general, involves less than 1% of the regulated genes [29]. Our studies emphasize the need for documentation and quality of all experimental processing steps, from sample acquisition to sample hybridization, in order to completely characterize gene expression differences between prostate donors, tumors and normal tissue adjacent to tumors.
In our experiment, tumor and adjacent normal specimens where taken from the same prostates and handled the same way. If differences in patient and donor tissue handling was the major issue driving differential expression in the tumor v donor and adjacent normal v donor comparisons, one would expect tumor v donor and adjacent normal to result in very similar expression profiles. However, we have shown that tumor v donor exhibits far greater differential expression than adjacent normal v donor (see Results). Furthermore, the differentially expressed genes seen in both tumor and adjacent normal include proto-oncogene and transcription factors that one might rationally expect to see in expectation of or in response to a local tumor. Therefore, while the possibility that some expression changes are due to differences in tissue handling cannot be formally ruled out, it is unlikely that the large and specific differences we observe in tumor v donor, tumor v adjacent normal and adjacent normal v donor are entirely due to processing differences. Clearly additional studies, including examination of patient process specimens that do not host prostate cancer (such as cystoprostatectomy for bladder cancer or prostates removed for benign hypertrophy) to examine this process further.
The most important finding from our analysis is the potential importance of the donor specimens and the possibility that a field effect exists around prostate tumors, resulting in significant molecular changes in histologically normal appearing tissue adjacent to prostate cancer. Significantly, evidence for such malignancy associated changes have been presented in other organs such as the cervix, bladder and breast [31-33]
Furthermore, a variety of methods such as chromosomal analysis [13], SAGE [14], ploidy analysis [15,16] have shown molecular abnormalities in normal appearing prostate adjacent to tumor. Image analysis has also been employed to identify consistent changes in "normal appearing" prostate tissue adjacent to tumor [17,18]. In one study cases of prostatic adenocarcinoma was consistently detected by examining histologically normal tissue using high-resolution image cytometry [18], and in another, combined highly sensitive and discriminating Fourier transform-infrared spectroscopy with statistical analysis was used to detect damaged DNA in normal appearing prostate tissue adjacent to cancer [34].
In expression analysis, while most published prostate studies have used adjacent normals as the baseline tissue, Dhansekaran [23], used both commercially available pooled donor normal tissue and adjacent normal tissue and noted differences in expression profile between the two specimen types. Genes that were differentially expressed in adjacent normals when compared to the pooled donor normals included signal transducers and transcription factors; and expression of these genes in adjacent normals was attributed to a field effect around tumors. Similarly, Yu [12] have noted dysregulation of selected genes in both adjacent normals and tumors when compared to donors. Prakash [27], found that gene expression in asymptomatic benign prostatic hyperplasia adjacent to tumors was different from asymptomatic BPH or symptomatic BPH not associated with tumors. The unique expression signature of BPH next to tumors included fos, jun, immediate early genes and this list was remarkably similar to the most up-regulated genes in the adjacent normals tissue in our study (see adjacent normal v donor, additional file 1).
Finally, within archives of the University of Pittsburgh Pathology Tissue Bank, there was a donor prostate, which was found to harbor prostate cancer. When run on the Affymetrix arrays, the tumor classified with the tumors samples rather than the donor samples. Although this is clearly no more than an anecdotal event, it is an interesting finding.
Though microarray technology represents a major advance and provides a powerful tool for high-throughput expression analysis, the most effective use of this technology requires careful consideration of baseline normal tissue. Our results here emphasize the need for careful examination of what constitutes normal tissue and the importance of future studies to fully characterize normal appearing tissue adjacent to prostate cancers.
Conclusions
Prostate tumor tissue, histologically normal tissue adjacent to tumors and donor normal prostate tissue exhibit unique gene expression profiles with tumor and adjacent normal profiles more similar to each other than to the donors. These results suggest that normal appearing tissue around prostate tumors may also be undergoing tumor related changes and that careful characterization of these different tissues is necessary to understand molecular changes in leading up to prostate cancer.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
URC was involved in the data analysis and interpretation and manuscript writing and revision. RD, as director of the Tissue Bank was involved in obtaining IRB approval and providing deidentified tissue for this research study. CM was involved in data analysis and interpretation. GM and MB as principal investigator and co-investigators of the grant titled "the Molecular Reclassification of Cancer" were responsible for design of the study, providing intellectual input and final approval of the version submitted for review. JG was responsible for providing intellectual direction, guidance for the analysis team, review and final approval of the manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Supplementary Material
Additional File 1
The fifty most up regulated and down regulated genes from the tumor v donor, tumor v adjacent normal and adjacent normal v donor comparison. The Affymetrix probe set id, gene names and assignment of biological process for each gene are shown. The biological process annotation includes information from Affymetrix, gene ontology and literature references.
Click here for file
Acknowledgements
This work was funded by 1 U01 CA86735-01 (to MB)"A Shared Resource for the Molecular Classification of Prostate Cancer Comprehensive Prostate Cancer Tissue Resource (CPCTR) Consortium, National Cancer Institute, 5 U01 CA88110-02 (to GM, MB is Co-Principal Investigator) "Molecular Reclassification of Prostate Cancer" Director's Challenge for the Molecular Classification of Cancer Consortium National Cancer Institute and 2000-98 (to JG) DOD National Medical Technology Test Bed An Advanced Tissue Banking Information System
Figures and Tables
Figure 1 Differential gene expression analysis of donor, tumor and adjacent normal protate cancer samples. Scatter plot of MAS 5.0 derived tumor vs donor, adjacent normal v donor and tumor v adjacent normal samples. For each probe set, the mean MAS 5.0 expression values of all the samples in each specimen group was calculated. Scatter plot were constructed using the mean values for each specimen group.
Figure 2 Regression analysis of permuted donors, adjacent normal and tumor samples. The 60 tumors and 63 adjacent normal tissues were segmented so that tumors and adjacent normal samples in each comparison were selected from different patients. The resulting tumor and adjacent normal samples were then subjected to regression analysis. Donor v tumor, donor v adjacent normal and adjacent normal comparisons were performed. Since the segmentation can be performed in many different ways, the analysis was performed 1000 times. The mean correlation coeifficient and standard deviation from each of these comparisons were plotted as box plots.
Figure 3 Overlayed SAM plots (for details, see Materials and Methods) from the donor v tumor, donor v adjacent normal and tumor v adjacent normal analyses. Each of the SAM plots was overlayed to direct comparison of the plots. The diagonal line represents no differential gene expression where the observed d value equals the expected d value after 1000 permutations of the class labels. Genes that are differentially expressed are displaced from the diagonal (greater than 0 for up regulation and less than 0 for down regulation). Genes that are more differentially expressed are more displaced from the diagonal than those that are closer to the diagonal. For each of the comparisons, a plot is generated from the d values of the 12625 probe sets in the two specimen groups. Red = donor v tumor plot; green = adjacent normal v tumor plot; black = adjacent normal v donor plot.
Figure 4 Gene Ontology annotation of differentially expressed gene lists. The fifty most upregulated genes from the donor v tumor, adjacent normal v tumor and tumor v adjacent normal comparisons were uploaded to Affymetrix's Gene Ontology Mining Tool, a, donor v tumor; b, donor v adjacent normal; c adjacent normal v tumor; The annotations is presented as a hierarchy of terms, from general to most specific terms (from left to right). The numbers in parenthesis indicate the number of genes that are annotated with the term. In all of the analysis, annotation of all the submitted probe sets is not achieved. Typically, annotation exists for approximately 60% of the probe sets.
Table 1 Differential gene expression in the tumor v donor, tumor v adjacent normal and adjacent normal v donor comparisons. The number of genes identified as differentially regulated at each delta (observed d value – expected d value; for details, see Materials and Methods) are shown. Also, shown are the number of up and down regulated genes at each delta. For each of these deltas, the false discovery rate was no greater than 2.5%.
Delta 3.0 Delta 2.0 Delta 1.56
Tumor v Donor 65 474 928
Up Regulated 10 121 305
Down Regulated 55 353 623
Tumor v Adjacent Normal 0 92 382
Up Regulated 0 58
Down Regulated 92 324
Adjacent Normal v Donor 12 86 254
Up Regulated 5 25 63
Down Regulated 7 61 191
==== Refs
Cancer facts and figures 2003
Sokoll LJ Chan DW Prostate-specific antigen Urology Clinics North America 1997 24 253 259 10.1016/S0094-0143(05)70370-0
Polasckik TJ Oesterling JE Partin AW Prostate specific antigen. Its discovery and biochemical characteristics Journal of Urology 1999 162 293 306 10411025 10.1097/00005392-199908000-00003
Takahashi M Rhodes DR Furge KA Kanayama H Kagawa S Haab BB Gene expression profiling of clear renal cell carcinoma: gene identification and prognostic classification PNAS 2001 98 9754 9759 11493696 10.1073/pnas.171209998
van't Veer LJ Dai H van de Vijver MJ He YD Hart AA Mao M Peterse HL van der Kooy K Marton MJ Witteveen AT Schreiber GJ Kerkhoven RM Roberts C Linsley PS Bernards R Friend SH Gene expression profiling predicts clinical outcome of breast cancer Nature 2002 415 530 536 11823860 10.1038/415530a
Pomeroy S Tamayo P Gaasenbeek M Sturla L Mangelo M McLaughlin ME Kim JYH Goumnerova LC Black PM Lau C Allen JC Zagzag D Olson JM Curran T Wetmore C Biegel JA Poggio T Mukherjee S Rifkin R Califano A Stolovitzky G Louis DN Mesirov JP Lander ES Golub TR Prediction of central nervous system embryonal tumoru outcome based on gene expression Nature 2002 415 436 442 11807556 10.1038/415436a
Geisler SJH Hastie T Eisen MB van de Rijn M Jeffrey SS Thorsen T Quist H Matese JC Brown PO Botsten D Lonning PE Borresen-Dale A-L Gene expression patterns of breast carcinomas distinguish tumor subcalsses with clinical implications PNAS 2001 98 10869 10874 11553815 10.1073/pnas.191367098
Beer DG Kardia SL Huang CC Giordano TJ Levin AM Misek DE Lin L Chen G Gharib TG Thomas DG Lizyness ML Kuick R Hayasaka S Taylor JM Iannettoni MD Orringer MB Hanash S Gene-experssion profiles predict survival of patients with lung adenocarcinoma Nature Medicine 2002 8 816 824 12118244
Golub TR Slomin DK Tamayo P Huard C Gaasenbeek M Mesirov JP Coller HLM Downing JR Caligiuri MA Bloomfield CD Lander ES Molecular classification of cancer: class discovery and class prediciton by gene expression monitoring Science 1999 286 531 537 10521349 10.1126/science.286.5439.531
Bhattacharjee A Richards WG Staunton J Li C Monti S Vasa P Ladd C Beheshti J Bueno R Gillette M Loda M Weber G Mark EJ Lander ES Wong W Johnson BE Golub TR Sugarbaker DJ Meyerson M Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses PNAS 2001 98 13790 13795 11707567 10.1073/pnas.191502998
Ramaswamy S Tamayo P Rifkin R Mukherjee S Yeang C-H Angelo M Ladd C Reich M Latulippe E Mesirov JP Poggio T Gerald W Loda Massimo Lander ES Golub TR Multiclass cancer diagnosis using tumor gene expression signatures PNAS 2001 98 15149 15154 11742071 10.1073/pnas.211566398
Yu YP Landsittel D Jing L Nelson J Ren B Liu L McDonald C Thomas R Dhir R Finkelstein S Michalopoulos G Becich M Luo JH Gene Expression Alterations in Prostate Cancer Predicting Tumor Aggression and Preceding Development of Malignancy Journal of Clinical Oncology 2004 2 2790 2799 10.1200/JCO.2004.05.158
Sandberg AA Chrosomal abnormalities and related events in prostate cancer Human Pathology 1992 23 368 380 1563737 10.1016/0046-8177(92)90083-F
Waghray A Schober M Feroze F Yao F Virgin J Chen YQ Identification of differentially expressed genes by serial analysis of gene epxression in human prostate cancer Cancer Research 2001 61 4283 4286 11358857
Bostwick DJ Prospective origins of prostate carcinoma. Prostatic intraepithelial neoplasia and atypical adenomatous hyperplasia Cancer Reserach 1996 78 330 336
Bostwick DJ Shan A Qian J Darson M Maihle NJ Jenkins RB Cheng L Independent origin of multiple foci of prostatic intraepithelial neoplasia Cancer 2000 83 1995 2002 10.1002/(SICI)1097-0142(19981101)83:9<1995::AID-CNCR16>3.0.CO;2-2
Montironi R Diaminiti L Santinelli A Magi GC Scarpelli M Giannulis I Mangili F Subtle changes in benign tissue adjacent to prostate neoplasia detected with a bayesian belief network Journal of Pathology 1997 182 442 449 9306966 10.1002/(SICI)1096-9896(199708)182:4<442::AID-PATH866>3.3.CO;2-G
Bartels PH Montironi R Duval da Silva V Hamilton PW Tissue architecture analysis of prostate cancer and its precursors: an innovative approach to computerized histometry European Urology 1999 35 484 491 10325510 10.1159/000019884
Mairinger TG Mikuz G Gschwendtner Nuclear chromatin texture analysis of nonmalignant tissue can detect adjacent prostatic adenocarcinoma The Prostate 1999 41 12 19 10440871 10.1002/(SICI)1097-0045(19990915)41:1<12::AID-PROS3>3.0.CO;2-#
Schadt E Li C Ellis B Wong WH Feature extraction and normalization algorithms for high-density oligonucleotide gene expression array data Journal of Cellular Biochemistry Supplement 2001 37 120 125 11842437
Tusher VGTR Chu G Significance analysis of microarrays applied to the ionizing radiation response PNAS 2001 98 5116 5121 11309499 10.1073/pnas.091062498
Ashburner M Ball C Blake JA Botstein D Butler H Cherry JM Davis AP Dolinski K Dwight SS Eppig JT Harris MA Hill DP Issel-Tarver L Kasarskis A Lewis S Matese JC Richardson JE Ringwald M Rubin GM Sherlock G Gene ontology: tool for the unification of biology. The gene ontology consortium Nature Genetics 2000 1 25 29
Dhanasekaran SM Barette TR Ghosh D Shah R Varambally S Kurachi K Pienta KJ Rubin MA Chinnaiyan AM Delineation of prognostic biomarkers in prostate cancer Nature 2001 412 822 826 11518967 10.1038/35090585
Luo J Duggan D Chen Y Sauvageot J Ewing CM Bittner ML Trent JM Isaacs WB Human Prostate Cancer and Benign Prostatic Hyperplasia: Molecular Dissection by Gene Expression Profiling Cancer Reserach 2001 61 4683 4688 11406537
Luo JH Yu YP Cieply K Lin F Deflavia P Dhir R Finkelstein S Michalopoulos G Becich M Gene expression analysis of prostate cancers Molecular Carcinogenesis 2002 33 25 35 11807955 10.1002/mc.10018
Chetcuti A Margan S Mann S Russell P Handelsman D Rogers J Dong Identification of differentialy expressed genes in organ-confined prostate cancer by gene expression array 2001 47 132 140 11340636
Prakash K Pirozzi G Elashoff M Munger W Waga I Dhir R Kakehi Y Getzenberg RH Symptomatic and asymptomatic benign prostatic hyperplasia: Molecular differentiation by using microarrays PNAS 2002 99 7598 7603 12032329 10.1073/pnas.112191399
Singh D Febbo PG Ross K Jackson DG Manola J Ladd C Tamayo P Renshaw AA D'Amico AV Richie JP Lander ES Loda M Kantoff PW Golub T Sellers WR Gene expression correlates of clinical prostate cancer behavior Cancer Cell 2002 1 203 209 12086878 10.1016/S1535-6108(02)00030-2
Dash A Maine IP Varambally S Shen R Chinnaiyan AM Rubin MA Changes in differential gene expression because of warm ischemia time of radical prostatectomy specimens Am J Pathol 2002 161 1743 1748 12414521
Rhodes DR Barett TR Rubin MA Ghosh D Chinnaiyan AM Meta-analysis of microarrays: interstudy validation of gene expression profiles reveals pathway dysregulation in prostate cancer Cancer Research 2002 62 4427 4433 12154050
MacAulay C Lam S Payne PW LeRiche JC Palcic B Malignancy-associated changes in bronchial epithelial cells in biopsy specimens Anal Quant Cytol Histol 1995 17 55 61 7766269
Montag AG Bartels P Dytch HE Lerma-Puertas E Michelassi F Bibbo M. Karyometric marker features in tissue adjacent to in situ cervical carcinoma Anal Quant Cytol Histol 1989 11 275 280 2765074
Montag AG Bartels PH Dytch HE Lerma-Puertas E Michelassi F Bibbo M Karyometric features in nuclei near colonic adenocarcinoma. Statistical analysis Anal Quant Cytol Histol 1991 13 159 167 1716896
Malins DC Johnson PM Barker EA Polissar NL Wheeler TM Anderson KM Cancer-related changes in prostate DNA as men age and early identification of metastasis in primary prostate tumors PNAS 2003 100 5401 5406 12702759 10.1073/pnas.0931396100
| 15892885 | PMC1173092 | CC BY | 2021-01-04 16:03:05 | no | BMC Cancer. 2005 May 13; 5:45 | utf-8 | BMC Cancer | 2,005 | 10.1186/1471-2407-5-45 | oa_comm |
==== Front
BMC CancerBMC Cancer1471-2407BioMed Central London 1471-2407-5-491590450910.1186/1471-2407-5-49Research ArticleFemale breast cancer incidence and survival in Utah according to religious preference, 1985–1999 Merrill Ray M [email protected] Jeffrey A [email protected] Department of Health Science, College of Health and Human Performance, Brigham Young University, Provo, Utah, USA2005 18 5 2005 5 49 49 8 11 2004 18 5 2005 Copyright © 2005 Merrill and Folsom; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Female breast cancer incidence rates in Utah are among the lowest in the U.S. The influence of the Church of Jesus Christ of Latter-day Saint (LDS or Mormon) religion on these rates, as well as on disease-specific survival, will be explored for individuals diagnosed with breast cancer in Utah from 1985 through 1999.
Methods
Population-based records for incident female breast cancer patients were linked with membership records from the LDS Church to determine religious affiliation and, for LDS Church members, level of religiosity. Incidence rates were age-adjusted to the 2000 U.S. standard population using the direct method. Cox proportional hazards model was used to compare survival among religiously active LDS, less religiously active LDS, and non-LDS with simultaneous adjustment for prognostic factors.
Results
Age-adjusted breast cancer incidence rates were consistently lower for LDS than non-LDS in Utah from 1985 through 1999. Rates were lower among LDS compared with non-LDS across the age span. In 1995–99, the age-adjusted incidence rates were 107.6 (95% CI: 103.9 – 111.3) for LDS women and 130.5 (123.2 – 137.9) for non-LDS women. If non-LDS women in Utah had the same breast cancer risk profile as LDS women, an estimated 214 (4.8%) fewer malignant breast cancer cases would have occurred during 1995–99. With religiously active LDS serving as the reference group, the adjusted death hazard ratio for religiously less active LDS was 1.09 (0.94 – 1.27) and for non-LDS was 0.86 (0.75 – 0.98).
Conclusion
In Utah, LDS lifestyle is associated with lower incidence rates of female breast cancer. However, LDS experience poorer survivability from breast cancer than their non-LDS counterparts. Parity and breastfeeding, while protective factors against breast cancer, may contribute to poorer prognosis of female breast cancer in LDS women.
==== Body
Background
Breast cancer is the most frequently diagnosed cancer among women in the United States [1]. Of 668,470 expected female cancer cases in 2004, 215,991 (32.3%) were breast cancer [1]. The incidence of female breast cancer is most common in developed countries such as the U.S. and Western Europe [2], and is higher among whites than other racial and ethnic groups [3]. Among the registries in the Surveillance, Epidemiology, and End Results (SEER) Program of the U.S. National Cancer Institute, female malignant breast cancer incidence rates are lowest in Utah [3], despite approximately 85% of the population being white, non-Hispanic [4].
About 70% of the 2.3-million population in Utah is affiliated with the Latter-day Saint (LDS or Mormon) religion [4,5]. Hence, female breast cancer incidence rates in Utah are largely representative of LDS women and their lifestyle behaviors. A study based on Utah data from 1971 through 1985 showed that LDS women had significantly lower age-adjusted breast cancer incidence rates than did non-LDS women [6]. A recent cross-sectional study involving non-Hispanic white females in Utah compared breast cancer risk factor behaviors between LDS and non-LDS [7]. This study focused on many factors previously shown to influence breast cancer, including age at first birth [8,9], number of pregnancies and number of births (parity) [10], lifetime duration of breastfeeding [10,11], and alcohol consumption [12]. LDS women compared with non-LDS women had a slightly older age at first birth, higher average number of pregnancies and children (parity), and more total years of breastfeeding. LDS women also displayed lower levels of alcohol consumption. A cross-sectional study conducted in Utah in the late 1970s likewise found LDS women to have a later age at first pregnancy, more pregnancies, and lower prevalence of alcohol consumption [13]. However, research has also shown that reproductive factors which may decrease the risk of breast cancer development may explain poorer breast cancer survival [14].
The current study updates the findings of Lyon et al. [6] to the years 1985–99 and also examines female breast cancer survival in Utah according to LDS status and level of religiosity for LDS.
Methods
Utah Cancer Registry (UCR) data were linked to LDS Church membership records to estimate breast cancer survival according to LDS (religiously active and less active) and non-LDS populations in Utah during 1985–99.
Utah Cancer Registry
The UCR, established in 1966, has continuously participated in the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute since 1973. UCR staff members and local cancer registrars identify incident cases of cancer among Utah residents through routine and systematic review of pathology reports, medical records, radiation therapy records, hospital discharge lists, and vital records. Tumor characteristics including histology, grade, and primary site are coded according to the International Classification of Disease for Oncology-Second Edition (ICDO-2) [15]. Breast cancer-specific death is coded according to the International Classification of Diseases, 9th Revision, as 174.0 – 174.9 [16], and 10th Revision, which uses an alphanumeric system and codes them as C50 [17]. Categories of stage of disease at diagnosis are documented in the Summary Staging Guide of the SEER Program of the National Cancer Institute [18]. Registry records also include information regarding treatment, survival, and patient characteristics such as age at diagnosis, gender, race/ethnicity, and place of residence at diagnosis. Such information is ascertained from specific statements in medical records, reports from private pathology laboratories and radiotherapy units, and death certificates. Cancer surveillance in Utah is conducted in accordance with standards instituted by the SEER Program and the North American Association of Central Cancer Registries [19,20].
In order to provide valid estimates of cancer survival, a high percentage of cancer cases must be routinely followed to ascertain both vital status and date of last contact. UCR records are linked four times each year with records of death certificates from the Office of Vital Records and Health Statistics from the Utah Department of Health. Results from these routine linkages identify cancer patients who have died, regardless of their cause of death. Registry staff members work closely with cancer registrars in local hospitals to document, through systematic review of medical records, the date of last contact for those cancer patients not known to be deceased. Records for these patients are also linked annually with administrative databases, including Medicaid reimbursement claims, Utah driver license records, and Utah voter registration lists; these databases are often a source of updated information regarding vital status and/or date of last contact. According to SEER Program standards, follow-up is considered to be current when the Registry documents that a patient has died, or when the Registry documents that a patient was alive within 18 months of the annual anniversary of the date of original cancer diagnosis. By this definition, 97.9% of the patients in the present study were determined to have complete follow-up at the time data were captured for analysis.
Linkage of cancer data with LDS church records
UCR records were linked to LDS church membership records to determine membership in the LDS church. A person was identified as a member of the LDS church if the membership record included a baptismal date. The linkage process took place under direct supervision of the Church and the UCR and was conducted in the Church's Member and Statistical Records Department. After the records were linked, all personal identifying information was stripped from the database to ensure confidentiality.
Records were linked using the probabilistic linking program LinkPro [21]. The program calculates probabilities to identify whether a pair of records refers to the same person. Ten variables that were common to both sets of records were used to link the records: first, middle, and last names; birth day; birth month; birth year; gender; zip code; vital status; and maiden name. SOUNDEX versions of the names were used in the matching process, while actual names were used in the review process. Records were linked if they matched on at least seven of the ten variables. Ambiguous links and records that matched on six of the ten variables were manually reviewed. There were approximately 120,000 incident cases of cancer identified in the UCR database from 1973 to 1999 and approximately 6.6 million records in the LDS Church database. There were 81,617 (68%) UCR records linked to a Church membership record. Of these linked records, 74,829 (92%) matched on at least seven of the ten variables.
In addition to information about baptism, LDS church membership records include information on whether born in the church and whether endowed in the temple. To receive one's temple endowment requires conscientious effort toward obedience to the lifestyle prescribed by LDS doctrine [22]. This includes adherence to certain health practices such as not smoking or consuming alcohol, abstention from sexual relationships outside of marriage, and being honest in ones dealings with others [23]. A man or woman aged 19 year or older who is considered worthy in a personal interview with a church authority may receive a temple endowment. Generally LDS men and women receive their endowment prior to serving an LDS mission or at the time of a temple marriage. Previous research has considered the temple endowment as an appropriate surrogate marker for religious commitment among adults in the LDS church [24]. Although the data allowed us to identify LDS church membership and religiosity among LDS women, information about religious preference and religiosity was not available among non-LDS women.
Data
The present study was based on 9,619 female microscopically confirmed, actively followed malignant breast cancer cases (ICDO-2 site code C50.0:C50.9) diagnosed in Utah from 1985 through 1999. There were 5,234 (54.4%) religiously active LDS, 1,369 (14.2%) less religiously active LDS, and 3,015 (31.4%) non-LDS. In addition to LDS membership and level of religiosity, the following variables were considered: age, marital status, summary stage (pathological), histological grade, number of primary cancers in one individual, and treatment. Because of the high percentage of whites in Utah [4], analyses are limited to whites only.
Age was categorized as 0–34, 35–44, 45–54, 55–64, 65–74, and 75 years and older; marital status was categorized into four groups: never married, married/cohabitating, previously married, and unknown; and calendar years were categorized into four groups: 1985–88, 1989–92, 1993–96, and 1997–99. Number of primary cancers in an individual describes the chronology of diagnosis of all primary malignant cancers over the entire lifetime of the person [19]. Localized tumors are confined to breast, regional tumors are spread to contiguous organs or lymph nodes, and distant tumors are spread to remote organs. Histological grade is defined by the SEER Program Coding Manual and by the International Classification of Diseases for Oncology, Second Edition in increasing level of severity as either low grade (well differentiated), medium grade (moderately differentiated), or high grade (poorly differentiated) [15,19]. These categories are approximately equivalent to the more widely used Gleason grading system as Gleason score 2–4 (low), 5–7 (medium), and 8–10 (high) [19]. Radiation therapy was identified if radiation was a first course of cancer-directed therapy. Surgery was classified as conservative surgery [none; no cancer-directed surgery of primary site; partial mastectomy, not otherwise specified (NOS); less than total mastectomy, NOS], mastectomy [total (simple) mastectomy, NOS; modified mastectomy; radical mastectomy, NOS; extended radical mastectomy], or other surgery (mastectomy, NOS; surgery, NOS) [19].
Cases who had died but had unknown date of death, whose cause of death was determined by death certificate or autopsy only, or who represented a second or later primary cancer were excluded from the survival analysis. After these exclusions, there were 8,731 cases available for this portion of the study.
SEER registries were included in the study if they provided data to the National Cancer Institute during all the years from 1985 through 1999. These registries are as follows: San Francisco-Oakland, Connecticut, Metropolitan Detroit, Hawaii, Iowa, New Mexico, Seattle (Puget Sound), Utah, and Metropolitan Atlanta.
Statistical analyses
Age-adjusted rates were derived using the direct method and standardized to the 2000 U.S. population. Counts used in the rate calculations were microscopically confirmed. LDS and non-LDS breast cancer incidence rates were compared with SEER incidence rates. Ninety-five percent confidence intervals for the incidence rate calculations were based on standard error estimates from the formula SE(rate) ≈ rate/(cancer cases)1/2 [25]. Population attributable-risk percent is used to estimate the impact of having a certain breast cancer risk profile in Utah.
Among LDS, population values were not available by level of religiosity. Hence, rates are presented for LDS and non-LDS. However, level of religiosity among LDS could be estimated among the cases such that the survival analysis considered religiously active LDS, religiously less active LDS, and non-LDS.
Survival time was calculated as the time interval between diagnosis and date of last information. For deceased cases, the date of last information was the date of death. For cases not known to be deceased, the date of last information was the date that the case was last known to be alive. Cases with death from breast cancer (the outcome of interest), and all other cases were censored at the time of last information. We estimated breast cancer-specific survival for cases where breast cancer is a single cancer primary or the first of multiple cancer primaries.
Bivariate comparisons were evaluated using the chi-square test. Survival estimates were calculated by the Cox proportional hazards method with one-month intervals [26,27]. Statistical significance based on Cox proportional hazards was determined using 95% confidence intervals. The appropriateness of the Cox proportional hazards model was assessed graphically. Statistical analyses were derived in Statistical Analysis System (SAS) software, version 9.0 (SAS Institute Inc., Cary, NC, USA, 2003).
Results
Bivariate analyses of the association between religion and selected variables for female malignant breast cancer patients in Utah, 1985–99 are displayed in Table 1. Significant differences in the distribution of patients among these groups were observed across age categories, marital status, cancer primaries, and histological grade. Religiously active LDS patients tended to be older and were more likely married or previously married. Religiously less active LDS were more likely to have multiple cancer primaries. The high percentage of unknown histological grade at diagnosis makes this variable impossible to evaluate. The median difference in rates between LDS and non-LDS women across the study years was 20.2 per 100,000. The smallest difference in rates was 8.5 in 1992 and the largest difference in rates was 43 in 1991.
Age-adjusted female malignant breast cancer incidence rates among white women in Utah are presented by LDS status and calendar year in Figure 1. The comparatively low rates in Utah compared with SEER (without Utah) exist across calendar years. The lower rates are primarily explained by LDS women, although non-LDS women also contributed to the lower rates.
For the combined years 1995 through 1999, lower female malignant breast cancer incidence rates among LDS compared with non-LDS women in Utah were observed across the age span (Figure 2). Age-adjusted breast cancer incidence rates were 107.6 (95% CI: 103.9 – 111.3) for LDS women and 130.5 (123.2 – 137.9) for non-LDS women. In SEER (without Utah) the age-adjusted breast cancer incidence rate was 141.9 (140.9 – 142.9). Hypothetically speaking, if non-LDS women in Utah had the same breast cancer risk profile as LDS women, 214 (4.8%) fewer malignant breast cancer cases would have occurred during 1995–99. If the 9 SEER regions had the same breast cancer risk profile as women in Utah, 12,261 (16.2%) fewer malignant breast cancer cases would have occurred. If the 9 SEER regions had the same breast cancer risk profile as LDS women in Utah, 16,947 (22.4%) fewer malignant breast cancer cases would have occurred.
A proportional hazards model was used to estimate the death hazard for female malignant breast cancer among patients, with religiously active LDS as the referent group. The death hazard ratio for religiously less active LDS was 1.09 (0.94 – 1.27) and for non-LDS was 0.86 (0.75 – 0.98). Adjusted hazard ratios for age and marital status were also computed for patients based on their already having survived 0 months, 6 months, 12 months, 18 months, and 24 months (Figure 3). Religiously less active LDS compared with religiously active LDS showed no significant difference in the death hazards due to breast cancer across each of the conditioned time periods. On the other hand, non-LDS compared with religiously active LDS had significantly lower death hazard rates for breast cancer for each of the conditioned time periods.
Discussion
Utah presents a unique area for breast cancer studies because of the relatively low incidence of breast cancer among its residents, and the lower risk of breast cancer among members of the LDS church compared with non-LDS in the state. Lifestyle behaviors common among members of the LDS church, such as higher birthrates, higher prevalence and duration of breastfeeding, and lower alcohol consumption have been associated with lower incidence rates of breast cancer. The significantly lower risk of breast cancer among LDS shows the potential preventive effect certain behaviors may have against breast cancer. Yet this study also showed poorer survivability among a population with a traditionally lower incidence rate of breast cancer. It appears that the same factors that are associated with a lower incidence rate of breast cancer are also associated with poorer prognosis once breast cancer is diagnosed. This paradoxical finding is consistent with the results of a study by Korzeniowski and Dyba who reported that "reproductive factors known to decrease the risk of breast cancer development have an adverse effect on prognosis" [14].
Results in the current paper confirm those found by Lyon et al. [6]. Specifically, age-adjusted rates are consistently lower for LDS than non-LDS women. In addition, both LDS and non-LDS women displayed lower breast cancer incidence rates than in SEER. Lower rates among LDS women were observed across the age span. The lower rates among LDS women were likely primarily explained by their having significantly higher average number of pregnancies and children (parity), total years breastfeeding, and lower alcohol consumption [7,13].
Not only did LDS women in Utah experienced lower breast cancer incidence rates than did women in SEER, non-LDS women in Utah also had lower rates. This may be attributed to a conforming effect wherein the non-LDS minority approximates the lifestyle behaviors of the LDS majority to increase their social acceptability [28]. Social and cultural factors influence behaviors such as breastfeeding [29]. Religious preference and the dominant religious preference of one's residence are two independent factors associated with differences in desired number of children [30]. A religious group may have certain reproductive standards, but when they come in contact with a religious group with different standards, their reproductive health attitudes may change [31]. When a majority group exerts moderate social pressure, especially if greater social acceptance is achievable, the minority group is more likely to conform to the majority's values [32]. Each of these factors fits the relationship between LDS and non-LDS in Utah and may explain non-LDS conformity to selected LDS practices.
It should be noted that the linked data did not provide information about religious preference or religiosity among the nearly 30% non-LDS women. However, if the women in the study represent a similar representation as those identified in a recent cross-sectional survey of Utah adult women, approximately 26% of the non-LDS women were religiously active, 41% were less religiously active, and 34% had no religious preference [7]. Daniels et al. showed that the significantly lower average number of pregnancies and children (parity), total years breastfeeding, and higher alcohol consumption in non-LDS women were primarily in less religiously active women and those with no religious preference [7].
The population attributable-risk percent was presented to indicate the amount of breast cancer that could have been avoided under the hypothetical situation that everyone in Utah experienced the same breast cancer risk profile as LDS women. If everyone in SEER had the same breast cancer risk profile as LDS women in Utah, this percentage was 22.4%. In other words, approximately 22.4% of all breast cancer in SEER could have been avoided had women in SEER experienced a similar breast cancer risk profile as LDS women in Utah. Applying this percentage to the U.S. female population in 2004, an estimated 48,382 new cases could have been avoided had women in the U.S. displayed similar breast cancer risk behaviors as LDS women in Utah.
There was not a significant difference in death hazard rates between religiously active and less active LDS. However, there was a significant difference in death hazard rates between religiously active LDS and non-LDS. Lower death hazard rates in non-LDS became more pronounced as we conditioned on months already survived from diagnosis. Two possible explanations may help explain this, proximity to last childbirth and diagnosis during the lactation period.
New studies have indicated that a more recent birth prior to the diagnosis of breast cancer is associated with poorer survivability [30-33]. Older studies had failed to show an association, arguing that poorer survivability was coincidental and likely the result of significant delays in diagnosis [34-37]. Religiously active LDS women generally have more children than their non-LDS counterparts. While a greater number of childbirths is not associated with a worse prognosis in breast cancer [32], this higher parity does raise the likelihood that religiously active LDS women will have a more recent birth than non-LDS at the time of breast cancer diagnosis.
A less conclusive, yet possible contributor to poorer survivability among active LDS, is diagnosis during the lactation period. One study noted that breast cancer diagnosed during the lactation period has been associated with poorer survival among women younger than 45 years [35]. This relationship persisted despite adjustment for nodal status, tumor size, and age. A more recent literature review, however, concluded that no epidemiologic evidence exists to indicate that breastfeeding increases the risk of breast cancer recurring or of a second breast cancer developing [41]. It is biologically plausible that breastfeeding may contribute to a reduction in the development and growth risk of breast cancer. Breastfeeding reduces the number of ovulations proportionally to its intensity, and maintaining a lower estrogen level than that observed during the menstrual cycle [42]; it mobilizes endogenous and exogenous carcinogens present in the ductal and lobular epithelial cell environment [43]; and it reduces pH, levels of estrogens, and local carcinogens of the lobules and ducts [44,45]. Due to the limited and conflicting evidence supporting an association between diagnosis during lactation and poorer prognosis of breast cancer, and in light of biological mechanisms during lactation which may actually limit cancer growth, the possibility should not be ruled out that poorer prognosis associated with diagnosis during lactation may actually be attributable to the childbirth which most lactating women would have recently experienced. Further research is needed to clarify this association.
Limitations
The temple endowment was used as a surrogate marker for religiosity among LDS women. Although receiving one's temple endowment requires conscientious effort toward obedience to the lifestyle prescribed by LDS doctrine, which includes certain health practices like not smoking or consuming alcohol and abstention from sexual relationships outside of marriage, the data did not allow us to identify whether a previously endowed individual continued to adhere to the doctrine of the church. Yet we assume that given the high level of religious commitment required to receive one's temple endowment, the tendency was for these individuals to continue adherence to the health practices of the LDS religion. A related religiosity measure to the temple endowment was not available for non-LDS women.
We were concerned with the degree of accurate assignment of the cause of death, but the influence of inaccurate specification of cancer death appeared to be very small. Bias may result when considering multiple cancer primaries because religiously active LDS are less likely to smoke cigarettes. Hence, they are less likely to get a cancer related to smoking, where these cancers tend to be more lethal (e.g., lung and pancreatic cancers). There would have been a selection bias if we had considered death from any cancer. However, limiting disease-specific death to breast cancer made the groups more comparable with respect to smoking history.
It was not possible to explore the association between histological grade and survivability because of the large number of patients in the "unknown" category. Nevertheless, the difference in distribution of histological grade among patients with known grade information was very similar and not statistically different (χ2(4) = 1.71, p = .789). There is no reason to believe that the "unknown" grade would have been distributed differently among the religious groups.
Finally, specific data on breast cancer risk behaviors was not available on the patient level. However, information was available on whether or not a person had previously received their temple endowment. This measure was used as a surrogate for a host of lifestyle behaviors previously observed among religiously active LDS in Utah, such as higher parity and total time breast feeding and lower prevalence of alcohol consumption.
Conclusion
LDS lifestyle is associated with lower incidence of breast cancer. The age distribution among LDS breast cancer patients in this study strengthens the argument that higher parity, lifetime breast feeding, and lower alcohol consumption have a preventive effect against breast cancer. Non-LDS in Utah approximate LDS behavior to increase social acceptability, serendipitously contributing to a relatively low breast cancer incidence. LDS showed poorer survival from breast cancer than non-LDS in Utah. Parity and breastfeeding, associated with lower risk of breast cancer, may contribute to poorer prognosis once breast cancer is diagnosed.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
Ray M. Merrill conceptualized the study, analyzed the data, and drafted the manuscript. Jeffrey A. Folsom assisted in interpreting the data and writing the manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Figures and Tables
Figure 1 Malignant breast cancer incidence in white women in Utah and SEER (without Utah)
Figure 2 Age-specific malignant breast cancer incidence among white women in Utah according to LDS status, 1995–99
Figure 3 Hazard ratios (95% confidence intervals) of death from breast cancer for religiously less active LDS and non-LDS compared with religiously active LDS conditioned on having already survived x months
Table 1 Bivariate analyses of selected factors among breast cancer patients by LDS status and level of religiosity in Utah, 1985–99
Religiously Active LDS Religiously Less Active LDS Non-LDS χ2 P value
No. % No. % No. %
Age at Diagnosis
00–34 119 2.3 55 4.1 91 3.1
35–44 463 9.1 165 12.3 465 15.6
45–54 962 18.8 250 18.6 639 21.5
55–64 1167 22.9 312 23.2 674 22.6
65–74 1299 25.5 351 26.1 668 22.4 149.7
75+ 1093 21.4 211 15.7 441 14.8 <.0001
Marital Status at Diagnosis
Never Married 123 2.3 110 8.0 217 7.2
Married (cohabitating) 3044 58.2 626 45.7 1944 64.4
Previously Married 2067 39.5 633 46.2 810 26.9 414.9
Unknown 0 0.0 0 0.0 45 1.5 <.0001
Breast Cancer Primaries
Single 4742 90.6 1200 87.7 2735 90.7 11.8
First of Multiple 492 9.4 169 12.3 281 9.3 .0028
Summary Stage (Pathological)
Localized 3208 61.3 839 61.3 1859 61.6
Regional 1756 33.5 443 32.4 982 32.6
Distant 166 3.2 54 3.9 106 3.5 4.3
Unknown 104 2.0 33 2.4 69 2.3 .6340
Histological Grade
Low (well-differentiated) 576 11.0 152 11.1 336 11.1
Medium (moderately diff.) 1796 34.3 463 33.8 1076 35.7
High (poorly diff./undiff.) 1272 24.3 357 26.1 796 26.4 13.7
Unknown 1590 30.4 397 29.0 808 26.8 .0337
Radiation Therapy
No 3504 67.0 896 65.5 1961 65.0 3.5
Yes 1730 33.0 473 34.5 1055 35.0 .1736
Surgery
Conservative Management 1835 35.1 508 37.1 1144 37.9
Mastectomy 3368 64.3 856 62.5 1858 61.6 8.4
Other Surgery 31 0.6 5 0.4 14 0.5 .0775
Year of Diagnosis
1985–88 1139 21.8 306 22.4 693 23.0
1989–92 1282 24.5 374 27.3 732 24.3
1993–96 1525 29.1 371 27.1 855 28.3 7.8
1997–99 1288 24.6 318 23.2 736 24.4 .2498
==== Refs
Jemal A Tiwari RC Murray T Ghafoor A Samuels A Ward E Feuer EJ Thun MJ American Cancer Society Cancer statistics, 2004 CA Cancer J Clin 2004 54 8 29 14974761
Ferlay J Bray F Pisani P Parkin DM GLOBOCAN 2002: Cancer Incidence, Mortality and Prevalence Worldwide Version 20 2004 IARC CancerBase No. 5 Lyon: IARCPress
National Cancer Institute Ries LAG Eisner MP Kosary CL Hankey BF Miller BA Clegg L Mariotto A Feuer EJ Edwards BK (eds) SEER Cancer Statistics Review, 1975–2001 Section IV 2004 Bethesda MD
US Census Bureau: Utah Quick Facts
Merrill RM Thygerson AL Religious preference, church activity, and physical exercise Prev Med 2001 33 38 45 11482994 10.1006/pmed.2001.0851
Lyon JL Gardner K Gress RE Cancer incidence among Mormons and non-Mormons in Utah (United States) 1971–85 Cancer Causes Control 1994 5 149 156 8167262 10.1007/BF01830261
Daniels M Merrill RM Lyon JL Stanford JB White GL Jr Assocations between breast cancer risk factors and religious practices in Utah Prev Med 2004 38 28 38 14672639 10.1016/j.ypmed.2003.09.025
Madigan MP Ziegler RG Benichou J Bryne C Hoover RN Proportion of breast cancer cases in the United States explained by well-established risk factors J Natl Cancer Inst 1995 87 1681 1685 7473816
Ewertz M Duffy SW Adami HO Kvale G Lund E Meirik O Mellemgaard A Soini I Tulinius H Age at first birth, parity and risk of breast cancer: a meta-analysis of 8 studies from the Nordic Countries Int J Cancer 1990 46 597 603 2145231
Collaborative Group on Hormonal Factors in Breast Cancer Breast cancer and breastfeeding: collaborative reanalysis of individual data from 47 epidemiological studies in 30 countries, including 50,302 women with breast cancer and 96,973 women without the disease Lancet 2002 360 187 195 12133652 10.1016/S0140-6736(02)09454-0
Lipworth L Bailey LR Trichopoulos D History of breast-feeding in relation to breast cancer risk: a review of the epidemiologic literature J Natl Cancer Inst 2000 92 302 312 10675379 10.1093/jnci/92.4.302
Lash TL Aschengrau A Active and passive cigarette smoking and the occurrence of breast cancer Am J Epidemiol 1999 149 5 12 9883788
West DW Lyon JL Gardner JW Cancer risk factors: an analysis of Utah Mormons and non-Mormons J Natl Cancer Inst 1980 65 1083 1095 6933240
Korzeniowski S Dyba T Reproductive history and prognosis in patients with operable breast cancer Cancer 1994 74 1591 1594 8062190
Percy C Van Holten V Muir C (eds) International Classification of Diseases for Oncology 1990 2 Geneva: World Health Organization
Public Health Service International Classification of Diseases, (9th Revision), Clinical Modification 1989 3 Washington, DC [DHHS Pub. No. (PHS) 89–1260.]
World Health Organization International Statistical Classification of Diseases and Related Health Problems 10th Revision 1992 1–3 Geneva
Shambaugh EM Weiss MA Axtell LM Summary Staging Guide for the Cancer Surveillance, Epidemiology, and End Results (SEER) Program US Department of Health and Human Services Public Health Service National Institutes of Health NIH Publication No 81-2313 1981
Surveillance Program, Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health Ries L Fritz A (eds) The SEER Program Code Manual 1998 3 Bethesda, MD
North American Association of Central Cancer Registries Standards for Completeness, Quality, Analysis, and Management of Data 2000 Standards for Cancer Registries, Vol. III
Wajda A Roos LL Layefsky M Singleton JA Record linkage strategies: Part II. Portable software and deterministic matching Methods Inf Med 1991 30 210 214 1943794
Edmunds JK Q&A: Questions and Answers New Era 1974 17
Alexader TG Mormonism in transition: a history of the Latter-day Saints 1890–1930 1996 Urbana and Chicago: University of Illinois Press
Mineau GP Smith KR Bean LL Adult mortality risks and religious affiliation: the role of social milieu in biodemographic studies Annales de Demographie Historique
Keyfitz N Sampling variance of standardized mortality rates Hum Biol 1966 38 309 317 5977534
Cox DR Regression models and life tables (with discussion) J Royal Stat Soc, Ser B Metho 1972 34 187 220
Cox DR Oaks D Analysis of survival data: 21 1984 London: Chapman and Hall
Cialdini RB Goldstein NJ Social influence: compliance and conformity Annu Rev Psychol 2004 55 591 621 14744228 10.1146/annurev.psych.55.090902.142015
Tiedje LB Schiffman R Omar M Wright J Buzzitta C McCann A Metzger S An ecological approach to breastfeeding MCN Am J Matern Child Nurs 2002 27 154 161 12015443 10.1097/00005721-200205000-00005
Lolarga E How many children would you like to have? ICHM Newsl 1983 14 1 4
Piran P Effects of social interaction between Afghan refugees and Iranians on reproductive health attitudes Disasters 2004 28 283 293 15344942 10.1111/j.0361-3666.2004.00259.x
Ehrentheil OF The effects of various degrees of social pressure Ment Health Soc 1979 5 141 150 470601
Rosenberg L Thalib L Adami HO Hall P Childbirth and breast cancer prognosis Int J Cancer 2004 111 772 776 15252849 10.1002/ijc.20323
Whiteman MK Hillis SD Curtis KM McDonald JA Wingo PA Marchbanks PA Reproductive history and mortality after breast cancer diagnosis Obstet Gynecol 2004 104 146 154 15229014
Kroman N Mouridsen HT Prognostic influence of pregnancy before, around, and after diagnosis of breast cancer Breast 2003 12 516 521 14659129 10.1016/S0960-9776(03)00159-0
Kroman N Wohlfahrt J Andersen KW Mouridsen HT Westergaard T Melbye M Time since childbirth and prognosis in primary breast cancer: population based study BMJ 1997 315 851 855 9353505
DiFronzo LA O'Connell TX Breast cancer in pregnancy and lactation Surg Clin North Am 1996 76 267 278 8610263 10.1016/S0039-6109(05)70438-2
Lethaby AE O'Neill MA Mason BH Holdaway IM Harvey VJ Overall survival from breast cancer in women pregnant or lactating at or after diagnosis. Aukland Breast Cancer Study Group Int J Cancer 1996 67 751 755 8824544 10.1002/(SICI)1097-0215(19960917)67:6<751::AID-IJC1>3.0.CO;2-Q
Chang YT Loong CC Wang HC Jwo SC Lui WY Breast cancer and pregnancy Zhonghua Yi Xue Za Zhi (Taipei) 1994 54 223 229 7982132
Hoover HC Jr Breast cancer during pregnancy and lactation Surg Clin North Am 1990 70 1151 1163 2218825
Helewa M Levesque P Provoncher D Lea RH Rosolowich V Shapiro HM Breast Disease Committee and Executive Committee and Council, Society of Obstetricians and Gynaecologists of Canada Breast cancer, pregnancy, and breastfeeding J Obstet Gynaecol Can 2002 24 164 180 12196882
McNeilly AS Tay CC Glassier A Physiological mechanism underlying lactational amenorrhea Ann NY Acad Sci 1994 709 145 8154698
Ing R Ho JHC Petrakis NL Unilateral breastfeeding and breast cancer Lancet 1977 2 124 127 69205 10.1016/S0140-6736(77)90131-3
Kennedy KI Effects of breastfeeding on women's health Int J Gynecol Obstet 1994 S11 S21
Harris JR Lippman ME Veronesi U Willett W Medical progress: breast cancer N Eng J Med 1992 327 319 328
| 15904509 | PMC1173093 | CC BY | 2021-01-04 16:03:04 | no | BMC Cancer. 2005 May 18; 5:49 | utf-8 | BMC Cancer | 2,005 | 10.1186/1471-2407-5-49 | oa_comm |
==== Front
BMC CancerBMC Cancer1471-2407BioMed Central London 1471-2407-5-521591345610.1186/1471-2407-5-52Research ArticleColon cancer in Luxembourg: a national population-based data report, 1988–1998 Scheiden René [email protected] Paul [email protected] Yolande [email protected] Nelly [email protected] Catherine [email protected] Division of Anatomical Pathology, National Health Laboratory, Luxembourg2 Department of Gastroenterology, Clinique Sainte-Thérèse, Luxembourg3 Division of preventive medicine, National Health Direction, Luxembourg4 Morphologic Tumour Registry, Luxembourg2005 24 5 2005 5 52 52 10 12 2004 24 5 2005 Copyright © 2005 Scheiden et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Over the last two decades time trends in incidence rates of colorectal cancer, changes in the proportions of stage at diagnosis and changes in the anatomic sub-site distribution of colon cancers have been reported in some European countries. In order to determine a strategy for early detection of colon cancer in the Grand-Duchy of Luxembourg, all consecutive colon adenocarcinomas diagnosed during the period 1988–1998 at a nation-wide level were reviewed.
Methods
The population-based data of the national Morphologic Tumour Registry report all new high-grade adenomas (i.e. high-grade intraepithelial adenomatous neoplasias) and all consecutive new invasive adenocarcinomas of the colon diagnosed in the central department of pathology. Attention has been focused on variations in incidence, stage, anatomical site distribution and survival rates. Rectal cancers were excluded.
Results
Over the study period, 254 new colonic high-grade adenomas and 1379 new invasive adenocarcinomas were found; the crude incidence rates of colon adenocarcinomas grew steadily by 30%. Comparing the two 5-year periods 1988–1992 and 1994–1998, the crude incidence rates of high-grade adenomas (stage 0) rose by 190%, that of stage I cases by 14.3%, stage II cases 12.9% and stage III cases 38.5%, whereas the crude incidence rates of stage IV cases decreased by 11.8%. The high-grade adenoma/adenocarcinoma ratio increased. The right-sided colonic adenocarcinomas in elderly patients (>69 years) increased by 76%. The observed survival rates correlated with tumour stages. The overall observed 5-year survival rate (stage I-IV) was 51 ± 3% (95% confidence interval).
Conclusion
The increasing incidence rates of colon adenocarcinomas, the persistence of advanced tumour stages (stage III), the mortality rates which remain stable, and the changing trends in the age- and sub-site distribution underline the need for preventive measures at the age of 50 in asymptomatic patients to reduce mortality from colo(rectal) cancer.
==== Body
Background
Since 1994, colorectal adenocarcinoma has been the third most frequent cancer in the Grand-Duchy of Luxembourg (Western Europe), preceded by breast and prostatic cancer [1-3]. In the United States of America (USA), Japan and France, there have been changes in the site distribution of large bowel cancers over the last decades [4-9]. Because of the lack of a systematic, organized screening for colo-rectal cancer in Luxembourg, the data presented here may help to define new preventive screening approaches, to increase funding and hasten the introduction of screening for this tumour. The aim of this study was to investigate changes in incidence, stage, anatomical site distribution, and the observed survival rates of colon cancer over two 5-year periods, 1988–1992 and 1994–1998. Analogous to the report on rectal cancer published earlier [10], descriptive epidemiological data on colon cancer were collected to underline the need for the initiation of a nation-wide strategy for the early detection of colorectal cancer.
Methods
Between January 1st, 1988 and December 31, 1998, all consecutive new cases of high-grade adenoma and all new cases of invasive colonic adenocarcinoma (COAC) were registered by the national Morphologic Tumour Registry (MTR) in Luxembourg. These cases had been exclusively diagnosed and "double-read" in the central department of pathology by nine senior pathologists. Over the decade the population increased from 374,900 to 429,000, – an average increase of 1.3% per year. In the elderly age group >69 years of age, there was a continuous increase by 1.8% (0.5 – 4.4%) [11]. Patients of all nationalities, race or ethnical origin living in Luxembourg were considered. Disease histology was limited to high-grade adenomas (i.e. adenomas with severe dysplasia) and invasive adenocarcinomas of the colon. Tumours recorded as other carcinomas, metastatic or recurrent disease, metachronous adenomas or invasive adenocarcinomas, malignant carcinoid and mesenchymal malignant tumours were excluded from the current review. For patients with synchronous colon neoplasias, only cases with the worst stage category were taken in account.
Data on patients with high-grade adenomas (i.e. stage 0 patients), who by definition could not have metastases in regional lymph nodes or distant metastases, were obtained from 254 biopsy-forceps and polypectomy specimens removed by 26 gastroenterologists and 11 senior-surgeons. Adenomatous proliferations in marginal zones of invasive adenocarcinomas and adenomas with severe dysplasia appearing as recurrent invasive disease within 2 years at the same site were not taken into account.
Data on 1158 surgical resection specimens allowed an interpretation in relation to the local and regional spread, the lymph node and the residual tumour status. Hence the stratification of the invasive colonic adenocarcinomas by stage (stage I-IV) led to the exclusion of patients with biopsy diagnosis alone and patients who had only undergone polypectomy without segmental resection (i.e. without regional lymphadenectomy). Patients with known preoperative debulking radiotherapy were not considered. The surgical resection specimens were analysed with respect to tumour-stages (stage I to IV), according to the guidelines of the Union Internationale Contre le Cancer (UICC) and the American Joint Committee on Cancer (AJCC) [12-14]. We defined stage I and stage II as early cancers and stage III and stage IV as advanced colon cancers.
To evaluate the influence of the number of colonoscopic procedures on the incidence rates and the stage distribution of colonic cancers in Luxembourg, the data on colonoscopies (1992–1998), gratefully made available by the National Health Found (NHF), were analysed [15]. The R-classification according to the TNM-system was performed by conventional methods [16,17]. In our series the histological examination of the proximal, distal and lateral (deep) line of resection was mandatory. R0 indicates no residual tumour; R1 corresponds to microscopically and R2 to macroscopically residual tumour, while Rx did not allow a statement on residual tumour.
The histopathological diagnoses were made according to the WHO-classification [18]. On this basis, we defined 'high grade' – adenomas, the equivalent of stage 0 or former adenocarcinoma in situ, as adenomas of tubular, villous or tubulo-villous histological type with high-grade intraepithelial neoplasia (i.e. severe dysplasia). This category includes cancer cells confined within the glandular basement membrane (intraepithelial) or lamina propria (intramucosal) with no extension through the muscularis mucosae into the submucosa.
We considered all colon segments as large bowel, with the exception of the rectum and the recto-sigmoid junction. Anatomically the rectum was defined as a 16 cm long segment between the ano-cutaneous line and the sigmoid colon. Cancers described at the recto-sigmoidal junction without statement on the centimetres from the anal margin were considered as rectal adenocarcinomas and were excluded. Left-sided colon cancers were defined as adenocarcinomas of the descending colon and the sigmoid colon. Right-sided colon cancers included adenocarcinomas situated above the splenic flexure (i.e. splenic flexure, transverse colon, hepatic flexure, ascending colon and caecum with its prolongation, the appendix vermicularis).
Beside the evaluation of the frequency of invasive COCA by the 17 'classic' 5-year age categories (0–4 years to 80 years and above) the changes of anatomic sub-site distribution in relation to 3 age groups young (<40 years of age), middle aged (40–69 years) and elderly (70 years and above) patients were analyzed. The observed survival rates of patients with colon cancer were measured from the time of diagnosis and calculated by the actuarial method (life-table) with a 95% confidence interval (c.i.). To evaluate the observed survival rates in relation to the anatomical extent (stage I-IV) and the surgical resection margins (R-status), 164 patients with colon adenocarcinoma diagnosed only by biopsy-forceps without consecutive surgical resection data in our files, who were without final stage and who are part of the 1379 patients with an invasive COCA, were analysed separately.
The mortality rates of colon cancer were issued from the anonymous files of the death certificates published by the National Health Direction (Ministry of Health) [19]. The age-standardized incidence rates of the colon cancers diagnosed in the Grand-Duchy of Luxembourg during the period 1983–1997 were compared with the data of other geographical European regions with similar population density and socio-economic characteristics, published by the WHO in "Cancer in Five Continents, volumes VI, VII, VIII" [1-3,20-22].
The statistical evaluations include the chi-square test (χ2) with a level of significance p < 0.05 and the life-table survival analysis. The age-standardized incidence rates were calculated by the direct method, the standard error of the age-standardized rates by the Poisson approximation [23].
Results
The histopathological diagnoses of 1379 consecutive invasive colon adenocarcinomas (COAC) were provided from 164 samples obtained by biopsy only (11.9%), 57 polypectomy specimens (4.1%) and 1158 surgical resection specimens (84.0%). The latter allowed a stratification by stage (UICC/AJCC, 1997) and had reliable follow-up data. The 1379 invasive adenocarcinomas of the colon involved 658 males (47.7%) and 721 females (52.3%); M/F-ratio of 1: 1.1. The mean age was 69.7 years (range: 26–97). During the study period, 254 patients were diagnosed with high-grade adenomas. These patients constitute a separate group from the 1379 invasive COAC.
The average, annual, age-specific rates of colon AC in Luxembourg over the period 1988–1998 were 31.1 per 100,000 for all ages and both genders, for males 30.3 per 100,000 and for females 31.9 per 100,000 (Figure 1). The comparison of the crude incidence rates of patients with colon AC diagnosed in the 5-year periods 1988–1992 and 1994–1998 revealed an increase by 13.5% for both genders from 28.9 to 32.8, for females by 15.5% from 29.6 to 34.2 and for males by 11.3% from 28.2 to 31.4 per 100,000.
The average, annual, age-standardized incidence rates (ASR-world population) of colon cancer (period 1988–1998) were 17.5 per 100,000, for males 20.5 per 100,000 and for females 15.4 per 100,000. Table 1 documents the world age-standardized incidence rates (ASR/W) of the invasive COAC in the Luxembourgish population (females and males) over the period 1983–1997 in comparison to other European countries.
The time trend (1988–1998) of the frequency of invasive COAC showed that the total number of invasive COAC rose significantly from 109 cases in the year 1988 to 162 cases in 1998 (in females from 61 to 93, in males from 48 to 69). Comparing the two 5-year periods 1988–1992 and 1994–1998, there was a significant increase in the absolute number of all COAC from 557 to 687 cases (p < 0.001). The absolute number of COAC in males increased significantly from 266 to 323 cases (p < 0.02), and in females significantly from 291 to 364 cases (p < 0.01).
Figure 2 shows the age-distribution of all patients with histologically confirmed invasive colonic adenocarcinoma (n = 1379 cases). Of these patients 1.7% were <40 years of age; 3.8% between 40 and 49 years; 41.0% between 50 and 69 years; 31.5% between 70 and 79 years and 22.0% of the patients were 80 years and above.
Concerning the COAC stage distribution, two peculiarities appeared at the extremes of patient age scales. Below the age of 40, none of the patients (n = 23) had early stage cancer (i.e. stage I or stage II). On the other hand, out of the 303 patients aged 80 years and above, most had stage II (39.0 %) and stage III (38.2 %) disease, whereas stage I (10.6 %) and stage IV (8.3 %) were much less frequent.
Time trends in relation to the tumour-stages [TNM-System (UICC/AJCC] are represented in Figure 3. During the two 5-year periods 1988–1992 and 1994–1998, there was a highly significant increase (p < 0.001) in the crude incidence rates of the stage 0 cases (i.e. high-grade colonic adenomas) by 190%, an increase in stage I cases by 14.3%, in stage II cases by 12.9%, in stage III cases by 38.5%, and a decrease in stage IV cases by 11.8%.
The relation of the 254 new colonic high-grade adenomas to the 1379 new invasive adenocarcinomas stratified by years is shown in Figure 4. The comparison of the average of crude incidences of the high-grade adenomas to the invasive adenocarcinomas for the two 5-year periods indicates a highly significant improvement of the ratio by 148% in the second period. There were no significant changes in the number or crude incidences of colorectal endoscopies or colonoscopies with biopsy examinations.
The distribution of the 1244 new invasive colon adenocarcinomas by anatomical site and two 5-year periods (1988–1992: n = 557 cases and 1994–1998: n = 687 cases) are given in Figure 5. Twelve cases (1.0%), which were not otherwise specified, had to be excluded. In relation to three age groups (< 40 years of age, 40 – 69 years and >69 years) the anatomical sub-site distribution shows a shift to right-sided colon adenocarcinomas by 9.2% in the 40 to 69 years age group (n = 553) and by 76.2% in the group of patients of >70 years of age (n = 658). The number of the left-sided colon cancers decreased by 14.5% in the 40–69 years age group and increased by 22.9% in those >70 years. Patients with no precise site and those of the year 1993 were excluded for statistical (two 5-year periods) comparison reasons. In Table 2 the anatomical sub-site distribution in relation to the three age groups and their age-specific rates per 100,000 is represented.
The overall observed survival rates of the 1379 patients with an invasive COAC, diagnosed by biopsy or polypectomy or surgical resection specimen were calculated and stratified by years: 1-year: 72 ± 2% (n = 997/1379); 2-year: 60 ± 3% (833/1379); 3-year: 54 ± 3% (n = 740/1379); 4-year: 48 ± 3% (n = 662/1379) and 5-year 44 ± 3% (n = 604/1379).
In Table 3, the observed 5-year survival rates of 931 invasive COAC stratified by stage and operation for cure (R0), and those of 58 patients with COAC with microscopically (R1) or macroscopically (R2) residual tumour after surgical resection are represented. The analysis of the observed survival rates of the 164 patients with colon AC, diagnosed by biopsy-forceps only (i.e. without known final stage), revealed that 70 patients (42.7%) survived 12 months, whereas 20 (12.2%) died in the first month after diagnosis, 46 (28.1%) within the next 6 months and 28 (17.1%) in the period from 6 to 12 months. The age-distribution of these patients showed that 10 (6.1%) patients were <50 years, 105 (64.0%) were aged between 50 and 79 years and 49 (29.9%) were >80 years of age.
The mortality rates for colon cancer in the Grand-Duchy of Luxembourg over the last 15 years (1984–1998), grouped by 5-year periods, did not change significantly (Table 4) [19]. There was a slight, insignificant (p < 0.05) decrease in the crude death rates from 26.3 per 100,000 in the period 1984–1988 to 23.8 per 100,000 in the period 1989–1993 and 23.9 per 100,00 in 1994–1998 [19].
Discussion
In contrast to the USA and Canada, the age-standardized incidence rates of colon cancer in Luxembourg steadly increased from 1983–1997 for both genders (Table 1). Our findings are in concordance with those of many other European countries, where the increase occurs mainly in the male population [20-22,24]. Some authors believe that the decreasing incidence rates in the USA are due to preventive cancer screening [25]. We found 3.2% cases with synchronous colon adenocarcinomas, which is comparable to the 3.0% and 4.8% of synchronous cancers identified by authors in other countries [26,27].
The effect of age was examined in relation to the classic age groups and in relation to three cohorts of patients, (a) under 40 years of age, (b) between 40 and 69 years, and (c) 70 years and older. The number of colon cancers increases around the age of 45 (Figure 2). This is consistent with the findings of Imperiale et al., who found a low incidence of colon adenomas in the age groups 40 to 49 years [28]. Patients under 40 years of age had a higher incidence of advanced stage colon cancers. Similar observations were reported by Mostafa et al. [29].
Considering that high-grade adenomas are obligate precancerous lesions with a slow progression, that polypectomy can mean prevention of cancer, and that the high-grade adenoma/invasive adenocarcinoma ratio (Figure 4) improved in the late 1990's, we observed evidence of earlier diagnoses [30]. We consider the continous registration of high-grade adenomas and determination of the adenoma-adenocarcinoma ratio as a useful additional quality assurance marker in evaluating clinical and histopathological diagnostic procedures. To explain the unexpected increase of precancerous colonic lesions, we analysed our files in order to identify parameters that might have changed, such as staff composition or other factors. Over the period 1992–1995 the number of physicians (n = 38) practicing endoscopy did not change and the number of high-grade adenomas (n = 109 cases) removed by each endoscopist varied between one and six cases. Considering that, the number and the crude annual incidence rate of the colonoscopies did not rise significantly over the time, that the staff of pathologists remained the same, the histopathological criteria and coding did not change, and that a systematic organized screening programme until the year 2000 was not launched and a spontanous, unorganized screening is not known, we believe that a more selective indication for colonoscopy examinations may be one of the causes of this increase. The abrupt change after 1993 in the number of stage 0-cases may be the consequence of the changes in the statute of the National Health Fund. In 1992 the notions of patients and medical care providers 'profiling' at the national level were introduced. At the same time, the media campaign for preventive medical care strategies against cancer (breast, malignant melanoma) launched by the governmental institutions in collaboration with the NHF and the Luxembourg Foundation against Cancer may have had a beneficial (secondary) effect. Not only the incidence of stage 0-cases rose, but we found also a positive influence on the crude incidence rates of stage I and stage II patients increasing over the two 5-year period (1988–1992) and (1994–1998) by 14.3 and 12.9% respectively. Unfortunately there has been a highly significant (p < 0.001) increase in stage III patients by 38.5% too. Colon AC in young patients (40 years of age or less) seems to be more aggressive, since those patients were diagnosed exclusively in stage III and stage IV. Since these patients often present a positive family history of colorectal cancer, there is an obvious need for health-care providers to heighten awareness, and to identify high risk persons in this population group [25,31,32].
In North America, Japan, France and other high-risk areas, there has been a proximal shift in the sub-site distribution of colorectal cancer [4,29,32-34]. Similar changes have occurred in Luxembourg. This proximal shift was found in both sexes, especially in patients aged 70 and above. In males the increase was 14.0%, in females 73.6%. Mitry et al. [33] found that right colon cancer rates had increased by 21.6% in males and 10.4% in females. This underlines the need to discuss the opportunity for total colonoscopy in patients of higher risk or elderly age groups [30].
In our cohort, the overall 5-year survival rates of the patients with surgery for colon cancer without distinction of the residual tumour-status were 46 ± 3% (95% c.i.). Because the data on age-specific risk of death from other causes than colon cancer during the 1990's are not yet available, the relative survival rates could not be calculated. It must be admitted that relative survival rates will give better data for colon cancer in Luxembourg than indicated by the observed survival rates reported here. The relative 5-year survival rates reported in the literature vary between 30.6 and 55.3% [6,35].
Because COAC incidence increases at the age 50 approximately in our series, because a significant shift to right-sided colon cancer has been detected in patients of 70 years of age and above and because survival rates would probably improve if the disease is treated in its early stages, a strategy to perform twice-lifetime colonoscopy (at ages 50 and 60 years or at the transition to the pension age with 65 years) for asymptomatic patients without family history or other risk factors, as discussed by others, needs further investigations [4,29,34,36,37]
Conclusion
In contrast to the time trends in the USA and Canada, we found increasing age-standardized incidence rates in colonic adenocarcinomas and an increase of the crude incidence rates especially in stage III patients. Despite the 4-fold increase in high-grade adenoma diagnoses (i.e. stage 0 cases), efforts should be reinforced in preventive strategies to detect more precancerous lesions and/or early tumour-stages, to reduce the true incidence of advanced tumour-stages at diagnosis, and by this the mortality rates. The findings of this study should provide baseline information and scientific evidence for the elaboration and implementation of cancer preventive and intervention strategies to those populations at average and high-risk for colorectal cancers. As long as new diagnostic procedures, such as stool-based DNA-test for colorectal tumours, are not yet available for mass-screening purposes, and as long as the effectiveness of a complete colonoscopy screening for colorectal cancer in asymptomatic patients beginning at the age of 50 has not been proven by population-based controlled trials, the data underline the need of at least a systematic faecal occult blood test (FOBT) screening for colorectal cancer beginning at the age of 50 [30,38,39]. Our data support mainly that screening could be considered in preventing deaths from colo(rectal) cancer. The findings can be used by the national health care authorities to define a screening strategy and to help in deciding the target age-groups in Luxembourg.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
All authors (RS, PP, YW, NK, CC) collaborated intensely on all aspects of the manuscript, from research design to data preparation and presentation. RS wrote, and all authors approved the final manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
We thank Mrs Mireille Braun, Mrs Martine Becker and M. Guy Weber for their helpful assistance during the preparation of this manuscript.
The study received financial support from the national Morphologic Tumour Registry (RMT a.s.b.l.). The opinions stated in this document are those of the authors and do not necessarily represent the official position of the RMT.
Figures and Tables
Figure 1 Time trend of the crude incidence rates of the invasive colon adenocarcinomas (n = 1379) by gender; 1988–1998.
Figure 2 Age-distribution of the invasive colonic adenocarcinomas (n = 1379 cases); 1988–1998.
Figure 3 Crude incidence rates of the high-grade adenomas (n = 254) and the invasive adenocarcinomas of the colon (n = 1379) stratified by stage (TNM/UICC-AJCC, 1997) [14].
Figure 4 Crude incidence rates and colonic high-grade adenoma / invasive adenocarcinoma-ratio in comparison to colonoscopies: 1988–1998; both genders; n = 254*/1379 cases (*diagnoses by biopsy only included).
Figure 5 Number of invasive colonic adenocarcinomas (n = 1244; cases of the year 1993 excluded) by anatomic site; 1988–1992 and 1994–1998. (N.O.S.* = not otherwise specified)
Table 1 Colon cancer in the European Community: world age-standardizedincidence rates [ASR(W)*], time trends: 1983–1987; 1988–1992; 1993–1997.
Males 83–87 88–92 93–97 Females 83–87 88–92 93–97
F/Bas Rhin 27.2 30.2 31.3 ↑ D/Saarland 19.4 20.4 21.5 ↑
D/Saarland 23.7 25.5 27.3 ↑ NL/Maastricht 17.1 17.9 19.4 ↑
I/Parma 23.0 24.4 27.0 ↑ DK/Denmark 19.3 19.9 18.6 ↓
IRL/Southern 21.8 24.2 25.3 ↑ IRL/Southern 19.7 20.3 18.3 ↓
E/Navarra 13.8 19.2 22.1 ↑ I/Parma 16.1 17.8 17.9 ↑
NL/Maastricht 19.7 21.9 22.1 ↑ UK/South Western 15.9 16.2 17.3 ↑
UK/South Western 18.2 19.2 22.1 ↑ F/Bas Rhin 17.4 18.8 16.9 ↓
L/Luxembourg 15.5 20.2 21.9 ↑ L/Luxembourg 11.3 14.9 15.0 ↑
DK/Denmark 20.3 20.6 20.7 ↑ S/Sweden 15.8 15.9 15.0 ↓
CH/St.Gall 16.4 16.5 19.7 ↑ E/Navarra 9.6 13.0 12.4 ↑
S/Sweden 17.5 17.7 17.7 ↔ CH/St.Gall 11.7 12.0 12.1 ↑
SF/Finland 11.9 12.8 14.5 ↑ SF/Finland 10.6 11.6 12.1 ↑
CND/Canada 27.8 26.9 25.9 ↓ CND/Canada 23.6 21.3 20.0 ↓
USA/Seer**, white 31.1 28.1 25.5 ↓ USA/Seer**, white 23.6 20.8 19.4 ↓
* Cancer incidence in five continents. Vol VI; Vol VII; Vol VIII [20, 21, 22]
** SEER: Surveillance, Epidemiology and End Results Program
Table 2 Invasive colon adenocarcinomas (n = 1232*) by anatomic site (left and right colon), by age groups (<40 years; 40–69 years; >69 years) and age-specific incidence rates; 1988–1992 and 1994–1998.
Age groups Number of incident cases (ri) Person- years of obervation (ni) Age-specific rates per 100,000 (ri/ni) p-values **
<40 years
colon right 1988–1992 5 1 072 099 0.5 p = n.s.
colon right 1994–1998 9 1 151 878 0.8
colon left 1988–1992 2 1072 099 0.2 p = n.s.
colon left 1994–1998 5 1151 878 0.4
40–69 years
colon right 1988–1992 130 676 772 19.2 p = n.s.
colon right 1994–1998 142 742 577 19.1
colon left 1988–1992 150 676 772 22.2 p = n.s.
colon left 1994–1998 131 742 577 17.6
>69 years
colon right 1988–1992 122 175 629 69.5 p < 0.001
colon right 1994–1998 215 196 145 109.6
colon left 1988–1992 144 175 629 82.0 p = n.s.
colon left 1994–1998 177 196 145 90.2
* excluded colon cancers N.O.S.(n = 12) and those of 1993 (n = 135)
** level of significance p < 0.05; n.s. = not significant
Table 3 Prognoses of invasive colonic adenocarcinomas resected for cure (R0) or with residual tumour (R1+R2) and stratified by stage-TNM/UICC [12, 13, 14, 23].
Stage TNM Observed 5-year survival rates (actuarial method, 95% confidence interval)
UICC, 5th edition R0 R1+R2 p-values ***
I * T1 N0 M0
T2 N0 M0 71 +/- 8%
(n = 129) 100% **
(n = 1) <0.5188
II * T3 N0 M0
T4 N0 M0 63 +/- 5%
(n = 388) 45 +/- 30%
(n = 11) <0.2392
III * anyT N1 M0
anyT N2 M0 38 +/- 5%
(n = 331) 4% **
(n = 25) <0.0007
IV * anyT anyN M1 17 +/- 8%
(n = 83) 5% **
(n = 21) <0.1584
I-IV * 51 +/- 3%
(n = 931) 14 +/- 9%
(n = 58) <0.0001
* only surgical specimens with available survival data
** number of cases too low for calculating the 95% confidence interval
*** level of significance p < 0.05
Table 4 Analysis of the mortality rates from all colon adenocarcinomas of the last 15 years (1984–1998) declared in Luxembourg by death certificate only [19].
Males Females both genders p-values*
1984–1988: 26.5/105 26.2/105 26.3/105
p = n.s.
1989–1993: 22.5/105 25.0/105 23.8/105
p = n.s.
1994–1998: 23.6/105 24.3/105 23.9/105
* level of significance p < 0.05 ; n.s. = not significant for both genders
==== Refs
Capesius C Scheiden R Groff P Kanz R Schneider F Wehenkel Cl Nouveaux cas de cancer au Luxembourg – Monographies des années 1985 – 1987 – 1988 – 1989 – 1990 – 1991 – 1992 – 1993 1991 Luxembourg: Registre Morphologique des Tumeurs au Grand-Duché de Luxembourg
Capesius C Scheiden R Groff P Nouveaux cas de cancer au Luxembourg – Monographie de l'année 1986 1987 Luxembourg: Registre Morphologique des Tumeurs au Grand-Duché de Luxembourg
Capesius C Scheiden R Groff P Kanz R Juchem JP Wehenkel Cl Nouveaux cas de cancer au Luxembourg – Monographies des années 1983 – 1984 – 1994 – 1995 – 1996 – 1997 – 1998 1997 Luxembourg: Registre Morphologique des Tumeurs au Grand-Duché de Luxembourg
Cheng X Chen VW Steele B Ruiz B Fulton J Liu L Carozza SE Greenlee R Subsite-specific incidence rate and stage of disease in colorectal cancer by race, gender, and age group in the United States, 1992–1997 Cancer 2001 92 2547 54 11745188 10.1002/1097-0142(20011115)92:10<2547::AID-CNCR1606>3.0.CO;2-K
Anderson LD Remington P Trentham-Dietz A Reeves M Assessing a decade of progress in cancer control Oncologist 2002 7 200 4 12065791 10.1634/theoncologist.7-3-200
Faivre-Finn C Bouvier-Benhamiche AM Phelip JM Manfredi S Dancourt V Faivre j Colon cancer in France: evidence for improvement in mangement and survival Gut 2002 51 60 4 12077093 10.1136/gut.51.1.60
Iacopetta B Are there two sides to colorectal cancer? Int J Cancer 2002 101 403 8 12216066 10.1002/ijc.10635
Takada H Ohsawa T Iwamoto S Yoshida R Nakano M Imada S Yoshioka K Okuno M Masuya Y Hasegawa K Kamano H Hioki K Muto T Koyama Y Changing site distribution of colorectal cancer in Japan Dis Colon Rectum 2002 45 1249 54 12352244 10.1007/s10350-004-6400-0
Yiu HY Whittemore AS Shibata A Increasing colorectal cancer incidence rates in Japan Int J Cancer 2004 109 777 81 14999789 10.1002/ijc.20030
Scheiden R Sand J Weber J Turk Ph Wagener Y Capesius C Rectal cancer in Luxembourg: a national population-based data report, 1988–1998 BMC Cancer 2003 3 27 14567762 10.1186/1471-2407-3-27
STATEC Données démographiques 1988–1998 1999 Luxembourg: Service central de la statistique et des études économiques
Hermanek P Sobin LH TNM classification of malignant tumours, UICC, 4th ed., 2nd revision 1992 Berlin Heidelberg New York: Springer
Hermanek P Henson DE Hutter RVP Sobin LH UICC TNM supplement 1993. A commentary on uniform use 1993 Berlin Heidelberg New York: Springer
Sobin LH Wittekind CH TNM classification of malignant tumours, UICC, 5th ed 1997 New York, Chichester, Weinheim, Brisbane, Singapore, Toronto: Wiley-Liss
Kieffer R Juchem JP Feider J Nombre de rectoscopies et colonoscopies avec et sans biopsies, années 1992–1998 2000 Luxembourg: Union des Caisses de Maladie
Hermanek P Sobin LH Hermanek P, Gospodarowicz MK, Henson DE, Hutter RVP, Sobin LH Colorectal cancer Prognostic factors in cancer UICC 1995 Berlin Heidelberg New York: Springer
Hermanek P Wittekind CH Residual tumour (R) classification and prognosis Semin Surg Oncol 1994 10 12 20 8115781
Jass JR Sobin LH Histological typing of intestinal tumours. WHO - Intestinal Histological Classification of Tumours, 2nd ed 1989 Berlin Heidelberg New York Tokyo: Springer
Hansen-Koenig D Schanck JM Roulleaux M Statistiques des causes de décès, années 1984 – 1998 1985 Luxembourg: Direction de la Santé, Ministère de la Santé
Parkin DM Muir SL Whelan SL Gao YT Ferlay J Powell J Cancer Incidence in Five Continents 1992 VI Lyon: IARC Scientific Publications NR120
Parkin DM Whelan SL Ferlay J Raymond L Young J Cancer Incidence in Five Continents 1997 VII Lyon: IARC Scientific Publications NR143
Parkin DM Whelan SL Ferlay J Teppo L Thomas DB Cancer Incidence in Five Continents 2002 VIII Lyon: IARC Scientific Publications NR155
Boyle P Parkin DM Jensen OM, Parkin DM, Mac Lennan R, Muir CS, Skeet RG Statistical methods for registries Cancer registration, principles and methods 1991 Lyon: IARC 126 158
Malila N Hakulinen T Epidemiological trends of colorectal cancer in the Nordic countries Scand J Surg 2003 92 5 9 12705545
O'Connell JB Maggard MA Liu JH Etzioni DA Livingston EH Ko CY Rates of colon and rectal cancers are increasing in young aldults Am Surg 2003 69 866 72 14570365
Oya M Takahashi S Okuyaua T Yamaguchi M Ueda Y Synchronous colorectal carcinoma:clinico-pathological features and prognosis Jpn J Clin Oncol 2003 33 38 43 12604723 10.1093/jjco/hyg010
Keating J Pater P Lolohea S Wickremesekera K The epidemiology of colorectal cancer: what can we learn from the New Zealand Cancer Registry? N Z Med J 2003 116 U437 12766783
Imperiale TF Wagner DR Lin CY Larkin GN Rogge JD Ransohoff D Results of screening colonoscopy among persons 40 to 49 years of age N Engl J Med 2002 346 1781 5 12050337 10.1056/NEJM200206063462304
Mostafa G Matthews BD Norton HJ Kercher KW Sing RF Heniford BT Influence of demographics on colorectal cancer Am Surg 2004 70 259 64 15055851
Winawer S Fletcher R Rex D Bond J Burt R Ferrucci J Ganiats Th Levin Th Woolf St Johnson D Kirk L Litin S Simmang C Colorectal cancer screening and surveillance: clinical guidelines and rationale-Update based on new evidence Gastroenterology 2003 124 544 560 12557158 10.1053/gast.2003.50044
Keswani SG Boyle MJ Maxwell JP 4thMains L Wilks SM Hunt JP O'Leary JP Colorectal cancer in patients younger than 40 years of age Am Surg 2002 68 871 6 12412713
Kotake K Honjo S Sugihara K Kato T Kodaira S Takahashi T Yasutomi M Muto T Koyama Y Changes in colorectal cancer during a 20-year period: an extended report from the multi-institutional registry of large bowel cancer, Japan Dis Colon Rectum 2003 46 S32 43 14530656
Mitry E Benhamiche AM Couillault C Roy P Faivre-Finn C Clinard F Faivre J Effect of age, period of diagnosis and birth cohort on large bowel cancer incidence in a well-defined French population,1976–1995 Eur J Cancer Prev 2002 11 529 34 12457104 10.1097/00008469-200212000-00004
Jubelirer SJ Wells JB Emmett M Broce M Incidence of colorectal cancer in West Virginia from 1993–1999: an update by gender, age, subsite and stage W V Med J 2003 99 182 6 14959509
Vines JJ Ardanaz E Arrazola A Gaminde J Population-based epidemiology of colorectal cancer: causality review An Sist Sanit Navar 2003 26 79 97 12759713
Vijan S Hwang EW Hofer TP Hayward RA Which colon cancer screening test? A comparison of costs, effectiveness, and compliance Am J Med 2001 111 593 601 11755501 10.1016/S0002-9343(01)00977-9
Khan A Shrier J Gordon PH Do distal adenomas mandate total colonoscopy? Surg Endosc 2003 17 886 90 12658426 10.1007/s00464-002-8743-8
Muller O Identification of colon cancer patients by molecular diagnosis Dig Dis 2003 21 315 9 14752221 10.1159/000075354
Faivre J Benhamiche AM Tazi MA Sankila R, Démaret E, Hakama M, Lynge E, Schouten LJ, Parkin DM for the European Network of Cancer Registries Evaluation of screening for colorectal cancer Evaluation and Monitoring of Screening Programmes 2000 Brussels-Luxembourg: European Commission, Europe Against Cancer Programme 213 222
| 15913456 | PMC1173094 | CC BY | 2021-01-04 16:03:05 | no | BMC Cancer. 2005 May 24; 5:52 | utf-8 | BMC Cancer | 2,005 | 10.1186/1471-2407-5-52 | oa_comm |
==== Front
BMC CancerBMC Cancer1471-2407BioMed Central London 1471-2407-5-641598241610.1186/1471-2407-5-64Research ArticleWWOX protein expression varies among ovarian carcinoma histotypes and correlates with less favorable outcome Nunez María I [email protected] Daniel G [email protected] John H [email protected] Martín C [email protected] Hyunsuk [email protected] Robert [email protected] Andres JP [email protected] Andrew K [email protected] Jinsong [email protected] Gordon B [email protected] C Marcelo [email protected] Department of Carcinogenesis, The University of Texas M.D. Anderson Cancer Center, Science Park-Research Division, Smithville TX, USA2 Department of Pathology, The University of Texas M.D. Anderson Cancer Center at Houston, TX, USA3 Molecular Therapeutics, The University of Texas M.D. Anderson Cancer Center at Houston, TX, USA4 Department of Pathology, Fox Chase Cancer Center, Philadelphia, PA, USA5 Ovarian Cancer Program, Fox Chase Cancer Center, Philadelphia, PA, USA2005 27 6 2005 5 64 64 29 3 2005 27 6 2005 Copyright © 2005 Nunez et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
The putative tumor suppressor WWOX gene spans the common chromosomal fragile site 16D (FRA16D) at chromosome area 16q23.3-24.1. This region is a frequent target for loss of heterozygosity and chromosomal rearrangement in ovarian, breast, hepatocellular, prostate carcinomas and other neoplasias. The goal of these studies was to evaluate WWOX protein expression levels in ovarian carcinomas to determine if they correlated with clinico-pathological parameters, thus providing additional support for WWOX functioning as a tumor suppressor.
Methods
We performed WWOX protein expression analyses by means of immunobloting and immunohistochemistry on normal ovaries and specific human ovarian carcinoma Tissue Microarrays (n = 444). Univariate analysis of clinical-pathological parameters based on WWOX staining was determined by χ2 test with Yates' correction. The basic significance level was fixed at p < 0.05.
Results
Immunoblotting analysis from normal ovarian samples demonstrated consistently strong WWOX expression while 37% ovarian carcinomas showed reduced or undetectable WWOX protein expression levels. The immunohistochemistry of normal human ovarian tissue sections confirmed strong WWOX expression in ovarian surface epithelial cells and in epithelial inclusion cysts within the cortex. Out of 444 ovarian carcinoma samples analyzed 30% of tumors showed lack of or barely detectable WWOX expression. The remaining ovarian carcinomas (70%) stained moderately to strongly positive for this protein. The two histotypes showing significant loss of WWOX expression were of the Mucinous (70%) and Clear Cell (42%) types. Reduced WWOX expression demonstrated a significant association with clinical Stage IV (FIGO) (p = 0.007), negative Progesterone Receptor (PR) status (p = 0.008) and shorter overall survival (p = 0.03).
Conclusion
These data indicate that WWOX protein expression is highly variable among ovarian carcinoma histotypes. It was also observed that subsets of ovarian tumors demonstrated loss of WWOX expression and is potentially associated with patient outcome.
==== Body
Background
The WWOX gene, originally cloned by our laboratory, spans a genomic region greater than 1 Mb in size and is the second most common chromosomal fragile site, FRA16D (16q23) [1,2]. Abnormalities affecting WWOX at the genomic and expression level have been reported in numerous neoplasias and cancer derived cell lines including, breast, ovarian, esophageal, lung, stomach, liver, pancreas and hematological malignancies [3-12]. We observed that ectopic WWOX expression inhibited anchorage independent growth and in vivo tumorigenicity of highly aggressive breast carcinoma lines, suggesting a putative tumor suppressor role for this novel protein [13,2].
WWOX encodes a 46 KD, 414-amino acid protein that contains two WW domains at the NH2 terminus and a short chain oxidoreductase (SDR) central domain [1]. The first WW domain- is involved in protein-protein interactions by binding the specific proline rich motif PPXY and several potential candidate partner proteins have been postulated [14,15]. Within the SDR domain, the presence of WWOX amino acid residues, serine 281, and 293-YNRSK-297 make up a catalytic signature motif conserved in short-chain steroid dehydrogenases [16]. We originally reported high WWOX mRNA expression levels in ovary, prostate, testis and breast [1]. In this study we analyzed WWOX protein expression pattern in normal ovary and ovarian carcinomas. We correlated WWOX protein expression with ovarian carcinoma histotypes and clinico-pathological parameters. In addition, since we recently observed a strong association between loss of WWOX expression and estrogen and progesterone receptor (ER and PR) status in breast cancer [12], we also investigated any potential association between expression of sex steroid hormone receptors and WWOX in ovarian cancer.
Methods
Western blot analysis
Total protein extracts were prepared from snap frozen tissue of 38 human ovarian carcinomas and 5 normal human ovarian tissues. As negative control for WWOX protein expression we used protein extracts from the ovarian cell line PEO1 that does not express WWOX due to a homozygous deletion affecting exons 4–8 of this gene [4], a kind gift of Dr. Hani Gabra at Imperial College London, UK. As positive control we used the same cell line stably transfected with a WWOX expressing vector (PE01-WWOX) [10,12]. Total cell protein lysates were made using RIPA buffer (50 mM Tris pH7.5, 150 mM NaCl, 0.5% sodium deoxycholate, 1% Triton X-100, 0.1% SDS) containing protease inhibitor cocktail (Roche, Mannheim, Germany). For western blotting 50 ug of total protein was separated by 12.5% SDS-PAGE and transferred to PVDF membranes (Millipore, Billerica, MA). Immunodetection was performed using Protein Detector™ (KPL, Gaithersburg, MD) western blotting reagents as described by the manufacturer. WWOX protein was detected using affinity-purified anti-WWOX rabbit polyclonal primary antibodies developed in our laboratory (final concentration 280 ng/ml) [12] and HRP conjugated anti-rabbit secondary antibody (KPL, city, state, 1:2000 dilution) followed by chemiluminescence autoradiography. Actin was used as the protein loading control and it was detected using monoclonal anti-actin antibody (ICN biomedicals, Burlingame, CA, 1:1000 dilution) and HRP conjugated anti-mouse secondary antibody (KPL, 1:5000). Quantitation of X-ray films exposed to western blot chemiluminescence-emitting membranes was performed using a Kodak digital science Image Station 440CF. Protein loading and signal intensity was controlled by normalizing each sample to the aforementioned positive control, PE01-WWOX as previously described [10,12].
Ovarian tissue microarrays
The MD Anderson Cancer Center ovarian TMA was prepared by D.R. at the J.L laboratory [17] with samples from 441 patients with primary epithelial ovarian cancer that had undergone surgery at M. D. Anderson Cancer Center between 1990 and 2001. Follow-up information was updated through June 2003. Histopathologic diagnoses assigned at the time of treatment were based on World Health Organization criteria, each sample was reclassified by grade based on the Gynecologic Oncology Group (GOG) criteria [18] and each case was also classified by disease stage according to the International Federation of Gynecology and Obstetrics (FIGO) system [19]. The appropriate institutional committee approved use of human tissue blocks and clinical records reviews. Each core was scored individually and the results are reported as the mean of at least two replicate core sample measurements [20].
We also used a second ovarian TMA set generated at the Fox Chase Cancer Center (FCCC) tumor bank by R.P. at the A.J.P.K laboratory. This TMA set included a total of 86 ovarian tumors and 21 normal ovarian samples. Cores of normal ovaries were used as positive controls. Only primary mucinous carcinomas of the ovary where included on this cohort of patients. Selection criteria was based on histopathological diagnosis made by a trained pathologist on whole sections, histochemical stainings, immuhohistochemical staining, and clinical assessment of the patient. By pooling the TMA sets from both institutions we were able to successfully analyze in duplicate WWOX protein staining from a total of 444 invasive surface epithelial derived primary ovarian carcinomas that included Serous (n = 375), Endometroid (n = 40), Mucinous (n = 10) and Clear Cell Carcinoma (CCC) (n = 19) histological subtypes. A subset of these cases (n = 323) was successfully processed and analyzed for allowing comparative analysis of WWOX protein expression with ER and PR status.
Immunostaining method
Anti-WWOX immunostaining was performed as previously reported [12]. Mouse monoclonal antibodies for ER, NCL-ER-6F11 (Novocastra, UK) and PR, NCL-PGR-312 (Novocastra, UK) were used according to manufacturer recommendations. The anti-PR antibody used in these studies is able to recognize only the A isoform of this receptor [21].
Evaluation of immunohistochemical staining
Staining intensity was measured using a Chromavision Automated Cellular Imaging System (Chromavision® ACIS®, San Juan Capistrano, CA) as previously described [12].
The methods for scoring cytoplasmic or nuclear staining are based on different program functions of the ACIS® and are the recommended by the manufacture. For anti-WWOX staining measurements we employed the generic DAB software application provided by ACIS. The area of each individual TMA core was considered for the measurements in its totality. The software determines brown intensity (i.e. positive stained cells) regardless of the area covered by the positive cells. The cutoff to differentiate positive and negative staining was determined to be a mean intensity of 63 (arbitrary staining intensity units, s.i.u.) over a total of 255 (color saturation scale). Therefore, cores with values = 63 s.i.u were 'negative' for WWOX immunostaining, i.e. no brown staining observable. Values between 63 and = 65 s.i.u. were considered to be in the 'weak/low' staining category, i.e. barely visible brown staining, 65 to 81 s.i.u were considered 'moderate' and cores with staining intensity values > 81 s.i.u were considered to fall in the 'strong' staining category. For sake of simplicity cases were classified in two groups: a) negative + low = Negative-Low WWOX group, i.e. any core with a value = 65 in staining intensity and b) moderate + strong = High WWOX group, i.e. any core with values above 65 in staining intensity. The Negative/Low WWOX group was composed of 79% (105/133) completely negative cases and 21% (28/133) weak cases. The mean WWOX intensity staining for normal ovarian surface epithelium (OSE) fell in the moderate category (mean value 70 ± 4).
Anti-ER and PR antibodies
For performing anti-ER and anti-PR determinations we utilized the nuclear antigen software application provided by ACIS. Only areas of tumor in each TMA core were considered for measurements. The free form drawing tool provided by the software was used to select tumoral areas and to exclude other structures. A final score was determined by the percentage of brown stained nuclei (i.e. positive cells) over the total of tumor cell nuclei measured (i.e. positive plus negative cells). Only cores with at least 10% tumor were included in the analysis. For the receptor analyses, positivity of nuclear staining was defined as follows: weak > 5% stained nuclei, moderate 5–40% stained nuclei and strong >50% stained nuclei.
Statistical methods
Univariate analysis of clinical-pathological parameters based on WWOX staining was determined by χ2 test with Yates' correction. The basic significance level was fixed at p < 0.05 and all data was analyzed using SPSS statistical software (Version 11.0; SPSS Inc., Chicago, IL).
Results
Western blot analysis
Immunoblotting analysis demonstrated that full length WWOX protein was the predominant WWOX isoform expressed in both normal ovary and ovarian carcinomas (Figure 1B). The anti-WWOX antibody used was raised against the WW domains [2] and should detect all potential WWOX isoforms. The specificity of this WWOX antibody in the immunoblotting analyses was demonstrated by observing no immunoreactive products in cell extracts from the PEO1 ovarian carcinoma cell line used as negative control (Figure 1A). In addition, as a positive control PEO1 cells were stably transfected with a WWOX expression vector (Figure 1A).
Normal ovarian tissues displayed a consistently strong WWOX specific signal while WWOX protein expression levels were extremely variable among tumor samples. Some tumors displayed barely detectable, if any, WWOX protein when compared to normal tissue, e.g. T108 while other samples had significantly higher WWOX levels e.g. T578 in Figure 1. We concluded that 26% (10/38) of tumors over-expressed WWOX, 34% (13/38) expressed normal WWOX levels and 40% (15/38) of tumors had levels lower than 50% that observed in normal ovary.
Pattern of WWOX staining in normal ovary
Initially we characterized the cellular localization of WWOX protein expression in normal ovaries by IHC using the antibody described in the previous section. The specificity of the WWOX antibody for IHC analysis was validated by observing that the immunoreactivity was abolished by pre-absortion to the recombinant GST-WWOX fusion protein used to raise the antibody (data not shown).
The analysis of TMA cores and whole sections of normal human ovary showed that WWOX protein is constitutively expressed at high levels in normal OSE cells (Figure 2A), in epithelial inclusion cysts within the cortex (Figure 2B) and in scattered granulosa-lutein cells surrounding aged corpora lutea or corpora albicans (not shown). Positive staining was also detected in one observed Walthard nest within the ovarian hilus and in a few stromal cell patches likely related with hormone production. In all cases the inmunostaining had a homogeneous and diffuse pattern that was localized to the cytoplasm.
WWOX staining in ovarian carcinomas
WWOX expression was highly variable among ovarian tumors (n = 444). WWOX staining intensity was determined in all four major surface epithelium derived ovarian carcinoma histotypes, i.e. Serous, Endometroid, Mucinous and Clear Cell (Table 1).
Thirty percent of ovarian carcinomas (133/444) showed loss of WWOX protein expression while 70% (311/444) demonstrated positive staining including cases with very strong staining (Figure 3A–I) (Table 1). Among serous carcinomas, 29% of the cases (109/375) fell in the negative/low group and 71% (266/375) stained moderately or strongly positive. The most typical WWOX staining pattern observed for all histotypes was cytoplasmic and diffuse, no tissues demonstrated any nuclear staining. Interestingly, some of the carcinomas showed a distinctive strong cell membrane staining pattern (Figure 3). Other tumors displayed a predominantly apical border staining, in conjunction with staining of what appeared to be luminal secretions (Figure 3B). Among endometroid carcinomas 23% of the cases (9/40) were negative/low and 77% (31/40) stained moderately or strongly positive for WWOX expression. This histological subtype showed a diffuse and apical cytoplasmic pattern of protein expression (Figure 3D, E). Among the CCC group, 42% of the cases (8/19) were negative/weak while 58% (11/19) stained moderately or strongly for WWOX (Figure 3G–I).
Within the mucinous carcinoma group, we observed that most tumors (7 out of 10 cases) did not stain for WWOX expression. Furthermore the three positive mucinous carcinomas were clearly below the mean value for normal OSE. The immunoreactivity localized to the cytoplasm as in the other histotypes but in a very specific perinuclear fashion (Figure 3J). The high rate of absence of WWOX protein expression among the mucinous carcinoma group was statistically different compared to the other three histotypes (p = 0.0131, Table 1).
WWOX staining analysis according to stage and grade
WWOX expression was next correlated with tumor Stages (FIGO). We observed that 23% of Stage I (7/31), 29% of Stage II (8/28), 31% of Stage III (74/242) and 48% of Stage IV (31/65) tumors showed negative/low WWOX protein expression. We detected a statistically significant trend between the decrease in WWOX expression and more advanced FIGO stages (-b = -0.135; p trend= 0.007, Table 2). No correlation was found between tumor grade (GOG) and WWOX staining (p = 0.707, Table 2).
WWOX staining analysis according to relapse and survival
An analysis of WWOX protein expression relative to disease relapse was performed in a subset of cases from the MDACC TMA (n = 354). Between relapsing and non-relapsing cases no statistical difference was observed regarding WWOX expression (p = 0.094) (Table 2). Among cases with progressive disease, 46% (27/59) showed negative/low WWOX levels of expression while 54% (32/59) fell in the positive category. It was possible to evaluate survival in cases from the MDACC group as shown by the Kaplan-Meier plot (Figure 4). Importantly, we observed a statistically significant correlation of WWOX expressing cases with longer overall survival and loss of WWOX protein expression correlated with shorter overall survival (p = 0.03).
WWOX staining analysis in correlation with ER and PR status
We analyzed the association of WWOX with ERα and PR status in ovarian carcinoma cases (n = 323). When ER status was correlated with WWOX expression levels no significant differences were found (Table 2). On the other hand, a statistically significant correlation was observed between WWOX expression and PR expression (p = 0.008, Table 2). In the WWOX negative cases 85% (70/82) were PR negative while only 15% (12/83) were PR positive.
Discussion
Since our original cloning of WWOX [1] abundant evidence has accumulated indicating that this gene likely plays a role in either tumor initiation or progression in various neoplasias including ovarian cancer [3-12]. WWOX spans the second most common chromosomal fragile site, FRA16D. This genomic region is prone to chromosome breakage, recombination and gross rearrangements. Multiple ovarian carcinoma studies have demonstrated high frequency of allelic losses for specific chromosomal regions on 16q [22] and since the losses have been found both in low and high-grade tumors it has been proposed to be an early event in ovarian carcinoma development [23]. Loss of heterozygosity at 16q23.2-q24.2 has been correlated with ovarian carcinoma metastasis and advanced tumor stages [24]. Comparative Genomic Hybridization (CGH) studies confirmed those observations also indicating high frequency of 16q21-q24 genomic losses in advanced invasive ovarian carcinoma stages [25,26]. Taken together the data indicates that a gene, likely WWOX, located at 16q23-24 is associated with a worse prognosis in ovarian cancer.
In this study WWOX protein expression in normal ovary was predominantly observed in the OSE and epithelial inclusions, both sites proposed to be where ovarian epithelial neoplastic transformation originates. Because of this finding together with the observations of Paige (2001) [4], that ovarian carcinoma cell lines have high frequency of genomic losses affecting the WWOX gene including homozygous deletions, we considered it of relevance to analyze WWOX protein expression among the four major surface epithelial derived ovarian carcinoma histotypes. Our analysis by immunoblotting and IHC demonstrated that about one third of ovarian carcinomas displayed extremely reduced or absent WWOX protein expression.
It is worth noting that in all instances, normal and tumor, WWOX staining was exclusively cytoplasmic and in some serous carcinomas staining was also localized to the apical cell membrane or luminal border. This is similar to our observations in breast tumors [12], where WWOX was always cytoplasmic without nuclear staining. This is also in agreement with observations from other groups [11]. This is in stark contrast with Watanabe (2003) [27] who observed that some cells of normal and tumor breast and gastric cases had WWOX protein expression localized to the nuclei. Possibly this discrepancy is due to the use of different antibodies.
In this ovarian cancer study, we also observed that Serous and Endometroid histotypes express normal or high WWOX but two rare but well described ovarian carcinoma histotypes, mucinous and clear cell (28,29,30), demonstrated a higher frequency of loss of WWOX protein expression. This association was more significant for the mucinous type, for which we observed that 70% (7/10) of cases were devoid of WWOX protein expression. Eventhough a small number of mucinous cases were studied the overall high frequency of decreased or loss of WWOX in these tumors as a group is intriguing. Borderline significance was found for the pure CCC for which 42% of cases demonstrated no or very low WWOX protein expression (Figure 3H versus 3G).
Primary mucinous ovarian tumors have been shown to carry a higher frequency of K-ras mutations as one of the few genetic hallmarks able to distinguish it from other histotypes, while CCC are characterized by a lack of p53 mutations. Mucinous carcinomas and CCC, has been associated with a higher frequency of resistance to chemotherapy (31). Interestingly, in our study, we observed a statistically significant trend between loss of WWOX expression and worse patient outcome. Patients whose tumors expressed WWOX at moderate or high levels fared better than those with low expression of this enzyme (Figure 4). We also found a statistically significant correlation with loss of WWOX and stage IV at initial diagnosis (FIGO). The association with overall survival could be due to an increased frequency of loss in higher stage tumors that are associated with a poorer outcome or alternatively due, in part, to an increased frequency of clear cell and mucinous tumors which have a lower likehood of responding to therapy [31]. It was also of interest that we observed a positive correlation between WWOX and PR expression. In contrast to our previous observations in breast cancer in which we observed a strong correlation between ER and PR with WWOX expression [12], in this ovarian study, only PR was associated with WWOX expression (Table 2). Specifically PR negative ovarian carcinomas also lacked WWOX expression. Progestins acting through the PR have been postulated to be protective for ovarian carcinoma development [32,33] due to a postulated ability of inhibiting cell proliferation and inducing apoptosis (34,35). We noticed that all (100%) of our analyzed mucinous carcinomas were PR negative which agrees with the literature regarding absence of PR expression in mucinous tumors [36,37] while 90% of CCC were PR negative. These correlations raise the question of whether the observed positive association between PR loss and WWOX loss is a consequence of the predominance of WWOX loss in the two aforementioned histotypes, rather than a direct mechanistic association between WWOX and PR. Changes in progesterone signaling and regulation of progesterone-responsive genes can be of critical significance in the ovarian tumorigenic process by itself [38]. The opposite could be true as well i.e. that high levels of WWOX expression is associated with PR expression and as a consequence related to the putative protective effect of progestins that in turn could be associated with more favorable patient outcomes.
Conclusion
We provide evidence that WWOX protein expression is frequently altered and highly variable in ovarian carcinomas. The loss of WWOX expression shows association with Mucinous and CCC histotypes more than the others and also shows a tendency with PR negative expression. Significantly, reduced WWOX protein expression correlates with less favorable outcome.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
CMA conceived, coordinated, designed the study, interpreted the data and revised the manuscript. MIN coordinated, performed pathological and immunohistochemical study, interpreted the data, drafted and write the report.DR constructed M.D. Anderson Cancer Center Tissue Microarray and interpreted the data. JHLM participated in preparation of the antibody, Western Blot analyses, interpretation of the data and critically reviewed the manuscript. MCA performed statistical analysis, figures and tables and interpreted the data. HK carried out Western Blot analyses. RP constructed Fox Chase Cancer Center Tissue Microarray. AJPKS, AG, JL and GM provided tumor samples, interpretation of the data and critically reviewed the manuscript. All of the authors have read and approved the final manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
The authors gratefully acknowledge Nancy W Abbey for her outstanding technical assistance. The authors acknowledge NCI RO1 CA102444 (C. M. Aldaz), SPORE in Ovarian Cancer P50 CA83639, tissue pathology core grant NCI PO1 CA64602 and ACS RSG-04-028-CCE (J. Liu), and center grant ES-07784.
Figures and Tables
Figure 1 WWOX protein expression in normal ovary and ovarian adenocarcinomas as determined by immunoblot analysis. A) Total protein extracts from PEO1 cell lines transfected with an empty vector or a WWOX expressing vector were analyzed by immunobloting with the anti-WWOX antibody. Note: no immunoreactive bands are observed in the vector transfected cell line. B) WWOX protein expression was determined by immunoblotting of total protein extracts from 38 ovarian carcinoma samples. Five normal ovarian tissue extracts are shown on the first five lanes. Quantitation of WWOX protein expression. Autoradiographs of WWOX and actin were digitized using the Kodak digital science Image Station 440CF. WWOX expression in each sample was normalizated to actin to correct for loading differences. In turn these numbers obtained from each tumor were normalized and expressed as relative to the normal ovarian values (i.e. Relative Expression).
Figure 2 WWOX immunohistochemical staining of normal ovary. A) Representative photomicrograph (20X) of normal ovary displaying positive staining in ovarian surface epithelial cells. B) Photomicrograph (20X) showing strong WWOX inmunostaining localizing to the cytoplasm of inclusion cyst epithelial cells.
Figure 3 WWOX inmunohistochemical staining in ovarian carcinoma samples by histotypes. A-C. Serous ovarian carcinomas. A, Strong-Moderate. Note heterogeneity in staining intensity pattern in this tumor sample; B, Moderate. Note predominance of apical staining in this papillary serous ovarian carcinoma; C Weak-Negative, WWOX lack of staining observed in approximately 30% of serous carcinoma cases. D-F. Endometroid ovarian carcinomas. D and E positive WWOX cytoplasmic staining and F negative staining. G-I. Clear Cell ovarian Carcinomas. G, representative photomicrograph of one of a moderately WWOX positive CCC case, while H and I, represent typical negative cases. J-L. Mucinous ovarian carcinomas, J, representative mildly positive case and K representative mucinous carcinoma of the endocervicoid subtype with demonstrating no WWOX staining. L, mucinous carcinoma of the intestinal subtype also negative for WWOX staining.
Figure 4 Kaplan Meier Plot analysis showing the pattern of Overall Survival relative to WWOX protein expression.
Table 1 WWOX intensity staining according to the four major epithelial derived ovarian carcinoma histotypes.
Histology
WWOX intensity
Total
Low (Negative/Weak)
High (Moderate/Strong)
Serous carcinoma 109/375 (29%) 266/375 (71%) 375
Endometroid carcinoma 9/40 (23%) 31/40 (77%) 40
Clear cell carcinoma 8/19 (42%) 11/19 (58%) 19
Mucinous carcinoma * 7/10 (70%) 3/10 (30%) 10
Total 133/444 (30%) 311/444 (70%) 444
* (χ2 = 8.67; p = 0.0131)
Table 2 Clinical parameters and steroid receptor status analyzed in correlation with WWOX staining.
Clinical parameters
WWOX intensity
Total
p value
Low (Negative/Weak)
High (Moderate/Strong)
Grade (GOG)
1 4 (23%) 13 (77%) 17 p = 0.707
2 9 (33%) 18 (67%) 27
3 107 (33%) 215 (67%) 322
Stage (FIGO)
I 7 (23%) 24 (77%) 31 p = 0.007
II 8 (29%) 20 (71%) 28
III 74 (31%) 168 (69%) 242
IV 31(48%) 34 (52%) 65
Relapse
No 31(32%) 66 (68%) 97 p = 0.09
Yes 61(31%) 137(69%) 198
Progressive disease 27(46%) 32 (54%) 59
ER
Negative 22 (25%) 66 (75%) 88 p = 0.984
Positive 59 (25%) 176 (75%) 235
PR
Negative 70 (29%) 170 (71%) 240 p = 0.00
Positive 12 (14%) 71 (86%) 83
==== Refs
Bednarek AK Laflin KJ Daniel RL Liao Q Hawkins KA Aldaz CM WWOX, a novel WW domain-containing protein mapping to human chromosome 16q23.3-24.1, a region frequently affected in breast cancer Cancer Res 2000 60 2140 2145 10786676
Ludes-Meyers JH Bednarek AK Popescu NC Bedford M Aldaz CM WWOX, the common chromosomal fragile site, FRA16D, cancer gene Cytogenet Genome Res 2003 100 101 110 14526170 10.1159/000072844
Krummel KA Roberts LR Kawakami M Glover TW Smith DI The characterization of the common fragile site FRA16D and its involvement in multiple myeloma translocations Genomics 2000 69 37 46 11013073 10.1006/geno.2000.6321
Paige AJ Taylor KJ Taylor C Hillier SG Farrington S Scott D Porteous DJ Smyth JF Gabra H and Watson JE WWOX: a candidate tumor suppressor gene involved in multiple tumor types Proc Natl Acad Sci U S A 2001 98 11417 11422 11572989 10.1073/pnas.191175898
Kuroki T Trapasso F Shiraishi T Alder H Mimori K Mori M Croce CM Genetic alterations of the tumor suppressor gene WWOX in esophageal squamous cell carcinoma Cancer Res 2002 62 2258 2260 11956080
Ishii H Vecchione A Furukawa Y Sutheesophon K Han SY Druck T Kuroki T Trapasso F Nishimura M Saito Y Ozawa K Croce CM Huebner K Expression of FRA16D/WWOX and FRA3B/FHIT genes in hematopoietic malignancies Mol Cancer Res 2003 1 940 947 14638866
Yendamuri S Kuroki T Trapasso F Henry AC Dumon KR Huebner K Williams NN Kaiser LR and Croce CM WW Domain containing oxidoreductase gene expression is altered in non-small cell lung cancer Cancer Res 2003 63 878 881 12591741
Aqeilan RI Kuroki T Pekarsky Albagha O Trapasso F Baffa R Huebner K Edmonds P Croce CM Loss of WWOX expression in gastric carcinoma Clin Can Res 2004 10 3053 3058
Kuroki T Yendamuri S Trapasso F Matsuyama A Aqueilan RI Alder H rattan S Cesari R Nolli ML Williams NN Mori M Kanematsu T and Croce CM The tumor suppressor gene WWOX at FRA 16D is involved in pancreatic carcinogenesis Clin Can Res 2004 10 2459 2465
Park SW Ludes-Meyers J Zimonjic DB Durkin ME Popescu NC Aldaz CM Frequent downregulation and loss of WWOX gene expression in human hepatocellular carcinoma Br J Cancer 2004 91 753 9 15266310
Guler G Ulner A Guler N Han S lliopoulos D Hauck WW McCue P Huebner K The fragile genes FHIT and WWOX are inactivated coordinately in invasive breast carcinoma Cancer 2004 100 1605 1614 15073846 10.1002/cncr.20137
Nunez MI Ludes-Meyers J Abba MC Kil H Abbey NW Page RE Sahin A Klein-Szanto A Aldaz CM Frequent loss of WWOX expression in breast cancer: correlation with estrogen receptor status Breast Cancer Res Treat 2005 89 99 105 15692750 10.1007/s10549-004-1474-x
Bednarek AK Keck-Waggoner CL Daniel RL Laflin KJ Bergsagel PL Kiguchi K Brenner AJ Aldaz CM WWOX, the FRA16D Gene, Behaves as a Suppressor of Tumor Growth Cancer Res 2001 61 8068 8073 11719429
Ludes-Meyers JH Kil H Bednarek AK Drake J Bedford MT Aldaz CM WWOX binds the specific proline-rich ligand PPXY: identification of candidate interacting proteins Oncogene 2004 23 5049 55 15064722 10.1038/sj.onc.1207680
Aqeilan RI Pekarsky Y Herrero JJ Palamarchuk A Letofsky J Druck T Trapasso F Han SY Melino G Huebner K Croce CM Functional association between Wwox tumor suppressor protein and p73, a p53 homolog Proc Natl Acad Sci U S A 2004 101 4401 6 15070730 10.1073/pnas.0400805101
Duax WL and Ghosh D Structure and function of steroid dehydrogenases involved in hypertension, fertility, and cancer Steroids 1997 62 95 100 9029722 10.1016/S0039-128X(96)00166-3
Rosen DG Huang X Deavers MT Malpica A Silva EG Liu J Validation of tissue microarray technology in ovarian carcinoma Mod Pathol 2004 17 790 7 15073602 10.1038/modpathol.3800120
Benda JA Zaino R Benda JA, Zaino R Histologic classification of tumors of the ovary Gynecologic Oncology Group Pathology Manual 1994 Buffalo, NY: Gynecologic Oncology Group
Staging announcement: FIGO cancer committee Gynecol Oncol 1986 25 383 5 10.1016/0090-8258(86)90092-2
Kononen J Bubendorf L Kallioniemi A Barlund M Schraml P Leighton S Torhorst J Mihatsch MJ Sauter G Kallioniemi OP . Tissue microarrays for high-throughput molecular profiling of tumor specimens Nat Med 1998 4 844 847 9662379 10.1038/nm0798-844
Mote PA Johnston Manninen T Tuohimaa P Clarke CL J Clin Pathol 2001 54 624 630 11477119 10.1136/jcp.54.8.624
Hansen LL Jensen LL Dimitrakakis C Michalas S Gilbert F Barber HR Overgaard J Arzimanoglou II Allelic imbalance in selected chromosomal regions in ovarian cancer Cancer Genet Cytogenet 2002 139 1 8 12547149 10.1016/S0165-4608(02)00620-9
Hauptmann S Denkert C Koch I Petersen S Schluns K Reles A Dietel M Petersen I Genetic alterations in epithelial ovarian tumors analyzed by comparative genomic hybridization Hum Pathol 2002 33 632 41 12152163 10.1053/hupa.2002.124913
Launonen V Mannermaa A Stenback F Kosma VM Puistola U Huusko P Anttila M Bloigu R Saarikoski S Kauppila A Winqvist R Loss of heterozygosity at chromosomes 3, 6, 8, 11, 16, and 17 in ovarian cancer: correlation to clinicopathological variables Cancer Genet Cytogenet 2000 122 49 54 11104033 10.1016/S0165-4608(00)00279-X
Patael-Karasik Y Daniely M Gotlieb WH Ben-Baruch G Schiby J Barakai G Goldman B Aviram A Friedman E Comparative genomic hybridization in inherited and sporadic ovarian tumors in Israel Cancer Genet Cytogenet 2000 121 26 32 10958937 10.1016/S0165-4608(00)00224-7
Suzuki S Moore DH 2nd Ginzinger DG Godfrey TE Barclay J Powell B Pinkel D Zaloudek C Lu K Mills G Berchuck A Gray JW An approach to analysis of large-scale correlations between genome changes and clinical endpoints in ovarian cancer Cancer Res 2000 60 5382 5 11034075
Watanabe A Hippo Y Taniguchi H Iwanari H Yashiro M Hirakawa K Kodama T Aburatani H An opposing view on WWOX protein function as a tumor suppressor CancerRes 2003 63 8629 8633
Scully RE Young RH Clement PB Tumors of the Ovary, maldeveloped gonads, fallopian tube and broad ligament Atlas of Tumor Pathology, 3rd series, fascicle 23 1998 Washington DC: Armed Forces Institute of Pathology
Rodriguez IM Prat J Mucinous Tumors of the Ovary Am J Surg Pathol 2002 26 139 152 11812936 10.1097/00000478-200202000-00001
Seidman JD Kurman RJ Ronnett BM Primary and metastatic mucinous carcinomas in the ovaries: Incidence In routine practice with a new approach to improve intraoperative diagnosis Am J Surg Pathol 2003 27 985 93 12826891 10.1097/00000478-200307000-00014
Sugiyama T Kamura T Kigawa J Terakawa N Kikuchi Y Kita T Suzuki M Sato I Taguchi K Clinical characteristics of clear cell carcinoma of the ovary: a distinct histologic type with poor prognosis and resistance to platinum-based chemotherapy Cancer 2000 88 2584 9 10861437 10.1002/1097-0142(20000601)88:11<2584::AID-CNCR22>3.0.CO;2-5
Risch HA Hormonal etiology of epithelial ovarian cancer, with a hypothesis concerning the role of androgens and progesterone J Natl Cancer Inst 1998 90 1774 86 9839517 10.1093/jnci/90.23.1774
Lau KM Mok SC Ho SM Expression of human estrogen receptor-alpha and -beta, progesterone receptor, and androgen receptor mRNA in normal and malignant ovarian epithelial cells Proc Natl Acad Sci U S A 1999 96 5722 7 10318951 10.1073/pnas.96.10.5722
Langdon SP Gabra H Bartlett JM Rabiaz GJ Hawkins RA Tesdale AL Ritchie AA Miller WR Smyth JF Functionality of the progesterone receptor in ovarian cancer and its regulation by estrogen Clin Cancer Res 1998 4 2245 51 9748145
Munstedt K Steen J Knauf AG Buch T von Georgi R Franke FE Steroid hormone receptors and long term survival in invasive ovarian cancer Cancer 2000 89 1783 91 11042574 10.1002/1097-0142(20001015)89:8<1783::AID-CNCR19>3.0.CO;2-D
Ford LC Berek JS Lagasse LD Hacker NF Heins Y Esmailian F Leuchter RS DeLange RJ Estrogen and progesterone receptors in ovarian neoplasms Gynecol Oncol 1983 15 299 304 6862289 10.1016/0090-8258(83)90047-1
Lindgren PR Cajander S Backstrom T Gustafsson JA Makela S Olofsson JI Estrogen and progesterone receptors in ovarian epithelial tumors Mol Cell Endocrinol 2004 221 97 104 15223136 10.1016/j.mce.2004.02.020
Lee P Rosen DG Zhu CC Silva EG Liu J Progesterone receptor expression as an independent prognostic marker in ovarian cancer revealed by tissue microarray Gynecol Oncol 2005 96 671 7 15721410 10.1016/j.ygyno.2004.11.010
| 15982416 | PMC1173095 | CC BY | 2021-01-04 16:03:03 | no | BMC Cancer. 2005 Jun 27; 5:64 | utf-8 | BMC Cancer | 2,005 | 10.1186/1471-2407-5-64 | oa_comm |
==== Front
BMC Cardiovasc DisordBMC Cardiovascular Disorders1471-2261BioMed Central London 1471-2261-5-121593263910.1186/1471-2261-5-12Research ArticleA systematic review of intravenous gamma globulin for therapy of acute myocarditis Robinson Joan L [email protected] Lisa [email protected] Ellen [email protected] Ben [email protected] Terry P [email protected] Department of Pediatrics, Stollery Children's Hospital and University of Alberta, Edmonton, Alberta, Canada2 Alberta Research Centre for Child Health Evidence, Department of Pediatrics, University of Alberta, Edmonton, Alberta, Canada2005 2 6 2005 5 12 12 4 6 2004 2 6 2005 Copyright © 2005 Robinson et al; licensee BioMed Central Ltd.2005Robinson et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Intravenous gamma globulin (IVGG) is commonly used in the management of acute myocarditis. The objective of this study was to systematically review the literature evaluating this practice.
Methods
We conducted a comprehensive search (electronic databases, trials registries, conference proceedings, reference lists, contact with authors) to identify studies evaluating the use of IVGG in adults and children with a clinical or histologically proven diagnosis of myocarditis of possible viral etiology and symptoms of less than six months duration. Two reviewers independently screened the searches, applied inclusion criteria, and graded the evidence.
Results
Results were described qualitatively; data were not pooled because only one randomized controlled trial (RCT) with 62 patients was identified. The RCT showed no benefit with respect to cardiac function, functional outcome, or event-free survival. A small, uncontrolled trial (n = 10) showed significant improvement in LVEF from a mean of 24% to 41% 12 months after IVGG in nine survivors. A retrospective cohort study of pediatric patients showed improvement in cardiac function and a trend towards improved survival in patients receiving IVGG (n = 21) versus historic controls (n = 25). Ten case reports and two case series (total n = 21) described improvement in cardiac function after administration of IVGG; two case reports showed no benefit of IVGG. One case of hemolytic anemia was attributed to IVGG.
Conclusion
There is insufficient data from methodologically strong studies to recommend routine use of IVGG for acute myocarditis. Future randomized studies that take into account the etiology of acute myocarditis will be required to determine the efficacy of IVGG.
==== Body
Background
Myocarditis is an inflammatory cardiomyopathy that occurs in all age groups [1]. Most cases are thought to be sub-clinical, but myocarditis can manifest as fulminant or chronic heart failure [2]. The inflammation is presumed to most commonly start as an infectious process, although autoimmune and idiopathic forms also occur [1]. Bacterial or protozoal myocarditis is rare in the developed world, with the vast majority of cases being viral [3]. Although most viruses that are pathogenic for humans can cause myocarditis, common etiologic agents are enteroviruses and adenoviruses [4]. It remains unclear if the primary problem in severe disease is ongoing damage from a virus, a post-infectious inflammatory reaction, or a combination of both factors. If ongoing infection is the primary problem, IVGG could be efficacious if it contains antibodies to the microbe. IVGG also has anti-inflammatory properties that prevent the formation of and downregulate cytokines [5] so could be efficacious even if the primary problem is a post-infectious inflammatory reaction.
The objective of this study was to review the evidence evaluating the use of IVGG in the treatment of patients with acute myocarditis. A secondary objective was to determine if there is an identifiable group of acute myocarditis patients (based on age, duration of symptoms, acuity of onset of symptoms, cardiac function at presentation, virologic results, or the presence or absence of histologic evidence of acute myocarditis on cardiac biopsy in patients where a biopsy was performed) who would benefit from IVGG. The review of randomized controlled trials has been registered with the Cochrane Collaboration and regular updates will be available in the Cochrane Library.
Methods
Searching
We systematically searched the following electronic databases: Cochrane Central Register of Controlled Trials (4th quarter, 2004), MEDLINE (1966 to January Week 4, 2005), EMBASE (1988 to Week 6, 2005), CINAHL (1982 to January Week 3, 2005), Web of Science (1975 to February 5, 2005), and several trial registries in addition to the Cochrane Heart Group's Trial Registry [6-11]. A comprehensive search strategy was developed by a medical research librarian based on the following terms: immunoglobulin, gammaglobulin, ivig, immunoglobulin, igg, immune, serum, myocarditis, cardiomyopathy, myocardiopathy, carditis, heart, inflammation. The complete search strategy is available from the authors on request. We also contacted the primary author of the RCT, and reviewed the reference lists of all selected articles. In addition, we handsearched proceedings from the following meetings for RCTs: American Heart Association (1999–2004), American College of Cardiology (1998–2005), European Society of Cardiology (1998–2004), and International Heart and Lung Transplantation Society (1998–2004). The search was not limited by language or publication status.
Study selection
Two reviewers independently screened the searches for potentially relevant studies. The full manuscript of all potentially relevant studies was retrieved and each study was assessed independently by two reviewers for inclusion using predetermined eligibility criteria. Primary studies of any design were eligible for inclusion. Inclusion criteria included reports of patients given IVGG for possible viral myocarditis within six months of onset of symptoms. Because of the poor sensitivity of cardiac biopsy as a diagnostic tool for acute myocarditis, a histologic diagnosis was not required. Exclusion criteria included reports of patients with evidence of ischemic heart disease, rheumatic heart disease, or any other non-viral etiology, onset of myocarditis less than six months postpartum (as the pathogenesis of postpartum myocarditis may differ from that of presumed viral myocarditis), or receipt of immunosuppressive therapy (unless this was not possible as they were reported as part of a case series). Reports of use of high-dose immunoglobulin directed at specific organisms were excluded as efficacy may be influenced by the formulation available and the accuracy of the etiologic diagnosis.
Assessment of methodological quality
Study quality was assessed independently by two reviewers and discrepancies were resolved by consensus. RCTs were evaluated using the previously validated Jadad 5-point score to assess randomization, double blinding, and losses to follow-up [12]. Allocation concealment was assessed as adequate, inadequate, or unclear [13]. Non-RCTs were graded according to the levels of evidence presented in Table 1.
Table 1 Levels of evidence for studies of therapeutic interventions from the Oxford Centre for Evidence-based Medicine (website title ) [14]
Level Study design
1 A Systematic review (with homogeneity) of randomized controlled trials
B Individual randomized controlled trial (with narrow confidence interval)
C All or none
2 A Systematic review (with homogeneity) of cohort studies
B Individual cohort study (including low quality randomized controlled trial, e.g., < 80% follow-up)
C "Outcomes" research; ecological studies
3 A Systematic review (with homogeneity) of case-control studies
B Individual case-control study
4 Case series (and poor quality cohort and case-control studies)
5 Expert opinion without explicit critical appraisal, or based on physiology, bench research or "first principles"
Data extraction
Data were extracted by one reviewer using a standard form and checked for accuracy and completeness by a second. The primary outcome was rate of survival without a transplant or requirement for placement of a left ventricular assist device. Secondary outcomes included change in echocardiographic measures of cardiac function, duration of hospitalization, and improvement in functional symptoms (determined by increased exercise tolerance as measured by any objective test and New York Heart Association Functional Capacity) when available. Data were collected on complications and adverse events.
Data analysis
Data from studies that were not RCTs were reported but not analyzed further. We planned to combine data from RCTs, to do sub-group analyses, and to test for publication bias, however these were not possible as only one RCT was identified. For the RCT, dichotomous data on efficacy (e.g. event-free survival) were expressed as an odds ratio (OR) with 95% confidence interval. Dichotomous data on adverse events were reported as a risk difference and number needed to harm with 95% confidence intervals. Continuous data (change in left ventricular ejection fraction and peak oxygen consumption) were converted to the mean difference with 95% confidence intervals. For peak oxygen consumption, we assumed a correlation of 0.5 and used the methods of Follmann [15] to calculate the standard deviations of the change from baseline estimates. Since the number per group was not given for this variable, an estimate of the sample size in each group had to be estimated by pro-rating the original group sample sizes to the new total sample size.
Results
Figure 1 presents a flow diagram of studies considered for inclusion in the review. Only one RCT evaluating IVGG for acute myocarditis has been reported to date [16]. The trial was of moderate methodological quality according to the Jadad scale (3 out of maximum 5 points, where 5 indicates highest quality); allocation concealment was unclear. The study enrolled 62 adults (mean age 43.0 +/- 12.3 years; 37 men), of which only ten had cellular inflammation on endomyocardial biopsy (four fulfilled the Dallas criteria for acute myocarditis, and three for borderline myocarditis). The authors reported that the given sample size would provide 80% power to detect a difference between groups of ≥ 8% in ejection fraction (EF) change scores. Patients were randomized to receive either 2 g/kg IVGG or an equivalent volume of 0.1% albumin in a blinded fashion. The incidence of death or requirement for cardiac transplant or placement of a left ventricular assist device was low in both groups. Event-free survival was not significantly different but favored the control group (OR 0.52, 95% CI 0.12, 2.30). Follow-up at 6 and 12 months showed no significant difference in improvement in left ventricular ejection fraction for cases and controls (mean difference 0.00, 95% CI -0.07, 0.07 at six months; 0.01, 95% CI -0.06, 0.08 at 12 months). Functional capacity as assessed by peak oxygen consumption was not significantly different in the two groups at 12 months (mean difference -0.80, 95% CI -4.57, 2.97). Infusion-related side effects occurred significantly more often in the treated group (RD 0.33, 95% CI 0.17, 0.50; number needed to harm = 3, 95% CI 2, 6), but all appeared to be mild.
Figure 1 Flow diagram of studies considered for inclusion in the review
Sixteen additional studies of various designs met the inclusion criteria [see Additional file 1]. These included a retrospective case series [17], an uncontrolled trial [18], two case series [5,19], and twelve case reports [20-31]. In a retrospective cohort study, Drucker compared children who were treated with IVGG (n = 21) to historic controls (n = 26); 65% of the sample was less than two years of age [17]. The treatment group showed improved cardiac function and a trend (though not statistically significant) towards improved survival. McNamara conducted an uncontrolled trial involving 10 adults (mean age 35.8 +/- 15 years) [18]. One patient with refractory arrhythmias and severe heart failure died during the infusion; the other nine patients showed an impressive improvement in cardiac function following administration of IVGG, with a significant increase in left ventricular ejection fraction at 12-month follow-up (p = 0.008). In ten case reports and both case series, improvement in cardiac function was described after use of IVGG in a total of 21 cases, although improvement was considered to be minimal in one case [26]. In the other two case reports, there was no benefit of IVGG in a patient presenting with hand, foot and mouth disease and acute myocarditis from coxsackievirus A16 [27] and in a patient with fulminant myocarditis of unclear etiology [28]. Hemolytic anemia was attributed to use of IVGG in one case report [26].
We could find no ongoing trials of the use of IVGG in acute myocarditis, although the European Study of Epidemiology and Treatment of Cardiac Inflammatory Diseases (ESETCID) is evaluating hyperimmunoglobulin for patients with cytomegalovirus-positive myocarditis [32].
Discussion
The small number of studies evaluating IVGG in the treatment of acute myocarditis reflects the immature state of this body of literature. We identified only one RCT (Level 1 evidence), which involved 62 adult patients with idiopathic cardiomyopathy (of which only 10 had histologic evidence of myocarditis) and showed no apparent benefit [9]. This is in contrast to an uncontrolled trial and numerous observational studies (Level 4 evidence), most of which suggested potential benefit. This indicates a possible bias towards publication of case reports or case series with positive results. The validity of evidence was generally poor, with the majority of included studies ranking low in terms of level of evidence. The most important threat to validity for fifteen of the seventeen included studies was the lack of controls, which could result in an overestimate of the benefit of IVGG. Spontaneous improvement in cardiac function is common with acute myocarditis and can be rapid or gradual, so it is possible that the improvement noted in these cases was part of the natural history of the disease. The retrospective cohort study demonstrated a greater improvement in cardiac function in patients given IVGG compared to historic controls [17]; this type of study is more susceptible to bias because of the inability to fully control for all potential confounders, such as other changes in patient management over the eight-year study period.
Acute myocarditis is a relatively non-specific entity, as the diagnosis is often clinical. Laboratory confirmation consists of microbiologic, histologic, and immunohistochemical methods. With regard to microbiologic confirmation, it is rare to isolate the etiologic agent from a myocardial biopsy (probably because the biopsy is usually done too late in the course of the illness), and identification of organisms by molecular techniques is in its infancy [4]. However, with the development of new effective antivirals, there should be increased efforts towards making a virologic diagnosis early in the course of myocarditis as it is possible that antivirals would improve the prognosis. Furthermore, there are case reports of hyperimmunoglobulin showing an apparent effect in cases of varicella [33], cytomegalovirus [34], and parvovirus [35] myocarditis. With regard to histologic confirmation, the Dallas criteria (lymphocyte infiltration with myocyte necrosis) [36] and more recently the World Heart Federation criteria (>14 leukocytes/mm2 with necrosis or degeneration) [37] have been used for histologic diagnosis, but the sensitivity and specificity of these criteria are not known. There are no standardized values for immunohistochemical markers [38]. Our aim in this study was to analyze reports of use of IVGG for presumed viral myocarditis, but it is possible that many of the patients in the reports did not have viral myocarditis (only 10 of the 62 patients in the RTC had cellular inflammation on endomyocardial biopsy). Once our ability to accurately diagnose viral myocarditis improves, it may be possible to identify a subset of patients who will respond to IVGG. This might be patients whose disease was precipitated by a specific virus, or patients who are treated with IVGG early in the course of their illness when they have ongoing viral replication in the myocardium. Perhaps pediatric patients are more likely to respond. Children are thought to be more likely to present in the acute inflammatory stage of illness [16], and may have a worse prognosis than do adults when they present with fulminant myocarditis [39,40]
In conclusion, the value of IVGG in patients with acute myocarditis is obscured by the poor quality of evidence. We were not able to identify a subgroup of patients who appear to be more likely to respond to IVGG. A large RCT is required to evaluate the efficacy of IVGG for acute myocarditis with emphasis on the etiology of the myocarditis. Until there are RCTs demonstrating benefit, use of IVGG for acute myocarditis should not be part of routine practice. Moreover, there is a great need for further studies of the pathophysiology of acute myocarditis, which would allow for a better understanding of the etiology and the natural history of the disease. This might allow for improved diagnostic criteria, which would make it much easier to design studies of treatment options. This may also assist in identifying sub-groups of patients where IVGG or other therapies have a greater potential to confer clinical benefit.
List of abbreviations
IVGG – intravenous gamma globulin
RCT – Randomized controlled trial
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
The idea for the study originated with JLR. The protocol was written by LH with help from JLR and EC. The literature review was completed by EC, and LH and JLR reviewed the papers and derived the data. Statistical analysis was done by BV. The manuscript was written by JLR and LH with input from TPK, EC and BV.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Supplementary Material
Additional File 1
Observational studies and nonrandomized trials examining the use of IVGG in acute myocarditis. This table summarizes all studies reporting the use of IVGG for acute myocarditis.
Click here for file
Acknowledgements
We thank Philip Berry and Marilyn Josefsson, from the Alberta Research Centre for Child Health Evidence, for administrative support and collection of articles.
==== Refs
Richardson P McKenna W Bristow M Maisch B Mautner B O'Connell J Olsen E Thiene G Goodwin J Gyarfas I Martin I Nordet P Report of the 1995 World Health Organization/International Society and Federation of Cardiology Task Force on the Definition and Classification of Cardiomyopathies Circulation 1996 93 841 2 8598070
Levi D Alejoes J Diagnosis and treatment of pediatric viral myocarditis Curr Opin Cardiol 2001 16 77 83 11224637 10.1097/00001573-200103000-00001
Towbin JA Myocarditis and pericarditis in adolescents Adolesc Med 2001 12 47 67 11224022
Martin AB Webber S Fricker FJ Jaffe R Demmler G Kearney D Zhang YH Bodurtha J Gelb B Ni J Acute myocarditis. Rapid diagnosis by PCR in children Circulation 1994 90 330 9 8026015
Kishimoto C Shioji K Kinoshita M Iwase T Tamaki S Fujii M Murashige A Maruhashi H Takeda S Nonogi H Hashimoto T Treatment of acute inflammatory cardiomyopathy with intravenous immunoglobulin ameliorates left ventricular function associated with suppression of inflammatory cytokines and decreased oxidative stress Intern J Cardiol 2003 91 173 8 10.1016/S0167-5273(03)00002-0
Pubmed
Curren Controlled Trials
The National Research Register
Center Watch Clinical Trials Listing Site
Cardiosource
New England Research Institutes Pediatric Cardiomyopathy Registry
Jadad AR Moore RA Carroll D Jenkinson C Reynolds DJ Gavaghan DJ McQuay HJ Assessing the quality of reports of randomized controlled trials: is blinding necessary? Control Clin Trials 1996 17 1 12 8721797 10.1016/0197-2456(95)00134-4
Schulz KF Chalmers I Hayes RJ Altman DG Empirical evidence of bias. Dimensions of methodological quality associated with estimates of treatment effects in controlled trials JAMA 1995 273 403 412 10.1001/jama.273.5.408
Centre for Evidence-Based Medicine
Follmann D Elliott P Suh I Cutler J Variance imputation for overviews of clinical trials with continuous variables J Clin Epidemiol 1992 45 769 73 1619456 10.1016/0895-4356(92)90054-Q
McNamara DM Holubkov R Starling RC Dec GW Loh E Torre-Amione G Gass A Janosko K Tokarczyk T Kessler P Mann DL Feldman AM Controlled trial of intravenous immune globulin in recent-onset dilated cardiomyopathy Circulation 2001 103 2254 9 11342473
Drucker NA Colan SD Lewis AB Beiser AS Wessel DL Takahashi M Baker AL Perez-Atayde AR Newburger JW Gamma-globulin treatment of acute myocarditis in the pediatric population Circulation 1994 89 252 7 8281654
McNamara DM Rosenblum WD Janosko KM Trost MK Villaneuva FS Demetris AJ Murali S Feldman AM Intravenous immune globulin in the therapy of myocarditis and acute cardiomyopathy Circulation 1997 95 2476 8 9184576
Wang CY Li Lu F Wu MH Lee CY Huang LM Fatal coxsackievirus A16 infection Pediatr Infect Dis J 2004 23 275 6 15014311
Takeda Y Yasuda S Miyazaki S Daikoku S Nakatani S Nonogi H High-dose immunoglobulin G therapy for fulminant myocarditis Jap Circ J 1998 62 871 2 9856608 10.1253/jcj.62.871
Nigro G Bastianon V Colloridi V Ventriglia F Gallo P D'Amati G Koch WC Adler SP Human parvovirus B19 infection in infancy associated with acute and chronic lymphocytic myocarditis and high cytokine levels: report of 3 cases and review Clin Infect Dis 2000 31 65 9 10913398 10.1086/313929
Tsai YG Ou TY Wang CC Tsai MC Yuh YS Hwang B Intravenous gamma-globulin therapy in myocarditis complicated with complete heart block: report of one case Acta Paediatr Taiwan 2001 42 311 3 11729711
Shioji K Matsuura Y Iwase T Kitaguchi S Nakamura H Yodoi J Hashimoto T Kawai C Kishimoto C Successful immunoglobulin treatment for fulminant myocarditis and serial analysis of serum thiredoxin – a case report Circulation Journal 2002 66 977 80 12381097 10.1253/circj.66.977
Tedeschi A Airaghi L Giannini S Ciceri L Massari FM High-dose intravenous immunoglobulin in the treatment of acute myocarditis. A case report and review of the literature J Intern Med 2002 251 169 73 11905592 10.1046/j.1365-2796.2002.00929.x
Stouffer GA Sheahan RG Lenihan DJ Patel P Lenihan DJ The current status of immune modulating therapy for myocarditis: a case of acute parvovirus myocarditis treated with intravenous immunoglobulin Am J Med Sci 326 369 74 14671501
Karaaslan S Oran B Caliskan U Baysal T Baspinar O Tas A Hemolysis after administration of high-dose immunoglobulin in a patient with myocarditis Turk J Haematol 2003 20 237 40
Khan MA Das B Lohe A Sharma J Neonatal myocarditis presenting as an apparent life threatening event Clin Pediatr (Phila) 2003 42 649 52 14552526
Kim HS Sohn S Park JY Seo JW Fulminant myocarditis successfully treated with high-dose immunoglobulin Int J Cardiol 2004 96 485 6 15301907 10.1016/j.ijcard.2003.05.037
Braun JP Schneider M Dohmen P Dopfmer U Successful treatment of dilative cardiomyopathy in a 12-year-old girl using the calcium sensitizer levosimendan after weaning from mechanical biventricular assist support J Cardiothorac Vasc Anest 2004 18 772 4 10.1053/j.jvca.2004.08.020
Abe S Okura Y Hoyano M Kazama R Watanabe S Ozawa T Saigawa T Hayashi M Yoshida T Tachikawa H Kashimura T Suzuki K Nagahashi M Watanabe J Shimada K Hasegawa G Kato K Hanawa H Kodama M Aizawa Y Plasma concentrations of cytokines and neurohumoral factors in a case of fulminant myocarditis successfully treated with intravenous immunoglobulin and percutaneous cardiopulmonary support Circ J 2004 68 1223 6 15564712 10.1253/circj.68.1223
English RF Janosly JE Ettedgui JA Webber SA Outcomes for children with acute myocarditis Cardiol Young 2004 14 488 93 15680069 10.1017/S1047951104005049
Maisch B Hufnagel G Schonian U Hengstenberg C The European Study of Epidemiology and Treatment of Cardiac Inflammatory Diseases (ESETCID) Eur Heart J 1995 16 173 5 8682090
Alter P Grimm W Maisch B Varicella myocarditis in an adult Heart 2001 85 e2 11119480 10.1136/heart.85.1.e2
Maisch B Pankuweit S Funck R Koelsch S Effective CMV hyperimmunoglobulin treatment in CMV myocarditis – a controlled treatment trial (Abstract #674) Proceedings of the European Society of Cardiology Annual Meeting: 28 Aug – 1 Sept 2004; Munich
Pankuweit S Lamparter S Funck R Maisch B Endomyocardial biopsy-guided diagnosis and treatment of inflammatory cardiomyopathies Dtsch Med Wochenschr 2004 129 2169 72 15457396 10.1055/s-2004-831860
Aretz HT Myocarditis: the Dallas criteria Human Pathol 1987 18 619 24 3297992
Maisch B Ristic AD Hufnagel G Funck R Alter P Tontsch D Pankuweit S Dilated cardiomyopathies as a cause of congestive heart failure Herz 2002 27 113 34 12025458 10.1007/s00059-002-2373-8
Wojnicz R Nowalany-Kozielska E Wojciechowska C Glanowska G Wilczewski P Niklewski T Zembala M Polonski L Rozek MM Wodniecki J Randomized, placebo-controlled study for immunosuppressive treatment of inflammatory dilated cardiomyopathy. Two-year follow-up results Circulation 2001 104 39 45 11435335
McCarthy RE 3rdBoehmer JP Hruban RH Hutchins GM Kasper EK Hare JM Baughman KL Long-term outcome of fulminant myocarditis as compared with acute (non-fulminant) myocarditis New Engl J Med 2000 342 690 5 10706898 10.1056/NEJM200003093421003
Mounts AW Amr S Jamshidi R Groves C Dwyer D Guarner J Dawson JE Oberste MS Parashar U Spevak P Alexander J A cluster of fulminant myocarditis cases in children, Baltimore, Maryland, 1997 Pediatr Cardiol 2001 22 34 9 11123124 10.1007/s002460010148
| 15932639 | PMC1173096 | CC BY | 2021-01-04 16:30:07 | no | BMC Cardiovasc Disord. 2005 Jun 2; 5:12 | utf-8 | BMC Cardiovasc Disord | 2,005 | 10.1186/1471-2261-5-12 | oa_comm |
==== Front
BMC Cardiovasc DisordBMC Cardiovascular Disorders1471-2261BioMed Central London 1471-2261-5-161597209510.1186/1471-2261-5-16Research ArticleDeterminants of racial/ethnic differences in blood pressure management among hypertensive patients Hicks LeRoi S [email protected] Shimon [email protected] David W [email protected] John Z [email protected] Division of General Internal Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA2 Department of Health Care Policy, Harvard Medical School, Boston, MA, USA3 Brigham and Women's-Faulkner Hospitalist Program, Brigham and Women's Hospital, Boston, MA, USA2005 22 6 2005 5 16 16 10 2 2005 22 6 2005 Copyright © 2005 Hicks et al; licensee BioMed Central Ltd.2005Hicks et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Prior literature has shown that racial/ethnic minorities with hypertension may receive less aggressive treatment for their high blood pressure. However, to date there are few data available regarding the confounders of racial/ethnic disparities in the intensity of hypertension treatment.
Methods
We reviewed the medical records of 1,205 patients who had a minimum of two hypertension-related outpatient visits to 12 general internal medicine clinics during 7/1/01-6/30/02. Using logistic regression, we determined the odds of having therapy intensified by patient race/ethnicity after adjustment for clinical characteristics.
Results
Blacks (81.9%) and Whites (80.3%) were more likely than Latinos (71.5%) to have therapy intensified (P = 0.03). After adjustment for racial differences in the number of outpatient visits and presence of diabetes, there were no racial differences in rates of intensification.
Conclusion
We found that racial/ethnic differences in therapy intensification were largely accounted for by differences in frequency of clinic visits and in the prevalence of diabetes. Given the higher rates of diabetes and hypertension related mortality among Hispanics in the U.S., future interventions to reduce disparities in cardiovascular outcomes should increase physician awareness of the need to intensify drug therapy more agressively in patients without waiting for multiple clinic visits, and should remind providers to treat hypertension more aggressively among diabetic patients.
==== Body
Background
Hypertension is among the most prevalent chronic diseases in the United States [1]. Despite the availability of effective medications and well-published guidelines for the treatment of hypertension [1-4], the majority (approximately 75%) of hypertension in the United States remains poorly controlled [5].
Hypertension is particularly burdensome among racial/ethnic minority groups and hypertension-related cardiovascular disease has been shown to be the greatest contributor to previously documented racial differences in mortality [5-12]. Although higher rates of hypertension control and a reduction in racial differences in outcomes from hypertension may be obtained by increasing providers' aggressiveness in intensifying therapy when indicated [2,12], several studies have demonstrated that providers often allow their patients to remain poorly controlled [12,13].
We previously examined the association of patients' race/ethnicity with processes of hypertension care [13]. We found that, among a cohort of hypertension patients with repeatedly elevated blood pressures, Hispanics were significantly less likely to have therapy intensified and were more likely to have uncontrolled blood pressure (BP) than were other racial and ethnic groups. In an effort to identify potential targets for interventions to improve hypertension care among our patients, we further examined which patient and provider characteristics may explain racial differences in rates of therapy intensification.
Methods
Study sample and procedures
To determine which patient-centered characteristics are associated with providers intensifying drug therapy for hypertension and whether provider experience is related to differences in intensification of therapy, we studied a random subset of 1,205 patients who had a minimum of two hypertension-related outpatient visits to one of twelve general medicine clinics in community health centers and community practices affiliated with a large urban academic medical center from July 1, 2001 through June 30, 2002 (totaling 3,257 visits). To determine hypertension-related visits, we reviewed the electronic medical record (EMR) for all clinic visits with a primary or secondary diagnostic code of hypertension (HTN) (ICD-9 401- 401.9, 405- 405.99). The study protocol was approved by the Human Studies Committee at the Brigham and Women's Hospital.
Medical record and administrative data
We hired three abstractors who were trained by the primary investigator to review the EMR of each patient in our study sample, each abstractor reviewed records for approximately 400 individual patients. From each hypertension-related visit note in the EMR they collected the following data: patient race/ethnicity, name of the patient's primary provider, patient age at time of initial study period visit, sex, primary insurer at time of initial study period visit, presence of comorbid disease (diabetes, congestive heart failure (CHF), coronary artery disease (CAD), or renal failure) listed on the patient problem list, BP control (defined using cut point of <130/85 for diabetic or renal failure patients and <140/90 for all others), and any changes made to antihypertensive drug therapy during visit (decrease or discontinuation of drug, change to another class of drug, or increase of drug dose or addition of new drug).
The EMR of each patient contains racial/ethnic data obtained via self-report the first time each patient registers in his/her clinic that then is classified by the data entry clerk as Hispanic ethnicity or not and race is then classified as Black, White, other, or unknown. Hence, it is impossible to know the country of origin of our Hispanic participants and we could not determine the exact racial/ethnic mix of patients classified as "other" or "unknown." For these reasons, we excluded patients who's EMR listed their racial/ethnic classification as "other" (N = 25) or "unknown" (N = 67) and we limited our analyses to White patients (who identify themselves as non-Hispanic), Black patients (who identify themselves as non-Hispanic), and self-identified Hispanic patients.
From the medical center's administrative database, we abstracted each provider's level of experience (intern, resident, or attending). Patient zip code was also obtained and linked to 2000 U.S. Census data to obtain the median annual household income in each patient's zip code.
Intensity of therapy
Our methods for identifying intensified cases among our cohort have been previously described [13]. Because we were examining the quality of care delivered to hypertension patients prior to July of 2002, approximately one year before the release of the Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation and Treatment of High Blood Pressure (JNC VII) [14], we used JNC VI definitions for blood pressure control in order to examine whether therapy was appropriately intensified. We classified each visit into two categories, intensified visits (an increase in intensity of drug therapy) versus non-intensified visits (a decrease or no change in intensity of drug therapy) according to previously published definitions of changes in medications [2]. We developed an algorithm to determine whether a patient received at least one increase in drug therapy (an increase in drug dose or addition of new medication) in response to a repeatedly elevated BP during the study period (Figure 1). Each patient with fewer than two visits with an elevated BP (N = 356) was excluded from the algorithm. Each patient with an uncontrolled BP at more than one visit was identified as either an intensified case (at least one drug increase) or a non-intensified case (no drug increases). Each reviewer examined a subset of 30 records; we then tested for inter-rater reliability and found excellent agreement among reviewers (kappa = 0.90).
Figure 1 Flow diagram of algorithm for determining an "intensified case." Inter-rater reliability was high (kappa 0.90). We identified a total of 782 cases as either an "intensified case (N = 600) or a "non-intensified case" (N = 157).
Our intensification algorithm is potentially limited because it does not account for differences in the number of times medication is increased in comparison to the number of uncontrolled BP visits for each patient. To address this issue, we created a secondary measure of intensification by calculating the proportion of times each patient had their therapy increased when their BP was uncontrolled (0 representing no increases and 1 representing an increase in therapy with every uncontrolled visit). We then determined whether the two intensification measures were correlated in order to further validate our algorithm and found that the two measures were highly correlated (coefficient 0.71, P <0.001). Because our algorithm-derived method has the additional advantage of using more than a single visit's BP in determining whether therapy intensification is indicated, we used this measure of intensification for all subsequent analyses.
Data analysis
We compared patients' demographic, clinical, and provider's characteristics by patient race/ethnicity (Table 1) using chi-squared tests for categorical and Student's t-test for continuous variables. We also estimated the association of being an intensified case with patients' demographic, clinical, and provider's characteristics (Table 2). We report two-tailed P values with statistical significance set at P≤0.05 for all analyses.
Table 1 Demographic and clinical characteristics of population by race and ethnicity
Variable White (N = 304) Black (N = 309) Hispanic (N = 144) P value*
Men (%) 27.3 24.3 35.4 0.05
Aged <65 years (%) 54.6 65.1 66.7 0.009
Annual household income†: <0.001
= $35,500 11.9 37.8 29.4
$35,501–$43,140 11.9 40.8 21.0
$43,141–$55,365 24.7 15.5 42.7
> $55,365 51.6 5.9 7.0
Insurance: <0.001
Private/Medicare (%) 87.7 69.1 40.3
Medicaid (%) 4.3 17.6 28.5
Free care/Self-pay (%) 8.0 13.4 31.3
Mean number of hypertension visits 2.8 3.0 2.8 0.06
Diabetic (%) 14.5 27.5 27.8 <0.001
Coronary artery disease (%) 5.3 4.2 2.1 0.02
Provider experience (%)‡: <0.001
Intern 2.1 9.3 10.1
Resident 4.8 23.0 10.1
Attending 93.2 67.8 79.8
*Using chi-square tests for categorical variables and ANOVA for mean number of hypertension visits.
†N = 734 for those patients with zip code available.
‡N = 691 for those patients with provider information available.
Table 2 Demographic and clinical characteristics of population by intensification of therapy
Variable Non-Intensified Case (N = 157) Intensified Case (N = 600) P value*
Patient race/ethnicity (%): 0.03
White 19.7 80.3
Black 18.1 81.9
Hispanic 28.5 71.5
Men (%) 29.1 27.7 0.74
Age: 0.10
<65 years 18.8 81.2
≥65 years 23.8 76.2
Annual household income†: 0.93
≤$35,500 20.4 79.6
$35,501–$43,140 19.7 80.3
$43,141–$55,365 22.4 77.6
> $55,365 20.5 79.5
Insurance: 0.15
Private/Medicare (%) 19.5 80.5
Medicaid (%) 27.8 72.2
Free care/Self-pay (%) 20.0 80.0
Mean number of hypertension visits 2.6 3.0 <0.001
Diabetic (%): 0.01
Yes 27.8 72.2
No 18.7 81.3
Coronary artery disease (%): 0.24
Yes 12.5 87.5
No 21.1 78.9
Provider training level (%)‡: 0.91
Intern 22.7 77.3
Resident 21.4 78.6
Attending 20.3 79.7
*Using chi-square tests for categorical variables and Student's t-test to compare mean hypertension visits.
†N = 734 for those patients with zip code available.
‡N = 691 for those patients with provider information available.
Using logistic regression, we assessed whether race/ethnicity was associated with intensification of therapy after adjusting for all measured confounders. Data were available on every variable for 685 of the 757 patients (90.5%) for multivariable analyses. We report adjusted odds ratios with 95% confidence intervals for the intensified cases. In secondary analyses, we included interaction terms for patient race/ethnicity and provider experience level to determine whether racial/ethnic differences in intensification differed by provider experience level. All non-significant interaction terms were removed from the final model. All models were estimated using SUDAAN statistical software to adjust for within clinic correlation of visits [15].
Results
Patient, clinical, and provider characteristics
Of the 757 patients, 304 (40%) were White, 309 (41%) were Black, and 144 (19%) were Hispanic (Table 1). The majority of patients in our cohort were women (72%) and most were either privately insured or had Medicare (71%). There were 169 (22%) patients in our cohort with diabetes. We were able to determine the primary provider for 691 patients, of who 44 (6.4%) received care from an intern, 89 (12.9%) received care from a resident, and 558 (80.8%) received care from an attending. Demographic and clinical differences between patients' racial/ethnic groups are presented in Table 1.
Intensification of therapy
Of the 757 patients with multiple visits whose BP was uncontrolled at two or more visits, there were 600 (79.3%) who had their medications intensified. Hispanic patients were significantly less likely to have their medications intensified than White and Black patients (Table 2). Diabetic patients and those with fewer visits during the study period were also less likely to have their medications intensified.
After adjustment for age, insurance status, number of hypertension-related visits, diabetes, and physician experience, there were no remaining racial/ethnic differences in rates of intensification (Table 3). Compared to patients aged = 65 years, younger patients were more likely to have their therapy intensified, and the odds of having therapy intensified increased with each visit. There were no significant interactions between race/ethnicity and provider experience in the multivariable model.
Table 3 Adjusted odds ratios* [95% C.I.] of being an intensified case
Variable Odds Ratios of being Intensified Case 95 % Confidence interval
Black† 1.09 [0.71–1.67]
Hispanic† 0.78 [0.58–1.06]
Age < 65 years‡ 1.61 [1.38–1.88]
Medicaid§ 0.76 [0.57–1.02]
Free care or self pay§ 1.22 [0.73–2.03]
Number of hypertension visits|| 1.37 [1.17–1.61]
Diabetes** 0.61 [0.34–1.08]
Intern provider†† 0.86 [0.39–1.88]
Resident provider†† 0.89 [0.55–1.46]
* Adjusted for patient race/ethnicity, age, insurance status, number of hypertension-related visits, diabetes, and physician experience.
†Whites use as reference group
‡Aged ≥ 65 years used as reference group
§Privately insured or Medicare used as reference group
||Represents increase in odds with each additional visit
**No diabetes used as reference group
††Attending provider used as reference group
Discussion
In our prior work, we found that Hispanic patients were more likely to receive the JNC recommended antihypertensive drug class then Whites, however, Hispanics were also significantly less likely than Whites to have their therapy appropriately intensified in response to an uncontrolled BP [13]. Furthermore, we found appropriate intensification of anti-hypertensive therapy was associated with subsequent BP control for all racial/ethnic groups, suggesting that the poorer rates of BP control among Hispanics in our prior study may have been due to significantly lower rates of antihypertensive medication intensification [13]. In this study, we found that these previously noted racial/ethnic disparities in rates of antihypertensive therapy intensification may be due to differences in visit patterns among patients and in physicians' aggressiveness in managing BP in diabetic patients, suggesting that racial/ethnic differences in disease severity are likely determinants of unequal treatment of uncontrolled hypertension.
There is substantial literature, that suggests that racial/ethnic minority groups are less likely to have their antihypertensive therapy appropriately intensified [16-19]. However, these studies were limited because the investigators were not able to assess practice patterns such as the frequency with which individual anti-hypertensive drugs were intensified in response to uncontrolled BP. We found that Hispanic patients in our cohort were also less likely to have their anti-hypertensive medications intensified at least once in response to repeatedly uncontrolled BP than were other racial/ethnic groups and our findings also expand beyond documenting racial/ethnic disparities in aggressiveness of therapy by determining the roles racial/ethnic differences in clinic utilization among patients and racial/ethnic differences in the prevalence of diabetes play in confounding differences in providers' aggressiveness in treating hypertension.
An important national priority in health care is the elimination of racial/ethnic disparities in healthcare; however, a better understanding of the determinants of disparities is needed to address this issue [20,21]. Our finding that higher rates of diabetes among Hispanics in our cohort play a major role in the insufficient management of their uncontrolled BP is of particular concern given that Hispanics suffer a disproportionately larger burden from hypertension and diabetes compared to Whites; and that Hispanics are at a higher risk of having hypertension and diabetes, are less likely to be aware that they are hypertensive, are more likely to have target organ damage, and have significantly higher age-adjusted diabetes and hypertension-related mortality compared to whites in the U.S [5,6,22,23]. Our findings are supported by several studies that have documented lower rates of BP control among diabetic patients [24,25], and others showing that providers often do not attain adequate BP control for patients, even after multiple opportunities to do so [2,24].
Our study has several limitations. We were unable to collect measures of patient adherence to prescribed therapy from the EMR. Providers may not want to intensify therapy at the same rate for patients they know are less compliant with therapy, although it is hard to identify these patients. We were also unable to determine English proficiency of each patient from the medical records. When a language barrier exists providers may be less likely to intensify therapy.
We examined disparities in quality of hypertension care, as measured by intensification of therapy, among a cohort of patients and physicians during 2001–2002 using the established guidelines available during that time period, the JNC VI, as the reference for our analyses. In comparison to JNC VI, the JNC VII guidelines recommend much more aggressive management of hypertension both in terms of the accepted level of BP control (130/80 for diabetic and renal failure patients and 140/90 for all others) and the recommendations to providers to intensify antihypertensive therapy more rapidly when BP is uncontrolled [14]. However, since the JNC VII guidelines were not available until 2003, it would have been impossible for providers in our study sample to have been fully aware of them and it would have been misleading to assess the quality of hypertension care among our cohort using quality guidelines that were not in existence during that time. By using the less aggressive guidelines that were in existence during the study period, we may have underestimated the gap in rates of intensification between racial/ethnic groups and between patients with diabetes and those without.
Lastly, we examined patients who received their care at primary care practices affiliated with a single large urban teaching hospital, and although there was substantial socioeconomic diversity in our sample our results may not be generalizable to smaller, rural, or non-teaching hospitals.
Conclusion
We found significant racial/ethnic differences in intensification of drug therapy, and that these differences were largely accounted for by differences in frequency of clinic visits and in the prevalence of diabetes. Future interventions should focus on increasing physician awareness of the need to intensify drug therapy more, particulary among Hispanic patients, and on encouraging providers to treat hypertension more intensively in diabetic patients.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
LH conceived of the study, and participated in its design and coordination and helped to draft the manuscript. SS participated in the design of the study, performed the statistical analysis, and helped to draft the manuscript. DWB and JZA participated in the design of the study, and helped to draft the manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
The authors would like to thank Deborah H. Williams for statistical programming assistance. This study was supported by a grant from the Agency of Healthcare Research and Quality (#3U18 HS11046). Dr. Hicks was supported by the Robert Wood Johnson Foundation's Harold Amos Medical Faculty Development Program (#043486).
==== Refs
Anonymous The sixth report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure Arch Intern Med 1997 157 2413 2446 9385294 10.1001/archinte.157.21.2413
Berlowitz DR Ash AS Hickey EC Friedman RH Glickman M Kader B Moskowitz MA Inadequate management of blood pressure in a hypertensive population N Engl J Med 1998 339 1957 1963 9869666 10.1056/NEJM199812313392701
Hyman DJ Pavlik VN Self-reported hypertension treatment practices among primary care physicians: blood pressure thresholds, drug choices, and the role of guidelines and evidence-based medicine Arch Intern Med 2000 160 2281 2286 10927724 10.1001/archinte.160.15.2281
Oliveria SA Lapuerta P McCarthy BD L'Italien GJ Berlowitz DR Asch SM Physician-related barriers to the effective management of uncontrolled hypertension Arch Intern Med 2002 162 413 420 11863473 10.1001/archinte.162.4.413
Hajjar I Kotchen TA Trends in prevalence, awareness, treatment, and control of hypertension in the United States, 1988–2000 JAMA 2003 290 199 206 12851274 10.1001/jama.290.2.199
Sundquist J Winkleby MA Pudaric S Cardiovascular disease risk factors among older black, Mexican-American, and white women and men: an analysis of NHANES III, 1988–1994. Third National Health and Nutrition Examination Survey J Am Geriatr Soc 2001 49 109 116 11207863 10.1046/j.1532-5415.2001.49030.x
Hyman DJ Pavlik VN Characteristics of patients with uncontrolled hypertension in the United States N Engl J Med 2001 345 479 486 11519501 10.1056/NEJMoa010273
Materson BJ Lessons on the interaction of race and anti-hypertensive drugs from the VA cooperative study group on anti-hypertensive agents Am J Hypertension 1995 8 91s 93s 10.1016/0895-7061(95)00305-3
Richardson AD Piepho RW Effect of race on hypertension and anti-hypertensive therapy Int J Clin Pharm Ther 2000 38 75 79
He J Klag MJ Caballero B Appel LJ Charleston J Whelton PK. Plasma insulin levels and incidence of hypertension in African Americans and Whites Arch Intern Med 1999 159 498 503 10074959 10.1001/archinte.159.5.498
Wong MD Shapiro MF Boscardin WJ Ettner SL Contribution of major diseases to disparities in mortality N Engl J Med 2002 347 1585 1592 12432046 10.1056/NEJMsa012979
Hyman DJ Pavlik VN Uncontrolled hypertension as a risk for coronary artery disease: patient characteristics and the role of physician intervention Diabetes Care 2003 26 355 359 12547862
Hicks LS Fairchild DG Horng MS Orav EJ Bates DW Ayanian JZ Determinants of JNC VI guideline adherence, intensity of drug therapy, and blood pressure control by race and ethnicity Hypertension 2004 44 429 34 15326088 10.1161/01.HYP.0000141439.34834.84
Chobanian AV Bakris GL Black HR Cushman WE Green LA Izzo JL Jones DW Materson BJ Oparil S Wright JT Roccella EJ the National High Blood Pressure Education Program Coordinating Committee The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 Report JAMA 2003 289 2560 2572 12748199 10.1001/jama.289.19.2560
Frane J SUDAAN: Professional Software for Survey Data Analysis 1989 Research Triangle Park, NC: Research Triangle Institute
Cushman WC Ford CE Cutler JA Margolis KL Davis BR Grimm RH Black HR Hamilton BP Holland J Nwachuku C Papademetriou V Probstfield J Wright JT JrAlderman MH Weiss RJ Piller L Bettencourt J Walsh M ALLHAT Collaborative Research Group Success and predictors of blood pressure control in diverse North American settings: the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT) J Clin Hypertens 2002 4 393 404
Sudano JJ Baker DW Antihypertensive medication use in Hispanic adults: a comparison with Black adults and White adults Med Care 2001 39 575 587 11414262 10.1097/00005650-200106000-00006
Henderson SO Bretsky P DeQuattro V Henderson B Treatment of hypertension in African Americans and Latinos: the effect of JNC VI on urban prescribing practices J Clin Hypertens 2003 5 107 112
Clause SL Hamilton RA Medicaid prescriber compliance with Joint National Committee VI hypertension treatment guidelines Ann Pharmacother 2002 36 1505 1511 12243597 10.1345/aph.1A451
Institute of Medicine Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care 2003 Washington: National Academy Pr
American College of Physicians Racial and ethnic disparities in health care: a position paper of the American College of Physicians Ann Intern Med 2004 141 226 232 15289223
US Department of Health and Human Services A Public Health Action Plan to Prevent Heart Disease and Stroke 2003 Atlanta, GA: US Department of Health and Human Services, Centers for Disease Control and Prevention
Centers for Disease Control and Prevention Health, United States, 2002 With Chartbook on Trends in the Heatlh of Americans 2002 Hyattsville, MD: US Department of Health and Human Services, Centers for Disease Control and Prevention DHHS publication no. 1232
Borzecki AM Wong AT Hickey EC Ash AS Berlowitz DR Hypertension control: how well are we doing? Arch Intern Med 2003 163 2705 2711 14662624 10.1001/archinte.163.22.2705
Harris M Health care and health status and outcomes for patients with type 2 diabetes Diabetes Care 2000 23 754 758 10840991
| 15972095 | PMC1173097 | CC BY | 2021-01-04 16:30:07 | no | BMC Cardiovasc Disord. 2005 Jun 22; 5:16 | utf-8 | BMC Cardiovasc Disord | 2,005 | 10.1186/1471-2261-5-16 | oa_comm |
==== Front
BMC Cardiovasc DisordBMC Cardiovascular Disorders1471-2261BioMed Central London 1471-2261-5-181598518010.1186/1471-2261-5-18Research ArticleThe BpTRU automatic blood pressure monitor compared to 24 hour ambulatory blood pressure monitoring in the assessment of blood pressure in patients with hypertension Beckett Linda [email protected] Marshall [email protected] Linda Beckett is currently a 3rd year Family Medicine Resident at the Dept of Family Medicine, Queen's University, Kingston, Ontario, Canada2 Marshall Godwin is a Professor, Queen's University and the Director, Centre for Studies in Primary Care, Department of Family Medicine, Queen's University, 220 Bagot Street, Kingston, Ontario, K7L 5E9, Canada2005 28 6 2005 5 18 18 29 12 2004 28 6 2005 Copyright © 2005 Beckett and Godwin; licensee BioMed Central Ltd.2005Beckett and Godwin; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Increasing evidence suggests that ABPM more closely predicts target organ damage than does clinic measurement. Future guidelines may suggest ABPM as routine in the diagnosis and monitoring of hypertension. This would create difficulties as this test is expensive and often difficult to obtain. The purpose of this study is to determine the degree to which the BpTRU automatic blood pressure monitor predicts results on 24 hour ambulatory blood pressure monitoring (ABPM).
Methods
A quantitative analysis comparing blood pressure measured by the BpTRU device with the mean daytime blood pressure on 24 hour ABPM. The study was conducted by the Centre for Studies in Primary Care, Queen's University, Kingston, Ontario, Canada on adult primary care patients who are enrolled in two randomized controlled trials on hypertension. The main outcomes were the mean of the blood pressures measured at the three most recent office visits, the initial measurement on the BpTRU-100, the mean of the five measurements on the BpTRU monitor, and the daytime average on 24 hour ABPM.
Results
The group mean of the three charted clinic measured blood pressures (150.8 (SD10.26) / 82.9 (SD 8.44)) was not statistically different from the group mean of the initial reading on BpTRU (150.0 (SD21.33) / 83.3 (SD12.00)). The group mean of the average of five BpTRU readings (140.0 (SD17.71) / 79.8 (SD 10.46)) was not statistically different from the 24 hour daytime mean on ABPM (141.5 (SD 13.25) / 79.7 (SD 7.79)). Within patients, BpTRU average correlated significantly better with daytime ambulatory pressure than did clinic averages (BpTRU r = 0.571, clinic r = 0.145). Based on assessment of sensitivity and specificity at different cut-points, it is suggested that the initial treatment target using the BpTRU be set at <135/85 mmHG, but achievement of target should be confirmed using 24 hour ABPM.
Conclusion
The BpTRU average better predicts ABPM than does the average of the blood pressures recorded on the patient chart from the three most recent visits. The BpTRU automatic clinic blood pressure monitor should be used as an adjunct to ABPM to effectively diagnose and monitor hypertension.
==== Body
Background
Hypertension is a continuous, independent, yet modifiable risk factor for cardiovascular, cerebrovascular and renal disease. It has been estimated that 62% of cerebrovascular disease and 49% of ischemic heart disease can be attributed to suboptimal blood pressure(BP) control [1].
Since 24 hour ambulatory blood pressure monitoring (ABPM) is currently recommended as the measurement of choice in difficult cases (uncertainty of diagnoses, fluctuating office visits, unresponsiveness to treatment, white coat affect(WCE)) [1-5] it is, in effect, the 'final arbiter' or 'gold standard' for the diagnosis of hypertension and the assessment of whether target has been achieved. The generally accepted blood pressure target on ABPM is a daytime average pressure of < 135/85 mmHG [2-4]; the target blood pressure when measured in the doctors office is < 140/90 mmHG.
Increasing evidence suggests that ABPM more closely predicts target organ damage than does clinic measurement. The Ohsama study found that cardiovascular mortality, but not all cause mortality, was more closely predicted by the daytime systolic blood pressure than clinic pressures [6]. ABPM also better predicted cardiovascular events such as MI, CHF, stroke and TIA [4,5] as well as other target organ damage such as ventricular hypertrophy, proteinuria, plasma creatinine, and stroke [5,7-14].
Many patients have clinically significant WCE, making clinic measurements an unreliable indicator of true blood pressure control [11]. Future guidelines may suggest ABPM as routine in the diagnosis and monitoring of hypertension. This would create difficulties as this test is expensive and often difficult to obtain.
Recently, automatic blood pressure measuring devices have been used either at home or in the clinic setting [16]. It has been found that the measurements taken at home, or while not in the presence of clinic staff, have a better correlation with daytime ABPM than do nurse or physician measurements [15-17]. Home or clinic self measurement is also preferred by patients over 24 hour monitoring [18].
The purpose of this study is to determine the possible clinical utility of the BpTRU automated blood pressure monitor in the diagnosis and monitoring of hypertension in the primary care clinic setting. Specifically, we set out i) to determine how BpTRU measurements related to ABPM measurements and ii) to determine the level of BpTRU measurement that best predicted a mean daytime blood pressure of <135 mmHG systolic and < 85 mmHG diastolic. The BpTRU monitor has been developed by VSM MedTech Ltd of Vancouver Canada specifically for the clinician's office.
Methods
The data used in this study is a subset of the data collected for two ongoing RCTs being conducted at the Centre for Studies in Primary Care at Queen's University, Kingston, Ontario, Canada – the Home Monitoring of Blood Pressure Study (ISRCTN25105161) and the Intensive Scheduled Management of Hypertension Study (ISRCTN05874865) which are funded by the Heart and Stroke Foundation of Ontario. A group of 481 subjects for which all relevant data were available were used for analyses of correlations.
Subjects were recruited from 51 family practices in eastern Ontario. All patients with a diagnosis of hypertension who were being treated with antihypertensive medications were identified in each practice. Each patient's chart was reviewed to abstract the blood pressures recorded on the patient's chart at the last three office visits where blood pressure was measured. Only one recording was used from any single office visit. If there was more than one recording at a given visit, the last measurement recorded for that visit was used. These visits ranged from several weeks to several months apart, depending on the practice of the physician regarding follow-up of hypertensive patients. If the mean of these three readings, taken at different visits, was ≥140/90, the patient was labeled as 'uncontrolled' by office measurement, meaning that the patient had not achieved the treatment target (≥130/80 was used for diabetics). The research nurse then contacted these uncontrolled patients and invited them to participate in the study. Subjects were excluded if they were <18 years of age, pregnant, or had a known secondary cause for their hypertension.
BpTRU measurements
The BpTRU device uses the oscillometric technique used by most ambulatory and home blood pressure measuring devices [19,20]. It is designed to take an initial reading while the clinician is present, and then with the patient alone in the room, proceeds to take 5 more measurements at intervals of 1–5 minutes and then provides an average of these five readings.
The specific steps we used were: i) the subjects were seated for at least 5 minutes, ii) the BpTRU cuff was applied to the non-dominant arm by the research nurse, iii) the initial BpTRU blood pressure reading was taken and recorded, iv) the staff then left the room while the BpTRU device took a minimum further 5 readings at intervals of either one minute or two minutes, v) these five readings were averaged by the device and this average was recorded. The BpTRU device has passed the standards of the British Hypertension Society and the Association of Advancement of Medical Instrumentation [20,21].
Ambulatory monitoring
All patients then had ABPM monitoring using oscillometric A&D Model TM2430 equipment (A&D Medical, Milpitas, California, USA). The ABPM equipment was applied at the same visit as the other research measurements. The cuff was fixed to the non-dominant arm and the device was set to obtain automatic readings every 15 minutes during the day (0600–2200) and every 30 minutes at night (2200–0600). This monitoring took place on working days and subjects were instructed to behave and work as usual. The A&D Model TM2430 has been clinically validated according to the British Hypertension Society protocols [22].
Results
Of the 481 subjects, 210 (43.6 %) were male and 271 (56.3 %) female. The average age was 64.9 (SD 11.59) with a range of 33 to 92 and average BMI was 30.6 (SD 5.22). All but 2 subjects were on antihypertensive medications. In essence, this was a population of treated known hypertensive patients.
Comparison of group mean blood pressures
Table 1 shows the mean and standard deviations(SD) of systolic and diastolic BP as measured in the family physicians' offices (the average of the blood pressure measurements recorded on the patient chart at the last three visits), the initial BpTRU reading, the average BpTRU reading, and the 24 hour daytime average. There was no statistical difference in group mean between clinic measurement and initial BpTRU readings, and no statistical difference between average BpTRU readings and ABPM daytime average.
Table 1 Mean systolic and diastolic BPs
Average of the blood pressures measured at the last three office visits 150.8 (SD10.26) / 82.9 (SD 8.44)
BpTRU initial reading 150.0 (SD21.33) / 83.3 (SD12.00)
BpTRU Average 140.0 (SD17.71) / 79.8 (SD 10.46)
24 hour daytime average 141.5 (SD 13.25) / 79.7 (SD 7.79)
Comparison of BP target achievement
A large proportion of those subjects who had uncontrolled hypertension according to the mean of the three last clinic BPs had lower blood pressure on either or both of BpTRU or 24 hour monitor. In 393 (81.7%) of the 481 subjects the systolic blood pressure was less with the BpTRU than with the clinic readings and in 312 (64.8%) of the 481 subjects the systolic blood pressure was less with daytime ABPM than with the clinic readings. Diastolic pressure similarly decreased in 332 (69.0%) using the BpTRU average and 292 (60.7%) with daytime ABPM. In all, 250 of the 470 (53.2%) were found by BpTRU monitor to have achieved the accepted clinic measurement target of <140/90 mmHG. ABPM revealed that 162 subjects (33.4%) were actually normotensive with a daytime average of <135/85 mmHG.
Correlations
Pearson correlations (Table 2) were calculated comparing the mean daytime systolic and diastolic ABPM results with the average of the blood pressure measurements recorded on the patient's office chart, the first BpTRU measurement taken in the presence of the staff, and with the average of five readings on the BpTRU device.
Table 2 Pearson Correlation coefficients
Mean 24 hr daytime systolic Mean 24 hr daytime diastolic
Mean of the blood pressure measurements at the last three office visits r = 0.145 r = 0.316
1st BpTRU measurement r = 0.473 r = 0.554
Average BpTRU(out of 5) r = 0.571 r = 0.610
Using BpTRU to predict achievement of targets
ABPM is accepted as the most reliable way to determine if blood pressure targets are achieved in hypertensive patients, but using ABPM after every medication adjustment is impractical and costly. To determine which level of BpTRU blood pressure best predicted achievement of target (i.e. <135/85) on ABPM, various prediction estimates (sensitivity, specificity, and predictive values) were calculated for different levels of BpTRU readings (Tables 3 and 4).
Table 3 Two-By-Two Tables And BpTRU Predictive Characteristics For Achievement Of ABPM Systolic Target
Systolic Target Achieved on ABPM (<135 mmHG mean daytime blood pressure)
Yes NO
< 140 mmHG on BpTRU Yes 131 137 Sens = 80%; Spec = 55% PPV = 49%; NPV = 84%
No 32 170
< 135 mmHG on BpTRU Yes 111 101 Sens = 68%; Spec = 67% PPV = 52%; NPV = 80%
No 52 206
< 130 mmHG on BpTRU Yes 86 59 Sens = 53%; Spec = 81% PPV = 59%; NPV = 76%
No 77 248
< 125 mmHG on BpTRU Yes 62 31 Sens = 39%; Spec = 90% PPV = 67%; NPV = 73%
No 101 276
< 120 mmHG on BpTRU Yes 42 12 Sens = 26%; Spec = 96% PPV = 78%; NPV = 71%
No 121 295
Table 4 Two-by-Two Tables and BpTRU predictive characteristics for achievement of ABPM diastolic target
Diastolic Target Achieved on ABPM (<85 mmHG mean daytime blood pressure)
Yes NO
< 90 mmHG on BpTRU Yes 341 58 Sens = 92%; Spec = 43% PPV = 86%; NPV = 61%
No 28 43
< 85 mmHG on BpTRU Yes 299 36 Sens = 81%; Spec = 64% PPV = 89%; NPV = 48%
No 70 65
< 80 mmHG on BpTRU Yes 238 13 Sens = 65%; Spec = 87% PPV = 95%; NPV = 40%
No 131 88
< 75 mmHG on BpTRU Yes 161 5 Sens = 44%; Spec = 95% PPV = 97%; NPV = 32%
No 208 96
< 70 mmHG on BpTRU Yes 82 1 Sens = 22%; Spec = 99% PPV = 99%; NPV = 26%
No 287 100
Discussion
The measurements of blood pressure done with a provider present, that is the mean of the physician office measurements, and the observed first BpTRU measurements were not significantly different from each other and probably are both affected by the white coat phenomenon. This also suggests that the mean of the last three office blood pressure measurements is a good proxy for the patient's current blood pressure, taken with a health care professional present (an observed blood pressure measurement). Both of these measures, that is, the mean of the last three office blood pressures and the first, observed reading from the BpTRU, were significantly higher than multiple measurements taken when a provider is not present, that is the mean of the five BpTRU measurements and the daytime mean on ABPM. The mean of the BpTRU and the daytime mean on ABPM were not significantly different.
Recommended BpTRU Thresholds
Our data suggest that the degree of agreement between the BpTRU and 24 hour ABPM is not sufficient for clinicians to use BpTRU alone to determine if BP targets have been achieved. However, since the agreement between the BpTRU and ABPM is so much better than the usual sphygmomanometer-based, observed, clinic measures, it seems reasonable to use the BpTRU to make treatment adjustment decisions to a predetermined BpTRU level and then confirm it with a 24 hour ABPM. If one considers Table 3, it would seem that a systolic BP level of <135 mmHG provides the best overall agreement with the 24 hour ABPM. Similarly, for the diastolic two-by-two tables in Table 4, one would likely choose <85 mmHG diastolic as the most appropriate BpTRU level for diastolic pressure.
Clinicians should consider treating patients to a level of <135/85 mmHG using the BpTRU or similar automated multiple reading device, and at that point conduct a 24 hour ABPM to confirm that a daytime mean pressure of <135/85 mmHG has been achieved. If it has not been achieved, the clinician should further treat to a BpTRU level of <130/80 mmHG or <125/75 mmHG before re-assessing with 24 hour ABPM.
Limitations
Our data are the best currently available to provide some sense of what a BP target level should be when using the BpTRU in office practice. However there are some limitations. The BpTRU and ABPM were carried out in a research setting not a true clinical setting. All the patients had uncontrolled blood pressure according to office BP measurements, so it does not represent a full spectrum; it does not include normotensive patients or patients where the chart records suggest target has been achieved. The data was collected in the course of another study. There is a need for a study that sets out, a priori, to compared BpTRU with ABPM in the full spectrum of patients, and which follows those patients for a longer term to assess clinical outcomes.
Conclusion
The control of hypertension is vital to decrease cardiovascular morbidity and mortality, however the current recommended BP targets are often not being met. There is also growing evidence that office measured sphygmomanometer-based blood pressures are unreliable and do not predict outcomes as well as ABPM, whereas there is increasing evidence from prospective trials that 24 hour monitoring has prognostic significance. We have shown that the BpTRU has potential to be used in the clinic setting to help overcome the difficulties caused by the WCE without the cost of having to conduct frequent 24 hour ABPMs.
Although this study demonstrates that the BpTRU has a sensitivity and specificity that are not ideal when compared to the ABPM device we used, it is superior to usual office measurement and can be used by clinicians as part of their strategy for determining whether BP target has been achieved. We suggest that the BpTRU be used to adjust treatment until patient's BpTRU pressure is below 135/85 mmHg and then a 24 hour ABPM be conducted to confirm. ABPM measurement is not practical as a means of monitoring targets after each medication adjustment but in conjunction with the BpTRU can form the basis for clinical decisions that will promote more effective control of hypertension.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
LB abstracted the data from the larger baseline dataset from the randomized controlled trials. She analysed the data, did the initial interpretation and wrote the initial draft of the article.
MG designed and is conducting the randomized controlled trials from which the data for this study was drawn. He worked with LB on the analysis and the data interpretation and helped with the substantial re-writing of the original draft of the manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
==== Refs
2003 World Health Organization(WHO)/International Society of Hypertension(ISH) statement on management of hypertension Journal of Hypertension 2003 21 1983 1992 14597836 10.1097/00004872-200311000-00002
The Canadian Hypertension recommendations Working group The 2001 Canadian Hypertension Recommendations Perspectives in Cardiology 2002 38 46
Verdecchia P Reference values for ambulatory blood pressure and self-measured blood pressure based on prospective outcome data Blood Pressure Monitoring 2001 6 323 327 12055410 10.1097/00126097-200112000-00011
Stassen JA Thijs L Fagard R O'Brien ET Clement D de Leeuw PW Mancia G Nachev C Palatini P Parati G Tuomilehto J Webster J Predicting cardiovascular risk using conventional vs ambulatory blood pressure in older patients with systolic hypertension. Systolic Hypertension in Europe Trial Investigators JAMA 1999 282 539 546 10450715 10.1001/jama.282.6.539
Redon J Campos C Narciso ML Rodico JL Pascual JM Ruilope LM Prognostic value of ambulatory blood pressure monitoring in refractory hypertension: a prospective study Hypertension 1998 31 712 718 9461245
Ohkubo T Imai Y Tsuji I Nagai K Watanabe N Minami N Itoh O Bando T Sakuma M Fukao A Satoh H Hisamichi S Abe K Prediction of mortality by ambulatory blood pressure monitoring versus screening blood pressure measurements: a pilot study in Ohasama Jour of Hypertension 1997 15 357 364 10.1097/00004872-199715040-00006
Devereux RB Pickering TG Relationship between the level, pattern and variability of ambulatory blood pressure and target organ damage in hypertension J Hypertens Suppl 1991 9 S34 8 1839035
Parati G Pomidossi G Albini F Malaspina D Mancia G Relationship of 24-hour blood pressure mean and variability to severity of target-organ damage in hypertension Journ Hypertension 1987 5 93 98
Zanchetti A Crepaldi G Bond MG Gallus GV Veglia F Ventura A Mancia G Baggio G Sampieri L Rubba P Collatina S Serrotti E Systolic and pulse blood pressures (but not diastolic blood pressure and serum cholesterol) are associated with alterations in carotid intima-media thickness in the moderately hypercholesterolaemic hypertensive patients of the Plaque Hypertension Lowering Italian Study Journ Hypertens 2001 19 79 88 10.1097/00004872-200101000-00011
Zanchetti A Bond MG Hennig M Neiss A Mancia G Dal Palu C Hansson L Magnani B Rahn KH Reid J Rodicio J Safar M Eckes L Ravinetto R Risk factors associated with alterations on carotid intima-media thickness in hypertension: baseline data from the European Lacidipine Study on atherosclerosis Journ Hypertens 1998 16 949 961 10.1097/00004872-199816070-00008
Vakopoulos NA Kotsis VT Pitiriga VC Toumanidis ST Lekakis JP Nanas SN Vemmos KN Stamatelopoulos SF Moulopoulos SD White coat effect in normotension and hypertension Blood Press Monit 2002 7 271 276 12409886 10.1097/00126097-200210000-00004
Verdecchia P Gianpaola R Porcellati C Schillaci G Pede S Bentivoglio M Angeli F Norgiolini S Ambrosio G Risk of cardiovascular disease in relation to achieved office and ambulatory blood pressure control in treated hypertensive subjects J Amer Coll Card 2002 39 878 885 10.1016/S0735-1097(01)01827-7
Verdecchia P Schillaci G Reboldi G Franklin SS Porcellati C Ambulatory monitoring for prediction of cardiac and cerebral events Clin and Research Develop 2001 6 211 216
Verdecchia P Angeli F Gattobigio R Clinical usefulness of ambulatory blood pressure monitoring J AM Soc Nephrol 2004 15 S30 S33 14684668 10.1097/01.ASN.0000093241.62751.95
Little P Barnet J Barnsley L Marjoram J Fitzgerald-Barron A Mant D Comparison of agreement between different measures of blood pressure in primary care and daytime ambulatory blood pressure BMJ 2002 7 293 300
Myers MG Valdivieso MA Use of an automated blood pressure recording device, the BpTRU, to reduce the "white coat effect" in routine practice Amer Journ Hypertens 2003 16 494 497 10.1016/S0895-7061(03)00058-X
Pavek K Nilsson G Patient-specific differences between blood pressure estimated from 24 h ambulatory measurements and serial office self -recordings Blood Pressure Monitoring 2002 7 163 168 12131073 10.1097/00126097-200206000-00004
Little P Barnett J Barnsley L Marjoram J Fitzgerald-Barron A Mant D Comparison of acceptability and preferences for different methods of measuring blood pressure in primary care BMJ 2002 325 258 259 12153924 10.1136/bmj.325.7358.258
Mattu GS Perry TL JrWright JM Comparisons of oscillometric blood pressure monitor (BPM-100Beta) with the auscultatory mercury sphygmomanometer Blood Pressure Monitoring 2001 6 153 159 11518839 10.1097/00126097-200106000-00007
Wright JM Mattu GS Perry TL JrGelfer ME Strange KD Zorn A Chen Y Validation of a new algorithm for the BPM-100 electronic oscillometric office blood pressure monitor Blood Pressure Monitoring 2001 6 161 165 11518840 10.1097/00126097-200106000-00008
Mattu GS Heran BS Wright JM Overall accuracy of the BpTRU – an automated electronic blood pressure device Blood Press Monit 2004 9 47 52 15021078 10.1097/00126097-200402000-00009
Palatini P Frigo G Bertolo O Roman E Da Corta R Winnicki M Validation of the A&D TM-2430 device for ambulatory blood pressure monitoring and evaluation of performance according to subjects' characteristics Blood Press Monit 1998 3 255 260 10212363
| 15985180 | PMC1173098 | CC BY | 2021-01-04 16:30:07 | no | BMC Cardiovasc Disord. 2005 Jun 28; 5:18 | utf-8 | BMC Cardiovasc Disord | 2,005 | 10.1186/1471-2261-5-18 | oa_comm |
==== Front
BMC GastroenterolBMC Gastroenterology1471-230XBioMed Central London 1471-230X-5-151589289510.1186/1471-230X-5-15Research ArticleClinicians' management strategies for patients with dyspepsia: a qualitative approach Knutsson Kerstin [email protected] Bodil [email protected] Margareta [email protected] Faculty of Odontology, Centre for Oral Health Sciences, Malmö University, Malmö, Sweden2 Department of Clinical Sciences, Gastroenterology and Hepatology Division, Malmö University Hospital, Lund University, Lund, Sweden3 Department of Community Medicine, Malmö University Hospital, Lund University, Lund, Sweden2005 15 5 2005 5 15 15 24 11 2004 15 5 2005 Copyright © 2005 Knutsson et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Symptoms from the upper gastrointestinal tract are frequently encountered in clinical practice and may be of either organic or functional origin. For some of these conditions, according to the literature, certain management strategies can be recommended. For other conditions, the evidence is more ambiguous. The hypothesis that guided our study design was twofold: Management strategies and treatments suggested by different clinicians vary considerably, even when optimal treatment is clear-cut, as documented by evidence in the literature. Clinicians believe that the management strategies of their colleagues are similar to their own.
Methods
Simulated case histories of four patients with symptoms from the upper gastrointestinal tract were presented to 27 Swedish clinicians who were specialists in medical gastroenterology, surgery, and general practice and worked at three hospitals in the southern part of Sweden. The patients' histories contained information on the patient's sex and age and the localisation of the symptoms, but descriptions of subjective symptoms and findings from examinations differed from history to history. Interviews containing open-ended questions were conducted.
Results
For the same patient, the management strategies and treatments suggested by the clinicians varied widely, as did the strategies suggested by clinicians in the same speciality. Variation was more pronounced if the case history noted symptoms but no organic findings than if the case history noted unambiguous findings and symptoms. However, even in cases with a consensus in the scientific literature on treatment, the variations in clinicians' opinion on management were pronounced.
Conclusion
Despite these variations, the clinicians believed that the decisions made by their colleagues would be similar to their own. The overall results of this study indicate that we as researchers must make scientific evidence comprehensible and communicate evidence so that clinicians are able to interpret and implement it in practice. Of particular significance is that scientific evidence leads to an evidence-based care which is effective clinical practice and to the promotion of health from the perspective of the patient, together with cost-effectiveness as a priority.
gastrointestinal tractdecision-makingdyspepsiaqualitative evaluation
==== Body
Background
The quality of health care is determined by two main factors: the quality of the judgements and decisions that determine what actions are to be taken, and the quality with which those actions are executed [1]. Within health care, there are wide variations in clinicians' judgements on diagnosis and in the management of patients with the same symptoms and diagnosis [2]. These variations are seen within different disciplines, among both experts and novices. In spite of this evidence, clinicians generally believe that the decisions made by their colleagues would be similar to their own, and hence they assume that there is a broad consensus in medical practice [2].
Patients with symptoms from the upper gastrointestinal tract are regularly seen in clinical practice. The symptoms may be either of organic origin – e.g. ulcer disease, oesophagitis, and malignancies in the oesophagus and the ventricle – or of functional origin [3]. Dyspepsia is a collective term and includes conditions in both categories. Dyspepsia is common, and the subjective symptoms in either category varybetween patients. During a 3-month period, about 30% of the adult population suffers from dyspepsia [4]. Among these sufferers, only a minority has ulcer diseases (10%) [5] or reflux (12%) [6]. According to the literature, certain management strategies are recommended for some of these conditions, for example reflux [7]. For other conditions, for example functional dyspepsia, the evidence is more ambiguous [8-11]. One may expect a wider variation in the latter than in the former treatment strategies.
The aim of this study was to describe, using a qualitative approach, the variation in the management strategies and treatments suggested by clinicians in three different disciplines for patients with symptoms from the upper gastrointestinal tract. According to this aim, the hypotheses that guided our design were:
1. Management strategies and treatments suggested by different clinicians vary considerably, even when optimal treatment is clear cut, as documented by evidence in the literature.
2. Clinicians believe that the management strategies of their colleagues will be similar to their own.
Methods
Informants
Informants were selected to represent clinicians who regularly encountered patients with dyspeptic symptoms in their daily practice and who thus were expected to have a treatment policy for these patients. We therefore invited Swedish clinicians who were specialists in medical gastroenterology, surgery, and general practice to participate in this study. All clinicians gave their consent to be interviewed. They also suggested other clinicians who might be interested in participating in the study. Altogether, 27 clinicians participated, nine from each of the three specialities. This number is the number commonly used in studies that use judgement analysis to ensure a variation in answers [12].
The specialists in medical gastroenterology (four women and five men) all worked at Lund University Hospital at the time of the study. The surgeons (one woman and eight men) worked at Lund University Hospital or Helsingborg Hospital. The general practitioners (two women and seven men) worked in the Public Health Service in the southern part of Sweden. The clinicians were 35–56 years (average 47 years) of age and their experience in their speciality ranged from 1 to 22 years (average 10 years).
Interviews and case scenarios
A useful approach for studying clinicians' strategies is judgement analysis [14], which describes the cognitive process involved in making a decision. It focuses on the actual decision made by the clinician and on which information, for example symptoms and clinical findings, that the clinician uses to reach that decision.
In our study, each of the clinicians was interviewed separately. The interviews were based on four case histories. The histories described frequent symptoms and findings in 30-year-old men seen in general practice and in specialist out-patient clinics (Table 1). Besides age and sex, all histories contained information on the localisation of symptoms, but information on subjective symptoms and findings from the examination varied from history to history. The questions, listed in Table 1, focused on how the clinician viewed whether there was a need for treatment, what management the clinician would suggest, which factors the clinician thought were most important to consider, and what decisions the clinician thought colleagues in their own speciality or in other specialities would make. The same questions were asked for each patient. The case histories were presented in the sequence described in Table 1. Thus, the questions were answered four times by each informant.
One of the authors (KK) with experience in judgement and decision analysis interviewed each informant at her or his office. Each interview began with the interviewer reading the first history. The interviewer then asked the questions aloud and wrote down the informant's answers after each question. If the informant wished, the history and questions were reread. At the end of the question-and-answer session after each case history, the interviewer read aloud the participant's answers and in cases of ambiguity, adjusted the answers. The interviews thus took the form of an oral questionnaire, but with the possibility to explain the answers more fully.
Content analysis
The analysis was performed after all data had been collected from the informants. Two of the authors (KK, MT) with experience in qualitative studies read the interview notes. In a first step, each of the clinicians' answers was scrutinised to find content or evaluations in common, which were then coded as concepts. The following is an example of answers coded as a concept: To question A ("Do you think that it is a problem to decide whether there is a need for treatment in a case like this?" and if yes: "What problems?") informants gave answers like "there is no demonstrable disease, but the patient has symptoms" and "there is no diagnosis but a suffering patient" (patients 1 and 2). These answers were coded as the concept "The patient suffers, but there is no distinct diagnosis".
In the second step, related concepts were combined into categories, common to all the case histories. The authors compared their coding and resolved any differences through discussion to reach a consensus. The concepts and categories were compared with the original answers to ensure that the answers were covered by the classifications.
Results
The varied answers of the clinicians are presented in Table 2, 3, 4. Different categories of problems existed that could explain the variation in the decision-making process. When answering the question "Do you think there is a problem to decide whether there is a need for treatment in a case like this?", five different categories of answers were given. For example, the basis for deciding whether or not to treat and what would be optimal treatment was ambiguous and, further, the evidence for treatment was poor. Clinicians also felt that they lacked competence in evaluating test results when making treatment decisions and that patient expectations and requirements were problems with patients 1–3. In these cases, the patients sometimes requested investigations and treatment, even though the clinician informed them that there was no reported evidence of effect in the literature for the requested treatment or investigation.
For the same patient, the management strategies considered by the different clinicians varied widely, including extensive examinations, non-pharmacological treatment, drug treatment, and surgery (Table 3). For patients 2 and 3, who had tested positive for Helicobacter pylori (H. pylori), some clinicians stated that they would suggest eradication treatment only if the patient had an ulcer, whereas other clinicians said they would suggest this treatment irrespective of the presence of ulcers. For patient 4, who had a duodenal ulcer, some clinicians suggested eradication treatment only if the patient tested positive for H. pylori, whereas others recommended that treatment irrespective of such test results. This variation was also observed among clinicians in the same speciality. Variation was more pronounced if the case history noted symptoms but no organic findings, as in patients 1 and 2, than if the case history noted unambiguous findings and symptoms, as in patients 3 and 4.
When asked "Which factors are most important to consider in your decision?" (Table 4), the clinicians defined three categories of information. For patients 1 and 2, whose symptoms were diffuse, several clinicians answered that the medical history was the most important piece of information to consider. They also claimed to need a more comprehensive medical history for patients 1 and 2 than for patients 3 and 4, whose symptoms were more obviously related to an organic diagnosis.
A majority of the clinicians believed that their treatment decisions would be similar to those of most of their colleagues in their speciality. Some gastroenterologists believed that surgeons would prefer surgery to medication, given the same test results. Several gastroenterologists and surgeons believed that family clinicians investigated less, informed more, and prescribed acid inhibitors on wider indications than gastroenterologists and surgeons.
Discussion
Methodological and results approaches
The four case histories in this study are representative of patients with conditions frequently seen in medical practice. Diseases of the gastrointestinal tract account for about 6% of all reported consultations in Sweden [13]. Gastritis, dyspepsia, and unspecified diseases in the ventricle and duodenum (patients 1 and 2) are diagnosed in 1.6% of the population; oesophagitis and reflux (patient 3) in 0.9%; and different ulcers (patient 4) in 0.6%.
The clinicians who participated in this study were not representative of a randomised selection of clinicians in Sweden but rather of a select group with a special interest in patients with symptoms from the gastrointestinal tract. Since their experience with these patients was extensive, they should have been able to develop a treatment policy. One would expect a variation in treatment strategy in this group to be more limited than among a randomised selection of clinicians.
The results underpin existing evidence that variations in medical practice exist [14-16]. This study presents variations both in treatment strategy and in what information is considered important for making treatment decisions. The histories of patients with diffuse symptoms but no objective findings (patients 1 and 2) gave rise to more extensive variations than did the case histories of patients 3 and 4 where the symptoms were more obviously related to a diagnosis (patient 3) or where more obvious organic changes existed (patient 4). Uncertainty in diagnosis could lead to uncertainty regarding which outcome of alternative interventions is optimal [17,18]. A meta-analysis that evaluates the most effective treatment in patients with functional dyspepsia [10] recommended the eradication of H. pylori if the treatment is to be effective from the patient's perspective, whereas other randomised, double-blind, controlled studies find that eradication has no beneficial effect [11]. These results were underpinned by the variations observed in this study.
Uncertainty due to lack of knowledge or professional competence may lead to qualitative differences. In this study, different management strategies were recommended for patients with reflux disease (patient 3), for example, eradication treatment as one strategy and changes in life-style as another. However, evidence in the literature presenting eradication as an optimal management of reflux is lacking [17]. Instead, this management strategy raises the cost to society and to the patient and causes unnecessary antibiotic pressure. Randomised, double-blinded, prospective studies conclude that the only indication for treating dyspepsia with proton pump inhibitors (PPIs) is the presence of an ulcer or reflux [7]. However, the majority of clinicians prescribed PPIs and H2-receptor antagonists for the treatment of dyspepsia, although no evidence of an effect with this treatment compared to placebo has been documented [9,10]. Thus, this regimen has led to high costs for society without any benefits. The drug costs for treatment of ventricular and duodenal ulcers and of reflux, including eradication treatment, were SEK 1.6 billion [USD 210 million] in 1998 in Sweden [13], while The Swedish Council on Technology Assessment in Health Care reports that society's direct and indirect costs for dyspepsia were between SEK 3.7 and 4.4 billion [USD 490 and 590 million] in 2000 [3].
From the informants' answers to the question "Which factors are most important to consider in your decision?", the completeness of some of the answers given in the interviews could be questioned. Most likely, the clinicians failed to answer the question in full as they left out many factors worthy of consideration. Other factors in the patient's life such as stress, mental mood, working situation, and diet were not mentioned by the clinicians in the interviews but should often be considered in treatment strategies in an actual clinical situation.
Within each of the three specialities, clinicians believed that their colleagues would treat patients in the same way as they themselves did. This aspect of "professional certainty" implies that clinicians believe that their practice is correct, irrespective of how much it in fact differs from that of other clinicians [18,19]. This unawareness of variation in the management of frequently seen patients may indicate a lack of communication and discussion about everyday cases. Such discussions are perhaps reserved for more "complex" and rare cases.
Opportunities to change clinicians' practice
Among the causes of variation in medical practice, the influence of factors like patient characteristics (e.g. age, sex, morbidity, and personal preferences) could be more or less regarded as legitimate to explain variations in practice [20]. Other factors, like resource capacity, could be influenced by, for example, budget restrictions while management policy and practice style are more resistant to change [20]. These latter factors should therefore be the targets of efforts to change. However, many attempts to implement evidence by information alone, for example in the form of clinical practice guidelines, have failed to change management strategies [20-23]. Instead, a combination of methods is most likely needed if a permanent change is to occur [23]. Furthermore, it is of utmost importance that potential barriers are identified and that the clinicians who will be affected support the clinical practice guidelines to be implemented.
In recent years, the individual autonomy of patients and letting patients' preferences influence the choice of intervention have been emphasised [24]. In this study, such a strategy could explain why some clinicians mentioned that they felt pressured by patients to perform an intervention, even when the optimal strategy was non-intervention.
Conclusion
In conclusion, our study adds to the present scientific literature by showing that, even in cases with a consensus in the scientific literature on treatment, clinicians can differ in their opinion of which management is optimal. Despite these variations, the clinicians believed that the decisions made by their colleagues would be similar to their own.
Overall, we as researchers must make scientific evidence comprehensible and communicate evidence in such a way that clinicians are easily able to interpret and implement it in practice. Of particular significance is that scientific evidence leads to an evidence-based care, which is effective clinical practice, and to the promotion of health from the perspective of the patient, together with cost-effectiveness as a priority. Cost-effectiveness is a vital concern. Targeting high patient satisfaction may lead to ineffectiveness if the economic consequences of a treatment strategy are ignored.
Declaration of competing interests
The authors declare that they have no competing interests.
Authors' contributions
Kerstin Knutsson, DDS, Odont dr, has special competence in judgement and decision-making within health care. KK contributed to the overall concept and design of the study and conducted the interviews. Grants from the Swedish Research Council (grant no. 521-2001-6341) supported this study.
Bodil Ohlsson, MD, PhD, is a specialist in gastroenterology and contributed with her knowledge in this area to the design of the study and the interpretation of the data.
Margareta Troein, MD, PhD, has special competence in qualitative methods in medical care and contributed to the qualitative analysis and interpretation of the data.
All authors read and approved the final manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
We thank Professor Åke Nilsson, Lund University Hospital, Lund University, Lund and Professor Stefan Lindgren, Malmö University Hospital, Lund University, Lund for their valuable opinions in the initial phase of this study and on the manuscript.
Figures and Tables
Table 1 Case histories and questions presented to the informants.
Patient 1. A 30-year-old man with symptoms from the upper part of the abdomen. The patient has had intermittent pain, made worse by stress, for a few years. One year ago an ultrasound examination and an oesophagogastroduodenoscopy were performed. No abnormal findings were registered. H. pylori serology was negative.
Patient 2. A 30-year-old man with symptoms from the upper part of the abdomen. The patient has had intermittent pain, made worse by stress, for a few years. One year ago an ultrasound examination and an oesophagogastroduodenoscopy were performed. No abnormal findings were registered. H. pylori serology was positive.
Patient 3. A 30-year-old overweight man with symptoms from the upper part of the abdomen and retrosternally. The pain worsens when he leans forward and when he rests in a prone position. He sometimes experiences a sour or bitter taste in his mouth. H. pylori serology was positive.
Patient 4. A 30-year-old man with symptoms from the upper part of the abdomen. The ultrasound examination revealed nothing abnormal, but the oesophagogastroduodenoscopy indicated a duodenal ulcer.
After each case the following questions were asked:
A. Do you think that it is a problem to decide whether there is a need for treatment in a case like this? If yes: What problems?
B. How would you manage a case like this?
C. Which factors do you think are most important to consider in your decision?
D. What do you believe your colleagues would decide in a case like this?
Table 2 Clinicians' answers coded as concepts and organised into categories. Answers of 27 clinicians to the question "Do you think that it is a problem to decide whether there is a need for treatment in a case like this?" If the physicians admitted that it was a problem, they were then asked "What problems?" Answers were coded as concepts and organised into categories for each patient. Numbers of answers are presented within parentheses. Each clinician may give several answers that could be included in different categories.
Categories Concepts
Patient 1 Patient 2 Patient 3 Patient 4
There is no problem to decide (16) (20) (19) (22)
Basis for treatment decision is insufficient There is no diagnosis (5) There is no diagnosis (3) The amount of discomfort is not clear (1)
More examinations are needed (2) No examination of Helicobacter pylori has been made (3)
Evidence for treatment is poor There is hardly any evidence for benefits of treatment (1)
It is difficult to treat dyspepsia (1)
Patient suffers, but there is no distinct diagnosis (2)
Psychosomatic problems (2) Patient suffers, but there is no distinct diagnosis (1) Recurrent condition (2)
Clinician is uncertain of her or his own competence Uncertainty about indication for treatment when Helicobacter pylori serology is positive (1) Uncertainty about indication for treatment when Helicobacter pylori serology is positive (1)
Patient's expectations Patient wishes treatment (1) Patient requires treatment due to positive Helicobacter pylori serology (2) Patient is not motivated to reduce weight (1)
Patient requires treatment due to positive Helicobacter pylori serology (2)
Table 3 Clinicians' answers coded as concepts and organised into categories. Answers of 27 clinicians to the question "How would you manage a case like this? " Answers were coded as concepts and organised into categories for each patient. Numbers of answers are presented within parentheses. Each clinician may give several answers that could be included in different categories.
Categories Concepts
Patient 1 Patient 2 Patient 3 Patient 4
Extend the examination Exclude coeliac disease, examine colon, liver, gall bladder (6)
Evaluate patient's psychosocial conditions (4)
Evaluate outcome of previous treatment (3) Oesophagogastroduodenoscopy, expiration tests for Helicobacter pylori (10)
Evaluate patient's psychosocial condition (2)
Evaluate outcome of previous treatment (1) Oesophagogastroduodenoscopy, expiration tests for Helicobacter pylori (18) Diagnostic tests for Helicobacter pylori (8)
Prescribe non-pharmacological treatment Reassuring information (8)
Expectancy (3)
Dietary advice, reduction of alcohol intake (11)
Reduction of stress (7) Reassuring information (7)
Expectancy (4)
Dietary advice (6)
Reduction of stress (3) Smoking cessation (2)
Weight reduction (3)
Dietary advice (3)
Unspecific life-style changes (6) Unspecific life-style changes (1)
Prescribe drugs against acidity Antacids (7)
H2-receptor antagonists (13)
Proton pump inhibitors (5)
Sucralphate (1) Antacids (7)
H2-receptor antagonists (9)
Proton pump inhibitors (6)
Sucralphate (1) Antacids (1)
H2-receptor antagonists (8)
Proton pump inhibitors (15) Proton pump inhibitors (11)
Prescribe triple treatment (antacid and antibiotics against Helicobacter pylori) Only if patient has an ulcer (7)
Yes, irrespective of whether patient has an ulcer (4) Only if patient has oesophagitis or an ulcer (1)
Yes, irrespective of whether patient has oesophagitis or an ulcer (1) Only if patient has a positive test for Helicobacter pylori (11)
Yes, irrespective of whether Helicobacter pylori serology is positive (14)
Prescribe other drugs Drugs which increase gut motility (2)
NSAID (1)
Bulking agent (1) Drugs which increase gut motility (1) Alginate (6)
Recommend surgery If patient has hiatus hernia (1)
Table 4 Clinicians' answers coded as concepts and organised into categories. Answers of 27 clinicians to the question "Which factors are most important to consider in your decision?" Answers were coded as concepts and organised into categories for each patient. Numbers of answers are presented within parentheses. Each clinician may give several answers that could be included in different categories.
Categories Concepts
Patient 1 Patient 2 Patient 3 Patient 4
Medical history Patient's age (4)
Symptoms including localisation of pain (12)
Life-style/stress (12)
Effects of previous medication (1)
Similar problems for a long time (3) Patient's age (5)
Symptoms including relation to meals (12)
Effects of previous medication (1)
Similar problems for a long time (2) Patient's age (2)
Symptoms generally and in relation to position (21) General state of health (1)
Symptoms (1)
Results from examinations Oesophagogastroduodenoscopy and ultrasound (6)
Test for Helicobacter pylori (5) Oesophagogastroduodenoscopy and ultrasound (1)
Test for Helicobacter pylori (7) Oesophagogastroduodenoscopy (3)
Test for Helicobacter pylori (1)
Weight (1) Oesophagogastroduodenoscopy (26)
Test for Helicobacter pylori (3)
Patient's expectations Patient's preferences (1) Patient requires treatment due to positive Helicobacter pylori serology (3) Patient requires treatment due to positive Helicobacter pylori serology (3)
==== Refs
Eddy DM Dowie J, Elstein A Variations in clinician practice: the role of uncertainty Professional judgement A reader in clinical decision making 1996 Cambridge: University Press 45 59
Wigton RS Brehmer B, Joyce CRB Applications of judgment analysis and cognitive feedback to medicine Human judgment The SJT view 1988 Amsterdam: Elsevier Science Publishers BV 227 245
SBU-The Swedish Council of Technology Assessment in Health Care Dyspepsia-methods of diagnosis and treatment Summary Stockholm 2001
Agréus L Svärdsudd K Nyrén O Tibblin G The epidemiology of abdominal symptoms: prevalence and demographic characteristics in a Swedish adult population. A report from the Abdominal Symptom Study Scand J Gastroenterol 1994 29 102 109 8171277
Johnsen R Straume B Førde OH Peptic ulcer and non-ulcer dyspepsia-a disease and a disorder Scand J Prim Health Care 1988 6 239 243 3266022
Johnsen R Bernersen B Straume B Førde OH Bostad L Burhol PG Prevalence of endoscopic and histologic findings in subjects with and without dyspepsia BMJ 1991 302 749 752 2021764
Richter JE Peura D Benjamin SB Joelsson B Whipple J Efficacy of omeprazole for the treatment of symptomatic acid reflux disease without esophagitis Arch Intern Med 2000 26 1810 1816 10.1001/archinte.160.12.1810
Farup PG Hovde O Breder O Are frequent short gastro-oesophageal reflux episodes the cause of symptoms in patients with non-ulcer dyspepsia responding to treatment with ranitidine? Scand J Gastroenterol 1995 30 829 832 8578179
Farup PG Hovde O Torp R Wetterhus S Patients with functional dyspepsia responding to omeprazole have a characteristic gastro-oesophageal reflux pattern Scand J Gastroenterol 1999 34 575 579 10440606 10.1080/003655299750024652
Moayyedi P Soo S Deeks J Forman D Mason J Innes M Delaney B Systematic review and economic evaluation of Helicobacter pylori eradication treatment for non-ulcer dyspepsia. Dyspepsia Review Group BMJ 2000 321 659 664 10987767 10.1136/bmj.321.7262.659
Talley NJ Vakil N Ballard ED 2ndFennerty MB Absence of benefit of eradicating Helicobacter pylori in patients with nonulcer dyspepsia N Engl J Med 1999 341 1106 1111 10511608 10.1056/NEJM199910073411502
Brehmer A Brehmer B Brehmer B, Joyce CRB What have we learned about human judgment from thirty years of policy capturing? Human judgment The SJT view 1988 Amsterdam: Elsevier Science Publishers BV 75 114
Apoteksbolaget Svensk läkemedelsstatistik 1998 Stockholm 1999 In Swedish.
Wigton RS Hoellerich VL Patil KD How physicans use clinical imformation in diagnosing pulmonary embolism. An application of conjoint analysis Med Decis Making 1986 6 2 11 3945182
Wennberg JE Understanding geographic variation in health care delivery N Engl J Med 1999 340 52 53 9878647 10.1056/NEJM199901073400111
Folland S Goodman AC Stano M The economics of health care 1993 New York: Macmillan
Wu JC Chan FK Wong SK Lee YT Leung WK Sung JJ Effect of helicobacter pylori eradication on oesophageal acid exposure in patients with reflux oesophagitis Aliment Pharmacol Ther 2002 16 545 552 11876709 10.1046/j.1365-2036.2002.01189.x
Chassin MR Explaining geographic variations: the enthusiasm hypothesis Med Care 1993 31 YS37 YS44 8492584
Åkerblom A Knutsson K Petersson K Reit C Rohlin M The major factors that influence endodontic retreatment decisions Swed Dent J 2003 27 23 9 12704945
Eckerlund I Essays on the economics of medical practice variations PhD thesis 2001 Stockholm School of Economics: The Economic Research Institute
Grol R Beliefs and evidence in changing clinical practice BMJ 1997 315 418 421 9277610
Grol R Grimshaw J From best evidence to best practice. Effective implementation of change in patients' care Lancet 2003 362 1225 1230 14568747 10.1016/S0140-6736(03)14546-1
Greco PJ Eisenberg JM Changing physicians' practice N Engl J Med 1993 329 1271 1274 8413397 10.1056/NEJM199310213291714
Coulter A Paternalism or partnership? Patients have grown up- and there's no going back BMJ 1999 319 719 720 10487980
| 15892895 | PMC1173099 | CC BY | 2021-01-04 16:03:27 | no | BMC Gastroenterol. 2005 May 15; 5:15 | utf-8 | BMC Gastroenterol | 2,005 | 10.1186/1471-230X-5-15 | oa_comm |
==== Front
BMC GenetBMC Genetics1471-2156BioMed Central London 1471-2156-6-241590449210.1186/1471-2156-6-24Methodology ArticleOn the use of haplotype phylogeny to detect disease susceptibility loci Bardel Claire [email protected] Vincent [email protected] Jean-Pierre [email protected] Pierre [email protected]énin Emmanuelle [email protected] Unité de recherche en Génétique Épidémiologique et structure des populations humaines, INSERM U535, Villejuif, France2 Laboratoire Bordelais de Recherche en Informatique, UMR 5800, Bordeaux, France3 Programme Avenir, INSERM U458, hôpital Robert Debré, AP-HP, Paris, France4 Fondation Jean Dausset, Paris, France2005 18 5 2005 6 24 24 21 1 2005 18 5 2005 Copyright © 2005 Bardel et al; licensee BioMed Central Ltd.2005Bardel et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
The cladistic approach proposed by Templeton has been presented as promising for the study of the genetic factors involved in common diseases. This approach allows the joint study of multiple markers within a gene by considering haplotypes and grouping them in nested clades. The idea is to search for clades with an excess of cases as compared to the whole sample and to identify the mutations defining these clades as potential candidate disease susceptibility sites. However, the performance of this approach for the study of the genetic factors involved in complex diseases has never been studied.
Results
In this paper, we propose a new method to perform such a cladistic analysis and we estimate its power through simulations. We show that under models where the susceptibility to the disease is caused by a single genetic variant, the cladistic test is neither really more powerful to detect an association nor really more efficient to localize the susceptibility site than an individual SNP testing. However, when two interacting sites are responsible for the disease, the cladistic analysis greatly improves the probability to find the two susceptibility sites. The impact of the linkage disequilibrium and of the tree characteristics on the efficiency of the cladistic analysis are also discussed. An application on a real data set concerning the CARD15 gene and Crohn disease shows that the method can successfully identify the three variant sites that are involved in the disease susceptibility.
Conclusion
The use of phylogenies to group haplotypes is especially interesting to pinpoint the sites that are likely to be involved in disease susceptibility among the different markers identified within a gene.
==== Body
Background
With the development of molecular techniques to identify genetic polymorphisms, numerous markers and in particular Single Nucleotide Polymorphisms (SNPs) [1,2] are now available within and between genes for establishing their possible role in disease susceptibility. One recurrent question in the literature is the way these markers could be used to test for association with complex diseases [3,4]. Should one focus on one marker at a time and simply compare allele or genotype distributions for the studied markers in cases and controls or should one consider haplotypes formed by several linked markers? Haplotypic methods have been suggested to be more powerful at detecting the role of a given genomic region in disease susceptibility [4-7]. Indeed, disease susceptibility may be due to the combined effects of variants at different markers. Different methods have been proposed to test for association between markers located on the same reconstructed haplotypes and disease susceptibility [4,7-10]. In these tests, the number of haplotypes being large, the degrees of freedom to compare cases and controls are also large, decreasing the power to detect the association. Moreover, as some haplotypes would only be carried by one or two individuals, there could be statistical problems owing to small sample sizes making difficult the evaluation of their possible effect on the susceptibility to the disease.
A solution to reduce these problems is to group haplotypes in order to decrease the degrees of freedom and to increase the number of individuals in the different haplotype groups. The cladistic method as described by Templeton et al. [11] is a method to carry out such groupings of haplotypes and to determine which haplotype or group of haplotypes is likely to be responsible for the phenotypic variation observed among the population. It consists in using parsimony methods to build a phylogeny of the haplotypes, and to group haplotypes according to the clades defined by the phylogenetic tree. When applied to a case/control data set, the proportions of cases and controls in different clades are compared. If a clade shows a significantly larger number of cases than the others, one will conclude, first, that there is an association between the disease and one haplotype or a group of haplotypes belonging to the clade, and, second, that the mutations defining the clade containing an excess of cases are good candidates to be functional gene polymorphisms involved in the disease susceptibility.
The cladistic analysis relies for a large part on the reconstruction of an accurate phylogenetic tree, but recombination is known to bias phylogenetic reconstruction processes [12]. The recent discovery of the haplotype block structure of the human genome [13] now provides an interesting framework for cladistic methods. Indeed, haplotype blocks define regions in which the recombination rate is quite low. Moreover, once a block is found to be associated with a disease, it will not be suitable to use classical methods based on recombination to fine map susceptibility loci. Haplotype phylogenies being based on the history of mutations may then help to identify disease susceptibility loci.
The cladistic method was first described in a series of five articles [11,14-17] and applied in different case-control studies focusing either on quantitative or qualitative data. For example, Haviland et al. used a cladistic analysis to study the association between the apolipoprotein AI-CIII-AIV and plasma lipid, lipoprotein and apolipoprotein levels [18]. Keavney et al. [19] used cladograms to localize the sites that significantly influence Angiotensin-I Converting Enzyme (ACE). Zhu et al. [20] worked on quantitative data simulated for the twelfth Genetic Analysis Workshop (GAW). Using regression analysis and analysis of variance (ANOVA), they were able to find a short region containing the simulated mutation. Wang et al. [21] used a nested linear model to analyze the association between ApoA4 haplotypes and plasma lipid level in the cladistic framework. Among the studies that consider discrete data is the one by Kittles et al. [22] who tested the association between haplotype variations on the Y chromosome and alcohol dependence and related personality traits. Lobos and Todd applied the same cladistic method to four RFLPs in the tyroxine hydroxylase gene [23], and to five SNPs in the dopamine receptor D2 gene [24]. Darlu and Génin [25] applied the method to the GAW 12 simulated data and were able to identify some of the disease susceptibility sites. For a more detailed review on the subject, see [26].
More recently Seltman et al. [27] developed a method that can be applied on family-based data. They proposed a test, the ET-TDT, that combines the transmission disequilibrium test (TDT) and the use of unrooted phylogenetic trees to group haplotypes. They further extended their method to the analysis of qualitative and quantitative data from case-parent trios or population-based studies [28]. Finally, an alternative method where phylogenetic trees are reconstructed by a distance method was proposed by Durrant et al. [29] and implemented in the software CLADHC.
From these different examples, cladistic methods appear to be innovative methods to detect an association between a candidate gene and a disease and to localize disease susceptibility sites. However, the validity and the power of these methods to detect association have only been tested in a very limited number of situations (fixed pattern of linkage disequilibrium, fixed phylogenetic tree) [27,29]. In this paper, we develop a new cladistic test (CT), based on the analysis of a rooted tree, which allows to make hypotheses about functional polymorphisms that are involved in the susceptibility to the disease. Through simulations on ten different tree topologies, we evaluate the conditions in which this cladistic method is efficient and compare it to other methods. Finally, we apply this method to a real data set concerning Crohn disease and the CARD15 gene [30].
Results
Association test
As detailed in the method section, four different tests are performed: a single locus allele-based test referred to as SbST (Site by Site Test), an haplotype-based test referred to as HT (Haplotypic Test), a test based on haplotype phylogenies referred to as CT (Cladistic Test) and a test based on the clustering of haplotypes described by Durrant et al. [29] and referred to as CLADHC. To compare their respective power to detect an association, simulations were performed under three disease models involving one (model 1) or two (model 2 and model 3) susceptibility sites for ten different tree topologies.
Results for model 1 are presented in Table 1 and 2. When the susceptibility site is included in the studied SNPs (Table 1), SbST is the most powerful test for all trees but one (tree 8) (between 99.1% and 99.5% depending on the tree, 99.35% on average), while the other tests have a weaker power (92.9%, 93.7%, and 91.2%, on average, for CT, HT, and CLADHC respectively). CT and CLADHC have almost the same average type I error, slightly but significantly lower than the type I error of HT and SbST. In these simulations, as the type I errors cannot be fixed a priori, powers may be difficult to compare. However, if the type I errors of CT and CLADHC were increased, their power would also be increased and, consequently, the difference in power with HT would be even more pronounced and the difference in power with SbST would be more reduced. In the trees showing comparable type one error (Trees 1, 5, 7), the power of SbST is clearly higher than the power of CT. When the susceptibility site is removed (Table 2), the performances of the four tests are, on average, similar (about 89%), CT being the most powerful test for four trees, SbST for four other trees, HT and CLADHC for one tree each. However, the type I errors being slightly different, by adjusting them one expects that CT and CLADHC could be on average, slightly more powerful than HT and SbST.
Table 1 Power to detect an association, one susceptibility site simulated and included in the analysis
Tree CT CLADHC HT SbST
1 96.4 (3.3) 88.9 (3.3) 91.1 (5.1) 99.3(3.4)
2 99.0 (4.4) 95.7 (4.1) 91.3 (6.0) 99.5(5.3)
3 86.0 (2.5) 91.1 (4.7) 91.2 (4.6) 99.3(4.4)
4 96.3 (3.8) 95.6 (2.9) 91.5 (4.2) 99.3(4.6)
5 88.8 (4.1) 95.3 (3.3) 90.4 (4.7) 99.1(4.6)
6 84.5 (3.5) 88.8 (2.7) 90.7 (4.4) 99.5(4.4)
7 97.4 (4.0) 96.3 (3.7) 91.9 (4.8) 99.2(4.3)
8 99.7 (3.2) 98.5 (2.4) 91.2 (4.9) 99.4 (4.7)
9 88.1 (3.5) 94.0 (4.4) 91.3 (4.7) 99.4(4.3)
10 92.5 (2.6) 93.0 (2.9) 91.3 (4.7) 99.5(3.6)
Average 92.9 (3.5) 93.7 (3.4) 91.2 (4.8) 99.35(4.4)
Std dev.a 5.63 (0.62) 3.24 (0.76) 0.41 (0.49) 0.13 (0.54)
Sample size: 100 cases and 100 controls, 1000 replicates, penetrance vector: [0.03;0.06;0.3], frequency of the susceptibility allele: 0.205 ± 0.005. The corresponding type I errors are indicated in italics within brackets. For each tree, the method giving the best result is underlined. CT: Cladistic Test, CLADHC: test developed by Durrant et al. [29], HT: Haplotypic Test, SbST: Site by Site Test.
a Standard deviation
Table 2 Power to detect an association, one susceptibility site simulated and removed from the analysis
Tree CT CLADHC HT SbST
1 94.8 (3.8) 89.1 (3.5) 91.2 (5.6) 89.5 (3.9)
2 94.0 (3.8) 92.7 (4.1) 87.6 (5.6) 98.5 (5.3)
3 79.3 (3.2) 88.9 (4.7) 86.2 (4.7) 94.2 (4.1)
4 88.7 (2.3) 85.7 (3.1) 87.8 (4.6) 93.6 (4.4)
5 85.6 (4.3) 94.4 (4.1) 90.5 (4.5) 94.0 (4.1)
6 78.6 (3.0) 81.6 (3.3) 88.0 (4.2) 67.0 (4.2)
7 92.4 (3.8) 90.5 (3.7) 87.8 (5.2) 92.7 (4.0)
8 99.7 (3.0) 98.6 (2.8) 91.2 (4.7) 99.6 (4.5)
9 91.9 (3.7) 89.2 (4.5) 91.2 (4.8) 89.1 (4.1)
10 88.8 (2.9) 82.8 (3.0) 81.3 (4.1) 79.1 (3.5)
Average 89,38 (3.4) 89.35 (3.7) 88,28 (4.8) 89,73 (4.2)
Std dev.a 6.71 (0.6) 5.2 (0.6) 3.06 (0.5) 9.81 (0.5)
Sample size: 100 cases and 100 controls, 1000 replicates, penetrance vector: [0.03;0.06;0.3], frequency of the susceptibility allele: 0.205 ± 0.005. The corresponding type I errors are indicated in italics within brackets. For each tree, the method giving the best result is underlined. CT: Cladistic Test, CLADHC: test developed by Durrant et al. [29], HT: Haplotypic Test, SbST: Site by Site Test.
a Standard deviation
As expected, the power is higher when the susceptibility site is included than when it is removed. In this latter case, the power depends on the degree of linkage disequilibrium (LD) between the susceptibility site and the other sites as expressed by the maximum value of LD, referred to as LDmax. Moreover, since the pattern of LD can be different from one tree to another, one expects more differences in power between trees when the susceptibility site is removed. Indeed the standard deviation of the power is larger in this case. This standard deviation is also particularly large for SbST (σ = 9.81). This test, being an allele-based test, is more influenced by LD than the three others tests that are haplotype-based tests, as proved by the high positive correlation observed between the power of SbST to detect association and the LDmax (Spearman rank correlation ρ equals 0.851, p-value < 0.01). For CT and CLADHC, Spearman rank correlations are not significant (p > 0.1) confirming that LD has a lesser impact on these two tests. Therefore, the high standard deviations observed for these two tests are probably more related to the phylogeny of haplotypes than to the linkage disequilibrium.
The results for model 2 and model 3, differing by the values of the penetrance vector, are presented in Table 3 and in Table 4 respectively. There is no real difference in power between the four tests for model 2 (about 97%). For model 3, the power of the four tests is approximately half the power for model 2 owing to the reduced value of the penetrance for the genotype associated to the highest risk in this model. In this case, SbST and CT are, on average, the most and the less powerful test respectively
Table 3 Power to detect an association for two susceptibility sites simulated under model 2
Model 2
Tree CT CLADHC HT SbST
1 97.8 (3.7) 99.3 (3.8) 97.7 (5.0) 99.1 (6.9)
2 95.1 (3.6) 97.7 (2.9) 97.9 (5.6) 95.8 (4.3)
3 94.2 (4.9) 99.4 (4.9) 97.9 (5.1) 98.6 (4.9)
4 97.6 (4.6) 97.8 (4.6) 97.8 (5.5) 98.6 (4.6)
5 98.5 (5.3) 99.5 (4.5) 98.9 (5.7) 98.2 (7.4)
6 98.9 (4.4) 97.9 (3.9) 98.5 (5.7) 96.9 (6.6)
7 93.0 (5.1) 93.5 (4.6) 96.9 (5.6) 95.5 (5.2)
8 95.2 (6.1) 99.0 (5.3) 98.2 (6.2) 95.4 (4.2)
9 96.7 (3.6) 97.3 (3.1) 97.6 (4.1) 97.7 (4.0)
10 99.9 (4.5) 99.5 (4.0) 98.2 (60.) 99.8 (5.8)
Average 96.7 (4.6) 98.06 (4.2) 97.96 (5.45) 97.56 (5.4)
Std dev.a 2.24 (0.8) 1.83 (0.8) 0.54 (0.6) 1.58 (1.2)
Sample size: 200 cases and 200 controls, 1000 replicates, penetrance: 0.9 for the homozygotes carrying the two susceptibility alleles, 0.3 for the other genotypes. The corresponding type I errors are indicated in italics within brackets. For each tree, the method giving the best result is underlined. CT: Cladistic Test, CLADHC: test developed by Durrant et al. [29], HT: Haplotypic Test, SbST: Site by Site Test
a Standard deviation
Table 4 Power to detect an association for two susceptibility sites simulated under model 3
Model 3
Tree CT CLADHC HT SbST
1 40.7 (4.7) 54.0 (4.5) 42.0 (5.9) 47.5 (4.7)
2 31.7 (3.4) 32.7 (3.9) 43.0 (5.9) 45.8 (5.3)
3 26.8 (4.2) 47.9 (4.4) 40.7 (6.4) 45.2 (3.5)
4 34.8 (4.8) 39.2 (4.7) 38.9 (7.0) 47.0 (4.4)
5 41.5 (5.6) 49.7 (4.7) 44.2 (6.6) 37.2 (4.6)
6 42.0 (3.6) 34.8 (4.7) 42.4 (5.6) 41.3 (5.3)
7 28.6 (5.2) 32.1 (4.7) 41.6 (6.4) 39.9 (4.3)
8 33.2 (4.3) 47.2 (4.0) 42.9 (6.1) 37.7 (4.0)
9 33.5 (4.4) 39.1 (4.1) 41.2 (7.0) 48.5 (5.3)
10 65.6 (6.6) 48.1 (4.1) 42.1 (7.8) 56.9 (4.2)
Average 37.84 (4.7) 42.48 (4.4) 41.9 (6.5) 44.7 (4.6)
Std dev.a 11.07 (0.9) 7.84 (0.3) 1.45 (0.7) 5.94 (0.6)
Sample size: 200 cases and 200 controls, 1000 replicates, penetrance: 0.6 for the homozygotes carrying the two susceptibility alleles, 0.3 for the other genotypes. The corresponding type I errors are indicated in italics within brackets. For each tree, the method giving the best result is underlined. CT: Cladistic Test, CLADHC: test developed by Durrant et al. [29], HT: Haplotypic Test, SbST: Site by Site Test
a Standard deviation
Localization of the susceptibility site(s)
The efficiency of SbST, CT and CLADHC to localize the susceptibility site(s) when it is included among the SNPs is presented in Figure 1 and 2. The efficiency of CT is plotted against the efficiency of SbST or CLADHC. To correctly interpret these figures, it has to be noted that the criteria used to compare the methods are not strictly identical. Indeed, the identified SNP is always unambiguously detected by the SbST method, since this is the site giving the most significant chi-square and two chi-squares are never exactly identical. On the other hand, the susceptibility site may not be the only one detected by CT because two or more sites could have the same values of the criteria (Vi, see the Methods section). However, in our simulations, the susceptibility site is the only one detected in from 80% (for 1 tree) to 100% (for 5 trees) of the replicates. When the susceptibility site is not found alone, it is almost always found with only one other site, rarely with two other sites (<0.5% of the replicates).
Figure 1 Comparison of the efficiency to localize the susceptibility site between CT, and SbST or CLADHC. The efficiency to localize the susceptibility site is measured by the percentage of replicates in which the simulated susceptibility site is either uniquely detected or detected among other putative sites. black circles: comparison of CT and SbST, crosses: comparison of CT and CLADHC. Each symbol corresponds to one of the ten tree topologies.
Figure 2 Comparison of the efficiency to localize the two susceptibility sites between CT and SbST. The efficiency to localize the two susceptibility sites is measured by the percentage of replicates in which the two sites are detected (black circles) or at least one of the two sites (white circles) Each symbol corresponds to one of the ten tree topologies. (A): penetrance 0.9 for homozygotes carrying the two susceptibility alleles and 0.3 for all other genotypes; (B): penetrance 0.6 for homozygotes carrying the two susceptibility alleles and 0.3 for all other genotypes.
For model 1 (Figure 1), CT is slightly less efficient than SbST (for 9 trees out of 10) and more efficient than CLADHC (for all 10 trees). For SbST, we note a high negative correlation between the efficiency to localize the susceptibility site and the LDmax between the susceptibility site and the other sites (Spearman rank correlation ρ equal -0.88 with a p-value of 0.008). It shows that the presence of a site in relatively high LD with the susceptibility site disturbs the localization process, increasing the uncertainty of the susceptibility site's identification. Interestingly, there is no such statistically significant correlation with CT and CLADHC (p > 0.08), due to the fact that these last two tests use both the information on the whole haplotypes and on their history through the tree reconstruction. The presence of sites in high LD with the susceptibility site does not prevent these two methods from localizing correctly the susceptibility site.
For model 2 and model 3, (Figure 2A and 2B respectively), CT is more or at least as efficient as SbST to localize the two sites, whatever the penetrance model. For the detection of at least one of the two sites, we can observe that, whatever the tree, CT is always more efficient than SbST under model 2, whereas this is only true for 6 out of the 10 trees under model 3.
Application to CARD15/NOD2 polymorphisms and Crohn disease
The reconstruction of the phylogenetic tree of the 33 haplotypes leads to a very high number of equally parsimonious trees. One thousand of them were retained and analyzed. In table 5, for the two rooting methods mfH and consH, the SNPs are ranked from the least to the most significant (based on the Vi parameter, see the Methods section). Association is detected with CT (pmfH = 2 × 10-5, pconsH = 3 × 10-5) and SNP 8 is selected as potential susceptibility site. If haplotypes carrying the susceptibility allele at SNP 8 are removed, an association can still be detected (pmfH = 4 × 10-5, pconsH = 3 × 10-5) and SNP 12 is identified as potential susceptibility site. When removing haplotypes with the susceptibility allele at SNP 12, there is still a remaining association (pmfH = 8 × 10-5, pconsH = 3 × 10-5) and depending on the rooting method either SNP 13 (with consH) or SNP 9 (with mfH) are retained. When haplotypes with the susceptibility allele at SNP 13 are removed, the association test is not significant (pmfH = 2.9 × 10-1, pconsH = 1.1 × 10-1). When haplotypes with the susceptibility allele at SNP 9 are removed, the association test is significant (pmfH = 2 × 10-5, pconsH = 5 × 10-5) and the identified site is SNP 13 for both rooting method. In the end, the combination of SNP 8, SNP 12 and SNP 13 is the most parsimonious combination that can explain the susceptibility to the disease. Moreover, we can note that these 3 SNPs are those showing the highest Vi on the whole data set. So, we finally have identified three SNPs involved in the susceptibility to Crohn's disease.
Table 5 Cladistic analysis of Crohn's data 1000 equiparsimonious trees are studied. SNPs are ranked from the least to the most significant. In bold, the presumed susceptibility sites previously identified by Hugot et al. [30].
least significant --------> most significant
mfHa SNP 5 SNP 9 SNP 6 SNP 7 SNP 13 SNP 12 SNP8
consHb SNP 9 SNP 5 SNP 6 SNP 7 SNP 13 SNP 12 SNP8
a Rooting on the most frequent haplotype
b Rooting on a consensus sequence
Discussion
In this paper, we have presented a method to perform phylogeny-based nested haplotype analysis of case/control data and introduced the cladistic test (CT). We have shown by simulations that the CT test is approximately as powerful to detect an association as a test that compares haplotype distributions in cases and controls with no prior grouping. However, a major advantage of CT towards other haplotypic tests is the possibility of making inferences on potential susceptibility sites. Indeed the method of parsimony used to build the phylogeny allows the reconstruction of character state changes on the tree and thus the identification of the most likely susceptibility sites. Finding the polymorphisms responsible for the susceptibility to a disease is an important issue in genetic epidemiology and in the past few years, different methods have been proposed that use linkage disequilibrium to fine-map candidate genes and to localize disease mutations ([31,32] and [33] for example) These methods are based on the fact that a disease variant arises on a particular haplotype, the haplotype and the disease thus being initially associated. Then, over time, this association is broken by recombination and only a small region of the ancestral haplotype is preserved around the disease variant. In such models, recombination is the event of interest. Other parameters such as mutations can be integrated in the models, but they are considered as nuisance parameters. The cladistic test developed here is different in the sense that it is based on the reconstruction of the evolutionary history of the mutations that occur to form the haplotypes. Contrary to the other fine-mapping methods, the event of interest is mutation, and recombination is a nuisance parameter. Through the simulation study, we have shown that this test is a powerful tool to suggest etiological SNPs. This is also illustrated here on Crohn disease since the cladistic test was able to correctly identify the 3 sites within the CARD15 gene that are already reported to be involved in the disease susceptibility [30].
The cladistic test requires the building of a phylogeny of the different haplotypes present in the sample. Different methods are available to build haplotype phylogenies: distance methods, parsimony methods and maximum likelihood (ML) methods. A parsimony method was chosen here because it allows the reconstruction of apomorphies that can be used to define potential sites involved in the disease susceptibility and because it runs faster than ML methods, thus allowing a simulation study. We have compared CT with another clustering method, CLADHC, a distance-based method that also differs from CT in the statistical analysis (CLADHC performs regression analysis, CT is based on chi-square tests). We have shown that the power of these two tests to detect association is quite similar, CT being slightly more powerful when one site is simulated, and CLADHC when two sites are simulated. For the localization of the susceptibility site, the efficiency of the two methods is difficult to compare because CT directly localizes the site on short sequences while CLADHC localizes a window containing the susceptibility site on longer sequences. The two test should thus be used in different situations. Nevertheless CT appears to be more efficient in our simulation conditions
In the phylogeny reconstruction, one is faced to different problems. The first one is the choice of the ancestral sequence to root the phylogeny. With real data, the ancestral sequence is usually not known, unless at least two outgroups can be postulated (in the parsimony context). In the absence of ancestral sequences, hypotheses have to be made, and they are numerous, like taking the most frequent haplotype, but this haplotype could be different from one population to an other or from one sampling to another, and this most frequent haplotype may not have a significantly different frequency from the next most frequents. Or one can take the consensus haplotype, but this sequence may not be observed in the sample, or not be among the most frequent sequences. In this study, our strategy was to consider the uncertainty of the ancestral sequence as a nuisance parameter, since our goal was not primarily to focus on this problem and because we must be in the same situation for all the performed simulations. Extensive further simulations will be needed to assess the properties of the different rooting methods. However, several ancestral hypotheses should be considered, discussed, and tested on real data, as we have done for the Crohn data. Second, the presence of recombinations would restrict the use of phylogenetic reconstruction. Indeed, phylogenetic reconstruction is known to be biased by recombinations [12] in a manner depending on how and when the recombination events occur in the tree. This context led us to simulate the history of mutations along the haplotypes without introducing recombinations between haplotypes. However, because in our method the reconstructed tree has not to represent the exact history of the haplotypes, but only gives a way to cluster them in an appropriate way, we believe that our method can tolerate some low degrees of recombination, as it is probably the case for the Crohn data. Further simulations would however be required to better assess this point. Third, the choice of the way characters are optimized on the tree is another important point in cladistic analysis. Two classical options can be used to optimize the character state changes along the tree: deltran, (delayed transformation) that favors convergences or acctran(accelerated transformation) that favors reversions. In this paper, only the results performed with the deltran option are presented. Simulations (one susceptibility site) have also been performed with the acctran option. For the association detection, the results are very similar to those obtained with deltran showing that this parameter does not influence the power of the CT method to detect association in our simulation conditions. For the localization of the susceptibility site, the results are different. The method is more efficient with the deltran option than with the acctran option for eight trees out of ten, it is less efficient for one tree and the results are equivalent for the last tree. It is partly due to to the uncertainties of the character S and to the frequency of the disease susceptibility allele. When the frequency of the susceptibility allele is low, as in our simulations, and when S is coded "?" in some nodes of the tree, one expects the change of S from 0 to 1 to occur later in the tree, and the delayed option (deltran) will then be more appropriate. Conversely, when the frequency of the disease is large, the change of S from 0 to 1 has more chances to occur earlier in the tree since the S mutation can then include more cases, and the accelerated option (acctran) will be more appropriate. However, when analyzing a real data set, it is advisable to compare the results obtained with both options.
The variability of the results obtained with the cladistic method is due for a minor part to the LD between the susceptibility site(s) and the other sites and for the major part to parameters specific to the tree. Among these parameters, the position of the mutation in the tree (near the root or the leaves, sample size of the clades near the mutations...) has already been reported to have an influence on the power of cladistic methods to detect association [27]. Apart from the position of the mutation, the presence of sites that co-mutate with the susceptibility site, the degree of multiple mutations of the susceptibility site in the tree, and the existence of one or more reversions for the susceptibility site influence the power of the cladistic test to detect an association, and they have an even greater impact on the efficiency of the cladistic test to localize the susceptibility site. As all these factors are not independent, the evaluation of their own effects remains problematic.
The four methods compared here (CT, HT, SbST and CLADHC) suppose that haplotypic data are available, which is not usually the case. The most likely haplotypes for an individual have to be reconstructed using numerical methods (for a review of these methods, see [34,35]). The availability of familial data may help to determine the phase of the markers and then, to obtain the most likely haplotypes by using the genetic information of the two parents. However, even when these familial data are not available, the numerical methods have been shown to be very efficient to reconstruct haplotypes, except for rare haplotypes that may either be missed or falsely created. In this work, since we choose to focus on the comparison between several methods, the problem of haplotype inference is ignored. Moreover, as the four studied methods are all based on already known or inferred haplotypes carried by the individuals, the uncertainty due to the haplotype inference should not play differently from one method to another. Further extension of the CT method will take this uncertainty into account by using, for example, likelihood-based tests.
Conclusion
In conclusion, as proved by our simulations and the Crohn example, the use of phylogenies to group haplotypes by clades and the nested analysis of case-control data on the basis of these clades turns out to be an interesting and complementary strategy for the genetic study of multifactorial diseases, especially to pinpoint the sites that are likely to be involved in disease susceptibility among the different markers identified within a gene.
Methods
Principle of the method
The material on which the method is based is a sample of haplotypes composed of a combination of SNPs, each haplotype being labeled either as control or as affected depending on the phenotype of the individual. After building the phylogenetic tree of these different haplotypes, a series of nested homogeneity tests are performed to detect differences in the distribution of cases and controls in the different clades. Once an association is detected, a new character is defined according to the proportion of cases carrying an haplotype. Then, it is optimized on the tree and the sites that significantly co-mutate with this new character are putative susceptibility sites for the disease.
Simulation study
To test the power of this method to detect an association and its efficiency to precisely localize the susceptibility site, we performed the following steps : i) simulation of the haplotypes and choice of the susceptibility site(s) (one or two susceptibility sites are considered) ; ii) attribution of a status (case or control) to these haplotypes taking into account the genetic model of the disease; iii) reconstruction of the phylogeny of haplotypes and inference of the character state changes along the branches of the tree; iv) association test: nested analysis of the case/control ratio in the clades; v) localization of the susceptibility site using the equiparsimonious (ie, all the trees that have the minimum number of character state changes) ; vi) estimation, by simulations, of the power to detect the association between haplotypes and the disease and comparison with other methods; vii) estimation of the efficiency to localize susceptibility sites and comparison with other methods.
Haplotype simulation
24 different haplotypes are simulated using the TREEVOLVE software (version 1.32) [36]. An ancestral haplotype sequence of 20 sites is randomly produced, a guide tree is generated using the coalescent model without recombination and the evolution of this ancestral sequence along the tree is simulated to obtain a sample of 24 different haplotypes. Since TREEVOLVE can only simulate the evolution of DNA sequences (4 nucleotides) and not the evolution of bi-allelic markers, we set the frequencies for bases A and T to very low values (A = T = 0.001 and G = C = 0.498) in order to obtain an ancestral sequence composed only of G and C, as an equivalent of SNPs coded by 0/1 character states. The mutation rate is set to 2 × 10-6, and the substitution rates are chosen so that only G-C transversions could occur: A - C = 0.001, A - G = 0.001, A - T = 0.001, C - T = 0.001, G - T = 0.001, G - C = 0.995. No heterogeneity in the substitution rate among sites is specified. The population size was set to 100,000 and its growth was stationary with no subdivision. Once the haplotypes are obtained by simulation, the susceptibility sites are chosen among the 20 sites. For the simulations with only one susceptibility site, the program picks up the first site in the sequence having a minor allele frequency (p) in the sample of haplotypes within the range F <p <F + 0.01 where F is a predefined allele frequency (in our simulations, F = 0.20). For two simulated sites, the program picks up the first two simulated sites verifying a user-defined constraint. In our simulations, the two sites are chosen such that f (A1B1) = f (A1B2) = f (A2B1) = f (A2B2) = 0.25, A1 and A2 being the two alleles at the first site and B1 and B2, the two alleles at the second site. When no site is found satisfying these conditions, a new set of haplotypes is simulated until the required conditions are obtained.
This entire procedure is repeated ten times to generate ten different data sets. The pairwise linkage disequilibrium (r2 measure, mean values for the 1000 replicates) and the tree topologies corresponding to these ten data sets are provided as Additional file 1 and 2.
Attribution of disease status
To generate the genotypes of each individual, pairs of haplotypes are sampled at random with replacement and the disease status (case or control) is determined by his genotype at the susceptibility site(s) and by the penetrances. In our simulations, three disease models are studied, involving either one susceptibility site (model 1) or two interacting susceptibility sites (model 2 and model 3). The first model is the disease model described in Bourgain et al. [37] that roughly corresponds to the effect of ApoE4 in Alzheimer's disease [38]. We set the penetrance of the three genotypes DD, Dd and dd to respectively PDD = 0.03, PDd = 0.06, Pdd = 0.30, d being the disease susceptibility allele. For model 2 and model 3, an at-risk haplotype formed by the combination of the alleles A2 at the first locus and B2 at the second locus is defined. The penetrance associated to the genotype A2B2A2B2 is set to 0.9 for model 2 and to 0.6 for model 3. All the other penetrances are set to 0.3 for both models.
The sampling process is carried on until N cases and N controls are obtained (N = 100 or 200 in our simulations, depending on the number of simulated susceptibility sites). This constitutes a replicate. As the haplotypes are sampled randomly from the set of 24 different haplotype, they are almost equi-frequent in the sample of cases and controls, and their frequencies are close to .
Phylogeny of haplotypes
All the different haplotypes are used to build a phylogenetic tree by a parsimony method which consists in choosing the tree that minimizes the number of mutation events [39]. The PAUP software (version 4.0b10 [40]) is used to reconstruct the tree. A heuristic search is performed, using stepwise addition and TBR (tree bisection and reconnection). All sites are equally weighted, and changes from allele 0 to allele 1 and from allele 1 to allele 0 are equally allowed for all sites, including the susceptibility site (unordered option). Among the list of all parsimonious trees, only the first one obtained is used for the association test, for computation time reasons and because we found that identical results are obtained for more than 98% of the equiparsimonious trees (data not shown). For the localization of susceptibility sites, all the equiparsimonious trees (or up to 100 different trees if there are too many equiparsimonious trees) are analyzed. The trees are rooted using the real ancestor obtained with TREEVOLVE. The character states are inferred along the branches by using the classical option deltran (delayed transformation), but acctran (accelerated transformation) was also investigated.
Association test
Starting from the root of the tree, series of nested homogeneity tests comparing the number of cases and controls in different clades are performed. The principle of the method is explained in Figure 3. Briefly, at each level of the tree, homogeneity in the distribution of cases and controls is tested among all the n clades defined at this level. If the test is significant, an association is detected and the analysis ends. If the test is not significant, one homogeneity test is performed between all the sub-clades descending from the n clades.
Figure 3 Description of the nested clade analysis. (A) shows the homogeneity test performed at level k (between clades C1 and C2). If it is not significant (B), a test will be performed at the following level (k+1), between all the sub-clades descending from clades C1 and C2, i.e between clades C1.1, C1.2, C2.1 and C2.2 (3 degree of freedom). If it is significant the analysis ends because an association is detected.
P-values of the homogeneity tests are calculated by Pearson chi-square tests except when only two clades are compared in which case a Fisher exact test is performed, and except when more than two clades are tested and the sample size is less than four in a category. In this latter case p-values are estimated by permutation tests.
The influence of the LD on the power of the different tests is assessed by using the r2 measure of LD.
Localization of the susceptibility sites
For each replicate, several equiparsimonious trees may exist. We will analyze the T first equiparsimonious given by PAUP, T being limited to 100 for computation time reasons. For a tree t, a new character S is allocated to each haplotype h. The state of S is "0", "1" or "?" depending on the proportion (ph) of cases carrying the haplotype h compared to the proportion p0 of cases in the whole sample.
if , S is coded "0" (high number of controls);
if , S is coded "1" (high number of cases);
else, S is coded "?" (missing data).
with nh being the number of individuals carrying the haplotype h.
This character S is optimized on the T equiparsimonious trees using PAUP and the deltran option. For each site i, let and be the observed number of times each transition (0→1 for and 1→0 for ) co-mutates with a 0→1 change of the character S on tree t. Let and be the expected number of co-mutations on tree t under the hypothesis of a random distribution of the mutations on tree t and an equal probability of mutation on each branch.
where (resp. ) is the number of 0→1 (resp. 1→0) transitions of the site i on tree t;
st is the number of 0→1 transition of the character S on tree t;
bt is the number of branches of tree t.
Then, for each site i on tree t, we measure the correlated evolution of the site i and the character S, by defining (resp. ) as follow:
then, for the T equiparcimonious trees, we define (resp. ) as follow:
Finally, Vi is defined as the max between and . The site or the two sites corresponding to the highest Vi are selected as putative susceptibility sites
Estimation of power and efficiency
For each of the ten samples of 24 haplotypes simulated along the ten different tree topologies, the process detailed above (attribution of disease status, phylogenetic reconstruction, association test and localization of the susceptibility site) is repeated 1000 times to obtain 1000 replicates, each of them including N cases and N controls. The power to detect the association is measured by counting the proportion of replicates in which a significant heterogeneity in the distribution of cases and controls is detected between clades. The efficiency of CT to localize the true susceptibility site is simply evaluated as the number of times, among the 1000 simulations, the true susceptibility site is among the detected sites. When two susceptibility sites are simulated, we evaluate the number of times the two sites are detected and the number of times at least one of the two sites is detected.
The test using the cladistic method (CT) is compared to three other association tests: i) a haplotypic test (HT) that compares the haplotype distributions in cases and controls: if h different types of haplotypes are observed, a chi-square test with h - 1 degree of freedom (df) is performed. As with the CT test, when sample sizes are small, a permutation procedure is used to perform the chi-square test. This HT test is only used to test for association and not to localize the susceptibility sites. ii) An allelic test, referred to as Site by Site Test (SbST), that compares the allele distributions in cases and controls at each site by a chi-square: if the number of sites is s, then s chi-squares, each with one df, are performed. The site or the two sites that give the most significant results are proposed as susceptibility sites. iii) A test based on CLADHC, the program developed by Durrant et al. [29]. In this test, the data set is analyzed by overlapping windows sliding along the haplotypes. In each window, a tree is reconstructed using a distance method, and a regression analysis is performed at each level of the tree (nested analysis). The level of the tree that maximizes the evidence of disease marker association in the likelihood-ratio test is selected. For each window, the program also provides a significant threshold calculated using the Bonferroni correction. In our simulations, a window size of 6 is selected. We consider the association as detected when at least one of the windows is significant. Concerning the localization of the susceptibility site, CLADHC can only find a window containing the susceptibility site, but not the susceptibility site itself. Therefore, we only use CLADHC in the case of one susceptibility site and we consider the localization as correct when the window with the maximum value of the statistic contains the susceptibility site.
For CT, SbST and CLADHC, we are confronted to a problem of multiple testing. When a real data set is analyzed, a permutation procedure can be used to estimate p-values of the association tests that are corrected for multiple testing. This procedure is very time-consuming and cannot be used on the simulations we have performed here. As an example, the 100,000 repetitions for the Crohn data run in about 24 hours on a Pentium III, 930 MHz, 512 Mo of RAM. Therefore, for SbST and CT, we estimate the nominal type I error required to obtain a global type-one error of 5% by a simulation under the null hypothesis of no association between the studied sites and the disease (5000 replicates). We found that for the different simulation conditions studied here, these nominal errors are equal to 1% for CT and varies from 0.2 to 0.4% for SbST. For the analysis with CLADHC, the program provides a significant threshold calculated using Bonferroni correction. As the Bonferroni correction is very conservative, to obtain similar type I errors with CLADHC as with CT, nominal type I errors were set to values varying from 15 to 17% for simulations with one susceptibility site and from 20 to 25% for simulations with two susceptibility sites.
Analysis of real data on Crohn disease
The data set is described in a paper of Hugot et al. (2001) [30] and includes 232 nuclear families with two affected children and their parents genotyped for 13 SNPs in the CARD15/NOD2 gene. Haplotypes were reconstructed in these families using GENEHUNTER 2.0b[41]. In each family, one affected child is selected at random to create the case sample (his two haplotypes are labeled cases). The control sample is formed with the parental haplotypes non transmitted to the selected children. The phylogenetic reconstruction assumes that no recombination has occurred between the SNPs. To determine if this was true for the different SNPs tested here or at least for a subset of them, linkage disequilibrium (LD) is estimated between all the SNPs. From the pairwise LD, a group of 7 SNPs (5, 6, 7, 8, 12, 9 and 13) can be identified as forming a block in strong LD among which no or very few recombinations are likely to have occurred (see Additional file 3). Interestingly, this same block of 7 SNPs was described by Vermeire et al. [42] in the CARD15/NOD2 gene. Only these 7 SNPs that form 33 different haplotypes are used in the cladistic analysis. The phylogenetic trees are reconstructed using the same parameters as in the simulations. However here, contrary to the simulations, the ancestral sequence being not known, two different analysis are performed using as ancestral sequence either the most frequently observed haplotype in our sample (mfH) or a consensus sequence formed by the combination of the most frequent alleles at each SNP (consH). For the association test, p-values are estimated on the first equiparsimonious tree obtained by PAUP, using an algorithm similar to the one described in a paper of Becker and Knapp (2004) [43]. This permutation process corrects for multiple testing in a lesser conservative way than the Bonferroni correction because it takes into account the dependency between the tests. For the localization, among all the equiparsimonious trees, 1000 of them are retained and analyzed with CT.
Authors' contributions
CB perfomed the simulation analyses, contributed to the conception of the study, to the elaboration of the algorithm and wrote the manuscript. VD contributed to the elaboration of the algorithm. J-PH provided the CARD15 data. PD and EG contributed to the design and to the conception of the study and to the manuscript preparation.
Supplementary Material
Additional File 1
Average pairwise linkage disequilibrium for the 10 simulated date sets. The average pairwise LD (over 1000 replicated) is calculated using the r2 measure for each of the 10 tree topologies (T1 to T10). The matrices are plotted with GOLD[44].
Click here for file
Additional File 2
Tree topologies of the 10 simulated date sets
Click here for file
Additional File 3
Pairwise linkage disequilibrium for the Crohn data. (A) shows the pairwise linkage disequilibrium (LD) calculated with the D' measure. (B) shows the LD calculated with the r2 measures. The matrices are plotted with GOLD [44]. A high degree of LD can be observed. The differences between the r2 and the D' values are explained by the difference in the allelic frequency for the different SNPs.
Click here for file
Acknowledgements
We wish to thank Marie-Claude Babron and two anonymous reviewers for helpful comments and Arnaud Legrand for letting us use one of his perl function. We are also grateful to Habib Zouali and Suzanne Lepage from the fondation Jean Dausset for providing us with Crohn data and to Caroline Durrant for kindly providing us with the software CLADHC. Many thanks to the runtime team from the LaBRI for letting us run a part of our simulations on their cluster.
==== Refs
Collins FS Preparing health professionals for the genetic revolution Jama 1997 278 1285 1286 9333274 10.1001/jama.278.15.1285
Collins FS Brooks LD Chakravarti A A DNA polymorphism discovery resource for research on human genetic variation Genome Res 1998 8 1229 1231 9872978
Schork NJ Fallin D Lanchbury S Single nucleotide polymorphisms and the future of genetic epidemiology Clin Genet 2000 58 250 264 11076050 10.1034/j.1399-0004.2000.580402.x
Zaykin DV Westfall PH Young SS Karnoub MA Wagner MJ Ehm MG Testing association of statistically inferred haplotypes with discrete and continuous traits in samples of unrelated individuals Hum Hered 2002 53 79 91 12037407 10.1159/000057986
Akey J Jin L Xiong M Haplotypes vs single marker linkage disequilibrium tests: what do we gain? European J of Hum Genet 2001 9 291 300 11313774 10.1038/sj.ejhg.5200619
Douglas JA Boehnke M Guillanders E Trent JM Gruber SB Experimentally-derived haplotyes substantially increase the efficiency of linkage disequilibrium studies Nat Genet 2001 28 361 364 11443299 10.1038/ng582
Fallin D Cohen A Essioux L Chumakov I Blumenfeld M Cohen D Schork NJ Genetic analysis of case/control data using estimated haplotype frequencies: application to APOE locus variation and Alzheimer's Disease Genome Res 2001 11 143 151 11156623 10.1101/gr.148401
Tiret L Amouyel P Rakotovao R Cambien F Ducimetière P Testing for association between disease and linked marker loci: a log-linear-mode analysis Am J Hum Genet 1991 48 926 934 2018040
Nielsen DM Ehm MG Zaykin DV Weir BS Effect of two- and three-locus linkage disequilibrium on the power to detect marker/phenotype association Genetics 2004 168 1029 1040 15514073 10.1534/genetics.103.022335
Zhao JH Curtis D Sham PC Model-free analysis and permutation tests for allelic associations Hum Hered 2000 50 133 139 10799972 10.1159/000022901
Templeton AR Boerwinkle E Sing CF A cladistic analysis of phenotypic associations with haplotypes inferred from restriction endonuclease mapping. I. Basic theory and an analysis of alcohol dehydrogenase activity in Drosophila Genetics 1987 117 343 351 2822535
Schierup MH Hein J Consequences of recombination on traditional phylogenetic analysis Genetics 2000 156 879 891 11014833
Gabriel SB Scaffner SF Nguyen H Moore JM Roy J Blumenstiel B Higgins J DeFelice M Lochner A Faggart M Liu-Cordero SN Rotimi C Adeyamo A Cooper R Ward R Lander ES Daly MJ Altshuler D The structure of haplotype blocks in the human genome Science 2002 296 2225 2229 12029063 10.1126/science.1069424
Templeton AR Sing CF Kessling A Humphries S A cladistic analysis of phenotypic associations with haplotypes inferred from restriction endonuclease mapping. II. The analysis of natural populations Genetics 1988 120 1145 1154 3147219
Templeton AR Crandall KA Sing CF A cladistic analysis of phenotypic associations with haplotypes inferred from restriction endonuclease mapping and DNA sequence data. III. Cladogram estimation Genetics 1992 132 619 633 1385266
Templeton AR Sing CF A cladistic analysis of phenotypic associations with haplotypes inferred from restriction endonuclease mapping. IV. Nested analysis with cladogram uncertainty and recombination Genetics 1993 134 659 669 8100789
Templeton AR A cladistic analysis of phenotypic associations with haplotypes inferred from restriction en-donuclease mapping or DNA sequencing. V. analysis of case/control sampling designs: Alzheimer's disease and the Apolipoprotein E locus Genetics 1995 140 403 409 7635303
Haviland MB Kessling AM Davignon J Sing CF Cladistic analysis of the Apolipoprotein AI-CIII-AIV gene cluster using a healthy French Canadian sample. I. Haploid analysis Ann Hum Genet 1995 59 211 231 7625767
Keavney B McKenzie CA Connell JMC Julier C Ratcliffe PJ Sobel E Lathrop M Farrall M Measured haplotype analysis of the angiotensin-I converting enzyme gene Hum Mol Genet 1998 7 1745 1751 9736776 10.1093/hmg/7.11.1745
Zhu X Cooper RS Chen G Luke A Eltson R Localization of the Q1 mutation by cladistic analysis Genet Epidemiol 2001 21 S594 S599 11793744
Wang GQ Pietro MD Roeder K Heng CK Bunker CH Hamman RF Kamboh MI Cladistic analysis of human Apolipoprotein A4 polymorphisms in relation to quantitative plasma lipid risk factors of coronary heart disease Ann of Hum Genet 2003 67 107 124 12675687 10.1046/j.1469-1809.2003.00023.x
Kittles RA Long JC Bergen AW Eggert M Virkkunen M Linnoila M Goldman D Cladistic association analysis of Y chromosome effects on alcohol dependence and related personality traits Proc Natl Acad Sci 1999 96 4204 4209 10097188 10.1073/pnas.96.7.4204
Lobos EA Todd RD Cladistic analysis of disease association with tyroxine hydroxylase : Application to manic-depressive disease and alcoholism Am J Med Genet 1997 74 289 295 9184313 10.1002/(SICI)1096-8628(19970531)74:3<289::AID-AJMG10>3.0.CO;2-K
Lobos E Todd RD Association analysis in an evolutionary context: cladistic analysis of the DRD2 locus to test for association with alcoholism Am J Med Genet 1998 81 411 419 9754627 10.1002/(SICI)1096-8628(19980907)81:5<411::AID-AJMG10>3.0.CO;2-F
Darlu P Génin E Cladistic analysis of haplotypes as an attempt to detect disease susceptibility Genet Epidemiol 2001 21 S602 S607 11793746
Heng CK Low PS Cladistic analysis: its application in association studies of complex diseases Ann Acad Med Singapore 2000 29 313 321 10976384
Seltman H Roeder K Devlin B Transmission/Disequilibrium test meets measured haplotype analysis: family-based association analysis guided by evolution of haplotypes Am J Hum Genet 2001 68 1250 1263 11309689 10.1086/320110
Seltman H Roeder K Devlin B Evolutionary-based association using haplotype data Genet Epidemiol 2003 25 48 58 12813726 10.1002/gepi.10246
Durrant C Zondervan KT Cardon LR Hunt S Deloukas P Morris AP Linkage disequilibrium mapping via cladistic analysis of single-nucleotique polymorphism haplotypes Am J Hum Genet 2004 75 35 43 15148658 10.1086/422174
Hugot JP Chamaillard M Zouali H Lesage S Cézard JP Belaiche J Almer S Tysk C O'Morain CA Gassull M Binder V Finkel Y Cortot A Modigliani R Laurent-Puig P Gower-Rousseau C Macry J Colombel JF Sahbatou M Thomas G Association of NOD2 leucin-rich repeat variants with susceptibility to Crohn's disease Nature 2001 411 599 603 11385576 10.1038/35079107
Lazzeroni LC Linkage disequilibrium and gene mapping: an empirical least-square approach Am J Hum Genet 1998 62 159 170 9490574 10.1086/301678
McPeek MS Strahs A Assessment of linkage disequilibrium by the decay of haplotype sharing with application to fine-scale genetic mapping Am J Hum Genet 1999 65 858 875 10445904 10.1086/302537
Rannala B Reeve JP High-resolution multipoint linkage-disequilibrium mapping in the context of a human genome sequence Am J Hum Genet 2001 69 159 178 11410841 10.1086/321279
Zhao H Pfeiffer R Gail MH Haplotype analysis in population genetics and association studies Pharmacogenomics 2003 4 171 178 12605551 10.1517/phgs.4.2.171.22636
Niu T Algorithms for inferring haplotypes Genet Epidemiol 2004 27 15368348
Grassly NC Rambaut A Treevolve, version 1.32 2000 10988022
Bourgain C Génin E Quesneville H Clerget-Darpoux F Search for multifactorial disease susceptibility genes in founder populations Ann Hum Genet 2000 64 255 265 11409410 10.1046/j.1469-1809.2000.6430255.x
APOE T Alzheimer Disease meta analysis consortium Effects of age, gender and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease J Am Med Assoc 1997 278 1349 1356 10.1001/jama.278.16.1349
Felsenstein J Inferring phylogenies, Sinauer Associates, Inc 2004 chap Chapter one: Parsimony methods 1 18 [ISBN:0878931775].
Swofford DL PAUP Phylogenetic Analysis Using Parcimony. Version 4.0b10 2002 Sunderland, Massachusetts: Sinauer Associates 12504223
Daly MJ Kruglyak L Pratt S Houstis N Reeve MP Kirby A Lander ES Genehunter, version 2.1 2001
Vermeire S Wild G Kocher K Cousineau J Dufresne L Bitton A Langelier D Pare P Lapointe G Cohen A Daly MJ Rioux J CARD15 genetic variation in a Quebec population: prevalence, genotype-phenotype relationship, and haplotype structure Am J Hum Genet 2002 71 74 83 12019468 10.1086/341124
Becker T Knapp M A powerful strategy to account for multiple testing in the context of haplotype analysis Am J Hum Genet 2004 75 561 570 15290652 10.1086/424390
Abecasis GR Cookson WO GOLD-graphical overview of linkage disequilibrium Bioinformatics 2000 16 182 183 10842743 10.1093/bioinformatics/16.2.182
| 15904492 | PMC1173100 | CC BY | 2021-01-04 16:38:18 | no | BMC Genet. 2005 May 18; 6:24 | utf-8 | BMC Genet | 2,005 | 10.1186/1471-2156-6-24 | oa_comm |
==== Front
BMC GenetBMC Genetics1471-2156BioMed Central London 1471-2156-6-301593265010.1186/1471-2156-6-30Research ArticleInferring haplotypes at the NAT2 locus: the computational approach Sabbagh Audrey [email protected] Pierre [email protected] Unité de Recherche en Génétique Epidémiologique et Structure des Populations Humaines, INSERM U535, Villejuif, France2005 2 6 2005 6 30 30 2 2 2005 2 6 2005 Copyright © 2005 Sabbagh and Darlu; licensee BioMed Central Ltd.2005Sabbagh and Darlu; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Numerous studies have attempted to relate genetic polymorphisms within the N-acetyltransferase 2 gene (NAT2) to interindividual differences in response to drugs or in disease susceptibility. However, genotyping of individuals single-nucleotide polymorphisms (SNPs) alone may not always provide enough information to reach these goals. It is important to link SNPs in terms of haplotypes which carry more information about the genotype-phenotype relationship. Special analytical techniques have been designed to unequivocally determine the allocation of mutations to either DNA strand. However, molecular haplotyping methods are labour-intensive and expensive and do not appear to be good candidates for routine clinical applications. A cheap and relatively straightforward alternative is the use of computational algorithms. The objective of this study was to assess the performance of the computational approach in NAT2 haplotype reconstruction from phase-unknown genotype data, for population samples of various ethnic origin.
Results
We empirically evaluated the effectiveness of four haplotyping algorithms in predicting haplotype phases at NAT2, by comparing the results with those directly obtained through molecular haplotyping. All computational methods provided remarkably accurate and reliable estimates for NAT2 haplotype frequencies and individual haplotype phases. The Bayesian algorithm implemented in the PHASE program performed the best.
Conclusion
This investigation provides a solid basis for the confident and rational use of computational methods which appear to be a good alternative to infer haplotype phases in the particular case of the NAT2 gene, where there is near complete linkage disequilibrium between polymorphic markers.
==== Body
Background
N-acetylation polymorphism is one of the earliest discovered and most intensively studied pharmacogenetic traits that underlie interindividual and interethnic differences in response to xenobiotics. In humans, acetylation is a major route of biotransformation for many arylamine and hydrazine drugs, as well as for a number of toxins and known carcinogens present in the diet, cigarette smoke and the environment [1-3]. Genetically determined differences in N-acetylation capacity have been proved to be important determinants of both the effectiveness of therapeutic response and the development of adverse drug reactions and toxicity during drug treatment [4]. In the last decades, numerous investigations have been made to elucidate the genetic basis of N-acetylation polymorphism in various ethnic groups in order to develop efficient genotyping tests and to adapt therapies to specific patients and populations in accordance with their genetic makeup. Some of the drugs excreted by acetylation are indeed crucial in the treatment of diseases representing a worldwide concern, such as tuberculosis and AIDS-related complex diseases [5,6]. Moreover, a number of epidemiological studies have suggested possible associations between the N-acetylator phenotype and a variety of complex human diseases, the most consistent findings being those regarding urinary bladder cancer and familial Parkinson's disease [7-10].
The gene coding for the arylamine N-acetyltransferase 2 (NAT2) enzyme has been established as the site of the classic human acetylation polymorphism [11-13] and the molecular basis of individual and interethnic variation in acetylation capacity is now well documented [14,15]. All mutations reported to date are found within the 870-bp coding region of the NAT2 gene. Among the seven single nucleotide polymorphisms (SNPs) that are commonly found in human populations, four result in an amino acid substitution that leads to a significant decrease in acetylation capacity (single base-pair substitutions at positions 191, 341, 590, 857). The other three are either silent mutations (C282T, C481T) or a non-synonymous substitution that does not alter phenotype (A803G).
In the consensus gene nomenclature of human NAT2 that encompasses all currently recognized alleles [16,17], sets of SNPs located throughout the coding region are linked in terms of haplotypes, that is they are organized as they segregate together on one individual's chromosome at the NAT2 locus. Each combination of SNPs identified so far constitutes a distinct haplotype that is treated as an allele of the haplotype system. The consideration of multilocus haplotypes seems more desirable since there is growing evidence that for genes containing multiple SNPs in high linkage disequilibrium (LD) such as NAT2 [18], haplotype structure rather than individual SNPs can be the principal determinant of phenotypic consequences [19-21]. A functional polypeptide is indeed the product of a haplotype, covering the entire coding region and coded by a single chromosome.
The NAT2 alleles described so far contain up to four of the acknowledged mutations in various combinations. Each allele is associated with an acetylator phenotype depending on which mutations they contain: for instance, substitutions at positions 191, 341, 590, and 857 are diagnostic for defective NAT2 function and hence for the slow acetylator phenotype (Table 1). Three NAT2 phenotypes have been described: subjects with two low activity alleles are classified as slow acetylators, while those with two functional alleles are considered rapid acetylators. If only one allele is of the slow type, an intermediate phenotype is observed. Many early studies did not distinguish between fast and intermediate acetylators, categorizing both types of subjects as fast acetylators.
Table 1 The major human NAT2 alleles and their associated phenotypea.
Allele Nucleotide change b Phenotype
G191A C282T T341C C481T G590A A803G G857A
NAT2*4 rapid
NAT2*5A x x slow
NAT2*5B x x x slow
NAT2*5C x x slow
NAT2*6A x x slow
NAT2*6B x slow
NAT2*7A x slow
NAT2*7B x x slow
NAT2*12A x rapid
NAT2*12B x x rapid
NAT2*13 x rapid
NAT2*14A x slow
NAT2*14B x x slow
Nucleotide substitutions shown in bold have a functional consequence on enzyme activity. Bold-faced alleles contain functional polymorphisms and are hence associated with the slow acetylator phenotype. Classification of NAT2 alleles into different clusters is based on the most functionally significant nucleotide substitution present: the NAT2*5, NAT2*6, NAT2*7 and NAT2*14 clusters possess signature nucleotide substitutions at positions 341, 590, 857 and 191, respectively and are hence all decreased function alleles ('slow alleles'). The others display enzymatic activity comparable to the rapid acetylator allele NAT2*4. There are significant interethnic differences in NAT2 allele distribution and frequency [14, 15].
a Adapted from Hein et al. [3]. NAT2 nomenclature is accessible on the internet at website
b Only changes from the reference sequence (NAT2*4) are indicated.
Problems may occur when individual multi-site NAT2 genotypes have to be assigned correctly to a particular combination of two multilocus haplotypes. Indeed, current routine genotyping and sequencing methods typically do not provide haplotype information in diploid organisms such as humans, and the gametic phase of haplotypes is inherently ambiguous when individuals are heterozygous at more than one locus. As illustrated in Figure 1, a subject carrying two inactivating mutations can be either rapid or slow acetylator depending on whether these mutations are located in the same or different chromosome, respectively. It is thus crucial to unequivocally assess mutation linkage patterns, this step being a prerequisite to obtain accurate haplotype frequency estimates in populations and reliable genotype-phenotype predictions.
Figure 1 The ambiguous gametic phase of haplotypes for a given multilocus genotype. To illustrate the relevance of linkage phase ascertainment, let us consider the following case of a four-site heterozygous individual at positions 191, 341, 481 and 803 within the NAT2 coding sequence. Eight possible combinations of haplotypes can be inferred from this multilocus genotype, two of whom are shown here. Depending on the location of mutations to either DNA strand, the individual's NAT2 genotype composed of two multilocus haplotypes will not be the same. Moreover, an incorrect resolution of mutation linkage patterns may entail an error in individual phenotype prediction: the subject will be classified either as a slow or as a rapid acetylator depending on the haplotypic combination chosen. Symbol (*) points at mutations leading to a decrease in NAT2 enzyme activity, while symbol (×) indicates those with no impact on the acetylator phenotype.
However, in spite of its high relevance, this issue has not been handled properly by most past studies investigating NAT2 polymorphisms. Early genotyping studies only screened for the presence of three polymorphisms (C481T, G590A, G857A), and a subject was defined as a slow acetylator if he was homozygous for one, or heterozygous for two (each located on one DNA strand), of this three nucleotide changes. Such a definition assumed that there could be no single allele with two or more of the tested mutations. In other studies that screened a larger number of SNPs within NAT2, patterns of LD between point mutations were often assumed, in reference to the haplotypes previously described and which are commonly found in populations of European origin. For instance, the designation of NAT2 alleles is usually based on the assumption that 481T and 803G are strongly linked to 341T, and 590A and 857A are linked to 282T [22]. However, in rare cases the typical allelic linkage pattern of mutations may be disrupted because of genetic recombination and this may result in misclassification of alleles. Indeed, although such assumed linkage patterns are very strong, other allelic variants carrying either unusual combinations of mutations or mutations in isolation have been described in a few cases [23]. Furthermore, the designation of NAT2 alleles in such a way that it necessarily conforms to the existing consensus nomenclature of acknowledged haplotypes precludes the disclosure of unexpected combinations of mutations, different from the established allelic variants, and hence, the discovery of new alleles. Such a manner of inferring haplotypes from unphased multilocus genotypes may introduce biases in NAT2 allele designation and individual phenotype prediction, and these potential biases are of higher magnitude when non-European populations are concerned. Most studies assumed particular patterns of linkage previously described in populations of European origin, but which may not hold in other ethnic groups. Indeed, recent works have shown that patterns of LD can differ markedly among populations with different ethnic and demographic backgrounds. As an example, Loktionov and colleagues [24] pointed out the high occurence of isolated mutations 803G and 282T (defining alleles NAT2*12A and NAT2*13, respectively) in Black South Africans, while these nucleotide changes are almost always tightly linked to other mutations in European populations [25]. Likewise, Dandara et al. [26] recently identified a novel mutation linkage pattern (NAT2*6E) that appeared to be common in three African populations and that had not yet been reported in Europeans. As well, Anitha et al. [27] revealed a new combination of acknowledged mutations (NAT2*5G) in the Malapandaram tribe of South India that has not been described so far in any other world population. The genotype-phenotype discordance observed in many ethnic groups where mutation linkages have not been extensively proven experimentally might result from such unexpected compound alleles. It is thus necessary to systematically verify the postulated allelic combinations.
To avoid such potential problems, many authors designed special analytical techniques to unequivocally determine the allocation of mutations to either DNA strand. Molecular methods using combinations of mutation-specific polymerase chain reaction (PCR) reamplification coupled to restriction mapping of the PCR products have been developed; these allow the separate analysis of each allele in order to obtain a complete map of both genes in every individual. Some studies applied these procedures to all multiply heterozygous subjects [24,28-31], while others limited their application to particular cases as those where an alternative linkage pattern of mutations would lead to a change in phenotype [5,27,32-36]. However, these experimental methods of molecular haplotyping are not entirely satisfying because they entail an additional cost and are currently labour-intensive, time-consuming, prone to experimental errors and difficult to automate. Therefore, they do not appear to be good candidates for routine clinical applications and for a generalization at a large scale.
A cheap and relatively straightforward alternative for haplotype reconstruction based on genotype data from unrelated individuals is the use of computational algorithms. The most widely used algorithms developed so far are based either on a parsimony, a maximum-likelihood, or a Bayesian approach (see [37] for a review). In the last decade, numerous investigations based on empirical data and extensive simulation studies have demonstrated that such in silico haplotype-inference methods could give effective and accurate prediction of haplotype phases, especially in regions with high LD values between polymorphic sites and small probabilities of recombination events [18,38,39]. Therefore, they could be fairly efficient alternatives to molecular-haplotyping methods when applied to NAT2 gene data. Surprisingly, to our knowledge, only three studies have used computational methods to reconstruct NAT2 haplotypes and estimate allele frequencies in population samples [40-42]. One explanation for such limited use may be the lack of evidence documenting the performance of in silico approaches when applied to actual NAT2 data. Indeed, the accuracy of these strategies, compared with molecular methods, needs to be assessed before their applications can be advocated at a large scale. A recent study provided preliminary results on this issue: Xu and colleagues [18] empirically evaluated and compared the accuracy of the Clark's algorithm [43], the expectation-maximisation (EM) algorithm and a Bayesian method implemented in the PHASE program [44] in phase inference at NAT2, taken as an example of a locus with pronounced LD over a 850-bp region. In this study, NAT2 haplotypes (consisting of five genotyping SNPs at position 282, 341, 481, 590, and 803 nt) were experimentally determined through cloning and sequencing in 81 individuals of European ancestry. They found that all three computational methods provided remarkably accurate and reliable estimates for NAT2 haplotype frequencies and individual haplotype phases.
The objective of the present study was to extend this investigation to more precisely assess the performance of the computational approach. We conducted an extensive study based on experimental data from a larger number of samples, issued from populations of various ethnic origin, and tested for haplotypes involving the seven major polymorphic loci of NAT2. Furthermore, the larger population samples investigated are of greater significance: as the sample size grows, there is more opportunity to observe rare haplotypes that are the most difficult to infer statistically. This comparative study is designed to evaluate the performance of different haplotyping algorithms and to assess the consistency of their estimates. In addition, it provides information on the impact of various data-set characteristics (sample size, haplotype frequency distribution, haplotype frequencies, deviation from Hardy-Weinberg (HW) equilibrium, ...) on estimation accuracy; we then explore the utility of data-based diagnostics for assessing probable accuracy.
Results
Molecular haplotyping of the NAT2 locus revealed between eight and twelve distinct haplotypes in each of the five population samples investigated. The theoretical maximum number of haplotypes for a set of seven biallelic variable sites is 128 (27) if there is random association between polymorphic sites, whereas it is only 8 in the absence of recombination, recurrent and back mutation. Hence, the small number of haplotypes observed at NAT2 suggests strong LD over the short physical distance spanning this gene. Indeed, we observed complete or near complete LD for all pairs of SNPs with sufficiently high frequencies (only alleles with frequencies in the range 0.05–0.95 were included in the analysis because estimates of LD for low-frequency alleles in small samples are not informative): 85% of all pairwise r2 values were highly significant (Exact p-value <0.0001). Although LD patterns were rather similar among the different population samples, substantial differences in LD levels were observed (Figure 2): the Korean sample, and especially the South African sample, displayed much smaller values of average pairwise r2 (0.27 and 0.20, respectively) than the two European and the Nicaraguan samples (values between 0.39 and 0.57), for which a strong haplotypic structure was observed.
Figure 2 Linkage disequilibrium (r2 value) between SNP markers in the NAT2 locus. Graphical representation of the disequilibrium matrices obtained through computation of the r2 coefficient between each pair of markers, for the Spanish, Korean and Black South African samples. The British and Nicaraguan samples provided patterns and levels of LD comparable to those of the Spanish data. For each marker pair, GOLD [60] plotted the color-coded pairwise r2 statistics at the Cartesian coordinates corresponding to marker location, and the plots were completed by interpolation. These graphs point out the strong level of LD between markers at positions 341, 481, and 803, as well as between SNPs located at 282 and 590: these markers are thus strongly predictive of one another. In Black South Africans, LD patterns are less pronounced and more diffuse across marker pairs.
Among the 1608 individuals investigated over the five data sets, 45.5% (732/1608) were either homozygous for all SNP sites or heterozygous at only one SNP site; thus, their haplotype pairs could be assigned directly. Besides, 35.7% (574), 10.0% (160), 0.9% (15), and 7.9% (127) individuals were heterozygous at two, three, four and five SNP sites, respectively. We inferred their haplotype phases with four computational haplotyping methods, and compared the results with those obtained through molecular haplotyping.
Since the Hapar program often provided several equally parsimonious solutions for a given multilocus genotype, it could not resolve a relatively large fraction of heterozygous individuals in each sample and hence, we could not deduce frequency estimates for the haplotypes observed. Therefore, we evaluated Hapar only on its ability to identify the set of haplotypes present in a sample.
Haplotype identification
Hapar found for each sample the smallest set of haplotypes that could explain the genotype data, and PL-EM, Haplotyper and PHASE provided the list of all the haplotypes selected to appear in at least one of the subjects in the "best" reconstruction, that is when the most likely pair of haplotypes is selected for each individual. The IH indices of the four programs are displayed for each population sample in Table 3. For the British and Korean samples, all computational methods identified exactly the same haplotypes as those determined experimentally. In contrast, in the other three samples, the algorithms sometimes inferred one additional haplotype, that was not actually present, and/or missed one haplotype that was shown to be present by means of molecular haplotyping. Nevertheless, these prediction errors always concerned rare haplotypes of frequency <0.75% (singletons in most cases). The PHASE algorithm performed the best.
Table 3 Performance of the four computational methods in haplotype identification, as measured by the IH index.
Hapar PL-EM Haplotyper PHASE
258 Spanish [45] 0.933 (1) 0.933 (1) 0.933 (1) 0.933 (1)
137 Nicaraguans [30] 0.952 (1) 0.952 (1) 0.909 (2) 0.952 (1)
112 UK Caucasians [24] 1 1 1 1
101 Black South Africans [24] 0.917 (2) 0.917 (2) 0.917 (2) 1
1000 Koreans [31] - * 1 1 1
Numbers in brackets indicate the number of haplotypes for which an error of prediction was made. * The size of the Korean sample was too large to be correctly handled by the Hapar program.
Prediction of individual haplotype phases
We also evaluated and compared the effectiveness of the computational methods in reconstructing haplotype pairs for individuals. Table 4 gives, for each data set and for each algorithm, the individual error rate. Whatever the method, the number of incorrectly reconstructed individuals was remarkably low, with error rates always under 4%. The largest number of mistakes were observed for the African sample and, among the three algorithms tested, PHASE yielded the lowest error rates. Furthermore, it is interesting to note that, in all cases of incorrectly predicted phases, there was no impact on phenotype prediction. Thus, despite these errors, the proportions of slow, intermediate and rapid acetylators in each population sample were in 100% agreement with those deduced from molecular haplotyping.
Table 4 Individual error rate in haplotype reconstruction
PL-EM Haplotyper PHASE
258 Spanish [45] 0.39% 0.39% 0.39%
137 Nicaraguans [30] 2.19% 3.65% 2.19%
112 UK Caucasians [24] 0.89% 0% 0%
101 Black South Africans [24] 3.96% 3.96% 2.97%
1000 Koreans [31] 0.30% 0.30% 0.30%
The individual error rate is defined as the ratio of erroneous phase calls to the total number of phase calls (see text).
Estimation of haplotype frequencies
A comparison of the haplotype frequencies determined molecularly with those estimated computationally showed very high concordance. Both PL-EM and PHASE methods provided similarity index (IF) values very close to the maximal value of 1 in all investigated data sets (Table 5). Such high values may be explained by the fact that the IF index gives more weight to common haplotypes whose frequencies are the most accurately estimated by computational algorithms. To investigate the effect of haplotype frequency on estimation accuracy, we plotted the change coefficient (C) against the larger of the two haplotype frequencies (Max [, p0i]), for all possible haplotypes with nonzero frequency estimates determined by either analysis in any of the five population samples. As shown in Figure 3, substantial percentage changes >30% occur only at the lowest haplotype frequencies (<0.007). Even the moderate changes (range 10%–30%) occur only when the frequency estimates are <0.03, and any change in percentage value >5% concerns only haplotype frequencies <0.035. Two-thirds (67%) of the haplotype frequency estimates showed either no change or a small change (< 3%). In Table 6, we compared the relative estimation accuracy of PL-EM and PHASE programs by computing the average change coefficient for three classes of haplotype frequencies. The two methods perform similarly for haplotypes with frequencies >0.05, whereas PHASE provides more accurate estimates when rarer haplotypes are concerned.
Table 5 Index of similarity (IF) between haplotype frequencies estimated with and without molecular haplotyping information.
PL-EM PHASE
258 Spanish [45] 0.996 0.996
137 Nicaraguans [30] 0.986 0.986
112 UK Caucasians [24] 0.994 0.998
101 Black South Africans [24] 0.981 0.988
1000 Koreans [31] 0.997 0.998
Computations of IF indices were based on the haplotype frequency estimates obtained by considering all possible haplotype configurations (with a nonzero probability) inferred for each subject, weighted by their estimated probability. Note that such estimates can be rather different from those obtained by gene counting on the basis of the "best" reconstruction (that is, when only the most probable pair of haplotype is selected for each sampled individual). Since Haplotyper only provides a summary of the frequency with which each haplotype occurred in the "best" reconstruction, it was excluded from the comparison.
Figure 3 The change coefficient (C) as a function of haplotype frequency. The change coefficient reflects the discrepancy between haplotype frequencies deduced from phase-known data and those estimated computationally (here with the PHASE program). All haplotypes occurring in any of the five population samples are considered.
Table 6 Average change coefficients of PL-EM and PHASE programs computed for three classes of haplotype frequency.
Haplotype frequency
< 1% 1–5% > 5%
PL-EM 30.6% 8.3% 1.2%
PHASE 17.4% 6.8% 1.2%
Partially resolved data sets
We also performed similar analyses on six other previously published data sets, in which linkage phase patterns were only partially resolved by molecular haplotyping. These data concerned 844 German [32], 248 Polish [33], 303 Turkish [34], 50 non-caste Dogons from Mali, 52 Gabonese and 60 Caucasians [5]. Haplotype phase information was available for 41%–74% individuals in these six population samples (including phase-resolved genotypes as well as non ambiguous homozygous or simply heterozygous genotypes). The PHASE algorithm was applied on the unphased genotype multilocus data of each of these samples, and a 100% concordance was observed between individual haplotype phase reconstruction through the computational method and the empirically determined linkage patterns, for all investigated data sets (data not shown). This means that, despite the efforts invested, in terms of work, time and money, to resolve mutation linkage phase in a part of each sample, no more information was added by molecular haplotyping than what could be extracted from computational algorithms applied to these data.
Discussion
This empirical study demonstrates how closely the frequencies computationally estimated from phase-unknown data approximate those from gene-counting estimates based on phase-known data. In the particular case of the NAT2 gene, where there is near complete LD between SNPs within the coding region, all in silico approaches provided highly effective and accurate estimates for haplotype frequencies and individual haplotype phases. Estimated frequencies of common haplotypes were nearly identical to those empirically determined, whereas rare haplotypes were occasionally miscalled when their presence/absence had to be inferred. As already pointed out by Stephens et al. [44] and Lin et al. [39] and confirmed in this study, lower-frequency variants are less easily estimated statistically; indeed, there is less contextual information about phase for singletons versus nonsingletons. Thus, for those research questions for which the NAT2 common haplotypes are most important, frequency estimates based on the unphased SNP-typing results from unrelated individuals will be sufficient. However, accurate identification of rare haplotypes may be critical for many researchers, such as population geneticists interested in detecting features of recent demographic history that are population-specific or signatures of selective effects in NAT2 sequences; as well as for epidemiologists and clinicians concerned with the possibility that rare haplotypes may be important for disease risk or for predicting drug response. In such cases, molecular haplotyping will be necessary to determine linkage phase unambiguously [57].
For a locus such as NAT2 where a strong haplotypic structure is observed, all algorithms provided highly effective and accurate results for haplotype reconstruction. Thus, such "ideal" data for statistical inference did not permit to properly discriminate between the different methods investigated. Nevertheless, despite roughly similar performances, slightly better results were observed with the PHASE program. In particular, PHASE outperformed the other programs when frequencies of rare haplotypes have to be inferred. This is consistent with the results of some previous studies which evaluated and compared the performance of several algorithms on both empirical and simulated data [44,54,61]. PHASE provided the most accurate reconstructions, probably because the true haplotypes conformed more closely to the assumptions of the approximate coalescent prior than to those of the Dirichlet prior.
Many factors may influence the estimation accuracy of computational approaches. They can be assessed empirically within a dataset, to be further used as "diagnostics" for predicting potential inaccuracies in estimation caused by features in the relevant data set [38].
Sample size did not appear to have a large effect on the haplotype frequency estimates comparing phase-known and phase-unknown results for the five data sets included in this study. Perhaps the low error rate observed in Koreans is partly due to the huge size of this sample (1000 individuals): an improvement in accuracy of the estimation procedure with increased sample size is indeed expected since information redundancy in the form of multiple copies of the same haplotype in the data set is required for the statistical algorithms to work properly [38,48]. On the other hand, computational methods may also perform best in small samples, in which there is little chance to observe rare haplotypes that are the most difficult to infer statistically. Nevertheless, since the number of new haplotypes is not expected to increase linearly with sample size, the analysis of sufficiently large samples should guarantee a good reliability in the resulting estimates.
Although most of the tested algorithms assume HW equilibrium, significant departures from HW proportions did not seem to have any impact on the accuracy of their predictions. HW equilibrium holds well for the Nicaraguan, UK Caucasian, and Black South African samples (nonsignificant results), whereas the genotype distribution in the Spanish and Korean samples show significant departures from HW proportions (Table 2). The data sets investigated are not the most suitable to evaluate the effect of a deviation from HW equilibrium: significant results for tests of HW ratios are quite close to the threshold value (5%), and in the case of the Korean sample, an excess homozygosity is observed, which should not compromise the algorithm performance. Indeed, in such a case, there is a balance between loss of accuracy caused by violation of HW equilibrium and gain of accuracy caused by the decrease in missing phase information through an excess of homozygotes [38,62].
Table 2 The five phase-resolved NAT2 molecular data sets investigated.
Population sample Proportion of phase-unknown multiple heterozygotesa NAT2 gene diversityb Deviation from the Hardy-Weinberg equilibrium (exact p-value)c
258 Spanish [45] 66.7% 0.65 0.012
137 Nicaraguans [30] 59.1% 0.70 0.072
112 UK Caucasians [24] 52.7% 0.69 0.222
101 Black South Africans [24] 63.4% 0.86 0.122
1000 Koreans [31] 50.0% 0.52 0.016
All population samples were genotyped for the same seven nucleotide changes (G191A, C282T, T341C, C481T, G590A, A803G, G857A), except Koreans where the C190T mutation was investigated instead of G191A.
aProportion of multiply heterozygous individuals with ambiguous genotype whose phase has been resolved molecularly.
bExpected heterozygosities for the NAT2 haplotyped system were estimated as where n is the number of gene copies in the sample, and pi is the sample frequency of the i-th haplotype.
cThe significance of deviations from Hardy-Weinberg equilibrium was tested for genotypic data with known gametic phase using the random-permutation procedure implemented in the Arlequin package [51]: a Fisher's exact test using a Markov chain random walk algorithm was performed for each data set. The resulting p-values were considered significant if inferior to 0.05 (significant p-values are shown in bold).
Among the five data sets investigated in this study, Black South Africans displayed the highest error rate in haplotype computational inference. One possible explanation may be the presence in this sample of a large number of different multiple heterozygotes with ambiguous multilocus genotypes, occurring at roughly similar frequencies (this is reflected in the high NAT2 gene diversity displayed by this population sample (Table 2)). Indeed, both the number of different ambiguous multiple heterozygous genotypes and their relative frequencies have been shown to be of high importance in the assessment of haplotype estimation accuracy [57]: both would be good indicators of the difficulty level of a given data set for haplotyping algorithms. The existence of many different multilocus genotypes uniformly distributed implies that many different haplotypes occur at low frequency, and that, consequently, greatest error and uncertainty occur in the estimation of haplotype frequencies (since no single haplotype is overwelmingly frequent). In contrast, the presence of a small number of multiple heterozygous genotypes at proportionately high frequencies implies that some individual haplotypes exist at high frequencies, and the estimation of those haplotype frequencies will be easier and accomplished with greater accuracy [38,57]. In such cases, molecular haplotyping may add little information for the resolution of haplotype phases.
The amount of LD between SNP markers may be another determining factor for the prediction of estimation reliability since when multiple polymorphic sites display little disequilibrium, as was observed in the African sample compared to the others, a large proportion of the chromosomes may occur as uncommon or rare haplotypes, implying a greater difficulty level in the statistical inference of haplotypes.
Therefore, we advocate to examine beforehand the unphased NAT2 genotype data for both the frequency distribution of multiply heterozygous genotypes and the level of LD between polymorphic markers; this will allow to assess the difficulty level displayed by the data set for statistical inference, and hence, to predict the ability and accuracy with which computational algorithms would infer haplotype phases from such data.
Of course, statistical methods can be used in conjunction with experimental methods to provide more accurate estimates of individual haplotypes. It has been claimed that the ability of certain computational methods to accurately assess the uncertainty associated with each phase call gives them the substantial practical advantage of allowing experimental effort to be directed at sites and/or individuals whose phases are most difficult to reconstruct statistically or that are critical to the conclusions of the study [20,44,61]. However, in our study, we observed that most erroneous phase calls inferred at the individual level were strongly supported, with a probability close to the maximal value of 1. Thus, these errors could not have been avoided since they would not have been selected for the molecular targeting. This stresses why, in the case of the discovery of a novel NAT2 allele through computational haplotyping methods, the unusual linkage pattern should always be confirmed by cloning and sequencing the allele under question, as advocated by Cascorbi and Roots [25] for novel allelic combinations detected by molecular techniques.
Throughout this study, we assumed that the NAT2 linkage patterns molecularly determined were the "true" ones, and hence, that there was no error in the haplotype assigments based on experimental methods. However, molecular techniques may have experimental error rates as high as the rate of statistical error associated with the computational haplotype determination algorithms [19]. Indeed, molecular haplotyping bears the risk of false positive or false negative allele-specific amplification (because of the nucleotide-dependent specificity of that technique) as well as uncomplete or non-specific digestions with the enzymes used in restriction analyses [25]. In the present study, we have estimated the computational error rates to be of no more than 3–4% for all investigated algorithms. This is not higher than the corresponding error rate from molecular haplotyping techniques, on the order of 2–3% [20]. Therefore, it is difficult to determine whether the discrepancies observed between experimental and computational estimates are actually due to statistical errors from algorithms; they may be due to technical errors during manipulations and the molecular data used as a reference for comparisons might be wrong.
The disadvantage of in silico approaches is that algorithmic techniques are statistical and require the analysis of a population rather than a single individual. This is not a limitation in clinical trials and epidemiological surveys, which are always performed on a cohort basis. In clinical pharmacy, however, if a specific individual's haplotypes are of interest to predict his response to drug treatment, his unphased multilocus genotype must be combined with a standard reference set of haplotypes to infer the phasing [20]. This implies a thorough knowledge of the NAT2 genotypic distribution in the ethnic population from which this individual was drawn.
Conclusion
This study demonstrates that computational methods can provide an effective and accurate prediction of haplotype phases, in the particular case of the NAT2 gene which displays high values of LD between polymorphic sites. The objective of this study is not to advocate the systematic use of computational approaches for NAT2 haplotype inference at the expense of molecular haplotyping methods. We are convinced that these last ones remain the most reliable and effective way to resolve linkage phase patterns and that they can produce, for a fixed sample size, much more precise estimates of haplotype frequencies than other approaches [63]. However, the considerable effort required to obtain and analyse individual chromosomes make alternative designs preferable; and the in silico approach appears to be the most practical one. Thus, for researchers not willing to invest time and money in the preliminary step of NAT2 haplotype reconstruction, the use of computational algorithms constitutes a safe and effective way to get reliable haplotypic data on which further analyses could be carried on. Once haplotypes are constructed, various statistical methods can be applied on NAT2 haplotype data to detect allele-disease associations or to classify patients according to their acetylation status.
Methods
NAT2 molecular data sets
To evaluate the performance of in silico approaches in NAT2 haplotype reconstruction, we based our study on data collected from the literature, for which linkage phase was resolved directly through molecular haplotyping. Molecular data from five previously published data sets were analysed: they concerned 258 Spanish from Central Spain [45], 137 Nicaraguans with a Central American Indian-European mixed origin [30], 112 British from the Cambridge area [24], 101 Black South Africans (mostly Tswana-speaking people) [24], and 1000 Koreans [31]. All subjects included in these studies were randomly selected, unrelated healthy volunteers whose ethnic origin had been clearly defined. In each population sample, seven SNPs were typed at NAT2 for all individuals (no missing data), and mutation linkage phase of all multiply heterozygous individuals was resolved molecularly through allele-specific PCR and restriction mapping. A summary description of the data sets is given in Table 2. These data provide an opportunity to compare haplotype frequencies estimated by direct gene counting on experimentally haplotyped data with haplotype frequencies estimated by haplotyping algorithms when phase information is ignored.
Throughout this report, we will use the term «phase-known» to refer to the individual's genetic constitution for the NAT2 haplotyped system, including the linkage phase of the component SNP alleles. Whereas we will use the term "phase-unknown" to refer to an individual's multilocus genotype in the absence of phase information.
Computational haplotyping methods
We evaluated the ability of four population-based haplotype inference methods to reconstruct NAT2 haplotypes from the phase-unknown genotype data.
Hapar
The first method is based on maximum parsimony: it searches for a set of minimum number of haplotypes that explain the observed genotype samples. Clark's method, the first developed algorithm for haplotype reconstruction [43] which can be viewed as a sort of parsimony approach, requires homozygote or single-site heterozygote in the sample to start its inferential cascade. Wang and Xu [46] overcame this limitation by designing an algorithm with a global optimization goal. This method, recently implemented in the Hapar program [46], was tested at its default settings on the phase-unknown NAT2 data.
PL-EM
We also applied the EM algorithm [47] to obtain the maximum-likelihood estimates of haplotype frequencies in the samples, given the observed data [48-50]. This algorithm starts with initial arbitrary values of haplotype frequencies and iteratively updates the frequency estimates, to maximize the log-likelihood function, until convergence is reached. Several EM-based algorithms have been developed. We used three different implementations, Arlequin [51], HAPLO [49] and PL-EM [52], that all gave us identical results on comparable analyses (data not shown). Thus, we presented only the results obtained with the PL-EM program: this software implements an algorithm derived from the standard EM but incorporating the computational strategy of partition-ligation [53] to handle a larger number of loci. We performed 50 independent runs with different initial conditions to minimize chances of local convergence so as to ensure finding the global maximum likelihood estimates. For a given unphased genotype pattern, the probability of each possible haplotype configuration was calculated by using the estimated population haplotype frequencies, and all compatible haplotype phases with nontrivial probabilities were generated. The haplotype pair with the greatest probability was considered to be the haplotype phase for each individual, and population haplotype frequencies were estimated as a function of each inferred haplotype pair, weighted by their estimated probability.
Haplotyper and PHASE
Finally, two Bayesian statistical methods based on Gibbs sampling procedure were applied to the phase-unknown NAT2 data. Such methods treat the unknown haplotypes as random quantities and combine prior information -beliefs about what sorts of patterns of haplotypes are expected to be observed in population samples- with the likelihood -the information in the observed data [54]. The conceptual difference between the two investigated Bayesian algorithms lies in the prior information incorporated into the statistical model. The algorithm implemented in the Haplotyper program [53] uses a Dirichlet prior distribution, which assumes that the genetic sequence of a mutant offspring does not depend on the progenitor sequence [54]. Instead, the algorithm implemented in the PHASE program [44] uses a prior approximating the coalescent, which is one of the evolutionary models most commonly used in population genetics (see [55] for a review): it assumes that unresolved haplotypes will tend to be the same as, or similar to, known haplotypes. We employed the lastest version of PHASE (PHASE v 2.1 [54]) to evaluate the performance of this method, using the default parameter values in the Markov chain Monte Carlo simulations. For each data set investigated, we applied the algorithm ten times with different seeds for the random number generator, and checked for consistency of the results across the independent runs in order to verify that the algorithm did not converge to a local, rather than global, mode of the posterior distribution. We chose the results from the run displaying the best average goodness-of-fit of the estimated haplotypes to the underlying coalescent model. Besides, to evaluate the Bayesian algorithm implemented in Haplotyper, we performed 20 independent runs of the program on each sample. This software could not be run directly on the 1000-Korean sample as it can only handle 500 individuals at most per data set. To circumvent this limitation, we randomly generated ten pairs of complementary data sets, each composed of 500 individuals, and we ran Haplotyper on each of them. Results were averaged over the ten complete data sets. Both programs Haplotyper and PHASE provide a list of the most likely pairs of haplotypes for each subject. They also quantify the uncertainty associated with each phase call by outputting an estimate of the probability that each call is correct. This prevents inappropriate overconfidence in statistically reconstructed haplotypes.
Measures of estimation accuracy
Computational algorithms of haplotype reconstruction may be used for many different purposes. We focus here on three particular tasks: finding the list of all haplotypes present in a sample, inferring the most likely pair of haplotypes for each sampled individual, and estimating haplotype frequencies in the population. Thus, three different measures of accuracy were used to evaluate the performance of the tested algorithms.
-haplotype identification
To assess accuracy in terms of haplotype identification, we used the IH index introduced by Excoffier and Slatkin [48]. It compares the number of different haplotypes detected experimentally with the number of different haplotypes inferred by the computer programs. We considered that a given haplotype is identified as being present in the true sample if its estimated frequency is above the threshold value of 1/(2n) in a population sample of n individuals. IH is given by:
where ktrue is the number of haplotypes in the true sample, kest is the number of estimated haplotypes with frequency above the threshold, and kmissed is the number of true haplotypes not identified in the sample.
Values of IH can vary between 1 (when the computational identified haplotypes are exactly the same as those determined experimentally) to 0 (when none of the true haplotypes are identified computationally).
- reconstruction of the haplotypes of each sampled individual
We specified the haplotype pair for an individual by choosing the most probable haplotype pair consistent with the individual's multilocus genotype. We measured performance by the individual error rate, which is the proportion of individuals whose haplotype pairs were incorrectly inferred by the program [53].
- estimation of sample haplotype frequencies
To examine how close the computationally estimated haplotype frequencies are to the observed frequencies in the phase-known data, we used the similarity index IF of Renkonen [56], defined as the proportion of haplotype frequencies in common between the estimated and observed frequency distributions [18,48].
where and p0i denote, respectively, the estimated and observed sample frequency of the i-th haplotype. This measure incorporates all h haplotype frequencies and thus captures the overall difference between estimated and observed frequencies for a particular data set. It varies between zero, when true haplotypes have estimated frequencies tending to zero, and one, when observed and estimated frequencies are identical.
Since this index gives more weight to the high-frequency haplotypes, we used a second criterion to assess the accuracy of computational algorithms in haplotype frequency estimation: the change coefficient C, defined in Tishkoff et al. [57] as
where Max [, p0i] indicates the maximum value of or p0i.
This coefficient measures the percentage change in haplotype frequencies across the two information conditions (phase-known versus phase-unknown data). C coefficients were computed for each possible haplotype in each population. The value of C ranges from 0 to 1, with 0 indicating that the estimated and observed frequency are identical. The maximal value of 1 indicates that molecular haplotyping showed either the presence of a haplotype that was assigned a zero through computational haplotyping, or vice versa.
Measure of pairwise LD between SNP markers
We used the phase-known data to quantify the amount of LD between all pairs of polymorphic sites by computing the correlation coefficient r2 [58] for each population sample separately. These statistics are expected to be 1 (perfect LD) when the variation is segregating in a population as only two distinct haplotypes. Statistical significance of LD between pairs of sites was assessed by Fisher's exact tests. Computations were performed with the software PowerMarker v3.21 [59], and a graphical summary of disequilibrium matrices was displayed by the GOLD program [60].
Abbreviations
Single nucleotide polymorphism (SNP)
Expectation-Maximisation (EM) algorithm
Linkage disequilibrium (LD)
N-acetyltransferase 2 (NAT2)
Authors' contributions
AS participated in the conception and design of the study, in collection of data, in performing all the computational analyses, and in drafting the manuscript. PD participated in the design of the study, in interpretation of data and in revising the article critically for important intellectual content. All authors read and approved the final manuscript.
==== Refs
Minchin RF Reeves PT Teitel CH McManus ME Mojarrabi B Ilett KF Kadlubar FF N-and O-acetylation of aromatic and heterocyclic amine carcinogens by human monomorphic and polymorphic acetyltransferases expressed in COS-1 cells Biochem Biophys Res 1992 185 839 844 10.1016/0006-291X(92)91703-S
Hein DW Doll MA Rustan TD Gray K Feng Y Ferguson RJ Grant DM Metabolic activation and deactivation of arylamine carcinogens by recombinant human NAT1 and polymorphic NAT2 acetyltransferases Carcinogenesis 1993 14 1633 1638 8353847
Hein DW Molecular genetics and function of NAT1 and NAT2: role in aromatic amine metabolism and carcinogenesis Mutat Res 2002 506–507 65 77
Meisel P Arylamine N-acetyltransferases and drug response Pharmacogenomics 2002 3 349 366 12052143 10.1517/14622416.3.3.349
Delomenie C Sica L Grant DM Krishnamoorthy R Dupret JM Genotyping of the polymorphic N-acetyltransferase (NAT2*) gene locus in two native African populations Pharmacogenetics 1996 6 177 185 9156695
Asprodini EK Zifa E Papageorgiou I Benakis A Determination of N-acetylation phenotyping in a Greek population using caffeine as a metabolic probe Eur J Drug Metab Pharmacokinet 1998 23 501 506 10323334
Cartwright RA Glashan RW Rogers HJ Ahmad RA Barham-Hall D Higgins E Kahn MA Role of N-acetyltransferase phenotypes in bladder carcinogenesis: a pharmacogenetic epidemiological approach to bladder cancer Lancet 1982 2 842 845 6126711 10.1016/S0140-6736(82)90810-8
Risch A Wallace DM Bathers S Sim E Slow N-acetylation genotype is a susceptibility factor in occupational and smoking related bladder cancer Hum Mol Genet 1995 4 231 236 7757072
Bialecka M Gawronska-Szklarz B Drozdzik M Honczarenko K Stankiewicz J N-acetyltransferase 2 polymorphism in sporadic Parkinson's disease in a Polish population Eur J Clin Pharmacol 2002 57 857 862 11936704 10.1007/s00228-001-0415-4
Chan DK Lam MK Wong R Hung WT Wilcken DE Strong association between N-acetyltransferase 2 genotype and PD in Hong Kong Chinese Neurology 2003 60 1002 1005 12654968
Blum M Grant DM McBride W Heim M Meyer UA Human arylamine N-acetyltransferase genes: isolation, chromosomal localization, and functional expression DNA Cell Biol 1990 9 193 203 2340091
Ohsako S Deguchi T Cloning and expression of cDNAs for polymorphic and monomorphic arylamine N-acetyltransferases from human liver J Biol Chem 1990 265 4630 4634 1968463
Blum M Demierre A Grant DM Heim M Meyer UA Molecular mechanism of slow acetylation of drugs and carcinogens in humans Proc Natl Acad Sci 1991 88 5237 5241 1675794
Grant DM Hughes NC Janezic SA Goodfellow GH Chen HJ Gaedigk A Yu VL Grewal R Human acetyltransferase polymorphisms Mutat Res 1997 376 61 70 9202739
Upton A Johnson N Sandy J Sim E Arylamine N-acetyltransferases – of mice, men and microorganisms Trends Pharmacol Sci 2001 22 140 146 11239577 10.1016/S0165-6147(00)01639-4
Vatsis KP Weber WW Bell DA Dupret JM Evans DA Grant DM Hein DW Lin HJ Meyer UA Relling MV Nomenclature for N-acetyltransferases Pharmacogenetics 1995 5 1 17 7773298
Hein DW Grant DM Sim E Update on consensus arylamine N-acetyltransferase gene nomenclature Pharmacogenetics 2000 10 291 292 10862519 10.1097/00008571-200006000-00002
Xu CF Lewis K Cantone KL Khan P Donnelly C White N Crocker N Boyd PR Zaykin DV Purvis IJ Effectiveness of computational methods in haplotype prediction Hum Genet 2002 110 148 156 11935321 10.1007/s00439-001-0656-4
Judson R Stephens JC Windemuth A The predictive power of haplotypes in clinical response Pharmacogenomics 2000 1 15 26 11258593 10.1517/14622416.1.1.15
Judson R Stephens JC Notes from the SNP vs. haplotype front Pharmacogenomics 2001 2 7 10 11258199 10.1517/14622416.2.1.7
McDonald OG Krynetski EY Evans WE Molecular haplotyping of genomic DNA for multiple single-nucleotide polymorphisms located kilobases apart using long-range polymerase chain reaction and intramolecular ligation Pharmacogenetics 2002 12 93 99 11875363 10.1097/00008571-200203000-00003
Zschieschang P Hiepe F Gromnica-Ihle E Roots I Cascorbi I Lack of association between arylamine N-acetyltransferase 2 (NAT2) polymorphism and systemic lupus erythematosus Pharmacogenetics 2002 12 559 563 12360107 10.1097/00008571-200210000-00008
Agundez JA Ladero JM Olivera M Lozano L Fernandez-Arquero M de laConcha EG Diaz-Rubio M Benitez J N-acetyltransferase 2 polymorphism is not related to the risk of advanced alcoholic liver disease Scand J Gastroenterol 2002 37 99 103 11858170 10.1080/003655202753387437
Loktionov A Moore W Spencer SP Vorster H Nell T O'Neill IK Bingham SA Cummings JH Differences in N-acetylation genotypes between Caucasians and Black South Africans: implications for cancer prevention Cancer Detect Prev 2002 26 15 22 12088198 10.1016/S0361-090X(02)00010-7
Cascorbi I Roots I Pitfalls in N-acetyltransferase 2 genotyping Pharmacogenetics 1999 9 123 127 10208651
Dandara C Masimirembwa CM Magimba A Kaaya S Sayi J Sommers de K Snyman JR Hasler JA Arylamine N-acetyltransferase (NAT2) genotypes in Africans: the identification of a new allele with nucleotide changes 481C>T and 590G>A Pharmacogenetics 2003 13 55 58 12544513 10.1097/00008571-200301000-00008
Anitha A Banerjee M Arylamine N-acetyltransferase 2 polymorphism in the ethnic populations of South India Int J Mol Med 2003 11 125 131 12469231
Martinez C Agundez JA Olivera M Martin R Ladero JM Benitez J Lung cancer and mutations at the polymorphic NAT2 gene locus Pharmacogenetics 1995 5 207 214 8528267
Agundez JA Olivera M Martinez C Ladero JM Benitez J Identification and prevalence study of 17 allelic variants of the human NAT2 gene in a white population Pharmacogenetics 1996 6 423 428 8946474
Martinez C Agundez JA Olivera M Llerena A Ramirez R Hernandez M Benitez J Influence of genetic admixture on polymorphisms of drug-metabolizing enzymes: analyses of mutations on NAT2 and C gamma P2E1 genes in a mixed Hispanic population Clin Pharmacol Ther 1998 63 623 628 9663176 10.1016/S0009-9236(98)90085-6
Lee SY Lee KA Ki CS Kwon OJ Kim HJ Chung MP Suh GY Kim JW Complete sequencing of a genetic polymorphism in NAT2 in the Korean population Clin Chem 2002 48 775 777 11978608
Cascorbi I Drakoulis N Brockmoller J Maurer A Sperling K Roots I Arylamine N-acetyltransferase (NAT2) mutations and their allelic linkage in unrelated Caucasian individuals: correlation with phenotypic activity Am J Hum Genet 1995 57 581 592 7668286
Mrozikiewicz PM Cascorbi I Brockmoller J Roots I Determination and allelic allocation of seven nucleotide transitions within the arylamine N-acetyltransferase gene in the Polish population Clin Pharmacol Ther 1996 59 376 382 8612380 10.1016/S0009-9236(96)90104-6
Aynacioglu AS Cascorbi I Mrozikiewicz PM Roots I Arylamine N-acetyltransferase (NAT2) genotypes in a Turkish population Pharmacogenetics 1997 7 327 331 9295061
Meisel P Schroeder C Wulff K Siegmund W Relationship between human genotype and phenotype of N-acetyltransferase (NAT2) as estimated by discriminant analysis and multiple linear regression:1. Genotype and N-acetylation in vivo Pharmacogenetics 1997 7 241 246 9241664
Kukongviriyapan V Prawan A Tassaneyakul W Aiemsa-Ard J Warasiha B Arylamine N-acetyltransferase-2 genotypes in the Thai population Br J Clin Pharmacol 2003 55 278 281 12630978 10.1046/j.1365-2125.2003.01766.x
Niu T Algorithms for inferring haplotypes Genet Epidemiol 2004 27 334 347 15368348 10.1002/gepi.20024
Fallin D Schork NJ Accuracy of haplotype frequency estimation for biallelic loci, via the expectation-maximization algorithm for unphased diploid genotype data Am J Hum Genet 2000 67 947 959 10954684 10.1086/303069
Lin S Cutler DJ Zwick ME Chakravarti A Haplotype inference in random population samples Am J Hum Genet 2002 71 1129 1137 12386835 10.1086/344347
Tanaka E Taniguchi A Urano W Nakajima H Matsuda Y Kitamura Y Saito M Yamanaka H Saito T Kamatani N Adverse effects of sulfasalazine in patients with rheumatoid arthritis are associated with diplotype configuration at the N-acetyltransferase 2 gene J Rheumatol 2002 29 2492 2499 12465141
Jorge-Nebert LF Eichelbaum M Griese EU Inaba T Arias TD Analysis of six SNPs of NAT2 in Ngawbe and Embera Amerindians of Panama and determination of the Embera acetylation phenotype using caffeine Pharmacogenetics 2002 12 39 48 11773863 10.1097/00008571-200201000-00006
Barrett JH Smith G Waxman R Gooderham N Lightfoot T Garner RC Augustsson K Wolf CR Bishop DT Forman D Investigation of interaction between N-acetyltransferase 2 and heterocyclic amines as potential risk factors for colorectal cancer Carcinogenesis 2003 24 275 282 12584178 10.1093/carcin/24.2.275
Clark AG Inference of haplotypes from PCR-amplified samples of diploid populations Mol Biol Evol 1990 7 111 122 2108305
Stephens M Smith NJ Donnelly P A new statistical method for haplotype reconstruction from population data Am J Hum Genet 2001 68 978 989 11254454 10.1086/319501
Agundez JA Olivera M Ladero JM Rodriguez-Lescure A Ledesma MC Diaz-Rubio M Meyer UA Benitez J Increased risk for hepatocellular carcinoma in NAT2-slow acetylators and CYP2D6-rapid metabolizers Pharmacogenetics 1996 6 501 512 9014199
Wang L Xu Y Haplotype inference by maximum parsimony Bioinformatics 2003 19 1773 1780 14512348 10.1093/bioinformatics/btg239
Dempster AP Laird NM Rubin DB Maximum likelihood from incomplete data via the EM algorithm J R Stat Soc 1977 39 1 38
Excoffier L Slatkin M Maximum-likelihood estimation of molecular haplotype frequencies in a diploid population Mol Biol Evol 1995 12 921 927 7476138
Hawley ME Kidd KK HAPLO: a program using the EM algorithm to estimate the frequencies of multi-site haplotypes J Hered 1995 86 409 411 7560877
Long JC Williams RC Urbanek M An E-M algorithm and testing strategy for multiple-locus haplotypes Am J Hum Genet 1995 56 799 810 7887436
Schneider S Roessli D Excoffier L Arlequin ver. 2.000: a software for population genetics data analysis 2000 Genetics and Biometry Laboratory, University of Geneva, Switzerland
Qin ZS Niu T Liu JS Partition-ligation-expectation-maximization algorithm for haplotype inference with single-nucleotide polymorphisms Am J Hum Genet 2002 71 1242 1247 12452179 10.1086/344207
Niu T Qin ZS Xu X Liu JS Bayesian haplotype inference for multiple linked single-nucleotide polymorphisms Am J Hum Genet 2002 70 157 169 11741196 10.1086/338446
Stephens M Donnelly P A comparison of bayesian methods for haplotype reconstruction from population genotype data Am J Hum Genet 2003 73 1162 1169 14574645 10.1086/379378
Hudson RR Futuyma D, Antonovics J Gene genealogies and the coalescent process Oxford surveys in evolutionary biology 1991 7 Oxford University Press, Oxford 1 44
Renkonen O Statisch-ökologische Untersuchungen über die terrestiche Kaferwelt der finnishen Bruchmoore Ann Zool Soc Bot Fenn Vanamo 1938 6 1 231
Tishkoff SA Pakstis AJ Ruano G Kidd KK The accuracy of statistical methods for estimation of haplotype frequencies: an example from the CD4 locus Am J Hum Genet 2000 67 518 522 10859209 10.1086/303000
Devlin B Risch N A comparison of linkage disequilibrium measures for fine-scale mapping Genomics 1995 29 311 322 8666377 10.1006/geno.1995.9003
Liu K Muse S PowerMarker: new genetic data analysis software Version 30 Free program distributed by the author over the internet
Abecasis GR Cookson WO GOLD – graphical overview of linkage disequilibrium Bioinformatics 2000 16 182 183 10842743 10.1093/bioinformatics/16.2.182
Stephens M Smith NJ Donnelly P Reply to Zhang etal Am J Hum Genet 2001 69 912 914 10.1086/323623
Osier M Pakstis AJ Kidd JR Lee JF Yin SJ Ko HC Edenberg HJ Lu RB Kidd KK Linkage disequilibrium at the ADH2 and ADH3 loci and risk of alcoholism Am J Hum Genet 1999 64 1147 1157 10090900 10.1086/302317
Zhao H Pfeiffer R Gail MH Haplotype analysis in population genetics and association studies Pharmacogenomics 2003 4 171 178 12605551 10.1517/phgs.4.2.171.22636
| 15932650 | PMC1173101 | CC BY | 2021-01-04 16:38:18 | no | BMC Genet. 2005 Jun 2; 6:30 | utf-8 | BMC Genet | 2,005 | 10.1186/1471-2156-6-30 | oa_comm |
==== Front
BMC GenetBMC Genetics1471-2156BioMed Central London 1471-2156-6-311593264610.1186/1471-2156-6-31Research ArticleGenome-wide screening for genes whose deletions confer sensitivity to mutagenic purine base analogs in yeast Stepchenkova Elena I [email protected] Stanislav G [email protected] Vladimir V [email protected] Youri I [email protected] Department of Genetics, Sankt-Petersburg State University, Sankt-Petersburg, 199034, Russia2 Laboratory of Molecular Genetics, National Institute of Environmental Health Sciences, RTP, NC 27709, USA3 Eppley Institute for Research in Cancer and Allied Diseases, the Department of Biochemistry and Molecular Biology, and the Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE 68198, USA2005 2 6 2005 6 31 31 26 1 2005 2 6 2005 Copyright © 2005 Stepchenkov et al; licensee BioMed Central Ltd.2005Stepchenkov et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
N-hydroxylated base analogs, such as 6-hydroxylaminopurine (HAP) and 2-amino-6-hydroxylaminopurine (AHA), are strong mutagens in various organisms due to their ambiguous base-pairing properties. The systems protecting cells from HAP and related noncanonical purines in Escherichia coli include specialized deoxyribonucleoside triphosphatase RdgB, DNA repair endonuclease V, and a molybdenum cofactor-dependent system. Fewer HAP-detoxification systems have been identified in yeast Saccharomyces cerevisiae and other eukaryotes. Cellular systems protecting from AHA are unknown. In the present study, we performed a genome-wide search for genes whose deletions confer sensitivity to HAP and AHA in yeast.
Results
We screened the library of yeast deletion mutants for sensitivity to the toxic and mutagenic action of HAP and AHA. We identified novel genes involved in the genetic control of base analogs sensitivity, including genes controlling purine metabolism, cytoskeleton organization, and amino acid metabolism.
Conclusion
We developed a method for screening the yeast deletion library for sensitivity to the mutagenic and toxic action of base analogs and identified 16 novel genes controlling pathways of protection from HAP. Three of them also protect from AHA.
==== Body
Background
The accurate replication and repair of genetic material, which is a prerequisite for normal functioning of the eukaryotic genome and the prevention of cancer, relies on coordinated and faithful DNA synthesis. One important mechanism that ensures a high fidelity of DNA replication is a "cleansing" of the DNA precursor pool from deoxyribonucleoside triphosphates containing a modified base [1-4]. Such modified bases may have ambiguous base-pairing properties that will result in a high mutagenic activity after their incorporation into DNA during replication. A classic example of the detoxification mechanism is the elimination of dUTP and 8-oxo-dGTP from the dNTP pool by the E. coli dUTPase and MutT proteins, respectively [1,5].
Purine analogs 6-hydroxyaminopurine (HAP) and 2-amino-HAP (AHA) are powerful mutagens in bacteria, yeast, and higher eukaryotes [6,7]. It has been suggested that HAP-deoxyriboside-triphosphate (dHAPTP) is a possible endogenous contaminant of nucleotide pools under peroxyl radical stress [8]. HAP and AHA closely resemble the natural purines, hypoxanthine and xanthine (Fig. 1), and therefore, could be exploited to investigate the mechanism preventing mutations that are caused by non-canonical purine nucleotides [9-11].
Figure 1 Chemical structures of HAP and AHA and natural purine bases.
It was proposed that purine salvage enzymes convert base analogs to the corresponding deoxyribonucleoside triphosphates, which are misincorporated or misreplicated during DNA synthesis, resulting in induction of mutations [12,13]. HAP-induced mutagenesis in yeast is elevated in strains with defects in proofreading activity of replicative DNA polymerases [14,15] and does not depend on excision, mutagenic recombination, and mismatch repair systems [14-16]. We have described several systems protecting cells from the mutagenic and inhibitory effects of HAP (see review [16]). One is the novel molybdenum cofactor-dependent system in E. coli [17]. It has yet to be determined if a similar system exists in higher eukaryotes. Another, versatile HAP-detoxification pathway relies upon the action of triphosphatase, Ham1p, which hydrolyze HAP-containing ribo- and deoxyribo-nucleotides to nucleoside monophosphates, and which prevent incorporation of base analog into DNA and RNA. We initially described the elevated sensitivity to HAP in yeast due to mutations in the HAM1 gene [18]. When we cloned and sequenced the HAM1 gene, we found that it has homologs in many organisms, from bacteria to humans [13], and proposed that the gene might code for new triphosphatase [16]. Then, the crystal structure of the Ham1p homologue from a thermostable bacterium (protein Mj0226) was determined [19]. It was found that the Ham1p ternary structure has common features with MutT. Homologs of the yeast Ham1p from other organisms possessed triphosphatase activity on dITP, ITP, XTP, and dHAPTP substrates (Kozmin and Pavlov, unpublished; Burgis and Cunnigham, personal communication; and [19-21]).
There are additional, less thoroughly studied, factors modulating purine base analogues mutagenesis in yeast (see [16] for review). For example, aah1 mutants are sensitive to HAP, suggesting that adenine deaminase Aah1p may deaminate HAP base to hypoxanthine [16].
In the present study, we carried out a genome-wide search for HAP and AHA sensitive mutants. The release of several complete sets of deletion mutants by the Yeast Deletion Project provides a powerful approach for different types of genome screens in yeast [22]. Haploid and diploid strains have already been used to detect new genes controlling sensitivity to different agents such as UV, ionising radiation, iron, and methyl methane sulfonate (MMS) [23-27], as well as spontaneous mutability [28]. This approach, when combined with other genomics approaches, helps to establish the biological functions of uncharacterized ORFs in yeast, many of which have human orthologs. This approach also allows us to decipher the network responses to endogenous and environmental stress [29]. The present study is the first systematic, genome-wide search for the mutations conferring sensitivity to mutagenic purine base analogs.
Results
Development of the screening method
To develop a useful method for searching the yeast mutants sensitive to base analogs, we calibrated the experimental conditions using the wild-type strain, BY4742, and two previously described HAP-sensitive mutants, ham1 and aah1 (see [6,16]), created on BY4742 background. As shown in Fig. 2 and described in Materials and Methods, yeast were grown in a 96-well microtiter plate and then transferred, using a multiprong replicator device, to YPD plates containing base analogs. An induction of the Canr mutants was monitored by replica-plating to the minimal-medium plates containing L-canavanine.
Figure 2 Scheme of the protocol for screening the yeast deletions library for base analog sensitivity and induced mutagenesis.
The results are presented in Fig. 3. The left panel of Fig. 3 shows the induction of canavanine-resistant mutants by HAP and AHA; and the right panel represents the survival of the tested strains on YPD plates in the presence of base analogs. In the wild-type strain, as in the ham1 and aah1 mutants, 1–3 spontaneous canavanine-resistant colonies per spot arise in the absence of mutagen (Fig. 3A and 3B, left panel). In our experimental conditions, 1 μg/ml of HAP did not induce Canr mutants in the wild-type strain. A moderate induction of Canr clones (fewer than ten per spot) was observed at 10 μg/ml of HAP and a very strong HAP-induced mutagenesis was observed in the wild-type strain at 100 μg/ml of HAP (Fig. 3A, left panel). For comparison, 100 μg/ml of AHA were only moderately mutagenic (compare Fig. 3A and Fig. 3E, left panel). Furthermore, both HAP and AHA did not affect the viability of the wild-type strain, even at the maximal concentration of 100 μg/ml (Fig. 3A and 3E, right panel).
In the ham1 strain, 1 μg/ml of HAP induced Canr mutants with the similar frequency that was observed in the wild-type strain at 2 orders in magnitude higher concentration of analog, 100 μg/ml (compare Fig. 3A and 3B, left panel, phenotype of hypermutability, HM). The hypersensitivity of the ham1 mutant to the toxic action of HAP was clearly detectable at 100 μg/ml of HAP (Fig. 3B, right panel). We will refer later to this phenotype as hypersensitivity, HS. Note that a reduction of the number of canavanine-resistant clones at 10 and 100 μg/ml of HAP, in comparison with 1 μg/ml of HAP observed in the ham1 mutant (Fig. 3B, left panel, another manifestation of hypersensitivity phenotype, HS), is also due to a dramatic decrease of survival. When the aah1 mutant was tested (Fig. 3B, second row, for HAP and Fig. 3F, first row, for AHA), the drop of viability was less severe than that for the ham1 mutant (phenotype of elevated sensitivity, S). HAP-induced mutagenesis was detectable at a low dose of 1 μg/ml, but was much less compared to the ham1 mutant (phenotype of elevated mutability, M). Mutagenesis was somewhat stronger at the dose 10 μg/ml and was not seen at 100 μg/ml (another manifestation of elevated sensitivity, S). For the aah1 mutant, AHA-induced mutagenesis was moderate at the dose of 10 μg/ml and very strong at a concentration of 100 μg/ml. The aah1 mutant exemplified what we expect to observe for mutants moderately sensitive to both HAP and AHA. These data suggested that the procedure we devised for micro-titre plate format is effective for the detection of mutants with altered parameters of HAP and AHA sensitivity and mutability.
Figure 3 Results of the screening of the yeast deletion library for elevated mutagenesis and sensitivity in micro-titer plates. Left panel – Mutagenesis on selective plates with canavanine. Right panel – The estimation of the number of colony-forming units on YPD medium.
Screening of the deletion strains library
We screened the yeast deletion strains library as described above. After an initial screening of 4,823 deletion strains, 43 mutants strains appeared to affect base analog-induced killing or mutagenesis. However, in subsequent testing of candidate strains in same type of plate tests, we have confirmed HAP-sensitivity of 16 mutants (Fig. 3, Table 1, column 4, where we refer to phenotypes of mutants according to abbreviations described in previous section). Next, we examined the mutability and survival of these 16 mutants in quantitative tests with HAP (see Materials and Methods). Based on the results of these two types of tests, we categorize HAP-sensitive strains in three groups, as shown in Table 1. Group I comprises, in addition to ham1 and aah1 strains, mutants ade12 and ade2. These strains were hypersensitive to the mutagenic and lethal action of HAP in both types of tests (Fig. 3 and Table 1, columns 4–6). Strains of this group were sensitive to the low doses (1 and/or 10 μg/ml) of HAP, in contrast to the wild-type strain. The ade12 mutant was almost as mutable as the ham1 strain, but the hypermutability could only be demonstrated in a quantitative test, due to poor plating efficiency (compare Fig 3B, row 3 and Table 1, column 5, row 3). The ade2 mutant was as mutable as the aah1 mutant (Table 1). Deletion mutants of the first group showed variable degree of sensitivity to HAP-induced killing Table 1, column 6).
Table 1 HAP-sensitivity of the mutants selected in our screening.
Class of mutants Gene or ORF name deleted Functional group Response HAP in spot tests† Induced mutant frequency (×10-7) by HAP# Survival in presence of HAP#
Wild type - 400 100%
Class I: mutants hypersensitive to HAP HAM1 DNA1 HM, HS 13000 17%
ADE12* DNA HM, HS 10000 30%
AAH1* DNA M, S 5500 30%
ADE2 DNA M, S 4400 70%
II class: Mutants sensitive to mutagenic effect of HAP VIP1 Cell2 M, S 840 76%
VID27 Metabolic3 M, S 600° 82%
IPK1 Metabolic M, S 1400 100%
ADE5,7 DNA M 1900 100%
ADE8 DNA M 1500 100%
ADE6 DNA M 1100 100%
RIM101 meiosis M 1100 100%
ADE3 DNA M 940 100%
ADE1 DNA M 860 100%
YGR035c unknown M 500° 100%
Yjl055w* Metabolic M 500° 100%
Class III: Mutants sensitive to killing YMl013c-a Unknown S 230° 60%
SHE4 Cell S 600° 30%
TRP2 Metabolic HS 250° 60%
†- HM – hypermutable, M – more mutable than wild-type, HS – hypersensitive, S – more sensitive than wild-type, see first paragraph od the Results Section for the explanation.
# – 25 μg/ml
1 – 'DNA' – includes genes involved in the control of DNA precursor metabolism, purine salvage, DNA repair.
2 – 'Cell' – includes genes involved in cytoskeleton organization, cell walls and organelles.
3 – 'Metabolic' – includes genes involved in general metabolic pathways.
* – These mutants were also sensitive to the mutagenic or toxic effect of AHA (see Fig. 3).
° – small difference from the wild-type strain was reproducible and statistically significant by Wilcoxon-Mann-Whitney test.
Eleven mutants fall into Group II. Mutants of this class were sensitive to the mutagenic effect of HAP, but their growth was not severely inhibited on HAP-containing medium. As a result, there is a smaller difference, in comparison to mutants of the group I, or no difference in the number of Canr mutants induced by 10 and 100 μg/ml of HAP in spot-tests (Fig. 3C, Table 1, column 4). These strains produced some HAP-induced Canr mutants at 10 μg/ml of HAP, whereas the parental strain was non-mutable at this HAP concentration. We also did not detect any substantial drops of viability after growth in liquid media containing 25 μg/ml of HAP (Table 1, column 6). Group II was not homogeneous in respect to HAP mutability and sensitivity. The six most sensitive mutants in the group are vip1, vid27, ade1, ade5,7, ade6, ade8, ipk1 and rim101 (see Table 1). These mutants showed a decrease in the number of Canr mutants in a qualitative test when concentration of HAP increased ten-fold (up to 100 μg/ml), which is an indication of some cell death at very high doses of HAP (Fig. 3C). Mutants yjl055w, ygr035c, and ade3 were more resistant to HAP, since the number of Canr colonies was similar at 10 and 100 μg/ml of HAP. As could be seen from the results of quantitative assay, mutant classification is quite conditional and there is substantial variation in responses between mutants of the Group II, but all of them were more mutable that the wild-type strain.
Finally, Group III includes mutants she4, trp2, and yml013c-a; which were sensitive to HAP-induced killing, but not to HAP-induced mutagenesis (Fig. 3D and Table 1, column 6). In quantitative tests the yml013c-a and trp2 mutants were even less sensitive to the mutagenic action of HAP than the wild-type strain (Table 1). The she2 mutant was slightly more mutable that the wild-type strain only in quantitative test. The existence of such a type of mutants suggests that the toxic effect of HAP in yeast may be not only due to the induction of lethal mutations, but also due to inhibition of certain metabolic pathways.
In the present study, we have also characterized three AHA-sensitive mutants, aah1, ade12, and yjl055w (Fig. 3E and 3F). Remarkably, all of these mutants were also sensitive to HAP (Fig. 3C and Table 1). Two of those mutants, aah1 and yjl055w, were AHA-hypermutable; whereas ade12 strain did not mutate in the presence of AHA, but was sensitive to AHA-induced killing. In a quantitative test, 50 μg/ml of AHA did not inhibit survival of the wild-type strain, aah1 and yjl055w strains; whereas survival of the ade12 mutant was reduced to 50%. In the aah1 and yjl055w strains, 50 μg/ml of AHA induced canavanine-resistant mutants with the frequencies 120 × 10-7 and 270 × 10-7, respectively, that was 4–9-folds higher than observed in the wild-type and ade12 strains (30 × 10-7, in both strains).
Discussion
In this study, we elaborated the technology for testing base analog-induced mutability and killing of thousands of yeast strains in microtiter format (see Fig. 2). We found that the method is quite sensitive and reliable. Next, we screened the library of haploid yeast strains carrying deletions in all nonessential ORFs for the sensitivity to mutagenic base analogs HAP and AHA. We have found 16 novel HAP-sensitive mutants that fall into several groups, based on the sensitivity profiles (Fig. 3 and Table 1). One group comprises the mutants that are HAP-hypermutable and grow poorly in the presence of HAP. Another class comprises strains with elevated HAP-mutability that grow normally on medium containing HAP. Finally, the third group includes the mutants sensitive to HAP-induced killing, but not to HAP-induced mutagenesis. We have also isolated three AHA-sensitive mutants. All of them were HAP sensitive as well. We summarized the properties of the genes found in our screening in Additional file 1.
One interesting result from our study is that none of the genes involved in the control of base analogs sensitivity except two genes, YML013c-a and ade12, were found in screenings for genes controlling sensitivity to the other types of mutagens, MMS, UV, and ionizing radiation [23-27] or for elevated spontaneous mutagenesis [28]. It was previously reported that deletion of the YML013c-a and ADE12 open reading frame specifically enhanced sensitivity to killing (as in case of HAP) induced by γ-radiation and bleomycin, but did not affect sensitivity to MMS, UV, and hydroxyurea [23,30]. It is known that there are overlaps of the sets of genes detected in genome screenings for the MMS-, UV- or ionizing radiation-sensitive strains [29]. Usually, those spectra include genes controlling DNA replication, recombination, and DNA repair. In our study, we did not find any of those genes. This is consistent with our earlier observation that the mutagenic action of HAP in S. cerevisiae does not depend on nucleotide excision repair, mutagenic repair, and mismatch repair [16]. A system to repair non-canonical purines and, probably HAP and AHA, in DNA has been recently characterized in E. coli [9,10]. It is possible that yeast S. cerevisiae lacks such a repair system.
Based on our data, we propose that, in yeast, the major base analogs protective mechanism is a control of the quality of DNA precursor pool that prevents incorporation of base analogs into DNA. This mechanism may work at several levels: transport of analogs into cells, detoxification of analogs by metabolic enzymes, maintenance of nucleotide pools, and fidelity control of DNA replication (Fig. 4). HAP and AHA are likely transported into the yeast cell by the same permeases, which are involved in transport of natural purines. One candidate is purine-cytosine permease, Fcy2p, a major purine (adenine, guanine, and hypoxanthine) and cytosine transporter in yeast [31]. According to our unpublished data, fcy2 mutants are resistant to HAP. Thus, the active transport of HAP is the first critical step in the HAP mutagenic pathway. The next step is a conversion of the base analog to the corresponding ribonucleoside monophosphate by enzymes of the purine salvage pathway. Previously we observed that the inactivation of the APT1 gene, encoding adenine phosphoribosyl transferase, led to a severe decrease of the mutagenic effect of HAP [16], suggesting that this enzyme plays a key role in the biosynthesis of HAP-riboside-5'-monophosphate (HAPMP). HAPMP then may be converted to the corresponding nucleoside triphosphate, which could be ambiguously incorporated into DNA by DNA polymerases and provoke replication errors in the subsequent replication cycles [13].
The mechanism preventing HAP- and AHA-induced toxicity most likely involves the conversion of base analogs to non-mutagenic metabolites by purine salvage enzymes. The main argument for this hypothesis is that HAP could be utilized by yeast cells as a sole purine source [13,18,32]. The first enzyme in this HAP and AHA detoxification pathway is adenine aminohydrolase, encoded by the AAH1 gene. Aah1p from several microorganisms has been biochemically characterized (see [33]). Is has a broad substrate specificity and is capable of converting both adenine and its six-substituted analogs into hypoxanthine in vitro. According to our data, yeast Aah1p may convert HAP to hypoxanthine [12] and AHA to guanine in vivo, since the inactivation of the AAH1 leads to a defect in this conversion that is readily detected by UV spectroscopy of yeast medium (unpublished observation). In the aah1 mutant, the base analog intracellular concentration increases. We propose that this causes the elevation of base analog-induced mutagenesis (Fig. 3B and 3E, Table 1).
Interestingly, in our screening we did not detect the amd1 mutant, deficient in AMP aminohydrolase, that catalyze deamination of AMP to IMP [34]. We disrupted this gene by the kanMX cassette in several yeast strains and did not see any effect on HAP-induced mutagenesis anywhere. Thus, deamination of HAP at the mononucleotide level does not play an important role in HAP detoxification. This can be due to several reasons: the inability of the Amd1p to hydrolyse HAPMP, the minor role of the AMD1 gene in yeast, or the short life-time of the HAPMP in yeast cells.
We have found that inactivation of adenilosuccinate synthase (ASS or Ade12p) encoded by the ADE12 gene strongly enhanced HAP-induced mutagenesis and AHA-induced killing (see Fig. 3B and 3F, and Table 1). The primary function of this enzyme is the conversion of IMP to SAMP in the pathway of AMP biosynthesis de novo (Fig. 4). We propose that the reason for this hypersensitivity is the dysregulation of purine biosynthesis, as follows. First, the blocking of this step of purine biosynthesis causes accumulation of IMP in the cell. The excess of IMP is probably toxic for the cell, since ade12 mutants have a slow-growth phenotype that can be rescued by blocks of the earlier steps of the de novo purine biosynthesis pathway (Dr. A. M. Zekhnov {St-Petersburg State University}, personal communication). Accumulated IMP can be phosphorylated to ITP by nucleotide phosporylases. Thus, we propose that, in the ade12 mutant, an excess of ITP may saturate Ham1p triphosphatase, an essential enzyme for the destruction of HAPTP and dHAPTP, which leads to increased HAP-sensitivity (see Fig. 3). The data obtained recently in bacteria are consistent with this hypothesis. It was shown that, in vitro, E. coli Ham1p homologues protein, RdgB, is a triphosphatase that acts to hydrolize non-canonical DNA precursors, dIPT and dXTP. The Ham1p protein was shown to possess a similar activity on dITP, dXTP, and dHAPTP substrates (Kozmin and Pavlov, unpublished; Burgis and Cunnigham, personal communication; and see refs. [19-21]). In E. coli, the rdgB mutation is synthetically lethal with recA. As proposed, absence of RdgB leads to a dramatic increase of hypoxanthine and xanthine in DNA. Accordingly, base excision repair of such modified bases occurring in opposite strands may generate double strand breaks that require the RecA function to be repaired. However, over-expression of adenilosuccinate synthase PurA (homolog of yeast Ade12p) suppresses this lethality [9]. This suggests a critical role of ASS in the regulation of intracellular concentration of genotoxic hypoxanthine-containing nucleotides.
We found that certain mutations affecting IMP biosynthesis de novo enhance HAP-induced mutagenesis (Table 1). Seven of sixteen newly identified genes controlling HAP and AHA sensitivity are involved in AMP biosynthesis (see Additional file 1 and Fig. 3). It is known that the regulation of the AMP biosynthesis pathway by adenine is mediated by SAICAR, one of the precursors in adenine biosynthesis de novo [35]. The accumulation of certain purine biosynthesis by-products may play a role in the regulation of the nucleotide pool. A defect in endogenous purine biosynthesis probably alters nucleotide pools to favour dHAPTP mis-incorporation into DNA or leads to HAP toxicity. In respect to this hypothesis, it is important that there is a difference in the level of HAP-induced mutagenesis among the strains carrying mutations in the genes of AMP biosynthesis. The less sensitive mutant is ade3 (Fig. 3 and Table 1). The ADE3 does not directly control any steps of purine biosynthesis. It encodes the C1-tetrahydrofolate synthase that provides C1-tetrahydrofolate, an indispensable precursor for AMP, histidine, thymidylate, and methionine biosynthesis (see Fig. 4). In this respect it is of interest that ade4, ade16 and ade17 mutants, also defective in IMP biosynthesis, were not found in our screen and were not sensitive to HAP or AHA when constructed de novo and tested directly (data not shown). The ADE4 stands apart because PRPP, a substrate of the product of the ADE4 gene, serves as a precursor for additional biosynthetic pathways. This prevents by-product accumulation and might be one of the explanations of lack of HAP sensitivity of the ade4 mutants. The single ade16 and ade17 mutants also do not lead to byproduct accumulation because ADE16 and ADE17 are isozymes and the inactivation of one gene does not block the pathway.
Figure 4 Purine salvage and purine biosynthesis de novo in yeast Saccharomyces cerevisiae. Intermediates of the purine biosynthesis de novo are designated in blue. The salvage pathway is presented in black. Genes, whose deletions lead to HAP and/or AHA sensitivity are highlighted by red boxes. The proposed conversions of HAP and AHA are represented in brackets below the adenine and guanine metabolites, respectively. Dashed arrows represent hypothetical pathways that were not demonstrated experimentally for a given substrate. Abbreviations:Purine biosynthesis de novo: PRPP – 5-phospho-ribosyl-1α-pyrophosphate, PRA – 5-phospho-β-D-ribosylamine, GAR – 5-phosphoribosylglycinamide, FGAR – 5'-phosphoribosyl-N-formyl glycinamide, FGAM – 5'-phosphoribosyl-N-formylglycinamidine, AIR – 5'-phosphoribosyl-5-aminoimidazole, CAIR – 5'-phosphoribosyl-5-aminoimidazole-4-carboxylate, SAICAR – 5'-phosphoribosyl-4-(N-succinocarboxamide)-5-aminoimidazole, AICAR – 5'-phosphoribosyl-4-carboxamide-5-aminoimidazole, FAICAR – 5'-phosphoribosyl-4-carboxamide-5-formamidoimidazole, SAMP – adenylosuccinate, 5,10-methylene-THF – 5,10-methylenetetrahydrofolate, 10-formyl-THF – 10-formyltetrahydrofolate. Salvage: Ade – adenine, AdeRib – adenosine, Hyp – hypoxanthine, Gua – guanine, Xan – xanthine.
We have found that 6 genes detected in our screening, VIP1, VID27, IPK1, YGR035c, YML013c-a and SHE4, are putatively involved in cell organization or genetically interact with cell-cycle control genes (see Additional file 1). This observation provides new perspectives on the mechanisms of base analogs-induced mutagenesis. It is possible that there is a specific structural route, mediated by cell cycle and cytoskeleton components, initiated by penetration of the analog inside the cell to its final target. We have also identified several hypothetical genes critical for the HAP and/or AHA resistance. This may be an initial clue to their functional significance.
Finally, we would like to mention that out of the 18 genes we found to be involved in HAP and AHA sensitivity control, 11 (60%) have orthologs in all groups of organisms, including mammals. Therefore, the results have relevance to higher eukaryotes and humans as well (see Additional file 1).
Conclusion
We identified novel mutants sensitive to mutagenic and toxic effects of purine base analogs. AHA sensitivity was not previously described for three of the mutants identified in this study. The results reveal a complex control of base analogue mutagenesis by genes encoding the components of metabolic pathways and cytoskeleton.
Methods
Yeast strains and media
We have used a set of 4,823 S. cerevisiae mutants carrying deletions of all non-essential ORFs created in the haploid strain BY4742 (MATα his3Δleu2Δlys2Δura3Δ). The information about the deletion strains set is available from the Yeast Deletion Project site: . Deletion strains were constructed by replacement of the ORF's with the kanMX4 cassette, which confers resistance to geneticin [36].
The standard yeast complete media (YPD) and minimal synthetic media (SD) were used [37]. Deletion strains were cultivated on YPD medium, supplemented with 200 μg/ml of geneticin. Sensitivity to HAP and AHA was examined on YPD media containing analogs in concentrations 100 μg/ml, 10 μg/ml and 1 μg/ml. SD medium containing 40 μg/ml of L-canavanine was used for the selection of Canr mutants.
Base analogs sensitivity tests
HAP was purchased from MP Biomedicals (Irvine, California, USA). AHA was custom- synthesized by Dr. I. Kuchuk at the Department of Chemistry of Indiana University (Bloomington, Indiana, USA) by the method of Janion [38]. Both chemicals were dissolved in DMSO (Fisher, USA) with mild heating. A single colony of each tested strain was inoculated into a well of 96-well microtitre plate containing 200 μl of liquid YPD medium (see Fig. 2). Microtiter plates were incubated for 2 days at 30°C with agitation, to reach a stationary phase (approximately 108 cells/ml). For mutagenesis assay, cells were then plated by a multiprong replicator device (approximately 5 μl of cell suspension per prong) to the YPD plates containing various concentrations of HAP or AHA, as shown on Fig. 2. After one day of incubation, the plates were replica-plated on SD minimal-medium plates containing L-canavanine. The plates were incubated 5 days and inspected for induction of Canr mutants.
For the survival test, cell cultures from the microplates were diluted in water in series of 96-well microplates, using a multichanel pipette (see Fig. 2). Diluted cells suspensions were plated to YPD plates containing HAP or AHA by a multiprong replicator device. After 2–3 days of incubation, the number of colonies was recorded. Strains that produced smaller colonies or a smaller number of colonies on the HAP-containing medium, relatively to wild-type strain, were classified as sensitive to killing.
Quantitative assay of the base analog-induced mutagenesis
For each strain and each concentration of base analogs to be tested, we prepared six independent cultures by inoculating a single colony into 1 ml of liquid YPD medium with or without mutagens. After two days incubation in the roller drum, the mutant frequencies were determined by plating of appropriately diluted cell suspensions on minimal-medium SD plates supplemented with L-canavanine (to determine the number of canavanine-resistant cells per culture), and on YPD plates (to obtain the total number of cells per culture). Then the frequency of mutants was calculated as described [14]. Each experiment was repeated at least three times. We have used several doses of HAP and found that in this type of test the most reproducible results are obtained at dose 25 μg/ml. The statistical significance of differences between variants was estimated by Wilcoxon-Mann-Whitney nonparametric criterion.
Authors' contributions
Youri Pavlov and Elena Stepchenkova designed this study. Elena Stepchenkova performed the experimental work and wrote the initial draft of the manuscript. Vladimir Alenin, Youri Pavlov, Stanislav Kozmin, and Elena Stepchenkova analyzed the data set and wrote the final version of the paper.
Supplementary Material
Additional File 1
Annotation of the genes whose deletion results in HAP and AHA sensitivity
Click here for file
Acknowledgements
We are grateful to Polina Shcherbakova for comments during this study and for critical reading of the manuscript. This work was supported in part, by NE DHHS LB506 grant #9934 for YIP, and by the CRDF grant provided by The Russian Ministry of Education # ST-012-0.
==== Refs
Hochhauser SJ Weiss B Escherichia coli mutants deficient in deoxyuridine triphosphatase J Bacteriol 1978 134 157 166 148458
Michaels ML Miller JH The GO system protects organisms from the mutagenic effect of the spontaneous lesion 8-hydroxyguanine (7,8-dihydro-8-oxoguanine) J Bacteriol 1992 174 6321 6325 1328155
Grollman AP Moriya M Mutagenesis by 8-oxoguanine: an enemy within Trends Genet 1993 9 246 249 8379000 10.1016/0168-9525(93)90089-Z
Kamiya H Mutagenic potentials of damaged nucleic acids produced by reactive oxygen/nitrogen species: approaches using synthetic oligonucleotides and nucleotides: survey and summary Nucleic Acids Res 2003 31 517 531 12527759 10.1093/nar/gkg137
Maki H Sekiguchi M MutT protein specifically hydrolyses a potent mutagenic substrate for DNA synthesis Nature 1992 355 273 275 1309939 10.1038/355273a0
Pavlov YI Noskov VN Lange EK Moiseeva EV Pshenichnov MR Khromov-Borisov NN The genetic activity of N6-hydroxyadenine and 2-amino-N6-hydroxyadenine in Escherichia coli, Salmonella typhimurium and Saccharomyces cerevisiae Mutat Res 1991 253 33 46 1870608
de Serres FJ The genetic toxicology of 2-amino-N6-hydroxyadenine in eukaryotic organisms: significance for genetic risk assessment Mutat Res 1991 253 5 15 1870610
Simandan T Sun J Dix TA Oxidation of DNA bases, deoxyribonucleosides and homopolymers by peroxyl radicals Biochem J 1998 335 233 240 9761719
Burgis NE Brucker JJ Cunningham RP Repair system for noncanonical purines in Escherichia coli J Bacteriol 2003 185 3101 3110 12730170 10.1128/JB.185.10.3101-3110.2003
Bradshaw JS Kuzminov A RdgB acts to avoid chromosome fragmentation in Escherichia coli Mol Microbiol 2003 48 1711 1725 12791149 10.1046/j.1365-2958.2003.03540.x
Kouzminova EA Rotman E Macomber L Zhang J Kuzminov A RecA-dependent mutants in Escherichia coli reveal strategies to avoid chromosomal fragmentation Proc Natl Acad Sci U S A 2004 101 16262 16267 15531636 10.1073/pnas.0405943101
Noskov V Negishi K Ono A Matsuda A Ono B Hayatsu H Mutagenicity of 5-bromouracil and N6-hydroxyadenine studied by yeast oligonucleotide transformation assay Mutat Res 1994 308 43 51 7516485
Noskov VN Staak K Shcherbakova PV Kozmin SG Negishi K Ono BC Hayatsu H Pavlov YI HAM1, the gene controlling 6-N-hydroxylaminopurine sensitivity and mutagenesis in the yeast Saccharomyces cerevisiae Yeast 1996 12 17 29 8789257 10.1002/(SICI)1097-0061(199601)12:1<17::AID-YEA875>3.3.CO;2-9
Shcherbakova PV Noskov VN Pshenichnov MR Pavlov YI Base analog 6-N-hydroxylaminopurine mutagenesis in the yeast Saccharomyces cerevisiae is controlled by replicative DNA polymerases Mutat Res 1996 369 33 44 8700180
Shcherbakova PV Pavlov YI 3'–>5' exonucleases of DNA polymerases epsilon and delta correct base analog induced DNA replication errors on opposite DNA strands in Saccharomyces cerevisiae Genetics 1996 142 717 726 8849882
Kozmin SG Schaaper RM Shcherbakova PV Kulikov VN Noskov VN Guetsova ML Alenin VV Rogozin IB Makarova KS Pavlov YI Multiple antimutagenesis mechanisms affect mutagenic activity and specificity of the base analog 6-N-hydroxylaminopurine in bacteria and yeast Mutat Res 1998 402 41 50 9675240
Kozmin SG Pavlov YI Dunn RL Schaaper RM Hypersensitivity of Escherichia coli Δ(uvrB-bio) mutants to 6-hydroxylaminopurine and other base analogs is due to a defect in molybdenum cofactor biosynthesis J Bacteriol 2000 182 3361 3367 10852865 10.1128/JB.182.12.3361-3367.2000
Pavlov Iu I [Mutants of Saccharomyces cerevisiae supersensitive to the mutagenic effect of 6-N-hydroxylaminopurine] Genetika 1986 22 2235 2243 3533720
Hwang KY Chung JH Kim SH Han YS Cho Y Structure-based identification of a novel NTPase from Methanococcus jannaschii Nat Struct Biol 1999 6 691 696 10404228 10.1038/10745
Chung JH Park HY Lee JH Jang Y Identification of the dITP- and XTP-hydrolyzing protein from Escherichia coli J Biochem Mol Biol 2002 35 403 408 12297000
Lin S McLennan AG Ying K Wang Z Gu S Jin H Wu C Liu W Yuan Y Tang R Cloning, expression, and characterization of a human inosine triphosphate pyrophosphatase encoded by the ITPA gene J Biol Chem 2001 276 18695 18701 11278832 10.1074/jbc.M011084200
Giaever G Chu AM Ni L Connelly C Riles L Veronneau S Dow S Lucau-Danila A Anderson K Andre B Functional profiling of the Saccharomyces cerevisiae genome Nature 2002 418 387 391 12140549 10.1038/nature00935
Bennett CB Lewis LK Karthikeyan G Lobachev KS Jin YH Sterling JF Snipe JR Resnick MA Genes required for ionizing radiation resistance in yeast Nat Genet 2001 29 426 434 11726929 10.1038/ng778
Birrell GW Giaever G Chu AM Davis RW Brown JM A genome-wide screen in Saccharomyces cerevisiae for genes affecting UV radiation sensitivity Proc Natl Acad Sci U S A 2001 98 12608 12613 Epub 12001 Oct 12616. 11606770 10.1073/pnas.231366398
Chang M Bellaoui M Boone C Brown GW A genome-wide screen for methyl methanesulfonate-sensitive mutants reveals genes required for S phase progression in the presence of DNA damage Proc Natl Acad Sci U S A 2002 99 16934 16939 Epub 12002 Dec 16913. 12482937 10.1073/pnas.262669299
Game JC Birrell GW Brown JA Shibata T Baccari C Chu AM Williamson MS Brown JM Use of a genome-wide approach to identify new genes that control resistance of Saccharomyces cerevisiae to ionizing radiation Radiat Res 2003 160 14 24 12816519
Davis-Kaplan SR Ward DM Shiflett SL Kaplan J Genome-wide analysis of iron-dependent growth reveals a novel yeast gene required for vacuolar acidification J Biol Chem 2004 279 4322 4329 14594803 10.1074/jbc.M310680200
Huang ME Rio AG Nicolas A Kolodner RD A genomewide screen in Saccharomyces cerevisiae for genes that suppress the accumulation of mutations Proc Natl Acad Sci U S A 2003 100 11529 11534 12972632 10.1073/pnas.2035018100
Begley TJ Samson LD Network responses to DNA damaging agents DNA Repair (Amst) 2004 3 1123 1132 15279801 10.1016/j.dnarep.2004.03.013
Westmoreland TJ Marks JR Olson JA JrThompson EM Resnick MA Bennett CB Cell cycle progression in G1 and S phases is CCR4 dependent following ionizing radiation or replication stress in Saccharomyces cerevisiae Eukaryot Cell 2004 3 430 446 15075273 10.1128/EC.3.2.430-446.2004
Weber E Rodriguez C Chevallier MR Jund R The purine-cytosine permease gene of Saccharomyces cerevisiae : primary structure and deduced protein sequence of the FCY2 gene product Mol Microbiol 1990 4 585 596 2191181
Koz'min SG Domkin VD Zekhnov AM Pavlov Iu I [Genetic control of metabolism of a mutagenic analog of 6-N-hydroxylaminopurine bases in Saccharomyces cerevisiae yeasts] Genetika 1997 33 591 598 9273315
Hartenstein RC Fridovich I Adenine aminohydrolase. An investigation of specificity J Biol Chem 1967 242 740 746 6017742
Sollitti P Merkler DJ Estupinan B Schramm VL Yeast AMP deaminase. Catalytic activity in Schizosaccharomyces pombe and chromosomal location in Saccharomyces cerevisiae J Biol Chem 1993 268 4549 4555 8440738
Rebora K Desmoucelles C Borne F Pinson B Daignan-Fornier B Yeast AMP pathway genes respond to adenine through regulated synthesis of a metabolic intermediate Mol Cell Biol 2001 21 7901 7912 11689683 10.1128/MCB.21.23.7901-7912.2001
Wach A Brachat A Pohlmann R Philippsen P New heterologous modules for classical or PCR-based gene disruptions in Saccharomyces cerevisiae Yeast 1994 10 1793 1808 7747518
Rose M Winston F Hieter P Methods in Yeast Genetics. A Laboratory Course Manual 1990 Cold Spring Harbor, NY: Cold Spring Harbor Laboratory Press
Janion C The synthesis and properties of N6-substituted 2-amino-purine derivatives Acta Biochim Pol 1976 23 57 68 7092
| 15932646 | PMC1173102 | CC BY | 2021-01-04 16:38:18 | no | BMC Genet. 2005 Jun 2; 6:31 | utf-8 | BMC Genet | 2,005 | 10.1186/1471-2156-6-31 | oa_comm |
==== Front
BMC GenomicsBMC Genomics1471-2164BioMed Central London 1471-2164-6-791592153310.1186/1471-2164-6-79DatabaseBcipep: A database of B-cell epitopes Saha Sudipto [email protected] Manoj [email protected] Gajendra PS [email protected] Institute of Microbial Technology Chandigarh, India2005 29 5 2005 6 79 79 30 9 2004 29 5 2005 Copyright © 2005 Saha et al; licensee BioMed Central Ltd.2005Saha et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Bcipep is a database of experimentally determined linear B-cell epitopes of varying immunogenicity collected from literature and other publicly available databases.
Results
The current version of Bcipep database contains 3031 entries that include 763 immunodominant, 1797 immunogenic and 471 null-immunogenic epitopes. It covers a wide range of pathogenic organisms like viruses, bacteria, protozoa, and fungi. The database provides a set of tools for the analysis and extraction of data that includes keyword search, peptide mapping and BLAST search. It also provides hyperlinks to various databases such as GenBank, PDB, SWISS-PROT and MHCBN.
Conclusion
A comprehensive database of B-cell epitopes called Bcipep has been developed that covers information on epitopes from a wide range of pathogens. The Bcipep will be source of information for investigators involved in peptide-based vaccine design, disease diagnosis and research in allergy. It should also be a promising data source for the development and evaluation of methods for prediction of B-cell epitopes. The database is available at .
==== Body
Background
The antigenic regions of protein recognized by the binding sites of immunoglobulin molecules are called B-cell epitopes [1]. These epitopes can be classified into two categories; i) conformational/discontinuous epitope, where residues are distantly separated in the sequence and brought into physical proximity by protein folding and, ii) linear/continuous epitope, comprised of a single continuous stretch of amino acids within a protein sequence that can react with anti-protein antibodies [2,3]. Most of the B-cell epitopes were thought to be discontinuous. However, in late 1980s it was shown that this conformational restriction is not a necessary condition for the production of protein-reactive anti-peptide antibodies [4]. The designing of the conformational epitopes is difficult and so experimental B-cell epitopes largely include linear epitopes. These linear epitopes can be exploited in the development of synthetic vaccines and disease diagnosis. A number of vaccines based on B-cell epitopes are currently under clinical phase trials against viruses [5], bacteria [6] and cancer [7]. These epitopes are also important for allergy research and in determining cross-reactivity of IgE-type epitopes of allergens [8].
A large number of B-cell epitopes have been reported in the literature in last two decades. There is a need to collect and compile these epitopes to evaluate the performance of existing B-cell epitope prediction methods and to further develop better methods [9,10]. We have observed that the performance of the existing physico-chemical scales is not very high [11]. Recently, Blythe and Flower examined 484 amino acid propensity scales in predicting of B-cell epitopes and found that even the best set of scales and parameters performed only marginally better than random [12]. The evaluation of the existing scales indicates that there is a need to develop better methods by using artificial intelligence techniques. The collection of B-cell epitopes should help in deriving new scales for accurate in silico prediction of linear epitopes. Also it will help the immunologist to understand the complex nature of immunogenic peptides and for the development of vaccines. There are many databases available on T-cell epitopes [13-15]. In contrast, there are limited number of databases on B-cell epitope for example JenPep [16,17] and HIVDB [18]. Recently, JenPep has been superseded by AntiJen 2.0, which has included peptides bound to MHC ligand, TCR-MHC Complexes, T cell epitope, TAP, B cell epitope molecules and immunological protein-protein interactions. AntiJen also contains peptide library, copy numbers and diffusion coefficient data. Though AntiJen provides information about different types of peptides (>24000 entries) from a single source but it provides limited information about B-cell epitopes and tools to analyze and retrieve the data. Recently, we have created a comprehensive database, Bcipep, of B-cell epitopes. Latest version of Bcipep contains 3031 entries, where each entry provides detailed description of a B-cell epitope. Currently, we have covered only the continuous B-cell epitopes. The aim of this database is to assist the scientific community working in the areas of synthetic peptide vaccines (based on B-cell epitopes) and allergy research. The database will complement the existing databases such as AntiJen [16,17].
Availability
The database is available at , (Mirror Site) and (SRS version).
Database construction
The PostgreSQL relational database management system (RDBMS) has been used for storing, retrieval and managing the data. The scripts, which provide interface between user and database, were written in PERL, CGIPerl and Pgperl. B-cell epitopes were collected from the literature (PubMed, ; ScienceDirect, ). A large number of HIV epitopes were extracted from a book [18].
Database description
The aim of Bcipep database is to provide; i) comprehensive information about B-cell epitopes, ii) tools for extraction and analysis of this information and, iii) hyperlinks to related databases. The overall architecture of Bcipep database is shown in Figure 1.
Figure 1 A schematic representation of Bcipep database.
Database information
General
This database provides compehensive information about the linear B-cell epitopes which includes; i) amino acid sequence of epitope, ii) source protein from which epitopes were obtained, iii) experimental methods used in accessing the immunogenic potential of epitopes, iv) pathogen group (e.g., bacteria, virus, fungi, protozoa) of source protein and, v) miscellaneous information in the 'Comment' field.
Immunogenicity and model organisms
The immunogenicity of a peptide is a semi-quantitative measure of its immunogenic potency. In Bcipep it is divided into three categories; i) immunodominant, if it increases 2–3 folds anti-peptide antibodies in comparison to reference or control (carrier protein, eg., BSA or KLH), ii) immunogenic, if it enhances anti-peptide antibodies by one-fold in comparison to reference, and iii) null-immunonogenic, where no difference was observed when compared to reference. This information is very important for developing B-cell epitope prediction method. The database also provides information about 'Model organism' used for immunization.
Antibodies and neutralization
The database provides full information about monoclonal or polyclonal antibodies produced against an epitope. The information includes, isotypes of immunoglobin and name/number of monoclonal antibodies. The database also contains information about neutralization potential of anti-peptide antibody, which is crucial for considering a peptide for synthetic vaccine design.
Links to databases
The Bcipep provides hyperlinks to various sequence databases in order to provide detailed information about peptides in database. The 'database reference' field consists name/code of protein available in SWISS-PROT [19]. The 'Antigenic structure' field consists of PDB codes [20] of protein structures having matching peptides. These PDB codes are linked to OCA browser in order to provide detailed structure information of these proteins. It also provides structure information about 242 antibodies, where each antibody is hyperlinked to PDB database through the OCA browser. The 'Publication reference' field provides full information about related publications with link to PUBMED [21]. Bcipep is also linked to MHCBN database [15] in order to identify the peptides that are B-cell as well as T-cell epitopes.
Web tools
Bcipep has following major web-based tools for retrieval and analysis of information in Bcipep database (Figure 1). These web tools have been designed to facilitate the user in retrieving information from database.
Keyword search
This option allows users to perform search on all fields of the database ('Peptide Sequence', 'Source Protein', 'Publication Reference', 'Database Reference'). One can restrict the keyword search on any specific field. It also allows users to select the fields to be displayed. An example of keyword search is shown in Figure 2a, where key word 'P26694' is searched in any filed of database. The output/result of this keyword search is shown in Figure 2b.
Figure 2 The typical display of Bcipep database for keyword search; a) input page of keyword search; and b) output of keyword search.
Peptide search
The database provides option to search a peptide in Bcipep. The tool will display full information about the peptides included in Bcipep. The server also permits users to search their query sequence in any pathogen group. Search can be restricted on the basis of immunogencity that is immunodominant, immunogenic or null-immunogenic. An example of input and output of peptide search is shown in Figures 3a and 3b respectively.
Figure 3 This example illustrate peptide search on Bcipep; a) Peptide search page; and b) result of peptide search.
Mapping of T-cell epitopes
This server allows searching of peptide in Bcipep against MHCBN database. The MHCBN database provides information about components of cell-mediated immunity like MHC binders/non-binders, T-cell epitopes and TAP binders [14]. The peptides related to cell-mediated immunity can be mapped on resultant B-cell epitopes obtained from keyword/peptide search by clicking on 'Peptide Sequence' field (Figures 2b and 3b). Thus, the server is useful in identifying the potential B-cell epitopes having T-cell epitopes (or MHC binders). The example of mapping of MHCBN peptides on B-cell epitope (by clicking on peptides sequence field of Figure 3b) is shown in Figure 4a. The full information of each map peptide can be obtained by clicking on the mapped sequence. One such example is shown in Figure 4a and 4b. The mapping allows user to detect the regions in B-cell epitope having promiscuous MHC binders (peptides that can bind to large number of MHC alleles) or T-cell epitopes.
Figure 4 Mapping of peptide in MHCBN database; a) mapping of MHCBN peptides on B-cell epitope, and b) full information about a MHCBN peptide.
Peptide mapping
The peptides of Bcipep can be mapped on query sequence using this option. The full information about mapped peptide can be obtained by clicking on it. The tool will assist the researchers in gaining knowledge about the known immunogenic or non-immunogenic regions in target protein of interest. The example input and output of peptide mapping is shown in Figures 5a and 5b respectively. The users can specify the pathogen group and/or immunogenicity level of peptides to be mapped on query sequence. As shown in Figure 5b, the graphical mapping of peptides/epitopes on query allows one to easily detect the regions that bind to large number of B-cell peptides.
Figure 5 Mapping of B-cell epitopes on antigen sequence, a) submission page of B-cell epitope mapping, and b) mapping results
BLAST search
This tool allows users to search their query protein against antigenic proteins maintained at Bcipep. The sequence of 1070 antigenic proteins has been obtained from SWISS-PROT. The similarity search is performed using the GWBLAST server . The GWBLAST also allows users to analyze the BLAST output like multiple alignments, phylogenetic analysis.
Online data submission
The database has the facility to submit data to Bcipep on-line via Internet. Users can submit information about their experimentally determined B-cell epitopes. We hope that immunologists will submit their information on B-cell epitope in Bcipep, similar to the sequence data at GenBank and SWISS-PROT. The Bcipep team will add more data from literature to maintain B-cell data up-to-date and cross check the data submitted by users to maintain quality of the data.
Potential utility and limitations
One of the major challenges in the field of subunit vaccine design is to identify the antigenic regions (B and T cell epitopes) that can generate antigen specific memory cells. Thus, the identification of regions/stretches on an antigen from the data pool of known epitopes is an important step in vaccine design. The Bcipep database would be very useful as it consists of comprehensive information about experimentally verified linear B-cell epitopes and tools for mapping these epitopes on an antigen sequence. In case query antigen contains known epitopes, this database might aid in the wet experimentation and lower the cost by reducing the overlapping repeats. This strategy is frequently used for the screening of transgenic proteins by searching linear IgE-binding epitopes [22]. Unlike discontinuous epitopes, the linear epitopes are easy to design, as they do not require tertiary structure information. Bcipep also provides information on neutralizing B-cell epitopes where an antibody generated against a B-cell epitope neutralizes the parent antigen. The current version of Bcipep provides neutralizing information on about 1309 such B-cell epitopes. This information is very important for selecting functional B-cell epitopes. This database also provides a link with MHCBN to search for overlapping regions of MHC binders and T-cell epitopes in the B-cell epitopes. Thus, the user can identify both antigenic regions that can activate B-cell and T-cell, which can lead to the development of better vaccine. The epitopes in Bcipep can be used to derive the rules for predicting B-cell epitopes.
The aim of designing synthetic linear peptides as epitope-vaccine is to induce neutralizing antibodies against the pathogen [23]. There are many reports that the linear B-cell epitopes were characterized as neutralizing antibodies as in Clostridium botulinum neurotoxin type A (Btx A)[24]. In Bcipep, there are 748 neutralizing anti-peptide antibodies entries. However, in some cases these linear epitope(s) fail to produce neutralizing antibodies and do not give protective immunity. For instance, it has been shown in the past that the antibodies against the synthetic peptides and short recombinant proteins of approximately 100 amino acids of hepatitis E virus (HEV) do not neutralize, suggesting that the HEV neutralization epitope(s) is conformation dependent [25]. The elicitation of a bactericidal and protective immune response to Borrelia burgdoferi decorin binding protein requires a properly folded conformation for the production of functional antibodies [26]. Recently, Corcoran et al, 2004, observed that B-cell memory is established and maintained against conformational epitopes of Parvovirus VP2 and against linear epitopes of VP1 but not against linear epitope VP2 [27]. Thus, it is not necessary that the linear B-cell epitope will always give rise to memory cells. One should also check the neutralizing information of B-epitopes, as only 748 B-cell epitopes out of 1309 in Bcipep were able to neutralize the parent protein.
For an effective use of Bcipep, it is important to understand the limitation of linear B-cell epitopes and data in Bcipep. The few limitations of current version of Bcipep are; i) it does not cover discontinuous epitopes, ii) it has limited number of unique peptides (1590) in 3031 entries and, iii) it contains peptides having only natural amino acids. One should be careful in using linear B-cell epitopes in developing epitope based subunit vaccine. The organism used for immunization (information included in the database) should also be taken into consideration, since immune response is T-helper cell (MHC-II-peptide complex) dependant and B-cell epitope alone may not generate protective antibodies [28]. In some cases, the nature of the adjuvant used and the route of immunization (information not included in the database) might also play important roles in the induction of protective anti-peptide antibody response against the pathogen [29-31].
Authors' contributions
SS collected and compiled the data as well as developed the web server. MB helped in designing website and stored data in PostgreSQL. GPSR conceived the idea and supervised the work.
Acknowledgements
Authors are thankful to Dr Grish C. Varshney for critically reading the manuscript. We are also thankful to Council of Scientific and Industrial Research (CSIR) and Department of Biotechnology (DBT), Govt. of India, for financial assistance.
==== Refs
Van Regenmortel MH Synthetic peptides versus natural antigens in immunoassaya Ann Biol Clin (Paris) 1993 51 39 41 7687834
Barlow DJ Edwards MS Thornton JM Continuous and discontinuous protein antigenic determinants Nature 1986 322 747 748 2427953 10.1038/322747a0
Langeveld JP martinez-Torrecuadrada J boshuizen RS Meloen RH Ignacio CJ Characterisation of a protective linear B cell epitope against feline parvoviruses Vaccine 2001 19 2352 2360 11257360 10.1016/S0264-410X(00)00526-0
Walter G Production and use of antibodies against synthetic peptides J Immunol Methods 1986 88 149 61 2420900 10.1016/0022-1759(86)90001-3
El Kasmi KC Muller CP New strategies for closing the gap of measles susceptibility in infants: towards vaccines compatible with current vaccination schedules Vaccine 2001 19 2238 2244 11257340 10.1016/S0264-410X(00)00452-7
Sabhanini L Manocha M Sridevi K Shashikiran D Rayanade R Rao DN Developing subunit immunogens using B and T cell epitopes and their constructs derived from F1 antigen of Yersinia pestis using novel delivery vehicles FEMS Immunol Med Microbiol 2003 1579 1 15
Kieber-Emmons T Luo P Qiu J Chang TY Insung O Blaszczyk-Thurin M Steplewski Z Vaccination with carbohydrate peptide mimotopes promotes anti-tumor responses Nat Biotechnol 1999 17 660 665 10404158 10.1038/10870
Selo I Clement G Bernard H Chatel J Creminon C Peltre G Wal J Allergy to bovine beta-lactoglobulin:specificity of human IgE to tryptic peptides Clin Exp Allergy 1999 29 1055 1063 10457108 10.1046/j.1365-2222.1999.00612.x
Odorico M Pellequer JL BEPITOPE: predicting the location of continuous epitope and patterns in proteins J Mol Recognit 16 20 22 12557235 10.1002/jmr.602
Alix AJ Predictive estimation of protein linear epitopes by using the program PEOPLE Vaccine 1999 18 311 314 10506656 10.1016/S0264-410X(99)00329-1
Saha S Raghava GPS Nicosia G, Cutello V, Bentley PJ, Timmis J BcePred: Prediction of continuous B-cell epitopes in antigenic sequences using physico-chemical properties ICARIS, LNCS 2004 3239 Springer 197 204
Blythe MJ Flower DR Benchmarking B cell epitope prediction: Underperformance of existing methods Protein Science 2005 14 246 248 15576553 10.1110/ps.041059505
Brusic V Rudy G Harrison LC MHCPEP, a database of MHC-binding peptides: update 1997 Nucleic Acids Res 1998 26 368 71 9399876 10.1093/nar/26.1.368
Rammensee H Bachmann J Emmerich NP Bachor OA Stevanovic S SYFPEITHI: database for MHC ligands and Peptide Motifs Immunogenetics 1999 50 213 219 10602881 10.1007/s002510050595
Bhasin M Singh H Raghava GPS MHCBN: A comprehensive database of MHC binding and non-binding peptides Bioinformatics 2003 19 666 667 10.1093/bioinformatics/btg055
Blythe MJ Doytchinova IA Flower DR JenPep: a database of quantitative functional peptide data for immunology Bioinformatics 2002 18 434 439 11934742 10.1093/bioinformatics/18.3.434
McSparron H Blythe MJ Zygouri C Doytchinova IA Flower DR JenPep: a novel computational information resource for immunobiology and vaccinology J Chem Inf Comput Sci 2003 43 1276 87 12870921 10.1021/ci030461e
Korber B Brander C Haynes B Koup R Kuiken C Moore J Walker B Watkins D HIV Monoclonal Antibodies "HIV Molecular Immunology 2001" 2002 Theoretical Biology and Biophysics group T-10, Mail Stop K710 Los Alamos national Laboratory, Los Alamus, New Mexico 87545 U.S.A IV-B-1 IV-B-278
Bairoch A Apweiler R The SWISS-PROT protein sequence database and its supplement TrEMBL in 2000 Nucleic Acids Res 2000 28 45 48 10592178 10.1093/nar/28.1.45
Westbrook J Feng Z Jain S Bhat TN Thanki N Ravichandran V Gilliland GL Bluhm WF Weissig H Greer DS Bourne PE Berman HM The Protein Data Bank: unifying the archive Nucleic Acids Res 2002 30 245 248 11752306 10.1093/nar/30.1.245
Wheller DL Church DM Lash AE Leipe DD Madden TL Pontius JU Schuler GD Schriml LM Tatusova TA Wagner L Rapp BA Database resources of National Center for Biotechnology Information: 2002 update Nucleic Acids Res 2002 30 13 16 11752242 10.1093/nar/30.1.13
Kleter GA Peijnenburg AA Screening of transgenic proteins expressed in transgenic food crops for the presence of short amino acid sequences identical to potential, IgE – binding linear epitopes of allergens BMC Structural Biology 2002
Xiao Y Lu Y Chen YH Epitope-vaccine as a new strategy against HIV-1 mutation Immunol Lett 2001 77 3 6 11348663 10.1016/S0165-2478(01)00187-0
Wu HC Yeh CT Huang YL Tarn LJ Lung CC Characterization of neutralizing antibodies and identification of neutralizing epitope mimics on the Clostridium botulinum neurotoxin type A Appl Environ Microbiol 2001 67 3201 3207 11425742 10.1128/AEM.67.7.3201-3207.2001
Meng J Dai X Chang JC Lopareva E Pillot J Fields HA Khudyakov YE Identification and characterization of the neutralization epitope(s) of the hepatitis E virus Virology 2001 288 203 211 11601892 10.1006/viro.2001.1093
Ulbrandt ND Cassatt DR Patel NK Roberts WC Bachy CM Fazenbaker CA Hanson MS Conformational nature of the Borrelia burgdorferi decorin binding protein A epitopes that elicit protective antibodies Infect Immun 2001 69 4799 4807 11447153 10.1128/IAI.69.8.4799-4807.2001
Corcoran A Mahon BP Doyle S B cell memory is directed toward conformational epitopes of parvovirus B19 capsid proteins and the unique region of VP1 J Infect Dis 2004 189 1873 1880 15122524 10.1086/382963
An LL Whitton JL A multivalent minigene vaccine, containing B-cell, cytotoxic T-lymphocyte, and Th epitopes from several microbes, induces appropriate responses in vivo and confers protection against more than one pathogen J Virol 1997 71 2292 2302 9032365
Obeid OE Stanley CM Steward MW Immunological analysis of the protective responses to the chimeric synthetic peptide representing T- and B-cell epitopes from the fusion protein of measles virus Virus Res 1996 42 173 180 8806185 10.1016/0168-1702(96)01311-1
Fernandez IM Snijders A Benaissa-Trouw BJ Harmsen M Snippe H Kraaijeveld CA Influence of epitope polarity and adjuvants on the immunogenicity and efficacy of a synthetic peptide vaccine against Semliki Forest virus J Virol 1993 67 5843 8 7690411
Todryk SM Kelly CG Lehner T Effect of route of immunisation and adjuvant on T and B cell epitope recognition within a streptococcal antigen Vaccine 1998 16 174 180 9607027 10.1016/S0264-410X(97)00183-7
| 15921533 | PMC1173103 | CC BY | 2021-01-04 16:39:54 | no | BMC Genomics. 2005 May 29; 6:79 | utf-8 | BMC Genomics | 2,005 | 10.1186/1471-2164-6-79 | oa_comm |
==== Front
BMC GenomicsBMC Genomics1471-2164BioMed Central London 1471-2164-6-801592153510.1186/1471-2164-6-80Research ArticleInsights into a dinoflagellate genome through expressed sequence tag analysis Hackett Jeremiah D [email protected] Todd E [email protected] Hwan Su [email protected] Marcelo B [email protected] Maria F [email protected] Thomas L [email protected] Debashish [email protected] Department of Biological Sciences and Roy J. Carver Center for Comparative Genomics, University of Iowa, Iowa City, IA 52242, USA2 Department of Ophthalmology and Center for Bioinformatics and Computational Biology, University of Iowa, Iowa City, IA 52242, USA3 Department of Pediatrics, University of Iowa, Iowa City, IA 52242, USA4 Departments of Biochemistry, Orthopaedics, Physiology, and Biophysics, University of Iowa, Iowa City, IA 52242, USA5 Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA 52242, USA2005 29 5 2005 6 80 80 2 2 2005 29 5 2005 Copyright © 2005 Hackett et al; licensee BioMed Central Ltd.2005Hackett et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Dinoflagellates are important marine primary producers and grazers and cause toxic "red tides". These taxa are characterized by many unique features such as immense genomes, the absence of nucleosomes, and photosynthetic organelles (plastids) that have been gained and lost multiple times. We generated EST sequences from non-normalized and normalized cDNA libraries from a culture of the toxic species Alexandrium tamarense to elucidate dinoflagellate evolution. Previous analyses of these data have clarified plastid origin and here we study the gene content, annotate the ESTs, and analyze the genes that are putatively involved in DNA packaging.
Results
Approximately 20% of the 6,723 unique (11,171 total 3'-reads) ESTs data could be annotated using Blast searches against GenBank. Several putative dinoflagellate-specific mRNAs were identified, including one novel plastid protein. Dinoflagellate genes, similar to other eukaryotes, have a high GC-content that is reflected in the amino acid codon usage. Highly represented transcripts include histone-like (HLP) and luciferin binding proteins and several genes occur in families that encode nearly identical proteins. We also identified rare transcripts encoding a predicted protein highly similar to histone H2A.X. We speculate this histone may be retained for its role in DNA double-strand break repair.
Conclusion
This is the most extensive collection to date of ESTs from a toxic dinoflagellate. These data will be instrumental to future research to understand the unique and complex cell biology of these organisms and for potentially identifying the genes involved in toxin production.
==== Body
Background
Dinoflagellates play critical roles in marine ecosystems as primary producers and grazers of other bacterial and eukaryotic plankton [1]. Approximately one-half of the ca. 4,000 species of dinoflagellates contain plastids, although many are mixotrophic [2]. Many taxa produce potent toxins and form harmful algal blooms, or "red tides", resulting from populations of more than 20 million cells per liter of seawater. The toxins cause a variety of poisonings that affect humans and marine wildlife [1] and have a significant impact on coastal ecosystems throughout the world [3]. Yet, other dinoflagellates, like Symbodinium, are central contributors to the health of reef ecosystems as the symbionts of corals [4]. Loss of the dinoflagellate symbiont results in coral bleaching. In addition to their ecological role, dinoflagellates display some fascinating and unique aspects of cell biology. One intriguing character is nuclear biology. The nucleus of dinoflagellates is unlike that of any other eukaryote because the chromosomes are condensed throughout the cell cycle except during DNA replication [5]. The morphologically similar chromosomes are attached to the nuclear envelope and can number in the hundreds [6]. Dinoflagellates also lack nucleosomes [7], instead the nuclear DNA is associated with basic proteins that are moderately similar to bacterial histone-like proteins (HLPs [8,9]). Dinoflagellates were thought to lack histones [10], but in a recent gene expression study, a putative histone H3 was annotated in Pyrocystis lunula, although the sequence was not analyzed further [11]. The general lack of nucleosomes raises many questions about transcription and gene regulation in these organisms. Dinoflagellate nuclei also contain vast amounts of DNA compared to other eukaryotes. Estimates range from 3 – 250 pg·cell-1, or approximately 3,000 – 215,000 megabases (MB) [12]. In comparison, human nuclei contain 3.2 pg·cell-1 (3,180 MB). The dinoflagellate nucleus contains such a high concentration of DNA that it exists in a liquid crystal state, which is responsible for the unique morphology [13,14]. The DNA to basic protein ratio of dinoflagellate chromosomes has been estimated to be 10:1, which is dramatically higher than the 1:1 ratio observed in most eukaryotes. This indicates that very little basic protein is associated with dinoflagellate chromosomes and that the crystal structure is the primary cause of the unusual morphology. Dinoflagellates are also the only eukaryotes to contain hydroxymethyluracil, a deaminated nucleotide that can be produced by oxidative damage of DNA, which replaces 12 – 70% of the thymidine [15]. The role of polyploidy or potentially, genome amplification within particular life history stages remains to be clarified for dinoflagellates. It is highly unlikely, however, given their relatively simple morphology that the immense DNA content is explained solely by gene content.
The most widespread plastid in dinoflagellates contains the unique photopigment peridinin. The "peridinin plastid" is remarkably different from this organelle in other eukaryotes because it lacks a typical genome. Plastids normally contain a circular genome of about 150 kb that encodes 100 – 200 genes that are necessary for plastid function. In peridinin-containing dinoflagellates, the plastid genome has been broken into minicircles that encode a single, or a few genes per circle. However, only 16 genes have been identified thus far on minicircles [16,17]. Recent studies show that most of the plastid genes have been transferred to the nucleus [18,19] with 15 of these genes found exclusively on the plastid genome in all other photosynthetic eukaryotes [18]. The peridinin dinoflagellates encode therefore the smallest number of plastid genes of any photosynthetic eukaryote, making them a model for understanding organellar gene transfer. Nuclear-encoded plastid proteins are targeted to the plastid using a tripartite N-terminal targeting signal [20]. As in Euglena, nuclear-encoded plastid proteins are co-translationally inserted into the endoplasmic reticulum and embedded in this membrane using a stop-transfer sequence in the N-terminus. Through algal endosymbioses, the dinoflagellates have been able to acquire four other types of plastids from distantly related evolutionary lineages including the haptophytes, cryptophytes, diatoms, and prasinophytes [1,21]. This aspect of their evolutionary history highlights the unmatched ability of dinoflagellates to capture and retain foreign plastids.
Alexandrium tamarense is one of the best-studied dinoflagellates. This species forms toxic blooms and causes paralytic shellfish poisoning through saxitoxin production. It has a peridinin-containing plastid and in North America, A. tamarense blooms from Alaska to Southern California in the Pacific and along the Canadian and New England coasts in the Atlantic. There has been a recent increase in blooms of A. tamarense and other Alexandrium species in other parts of the world making this genus of high importance to the world's fisheries. We undertook a gene discovery project with this organism using expressed sequence tag (EST) data to investigate dinoflagellate evolution and to create a genomic resource for scientists working on different aspects of A. tamarense and dinoflagellate biology. The EST method was the most reasonable approach in this case because haploid A. tamarense cells contain approximately 143 chromosomes and have a genome size of 200 pg/cell (ca. 200,000 Mb [Erdner and Anderson unpublished data]). Our EST results comprise the first extensive high-throughput, genome-wide data set for a dinoflagellate.
Results and discussion
Clustering and sequence analyses
The collection of 11,171 ESTs comprised of single-pass 3'-reads (483 from the start library and 10,688 from the normalized library) from A. tamarense was assembled into 6,723 clusters. The normalized library showed a high degree of complexity, with a novelty rate of 60.18% and about 52% of the sequenced clones contained inserts that were longer than the single sequence read (ca. 750 bp). Clustering of the total EST set showed that most of the reads were singletons (4,618 sequences) and the largest cluster was comprised of 46 ESTs that are closely related to HLPs (Table 1). Other highly represented transcripts were those encoding luciferin-binding protein (a protein involved in the regulation of bioluminescence) and several photosynthetic proteins (e.g., Rubisco, ATP synthase C chain, light harvesting proteins). Several large clusters were transcripts that lacked a similarity (e-value < e-5) to known proteins. One of these ESTs has an open reading frame that encodes a protein with a potential plastid-targeting signal (Figure 1A). Interestingly, database searches against NCBI's nr and dbEST returned hits only to other dinoflagellate ESTs. Another of the largest clusters only had hits to ESTs from other dinoflagellates (Figure 1B). These two proteins are therefore candidates for dinoflagellate-specific proteins.
Table 1 Cluster size and frequency of the A. tamarense ESTs.
Cluster Size Frequency Cluster Size Frequency Best BLAST hit(s)
1 4618 14 7
2 1249 15 1 unknown
3 427 16 1 HSP90
4 176 17 4 peridinin-chl a protein, Cytochrome C6, EF1-alpha, unknown
5 81 18 1 ATP synthase C chain
6 44 19 2 Form II Rubisco, unknown putative dino. specific protein
7 32 21 1 fucoxanthin chlorophyll a/c binding protein like
8 15 22 1 Unknown putative plastid protein
9 21 23 1 Unknown
10 13 24 3 peridinin-chlorophyll a protein, ATP synthase C chain, unknown
11 10 29 1 luciferin-binding protein
12 7 46 1 histone-like protein/basic nuclear protein
13 6
Figure 1 Putative dinoflagellate-specific proteins. Amino acid sequence alignments of putative dinoflagellate-specific proteins. A) putative plastid protein that was highly represented in the A. tamarense cDNA library (cluster size = 22). A. tamarense sequences 1, 2, and 3 correspond to clones GC1-aba-e-13, GC1-abh-e14, and GC1-abd-o-22, respectively, and are aligned with highly similar ESTs from the dinoflagellates L. polyedrum (CD809498) and P. lunula (BU582532). The boxed region indicated a possible plastid targeting sequence. B) Putative dinoflagellate specific protein with significant blast hits only to other dinoflagellate ESTs. The Alexandrium sequence corresponds to clone UI-D-GC1-abh-f-23-0-UI.
Figure 2 GO category assignment of A. tamarense ESTs. Classification of 1,203 A. tamarense ESTs into the GO categories.
Each cluster was searched against the SwissProt protein database using blastx. A total of 515 hits with an e-value less than 1e-20 were identified that terminated within 10 amino acids of the end of the SwissProt entry. From these hits, we estimated that the 3'-UTRs ranged in length from 25 – 620 nt with a mean length of 155 nt. This is shorter than the average length observed for fungi (~200 nt) and metazoans (300–600 nt) [22]. However, this analysis is likely to be an underestimate of the average 3'-UTR length because only ESTs that were sequenced into the coding region were included in the analysis. The 3'-UTRs of A. tamarense cDNAs are also interesting because of their apparent lack of a polyA signal. Both simple n-mer searches (e.g. hexamer, pentamer) and the Gibb's sampler were used to assay the canonical region from -11 to -30 preceding the polyadenylation site in search of a polyadenylation signal. We were unable to find a single or a related set of hexamers or pentamers that are enriched in the 3'-UTRs (data not shown). Clearly, polyadenylation of transcripts occurs in A. tamarense, however, the mechanism by which this process takes place apparently does not involve a typical polyA signal. These ESTs were also analyzed for GC-content and codon usage. Coding region GC-content was 60.8%, whereas GC-content in the 3'-UTR was slightly less at 57.6%. The GC-content is reflected in the codon usage (Table 2), whereby 3rd positions are strongly biased towards Gs or Cs. The stop codon TGA is also significantly favoured over TAG and TAA (frequencies of 411, 71, and 25 occurrences, respectively). The accession numbers of SwissProt hits with an e-value of 9e-10 and below (1,292 sequences) were submitted to the ProToGo server for GO category assignment [23]. A total of 1,203 of the SwissProt accession numbers could be assigned to GO categories. The results are summarized in Figure 2. The functional distribution of the A. tamarense ESTs that could be placed among GO categories is typical of other eukaryotes. However, the overall small number (i.e., 20%) of significant hits to GenBank is surprising, suggesting that many A. tamarense proteins may be either highly diverged and/or encode novel dinoflagellate-specific functions (e.g., Figure 1), or the sequence does not extend into the coding region of the transcript.
Table 2 Codon Usage in the A. tamarense ESTs.
TTT F 703 23.1% TCT S 482 10.0% TAT Y 372 18.8% TGT C 251 15.6%
TTC F 2335 76.9% TCC S 1348 27.9% TAC Y 1612 81.2% TGC C 1356 84.4%
TTA L 61 0.9% TCA S 413 8.6% TAA * 29 5.6% TGA * 411 79.8%
TTG L 1118 15.7% TCG S 926 19.2% TAG * 75 14.6% TGG W 1051 100.0%
CTT L 902 12.7% CCT P 751 17.6% CAT H 464 25.7% CGT R 475 9.6%
CTC L 2296 32.3% CCC P 1382 32.4% CAC H 1340 74.1% CGC R 1779 35.8%
CTA L 139 2.0% CCA P 829 19.4% CAA Q 433 14.6% CGA R 426 8.6%
CTG L 2596 36.5% CCG P 1307 30.6% CAG Q 2535 85.4% CGG R 1128 22.7%
ATT I 715 19.1% ACT T 542 13.1% AAT N 508 21.0% AGT S 344 7.1%
ATC I 2770 74.1% ACC T 1442 34.9% AAC N 1915 79.0% AGC S 1310 27.2%
ATA I 253 6.8% ACA T 638 15.4% AAA K 415 8.5% AGA R 253 5.1%
ATG M 2096 100.0% ACG T 1510 36.5% AAG K 4485 91.5% AGG R 910 18.3%
GTT V 686 11.2% GCT A 1195 15.2% GAT D 1117 24.9% GGT G 943 13.8%
GTC V 2214 37.8% GCC A 2899 36.8% GAC D 3371 75.1% GGC G 3957 58.1%
GTA V 268 4.6% GCA A 1559 19.8% GAA E 750 13.8% GGA G 767 11.3%
GTG V 2694 46.0% GCG A 2218 28.2% GAG E 4682 86.2% GGG G 1142 16.8%
Analysis is of 515 proteins (81,893 codons). Third position nucleotide usage was T = 12.8%, A = 9.3%, C = 40.7%, G = 37.2%. The asterisk (*) indicates a stop codon.
Figure 3 Analyses of A. tamarense histone H2A.X. A) Alignment of A. tamarense H2A.X with eukaryotic homologs. The alignment is shaded according to the level of conservation. The symbols above the alignment indicate the location of functional residues (T = trypsin cleavage site, ^ = arginines that contact the DNA helix, * = H2A-H2B interaction sites, U = ubiquitination site). The annotation below the alignment indicates conserved structural features including the α-helices, loops, and the SQ(E/D)Φgotif. B) A ML tree of H2A and H2A.X. The numbers above and below the branches are the results of ML and NJ bootstrap analyses, respectively. The thick branches indicate > 0.95 posterior probability from Bayesian inference. Only bootstrap values ≥ 50% are shown. Branch lengths are proportional to the number of substitutions per site (see scale bar).
Dinoflagellate gene content and gene families
Of species with sequenced genomes, the apicomplexan Plasmodium falciparum is the most closely related organism to A. tamarense. Both of these species are members of the alveolate lineage with dinoflagellates and apicomplexans forming a monophyletic clade that is sister to the ciliates (e.g., [23]). Sequence comparisons using BLAST revealed that 609 of the 6723 A. tamarense ESTs had a significant hit (e-value less than 1e-10) to P. falciparum proteins. The top 20 most significant hits are shown in Table 3. The most highly conserved proteins between these organisms include many "housekeeping" proteins such as α-tubulin and heat shock protein 70. Despite their close evolutionary relationship, there are however likely to be substantial differences between A. tamarense and P. falciparum with respect to gene content. Due to the apicomplexan intracellular lifestyle, P. falciparum has lost most of the genes related to plastid function as well as other metabolic genes. Many of these same proteins appear in the list of the top BLAST hits against the nr database of GenBank (Table 4). There were 1,349 hits to the nr database that were better than 1e-10.
Table 3 Top 20 A. tamarense EST blast hits against the genome of the apicomplexan P. falciparum.
A. tamarense EST E-Value GI Number Protein Description
UI-D-GC1-aao-m-13-0-UI 1.00E-112 23613558 α-tubulin
UI-D-GC1-aav-f-09-0-UI 6.00E-86 23508137 flavoprotein subunit of succinate dehydrogenase
UI-D-GC1-aad-d-15-0-UI 9.00E-86 23509363 serine/threonine protein phosphatase
UI-D-GC0-aae-b-08-0-UI 2.00E-85 23509135 actin
UI-D-GC1-aaz-h-12-0-UI 3.00E-85 23507885 26S proteasome regulatory subunit 4
UI-D-GC1-abe-o-23-0-UI 8.00E-85 23510155 bifunctional dihydrofolate reductase-thymidylate synthase
UI-D-GC1-abh-e-16-0-UI 1.00E-84 23612827 hsp70
UI-D-GC0-aae-p-02-0-UI 2.00E-84 23613232 adenosylhomocysteinase
UI-D-GC1-aay-i-10-0-UI 3.00E-82 16804988 helicase
UI-D-GC1-aau-b-16-0-UI 1.00E-80 23509325 eukaryotic translation initiation factor 2 gamma subunit
UI-D-GC0-aae-h-03-0-UI 8.00E-78 23509820 glyceraldehyde-3-phosphate dehydrogenase
UI-D-GC1-aao-o-20-0-UI 4.00E-77 23508006 ADP ribosylation factor 1
UI-D-GC0-aae-f-01-0-UI 1.00E-76 23509545 calmodulin
UI-D-GC1-abb-n-18-0-UI 2.00E-76 23510206 eukaryotic initiation factor
UI-D-GC1-abf-g-07-0-UI 4.00E-75 23612467 HSP86
UI-D-GC1-abd-m-07-0-UI 2.00E-74 23612587 40S ribosomal protein S5
UI-D-GC0-aae-b-08-0-UI 3.00E-74 23509345 actin II
UI-D-GC1-aab-m-24-0-UI 4.00E-74 23509670 ribosomal protein S2
UI-D-GC1-aar-f-11-0-UI 3.00E-72 23509852 protein serine/threonine phosphatase
UI-D-GC1-aao-b-16-0-UI 1.00E-69 23509877 RNA helicase 1
Table 4 Top 20 hits of the A. tamarense ESTs to the GenBank nr database.
A. tamarense EST E-Value GI Number Protein Description Organism
UI-D-GC1-abg-i-22-0-UI 1.00E-110 845405 ribulose 1,5-bisphosphate carboxylase Gonyaulax polyedra
UI-D-GC1-aao-m-13-0-UI 1.00E-109 135433 alpha tubulin Oxytricha granulifera
UI-D-GC1-abh-e-16-0-UI 2.00E-98 20143982 hsp70 Crypthecodinium cohnii
UI-D-GC1-abe-o-23-0-UI 1.00E-96 1169423 bifunctional dihydrofolate reductase-thymidylate synthase Arabidopsis thaliana
UI-D-GC0-aae-p-02-0-UI 1.00E-91 4416330 S-adenosyl-homocysteine hydrolase like protein Alexandrium fundyense
UI-D-GC0-aae-h-11-0-UI 2.00E-91 21913167 oxygen evolving enhancer 1 precursor Heterocapsa triquetra
UI-D-GC1-abh-d-23-0-UI 4.00E-91 32307578 glutamate 1-semialdehyde 2,1-aminomutase Bigelowiella natans
UI-D-GC1-abe-e-15-0-UI 1.00E-89 27450753 proliferating cell nuclear antigen Pyrocystis lunula
UI-D-GC1-abb-n-18-0-UI 3.00E-88 28277876 Similar to DEAD box polypeptide 48 Danio rerio
UI-D-GC1-aav-f-09-0-UI 3.00E-87 15240075 succinate dehydrogenase flavoprotein subunit, mitochondrial Arabidopsis thaliana
UI-D-GC1-abc-o-16-0-UI 8.00E-85 13560096 ALA dehydratase Gonyaulax polyedra
UI-D-GC1-aao-o-20-0-UI 1.00E-83 7025460 ADP ribosylation factor 1 Toxoplasma gondii
UI-D-GC0-aae-b-23-0-UI 5.00E-83 1076185 luciferin-binding protein Gonyaulax polyedra
UI-D-GC1-aay-i-10-0-UI 9.00E-83 18416493 DEAD/DEAH box helicase, putative Arabidopsis thaliana
UI-D-GC1-aau-b-16-0-UI 1.00E-82 4503507 eukaryotic translation initiation factor 2, subunit 3 gamma Homo sapiens
UI-D-GC1-aad-d-15-0-UI 5.00E-81 1346753 Serine/threonine protein phosphatase PP1 isozyme 2 Acetabularia cliftonii
UI-D-GC1-aaz-h-12-0-UI 1.00E-77 23507885 26S proteasome regulatory subunit 4, putative Plasmodium falciparum
UI-D-GC1-abc-m-19-0-UI 1.00E-77 32307576 geranyl-geranyl reductase Bigelowiella natans
UI-D-GC1-abj-e-13-0-UI 2.00E-76 4033509 Calmodulin Tetrahymena pyriformis
UI-D-GC1-abd-m-07-0-UI 3.00E-75 6831665 40S ribosomal protein S5 Cicer arietinum
As previously mentioned, our bioinformatic analyses identified 6,723 clusters of unique genes. However, this is likely to be a conservative estimate of the number of unique transcripts that were sequenced. A combination of short 3'-UTRs and highly conserved coding regions caused many related transcripts to be assembled together, even though their 3'-UTRs contained sequence differences. For example, two large clusters comprise ESTs that correspond to the plastid atpH gene that encodes the ATP synthase C chain. This gene is normally plastid encoded in other photosynthetic eukaryotes. These two clusters form closely related, but clearly distinct sets of transcripts. An additional atpH-encoding transcript was identified by a single EST. Together, the three clusters contain 43 ESTs, 16 of which are unique. The N-terminal extensions, which encode the tripartite plastid-targeting signals, share an average 74.3% nucleotide and 68.6% amino acid identity, respectively. Similar to many other species, the dinoflagellate transit peptides appear to be under selection to maintain hydrophobicity rather than a conserved amino acid sequence. This may explain why the nucleotide conservation is greater than that of the encoded amino acids. Five hydrophobic amino acids (phenylalanine, leucine, isoleucine, methionine, and valine) are, for example, encoded by codons with a T in the second position. This combined with the high GC-content at third positions results in higher conservation at second and third positions than at first positions. In addition, the high proportion of alanine (28.6%), leucine (10.2%), and valine (11.8%) rather than phenylalanine (2.4%), isoleucine (3.6%), methionine (4.3%, excluding starting methionine), and tyrosine (0.3%) in the N-terminal extensions may reflect the underlying GC-richness, because alanine, leucine, and valine are encoded by GC-rich codons. It is unclear if these amino acids are evolutionarily selected for specifically, or if they are selected for the combination of their hydrophobic character and the GC-content of their codons. In contrast, the conserved core of the protein shared an average 88.4% nucleotide and 98% amino acid identity, respectively, which corresponds to the more typical pattern of third position variation resulting from selection. The 3'-UTRs of the atpH genes show substantial variation and were difficult to align. There are several groups of more closely related 3'-UTRs that may be the result of recently duplicated genes. In all, there are five alignable groups of UTRs (and one singleton) that may have originated from more closely related genes.
Histone and histone-like proteins in dinoflagellates
A significant finding of this study is the identification of two rare (2/11,171) ESTs that encode a partial histone H2A.X. The longest cDNA isolated from the library using PCR was predicted to encoded a protein of 169 amino acids that shares high sequence identity to eukaryotic histone H2A.X (Figure 3A). This clone putatively lacked only the start codon at the N-terminus. The divergent N-terminus of A. tamarense H2A.X is somewhat longer than in other homologs but the remainder of the sequence is conserved (in particular the α-helices of the histone fold). Several functional residues from the known crystal structure are also present in A. tamarense H2A.X including the lysine at the trypsin cleavage site, the arginines in the loops that interact with the DNA α-helix, and the lysine ubiquitination site [24]. The sites of interaction with histone H2B are also present.
Figure 4 Analysis of dinoflagellate HLPs. A) HLPs from dinoflagellates (red taxa names) and bacteria (blue) and HU proteins from bacteria (black). B) The predicted secondary structure of HLPs from A. tamarense and B. pertussis aligned with the known secondary structure of E. coli HU. Curled lines indicate α-helices and jagged lines indicate β-strands. The arrow indicates the position of a conserved lysine. The asterisk indicates the proline that intercalates into the DNA in HU proteins. C) An ML tree of HU and HLP proteins from bacteria and eukaryotes. The numbers above and below the branches result from ML and NJ bootstrap analyses, respectively. The thick branches indicate > 0.95 posterior probability from Bayesian inference. Only bootstrap values ≥ 50% are shown. Branch lengths are proportional to the number of substitutions per site (see scale bar).
H2A.X proteins are closely related to the canonical H2A except for the C-terminus which contains the distinctive SQ(E/D)Φ motif (where Φ is a hydrophobic residue). H2A.X plays an important role in the recognition and repair of double-strand DNA breaks by non-homologous end-joining. At the site of double-strand breaks, the serine of the SQ(E/D)Φ motif is rapidly phosphorylated [25]. The phosphorylation signal spreads a large distance down the chromosome around the breaks, signalling the recruitment of the DNA repair proteins Rad50, Rad51, and BRCA1 [26,27]. We also identified histone H2A and H2A.X from the haptophyte Emilania huxleyi through high-throughput EST sequencing of this alga (J. D. H. and D. B. unpublished data). Phylogenetic analysis places A. tamarense H2A.X in its predicted position (with moderate bootstrap support) as sister to the E. huxleyi homolog within a group of chromalveolates that includes haptophytes, stramenopiles, and apicomplexans (Figure 3B). H2A.X from A. tamarense, E. huxleyi, and Toxoplasma gondii do not, however, form a monophyletic group suggesting multiple origins within chromalveolates. This is not surprising because H2A.X appears to have arisen independently many times during eukaryotic evolution [28,29].
We tested the strength of these results using the Approximately Unbiased (AU-) statistical test. A 16-taxon ML backbone tree was generated without A. tamarense H2A.X and then we made a set of 17-taxon trees by placing this sequence on every possible branch (29 in total). This analysis provides good support for the position shown in Figure 3B (P = 0.827), however, many alternative positions were included in the 5% confidence set of trees (i.e., as sister to Thalassiosira pseudonana, Phaeodactylum tricornutum, Homo sapiens, or Drosophila melanogaster, and at the base of or sister to either of the land plants). The lack of robust phylogenetic signal for the divergence point of A. tamarense H2A.X likely reflects the short length and high conservation of these histones.
Dinoflagellate chromosomes do not contain nucleosomes, instead the DNA is associated with HLPs [10,30,31]. The similarity between dinoflagellate HLPs and bacterial HU and HLPs has only recently been noted and these proteins have not yet been subjected to phylogenetic analysis with a broad taxon sampling [32]. In our A. tamarense EST data, HLPs were the most highly represented transcripts (45/11,171 ESTs) and encoded 5 closely related proteins. Alignment of the HLPs from A. tamarense and other dinoflagellates with HLPs and HU proteins from bacteria and eukaryotes showed moderate sequence similarity (a representative alignment is shown in Figure 4A). This alignment was constructed using information from secondary structure predictions (discussed below).
One group of proteins (referred to here as bacterial HLPs) is more closely related to dinoflagellate HLPs and includes Bph2 from Bordetella pertussis. Bph2 has a role in virulence gene expression and shares limited (likely convergent) sequence similarity with histone H1 [33]. The dinoflagellate and bacterial HLPs also contain an N-terminal extension in comparison to HU proteins. This extension is rich in alanine, lysine, and proline, which is reminiscent of the C-terminus of histone H1. The dinoflagellate HLP N-termini are however, also enriched in methionines. Compared to the bacterial HLPs, this N-terminal region is generally shorter in the dinoflagellates, although there is variability among species in both groups (Figure 4A). In contrast to the primary sequence, secondary structure predictions for these three classes of proteins are remarkably similar. The crystal structure of E. coli HU has been determined (PBD ID: 1MUL) and the known secondary structure was compared to the predicted secondary structures of B. pertussis Bph2 and an A. tamarense HLP (Figure 4B). Both types of HLPs are predicted to have two α-helices that are identical in size and spacing to the N-terminal helices in E. coli HU, followed by two β-strands that are similar in size and position. We conclude from this analysis that dinoflagellate HLPs show structural similarity to HU proteins from bacteria, however, it is unclear if these proteins are functional homologs. It is also apparent that dinoflagellate HLPs are distantly related to bacterial HU proteins. The dinoflagellates have one putatively homologous functional residue corresponding to Lys3 (arrow in Figure 4A) of HU proteins, which interacts with the DNA and is involved in wrapping the DNA around the protein [34]. A proline residue (asterisk in Figure 4A), which intercalates into the DNA during HU binding, appears to be conserved among HU proteins and bacterial HLPs, but is not present in the dinoflagellate HLPs [35]. However, there are several prolines conserved among dinoflagellates in the C-terminal end of the protein. The C-terminal arms of HU are critical for the interactions that bend the DNA. Given the low level of sequence similarity and the absence of a homologous proline in this region, it is unclear if the dinoflagellate HLPs are able to interact with DNA in the same manner as HU proteins.
In our phylogenetic analyses, the proteobacterial HLPs form a well-supported monophyletic group with the dinoflagellates (Figure 4C) suggesting an origin of the dinoflagellate gene through lateral transfer (followed by several rounds of gene duplication). It is also noteworthy that dinoflagellates are the only eukaryotes to possess a proteobacterial form II rubisco [36]. The position of the dinoflagellate HLPs is distinct from that of other eukaryotic HU proteins. These latter proteins group with the canonical HU proteins from bacteria and have likely originated through intracellular transfer from the mitochondrial or plastid endosymbiont. Statistical support for the monophyly of the dinoflagellate and proteobacterial HLPs was tested using the AU-test. In these analyses (details not shown), a sister group relationship between the HLPs was the most highly favored topology (P = 0.659) and all other positions for the dinoflagellates (except branching inside the bacterial HLP clade) had significantly lower probabilities (P < 0.05).
Dinoflagellates no longer use the nucleosome as the major DNA packaging protein complex. Chromosomal DNA strands in these taxa are smooth, in contrast to the "beads on a string" conformation in other eukaryotes [12]. The chromosome structure is also unique in that they are uniform in size and morphology, remain condensed throughout the cell cycle, and are birefringent, indicating a liquid crystal state [5,14,37]. Transcription is thought to take place in DNA loops that protrude from the condensed chromosome [38]. It appears that dinoflagellates have acquired DNA binding proteins from a proteobacterium possibly to facilitate the compaction of their immense genomes. HU and related proteins from bacteria induce sharp bends in DNA strands and some models suggest that HLPs are responsible for creating DNA bends at the periphery of the chromosomes [39,40]. Immunolocalization shows dinoflagellate HLP to be associated with the periphery of chromosomes [41].
However, the HLP concentration is very low relative to DNA content. Dinoflagellate chromosomes have a 1:10 protein:DNA ratio (in contrast to the 1:1 ratio in other eukaryotes). The HLP concentration may therefore be too low to function in DNA compaction, rather they may act as transcriptional regulators [41,42].
In summary, our discovery of H2A.X in A. tamarense shows that, whereas dinoflagellates appear to no longer use nucleosomes for DNA packaging, at least one histone has been retained and is weakly expressed. Interestingly, in a recent paper, histone H3 appears in a table of redox-regulated genes in the dinoflagellate Pyrocystis lunula [11]. Until now, only these two histones have been identified in dinoflagellates and it is unclear if all dinoflagellates possess either of these two genes, or others that have not yet been found. If other histones are present (which is likely), they may however also be expressed at a low level (as is the case for A. tamarense H2A.X). This would render difficult their identification using the EST-based approach unless comprehensive sequencing of normalized and subtracted cDNA libraries is used. In metazoans, replication-dependant canonical histone (H2A, H2B, H3 and H4) mRNAs are not polyadenylated, raising the possibility that they have been excluded from this poly-A primed cDNA library [43]. However, these histone mRNAs are polyadenylated in plants, apicomplexans, and ciliates, suggesting that if they are present, they may be in dinoflagellates as well [44-46]. Given the important role that H2A.X plays in DNA repair, we speculate that this gene may have been maintained specifically to perform this function. Consistent with this idea, the core region of A. tamarense H2A.X is highly conserved, indicating that it may still be able to interact with DNA in a manner similar to H2A in other species.
Conclusion
This collection of ESTs is the most extensive genomic resource for a toxic dinoflagellate species to date and provides a useful glimpse into its nuclear genome. These data will be instrumental to future research to understand the unique and complex cell biology of these organisms and for understanding the method of toxin production in these species. We have likely not yet exhausted the gene discovery potential using the EST approach (i.e., note the high discovery rate of our normalized library). In the future, we will use serial subtraction of cDNA libraries to improve/maintain the novelty rate of our cDNA library and create cDNA libraries from A. tamarense under various growth conditions and life history stages to get generate a more complete catalog of the gene content of this important organism.
Methods
Library construction
Total RNA from a culture of the toxic dinoflagellate Alexandrium tamarense (CCMP 1598) was extracted using Trizol (GibcoBRL) and mRNA purified using the Oligotex mRNA Midi Kit (Qiagen). This culture strain was produced by isolating a single cyst, a diploid resting stage that produces haploid vegetative cells by meiosis. However, it is unknown if a single or multiple vegetative cells were isolated after antibiotic treatment to make the culture axenic. If a single vegetative cell was isolated, the culture would be clonal. The culture was grown at 20°C on a 13:11 hour light:dark cycle (80 μEinsteins of light) in L1 media. Start and normalized directionally cloned (3' NotI-5'EcoR1) cDNA libraries were constructed as previously described [47]. ESTs were sequenced from the 3' end to maximize clustering accuracy using the 3' untranslated region (UTR). All ESTs were processed as previously described [48]. Identification of a total of a non-redundant "unigene" set of 6,723 unique clusters from 11,171 sequences was accomplished using using UIcluster v3.0.5 [49].
Phylogenetic analyses
Data was gathered from GenBank (including the recently released Karenia brevis EST data, Frances Van Dolah, unpublished data) using blast searches. Maximum likelihood (ML) analyses were done with PHYLIP using the JTT model of protein evolution with gamma corrected rates (JTT + Γ) with 5 random additions [50]. ML bootstrap analyses (100 replications) were done as described with either 5 (histone H2A) or 1 (HLPs) rounds of random taxon addition. Bayesian analyses were done using MrBayes V3.0b4 [51]. Four chains (1 cold, 3 heated) were run for 1 million generations, sampled every 1000 generations, using the JTT + Γ model. The first 500 trees were discarded as burn-in. Neighbor joining (NJ) bootstrap (500 replicates) analyses were done with PHYLIP using the JTT + Γ model. Minimum evolution (ME) analyses done with PHYLIP using the JTT + Γ model with global rearrangements and 10 rounds of random taxon addition (1 round was used in the bootstrap analysis).
The Approximately Unbiased test was done using CONSEL [52]. ML trees without the groups of interest were generated as described above. A pool of trees was then generated by adding the group of interest (A. tamarense H2A.X or dinoflagellate HLPs) to every possible branch in the ML tree. For the HLP analyses, a reduced taxon set was used that included Bordetella, Ralstonia, Xylella, Pasteurella, Nostoc, Synechocystis, Agrobacterium, Rikettsia, Escherichia, Guillardia, Cyanidioschyzon, Sorghum, Toxoplasma, Xenopus, and Homo. A. tamarense 1 and C. cohnii HCC2 were added as a monophyletic group to every branch in this reduced ML tree. Secondary structure prediction was done using Jpred [53, 54]. The consensus secondary structures were used in the comparison to the know structure of E. coli HU (PDB ID: 1MUL).
Authors' contributions
JDH constructed the cDNA libraries and did the sequence and phylogenetic analyses, the Blast and GO analyses on the EST dataset, the histone and HLP analyses, and drafted the manuscript. TES did many of the other global sequence analyses of the EST dataset. HSY contributed intellectually to the manuscript. Library construction and high-throughput EST sequencing was done in the laboratory of MBS and was supervised by MFB. The bioinformatics group led by TLC did the EST sequence processing and clustering. DB conceived of and supervised this study and contributed to the manuscript. All authors read and approved the final manuscript.
Acknowledgements
JDH was supported by an Institutional NRSA (T 32 GM98629) from the National Institutes of Health. This work was supported by grants from the National Science Foundation awarded to DB (DEB 01-07754, MCB 02-36631). TES was partially supported by a Career Development Award from Research to Prevent Blindness.
==== Refs
Hackett JD Anderson DM Erdner DL Bhattacharya D Dinoflagellates: A remarkable evolutionary experiment. American Journal of Botany 2004 91 1523 1534
Graham LE Wilcox LW Algae 2000 Upper Saddle River, NJ , Prentice-Hall
Hallegraeff GM A review of harmful algal blooms and their apparent global increase. Phycologia 1993 32 79 99
Trench RK Taylor FJR Dinoflagellates in non-parasitic symbioses The Biology of Dinoflagellates 1987 Oxford, UK , Blackwell 530 570
Dodge JD Godward MBE The Dinophyceae The chromosomes of the algae 1966 New York, New York, USA , St. Martin's Press 96 115
Oakley B Dodge JD Kinetochores associated with the nuclear envelope in the mitosis of a dinoflagellate, Journal of Cell Biology 1974 63 322 325 4473133 10.1083/jcb.63.1.322
Rizzo PJ The enigma of the dinoflagellate chromosome Journal of Protozoology 1991 38 246 252
Rizzo PJ Comparative aspects of basic chromatin proteins in dinoflagellates Biosystems 1981 14 433 443 6175358 10.1016/0303-2647(81)90048-4
Wong JTY New DC Wong JCW Hung VKL Histone-Like Proteins of the Dinoflagellate Crypthecodinium cohnii Have Homologies to Bacterial DNA-Binding Proteins Eukaryotic Cell 2003 2 646 650 12796310 10.1128/EC.2.3.646-650.2003
Rizzo PJ Those amazing dinoflagellate chromosomes Cell Res 2003 13 215 217 12974611
Okamato OK Hastings JW Genome-wide analysis of redox-regulated genes in a dinoflagellate Gene 2003 321 73 81 14636994 10.1016/j.gene.2003.07.003
Spector DL Spector DL Dinoflagellate Nuclei Dinoflagellates 1984 Orlando, Florida, USA , Academic Press, Inc. 107 147
Livolant F Bouligand Y New observations on the twisted arrangement of dinoflagellate chromosomes. Chromosoma 1978 68 21 44 10.1007/BF00330370
Gautier A Michel-Salamin L Tosi-Couture E McDowall AW Dubochet J Electron microscopy of the chromosomes of dinoflagellates in situ: confirmation of Bouligand's liquid crystal hypothesis. Journal of Ultrastructure and Molecular Structure Research 1986 97 10 30 10.1016/S0889-1605(86)80003-9
Rae PMM Hydroxymethyluracil in eukaryote DNA: A natural feature of the Pyrrophyta (Dinoflagellates). Science 1976 194 1062 1064 988637
Zhang Z Green BR Cavalier-Smith T Single gene circles in dinoflagellate chloroplast genomes Nature 1999 400 155 159 10408440 10.1038/22099
Barbrook AC Howe CJ Minicircular plastid DNA in the dinoflagellate Amphidinium operculatum Mol Gen Genet 2000 263 152 158 10732684 10.1007/s004380050042
Hackett JD Yoon HS Soares MB Bonaldo MF Casavant TL Scheetz TE Nosenko T Bhattacharya D Migration of the plastid genome to the nucleus in a peridinin dinoflagellate Curr Biol 2004 14 213 218 14761653 10.1016/S0960-9822(04)00042-9
Bachvaroff TR Concepcion GT Rogers CR Herman EM Delwiche CF Dinoflagellate expressed sequence tag data indicate massive transfer of chloroplast genes to the nuclear genome Protist 2004 155 65 78 15144059 10.1078/1434461000165
Nassoury N Cappadocia M Morse D Plastid ultrastructure defines the protein import pathway in dinoflagellates. Journal of Cell Science 2003 116 2867 2874 12771189 10.1242/jcs.00517
Schnepf E Elbrachter M Dinophyte chloroplasts and phylogeny - A review Grana 1999 [ print.] 38 81 97
Mazumder B Seshadri V Fox PL Translational control by the 3'-UTR: the ends specify the means Trends in Biochemical Sciences 2003 28 91 98 12575997 10.1016/S0968-0004(03)00002-1
Bhattacharya D Yoon HS Hackett JD Photosynthetic eukaryotes unite: endosymbiosis connects the dots Bioessays 2004 26 50 60 14696040 10.1002/bies.10376
Luger K Mader AW Richmond RK Sargent DF Richmond TJ Crystal structure of the nucleosome core particle at 2.8 A resolution Nature 1997 389 251 260 9305837 10.1038/38444
Rogakou EP Pilch DR Orr AH Ivanova VS Bonner WM DNA double-stranded breaks induce histone H2AX phosphorylation on serine 139 J Biol Chem 1998 273 5858 5868 9488723 10.1074/jbc.273.10.5858
Rogakou EP Boon C Redon C Bonner WM Megabase chromatin domains involved in DNA double-strand breaks in vivo J Cell Biol 1999 146 905 916 10477747 10.1083/jcb.146.5.905
Paull TT Rogakou EP Yamazaki V Kirchgessner CU Gellert M Bonner WM A critical role for histone H2AX in recruitment of repair factors to nuclear foci after DNA damage Curr Biol 2000 10 886 895 10959836 10.1016/S0960-9822(00)00610-2
Thatcher TH Gorovsky MA Phylogenetic analysis of the core histones H2A, H2B, H3, and H4 Nucleic Acids Res 1994 22 174 179 8121801
Malik HS Henikoff S Phylogenomics of the nucleosome Nat Struct Biol 2003 10 882 891 14583738 10.1038/nsb996
Allen JR Roberts M Loeblich AR Klotz LC Characterization of the DNA from the dinoflagellate Crypthecodinium cohnii and implications for nuclear organization Cell 1975 6 161 169 1237354 10.1016/0092-8674(75)90006-9
Wong JT New DC Wong JC Hung VK Histone-like proteins of the dinoflagellate Crypthecodinium cohnii have homologies to bacterial DNA-binding proteins Eukaryot Cell 2003 2 646 650 12796310 10.1128/EC.2.3.646-650.2003
Goyard S Identification and characterization of BpH2, a novel histone H1 homolog in Bordetella pertussis J Bacteriol 1996 178 3066 3071 8655481
Grove A Saavedra TC The role of surface-exposed lysines in wrapping DNA about the bacterial histone-like protein HU. Biochemistry 2002 41 7597 7603 12056890 10.1021/bi016095e
Swinger KK Lemberg KM Zhang Y Rice PA Flexible DNA bending in HU–DNA cocrystal structures EMBO Journal 2003 22 3749–3760 12853489 10.1093/emboj/cdg351
Morse D Salois P Markovic P Hastings JW A nuclear-encoded form II RuBisCO in dinoflagellates Science 1995 268 1622 1624 7777861
Loeblich AR Dinoflagellate evolution: speculation and evidence J Protozool 1976 23 13 28 944775
Soyer-Gobillard MO Geraud ML Coulaud D Barray M Theveny B Revet B Delain E Location of B- and Z-DNA in the chromosomes of a primitive eukaryote dinoflagellate J Cell Biol 1990 111 293 304 2380241 10.1083/jcb.111.2.293
Sandman K Pereira SL Reeve JN Diversity of prokaryotic chromosomal proteins and the origin of the nucleosome Cell Mol Life Sci 1998 54 1350 1364 9893710 10.1007/s000180050259
Bouligand Y Norris V Chromosome separation and segregation in dinoflagellates and bacteria may depend on liquid crystalline states Biochimie 2001 83 187 192 11278068 10.1016/S0300-9084(00)01211-6
Sala-Rovira M Geraud ML Caput D Jacques F Soyer-Gobillard MO Vernet G Herzog M Molecular cloning and immunolocalization of two variants of the major basic nuclear protein (HCc) from the histone-less eukaryote Crypthecodinium cohnii (Pyrrhophyta) Chromosoma 1991 100 510 518 1764969 10.1007/BF00352201
Chudnovsky Y Li JF Rizzo PJ Hastings JW Fagan TF Cloning, expression, and characterization of a histone-like protein from the marine dinoflagellate Lingulodinium polyedrum (Dinophyceae). Journal of Phycology 2002 38 543 550 10.1046/j.1529-8817.2002.t01-1-01186.x
Dominski Z Marzluff WF Formation of the 3' end of histone mRNA Gene 1999 239 1 14 10571029 10.1016/S0378-1119(99)00367-4
Chaboute ME Chaubet N Gigot C Philipps G Histones and histone genes in higher plants: structure and genomic organization Biochimie 1993 75 523 531 8268253 10.1016/0300-9084(93)90057-Y
Liu X Gorovsky MA Cloning and characterization of the major histone H2A genes completes the cloning and sequencing of known histone genes of Tetrahymena thermophila. Nucleic Acids Research 1996 24 3023 3030 8760889 10.1093/nar/24.15.3023
Rawat DS Sharma I Jalah R Lomash S Kothekar V Pasha ST Sharma YD Identification, expression, modeled structure and serological characterization of Plasmodium vivax histone 2B Gene 2004 337 25 35 15276199 10.1016/j.gene.2004.03.035
Bonaldo MF Lennon G Soares MB Normalization and subtraction: two approaches to facilitate gene discovery Genome Res 1996 6 791 806 8889548
Scheetz TE Laffin JJ Berger B Holte S Baumes SA Brown R Chang S Coco J Conklin J Crouch K Donohue M Doonan G Estes C Eyestone M Fishler K Gardiner J Guo L Johnson B Keppel C Kreger R Lebeck M Marcelino R Miljkovich V Perdue M Qui L Rehmann J Reiter RS Rhoads B Schaefer K Smith C Sunjevaric I Trout K Wu N Birkett CL Bischof J Gackle B Gavin A Grundstad AJ Mokrzycki B Moressi C O'Leary B Pedretti K Roberts C Robinson NL Smith M Tack D Trivedi N Kucaba T Freeman T Lin JJ Bonaldo MF Casavant TL Sheffield VC Soares MB High-throughput gene discovery in the rat Genome Res 2004 14 733 741 15060017 10.1101/gr.1414204
Trivedi N Bischof J Davis S Pedretti K Scheetz TE Braun TA Roberts CA Robinson NL Sheffield VC Soares MB Casavant TL Parallel creation of non-redundant gene indices from partial mRNA transcripts Future Generation Computer Systems 2002 18 863 870 10.1016/S0167-739X(02)00059-6
Felsenstein J PHYLIP (Phylogeny Inference Package) version 3.6 (Department of Genetics, University of Washington, Seattle, WA). 2002
Huelsenbeck JP Ronquist F MrBayes: Bayesian inference of phylogenetic trees Bioinformatics 2001 17 754 755 11524383 10.1093/bioinformatics/17.8.754
Shimodaira H Hasegawa M CONSEL: for assessing the confidence of phylogenetic tree selection. Bioinformatics 2001 17 1246 1247 11751242 10.1093/bioinformatics/17.12.1246
Cuff JA Clamp ME Siddiqui AS Finlay M Barton GJ Jpred: A Consensus Secondary Structure Prediction Server Bioinformatics 1998 14 892 893 9927721 10.1093/bioinformatics/14.10.892
Jpred: A consensus secondary structure prediction server
| 15921535 | PMC1173104 | CC BY | 2021-01-04 16:39:53 | no | BMC Genomics. 2005 May 29; 6:80 | utf-8 | BMC Genomics | 2,005 | 10.1186/1471-2164-6-80 | oa_comm |
==== Front
BMC GeriatrBMC Geriatrics1471-2318BioMed Central London 1471-2318-5-81594388110.1186/1471-2318-5-8Research ArticleFoot pressure distribution during walking in young and old adults Hessert Mary Josephine [email protected] Mitul [email protected] Jason [email protected] Kun [email protected] Lewis A [email protected] Vera [email protected] Division of Gerontology, Beth Israel Deaconess Medical Center Harvard Medical School, Boston 02215 MA, USA2005 19 5 2005 5 8 8 13 11 2004 19 5 2005 Copyright © 2005 Jo Hessert et al; licensee BioMed Central Ltd.2005Jo Hessert et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Measurement of foot pressure distribution (FPD) is clinically useful for evaluation of foot and gait pathologies. The effects of healthy aging on FPD during walking are not well known. This study evaluated FPD during normal walking in healthy young and elderly subjects.
Methods
We studied 9 young (30 ± 5.2 years), and 6 elderly subjects (68.7 ± 4.8 years). FPD was measured during normal walking speed using shoe insoles with 99 capacitive sensors. Measured parameters included gait phase characteristics, mean and maximum pressure and force, and relative load.
Time-series measurements of each variable for all sensors were grouped into 9 anatomical masks.
Results
Elderly subjects had lower normalized maximum pressure for the medial and lateral calcaneal masks, and for all medial masks combined. In the medial calcaneus mask, the elderly group also had a lower absolute maximum and lower mean and normalized mean pressures and forces, compared to young subjects. Elderly subjects had lower maximum force and normalized maximum force and lower mean force and normalized mean forces in the medial masks as well.
Conclusion
FPD differences between the young and elderly groups were confined to the calcaneus and hallux regions and to the medial side of the foot. In elderly subjects, weight bearing on the lateral side of the foot during heel touch and toe-off phases may affect stability during walking.
==== Body
Background
Measurement of foot pressure distribution (FPD) is clinically useful because it can identify anatomical foot deformities [1], guide the diagnosis and treatment of gait disorders and falls, as well lead to strategies for preventing pressure ulcers in diabetes. Age-related anatomical and physiological changes in foot bone and ligament structure affect FPD during gait [1]. Gait analysis of healthy elderly people has revealed decreased stride length, reduced step force and increased variability in gait parameters. These findings indicated that unsteadiness during walking is increased in the community-dwelling elderly people, posing a risk for falls [2]. Age was independently associated with lower pressure under the heel, midfoot, and hallux in the multivariate analysis [3]. Foot pressure studies during walking have focused on specific pathology and deformity [4-6] specific anatomical areas [7], exercise [8] and younger subjects [9-11]. Knowledge of the plantar FPD map during normal walking in healthy elderly people is lacking. It is not known if distribution of plantar pressure, force, and load across several anatomical regions of the foot during walking is different between young and old. To determine the effects of normal aging on FPD, we evaluated the anatomical distribution of plantar pressure, force, and relative loads in healthy young and old subjects during walking.
Methods
Subjects
The study was performed in the Syncope and Falls in the Elderly (SAFE) Laboratory at the Beth Israel Deaconess Medical Center, and all subjects signed informed consent approved by the Institutional Review Board. Subject characteristics are shown in the Table 1: 9 young subjects (5 men and 4 women; mean age 30 ± 5.2 years, mean ± SD, range 23–39 years), and 6 elderly subjects (4 men and 2 women, mean age 68.7 ± 4.8, range 63–74 years). All subjects were screened with a detailed medical history, physical activity questionnaire, electrocardiogram, and were not treated for any systemic disease. Inclusion criteria were: age range 20–40 or 60–80 years, ability to walk a flight of stairs, and ability to walk for 12 minutes. All subjects were normotensive by medical history, confirmed by measurements of the sitting and standing heart rate and blood pressure. Height and body mass were measured and used in FPD analysis. Shoe size and foot imprints were taken to determine the insole size. Exclusion criteria were: neurological or musculoskeletal abnormalities affecting gait, peripheral neuropathies, diabetes, past hip/leg/foot trauma or surgery, dementia, epilepsy, alcohol, smoking and other drug abuse, current pregnancy, history or physical evidence for coronary artery disease, abnormal electrocardiogram (ST-T wave changes, old myocardial infarction, arrhythmias, bundle branch block), history of more than one fall or syncope in the past year, orthostatic hypotension, systemic disease requiring continuous medical treatment for >1 month, malignant neoplasms, hepatic, renal, heart disease or failure, hypertension, and body mass index (BMI) >35. The arch indexes of the subjects were not measured.
Table 1 Demographic characteristics
Demographics Young Old P
Age (years) 30 ± 5.2 68.7 ± 4.4 <0.0001
Men/Women 4/5 2/4
Mass (kg) 72.3 ± 7.5 70.3 ± 13.6 NS
Height (cm) 175 ± 9.5 169.9 ± 7.8 NS
BMI 23.2 ± 4.6 24.2 ± 3.1 NS
NWS (m/s) 1.25 ± 0.25 1.2 ± 0.2 NS
Stride (s) 1.1 ± 0.2 1.04 ± 0.1 NS
Step (s) 0.6 ± 0.1 0.6 ± 0.1 NS
Stance (s) 0.6 ± 0.1 0.6 ± 0.1 NS
Swing (s) 0.5 ± 0.1 0.4 ± 0.04 NS
Rate Perceived Exertion (RPE) 2.5 ± 1.4 4.2 ± 1.2 0.004
Δ RPE Beginning-End 0.22 ± 0.7 0.1 ± 0.4 NS
Physical Activity Questionnaire 4.8 ± 1.1 4.9 ± 1.1 NS
Mean ± SD
NWS – normal walking speed
BMI – body mass index
Experimental protocol and data acquisition
Foot pressure distribution was measured during walking on the treadmill at individual normal walking speed. A treadmill was used to ensure a consistent speed, despite of its artificial milieu, as plantar pressure and force vary at different gait speeds [6]. Self-paced normal walking speed (NWS) was determined with hallway walking for 12 minutes. During walking, the subject was followed by the investigator for safety and timing purposes. Total distance (m) was divided by the walking time to determine individual NWS. Gait characteristics at NWS (step, stride, stance and percentage of the initial and terminal double stance) were not different between the groups (Table 1). The treadmill walk started at 0.8 mph for all subjects and increased 0.2 mph every 30 seconds until NWS was achieved. All subjects walked at their NWS for 6 minutes. FPD analysis was done on 100 steps (50 left and 50 right) selected from steady data segments after 2 minutes of sustained treadmill walking. At the end of walking, the treadmill decelerated over 1-minute and stopped. Subjects rated perceived exertion using 10-point Borg Rating Perceived Exertion scale [12] before the treadmill walk started, at the end of the speed increase period, and at the end of normal walking. Subjects sat on a chair while heart rate and blood pressure were monitored for six additional minutes during the post-walk period. Foot pressure distribution was measured using the shoe insoles with 99 capacitive sensors, connected to a small portable data acquisition device that sampled pressure for each sensor at 50 Hz (Pedar Mobile, Novel Electronics Inc., GmbH Munich, Germany). The insoles were calibrated regularly using a 'Trublu' calibration device (Novel GmbH, Munich, Germany). Two insole sizes (size WW = European shoe size 40/41, size XW = European 41/42) were used to account for differences in foot sizes. To control for differences in personal footwear, all subjects were provided with a standard, thin pair of slippers.
Data analysis
All data were visually inspected prior to analysis to assure high quality of data acquisition.
Figure 1A shows distribution of maximum pressure for one step for all sensors. Time-series pressure measurements for all sensors were grouped into nine anatomical masks [5,13,14] (Figure 1B). These masks corresponded to the following anatomical areas: medial calcaneus, lateral calcaneus, medial arch, lateral arch, first metatarsal, metatarsals two and three, metatarsals four and five, hallux, and toes. The following 5 variables were calculated for the each mask: maximum pressure, maximum force, mean pressure, mean force, and relative load. All variables were calculated for each step and then averaged over the 50 steps for each foot. Maximum pressure was defined as the greatest pressure any single sensor in each mask measured in a single step, and these values were averaged separately for each mask over 50 steps. Mean pressure was defined as the average of all activated sensors in a mask for a single step. To calculate maximum and mean forces, the pressure time-series data were converted to force by multiplying each pressure value with the cross-sectional area of the corresponding sensor. All sensors in a defined mask were added together for each time frame to give the summed time-series for force, which was the total force for each mask. The maximum force was defined as the greatest force exerted for each mask in a single step. The mean force was defined as the average force exerted in each mask for a single step. Body weight was significantly different between men and women (p < 0.0001). All variables were normalized by body weight (BW) and the area of each mask, to account for these factors. Relative load was defined as the ratio of the total force in a specific mask to the total force of all masks combined, expressed as a percentage [5].
Figure 1 Foot pressure distribution. A. Maximum pressure distribution on all sensors during stance for one subject. B. The nine anatomical masks superimposed on the insole (MC = medial calcaneus, LC = lateral calcaneus, MA = medial arch, LA = lateral arch, MT1 = first metatarse, 3 = second and third metatarse, 4 = fourth and fifth metatarse, H = hallux, and T = toes).
Statistical analysis
The maximum and mean pressure and force were compared between the groups for all masks. In addition, we compared the mean and maximum pressure and force in the medial masks (medial calcaneus, medial arch, first metatarsal, and hallux) to the lateral masks (lateral calcaneus, lateral arch, second and third metatarsal, and toes) and between the groups. We also compared the anterior masks (hallux, toes, first metatarsal, second and third metatarsal, and fourth and fifth metatarsals) to the posterior masks (medial arch, lateral arch, medial calcaneus, and lateral calcaneus) and the anterior masks (hallux and first metatarsal) similarly. Within group comparisons between masks were done using nonparametric ANOVA (Friedman test). Comparisons between groups were done using Wilcoxon nonparametric test using JMP 5.0.1 software (SAS Institute 2003).
Results
Foot pressure distribution was highly significantly different between masks for the young and old groups for all variables (maximum and mean pressures p < 0.00001, normalized maximum and mean pressures <0.00001 and maximum and mean force p < 0.00001 and normalized maximum and mean force p < 0.00001). Differences in the foot pressure distribution between the young and old groups for the maximum and mean pressures were confined to the calcaneus region and to the medial masks of the foot. Figure 2 shows differences in maximum pressure distribution (normalized for body weight (BW)) for all 9 anatomical regions. Elderly subjects had lower normalized maximum pressure in the medial (3.2 ± 0.5 vs. 4.6 ± 1.1 %BW, p = 0.001) and lateral (2.8 ± 0.6 vs. 3.4 ± 0.8 %BW, p = 0.036) calcaneal masks, for all medial masks combined (2.6 ± 0.2 vs. 3.3 ± 0.2 %BW/cm2, p = 0.019) and marginally reduced in the hallux mask (2.5 ± 1.2 vs. 3.7 ± 1.6%BW/cm2, p = 0.07). In the medial calcaneus region, the elderly group also had lower maximum pressure (22.2 ± 6.3 vs. 32.9 ± 11.8 N/cm2, p = 0.01), as well as lower mean (6.2 ± 1.8 vs. 8.9 ± 3.1 N/cm2, p = 0.01) and normalized mean pressure (0.9 ± 0.2 vs. 1.2 ± 0.2 %BW/cm2, p = 0.0006) (Figure 3A). The elderly subjects had also lower maximum force (240.9 ± 77.9 vs. 328.4 ± 138.7 N, p = 0.049) and normalized maximum force (34.3 ± 6.2 vs. 45.6 ± 8.5 %BW, p = 0.001) and the mean force (126.3 ± 34.9 vs. 178.8 ± 71.0 N, p = 0.02) and the normalized mean forces (18.3 ± 3.5 vs. 24.6 ± 4.2 %BW/ cm2, p = 0.0006) (Figure 3B). In the medial region masks, the elderly group had reduced maximum pressure (17.7 ± 1.6 vs. 23.2 ± 1.4 N/cm2, p = 0.02), reduced normalized maximum pressure (2.6 ± 0.2 vs.3.3 ± 2.0 %BW, p = 0.019); and reduced normalized mean pressure (0.5 ± 0.1 vs. 0.7 ± 0.1 % BW, p = 0.037) and borderline mean pressure (3.5 ± 0.5 vs. 4.8 ± 0.4 N/cm2, p = 0.06). In all anterior region masks, the elderly group exerted lower mean pressure (4.1 ± 2.3 vs. 4.8 ± 2.2 N/cm2, p = 0.046), borderline reduced mean force (57.3 ± 36.0 vs. 67.2 ± 33.6 N, p = 0.052) and borderline reduced normalized mean force (8.2 ± 4.5 vs. 9.8 ± 5.0 %BW, p = 0.055).
Figure 2 Pressure distribution by anatomical region. Normalized maximum pressure distribution for the young (white bar) and elderly (black bar) group for each anatomical region (medial calcalneus mask p = 0.0001, lateral calcaneus mask p = 0.03).
Figure 3 Medial calcaneus mask. A. The average maximum and mean pressures, and normalized mean and maximum pressures for medial calcaneus mask for young and old subjects (**p = 0.01, *** normalized maximum pressure p = 0.001, *** normalized mean pressure p = 0.0006). B. The average mean and maximum forces and normalized mean and maximum forces for medial calcaneus for the young and old groups (mean ± SD, maximum force * p = 0.05 *** normalized maximumn force p = 0.001, mean force * p = 0.02, *** normalized mean force p = 0.0006).
In the anterior medial region (hallux and first metatarsal), the elderly group displayed reduced mean pressure (3.6 ± 2.2 vs. 4.7 ± 2.1 N/cm2, p = 0.03), reduced normalized mean pressure (0.5 ± 0.03 vs. 0.7 ± 0.3 % BW, p = 0.027). The relative load in the medial masks (11.0 ± 8.8 vs.12.0 ± 7.8%) and the lateral masks (11.2 ± 6.8 vs.10.4 ± 6.2%) were not different. The relative load over the medial and lateral arches was not different between groups. Elderly subjects lower medial pressure values compared to young subjects, indicates that older people had tendency for greater weight bearing on the lateral mask relative to young subjects. The arch height, has not been measured, however, the contact mid-foot area was not different between the groups.
Rate perceived exertion was higher in the older subjects at the end of treadmill speed increment (beginning of normal walk) (p < 0.01), as well as at the end of normal treadmill walking (p < 0.004). However, the difference in perceived exertion between the beginning and end of normal walk was not significant between groups. There was no significant difference between groups in the physical activity questionnaire on the scale 0–10 (Table 1).
Discussion
Our study has shown that elderly people exert less pressure and force under the medial masks of the foot (medial calcaneus, hallux, anterior and posterior medial masks) during heel touch and toe-off phase. This implicates that elderly subjects preferentially bear weight on the lateral foot during normal walking. Lateralization of foot pressure suggested that medial weight bearing from heel-strike to toe-off is limited in older people compared to younger subjects. Well-distributed weight bearing and foot pressure compensate for the forces and heavy loads imposed on the foot during normal walking. Treadmill walking is different than normal walking due to an inability to change speed voluntarily and reduced stride variability. Although an artificial pace and walking environment are imposed by use of a treadmill, it was a tool used to maintain experimental control. Because foot pressure distribution is affected by walking speed and stride variability, [6] it was deemed necessary to control the speed using treadmill walking. In the posterior masks, the older subjects exerted lower maximum pressure and force on the calcaneus region when normalized for body weight, indicating that, along with the results above, maximum pressure at heel strike is also lower in old subjects than in young subjects. These findings may indicate that forces needed to stabilize the ankle during heel touch phase are reduced in older people. In the anterior masks, the elderly subjects also exerted lower normalized mean pressure and lower normalized mean force compared to young subjects. These findings, supported by results in the hallux mask, support the notion that old subjects have lesser ability to push-off in anticipation of the swing phase.
Walking may present a challenge to elderly people, and several age-related gait changes have been identified [2,3]. Morag et al. 1997[3] found that age correlated with heel pad stiffness, but to a lesser degree with walking speed, soft tissue characteristics, and height of the medial longitudinal arch. Our study did not confirm an age-related arch-flattening phenomenon to the extent of altered FPD, as forces in the medial arch area were not different between groups. Normal walking speed, stride intervals, timing within the gait cycle and the relative load in the arch area were similar between young and old subjects. These findings rebuke the notion that age-related decline in pressure is due to flattening of the longitudinal arch or that the stride length would be the primary factor underlying the reduced pressure and forces at heel strike. Anatomical foot structure, including soft tissue thickness and arch height, account for 35% of plantar pressure differences during gait [6]. Pressure values under the heel and midfoot are predominantly affected by weight bearing at the heel strike and midstance, whereas pressures in the anterior regions are determined to a greater extent by flexibility, muscle strength, and muscle recruitment [5]. Therefore, age-related soft tissue and bony structure degradation may reduce the capability of the plantar foot to deflect load [15]. FPD pattern in older people was similar to the pattern of experimentally reduced plantar sensation by cooling, emphasizing that decline in proprioception with aging may contribute to these results [11]. Older runners exhibited significantly more knee flexion at heel strike, but the range of motion and peak maximal vertical forces were reduced. The ground impact force and the initial rate of loading at heel strike were greater, indicating loss of shock absorbing capacity in older people [8].
Limitations
The number of subjects in our study was relatively small, but was comparable to other studies of gait and foot pressure [5,9]. However, our study used the large number of steps during steady walking compared to previous studies. Moreover, selection of steps from the middle portion of the walk minimized inconsistencies that may accompany gait initiation and termination [5]. The foot shape (high vs. flat arch) has not been assessed. However, the midfoot contact area and the relative load in the medial and lateral arch masks were not different between groups.
Conclusion
Healthy aging affects the dynamics of foot pressure distribution during normal walking. The forces and pressures under the medial foot masks were reduced in elderly people, resulting in lower propulsion during the step from the heel-touch to the toe-off phases. Clinically, lateralized foot pressure and lessened propulsion may affect walking ability in elderly people, posing difficulties in balance, forward thrust, and terrain adaptation.
List of abbreviations
BMI = body mass index
BW = body weight
FPD = foot pressure distribution
NWS = normal walking speed
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
MH – the recipient of American federation on Aging Scholarship, designed and performed data analysis and wrote the first version of the manuscript. MV – participated in the experiments, software development and analysis. JL – participated in the experiments and analysis. KH – participated in the statistical analysis. LL – contributed to data interpretation and manuscript preparation. VN – designed the study, conducted the experiments, participated in the analysis, data interpretation, and manuscript preparation.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
This study was sponsored by The Older American Pepper Center Grant 2P60 AG08812-11; Research Resource Cores A and B and the General Clinical Research Center grant MO1-RR01302. The authors wish to thank Shiva Gautam PhD for consultation on statistical methods.
==== Refs
Rodgers MM Dynamic foot biomechanics. J Orthop Sports Phys Ther 1995 21 306 316 7655474
Hausdorff JM Edelberg HK Mitchell SL Goldberger AL Wei JY Increased gait unsteadiness in community-dwelling elderly fallers. Arch Phys Med Rehabil 1997 78 278 283 9084350 10.1016/S0003-9993(97)90034-4
Morag E Cavanagh PR Structural and functional predictors of regional peak pressures under the foot during walking. J Biomech 1999 32 359 370 10213026 10.1016/S0021-9290(98)00188-2
Phillipson A Dhar S Linge K McCabe C Kleneman L Foot Ankle Int 1994 15 595 598 7849974
Kimmeskamp S Henning EM Heel to toe motion characteristics in Parkinson patients during free walking. Clin Biomech 2001 16 806 812 10.1016/S0268-0033(01)00069-9
Cavanagh PR Morag E Boulton AJ Young MJ Deffner KT Pammer SE The relationship of static foot structure to dynamic foot function. J Biomech 1997 30 243 250 9119823 10.1016/S0021-9290(96)00136-4
Luger EJ Nissan M Karpf A Steinberg EL Dekel S Patterns of weight distribution under the metatarsal heads. J Bone Joint Surg Br 1999 81 199 202 10204920 10.1302/0301-620X.81B2.9353
Bus SA Ground reaction forces and kinematics in distance running in older-aged men. Med Sci Sports Exerc 2003 35 1167 1175 12840638
Lawless MW Reveal GT Laughlin RT Foot pressures during gait: a comparison of techniques for reducing pressure points. Foot Ankle Int 2001 22 594 597 11503987
Imamura M Imamura ST Salomao O Perera CA De Carvalho AE Neto RB Pedobarometric evaluation of the normal adult male foot. Foot Ankle Int 2002 23 804 810 12356177
Eils E NOlte S Tewes M Thorwesten L Volker K Rosenbaum D Modified pressure distribution patterns in walking following reduction of plantar sensation. J Biomech 2002 35 1307 1313 12231276 10.1016/S0021-9290(02)00168-9
Borg G Perceived exertion as an indicator of somatic stress. Scand J Rehab Med 1970 2 92 98
Kanatli U Yetkin H Bolukbasi S Evaluation of the transverse metatarsal arch of the foot with gait analysis. Arch Orthop Trauma Surg 2003 123 148 150 12734711
Kellis E Plantar pressure distribution during barefoot standing, walking and landing in preschool boys. Gait Posture 2001 14 92 97 11544059 10.1016/S0966-6362(01)00129-1
Weijers RE Walenkamp GH van Mameren H Kessels AG The relationship of the position of the metatarsal heads and peak plantar pressure. Foot Ankle Int 2003 24 349 353 12735379
| 15943881 | PMC1173105 | CC BY | 2021-01-04 16:30:32 | no | BMC Geriatr. 2005 May 19; 5:8 | utf-8 | BMC Geriatr | 2,005 | 10.1186/1471-2318-5-8 | oa_comm |
==== Front
BMC Health Serv ResBMC Health Services Research1472-6963BioMed Central London 1472-6963-5-471597812610.1186/1472-6963-5-47Research ArticleDo medical outpatients want 'out of hours' clinics? Feeney Claire L [email protected] Nicola J [email protected] Martyn R [email protected] Department of Respiratory Medicine, NHLI at Charing Cross Hospital, Imperial College, St Dunstans Road, London W6 8RP, UK2005 24 6 2005 5 47 47 7 1 2005 24 6 2005 Copyright © 2005 Feeney et al; licensee BioMed Central Ltd.2005Feeney et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Patient choice is a major theme in current healthcare delivery. Little is known about patients' wishes regarding the timing of medical outpatient clinics.
Methods
A questionnaire survey of 300 sequential patients attending cardiac and respiratory clinics to determine patients preferences for out of hours and weekend outpatient clinics. (Out of hours defined as a clinic after 5 pm on Mon – Fri)
Results
Two hundred and 64 patients completed the survey of which 165 (62.5%) wanted either an out of hours clinics or a weekend clinic. Sixty four (38.8%) specifically stated that this was because of work commitments but for many others, the reasons given were easy to justify.
Conclusion
Current provision for outpatient consultation may not be convenient for many patients with heart and lung disease. A fuller evaluation of the cost and benefits of more flexible clinic hours is now needed.
==== Body
Background
Patient choice is a key part of current U.K. National Health Service (NHS) Strategy [1]. At a time when the population has access to 24 hour banking and to supermarkets which are open 24 hours a day, specialist consultations in U.K. hospitals for non-emergency conditions remain largely confined to the hours of 9-5 pm. In this regard it would appear that the NHS has failed to keep pace with a society which generally demands fast, convenient and 24/7 services.
The Department of Health's 10 year plan has echoed these sentiments and specifically states that the NHS has been too slow to change its ways of working to meet modern expectations in this consumer age. While it recognises that the NHS is under funded, money alone can only be a starting point. Cost-effectiveness, it states, is the key to success and this can only be achieved if available resources are used to achieve real benefits for patients. Clearly, the redundancy of most outpatient clinics after 5 pm and during the weekend is not an efficient use of resources, nor is it a modern way of working.
Medical practice nowadays strives to be patient-centred [2]. There is good evidence that involving patients in decision-making and listening to the patient voice improves health outcomes and patient satisfaction. Hence, when we undertook an extensive literature review, we were surprised to find no published work concerning medical patients' views on out of hours clinics in secondary care. Given the current government proposals we felt it necessary to explore patients' views about out of hours clinics amongst patients attending medical outpatients' clinics in a central London teaching hospital.
After embarking on our study of medical outpatients we subsequently found two other reports on patients' opinions on out of hours ophthalmology clinics. The first is a study of patients with ophthalmological conditions attending a hospital in Leeds and Bristol which looked at whether patients found their current appointments and surgery times convenient or inconvenient [3]. They found that 89% of their patients were apparently happy with their current appointment times but when asked about alternatives would find Saturday mornings convenient. The second study was a critique of the first and reported the responses of 100 consecutive patients attending Saturday morning ophthalmology clinics at an outer London hospital [4]. They were asked whether they preferred a Saturday morning clinic, a regular 9-5 appointment, or whether they didn't mind either. They found that 50% had no preference, 41% preferred a Saturday morning and only 9% preferred a 9-5 pm weekday appointment. Both these studies have their limitations in that the first essentially asked about convenience not preference and the second may be affected by bias in that verbal responses alone were reported of a select group of patients i.e. only those already attending a Saturday morning clinic. These studies are based in ophthalmology clinics and may not be representative of all patients attending hospital outpatient clinics. Our study is based on respiratory and cardiology outpatient clinics. These two disease areas account for a major part of the burden of medical illness in the UK with 8 million people having lung disease alone.
Methods
Centre of data collection: Charing Cross Hospital, London
Clinics: Respiratory, Monday morning, Wednesday morning and Thursday afternoons; Cardiology, Thursday morning
Duration of data collection: 6 months
Patient Profile: Outpatients routed through the central booking office (excluding rapid or open access respiratory and cardiology clinics).
300 sequential attendees at Cardiorespiratory clinics were asked to complete a questionnaire [see additional file 1] to determine their opinions regarding access to out of hours (defined as after 5.00 pm) and weekend outpatient clinics. They were then asked to give up to five reasons as to why they might be interested in such clinics. The patients included a mixture of patients attending for the first time and those attending for follow-up appointments. The reception staff were specifically asked to give the questionnaire to all patients who had not previously received them. The items selected for inclusion in the questionnaire had been raised repetitively in another study (not yet published) looking at reasons why patients did not attend clinics (forgetfulness, long waits, seeing a different doctor each time, nowhere to park, time off work, no one available for childcare).
Data was analysed using the statistical package SPSS (version 12.0), however as this was an observational study power calculations were not calculated and data was only subjected to descriptive analysis
Results
264 completed questionnaires were obtained (response rate 88%) from 124 males and 122 females with a mean age (SD) of 58 years (16.94). 144 of the patients were attending with a respiratory condition (amongst which were 52 with asthma, 18 with sleep related breathing disorders, 13 with unexplained cough) 65 with a cardiac condition (25 with ischaemic heart disease, 12 with arrhythmias, 9 with hypertension), and the remainder did not state their condition or had an ill-defined medical problem.
165 patients (62.5%) wanted either an out of hours clinic or a clinic on a Saturday or Sunday. Of the reasons given, 81 patients (49.1%) said it was the greater flexibility that such clinics offered with 64 (38.8%) specifically stating that it was because they worked during the day. Forty one (24.8%) responded that it was easier for them to get to the hospital in the evening because someone could drive them there. The same number responded that it was easier to get someone to accompany them in the evening, and 22 (13.3%) stated that the reason was because they had family commitments during the day. 18 patients listed other reasons (see Table 1) which included important practical issues such that parking restrictions in the environs of the hospital would not apply in the evening and at weekends.
Table 1 'Other' Reasons volunteered by patients for wanting out of hours clinics
Reason Number of patients
I am a shiftworker or self-employed so out of hours clinics would be more convenient 4
Less traffic and less stressful to get to the hospital 3
Parking restrictions would not apply 3
I would not have to finance child care at these times 3
Waiting times would probably be reduced 2
When the responses were sub-analysed according to whether the respondent was over or under the age of 65 years, 152 patients were seen to be under the age of 65. Of those 152 patients, 110 (72.4%) expressed a preference for out of hours clinics, whereas amongst the 100 patients aged over 65, 49 (49%) expressed such a wish. Not surprisingly amongst those aged under 65, the commonest reason stated for why they were interested in an out of hours clinic was that they worked during the daytime, and this response was given by 58 out of the 110 of the patients (53%)
The responses also varied according to the medical condition of the patient. Of the 144 patients attending with a respiratory condition, 97 (67.4%) wanted out of hours clinics, compared to 36 out of the 65 (55.4%) patients attending with a cardiac condition. However, the mean age of respiratory patients was 55 years compared to 65 years in the cardiac group.
Of those patients who wanted out of hours clinics, weekend clinics appeared to be consistently more popular than evening clinics and this trend was upheld even when the responses were analysed according to age, gender and medical condition.
Discussion
The majority of medical outpatients we questioned would like more flexible timing of clinics. The reasons expressed to justify such a preference appear to be entirely reasonable, such as work commitments during the day. An extension of hours for routine consultations may therefore enhance care for those who are in employment. It also represents a logical fuller use of outpatient consultation facilities. However, out of hours clinics involve more than a doctor-patient consultation. Additional reception and nursing staff are likely to be needed and if the consultation is to be truly effective for the patient they would need to be able to have simple investigations like blood tests, ECG and imaging tests at the same time. Further economic evaluation of the cost of making such services available would be necessary before the widespread introduction of out of hours clinics. However, not all outpatients require investigations and it may not be difficult to construct a list of conditions where patient attending for follow-up can be offered out of hours services without other departments needing to be available.
The patients surveyed in this study were patients with medical conditions attending an inner city London teaching hospital. In a patient centred health service similar studies should probably be done amongst those with other conditions living in other areas.
The response rate for our study was high and reasons for non response are not known but could include the patient having gone straight into see the doctor and having no waiting period in which to complete the form. In a multicultural society some may have had difficulty with a questionnaire in the English language and up to 15% of patients attending some UK out patient clinics may be functionally illiterate [5]. The response rate is unlikely to have altered the validity of the conclusions which are similar to one study in an ophthalmology clinic [4] but dissimilar to another [3]. The differences almost certainly reflect the question which is asked (stating actual preferences versus stating satisfaction with what you have) and how it is asked and by whom.
Conclusion
We feel that this is an interesting and important area of research with the results suggesting that the hours of opening of traditional medical outpatients clinics should be extended. Each hospital and each speciality should probably survey their own clientele, but to enable comparisons to be made some form of standardised wording should be used and the questionnaire itself should be included in any subsequent report.
Competing interests
MRP, CF and NJR do not have any significant competing interests (financial or non-financial).
Authors' contributions
MRP developed the study design and protocol. NJR and CF were responsible for implementing the study and analysing the results. All contributed to drafting the report and approved final manuscript.
Additional file 1:
Pre-publication history
The pre-publication history for this paper can be accessed here:
Supplementary Material
Additional File 1
A copy of the questionnaire used for this study.
Click here for file
==== Refs
Department of Health The NHS Plan: a plan for investment, a plan for reform presented to Parliament by the Secretary for Health by Command of Her Majesty, July 2000 London Stationery Office 2000
Stewart M Brown JB Donner A McWhinney IR Oates J Weston WW Jordan J The impact of patient-centered care on outcomes J Fam Pract 2000 49 796 804 11032203
Churchill AJ Gibbon C Anand S McKibbin M Public opinion on weekend and evening outpatient clinics Br J Ophthalmol 2003 87 257 8 12598431 10.1136/bjo.87.3.257
Zaidi FH Lee N Public opinion favours out-of-hours clinics interviews challenge multi-centre questionnaire [electronic response to Churchill etal. Public opinion on weekend and evening outpatient clinics] bjophthalmolcom 2003 16 April 2003
Gordon M Hampson R Capell H Madhok R Illiteracy in rheumatoid arthritis patients as determined by the Rapid Estimate of Adult Literacy in Medicine (REALM) score Rheumatology 2002 41 750 754 12096223 10.1093/rheumatology/41.7.750
| 15978126 | PMC1173106 | CC BY | 2021-01-04 16:31:49 | no | BMC Health Serv Res. 2005 Jun 24; 5:47 | utf-8 | BMC Health Serv Res | 2,005 | 10.1186/1472-6963-5-47 | oa_comm |
==== Front
BMC Med ImagingBMC Medical Imaging1471-2342BioMed Central London 1471-2342-5-41592707210.1186/1471-2342-5-4Research ArticleA new anisotropy index on trabecular bone radiographic images using the fast Fourier transform Brunet-Imbault Barbara [email protected] Gerald [email protected] Christine [email protected] Rachid [email protected] Claude-Laurent [email protected] Equipe Inserm 658, Hôpital Porte Madeleine, BP 2439, 45032 Orléans Cedex 1, France2 Laboratoire d'Electronique, Signaux, Images, Université d'Orléans, BP 6744, 45067 Orléans, France2005 31 5 2005 5 4 4 1 9 2004 31 5 2005 Copyright © 2005 Brunet-Imbault et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
The degree of anisotropy (DA) on radiographs is related to bone structure, we present a new index to assess DA.
Methods
In a region of interest from calcaneus radiographs, we applied a Fast Fourier Transform (FFT). All the FFT spectra involve the horizontal and vertical components corresponding respectively to longitudinal and transversal trabeculae. By visual inspection, we measured the spreading angles: Dispersion Longitudinal Index (DLI) and Dispersion Transverse Index (DTI) and calculated DA = 180/(DLI+DTI). To test the reliability of DA assessment, we synthesized images simulating radiological projections of periodic structures with elements more or less disoriented.
Results
Firstly, we tested synthetic images which comprised a large variety of structures from highly anisotropic structure to the almost isotropic, DA was ranging from 1.3 to 3.8 respectively. The analysis of the FFT spectra was performed by two observers, the Coefficients of Variation were 1.5% and 3.1 % for intra-and inter-observer reproducibility, respectively. In 22 post-menopausal women with osteoporotic fracture cases and 44 age-matched controls, DA values were respectively 1.87 ± 0.15 versus 1.72 ± 0.18 (p = 0.001). From the ROC analysis, the Area Under Curve (AUC) were respectively 0.65, 0.62, 0.64, 0.77 for lumbar spine, femoral neck, total femoral BMD and DA.
Conclusion
The highest DA values in fracture cases suggest that the structure is more anisotropic in osteoporosis due to preferential deletion of trabeculae in some directions.
==== Body
Background
The cancellous bone microarchitecture corresponds to the spatial organization and morphology of the trabecular network. Sugita et al. [1] observed that the mechanical behavior of the cancellous bone varied following the testing direction; these variations were interpreted as an anisotropic feature of the bone stress. Trabecular bone anisotropy corresponds to the preferential orientation(s) of trabeculae. Anisotropy is constituted under the influence of prefererential oriented strength applied to bone [2] and permits to establish resistance to these strengths in a given preferential direction. Sugita et al. [1] concluded that anisotropy of the cancellous bone should be considered to predict the fracture risk.
The determination of collagen and crystal orientation in connective tissues at molecular scale has been studied, for instance by diffraction [3-6]. Amorphous materials such as reinforced concrete have been characterized by x-rays and the orientation of fibers investigated by the Fourier transform method [7]. Defossez et al. assessed several methods on images of the femoral neck region: co-occurrence and run length matrix, spatial-frequency and fractal techniques to determine the trabecular direction [8]. These methods exhibited a high degree of accuracy, suggesting a possibility of trabecular orientation characterization in clinical practice [8].
Different methods are available to characterize the structural anisotropy on bone radiographs. In 1970, Singh et al. [9] developed a semi-quantitative index applied to femoral neck radiographs. This index is based on the existence of several arches of trabeculae in the femoral neck. Some arches preferentially disappear with age and osteoporosis, and the count of these arch systems can be used to determine the Singh index. Aggarwal et al. [10] developed a similar index for the calcaneus. Whitehouse et al. [11] introduced the Mean Intercept Length (MIL) defined as the average length between two bone/marrow interfaces. The MIL polar diagram generates an ellipse for 2D slice images [11] or projectional images such as radiographs [12], and an ellipsoid for 3D images [13]. A MIL tensor can be calculated [13] by fitting the MIL values and can be used to determine the Degree of Anisotropy (DA) [14]. The MIL method requires a previous binarization of the gray-level images, then it is a suitable method for the calculation of DA from 3D images obtained by Quantitative Computed Tomography (QCT) [15,16] or Magnetic Resonance Imaging [17]. Therefore, the binarization on 2D radiographs remains a critical step due to partial volume effect. The MIL method was used by Luo et al. [18] to compare the anisotropy of the 3D structure and of the 2D projected image of one in vitro sample and 14 simulation models derived from this sample. The authors reported a very good correlation (r = 0.99) between anisotropy values assessed on the 3D trabecular structure and the 2D projection images. Luo et al. [18] insisted on the interest of the estimation of architectural fabric from plain radiographs.
Few methods evaluating the trabecular structure have been developed on radiographs. Caldwell et al. [19] developed a method characterizing trabecular bone structure on vertebral digitized radiographs. An evaluation of the orientation named the fraction orientation edges is obtained from the histogram of the magnitude of the edge gradient versus the direction of the edges. Geraets et al. [20] developed an index called Line Fraction Deviation (LFD) derived from the tresholded radiographs and based on the fraction of bone pixels. A diagram plotting the standard deviation of this fraction in all directions could reflect the orientation of the trabecular bone. This method has been found more sensitive than MIL method on bone radiographs to evaluate anisotropy [12]. Jiang et al. [21] developed a method for a non invasive evaluation of bone mechanical properties: textural features, the global Minkowski dimension and trabecular orientation were determined using Minkowski dimension analysis. Jiang et al. demonstrated the contribution of normalized Bone Mineral Density (BMD), structural features and patient age to bone mechanical properties. In 1993, Oxnard reported slight visible microarchitectural changes from the Fourier transform on bone radiographic images but no parameter calculation was performed [22]. The same group worked on vertebral bodies T1 to L5 in seven male columns and applied the FFT to the radiographic images of these vertebrae. They characterized the orientation and size of the architectural elements of vertebral cancellous bone, and underline the potential of this technique to define the effects of ageing [23]. Wigderowitz et al. considered the properties of Fast Fourier Transform (FFT) to evaluate trabecular bone structure: the directional pattern of frequencies with high-magnitude can identify the orientation of trabeculae. He defined three indices including spectral trabecular index, longitudinal and transversal trabecular indices [24]. These indices approximate the evaluation of the trabecular structure in terms of trabeculae spacing and orientation. Wigderowitz et al. concluded that this quantification detects structural changes occurring with age and may be useful in osteoporosis studies [24]. Caligiuri et al. [25] also used the FFT to perform a structural analysis of the spine trabecular bone. The hypothesis was that the magnitude and the first moment of the power spectrum could correspond to the coarseness or the fineness of the texture pattern. The two texture measurements were compared to BMD. Caligiuri et al. concluded that this texture analysis might lead to a better prediction of the osteoporotic fracture risk [25]. Recently, Gregory et al. have proposed a FFT-based analysis of trabecular bone structure on hip radiographs from patients with and without hip fracture. They worked on FFT profiles parallel and perpendicular to the preferred orientation. Principal conponents analysis was used to generate scores from the profiles and was able to discriminate fracture and control groups better than fractal dimension [26].
Our research group has previously experienced fractal analysis on bone radiographs [27-29]. The measured parameter (Hurst coefficient) offers a global evaluation of the image irregularity, of its complexity. It is considered as an indicator of roughness. The Maximum Likelihood Estimator is applied first on one direction, then the process is repeated in 36 directions by 10 degrees steps. The directional results can be expressed on a polar diagram that can be itself be fitted to an ellipse; the shape of this polar diagram can be characterized in order to determine the textural anisotropy [30,31]. When comparing radius and calcaneus in the same subjects, Lespessailles et al. have shown significant differences [31] but the interpretation is equivocal because this technique characterizes the variations of grey level roughness following directions, and not directly the trabecular network orientation.
The osteoporotic fracture risk prediction is important especially in postmenopausal women. BMD is currently measured in clinical practice and textural parameters can be assessed on trabecular bone radiographs [19-22,24,25,31], but the anisotropy was not clearly quantified in these texture analyses. To address this question, we have worked on a quantitative evaluation of anisotropy on bone radiographs. The development of a structural parameter such as DA from radiographs is very promising; this parameter could be complementary of the BMD and of fractal texture parameters in the explanation of bone strength.
We describe here a new quantitative method based on the FFT to obtain anisotropy indices on bone radiographs of the calcaneus and a validation on synthetic images. The intra and inter-observer reproducibility and a pilot clinical study comparing osteoporotic fracture cases to control cases are presented.
Methods
Population of the pilot study
Postmenopausal women were recruited from a cross-sectional unicenter case control study. The protocol screened 400 women: 349 were enrolled. The inclusion and exclusion criteria have been previously described in details [28]. For this preliminary study, a sample of 22 osteoporotic fracture cases was randomly selected, and was secondarily age-matched with 44 control cases (for each age, we randomly selected two control cases with an equal age ± 5 years). The distribution of fracture cases was 1 hip fracture, 5 wrist fractures, 11 vertebral fractures and 5 metatarsus fractures, all these fractures were considered as low energy fractures. The ages of the control and fracture cases ranged from 45 to 87 years. The mean age was 69.2 ± 11.9 years for fracture cases and the mean age was 69.0 ± 11.7 years for control cases.
The BMD was measured by dual energy x-ray absorptiometry (Hologic® 4500 device) at lumbar spine and femoral neck. The mean lumbar spine BMD was respectively 0.814 ± 0.09 g.cm-2 and 0.895 ± 0.16 g.cm-2 (p < 0.05) for fracture cases and control cases. The mean femoral neck BMD was respectively 0.650 ± 0.09 g.cm-2 and 0.686 ± 0.12 g.cm-2 (ns) for the fracture cases and control cases.
Study design
Image realization
This study was performed on trabecular bone radiographic images of the calcaneus. The calcaneus radiographic images were performed following a standardized procedure reported elsewhere [27]. Briefly, the X-ray tube voltage (48 kV), the exposure conditions (18 mAs) and the focal-calcaneus distance (1 meter) were fixed for all patients. Kodak single emulsion Min RG films were used and all developed by the same film processor at fixed developer and fixer temperatures.
In order to obtain digitized images of the calcaneus trabecular bone, the radiographic films were digitized with an AGFA Duoscan scanner (AGFA GEVAERT N.V., Morstel, Belgium) with 256 gray-levels. Calcaneus is known to be a heterogeneous site of trabecular bone [32]. For this reason we have selected a large region of interest (ROI) of 2.7 × 2.7 cm2 (256 × 256 pixels with a pixel size of 105 μm). The ROI of 256 × 256 pixels (Figure 1) was defined from anatomic marks [27]. The basis of the ROI was positioned on a line linking the plantar aponeurosis insertion to the superior end of the Achilles tendon insertion, the ROI comprising both compressive and tensile trabecular network [10].
Noise filtering
The low frequency noise of an image corresponds to the gray-value variations over large distances, due to the radiological artifacts and to the fat tissues projections on the radiograph. In order to remove the low frequency noise and to take into account only trabecular components of the image, we used a convolution filter previously described by Geraets [33]. A kernel box was used; for each pixel, the average gray-value of the box was allocated to the box middle pixel. The new image obtained is the low-frequency image. The window must be small enough to extract the low frequency noise and large enough to prevent the trabecular pattern leaking into the low frequency region. For our images, the optimal size of the box was 25 × 25 pixels. The filtered image was obtained by subtracting the low-frequency image from the original images, this filter also removed cross of high intensity centered on the central pixel due to the finite bondaries of the ROI.
Fourier transform
The Fourier transform represents a signal in spatial frequency space. An image can be considered as a repartition of bright intensities in a (xOy) plane and can be expressed as a two-dimensional function f(x, y). The Fourier transform is expressed by a function F(μ,υ) with the two variables μ and υ corresponding to spatial frequencies in (μ Oυ) plane. The 2D Fourier transform spectrum of an image is expressed by the following formula:
where μ, υ and x, y are the respective variables of the frequency and the spatial domains and N the size of the image.
Any periodic structure in the original spatial-domain image is represented by peaks in the frequency-domain image at a distance corresponding to the period and a direction at right angle of the original orientation. If a mild degree of disorientation is introduced in an oriented periodic structure, the frequencies of the Fast Fourier transform (FFT) spectrum are spread over an angle corresponding to the deviation of the structure in the original image. By analogy, we hypothesized that the periodic structure is represented by trabeculae projection, and the degree of disorientation by anisotropy.
The magnitude of the transform corresponds to:
where Re = real part of the FFT and Im = the imaginary part of FFT.
The FFT was calculated on the gray level filtered images of the trabecular bone using the Visilog 5.1 software (Noesis). Then the magnitudes of the frequency images were divided to the total magnitude of the transform to normalize the contrast in the images according to the following formula:
Measurements on FFT spectrum
Trabecular bone was assimilated to an oriented structure with two main directions, the ROI including longitudinal and transversal trabeculae (Figure 1). All the FFT spectra of the calcaneus radiographs involved horizontal and vertical conponents (Figures 2 and 3). The horizontal components were indicative of the longitudinal trabeculae fabric and the vertical components were indicative of the transverse trabeculae fabric. We have to notice that the so-called horizontal and vertebral trabeculae were so described on the ROI, which was slightly rotated by comparison to the original image. The limit between high energy area representing trabeculae and low energy area corresponding to the noise on the FFT spectrum were visually determined by the operator. We measured the spreading angles of the longitudinal and the transversal trabeculae named respectively the Dispersion Longitudinal Index (DLI) and the Dispersion Transverse Index (DTI). In order to obtain an average value, the DTI and DLI parameters were measured in the two symmetrical parts of the FFT spectrum conponents (Figures 2b and 3b).
An index relative to the trabecular fabric or degree of anisotropy was derived from the measured parameters DLI and DTI. The Degree of Anisotropy (DA) was defined as:
For a perfectly isotropic structure, the FFT spectrum has a disc shape and DA is equal to unity. More isotropic trabecular bone structures will have DA values closer to unity.
Figures 2 and 3 illustrate two examples of digitized radiographic images and FFT spectra of trabecular bone at calcaneus. Figure 2 corresponds to a control case and Figure 3 to a vertebral fracture case.
Synthetic images
To test the reliability of DA assessment, we tested this method on projected volume with known disorientations. We synthesized 6 series of 8 images composed of beam like structures more or less aligned following two directions in order to obtain structures close to trabecular bone of calcaneus. For the less anisotropic structure, horizontal and vertical disorientations varied from 0 to 80° (Figure 4a), and for the most anisotropic structure, the disorientation of the beam like structures varied from 0 to 17° (Figure 4c). These synthetic images comprised a wide variety of structures, from anisotropic to almost isotropic, a variety much wider than expected in the clinical X-rays. The projections of these volumes were analyzed with the same software as bone radiographs.
Data analysis
Intra and inter-observer reproducibility of the measurements
The two measured parameters DLI and DTI and the derived parameter DA were determined to calculate the intra and inter-observer reproducibility. To determine the intra-observer reproducibility, a single observer performed two sets of measurements on the FFT spectra of 20 subjects with a one day interval between each set. To determine the inter-observer reproducibility, two sets of measurements were performed on the FFT spectra of 20 subjects by two observers. The observers were blinded for each sets of measurements.
The intra-observer and inter-observer reproducibilities were calculated for n subjects with the root mean square RMS average according to the following formula [34]:
where SDj is the standard deviation for the subject j and is the average of the measurements for the subject j.
Clinical evaluation
Results in these two groups were compared using Student's t-test for comparisons of the means after checking Gaussian distribution. The area under ROC curves was calculated for BMD measurements and DA.
Results
The results of synthetic images are represented on Table 1. The DA varied from 1.3 to.3.6, respectively corresponding from more anisotropic (Figures 4a and 4b) to almost isotropic structures (Figures 4c and 4d).
Table 2 shows the intra-observer and inter-observer RMSCVs. The RMSCVs of DA were respectively 1.5% and 3.1 %
Table 3 presents the results of the fabric indices obtained on the 22 osteoporotic fracture cases and 44 control cases. Results of DLI and DTI were statistically significant lower in osteoporotic cases (p < 0.01, p < 0.05, respectively) leading to a significantly higher DA.
In control cases DA was closer to 1 due to a large spreading of frequencies in the FFT spectra while DA was higher in osteoporotic cases in relation to a narrower frequency spreading. Comparing the DA values from Table 3 to Table 1, it appears that the controls (DA = 1.7) were in the 0–55° category and the fractures cases (DA = 1.9) were in the 0–45° category. The difference of the mean of DA between cases and controls was 8.7 % and close to the figured variation corresponding to the 95% confidence interval of the measurements [35].
Differences in DA determined by spectral analysis (p < 0.01) and lumbar spine BMD (p < 0.05) were significant (Figure 5). Whereas the difference between fracture cases and controls for femoral neck BMD was not significant. From the ROC analysis, the Area Under Curve (AUC) were respectively 0.65, 0.62, 0.64, 0.77 for lumbar spine BMD, femoral neck BMD, total femoral BMD and DA. There is a trend to higher AUC for DA comparatively to BMD measurements, but according to the small size of the population the statistical significance was not reached.
Discussion
We have developed a new index of trabecular bone anisotropy on radiographs based on a spectral analysis of the gray-level images. In this pilot study, this new index applied to radiographs of the calcaneus has shown a reasonable reproducibility for a technique at its first step of development. As it was demonstrated with synthetic images, the DA of an almost isotropic structure is close to one and the DA of an anisotropic structure is greater than one. We hypothesized that the trabeculae did not randomly disappear, the effect might be a reduction of frequencies on the FFT spectra in preferential directions leading to an increase of anisotropy. The results of this pilot study involving 22 osteoporotic fracture cases and 44 controls suggest that the DA parameter may be potentially useful to distinguish fracture cases from control cases.
The main interest of this technique is that it can be applied directly to gray level radiographic images without previous binarization. The radiographic technique provides a projection image. However a good 2D-3D correlation has been described concerning microarchitecture [29] and anisotropy [18] from gray level analysis.
The significantly higher DLI and DTI in control cases suggest that there are more various orientations of the elemental structures around the two main orientations (longitudinal and transversal) in control cases than in osteoporosis cases with vertebral fractures. The larger range of orientations in controls corresponds to a lesser anisotropic structure than in osteoporosis. DTI was the best discriminant parameter between fracture patients and control cases but also the less reproducible. There are only few transversal trabeculae comparatively to longitudinal ones and they disappear first with osteoporosis due to a less contribution in bone strength. The difference between fracture cases and controls was close to errors attributed to the intra or inter-observer reproducibility. The intra-observer reproducibility is close to the 1 to 2% of reproducibility found in usual bone densitometry method as dual x-ray absorptiometry [37]. The poor inter-observer reproducibility is due to the difficulty to identify the limit between high energy area of the spectrum (corresponding to trabeculae) and low energy area (corresponding to noise) in relation to the few numbers of trabeculae projections. Since the population size is small, further studies are required with larger groups. We could expect more stringent results with a more homogenous population of fractured patients with vertebral fracture, for instance.
The higher anisotropy found in osteoporosis cases is in accordance with the findings of Newitt et al. [38] who report that the increase of bone resorption in osteoporosis leads to a loss of thinner trabeculae first, resulting in an increase of anisotropy. The study of Newitt et al. was performed with the MIL method on 3D magnetic resonance images at the radius. The MIL method is widely used to determine the trabecular 3D structure anisotropy but some authors [39,40] discuss its reliability since it reflects the boundary orientation rather than the real anisotropy of the structural elements.
This concept of transversal and longitudinal systems of trabeculae must be cautiously interpreted in our study. Indeed the ROI on the calcaneus radiographic images is tilted around 45 degrees (Figure 1). The trabeculae were named longitudinal and transversal in reference to the radiographic image (Figure 1) and not to the ROI orientation (Figures 2a and 3a). Longitudinal trabeculae correspond to the compressive trabecular network extended from the subtalar joint and the transverse to the tensile trabecular network sweeping backwards and upwards the great tuberosity [41].
The anisotropy of trabecular bone is different according to the skeletal sites: in a study comparing the properties of calcaneus, distal femur, proximal femur and vertebrae on human specimens, Majumdar et al. [17] found the highest anisotropy of trabecular bone at the calcaneus followed by distal femur and proximal femur, vertebrae constituting the least anisotropic site.
Our results corroborate the studies of Geraets et al. [33] on hip and radius, Wigderowitz et al. [24] on wrist radiographs, Mosekilde et al. [42] on vertebrae and Ciarelli et al. [43] on femoral head samples. The Line Fraction Deviation was developed by Geraets on binarized radiographic images, and leads to the determination of the preferential orientations. There was no calculation of an anisotropy index but it was possible to quantify the anisotropy from the deviation of polar diagram from a circle.
The lower values of the Line Fraction Deviation index found in osteoporotic subjects were consistent with the early loss of the secondary compressive trabecular group of the hip [44]. Moreover, Geraets et al. showed in a study of the distal radius that the Line Fraction Deviation values decreased along the transversal direction with age whereas the orientation along the axial direction remains stable during the entire life [33]. Wigderowitz et al. [24] found using the spectral analysis at the distal radius that the transversal trabeculae are preferentially absorbed, thinned and spared with age. Mosekilde et al. in vertebrae [42] showed that compressive strength was greater in the vertical direction than in the transversal direction. This anisotropy in vertebral strength increased with age and indicated according to the authors that the transverse trabeculae were selectively removed. Buck et al. have found that the oblique conponents declined in the cranio-caudal direction particularly for age superior to 60 years leading to variation in anisotropy [23]. Ciarelli et al. [43] also found that fracture cases have proportionally more trabeculae aligned along the primary load axis (and thus proportionally fewer transverse trabeculae) than control cases; the authors hypothesized that the loss of transverse trabeculae leads to the difference in anisotropy between groups. Zhao et al. characterized iliac trabecular bone by micro-QCT and showed that trabeculae thinning led to a more isotropic structure in the first postmenopausal years whereas the structure became more anisotropic in the later years [45]. They hypothesized that, in the later years, the remaining trabeculae would be more widely separated, less connected and some more thickened leading to an increase of anisotropy.
It has been well established that the calcaneus structure is heterogeneous [32,46]. Lin et al. [32] have studied the calcaneus microarchitecture on MRI images. They analyzed 20 to 25 ROIs 1 × 1 cm2 in each calcaneus. They found a spatial heterogeneity in the posterior region of 40 %. In our study the ROI was 2.7 × 2.7 cm2 and represented a much larger area; it was accurately defined by anatomic marks, this point avoiding large variation in fractal analysis [27]. Furthermore our ROI contained both transversal and longitudinal trabeculae, if transversal trabeculae disappeared, it should be possible to calculate DA and a high value will be obtained. As the DLI and DTI measurements were not yet automated, the parameters were measured in the two symmetrical parts of the FFT spectrum in order to obtain an average value. In a near future the automation of our method could be performed, allowing applications to large sets of images. In spite of this lack of automatization the reproducibility of the DA parameter was acceptable and allowed for the accurate characterization of osteoporosis changes in small series. At this first step of development, this clinical study must be considered as a preliminary study evaluating the potential of this anisotropy evaluation.
Conclusion
This study has shown that the DA can be determined on plain radiographs using spectral analysis. The reproducibility of the DA values may be improved by automating the method. The distinction between fracture cases and control cases is very promising, but further studies are necessary to know if the DA evaluation could improve the osteoporotic fracture risk determination when combined with BMD and other textural parameters such as fractal analysis.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
BBI participated in the design of the study, carried out the measurements and the manuscript preparation, G L carried out measurements of reproducibility and synthetic images, CC performed statistical analysis and participated to the manuscript preparation, R H supervised the application of the Fourier Transform and CLB carried out the design of the study and supervised the manuscript preparation.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Figures and Tables
Figure 1 Radiographic image of the calcaneus showing the localization of the Region of Interest (ROI). Inside the ROI, longitudinal trabeculae correspond to the compressive trabecular network extended from the subtalar joint and the transverse to the tensile trabecular network sweeping backwards and upwards the great tuberosity. Arrows show anatomical landmarks corresponding to the bottom of the ROI.
Figure 2 Control case a: ROI of the digitized radiographicimage of calcaneus trabecular bone. b: FFT spectrum A: corresponds to longitudinal trabeculae B: corresponds to transverse trabeculae DLI: Dispersion Longitudinal Index, spreading angle of the longitudinal trabeculae DTI: Dispersion Transverse Index, spreading angle of the transverse trabeculae
Figure 3 Vertebral fracture case a Region of Interest (ROI) of the digitized radiographic image of calcaneus trabecular bone. b FFT spectrum DLI : Dispersion Longitudinal Index, spreading angle of the longitudinal trabeculae DTI : Dispersion Transverse Index, spreading angle of the transverse trabeculae
Figure 4 Synthetic images a: Synthetic image of astructure with orientations between 0 and 80° in 3 dimensional space b: Fast Fourier Transform (FFT) spectrum of the image 4a c: Synthetic image of a structure with orientations between 0 and 17° in 3 dimensional space d: FFT spectrum of the image 4c
Figure 5 Box plots of lumbar spine BMD and DA. A T-test was used to compare controls and fractured patients.
Table 1 DA assessment on synthetic images composed of cylinders more or less aligned following two directions leading to isotropic and anisotropic structures.
Synthetic images
Angles 0–80° 0–69° 0–52° 0–40° 0–28° 0–17°
DA 1.3 1.3 1.8 1.9 2.5 3.8
Table 2 Root Mean Square Standard Deviation Coefficient Variation RMSCV(%) for measured indices DLI and DTI and the degree of anisotropy.
Intra-observer reproducibility Inter-observer reproducibility
CV(%) CV(%)
Measured parameter
DLI 2.4 3.4
DTI 2.4 4.1
Calculated parameter
DA 1.5 3.1
DLI: Dispersion Longitudinal Index
DTI: Dispersion Transversal Index
DA: Degree of Anisotropy
Table 3 Fabric indices (mean ± SD) from the fabric parameters in osteoporotic fracture cases and control cases.
Osteoporotic fractures Controls Statistical significance p
DLI 55.6 ± 6.2 59.1 ± 6.6 0.04
DTI 41.3 ± 5.9 46.8 ± 6.7 0.002
DA 1.87 ± 0.15 1.72 ± 0.18 0.001
==== Refs
Sugita H Oka M Toguchida J Nakamura T Ueo T Hayami T Anisotropy of osteoporotic cancellous bone Bone 1999 24 513 16 10321912 10.1016/S8756-3282(99)00021-6
Frost HM The mechanostat: a proposal pathogenic mechanism of osteoporosis and the bone mass effects of mechanical and nonmechanical agents Bone Miner 1987 2 73 85 3333019
Aspden RM Hukins DWL Determination of the direction of preferrred orientation and the orientation distribution function of collagen fibrils in connective tissues from high X-ray diffraction patterns J of Applied Crystallography 1979 12 306 311 10.1107/S0021889879012516
Kirky MC Aspden RM Hukins DWL Determination of the orientation distribution function for collagen fibrils in a connective tissu site from a high angle X-ray diffraction pattern J of Applied Crystallography 1988 21 929 934 10.1107/S0021889888008040
Wilkinson S Hukins DWL Automatic determination of diffuse-peak positions and the centre of a diffraction pattern J of Applied Crystallography 1999 32 332 335 10.1107/S0021889898016161
Jaschouz D Paris O Roschger P Hwang HS Fratzl P Pole figure analysis of mineral nanoparticle orientation in individual trabecula of human vertebral bone J of Applied Crystallography 2003 36 494 498 10.1107/S0021889803000566
Redon C Chermant L Chermant J Coster M Assessment of fibre orientation in reinforced concrete using Fourier image transform J Microsc 1998 191 258 265 9767490 10.1046/j.1365-2818.1998.00393.x
Defossez H Hall RM Walker PG Wroblewski BM Siney PD Purbach B Determination of the trabecular bone direction from digitised radiographs Med Eng Phys 2003 25 719 29 14519344 10.1016/S1350-4533(03)00123-1
Singh M Nagrath AR Maini PS Changes in trabecular pattern of the upper end of the femur as an index of osteoporosis J Bone Joint Surg Am 1970 52 457 67 5425640
Aggarwal ND Singh GD Aggarwal R Kaur RP Thapar SP A survey of osteoporosis using the calcaneum as an index Int Orthop 1986 10 147 53 3744635 10.1007/BF00267758
Whitehouse WJ The quantitative morphology of anisotropic trabecular bone J Microscopy 1974 101 153 68
Geraets WG Comparison of two methods for measuring orientation Bone 1998 23 383 8 9763152 10.1016/S8756-3282(98)00117-3
Harrigan TP Mann RW Characterization of microstructural anisotropy in orthotropic materials using a second rank tensor J Mater Sci 1984 19 761 67 10.1007/BF00540446
Goulet RW Goldstein SA Ciarelli MJ Kuhn JL Brown MB Feldkamp LA The relationship between the structural and orthogonal compressive properties of trabecular bone J Biomechanics 1994 27 375 89 10.1016/0021-9290(94)90014-0
Rüegsegger P Koller B Müller R A microtomographic system for the nondestructive evaluation of bone architecture Calcif Tissue Int 58 24 29 8825235
Fajardo RJ Muller R Three-dimensional analysis of nonhuman primate trabecular architecture using micro-computed tomography Am J Phys Anthropology 2001 115 327 36 10.1002/ajpa.1089
Majumdar S Kothari M Augat P Newitt DC Lin JC Lang T Lu Y Genant HK High-resolution magnetic resonance imaging: three-dimensional bone architecture and biomechanical properties Bone 1998 22 445 54 9600777 10.1016/S8756-3282(98)00030-1
Luo G Kinney JH Kaufman JJ Haupt D Chiabrera A Siffert RS Relationship between plain radiographic patterns and three-dimensional trabecular architecture in the human calcaneus Osteoporosis Int 1999 9 339 45 10.1007/s001980050156
Caldwell CB Willett K Cuncins AV Hearn TC Characterization of vertebral strength using digital radiographic analysis of bone structure Med Phys 1995 22 611 15 7643801 10.1118/1.597548
Geraets WG Van der Stelt PF Lips P Elders PJM Van Ginkel FC Burger EH Orientation of the trabecular pattern of the distal radius around the menopause J Biomechanics 1997 30 363 70 10.1016/S0021-9290(96)00154-6
Jiang C Giger ML Chinander MR Martell JM Kwak S Favus MJ Characterization of bone quality using computer-extracted radiographic features Med Phys 1999 26 872 9 10436887 10.1118/1.598604
Oxnard CE Bone and bones, architecture and stress, fossils and osteoporosis J Biomechanics 1993 26 63 79 10.1016/0021-9290(93)90080-X
Buck AM Price RI Sweetman IM Oxnard CE An investigation of thoracic and lumbar cancellous vertebral architecture using power-spectral analysis of plain radiographs J Anat 2002 200 445 56 12090391 10.1046/j.1469-7580.2002.00051.x
Wigderowitz CA Abel EW Rowley DI Evaluation of cancellous structure in the distal radius using spectral analysis Clin Orthop Related Res 1997 335 152 61 10.1097/00003086-199702000-00014
Caligiuri P Giger ML Favus MJ Hong J Doi K Dixon LB Computerized radiographic analysis of osteoporosis : preliminary evaluation Radiology 1993 186 471 474 8421753
Gregory JS Stewart A Undrill PE Reid DM Aspden RM Identification of hip fracture patients from radiographs using Fourier analysis of the trabecular structure: a cross-sectional study BMC Med Imaging 2004 4 4 15469614 10.1186/1471-2342-4-4
Benhamou CL Lespessailles E Jacquet G Harba R Jennane R Loussot T Tourliere D Ohley W Fractal organization of trabecular bone images on calcaneus radiographs J Bone Miner Res 1994 9 1909 18 7872056
Benhamou CL Poupon S Lespessailles E Loiseau S Jennane R Siroux V Ohley W Pothuaud L Fractal analysis of radiographic trabecular bone texture and bone mineral density: two complementary parameters related to osteoporotic fractures J Bone Miner Res 2001 6 697 704
Pothuaud L Lespessailles E Harba R Jennane R Royant V Eynard E Benhamou CL Fractal analysis of trabecular bone texture on radiographs: discriminant value in postmenopausal osteoporosis Osteoporosis Int 1998 8 618 25 10.1007/s001980050108
Jiang C Pitt RE Bertram JEA Aneshansley DJ Fractal-based image texture analysis of trabecular bone architecture Med Bio Engineer Computing 1999 37 413 18
Lespessailles E Jacquet G Harba R Jennane R Loussot T Viala JF Benhamou CL Anisotropy measurement obtained by fractal analysis of trabecular bone at the calcaneus and radius Rev Rhum [Eng Ed] 1996 63 337 43
Lin JC Amling M Newitt DC Selby K Srivastav SK Delling G Genant HK Majumdar S Heterogeneity of trabecular bone structure in the calcaneus using magnetic resonance imaging Osteoporosis Int 1998 8 16 24 10.1007/s001980050043
Geraets WGM Van der Stelt PF Netelenbos CJ Elders PJM A new method for automatic recognition of the radiographic trabecular pattern J Bone Miner Res 1990 5 227 33 2333781
Glüer C Blake G Lu Y Blunt BA Jergas M Genant HK Accurate assessment of precision errors: how to measure the reproducibility of bone densitometry techniques Osteoporosis Int 1995 5 262 70 10.1007/BF01774016
Rosner B Willett WC Spiegelman D Correction of logistic regression relative risk estimates and confidence intervals for systematic within-person measurement error Stat Med 1989 8 1051 69 2799131
Pothuaud L Benhamou CL Porion P Lespessailles E Harba R Levitz P Fractal dimension of trabecular bone projection texture is related to three-dimensional microarchitecture J Bone Miner Res 2000 15 691 99 10780861
Genant HK Engelke K Fuerst T Gluer CC Grampp S Harris ST Jergas M Lang T Lu Y Majumdar S Mathur A Takada M Noninvasive assessment of bone mineral and structure: state of the art J Bone Miner Res 1996 11 707 30 8725168
Newitt DC Majumdar S Van Rietbergen B Von Ingersleben G Harris ST Genant HK Chesnut C Garnero P Mc Donald B In vivo assessment of architecture and micro-finite element analysis derived indices of mechanical properties of trabecular bone in the radius Osteoporosis Int 2002 131 6 17
Odgaard A Jensen EB Gundersen JG Estimation of structural anisotropy based on volume orientation. A new concept J Microscopy 1990 157 149 62
Cruz-Orive LM Karlsson LM Larsen SE Wainschtein F Characterizing anisotropy : a new concept Micron and Microscopica Acta 1992 23 75 76 10.1016/0739-6260(92)90076-P
Jhamaria NL Lal KB Udawat M Banerji P Kabra SG The trabecular pattern of the calcaneum as an index of osteoporosis J of Bone and Joint Surgery 1983 65 195 98
Mosekilde L Viidik A Mosekilde L Correlation between the compressive strength of iliac and vertebral trabecular bone in normal individuals Bone 1985 6 291 95 4096861 10.1016/8756-3282(85)90317-5
Ciarelli TE Fyrie DP Schaffler MB Goldstein SA Variations in three-dimensional cancellous bone architecture of the proximal femur in female hip fractures and in controls J Bone Miner Res 2000 15 32 40 10646112
Geraets WG Van der Stelt PF Lips P Van Ginkel FC The radiographic trabecular pattern of hips in patients with hip fractures and in elderly control subjects Bone 1998 22 165 73 9477240 10.1016/S8756-3282(97)00233-0
Zhao J Jiang Y Recker RR Draper mW Genant HKI liac three-dimensional trabecular microarchitecture in premenopausal healthy women and postmenopausal osteoporotic women with and without fracture J Bone Miner Res 2001 17 S468
Laugier P Fournier B Berger G Ultrasound parametric imaging of the calcaneus: in vivo results with a new device Calcif Tissue Int 1996 58 326 31 8661966 10.1007/s002239900053
| 15927072 | PMC1173107 | CC BY | 2021-01-04 16:03:35 | no | BMC Med Imaging. 2005 May 31; 5:4 | utf-8 | BMC Med Imaging | 2,005 | 10.1186/1471-2342-5-4 | oa_comm |
==== Front
BMC MicrobiolBMC Microbiology1471-2180BioMed Central London 1471-2180-5-271590449610.1186/1471-2180-5-27Research ArticleHinT proteins and their putative interaction partners in Mollicutes and Chlamydiaceae Hopfe Miriam [email protected] Johannes H [email protected] Birgit [email protected] Institute of Medical Microbiology, Moorenstrasse 5, 40225 Duesseldorf, Germany2 Chair of Functional Genome Research of Microorganisms, University Street 1, Heinrich-Heine-University, 40225 Duesseldorf, Germany3 Center of Biological and Clinic Research, University Street 1, Heinrich-Heine-University, 40225 Duesseldorf, Germany2005 18 5 2005 5 27 27 24 11 2004 18 5 2005 Copyright © 2005 Hopfe et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
HinT proteins are found in prokaryotes and eukaryotes and belong to the superfamily of HIT proteins, which are characterized by an histidine-triad sequence motif. While the eukaryotic variants hydrolyze AMP derivates and modulate transcription, the function of prokaryotic HinT proteins is less clearly defined. In Mycoplasma hominis, HinT is concomitantly expressed with the proteins P60 and P80, two domains of a surface exposed membrane complex, and in addition interacts with the P80 moiety.
Results
An cluster of hitABL genes, similar to that of M. hominis was found in M. pulmonis, M. mycoides subspecies mycoides SC, M. mobile and Mesoplasma florum. RT-PCR analyses provided evidence that the P80, P60 and HinT homologues of M. pulmonis were polycistronically organized, suggesting a genetic and physical interaction between the proteins encoded by these genes in these species. While the hit loci of M. pneumoniae and M. genitalium encoded, in addition to HinT, a protein with several transmembrane segments, the hit locus of Ureaplasma parvum encoded a pore-forming protein, UU270, a P60 homologue, UU271, HinT, UU272, and a membrane protein of unknown function, UU273. Although a full-length mRNA spanning the four genes was not detected, amplification of all intergenic regions from the center of UU270 to the end of UU273 by RT-PCR may be indicative of a common, but unstable mRNA.
In Chlamydiaceae the hit gene is flanked upstream by a gene predicted to encode a metal dependent hydrolase and downstream by a gene putatively encoding a protein with ARM-repeats, which are known to be involved in protein-protein interactions. In RT-PCR analyses of C. pneumoniae, regions comprising only two genes, Cp265/Cp266 and Cp266/Cp267 were able to be amplified. In contrast to this in vivo interaction analysis using the yeast two-hybrid system and in vitro immune co-precipitation revealed an interaction between Cp267, which contains the ARM repeats, Cp265, the predicted hydrolase, and Cp266, the HinT protein.
Conclusion
In the Mollicutes HinT proteins were shown to be linked with membrane proteins while in the Chlamydiaceae they were genetically and physically associated with cytoplasmic proteins, one of which is predicted to be a metal-dependent phosphoesterase. Future work will elucidate whether these differing associations indicate that HinT proteins have evolved independently or are indeed two hotspots of a common sphere of action of bacterial HinT proteins.
==== Body
Background
The detection of an unusual, highly conserved sequence motif "His-phi-His-phi-His-phi-phi" (phi representing hydrophobic amino acids) in a variety of organisms of all kingdoms led to the definition of a new family of proteins named HIT (histidine triad) [1]. This family has three main branches: the fragile histidine triad (FHit)-related proteins found in animals and fungi, which act as di-adenosine polyphosphate hydrolases and function as tumor suppressors in humans and mice [2] (although the tumor suppressing function is not dependent on ApppA hydrolysis [3]), the GalT (galactose 1 phosphate uridylytransferase) homologues, which have a modified "His-phi-His-phi-Gln" motif, which transfers nucleoside monophosphates to phosphorylated secondary substrates rather than hydrolyzing them [4], and the Histidine-triad nucleotide binding (HinT) homologues, which in eukaryotes are intracellular receptors and hydrolases of purine mononucleotides [5]. Although HinT homologues are found in all kingdoms and this family is the most ancient and widespread branch of the HIT proteins, the cellular function, the substrates and the interaction partners of HinT proteins are largely unknown. In prokaryotes, knowledge of HinT proteins is generally restricted to sequence analyses. In the cell wall-less prokaryote Mycoplasma hominis, the cytoplasmic HinT protein interacts with a surface localized membrane complex by binding to the P80 moiety. Interestingly, the genes encoding P80 and P60, the domains of the membrane complex, form an operon with the HinT gene [6]. The identification of a homologous hit locus in M. pulmonis and access to several sequenced prokaryotic genomes enabled us, in this study, to hypothetically identify interaction partners and thus propose a functional role for HinT in bacteria with small genomes.
Results
To find out more about the function of prokaryotic HinT proteins we first analyzed the hit loci of bacteria with a restricted genome, with the view that they might represent a model for organisms possessing the minimal genetic make-up essential for life as a free-living organism. As polycistronically organized genes often encode proteins that are functionally related (e.g. in a protein-complex formation or as part of a common pathway) we ran a search of known genome sequences for genes closely neighbouring or overlapping the hit gene. Species from the Mollicutes and the Chlamydiaceae fulfill these requirements and were thus analyzed.
Mollicutes are phenotypically distinguished from other bacteria by their minute size and total lack of a cell wall. They have evolved as a branch of gram-positive bacteria by a process of reductive evolution. The significant genome "condensation" (for example the genome of M. genitalium is only 580 kbp) was made possible by adopting a parasitic behavior. The primary habitats of human and animal mycoplasmas are the mucous surfaces which they colonize during infection [7]. While the intracellular localization of Mollicutes in insect tissues is well established, cell entry of human or animal mycoplasmas seems to be rare and possibly mediated by a site-directed, receptor-mediated event found in chlamydia [8]. However, Chlamydiaceae have a number of features in common with mycoplasmas: their small genomes predict a limited metabolic capability, their major target tissue are mucous membranes and they also cause ocular and sexually transmitted diseases. In contrast, the chlamydia are obligate-intracellular bacteria that undergo a unique developmental cycle in which is an alteration in size between the small metabolically inactive infectious elementar body and the relatively large, metabolically active reticular body which is adapted for intracellular growth [9]. Bearing in mind, that in M. hominis the HinT-interacting protein is a secreted antigen and thus predicted to play a role in the pathogenicity of mycoplasmas we expand this analysis to include a family of obligate-intracellular organisms known to secrete antigens in the inclusion body in the infected cell.
Organization of the hit-locus in Mollicutes
Hit loci with a genomic organization comparable to that of M. hominis [6], with the hitAB genes encoding two membrane proteins and hitL encoding the cytoplasmic HinT, were detected in nearly half of the mollicute genomes analyzed (Figure 1A). The highest similarity was found with the hit locus of M. pulmonis. The MYPU_0080 encoded protein had 44.3 % identity to the M. hominis HinT protein, and the predicted MYPU_0060 and MYPU_0070 proteins were 23.8 % and 26.6 % identical to the membrane proteins P80 and P60 of M. hominis, which were encoded by hitAB. MYPU_0060 had structural features similar to those of P80, with an amino-terminal signal sequence with a predicted signal peptidase I (SPase I) cleavage site and a predominantly alpha-helical structure [10]. MYPU_0070 began with an amino-terminal signal sequence of transmembrane helix (from AA 5 to AA 20) and a signal peptidase II recognition site with a lipoprotein attachment site at position 27. Thus, MYPU_0070 of M. pulmonis appears to encode a P60 homologue, a cysteine-anchored lipoprotein. The order of genes within the hit loci of M. mycoides subsp. mycoides SC (MSC), Mesoplasma florum (MF) and M. mobile (MMOB) was similar with two genes predicted to encode membrane proteins and a downstream hitL gene. The similarities between the predicted sequences of MSC_0500, MF_235 and MMOB_910, and P80 of M. hominis were quite low and the proteins would be significantly larger than P80. While MMOB_910 contained a signal peptidase I recognition site, like P80, MSC_0500 and MF_235 were pro-lipoproteins with an amino-terminal SPase II recognition sequence. Only MSC_500 was predicted to have a predominantly alpha-helical structure, MF_235 being predicted to have a secondary structure of alternate alpha helical and beta sheet regions and MMOB_910 to consist mainly of beta sheets (data not shown). The proteins encoded by the gene next to hitL had little similarity with P60 of M. hominis when the whole sequence was compared. However, when the P60 protein region from AA 164 to AA 177 (CS1; ELQKMLLAKLYLLK) was used, identities of 43 % (MMOB_900) to 57% (MYPU_0070) were detected and scrutiny of the sequence from AA 226 to AA 234 (CS2; LYLMKYLVE) revealed 60 % (MYPU_0070) to 70 % identity (MMOB_900). The corresponding proteins of Mesoplasma florum and M. mycoides subsp. mycoides SC did not contain these conserved sequences. The different HinT homologues had the highest identity with the HinT protein of M. hominis, ranging from 44.3 % (MF_233) to 55.7 % (MMOB_890).
Hit loci with a different genomic organization were identified in the mollicutes Ureaplasma parvum,M. pneumoniae and M. genitalium (Figure 1B). While UU271 of U. parvum, the gene immediately upstream of hitL encoded a putative P60 homologue possessing the P60 consensus sequences CS1 (35.7 % identity) and CS2 (30% identity), it differed from all other P60 homologues in possessing a SPase I recognition sequence and two other transmembrane helices (AA 355 to AA 375 and AA 407 to AA 427). The UU273 gene, immediately downstream of hitL, encoded a protein with two transmembrane spanning helices, but with no significant similarity to other known proteins. The deduced protein sequence of UU270 did not have any sequence similarity with P80. With six transmembrane segments, it appeared more likely to form a pore than to be surface exposed. The organization of the hit locus of U. parvum appeared intermediate between the hit loci described above and those of M. pneumoniae and M. genitalium. The sequence identity between the ureaplasma HinT and the HinT proteins of M. pneumoniae (42.7 %) and M. genitalium (47.4 %) was higher than that between HinT of U. parvum and M. hominis (39.2 %), and the genes immediately upstream of hitL encoded proteins with seven (MPN_274) or five (MG_133) transmembrane domains (Figure 1B). MPN_274 is predicted to encode a permease of an ABC transporter [11] suggesting a comparable function in M. genitalium and probably also in U. parvum. Thus, these hit loci of Mollicutes analyzed appear to have a hitL gene flanked by genes that are predicted to encode membrane-anchored proteins.
As in M. gallisepticum, the hitL gene is not flanked by other genes on the same strand, also exceptions of a polycistronic organization of the hitL gene seem to exist within the Mollicutes.
Organization of the hit loci in Chlamydiaceae
In the obligately intra cellular Chlamydiaceae the order of genes within the hit loci and the function of the encoded proteins appeared to be highly conserved, but distinctly different from that of the Mollicutes (Figure 1C). In all chlamydial species analyzed, the gene upstream of hitL encoded a putative cytoplasmic protein with the signature sequence of a metal-dependent protein hydrolase and a large number of metal binding residues (IPR003226/UPF0160), probably indicative of a phosphoesterase function, and an oligonucleotide/oligosaccharide-binding OB fold (IPR008994). The deduced protein sequence of the gene located downstream of hitL contained a 37–47 AA long tandemly repeated ARM repeat fold (IPR008938), which forms a right-handed superhelix and has been implicated in the mediation of protein-protein interactions [12]. Cp267 contained an RGD motif, which plays a role in cell adhesion [13]. However, the presence of RGD in a sequence alone is not sufficient to suggest a biological function for this motif [14]. The presence of two transmembrane helices (AA 314 to AA 334 and AA 428 to AA 448) suggested that it is more likely that Cp267 may interact with the bacterial cell membrane. In all other chlamydial species analyzed, the Cp267 homologues did not contain domains suggestive of membrane attachment.
Are the hit loci genes co-expressed?
In bacteria, overlapping genes on the same coding strand may indicate the polycistronic organization of these genes, and co-expressed proteins are often related in function.
As the hit locus of M. hominis is an operon containing three genes [6] the next step was to analyze whether the polycistronic organization of hit genes was conserved within the Mollicutes and whether this also occurred in Chlamydiaceae. Initially, we chose M. pulmonis, the species with the greatest similarity to M. hominis, for reverse transcription (RT) PCR analysis. To identify the likely boundaries of an mRNA containing MYPU_0060, MYPU_0070 and MYPU_0080, two different primers upstream of the MYPU_0060/hitA gene and three primers downstream of the hitL gene were used (Fig. 2A). Amplification occurred with primers binding just upstream of the predicted promoter regions 1 or 2 and just downstream of the TAA stop codon of the hitL gene (Fig. 2B, lanes A and B) indicating a polycistronic mRNA. Amplification was not seen with a primer hybridizing to the sequence downstream of a predicted hairpin loop structure after the TAA stop codon of hitL (Figure 2B, lanes C1 and C2) suggesting that the mRNA terminates at the predicted hairpin structure.
Next, we examined the genes flanking hitL in U. parvum. Amplicons which spanned the intergenic regions were obtained with primers hybridizing to the center of UU270 and to the 3'-end of UU272 (Fig. 3C), and with primers hybridizing to the 5'-end of UU271 and to the 3'-end of UU273 (Fig. 3D). No amplification occurred with a primer hybridizing to the 5'-end of UU270 and the 3'-end of hitL (Fig. 3A and 3B). These data suggest that HinT is expressed with the flanking genes UU271 and UU273. These findings are in accordance with the predicted termination of transcription by a hairpin loop with a stem energy of -9.1 kcal mole-1 located 33 nt downstream of the UU273 gene [15]. Of the organisms analyzed so far U. parvum was the most demanding organism of the Mollicutes in terms of DNA-free, full-length total RNA preparation. Thus the detection of a common RNA from the center of UU270 up to UU273 (Fig. 3D) may be due to an unstable RNA or indicatory for UU270 not taking part in the operon structure.
To characterize the organization of hit loci genes within the Chlamydiaceae we analyzed the locus in Chlamydophila pneumoniae. The genes Cp266 (encoding HinT), Cp267 and Cp268, which is predicted to encode a solute symporter family protein [16], were predicted to comprise an operon. No amplification occurred when a primer pair that hybridized upstream of Cp265 and downstream of Cp267 was used (data not shown). Amplification was detected using primers binding within each gene (Figure 4A,B,C) and with primers binding within Cp265 and Cp266 (Fig. 4D) and within Cp266 and Cp267 (Fig. 4E). The predicted co-expression of Cp267 and Cp268 downstream of which several putative transcription terminators were detected, was not supported by RT-PCR analysis (Fig. 4F), with amplification being obtained when using genomic DNA as a template but not with cDNA.
Interactions between the proteins encoded by the hit locus of C. pneumoniae
As the stability of an RNA is increased in regions with pronounced secondary structures, such as transcriptional terminators, and is often decreased in regions lacking such protective structures [17], partial degradation of the chlamydial mRNA may have occurred. The results from RT-PCR analysis of the mRNA of CP265, Cp266 and Cp267 suggest an operon producing a transient mRNA thus suggesting a physical interaction between the products of these genes. Therefore we analyzed the interactions between Cp265, Cp266 and Cp267 using the yeast two-hybrid system [18]. The system is based on the modular organization of the transcription factor GAL4, which has a DNA-binding domain (DB) and an activation domain (AD). When GAL4 binds (via DB) to its cognate binding site, the activation domain AD is brought close to the promoter and activates transcription of the reporter genes lacZ and HIS3. In the yeast two-hybrid system these two domains, which alone are not able to activate transcription, are separately cloned into pGADT7 (AD) and pGBKT7 (BD) and expressed in fusion with the proteins under investigation. Growth of a histidine dependent yeast strain on histidine deficient media will only occur after transformation with both plasmids if the AD and DB domains are apposed by an interaction between the fusion proteins, which will result in transcription of the reporter genes. The plasmids pGADT7-T and pGBKT7-53, which encode the SV40 large T-antigen and the murine p53 protein, respectively served as a positive control (Fig. 5 K+; Fig. 6A).
HinT is known to dimerize [19,20]. We introduced the coding region of M. hominis HinT into both pGADT7 and pGBKT7 and transformed the histidine dependent yeast strain AH109 with them. Quantification of transcriptional activation of the reporter gene was achieved using a liquid β-galactosidase assay measuring the hydrolysis of 4-methylumbelliferyl-β, D-galactopyranoside (MUG), yielding the fluorescent molecule 4-methylumbelliferone (4 MU). As expected, dimerization of the fused HinT peptides led to apposition of the AD and DB domains generating a functional transcription factor. The transcription of the reporter genes resulted in growth of the yeast on histidine-deficient agar plates (Fig. 5, top row, left plate) and production of β-galactosidase (Fig. 6C). Next we analyzed whether the proteins encoded by the hit locus of C. pneumoniae interacted. The coding regions of Cp265, Cp266 and Cp267 were introduced into pGADT7 and pGBKT7 and expressed in yeast in all possible combinations. As shown in Figure 5, large colonies, comparable in size to those of the positive control, were produced by yeast that expressed Cp265 fused to both the binding and the activation domain. This suggested a strong interaction between the molecules of the Cp265 protein. All other combinations of plasmids encoding Cp265, Cp266 and Cp267 only led to the growth of small colonies, a finding that was difficult to interpret. To differentiate between strong and weak interactions, the β-galactosidase assay was used. As shown in Fig. 6, the measurement of β-galactoside activity indicated an interaction between Cp267 and Cp265, Cp266 and Cp267 itself, independent of the fusion partner (the AD or DB domains of the GAL4 protein). Surprisingly, dimerization of Cp266 (HinT) was not detected, although Cp265 interacted strongly with itself. Cp267 did not activate transcription by itself (Fig. 6A. 267/BD and 267/AD) nor did it interact with the unrelated protein SV40 large T antigen (T/267) or murine tumor suppressor p53 (267/p53) to activate transcription, as in all these cases the β-galactosidase activity was at background levels (Fig. 6A).
Immune co-precipitation of Cp265, Cp266 and Cp267
To confirm the findings derived from the two-hybrid analyses we performed protein-binding assays in vitro. Protein C-tagged Cp265, Cp266 and Cp267 were expressed in E. coli and purified by affinity chromatography (Fig. 7A). Each protein was then incubated with equal amounts of [35S]-labeled Cp265, Cp266 or Cp267 in vitro and precipitated with anti-Protein C antibodies. As shown in Fig. 7B, the supernatants of the different samples contained comparable amounts of the respective isotope labeled proteins. As expected the [35S] labeled Cp proteins alone were neither precipitated by unrelated membrane proteins, such as Protein C-tagged OppA of M. hominis nor by the anti-Protein C-sepharose itself (Fig. 7C). In contrast, an interaction of Cp266 with Cp267 was suggested by co-precipitation of significant amounts of Cp266 [35S] with Cp267C, and Cp267 [35S] with Cp266C (Fig. 7C). The other findings from the two-hybrid analyses were also confirmed as both Cp265 and Cp267 were found to dimerize and there was no interaction between Cp265 and Cp266. Interestingly dimerization of Cp266 (HinT) which was not detected by the two-hybrid system, was demonstrated in this co-precipitation assay.
Thus, we can conclude that the chlamydial proteins Cp265, Cp266 (HinT) and Cp267 have a tendency to dimerize and Cp267 interacts with both Cp265 and Cp266.
Discussion
A remarkable feature of HinT proteins is their ubiquity. They are found in all kingdoms ranging from Mycoplasma genitalium, the smallest prokaryote, to one of the most complex eukaryotes, the human [1,19]. However the function of this homo-dimer in the cytoplasm of these different organisms has only been closely examined in eukaryotes, where it has been characterized as an intracellular receptor for purine ribonucleotides [4,5], especially for hydrolases of 5'-monophosphoramide substrates such as AMP-lysine [21], with the histidine triad motif forming the α-phosphate binding site [20]. HinT has been shown to associate with the protein microphthalmia, an important transcription factor that controls growth and function in mast cells and melanocytes [22], to interact with the human cyclin-dependent kinase 7 (Cdk7), a subunit of the RNA polymerase II C-terminal domain kinase Cdk7/Kin28 [23], and to act as a positive regulator of the yeast Cdk7 homologue Kin28 [21]. That it may not be the key regulator of Cdk7 activity was recently suggested by analysis of HinT-/- knock-out mice [24]. This led to the hypothesis that eukaryotic HinT homologues are involved in the regulation of transcriptional processes by hydrolyzing related adenylyl-modified proteins [25].
The observation that HinT homologues are ubiquitous and that they are even encoded by the smallest bacterial genomes, suggests that HinT was present at the cellular root of the tree of life and that its preservation is advantageous for the survival of cells [20]. However the function of bacterial HinT homologues seems to be quite different from those of eukaryotes. In M. hominis HinT had been demonstrated to interact both physically and genetically with a surface-localized membrane complex by binding to the P80 domain [6]. The data presented here suggest that the co-expression of HinT with membrane proteins is prevalent within the Mollicutes. Comparable organization of the hit-loci was found in Mycoplasma hominis, M. pulmonis, M. mycoides subsp. mycoides SC, M. mobile and Mesoplasma florum. Analysis of further genomes will most likely lengthen this list. A genomic DNA fragment of M. bovis encoding the amino-terminal end of a P80 homologue has been sequenced and this homologue is predicted to possess an SPase I cleavage site. In M. hyorhinis, a nearly complete hit locus, encoding P80, P60 and HinT homologues has been found adjacent to a genomic region encoding the high affinity transport system (personal communication of Michael Calcutt, Columbia, MO, USA) [26]. The organization of the hitABL genes in an operon, as recently demonstrated for M. hominis [6] and shown here for M. pulmonis, suggests polycistronic expression of the hit loci genes. However, it remains to be elucidated whether the encoded proteins have comparable functions to those already shown in M. hominis. P80 of M. hominis was recently shown to reside in the membrane as a precursor protein and to be secreted into the extra cellular milieu as a 10 kDa smaller antigen. Processing of P80 was suggested to be initiated by SPase I cleavage [27]. While the P80 homologues in M. mobile and M. bovis also contained signal sequences for SPase I cleavage, those in M. mycoides subsp. mycoides SC and Mesoplasma florum were putative pro-lipoproteins. Secretion of lipoproteins has been observed in M. hominis [6] and other bacteria [28], indicating that similar function may be still possible.
M. pneumoniae and M. genitalium each had only one gene adjacent to hitL encoding a pore-forming protein with homologies to ABC permeases, suggesting they are part of a distinct phylogenetic branch. Interestingly, in M. penetrans the gene upstream of hitL also encodes a protein of an ABC transporter, an ATPase [29]. The hit locus of U. parvum, which contained a P60 homologue and a gene encoding a permease, may have functions that are a hybrid of those of M. hominis and the M. pneumoniae groups. RT-PCR analyses infer the presence of a mRNA encoding HinT and UU271, a P60-homologue, and a membrane protein of unknown function. Thus, the interaction of HinT with membrane proteins seems to be a common phenomenon in Mollicutes.
A quite different situation was detected in the Chlamydiaceae. Although we were not able to establish definitely the presence of a polycistronic mRNA derived from the three genes comprising hit locus, the overlap of the hitL gene with the upstream gene, as well as the conserved order of the three genes within the hit loci of Chlamydiaceae, suggested a relationship between the gene products. Analysis of Cp265, Cp266 (HinT) and Cp267 in the yeast two-hybrid system and immune co-precipitation assays confirmed our hypothesis that these proteins interacted and demonstrated that they form homo-dimers. Cp267, a protein with large areas of ARM repeats, which are known to mediate protein-protein interactions [30], was shown to interact with HinT, a protein known in eukaryotes to influence transcriptional activation, as well as with Cp265, a putative metal-dependent hydrolase with a binding fold for short, single stranded nucleic acids. These findings suggest that in Chlamydiaceae, the function of HinT may be more closely related to intracellular processes than to interactions with the extracellular milieu, as suggested by the findings on Mollicutes.
Conclusion
The data presented here demonstrate that HinT proteins of the Chlamydiaceae associate with probable cytosolic proteins likely to function in the regulation of cellular processes, such as nucleotide metabolism. This function would be similar to that of homologues in eukaryotes, where HinT has been shown to influence transcription. The finding that HinT proteins of the Mollicutes interact both physically and genetically with membrane proteins may reflect a phylogenic shift towards a different function in this group, or may indicate an additional function of bacterial HinT proteins. Our future work will focus on decoding the intra- and extra-cellular processes that bacterial HinT proteins are involved in.
Methods
DNA manipulations
All routine DNA manipulation techniques, including plasmid preparation, restriction endonuclease analysis, ligation and transformation of E. coli were performed as described by Sambrook et al. [31] or according to the manufacturers' recommendations (Qiagen, Hilden, Germany, and Roche Applied Science, Mannheim, Germany).
Bacterial strains and plasmids
The plasmids pXB (Roche Applied Science, Mannheim, Germany), pGADT7 and pGBKT7 (BD Bioscience Clontech, Palo Alto, USA) were used as expression vectors for the heterologous expression of Cp265, Cp266 and Cp267. The pXB plasmids were propagated in Escherichia coli DH5α F'(Life Technologies), pGADT7 and pGBKT7 in yeast AH109 cells (BD Biosciences Clontech, Palo Alto, CA USA).
Sequence analysis
Analysis of the DNA and protein sequences and the design of oligonucleotides were facilitated by the Lasergene software (DNA Star Inc., Madison Wisc.).
The genomes listed in table 1 were analyzed using the web site of NCBI .
Computer-based prediction of transcription termination was performed using the GeneBee service (online ). Distant relation-ships between HinT protein sequences of the analyzed Mollicutes were determined by using the BLAST method through Molligen 1.4 [32]. Conserved domains of proteins were predicted using the Conserved Domain Database (CDD) or the InterPro service (, ).
RT-PCR
RNA was prepared from exponential phase cultures of M. pulmonis and U. parvum as described by Chomczynski and Sacchi [33]. Chlamydophila pneumoniae respiratory isolate GiD was used for all experiments [34]. Chlamydial RNA was prepared from HEp-2 cells 2 days post-infection as described by Mölleken et al. (Mölleken et al., manuscript in preparartion). Before use as a template for RT-PCR, contaminating traces of DNA were digested with DNase I as described previously [35]. Overlapping regions of the Ureaplasma and Chlamydophila genes were amplified using the Expand Template PCR system (Roche Applied Science, Mannheim, Germany) by standard PCR conditions (initial cycle of 5 min at 95°C; 35 cycles of 1 min at 95°C, 1 min at 50°C (U. parvum) or 58°C (C. pneumoniae), 2.5 min at 68°C). The hit operon of M. pulmonis was amplified using the Expand Long Template PCR system by standard PCR conditions (initial cycle of 5 min at 95°C; 10 cycles of 1 min at 95°C, 1 min at 44°C, 4 min at 68°C; addition of 0.5 U polymerase; then 20 cycles of 1 min at 95°C, 30 sec at 44°C, 4 min (+ 20 sec per cycle) at 68 °C). Southern blot analysis was performed as described previously [6].
Construction of plasmids
The regions encoding Cp265, Cp266 and Cp267 in C. pneumoniae GiD [34] were amplified by PCR with the primers Cp1 to Cp6 (Table 2). The amplicons were cut at the primer-introduced restriction endonuclease cleavage sites for BamHI and SacI, and ligated in-frame into the expression vector pGADT7. The EcoRI/SacI inserts in the pGADT7 constructs were then ligated in-frame into EcoRI/PstI-digested pGBKT7.
For heterologous expression of the protein-C tagged proteins, CP265C, Cp266C and Cp267C, in E. coli, the Cp inserts of the respective pGADT7 plasmids were digested with SacI, the ends bluntened by incubation with 3 units S1 nuclease (Amersham Bioscience, Freiburg, Germany) for 30 min at 37°C and subsequently cut with EcoRI. The blunt-end/EcoRI digested Cp265, Cp266 and Cp267 fragments were cloned in-frame into the blunt-end/EcoRI digested plasmid pXB and propagated in E. coli Dh5α F'.
All plasmid constructs were confirmed by DNA sequencing (ABI 373 A machine) [36].
Expression and purification of Cp265C, Cp266C and Cp267C
One liter of LB broth (Gibco BRL, Life Technologies Inc., Gaithersburg, USA) containing ampicillin (100 μg/ml) was inoculated with the respective E. coli DH5α F' clone and incubated for 16 h at 37°C with vigorous shaking. The cells were harvested by centrifugation (15,000 × g, 20 min, 4°C) and frozen at -70°C. After thawing on ice, the cells were resuspended in 40 ml buffer A (120 mM NaCl, 1 mM CaCl2, 20 mM Tris-HCl pH 7.5) and disrupted by three repeated freeze-thaw cycles in liquid nitrogen, followed by three bursts of sonication on ice (5 min bursts at 95 W with a 1 min cooling period between each burst). Insoluble material was sedimented (15,000 × g, 20 min, 4°C) and the supernatant was transferred to an anti-Protein C affinity matrix (Roche Applied Science, Mannheim, Germany). Bound proteins were eluted from the anti-Protein C affinity matrix with 2 mM EDTA.
SDS-PAGE and immunostaining of proteins
Proteins were separated on 12 or 15 % polyacrylamide gels [37], transferred to nitrocellulose (Schleicher and Schüll, Dassel, Germany) using a semi-dry blotting apparatus (Phase, Mölln, Germany) [38], and immunostained using anti-Protein C peroxidase (Roche Applied Science, Mannheim, Germany), anti HA-antibody (pGADT7) or anti c-myc antibody (pGBKT7) (BD Bioscience Clontech, Palo Alto, USA).
Immune co-precipitation assay
The [35S]-labeled Cp265, Cp266 and Cp267 proteins were generated from pGADT7 and pGBKT7 fusion vectors by in vitro translation using a T7 coupled transcription/translation system in the presence of [35S]-methionine (Promega, Madison, USA). Two micrograms of purified Protein C-tagged protein were incubated with 10 μl of the [35S]-labeled protein in buffer B (20 mM Tris/HCl (pH 7.5), 75 mM KCl, 0.1 mM EDTA, 2.5 mM MgCl2, 0.05 (v/v) % Igepal, 2 mM DTT, 10 (v/v) % glycerol and 2 mM CaCl2) for 1 h [39]. Thereafter, a 5 μl aliquot of a slurry of the anti-Protein C matrix, equilibrated in buffer B containing 5 μg BSA, was added to each sample and the mixture further incubated for 1 h. The Protein C-matrix was washed eight times in buffer B, resuspended in 20 μl of SDS-PAGE sample buffer and heated at 95°C for 5 min. The proteins were then analyzed by 15 % SDS-PAGE and autoradiography using a phosphorimager (Fujifilm FLA 3000).
Yeast two-hybrid assays
The MATCHMAKER Gal4 two-hybrid system (BD Bioscience Clontech, Palo Alto, USA) was used for interaction assays. AH109 cells were co-transformed with the Cp265, Cp266 or Cp267 expressing pGADT-T7 and pGBKT7 plasmids, grown in small scale cultures and plated onto histidine deficient agar plates, followed by a β-galactosidase colony lift filter assay. All procedures were carried out as outlined in the BD Bioscience Clontech protocol. The β-galactosidase assay was performed after the inoculation of 7.5 ml YPD Medium with 0.5 ml overnight culture in selective medium and incubation for five hours at 30°C until the culture reached an OD600 of 0.4 to 0.6. The cells were harvested by centrifugation at 14,000 × g for 1 min and re-suspended in 300 μl Buffer Z (Na2HPO4+ 7 × H2O, NaH2PO4 + 4 × H2O, KCl, MgSO4 × 7 H2O, pH7.0). Lysis of the cells was achieved with four cycles of freezing in liquid nitrogen and thawing at 37°C. Soluble and insoluble components were separated by centrifugation at 14000 × g for 2 min. The β-galactosidase activity was measured using a FluorAce™ β-galactosidase Reporter Assay kit (BioRad, Hercules, USA).
Authors' contributions
MH carried out the immunoassays and Yeast TwoHybrid assays. BH carried out the molecular genetic studies. BH and JH participated in the design of the study and drafted the manuscript. All authors have read and approved of the final manuscript.
Acknowledgements
This work was supported by the Deutsche Forschungsgemeinschaft (DFG-HE 2028/3-2). We thank Michael Calcutt (Columbia, MO, USA) for information about the hit loci in M. bovis and M. hyorhinis, Marzena Wyschkon for excellent technical assistance and Colin MacKenzie for critically reading the manuscript. Katja Mölleken is thanked for preparation of C. pneumoniae RNA and genomic DNA.
Figures and Tables
Figure 1 Schematic of the hit loci in Mollicutes and Chlamydiaceae. A schematic representation of genes within the hit loci of the following species: A) M. pulmonis, M. mycoides subsp. mycoides SC, Mesoplasma florum and M. mobile containing genes homologous to hitABL of M. hominis; B) U. parvum, M. pneumoniae and M. genitalium, each containing a gene upstream of hitL predicted to encode an integral pore-forming protein; and C) C. pneumoniae, C. trachomatis, C. muridarum and C. caviae containing hitL flanking genes predicted to encode, upstream, a protein with the signature sequence of a metal-dependent hydrolase (light blue region), with an OB nucleic acid binding fold (dark blue region) and, downstream, a protein with ARM repeats (red regions), which are known to mediate protein-protein interactions. Triangles indicate signal peptidase recognition sites of SPase I and SPase II. Transmembrane regions are depicted as striped regions. The position of the RGD tri-peptide is marked by a dotted region.
Figure 2 RT-PCR analysis of M. pulmonis. A. The regions amplified by RT-PCR are shown below the genomic region encompassing MYPU_0060, MYPU_0070 and MYPU_0080. The primers used and the lengths of the amplicons are indicated. B. Amplicons were separated on a 0.8 % agarose gel and subjected to Southern blot analysis, here shown for the MYPU_0070 specific probe, using digoxigenin (DIG)-labeled probes hybridizing to each of the three genes, detected using chemiluminescence. Bands of lower length as expected are degradation products. M, DIG-labeled DNA molecular weight marker VII (Roche Biochemicals).
Figure 3 RT-PCR analysis of U. parvum. A. The positions of the different amplicons are shown below the schematic of the hit locus genes of U. parvum. The primers used (Table 2) and the lengths of the amplicons are indicated. B. The PCR products (A – D) for genomic DNA (g), cDNA (c) and RNA (r) were separated on a 0.6 % agarose gel and stained with ethidium bromide. Southern blot analysis was performed with digoxigenin (DIG)-labeled probes hybridizing to one of the four genes, (here shown for UU272 probing), and detected using chemiluminescence. M, Gene Ruler 1 kb DNA ladder (Fermentas).
Figure 4 RT-PCR analysis of C. pneumoniae. A. Below the schematic of the hit locus of C. pneumoniae the positions of the PCR amplicons (A – F) are shown. Genomic DNA (g), cDNA (c) and RNA without RT reaction (r) are used as templates. B. The PCR products were separated on a 0.8 % agarose gel and subjected to Southern blot analysis with DIG-labeled probes hybridizing to Cp265 (A, D), Cp266 / hitL (B, E) Cp267 (C, F) with visualization using chemiluminescence. In E, the signals of lower length as 1.4 kb may be due to primer dimerization. M, DIG-labeled DNA molecular weight marker VII (Roche Biochemicals)
Figure 5 The yeast-two hybrid assay. AH109 were co-transformed with the pGADT7 (AD) and pGBKT7 (BD) constructs containing hitL of M. hominis, Cp265, Cp266 or Cp267 from C. pneumoniae, pGADT7-T, expressing the SV40 large T-antigen and pGBKT7-53, expressing the murine p53 protein (K+), or pGADT7 and pGBKT7 without fusion partners (K-). Yeast cultures were incubated at 30°C on histidine-deficient agar plates for 4 days.
Figure 6 Quantitation of β-galactosidase activity. In yeast cells, co-transformed with pGADT7 (AD) and pGBKT7 (BD) constructs as indicated, β-galactosidase activity was quantified using 4-methylumbelliferyl-galactopyranoside (MUG) hydrolysis to the fluorescent molecule, 4-methylumbelliferone (4 MU). The fluorescence of 4 MU was excited at 360 nm and emission measured at 460 nm.
Figure 7 Immune co-precipitation. A. Affinity purified proteins, Cp265 (265C), Cp266 (266C), Cp267 (267C) and OppAC, were analyzed on 15 % SDS-polyacrylamide gels by Coomassie staining (C) or on Western blots by immunostaining with an anti-Protein C antibody (W). [35S]-labeled Cp265, Cp266 and Cp267 (Captives) were incubated at room temperature for 1 h with Cp265C, Cp266C, Cp267C and OppAC (Catcher). Immune complexes were precipitated with anti-Protein C-matrix, and the supernatants (B.) and precipitates (C.) analyzed on 15 % SDS-polyacrylamide gels by autoradiography using a phosphorimager. As a negative control, the [35S]-labeled proteins were subjected to the Protein C-matrix without a catcher (Sepha.αC). M, prestained low-molecular weight marker (Biorad)
Table 1 Organisms used for genome sequence analyses
Chlamydophila caviae GPIC NC_003361
Chlamydia muridarum NC_002620
Chlamydophila pneumoniae AR39 NC_002179
Chlamydia trachomatis D/UW-3/CX NC_000117
Mesoplasma florum L1 NC_006055
Mycoplasma gallisepticum R NC_004829
Mycoplasma genitalium G-37 NC_000908
Mycoplasma mobile 163 K NC_006908
Mycoplasma mycoides spp.mycoides SC str. PG1 NC_005364
Mycoplasma pneumoniae M129 NC_000912
Mycoplasma penetrans HF2 NC_004432
Mycoplasma pulmonis UAB CTIP NC_002771
Parachlamydia sp. UWE25 NC_005861
Ureaplasma parvum serovar 3 str. ATCC 700970 NC_002162
Table 2 Primers used in PCR
Primer Length Sequence (5'-3')
MP1 27 ATTTATTTTTGATTACTATTTTTGAAC
MP2 23 AATTTGTTTTATTATTTTGTTTA
MP8 20 TTAATGTTCATGTCCTTCTT
MP9 21 AATCCAGAAAGTTTTTTTATT
MP12 24 ATTTGTTATTGCTAAAAGATTGTA
UU1 22 ATGATCAATAAAAACAAAAAAT
UU2 19 GCGCCGTTAGTGATGTTAG
UU6 32 TGAGCTCTTCCATATTTTTTGATTATACCATA
UU7 23 AAAAACGAATTGCCTCTATGTAT
Cp1 21 CATGATGCGCGTGGAGTAGGT
Cp2 25 TCCAAGAAGCATTGGTACTCACGAT
Cp3 22 CGGTTTCCATGGCTTCTCTGAC
Cp4 29 TTATCGATGGATTGATAGATTGTGAAAAG
Cp5 22 GGACGCCCACCTAAAAGATGAA
Cp6 21 TTTCGCTTGGTCCCTCTCCTG
Cp7 25 GCTCTTTCAATATCTTCACGGCTCA
Cp8 28 TACGGTGCTGAGCTTAAAGATAGAAATG
Cp_265 up 27 ATGGATCCTAATGGAGGATTGGCTAAG
Cp_265 low 29 TTGAGCTCTCATATGATCCCTCTATCTTG
Cp_266 up 27 TTAGGATCCTCATGCCTACGTGCTTTG
Cp_266 low 29 TTTGAGCTCATCAGGCTATAGCACCTAAA
Cp_267 up 23 ATTGGATCCCCATGTTCGGCTCG
Cp_267 low 30 TTAGAGCTCACTTGAAAATAGAGAAAAGAG
Cp1 BamHI 27 ATGGATCCATGGAGGATTGGCTAAG
Cp2 BamHI 27 TTAGGATCCATGCCTACGTGCTTTG
Cp3 BamHI 23 ATTGGATCCATGTTCGGCTCG
==== Refs
Seraphin B The HIT protein family: a new family of proteins present in prokaryotes, yeast and mammals DNA Seq 1992 3 177 179 1472710
Fong LY Fidanza V Zanesi N Lock LF Siracusa LD Mancini R Siprashvili Z Ottey M Martin SE Druck T McCue PA Croce CM Huebner K Muir-Torre-like syndrome in Fhit-deficient mice Proc Natl Acad Sci U S A 2000 97 4742 4747 10758156 10.1073/pnas.080063497
Pace HC Garrison PN Robinson AK Barnes LD Draganescu A Rosler A Blackburn GM Siprashvili Z Croce CM Huebner K Brenner C Genetic, biochemical, and crystallographic characterization of Fhit-substrate complexes as the active signaling form of Fhit Proc Natl Acad Sci U S A 1998 95 5484 5489 9576908 10.1073/pnas.95.10.5484
Brenner C Hint, Fhit, and GalT: function, structure, evolution, and mechanism of three branches of the histidine triad superfamily of nucleotide hydrolases and transferases Biochemistry 2002 41 9003 9014 12119013 10.1021/bi025942q
Brenner C Bieganowski P Pace HC Huebner K The histidine triad superfamily of nucleotide-binding proteins J Cell Physiol 1999 181 179 187 10497298 10.1002/(SICI)1097-4652(199911)181:2<179::AID-JCP1>3.0.CO;2-8
Kitzerow A Henrich B The cytosolic HinT protein of Mycoplasma hominis interacts with two membrane proteins Mol Microbiol 2001 41 279 287 11454219 10.1046/j.1365-2958.2001.02524.x
Razin S Yogev D Naot Y Molecular biology and pathogenicity of mycoplasmas Microbiol Mol Biol Rev 1998 62 1094 1156 9841667
Mernaugh GR Dallo SF Holt SC Baseman JB Properties of adhering and nonadhering populations of Mycoplasma genitalium Clin Infect Dis 1993 17 S69 S78 8399942
Bavoil PM Hsia R Ojcius DM Closing in on Chlamydia and its intracellular bag of tricks Microbiology 2000 146 2723 2731 11065351
Robson B Garnier J Protein structure prediction Nature 1993 361 506 8429904 10.1038/361506a0
Himmelreich R Hilbert H Plagens H Pirkl E Li BC Herrmann R Complete sequence analysis of the genome of the bacterium Mycoplasma pneumoniae Nucleic Acids Res 1996 24 4420 4449 8948633 10.1093/nar/24.22.4420
Mulder NJ Apweiler R Attwood TK Bairoch A Barrell D Bateman A Binns D Biswas M Bradley P Bork P Bucher P Copley RR Courcelle E Das U Durbin R Falquet L Fleischmann W Griffiths-Jones S Haft D Harte N Hulo N Kahn D Kanapin A Krestyaninova M Lopez R Letunic I Lonsdale D Silventoinen V Orchard SE Pagni M Peyruc D Ponting CP Selengut JD Servant F Sigrist CJA Vaughan R Zdobnov EM The InterPro Database, 2003 brings increased coverage and new features Nucleic Acids Res 2003 31 315 318 12520011 10.1093/nar/gkg046
Everest P Li J Douce G Charles I De Azavedo J Chatfield S Dougan G Roberts M Role of the Bordetella pertussis P.69/pertactin protein and the P.69/pertactin RGD motif in the adherence to and invasion of mammalian cells Microbiology 1996 142 3261 3268 8969522
Torshin IY Structural criteria of biologically active RGD-sites for analysis of protein cellular function – a bioinformatics study Med Sci Monit 2002 8 BR301 BR312 12165734
Schultz J Copley RR Doerks T Ponting CP Bork P SMART: a web-based tool for the study of genetically mobile domains Nucleic Acids Res 2000 28 231 234 10592234 10.1093/nar/28.1.231
Ermolaeva MD White O Salzberg SL Prediction of Operons in Microbial Genomes Nucleic Acids Res 2001 9 1216 1221 10.1093/nar/29.5.1216
Rahut R Klug G mRNA degradation in bacteria FEMS Microbiol Rev 1999 23 353 370 10371038 10.1016/S0168-6445(99)00012-1
Chien CT Bartel PL Sternglanz R Fields S The two-hybrid system: a method to identify and clone genes for proteins that interact with a protein of interest Proc Natl Acad Sci U S A 1991 88 9578 9582 1946372
Lima CD Klein MG Weinstein IB Henrickson WA Three-dimensional structure of human protein kinase C interacting protein 1, a member of the HIT family of proteins Proc Natl Acad Sci USA 1996 93 5357 5362 8643579 10.1073/pnas.93.11.5357
Brenner C Garrison P Gilmour J Peisach D Ringe D Petsko GA Lowenstein JM Crystal structures of HinT demonstrate that histidine triad proteins are GalT-related nucleotide-binding proteins Nature Struct Biol 1997 4 231 238 9164465 10.1038/nsb0397-231
Bieganowski P Garrison PN Hodawadekar SC Faye G Barnes LD Brenner C Adenosine monophosphoramidase activity of Hint and Hnt1 supports function of Kin28, Ccl1, and Tfb3 J Biol Chem 2002 277 10852 10860 11805111 10.1074/jbc.M111480200
Razin E Zhang ZC Nechushtan H Frenkel S Lee YN Arudchandran R Rivera J Suppression of microphthalmia transcriptional activity by its association with protein kinase C-interacting protein 1 in mast cells J Biol Chem 1999 274 34272 34276 10567402 10.1074/jbc.274.48.34272
Korsisaari N Makela TP Interactions of Cdk7 and Kin28 with Hint/PKCI-1 and Hnt1 histidine triad proteins J Biol Chem 2000 275 34837 34840 10958787 10.1074/jbc.C000505200
Korsisaari N Rossi DJ Luukko K Huebner K Henkemeyer M Makela TP The histidine triad protein Hint is not required for murine development or Cdk7 function Mol Cell Biol 2003 23 3929 3935 12748294 10.1128/MCB.23.11.3929-3935.2003
Krakowiak A Pace HC Blackburn GM Adams M Mekhalfia A Kaczmarek R Baraniak J Stec WJ Brenner C Biochemical, crystallographic, and mutagenic characterization of Hint, the AMP-lysine hydrolase, with novel substrates and inhibitors J Biol Chem 2004 279 18711 18716 14982931 10.1074/jbc.M314271200
Dudler R Schmidhauser C Parish RW Wettenhall RE Schmidt T A mycoplasma high-affinity transport system and the in vitro invasiveness of mouse sarcoma cells EMBO J 1988 7 3963 3970 3208756
Hopfe M Hoffmann R Henrich B P80, the HinT interacting membrane protein, is a secreted antigen of Mycoplasma hominis BMC Microbiol 2004 4 46 15579213 10.1186/1471-2180-4-46
Antelmann H Tjalsma H Voigt B Ohlmeier S Bron S van Dijl JM Hecker M A proteomic view on genome-based signal peptide predictions Genome Res 2001 11 1484 1502 11544192 10.1101/gr.182801
Sasaki Y Ishikawa J Yamashita A Oshima K Kenri T Furuya K Yoshino C Horino A Shiba T Sasaki T Hattori M The complete genomic sequence of Mycoplasma penetrans, an intracellular bacterial pathogen in humans Nucleic Acids Res 2002 30 5293 5300 12466555 10.1093/nar/gkf667
Morimoto K Sato S Tabata S Nakai M A HEAT-repeats containing protein, IaiH, stabilizes the iron-sulfur cluster bound to the cyanobacterial IscA homologue, IscA2 J Biochem (Tokyo) 2003 134 211 217 12966069
Sambrook J Fritsch EF Maniatis T Molecular cloning: a laboratory manual 1989 Cold Spring Harbor Laboratory Press. Cold Spring Harbor. N.Y
Barre A de Daruvar A Blanchard A MolliGen, a database dedicated to the comparative genomics of Mollicutes Nucleic Acids Res 2004 32 307 310 14722225 10.1093/nar/gkh114
Chomczynski P Sacchi N Single-step method of RNA isolation by acid guanidinium thiocyanate-phenol-chloroform extraction Anal Biochem 1987 162 156 159 2440339 10.1016/0003-2697(87)90021-2
Jantos CA Heck S Roggendorf R Sen-Gupta M Hegemann JH Antigenic and molecular analyses of different Chlamydia pneumoniaestrains J Clin Microbiol 1997 35 620 623 9041400
Henrich B Hopfe M Kitzerow A Hadding U The adherence-associated lipoprotein P100, encoded by an opp operon structure, functions as the oligo-peptide-binding domain OppA of a putative oligopeptide transport system in Mycoplasma hominis J Bacteriol 1999 181 4873 4878 10438757
Sanger F Nicklen S Coulson AR DNA sequencing with chain-terminating inhibitors Proc Natl Acad Sci USA 1977 74 5463 5467 271968
Laemmli UK Cleavage of structural proteins during the assembly of the head of bacteriophage T4 Nature 1970 227 680 685 5432063
Towbin H Stachelin T Gordon J Electrophoretic transfer of proteins from polyacrylamide gels to nitrocellulose sheets: procedure and some applications Proc Natl Acad Sci USA 1979 76 4350 4354 388439
Takeshita A Yen PM Ikeda M Cardona GR Liu Y Koibuchi N Norwitz ER Chin WW Thyroid hormone response elements differentially modulate the interactions of thyroid hormone receptors with two receptor binding domains in the steroid receptor coactivator-1 J Biol Chem 1998 273 21554 21562 9705285 10.1074/jbc.273.34.21554
| 15904496 | PMC1173108 | CC BY | 2021-01-04 16:03:39 | no | BMC Microbiol. 2005 May 18; 5:27 | utf-8 | BMC Microbiol | 2,005 | 10.1186/1471-2180-5-27 | oa_comm |
==== Front
BMC MicrobiolBMC Microbiology1471-2180BioMed Central London 1471-2180-5-301590721910.1186/1471-2180-5-30Methodology ArticleAn improved method for rapid generation of unmarked Pseudomonas aeruginosa deletion mutants Choi Kyoung-Hee [email protected] Herbert P [email protected] Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, Colorado, USA2005 23 5 2005 5 30 30 2 3 2005 23 5 2005 Copyright © 2005 Choi and Schweizer; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Traditional gene replacement procedures are still time-consuming. They usually necessitate cloning of the gene to be mutated, insertional inactivation of the gene with an antibiotic resistance cassette and exchange of the plasmid-borne mutant allele with the bacterial chromosome. PCR and recombinational technologies can be exploited to substantially accelerate virtually all steps involved in the gene replacement process.
Results
We describe a method for rapid generation of unmarked P. aeruginosa deletion mutants. Three partially overlapping DNA fragments are amplified and then spliced together in vitro by overlap extension PCR. The resulting DNA fragment is cloned in vitro into the Gateway vector pDONR221 and then recombined into the Gateway-compatible gene replacement vector pEX18ApGW. The plasmid-borne deletions are next transferred to the P. aeruginosa chromosome by homologous recombination. Unmarked deletion mutants are finally obtained by Flp-mediated excision of the antibiotic resistance marker. The method was applied to deletion of 25 P. aeruginosa genes encoding transcriptional regulators of the GntR family.
Conclusion
While maintaining the key features of traditional gene replacement procedures, for example, suicide delivery vectors, antibiotic resistance selection and sucrose counterselection, the method described here is considerably faster due to streamlining of some of the key steps involved in the process, especially plasmid-borne mutant allele construction and its transfer into the target host. With appropriate modifications, the method should be applicable to other bacteria.
==== Body
Background
The elucidation of the P. aeruginosa strain PAO1 genome sequence in 2000 [1] opened the doors for genome- and proteome-scale research with this important opportunistic pathogen. These include the availability of commercial (Affymetrix, Santa Clara, CA) P. aeruginosa GeneChips® for transcriptome analyses [2], as well as the P. aeruginosa PAO1 gene collection for high-throughput expression and purification of recombinant proteins [3]. A comprehensive transposon mutant library was generated containing over 30,000 sequence-defined mutants, corresponding to an average of five insertions per gene [4].
However, despite the development of many genetic tools for P. aeruginosa over the past decade [5,6], isolation of defined deletion mutants is still a relatively tedious process, which relies on construction of deletion alleles, most often tagged with an antibiotic resistance gene, on a suicide plasmid, followed by recombination of the plasmid-borne deletions into the chromosome, usually after conjugal transfer of the suicide plasmid (reviewed in [6]). Merodiploids arising from chromosomal integration of the suicide plasmid are resolved by utilization of a counterselectable marker, most often Bacillus subtilis sacB (sucrose counterselection) [7] or, less frequently, rpsL (streptomycin counterselection)[8]. In cases where the antibiotic selection markers are flanked by site specific recombination sites, e.g., the Flp recombinase target (FRT) [9] or Cre recombinase (loxP) [10] sites, they can subsequently be deleted from the chromosome, resulting in unmarked deletion mutants.
Unfortunately, the previously described method for one-step inactivation of chromosomal genes in Escherichia coli using PCR products [11] does not work in P. aeruginosa, although we have used a modification [12] of this approach where the target gene is first cloned into a plasmid, followed by λ RED-mediated recombination of a PCR-generated mutated copy of the gene [13]. Here, we describe a more streamlined method for generation of chromosomal deletion mutants. In this method, a "mutant" fragment containing the 5' and 3' flanking regions of the target gene plus the antibiotic resistance gene is assembled by a modified [14] PCR overlap extension protocol [15] and then cloned into a suicide vector using the Gateway recombinational cloning system, similarly to a previously described method [16]. The plasmid-borne deletion allele is then transferred to P. aeruginosa utilizing a rapid transformation procedure and recombined into the chromosome. The transformants are often merodiploids which are then resolved by sucrose counterselection against the undesired wild-type sequences. The antibiotic resistance marker is subsequently deleted from the chromosome by Flp recombinase.
Results
Construction of a Gateway-compatible suicide vector
We previously described the pEX family of relatively small, fully sequenced suicide plasmids which are now widely used for gene replacement experiments in P. aeruginosa and related bacteria [9]. Wolfgang et al. [16] recently described a Gateway-compatible pEX18Gm derivative. Here, we modified pEX18Ap for use as a Gateway destination vector for cloning of mutations marked with a gentamycin resistance (Gmr) encoding gene. We prefer using the Gmr marker because it is more easily transferable between P. aeruginosa chromosomes by transformation with chromosomal DNA fragments when compared to other selection markers [17]. The resulting vector pEX18ApGW (Fig. 1) contains the functional sequences for recombination-based cloning (attR1 and attR2) and the ccdB counterselection marker, while maintaining the sacB counterselection marker for downstream resolution of merodiploids.
Generation of a mutant fragment by PCR overlap extension
The amplification of each mutant fragment was achieved in a two step PCR that required 8 PCR primers, 4 of which were unique for each fragment to be mutated and 4 of which were common primers (Table 1). The gene-specific portions of the unique primers were designed to yield Tm's of 55–57°C and PCR fragments ranging from ~200 to 600 bp. These parameters enabled utilization of the same PCR conditions for different target genes, while at the same time provided for amplification of sufficient chromosomal DNA to allow for efficient homologous recombination of plasmid-borne sequence with the chromosome.
The basic strategy for generation of the mutant fragment by PCR overlap extension is illustrated in Fig. 2. In PCR1, the four gene-specific primers are used to amplify the 5' and 3' regions of the target gene. Simultaneously, two of the common primers, Gm-F and Gm-R, are used to amplify the Gmr cassette flanked by FRT sites from a pPS856 template. Since the Gmr fragment is used for all constructs, it can be prepared in larger amounts ahead of time and stored until needed. Fig. 3A illustrates typical results of PCR1 utilizing the example of P. aeruginosa gene PA1520, encoding a putative transcriptional regulator of the GntR family. When we adhered to the prescribed PCR conditions, the amplified fragments were very clean. It was especially prudent to follow the conditions for PCR amplification of the Gmr FRT fragment since the FRT sites possess significant secondary structures.
The PCR fragments were gel-purified and equal amounts (50 ng) of each were combined for PCR2. PCR2 was allowed to proceed for 3 cycles in the absence of exogenous primers, which for PA1520 yields the intermittent 1,709 bp 'attB1-PA1520'-FRT-Gm-FRT-'PA1520-attB2' fragment illustrated in Fig 3A. The common Gateway primers GW-attB1 and GW-attB2 were then added and the PCR continued for another 25 cycles to obtain the final, recombination-proficient DNA fragment, which constituted the predominant PCR product at this stage (Fig. 3B). For PA1520, the resulting 1,735 bp attB1-PA1520'-FRT-Gm-FRT-'PA1520-attB2 fragment was gel-purified and used for the BP clonase reaction for construction of an entry clone.
BP and LR clonase reactions
The BP and LR clonase reactions (Fig. 4) were performed according to Invitrogen's (Carlsbad, CA) Gateway cloning manual. For the BP clonase reaction pDONR221 was used, but only half of the recommended BP clonase enzyme mix. Gmr and kanamycin resistant (Kmr) DH5α or HPS1 transformants were selected and the presence of the correct plasmids was confirmed by XbaI digestion (the FRT sites flanking the Gmr gene each contain a single XbaI site). The insert of a correct pDONR-Gene::Gm entry clone was then recombined into the destination vector pEX18ApGW using the LR clonase protocol, again using only half of the recommended amount of LR clonase mix. Recombinants were transformed into DH5α and Apr colonies were selected. We noticed that, at least under the conditions we used, many transformants exhibited a Apr Kmr phenotype, indicating that they either contained both pDONR-Gene::Gm and pEX18ApGW-Gene::Gm or, more likely, a cointegrate of both plasmids. The presence of the correct pEX18ApGW-Gene::Gm in transformants that were only Apr was confirmed by XbaI digestion.
Gene replacement
To expedite gene replacement, an improved electroporation method [17] was used for transfer of the suicide plasmid pEX18ApGW-Gene::Gm into P. aeruginosa instead of the traditionally employed conjugation method. Although after transfer into P. aeruginosa double cross-over events can occur frequently (>50%), they can also be rare (<1–5%). In the latter instance, merodiploids formed via integration of the suicide plasmid by a single cross-over event (Fig. 4). The merodiploid state was then resolved via sucrose selection in the presence of gentamycin, resulting in deletion of the wild type gene. For generation of unmarked deletion mutants, the Gmr marker was subsequently removed by deletion of a 967 bp fragment using Flp recombinase. The presence of the desired deletion in either the marked or unmarked PA1520 mutant was verified by colony PCR utilizing the gene-specific up and down primers (Fig. 5).
Deletion of 25 genes encoding transcriptional regulators of the GntR family
We are interested in characterizing the activator involved in regulation of expression of the fabAB operon, which encodes two essential enzymes of de novo fatty acid biosynthesis [18]. Expression of the fabAB operon is repressed by exogenously added fatty acids, most effectively by oleic acid, and preliminary results from our laboratory indicate that this may be due to relief of activation by a transcriptional regulator which binds to a 30 nucleotide site located in the fabAB promoter region (Choi and Schweizer, unpublished results). This 30 bp region is only found and conserved in Pseudomonas spp. Its deletion dramatically reduces transcription of the fabAB operon and the residual transcriptional activity is no longer fatty acid responsive (Fig. 6). In E. coli, transcriptional activation of the unlinked fabA and fabB genes is achieved by FadR, a regulator belonging to a group of transcriptional regulators with the GntR family signature [19,20]. The PAO1 chromosome encodes more than 30 regulatory proteins with this signature. Of these, 27 have not been assigned function. Using the methodology described above for one of these genes, PA1520, we deleted 25 of the 27 genes (we could not delete the presumably essential PA1285 and PA2299) in less than 4 weeks in strain PAO1 with a chromosomally integrated fabA'-lacZ transcriptional fusion and analyzed β-galactosidase expression in the resulting mutant strains (Fig. 6). In exponential phase cells, the overall pattern of fabA expression was indistinguishable from the parental strain in all 25 mutants, indicating that none of these genes encodes the fabAB activator. We would have expected an expression pattern similar to that observed in the PAO1::fabAΔ30'-lacZ control strain which contains a deletion of the 30 nucleotide putative activator-binding site.
Discussion
In our experience, the method described here for generation of unmarked deletion mutants is the fastest available to date. From start to finish, an individual unmarked P. aeruginosa mutant can be generated and characterized in ~14 days, which is up to one week faster than using our previously described method [9]. However, the main advantage of the method does not lie in individual mutant generation but in the speed by which collective deletion mutant pools can be generated. For example, we isolated unmarked deletions in 25 of the 27 genes encoding transcriptional regulators of the GntR family in less than 4 weeks. Two genes could not be deleted, presumably because they encode essential proteins. Besides speed, what are some of the other unique features of this method?
First, the deletion of gene sequences is not restricted by the natural availability or synthetic generation of restriction sites that are subsequently used to delete intervening sequences. With proper primer location, the PCR-based method allows clean deletion of more-or-less the entire coding sequence without fear of generating truncated genes which potentially produce products with undesired side effects.
Second, Flp excision of the antibiotic resistance gene cassette leaves behind a short 85 bp FRT scar which does not exhibit any known polar effects on downstream genes. The method is therefore uniquely suited to study genes organized in polycistronic units. Flp excision is a very straightforward procedure with efficiencies approaching 100% [9].
Third, the method is economical, especially in a more high-throughput format. PCR overlap extension requires only four gene specific primers of reasonable length which keeps oligonucleotide costs to a minimum. In comparison to traditional methods, it also requires fewer hands-on steps and gene-specific reagents (e.g., restriction enzymes).
Conclusion
Although not yet as fast as the PCR fragment-directed gene replacement method described for E. coli, the PCR- and recombinational cloning based method described opens the door for high-throughput generation of P. aeruginosa deletion mutants on a genome-wide scale. With appropriate modifications, i.e., choice of appropriate selection markers and Gateway-compatible gene replacement vectors, the method should be applicable to the many other bacteria in which the pEX vector system can be applied [6].
Methods
Media
Escherichia coli and P. aeruginosa strains were maintained on Luria-Bertani medium (LB; 10 g per liter tryptone, 5 g per liter yeast extract, 10 g per liter NaCl; Becton, Dickinson & Co., Sparks, MD). For plasmid maintenance in E. coli, the medium was supplemented with 100 μg per ml ampicillin, 25 μg per ml chloramphenicol, 35 μg per ml kanamycin or 15 μg per ml gentamycin. For marker selection in P. aeruginosa, 200 μg per ml carbenicillin and 30 μg per ml of gentamycin was used, as appropriate.
β-galactosidase activity assays
Cells were grown at 37°C with shaking to exponential phase (optical density at 540 nm ~0.4–0.8) in LB medium with 0.05% Brij 58 +/- 0.05% oleic acid. β-galactosidase activity was measured in chloroform/sodium dodecyl sulfate-permeabilized cells and its activity calculated as previously described [21].
Standard DNA procedures
Routine procedures were employed for manipulation of DNA [22]. Plasmid DNAs were isolated using the QIAprep Mini-spin kit (Qiagen, Valencia, CA) and P. aeruginosa chromosomal DNA was obtained using the QIAamp DNA Mini Kit. DNA fragments were purified from agarose gels utilizing the QIAquick gel extraction kit.
Construction of the Gateway-compatible gene replacement vector pEX18ApGW
The previously described gene replacement vector pEX18Ap [9] was modified by cloning of a 1,755 bp HindIII-KpnI fragment from pUC18-mini-Tn7T-Gm-GW (GenBank accession number AY737004), followed by transformation into the gyrA strain DB3.1 (Invitrogen).
1st round PCRs
PCR-amplification of the gentamycin resistance gene cassette
A 50 μl PCR reaction contained 5 ng pPS856 [9] template DNA, 1x HiFi Platinum Taq buffer, 2 mM MgSO4, 200 μM dNTPs, 0.2 μM of Gm-F and Gm-R (Table 1) and 5 units of HiFi Platinum Taq polymerase (Invitrogen). Cycle conditions were 95°C for 2 min, followed by 30 cycles of 94°C for 30 s, 50°C for 30 s, and 68°C for 1 min 30 s, and a final extension at 68°C for 7 min. The resulting 1,053 bp PCR product was purified by agarose gel electrophoresis and its concentration determined spectrophotometrically (A260 nm) in an Eppendorf Biophotometer (Hamburg, Germany) and using the 50–2000 μl Eppendorf UVettes
PCR-amplification of 5' and 3' gene fragments
Two 50 μl PCR reactions were prepared. The first reaction contained 20 ng chromosomal template DNA, 1x HiFi Platinum Taq buffer, 2 mM MgSO4, 5% DMSO, 200 μM dNTPs, 0.8 μM of PA1520-UpF-GWL and PA1520-UpR-Gm (Table 1) and 5 units of Platinum Taq polymerase. The second reaction contained the same components as the first, but 0.8 μM of PA1520-DnF-Gm and PA1520-DnR-GWR (Table 1). Cycle conditions were 94°C for 5 min, followed by 30 cycles of 94°C for 30 s, 56°C for 30 s, and 68°C for 30 s, and a final extension at 68°C for 10 min. The resulting PCR products were purified by agarose gel electrophoresis and their concentrations determined spectrophotometrically (A260 nm).
2nd round PCR
A 50 μl PCR reaction contained 50 ng each of the PA1520 5' and 3' purified template DNAs, and 50 ng of FRT-Gm-FRT template DNA prepared during 1st round PCR. The reaction mix also contained 1x HiFi Platinum Taq buffer, 2 mM MgSO4, 5% DMSO and 200 μM dNTPs, and 5 units of HiFi Platinum Taq polymerase. After an initial denaturation at 94°C for 2 min, 3 cycles of 94°C for 30 s, 55°C for 30 s, and 68°C for 1 min were run without added primers. The third cycle was paused at 30 s of the 68°C extension, primers GW-attB1 and GW-attB2 were added to 0.2 μM each, and the cycle was then finished by another 30 s extension at 68°C. The PCR was completed by 25 cycles of 94°C for 30 s, 56°C for 30 s, and 68°C for 5 min, and a final extension at 68°C for 10 min. The resulting major PCR product was purified by agarose gel electrophoresis and its concentrations determined spectrophotometrically (A260 nm). The identity of the PCR fragment was confirmed by XbaI digestion (each FRT site of the FRT-Gm-FRT fragment contains a XbaI site).
BP and LR clonase reactions
The BP and LR clonase reactions for recombinational transfer of the PCR product into pDONR221 and pEX18ApGW, respectively, were performed as described in Invitrogen's Gateway cloning manual, but using only half of the recommended amounts of BP and LR clonase mixes and either E. coli DH5α [23] or HPS1 [24] as host strains. The presence of the correct fragments in transformants obtained with DNA from either clonase reaction was verified by digestion with XbaI because each FRT site flanking the Gmr gene contains a XbaI site. However, before plasmid isolation from transformants obtained with DNA from the LR clonase reaction, 25–50 transformants were i) patched on LB+Km and LB+Ap plates, and ii) simultaneously purified for single colonies on LB+Ap plates. This was necessary to distinguish between those colonies containing only the desired pEX18ApGW-Gene::Gm from those containing this plasmid and the frequently contaminating pDONR-Gene::Gm (pEX18Ap-derived plasmids confer Apr and pDONR plasmids confer Kmr). Plasmids were then isolated from Apr Kms transformants and analyzed by XbaI digestion. In those extremely rare instances where all patched transformants contained a mixed plasmid population (<1% of to date performed LR clonase reactions), retransformation with Apr selection was necessary to obtain colonies containing only pEX18ApGW-Gene::Gm.
Transfer of plasmid-borne deletions to the P. aeruginosa chromosome
A rapid electroporation method described elsewhere [17] was used to transfer the pEX18ApGW-borne deletion mutations to P. aeruginosa. Briefly, 6 ml of an overnight culture grown in LB medium was harvested in 4 microcentrifuge tubes by centrifugation (1–2 min, 16,000 × g) at room temperature. Each cell pellet was washed twice with 1 ml of room temperature 300 mM sucrose and they were then combined in a total of 100 μl 300 mM sucrose. For electroporation, 300-500 ng of plasmid DNA was mixed with 100 μl of electrocompetent cells and transferred to a 2 mm gap width electroporation cuvette. After applying a pulse (settings: 25 μF; 200 Ohm; 2.5 kV on a Bio-Rad GenePulserXcell™), 1 ml of LB medium was added at once, and the cells were transferred to a 17 × 100 mm glass or polystyrene tube and shaken for 1 h at 37°C. The cells were then harvested in a microcentrifuge tube. 800 μl of the supernatant was discarded and the cell pellet resuspended in the residual medium. The entire mixture was then plated on two LB plates containing 30 μg per ml Gm (LB+Gm30). The plates were incubated at 37°C until colonies appeared (usually within 24 h). Under these conditions, the transformation efficiencies were generally 30–100 transformants per μg of DNA. A few colonies were patched on LB+Gm30 plates and LB+Cb200 plates to differentiate single- from double cross-over events. To ascertain resolution of merodiploids, Gmr colonies were struck for single colonies on LB+Gm30 plates containing 5% sucrose. Gmr colonies from the LB-Gm-sucrose plates were patched onto LB+Gm30+5% sucrose, as well as LB plates with 200 μg per ml carbenicillin (LB+Cb200). Colonies growing on the LB-Gm-sucrose, but not on the LB-carbenicillin plates were considered putative deletion mutants. The presence of the correct mutations was verified by colony PCR. To do this, a single, large colony (or the equivalent from a cell patch) was picked from a LB-Gm-sucrose plate, transferred to 30 μl H2O in a microcentrifuge tube and boiled for 5 min. Cell debris was removed by centrifugation in a microcentrifuge fuge (2 min; 16,000 × g), and the supernatant was transferred to a fresh tube which was placed on ice. 5 μl of the supernatant was used as source of template DNA in a 50 μl PCR reaction containing Taq buffer, 1.5 mM MgSO4, 5% DMSO, 0.6 μM each of PA1520-UpF-GWL and PA1520-DnR-GWR, 200 μM dNTPs and 5 units Taq polymerase (Fermentas, Hanover, MD). Cycle conditions were 95°C for 5 min, followed by 30 cycles of 95°C for 45 s, 55°C for 30 s, and 72°C for 2 min, and a final extension at 72°C for 10 min. PCR products were analyzed by agarose gel electrophoresis.
Flp-mediated marker excision
Electrocompetent cells of the newly constructed mutant strain were prepared as described in the preceding paragraph and transformed with 20 ng of pFLP2 [9] DNA as described above. After phenotypic expression at 37°C for 1 h, the cell suspension was diluted 1:1,000 and 1:10,000 with either LB or 0.9% NaCl, and 50 μl aliquots were plated on LB+Cb200 plates and incubated at 37°C until colonies appeared. Transformants were purified for single colonies on LB+Cb200 plates. Ten single colonies were tested for antibiotic-susceptibility on LB ± Gm30 plates and on a LB+Cb200 plate. Two Gms Cbr isolates were struck for single colonies onto a LB+5% sucrose plate and incubated at 37°C until sucrose-resistant colonies appeared. Ten sucrose-resistant colonies were retested on a LB+5% sucrose (master) plate and a LB+Cb200 plate. Finally, two sucrose-resistant and Cbs colonies were struck on LB plates without antibiotics, and their Cbs and Gms phenotypes confirmed by patching on LB ± Cb200 and LB ± Gm30 plates. Deletion of the Gmr marker was assessed by colony PCR utilizing the conditions and primers described in the preceding paragraph
Authors' contributions
KHC, performance of experiments, writing of manuscript.
HPS, design and coordination of the study, data evaluation, direct supervision of experimental work, writing of manuscript.
All authors read and approved the final manuscript.
Supplementary Material
Additional File 1
Table 2 – Sequences of PCR primers used to amplify genes encoding transcriptional regulators of the GntR family
Click here for file
Acknowledgements
This work was supported by NIH grant AI058141 to HPS. The authors wish to thank Dr. Donald Moir (Microbiotix, Inc.) for helpful advice regarding use of the PCR overlap extension technology with GC-rich DNA.
Figures and Tables
Figure 1 Map of the Gateway-compatible pEX18ApGW. This vector was derived by cloning a Gateway conversion fragment (grey) into the multiple cloning site of pEX18Ap (black). Only selected restriction enzyme cleavage sites are shown. Abbreviations: attR1 and attR2, bacteriophage λ recombination sites; bla, β-lactamase-encoding gene; cat, chloramphenicol acetyl transferase-encoding gene; ccdB, gene encoding gyrase-modifying enzyme (CcdB poisons host DNA gyrase by forming a covalent complex with the DNA gyrase A subunit and thus serves as a counter-selectable marker in gyrA+ cloning hosts [25]); ori, ColE1-derived replication origin; oriT, origin of conjugal transfer; sacB, Bacillus subtilis levansucrase-encoding gene. The sequence of this plasmid was deposited in GenBank and assigned accession number AY928469.
Figure 2 Schematic illustration of mutant fragment generation by overlap extension PCR. During first round PCR (PCR1), the 5' and 3' ends of the target genes, as well as the gentamycin (Gm) resistance cassette are amplified using four gene-specific primers (G-UpF-GWL, G-UpR-Gm, G-DnF-Gm and G-DnR-GWR) and the common Gm-specific primers (Gm-F and Gm-R). This generates three fragments with partial overlaps either to each other (indicated by the blue boxes signifying Gm overlap) or the attB1 and attB2 λ recombination sites (indicated by the green and pink boxes). These purified fragments are then assembled in vitro by overlap extension during second round PCR (PCR2) using common primers GW-attB1 and GW-attB2, resulting in a recombination-proficient mutant PCR fragment.
Figure 3 PCR amplification of the Gm FRT cassette, PA1520 gene fragments and the overlap extension product. A. First round PCR fragments. The left panel illustrates amplification of the 1,053-bp Gmr fragment from pPS856 which contains 24 bp (right) and 25 bp (left) overlaps with the PA1520' and 'PA1520 fragments (blue boxes). The right panel illustrates amplification of the PA1520' and 'PA1520 fragments. The 5' fragment contains 388 bp of chromosomal DNA, 25 bp overlapping the left side of the Gmr fragment and 16 bp overlapping the GW-attB1 primer. Similarly, the 3' fragment contains 236 bp of chromosomal DNA, 24 bp overlapping the right side of the Gmr fragment and 16 bp overlapping the GW-attB2 primer. The sequences of the gene-specific and common primers are listed in Table 1. B. Second round PCR. The purified fragments shown in panel A were used in the second round PCR illustrated in Fig. 2 to derive the indicated attB1-PA1520'-FRT-Gm-FRT-'PA1520-attB2 fragment. The entire 50 μl second round PCR reaction was subjected to agarose gel electrophoresis. The desired DNA fragment constituting the major product marked by the arrow was excised from the gel, purified and then used for the BP clonase reaction. Lanes labeled M in both panels contained Hi-Lo molecular size markers from Minnesota Molecular (Minneapolis, MN).
Figure 4 Gateway-recombinational cloning and return of the plasmid-borne deletion allele to the P. aeruginosa chromosome. The mutant DNA fragment generated by overlap extension PCR is first cloned into pDONR221 via the BP clonase reaction to create the entry clone pDONR221-Gene::Gm, which then serves as the substrate for LR clonase-mediated recombination into the destination vector pEX18ApGW. The resulting suicide vector pEX18ApGW-Gene::Gm is then transferred to P. aeruginosa and the plasmid-borne deletion mutation is exchanged with the chromosome to generate the desired deletion mutant. Please note that, as discussed in the text, gene replacement by double-crossover can occur quite frequently, but it can also be a rare event in which case allele exchange happens in two steps involving homologous recombination. First, the suicide plasmid is integrated via a single-crossover event resulting in generation of a merodiploid containing the wild-type and mutant allele. Second, the merodiploid state is resolved by sacB-mediated sucrose counterselection in the presence of gentamycin, resulting in generation of the illustrated chromosomal deletion mutant. An unmarked mutant is then obtained after Flp recombinase-mediated excision of the Gm marker.
Figure 5 PCR analysis of marked and unmarked P. aeruginosa PA1520 deletion strains. Colony PCR was performed on either wild-type PAO1 and its PA1520 mutant derivatives, either containing a marked (PA1520::FRT-Gm-FRT) or unmarked (PA1520::FRT) PA1520 deletion. The sizes of the expected PCR fragments are indicated. Note that the short deletion removes 41 bp of the PA1520 coding sequence, corresponding to codons 131 to 145, but replaces these sequences with a 85 bp FRT scar. Lane M contained Hi-Lo molecular size markers of the indicated sizes from Minnesota Molecular.
Figure 6 Effect of deletions of P. aeruginosa GntR homologs on fabA expression. The indicated genes were deleted in strain PAO1 containing a chromosomally integrated fabA'-lacZ fusion (labelled PAO1). The control was PAO1 with a fabAΔ30'-lacZ fusion; this strain harbours the same fabA'-lacZ fusion but contains a deletion of the putative 30 nucleotide activator-binding site in the fabA promoter region. Strains were grown to mid-log phase in LB medium containing 0.05% Brij 58 +/- 0.05% oleic acid and β-galactosidase expression was monitored in triplicate samples. The dotted line marks expression levels observed in the putative activator binding-site mutant and similar levels would be expected in an activator mutant.
Table 1 PCR oligonucleotides
Name Sequence (5'→3')1
Gene-specific primers
G-UpF-GWL2 TACAAAAAAGCAGGCTccgatcagttgcaacacatc
G-UpR-Gm2 TCAGAGCGCTTTTGAAGCTAATTCGttgttcctgcaccaccatct
G-DnF-Gm2 AGGAACTTCAAGATCCCCAATTCGccggcgagttccacctgaa
G-DnR-GWR2 TACAAGAAAGCTGGGTggttgagcttgctgtcgata
Common primers
Gm-F CGAATTAGCTTCAAAAGCGCTCTGA
Gm-R CGAATTGGGGATCTTGAAGTTCCT
GW-attB1 GGGGACAAGTTTGTACAAAAAAGCAGGCT
GW-attB2 GGGGACCACTTTGTACAAGAAAGCTGGGT
1Sequences in capital letters are common for all genes amplified and overlap with the Gm or attB primer sequences. Lower-case letters indicate gene-specific sequences, here PA1520. PCR oligonucleotide sequences for all 27 genes amplified in this study are given in Table 2 (see Additional file 1).
2G, gene specific sequence, here PA1520.
==== Refs
Stover CK Pham XQ Erwin AL Mizoguchi SD Warrener P Hickey MJ Brinkman FSL Hufnagle WO Kowalik DJ Lagrou M Garber RL Goltry L Tolentino E Westbrock-Wadman S Yuan Y Brody LL Coulter SN Folger KR Kas A Larbig K Lim R Spencer D Wong GKS Wu Z Paulsen IT Reizer J M.H. Saier R.E.W. Hancock Lory S Olson MV Complete genome sequence of Pseudomonas aeruginosa, an opportunistic pathogen. Nature 2000 406 959 964 10984043 10.1038/35023079
Goodman AL Lory S Analysis of regulatory networks in Pseudomonas aeruginosa by genomewide transcriptional profiling Curr Opin Microbiol 2004 7 39 44 15036138 10.1016/j.mib.2003.12.009
LaBaer J Qiu Q Anumanthan A Mar W Zuo D Murthy TVS Taycher H Halleck A Hainsworth E Lory S Brizuela L The Pseudomonas aeruginosa PAO1 gene collection Genome Res 2004 14 2190 2200 15489342 10.1101/gr.2482804
Jacobs MA Alwood A Thaipisuttikul I Spencer DH Haugen E Ernst S Will O Kaul R Raymond CK Levy R Chun-Rong L Guenthner D Bovee D Olson MV Manoil C Comprehensive transposon mutant library of Pseudomonas aeruginosa. PNAS 2003 100 14339 14344 14617778 10.1073/pnas.2036282100
Suh SJ Silo-Suh LA Ohman DE Development of tools for the genetic manipulation of Pseudomonas aeruginosa J Microbiol Methods 2004 58 203 212 15234518 10.1016/j.mimet.2004.03.018
Schweizer HP de Lorenzo V Ramos JL Molecular tools for genetic analysis of pseudomonads. The Pseudomonads - Genomics, life style and molecular architecture 2004 I New York, Kluwer Academic/Plenum 317 350
Schweizer HP Allelic exchange in Pseudomonas aeruginosa using novel ColE1-type vectors and a family of cassettes containing a portable oriT and the counter-selectable Bacillus subtilis sacB marker. Mol Microbiol 1992 6 1195 1204 1588818
Stibitz S Use of conditionally counterselectable suicide vectors for allelic exchange. Methods Enzymol 1994 235 458 465 8057916
Hoang TT Karkhoff-Schweizer RR Kutchma AJ Schweizer HP A broad-host-range Flp-FRT recombination system for site-specific excision of chromosomally-located DNA sequences: application for isolation of unmarked Pseudomonas aeruginosa mutants. Gene 1998 212 77 86 9661666 10.1016/S0378-1119(98)00130-9
Quenee L Lamotte D Polack B Combined sacB-based negative selection and cre-lox antibiotic marker recycling for efficient gene deletion in Pseudomonas aeruginosa Biotechniques 2005 38 63 67 15679087
Datsenko KA Wanner BL One-step inactivation of chromosomal genes in Escherichia coli K-12 using PCR products. Proc Natl Acad Sci USA 2000 97 6640 6645 10829079 10.1073/pnas.120163297
Gust B Challis GL Fowler K Kieser T Chater KF PCR-targeted Streptomyces gene replacement identifies a protein domain needed for biosynthesis of the sesquiterpene soil oder geosmin. Proc Natl Acad Sci USA 2003 100 1541 1546 12563033 10.1073/pnas.0337542100
Chuanchuen R Murata T Gotoh N Schweizer HP Substrate-dependent utilization of OprM or OpmH by the Pseudomonas aeruginosa MexJK efflux pump Antimicrob Agents Chemother 2005 49 2133 2136 15855547 10.1128/AAC.49.5.2133-2136.2005
Herring CD Blattner FR Conditional lethal amber mutations in essential Escherichia coli genes. J Bacteriol 2004 186 2673 2681 15090508 10.1128/JB.186.9.2673-2681.2004
Horton RM Cai ZL Ho SN Pease LR Gene splicing by overlap extension: tailor-made genes using the polymerase chain reaction. Biotechniques 1990 8 528 535 2357375
Wolfgang MC Lee VT Gilmore ME Lory S Coordinate regulation of bacterial virulence genes by a novel adenylate cyclase-dependent signaling pathway Dev Cell 2003 4 253 263 12586068 10.1016/S1534-5807(03)00019-4
Choi KH Kumar A Schweizer HP A 10 min method for preparation of highly electrocompetent Pseudomonas aeruginosa cells: application for DNA fragment transfer between chromosomes and plasmid transformation J Microbiol Methods
Hoang TT Schweizer HP Fatty acid biosynthesis in Pseudomonas aeruginosa: cloning and characterization of the fabAB operon encoding b-hydroxydecanoyl-acyl carrier protein dehydratase (FabA) and b-ketoacyl-acyl carrier protein synthase I (FabB). J Bacteriol 1997 179 5326 5332 9286984
van Aalten DMF DiRusso CC Knudsen J Wierenga RK Crystal structure of FadR, a fatty acid-responsive transcription factor with a novel acyl coenzyme A-binding fold. EMBO J 2000 19 5167 5177 11013219 10.1093/emboj/19.19.5167
van Aalten DMF DiRusso CC Knudsen J The structural basis of acyl coenzyme A-dependent regulation of the transcription factor FadR. EMBO J 2001 20 2041 2050 11296236 10.1093/emboj/20.8.2041
Miller JH A Short Course in Bacterial Genetics. 1992 Cold Spring Harbor, N.Y., Cold Spring Harbor Laboratory Press
Sambrook J Russell DW Molecular Cloning 2001 Third Cold Spring Harbor, NY, Cold Spring Harbor Laboratory Press
Liss L New M13 host: DH5aF' competent cells. Focus 1987 9 13
Schweizer HP A method for construction of bacterial hosts for lac-based cloning and expression vectors: a complementation and regulated expression. BioTechniques 1994 17 452 456 7818896
Bernard P Gabant P Bahassi EM Couturier M Positive selection vectors using the F plasmid ccdB killer gene. Gene 1994 148 71 74 7926841 10.1016/0378-1119(94)90235-6
| 15907219 | PMC1173109 | CC BY | 2021-01-04 16:03:41 | no | BMC Microbiol. 2005 May 23; 5:30 | utf-8 | BMC Microbiol | 2,005 | 10.1186/1471-2180-5-30 | oa_comm |
==== Front
BMC MicrobiolBMC Microbiology1471-2180BioMed Central London 1471-2180-5-331592151310.1186/1471-2180-5-33Research ArticleVariability and conservation in hepatitis B virus core protein Chain Benjamin M [email protected] Richard [email protected] Department of Immunology and Molecular Pathology, University College London, 46 Cleveland St., London, W1T 4JF UK2 Department of Infection, University College London, 46 Cleveland St, London, W1T 4JF, UK2005 27 5 2005 5 33 33 2 12 2004 27 5 2005 Copyright © 2005 Chain and Myers; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Hepatitis B core protein (HBVc) has been extensively studied from both a structural and immunological point of view, but the evolutionary forces driving sequence variation within core are incompletely understood.
Results
In this study, the observed variation in HBVc protein sequence has been examined in a collection of a large number of HBVc protein sequences from public sequence repositories. An alignment of several hundred sequences was carried out, and used to analyse the distribution of polymorphisms along the HBVc. Polymorphisms were found at 44 out of 185 amino acid positions analysed and were clustered predominantly in those parts of HBVc forming the outer surface and spike on intact capsid. The relationship between HBVc diversity and HBV genotype was examined. The position of variable amino acids along the sequence was examined in terms of the structural constraints of capsid and envelope assembly, and also in terms of immunological recognition by T and B cells.
Conclusion
Over three quarters of amino acids within the HBVc sequence are non-polymorphic, and variation is focused to a few amino acids. Phylogenetic analysis suggests that core protein specific forces constrain its diversity within the context of overall HBV genome evolution. As a consequence, core protein is not a reliable predictor of virus genotype. The structural requirements of capsid assembly are likely to play a major role in limiting diversity. The phylogenetic analysis further suggests that immunological selection does not play a major role in driving HBVc diversity.
==== Body
Background
The evolutionary pressures that have driven Hepatitis B virus (HBV) variation remain incompletely understood. Using whole HBV genotype sequencing, this variability can usefully be classified into at least eight families (genotypes) with a characteristic geographic distribution (reviewed in [1]). Alternatively, HBV strains can be classified serologically on the basis of antibody to surface antigen (subtypes). These two classifications broadly correlate, although some subtypes appear in more than one genotype. The extent of genetic diversity reflects the evolutionary history of the virus and the rate of genomic mutation, as well as gene specific selection forces. Several models of HBV evolution have been proposed (reviewed in [2,3]) but fundamental parameters, such as the rate of interspecies transmission or the rate of nucleotide mutation (the molecular clock) remain unresolved [3]. Nevertheless, it is generally assumed that the emergence of HBV families may reflect adaptation to the genotype of the prevalent human host population [4].
The clinical course of HBV infection is very variable. Acute infections in adults are usually effectively controlled, but occasionally lead to fulminant hepatitis and death. In a proportion of individuals however, infection leads to chronic viral replication, which can lead to severe liver damage or hepatocellular carcinoma. Host factors including immune status clearly play a major role in determining clinical outcome. For example, perinatal transmission leads to up to 90% chronic carriership, while the figure is less than 10% for adults. However, pathogenicity has also been linked to virus genotype and several different mechanisms have been proposed for this observation [5,6]. Sequence changes occurring during the course of infection (longitudinal diversity) have also been extensively documented. One common example is the introduction of a stop codon in the precore region which results in downregulation of secretion of a soluble form of HBV core protein (HBVe) whose function remains unclear [7,8]. Interestingly, the downregulation of HBVe secretion is often associated with the appearance of anti-HBVe antibodies in serum, suggesting the protein itself may induce some form of immunological tolerance [7,9].
The role of adaptive immunity both in determining the course of HBV infection and in driving HBV evolution is of special interest. Although pre-existing antibody to HBV surface protein (HBVs) (for example in vaccinated individuals) clearly provides strong protection, antibody to this antigen in natural infection is a late event, usually subsequent to effective control for viremia. In contrast, antibody to HBV core (HBVc), although this protein is internal to the virion, occurs early in infection in almost all infected individuals, irrespective of their ability to control viral replication [10]. T helper and cytotoxic responses to several proteins of HBV have also been detected, and the presence of a higher frequency of HBV specific CTL in liver is associated with the ability to control viremia [11]. As might be predicted CTL responses are not limited to structural proteins, but recognise several non-structural viral proteins. Virus specific T cell immune responses are most readily detected in individuals who effectively control viral replication. In chronically infected individuals, these responses are often much more difficult to detect, suggesting that the chronic state is associated with the establishment of some form of immunological tolerance [12].
HBVc antigen is a small protein, whose three-dimensional structure has been determined by X-ray crystallography [13], and whose immunogenicity in terms of both antibody and T cell responses has been studied rather extensively in both mouse and man. It thus represents an ideal starting point for studies aimed at relating antigen structure to immune response. Indeed longitudinal studies on small groups of HBV infected individuals have suggested that variation is more common in B cell and T helper cell epitopes, suggesting a possible immune driven escape mechanism [14]. As a basis for further functional exploration we have documented HBVc variation in detail. In this study we have collected several hundred protein sequences of HBVc from public databases, and have re-examined variation in relation to structure, immunogenicity and genotype.
Results and discussion
742 protein HBVc sequences were retrieved from the NCBI protein database after some manual curation of very short sequence fragments. The mature HBVc protein sequences 1–185 (not including the precore region) were aligned and the number of polymorphisms found at each position (defined as amino acids occurring in more than 1% of the sequences at each site) was determined (see Additional file 1). A plot of the number of variants at each position is shown in fig 1a and the major structural features, including the four alpha helices, the proline rich loop and the C-terminal arm [13] of the protein are shown in fig 1b. Over three quarters (141/185) of positions are completely invariant. Variation clustered within certain regions of the protein, with 18 of the 45 variable amino acids found within positions 59-100.
Sequence variation in core protein may reflect the overall genotypic variation among HBV strains driven by drift or other unknown factors ("hitchhiking"). Alternatively, specific selection pressures may operate on HBVc driving diversity independently. In order to approach this question, the relationship between HBVc variation and HBV genotype was explored. Using text querying of the data base, a subset of 402 sequences were selected which had been assigned genotype A-D (these were the most frequent assigned genotypes within this set) by analysis of whole genome sequence or sequences outside the core region. These 402 core protein amino acid sequences were aligned and compared to each other and to the overall consensus sequence using Protdist, a Phylip program using the Jones-Taylor-Thornton model [15]. The distribution of distances between each sequence and the consensus was then plotted for each viral genotype as given in the database record (fig 2). The distance distribution profiles of the different genotypes were largely overlapping, suggesting that there was no correlation between distance from consensus and genotype.
In an alternative approach, the relationship between all the different core sequences was determined using Fitch-Margoliash least squares analysis, and plotted as an unrooted tree (fig 3). The different genotypes of each virus are colour coded. Although some broad clustering of genotypes was evident, a significant amount of "mixing" can be observed. Similar qualitative results were obtained when phylogeny was determined by Neighbour Joining analysis (using Phylip program Neighbor) or by parsimony (using Phylip program ProtPars).
This phenomenon was analysed in more detail in a subset of 40 full length core protein sequences selected from various sections of the tree illustrated in fig 3 (see Table 1). The phylogenetic relationship between these forty sequences was analysed again, using Neighbour-Joining (a less computation intense method) incorporating a 1000 fold bootstrap replicate in order to validate the tree topology. The results of this analysis are shown in fig 4a. In this smaller subset, genotypes A and D are reasonably well resolved, but genotypes B and C are extensively jumbled. One instance of this is illustrated by two identical sequences (1 and 40 in fig 4) derived from genotypes B and C respectively. The DNA sequences corresponding to each of these forty protein sequences were then obtained from GenBank, and analysed using the same bootstrapped Neighbour-Joining procedure. The tree obtained is shown in fig 4b. As expected, the bootstrap values are in general higher for the DNA tree (since three times as much sequence information is being analysed). The DNA sequences are somewhat more efficient at classifying B and C as separate grouping. In particular the two identical protein sequences (1 and 40 in figure) are well separated and correctly classified by the DNA phylogeny. Overall, however, significant misclassification remains, reflecting either incorrect genotyping, recombination between viral strains [16,17], or simply insufficient discrimination based on these relatively short viral sequences.
Taken together, this data suggested the forces driving the evolution of core were partially independent of the evolutionary forces driving diversification of overall genotype.
The evolutionary pressures on sequence diversity were analysed in more detail by analysing synonymous (S) /nonsynonymous (N) nucleotide variation within the 40 viral sequences shown in Table 1. The overall distribution pattern of synonymous /nonsynonymous mutation rates is shown in fig 5a. The protein shows evidence of strong purifying selection throughout the sequence, with dN/dS ratios (using a sliding window of 36 base pairs) mostly below 0.1, The apparent dS rate was not homogenous along the length of the gene. The sharp decrease in substitution rate from around position 110 most likely reflects the start of the overlapping open reading frame of the polymerase, and this area was therefore excluded from further analysis. The identification of site-specific positive or neutral selection operating within an area of overall purifying selection has received considerable attention [18-21], and a number of methodologies have been adopted. We applied maximum-likelyhood analysis as implemented using Bayes Empirical Bayes method in the software package PAML [22] and compared a number of models of site-specific selection distribution [18]. The best likelihood value was obtained using model 8 (see Methods) which includes a positive selection subset. The posterior probabilities for the positive (ω = 1.38) classes are plotted in fig 5b. Interestingly, only one position showed a probability of >90 of being positively selected, with two more approaching 50% probability. In contrast 133 out of 140 codons showed a probability of >90% of negative purifying selection. Thus there appears to be only very limited amount of positive selection within the HBV core sequence.
The sequence information in Additional file 1/fig 1 was rationalised on the three dimensional structure of the capsid obtained from the Brookhaven Data Base. As evident in fig 6 the variation in sequence is concentrated on the spikes at the outer surface of the capsids. All the amino acids with three or more variants are found on the outer surface of the capsid (fig 6b upper panel) while the internal surface facing the capsid lumen are relatively conserved (fig 6b, lower panel).
A detailed alanine mutagenesis study has been carried out mapping those amino acids critical to proper capsid formation, and/or required for envelopment and virion formation [23]. Mutation of 24 amino acids was found to block capsid formation, virion formation or both. The position of these mutations on the 3D structure is shown in fig 7. The position of this set of mutations is quite widely distributed over the structure, suggesting multiple essential interactions are absolutely required either for proper capsid assembly, or for envelope and virion assembly. However, interestingly, all but one of these 24 amino acids were found to be invariant in the data set analysed in this study. The only exception observed was at position 129, where changing proline to alanine was found to block both capsid and virion formation. Both glutamine and threonine are found in a proportion of virus sequences at this position, and further mutagenesis will be required to clarify the constraints imposed by the requirements of virion formation on the sequence at this particular position. Thus the structural requirements of virion assembly seem to impose a significant restraint on HBVc diversity. However, several positions which were found to tolerate alanine mutagenesis in terms of capsid/virion assembly were nevertheless invariant in the set of sequences examined here. The overall high degree of conservation in HBVc therefore probably reflects the multiple functions required from this protein, including control of intracellular targeting [5], pregenome/DNA polymerase packaging, capsid disassembly and viral maturation.
Pressure by the host immune system is one obvious candidate driving variation in the protein sequence of HBVc. CD8 cytotoxic cells are believed to play a key role in controlling virus replication during HBV infection [24,25]. Several CD8 T cell epitopes have been characterised in detail (e.g. [26-28]) by the use of T cell clones and lines or by elution from HLA [29]. Some of the sequences are shown in fig 7, together with the known variant sequences in the dataset analysed in this study. Although several of the epitopes lie within the more conserved inner region of the capsid, two of the epitopes show substantial polymorphism (fig 8). Interestingly, a previous paper did not find any evidence for emergence of mutations within the major CD8 epitopes during chronic HBV infection [30].
The evidence implicating CD4 T cells in HBV control remains much less clear. Furthermore, although regions containing CD4 epitopes have been described, many of the epitopes are not very well characterised. One putative "immunodominant" CD4 T cell epitope (amino acids 50-69) does contain a number of variable amino acids (fig 9a), and indeed changes in its sequence have been related directly to changes in T cell response in vivo [31]. A second epitope (core region 147-156) identified as a major target in HLADR13 individuals has also been examined in some detail [32]. Interestingly this epitope also shows considerable variation (fig 9a) including a mutation at position 151 shown to be essential for T cell recognition. The epitope also spans the region of a two amino acid insertion which is found exclusively in viruses of genotype A. Further detailed mapping of CD4 T cell recognition sites, in relation to natural sequence variation would be seem to be an area of great interest.
Finally, considerable information has been accumulated on the interaction of antibodies to HBV capsids. As shown in fig 9b[10] the major defined antibody specificities lie on the outside of the capsid structure, particularly at the tip of the spikes and at the junctions between adjacent spikes. These regions do indeed contain the majority of the HBVc sequence variation, although the most variable amino acids themselves have not been identified as known antibody contacts [33]. However, the contribution of anti-HBVc antibody to protection remains unclear, particularly since the capsid in intact virions is presumably largely shielded from antibody by the HBV envelope.
Conclusion
This study makes use of the large number of HBVc sequences now available in public databases to characterise sequence variation in HBVc. One limitation of such an approach is that detailed clinical information associated with infection is not available, and in particular, it is not possible to examine variability in the context of the longitudinal course of an HBV infection. This is likely to be an important factor since mutations are often found to arise late in infection, associated with a variety of clinical outcomes (e.g. [34,35]). In addition few of the available sequences have been checked for their ability to make competent infectious virus, and some sequences may therefore represent non-functional proteins. However, despite these limitations, the data available does allow some general conclusions.
Overall, HBVc contains a large proportion of invariant amino acids, and a strong over representation of synonymous versus non-synonymous mutations at almost every codon. Both features suggest the presence of strong constraining forces on sequence diversity. Virion assembly is likely to provide one major constraining force [23]. As reported previously (e.g. [14]) sequence diversity appears to be clustered, and mapped predominantly to the spike and external surface of the capsid. These positions may allow greater flexibility in terms of virion assembly.
One significant consequence of the strong purifying selection is that protein sequence is a poor predictor of genotype for this gene. DNA sequence which reflects predominantly synonymous mutations, is a better discriminator, particularly in resolving genotypes B and C. Longer sequence analysis, however, is clearly necessary to obtain reliable genotyping information.
The putative role of immune selection in driving HBV core diversity is much more unclear. Direct evidence for positive selection, at least using the analysis presented here, identifies only a single amino acid (position 74 at the tip of the viral spike) as showing evidence for positive selection of diversity. Nevertheless, it is clear that several polymorphic positions lie within T or B cell epitopes. Hence, while the overall effect of immune selection on HBV sequence diversity may be small, sequence diversity may have a significant effect on the immune response at an individual level. The data analysis given here will help inform further analysis of the HBV-specific immune response. The combination of T cell and antibody recognition studies with directed mutagenesis of HBVc should determine more precisely the relationship between structure, immunity and pathogenicity.
Methods
Human HBVc sequences were retrieved from the NCBI protein sequence database [36], limiting the search to organism = Hepatitis B virus and searching for core protein. Additional classification into genotypes A-D was done using the text search tool to look for "genotype X". A proportion of hits were verified by manual inspection.
The initial 780 hits were aligned using the EMMA program on EMBOSS (a version of Clustal)(see[37] using the BLOSUM 62 similarity matrix. The alignment was further refined by manual inspection using the sequence editor Bioedit, and very short or badly aligned sequences removed. The frequency of amino acids at each position was determined using the EMBOSS program PROPHECY. The matrix observed was converted into polymorphism frequency by setting a cut-off of 1% frequency at each position.
A phylogenetic tree of the HBVc sequences was created using the Phylip program Kitsch [38]), which uses a Fitch-Margoliash criterion based on a distance matrix obtained using the Phylip program Protdist. The tree was displayed using Treeview [39], copied in Adobe Illustrator and color coded according to genotype. Because this method is extremely processor intensive (the best tree is analysed at each iteration) it was not possible to bootstrap. Analyses of the same data were also done using nearest neighbor analysis (using the Phylip program Neighbor) and parsimony using the EMBOSS (loc cit) program EPROTPARS. Although the fine details of the trees varied between methods the overall qualitative conclusion were the same. In order to further validate the conclusions of the phylogeny, 40 sequences (shown in Table 1) chosen manually to cover the major branches of the tree shown in fig 3 were reanalysed using the Nearest Neighbour with bootstrap option (1000 bootstraps) of ClustalW [40]. The consensus tree set was plotted in Treeview and coloured in Illustrator. Similar analysis was carried out on an alignment of the DNA sequences corresponding to each protein sequence.
The analysis of synonymous/nonsynonymous mutations rates was carried out initially using the program DNASP3.0 [41] (using the Nei/ Gojobori algorithm) with a 36 base pair sliding window shifted by 9 nucleotides. A more detailed analysis at individual codons was carried out using the program PAML version 3.14 (using maximum likelihood Bayes Empirical Bayes inference, as described in [20]). Analysis was carried out using a variety of selection models, but the output represented in fig 5 used model 8 [22]. The models assume that the selection pressure (measured as ω) operating at each codon can fall within a range of different classes. Model 8 assumes a distribution of negative selection values (for all of which ω <1), or a positive selection class with ω = 1.38. This model was found to give the best likelihood estimate. The program then calculates the posterior probability (p value) that each codon within a sequence falls within a particular class.
The crystal structure of HBVc was retrieved as a pdb file from the Brookhaven database, and displayed and coloured using RasMol software (version 2.7.1.1 for Windows). Figures 6 and 7 show the structure of four identical monomers, to illustrate the spikes and their interaction, while figs 8 and 9 show a single monomer for clarity.
Abbreviations
Hepatitis B virus HBV; Hepatitis B core protein HBVc; Hepatitis B surface protein HBVs
Authors' contributions
RM provided bioinformatics support and expertise, and carried out the phylogenetic analysis shown in fig 4. BMC initiated the project and was responsible for the text, and the data and analysis shown in the other figures.
Supplementary Material
Additional File 1
Amino acid polymorphisms along the HBVc sequence. Table containing all the polymorphic amino acid residues found at each position along the 742 HBV sequences analysed.
Click here for file
Acknowledgements
I am grateful for much useful discussion with many colleagues at UCL, in particular to Paul Kellam for help with the bioinformatics, to Ziheng Yang for initial help setting up PAML and to Richard Tedder, Antonio Bertoletti, Mala Maini and Nikolai Naoumov for advice on HBV. I am grateful to Dr. Volker Bruss (University of Goettingen) for his help and advice. I am also very grateful to the staff at the UK HGMP Resource Centre for a lot of help and patience with running the various Bioinformatic programs.
Figures and Tables
Figure 1 Sequence variation along the HBVc sequence. a) The number of polymorphisms (variants occurring in more than 1 % sequences examined) found at each position of the HBVc sequence. See additional file 1 for full data. b) Major features of secondary structure along HBVc [13]. Blue : α-helix Green : Proline rich loop; Red : C-terminal arm.
Figure 2 Relationship between HBVc sequence and genotype. The 403 sequences from viruses of known genotype were aligned and compared to the consensus. The distance of each sequence from the consensus was calculated using maximum likely-hood model (Jones-Taylor-Thornton). The frequency distribution of distance from consensus was then plotted for each genotype A-D.
Figure 3 Analysis of the relationships between HBVc sequences. All the sequences were classified and plotted as an unrooted tree using the Fitsch Margoliash criterion (Kitsch, see Materials and Methods). Where known the genotype is indicated by colour coding (Yellow = A, Green = B, Blue = C, Red = D). Sequences of unknown genotype are in black.
Figure 4 Analysis of 40 protein and DNA HBVc sequences. The 40 sequences detailed in Table 1 were analysed using Neighbor Joining analysis of both protein (panel a) and DNA (panel b) and plotted using TreeView. The bootstrap values (as percentage) are shown in smaller font. The accession number corresponding to each numbered sequence is shown in Table 1. The genotype is indicated by colour coding (Yellow = A, Green = B, Blue = C, Red = D).
Figure 5 Synonymous/nonsynonymous mutation rates and selection in HBVc. Panel a shows the distribution of synonymous (dS) and non-synonymous (dN) substitutions (the number of such substations per site), and the ratio dN/dS along the sequence of HBVc. Gaps indicate dS = 0. Panel b shows the posterior probability p+ that dN/dS>1 for each position of HBVc, as calculated by PAML. The probability that dN/dS<1 (purifying selection) is not plotted for clarity but is given by (1- p+).
Figure 6 Sequence variation in the context of capsid structure. The crystal structure formed by four HBVc subunits was displayed and coloured using RasMol software. Positions containing 2 polymorphisms are coloured blue, 3 polymorphisms are coloured orange, and 4 or above are coloured red. Grey amino acids are invariant. a) The structure is displayed in ribbon form, showing a vertical section though the capsid, with two spikes projecting upwards, and the internal face of the capsid shown at the bottom of the picture. b) The structure is displayed in space fill. Upper Panel The structure is displayed so that the spikes and outward surface of the capsid are shown towards the viewer, and only the outer surface of the capsid is visible. Lower Panel The structure is rotated by 180 degrees so only the lower (inner) face of the capsid is visible.
Figure 7 Structural constraints and HBV diversity. The crystal structure formed by four HBVc subunits was displayed and coloured using RasMol software. The position of the amino acid identified as essential for virion formation (violet) or for both capsid and virion assembly (green) [23] are shown. The rest of the colour coding is as shown in fig 6.
Figure 8 Variation within CD8 T cell epitopes of HBVc. Five of the best defined class I T cell epitopes from HBVc (for references see text) are shown together with alternative amino acids found at each position. The position of the epitopes (green) within the HBVc three dimensional structure is shown in the right hand panel. The rest of the colour coding is as shown in fig 6.
Figure 9 Variation with CD4 and antibody epitopes of HBVc. a) Two of the best defined CD4 epitopes within HBVc (taken from [31,32]) are shown together with alternative amino acids found at each position. The position of the epitope 50#150;69 is shown in the context of the HBVc three dimensional structure above(in green). The rest of the colour coding is as shown in fig 6. Epitope 147#150;156 is not shown since this region of HBVc was excluded in the crystallographic study. b) The best defined antibody epitopes (taken from [33]) are shown (in green) in the context of the HBVc three dimensional structure above. The rest of the colour coding is as shown in fig 6.
Table 1 Accession numbers and genotype for HBV sequences analysed in fig 4
Number Accession number Genotype
Protein DNA
1. AAK81691 AY040627 C
2. AAO41301 AY167091 C
3. AAP06648 AY206392 C
4. AAL31832 AF324119 C
5. AAP06544 AY206375 B
6. AAP06549 AY206376 C
7. AAL31776 AF323466 B
8. AAL31802 AF324088 B
9. AAP06642 AY206391 B
10. AAP79869 AY233296 D
11. AAP31176 AY269059 D
12. AAR19326 AY230115 D
13. BAC57440 AB090269 D
14. AAL31837 AF324124 A
15. AAF24670 AF121240 D
16. BAD02318 AB126581 D
17. AAL31826 AF324112 D
18. AAP31178 AY269061 D
19. BAA85376 AB033559 D
20. AAP31169 AY269052 D
21. BAC92696 AB106885 B
22. BAC92693 AB106884 B
23. AAR19322 AY230111 A
24. AAL31839 AF324126 A
25. AAP79778 AY233283 A
26. AAL31785 AF324071 A
27. AAP79724 AY233275 A
28. AAP79715 AY233274 A
29. AAP79729 AY233276 A
30. AAP79736 AY233277 A
31. AAL31856 AF324143 A
32. AAG49707 AF223961 C
33. AAP06636 AY206390 B
34. AAF24738 AF121250 B
35. BAA32843 AB014363 C
36. AAP31199 AY269084 C
37. AAL31815 AF324101 C
38. AAL31819 AF324105 C
39. AAL31781 AF324066 B
40. AAF24705 AF121245 B
==== Refs
Kidd-Ljunggren K Miyakawa Y Kidd AH Genetic variability in hepatitis B viruses J Gen Virol 2002 83 1267 1280 12029141
Robertson BH Margolis HS Primate hepatitis B viruses - genetic diversity, geography and evolution Rev Med Virol 2002 12 133 141 11987138 10.1002/rmv.348
Bollyky PL Holmes EC Reconstructing the complex evolutionary history of hepatitis B virus J Mol Evol 1999 49 130 141 10368441
Jazayeri M Basuni AA Sran N Gish R Cooksley G Locarnini S Carman WF HBV core sequence: definition of genotype-specific variability and correlation with geographical origin J Viral Hepat 2004 11 488 501 15500549 10.1111/j.1365-2893.2004.00534.x
Jazayeri MS Dornan ES Boner W Fattovich G Hadziyannis S Carman WF Intracellular distribution of hepatitis B virus core protein expressed in vitro depends on the sequence of the isolate and the serologic pattern J Infect Dis 2004 189 1634 1645 15116300 10.1086/382190
Torre F Naoumov NV Clinical implications of mutations in the hepatitis B virus genome Eur J Clin Invest 1998 28 604 614 9767354 10.1046/j.1365-2362.1998.00346.x
Carman WF Jacyna MR Hadziyannis S Karayiannis P McGarvey MJ Makris A Thomas HC Mutation preventing formation of hepatitis B e antigen in patients with chronic hepatitis B infection Lancet 1989 2 588 591 2570285 10.1016/S0140-6736(89)90713-7
Tong SP Diot C Gripon P Li J Vitvitski L Trepo C Guguen-Guillouzo C In vitro replication competence of a cloned hepatitis B virus variant with a nonsense mutation in the distal pre-C region Virology 1991 181 733 737 2014646 10.1016/0042-6822(91)90908-T
Chan HL Hussain M Lok AS Different hepatitis B virus genotypes are associated with different mutations in the core promoter and precore regions during hepatitis B e antigen seroconversion Hepatology 1999 29 976 984 10051506 10.1002/hep.510290352
Vanlandschoot P Cao T Leroux-Roels G The nucleocapsid of the hepatitis B virus: a remarkable immunogenic structure Antiviral Res 2003 60 67 74 14638400 10.1016/j.antiviral.2003.08.011
Maini MK Boni C Ogg GS King AS Reignat S Lee CK Larrubia JR Webster GJ McMichael AJ Ferrari C Williams R Vergani D Bertoletti A Direct ex vivo analysis of hepatitis B virus-specific CD8(+) T cells associated with the control of infection Gastroentorology 1999 117 1386 1396
Kakimi K Isogawa M Chung J Sette A Chisari FV Immunogenicity and tolerogenicity of hepatitis B virus structural and nonstructural proteins: implications for immunotherapy of persistent viral infections J Virol 2002 76 8609 8620 12163580 10.1128/JVI.76.17.8609-8620.2002
Wynne SA Crowther RA Leslie AG The crystal structure of the human hepatitis B virus capsid Mol Cell 1999 3 771 780 10394365 10.1016/S1097-2765(01)80009-5
Carman WF Boner W Fattovich G Colman K Dornan ES Thursz M Hadziyannis S Hepatitis B virus core protein mutations are concentrated in B cell epitopes in progressive disease and in T helper cell epitopes during clinical remission J Infect Dis 1997 175 1093 1100 9129071
Jones DT Taylor WR Thornton JM The rapid generation of mutation data matrices from protein sequences Comput Appl Biosci 1992 8 275 282 1633570
Sugauchi F Orito E Ichida T Kato H Sakugawa H Kakumu S Ishida T Chutaputti A Lai CL Ueda R Miyakawa Y Mizokami M Hepatitis B virus of genotype B with or without recombination with genotype C over the precore region plus the core gene J Virol 2002 76 5985 5992 12021331 10.1128/JVI.76.12.5985-5992.2002
Bollyky PL Rambaut A Harvey PH Holmes EC Recombination between sequences of hepatitis B virus from different genotypes J Mol Evol 1996 42 97 102 8919861
Yang Z Nielsen R Codon-substitution models for detecting molecular adaptation at individual sites along specific lineages Mol Biol Evol 2002 19 908 917 12032247
Wong WS Yang Z Goldman N Nielsen R Accuracy and power of statistical methods for detecting adaptive evolution in protein coding sequences and for identifying positively selected sites Genetics 2004 168 1041 1051 15514074 10.1534/genetics.104.031153
Yang Z Wong WS Nielsen R Bayes Empirical Bayes Inference of Amino Acid Sites under Positive Selection Mol Biol Evol 2005
Suzuki Y Gojobori T A method for detecting positive selection at single amino acid sites Mol Biol Evol 1999 16 1315 1328 10563013
Yang Z PAML: a program package for phylogenetic analysis by maximum likelihood Comput Appl Biosci 1997 13 555 556 9367129
Ponsel D Bruss V Mapping of amino acid side chains on the surface of hepatitis B virus capsids required for envelopment and virion formation J Virol 2003 77 416 422 12477846 10.1128/JVI.77.1.416-422.2003
Maini MK Bertoletti A How can the cellular immune response control hepatitis B virus replication? J Viral Hepat 2000 7 321 326 10971819 10.1046/j.1365-2893.2000.00234.x
Thimme R Wieland S Steiger C Ghrayeb J Reimann KA Purcell RH Chisari FV CD8(+) T cells mediate viral clearance and disease pathogenesis during acute hepatitis B virus infection J Virol 2003 77 68 76 12477811 10.1128/JVI.77.1.68-76.2003
Webster GJ Reignat S Brown D Ogg GS Jones L Seneviratne SL Williams R Dusheiko G Bertoletti A Longitudinal analysis of CD8+ T cells specific for structural and nonstructural hepatitis B virus proteins in patients with chronic hepatitis B: implications for immunotherapy J Virol 2004 78 5707 5719 15140968 10.1128/JVI.78.11.5707-5719.2004
Sobao Y Sugi K Tomiyama H Saito S Fujiyama S Morimoto M Hasuike S Tsubouchi H Tanaka K Takiguch M Identification of hepatitis B virus-specific CTL epitopes presented by HLA-A*2402, the most common HLA class I allele in East Asia J Hepatol 2001 34 922 929 11451178 10.1016/S0168-8278(01)00048-4
Missale G Redeker A Person J Fowler P Guilhot S Schlicht HJ Ferrari C Chisari FV HLA-A31- and HLA-Aw68-restricted cytotoxic T cell responses to a single hepatitis B virus nucleocapsid epitope during acute viral hepatitis J Exp Med 1993 177 751 762 7679709 10.1084/jem.177.3.751
Tsai SL Chen MH Yeh CT Chu CM Lin AN Chiou FH Chang TH Liaw YF Purification and characterization of a naturally processed hepatitis B virus peptide recognized by CD8+ cytotoxic T lymphocytes J Clin Invest 1996 97 577 584 8567982
Rehermann B Pasquinelli C Mosier SM Chisari FV Hepatitis B virus (HBV) sequence variation of cytotoxic T lymphocyte epitopes is not common in patients with chronic HBV infection J Clin Invest 1995 96 1527 1534 7544809
Torre F Cramp M Owsianka A Dornan E Marsden H Carman W Williams R Naoumov NV Direct evidence that naturally occurring mutations within hepatitis B core epitope alter CD4+ T-cell reactivity J Med Virol 2004 72 370 376 14748060 10.1002/jmv.20016
Cao T Desombere I Vanlandschoot P Sallberg M Leroux-Roels G Characterization of HLA DR13-restricted CD4(+) T cell epitopes of hepatitis B core antigen associated with self-limited, acute hepatitis B J Gen Virol 2002 83 3023 3033 12466479
Belnap DM Watts NR Conway JF Cheng N Stahl SJ Wingfield PT Steven AC Diversity of core antigen epitopes of hepatitis B virus Proc Natl Acad Sci U S A 2003 100 10884 10889 12954985 10.1073/pnas.1834404100
Naoumov NV Thomas MG Mason AL Chokshi S Bodicky CJ Farzaneh F Williams R Perrillo RP Genomic variations in the hepatitis B core gene: a possible factor influencing response to interferon alfa treatment Gastroentorology 1995 108 505 514
Chuang WL Omata M Ehata T Yokosuka O Ito Y Imazeki F Lu SN Chang WY Ohto M Precore mutations and core clustering mutations in chronic hepatitis B virus infection Gastroentorology 1993 104 263 271
NCBI Protein Sequence Database
Clustal 2005
Kitsch 2005
Treeview 2005
Thompson JD Higgins DG Gibson TJ CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice Nucleic Acids Res 1994 22 4673 4680 7984417
Rozas J Rozas R DnaSP version 3: an integrated program for molecular population genetics and molecular evolution analysis Bioinformatics 1999 15 174 175 10089204 10.1093/bioinformatics/15.2.174
| 15921513 | PMC1173110 | CC BY | 2021-01-04 16:03:39 | no | BMC Microbiol. 2005 May 27; 5:33 | utf-8 | BMC Microbiol | 2,005 | 10.1186/1471-2180-5-33 | oa_comm |
==== Front
BMC NeurosciBMC Neuroscience1471-2202BioMed Central London 1471-2202-6-441598517910.1186/1471-2202-6-44Research ArticleGenes involved in Drosophila glutamate receptor expression and localization Liebl Faith LW [email protected] David E [email protected] Dept. of Biological Sciences, University of Illinois at Chicago, Chicago, USA2 Dept. of Cell and Structural Biology, Univ. of Illinois at Urbana-Champaign, Urbana, USA2005 28 6 2005 6 44 44 9 5 2005 28 6 2005 Copyright © 2005 Liebl and Featherstone; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
A clear picture of the mechanisms controlling glutamate receptor expression, localization, and stability remains elusive, possibly due to an incomplete understanding of the proteins involved. We screened transposon mutants generated by the ongoing Drosophila Gene Disruption Project in an effort to identify the different types of genes required for glutamate receptor cluster development.
Results
To enrich for non-silent insertions with severe disruptions in glutamate receptor clustering, we identified and focused on homozygous lethal mutants in a collection of 2185 BG and KG transposon mutants generated by the BDGP Gene Disruption Project. 202 lethal mutant lines were individually dissected to expose glutamatergic neuromuscular junctions, stained using antibodies that recognize neuronal membrane and the glutamate receptor subunit GluRIIA, and viewed using laser-scanning confocal microscopy. We identified 57 mutants with qualitative differences in GluRIIA expression and/or localization. 84% of mutants showed loss of receptors and/or clusters; 16% of mutants showed an increase in receptors. Insertion loci encode a variety of protein types, including cytoskeleton proteins and regulators, kinases, phosphatases, ubiquitin ligases, mucins, cell adhesion proteins, transporters, proteins controlling gene expression and protein translation, and proteins of unknown/novel function. Expression pattern analyses and complementation tests, however, suggest that any single mutant – even if a mutant gene is uniquely tagged – must be interpreted with caution until the mutation is validated genetically and phenotypically.
Conclusion
Our study identified 57 transposon mutants with qualitative differences in glutamate receptor expression and localization. Despite transposon tagging of every insertion locus, extensive validation is needed before one can have confidence in the role of any individual gene. Alternatively, one can focus on the types of genes identified, rather than the identities of individual genes. This genomic approach, which circumvents many technical caveats in favor of a wider perspective, suggests that glutamate receptor cluster formation involves many cellular processes, including: 1) cell adhesion and signaling, 2) extensive and relatively specific regulation of gene expression and RNA, 3) the actin and microtubule cytoskeletons, and 4) many novel/unexplored processes, such as those involving mucin/polycystin-like proteins and proteins of unknown function.
==== Body
Background
The vast majority of fast synaptic transmission in the mammalian central nervous system is glutamatergic. Proper expression, localization, and regulation of glutamate receptors are critical for brain development and plasticity. Not surprisingly, the molecular mechanisms controlling glutamate receptor expression, localization, and stability are of great interest. The most common recent approach to understanding these mechanisms has been biochemical: Proteins are identified based on a biochemical interaction with a glutamate receptor subunit. This approach has identified a number of important candidates, some of which have been subsequently shown to play important roles in glutamate receptor trafficking and stability at the PSD (for review see [1,2]).
An alternative approach is forward genetics: Mutant animals are screened for alterations in glutamate receptor localization. Perhaps the most well-known glutamate receptor trafficking protein identified via genetics is stargazin, which is disrupted in stargazer mutant mice [3]. The identification of stargazin was serendipitous; mammalian genetic screens are unfortunately still relatively time-consuming and expensive (though this may change as RNAi techniques advance). Most forward genetic screens glutamate receptor mutants have used C. elegans. Studies using C. elegans have highlighted the importance of ubiquitination, CamKII, and PDZ proteins in controlling glutamate receptor number, and identified a novel protein required for nematode glutamate receptor function [4-7]. Unfortunately, glutamatergic synapses in C. elegans are accessible for electrophysiology only with great difficulty. The subunit composition of C. elegans receptors in vivo has also not yet been determined, which hinders the study of subunit-specific trafficking mechanisms.
Drosophila are not only amenable to powerful genetics, but also contain glutamatergic neuromuscular junctions (NMJs) that are individually identifiable and accessible throughout development to high-resolution electrophysiological and microscopic techniques. These techniques have revealed a significant amount of information concerning this popular model synapse, including the exact subunit composition of glutamate receptors in vivo. Drosophila NMJs contain two subtypes of postsynaptic glutamate receptor, which are molecularly, pharmacologically, and spatially distinct [8-11]. The 'A' receptor subtype contains the subunit GluRIIA, in combination with subunits GluRIIC, GluRIID, and GluRIIE. The 'B' receptor subtype contains the subunit GluRIIB, in combination with the subunits GluRIIC, GluRIID, and GluRIIE. Both receptor subtypes are most similar in sequence to mammalian kainate receptors. The Drosophila genome also encodes receptor subunits with high similarity to mammalian AMPA, delta, and NMDA receptor subunits, but these proteins are not found postsynaptically in the NMJ. Virtually nothing is known about the molecular mechanisms that control Drosophila glutamate receptor expression, localization, and stability.
To determine the molecular mechanisms controlling Drosophila glutamate receptor expression, localization, and stability, we are screening transposon insertion mutants generated by the Berkeley Drosophila Gene Disruption Project [12]. This mutant collection contains insertions in over 40% of the entire genome, and the insertion site for almost every mutant has already been identified by inverse PCR. With the addition of transposon insertions from other collections, it is likely that Drosophilists will have access to insertion mutants of almost every gene in the fly genome within a few years. Theoretically, one could quickly and efficiently identify the complete list of genes required for any particular process simply by examining a non-redundant set of mutants for a phenotype of interest. We are testing this idea and using this approach to define the broad categories of genes required for glutamate receptor cluster formation. We identified 57 lethal mutants with qualitatively abnormal glutamate receptor clusters. Here, we present this list and discuss the types of genes that are, and are not, represented. Because of the high prevalence of background mutations even in transposon mutant collections, the role of individual genes must be extensively confirmed before a role for any particular protein is assumed. However, this problem may be circumvented, and perhaps more insight gained, by focusing on the types of genes identified rather than the identity of individual genes. We do so here.
Results
We sought to identify Drosophila mutants with abnormal glutamate receptor cluster development. Elimination of Drosophila NMJ glutamate receptors results in paralysis and embryonic lethality [9]. Mutations that reduce (but do not eliminate) NMJ glutamate receptors allow hatching, but typically cause larval or pupal lethality [8-10]. Any effective screen for glutamate receptor cluster formation mutants must therefore include examination of homozygous lethal mutants. However, proper examination of glutamate receptor clusters in embryos and larvae requires technically challenging dissection techniques and time-consuming confocal microscopy. Therefore, we sought to minimize examination of mutants that do not have glutamate receptor cluster defects. To do this, we made the assumption, based on the studies cited above, that mutants with severe defects in glutamate receptor cluster formation are more likely to be homozygous lethal. Thus, the first step in our screen for mutants with reduced or eliminated glutamate receptors was identification of recessive lethal transposon mutants (e.g. insertions lines with no homozygous viable adults). We concentrated on the collection of GT1 and SuPor-P insertion mutants, since these transposons were engineered for maximal gene disruption [13,14]. Of 2185 mutants (representing insertions in approximately 16% of the entire genome), 220 insertion lines contained lethal mutations. Because a prerequisite for NMJ glutamate cluster formation is development of neuromusculature, we examined dechorionated embryos from each of the 220 stocks to ensure that homozygous mutants developed into 'morphologically mature' late stage embryos typical of wildtype animals 16–17 hr after egg laying, AEL, which is when NMJs begin to form [15-18]. Morphological maturity was based on the presence of characteristics typical of late stage 17: clear segmentation, mouthhooks, condensed CNS, malphigian tubules, and visible trachea. 205 of 220 (93%) of the homozygous lethal mutants formed morphologically mature embryos. 202 of these mutants were rebalanced using a GFP-tagged balancer chromosome for unambiguous identification of homozygous mutant animals. We were unable to rebalance 3 mutant lines using chromosome-appropriate GFP-tagged balancers, possibly because the insertion mutant chromosome and balancer chromosome both contained lethal mutations that fail to complement. We then verified that all 202 GFP-balanced stocks did indeed carry recessive lethal mutations and determined the latest stage to which homozygous (non GFP) embryos and larvae lived.
For each of the 202 balanced lines, several (typically 5–10) homozygous mutant animals, along with control heterozygous siblings, were manually dissected at the latest viable stage to expose NMJs on ventral longitudinal muscles, then fixed and stained using anti-HRP antibodies that recognize all neuronal membrane (including peripheral axons and NMJs) and anti-GluRIIA antibodies. After dissection, fixation, and staining, each of the 202 rebalanced mutant lines was examined for changes in NMJ morphology and glutamate receptor expression using laser-scanning confocal fluorescent microscopy. 57 of the 202 rebalanced lethal mutants (28%) displayed consistent (most NMJs in several animals) defects in glutamate receptor expression without severe presynaptic morphological abnormalities (e.g. 57 mutants were identified in which NMJs formed, but glutamate receptor clusters were altered). Examples of some of these phenotypes, from both embryonic and larval NMJs, are shown in Fig. 1.
All phenotypes could be classified into one of two broad categories: 1) loss of glutamate receptors (fewer glutamate receptor clusters or smaller individual clusters), or 2) gain of glutamate receptors (more clusters or larger clusters). We relied on cluster size and number because cluster size and number measurements (compared to fluorescence intensity measurements) avoid a requirement for fluorescence intensity calibration or problems associated with potential differences in background immunofluorescence between genotypes. Assuming constant receptor density, cluster size should be directly proportional to the number of clustered receptors. In support of this assumption, immunoreactive cluster sizes correlate well with high-resolution patch-clamp electrophysiological measurements between genotypes [11,19,20] and throughout embryonic/larval NMJ development (Featherstone, unpublished observations).
Most (84%) of the mutants with disruptions in glutamate receptor clusters showed a qualitative loss in receptors. Severe loss of GluRIIA was always associated with embryonic/L1 lethality. One example is P{SUPor-P}KG00333, which shows a complete loss of A-type receptors despite the presence of morphologically normal presynaptic terminals (Fig. 1A, left). Some mutants with loss of receptors survived until pupation. An example of a third instar viable mutant, P{SUPor-P} ChroKG03258, with reduced GluRIIA is shown in Fig. 1B (middle column).
A minority (16%) of third instar viable mutants showed a qualitative increase in GluRIIA immunoreactivity. An example of one of these mutants, P{SUPor-P} vriKG01220, is shown in Fig. 1B (right column). Except for P{SUPor-P}KG00212, all of the mutants that displayed an increase in GluRIIA immunoreactivity were viable as third instar larvae and also displayed an increase in the number of presynaptic boutons. This presynaptic phenotype is consistent with previous Drosophila studies showing that overexpression of postsynaptic GluRIIA causes presynaptic overgrowth [21]. BG and KG transposons are designed to generate loss of function mutations. Therefore, the isolation of mutants with increased receptor cluster size suggests that receptor insertion and clustering per se are not rate-limiting. There are molecular mechanisms, revealed by our screen, that actively restrain the number of synaptic glutamate receptors.
For all of the mutants identified in our screen, the Gene Disruption Project has precisely determined the genomic insertion site of the transposon using inverse PCR. In the vast majority of cases, inverse PCR results were consistent with a unique insertion, and in most cases the flanking genomic sequence revealed that the insertion was in an annotated gene. For each of the mutants identified in our screen, we used the BDGDP P-screen database and/or BLAST searches with flanking genomic sequence from iPCR results to identify which gene was mutated by the inserted P-element. Putative functions were assigned to each of these genes based on previous publications, FlyBase annotations, and/or Genbank BLAST searches. We binned each of the insertion site genes into one of the following functional categories: 1) extracellular matrix proteins (mucins), 2) cell adhesion proteins 3) cytoskeleton proteins, cytoskeletal regulators, and adaptor proteins, 4) kinases and phosphatases, 5) ubiqitination proteins (ubiquitin ligases), 6) transporters/pumps, 7) proteins involved in gene expression and protein translation, 8) enzymes, and 9) proteins of unknown/novel function. These categories, and the relative number of proteins in each category, are illustrated by Figure 2. All categories shown in Figure 2 were represented by at least two mutant genes.
Table 1 contains the complete list of all mutants identified in our screen, listed by functional category. For each mutant, Table 1 indicates whether the phenotype was loss (down arrow) or increase (up arrow) in postsynaptic glutamate receptors. Table 1 also lists the Drosophila gene in which each transposon is inserted, and the mouse homolog of each of those genes (identified by BLASTP against the mouse genome refseq protein database; ).
A definitive test of whether any particular gene is required for glutamate receptor cluster development requires precise excision of each P-element insertion, or transgenic rescue, followed by re-examination of the NMJ at the same developmental stage – a task which is not practical on a genomic scale. However, we performed two broad types of checks to identify potential caveats in our results: expression analysis and complementation tests for lethality.
Drosophila glutamate receptors are expressed in neurons and muscles. Thus, any gene required for expression and/or localization of glutamate receptors should be expressed in neurons and/or muscles. The Drosophila gene expression database (accessed at: ) describes expression patterns of approximately 3300 different Drosophila genes (~24% of the genome), as determined by embryonic in situ cDNA hybridization [22]. Of these 3300 genes, which presumably represent a random 'sampling' of the genome, 2350 (71%) are expressed in the nervous system and/or body wall muscles. The gene expression database contains data for 28 (49%) of the genes identified in our study. 24 (86%) of these genes identified by our screen are expressed in the nervous or muscular systems. 4 (14%) of the genes identified in our screen are annotated as not detectably expressed in the nervous or muscular systems. Thus, most (86%) of the genes identified in our screen have expression patterns consistent with the conclusion that these genes are important for glutamate receptor cluster development, but we did not identify neuronal and muscle genes significantly above the level expected by a random sampling of the genome – possibly because the fraction of genes expressed in neurons and muscles (71%) is quite high to begin with. There may also be cell non autonomous roles for some genes with regard to receptor expression and/or localization.
Although all of the mutants identified in our screens displayed a receptor phenotype, and all of the mutants contain a unique P-element insertion, an important genetic caveat is that the receptor phenotype may not actually be caused by the transposon insertion. For example, the P-element mobilizations that generated each of the P-element alleles for the gene disruption project may have also created second-site mutations in an unknown locus. Spontaneous mutations can also be easily stabilized and propagated in a stock carrying a balanced lethal mutant chromosome such as those screened here. To estimate the frequency of background mutations in this transposon mutant collection, we performed complementation tests to determine whether the P-element insertions failed to complement lethal alleles of the same insertion locus. Of the 57 mutants identified in our screen, 20 were tested for complementation to deficiencies that remove the insertion site. Ten (50%) of the complementation tests failed, suggesting that lethality in half of the mutants may be caused by a mutation other than the P-element insertion. These results are consistent with those from a related screen for presynaptic morphology mutants (Liebl FLW, Werner KM, McCabe BD, Featherstone DE: A Genome-Wide P-element screen for Drosophila synaptogenesis mutants. Manuscript in preparation), which included complementation tests to over 80 genes. Complementation did not appear to be biased for any particular type of gene (in this or the related Liebl et al study). We did not systematically test for complementation of the receptor cluster phenotypes.
Discussion
In an effort to identify new genes required for glutamate receptor cluster development, we screened lethal transposon insertion mutants for alterations in postsynaptic glutamate receptor clusters. 202 lethal insertion lines, representing insertions in ~1.4% of the genome, were manually dissected and glutamate receptor clusters were examined using immunocytochemistry and confocal microscopy. This screen identified 57 mutations in 56 different loci. Transposon mutageneses are becoming increasingly popular, because a transposon insertion simultaneously mutates and 'tags' a gene. An assumption of all transposon mutagenesis (and subsequent screens) is that the insertion locus is responsible for any observed phenotype. Expression analysis showed that the expression pattern of insertion loci identified in our screen is broadly consistent with that expected from genes involved in glutamate receptor cluster development, but also not compellingly different (86% vs. 71%) from that expected from a random sampling of the genome. Furthermore, complementation tests suggest that approximately one-half of the lethality observed in our screen was not due to disruption of the insertion locus. Thus, it is impossible to definitively say which particular genes are important without extensive validation of each candidate. And even with extensive validation sufficient to confirm that a particular locus is involved, it is difficult to know whether a gene's role in receptor cluster formation is indirect with regard to glutamate receptor cluster formation (i.e. whether a gene product regulates another protein which in turn clusters receptors). Nevertheless, one cannot discount our results without also casting aside the fact that decades of forward genetic screens have successfully identified many genes critical for many different processes [23]. But how does one decide which screen 'hits' to trust, and is there any way to usefully interpret results of forward genetic screens?
Should we exclude from consideration all mutants in which lethality was complemented (and conversely accept all mutants in which lethality failed to be complemented)? This depends on the degree of coupling between two different phenotypes: lethality and abnormal glutamate receptor cluster development. To enrich for mutants with receptor cluster defects, we examined only homozygous lethal mutants, on the assumption that GluRIIA cluster defects and lethality are strongly linked. Indeed, all of the mutants showing severe loss of GluRIIA were embryonic/first instar lethal. Nevertheless, this assumption probably does not hold for all mutants. At the time this screen was initiated, it was assumed that all Drosophila NMJ glutamate receptors contained the subunit GluRIIA, and that the viability of GluRIIA null mutants was due to substitution by the alternate subunit GluRIIB [24]. Thus, the presence and localization of GluRIIA was considered an accurate marker for all NMJ receptors. Subsequently, we and others have determined that the Drosophila NMJ contains two independently assembled and localized subtypes of postsynaptic glutamate receptors: A-type receptors, that contain the subunit GluRIIA (plus GluRIIC, GluRIID, and GluRIIE, but not GluRIIB), and B-type receptors, which contain the subunit GluRIIB (plus GluRIIC, GluRIID, and GluRIIE, but not GluRIIA) [8-10]. GluRIIA therefore serves as a tag for only one-half to two-thirds (depending on developmental stage; Featherstone, unpublished) of fly NMJ glutamate receptors. Complete elimination of A-type receptors does not result in lethality [24,25]. Conversely, lethality can obviously be caused by many defects other than loss of NMJ glutamate receptors. Since viability and glutamate receptor cluster development may be only loosely coupled, complementation tests for lethality indicate relatively little about the reliability with which our screen identified genes required for proper glutamate receptor cluster formation (although these complementation results do give important insights into the properties of this mutant collection, and transposon mutageneses in general). Similarly, the large fraction of genes expressed in the neuromusculature makes it difficult to judge, based on expression, whether any particular gene has simply been randomly selected. Thus, we are left with uncertainty regarding any particular gene until that gene's role in synaptogenesis can be extensively validated – a prospect that is not practical on a genomic scale. However, the sequencing of several metazoan genomes, along with the realization that the function of homologous proteins tends to be conserved across genomes, opens the possibility of another approach, as demonstrated in our study: 'functional category analysis.'
Functional category analysis involves screening a non-redundant collection of mutants for the phenotype of interest, assigning putative functions bioinformatically, and categorizing the 'hits' by function. The goal of this approach is not to generate a definitive list of individual proteins involved in a process, but to gain insight into the types and relative numbers of proteins required. All of the categories shown in Figure 2, for example, are represented by several mutants. Therefore, even with a 50% accuracy rate (which would be a worst case estimate; the real accuracy is probably substantially higher – see below), the gene function categories are likely to be correctly identified. Functional category analysis recognizes that not all hits will be valid, that not all genes will play roles specific to a particular process, and that many proteins are only indirectly required. Functional category analysis reveals unexplored areas of relevant biology and provides a broad roadmap for further study. For example: instead of studying the individual genes identified in Table 1 (which is arguably a hit-and-miss endeavor unlikely to shed much global insight into the process), we plan to focus research toward understanding how RNA regulation and regulated translation are involved in glutamate receptor cluster formation. Similarly, we are directing efforts toward understanding the interactions of receptors with the actin and microtubule-based cytoskeletons. Preliminary results suggest that this approach is insightful and effective [20]; Liebl, Karr, & Featherstone, unpublished observations).
What percentage of the genome is involved in glutamate receptor cluster development? Our results allow this question to be addressed (at least with regard to the Drosophila NMJ). If glutamate receptor cluster development and lethality are completely uncoupled, then our results imply that approximately 28% (57/202) of the entire Drosophila genome is required for glutamate receptor cluster development. Depending on the percentage of insertions that were too hypomorphic to show qualitatively detectable phenotypes via immunocytochemistry, that percentage could be higher. Glutamate receptor cluster formation and lethality, however, are not unrelated phenotypes. Therefore, 28% is likely to be a gross overestimate. Complete loss of Drosophila NMJ glutamate receptors results in paralysis and embryonic lethality [9], and mutations that reduce (but do not eliminate) NMJ glutamate receptors allow hatching, but typically cause larval or pupal lethality [8-10]. In the present study, all severe loss of function phenotypes were associated with embryonic/early larval lethality. If all GluRIIA cluster mutants are lethal, then mutants with normal glutamate receptor clusters would have been eliminated in the selection for lethality early in the screen (indeed, this was the rationale for this step). In this case, our results suggest that approximately 2.6% (57/2185) of the genome is required for glutamate receptor cluster formation. This estimate, however, is also likely to be flawed; although severe disruptions in glutamate receptor cluster formation cause lethality, not all lethality is likely due to disruptions in glutamate receptor cluster formation. Mutations that trigger loss of GluRIIA are not necessarily lethal [24,25]. Lethality and GluRIIA cluster phenotypes are not absolutely coupled, and therefore 2.6% is likely too low of an estimate.
Given the uncertainties above, we can say only that somewhere between 2.6 and 28% of the fly genome (360–3900 genes) is required for NMJ glutamate receptor cluster formation. This is a wide range, which in any case represents a surprisingly large number of genes. Is this reasonable? Do all of these genes represent specific machinery for glutamate receptor cluster expression and clustering? To answer these questions, it is helpful to consider the types of genes identified in the screen. As noted earlier, the role of each individual gene needs to be validated before placing too much emphasis on any particular protein's role. But a general discussion of the genes implicated is helpful for evaluation of the general results.
In support of the idea that our screen correctly identified genes required for glutamate receptor cluster formation, some of the types of genes identified in our screen have been previously identified as important for postsynaptic development. Polo, for example, was identified in our screen, and mammalian polo-like kinases are receiving increasing attention as important players in synapse development [26]. We also identified several other kinases and phosphatases. Activation of the mitogen activated protein kinase (MAPK) pathway facilitates AMPAR surface expression [27,28], and interaction of AMPAR GluR2 subunits with GRIP and PICK1 is dependent upon the phosphorylation of the GluR2 subunit [29,30]. Our screen also isolated mutants in two different ubiquitin ligases. Consistent with this, ubiquitination is known to regulate glutamate receptor number and synapse development [6,31]. Our screen identified a fly neuroligin family member, and mammalian neuroligins were recently implicated in postsynaptic development [32].
One of the largest groups of genes identified in our screen encodes proteins that comprise or regulate the actin and/or microtubule cytoskeletons. Glutamate receptors, like many other proteins, are thought to be transported along microtubules, and anchored to the synaptic actin cytoskeleton [33-35]. In support of this, we've recently found that GluRIIA-containing receptors are specifically linked to the actin cytoskeleton via the 4.1 homolog coracle, which interacts directly with GluRIIA [20]. We've also found that regulation of synaptic microtubules affects fly NMJ glutamate receptor cluster development (see below). The cytoskeleton might not only be important for receptor protein localization; trafficking and localization of synapse-specific mRNAs (see below) probably also relies on the cytoskeleton. Consistent with this, untranslated regions of GluRIIA appear to be required for proper synaptic receptor localization in the fly NMJ (Karr & Featherstone, unpublished).
Other types of genes identified by the screen are consistent with what one might expect. For example, many of the genes identified in our screen are involved in gene expression or protein translation. Mutation of a transcription factor or component of the translation machinery would be expected to disrupt many downstream things, including production of the cellular machinery required for postsynaptic development. Since our screen specifically excluded mutants which did not develop to the later stages of embryogenesis, and which did not form neuromuscular junctions, our screen may have highlighted components of pathways specific for a subset of cell differentiation steps that includes glutamate receptor cluster formation. Some of this machinery is possibly localized to the synapse. Drosophila GluRIIA mRNA is localized to the NMJ and locally translated [36]. Mammalian glutamate receptors may also rely on local translation and editing for surface expression [37-39]. Preliminary results also suggest that Drosophila NMJ glutamate receptor cluster formation depends on a burst of receptor subunit transcription that follows contact between pre and postsynaptice cells (Karr & Featherstone, unpublished).
Our screen also revealed some important surprises. For example, we identified insertions in two different putative mucin-encoding genes. Mammalian mucins are secreted glycoproteins that are widely implicated in tumor cell adhesion but have no previously identified role in the nervous system [40]. Are these false positives or important insights into postsynaptic development? Interestingly, the 'mucin' genes identified in our screen are also similar to the C. elegans polycystin gene lov-1, which is localized to the ciliated sensory endings of dendrites required for male mating behavior, where it may be critical for regulating localization of other transmembrane proteins [41,42]. Our screen also identified the exocyst protein sec-8. Sec-8 has recently been implicated in NMDA receptor trafficking but has not been shown to regulate non-NMDA receptor localization, and the mechanism by which it (and other sec proteins) functions remains unclear [43,44]. We are particularly interested in validating and studying the most surprising candidates from out screen, and have done so for sec 8. This work (Liebl FLW, Chen K, Karr J, Sheng Q, Featherstone DE: Altered Synapse Development in Drosophila Sec 8 Mutants. Manuscript in preparation, and Liebl & Featherstone, unpublished) reveals that Drosophila sec 8 regulates the synaptic microtubule cytoskeleton to facilitate transmembrane protein localization (Thus the inclusion of sec 8 as a 'cytoskeletal regulator' in Table 1). Thus, even the surprises identified by our screen are, so far, apparently reasonable. But note that even validated candidates, such as sec 8, may not work directly or specifically on glutamate receptors.
Approximately 12% of the genes identified in our screen encode proteins with unknown or novel function. A better understanding of these genes is important for understanding both those protein families and synaptogenesis – assuming these proteins are really regulators of receptor cluster formation. Even with a 50% success rate in identifying genes involved in receptor cluster formation – and the arguments and data above suggest the success rate was much higher – it is clear that novel genes encode a large fraction of proteins required for glutamate receptor cluster development in the fly NMJ. Therefore, major unexplored areas apparently may exist with regard to postsynaptic development. Interestingly, our screen did not isolate any PDZ-domain or MAGUK proteins, which are widely regarded as essential trafficking and scaffold proteins at mammalian glutamatergic synapses [45]. However, this may not reflect a complete lack of importance for these proteins in fly NMJ glutamate receptor localization. Drosophila discs-large (DLG) is the sole fly representative of the mammalian DLG/SAP 97/SAP102/PSD-95 protein family; DLG is important for formation of fly NMJ glutamate receptor clusters that contain the subunit GluRIIB, but not those containing GluRIIA [11]. Because we screened only for alterations in GluRIIA immunoreactivity, we would not have isolated DLG mutants. However, our results do support the idea that PDZ proteins are not predominant components of the glutamate receptor localization/stabilization machinery in Drosophila NMJs.
Many of the genes implicated by our screen probably do not work directly or specifically. Kinases only have to regulate something that in turn regulates receptor cluster formation. Transcription and translation factors probably control expression of multiple proteins required for PSD formation. Given the fact that many proteins definitively required for glutamate receptor cluster formation may not work directly, it is reasonable that a large percentage of the genome appears to be required. In other words, it is not difficult to identify proteins required for receptor cluster development, and we feel that the demonstration of such by itself does not give real insight into receptor cluster formation. An alternative approach, which we call 'functional category analysis' and introduce here, is to focus on the types of genes identified rather than the identities of individual genes, in an effort to gain larger insights into the entire process. Subsequent work can then be directed at investigating the processes represented by these gene types, rather than validation of individual genes that may or may not work directly or be applicable to other synapses and organisms. For example, many microtubule and actin regulators were identified in our screen. The target for these proteins, obviously, is likely to be cytoskeletal proteins instead of receptors. But their identification tells which types of cytoskeleton might be important for glutamate receptor cluster formation. Using these clues, we subsequently determined that microtubules are important for fly glutamate receptor trafficking (Liebl FLW, Chen K, Karr J, Sheng Q, Featherstone DE: Altered Synapse Development in Drosophila Sec 8 Mutants. Manuscript in preparation, and Liebl & Featherstone, unpublished), and that A-type receptors are anchored via the 4.1 protein coracle to postsynaptic actin [20].
Conclusion
We identified 57 transposon mutants with qualitative differences in glutamate receptor expression and localization. Mutant gene identities need to be validated despite the fact that mutant genes are tagged. Focus on the types of genes identified ('functional category analysis') may provide more useful insight into the process of glutamate receptor cluster formation, compared to focus on individual genes. Our results suggest that glutamate receptor cluster formation involves cell adhesion and signaling, extensive and relatively specific regulation of gene expression and RNA regulation, the actin and microtubule cytoskeletons, and many novel/unexplored processes such as those involving mucin/polycystin-like proteins and proteins of unknown function.
Methods
NMJ staining and microscopy was performed as previously described [9,19]. Briefly, animals were dissected and fixed for 30–60 min in Bouin's fixative. Late stage embryos were dechorionated in bleach and then manually devitellinated and dissected. Mouse monoclonal anti-GluRIIA ('8B4D2' Iowa Developmental Studies Hybridoma Bank, Iowa City, IA) was used at 1:100. Fluorescently conjugated anti-HRP (Jackson Immunoresearch Labs, West Grove, PA) was used at 1:100. Goat anti-rabbit or goat anti-mouse fluorescent (FITC or TRITC) secondary antibodies (Jackson Immunoresearch Labs, West Grove, PA) were used at 1:400. Confocal images were obtained using an Olympus FV500 laser-scanning confocal microscope. Image analysis and quantification was performed using ImageJ software.
Complementation analysis was performed by crossing GFP-balanced P-element mutant stocks to a balanced stock containing a deficiency that removes the insertion site. The F1 generation of each cross was examined for the presence or absence of adult flies carrying neither balancer chromosome. Thus, P-element insertion chromosomes were tested for their capacity to complement the viability of the lethal mutations in the gene carrying the P-element insertion.
All P-element stocks were obtained from Bloomington Stock Center flystocks.bio.indiana.edu. 'Control' genotypes in all experiments are w1118.
Authors' contributions
FLWL performed most of the immunocytochemistry and microscopy. Analysis was jointly performed by FLWL and DEF.
Acknowledgements
Thanks to Qi Sheng and Pei-San Ng for technical assistance. This work was supported by NIH/NINDS R01 NS045628 to D.F
Figures and Tables
Figure 1 Example phenotypes identified in the screen. A: NMJs on embryonic ventral longitudinal muscles 7, 6, and 13, visualized using anti-HRP antibodies (which stain all neuronal membrane) and anti-GluRIIA antibodies (which stain postsynaptic glutamate receptors). HRP immunoreactivity is red; GluRIIA immunoreactivity is green. In wildtype NMJs (A, left column), GluRIIA immunoreactivity appears as puncta, representing clusters of postsynaptic glutamate receptors. In homozygous P{SUPor-P}KG00333 mutants (A, right column), GluRIIA immunoreactivity is eliminated. B: NMJs on third instar larval longitudinal muscles 7 and 6, visualized using anti-HRP and anti-GluRIIA antibodies. In wildtype NMJs (B. left column), GluRIIA immunoreactivity appears as large blobs, representing developmentally merged puncta, at sites of innervation. In homozygous P{SUPor-P}Chro [KG03258] mutants (B, middle column), synaptic GluRIIA immunoreactivity is dramatically decreased, although extrasynaptic receptors remain prominent. In contrast, synaptic GluRIIA immunoreactivity is dramatically increased in homozygous P{SUPor-P}vri [KG01220] mutants (B, right column). Scale bars: 10 micrometers.
Figure 2 Pie chart showing the different types of proteins encoded by the insertion loci identified in the screen. The size of the pie wedge represents the proportion of genes of each type identified. Functional categories were based on previously published studies of the Drosophila gene and/or sequence similarity to functionally annotated mouse genes. Table 1 contains a complete list of the genes represented in this chart.
Table 1 Genes affected in glutamate receptor expression/localization mutants. Complete list of the mutants identified in the screen. Table 1 lists all of the mutants identified in the screen, organized by putative function of the protein encoded by the gene in which the transposon is inserted. The qualitative glutamate receptor phenotype in the Drosophila mutants is indicated by an arrow pointing upwards (for an increase in immunocytochemically detectable GluRIIA) or downwards (for a decrease in immunocytochemically detectable GluRIIA). The third column lists the Drosophila gene that is mutated by the transposon insertion; superscript letters represent complementation test results: 'f' = transposon insertion failed to complement a deficiency covering the region, and 'c' = insertion complemented a deficiency. Note that the confirmed presence of a background lethal mutation (denoted by 'c') does not indicate whether the NMJ phenotype is also complemented. The fourth column lists the mouse homolog, as determined by best BLAST match to an annotated gene in the mus musculus refseq database.
Allele Phenotype Mutant gene Mouse protein
Extracellular matrix
P{SUPor-P}CG18819 [KG01657] ↓ CG32814 mucin
P{SUPor-P}CG14713 [KG05924] ↓ CG14713 mucin
Cell adhesion
P{SUPor-P}mys [KG02930] ↓ mys beta integrin
P{SUPor-P}KG00212 ↑ Nrt neuroligin
Cytoskeleton, cytoskeletal regulators, and adaptor proteins
P{SUPor-P}CG10540 [KG02261] ↓ CG10540
c
actin capping protein
P{SUPor-P}KG01009 ↓ Tkr actinfilin
P{SUPor-P}pnut [KG00478] ↑ pnut
f
septin
P{SUPor-P}didum [KG04384] ↓ didum
c
myosin V
P{SUPor-P}neb [KG05913] ↓ neb
f
kinesin
P{SUPor-P}KG05547 ↓ Cdic dynein intermediate chain
P{SUPor-P}CG2095 [KG02723] ↓ CG2095
f
sec 8
P{SUPor-P}lap [KG06751] ↓ lap synaptosomal protein 91
P{SUPor-P}noodle [KG03815] ↓ CG3210 dynamin
Kinases & Phosphatases
P{SUPor-P}KG06341 ↓ KP78a
f
MAP/MT affin.-reg. kinase
P{SUPor-P}SNF4Aγ [KG00325] ↓ SNF4γ AMP-activated kinase
P{SUPor-P}trbl [KG02308] ↓ trbl AMP-activated kinase
P{SUPor-P}KG04591 ↑ CG15072
c
SNF-like kinase
P{SUPor-P}KG02006 ↓ Rheb RAS-homolog
P{SUPor-P}polo [16-1] ↓ polo polo-like kinase
P{SUPor-P}KG00853 ↓ CG10082
c
inositol hexaphosphate kin.
P{SUPor-P}CG32666 [KG03058] ↓ CG32666 serine-threonine kinase
P{SUPor-P}KG00564 ↓ ia2 rec. tyrosine phosphatase
P{SUPor-P}l(1)G0003 [KG02485] ↓ l(1)G003
f
Rab coupling protein
Ubiquitination
P{SUPor-P}Cbl [KG03080] ↓ Cbl E3 ubiquitin ligase
P{GT1}sina [BG02648] ↓ sina sina (ubiquitin ligase)
Transporters
P{SUPor-P}CG5802 [KG01634] ↑ CG5802
f
UDP-galactose translocator
P{SUPor-P}KG02272 ↓ CG8029
f
lysosomal H+ ATPase
P{SUPor-P}Vha44 [KG00915] ↓ Vha44 vacuolar H+ ATPase
Unknown
P{SUPor-P}oaf [KG03408] ↑ oaf
c
D130038B21 RIKEN cDNA
P{SUPor-P}KG03591 ↓ CG32345 hyp. Protein XP_355833
P{SUPor-P}cmp44E [KG03925] ↓ cmp44E
c
'similar to KIAA0953'
P{SUPor-P}CG2185 [KG02712] ↑ CG2185 calcium binding P22
P{SUPor-P}KG00333 ↓ CG15358 cd209e antigen
P{SUPor-P}CG31694 [KG04350] ↑ CG31694
f
interferon development reg.
P{GT1}l(2)35Di [BG02008] ↓ l(2)35Di
c
[none]
P{SUPor-P}KG06339 ↓ [none]
Enzymes
P{SUPor-P}CG4825 [KG06018] ↓ CG4825 phosphatidylserine synth.
P{SUPor-P}TppII [KG03294] ↓ TppII
c
tripeptidyl peptidase II
Gene expression & Translation
P{SUPor-P}KG02920 ↓ hsrω
f
ladybird homeobox-1-like
P{SUPor-P}KG02514 ↓ hbn aristaless-rel. homeobox
P{SUPor-P}KG03852 ↓ Ntf-2 nuclear transport factor-2
P{SUPor-P}Trn-SR [KG04870] ↓ CG2848 transportin 3
P{GT1}CG10689 [BG01776] ↓ CG10689 DEAH box polypeptide
P{SUPor-P}CG11107 [KG02727] ↓ CG11107 DEAH box polypeptide
P{SUPor-P}pnt [KG04968] ↓ pnt avian leukemia oncogene
P{SUPor-P}KG00625 ↓ CG18591 snrpE
P{SUPor-P}RpL3 [KG05440] ↓ RpL3
f
ribosomal protein L3
P{SUPor-P}KG03101 ↓ Ef2b translation elong. factor 2
P{SUPor-P}crp [KG00953] ↓ crp transcription factor AP-4
P{SUPor-P}E2f [KG03332] ↑ E2f E2f transcription factor
P{SUPor-P}armi [KG04664] ↓ armi
c
Moloney leukemia virus 10
P{SUPor-P}vri [KG01220] ↑ vri interleukin3 reg. nuc. factor
P{SUPor-P}Kr-h1 [KG00354] ↓ Kr-h zinc finger protein
P{SUPor-P}Bgb [KG03779] ↓ Bgb core binding factor beta
P{SUPor-P}KG06256 ↓ Chro
c
Domino (histone deactyl.)
P{SUPor-P}Chro [KG03258] ↓ Chro Domino (histone deactyl.)
P{SUPor-P}EcR [KG04522] ↓ EcR nuclear receptor 1, group H
==== Refs
DeLaRue SA Henley JM Proteins involved in the trafficking and functional synaptic expression of AMPA and KA receptors TheScientificWorldJOURNAL 2002 2 461 482 12806030 10.1100/tsw.2002.97
Bredt DS Nicoll RA AMPA receptor trafficking at excitatory synapses Neuron 2003 40 361 379 14556714 10.1016/S0896-6273(03)00640-8
Chen L Chetkovich DM Petralia RS Sweeney NT Kawasaki Y Wenthold RJ Bredt DS Nicoll RA Stargazing regulates synaptic targeting of AMPA receptors by two distinct mechanisms Nature 2000 408 936 943 11140673 10.1038/35050030
Rongo C Whitfield CW Rodal A Kim SK Kaplan JM LIN-10 is a shared component of the polarized protein localization pathways in neurons and epithelia Cell 1998 94 751 759 9753322 10.1016/S0092-8674(00)81734-1
Rongo C Kaplan JM CaMKII regulates the density of central glutamatergic synapses in vivo Nature 1999 402 195 199 10647013 10.1038/46065
Burbea M Dreier L Dittman JS Grunwald ME Kaplan JM Ubiquitin and AP180 regulate the abundance of GLR-1 glutamate receptors at postsynaptic elements in C. elegans Neuron 2002 35 107 120 12123612 10.1016/S0896-6273(02)00749-3
Zheng Y Mellem JE Brockie PJ Madsen DM Maricq AV SOL-1 is a CUB-domain protein required for GLR-1 glutamate receptor function in C. elegans Nature 2004 427 451 457 14749834 10.1038/nature02244
Marrus SB Portman SL Allen MJ Moffat KG DiAntonio A Differential localization of glutamate receptor subunits at the Drosophila neuromuscular junction J Neurosci 2004 24 1406 1415 14960613 10.1523/JNEUROSCI.1575-03.2004
Featherstone DE Rushton E Rohrbough J Liebl F Sheng Q Rodesch CK Broadie K An Essential Drosophila Glutamate Receptor Subunit That Functions in Both Central Neuropil and Neuromuscular Junction Journal of Neuroscience 2005
Qin G Schwarz TL Kittel RJ Schmid A Rasse TM Kappei D Ponimaskin E Heckmann M Sigrist SJ Four subunits are essential for expressing the synaptic glutamate receptor at neuromuscular junctions in Drosophila Journal of neuroscience 2005
Chen K Featherstone DE Discs-large (DLG) is clustered by presynaptic innervation and regulates postsynaptic glutamate receptor subunit composition in Drosophila BMC Biol 2005 3 1 15638945 10.1186/1741-7007-3-1
Bellen HJ Levis RW Liao G He Y Carlson JW Tsang G Evans-Holm M Hiesinger PR Schulze KL Rubin GM Hoskins RA Spradling AC The BDGP gene disruption project: single transposon insertions associated with 40% of Drosophila genes Genetics 2004 167 761 781 15238527 10.1534/genetics.104.026427
Roseman RR Johnson EA Rodesch CK Bjerke M Nagoshi RN Geyer PK A P element containing suppressor of hairy-wing binding regions has novel properties for mutagenesis in Drosophila melanogaster Genetics 1995 141 1061 1074 8582613
Lukacsovich T Asztalos Z Awano W Baba K Kondo S Niwa S Yamamoto D Dual-tagging gene trap of novel genes in Drosophila melanogaster Genetics 2001 157 727 742 11156992
Broadie KS Bate M Development of the embryonic neuromuscular synapse of Drosophila melanogaster J Neurosci 1993 13 144 166 8093713
Yoshihara M Rheuben MB Kidokoro Y Transition from growth cone to functional motor nerve terminal in Drosophila embryos J Neurosci 1997 17 8408 8426 9334414
Rheuben MB Yoshihara M Kidokoro Y Ultrastructural correlates of neuromuscular junction development Int Rev Neurobiol 1999 43 69 92 10218155
Featherstone DE Broadie K Surprises from Drosophila: genetic mechanisms of synaptic development and plasticity Brain Res Bull 2000 53 501 511 11165785 10.1016/S0361-9230(00)00383-X
Featherstone DE Rushton E Broadie K Developmental regulation of glutamate receptor field size by nonvesicular glutamate release Nat Neurosci 2002 5 141 146 11753421 10.1038/nn789
Chen K Merino C Sigrist SJ Featherstone DE The 4.1 protein coracle mediates subunit-selective anchoring of Drosophila glutamate receptors to the postsynaptic actin cytoskeleton Journal of Neuroscience (in press) 2005
Sigrist SJ Thiel PR Reiff DF Schuster CM The postsynaptic glutamate receptor subunit DGluR-IIA mediates long-term plasticity in Drosophila J Neurosci 2002 22 7362 7372 12196557
Tomancak P Beaton A Weiszmann R Kwan E Shu S Lewis SE Richards S Ashburner M Hartenstein V Celniker SE Rubin GM Systematic determination of patterns of gene expression during Drosophila embryogenesis Genome Biol 2002 3 RESEARCH0088 12537577 10.1186/gb-2002-3-12-research0088
St Johnston D The art and design of genetic screens: Drosophila melanogaster Nat Rev Genet 2002 3 176 188 11972155 10.1038/nrg751
DiAntonio A Petersen SA Heckmann M Goodman CS Glutamate receptor expression regulates quantal size and quantal content at the Drosophila neuromuscular junction J Neurosci 1999 19 3023 3032 10191319
Petersen SA Fetter RD Noordermeer JN Goodman CS DiAntonio A Genetic analysis of glutamate receptors in Drosophila reveals a retrograde signal regulating presynaptic transmitter release Neuron 1997 19 1237 1248 9427247 10.1016/S0896-6273(00)80415-8
Seeburg DP Pak D Sheng M Polo-like kinases in the nervous system Oncogene 2005 24 292 298 15640845 10.1038/sj.onc.1208277
Krapivinsky G Medina I Krapivinsky L Gapon S Clapham DE SynGAP-MUPP1-CaMKII synaptic complexes regulate p38 MAP kinase activity and NMDA receptor-dependent synaptic AMPA receptor potentiation Neuron 2004 43 563 574 15312654 10.1016/j.neuron.2004.08.003
Huang CC You JL Wu MY Hsu KS Rap1-induced p38 mitogen-activated protein kinase activation facilitates AMPA receptor trafficking via the GDI.Rab5 complex. Potential role in (S)-3,5-dihydroxyphenylglycene-induced long term depression J Biol Chem 2004 279 12286 12292 14709549 10.1074/jbc.M312868200
McDonald BJ Chung HJ Huganir RL Identification of protein kinase C phosphorylation sites within the AMPA receptor GluR2 subunit Neuropharmacology 2001 41 672 679 11640921 10.1016/S0028-3908(01)00129-0
Matsuda S Launey T Mikawa S Hirai H Disruption of AMPA receptor GluR2 clusters following long-term depression induction in cerebellar Purkinje neurons Embo J 2000 19 2765 2774 10856222 10.1093/emboj/19.12.2765
Ehlers MD Activity level controls postsynaptic composition and signaling via the ubiquitin-proteasome system Nat Neurosci 2003 6 231 242 12577062 10.1038/nn1013
Chih B Engelman H Scheiffele P Control of excitatory and inhibitory synapse formation by neuroligins Science 2005 307 1324 1328 15681343 10.1126/science.1107470
Whatley VJ Harris RA The cytoskeleton and neurotransmitter receptors Int Rev Neurobiol 1996 39 113 143 8894846
Rubio ME Selective targeting of glutamate receptors in neurons Mol Neurobiol 2000 21 1 19 11327147 10.1385/MN:21:1-2:001
Matus A Postsynaptic actin and neuronal plasticity Curr Opin Neurobiol 1999 9 561 565 10508747 10.1016/S0959-4388(99)00018-5
Sigrist SJ Thiel PR Reiff DF Lachance PE Lasko P Schuster CM Postsynaptic translation affects the efficacy and morphology of neuromuscular junctions Nature 2000 405 1062 1065 10890448 10.1038/35016598
Tang SJ Schuman EM Protein synthesis in the dendrite Philos Trans R Soc Lond B Biol Sci 2002 357 521 529 12028789 10.1098/rstb.2001.0887
Greger IH Khatri L Ziff EB RNA editing at arg607 controls AMPA receptor exit from the endoplasmic reticulum Neuron 2002 34 759 772 12062022 10.1016/S0896-6273(02)00693-1
Greenough WT Klintsova AY Irwin SA Galvez R Bates KE Weiler IJ Synaptic regulation of protein synthesis and the fragile X protein Proc Natl Acad Sci U S A 2001 98 7101 7106 11416194 10.1073/pnas.141145998
Aksoy N Akinci OF Mucin macromolecules in normal, adenomatous, and carcinomatous colon: evidence for the neotransformation Macromol Biosci 2004 4 483 496 15468240 10.1002/mabi.200300099
Hu J Barr MM ATP-2 interacts with the PLAT domain of LOV-1 and is involved in Caenorhabditis elegans polycystin signaling Mol Biol Cell 2005 16 458 469 15563610 10.1091/mbc.E04-09-0851
Jauregui AR Barr MM Functional characterization of the C. elegans nephrocystins NPHP-1 and NPHP-4 and their role in cilia and male sensory behaviors Exp Cell Res 2005 305 333 342 15817158 10.1016/j.yexcr.2005.01.008
Sans N Prybylowski K Petralia RS Chang K Wang YX Racca C Vicini S Wenthold RJ NMDA receptor trafficking through an interaction between PDZ proteins and the exocyst complex Nat Cell Biol 2003 5 520 530 12738960 10.1038/ncb990
Hoogenraad CC Sheng M The return of the exocyst Nat Cell Biol 2003 5 493 495 12776120 10.1038/ncb0603-493
Kim E Sheng M PDZ domain proteins of synapses Nat Rev Neurosci 2004 5 771 781 15378037 10.1038/nrn1517
| 15985179 | PMC1173111 | CC BY | 2021-01-04 16:03:47 | no | BMC Neurosci. 2005 Jun 28; 6:44 | utf-8 | BMC Neurosci | 2,005 | 10.1186/1471-2202-6-44 | oa_comm |
==== Front
BMC PediatrBMC Pediatrics1471-2431BioMed Central London 1471-2431-5-111590721410.1186/1471-2431-5-11Research ArticleAge related clinical features of childhood Coeliac disease in Australia Stone Monique L [email protected] Timothy D [email protected] Kylie E [email protected] Vivienne H [email protected] Andrew S [email protected] Departments of General Paediatrics, Sydney Children's Hospital, High St Randwick NSW 2031 Australia2 Gastroenterology, Sydney Children's Hospital, High St Randwick NSW 2031 Australia3 Nutrition & Dietetics, Sydney Children's Hospital, High St Randwick NSW 2031 Australia4 Department of Pathology, Anatomical Pathologist, Department of Patholgy, SEALS Sydney Children's Hospital, Randwick 2031 Australia5 School of Women's and Children's Health, University of New South Wales, Sydney, Australia2005 21 5 2005 5 11 11 2 2 2005 21 5 2005 Copyright © 2005 Stone et al; licensee BioMed Central Ltd.2005Stone et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
To describe the presenting clinical features of coeliac disease in a single paediatric centre, and to determine if the presenting features vary with age.
Methods
A review was conducted of children who had been referred with clinical suspicion of coeliac disease to the paediatric gastroenterology department of a tertiary paediatric hospital in Sydney, Australia. Coeliac disease was defined using standard histological criteria. Medical records were reviewed retrospectively.
Results
Clinical data were available for 74 cases of proven coeliac disease. Only 9% of patients were less than 2 years of age at diagnosis. Pre-school children (age <5 years) presented with different symptoms to school children (age ≥ 5 years). The most common presenting features in younger children were diarrhoea, irritability and weight loss. However, in older children, abdominal pain was the most common presenting feature.
Conclusion
We found a significant difference in the clinical features of coeliac disease in pre-school compared to school age children.
==== Body
Background
There has been an apparent increase in the incidence of coeliac disease (coeliac disease) over the past 30 years [1]. For instance, the number of reported cases in the Netherlands increased from 0.18 per 1000 live births from 1975–1990, to 0.54 per 1000 live births 1993–1994 [1]. There is also increasing recognition that symptomatic coeliac disease may be the tip of the iceberg, with many more asymptomatic cases in the community [2-4].
It is unclear whether the changing prevalence of reported cases of coeliac disease is due to a real increase in the number of cases, enhanced awareness of disease or more reliable serological testing. Dietary changes, such as earlier introduction of gluten, have been suggested as contributing to the changing presentation of coeliac disease in some populations [5,6]. Breast feeding, in particular breast feeding after the introduction of gluten, is protective against the development of coeliac disease [7].
There are few data on the clinical features, incidence and prevalence of coeliac disease in Australian populations. In a population based screening study from a rural community of Western Australia, 10/3001 were positive for anti-endomysial antibodies. This community was of predominantly Anglo-Celtic origin [4]. Australians come from diverse ethnic backgrounds, thus the prevalence reported in this community cannot be generalised to the Australian population.
The primary aim of this study was to describe the clinical features of children diagnosed with coeliac disease at one tertiary paediatric centre in Australia. Our secondary aim was to determine the presentation patterns of coeliac disease in the local community at different ages.
Methods
A retrospective cross sectional study was conducted at Sydney Children's Hospital, one of two tertiary referral paediatric hospitals in Sydney, Australia. The study population consisted of infants and children who had been referred to the Gastroenterology Department at Sydney Children's Hospital for investigation of possible coeliac disease between 1997 and 2002. Subjects were identified through records kept by the Departments of Nutrition and Dietetics, Gastroenterology, and Anatomical Pathology. Ethics approval was granted from the South East Sydney Area Health Service Research Ethics Committee-Eastern Section.
Cases and clinical features
Cases were defined as those with histological confirmation of coeliac disease [8]. A single pathologist reviewed all slides. Where the histological diagnosis of coeliac disease was uncertain, clinical and laboratory features, including response to gluten free diet, were included.
The clinical details of each patient were extracted from the medical records retrospectively. Features of interest included presenting symptoms as well as the symptoms and signs elicited during consultation with a paediatric gastroenterologist. Weight and height measurements at diagnosis were documented. SD (standard deviation) scores were calculated using reference data [9]. The ethnic mix for the reference population of children admitted to Sydney Children's Hospital was described using child's country of birth.
Laboratory investigations
The results of haemoglobin, iron studies, serum IgA, anti-gliadin (AGA) and anti-endomysial antibodies (EMA) were obtained from each patient's medical records. AGA and EMA tests had been performed at SEALS (South Eastern Area Laboratory Service, Kogarah, NSW). The SEALS laboratories measure EMA using indirect immunoflurescence, anti-human FITC conjugate IgA against monkey distal oesophagus. The slides are prepared by MeDICa (Encinitas, CA 92024). A value of 10 is used for as positive cut off. AGA were measured by commercial immunoassay kits (Analytica Ltd, Castle Hill NSW Australia). The cut off values used for children were IgA>25 and IgG >46.
Low haemoglobin values for age were defined as those less than the reference range for age used by the hospital laboratory (SEALS). The low end of the normal range for children 6 months to 2 years was 104 g/L; 2–4 years 107 g/L; 4–8 years 110 g/L; 8–12 y 113 g/L; >12 y 130 g/L. Patients were considered iron deficient on the basis of a microcytic blood film, low serum iron, low serum ferritin, and elevated iron binding capacity.
Statistical analysis
Data were analysed by simple descriptive analysis performed manually and using Excel (Microsoft Office 97). Fisher's Exact tests were used to compare independent data using STATA [10]. Where data was not available, summary statistics were performed using only the data available.
Results
Subjects
A total of 119 patients were identified over the six year period. Forty-three patients were excluded as there was another medical reason to explain their histological features or reason for dietetic referral. The medical records were unable to be located for two patients, leaving 74 subjects with coeliac disease available for analysis. The male: female ratio of patients was 1:2. The age at diagnosis ranged from 11 months to 14 years with median of 5.5 years. Seven patients (9% of total group) were less than 2 years of age (Figure 1). The ethnic mix (based on country of birth) of all admissions to SCH consists of approximately 94% Australian, 2% Asian, 1% UK and Europe, 0.05% Africa, and 0.02% Pacific Islands (data compiled by MS using admission data for Sydney Children's Hospital for 2002).
Figure 1 Age at Presentation of Coeliac disease in the cohort of 74 subjects. This figure illustrates the age distribution of the 74 subjects with coeliac disease in this study. Infants less than 2 years of age represented only 12% of the population. 27% of subjects were aged between 4 and 5 years, 36% were aged between 5 and 10 years, 26% were more than 10 years.
Clinical features
Sixty nine of the seventy four children had presented with symptoms (Table 1). Full details of the presenting symptoms were available in 65 of the patients. Twenty nine of these children were aged less than five (preschool) and forty were aged five years or greater. The most common presenting symptoms in younger children (those <5 years) were diarrhoea (59%), irritability (34%) and weight loss (38%). In older children (≥ 5 years), the most common presenting feature was abdominal pain (55%), followed by diarrhoea (26%). Twenty-three percent of the symptomatic children had > 3 presenting symptoms.
Table 1 Clinical features of 69 symptomatic children with Coeliac disease
Age < 5 years n = 29 (% of group) Age ≥ 5 years n = 40 (% of group)
Abdominal pain 6 (20) 25 (62.5)*
Diarrhoea 17 (59) 12 (30)*
Tiredness/lassitude 9 (31) 9 (22.5)
Abdominal distension 16 (55) 9 (22.5)*
Constipation 4 (14) 5 (12.5)
Irritability 10 (34) 6 (15)*
Mouth Ulcers 2 (7) 6 (15)
Anaemia 5 (17) 10 (25)
Weight loss or lack of expected weight gain 11 (35) 6 (15)*
Anorexia and vomiting 7 (24) 0*
(*p < 0.05) This table displays the number of subjects with each symptom. The numbers in brackets describe the percentage of the age group with that symptom.
Five patients had no gastrointestinal symptoms at diagnosis. Four of these patients had positive coeliac serology during routine complication screening for type 1 diabetes (T1DM). The fifth patient had coeliac serology performed as part of investigation into recurrent infections.
Overall, ten children were noted to have other medical problems potentially related to the development of coeliac disease. Five patients had T1DM, two patients had Trisomy 21, two patients had juvenile rheumatoid arthritis, and one patient had Raynaud's phenomenon. Fourteen of the 79 (18%) patients had a family history of coeliac disease in a first degree relative.
The mean weights and heights of the subjects with coeliac disease were not significantly different to the reference sex and age matched population (mean weight SD -0.45 ± 0.14; mean height SD -0.4 ± 0.17). However, 5% of the children with coeliac disease had a weight SD score of more than 2 SD below the mean and 12% of children had a height SD score of more than 2 SD below the mean.
Laboratory data
Seventeen of 64 (26%) patients with haemoglobin levels available had haemoglobin levels below the reference range for age (mean haemoglobin 118 g/L ± 0.2). Thirty two of 37 (86%) patients who had iron studies available were deemed iron deficient (low serum iron and ferritin). Of those who were biochemically iron deficient, 8 (25%) had normal haemoglobin values for their age.
IgG AGA was elevated in 97% of cases. IgA AGA was elevated in 94% of cases. There were no patients with IgA deficiency. EMA were elevated in 97% of this group of children. There were two patients with positive EMA antibodies who had negative AGA, on the other hand there was one patient (aged 9 years) with negative EMA who had positive AGA.
Discussion
This study describes the clinical features at presentation in a group of Australian children diagnosed with coeliac disease during a time of increasing awareness of this disease and widespread availability of reliable laboratory screening tests. The children included in this retrospective review presented with a wide variety of clinical features. The most common clinical features of coeliac disease in younger children were the so-called classical symptoms of diarrhoea, irritability and weight loss. However, older children more commonly presented with abdominal pain. There were few cases without gastrointestinal symptoms in our cohort.
The clinical features of the children in this study were similar to the clinical features described from populations in New Zealand [11], South Yorkshire [12] and Sweden [13]. Although abdominal pain is a common symptom of older children with coeliac disease, there is no association between classical recurrent abdominal pain and coeliac disease [14].
Anaemia was identified in approximately one quarter of the cases. Furthermore, many children had laboratory evidence of iron deficiency but were not anaemic at the time of diagnosis. Unfortunately only 86% of subjects had a full blood count taken, and 50% had blood taken for iron studies. Thus the true prevalence of anaemia and iron deficiency is uncertain. Cross sectional studies have identified a high prevalence of coeliac disease in patients with iron or folate deficiency [15,16]. The incidence of coeliac disease in patients in the community presenting only with iron or folate deficiency has been reported at 4.7% [15]. Anaemia was reported in only 5% of children with coeliac disease from the Netherlands [1]. In the United Kingdom, iron deficiency anaemia was reported in approximately 20% of adults with coeliac disease. Although the current data may have underestimated the true incidence of anaemia and iron deficiency, it is likely higher than that reported in these previous cohorts.
Growth failure in height and weight was not as common in this cohort as was described in coeliac children from the Netherlands, where 49.7% of children had poor growth [1]. In our study, 5% of children had a weight more than 2 SD below the mean, and 12% of children had a height more than 2 SD below the mean. Growth failure is more commonly seen in children diagnosed at a younger age than in our study [17]. The discrepancy in reported growth failure may also be due to different definitions of growth failure. In addition, because this was a retrospective study, it was not possible to obtain adequate information about growth velocity or of the children's genetic growth potential.
The children in our study were older at the time of diagnosis than previous surveys of children with coeliac disease. In a cohort of patients diagnosed between 1950 and 1969, 70 of 91 were less than 2 years at the time of diagnosis and only 3 were more than 6 years. In a smaller cohort of children diagnosed between 1972 and 1975, 32 of 42 were less than 2 years at the time of diagnosis and 6 were greater than 6 years [18]. In the Netherlands, the proportion of children with coeliac disease aged < 2 yrs has remained at about 60% from 1975 to 1994 [1]. An epidemic in coeliac disease in Swedish Children in the 1980's paralleled the change in feeding practices at the time, in particular increased exposure to wheat, rye and barley and decreased duration of breast feeding [5]. A prospective study of coeliac disease in infants showed that a longer duration of breast feeding, smaller amounts of gluten in the diet in infants less than 12 months [17] and breast feeding after gluten is introduced to the diet reduces the risk of coeliac disease in infants less than 2 years [7]. Thus, the later age of acquiring coeliac disease in the Australian population may be due to the delayed introduction of solids in the diet of Australian children. The current recommendations in Australia are to introduce solids at 6 months (NHMRC Dietary Guidelines for Children and Adolescents in Australia 1993).
In this study, there were relatively few cases of coeliac disease detected by the screening of at risk groups. This contrasts with the worldwide trend of an increased prevalence of coeliac disease detected by screening [2,19-22]. A large multi-centered study of children and adults in the United States of America showed that the prevalence of celiac disease was 1:22 in first degree relatives, 1:56 in symptomatic individuals or a disorder known to be associated with celiac disease (type 1 diabetes, down syndrome, anemia, arthritis, osteoporosis, infertility and short stature), and 1:133 in the not-at-risk population [23].
In our study, the best screening test in children aged over 2 years with symptoms of, or who are at risk of, coeliac disease was IgA EMA. Other studies have shown that this test has a sensitivity of 95–98%, specificity of 94–95%, positive predictive value of 91–95% and negative predictive value of 96–98% [24]. For children less than 2 years of age, IgA AGA may be more reliable [24]. Increasingly over the last few years, reports suggest that tissue-transglutaminase (tTG) antibody may be even more reliable than EMA as a screening test [25,26], and in addition is more reproducible and reliable. This test was not available during the period of this review. Although the utility of these newer tests is improved compared to AGA antibodies, they are not yet accepted as diagnostic tests. Any child with symptoms suspicious of coeliac disease, even if negative serology, warrants further review by a paediatric gastroenterologist, as a small bowel biopsy remains the gold standard test for diagnosis of coeliac disease.
Conclusion
Coeliac disease in children does not always present with classical clinical features, especially in older children. The possibility of coeliac disease should be considered in any child presenting with diarrhoea, irritability and weight loss, and particularly in older children with abdominal pain. With the widespread availability of minimally invasive screening tests for coeliac disease, identifying cases in at risk groups by screening should also be considered.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
MS conceived the study, performed the data collection and statistical analysis and drafted the manuscript; KW for assistance in collecting the data and reviewing the manuscript; VT performed the histological examination of the biopsy specimens; AD and TB were involved in the study design, writing and reviewing of the manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
Dr Phillip Emder for his support and review of the manuscript.
==== Refs
K GE Mearin ML Franken HCM Houwen RHJ Hirasing RA Vandenbrouche JP Twenty Years of childhood coeliac disease in The Netherlands: a rapidly increasing incidence? Gut 1997 40 61 66 9155577
Day AS Cook HB Whitehead M Abbott GD Anti-endomysial and anti-gliadin antibodies in screening for coeliac disease in children at greater risk of developing coeliac disease N Z Med J JID - 0401067 2000 113 412 413
Csizmadia CGDS Mearin ML von Blomberg BME Brand R Verloove-vanhorick SP An iceberg of childhood coeliac disease in the Netherlands The Lancet 2003 353 813 814 10.1016/S0140-6736(99)00243-3
Hovell CJ Collett JA Vautier G Cheng AJP Sutanto E Mallon DF Olynyk JK Cullen DJE High prevalence of coeliac disease in a population-based study from Western Australia: a case for screening? Medical Journal of Australia 2001 175 247 250 11587254
Ivarsson A Persson LA Nystrom L Ascher H Cavell B Dannaeus A Lindberg T Lindquist B Stenhammar L Hernell O Epidemic of coeliac disease in Swedish children Acta Paediatrica 2000 89 165 171 10709885 10.1080/080352500750028771
Challacombe DN Mecrow IK Ellliott K Clarke FJ Wheeler EE Changing infant feeding practices and declining incidence of coeliac disease in West Somerset Archives of Disease in Childhood 1998 79 198 199
Ivarsson A Hernell O Stenlund H Persson LA Breast-feeding protects against celiac disease American Journal of Clinical Nutrition 2002 75 914 921 11976167
Report of the Working Group of European Society of Paediatric Gastroenterology and Nutrition Revised Criteria for the Diagnosis of Coeliac Disease Archives of Disease in Childhood 2003 1990 909 911
Hamill PVV Drizd TA Johnson CL Reed RB Roche AF Moore WM Physical Growth: National Centre for Health Statistics percentiles. American Journal of Clinical Nutrition 1979 32 607 629 420153
Corporation S Stata 6.0 2003 702 University Drive College Station Texas 77840 USA
R U ML Y N S Coeliac Disease: incidence and Prevalence in Wellington 1985-1992 New Zealand Medical Journal 1994 107 195 197 8196863
Sanders DS Hurlstone DP Stokes RO Rashid F Milford-Ward A Hadjivassiliou M Lobo AJ Changing face of adult coeliac disease: experience of a single university hospital in South Yorkshire Postgraduate Medical Journal 2001 31 33
Ludvigsson J Ansved P Falth-Magnusson K Hammersjo J Johansson C Edvardsson S al Symptoms and Signs have changed in Swedish Children with Coeliac disease Journal of Pediatric Gastroenterology and Nutrition 2004 181 186 14734881 10.1097/00005176-200402000-00015
Fitzpatrick KP Sherman PM Ipp M Saunders N Macarthur C Screening for celiac disease in children with recurrent abdominal pain Journal of Pediatric Gastroenterology and Nutrition 2001 33 250 252 11593117 10.1097/00005176-200109000-00004
Howard MR Turnbull AJ Morley P Hollier P Webb.R Clarke A A prospective study on the prevalence of undiagnosed coeliac disease in laboratory defined iron and folate deficiency Journal of Clinical Pathology 2002 55 754 757 12354801 10.1136/jcp.55.10.754
Ransford RA Hayes M Palmer M Hall MJ A controlled, prospective screening study of celiac disease presenting as iron deficiency anemia Journal of Clinical Gastroenterology 2002 35 228 33 12192198 10.1097/00004836-200209000-00006
Ascher H Holm K Kristiansson B Maki M Different features of coeliac disease in two neighbouring countries Archives of Disease in Childhood 1993 69 375 380 8215549
Walker-Smith J Murch S Diseases of the Small Intestine in Childhood 1999 Oxford UK, Isis Medical Media Ltd
Bingley PJ Williams AJK Norcross AJ Unsworth DJ Lock RJ Ness AR Jones RW Undiagnosed coeliac disease at age seven:population based prospective birth cohort study British Medical Journal 2004 328 322-323 14764493
Carlsson AK Axelsson IE Borulf SK Bredberg AC Ivarsson SA Serological screening for celiac disease in healthy 2.5-year-old children in Sweden Pediatrics JID - 0376422 2001 107 42 45 10.1542/peds.107.1.42
Bowron A Moorghen M Morgan JE Osborne JR Stansbie D Stone JE Cost-effective strategy for the serological investigation of coeliac disease Ann Clin Biochem JID - 0324055 2000 37 ( Pt 4) 467 470 10.1258/0004563001899654
Chan AW Butzner JD McKenna R Fritzler MJ Tissue transglutaminase enzyme-linked immunosorbent assay as a screening test for celiac disease in pediatric patients Pediatrics JID - 0376422 2001 107 E8 10.1542/peds.107.1.e8
Fasano A Berti I Gerarduzzi T Not T Colletti RB Drago S Elitsur Y Green PHR Guandalini S Hill ID Pietzak M Ventura A Thorpe M Kryszak D Fornaroli F Wasserman SS Murray JA Horvath K Prevalence of celiac disease in At-Risk and Not-at-Risk Groups in the United States Archives of Internal Medicine 2003 163 286 292 12578508 10.1001/archinte.163.3.286
Farrell RJ Kelly CP Celiac Sprue The New England Journal of Medicine 2002 346 180 11796853 10.1056/NEJMra010852
Dickey W McMillan SA Hughes DF Sensitivity of serum tissue transglutaminase antibodies for endomysial antibody positive and negative coeliac disease Scand J Gastroenterol JID - 0060105 2001 36 511 514 10.1080/003655201750153359
Salmaso C Ocmant A Pesce G Altrinetti V Montagna P Descalzi D Martino S Bagnasco M Mascart F Comparison of ELISA for tissue transglutaminase autoantibodies with antiendomysium antibodies in pediatric and adult patients with celiac disease Allergy JID - 7804028 2001 56 544 547 10.1034/j.1398-9995.2001.056006544.x
| 15907214 | PMC1173112 | CC BY | 2021-01-04 16:31:06 | no | BMC Pediatr. 2005 May 21; 5:11 | utf-8 | BMC Pediatr | 2,005 | 10.1186/1471-2431-5-11 | oa_comm |
==== Front
BMC Public HealthBMC Public Health1471-2458BioMed Central London 1471-2458-5-461590451110.1186/1471-2458-5-46Research ArticleRural residence is not a risk factor for frequent mental distress: a behavioral risk factor surveillance survey Rohrer James E [email protected] Tyrone F [email protected] Jimmy [email protected] Department of Family and Community Medicine, Texas Tech University Health Sciences Center, 1400 Commonwealth Drive, Amarillo Texas 79106, USA2 Department of Health Management and Policy, University of North Texas Health Science Center, School of Public Health, Fort Worth, TX, USA3 Texas Department of State Health Services, Center for Health Statistics, Austin, Texas, USA2005 16 5 2005 5 46 46 23 2 2005 16 5 2005 Copyright © 2005 Rohrer et al; licensee BioMed Central Ltd.2005Rohrer et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Residents of rural areas may be at increased risk of mental health problems. If so, public health programs aimed at preventing poor mental health may have to be customized for delivery to rural areas. The purpose of this study was to examine the relationship between residing in a rural area and frequent mental distress, which is one indicator of poor mental health.
Methods
The Behavioral Risk Factor Surveillance System (BRFSS) survey for the state of Texas was the source of information about obesity, demographic characteristics, and frequent mental distress (FMD). FMD was defined as poor self-rated mental health during at least half of the days in the last month. Adjusted odds for FMD were computed for rural and suburban respondents relative to urban respondents.
Results
FMD was found to be independently associated with lower education, being younger, being non-Hispanic, being unmarried, and being female. FMD also was associated with being obese or underweight and suburban residence (relative to metro-central city). FMD was not more common among rural respondents than in the metro-central city.
Conclusion
Rural respondents were not at greater risk of frequent mental distress than urban respondents in this sample. Programs seeking to improve community mental health should target persons with less education and extremes in body weight, along with women and single persons, regardless of whether they live in rural or urban areas.
==== Body
Background
The concern for health disparities extends to residents of rural areas, who are recognized to face distance barriers when seeking to access health services. Concerns about disparities apply to mental as well as physical health. Studies addressing rural residence as a risk factor for poor mental health are important to verify the existence of a disparity and to clarify its nature.
Singh and Siahpush studied rural residence as a risk factor for suicide. They reported that suicide risk increases for males with increasing levels of rurality and that the rural-urban differentials are increasing over time. Rural suicide rates also were higher for women but the rural-urban differential was found to be decreasing over time [1].
Recently, national experts have emphasized the recognition of mental health as a public health problem [2-4]. Suicide, though important, may not be the most important focus for a public health approach to mental health. Community health programs typically are targeted at moderately healthy populations, not the seriously ill, because the goal is prevention so as to avoid the need for treatment. Less serious mental health concerns affect a large fraction of the population. The more common mental health problems often are preventable and may be amenable to health promotion programs involving self-help strategies. Population surveys such as the one reported here naturally are more relevant to the less severe, more common mental health issues.
Rural health advocates frequently make the case that rural residents have worse health than residents of urban areas, implying that residing in a rural area is a risk factor for poor health [5]. However, it is also possible that the causes of poor health are the same regardless of where one lives, and thus programs should be targeted not at rural locations but at populations that are afflicted with the genuine risk factors (e.g., poverty, low educational attainment, and age).
The purpose of the study reported here was to investigate the relationship between rural residence and frequent mental distress, which can be described as poor self-rated mental health. This study differs from some earlier studies in that it includes a variable representing rural or urban residence in an analysis of data drawn from the Behavioral Risk Factor Surveillance System (BRFSS). The BRFSS does not ordinarily contain a variable representing rural or urban residence of the respondent. The Texas Department of State Health Services recently created such a variable, permitting comparisons that previously were not possible.
Methods
Data were obtained from the 2003 Texas Behavioral Risk Factor Surveillance (BRFSS) survey. The Texas Behavioral Risk Factor Surveillance System (BRFSS), sponsored by the Texas Department of State Health Services in partnership with the Centers for Disease Control and Prevention (CDC), is an ongoing random-digit dialed telephone survey that collects information from the non-institutionalized, civilian adult population. BRFSS surveys adhere to the highest scientific standards for telephone researchand pose questions relating to health status, personal health habits, and use of preventive health services. The 2003 survey data were collected over a 12-month period frominterviews with 6,035 Texas residents. The overall cooperation rate, or proportion of individuals actually contacted on the phone who completed the survey, was 70%. The more conservative response rate favored by the Council of American Survey Research Organizations (CASRO), which adjusts for the estimated number of eligible respondents in the samplewho could not be contacted due to technical or other barriers, was 41%.
Missing values were excluded from the analyses if they constituted less than 5% of cases for an independent variable. Missing dummy variables were created for independent variables for which 5% or more of the cases had missing values (household income and body mass index). The data set contained 5,757 observations.
Measures
The dependent variable was frequent mental distress, which was assessed with the following question: "Now, thinking about your mental health, which includes stress, depression and problems with emotions, for how many days during the past 30 days was your mental health not good?" Frequent mental distress was defined as having 14 or more days of "not good" mental health.
The primary independent variable of interest was whether the individual lived in a metropolitan, suburban, or non-metropolitan/rural area. Many prior studies have categorized the area of residence as metropolitan vs. non-metropolitan. However, a dichotomous classification may mask important differences between residents of highly urban and suburban areas. Thus, we chose a more detailed classification system of metropolitan-central city, metropolitan-suburban, and non-metropolitan areas based on respondents' reports of their county of residence. Metropolitan-central city was defined as an urban core county containing 50,000 or more persons. Metropolitan-suburban was defined as a metropolitan county adjacent to a core metropolitan-central city area. All other counties were considered non-metropolitan or rural.
Additional independent factors included demographics and body mass index. Demographic variables were age category (18–24, 25–34, 35–44, 45–54, 55–64, and 65+), race/ethnicity (non-Hispanic white, Hispanic, black, and other), gender, marital status (single/never married/divorced/widowed vs married/member of a couple), educational status (less than a high school degree, a high school degree, some college, and college graduate), and household income (<$25,000, $25,000 to $75,000, ≥$75,000, and income missing). Body mass index (BMI) categories were defined as obese (BMI ≥ 30), overweight (BMI 25–29.99), normal weight (BMI <25 and ≥ 18.5), underweight (BMI < 18.5), and a BMI missing category.
Analyses
The percentage of respondents with frequent mental distress (FMD) was calculated by urban/rural residence and all other independent variables. Multivariate logistic regression analyses were conducted to estimate adjusted odds ratios (AORs) for selected risk factors. Data were weighted to reflect the demographic distributions of the sample. Because we were interested in testing whether the predictors of FMD differ between residents of metropolitan-central city, metropolitan-suburban, and non-metropolitan areas, we then stratified the analyses by metropolitan status. STATA 8.0 was used to conduct descriptive and multivariate analyses to account for the complex sampling scheme and population weights [6].
Results
Frequent mental distress was reported by 9.79% of the respondents. The first column of Table 1 describes respondents' demographic, social, economic, and body mass characteristics. Approximately 62% and 21% of respondents lived in metropolitan-central city and metropolitan-suburban areas, respectively, whereas about 17% resided in non-metropolitan counties. The second column describes the percentage of respondents with frequent mental distress by each selected risk or independent variable. Residents of metropolitan-suburban areas had the highest rate of FMD (11.92%). Those residing in metropolitan-central city and non-metropolitan areas had similar rates of FMD (9.34 and 8.77%). After adjustment for other variables, persons in metropolitan-suburban areas had a significantly higher odds of FMD compared to metropolitan-central city residents (AOR = 1.37). Non-metropolitan residents did not have a significantly different adjusted odds of FMD as compared to individuals residing in metropolitan-central city areas.
Table 1 Prevalence of frequent mental distress (FMD) and adjusted odds ratios (AOR) for selected risk factors, State of Texas, 2003, (N=5,757)
Risk variable Overall % % with FMD (95% CI) AOR* (95% CI) N = 5,757 P value
Residence
Metropolitan-central city 61.50 9.34 (8.24–10.44) Reference
Metropolitan-suburb 21.23 11.92 (9.77–14.07) 1.37 (1.06–1.77) 0.016
Non-metropolitan 17.27 8.77 (6.59–10.96) 0.86 (0.63–1.18) 0.350
Age group
18–24 14.66 11.92 (8.80–15.05) Reference
25–34 20.23 6.79 (5.04–8.54) 0.92 (0.62–1.34) 0.635
35–44 21.09 9.26 (6.91–11.60) 1.17 (0.78–1.69) 0.488
45–54 18.08 11.40 (9.32–13.49) 1.26 (0.86–1.85) 0.227
55–64 11.88 10.39 (8.29–12.50) 0.91 (0.59–1.41) 0.675
65+ 14.07 8.57 (6.84–10.32) 0.51 (0.33–0.78) 0.002
Race/ethnicity
non-Hispanic white 58.94 9.54 (8.61–11.68) Reference
Hispanic 28.91 9.22 (7.51–10.95) 0.56 (0.41–0.75) <0.001
Non-Hispanic Black 8.20 13.58 (9.47–17.68) 0.90 (0.62–1.31) 0.587
Other 3.95 9.72 (5.20–14.24) 1.15 (0.67–0.98) 0.607
Sex
Female 50.91 12.06 (10.80–13.31) Reference
Male 49.09 7.44 (6.16–8.73) 0.60 (0.48–0.76) <0.001
Marital status
Single/never married 38.65 13.28 (11.58–14.98) Reference
Married 61.35 7.61 (6.61–8.61) 0.66 (0.54–0.82) <0.001
Educational status
< high school degree 17.52 13.61 (10.96–16.26) Reference
high school degree 27.44 12.84 (10.77–14.91) 0.80 (0.59–1.10) 0.172
some college 26.51 8.72 (7.20–10.24) 0.53 (0.37–0.74) <0.001
College graduate 28.53 5.50 (4.41–6.60) 0.38 (0.26–0.55) <0.001
Household income
<$25,000 30.01 15.79 (13.68–17.90) Reference
$25,000 to $75,000, 39.27 7.50 (6.28–8.72) 0.52 (0.40–0.67) <0.001
≥$75,000 18.85 6.40 (4.75–8.06) 0.49 (0.33–0.71) <0.001
Missing 11.87 7.58 (5.41–9.75) 0.50 (0.35–0.71) <0.001
Body mass index
Obese 23.02 12.66 (10.58–14.75) 1.56 (1.19–2.05) 0.001
Overweight 34.61 8.76 (7.31–10.21) 1.22 (0.93–1.60) 0.159
Normal 34.07 8.18 (6.75–9.61) Reference
Underweight 2.08 24.38 (15.00–33.76) 3.15 (1.82–5.45) <0.001
BMI missing 6.22 8.85 (5.42–12.27) 0.88 (0.53–1.44) 0.602
CI = confidence interval.
*Adjusted for all other variables in Table 1. N = 5,757 prior to weighting.
Age differences in FMD were revealed as those 65 years and older had a significantly lower adjusted odds of FMD than individuals between 18 and 24 years of age (AOR = 0.51). In regard to race/ethnicity, a higher percentage of Blacks/African Americans (non-Hispanic) reported FMD than non-Hispanic whites, Hispanics, or other non-Hispanic racial groups. However, when adjusting for other factors, only Hispanics' odds of FMD differed from non-Hispanic whites' (AOR = 0.56). Males exhibited a significantly lower adjusted odds of FMD (AOR = 0.60) as compared to females. Married or living-together persons had a significantly lower adjusted odds of FMD than single persons (AOR = 0.66). Educational attainment and household income, two indicators of socioeconomic status, were also associated with FMD. Compared with those with less than a high school degree, individuals with some college education as well as those who were college graduates had lower adjusted odds of FMD (AOR = 0.53 and 0.38, respectively). Similarly, individuals who had higher household incomes experienced a lower adjusted odds of FMD. Body mass index categories of obesity and underweight were associated with substantially higher odds (AORs = 1.56 and 3.15, respectively) of FMD as compared to normal weight persons.
We also performed analyses of the predictors of FMD by metropolitan-central city, metropolitan-suburban, and non-metropolitan status (Table 2). The findings for each model were similar with a few notable exceptions. Among those residing in metropolitan-central city areas, Hispanics had a significantly lower odds (AOR = 0.53, 95% CI = 0.37–0.77) of FMD than non-Hispanic whites. However, among residents of metropolitan-suburban and non-metropolitan areas, the odds of FMD did not differ between Hispanics and non-Hispanic whites. Similarly, male gender was significant in the model for metropolitan-central city residents (AOR = 0.50, 95% CI = 0.37–0.68) but insignificant in the remaining two models. Married or living-together persons were less likely to have FMD among metro-central city respondents, but marital status was not significant elsewhere in the state.
Table 2 Adjusted odds ratios (AOR) of frequent mental distress (FMD), stratified by metropolitan status
Risk variable Metropolitan-Central City N = 3,505 P value Metropolitan-Suburban N = 1,251 P value Non-Metropolitan N = 1,001 P value
AOR * (95% CI) AOR * (95% CI) AOR * (95% CI)
Age group
18–24 Reference Reference Reference
25–34 1.25 (0.77–2.03) 0.366 0.40 (0.19–0.85) 0.016 0.94 (0.32–2.72) 0.904
35–44 1.40 (0.85–2.30) 0.186 0.63 (0.28–1.40) 0.256 1.73 (0.64–4.67) 0.283
45–54 1.42 (0.87–2.30) 0.157 0.96 (0.46–1.98) 0.904 1.49 (0.50–4.46) 0.476
55–64 1.16 (0.65–2.09) 0.614 0.59 (0.25–1.37) 0.218 0.93 (0.31–2.77) 0.892
65+ 0.60 (0.33–1.08) 0.091 0.26 (0.11–0.59) 0.001 0.77 (0.29–2.02) 0.586
Race/ethnicity
Non-Hispanic white Reference Reference Reference
Hispanic 0.53 (0.37–0.77) 0.001 0.49 (0.23–1.03) 0.058 0.88 (0.41–1.88) 0.738
Non-Hispanic Black 0.90 (0.59–1.39) 0.648 0.88 (0.31–2.46) 0.804 0.90 (0.33–2.50) 0.845
Other 1.23 (0.62–2.43) 0.547 0.81 (0.25–2.63) 0.725 1.57 (0.37–6.65) 0.540
Sex
Female Reference Reference Reference
Male 0.50 (0.37–0.68) <0.001 0.73 (0.47–1.14) 0.171 0.77 (0.44–1.36) 0.368
Marital status
Single/never married Reference Reference Reference
Married 0.56 (0.43–0.74) <0.001 0.81 (0.50–1.30) 0.384 0.98 (0.56–1.70) 0.931
Educational status
< high school degree Reference Reference Reference
high school degree 0.75 (0.51–1.12) 0.165 0.85 (0.44–1.61) 0.623 0.90 (0.42–1.96) 0.800
some college 0.59 (0.38–0.92) 0.018 0.36 (0.17–0.77) 0.008 0.71 (0.31–1.62) 0.420
College graduate 0.42 (0.26–0.67) <0.001 0.41 (0.20–0.83) 0.013 0.15 (0.05–0.50) 0.002
Household income
<$25,000 Reference Reference Reference
$25,000–$75,000 0.53 (0.38–0.74) <0.001 0.56 (0.32–0.97) 0.040 0.34 (0.17–0.71) 0.004
≥$75,000 0.51 (0.33–0.80) 0.003 0.36 (0.16–0.82) 0.016 0.94 (0.38–2.42) 0.905
Income missing 0.45 (0.28–0.71) 0.001 0.62 (0.27–1.39) 0.245 0.41 (0.18–0.96) 0.040
Body mass index
Obese 1.96 (1.37–2.80) <0.001 1.04 (0.61–1.79) 0.881 1.28 (0.58–2.87) 0.542
Overweight 1.19 (0.82–1.72) 0.357 1.16 (0.70–1.92) 0.562 1.69 (0.78–3.63) 0.181
Normal Reference Reference Reference
Underweight 2.98 (1.54–5.78) 0.001 1.26 (0.37–4.29) 0.710 11.94 (3.66–38.97) <0.001
BMI missing 0.22 (0.67–2.23) 0.513 0.35 (0.11–1.16) 0.087 0.74 (0.19–2.83) 0.656
CI = confidence interval.
* Adjusted for all other variables in Table 1.
Discussion
The theory that residing in a rural location rather than an urban area is a risk factor for frequent mental distress is not supported by our data. Instead, persons living in suburbia were found to be at risk for FMD after adjusting for other risk factors. We suspect that some stressors may be at work in the suburbs that are not found in rural areas or central cities. This warrants further investigation.
In our data, lifestyle variables (obesity and underweight), Hispanic ethnicity, female gender, being unmarried, and having less education are more important risk factors for FMD than rural residence. Because obesity and underweight are related to frequent mental distress, public health programs designed to achieve normal body weight might improve mental health [7]. The potential for population-level health promotion strategies to reduce the prevalence of mental health problems is important, since the medical care system has been chastised for its insensitivity to underlying mental health problems among patients who present with physical symptoms [8-11]. Efforts directed at improving the quality of mental health services delivered in primary care settings have had mixed results [9]. Clearly, this is another case where population-based preventive strategies by public health agencies might be more effective than individualized medical treatment of mental health problems, at least for less severe or incipient cases [7,11].
The widespread and increasing [12-14] prevalence of frequent mental distress in the population (8.6 percent of adults nationally a decade ago and ten percent in 2001 [13]) necessitates a public health response. In addition, the psychological consequences of any future terrorist attacks or natural disasters will require population-based responses that can reach large numbers of people in a short time [15].
Conclusion
This study examined how rural residence was related to frequent mental distress in the general population in a single state. Our findings are a direct result of the modeling strategy employed. Accordingly, replication of these results by other investigators is important. Limitations of the study include a modest participation rate, the cross-sectional design, and the loss of some cases due to missing data. The cross-sectional nature of the study makes causal conclusions impossible. Furthermore, the use of a self-reported single item to measure frequent mental distress does not equate to providing diagnostic information. Another important limitation is that most seriously mentally ill persons are likely to be missed by a survey such as this because they at increased risk of being homeless or otherwise unavailable for telephone interviews. Nevertheless, the single item has been accepted by public health researchers for use in population surveys [11-14,16-18].
Health status in rural populations is believed to be lower than in urban areas, partly due to higher rates of poverty [5]. This assertion specifically relates to rates of chronic disease, infant mortality, injury rates, trauma mortality, and overall mortality. However, most government sponsored surveys do not include a variable that reflects urban or rural residence. Our study is the first to use a Behavioral Risk Factor Surveillance System (BRFSS) survey with a variable reflecting rural residence. Our results do not support the concern about rural residence being a risk factor for poor mental health. The risk factors for poor mental health are found in urban as well as rural areas, although the delivery of services may be more difficult in rural areas.
When Singh and Siahpush reported that suicide rates were higher in rural areas, they attributed this finding partly to social isolation [1]. If this theory was correct, then we would expect frequent mental distress also to be more prevalent among rural respondents in our data. However, we did not find rural respondents to be at greater risk of frequent mental distress than urban respondents. We question the generalization that rural people experience greater levels of social isolation, since rural communities sometimes may be more integrated and supportive than urban neighborhoods.
Community health programs that are supported by strong evidence will, for the most part, focus on three strategies: policy changes, mass communication, and targeted health education [19]. Applied to risk factors for frequent mental distress, examples of policy changes might be zoning practices that promote physical activity, labeling of unhealthy menu items in restaurants, and increases in liquor and cigarette taxes. Media campaigns could be employed to raise awareness about anxiety, depression, stress, and healthy coping strategies. The third approach to community mental health is to target health education programs at persons who are at high risk. In Texas, this would be the elderly, the poor, and persons who are undereducated. Since none of these population-based strategies involve personal health services or require substantial investments in physical plant, they could each be carried out without regard to whether the targeted populations reside in rural or urban areas.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
TFB carried out the statistical analysis, wrote the methods section, and wrote the results section. JB wrote the section on sampling and the BRFSS in Texas. JER conceived of the study, planned the design, and wrote the background, discussion and conclusions.
Pre-publication history
The pre-publication history for this paper can be accessed here:
==== Refs
Singh GK Siahpush M Increasing rural-urban gradients in US suicide mortality, 1970–1997 Am J Public Health 2002 92 1161 7 12084702
Institute of Medicine Reducing Suicide: a National Imperative 2002 Washington, DC: National Academic Press
U.S. Department of Health and Human Services Mental Health: A Report of the Surgeon General 1999 Rockville, MD
U.S. Department of Health and Human Services Mental Health: Culture, Race, and Ethnicity – A Supplement to Mental Health: A Report of the Surgeon General 2001 Rockville, MD
Ricketts TC Johnson-Webb KD Randolph RK Ricketts TC Populations and Places in Rural America Rural Health in the United States 1999 New York: Oxford University Press 7 24
StataCorp Stata Statistical Software: Release 80 2003 College Station, TX: Stata Corporation
Rohrer JE Pierce R Blackburn C Lifestyle and mental health Preventive Medicine 2005 40 438 443 15530596 10.1016/j.ypmed.2004.07.003
Wells K Quality of Care for Primary Care Patients With Depression in Managed Care Arch Fam Med 1999 8 529 536 10575393 10.1001/archfami.8.6.529
Thompson D Hylan T McMullen W Romeis M Buesching D Oster G Predictors of a Medical-Offset Among Patients Receiving Antidepressant Therapy Am J Psychiatry 1998 155 824 827 9619157
Sturm R The Myth of Medical Cost Offset Am J Psychiatry 2001 52 738 740
Rohrer JE Medical care usage and self-rated mental health BMC Public Health 2004 4 3 15070417 10.1186/1471-2458-4-3
Zack MM Moriarty DG Stroup DF Ford ES Mokdad AH Worsening Trends in Adult Health-Related Quality of Life and Self-Rated health – United States, 1993–2001 Public Health Reports 2004 119 493 505 15313113 10.1016/j.phr.2004.07.007
Zahran HS Kobau R Moriarty DG Zack MM Giles WH Lando J Self-Reported Frequent Mental Distress Among Adults – United States, 1993–2001 MMWR 2004 53 963 966 15496824
Strine TW Balluz L Chapman DP Morarity DG Owens M Mokdad AH Risk Behaviors and Healthcare Coverage Among Adults by Frequent Mental Distress Status, 2001 Am J Prev Med 2004 26 213 216 15026100 10.1016/j.amepre.2003.11.002
Silver RC Holman EA McInntosh DN Poulin M Gil-Rivas V Nationwide Longitudinal Study of Psychological Responses to September 11 JAMA 2002 288 1235 1244 12215130 10.1001/jama.288.10.1235
Centers for Disease Control and Prevention Measuring Healthy Days 2000 Atlanta, Georgia
Brown DW Balluz LS Ford ES Giles WH Strine TW Moriarty DG Croft JB Mokdad AH Associations Between Short- and Long-Term Unemployment and Frequent Mental Distress Among a National Sample of Men and Women J Occup Environ Med 2003 45 1159 1166 14610397
Moriarty DG Zack MM Kobau The Centers for Disease Control and Prevention's Healthy Days Measures-Population tracking of perceived physical and mental health over time Health and Quality of Life Outcomes 2003 1 37 14498988 10.1186/1477-7525-1-37
Merzel C D'Afflitti J Reconsidering community-based health promotion: promise, performance, and potential Am J Public Health 2003 93 557 74 12660197
| 15904511 | PMC1173113 | CC BY | 2021-01-04 16:28:56 | no | BMC Public Health. 2005 May 16; 5:46 | utf-8 | BMC Public Health | 2,005 | 10.1186/1471-2458-5-46 | oa_comm |
==== Front
BMC Public HealthBMC Public Health1471-2458BioMed Central London 1471-2458-5-471590451210.1186/1471-2458-5-47Research ArticlePrevalence of nonvitamin, nonmineral supplement usage among students in a Turkish university Ayranci Unal [email protected] Nazan [email protected] Osman [email protected] Medico Social Center, Osmangazi University 26480 Meselik Eskisehir Turkey2 Medical Faculty, Dietitian Division, Osmangazi University 26480 Meselik Eskisehir Turkey3 Medical Faculty, Internal illnesses Department, Osmangazi University 26480 Meselik Eskisehir Turkey2005 16 5 2005 5 47 47 3 12 2004 16 5 2005 Copyright © 2005 Ayranci et al; licensee BioMed Central Ltd.2005Ayranci et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
There have been multiple studies carried out in many countries with regard to the use of nonvitamin, nonmineral (NVNM) supplements. These studies have shown that the use of NVNM supplements is on the increase throughout the world, particularly in western countries. The aim of this study was to assess the extent of NVNM supplement use among Turkish university students.
Methods
The survey was conducted between September and December 2004 at Osmangazi University, a public university located in the west of Turkey. Responses were analysed, using the chi-square (x2) test, t test and percent (%) ratios, according to gender and consumers. Differences were considered significant for p ≤ 0.05.
Results
Of 2253 students attending the university, 1871 participated in the survey (909 men and 962 women). Overall, the prevalence of NVNM supplement use was 16.5% (16.6% in men and 16.3% in women, p < 0.05).
The three most commonly given reasons for use were 'improvement of energy and vitality (78.6%)', 'promotion of weight loss (71.1%)', followed by 'enhancement of athletic performance (64.3%)'. Twenty-six of the 308 reported NVNM users (26/308, 8.4%) reported having experienced an adverse reaction. Television (76.3%), magazines/newspapers (41.5%) and internet websites (37.3%) were the most frequently used sources for obtaining information about NVNM supplements. The three most frequently used NVNM supplements were echinacea, ginseng, and gingko biloba (38.6%, 36.4%, and 32.8%, respectively). Nutritional scores were higher in NVNM supplement users than in non-users (66.510.8 vs. 62.712.7) (p < 0.001). Users and nonusers of NVNM supplements differed significantly according to sex, age, Body Mass Index (BMI) values, types of school, mother and fathers' education levels, family income, most permanent place of residence up to the time of survey, smoking status, and participating in sports.
Conclusion
The results indicate that the prevalence of NVNM supplement use is relatively modest among Turkish university students and more information is needed on why people use particular NVNM supplements.
==== Body
Background
Dietary supplements are defined in the United States Dietary Supplement Health and Education Act of 1994 (United States DSHEA) as any product (other than tobacco) intended to supplement the diet that bears or contains one or more of the following ingredients: a vitamin, a mineral, an herb or other botanical, an amino acid, a supplement used by man to supplement the diet by increasing the total dietary intake, or a concentrate, metabolite, constituent, extract, or combination of any ingredient described above [1].
Hankin [2] and Radimer et al. [3] used the term 'nonvitamin, nonmineral (NVNM) supplements' to differentiate a new class of dietary supplements. NVNM supplements include products such as chrondroitin, sulfate, kava kava, ginseng, echinacea, ginkgo biloba, garlic herbals, botanicals, protein and amino acids, as well as Brewer's yeast and shark cartilage [3-5].
Although use of NVNM supplements is increasing in popularity, patterns of use for these supplements are not well known, and what is available is not always consistent, clear, or easily accessible [3].
People have reported a variety of reasons for taking dietary supplements, including decreasing their susceptibility to health problems such as stress, colds, heart attacks, osteoporosis, neural tube defects, dental caries and cancer, as well as to increase energy [6,7]. The supplements typically can be considered as falling into three distinct categories: supplements that are believed to add nutrients to a system that owing to inadequate dietary practices might otherwise be lacking [8]; supplements that allege rapid weight loss and maintenance of the loss [9], or conversely, supplements that are believed to result in weight gain or muscle development [10]. Furthermore, the rise in popularity of freely available substances purported to enhance performance, such as androsterone (a steroid precursor), and creatine (an amino acid derivative), has also been documented [11,12]. To date, however, the taking of nutritional preparations has not consistently indicated a competitive advantage other than a possible placebo effect, or one resulting from the treatment of concurrent nutritional deficiencies [13]. Consequently, according to the United States Commission on Dietary Supplement Labels, it is important for health and nutrition professionals to become more knowledgeable about all types of dietary supplements in order to help consumers make appropriate choices [14].
Variables that have been found to have a relationship with supplement use are race or ethnicity, age, education, income and lifestyle variables such as drinking, smoking, and exercising [15,16].
There is documented evidence that the use of NVNM supplements in western society is high, and its use is increasing worldwide [17-20].
In some countries, such as Germany, many botanical products are classified as drugs, and thus are subject to quality, safety, and efficacy regulations [21]. In the United States, although it is acknowledged that some dietary supplements, particularly botanicals, are used to prevent and treat diseases, DSHEA distinguishes these products from drugs and food additives and thus they are not subject to the same regulations [1,4,5]. Use of NVNM supplements increased substantially with the passage of the DSHEA [1], which gave manufacturers greater freedom to market more products as dietary supplements and to provide information about their purported benefits in package labeling and advertising. Although the United States Food and Drug Administration (FDA) regulates additives and drugs, premarket review of dietary supplements is minimal [22].
The use of NVNM supplements has increased recently in many countries, a fact also reflected in our country. However, while the worldwide rate of consumption of these supplements is near to 50% [17-19], it is still rather low in developing countries. This may be put down to indications that those with higher education and income levels seem to be comparatively more likely to use supplements [15]. In Turkey, there is no regulation of NVNM supplements in that they are widely available over the counter from such places as pharmacies and markets without a prescription. There is no regulation or health policy on the use of NVNM supplements, and furthermore, data on the prevalence and use of NVNM supplements are limited or non-existent [23]. Finally, there is a need to understand the frequency with which people use supplements and what variables are associated with particular frequencies of use.
In general, although we consider Turkish NVNM supplement consumption to fit into the prevalence patterns for developing countries, to our knowledge, no data is available either concerning use in Turkish students or the population as a whole. For this reason, the objective of this survey was to quantify the prevalence of NVNMS usage among university students; to identify supplements consumed and rationale for usage; to identify sources of supplement information; and to relate usage to selected demographic characteristics.
Methods
Sampling
The survey was conducted between September 2004 and December 2004 at Osmangazi University, a public university located in the west of Turkey. All students from the schools of medicine, engineering and architecture, science and literature, economics, education, and the college of health services were invited to participate. Participation was voluntary and anonymous, and the Director of the Institution approved the survey.
Subjects
Subjects were randomly selected with a stratified sampling method. Osmangazi University is an urban, mid-sized university with six schools, all of which were included in the survey. At least one class from the first, second, third and fourth years in each department were randomly selected to participate in the survey. The sample size for the survey was determined by multiplying at least 10% by the number of the students: the total numbers of the students in each department and in our survey, respectively, were 1097 and 203 for the school of medicine; 4212 and 561 for the school of engineering and architecture; 3556 and 403 for the school of science and literature; 1394 and 178 for the school of economics; 858 and 177 for the school of education; and 302 and 212 for the college of health services.
Students were excluded from the survey due to: unwillingness to participate (n = 186), handing in incomplete questionnaires (n = 87), and non-attendance of class (n = 109). Thus, the response rate for sample respondents was 83% (1871/2253) of 2253 subjects, with ages ranging from 17 to 28, leaving a total of 1871 students (962 women, 909 men).
Questionnaire and interview schedules
Completion of the questionnaire was self-reporting on the part of the students. The dates on which the study would be conducted were determined in cooperation with class teachers in the schools concerned. The students completed questionnaires in the presence of a member of the research team.
The first section of questionnaire
This section identified consumption of NVNM supplements during the survey or the past year, previous use of dietary supplements, and the probability of students considering the use of NVNM supplements in the near future. If participants reported having used a NVNM supplements during the survey period or the year prior to the study, they were further questioned on a number of topics related to consumption: the number used; the name of the product(s), 73 of which were written on the questionnaire; frequency of use of each product; total product consumption; length of product use; the reasons for using NVNM supplements, revised from previous studies [24,25]; and general demographic information such as age, sex, cigarette smoking, body height and weight, affiliation to which school of the university, class, marital status, parents' education level, and parents' total income level.
The second section of questionnaire
This section included the items related to nutritional beliefs about NVNM supplements. Subjects' views about NVNM supplement use and the health benefits associated with it were used to assess the motivational factors related to supplement use in this population. Items were based on those of previous studies [24-28], and also contained the most frequently consumed food items in the Turkish population. Twenty two opinions were expressed, consisting of such items as 'vitamins and minerals can provide energy', 'maintain health', increase longevity', 'reduce stress' 'prevent colds', 'improve mental function', 'reduce the risk of chronic diseases', or 'aid in recovery from fatigue', all of which were assessed to be commonly-held assumptions connected with use of the supplements. For this section, a five-point Likert scale was used, and responses were scored from one (disagree very strongly) to five (agree very strongly). Thus, the higher score showed a stronger belief on the students' part that NVNM supplements could provide specific health benefits. Applying it to a sample of 59 randomly selected students from same schools assessed the reproductivity of the questionnaire. The students who participated in the test/retest procedure were not included in the final analyses.
Statistical analysis
Frequency, mean, and standard deviation (SD) were calculated, and the t test compared scores on nutritional beliefs between users and non-users, or women and men. The chi-square test (x2) examined the relation between general characteristics and NVNM supplements use. The percentages of the reasons cited for using NVNM supplements arranged according to sex, were calculated by first extracting out of the total figure male and female students' numbers for NVNM supplements usage, and the significance between men and women was evaluated using cross tables. The reliability of the internal consistency of data concerning nutritional beliefs collected from the pretest was calculated by Cronbach's alpha and was found to be 0.96, indicating a high internal consistency across nutritional-belief statements. Consequently, belief statement use was used for the final survey. Statistical analyses were performed using SPSS for Windows (Version 10.0, SPSS Inc., Chicago, Illinois). The standard used for statistical significance was p ≤ 0.05. The data were analyzed using descriptive statistics including means, standard deviations, and frequency distributions.
Results
Of the participants, 909 (48.6%) were men and 962 (51.4%) women. The average age of the participants was 19.9 years (range = 17 to 28 years). Nearly half of the students (49.9%) were between the ages of 19–20. Most (74.8%) were of normal weight. More than 50% of the students (53.9%) were from the schools of engineering and architecture, and science and literature. Most students (72.4%) were in their freshman or sophomore years. Almost 100% (97.9%) were single or divorced. The proportion of students whose mothers had an education level of secondary school and lower was 61.0%, with the figure of 35.0% reported for students' fathers. Most students' level of family income (47.0%) was low. The majority of the students reported living in villages or cities (85.1%), and 26.0% were current smokers. The percentage of those participating in sport was 15.4%, and 18.0% reported exercising more than 3 times per month. Most (74.3%) rated their health as 'good/excellent'. There were significant differences between men and women according to all the descriptive information. The more detailed general characteristics of users and non-users of NVNM supplements are shown in Table 1.
Table 1 General characteristics of users and non-users of nonvitamin/nonmineral supplements
Non-users
n(%)
1563(83.5) Users
n(%)
308(16.5) Total
n(%)
1871(100.0)
Sex x2 = 5.594; p = 0.018
Men 758(83.4) 151(16.6) 909(48.6)
Women 805(83.7) 157(16.3) 962(51.4)
Ages x2 = 35.732; p = 0.000
≤ 18 358(86.7) 55(13.3) 413(22.1)
19–20 789(84.6) 144(15.4) 933(49.9)
21–22 292(85.1) 51(14.9) 343(18.3)
≥ 23 124(68.1) 58(31.9) 182(9.7)
BMI values x2 = 73.392; p = 0.000
Underweight (<18.5) 199(67.7) 95(32.3) 294(15.7)
Normal weight (≥ 18.5 – ≤ 24.99) 1212(86.6) 187(13.4) 1399(74.8)
Overweight (≥ 25 – ≤ 29.9) 121(90.3) 13(9.7) 134(7.2)
Obese (≥ 30 – ≤ 39.9) 31(70.5) 13(29.5) 44(2.4)
Type of school x2 = 23.573; p = 0.000
Medicine 164(79.2) 43(20.8) 207(11.1)
Engineering and architecture 536(88.4) 70(11.6) 606(32.4)
Science and literature 332(82.4) 71(17.6) 403(21.5)
Economics 204(79.7) 52(16.9) 256(13.7)
Education 144(77.0) 43(23.0) 187(10.0)
College of health services. 183(86.3) 29(13.7) 212(11.3)
Year in school ns
Freshman 570(85.6) 96(14.4) 666(35.6)
Sophomore 556(80.8) 132(19.2) 688(36.8)
Junior 168(86.2) 27(13.8) 195(10.4)
Senior 269(83.5) 53(16.5) 322(17.2)
Marital status ns
Single 1520(83.7) 296(16.3) 1816(97.1)
Married 33(82.5) 7(17.5) 40(2.1)
Divorced/widow(er)/separated 10(66.7) 5(33.3) 15(0.8)
Mother's education level x2 = 11.940; p = 0.008
Primary school and lower 848(84.8) 152(15.2) 1000(53.4)
Secondary school 106(74.1) 37(25.9) 143(7.6)
High school 395(84.9) 70(15.1) 465(24.9)
College or university 214(81.4) 49(18.6) 263(14.1)
Father's education level x2 = 7.807; p = 0.050
Primary school and lower 416(87.6) 59(12.4) 475(25.4)
Secondary school 149(83.2) 30(16.8) 179(9.6)
High school 537(81.7) 120(18.3) 657(35.1)
College or university 461(82.3) 99(17.7) 560(29.9)
Family income x2 = 22.971; p = 0.000
Low 763(86.7) 117(13.3) 880(47.0)
Moderate 566(83.4) 113(16.6) 679(36.3)
High 234(75.0) 78(25.3) 312(16.7)
Most permanent place of residence x2 = 13.642; p = 0.001
Village/town 141(79.7) 36(20.3) 177(9.5)
City 1207(85.3) 208(14.7) 1415(75.6)
Metropolis 215(77.1) 64(22.9) 279(14.9)
Smoking status x2 = 15.435; p = 0.000
Nonsmoker 1093(85.7) 183(14.3) 1276(68.2)
Current smoker 390(80.1) 97(19.9) 487(26.0)
Former smoker 80(74.1) 26(25.9) 108(5.8)
Participation in sport x2 = 9.193; p = 0.010
No 724(82.5) 154(17.5) 878(46.9)
Former 580(82.4) 124(17.6) 704(37.6)
Yes 259(89.6) 30(10.4) 289(15.4)
Exercise x2 = 12.205; p = 0.002
Never 440(83.5) 87(16.5) 527(28.2)
Fewer than 3 times per month 862(85.6) 145(14.4) 1007(53.8)
More than 3 times per month 261(77.4) 76(22.6) 337(18.0)
Self-reported health ns
Fair/poor 400(83.2) 81(16.8) 481(25.7)
Good-excellent 1163(83.7) 227(16.3) 1390(74.3)
The duration of supplement use was cited as 'between 1 and 6 months' by 65.3%, followed by 'between 6 and 12 months' and 'more than one year' (23.1% and 11.7%, respectively). More than 50% of supplement users (53.6%) were taking just one supplement at the time of this survey, followed by those using 2 supplements (38.6%) and 3 or more (7.8%). The average number of supplement taken was 1.6 (standard deviation = 0.6). Most students (68.2%) rated the frequency of supplement use as 'once/twice a day' (37.0%) or 'once every other day' (31.2%), followed by 'once/twice a week' (20.5%) and 'once/twice a month' (11.4%). No difference was revealed between men and women by supplement use (Unshown data).
Table 2 presents reasons cited for using NVNM supplements. The four most commonly given reasons for use were 'improvement of energy and vitality' (78.6%), 'promotion of weight loss' (71.1%), followed by 'enhancement of athletic performance' (64.3%) and 'retardation the onset of aging' (63.3%). Women were more likely to be using supplements to promote weight loss, burn-up fat, prevent colds, improve memory, and relieve stress; whereas men were more likely to use supplements to enhance athletic performance, retard the onset of aging, build muscle, and improve sexual function.
Table 2 Reasons cited for using nonvitamin/nonmineral supplements by sex
Men
n(%)
151(49.0) Women
n(%)
157(51.0) Total
n(%)
308(100.0) x2; P values
Improve energy and vitality 128(49.6) 114(50.4) 242(78.6) ns
Promote weight loss 92(42.1) 127(57.9) 219(71.1) 5.59; 0.018
Enhance athletic performance 117(59.1) 81(40.9) 198(64.3) 6.54; 0.011
Retard aging 124(63.6) 71(46.4) 195(63.3) 14.41; 0.000
Burn-up fat 55(35.1) 102(64.9) 157(50.9) 14.07; 0.000
Prevent(threat) colds(sore throat) 41(35.4) 75(64.6) 116(37.6) 9.97; 0.002
Promote skin(hair) health 41(41.8) 57(58.2) 98(31.8) ns
Build muscle 71(74.3) 24(25.7) 95(30.8) 23.25; 0.000
Supplement inadequate diet due to nutrition deficiency 48(53.9) 41(46.1) 89(28.9) ns
Improve memory 33(39.3) 51(60.7) 84(27.3) 3.86; 0.05
Relieve stress (improve mood) 29(37.7) 48(62.3) 77(25.0) 4.67; 0.03
Improve sexual function 55(79.7) 14(20.3) 69(22.4) 24.36; 0.000
Enhance sleep 22(52.4) 20(47.6) 42(13.6) ns
Reduce dangers of cigarette smoking 18(52.9) 16(47.1) 34(11.1) ns
Improve circulation 18(58.1) 13(41.9) 31(10.1) ns
Gain weight 18(62.1) 11(37.9) 29 (9.4) ns
Prevent illnesses such as cancer, osteoporosis, menopause, hypertension, kidney stones 9(42.9) 12(57.1) 21 (6.8) ns
Note: Subjects could list more than one reason for nonvitamin, nonmineral supplement usage
In general, when the scores obtained from all the nutritional beliefs between men and women were taken into consideration, women agreed on the effects obtained from taking NVNM supplements more strongly than men in the categories: 'important in maintaining health', 'stress reduction', and 'enhancement sleep', whereas men agreed more strongly on 'improvement sexual function' than women (Unshown data).
Twenty-six of the 308 NVNM users (26/308, 8.4%) reported having had an adverse reaction to an NVNM supplement. Of 26, the two most adverse effects were nausea and vomiting (61.5%, 30.7%, respectively), followed by gastrointestinal disturbances (15.4%), flashing (11.5%) and liver insufficiency (7.7%), Subjects could list more than one complication cited for NVNM usage (Unshown data).
The most frequent used sources for obtaining information about supplements were television (76.3%), magazines/newspapers (41.5%) and internet websites (37.3%); followed by family (20.1%), friends (19.8%), school and teachers (16.5%), books (13.3), radio (5.8%), health food stores (0.5%) and agricultural engineers (0.3%). The rates of those citing dietetic professionals, and doctor and nurse as their sources were only 4.2% and 6.8%, respectively (Unshown data).
Of 1871, 308 students (16.5%) reported using NVNM supplements during the past year, 23.0% students indicated that they were considering NVNM use in the near future. About 10% (9.7%) reported past usage. The data revealed no difference between men and women according to supplement usage. There were also no differences between men and women in the categories 'use of NVNM during the past year', 'considering NVNM supplement use in the future', and 'past usage of NVNM supplements' (p > 0.05 for each one) (Unshown data).
Of the 1690 students reporting no use of NVNM supplements in the past, 44.3% indicated that they had not considered using supplements, 34.7% reported that they had only thought about using supplements, and 11.6% reported that they had been unaware of the presence of supplements. There was a 9.4% non-response rate (Unshown data).
Table 3 summarizes information regarding the prevalence of NVNM supplement use. The three most commonly used supplements were reported as echinacea, ginseng, and gingko biloba (38.6%, 36.4%, and 32.8%, respectively). Since all of the 73 most commonly purchased supplements in Turkey and the world were listed on the questionnaire, the students reported using no supplements other than those listed.
Table 3 Prevalence of use of nonvitamin, nonmineral supplements
Total
n(%)
308(100.0)
Echinacea 119(38.6)
Ginseng 112(36.4)
Gingko biloba 101(32.8)
Protein powder and or Amino acids 89(28.9)
Fish oil 84(27.3)
Bee pollen 78(25.3)
Garlic 64(20.8)
Green Tea 61(19.8)
Bee pollen 57(18.5)
St. John's wort 51(16.5)
Ginger 47(15.2)
Creatine 45(14.6)
Aloe 27 (8.7)
Lecithin 25 (8.1)
Flax 21 (6.8)
Chestnut seed 19 (6.2)
Valerian 16 (5.2)
Burdock root 15 (4.9)
Coenzyme Q 15 (4.9)
Goldenseal 12 (3.9)
Cranberry 11 (3.6)
Guarana 9 (2.9)
Chamomile tea 8 (2.6)
Sam-E 7 (2.3)
Kava kava 7 (2.3)
Melatonin 6 (1.9)
Dong Quai 4 (1.3)
Angelica 3 (0.9)
Cayenne 2 (0.6)
Borage 2 (0.6)
Astragalus 1 (0.3)
Evening primrose 1 (0.3)
The percentages total to more than 100% because some respondents reported taking more than one NVNM supplement
Table 4 shows that NVNM supplement use correlated to nutritional beliefs. Of all the beliefs, the links between 'supplement use and recovery from fatigue' and 'supplement use and prevention/threat colds/sore throat' were the ones with which users and non-users most agreed. The lower degree of perception of any 'relationship between supplement use and improved mental health' was similar between users and non-users. In general, when all the nutritional beliefs between users and non-users were taken into consideration, users agreed on the effects obtained from taking NVNM supplements more strongly than non-users except for the categories of 'prevention/threat of colds/sore throat', 'prevention of mental illnesses', 'burning-up fat accumulating in the body', 'promotion of more weight loss', and 'reduction of the harmful effects of cigarette smoking'. Of the 22 beliefs, the score from only one item, 'burning-up fat accumulating in the body' was found to be lower in users than in the non-users.
Table 4 Nutritional beliefs about nonvitamin/nonmineral supplements of supplement users and non-users*
Belief statement Non-users†
n(%)
1563(83.5) Users†
n(%)
308(16.5) P values‡
Improve energy and vitality 2.8 ± 0.8 3.2 ± 0.8 0.000
Important in maintaining health 2.9 ± 0.8 3.3 ± 0.8 0.000
Provide living longer 2.7 ± 0.8 2.8 ± 0.7 0.000
Help recovery from fatigue 3.0 ± 0.8 3.3 ± 0.7 0.000
Reduce stress 2.8 ± 0.7 3.0 ± 0.8 0.012
Prevent/threat colds/sore throat 3.1 ± 0.8 3.2 ± 0.7 ns
Prevent mental illnesses 2.7 ± 0.8 2.8 ± 0.8 ns
Improve mental health 2.6 ± 0.8 2.7 ± 0.8 0.016
Reduces risk of chronic illnesses 2.8 ± 0.7 3.0 ± 0.8 0.000
Retard aging 2.7 ± 0.9 2.9 ± 0.8 0.000
Burn fat accumulating in the body 2.9 ± 0.8 2.8 ± 0.8 ns
Promote weight loss more 2.8 ± 0.7 2.9 ± 0.8 ns
Build muscle more 2.9 ± 0.8 3.1 ± 0.7 0.000
Enhance athletic performance 2.9 ± 0.8 3.1 ± 0.8 0.001
Enhance sleep 2.8 ± 0.8 3.0 ± 0.8 0.000
Improve sexual function 2.8 ± 0.8 3.0 ± 0.8 0.000
Improve circulation 2.9 ± 0.8 3.2 ± 0.7 0.000
Supplement inadequate diet due to nutrition deficiency 2.9 ± 0.8 3.2 ± 0.8 0.000
Improve memory 2.8 ± 0.8 3.0 ± 0.8 0.001
Promote skin/hair health 2.9 ± 0.8 3.1 ± 0.8 0.000
Gain weight 3.0 ± 0.8 3.1 ± 0.8 0.009
Reduce dangers of cigarette smoking 2.7 ± 0.9 2.8 ± 0.9 ns
*Values are shown as mean ± standard deviation
† A five-point Likert scale was used; disagree very strongly (one point) to agree very strongly (five points)
‡ t test
Discussion
To our knowledge, this is the first survey on NVNM supplements use conducted in Turkey. This survey allowed the assessment of the prevalence of NVNM supplement use in a sample of university students from different departments.
Our results indicate that about one in six students (16.5%) consumed one or more NVNM supplement during the past year. While our finding is compatible with some other study results, it is not with others: Radimer et al. [3] found that between 3.3 and 12% of respondents to their survey reported using NVNM supplements in 1994 and 1995, respectively. In a survey on a 1000 non-patient student population by Perkin et al. [25], a NVNM supplement usage rate of 26.3% was observed. Eisenberg et al. [29] reported this proportion as 12.1%. Furthermore, in a survey relevant to NVNM supplement use over a 12-month period by adult members of a large health maintenance organization, an estimated 32.7% of adults used at least one NVNM supplement [30]. Newberry et al. [31] reported that out of 272 college students canvassed, 48.5% had taken an NVNM supplement during the previous year and in a survey in the United States, it was found that 14.5% of the adults reported having used a NVNM supplement during the previous year [32]. The aforementioned studies show that the rate of NVNM supplement usage ranges from 3.3 to 48.5%. One explanation for these differences in reported usage rates could be the variation in how questions were asked regarding time frame and the types of supplements used. A further possibility could be relevant to individuals' sociodemographic characteristics, such as race or ethnicity, age, education, income and lifestyle variables such as drinking, smoking, and exercising [15,16].
As in other populations, echinacea, ginseng, gingko biloba, and protein powder and or amino acids were reported by this population to be the most popular supplements [3,33-35]. Wingate [33] found that in 1997 the three most reportedly used supplements were garlic, ginseng, and ginkgo biloba. Similarly, the three most commonly consumed NVNM supplements reported in the Slone Survey [36], conducted from 1998 to 1999, were ginseng, ginkgo biloba extract, and allium sativum. This high use of supplements in Turkey and the rest of the world may be due to the fact that those products are prevalent in the market.
In this survey, most students reported that they were healthy. This was reflected in the rationale offered by the students for supplement usage, such as increasing energy and enhancing athletic performance.
In this survey, a positive relationship was seen to exist between exercising and NVNM supplement usage. Both behaviors may be perceived as congruent with disease prevention. NHANES III [3] also found a positive relationship between exercise and NVNM usage.
The current survey found that former smokers used NVNM supplements most, which is in line with the NHANES III survey [3]. One explanation for this is that usage could be viewed as offsetting a negative behavior [25].
In this survey, 9.7% of the students reported past usage, 16.5% currently usage and 23.0% potential for use in the future. That these findings show increasing trends in the use of supplements with a corresponding increase in time may be due to media reports or advertisements in local newspapers about provision of energy and vitality, an increase in athletic performance, the retarding of aging, and the reduction of the risk of chronic diseases such as hypertension, colon cancer, breast cancer, kidney stones, and osteoporosis [37-39]. A further explanation may be that the use of NVNM supplements increased substantially with the passage of the United States Dietary Supplement Health and Education Act of 1994 (DSHEA), which gave manufacturers greater freedom to market more products through purported benefits reported in package labeling and adverting [1].
Twenty-six of the 308 NVNM users (26/308, 8.4%) reported having experienced an adverse reaction to an NVNM supplement. This rather high rate is in line with results published by Newberry et al. [31], which reported a reaction rate of 6.9%. This may be due to the fact that the majority of the students did not seek nutrition information from reliable sources such as doctors, nurses or dietetic professionals. In this survey, only 11.0% of supplement users cited doctors, nurses, and dietetic professionals as sources of information. However, it is important that students get nutrition information from reliable sources and receive proper nutrition education. To put this another way, that 76% of the respondents obtained information about supplementation from television may indicate that television has enormous implications for educational and public policy initiatives, and that television should be used to get more health information about supplementation.
The nutritional beliefs that subjects questioned had concerning supplements were an important factor for their use of supplements. Supplement users agreed more strongly than non-users on the health benefits of supplement use for the majority of items. Others reported similar findings [9,26].
In this survey, NVNM supplement use was higher in men than in women, in line with Radimer et al.' survey [3]. However, these findings are not concordant with data reported from Malaysia (40), where the prevalence of supplement use was higher in women (14.9% vs. 9.7%, respectively). No apparent reasons were disclosed for such differences; it is possible that NVNM supplement use might be related to a desire to increase athletic performance in men [41], but further studies are needed to better assess this result.
In this survey, nutritional knowledge average scores were low in both sexes (63.3 ± 12.4 for a maximum score of 110), probably because of the absence of nutritional education in primary, secondary, high schools or university in our country.
NVNM supplement use by the students was different according to sex, age, Body Mass Index (BMI) values, school type, mother and fathers' education levels, family income, most permanent place of residence, smoking status, participating in sport, and exercise. This finding shows that the rationale for supplements use changes according to subjects' general characteristics.
Of further interest is the trend for more female students in the current sample to indicate use of significantly more supplements than males. Parallel to our survey, this finding highlights the fact that female students are more likely to be dieting to lose weight, whereas male students are more likely to be controlling their diet to gain weight and build muscle, which is compatible with some other studies [42,43].
We are well aware of the limitations of the present survey. Firstly, it was performed in a single institution, and therefore the sample may not be representative of all Turkish students. Another limitation on the data was the use of the self-reporting system employed in this survey. This may have given rise to bias.
Conclusion
This descriptive analysis helps to provide a clearer picture of NVNM supplement use. Not only does it indicate that students are indeed using or considering using supplements as a viable means to achieve their short-term fitness and or appearance goals, but also which products are most likely to be used, and indeed which individuals are most in need of education and information concerning the use and abuse of certain dietary aids. Further research, therefore, needs to focus on how NVNM nutritional supplements use information can be applied to specific user groups.
Monitoring the use of NVNM supplements within the community or university students should be of interest because these substances may affect health or interact with other medications [44]. The respondents in this survey reported 85 cases of interactions between St John's wort and prescription medications. Dietetic professionals and physicians need to consider evaluating NVNM supplement use when assessing overall nutrient and medication use by clients or students.
In summary, our results in this sample of Turkish students indicate that the prevalence of NVNM supplement use is still relatively modest, and neither associated with a healthier lifestyle nor related to a better nutritional knowledge. The need for further research on the relationships between dietary supplements and health has also been highlighted in the 1997 report by the United States Commission on Dietary Supplement Labels [45].
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
AU conceived of the study, performed its design and coordination, sequence alignment, collected the data, performed the statistical analyses and drafted the manuscript, SN and SO collected the data and entered the data to SPSS packet program, All authors read and approved the final manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
We thank all the students from the University of Osmangazi, Eskisehir, who participated in this survey, and the lecturers of the schools, who helped in the collection of data.
==== Refs
Dietary Supplement Health and Education Act of 1994 Publ No 103-417, 108 Stat 4325 October 25, 1994
Hankin J Keeping up with the increasing popularity of nonvitamin, nonmineral supplements J Am Diet Assoc 2000 100 419 420 10767896 10.1016/S0002-8223(00)00129-2
Radimer KL Subar AF Thomsan FE Nonvitamin, nonmineral dietary supplements: Issues and findings from NHANES III J Am Diet Assoc 2000 100 447 454 10767902 10.1016/S0002-8223(00)00137-1
Nesheim MC Regulation of dietary supplements Nutr Today 1998 33 62 68
Nesheim MC What is the research base for the use of dietary supplements? Public Health Nutr 1999 2 35 38 10452729
Worthington RB Breskin M Supplementation patterns of Washington State dietitians J Am Diet Assoc 1984 84 795 800 6736507
Read MH Bock MA Carpenter K Medeiros D Ortiz M Raab C Schutz H Sheehan E Williams DK Health beliefs and supplement use: adults in seven western states J Am Diet Assoc 1989 89 1812 1813 2592714
Schulz IO Factors influencing the use of nutritional supplements by college students with varying levels of physical activity Nutr Res 1988 8 459 466
Thompsen PA Terry RD Amos RJ Adolescents' beliefs about and reasons for using vitamin/mineral supplements J Am Diet Assoc 1987 87 1063 1065 3611554
Wolfe RR Protein supplements and exercise J Am Clin Nutr 2000 551 557
Rubinstein ML Federman DG Sports supplements. Can dietary additives boost athletic performance and potential? Postgrad Med 2000 108 103 106 11021262
Smith J Dahm DL Creatine use among a select population of high school athletes Mayo Clin Proc 2000 75 1257 1263 11126833
Clarkson PM Nutrition for improved sports performance. Current issues on ergogenic aids Sports Med 1996 21 393 401 8784959
National Institutes of Health What are Dietary Supplements? Office of Dietary Supplements Web Site Accessed February 8, 2000
Messerer M Johansson S-E Wolk A Sociodemographic and health behaviour factors among dietary intake among dietary supplement and natural remedy users Eur J Clin Nutr 2001 55 1104 1110 11781678 10.1038/sj.ejcn.1601272
Greger JL Dietary supplement use: consumer characteristics and interests J Nutr 2001 131 1339S 1343S 11285350
Eisenberg DM Kessler RC Foster C Norlock FE Calkins DR Delbanco TL Unconventional medicine in the United States-Prevalence, Costs, and Patterns of Use N Engl J Med 1993 328 246 252 8418405 10.1056/NEJM199301283280406
Fisher P Ward A Medicine in Europe: Complementary medicine in Europe BMJ 1994 309 107 111 8038643
MacLennan AH Wilson DH Taylor AW Prevalence and cost of alternative medicine in Australia Lancet 1996 347 569 573 8596318 10.1016/S0140-6736(96)91271-4
Barnes J Abbot NC Harkness EF Ernst E Articles on complementary medicine in the Mainstream medical literature: an investigation of MEDLINE, 1966 through 1996 Arch Intern Med 1999 159 1721 5 10448774 10.1001/archinte.159.15.1721
Mitka M FDA never promised an herb garden-but sellers and buyers eager to see one grow JAMA 1998 280 1554 1556 9820245 10.1001/jama.280.18.1554
Kurtzweil P An FDA guide to dietary supplements FDA Consumer 1998 32 28 35 9779010
Erozturk N Bir Yudum Saglik, Anahtar Kitaplar yayinevi, Istanbul 2000
Kim SH Han JH Keen CL Vitamin and mineral supplement use by healthy teenagers in Korea: Motivating factors and dietary consequences Nutrition 2001 17 373 380 11377129 10.1016/S0899-9007(00)00582-7
Perkin JE Wilson WJ Schuster K Rodriguez J Chabot AL Prevalence of nonvitamin, nonmineral supplement usage among university students J Am Diet Assoc 2002 102 412 414 11902377 10.1016/S0002-8223(02)90096-9
Eldridge AL Sheehan ET Foot supplement use and related beliefs: survey of community college students J Nutr Edu 1994 26 259
Sobal J Muncie HL Vitamin/mineral supplement use among adolescents J Nutr Edu 1988 20 314
Bell A Dorsch KD Mccreary DR Hovey R A look at nutritional supplement use in adolescents J Adolescent Health 2004 34 508 516 10.1016/j.jadohealth.2003.07.024
Eisenberg DM Davis RB Ettner SL Appel S Wilkey S Rombay MV Kessler RC Trends in alternative medicine use in the United States, 1990–1997: Results of a follow-up national survey JAMA 1998 280 1569 1575 9820257 10.1001/jama.280.18.1569
Americans' Food and Nutrition Attitudes and Behaviors American Dietetic Association's Nutrition and You Trends 2000 Accessed October 2, 2004
Newberry H Beerman K Duncan S McGuire M Hillers V Use of nonvitamin, nonmineral dietary supplements among college students J Am Coll health 2001 50 123 129 11765248
Millen AE Dodd KW Subar AF Use of vitamin, mineral, nonvitamin, nonmineral, and nonmineral supplements in the United States: The 1992, and 2000 National Health Interview Survey Results J Am Diet Assoc 1987 104 942 950 15175592 10.1016/j.jada.2004.03.022
Wingate P Consumers not supplement brand survey Natural Food Merchandiser 1998 Boulder, CO: New Hope Communications
Bennet J Brown CM Use of herbal remedies by patients in a health maintenance organization J Am Pharm Assoc (Wash) 2000 40 353 358 10853535
Planta M Gundersen B Petitt JC Prevalence of the use of herbal products in a low-income population Fam Med 2000 32 252 257 10782371
Kaufman DW Kelly JP Rosenberg L Anderson TE Mitchell AA Recent patterns of medication use in the ambulatory adult population of the United States: The Slone Survey JAMA 2002 287 337 344 11790213 10.1001/jama.287.3.337
Miller GD Anderson JJ The role of calcium in prevention of chronic diseases J Am Coll Nutr 1999 371 372
Singh V Raidoo D Harries CS The prevalence, patterns of usage and people's attitude towards complemantaryand alternative medicine among the Indian community in Chatsworth, South Africa BMC Complementary and Alternative Medicine 2004 3 1 7
Fennel D Determinants of supplement usage Preventive Med 2004 39 932 939 10.1016/j.ypmed.2004.03.031
Mazlan Bin Y Vitamin use and beliefs among students at a Malaysian university J R Soc Health 1990 110 132 134 2121980
Schwenk TL Costley CD When food becomes a drug: nonanabolic nutritional supplements use in athletes Am J Sports Med 2002 30 907 916 12435662
Rosen JC Gross J Prevalence of weight reducing and weight gaining in adolescent girls and boys Health Psychol 1987 6 131 147 3470177 10.1037//0278-6133.6.2.131
McCreary D Sasse DK Gender differences in high school students' dieting behavior and their correlates Int J Mens Health 2002 1 195 213
Fugh-Berman A Ernst E Herb-drug interactions: Review and assessment of report reliability J Clin Pharmacol 2001 52 587 595 10.1046/j.0306-5251.2001.01469.x
Report of the Commission on Dietary Supplement Labels Washington, DC: Office of Disease Prevention and Health Promotion 1997
| 15904512 | PMC1173114 | CC BY | 2021-01-04 16:28:56 | no | BMC Public Health. 2005 May 16; 5:47 | utf-8 | BMC Public Health | 2,005 | 10.1186/1471-2458-5-47 | oa_comm |
==== Front
BMC Public HealthBMC Public Health1471-2458BioMed Central London 1471-2458-5-521591068210.1186/1471-2458-5-52Research ArticleAre non-responders in a quitline evaluation more likely to be smokers? Tomson Tanja [email protected]örnström Catrine [email protected] Hans [email protected] Asgeir [email protected] Stockholm Center for Public Health, Tobacco Prevention, Box 175 33, 118 91 Stockholm, Sweden2 Department of Public Health Sciences, Karolinska Institutet, Norrbacka S2, 171 76 Stockholm, Sweden3 Department of Oncology-Pathology, Karolinska Institutet, Sweden2005 23 5 2005 5 52 52 15 3 2005 23 5 2005 Copyright © 2005 Tomson et al; licensee BioMed Central Ltd.2005Tomson et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
In evaluation of smoking cessation programs including surveys and clinical trials the tradition has been to treat non-responders as smokers. The aim of this paper is to assess smoking behaviour of non-responders in an evaluation of the Swedish national tobacco cessation quitline a nation-wide, free of charge service.
Methods
A telephone interview survey with a sample of people not participating in the original follow-up. The study population comprised callers to the Swedish quitline who had consented to participate in a 12 month follow-up but had failed to respond. A sample of 84 (18% of all non-responders) was included. The main outcome measures were self-reported smoking behaviour at the time of the interview and at the time of the routine follow-up. Also, reasons for not responding to the original follow-up questionnaire were assessed. For statistical comparison between groups we used Fischer's exact test, odds ratios (OR) and 95% confidence intervals (CI) on proportions and OR.
Results
Thirty-nine percent reported to have been smoke-free at the time they received the original questionnaire compared with 31% of responders in the original study population. The two most common reasons stated for not having returned the original questionnaire was claiming that they had returned it (35%) and that they had not received the questionnaire (20%). Non-responders were somewhat younger and were to a higher degree smoke-free when they first called the quitline.
Conclusion
Treating non-responders as smokers in smoking cessation research may underestimate the true effect of cessation treatment.
==== Body
Background
Tobacco is one of the leading causes of the global burden of disease, [1] demanding effective intervention strategies [2]. Smoking cessation treatment is generally considered to be among the most cost-effective life saving interventions in the health system [3] and telephone helplines for smoking cessation (quitlines) have proved to be both effective and cost-effective [4-6].
In evaluation of smoking cessation programs including surveys and clinical trials the tradition has been to treat non-responders as smokers [7-12]. However, bias due to failure to respond to follow-up is seldom assessed [13] for the different types of interventions and presently no reliable data exists supporting the pre-judgement that non-responders are more likely than responders to be present smokers. The existing empirical data on difference in smoking between responders and non-responders is often based on public health surveys [10]. However, the possibility exists that non-responders in smoking cessation programs using a telephone quitline may differ from non-responders in general health surveys. Thus, to categorically classify non-responders as smokers may underestimate the true effectiveness of smoking cessation treatment [9]. To our knowledge no previous studies investigating telephone treatment for smoking cessation have assessed the effect of non-response on reported abstinence rates.
In the present study we compare abstinence rates and population characteristics in responders and non-responders included in an evaluation of the Swedish quitline and assess reasons for not responding to the original follow-up questionnaire.
Methods
Study population
The original study base included 1606 individuals in different stages of change who 12 months earlier had contacted the Swedish quitline for help with smoking cessation. All had accepted to receive a follow-up questionnaire 12 months after first contact with the quitline and participated in the original follow-up. First contacts were made from February 2000 to November 2001 and the follow-up questionnaires were mailed out February 2001 to November 2002. After two reminders answers were collected from 1131 individuals (70%) leaving 475 non-responders. A sample of 84 (18 % of the total non-response) was included in the present assessment of non-responders (Fig 1). In the beginning of November 2002 we identified all 84 patients who had not responded to the follow-up questionnaire during the previous four months. The relative narrow time window was to minimise recall bias.
Figure 1 Graphic description of subjects in the study base.
Data collection
The non-responders were contacted by a telephone interview during the autumn 2002. Each interview took approximately five minutes to perform and was conducted by only one person, to minimise interviewer bias. Attempts were made to phone first three times during daytime and then twice during evenings/weekends. Since all subjects had completed a questionnaire earlier (following their first call to the quitline) all background information, such as gender, age, language, tobacco habits and telephone number, was already available. In the original follow-up questionnaire abstinence was defined as "not a single puff of smoke during the previous seven days", which is a commonly used definition of point prevalence abstinence in larger surveys [12,14,15]. Two questions were used to assess present smoking behaviour: Have you smoked at least one single puff during the previous seven days? Has your smoking behaviour changed since you received the follow-up questionnaire? An additional retrospective question was asked to assess smoking behaviour at the time of the original 12 month follow-up: Have you smoked (one puff or more) in the week previous to receiving the follow-up questionnaire? The date when the original questionnaire was sent out was specified for all subjects. The interview was completed with a question on why he/she had not returned the original questionnaire. Ethical approval was obtained by Karolinska Institutet (Dnr 00-367).
Statistical methods and presentation of data
We compared the prevalence of abstinence in the original study population (responders) with the 46 non-responders participating in the present study. In the table we start by comparing abstinence in the two groups at the time of the original follow-up and then at the time of the telephone interview.
Reasons stated by the subjects for not returning the original follow-up questionnaire are presented in a table as proportion of those 46 participating in the telephone interview. Reasons identified by the interviewer for not participating in the telephone interview are presented in the text as proportion of those 38 not participating.
Non-responders (at 12 month follow-up) participating in the telephone interview were compared with responders in the original study population in terms of population characteristics (sex, age, smoke-free at first call, and using nicotine at first call). These data are presented in table form. In the table we also present background data on all 84 non-responders selected for the study and the 38 non-responders not participating in the telephone interview. In the table we dichotomised age as a two category variable (≤40, ≥41), nicotine use at baseline as "yes" or "no" and stages of change as "still smoking at the time of first contact" and "smoke free at the time of first contact".
For statistical comparison between groups we calculated Fisher's exact test, odds ratios (OR) and 95% confidence intervals (CI) on proportions and OR. In table 1 we used one- sided CI on the proportions since our main focus was on the lower limits. Statistical analyses were carried out using the Statistical Package for the Social Sciences (SPSS 11.5).
Table 1 Percentage and proportions of abstinence in the original study population (responders) and the present study population (non-responders) at 12 months follow-up, and at the time of the telephone interview.
Original study population The present study population participating in the telephone interview
Abstinent at 12 months Abstinent at 12 months Abstinent at the time of the tel. Interview
% (n/N) One-sided 95%CI % (n/N) One-sided 95%CI % (n/N) One-sided 95%CI
Men 30 (69/226) 63 (5/8) 38 (3/8)
≥25 ≥29 ≥11
Women 31(285/905) 34 (13/38) 26 (10/38)
≥29 ≥22 ≥15
Total 31 (354/1131) 39 (18/46) 28 (13/46)
≥29 ≥27 ≥18
Results
Of the 84 subjects not responding to the original questionnaire at 12 month follow-up (non-responders) recruited for the study base 55% (46/84) participated. Of the 38 subjects not participating 61% (23/38) could not be reached, 29% (11/38) declined, and 10% (4/38) were either sick or dead (not in table).
Abstinence
Of the 46 subjects participating in the present study 39% reported to have been smoke-free at the time when they received the original follow-up questionnaire (abstinent at 12 months) compared with 31% of responders in the original study population (Table 1). No significant difference in abstinence was noted between the present study population and the original study population (Table 1). However, men in the present study population were somewhat more likely to report being abstinent at 12 months compared with the men in the original study population (Table 1). The reported higher level of 12 months abstinence in men did not persist at the time of the telephone interview (Table 1). One woman did not remember whether or not she was abstinent at twelve months and was treated as a smoker.
Reasons for not returning the postal questionnaire
The most common reason stated for not having returned the original questionnaire was claiming that they had returned it (Table 2). Approximately one in ten stated that they had believed that abstinence was a prerequisite for answering and therefore had not returned the questionnaire since they were smoking at the time (Table 2).
Table 2 Stated reasons among 46 participants for not returning the postal questionnaire
% (n)
Claimed to have returned the questionnaire 35 (16)
Had not received the questionnaire/moved 20 (9)
Thought abstinence was a prerequisite for answering 13 (6)
Do not know 13 (6)
Forgot to return it 9 (4)
Uninterested 6 (3)
Had lost the questionnaire 4 (2)
Total 100 (46)
Comparison with responders
The non-responders comprising the study base in the present study were somewhat younger than the responders in the original study population (Table 3). The mean ages being 47 for the responders and 42 for the non-responders (data not in table). Men and women were equally represented both among responders and non-responders. Non-responders tended to a higher degree to have been smoke-free when they first called the quitline (Table 3). They were also significantly more likely to have been totally nicotine free at first call compared with the responders (Table 3).
Table 3 Population characteristics of responding and non-responding subjects. Comparing 46 non-responders participating in the non-response analysis with the 1131 responders in the original study population.
Total Total sample of non-responders Non-responders not participating in the telephone interview Non-responders participating in the telephone interview Responders in the original study Comparison ¶
% (n) 100 (84) % (n) 100 (38) % (n) 100 (46) % (n) 100 (1131) OR 95%CI
Sex
Male (Ref) 20 (17) 24 (9) 17 (8) 20 (226)
Female 80 (67) 76 (29) 83 (38) 80 (905) 1.2 0.5 – 2.6
Age distribution:
≥ 41 (Ref) 58 (49) 61 (23) 57 (26) 67 (755)
≤ 40 42 (35) 39 (15) 43 (20) 33 (376) 1.5 0.9 – 2.8
Smoke-free at first call:
No (Ref) 73 (61) 76 (29) 70 (32) 77 (875)
Yes 27 (23) 24 (9) 30 (14) 23 (256) 1.5 0.8 – 2.8
Using nicotine* at first call:
Yes (Ref) 82 (69) 87 (33) 78 (36) 89 (1010)
No 18 (15) 13 (5) 22 (10) 11 (121) 2.3 1.1 – 4.8
*Total consumption of nicotine, including smoked and smoke-free tobacco and NRT.
¶Comparing non-responders participating in the telephone interview to responders
Discussion
Our results indicate that non-responders in follow-ups of large cohorts of smokers trying to quit with the aid of telephone quitlines, should not by definition be considered as treatment failures.
If anything, the non-responders in the present study reported higher abstinence rates at the time when they were supposed to return the original follow-up questionnaire. The observed trend of overrepresentation of non-smokers among non-responders may be explained by the fact that they were more likely to be nicotine free at first call to the quitline. In the original follow-up we presented data separately for different stages of change. Those who were in the contemplation stage at first call reported 12-month abstinence in 19% of the cases compared with 22% for those in preparation and 53% for people who were in the action stage at first call [14]. Thus, being nicotine free at first call is a significant predictor for abstinence at 12 months. Our results indicate that classifying non-responders as smokers may underestimate the true treatment effect of quitlines in line with a recent Dutch study [17].
There is a tendency to view non-responders as a homogenous group with common characteristics but studies have not confirmed this to be the case [16]. A previous Swedish study comparing prevalence of smokers amongst non-responders to a general health survey with responders, showed a tendency for an overrepresentation of smokers amongst non-responders, especially in low income groups [10]. Contrary, a study from Holland did not find such differences [18]. However, caution is needed when comparing these studies to the present study since it is possible that non-responders in general health surveys may differ from non-responders in studies assessing abstinence rates after smoking cessation treatment.
Based on a response rate of approximately 70% in the original study, our results suggest that non-responders in the assessment of quitlines are probably not more likely than responders to be smokers at the time of follow-up. However, the possibility exists that non-responders in studies with lower response rate may differ from the present study population and our results may only apply for studies with a similar or higher response rate. The present results are in line with a study based on a one-year follow-up of participants from a national "Quit and Win" contest where bias in smoking prevalence because of non-response was studied [19].
Approximately one in three (29%) of those who were reached by telephone refused to participate in the interviews. There is a high probability that those individuals may be present smokers.
Methodological considerations include the relative low number of subjects compromising statistical power. The data indicate that non-responders are not more likely than responders to be smokers. However, owing to small numbers we are not able to conclude that the non-responders may be more likely to be smoke-free as the data indicates.
Another problem is the retrospective assessment of smoking behaviour at the time the non-responders were supposed to have turned in the questionnaire. Obviously recall bias may have affected the answers. A more conservative way to interpret the data is to compare the responders in the original study with non-responders smoking behaviour at the time of the telephone interview (Table 1, columns one and three). This more conservative comparison does not change the main results that using methods with no visual contact between counsellor and patient, non-responders may well fail to respond due to other reasons than active smoking.
As in all questionnaire surveys on smoking cessation the possibility of underreporting of smoking may exist e.g. due to the impact of social desirability (the desire to appear good). However, since this would most probably affect all subjects equally it is not a major concern in the present study. Also, a self-reported smoking status appears to be a reliable indicator of actual smoking-status [20] and the effect of social desirability in smoking cessation studies is probably less than previously suggested [21]. Further, in a recent study assessing if subjects who decline cotinine tests are lying about their smoking behaviour it was found that failure to comply may result from external factors such as demands or random factors such as being too busy at the time [22]. In the present study, thirteen percent stated that they thought abstinence was a prerequisite for returning the questionnaire (Table 2). This is a pedagogical problem that needs to be taken seriously since this may be a potential source of bias although not a major problem in the present study.
Conclusion
The present study, one of the first of its kind, indicates that routinely treating non-responders as smokers in smoking cessation research may underestimate the true effect of cessation treatment.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
Tanja Tomson have made substantial contributions to conception and design, analysis and interpretation of data. She has been writing all drafts of this paper.
Catrine Björnström have contributed in the planning, design and analysis of this paper and have given final approval of the version to be published.
Hans Gilljam participated in the planning of the study design and assisted in the writing of the paper. He have given final approval of the version to be published
Asgeir Helgason have made substantial contributions to conception and design, analysis and interpretation of data. He has been involved in drafting the paper and have given final approval of the version to be published.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
The authors would like to thank Mats Toftgård (Tobacco Prevention) for statistical advice. All staff members at the Swedish quitline are also acknowledged.
The Swedish quitline is funded by the Swedish Government through, The National Institute of Public Health, and the Swedish Cancer Society.
==== Refs
Ezzati M Rodgers A Vander Hoorn Anthony Rodgers Stephen Vander Hoorn Cristopher MurrayJL the Comparative Risk Assessment Collaborating Group Selected major risk factors and global and regional burden of disease Lancet 2002 360 1347 1360 12423980 10.1016/S0140-6736(02)11403-6
Ezzati M Lopez Ad Estimates of global mortality attributable to smoking in 2000 Lancet 2003 362 847 852 13678970 10.1016/S0140-6736(03)14338-3
Tengs TO Adams ME Pliskin JS Safran DG Siegel JE Weinstein MC Graham JD Five-hundred life-saving interventions and their cost-effectiveness Risk Anal 1995 15 369 390 7604170
Zhu S-H Anderson CM Tedeschi GJ Rosbrook B Jonson CE Byrd M Guitierrez-Terrell E Evidence of real-world effectiveness of a telephone quitline for smokers N Engl J Med 2002 347 1087 1093 12362011 10.1056/NEJMsa020660
World Bank Curbing the epidemic: governments and the economics of tobacco control 1999 6 Washington (DC): The World Bank 67 85
Tomson T Helgason Á Gilljam H Quitline in smoking cessation – a cost-effectiveness analysis Int J Technol Assess Health Care 2004 20 469 474 15609797
Kotaniemi J-T Hassi J Kataja M Jönsson E Laitinen LA Sovijärvi ARA Lundbäck B Does non-responder bias have a significant effect on the results in a postal questionnaire study? Eur J Epidemiol 2001 17 809 817 12081098 10.1023/A:1015615130459
Janzon L Hanson BS Isacsson S-O Lindell S-E Steen B Factors influencing participation in health studies. Results from prospective population study "Men born in 1914" in Malmö, Sweden J Epidemiol Community Health 1986 40 174 177 3746180
Rönmark E Lundqvist A Lundbäck B Nyström L Non- responders to a postal questionnaire on respiratory symptoms and diseases Eur J Epidemiol 1999 5 293 299 10.1023/A:1007582518922
Boström G Hallqvist J Haglund BJA Romelsjö A Svanström L Diderichsen Socioeconomic Differences in Smoking in an urban Swedish Population Scand J Soc Med 1993 21 77 82 8367686
Hill A Roberts J Ewings P Gunell D Non-response bias in a lifestyle survey J Public Health Med 1997 19 203 207 9243437
Lichtenstein E Glasgow RE Smoking cessation: What Have We Learned Over the Past Decade? J Consult Clin Psych 1992 60 518 527 10.1037//0022-006X.60.4.518
Austin MA Criqui MH Barett-Connor E Holdbrook MJ The effect of response bias on the odds ratio Am J Epidemiol 1981 114 137 143 7246521
Helgason Á Tomson T Lund KE Galanti R Ahnve S Gilljam H Factors related to abstinence in a telephone helpline for smoking cessation Eur J Public Health 2004 14 306 310 15369039 10.1093/eurpub/14.3.306
Fiore MC Bailey WC Cohen SJ Dorfman SF Goldstein MG Gritz ER Heyman RB Jaén CR Kottke TE Lando HA Mecklenburg RE Mullen PD Nett LM Robinson L Stitzer ML Tommasello AC Villejo L Wewers ME Treating Tobacco Use and Dependence A clinical practice guideline 2000 Rockville, MD: U.S. Dept of Health and Human Services. Public Health Service
Etter J-F Perneger TV Analysis of Non-Response Bias in a Mailed Health Survey J Clin Epidemiol 1997 50 1123 1128 9368520 10.1016/S0895-4356(97)00166-2
Kaper J Wagena EJ Willemsen MC van Schayck CP Reimbursement for smoking cessation tretment may double the abstinence rate: results of a randomised trial Addiction 5 May 2005.
Rupp I Triemstra M Boshuizen HC Jacobi CE Dinant HJ Van der Bos GAM Selection bias due to non-response in a health survey among patients with rheumatoid arthritis Eur J Public Health 2002 12 131 135 12073751 10.1093/eurpub/12.2.131
Tillgren P Ainetdin T Stjerna M-L Classification of non-respondents in a population-based tobacco cessation contest-"Quit and Win" Scand J Public Health 2000 28 77 78 10817318
Caraballo RS Giovino GA Pechacek TF Mowery PD Factors Associated with Discrepancies between Self-Reports on Cigarette Smoking and Measured Serum Cotinine Levels among Persons Aged 17 Years and Older Am J Epidemiol 2001 153 807 814 11296155 10.1093/aje/153.8.807
Krosnick J A. Survey Research Annu Rev Psychol 1999 50 537 567 15012463 10.1146/annurev.psych.50.1.537
Zhu S-H Cummings S Lin A Koon C Are subjects who decline cotinine tests lying about their smoking? Poster presented at the 10th Annual Conference February 19–21 2004 Society for Research of Nicotine and Tobacco, Scottsdale, Arizona
| 15910682 | PMC1173115 | CC BY | 2021-01-04 16:28:58 | no | BMC Public Health. 2005 May 23; 5:52 | utf-8 | BMC Public Health | 2,005 | 10.1186/1471-2458-5-52 | oa_comm |
==== Front
BMC Public HealthBMC Public Health1471-2458BioMed Central London 1471-2458-5-541592153610.1186/1471-2458-5-54Study ProtocolEpidemiological study air disaster in Amsterdam (ESADA): study design Slottje Pauline [email protected] Anja C [email protected] Jos WR [email protected] Anke B [email protected] der Ploeg Henk M [email protected] Inge [email protected] Nynke [email protected] Joost A [email protected] Lex M [email protected] Mechelen Willem [email protected] Tjabe [email protected] Institute for Research in Extramural Medicine, VU University Medical Center, Van der Boechorststraat 7, 1081 BT Amsterdam, the Netherlands2 Department of Public and Occupational Health, VU University Medical Center, Amsterdam, the Netherlands3 Department of Child and Adolescent Psychiatry, Erasmus Medical Center, Rotterdam, the Netherlands4 Department of Clinical Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, the Netherlands5 Department of Medical Psychology, VU University Medical Center, Amsterdam, the Netherlands6 KLM Health Services, Schiphol Airport, the Netherlands2005 30 5 2005 5 54 54 10 5 2005 30 5 2005 Copyright © 2005 Slottje et al; licensee BioMed Central Ltd.2005Slottje et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
In 1992, a cargo aircraft crashed into apartment buildings in Amsterdam, killing 43 victims and destroying 266 apartments. In the aftermath there were speculations about the cause of the crash, potential exposures to hazardous materials due to the disaster and the health consequences. Starting in 2000, the Epidemiological Study Air Disaster in Amsterdam (ESADA) aimed to assess the long-term health effects of occupational exposure to this disaster on professional assistance workers.
Methods/Design
Epidemiological study among all the exposed professional fire-fighters and police officers who performed disaster-related task(s), and hangar workers who sorted the wreckage of the aircraft, as well as reference groups of their non-exposed colleagues who did not perform any disaster-related tasks. The study took place, on average, 8.5 years after the disaster. Questionnaires were used to assess details on occupational exposure to the disaster. Health measures comprised laboratory assessments in urine, blood and saliva, as well as self-reported current health measures, including health-related quality of life, and various physical and psychological symptoms.
Discussion
In this paper we describe and discuss the design of the ESADA. The ESADA will provide additional scientific knowledge on the long-term health effects of technological disasters on professional workers.
==== Body
Background
In the early evening of October 4th, 1992, an El Al Boeing 747-F cargo aircraft lost two of its engines just after take off from Schiphol Airport and crashed into two apartment buildings in the Bijlmermeer, a densely populated suburb of Amsterdam (the Netherlands) [1]. The air disaster killed 43 people, and destroyed 266 apartments [1,2]. Fire-fighters and police officers were called to the scene to extinguish fires, to search and rescue people, to assist in the identification of human remains and personal belongings, to secure the surroundings and to clean-up the devastated area. Many of them were faced with bewildered residents and extensive destruction, and some witnessed dead or injured victims. Within a few days the wreckage of the aircraft was transported to a hangar at Schiphol Airport, where employees (i.e. 'hangar workers') sorted and inspected the wreckage.
In the extensive aftermath of the disaster, rumors and questions arose about the cause of the accident, the contents of the cargo, potential exposure to hazardous materials, and health consequences [2,3]. Every now and then the media highlighted stories of individual victims, as well as uncertainties about potential exposures during the disaster [4]. One of the major topics concerned exposure to depleted uranium from the aircraft's balance weights, particularly because some of the depleted uranium has never been recovered from the rubble [1]. However, the authors of a retrospective risk analysis "considered it improbable that the missing uranium had indeed led to the reported health complaints" [5]. Nonetheless, it appeared that a growing number of exposed workers and affected residents reported health complaints, which some of them attributed to the disaster [6]. Public and political unrest thus waxed and waned in the aftermath of the disaster [2,3]. Eventually, a parliamentary inquiry, that was held in 1998, recommended an epidemiological study on the health effects of the disaster [1].
About the same time, in 1998, the employers of professional fire-fighters and police officers in Amsterdam decided to start an independent assessment of the health status of professional workers involved in the disaster. The mayor of Amsterdam assigned their occupational health service, the KLM Health Services, to organize this assessment. The employer of the hangar workers at Schiphol Airport joined this initiative, as did government representatives of the affected inhabitants and volunteer workers. It was decided to offer a medical examination to all people involved in the air disaster, residents as well as assistance workers, and that an epidemiological study would be performed simultaneously by the Institute for Research in Extramural Medicine (EMGO Institute). In this paper we report on the design of the epidemiological study among professional assistance workers: the Epidemiological Study Air Disaster in Amsterdam (ESADA). Unfortunately, the epidemiological study among residents had to be cancelled, due to low response rates.
The ESADA is the first epidemiological study that has ever been conducted after a major technological disaster in the Netherlands. The aim of this study is to assess the long-term psychological and physical health effects of occupational exposure to the air disaster in Amsterdam on professional assistance workers, i.e. fire-fighters, police officers and hangar workers. Based on the scientific literature on the health effects of disasters, the main hypotheses of the ESADA concern unexplained physical symptoms [7-12], and post-traumatic stress symptoms and associated psychological symptoms [13-15]. Due to the fact that the ESADA originated partly from societal concerns, we considered it necessary to also include some additional outcomes that will answer questions for some of the affected people, which, in turn, might help to reassure them. These societal questions relate to depleted uranium, Mycoplasma species and carnitine levels in plasma. The first of these questions stems from the concerns about the depleted uranium from the aircraft's balance weights, described above. The other two questions are primarily based on an alleged resemblance between the symptoms of some of the people affected by the air disaster in Amsterdam and the symptoms of patients with chronic fatigue syndrome (CFS) and Gulf War (I) Syndrome (GWS). Although some authors may have suggested a link between these syndromes and Mycoplasma species [16-21] or carnitine deficiency [22-26], others have rejected the existence of such links [27-29].
In this paper we describe and discuss the design of the ESADA. More details on the (organization of the) ESADA can be found on its website [30].
Methods / Design
Design
The ESADA is designed as a historical cohort study, in which the health status of the professional fire-fighters, police officers and hangar workers who were occupationally exposed to the air disaster in Amsterdam is compared with the health status of reference groups of workers with the same jobs and employers at the time of the disaster, but who were not occupationally exposed to this disaster.
Study population
The ESADA study population consisted of professional fire-fighters, police officers and hangar workers. Eligible subjects had to (1) sign informed consent; (2) have sufficient mastery of the Dutch language to fill in the questionnaires; and (3) belong to one of the following three occupational groups:
1) All professional fire-fighters who were, according to company records, employed in the Amsterdam fire department at the time of the disaster. Additional professional fire-fighters who started working in this fire department after the disaster were also invited to participate in the study, as almost the entire fire department had been exposed to the disaster.
2) All police officers (i.e. constables, warrant officers, sergeants and their supervisors) who were, according to company records, employed in the Amsterdam-Amstelland regional police force on the date of the disaster (October 4th, 1992), and were still employed there on the 1st of January 2000.
3) All the hangar workers registered as working for one of the departments involved in the transport, security and sorting of the wreckage on the date of the disaster (October 4th, 1992), and who reported to have been involved in these activities; as well as a random sample, matched with their colleagues for age, sex, department and job title, who were also registered as working for these departments on 30th November 1992, but who did not report to have been involved in any disaster-related activities.
Procedures and data-collection
The study design was approved by the two independent Medical Ethics Committees of the medical facilities involved in this project: the VU University Medical Center (VUmc) and the 'Onze Lieve Vrouwe Gasthuis' (OLVG) in Amsterdam. Potential participants were initially informed about the study via announcements in staff magazines, after which they were approached via personal letters, and eventually by telephone. All participants signed informed consent and participated voluntarily. Data were collected at the Prinsengracht out-patient clinic of the OLVG from January 2000 to March 2002, i.e. on average 8.5 years after the disaster. In addition, data on about half of the hangar workers were collected at Schiphol Airport for logistic reasons. Trained medical research assistants checked that the questionnaires had been completed, measured body height and weight, drew blood samples, and assisted with the collection of urine and saliva samples. A team of administrative employees carried out the data-entry of the questionnaires. Data of each participant were entered twice by two of these employees independently, after which inconsistencies were reviewed and any mistakes rectified. All remaining problems in the interpretation of data, such as dubious handwriting, were consistently resolved by one of the authors (AH, PS or AW).
Blood, saliva and urine samples were dealt with according to standard procedures for collection, transportation, storage and laboratory analysis. Laboratory technicians could have been aware that the samples were from the ESADA, but they were blinded for exposure and health status. The laboratories were all certified according to accredited Dutch standards.
Occupational exposure to the disaster
All participants were asked to fill in a questionnaire on occupational exposure to the air disaster. This questionnaire addressed several specific disaster-related tasks, and also the total time spent on these tasks and the location in which they were performed (e.g. on or near the disaster site, in the hangar where the wreckage was temporarily placed, or elsewhere). They were also asked to describe any other disaster-related task(s) that they had performed. Answers to the latter question were categorized (by PS and AW). The questionnaire also covered disaster-related psychosocial events in a number of items on personal experiences during the disaster (e.g. "were you in life-threatening danger?", "did you see the disaster scene during the first hours after the crash?", and "were any of your family members injured?").
These personal records of occupational exposure to the disaster were used to define 'exposed' workers, i.e. those who reported at least one disaster-related task, and 'non-exposed' workers, i.e. those who did not report any disaster-related tasks.
In addition to comparing exposed and non-exposed workers, we examined exposure-response relationships among exposed workers, in which level of exposure is characterized by the type of tasks and psychosocial events and the duration of exposure. As an additional dimension of level of exposure, we took into account the differences in potential psychotraumatic impact of exposure items, based on criterion A1 of the diagnostic criteria for Post Traumatic Stress Disorder (PTSD; American Psychiatric Association [APA]; Diagnostic and Statistical Manual of Mental Disorders-IV-Text Revision [DSM-IV-TR, 2000]) [31]. This criterion states that "the person has experienced, witnessed, or been confronted with an event or events that involve actual or threatened death or serious injury, or a threat to the physical integrity of oneself or others". Five experts on PTSD from different universities and psychiatric hospitals independently rated the likelihood of potentially psychotraumatic disaster-related tasks and events to meet this criterion on a 4-point Likert Scale ranging from 1 = 'very unlikely' to 4 = 'very likely'. Subsequently, we assumed that items with a mean item score of three or higher met the A1 criterion for PTSD (i.e. A1 tasks and events), as opposed to items with a lower mean score (i.e. non-A1 tasks and events). Table 1 lists the disaster-related tasks and the psychosocial events according to their potential psychotraumatic impact.
Table 1 Disaster-related tasks and psychosocial events according to their potential psychotraumatic impact
A1* (traumatic) Non-A1* (non-traumatic)
Tasks 1. Identification or recovery of victims from the rubble/transport or search for human remains
2. Rescue people 1. Fire-extinguishing
2. Clean up of destructed area
3. Transport of injured victims
4. Provide first aid/support injured victims or workers
5. Security tasks (surveillance, prevent burglary, keep disaster area free of bystanders)
6. Other tasks (e.g. traffic management)
7. Sort wreckage in hangar (at Schiphol Airport)
8. Other tasks in hangar in the presence of the wreckage
9. Transport of wreckage
10. Burning of contaminated soil remnants (from disaster site)
Psychosocial events 1. Having been in life-threatening danger during disaster
2. Personal injuries due to disaster
3. Witnessed dead or injured victims
4. Having been in or near one of the destroyed buildings at the time of the disaster
5. Immediate family members (partner, children) died / in life-threatening danger / injured due to the disaster
6. Other family members died due to the disaster 1. Saw the aircraft crash / saw or heard the aircraft when it crashed
2. Felt or heard the impact of the crash
3. Saw the fire
4. Saw the disaster site during the first hours after the crash/when the wreckage was still there
5. Other family members in life-threatening danger or injured due to the disaster
6. Friends or acquaintances died, injured or in life-threatening danger due to the disaster
7. Apartment of other family members, friends, or acquaintances damaged due to the disaster
8. Lived in the affected suburb of Amsterdam (Bijlmermeer) at the time of the disaster
9. Visited the hangar where the wreckage was kept
*A1 and non-A1 = items with a mean score of ≥ 3 or <3, respectively, on a 4 point Likert Scale indicating the likelihood for an item to meet criterion A1 for post-traumatic stress disorder (from 'very unlikely' [=1] to 'very likely' [=4]) (see Methods).
Main health outcomes
Self-reported health measures
• Post-traumatic stress symptoms: (a) The Dutch 22-item Self-Rating Inventory for PTSD (SRIP) [32-34] and, among exposed subjects only, (b) The 15-item Dutch version of the Impact of Event Scale (IES), which addressed post-traumatic stress symptoms with explicit reference to the air disaster in Amsterdam [35-37].
• General mental health: (a) The 90-item Symptom Checklist (SCL-90) [38,39]; (b) The 20-item General Health Questionnaire (GHQ-12) [40].
• Fatigue and associated symptoms: The 20-item Checklist Individual Strength (CIS) [41,42].
• Health-related quality of Life: The MOS 36-item Short-Form Health Survey (SF-36) [43,44].
• Chronic conditions: One questionnaire assessed the current presence and history of the following chronic conditions, which are considered to have a significant impact on well-being: diabetes; stroke, brain hemorrhage or infarction; heart attack; other heart problems (such as heart failure, or angina pectoris); cancer; chronic osteoarthritis (wear) of the hip or knee joints; hypertension; asthma, chronic bronchitis or lung emphysema (Chronic Obstructive Pulmonary Disease [COPD]); serious or persistent intestinal disorders (longer than 3 months); chronic stomach disorders, stomach or duodenal ulcers; serious or persistent back complaints (including hernias); chronic inflammation of the joints (chronic rheumatism, rheumatoid arthritis). Workers with these chronic conditions were subsequently asked in what year the onset was, to determine whether this was before the disaster took place.
• Physical symptoms: Multiple questionnaires were used to assess the current presence of various physical symptoms, such as a number of respiratory, musculoskeletal, and skin symptoms.
• Attribution of current problems to the air disaster in Amsterdam and its aftermath. Another questionnaire assessed the extent to which exposed workers related any of their current physical, psychological or practical/financial problems to the air disaster and its aftermath. Those who attributed physical symptoms to the disaster and its aftermath were asked to specify these symptoms.
Laboratory outcomes
General laboratory tests [1]:
• Hematological and blood chemical outcomes: hemoglobin, leukocyte count, differential count, platelet count and mean corpuscular volume (Sysmex SE 9000, TOA medical electronics Co. ltd); potassium (Roche Modular ISE900, Roche Diagnostics); creatinine, alkaline phosphatase, gamma-glutamyl transferase, alanine aminotransferase, creatine kinase and C-reactive protein (Roche Modular P800, Roche Diagnostics); ferritin and thyroid stimulating hormone (Centauer, Bayer Diagnostics); β2-microglobuline (IMx Abbott).
• Autoantibodies: nuclear antigen antibodies, anti-double stranded DNA antibodies [46], Immunoglobulin (IgM) rheumatoid factor [47], antineutrophil cytoplasmic antibodies [48,49], and cardiolipin antibodies [50,51].
• Urine outcomes: creatinine (Hitachi 747, Roche Diagnostics GmbH, Mannheim, Germany); micro-albumin (Beckman Array 360 system); and β2-microglobuline (IMx Abbott); screening for protein, glucose, pH, blood and leukocytes (teststrip Boehringer Mannheim B.V.), followed by microscopic evaluation of the urinary sediment if indicated.
• Saliva outcome: cortisol concentration (Wizard 1470, Perkin Elmer).
Additional laboratory tests with respect to the societal questions:
• Uranium 238: concentration in urine (Inductively Coupled Plasma-Mass Spectrometry [ICP-MS] analyser, Finnigan Mat Element) and, at concentrations above 50 ng/l or above 50 ng/g creatinine, also the ratio of uranium 235/238 isotopes [52].
• Total and free carnitine: concentration in blood plasma (Mira Plus, Roche Diagnostics) [53,54].
• DNA of any Mycoplasma species: presence in peripheral blood mononuclear cells (DNA-isolation, Magna Pure, Roche Diagnostics; real time PCR, Taqman, Applied Biosystems); positive samples were subsequently evaluated for the presence of DNA of Mycoplasma fermentans [55,56].
Self-reported socio-demographic characteristics
• Age: at time of assessment in years.
• Sex: male or female.
• Ethnicity: categorized into those who considered themselves as European (i.e. Dutch, British, Dutch/Irish, Dutch/Chinese, Dutch/Indonesian, Portuguese, Spanish, Dutch/ Spanish and European), and others (e.g. Moroccan, Turkish, Surinam).
• Level of education: highest level of education completed, categorized as: high (higher vocational education, university); medium (intermediate vocational education, higher general secondary education, or pre-university education); and low (no education, elementary school, lower vocational education, or lower general secondary education).
• Current executive function: yes (i.e. supervising one or more people) or no.
• Level of physical activity: the total number of hours spent each week on physical activities such as physical exercise, gardening and housekeeping, classified into high, medium and low according to the 33rd and 66th percentiles.
• Alcohol consumption: Usual and exceptional consumption of alcoholic beverages, classified into: none; light-moderate; and (extremely) excessive, i.e. consumption of (a) six or more glasses on 9–20 days a month and on 3–4 days in the last week, (b) four or more glasses on at least 21 days a month and on at least 5 days in the last week, and/or (c) more than six glasses a day, on a weekly basis.
• Cigarette-smoking: categorized as: never, former smoker, and current smoker.
• Negative life events: the number of reported negative life events, based on a questionnaire which specified 13 such events and also included two open-ended questions in which other events could be described. Subjects were asked to indicate whether any of these events happened to them before or after the disaster.
Role of funding sources
The study was funded by the Dutch Ministry of Health, Welfare and Sports; the City of Amsterdam; the Amsterdam-Amstelland regional police force; and KLM Royal Dutch Airlines. The funding sources had no role in the collection, analysis, or interpretation of the data, or in the decision to submit a manuscript for publication.
Discussion
In recent years there has been increasing scientific and societal interest in the health consequences of man-made, technological disasters, i.e. a collective stressful experience with a sudden onset due to technological failure. Technological disasters have had psychiatric consequences [13-15,57], such as PTSD, as well as medical consequences, in particular those of toxic exposures [58-61]. In addition to direct toxic health effects, the mere suspicion and fear of exposure to hazardous materials can also take its toll on the quality of physical, psychological and social well-being in the community [62-64].
Technological disasters strike unexpectedly and suddenly, which puts time-pressure on researchers to develop study protocols, gather exposure data, call in multidisciplinary experts, and obtain financial resources for immediate epidemiological research. Disaster researchers may also have to deal with complicated socio-political and legal aspects. In addition, they have to face a number of methodological problems. These difficulties include: (a) defining the entire potentially 'affected' population and appropriate reference groups; (b) contacting potential participants, particularly in the case of evacuation and hospitalization; low response rates; usually without data on non-respondents [65]; (c) collecting exposure data immediately after the event, which is actually also needed for long-term epidemiological studies.
Probably due to these difficulties, evidence from large-scale epidemiological studies that have been carried out after technological disasters is rather scarce [66,67]. Furthermore, before-after comparisons are rare and only possible by chance in ongoing research projects, due to the unexpected nature of technological disasters [68-70]. Most of the studies that have been conducted so far have relied on 'convenience samples', which were mainly composed of those who were directly affected, such as victims and residents; were based on non-epidemiological study designs; and used group-level or retrospective, self-reported exposure data, which can be affected by recall and reporting bias [71-74].
ESADA approach
The purpose of the ESADA is to assess long-term health effects of occupational exposure to the air disaster in Amsterdam on professional assistance workers. In view of the above-mentioned difficulties in epidemiological research on disasters, the ESADA has some strong methodological points. With respect to the study population, we have been able to identify the complete cohort of exposed and non-exposed workers accurately, based on company records of employment at the time of the disaster.
Another strong point of the ESADA is that we included reference groups of colleagues, who had the same jobs and employers, but who were not occupationally exposed to the disaster. Hence, we are able to draw group-level conclusions on associations between health status and occupational exposure to the disaster.
With respect to exposure assessment, we were able to collect individual data on occupational exposure to the air disaster. Moreover, this consisted of multiple aspects of self-reported occupational exposure, including the duration and location of various disaster-related tasks and the experience of potentially stressful events during these tasks. Finally, we also included various assessments of long-term health, such as laboratory tests and self-reported symptoms and health-related quality of life, to obtain an integral evaluation of health status.
Notwithstanding these strong methodological qualities, some limitations of the ESADA design should also be mentioned. Firstly, although company records of employment were available, we still had to resolve a few difficulties regarding the definition of the study population. For the fire-fighters, this was due to the fact that almost the entire fire department of Amsterdam had been exposed to the disaster. Therefore, in order to achieve an adequate reference group, we decided to also include fire-fighters who joined this fire department after the disaster took place. With respect to the police officers, we were unable to trace those who had left the Amsterdam-Amstelland regional police force in the years after the disaster, due to administrative difficulties. Hence, it was necessary to restrict this group to those who were still working for this police force in 2000.
A second methodological issue concerns the self-report nature of occupational exposure status, and the average time-lag of 8.5 years between the disaster and the assessment. Due to administrative deficiencies in the historic registration of the exposure status, we used our detailed questionnaire data to define exposure status for all workers. Strictly speaking, the ESADA is therefore not a historic cohort study, but a cross-sectional one. The time-lag between the disaster and the exposure assessment may have led to recall bias, especially concerning certain details of exposure to the disaster, such as the duration of activities. However, it seems reasonable to assume that the workers did recollect whether or not they performed any as opposed to no disaster-related tasks, which was used to define occupational exposure status. It is therefore very unlikely that recall bias has resulted in (non-)differential misclassification of exposed and non-exposed workers. Nevertheless, recall bias should be kept in mind with respect to exposure-response relationships. We included multiple aspects of level of exposure, such as the duration and the potential psycho-traumatic character of disaster-related tasks, as it is unknown which aspect of occupational exposure to disasters is relevant for long-term health. However, we may still have missed other potentially relevant aspects, such as exposure to disaster-related media reports in the aftermath of the disaster [4,75].
Thirdly, we acknowledge the fact that, with the exception of the laboratory variables, we rely on self-reported health outcomes. However, most of the health questionnaires that we used have been validated and widely accepted, except for those used to assess the physical symptoms. Differential misclassification in self-report health measures could occur if exposed workers are more likely than non-exposed workers to interpret and report bodily sensations as symptoms. On the other hand, hypervigilance and hypochondria themselves could well be adverse health effects of (toxicological) disasters [76,77].
In conclusion, to increase our knowledge of potential health consequences of (technological) disasters, it is important to be prepared for epidemiological disaster research. Incorporating basic multidisciplinary, epidemiological research protocols into disaster management plans will stimulate scientifically sound research on the health effects of disasters. The ESADA will provide additional scientific knowledge on the long-term health effects of technological disasters on professional workers.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
All authors participated in the multidisciplinary ESADA project team of the EMGO Institute, provided comments on the draft versions and approved the final manuscript. PS drafted the manuscript and performed statistical analyses. AH coordinated the acquisition of data and supervised the first part of the ESADA study. JT contributed to the design and supervised the statistical analyses. AW coordinated the rating of the potential psychotraumatic impact of exposure items and performed statistical analyses. HP and IB participated in the conception and design of the ESADA with respect to psychological outcomes, and IB rated the potential psychotraumatic impact of exposure items. NS supervised the second part of the ESADA. As Medical Director JB coordinated the data-collection. LB contributed to the design of the ESADA. WM contributed to the design and is Vice-President of the ESADA project team. TS conceived the study, and participated in its design and coordination as President of the ESADA project team.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
We wish to thank everyone who contributed to the organization and data-collection as well as the funding sources of the ESADA.
==== Refs
Meijer ThAM Een Beladen Vlucht Eindrapport Bijlmer Enquete [Final Report on the Parliamentary Enquiry Air Disaster in Amsterdam] 1999 's-Gravenhage: Sdu Uitgevers
Boin A Duin van M Heyse L Toxic fear: the management of certainty in the wake of the Amsterdam air crash J Hazard Mater 2001 88 213 34 11679195 10.1016/S0304-3894(01)00268-0
Yzermans CJ Gersons BPR Havenaar JM, Cwickel JG, Bromet EJ The Chaotic Aftermath of an Airplane Crash in Amsterdam: A Second Disaster Toxic turmoil Psychological and Societal Consequences of Ecological Disasters 2002 New York: Kluwer Academic/ Plenum Publishers 85 98
Vasterman P IJzermans J Ziek van de ramp of van het nieuws óver de ramp? [Ilness due to the disaster itself or due to the news about the disaster?] Tijdschr Mediageschiedenis 2002 5 89 109
Uijt de Haag PA Smetsers RC Witlox HW Eisenga AH Evaluating the risk from depleted uranium after the Boeing 747-258F crash in Amsterdam, 1992 J Hazard Mater 2000 76 39 58 10863013 10.1016/S0304-3894(00)00183-7
Donker GA Yzermans CJ Spreeuwenberg P Van der Zee J Symptom attribution after a plane crash: comparison between self-reported symptoms and GP records Br J Gen Pract 2002 52 917 22 12434961
Leon GR Overview of the psychosocial impact of disasters Prehospital Disaster Med 2004 19 4 9 15453154
Clauw DJ Engel CC JrAronowitz R Jones E Kipen HM Kroenke K Ratzan S Sharpe M Wessely S Unexplained symptoms after terrorism and war: an expert consensus statement J Occup Environ Med 2003 45 1040 8 14534444
Jones E Hodgins-Vermaas R McCartney H Everitt B Beech C Poynter D Palmer I Hyams K Wessely S Post-combat syndromes from the Boer war to the Gulf war: a cluster analysis of their nature and attribution BMJ 2002 324 321 4 11834557 10.1136/bmj.324.7333.321
Koscheyev VS Leon GR Gourine AV Gourine VN The psychosocial aftermath of the Chernobyl disaster in an area of relatively low contamination Prehospital Disaster Med 1997 12 41 6 10166374
Havenaar J Rumyantzeva G Kasyanenko A Kaasjager K Westermann A Van den Brink W Savelkoul J Health effects of the Chernobyl disaster: illness or illness behavior? A comparative general health survey in two former Soviet regions Environ Health Perspect 1997 105 1533 7 9467078
Collins DL de Carvalho AB Chronic stress from the Goiania 137Cs radiation accident Behav Med 1993 18 149 57 8461486
Katz CL Pellegrino L Pandya A Ng A DeLisi LE Research on psychiatric outcomes and interventions subsequent to disasters: a review of the literature Psychiatry Res 2002 110 201 17 12127471 10.1016/S0165-1781(02)00110-5
Norris FH Friedman MJ Watson PJ Byme CM Diaz E Kaniasty K 60,000 disaster victims speak: Part I. An empirical review of the empirical literature, 1981–2001 Psychiatry 2002 65 207 39 12405079
Bromet E Dew MA Review of psychiatric epidemiologic research on disasters Epidemiol Rev 1995 17 113 9 8521929
Nasralla M Haier J Nicolson GL Multiple Mycoplasmal Infections detected in blood of patients with chronic fatigue syndrome and/or fibromyalgia syndrome Eur J Clin Microbiol Infect Dis 1999 18 859 65 10691196 10.1007/s100960050420
Vojdani A Choppa PC Tagle C Andrin R Samimi B Lapp CW Detection of Mycoplasma genus and mycoplasma fermentans by PCR in patients with chronic fatigue syndrome FEMS Immunol Med Microbiol 1998 22 355 65 9879928 10.1016/S0928-8244(98)00108-4
Nicolson GL Gan R Haier J Multiple co-infections (Mycoplasma, Chlamydia, human herpes virus-6) in blood of chronic fatigue syndrome patients: association with signs and symptoms APMIS 2003 111 557 66 12887507 10.1034/j.1600-0463.2003.1110504.x
Nijs J Nicolson GL De Becker P Coomans D De Meirleir K High prevalence of Mycoplasma infections among European chronic fatigue syndrome patients. Examination of four Mycoplasma species in blood of chronic fatigue syndrome patients FEMS Immunol Med Microbiol 2002 34 209 14 12423773 10.1016/S0928-8244(02)00398-X
Endresen GK Mycoplasma blood infection in chronic fatigue and fibromyalgia syndromes Rheumatol Int 2003 23 211 5 12879275 10.1007/s00296-003-0355-7
Collins JF Donta ST Engel CC Baseman JB Dever LL Taylor T Boardman KD Martin SE Wiseman AL Feussner JR The antibiotic treatment trial of Gulf War Veterans' Illnesses: issues, design, screening, and baseline characteristics Control Clin Trials 2002 23 333 53 12057884 10.1016/S0197-2456(02)00192-7
Kuratsune H Yamaguti K Takahashi M Misaki H Tagawa S Kitani T Acylcarnitine deficiency in chronic fatigue syndrome Clin Infect Dis 1994 18 S62 7 8148455
Kuratsune H Yamaguti K Lindh G Evengard B Takahashi M Machii T Matsumura K Takaishi J Kawata S Langstrom B Kanakura Y Kitani T Watanabe Y Low levels of serum acylcarnitine in chronic fatigue syndrome and chronic hepatitis type C, but not seen in other diseases Int J Mol Med 1998 2 51 6 9854142
Plioplys AV Plioplys S Serum levels of carnitine in chronic fatigue a syndrome: clinical correlates Neuropsychobiology 1995 32 132 8 8544970
Plioplys AV Plioplys S Amantadine and L-carnitine treatment of chronic fatigue syndrome Neuropsychobiology 1997 35 16 23 9018019
Vermeulen RC Scholte HR Exploratory open label, randomized study of acetyl- and propionylcarnitine in chronic fatigue syndrome Psychosom Med 2004 66 276 82 15039515 10.1097/01.psy.0000116249.60477.e9
Komaroff AL Bell DS Cheney PR Lo SC Absence of antibody to Mycoplasma fermentans in patients with chronic fatigue syndrome Clin Infect Dis 1993 17 1074 5 8110942
Vernon SD Shukla SK Reeves WC Absence of Mycoplasma species DNA in chronic fatigue syndrome J Med Microbiol 2003 52 1027 8 14532349 10.1099/jmm.0.05316-0
Soetekouw PM Wevers RA Vreken P Elving LD Janssen AJ Veen van der Y Bleijenberg G Meer van der JW Normal carnitine levels in patients with chronic fatigue syndrome Neth J Med 2000 57 20 4 10862998 10.1016/S0300-2977(00)00030-9
ESADA Website
APA Diagnostic and statistical manual of mental disorders-IV-TR Washington, DC 2000
Hovens JE Ploeg van der HM Bramsen I Klaarenbeek MTA Schreuder JN Rivero VV The development of a Dutch Self-rating Inventory for Posttraumatic Stress Disorder Acta Psychiatr Scand 1994 90 172 83 7810340
Hovens JE Bramsen I Ploeg van der HM Zelfinventarisatielijst Posttraumatische Stress stoornis (ZIL) Handleiding [Self-Rating Inventory for Post-traumatic stress disorder (PTSD) Manual] 2000 Lisse: Swets Test Publishers
Hovens JE Ploeg van der HM Bramsen I Reuling I Test-retest reliability of the Self-rating Inventory for PTSD Psychol Rep 2000 87 735 7 11191377
Joseph S Psychometric Evaluation of Horowitz's Impact of Event Scale: A Review J Trauma Stress 2000 13 101 13 10761177 10.1023/A:1007777032063
Horowitz MJ Wilner N Alvarez W Impact of Event Scale: A measure of subjective stress Psychosom Med 1979 41 209 18 472086
Brom D Kleber RJ De Schok Verwerkings Lijst. [Impact of Event Scale] Ned Tijdschr Psychol 1985 40 164 8
Arrindell WA Ettema JHM Handleiding bij een multidimensionele psycho-pathologie indicator [Manual for a multidimensional psycho-pathology indicator] 1986 Lisse: Swets & Zeitlinger
Arrindell WA Ettema JHM Handleiding bij een multidimensionele psycho-pathologie indicator [Manual for a multidimensional psycho-pathology indicator] 2003 Lisse: Swets & Zeitlinger
Koeter MWJ Ormel J General Health Questionnaire: Nederlandse bewerking, handleiding [Dutch version of manual] 1991 Lisse: Swets & Zeitlinger
Vercoulen JHMM Swanink CMA Fennis JFM Galama JMD Meer van der JWM Bleijenberg G Dimensional assessment of chronic fatigue syndrome J Psychosom Res 1994 38 383 92 7965927 10.1016/0022-3999(94)90099-X
Beurskens AJHM Bultmann U Kant I Vercoulen JHMM Bleijenberg G Swaen MHG Fatigue among working people: validity of a questionnaire measure Occup Environ Med 2000 57 353 7 10769302 10.1136/oem.57.5.353
Ware JE Snow KK Kosinski M Gandek B SF-36 Health Survey, Manual & Interpretation Guide 1997 Boston: Nimrod Press
Aaronson NK Muller M Cohen PDA Essink-Bot M Fekkes M Sanderman R Sprangers MAG Velde te A Verrips E Translation, Validation, and Norming of the Dutch Language Version of the SF-36 Health Survey in Community and Chronic Disease Populations J Clin Epidemiol 1998 51 1055 68 9817123 10.1016/S0895-4356(98)00097-3
Leusden van HAIM Diagnostisch Kompas: voorlichting over aanvullende diagnostiek [Diagnostic Compass: information on diagnostic tests] 2003 3 Amstelveen: College voor zorgverzekeringen (CVZ)
Smeenk R Van der Ley G Aarden L Measurements of low avidity anti-dsDNA by the crithidia luciliae test and the PEG assay Clin Exp Immunol 1982 49 603 10 6756723
Faith A Pontesilli O Unger A Panayi GS John PJ ELISA assays for IgM and IgG rheumatoid factors Immunol Methods 1982 55 169 77 10.1016/0022-1759(82)90029-1
Wiik A Delineation of a standard procedure for indirect immunofluorescence detection of ANCA APMIS Suppl 1989 6 12 3 2660875
Giessen van der M Huiteman MG Cohen Tervaert JW Kallenberg CGM A technical note on the routinely performed ANCA detection APMIS 1989 97 37
Harris EN Special report. The Second International Anti-cardiolipin Standardization Workshop/the Kingston Anti-Phospholipid Antibody Study (KAPS) group Am J Clin Pathol 1990 94 476 84 2220676
Rupin A Gruel Y Watier H Girard AC Leroy J Bardos PJ ELISA for the detection of anticardiolipin antibodies Immunol Methods 1991 138 225 31 10.1016/0022-1759(91)90170-K
Tresl I Wannemacker de G Quetel CR Petrov I Vanhaecke F Moens L Taylor PD Validated measurements of the uranium isotopic signature in human urine samples using magnetic sector-field inductively coupled plasma mass spectrometry Environ Sci Technol 2004 38 581 6 14750735 10.1021/es0346025
Cederblad G Harper P Lindgren K Spectrophotometry of carnitine in biological fluids and tissue with a Cobas Bio centrifugal analyzer Clin Chem 1986 32 342 6 3943195
Wan L Hubbard RW Determination of free and total carnitine with a random-access chemistry analyzer Clin Chem 1998 44 810 6 9554493
Kuppeveld van FJ Logt van der JT Angulo AF Zoest van MJ Quint WG Niesters HG Galama JM Melchers WJ Genus- and species-specific identification of mycoplasmas bij 16S rRNA amplification Appl Environ Microbiol 1992 58 2606 15 1381174
Blanchard A Hamrick W Duffy L Baldus K Cassell GH Use of the polymerase chain reaction for detection of Mycoplasma fermentans and Mycoplasma genitalium in the urogenital tract and amniotic fluid Clin Infect Dis 1993 17 S272 9 8399929
Shalev AY Tuval-Mashiach R Hadar H Posttraumatic stress disorder as a result of mass trauma J Clin Psychiatry 2004 65 4 10 14728091
Pesatori AC Consonni D Bachetti S Zocchetti C Bonzini M Baccarelli A Bertazzi PA Short- and long-term morbidity and mortality in the population exposed to dioxin after the "Seveso accident" Ind Health 2003 41 127 12916742
Dhara VR Dhara R The Union Carbide disaster in Bhopal: a review of health effects Arch Environ Health 2002 57 391 404 12641179
Bard D Verger P Hubert P Chernobyl, 10 years after: health consequences Epidemiol Rev 1997 19 187 204 9494782
Gelpi E Paz de la MP Terracini B Abaitua I Camara de la AG Kilbourne EM Lahoz C Nemery B Philen RM Soldevilla L Tarkowski S The Spanish toxic oil syndrome 20 years after its onset: a multidisciplinary review of scientific knowledge Environ Health Perspect 2002 110 457 64 12003748
Collins DL Human responses to the threat of or exposure to ionizing radiation at Three Mile Island, Pennsylvania, and Goiania, Brazil Mil Med 2002 167 137 8 11873499
Havenaar JM Cwikel JG Bromet EJ Toxic Turmoil Psychological and Societal Consequences of Ecological Disasters 2002 New York: Kluwer Academic / Plenum Publishers
Gray P The Human Consequences of the Chernobyl Nuclear Accident A strategy for Recovery, Chernobyl Report-Final-250102 edn 2002
Foster K Campbell D Crum J Stove M Non-response in a population study after an environmental disaster Public Health 1995 109 267 73 7667491
Logue JN Melick ME Hanssen H Research issues and directions in the epidemiology of health effects of disasters Epidemiol Rev 1981 3 140 62 7030759
Lechat MF The epidemiology of health effects of disasters Epidemiol Rev 1990 12 192 8 2286219
Dirkzwager AJ Yzermans CJ Kessels FJ Psychological, musculoskeletal, and respiratory problems and sickness absence before and after involvement in a disaster: a longitudinal study among rescue workers Occup Environ Med 2004 61 870 2 15377775 10.1136/oem.2003.012021
Alexander DA Wells A Reactions of police officers to body-handling after a major disaster. A before-and-after comparison Br J Psychiatry 1991 159 547 55 1751866
Reijneveld SA Crone MR Verhulst FC Verloove-Vanhorick SP The effect of a severe disaster on the mental health of adolescents: a controlled study Lancet 2003 362 691 6 12957091 10.1016/S0140-6736(03)14231-6
Roht LH Vernon SW Weir FW Pier SM Sullivan P Reed LJ Community exposure to hazardous waste disposal sites: assessing reporting bias Am J Epidemiol 1985 122 418 33 4025292
Kaye WE Hall HI Lybarger JA Recall bias in disease status associated with perceived exposure to hazardous substances Ann Epidemiol 1994 4 393 7 7981847
Hopwood DG Guidotti TL Recall Bias in Exposed Subjects Following a Toxic Exposure Incident Arch Environ Health 1988 43 234 7 3382248
Lees-Haley PR Brown RS Biases in perception and reporting following a perceived toxic exposure Percept Mot Skills 1992 75 531 44 1408616
Small GW Borus JF The influence of newspaper reports on outbreaks of mass hysteria Psychiatr Q 1987 58 269 78 3438359 10.1007/BF01064608
Vyner HM The psychological dimensions of health care for patients exposed to radiation and the other invisible environmental contaminants Soc Sci Med 1988 27 1097 103 3059508 10.1016/0277-9536(88)90304-8
Havenaar JM Brink van den W Psychological factors affecting health after toxicological disasters Clin Psychol Rev 1997 17 359 74 9199857 10.1016/S0272-7358(97)00009-3
| 15921536 | PMC1173116 | CC BY | 2021-01-04 16:28:56 | no | BMC Public Health. 2005 May 30; 5:54 | utf-8 | BMC Public Health | 2,005 | 10.1186/1471-2458-5-54 | oa_comm |
==== Front
BMC Public HealthBMC Public Health1471-2458BioMed Central London 1471-2458-5-561592980010.1186/1471-2458-5-56Research ArticleRapid assessment of injection practices in Cambodia, 2002 Vong Sirenda [email protected] Joseph F [email protected] Srun [email protected] Seiharath [email protected] Susan [email protected] Yvan [email protected] James [email protected] Division of Viral Hepatitis, Centers for Disease Control and Prevention, Atlanta, GA, USA2 World Health Organization Consultant3 Ministry of Health, Phnom Penh, Cambodia4 World Health Organization, Resident Advisor, India5 World Health Organization, Phnom Penh Office, Cambodia2005 2 6 2005 5 56 56 11 11 2004 2 6 2005 Copyright © 2005 Vong et al; licensee BioMed Central Ltd.2005Vong et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Injection overuse and unsafe injection practices facilitate transmission of bloodborne pathogens such as hepatitis B virus (HBV), hepatitis C virus (HCV), and human immunodeficiency virus (HIV). Anecdotal reports of unsafe and unnecessary therapeutic injections and the high prevalence of HBV (8.0%), HCV (6.5%), and HIV (2.6%) infection in Cambodia have raised concern over injection safety. To estimate the magnitude and patterns of such practices, a rapid assessment of injection practices was conducted.
Methods
We surveyed a random sample of the general population in Takeo Province and convenience samples of prescribers and injection providers in Takeo Province and Phnom Penh city regarding injection-related knowledge, attitudes, and practices. Injection providers were observed administering injections. Data were collected using standardized methods adapted from the World Health Organization safe injection assessment guidelines.
Results
Among the general population sample (n = 500), the overall injection rate was 5.9 injections per person-year, with 40% of participants reporting receipt of ≥ 1 injection during the previous 6 months. Therapeutic injections, intravenous infusions, and immunizations accounted for 74%, 16% and 10% of injections, respectively. The majority (>85%) of injections were received in the private sector. All participants who recalled their last injection reported the injection was administered with a newly opened disposable syringe and needle. Prescribers (n = 60) reported that 47% of the total prescriptions they wrote included a therapeutic injection or infusion. Among injection providers (n = 60), 58% recapped the syringe after use and 13% did not dispose of the used needle and syringe appropriately. Over half (53%) of the providers reported a needlestick injury during the previous 12 months. Ninety percent of prescribers and injection providers were aware HBV, HCV, and HIV were transmitted through unsafe injection practices. Knowledge of HIV transmission through "dirty" syringes among the general population was also high (95%).
Conclusion
Our data suggest that Cambodia has one of the world's highest rates of overall injection usage, despite general awareness of associated infection risks. Although there was little evidence of reuse of needles and syringes, support is needed for interventions to address injection overuse, healthcare worker safety and appropriate waste disposal.
==== Body
Background
In many developing countries and countries with economies in transition, health care injections are overused and are frequently administered in an unsafe manner [1,2]. The World Health Organization (WHO) estimates that 20 million new hepatitis B virus (HBV) infections, 2 million new hepatitis C virus (HCV) infections, and 260,000 new HIV infections are associated with unsafe injections each year worldwide [3].
Concerns have been expressed over the use of injections within the Kingdom of Cambodia (2003 United Nations population estimate 14.1 million). Anecdotal reports suggest that therapeutic injections are often unnecessary and administered in an unsafe manner, and healthcare waste is inappropriately disposed [4-6]. A high prevalence of HIV infection has been documented in Cambodia, with 2.6% of the general population infected [7]. Cambodia also has high levels of HBV and HCV infection endemicity. A 1991 community-based study indicated that 8.0% of the population was hepatitis B surface antigen positive and 6.5% was anti-HCV positive [8]. The proportion of bloodborne pathogen infections in Cambodia attributable to unsafe injections is not known.
To estimate the magnitude and patterns of unsafe injection practices in Cambodia, a rapid assessment of injection practices was conducted. The objectives of the assessment were to describe healthcare injection practices, including measures of injection frequency and injection safety, and determine knowledge, attitudes and practices related to medical injections among the general population and healthcare providers. This assessment focused mainly on the unregulated private healthcare sector, in which 70% of Cambodians seek medical care [9].
Methods
Overview
The assessment was conducted using methods established by WHO for the rapid assessment of injection practices [10]. As detailed in the following sections, we interviewed members of the general population, healthcare workers responsible for prescribing injections (i.e., "prescribers"), and healthcare workers responsible for administering injections (i.e., "injection providers"). All data were collected during face-to-face interviews using standardized questionnaires and forms adapted from the WHO assessment guide [10]. The general population sample was drawn from Takeo province (1998 population census 790,168), a rural province located in southeastern Cambodia near the Vietnamese border. Prescribers and injection providers were sampled in Takeo province and in Phnom Penh (1998 population census 999,809), Cambodia's largest city [11].
General population
We surveyed 500 Takeo province residents in November and December 2002 using standard cluster sampling methodology. To obtain a total of 500 participants, we surveyed 25 participants each in the catchment area of 20 district health centers. The 20 district health centers were selected by probabilities proportional to the population size of their catchment areas [12]. For each health center selected, one village was chosen at random to be surveyed. Households were sampled at random until 25 participants were included. Verbal informed consent was obtained from all household members >16 years old to participate in the survey. For persons ≤ 16 years old, informed consent was obtained from a parent or guardian. For each participant, basic demographic data were collected, as well as the number of injections received during the 6 month period beginning on April 13, 2002 (New Year's Day in Cambodia). Injections were categorized as therapeutic injections, immunizations, and intravenous infusions. Participants >16 years of age were also interviewed regarding their knowledge and attitudes about injections.
Prescribers and injection providers
We surveyed prescribers and injection providers in Takeo province and Phnom Penh in November and December 2002. In Takeo province, a convenience sample of 30 prescribers and 30 injection providers was accessed through the province's five public hospitals. In Phnom Penh, 30 prescribers were randomly selected from a list of registered private outpatient clinics and 30 injection providers were selected from 11 of the city's 13 private hospitals. For all prescribers, regardless of where they were identified, the survey focused on their medical practices in their private outpatient clinics. We ascertained their knowledge, attitudes and practices regarding injections. Injection frequency was determined by asking prescribers to estimate the total number of prescriptions they wrote per week and the number that included an injection or infusion. Injection providers were interviewed regarding their knowledge of disease transmission risks through unsafe injections, their hepatitis B vaccination status and the frequency of needle stick injuries during the previous 12 months. In addition, we observed each injection provider administer one injection. During all hospital visits, information was recorded regarding the use of incinerators and the presence of used needles and syringes and other medical equipment on the grounds of the facility.
Data analysis
Proportions, means, and confidence intervals were calculated using EpiInfo 6.04d (CDC, Atlanta, Georgia) with adjustment for the cluster sampling design effect. Univariate and multivariate analyses of variables associated with receiving injections were performed using SAS software version 8 (SAS Institute, Cary, North Carolina).
Results
General population
The overall injection rate was 5.9 injections per person-year (95% CI: 5.3 – 6.7), with 40% of the participants reporting receipt of one or more injections during the previous 6 months (Table 1). Therapeutic injections accounted for 74% of the total number of injections reported, followed by intravenous infusions (16%), and immunization (10%). Among individuals who had any exposure to injections, nearly one-half reported receiving ≥ 5 injections. This group represented only 18% of all participants but accounted for 69% of the total injections reported.
Table 1 Characteristics of study participants, Takeo province, Cambodia, 2002
Total (n = 500) Children* (n = 212) Adult women (n = 189) Adult men (n = 99)
Age:
median 22 9 38 37
range (years) 0–80 0–16 17–79 17–80
Injection experiences (6-month period)
Number of injections 1483 557 713 213
Overall injection rate (per person-year) 5.9 5.3 7.5 4.3
Proportions of subjects who received:
≥ 1 vaccine injection 15% 35% 0% 0%
≥ 1 therapeutic injection 32% 31% 39% 20%
≥ 1 intravenous infusion 16% 16% 18% 14%
≥ 1 injection (any type) 40% 46% 42% 24%
≥ 5 injections (any type) 18% 18% 22% 9%
Knowledge and attitudes^
Trusted practitioners if no injections prescribed 90% ND 90% 89%
Preferred injection for treatment of fever 32% ND 35% 26%
Believed injections more powerful than oral medication 47% ND 50% 40%
Aware that dirty syringes can transmit HIV 95% ND 96% 93%
Aware that dirty syringes can transmit hepatitis 59% ND 60% 57%
ND = not determined
* participants aged ≤ 16 years
^ adults only (288 total respondents)
The pattern of injection use differed by age and sex. Among adults, women were more likely than men to report receiving any (42% vs. 28%, p < 0.001) or frequent injections (i.e., ≥ 5 injections during the previous 6 months; 22% vs. 9%, p < 0.001) (Table 1). Women were also more likely than men to report having received ≥ 1 therapeutic injection (39% vs. 20%, p = 0.001). Similar proportions of men, women and children reported receiving intravenous infusions, ranging from 14 – 18%. Immunizations were limited to children, with 35% of children reporting having received ≥ 1 immunization.
Ninety-six adult participants (93% of those reporting one or more injection in the previous 6 months) could recall the details of their last injection. All reported the injection was administered with a newly opened disposable syringe and needle. The majority (85%) of these injections was administered by health care workers; at least 13% were administered by lay persons (Figure 1). Injections were most commonly administered in the patient's home (65%) or in a private clinic (20%). Only 13% of injections were administered at public hospitals or public health centers.
Figure 1 Distribution of injections by provider type and setting*, Takeo Province, Cambodia, 2002 (n = 96) *Data refer to the most recent injection received by adults reporting ≥ 1 injection in the previous 6 months
Of the 288 subjects interviewed, 90% reported they would trust a medical practitioner who did not prescribe an injection (Table 1). However, 47% (134/288) believed that therapeutic injections are more powerful than oral medications, with 75% (100/134) of these persons attributing a faster healing effect to injections. In addition, 32% of the respondents reported they preferred injections over oral medications for the treatment of illnesses characterized by fever. Knowledge of the HIV transmission risk associated with "dirty" syringes and needles was very high (95%), though only 59% of respondents were aware that hepatitis could be transmitted in this manner. None of the knowledge or attitude variables or other characteristics (besides gender) were associated with the receipt of injections. This was true even when the analyses were restricted to comparisons of persons reporting no injections versus frequent injection use (i.e., ≥ 5 injections during the previous 6 months).
Prescribers
The 60 prescribers interviewed were registered medical doctors or medical assistants. Prescribers estimated that nearly half (47%) of the total prescriptions they wrote included either a therapeutic injection (34%) or an intravenous infusion (14%) (Table 2). The overall prescription rates and distribution by type was similar in Phnom Penh and Takeo Province. The main reasons cited for prescribing injections were illness severity (44%) and perceived patient preferences for injectable medications (40%). Seventy-seven percent of prescribers believed that injection prescriptions resulted in greater reimbursement. Only one prescriber perceived himself as over-prescribing injections. Most (92%) prescribers were aware that HIV, HBV and HCV could be transmitted through unsafe injections (Table 2).
Table 2 Characteristics of injection prescribers and providers, Takeo province, Cambodia, 2002
Total (n = 60) Takeo Province (n = 30) Phnom Penh (n = 30)
Characteristics of prescribers1
Medication prescription rate (prescriptions/week)
average 20 21 20
median 20 21 20
range 4–140 4–140 7–140
Prescriptions including an injection2 47% 48% 45%
therapeutic injection 34% 32% 35%
intravenous infusion 14% 18% 10%
Main reason for prescribing injections
illness severity 44% 50% 37%
patient preference 40% 40% 40%
more effective than oral medications 12% 7% 17%
reimbursement 9% 7% 10%
Preferred injectable med for treatment of febrile illness 64% 47% 80%
Believed patient trust requires injection prescription 42% 53% 30%
Believed reimbursement is higher for patient visits that result in injection prescription 77% 87% 66%
Perceived themselves as over-prescribing injections 2% 3% 0%
Knew HIV, HBV and HCV can be transmitted through unsafe injections 92% 87% 97%
Characteristics of injection providers
Completed hepatitis B vaccination series 20% 7% 33%
Needlestick injury in last 12 months 53% 50% 57%
Average number (and range) of needlesticks in past 12 months among those reporting one or more 1.7 (1–10) 1.4 (1–6) 2.0 (1–10)
Use of single use needles and syringes3 98% 97% 100%
Safety box (i.e., sharp container) present in injection administration area3 25% 37% 13%
Reported having sufficient number of sharps boxes 85% 77% 93%
Practiced two hand recapping of used needles3 58% 53% 60%
Left used sharps in preparation area3 13% 23% 3%
Knew HIV, HBV and HCV can be transmitted through unsafe injections 90% 87% 93%
1 Prescribers' responses pertain to their private outpatient practices
2 Denominator is the total number of weekly prescriptions
3 Based on observation of provider by the investigators
Injection providers
All 60 injection providers interviewed were registered nurses, only 20% of whom had received the complete hepatitis B vaccination series. During our observations, 59 (98%) providers used new single use syringes (i.e., traditional plastic disposable syringes) and needles and one administered the injection with sterilized reusable equipment. Over half (58%) of the providers were observed practicing two-handed recapping of used injection equipment and 53% reported they had sustained a needlestick injury during the past 12 months. For only 25% of providers, a safety box (i.e. sharps container) was observed in close proximity to the injection area, yet 85% reported having a sufficient number of safety boxes. We observed that 13% of providers left used sharps in the injection preparation area (23% in Takeo province and 3% in Phnom Penh city). Ninety percent of injection providers stated they were aware that HIV, HBV and HCV could be transmitted through unsafe injections (Table 2).
Waste disposal
In the general population survey in Takeo province, 32% (23/72) of participants who reported receiving their last injection in their home reported that the used injection equipment was left behind by the injection provider. Used sharps were observed on the grounds outside three of the five public hospitals in Takeo province, but not on the grounds of any of the 11 private hospitals in Phnom Penh. Incinerators and sharps pits in which used sharps waste could be burned or buried were present at all of the Takeo hospitals. In Phnom Penh, sharps pits were available in two hospitals. In the remaining nine hospitals, sharps waste was collected along with non-medical waste for disposal at the city landfill.
Discussion
The rapid assessment of injection practices described in this paper suggests that injections are prescribed and administered in Cambodia at excessive rates. Intravenous infusions were common among the general population surveyed and represented approximately one-third of all injections prescribed in private outpatient clinics. Using WHO standardized measures as a basis for comparison, our assessment indicates that Cambodia has one of the highest rates of overall therapeutic injection usage ever reported worldwide [1,2]. Studies conducted in other countries in the region have documented rates of 2–4 injections/person/year; approximately one third lower than in Cambodia [2].
This assessment documented potentially harmful injection practices including inadequate handling and disposal of used injection equipment. Given the country's high prevalence of HIV, HBV, and HCV, the overuse and misuse of injections carry substantial risks. While reuse of injection equipment was uncommon in this survey, the high prevalences of bloodborne infections may reflect past practices of needle and syringe reuse. We did observe breaks in aseptic technique (e.g., used sharps left in the injection preparation area) that may facilitate cross-contamination during injection preparation [13,14]. Other infection control breaks such as mishandling of sterile materials and improper use of multidose vials have been frequently implicated in the transmission of bloodborne viral and bacterial infections, but were not studied in this survey [13,15]. Anecdotal reports suggest that used needles and syringes might be repackaged and resold as new. While there was no evidence to suggest this practice was occurring in Cambodia, we did not evaluate the sterility of needles and syringes. In addition, many of the injection providers in our survey engaged in high risk behaviors (e.g., two-handed recapping needle), highlighting the need for training and other interventions aimed at reducing occupational exposures and infection risks.
The patterns of attitudes, knowledge and practices regarding injections among the general population and health professionals observed in Cambodia were similar to those in many countries with high frequencies of injections and comparable healthcare systems such as Pakistan, India, and Indonesia [16-18]. In these countries as in Cambodia, patients and prescribers frequently believe that injections are more effective than oral treatments, and few health professionals perceive themselves as over-prescribing injections. This study and others have also shown that many healthcare providers believed that patients' trust hinged on injection prescriptions, whereas only a minority of patients actually stated that they prefer injections for treatment of conditions that could be treated with oral medications. Both misconceptions may facilitate injection overuse.
In this study, almost half of the prescriptions made by the private providers we surveyed contained at least one injection, compared with a previous finding that only 2% of prescriptions written in public sector outpatient clinics included injections [19]. Financial interests might lead some private health professionals to over-prescribe injectable medications [16]. Since oral and intravenous medications are readily available directly from pharmacies without prescriptions, it is possible that private healthcare providers provide and promote injections and infusions as a way to attract patients [20]. These factors might partly explain the popularity of the private sector compared with the public healthcare sector where the cost for clinic visits is lower and medications are available free of charge, but are dispensed according to standardized treatment protocols which generally specify oral formulations.
High levels of awareness of infection risks associated with syringe and needle reuse, particularly regarding HIV were documented in this study. This is consistent with results of a recent national Demographic Health Survey [9] and likely reflects Cambodia's efforts during the late 1990's to educate the general public regarding risk factors for HIV infection. These education campaigns included information on the risk of transmission of HIV from re-used syringes. Following the campaigns, disposable needles and syringes became widely available in Cambodia at a relatively low cost. It is possible that the increased awareness of HIV infection risks associated with injections led to increased utilization of disposable needles and syringes rather than a shift toward alternative forms of treatment.
This assessment had several limitations. First, the survey did not capture the medical indications that were associated with either prescription or receipt of injections. Second, resource constraints required the general population surveys to focus on one province instead of being conducted nationwide. Takeo province was selected because it is the third most populated province, its economic status is in the middle of the national spectrum, and like the general Cambodian population it is mainly rural [9]. Third, because only formal health professionals were surveyed, we could not assess practices in the informal health sector. We found that approximately one-in-seven injections in Takeo province were administered by untrained paramedical and lay health care workers and their practices may differ from health care workers in the formal sector.
There is growing consensus that improvements in injection safety and overuse in developing countries can be achieved [21]. Such efforts require multidisciplinary engagement and behavioral changes on the parts of both patients and health professionals, including those from the private healthcare sector [22]. Although large-scale interventions to improve the safety of therapeutic injections are limited, several demonstration projects have proven to be effective and relatively long lasting. Studies in Indonesia demonstrated a sustained 19% reduction in injection rates following "interactional group discussions," an intervention that brings health care providers and patients together to discuss their preferences regarding injections and oral medications [18,23]. In Burkina Faso, interventions targeted at providing sufficient quantities of single-use syringes and needles resulted in >90% reductions in unsafe injections that have been sustained for at least 5 years [24].
Comprehensive interventions aimed at reducing overuse of injections, promoting rational use of oral and injectable medications, and reinforcing safe injection and waste disposal practices are likely to be cost-effective in Cambodia [25,26]. While initial efforts in injection safety have been largely focused on infant immunization, Cambodia is now expanding this initiative to include curative care, with an emphasis on the private sector. A national plan of action has been developed to decrease injection use and promote injection safety in accordance with WHO guidelines. The plan aims to involve multidisciplinary partners and improve coordination among relevant departments in the Ministry of Health. This plan also includes demonstration projects that address specific issues related to injection use in the private sector. It is hoped that Cambodia's efforts to address its injection safety and overuse problems will provide an example for other countries that are beginning to confront this important public health issue.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
SV, SS, SS and JT adapted the WHO assessment design to Cambodia. SV, SS, and SS conducted the survey, supervised different aspects of its implementation and collected data. SV and JP synthesized analyses and led the writing. SG helped interpret findings and review drafts of the manuscript. YH conceptualized the assessment and reviewed drafts of the manuscript. All authors read and approved the final manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
We are grateful to Drs. Hok Phalla and Thou Chourn of the Cambodian National Institute for Public Health, and Mrs. Mam Boravann of the Cambodian Department of Drugs and Foods for their collaboration in conducting the survey.
==== Refs
Hutin YJ Hauri AM Armstrong GL Use of injections in healthcare settings worldwide, 2000: literature review and regional estimates BMJ 2003 327 1075 14604927 10.1136/bmj.327.7423.1075
Simonsen L Kane A Lloyd J Zaffran M Kane M Unsafe injections in the developing world and transmission of bloodborne pathogens: a review Bull World Health Organ 1999 77 789 800 10593026
Hauri AM Armstrong GL Hutin YJ The global burden of disease attributable to contaminated injections given in health care settings Int J STD AIDS 2004 15 7 16 14769164 10.1258/095646204322637182
Rational Use of Drugs for In-patients, Referral Hospital: Referral Hospital Audit, Baseline Survey Ministry of Health/GSP survey 1999
WHO Medical waste management, Phnom Penh, Cambodia proceedings of the 4th International Safe Injection Global Network (SIGN) annual meeting: 24–25 October 2002; Phnom Penh, Cambodia 2002
Medical waste management in Phnom Penh, Cambodia 2001 Blacksmith Institute, NY, USA/Government of Cambodia
Cohen J Asia – the next frontier for HIV/AIDS. Two hard-hit countries offer rare success stories: Thailand and Cambodia Science 2003 301 1658 62 14500955 10.1126/science.301.5640.1658
Thuring EG Joller-Jemelka HI Sareth H Sokhan U Reth C Grob P Prevalence of markers of hepatitis viruses A, B, C and of HIV in healthy individuals and patients of a Cambodian province Southeast Asian J Trop Med Public Health 1993 24 239 49 7505485
Cambodia 2000: Results from the Demographic and Health Survey Stud Fam Plann 2002 33 269 73 12385088 10.1111/j.1728-4465.2002.00269.x
Injection Practices: rapid assessment guide WHO 2002
1998 Census of Cambodia
Bennett S Woods T Liyanage WM Smith DL A simplified general method for cluster-sample surveys of health in developing countries World Health Stat Q 1991 44 98 106 1949887
Hutin Y Hauri A Chiarello L Catlin M Stilwell B Ghebrehiwet T Garner J Injection Safety Best Practices Development Group. Best infection control practices for intradermal, subcutaneous, and intramuscular needle injections Bull World Health Organ 2003 81 491 500 12973641
Centers for Disease Control and Prevention (CDC) Transmission of hepatitis B and C viruses in outpatient settings – New York, Oklahoma, and Nebraska, 2000–2002 MMWR Morb Mortal Wkly Rep 2003 52 901 6 14508437
Williams IT Perz JF Bell BP Viral hepatitis transmission in ambulatory health care settings Clin Infect Dis 2004 38 1592 8 15156448 10.1086/420935
Raglow GJ Luby SP Nabi N Therapeutic injections in Pakistan: from the patients' perspective Trop Med Int Health 2001 6 69 75 11263465 10.1046/j.1365-3156.2001.00653.x
Lakshman M Nichter M Contamination of medicine injection paraphernalia used by registered medical practitioners in South India: an ethnographic study Soc Sci Med 2000 51 11 28 10817465 10.1016/S0277-9536(99)00426-8
Hadiyono JE Suryawati S Danu SS Sunartono Santoso B Interactional group discussion: results of a controlled trial using a behavioral intervention to reduce the use of injections in public health facilities Soc Sci Med 1996 42 1177 83 8737436 10.1016/0277-9536(95)00391-6
Chareonkul C Khun VL Boonshuyar C Rational drug use in Cambodia: study of three pilot health centers in Kampong Thom Province Southeast Asian J Trop Med Public Health 2002 33 418 24 12236445
Hardeman W Van Damme W Van Pelt M Por I Kimvan H Meessen B Access to health care for all? User fees plus a Health Equity Fund in Sotnikum, Cambodia Health Policy Plan 2004 19 22 32 14679282 10.1093/heapol/czh003
Safe Injection Global Network (SIGN) annual meeting reports, 1999–2003
The WHO Strategy regarding injection safety
Santoso B Suryawati S Prawaitasari JE Small group intervention vs formal seminar for improving appropriate drug use Soc Sci Med 1996 42 1163 8 8737434 10.1016/0277-9536(95)00390-8
Logez S Increased access to injection equipment in Burkina Faso the proceedings of the 3rd Annual International SIGN meeting: 30–31 August 2001 2001 New Delhi, India. WHO 35 35
Dziekan G Chisholm D Johns B Rovira J Hutin YJ The cost-effectiveness of policies for the safe and appropriate use of injection in healthcare settings Bull World Health Organ 2003 81 277 85 12764494
World Bank Cambodia at glance
| 15929800 | PMC1173117 | CC BY | 2021-01-04 16:28:55 | no | BMC Public Health. 2005 Jun 2; 5:56 | utf-8 | BMC Public Health | 2,005 | 10.1186/1471-2458-5-56 | oa_comm |
==== Front
BMC Public HealthBMC Public Health1471-2458BioMed Central London 1471-2458-5-601593510410.1186/1471-2458-5-60Research ArticleRoutine testing for IgG antibodies against hepatitis A virus in Israel Samuels Noah [email protected] Maccabi Healthcare Services, 130 Rachmilevich Street, Jerusalem 97791, Israel2005 6 6 2005 5 60 60 15 12 2004 6 6 2005 Copyright © 2005 Samuels; licensee BioMed Central Ltd.2005Samuels; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Viral hepatitis is highly endemic in Israel, with the hepatitis A virus (HAV) responsible for most cases. Improved socioeconomic factors, as well as the universal vaccination of infants (introduced in 1999) has resulted in a decline in infection rates in Israel. This study examines the benefits of routine testing for anti-HAV IgG in high-risk population.
Methods
A retrospective examination of the files of teenage and adult patients (aged 16–99 years; mean 33.9) in two primary care clinics found 1,017 patients who had been tested for anti-HAV IgG antibodies for either general healthcare screening or ongoing follow-up for chronic illness. Seropositive patients were then asked regarding recall of past hepatitis (i.e. jaundice, regardless of viral etiology); post-exposure prophylaxis with immune serum immunoglobulin (ISG); and active immunization with inactivated virus. Seronegative patients were subsequently sent for active immunization.
Results
Of the1,017 patient records studied (503 male, 514 female), a total of 692 were seropositive (354 males, 338 females; P = 0.113). Seropositivity rates increased with age (p < 0.005), and were highest among those born in Middle Eastern countries other than Israel (91.3%) and lowest among immigrants from South America (44.1%; P < 0.005). 456 of the seropositive patients were interviewed, of whom only 91 recalled past illness while 103 remembered receiving post-exposure prophylaxis (ISG) and 8 active vaccination. Those who were unaware of past infection were more likely to have been vaccinated with ISG than those who were aware (26.3% vs. 7.7%; p < 0.005).
Conclusion
The relatively high prevalence rate of anti-HAV seropositivity in our study may me due to the fact that the study was conducted in a primary care clinic or that it took place in Jerusalem, a relatively poor and densely populated Israeli city. Most of the seropostive patients had no recollection of prior infection, which can be explained by the fact that most hepatitis A infections occur during childhood and are asymptomatic. Routine testing for anti-HAV IgG in societies endemic for HAV would help prevent seropositive patients from receiving either post-exposure or preventive immunization and target seronegative patients for preventive vaccination.
==== Body
Background
For years Israel has been considered to be endemic for viral hepatitis, with an incidence of reported cases five to ten times that observed in the United States [1]. Most cases of viral hepatitis in Israel are caused by the hepatitis A virus (HAV), and in the 1970's the Israeli Ministry of Health instituted a wide-scale program of post-exposure prophylaxis with immune serum globulin (ISG). In 1999 universal immunization with inactivated virus (Havrix; Smith Klein Beecham) was instituted for infants, the first dose being given at 18 months and the second at 24 – 30 months of age [2]. The Israel Defense Forces (IDF) have instituted vaccination programs as well, first with ISG and, more recently, with the inactivated virus [3].
Vaccination programs, as well socioeconomic changes, have led to a significant reduction in the prevalence of HAV infection in Israel today [4,5]. In the United States, the U.S. Advisory Committee on Immunization Practices has given clear recommendations for vaccinating communities with high rates of infection (>20 cases per 100,000) or populations at risk for liver failure [6]. However, no guidelines exist for routine testing for HAV serology prior to vaccination, a policy which could potentially prevent unnecessary immunizations (both active and passive) in seropositive patients as well as target those who are seronegative for active immunization. The following study examined the current prevalence of anti-HAV serology in a selected Israeli population (patients presenting to a primary care clinic), evaluating the benefits of routine testing for populations at risk.
Methods
The records of teenage and adult patients (aged 16–99 years; mean 33.9) from two primary care clinics in Jerusalem, Israel, were retrospectively searched for anti-HAV IgG serology. The clinics are affiliated with the Maccabi Health Care Services, one of four government-funded services available to all Israeli citizens. Patients had undergone general blood tests for a number of reasons, either for follow-up of existing illness (none of which were hepatic-related) or for routine health screening, including anti-HAV IgG serology. A total of 1,017 patient files were found which contained serological results of anti-HAV antibodies from blood analyzed in the health fund's central lab, which used a microparticle enzymatic assay (MEA; AxSYM System, Abbott Diagnostics). Patients who tested seropositive for HAV were then contacted (either in person or by phone) and asked regarding the following: demographic data (country of birth); whether or not they remembered being sick with hepatitis (i.e. clinical jaundice, with or without known serological evidence of active HAV infection), and when; and whether or not they had been immunized, either passively (ISG) or actively (inactivated virus), and when. Recall of past infection was based on patient reporting alone and not through review of medical or laboratory records. Data was compiled and analyzed using the Microsoft Excel program.
Results
Prevalence of HAV seropositivity
As mentioned above, a total of 1,017 patient records (503 males and 514 females) were found to contain results of anti-HAV antibodies (from March 1998 to September 2003). The mean age of the study group was 33.9 years; 37.8 among males (range: 16–99) and 31.2 among females (range: 16–87). Among the recorded results, 692 (68.0%) were seropositive – 354 of the male patients (70.4%) and 338 of the female patients (65.8%; p = 0.113). The rates of seropositivity increased with age (see Figure 1; p < 0.005), and remained constant throughout the years of the study (p = 0.451).
Figure 1 Prevalence of positive HAV serology according to age (%)
Patients who were born in Middle Eastern countries other than Israel had the highest seropositive rate (91.3%), while those born in South America the lowest (44.1%; p < 0.005. See Figure 2). Immigrants from the Eastern Bloc countries (former Soviet Bloc and Eastern Europe) had a significantly higher prevalence of anti-HAV antibodies than native Israelis (70.3% vs. 58.7%; p = 0.016).
Figure 2 Prevalence of positive HAV serology according to country of birth(%). * Eastern Bloc = former USSR and Eastern European countries** Western Bloc = North America and Western Europe
Recall of past infection and immunization
Of the 658 patients with anti-HAV antibodies, 456 were interviewed and asked regarding past infection and vaccinations (231 males and 225 females). Only 91 had any recollection of prior illness (20.0%) – 51 of the males interviewed (22.1%) and 40 of the females (17.8%; p = 0.249), all of them at least 5 years prior to undergoing the serological testing. A total of 103 respondents remembered receiving post-exposure prophylaxis (passive immunization) with ISG. Those who were unaware of past infection were more likely to have been vaccinated with ISG than those who were aware (26.3% vs. 7.7%; p < 0.005). The reasons given for receiving ISG are listed in Table 1. Eight patients (2 male, 6 female) reported receiving the inactivated virus vaccine, of which none were aware of prior illness.
Table 1 Reasons for Passive Immunization* in Seropositive Patients
Reason Male (n) Female Total
Post-exposure prophylaxis 25 25 50
Travel to endemic country 10 3 13
Army Service 14 3 17
Other 17 6 23
Total 66 37 103
* passive immunization = immune serum globulin
Discussion
Although Israel is considered endemic for HAV infection, the prevalence of anti -HAV antibodies in our study population (68%) is much higher than that found in other studies, especially among the under-20 age group (62.8%). In a 1996 study of teenagers undergoing pre-draft evaluation, only 38.4% were seropositive [5], while serum samples from the Israeli Center for Disease Control's national serum bank in 1989 were seropositive for HAV in only 27% of 16 year-olds [4]. The relatively high prevalence of anti-HAV antibodies found in our study may be due to the fact that the study was conducted in a primary care clinic, with higher morbidity rates than the general population, though not liver-related. Another factor is the fact that both clinics are located in Jerusalem, one of Israel's poorest and most densely populated cities. Many of the patients were ultra-orthodox Yeshiva students who are at greater risk for HAV infection [7] and are not drafted into the IDF. At the same time, the higher rate of seropositivity among immigrants from Eastern bloc countries is consistent with the findings of an earlier study of this population [8], though another study of pre-draft teenagers did not find a significant difference between these immigrants and native Israelis [9].
Most of the seropositive patients in our study (80%) had no prior recollection of HAV infection. For 70% of children under the age of 6 (in communities with high rates of hepatitis A, 30–40% of children acquire infection before the age of 5 6) HAV infection is a self-limited, subclinical disease [10]. Among older children and adults, infection is usually symptomatic, with jaundice occurring in more than 70% of patients [11]. Signs and symptoms usually last less than 2 months, although 10–15% of symptomatic persons have prolonged or relapsing disease lasting up to 6 months [12]. Case fatality rates also increase with age, rising from 1.5/1000 among children less than 5 years old to 27/1000 after age 50 [13], making vaccination of unimmunized adults that much more important.
Both ISG and inactivated HAV vaccines are safe, though not without potential side effects both locally and systemically [6,14]. Aside from having to undergo two injections within a span of 6 months to a year, adult patients in Israel are required to purchase the active vaccine themselves. Seropositive patients in our study who were unaware of their immune status were more likely (by a factor of 3.4) to have unnecessarily received ISG (unnecessarily since they most likely have lifetime immunity) than those who were aware of past infection. This is probably an underestimate, since both post-exposure and pre-induction vaccinations have been implemented in Israel for nearly thirty years, and it is likely that many have forgotten receiving immunizations in the distant past. For the eight patients who received the inactivated virus without prior serological testing, it is possible (and even probable) that they too were immunized unnecessarily. Now it is too late to know whether their current seropositive status is a result of past occult infection (with lifetime immunity) or active immunization. These patients will now have to receive periodic booster vaccinations, which may have been unnecessary if prior immune status had been checked. Testing for HAV serology prior to active immunization has been shown to be both cost-effective and economically valid for Israeli travelers, assuming a cost of $130 for vaccination (which is subsidized but not free for the patient) and $30 for the IgG test (free for the patient) [15]. This may be true for the general population as well.
Conclusion
The recent adoption of a nationwide infant HAV immunization policy in Israel has also been found to be both medically and economically justifiable [16]. However, this program is aimed at the infant population, for the purpose of preventing early childhood infection. Screening the adult population in endemic countries like Israel would enable seronegative adults to receive the inactivated virus, thus preventing morbidity and mortality resulting from infection. For the seropositive adult population, unnecessary immunizations could be avoided. Asking patients whether or not they need to be vaccinated is, at best, unreliable, since most cases of HAV infection occur in childhood and are asymptomatic, and even in cases where jaundice is present the cause may not necessarily be HAV. The health establishment in Israel needs to investigate the benefits of routing testing for anti-HAV serology, especially among the high-risk adult population who were not actively immunized during childhood or military service. Such routine testing is feasible, especially in an era where it is accepted practice to conduct routine screening tests for a number of preventive measures.
Competing interests
The author(s) declare that they have no competing interest.
Authors' contributions
The design and implementation of the study, as well as statistical analysis of the data, were all done by the author (NS).
Pre-publication history
The pre-publication history for this paper can be accessed here:
==== Refs
Green MS Block C Slater P Rise in the incidence of viral hepatitis in Israel despite improved socioeconomic conditions Rev Infect Dis 1989 11 464 69 2749104
Anis E Leventhal A Roitman M Slater PE [Introduction of routine hepatitis A immunization in Israel: the first in the world. Hebrew] Harefuah 2000 138 177 80 10883087
Gdalevich M Gillis D Mimouni D Grotto I Shpilberg O [Trends in epidemiology of hepatitis in the Israel Defense Forces – direction over several years. Hebrew] Harefuah 2000 138 755 57 10883230
Green MS Aharonowitz G Shohat T Levine R Anis E Slater PE The changing epidemiology of viral hepatitis A in Israel Israel Med Assoc J 2001 3 347 51
Gdalevich M Grotto I Mandel Y Mimouni D Shemer J Ashkenazi I Hepatitis A antibody prevalence among young adults in Israel – the decline continues Epidemiol Infect 1988 121 477 79 9825802 10.1017/S0950268898001198
MMWR Prevention of Hepatitis A through active or passive immunization: recommendations of the Advisory Committee on Immunization Practices (ACIP) MMWR 1999 48 1 37
Lerman Y Chodik G aloni H Ribak J Ashkenazi S Occupations at increased risk of hepatitis A: a 2-year nationwide historical prospective study Am J Epidemiol 1999 150 312 20 10430237
Karetnyi YV Mendelson E Shlyakhov E Prevalence of antibodies against hepatitis A virus among new immigrants in Israel J Med Virol 1995 46 61 65 7623008
Almog R Low M Cohen D Prevalence of anti-hepatitis A antibodies, hepatitis B viral markers, and anti-hepatitis C antibodies among immigrants from the former USSR who arrived in Israel during 1990–1991 Infection 1999 27 212 17 10378135
Hadler SC Webster HM Erben JJ Swanson JE Maynard JE Hepatitis A in day-care centers: a community wide assessment N Engl J Med 1980 302 1222 27 6245363
Lednar WM Lemon SM Kirkpatrick JW Redfield RR Fields ML Kelley PW Frequency of illness associated with epidemic hepatitis A virus infection in adults Am J Epidemiol 1985 122 226 33 3860002
Glikson M Galun E Oren R Tur-Kaspa R Shouval D Relapsing hepatitis A. Review of 14 cases and literature survey Medicine 1992 71 14 23 1312659
Benenson AS Control of Communicable Diseases Manual 1995 6 American Public Health Association 217
Lemon SM Thomas DL Vaccines to prevent viral hepatitis N Engl J Med 1997 336 196 204 8988900 10.1056/NEJM199701163360307
Schwartz E Raveh D The prevalence of hepatitis A antibodies amongIsraeli travelers and the economic feasibility of screening before vaccination Int J Epidemiol 1998 27 118 20 9563704 10.1093/ije/27.1.118
Ginsberg GM Slater PE Shouval D Cost-benefit analysis of a nationwide infant immunization programme agains hepatitis A in an area of intermediate endemicity J Hepatol 2001 34 92 99 11211913 10.1016/S0168-8278(00)00007-6
| 15935104 | PMC1173118 | CC BY | 2021-01-04 16:28:55 | no | BMC Public Health. 2005 Jun 6; 5:60 | utf-8 | BMC Public Health | 2,005 | 10.1186/1471-2458-5-60 | oa_comm |
==== Front
BMC Public HealthBMC Public Health1471-2458BioMed Central London 1471-2458-5-621593874610.1186/1471-2458-5-62Research ArticleDOTS improves treatment outcomes and service coverage for tuberculosis in South Ethiopia: a retrospective trend analysis Shargie Estifanos B [email protected]ørn Bernt [email protected] University of Bergen Centre for International Health, Armauer Hansens Hus, N-5021 Bergen, Norway2 Southern Nations, Nationalities and Peoples' Regional State Health Bureau, P. O. Box 149, Awassa, Ethiopia2005 6 6 2005 5 62 62 12 1 2005 6 6 2005 Copyright © 2005 Shargie and Lindtjørn; licensee BioMed Central Ltd.2005Shargie and Lindtjørn; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
DOTS as a strategy was introduced to the tuberculosis control programme in Southern region of Ethiopia in 1996. The impact of the programme on treatment outcomes and the trend in the service coverage for tuberculosis has not been assessed ever since. The aim of the study was to assess trends in the expansion of DOTS and treatment outcomes for tuberculosis in Hadiya zone in Southern Ethiopia.
Methods
19,971 tuberculosis patients registered for treatment in 41 treatment centres in Hadiya zone between 1994 and 2001 were included in the study. The data were collected from the unit tuberculosis registers. For each patient, we recorded information on demographic characteristics, treatment centre, year of treatment, disease category, treatment given, follow-up and treatment outcomes. We also checked the year when DOTS was introduced to the treatment centre.
Results
Population coverage by DOTS reached 75% in 2001, and the proportion of patients treated with short course chemotherapy increased from 7% in 1994 to 97% in 2001. Treatment success for smear-positive tuberculosis rose from 38% to 73% in 2000, default rate declined from 38% to 18%, and treatment failure declined from 5% to 1%. Being female patient, age 15–24 years, smear positive pulmonary tuberculosis, treatment with short course chemotherapy, and treatment at peripheral centres were associated with higher treatment success and lower defaulter rates.
Conclusion
The introduction and expansion of DOTS in Hadiya has led to a significant increase in treatment success and decrease in default and failure rates. The smaller institutions exhibited better treatment outcomes compared to the larger ones including the zonal hospital. We identified many patients with missing information in the unit registers and this issue needs to be addressed. Further studies are recommended to see the impact of the programme on the prevalence and incidence of tuberculosis.
==== Body
Background
Ethiopia stands among the world's top 22 tuberculosis (TB) high-burden countries, with an estimated annual incidence of 250 TB cases/105 population [1,2]. In the Southern Ethiopia Regional State (SNNPRS), TB is among the leading causes for sickness and death [3]. As in many other resource-constrained settings, treatment outcomes for tuberculosis have not been satisfactory [4], mainly due to poor treatment compliance and low coverage of short course chemotherapy (SCC). Delays in the diagnosis and treatment initiation, the devastating HIV/AIDS epidemic and the potential threat of anti-tuberculosis drug resistance represent serious threats to the TB control effort in the region. The HIV co-infection among TB patients in the region is estimated at 19% [5].
Directly Observed Treatment, Short-course (DOTS) was introduced in the region in 1996. However, the impact of DOTS and its effectiveness in the regional context has not been assessed yet. Global reviews [6] and reports from Asian, African and East European countries [7-9] have favourable implications for the DOTS strategy. On the contrary, some randomised controlled studies have failed to establish the superiority of the most notable component of this strategy, direct observation of treatment, over the conventional non-observed treatment in improving treatment outcomes [10,11]. Nevertheless, DOTS is widely accepted and practised, with some TB high-burden countries achieving almost full coverage of their populations [2]. DOTS is equally effective in curing TB patients with HIV co-infection [9,12] and hence, its importance in the era of the HIV/AIDS epidemic.
With this study, we aimed to assess the results and trends in the expansion of DOTS in Hadiya Zone, Southern Ethiopia.
Methods
Study setting
We did the study in Hadiya zone, Southern Ethiopia (see map in Figure 1), with a population of 1.2 million [13,14]. In addition to fifteen diagnostic centres, five health centres and 21 health stations provide treatment for TB patients referred or transferred from the diagnostic centres, thus making the number of treatment centres 41. All treatment units have standard Unit Registers from the National Tuberculosis and Leprosy Control Programme (TLCP). TB drugs used in a combination of two or more in the region included isoniazid (H), rifampicin (R), pyrazinamide (Z), ethambutol (E), streptomycin (S) and thioacetazone (T).
The TB and Leprosy control programs were run as two separate vertical programs funded and managed mainly by the All African Leprosy and Rehabilitation Training Centre (ALERT) until the end of 1996 when the National and Regional TLCP took over the responsibility. The zonal TLCP gets administrative and technical support from the regional TLCP, and monitors the activities in the diagnostic and treatment centres through its seven woreda (district) offices. The woreda health offices have standard district TB registers from the National TLCP, and are responsible for the distribution of drugs and reagents, supervision of day to day activities in the treatment units, collection of slides for quality control and record keeping. Quarterly reports on cases detected and treatment outcomes from the woredas are gathered at the zonal level and sent to the regional TLCP.
In 1994, only Hossana Hospital provided unobserved SCC for critically sick smear-positive pulmonary TB (PTB+), miliary TB and tuberculosis meningitis cases. DOTS was initiated in 1996 in two health facilities and gradually expanded, first to the health centres in all woredas and then to the health stations. Details of treatment regimens for various categories of patients under DOTS are given in the NTLCP manual [15]. In brief, all new patients were treated with SCC (two months on RHZ +/- E or S, followed by 6 months on EH or RH), and were required to take their medications under direct supervision by the health workers at least during the intensive phase of treatment. During this phase, only critically ill patients were hospitalised, while the rest received treatment on ambulatory basis. Re-treatment cases were treated with SERHZ for 2 months, ERHZ for 1 month and ERH for 5 months. In non-DOTS areas treatment with SCC was limited to critically sick PTB+, TB meningitis and miliary TB cases while others received LCC (two months on EH +/-S, followed by 10 months on EH; TH had also been used as an alternative to EH until its recent withdrawal).
Design and data collection
This is a retrospective trend analysis. The Unit Registers reviewed contain basic information such as patient's age, sex, address, category, TB type, drug regimen, date treatment started, treatment follow-up, follow-up sputum result and treatment outcomes.
We visited all 41 TB treatment centres during July-November 2002. We checked when DOTS was initiated in each health institution and looked for the availability of TB drugs and reagents during the time of visit. We then reviewed the Unit Registers and entered the data to the computer. At three peripheral treatment centres where the unit registers could not be found, the respective district TB registers were reviewed. For each TB case, we copied the data from the registers to a computer program, SPSS for windows [16], according to the standard definitions of the National TLCP [15] on disease classification, patient categories, treatment regimens and treatment outcomes. To ensure the quality of data entered into the computer database, two people independently cross-checked each entry.
Data analysis and Statistics
The data were analysed using SPSS for Windows version 11.0 [16]. For categorical data, we used proportions with 95% confidence intervals, Odds ratio and Chi-square test to compare different groups. Multivariate analysis using logistic regression model was used to analyse the association between treatment outcomes and potential predictor variables. We set the level of statistical significance at 5%.
Treatment outcomes were analysed for the years 1994–2000 because a considerable proportion of patients registered during 2001 were still on treatment during the time of data collection. (The Ethiopian fiscal year goes from July to June. Fiscal year 2001, for example, goes from July 2001 through June 2002, and our study was commenced in July 2002). Patients with unrecorded treatment outcome were analysed as defaulters.
Results
Patient registration and case notification
A total of 19971 tuberculosis patients, 11138 (55.8%) males and 8819 (44.2%) females were registered between 1994 and 2001 with the mean (SD) age of 25.6 (13.2) years. Forty-six percent (n = 9232) of the patients were PTB+ cases. Overall, 18687 (93.6%) patients were registered as new cases, 558 (2.8%) as transferred in, 273 (1.4%) as return after default, 142 (0.7%) as failure and 139 (0.7%) as relapse cases whereas patient category was not recorded for 172 (0.9%) cases. Table 1 shows the general characteristics of the patients.
Table 1 General Characteristics of the study subjects (n = 19971), 1994–2001
Characteristics Number Percent
Age group (years)
0–14 3356 16.8
15–24 6262 31.4
25–34 5366 26.9
35–44 2706 13.5
45–54 1248 6.2
55–64 501 2.5
≥ 65 220 1.1
Unknown 312 1.6
Sex
Male 11138 55.8
Female 8819 44.2
Not mentioned 14 0.1
Patient Category
New 18687 93.6
Transferred-in 558 2.8
Return after default 273 1.4
Failure 142 0.7
Relapse 139 0.6
Unknown 172 0.9
TB Classification
Pulmonary positive 9232 46.2
Pulmonary negative 4225 21.2
Extra-pulmonary 6453 32.3
Unknown 61 0.3
Treatment Centre
Hossana Hospital 5362 26.8
Lemmo district health facilities 4011 20.1
Shashogo district health facilities 1208 6.0
Misha district health facilities 2660 13.3
Gibe district health facilities 1984 9.9
Soro district health facilities 2313 11.6
Duna district health facilities 216 1.1
Badewacho district health facilities 2217 11.1
The proportion of women among TB patients registered for treatment remained at the range of 40–45% across the years and at the range of 43–47% across the age groups below 45. However, among patients older than 45 years, the proportion of women was significantly lower (31%; 95%CI 29–33) compared to those below 45 (46%; 95%CI 45–47).
Among new cases, 46% (n = 8557) were PTB+ patients. Except for the years 1997 (38%; 95%CI 36–40) and 2000 (56%; 95%CI 54–58), this proportion showed little variations in the range of 40–50%. Table 2 shows a trend in the case notification of PTB+ over the study period. The proportion of expected PTB+ incident cases notified increased from 45% in 1994 to 116% in 1999, and declined to 67% in 2001.
Table 2 Trends in case notification of smear-positive pulmonary TB, Hadiya Zone, 1994–2001
Year Zonal Population* New PTB+ cases Reported (n = 8558) Case Notification/ 105 persons/year Proportion of estimated PTB+ incident cases notified, %**
1994 1004000 512 49 45.2
1995 1070160 1025 96 87.9
1996 1101195 1162 106 96.8
1997 1133129 946 84 76.6
1998 1165990 1277 110 100.5
1999 1199804 1510 126 115.5
2000 1234598 1267 103 94.2
2001§ 1174118 858 73 67.0
*Projected from the 1994 Population and Housing Census, CSA [13]
**Estimated Incidence of PTB+ = 109/105 persons/year based on the WHO estimates of the Global Burden of Tuberculosis for 1997 [1]
§ Population adjusted as an area with about 70–80 thousand population was taken away from Hadiya to the neighbouring Silti zone between years 2000 and 2001
PTB+: smear-positive pulmonary tuberculosis
Treatment given
Forty percent (n = 7919) of patients received SCC. Treatment regimen was not recorded for 981 (5%) cases. Table 3 presents trend in treatment regimens across the years by TB classification. The proportion of patients treated with SCC increased from 7% in 1994 to 58% in 1999, and 97% in 2001 (χ2trend, p < 0.001).
Table 3 Trend in treatment regimens for the different categories of patients (n = 19970).*
Category 1994 n (%) 1995 n (%) 1996 n (%) 1997 n (%) 1998 n (%) 1999 n (%) 2000 n (%) 2001 n (%)
All TB cases 1106 2201 2895 2742 3388 3253 2435 1950
SCC 73 (7) 311 (14) 288(10) 471 (17) 927 (27) 1881 (58) 2085 (86) 1883 (97)
LCC 1011 (91) 1684 (77) 2360 (82) 2097 (77) 2292 (68) 1302 (40) 304 (12) 20 (1)
No record 22 (2) 206 (9) 247 (8) 174 (6) 169 (5) 70 (2) 46 (2) 47 (2)
New PTB+ 512 1025 1162 946 1277 1510 1267 858
SCC 9 (2) 111 (11) 94 (8) 232 (24) 537 (42) 1170 (78) 1187 (94) 837 (97)
LCC 496 (97) 780 (76) 938 (81) 611 (65) 660 (52) 321 (21) 68 (5) 7 (1)
No record 7 (1) 134 (13) 130 (11) 103 (11) 80 (6) 19(1) 12 (1) 14 (2)
New PTB- 258 385 402 382 807 772 487 393
SCC 12 (5) 66 (17) 90 (22) 109 (28) 225 (28) 395 (51) 402 (83) 379 (96)
LCC 242 (94) 286 (74) 248 (62) 251 (66) 543 (67) 362 (47) 73 (15) -
No record 4 (1) 33 (9) 64 (16) 22 (6) 39 (5) 15 (2) 12 (2) 14 (4)
New EPTB 257 668 1177 1176 1124 721 528 570
SCC 19 (8) 73 (11) 57 (5) 70 (6) 97 (9) 197 (27) 385 (73) 559 (98)
LCC 232 (90) 565 (85) 1081 (92) 1067 (91) 993 (88) 513 (71) 138 (26) 6 (1)
No record 6 (2) 30 (4) 39 (3) 39 (3) 34 (3) 11 (2) 5 (1) 5 (1)
Relapse 8 13 21 29 15 19 19 15
SCC 2 (25) 10 (77) 12 (57) 21 (72) 13 (87) 17 (90) 19 (100) 14 (93)
LCC 4 (50) 2 (15) 9 (43) 6 (21) 2 (13) 2 (10) - -
No record 2 (2) 1 (8) - 2 (7) - - - 1 (7)
After default 35 56 27 45 33 25 21 31
SCC 5 (14) 14 (25) 15 (56) 20 (45) 15 (46) 21 (84) 17 (81) 30 (97)
LCC 30 (86) 39 (70) 11(41) 23 (51) 18 (54) 4 (16) 4 (19) -
No record - 3 (5) 1 (3) 2 (4) - - - 1 (3)
After failure 28 38 17 17 13 19 8 2
SCC 26 (93) 35 (92) 15 (88) 13 (77) 11 (85) 14 (74) 8 (100) 2 (100)
LCC 2 (7) 3 (8) 2 (12) 4 (23) 2 (15) 5 (26) - -
No record - - - - - - - -
Transferred in 6 3 65 131 89 120 86 57
SCC - - 3 (5) 3 (2) 22 (25) 43 (36) 53 (62) 38 (67)
LCC 5 (83) 2 (67) 55 (84) 124 (95) 58 (65) 57 (47) 19 (22) 7 (12)
No record 1 (17) 1 (33) 7 (11) 4 (3) 9 (10) 20 (17) 14 (16) 12 (21)
Missing info 2 13 17 10 20 46 13 29
SCC - 2 (15) 1 (5) 3 (30) 3 (15) 11 (24) 9 (69) 29 (100)
LCC - 7 (54) 12 (71) 6 (60) 11 (55) 30 (65) 2 (16) -
No record 2 4 (31) 4 (24) 1 (10) 6 (30) 5 (11) 2 (15) -
* Percentages are out of the total cases registered in the same category during the year.
PTB+ = smear-positive pulmonary tuberculosis; PTB- = smear-negative pulmonary tuberculosis; EPTB = extra-pulmonary tuberculosis
SCC = short course chemotherapy (2 months on RHZ+/- E or S, followed by 6 months on EH or RH)
LCC = long course chemotherapy (2 months on EH +/- S, followed by 10 months on EH; TH had also been used as an alternative to EH until its recent withdrawal).
R = Rifampicin,; H = Isoniazid; Z = Pyrazinamide; E = Ethambutol; S = Streptomycin; T = Thioacetazone.
During 1994–1997, more PTB- patents received SCC compared to PTB+ patients (19% vs. 12%; p < 0.05) and EPTB patients (19% vs. 7%; p < 0.05) among new cases of TB (Table 3). This trend was reversed after 1997 when more PTB+ patients (76%) were put on SCC, followed by PTB- (57%) and EPTB (42%). There was no significant difference in the treatment regimens across the age groups and between the two sexes.
Follow-up
Of the 8557 new PTB+ cases, sputum examination was repeated at the end of two months treatment for 60% (n = 5112), and 7.8% (n = 401) remained positive for AFB. At the end of five months treatment, 2747 (32%) patients had their sputum examined for AFB, and 78 (2.8%) remained smear-positive. 1823 (21%) patients had their sputum examined for AFB at (a month prior to) treatment completion, and 1.4% (n = 26) remained smear-positive. There has been a continuous and significant decline over time in the sputum positivity at two months irrespective of treatment regimen (Table 4).
Table 4 Trends in the follow-up smear results for new smear positive pulmonary tuberculosis
2nd month 5th month End of treatment
Examined for AFB (% total) sm+ Examined for AFB (% total) Sm+ Examined for AFB (% total) sm+
Cases on SCC
1994 6 (67) 0 5 (56) 0 3 (33) 0
1995 79 (71) 18 (23%) 53 (48) 4 (8%) 33 (30) 0
1996 68 (72) 15 (22%) 38 (40) 2 (5%) 25 (27) 0
1997 155 (67) 14 (9%) 94 (41) 0 74 (32) 2 (3%)
1998 342 (64) 24 (7%) 183 (34) 0 140 (26) 0
1999 824 (70) 52 (6%) 411 (35) 7 (2%) 365 (31) 2 (0.5%)
2000 817 (69) 43 (5%) 439 (37) 9(2%) 316 (27) 2 (1%)
2001§ 527 (63) 13 (3%) 171 (20) 1 (0.6%) 121 (14) 0
Cases on LCC
1994 330 (66) 45 (14%) 154 (31) 19 (12%) 86 (18) 5 (6%)
1995 508 (65) 75 (15%) 354 (45) 15 (4%) 179 (23) 4 (2%)
1996 564 (60) 59 (11%) 385 (41) 7 (2%) 223 (24) 4 (2%)
1997 302 (49) 15 (5%) 188 (31) 5 (3%) 86 (14) 3 (4%)
1998 263 (40) 19 (7%) 127 (19) 7 (6%) 80 (12) 2 (3%)
1999 182 (57) 7 (4%) 86 (27) 1 (1%) 68 (21) 2 (3%)
2000 46 (68) 1 (2%) 9 (13) 0 4 (6) 0
2001§ 2 (29) 1 2 (29) 0 1 (14) 0
Unknown regimen
1994 0 0 2 (29) 1 2 (29) 0
1995 9 (7) 0 4 (3) 0 3 (2) 0
1996 25 (19) 0 9 (7) 0 3 (2) 0
1997 23 (22) 0 11 (11) 0 3 (3) 0
1998 27 (34) 0 19 (24) 0 5 (6) 0
1999 4 (21) 0 1 (5) 0 1 (5) 0
2000 4 (33) 0 1 (8) 0 0 0
2001§ 5 (36) 0 17) 0 2 (14) 0
sm+ = sputum smear positive for acid-fast bacilli out of examined.
SCC = short course chemotherapy; LCC = long course chemotherapy; AFB = acid-fast bacilli.
§Follow-up smears for the 5th month and end of treatment were not complete for the year 2001 as a considerable number of patients were still on treatment during the time of data collection.
Sputum positivity at the completion of fifth month treatment remained at the range of 0–2% for those on SCC, with the exception of 1995 and 1996 that exhibited 8% and 5% respectively. For those on LCC, smear positivity at 5th month decreased from 12% in 1994 to 1% in 1999. Overall, patients on LCC contributed more to the 5th month and end of treatment smear-positivity (treatment failure), than those on SCC (p < 0.05; table 4).
Treatment results
We analysed treatment outcomes for the years 1994–2000 and, as a result, we evaluated 16943 (85% of the total) cases. Of these, 8268 (49%) successfully completed treatment, 3151 (18.6%) defaulted, 110(0.6%) had treatment failure, 446 (2.6%) died and 2000 (10%) were transferred out, while 2968 (17.5%) had no record of treatment outcomes. Assuming that patients with unrecorded treatment outcome had all defaulted from treatment, a total of 6119 (36.1%) patients defaulted.
Among new PTB+ (and all TB) patients, treatment success was higher among patients on SCC, while default and failure rates were higher among those on LCC (Table 5). Death in all categories was higher among those on SCC. Among new cases on SCC, PTB+ cases had 1.8 (65% vs.37%) and 1.4 (65% vs. 48%) times higher rate of treatment success compared to PTB- and EPTB cases, respectively (p < 0.001). Female PTB+ patients had significantly higher treatment success (58% vs. 54%; p = 0.001) and lower defaulter rate (26% vs. 30%; p < 0.001) than males.
Table 5 Treatment outcomes for different categories of patients on short and long course regimens (n = 16943)
New cases
PTB+ (%) PTB- (%) EPTB (%) Relapse (%) After default (%) After failure (%) Transferred in (%)
Patients on SCC
Treatment success 2166 (65) 475 (37) 436 (48) 62 (66) 49 (46) 65 (53) 79 (64)
Default* 726 (22) 483 (37) 320 (36) 13 (14) 45 (42) 31 (25) 33 (26)
Failure 25 (0.7) - - 2 (2) 1 (1) 6 (5) 3 (2)
Death 117 (3.5) 72 (5) 24 (3) 11 (12) 5 (5) 2 (1) 2 (2)
Transferred out 306 (9) 269 (21) 118 (13) 6 (6) 7 (7) 18 (15) 7 (6)
Patients on LCC
Treatment success 1986 (51) 772 (39) 1932 (42) 14 (56) 32 (25) 11 (61) 189 (59)
Default* 1365 (35) 972 (48) 1922 (42) 8 (33) 79 (61) 2 (11) 24 (8)
Failure 66 (2) - - 1 (4) 2 (2) 3 (17) 1 (0.3)
Death 107 (3) 57 (3) 37 (1) 2 (8) 2 (2) 1 (5) 7 (2)
Transferred out 350 (9) 204 (10) 697 (15) - 14 (11) 1 (6) 3 (1)
* Patients with missing treatment outcome information were assumed to have defaulted and analysed as defaulters.
PTB+ = smear positive pulmonary tuberculosis; PTB- = smear negative pulmonary tuberculosis; EPTB = extra-pulmonary tuberculosis
SCC = short course chemotherapy (2 months on RHZ+/- E or S, followed by 6 months on EH or RH)
LCC = long course chemotherapy (2 months on EH +/-S, followed by 10 months on EH; TH had also been used as an alternative to EH until its recent withdrawal).
R = Rifampicin,; H = Isoniazid; Z = Pyrazinamide; E = Ethambutol; S = Streptomycin; T = Thioacetazone.
Patients registered as "return after default", had significantly lower treatment success compared to new cases, both for all TB (34% vs. 49%; p < 0.001), and for PTB+ (34% vs. 58%; p < 0.001). Furthermore, return after default cases were more likely to default again compared to new cases among PTB+ patients (53% vs. 29%; p < 0.001) and all TB patients (53% vs. 36%; p < 0.001). Treatment failure was five times higher among cases that received re-treatment for previous failure compared to new cases of PTB+ (6.4% vs. 1.2%; p < 0.001); however, both groups had comparable treatment success, mainly due to a lower defaulter rate among failure cases (24% vs. 29%).
Patients for whom follow-up sputum smear remained positive at the second month during treatment had significantly lower treatment success than those with negative smear result (53% vs. 74%; p < 0.001), mainly as a result of higher defaulter (24% vs. 18%) and failure (10% vs. 1%) rates among the former group.
Table 6 presents treatment outcomes for new cases of TB across the years. A steady rise in treatment success and decline in defaulter rate was noticed particularly among patients on SCC. Treatment failure showed a remarkable decline in both SCC and LCC groups. Death rate did not show much variation across the years.
Table 6 Treatment outcomes across the years for new cases of tuberculosis
1994 n (%) 1995 n (%) 1996 n (%) 1997 n (%) 1998 n (%) 1999 n (%) 2000 n (%)
PTB+ on SCC
Treatment success 5 (42) 40 (34) 45 (38) 122 (47) 338 (60) 811 (69) 805 (74)
Default* 5 (42) 61 (51) 50 (42) 77 (30) 114 (20) 225 (19) 194 (17)
Failure - 3 (3) 2 (2) 2 (1) - 8 (1) 10 (1)
Death - 4 (3) 2 (2) 10 (4) 24 (4) 44 (4) 33 (3)
Transferred out 2 (17) 11 (9) 20 (17) 46 (18) 89 (16) 88 (7) 50 (5)
PTB+ on LCC
Treatment success 188 (38) 384 (48) 564 (56) 271 (45) 308 (52) 231 (72) 40 (68)
Default* 190 (38) 298 (38) 304 (30) 246 (40) 240 (40) 72 (22) 15 (25)
Failure 23 (5) 18 (2) 8 (1) 8 (1) 6 (1) 3 (1) -
Death 17 (3) 21 (3) 18 (2) 20 (3) 19 (3) 9 (3) 3 (5)
Transferred out 78 (16) 71 (9) 107 (11) 63 (10) 24 (4) 6 (2) 1 (2)
PTB- on SCC
Treatment success 1 (8) 15 (23) 18 (20) 32 (29) 67 (30) 153 (39) 189 (47)
Default* 8 (67) 40 (60) 67 (74) 55 (50) 85 (38) 116 (29) 112 (28)
Death 1 (8) 6 (9) 2 (2) 10 (9) 8 (4) 25 (6) 20 (5)
Transferred out 2 (17) 5 (8) 3 (3) 12 (11) 65 (29) 101 (26) 81 (20)
PTB- on LCC
Treatment success 107 (44) 88 (31) 84 (34) 78 (31) 199 (37) 182 (50) 34 (47)
Default* 101 (42) 163 (57) 127 (51) 141 (57) 280 (51) 135 (37) 25 (34)
Death 4 (2) 5 (2) 6 (2) 5 (2) 16 (3) 20 (6) 1 (1)
Transferred out 30 (12) 30 (11) 31 (13) 27 (11) 48 (9) 25 (7) 13 (18)
EPTB on SCC
Treatment success 4 (21) 19 (26) 25 (44) 29 (32) 43 (44) 101 (51) 215 (56)
Default* 11 (58) 43 (59) 29 (51) 30 (33) 29 (30) 68 (35) 110 (28)
Death 2 (11) 6 (8) 1 (2) 3 (4) 1 (1) 4 (2) 7 (2)
Transferred out 2 (11) 5 (7) 2 (4) 28(31) 24 (25) 24 (12) 53 (14)
EPTB on LCC
Treatment success 80 (35) 274 (49) 559 (52) 387 (36) 341 (34) 222 (43) 69 (50)
Default* 122 (52) 203 (36) 321 (30) 412 (39) 553 (56) 253 (49) 58 (42)
Death 2 (1) 3 (1) 3 (0.3) 7 (1) 8 (1) 14 (3) -
Transferred out 28 (12) 85 (15) 198 (18) 260 (24) 91 (9) 24 (5) 11 (8)
* Patients with missing information on treatment outcome were assumed to have defaulted and analysed as defaulters.
PTB+ = smear positive pulmonary tuberculosis; PTB- = smear negative pulmonary tuberculosis; EPTB = extra-pulmonary tuberculosis
SCC = short course chemotherapy (2 months on RHZ+/- E or S, followed by 6 months on EH or RH)
LCC = long course chemotherapy (2 months on EH +/-S, followed by 10 months on EH; TH had also been used as an alternative to EH until its recent withdrawal).
R = Rifampicin,; H = Isoniazid; Z = Pyrazinamide; E = Ethambutol; S = Streptomycin; T = Thioacetazone.
When we adjusted the outcome measures for treatment results by various potentially confounding variables, significantly higher treatment success was exhibited among female patients, those 15–24 years, patients treated with SCC, those on re-treatment for relapse, PTB+ cases, those treated during 2000 and those treated in the Lemmo district health facilities (Table 7). Meanwhile, male patients, patients aged 45–54, PTB- cases, those on LCC, return after default cases and those treated in Duna district health facilities exhibited significantly higher default rate.
Table 7 Adjusted odds ratios for various factors that might affect treatment outcomes among registered tuberculosis patients
Treatment success (all TB) Default (all TB)
Characteristic Percent1 Adjusted OR* (95% CI) p-value Percent1 Adjusted OR* (95% CI) p-value
Sex
Male 45.5 1.00 37.5 1.00
Female 49.4 1.15(1.08–1.23) <0.001 34.0 0.88(0.82–0.94) <0.001
Age group (years)
0–14 42.6 0.83 (0.75–0.92) <0.001 41.2 1.17 (1.06–1.30) 0.002
15–24 (reference group) 51.1 1.00 33.4 1.00
25–34 47.5 0.84(0.77–0.91) <0.001 34.4 1.07 (0.98–1.17) 0.14
35–44 45.7 0.76 (0.68–0.84) <0.001 36.1 1.14 (1.03–1.28) 0.02
45–54 44.9 0.69 (0.60–0.79) <0.001 37.7 1.26 (1.09–1.46) 0.002
55–64 51.4 1.04 (0.84–1.29) 0.71 35.4 1.04 (0.81–1.27) 0.90
≥ 65 37.4 0.67 (0.48–0.93) 0.02 43.7 1.27 (0.92–1.726 0.15
Patient category
New 47.0 1.00 35.9 1.00
Transferred-in 59.5 1.09 (0.89–1.36) 0.40 35.7 1.19 (0.95–1.48) 0.13
Return after default 33.9 0.68 (0.51–0.92) 0.01 52.9 1.57 (1.19–2.07) 0.002
Treatment failure 54.3 1.30 (0.91–1.86) 0.15 23.6 0.72 (0.48–1.09) 0.12
Relapse 62.9 1.51(1.01–2.26) 0.05 16.9 0.50 (0.30–0.82) 0.006
TB type
Pulmonary positive 55.3 1.00 28.7 1.00
Pulmonary negative 37.5 0.55 (0.50–0.60) <0.001 43.7 2.06 (1.87–2.26) <0.001
Extra-pulmonary 42.4 0.51 (0.47–0.55) <0.001 41.1 1.94 (1.78–2.11) <0.001
Treatment regimen
Short course chemotherapy 55.5 1.00 27.7 1.00
Long course chemotherapy 45.0 0.68 (0.62–0.75) <0.001 40.9 1.46 (1.33–1.61) <0.001
Treatment Centre**
Hossana Hospital 27.0 1.00 40.0 1.00
Lemmo district HF 60.4 5.14 (4.62–5.72) <0.001 20.6 0.28 (0.25–0.31) <0.001
Shashogo district HF 50.8 2.81 (2.41–3.28) <0.001 44.1 1.18 (1.01–1.37) 0.04
Misha district HF 60.3 4.78 (4.23–5.39) <0.001 33.0 0.58 (0.51–0.65) <0.001
Gibe district HF 60.7 4.78 (4.20–5.45) <0.001 26.2 0.51 (0.45–0.59) <0.001
Soro district HF 50.5 2.70 (2.39–3.06) <0.001 42.5 1.11 (0.98–1.26) 0.09
Duna district HF 30.2 0.77 (0.55–1.08) 0.12 67.3 5.18 (3.71–7.24) <0.001
Badewacho district HF 41.1 1.64 (1.44–1.86) <0.001 54.4 2.11 (1.86–2.40) <0.001
Year of treatment
1994 38.4 1.00 42.7 1.00
1995 40.6 1.18 (0.99–1.39) 0.06 39.9 1.17 (1.00–1.37) 0.05
1996 48.7 1.29 (1.10–1.51) 0.002 33.3 0.83 (0.71–0.97) 0.02
1997 38.9 0.72 (0.61–0.85) <0.001 39.5 1.08 (0.93–1.27) 0.32
1998 41.9 0.74 (0.63–0.87) <0.001 43.8 1.20 (1.03–1.40) 0.02
1999 56.7 1.37 (1.16–1.62) <0.001 30.0 0.59 (0.5–0.70) <0.001
2000 59.8 1.41 (1.18–1.69) <0.001 25.8 0.54 (0.45–0.65) <0.001
OR = odds ratio; CI = confidence intervals; HF = Health facilities
* All the variables in the table are included in the model.
** All treatment centres in a district grouped together as a unit.
1 Percentage out of total registered for treatment. Patients with missing outcome record were assumed to have defaulted and analysed as defaulters.
Trend over time
DOTS was initiated in 1996 in a hospital and one health centre, with potential population coverage of 25% (defined as population living within 2 hours walking distance from a health facility; estimated at 250,000 for the hospital and 25000 for the health centre). The number of health facilities providing DOTS increased to 10 in 1997, 30 in 1999 and 41 in 2001, making the population coverage by DOTS 31%, 58% and 75% respectively. The proportion of patients treated with SCC increased from 7% in 1994 to 27% in 1998, 58% in 1999, and 97% in 2001. 95% (39/41) of the treatment centres had at least isoniazid, rifampicin, pyrazinamide and ethambutol at the time of visit for data collection. Reagents for Acid-fast stain were available in nine of the 13 diagnostic centres functioning at the time.
Simultaneously, treatment success for new PTB+ patients (on SCC and LCC together) increased from 38% in 1994 to 56% in 1998, 70% in 1999 and 73% in 2000 (χ2trend, p < 0.001). Defaulting among new PTB+ patients declined from 38% in 1994 to 30% in 1998, 20% in 1999 and 18% in 2000 (χ2trend, p < 0.001). Treatment failure decreased from 5% in 1994 to 1% in 2000. The proportion of reported deaths remained unchanged over years with some variations in the range of 2–5%.
Treatment at small and large centres
Thirty-one out of 40 (77.5%) peripheral treatment centres had significantly higher treatment success, and 28 (70%) of them had significantly lower defaulter rate compared to the zonal hospital (details not shown). Further comparison by districts revealed that six of the seven rural districts had significantly better treatment success while three out of seven had lower defaulter rate than the zonal hospital (Table 7).
Discussion
The results of our study show that there has been a continuous increase in treatment success and eventual decline in defaulter and failure rates in parallel to the expansion and decentralisation of DOTS to the lower treatment units. Treatment with SCC increased from a very low coverage in 1994 to almost full coverage in 2001 partly due to the expansion of DOTS (with SCC as one of its elements), and partly due to the regional TLCP commitment to SCC both in DOTS and non-DOTS areas. However, trends in case detection and notification showed inconsistencies over years.
In the hierarchy of study designs, observational studies come after the randomised controlled trials [17]. Nevertheless, in the real field condition, where randomised trials are not logistically feasible, such observational study designs may provide important and valid information. Our study design does not allow comparison of treatment outcomes between the DOTS and non-DOTS areas. However, this study gives us a valuable information on the program performance before and along the course of expanding DOTS in this resource-constrained rural setting.
Four years after the introduction of DOTS in the zone, it has been possible to achieve treatment success of 73% in 2000 for new PTB+ patients. Faring well towards the WHO/IUATLD recommended 85%, this confirms the finding of other studies [7,18] that the DOTS strategy works well in resource-constrained settings with low overall health coverage. Increased coverage by SCC, improved access to care through decentralisation of the service and improved patient follow-up with the introduction of DOTS have most likely played a significant role in improving the treatment outcomes.
Higher treatment success and lower default among female patients confirms previous study findings [11]. However, the proportion of females among patients registered for TB treatment was found to be consistently low, and it was exceptionally lower among patients older than 45 years. This may reflect a genuine gender difference in the TB epidemiology [19-21]. However, the possibility of this being a reflection of gender differentials in access to health care within the society may need to be ruled out by further studies.
Patients treated at the peripheral treatment centres exhibited better treatment outcomes compared to those treated in the zonal hospital, which implies better follow-up of cases or better access to the TB care services.
Despite significant decline in defaulter rate over time, patients that received re-treatment as "return after default", were much more likely to default again compared to new patients. This group of defaulters seems refractory to the conventional approach of treatment supervision; social and cultural factors that might play a role need to be explored. More death among patients on SCC was an indication of the policy that severely sick patients and those co-infected with HIV be a priority for treatment by SCC and these groups were more likely than others to die. Though lower among patients on SCC, the high proportion of failure among patients retreated for previous failure might signal the emergence of multi-drug resistant TB (MDR-TB). Earlier studies have shown that MDR has so far been below 1% [22,23].
The proportion of PTB+ was fairly stable in the range of 40–50% across the years, which indicates that the diagnosticians uniformly observed the diagnostic algorithms recommended by the NTLCP. The case detection rate (CDR), as estimated by the proportion of expected incident cases notified, showed an encouraging increase from 45% in 1994 to 115% in 1999, well above the CDR recommended by the WHO. The most plausible explanation for this might be that the vigorous implementation of the program during the earlier years of introduction of DOTS might have enabled detection of a big pool of prevalent cases of TB. But the pace in case detection could not be maintained during 2000 and 2001 when the CDR fell to 94% and 67% respectively. Reduction in the incidence of TB could be a possible explanation, but one cannot justify such a fast decline in a very short time. This calls for some case detection improvement initiatives to be in place as the proportion of TB cases detected and cured under DOTS is one of the health-related indicators of the millennium development goals [24]. Quality of the laboratory services and the possibility of under-reporting are among factors to be explored further.
Two major areas of program weakness need to be addressed. First, 94% of the patients were registered as new cases, which suggests that some re-treatment cases had been wrongly classified as new. Further, treatment outcomes have not been recorded for about one-fifth of the patients. Improving the record keeping system seems to be an immediate priority. Second, the proportion of PTB+ patients who had follow-up sputa examined for AFB was low. The threat of anti-TB drug resistance is imminent, and it is important to strengthen patient follow-up with sputum examinations. About one-third of the peripheral diagnostic facilities lacked reagents for Ziehl-Neelsen stain during the time of visit, and this might partly explain the low performance.
Conclusion
The introduction and expansion of DOTS in Hadiya has led to a significant increase in treatment success and decrease in default and failure rates. The smaller institutions exhibited better treatment outcomes compared to the larger ones including the zonal hospital. The high number of patients with missing information in the unit registers is perhaps an issue that needs to be addressed as urgently as possible. Further studies are recommended to see the impact of the programme on the prevalence and incidence of tuberculosis.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
EBS was the principal investigator and participated in the design of the study, conducted the study, performed data entry and analysis, and wrote the manuscript. BL was the project co-ordinator and participated in the design, data analysis and write-up of the manuscript.
Figure 1 Map of Ethiopia with the study area highlighted. Ethiopia is administratively divided into nine regional states and two city administrations, and the Southern Nations, Nationalities and Peoples' Regional State (SNNPRS) accounts for one-fifth (13 million) of the total population of the country. The study area (Hadiya zone) has got a population of 1.2 million.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
We would like to thank the Southern Nations, Nationalities and Peoples' Regional Health Bureau, the regional and zonal TLCP and the staff of respective health facilities involved in the study for their genuine support during the field data collection. The Centre for International Health, University of Bergen funded this study.
==== Refs
Dye C Scheele S Dolin P Pathania V Raviglione MC Consensus statement. Global burden of tuberculosis: estimated incidence, prevalence, and mortality by country. WHO Global Surveillance and Monitoring Project JAMA 1999 282 677 686 10517722 10.1001/jama.282.7.677
World Health Organization 5050:Towards a TB-free future 2001 Geneva, WHO
Southern Ethiopia Regional State Health Bureau The Health Sector Development Plan (2000-2004) 2001 Awassa, RHB
Lindtjørn B Madebo T The outcome of tuberculosis treatment at a rural hospital in Southern Ethiopia Tropical Doctor 2001 31 132 135 11444329
Yassin MA Takele L Gebresenbet S Girma E Lera M Lendebo E Cuevas LE HIV and Tuberculosis Coinfection in the Southern Region of Ethiopia: A Prospective Epidemiological Study Scand J Infect Dis 2004 36 670 673 15370654 10.1080/00365540410020848
Pio A Luelmo F Kumaresan J Spinaci S National tuberculosis program review: experience over the period 1990-95 Bull World Health Organ 1997 75 569 581 9509630
Zhang L-X Tu D H Enarson D A The impact of directly observed treatment on the epidemiology of tuberculosis in Beijing Int J Tuberc lung Dis 2000 4 904 910 11055756
Kazeonny B Khorosheva T Aptekar T Rybka L Kluge H Jakubowiak W Pashkevich D Evaluation of Directly Observed Therapy Short Course strategy for treating tuberculosis- Orel Oblast, Russian Federation, 1999-2000 MMWR 2001 50 204 206
Kassim S Sassam-Morokro M Akhan A Abouya L Y Digbeu H Yesso G Coulibaly I M Coulibaly D Whitaker P J DR et al Two-year follow-up of persons with HIV-1 and HIV-2-associated pulmonary tuberculosis treated with short-course in West Africa AIDS (London, England) 1995 9 1185 1191 8519456
Volmink J Garner P Directly observed therapy for treating tuberculosis (Chocrane Review) 2001 Oxford, The Chocrane Library
Wally JD Khan MA Newell JN Khan MH Effectiveness of the direct observation component of DOTS for tuberculosis: a randomised controlled trial in Pakistan Lancet 2001 357 664 669 11247549 10.1016/S0140-6736(00)04129-5
Kelly P M Cumming R G Kaldor J M HIV and tuberculosis in rural sub-Saharan Africa: a cohort study with two-year follow-up Transactions of the Royal Society of Tropical Medicine and Hygiene 1999 93 287 293 10492761 10.1016/S0035-9203(99)90025-1
Central Statistics Authority The 1994 Population and Housing Census of Ethiopia: Results for the Southern Nations, Nationalities and People's Region 1996 Addis Ababa, CSA
Hadiya zonal department of Planning and Economic Development The popolation of Hadiya zone by woredas: projected from the results of 1994 Population and Housing Census 2002 Hossana,
Ministry of Health of Ethiopia Tuberculosis and Leprosy Control Programme Manual 2002 2nd Addis Ababa, MOH
SPSS for windows. Release 11.0.0 (19 Sep 2001). Standard Version 2001 , SPSS inc.
Grimes DA Schulz KF An overview of clinical research: the lay of the land Lancet 2002 359 57 61 11809203 10.1016/S0140-6736(02)07283-5
Balasubramanian V N Oommen K Samuel R DOT or not? Direct observation of anti-tuberculosis treatment and patient outcomes, Kerala State, India Int J Tuberc lung Dis 2000 4 409 413 10815733
Holmes C B Hausler H Nunn P A review of sex differences in the epidemiology of tuberculosis Int J Tuberc lung Dis 1998 2 96 104 9562118
Hamid Salim M A Declercq E Van Deun A Saki K A R Gender differences in tuberculosis: a prevalence survey done in Bangladesh Int J Tuberc lung Dis 2004 8 952 957 15305476
Balasubramanian R Garg R Santha T Gopi P G Subramani R Chandrasekaran V Thomas A Rajeswari R Ananadakrishnan S Perumal M Niruparani C Sudha G Jaggarajamma J Frieden T R Narayanan P N Gender disparities in tuberculosis: report from a rural DOTS programme in south India Int J Tuberc lung Dis 2004 8 323 332 15139471
Demissie M Gebeyehu M Berhane Y Primary resistance to anti-tuberculosis drugs in Addis Ababa, Ethiopia Int J Tuberc lung Dis 1997 1 64 67 9441061
Demissie M Lemma E Gebeyehu M Lindtjørn B Sensitivity to Anti-tuberculosis Drugs in HIV-positive and -negative Patients in Addis Ababa Scand J Infect Dis 2001 33 914 919 11868765 10.1080/00365540110076822
World Health Organization The World Health Report 2003: Shaping the Future 2003 Geneva, WHO
| 15938746 | PMC1173119 | CC BY | 2021-01-04 16:28:55 | no | BMC Public Health. 2005 Jun 6; 5:62 | utf-8 | BMC Public Health | 2,005 | 10.1186/1471-2458-5-62 | oa_comm |
==== Front
BMC PsychiatryBMC Psychiatry1471-244XBioMed Central London 1471-244X-5-251591069210.1186/1471-244X-5-25Research ArticlePretreatment Beck Depression Inventory score is an important predictor for Post-treatment score in infertile patients: a before-after study Khademi Afsaneh [email protected] Ashraf [email protected] Marzieh [email protected] Fatemeh [email protected] Ali Ahmadi [email protected] Infertility Ward, Shariati Hospital, Tehran University of Medical Sciences, North Kargar Street, Tehran, 14114, I R Iran2 Vali-e-Asr Reproductive Health Research Center, Vali-e-Asr Hospital, Emam Khomeini Hospital, Tehran University of Medical Sciences, Keshavarz Blvd, Tehran, 14194, I R Iran3 Roozbeh Hospital, Tehran University of Medical Sciences, South Karger Street, Tehran, 13185, I R Iran2005 24 5 2005 5 25 25 3 10 2004 24 5 2005 Copyright © 2005 Khademi et al; licensee BioMed Central Ltd.2005Khademi et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
The experience of infertility can be extremely stressful. Some of the risk factors for depression in infertility are being female, repeated unsuccessful treatment cycles or a 2 to 3 year history of infertility, low socioeconomic status, foreign nationality, lack of partner support, life events and previous depression. In this study, we analyzed the Beck Depression Inventory score at the beginning and the end of infertility treatment, to determine which factors may influence the BDI score after treatment of infertility.
Methods
In a before-after study, in a university-affiliated teaching hospital, 251 women who had been visited for assisted reproductive technology infertility treatment participated in the study. BDI score was assessed before and after treatment of infertility.
Results
The mean BDI score rose after unsuccessful treatment and dropped after successful treatment. Those with lower education levels had a higher BDI score before treatment. BDI score after treatment was positively correlated with pretreatment BDI scoreand duration of infertility.
Conclusion
BDI score after treatment was strongly connected to the BDI score before treatment, the result of therapy and to the duration of infertility. The influence of duration of infertility on BDI score after treatment of infertility is weak. So a simple method to screen patients at risk of depression after infertility treatment is determining pretreatment BDI score and predicting the result of infertility treatment by other risk factors.
==== Body
Background
Almost 21% of the female population experience major depression in their life [1]. Twice as many females experience some form of depression when compared to male [2]. Female depression has higher risk on first onset, can last longer, and often recur [3,4]. There is established relationship between life stress and depression [5].
Infertility is a stressful event in life of human being. In a comparison to patients with other medical conditions, psychological symptoms associated with infertility are similar to those related to cancer, hypertension, and cardiac rehabilitation [6]. Infertile women, in comparison with control group, showed higher scores on the depression and anxiety scales [7,8].
Evidentially, depression has some neurobiological and hormonal mechanisms. Changes in ovarian hormones are likely necessary, but not sufficient for inducing depression [9]. The risk of relapse after treatment is 2.5 times higher in women; on the other hand, non-remission rate is similar in both sexes [10]. It appears that the sex difference cannot explain the sex-ratio relapse rate. As a result, there should be multiple factors including sex for inducing depression overall and in infertile subjects [3]. Many studies have been considered to determine risk factors of depression in infertility. In some studies, risk factors include female gender, repeated treatment cycles, unsuccessful treatments, low socioeconomic state, foreign nationality, lack of partner's support for women, life events for female, previous depression, and 2 to 3 years history of infertility [8,11,12]. However, some of these factors such as short period of infertility and husband cooperation have not been confirmed in other studies [12,13]. The above-mentioned studies were designed as cross-sectional studies. So far, there is no prospective cohort or before-after study to find predictors of depression in infertile patients after treatment except a single one [14]. Lok et al showed that severity of depression following a failed treatment was positively associated with the duration of infertility. However, the post-treatment BDI scores were not associated with type of infertility treatment received, age, education, cause of infertility and number of previous treatments received [14].
Screening depression is a difficult task. The reason being is that there are numerous questionnaires for interpretation of psychological symptoms. Beck Depression Inventory (BDI) was developed and revised by Beck et al [15,16]. This 21-item self-report questionnaire was intended to assess the severity of current depressive symptomatology in the psychiatric population. It is written on a fifth or sixth-grade reading level. It requires minimal time and no special training to administer. The BDI has been used, extensively, in clinical diagnosis and research [15,16]. Versions in other languages are confirmed and used, as well [17-19]. In our study, Persian version of BDI has been employed.
We analyzed Beck Depression Inventory score at the beginning and at the end of treatment cycle to determine which factors may influence the score of BDI, after treatment of infertility.
Methods
Between April 2003 and 2004, 350 infertile women, whom had been visited in the Infertility Ward of Shariati Hospital in Tehran, participated in a prospective before-after study.
Exclusion criteria were out of Tehran residency, definite diagnosis of mood disorders (with or without current treatment), medications reportedly associated with depression (e.g. steroidal contraceptives), and medical conditions associated with depression such as thyroid dysfunction and diabetes mellitus [20]. All subjects signed informed consent. Demographic data collected included age, education, type of infertility, duration of infertility, cause of infertility, and history of previous treatment (expressed as number). Candidates were asked to complete BDI (BDI1) in their first visit, during waiting periods, at the outpatient clinic. The questionnaire was completed by an assistant for uneducated subjects. Accordingly, BDI score was calculated.
Index score of ≤9 is considered to be within normal range, a score of 10 to 15 shows minimal depressive symptomatology, a score of 16–31 points toward mild depression, a score of 32–47 is in favor of moderate depression and a score of >47 indicates severe depression [16].
Due to rules of ethics, 10 patients who had the score of 47 or above were informed about their condition. Eight of these 10 patients were excluded from study since it was essential for them to seek psychiatric consultation as soon as possible. We continued the study with 342 patients. The treatment consisted of either intrauterine insemination (IUI) or assisted reproductive technology (ART). IUI candidates were excluded from the study. Therefore, the sample size was 257. At day 16 after embryo transfer, a positive result of treatment was defined as beta hCG (β-hCG) ≥200 IU/ml. One to Three weeks after receiving result of β-hCG, patients were asked to complete the second BDI (BDI2).
This study was approved by ethics committee of Tehran University of Medical Sciences. The statistical analysis was performed using the Statistical Package for Social Sciences, version 10.0 (SPSS Inc., Chicago, IL). The primary outcome measure was the score of BDI after treatment. Data was expressed as means +/-SD and percentile of total. The tests being used were Wilcoxon Signed Ranks test, Mann-Whitney test, one way ANOVA, multiple regression analysis, and chi-square test.
Results
A total number of 257 women were entered into the study after completing BDI1. Six (2.3%) patients refused answering BDI2. As a result, there were 251 paired complete questionnaires.
Demographic characteristics of patients are given in Table 1. We divided the patients into four groups based on cause of infertility. The prevalence was lowest in unexplained infertility (10%) and highest in female infertility (43%). The education level was divided into six groups. A large number of participants were at intermediate education level (35.1%) and a few of them were uneducated (2.4%). The number of previous attempts for treatment of infertility (IUI and/or ART) defers from 0 (24.7%) to 11 times (0.4%). Positive result of β-hCG was achieved in 61 patients (24.3%) (Table 1).
Table 1 Demographic characteristics of subjects
Characteristic No. Mean(± SD) or %
Age (y) 251 28.9 ± 5.5
Duration of infertility (y) 251 6.9 ± 4.5
No. of previous treatment 251 1.3 ± 1.4
Education No education 6 2.4
Primary school 36 14.3
Junior school 60 23.9
High school 12 4.8
Intermediate education 88 35.1
University 49 19.5
Type of infertility Primary 230 91.6
Secondary 21 8.4
Cause of infertility Male 86 34.3
Female 108 43
Combined 32 12.7
Unexplained 25 10
Result of β-hCG Positive 61 24.3
Negative 190 75.7
The differences of somatic variables were analyzed between pregnant and non-pregnant subgroups. Pregnant subjects were younger (P < 0.000), and had shorter duration of infertility (P = 0.005). There were no statistically significant difference in terms of type of infertility, education, cause of infertility, mean number of previous treatment, and mean score of BDI1 (Table 2).
Table 2 Comparison of demographic characteristics between pregnant and non-pregnant subjects
Pregnant (n = 61) Non-pregnant (n = 190) P
Mean age (y) 26.6 ± 4.2 29.6 ± 5.7 <.000
Duration of infertility (y) 5.5 ± 3.7 7.4 ± 4.6 .003
Primary infertility (%) 58 (95.1) 172 (90.5) NS
Cause of infertility (%) Male 22 (36.1) 64 (33.7) NS
Female 27 (44.3) 81 (42.6)
Both 7 (11.5) 25 (13.2)
Unknown 5 (8.2) 20 (10.5)
Education (%) No education 0 6 (3.2) NS
Primary school 6 (9.8) 30 (15.8)
Guiding school 11 (18) 49 (25.8)
High school 3 (4.9) 9 (4.7)
Completed high school 29 (47.5) 59 (31.1)
University 12 (19.7) 37 (19.5)
Previous treatment 1.2 ± 1.4 1.3 ± 1.4 NS
BDI1 score 14.6 ± 11.3 14.5 ± 9.8 NS
The BDI score at the beginning of the study (BDI1) was within normal range (0–15) in 61% of patients. In 31% the score was 16–31, suggestive of mild depression, and only 8% of the women had BDI score higher than cutoff score (≥32), suggestive of moderate and severe depressive symptoms.
After knowing the results of β-hCG, BDI score changed. After treatment, 47% of the whole sample was within normal range. In pregnant and non-pregnant subjects, normal score of BDI2 was found 95.1% and 31.6%, respectively. The difference in percentile between pregnant and non-pregnant patients were statistically significant (P <.000).
Our main outcome was evaluation of factors that can influence BDI2 score. When BDI2 score was considered as dependent variable, in a multiple regression analysis, it was positively correlated with BDI1 score (r = 0.61, P < .000) and duration of infertility (r = 0.15, P < .000). Negative correlation was found between BDI2 score and result of therapy (r = - .51, P = .000). Eighty six percent of variation of BDI2 score could be predicted by the above three variables. There was no correlation between BDI2 score and age, education, number of previous treatment, and type of infertility.
The mean score of BDI2 was evaluated in relation to cause of infertility. The mean score in male factor was less than other groups. The difference between groups was statistically significant (Table 3).
Table 3 Mean score of BDI1 and BDI2 in relation to cause of infertility
Cause of infertility Mean of BDI1 Mean of BDI2
Male 11.2 ± 8.9 14.6 ± 11.3 P < .000* Z = -4.168
Female 15.8 ± 11 21.1 ± 13.2 P < .000* Z = -4.745
Combined 16.7 ± 9.2 21.9 ± 14.3 P = .006* Z = -2.735
Unknown 15.2 ± 9.5 19.9 ± 10.5 P = .02* Z = -2.303
P = .006** P = .002**
Total 14.3 ± 10.2 18.9 ± 12.8 P < .000 Z = -7.196
*: difference between variables in row
**: difference between variables in columns
Mean of BDI2 score rose after unsuccessful treatment and dropped after a successful treatment (Table 4).
Table 4 Comparison of mean BDI1 and BDI2 in pregnant and non-pregnant subjects
pregnant Non-pregnant P
BDI1 (mean ± SD) 13.6 ± 11.3 14.5 ± 9.8 .28 (Z = -1.079)
BDI2 (mean ± SD) 6.2 ± 5.4 22.9 ± 11.8 <.000 (Z = -9.180)
P <.000 (Z = -5.845) <.000 (Z = -11.481)
We observed the factors that affect BDI2 score in pregnant and non-pregnant groups, separately. In pregnant subjects, BDI2 score was positively correlated with BDI1 score (r = 0.82, P < .000). In non-pregnant patients, BDI2 score was positively correlated with BDI1 score (r = 0.8, P < .000), and duration of infertility (r = 0.17,P = .001).
We studied BDI1 score, as well. In a multiple regression analysis, BDI1 score was negatively correlated with education (r = -0.26, P < 0.000). There was no association between BDI1 score and age, duration of infertility, previous fertility, and number of previous cycles of treatment. Only 26% of variation of BDI1 could be predicted by the factor of education.
In subgroups of infertility cause, the mean score of BDI1 in male factor was less than other groups. The difference between the groups was statistically significant (Table 3).
Discussion
The purpose of this study was to describe the subgroups of infertile women at risk of depression after treatment of infertility. This study can be valuable because it is using a self-reported inventory that differs in both cost and time from psychiatric structured interview. Nevertheless the shortcomings of this inventory, it has been widely used in research. Sensitivity and specificity of Beck Depression Inventory is not high but is reasonable. Beck et al suggested that a score greater than 9 points to depression symptomatology [16]. BDI score were also categorized in subgroups. The score of 9 and less shows normal range, a score of 10–15 indicates at least mild to moderate depressive symptoms, and a score of 16 and above indicates clinical depression [21]. We chose the second version since it screens subgroups of depression more precisely.
In this study, the prevalence of depressive symptomatology as assessed by BDI1 score ≥ 16 was 39%, while the prevalence of moderate to severe depression(BDI ≥ 32) In an interesting study, the questionnaires were sent through internet to estimate degree of some psychological characteristics such as depression. Based on this study, authors found out that more than one quarter of patients could be considered moderately or severely depressed [22]. In screening depression in pregnancy, researchers chose a score greater than 9 and 43% of their population scored above this cutoff. As they designated BDI score greater than 15 as abnormal, nevertheless, the score exceeded the cutoff value in 19% of patients. In that study, a cutoff value greater than 15 yields a sensitivity of 0.83, a specificity of 0.89, a positive predictive value of 0.50, and a negative predictive value of 0.98 [21]. One of the best ways to determine the prevalence of a disease or symptom in relation to a risk factor is to compare a case group with a well-chosen control group. Domar et al showed that the prevalence of depression was 25.8% in infertile women compared with 13.2% in women who were waiting for a routine gynecologic examination [8]. These percentiles were reported to be 36.7% compared to 18.4% in another study [23]. Therefore, it is important that self-report questionnaires used for screening a disease should have a cutoff point reaffirmed either by a gold standard test or control group.
The main outcome of this study was determining factors that may influence BDI2. The score after treatment (BDI2) was correlated with the score of BDI before treatment and duration of infertility and with the result of therapy.
Hence, Table 4 shows no statistically significant difference between mean score of BDI1 in the two groups, we assume that the factors affecting BDI1 in the pregnant group and those in the non-pregnant group are the same.
As BDI1 had a strongest affect on BDI2, a regression analysis considering BDI1 as a dependent variable was performed. It was found out that BDI1 score decreases as the level of education increases. In a stepwise regression, we failed to show any other factors to have relation with BDI1 score. There have been studies in which correlation between BDI score and demographic characteristics were evaluated. Demyttenaere et al showed that age, duration of infertility, and numbers of previous IVF attempts are factors affecting BDI score, but there was no data about level of education [24]. On the other hand, Beutel et al reported the correlation between education and depression (Spearsman correlation = -0.15 P < .05) [11]. This inverse relationship between education and BDI1 score was considerable in our study (r = -0.26). This relationship can be explained by cultural views. It seems that high-educated people have objectives other than fertility to focus on.
Data about age and risk of depression is not conclusive. Some studies have reported associations been them [11,24,25], while other studies could not show any relationships between these two [14,26]. We suggested that other variables could act as intermediate variables between age and BDI1. Because of the strength of theses variables, the effect of age was hidden in multivariate analysis.
The second important factor was the result of therapy. Apparently, subjects who are at risk of depression are more prone to develop depression at the time of exposure to life events.
The third factor that had influence on BDI2 was duration of infertility. The association of BDI score after treatment with duration of infertility in subgroup with failed treatment was showed in another study [14]. In our study, BDI2 is associated positively with duration of infertility. However, the strength of this association is low (r = 0.15). It seems that such a low influence cannot play a significant role in practice. The assumption on whether the association between duration of infertility and post-treatment BDI score is a straight association or depends on intermediate variables such as number of treatment failure experiences needs more studies [27].
The perception of woman about the cause of infertility may change her BDI score. Pressure on infertile women with female factor infertility is high. The risk of depressive symptomatology is lower when a woman thinks that the problem is male factor. Combined factor indicates a severe problem, so it is reasonable that BDI score rises by this diagnosis (Table 3). This type of cultural view has been showed in countries with family-based societies [28].
We emphasize that a number of meaningful relationships were introduced in other studies which were not mentioned here. Thus, in prospective studies other variables should be included and other more sensitive tools should be used.
The other limitation of this study was using BDI for uneducated subjects that might induce a bias. It is clear that designing studies using interviews instead of questionnaires will be more valuable.
Conclusion
Our findings suggest a plan for screening women who are prone to depression after infertility treatment. It is obvious that there is no significant difference among them before treatment (Table 2). Answering the following two simple questions can conduct the physician to screen these women.
1. Is my patient at risk of depression (due to BDI1 score) at the beginning of the treatment?
2. What will be the result of therapy?
Therefore, the physician can predict subjects who may need psychological supportive programs at the beginning of treatment cycles.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
AK, AA and MA drafted the manuscript. AK performed the statistical analysis. AK, AAA and FR participated in the study design and coordination. All authors read and approved the final manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
We gratefully acknowledge the participation of Dr. Ehsan Akbari Hamed and the infertility ward crew of Shariati Hospital: Nahid Abbassi, Roghaeh Amrollahi, and Mehrnoosh Amini. This study was supported by Vali-e-Asr Reproductive Health Research Center, Tehran University of Medical Sciences.
==== Refs
Yonkers KA Chantilis SJ Recognition of depression in obstetric/gynecology practices Am J Obstet Gynecol 1995 173 632 8 7645645 10.1016/0002-9378(95)90295-3
Desai HD Jann MW Major depression in women: a review of the literature J Am Pharm Assoc (Wash) 2000 40 525 37 10932463
Kessler RC Epidemiology of women and depression J Affect Disord 2003 74 5 13 12646294 10.1016/S0165-0327(02)00426-3
Lucht M Schaub RT Meyer C Hapke U Rumpf HJ Bartels T von-Houwald J Barnow S Freyberger HJ Dilling H John U Gender differences in unipolar depression: a general population survey of adults between age 18 to 64 of German nationality J Affect Disord 2003 77 203 11 14612220 10.1016/S0165-0327(02)00121-0
Paykel ES Stress and affective disorders in humans Semin Clin Neuropsychiatry 2001 6 4 11 11172528 10.1053/scnp.2001.19411
Domar AD Zuttermeister PC Friedman R The psychological impact of infertility: a comparison with patients with other medical conditions J Psychosom Obstet Gynaecol 1993 45 52 8142988
Wischmann T Stammer H Scherg H Gerhard I Verres R Psychosocial characteristics of infertile couples: a study by the 'Heidelberg Fertility Consultation Service' Hum Reprod 2001 16 1753 61 11473978 10.1093/humrep/16.8.1753
Domar AD Broome A Zuttermeister PC Seibel M Friedman R The prevalence and predictability of depression in infertile women Fertil Steril 1992 58 1158 63 1459266
Bloch M Schmidt PJ Danaceau M Murphy J Nieman L Rubinow DR Effects of gonadal steroids in women with a history of postpartum depression Am J Psychiatry 2000 157 924 30 10831472 10.1176/appi.ajp.157.6.924
Kuehner C Gender differences in the short-term course of unipolar depression in a follow-up sample of depressed inpatients J Affect Disord 1999 56 127 39 10701470 10.1016/S0165-0327(99)00035-X
Beutel M Kupfer J Kirchmeyer P Kehde S Köhn FM Schroeder-Printzen I Gips H Herrero HJ Weidner W Treatment-related stresses and depression in couples undergoing assisted reproductive treatment by IVF or ICSI Andrologia 1999 31 27 35 9949886 10.1046/j.1439-0272.1999.00231.x
Kee BS Jung BJ Lee SH A study on psychological strain in IVF patients J Assist Reprod Genet 2000 17 445 8 11062855 10.1023/A:1009417302758
Chiba H Mori E Morioka Y Kashiwakura M Nadaoka T Saito H Hiroi M Stress of female infertility: relations to length of treatment Gynecol Obstet Invest 1997 43 171 7 9127130
Lok IH Lee DT Cheung LP Chung WS Lo WK Haines CJ Psychiatric morbidity amongst infertile Chinese women undergoing treatment with assisted reproductive technology and the impact of treatment failure Gynecol Obstet Invest 2002 53 195 9 12186982 10.1159/000064560
Beck AT Ward CH Mendelson M Mock J Erbaugh J An inventory for measuring depression Arch Gen Psychiatry 1961 4 561 71 13688369
Beck A Steer R Garbin M Psychometric properties of the beck Depression Inventory: Twenty-five years of evaluation Clin Psychol Rev 1988 8 122 32 10.1016/0272-7358(88)90053-0
Tekbas OF Ceylan S Hamzaoglu O Hasde M An investigation of the prevalence of depressive symptoms in newly recruited young adult men in Turkey Psychiatry Res 2003 119 155 62 12860369 10.1016/S0165-1781(03)00125-2
Coelho R Martins A Barros H Clinical profiles relating gender and depressive symptoms among adolescents ascertained by the Beck Depression Inventory II Eur Psychiatry 2002 17 222 6 12231268 10.1016/S0924-9338(02)00663-6
Kojima M Furukawa TA Takahashi H Kawai M Nagaya T Tokudome S Cross-cultural validation of the Beck Depression Inventory-II in Japan Psychiatry Res 2002 110 291 9 12127479 10.1016/S0165-1781(02)00106-3
Akiskal HG Sadock BJ, Sadock VA Mood disorders: Clinical Features Comprehensive Textbook in Psychiatry 2000 7 Philadelphia: Lippincott Williams and Wilkins 369 70
Holcomb WL JrStone LS Lustman PJ Gavard JA Mostello DJ Screening for depression in pregnancy: Characteristics of the Beck Depression Inventory Obstet Gynecol 1996 88 1021 5 8942846 10.1016/S0029-7844(96)00329-8
Epstein YM Rosenberg HS Grant TV Hemenway BAN Use of the internet as the only outlet for talking about infertility Fertil Steril 2002 78 507 14 12215325 10.1016/S0015-0282(02)03270-3
Thiering P Beaurepaire J Jones M Saunders D Tennant C Mood state as a predictor of treatment outcome after in vitro fertilization/embryo transfer technology (IVF/ET) J Psychosom Res 1993 37 481 91 8350290 10.1016/0022-3999(93)90004-Y
Demyttenaere K Bonte L Gheldof M Vervaeke M Meuleman C Vanderschuerem D D'Hooghe T Coping style and depression level in in vitro fertilization Fertil Steril 1998 69 1026 33 9627288 10.1016/S0015-0282(98)00089-2
Guz H Ozkan A Sarisoy G Yanik F Yanik A Psychiatric symptoms in Turkish infertile women J Psychosom Obstet Gynaecol 2003 24 267 71 14702887
Matsubayashi H Hosaka T Izumi S Suzuki T Makino T Emotional distress of infertile women in Japan Hum Reprod 2001 16 966 9 11331646 10.1093/humrep/16.5.966
Boivin J Takefman JE Tulandi T Brender W Reactions to infertility based on extent of treatment failure Fertil Steril 1995 63 801 7 7890066
Dyer SJ Abrahams N Hoffman M van der Spuy ZM Men leave me as I cannot have children: women's experiences with involuntary childlessness Hum Reprod 2002 17 1663 8 12042295 10.1093/humrep/17.6.1663
| 15910692 | PMC1173120 | CC BY | 2021-01-04 16:33:02 | no | BMC Psychiatry. 2005 May 24; 5:25 | utf-8 | BMC Psychiatry | 2,005 | 10.1186/1471-244X-5-25 | oa_comm |
==== Front
BMC SurgBMC Surgery1471-2482BioMed Central London 1471-2482-5-151597813410.1186/1471-2482-5-15Research ArticleThe management of large perforations of duodenal ulcers Gupta Sanjay [email protected] Robin [email protected] Rajeev [email protected] Ashok [email protected] Department of Surgery, Government Medical College and Hospital, Sector 32, Chandigarh 160 030 India2005 25 6 2005 5 15 15 8 11 2004 25 6 2005 Copyright © 2005 Gupta et al; licensee BioMed Central Ltd.2005Gupta et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Duodenal ulcer perforations are a common surgical emergency, but literature is silent on the exact definition, incidence, management and complications of large perforations of duodenal ulcers.
Methods
The case files of 162 patients who underwent emergency laparotomy for duodenal ulcer perforations over a period of three years (2001 – 2003) were retrospectively reviewed and sorted into groups based on the size of the perforations – one group was defined as 'small 'perforations (less than 1 cm in diameter), another 'large' (when the perforation was more than 1 cm but less than 3 cms), and the third, 'giant'(when the perforation exceeded 3 cm). These groups of patients were then compared with each other in regard to the patient particulars, duration of symptoms, surgery performed and the outcome.
Results
A total of 40 patients were identified to have duodenal ulcer perforations more than 1 cm in size, thus accounting for nearly 25 % of all duodenal ulcer perforations operated during this period. These patients had a significantly higher incidence of leak, morbidity and mortality when compared to those with smaller perforations.
Conclusion
There are three distinct types of perforations of duodenal ulcers that are encountered in clinical practice. The first, are the 'small' perforations that are easy to manage and have low morbidity and mortality. The second are the 'large' perforations, that are also not uncommon, and omental patch closure gives the best results even in this subset of patients. The word 'giant' should be reserved for perforations that exceed 3 cms in diameter, and these are extremely uncommon.
==== Body
Background
Duodenal ulcer perforations are a common cause of peritonitis. The classic, pedicled omental patch that is performed for the 'plugging' of these perforations was first described by Cellan-Jones in 1929 [1], although it is commonly, and wrongly attributed to Graham, who described the use of a free graft of the omentum to repair the perforation in 1937 [2]. In this, a strand of omentum is drawn over the perforation and held in place by full thickness sutures placed on either side of the perforation, and this procedure has become the "gold standard" for the treatment of such perforations. However, occasionally, large perforations of the duodenum may be encountered in which there exists the threat of post-operative leakage following closure by this simple method [3,4]. Here, other surgical options such as partial gastrectomy, jejunal serosal patch, jejunal pedicled graft, free omental plug, suturing of the omentum to the nasogastric tube, proximal gastrojejunostomy, or, even, gastric disconnection may be deemed necessary for adequate closure [3-8].
Very little data is available in literature regarding the definition, incidence, and the management of large perforations of duodenal ulcers. This paper represents our experience with the management of this subset of duodenal ulcer perforations over a period of three years from January 2001 to December 2003.
Methods
A total of 162 patients underwent emergency surgery for duodenal ulcer perforations at our hospital over a period of three years (January 2001 to December 2003). The case files of all these patients were analyzed, and the patients were sorted into four groups according to the size of the perforation noted intra-operatively – Group 1 (less than1 cm perforation); Group 2 (1 cm to 2 cm); Group 3 (2 cms to 3 cms); and, Group 4 (more than 3 cms perforation). No cases of anterior and posterior ulcers, or multiple perforations were encountered while reviewing the operative notes. The technique of omentopexy was essentially the same in all the cases – a total of three sutures were placed onto the normal, healthy duodenum on either side of the perforation, a strand of omentum was placed directly onto the perforation, and the sutures were knotted above this. No attempt was made to close the perforation prior to placing the omentum as a graft.
The case files of all the patients were retrospectively analyzed for patient particulars, intra-operative findings, surgery performed, post-operative stay, morbidity and mortality. The groups were then compared with each other in terms of age, leak rates, hospital stay, morbidity, mortality and the surgery performed. Statistical analysis was done using the chi-square and the t- test by an independent comparison of each group singly against another by a statistician who was blinded to the study. A p value of < 0.05 was taken as significant.
It was found that the perforations between 1 cm and 3 cm in size (Groups 2 and 3 as above) behaved in a similar manner statistically, and therefore, the patients these two groups were combined to give a single group. We finally ended up with 3 groups of perforations – Group A (less than1 cm perforations), Group B (perforations between 1 cm and 3 cms in size), and Group C (more than 3 cms perforation).
Results
Of the total of 162 patients that underwent emergency surgery for duodenal ulcer perforations at our hospital over three years, there were 148 males (91.36 %) and 14 female (8.64 %) patients, giving a male to female ratio of 10.57 : 1. The average age of the patients was 40.63 years (range 15 – 82 years), with an almost equal age of occurrence for males (40.52 years) and females (41.78 years).
All the patients were divided into three groups as explained above. Group A was deemed to be the small perforation group, Group B was called 'large' perforations, and Group C, 'giant' perforations. The majority of patients came under the 'small' perforation group, but there were 38 patients (23.46 %) with large perforations as per our definition. These patients had a higher age of presentation (47.18 years) than the patients with smaller perforations (39.46 years). Giant perforations, or perforations greater than 3 cms in size were seen only 2 cases, accounting for a small percentage (1.23 %) of all cases seen.
When the small perforation group was compared with the larger perforations, it was found that the large perforations had a higher morbidity (x2 = 37.4503, p < 0.05), leak rate (x2 = 4.9117, p < 0.05), and hospital stay (t value 5.117, p < 0.001) and that this difference was statistically significant. This therefore, lends support to the popular opinion that large perforations have a worse outcome.
Overall, the commonest surgery performed was the Cellan-Jones omental patching – in 119 of the 122 cases in Group A; 30 of the 38 patients in Group B. When the results of omental patch were compared between the two groups, no significant difference was found in the leak rates (x2 = 2.8698; p > 0.5) and mortality (x2 = 1.4732; p > 0.1), thereby implying that this was an equally effective method for the closure of larger perforations also. Jejunal serosal patch using a loop of the jejunum, and antrectomy (4 cases each) were the other surgeries performed in Group B, when closure with the omentum was thought to be unsafe by the operating surgeon. Five (12.5 %) patients of this group had a leak following closure of the perforation; 3 following omental patch and 1 each after performance of jejunal serosal patch and antrectomy, whereas only 3 cases developed leak in Group A (2 after omental patch and 1 after truncal vagotomy and pyloroplasty).
Two cases had 'giant' perforations extending onto the pylorus – in one, resection and Billroth II reconstruction was performed, and in the other, jejunal serosal patch. The patient who underwent resection had presented late, and succumbed to septicaemia on the very first post-operative day. The other remained well and was discharged on the 11th post-operative day.
Overall, the patients with large perforations (Group B) had significantly increased hospital stay, leak rates, and morbidity (Table 1). The hospital stay was almost double for these patients (13.65 days versus 6.93 days). Although the overall morbidity was 48.76 %, it was much higher in the larger perforations (groups B and C). The common morbidity encountered was chest infections (39 cases), but wound infection (12 cases), biliary leak (08 cases), intra-abdominal abscesses (06 cases), burst abdomen (06 cases), renal failure (02 cases), DIC (04 cases), jaundice and upper gastrointestinal bleeding (01 case each) were also recorded. The mortality in this series was 8.64 % (14 cases), and again, it was significantly higher in perforations more than 1 cm in size (x2 = 3.8940; p < 0.05). Table 1 gives the details of all the three groups.
Table 1 Patient data
Group A – 'Small' (Less than 1 cm) Group B – 'Large' (1 cm – 3 cm) Group C – 'Giant' (More than 3 cm)
Number of cases 122 (75.31 %) 38 (23.46 %) 02 (1.23 %)
Average age 39.46 years 47.18 years 37.50 years
Male/Female 109 : 13 37 : 1 2 : 0
Average Duration of Symptoms 2.5 days 3.18 days 3.50 days
Surgery Performed Omental Patch 119 ** Pyloroplasty 03 * Omental Patch 30 *** Jejunal Serosal Patch 04 * Antrectomy 04 * Antrectomy and Billroth II 01 Jejunal Serosal Patch 01
Post-operative Leak 03 (2.46 %) 05 (13.16 %) -
Morbidity 41 37 01
Post-operative Hospital Stay 6.93 days 13.65 days 6.00 days
Mortality 07 (5.74 %) 06 (15.79 %) 01 (50 %)
Each * indicates one post-operative leak
Discussion
Duodenal ulcer perforation is a common surgical emergency in our part of the world. The overall reported mortality rate varies between 1.3 to nearly 20 % [9-11] in different series, and recent studies have shown it to be around 10 % [11]. Factors such as advancing age, concomitant disease, preoperative shock, size of the perforation, delay in presentation and operation, have all been defined by various authors to be risk factors for mortality in such a situation [9-11]. Although the size of a perforation is an important measure in determining the outcome, a review of literature failed to reveal, any accepted definition of either small or giant perforations of duodenal ulcers. Neither could we come across any specific recommendations regarding the management of giant / large perforations, which are said to be "difficult" to manage and have anecdotally been associated with high leak rates and mortality. This is in contrast to the well accepted and documented definition of giant duodenal ulcers (more than 2 cms in size), which may or may not perforate, but are usually considered to be an indication for definitive, elective ulcer surgery [8,12].
Commonly, duodenal ulcer perforations are less than 1 cm in greatest diameter, and as such, are amenable to closure by omentopexy [3]. Our experience does seem to validate this, and this subset of 'small' perforations does seem to have the best outcome. It is the perforations that are larger that have been the cause of much confusion in their definition and management. The size of such 'giant' sized perforations has arbitrarily been defined by various authors as being greater than 0.5 cms [7], 1 cm [3,4], or 2.5 cms [6] in greatest diameter, but we failed to uncover any specific size in available English language literature beyond which to label these perforations as "giant". These perforations are considered particularly hazardous because of the extensive duodenal tissue loss and surrounding tissue inflammation, which are said to preclude simple closure using omental patch, often resulting into post-operative leak or gastric outlet obstruction [3,4]. The tendency to leak may further be aggravated by the high intraluminal pressures, extrusion of the duodenal mucosa through the closure, and, autodigestion by the pancreatic enzymes and bile, thereby further compromising an already sick patient [13].
Our data seems to suggest that based on the size, duodenal perforations can be classified into three main groups (1) small perforations that are less than 1 cm in size, and have the best outcome; (2) large perforations, that have a size between 1 cm and 3 cms; and, (3) giant perforations that exceed 3 cm size. The usage of the word 'giant' for a duodenal perforation should be restricted to such large defects, where omentopexy may be deemed unsafe, and other options may be thought to be necessary.
In the absence of any specific definition and guidelines regarding the management of such large / giant perforations in literature, different authors have recommended varied surgical options from time to time, based on their experience and research. These have included resection of the perforation bearing duodenum and the gastric antrum in the form of a partial gastrectomy, with reconstruction as either a Billroth I or II anastomosis, or the more morbid procedure of gastric disconnection in which vagectomy, antrectomy, gastrostomy, lateral duodenostomy and feeding jejunostomy are performed, with restoration of intestinal continuity electively after 4 weeks of discharge [8]. Others have recommended conversion of the perforation into a pyloroplasty, or, closure of the perforation using a serosal patch or a pedicled graft of the jejunum, or, the use of a free omental plug to patch the defect, and even, suturing of the omentum to the nasogastric tube [3-8]. Proximal gastrojejunostomy and / or vagotomy may be added to these procedures to provide diversion and a definitive acid reducing procedure respectively [8]. However, as can be appreciated, each of these procedures not only prolongs the operating time, but also requires a level of surgical expertise that may not be available in the emergency [6]. In addition, each of these procedures has it own morbidity that may add up significantly to alter the final outcome of the patient, and more importantly, none of them is immune to the risk of leak in the post-operative period, which has been the main concern against performing the omental patch in larger perforations [3,4].
The results of omentopexy in small and large sized perforations in the present series give statistically similar results. The leak rates and mortality of the two groups after omentopexy remain comparable, thereby suggesting that this may be considered as the procedure of choice in all perforations upto a size of 3 cms. The procedure is simple and easy to master, and, avoids the performance of a major resection in a patient who is already compromised. In fact, Sharma et al also reported the success of the omental plug in perforations of duodenal ulcers more than 2.5 cms in size; only, they preferred using a free graft of the omentum rather than a pedicled one [6]. We feel that mobilization of the omentum on its pedicle from the colon, and placement of sutures into the normal duodenum away from the perforation makes the performance of omental patch safe even in the presence of large sized perforations.
In the present series, only 2 cases were defined to be 'giant' according to the size (more than 3 cm) that we have defined – one underwent antrectomy and Billroth II reconstruction, the other, a jejunal serosal patch. The first patient (antrectomy) succumbed to the ongoing septicaemia on the very first post-operative day, but the other patient survived. This is the group of patients with truly giant perforations who need to be analyzed further to determine the best course of action i.e. resectional versus non-resectional surgery. However, the less number of patients in this group did not allow us to reach any definite conclusion regarding their ideal management. Further study is needed to optimize our efforts to this target group.
Conclusion
Duodenal perforations should be classified as small, large or giant according to their size encountered at laparotomy. In the emergency setting, such patients are often seriously ill and it is not advisable to perform major surgical procedures on them. The Cellan-Jones omental patch is simple, can be performed in a relatively short time, and remains dependable even for the closure of large sized perforations (i.e. perforations upto 3 cms in size). The addition of a feeding jejunostomy and placement of a tube drain in the Morrison's space may offer a further sense of ''security'' to the operating surgeon, keeping by open the option of maintaining the nutrition of the patient as well as creating a controlled duodenal fistula in case of a post-operative leak. The word ''giant'' should be reserved only for perforations that exceed 3 cm in diameter.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
SG carried out acquisition, statistical analysis and interpretation of the data and drafting of the initial manuscript
RK conceptualized the paper, and was involved in the interpretation of data, drafting of the manuscript, and revising it critically for the intellectual content
RS carried out drafting of the manuscript, and revised it critically for the intellectual content till the final version was reached
AKA helped in the revisions of the intellectual content and gave final approval of the version to be published.
All authors have read and approved the final manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
==== Refs
Cellan-Jones CJ A rapid method of treatment in perforated duodenal ulcer BMJ 1929 36 1076 7
Graham RR The treatment of perforated duodenal ulcers Surg Gynecol Obstet 1937 64 235 8
Chaudhary A Bose SM Gupta NM Wig JD Khanna SK Giant Perforations of Duodenal Ulcer Ind J Gastroenterol 1991 10 14 5
Karanjia ND Shanahan DJ Knight MJ Omental patching of a large perforated duodenal ulcer: a new method Br J Surg 1993 80 65 8428298
McIlrath DC Larson RH Surgical management of Large Perforations of the Duodenum Surg Clin North Am 1971 51 857 61 4329579
Sharma D Saxena A Rahman H Raina VK Kapoor JP 'Free Omental Plug': A Nostalgic Look at an Old and Dependable Technique for Giant Peptic Perforations Dig Surg 2000 17 216 8 10867452 10.1159/000018837
Jani K Saxena AK Management of Large Sized Duodenal Peptic Perforations by Omental Plugging – A New Technique: A Prospective Randomised Study of 100 patients Ind J Surg 2000 62 134 8
Cranford CA Olson RO Bradley EL III Gastric Disconnection in the Management of Perforated Giant Duodenal Ulcer Am J Surg 1988 155 439 42 3344908
Hermansson M von Holstein CS Zilling T Surgical approach and Prognostic factors after peptic ulcer perforation Eur J Surg 1999 165 566 72 10433141 10.1080/110241599750006479
Boey J Choi KY Alagaratnam TT Poon A Risk Stratification in Perforated Duodenal Ulcers. A Prospective Validation of Predictive Factors Ann Surg 1986 205 22 6 3800459
Rajesh V Sarathchandra S Smile SR Risk factors predicting operative mortality in perforated peptic ulcer disease Tropical Gastroenterol 2003 24 148 50
Nussbaum MS Schusterman MA Management of Giant Duodenal Ulcer Am J Surg 1985 149 357 61 3976991
Walley BD Goco I Duodenal Patch Grafting Am J Surg 1980 140 706 8 7435834 10.1016/0002-9610(80)90064-1
| 15978134 | PMC1173121 | CC BY | 2021-01-04 16:28:04 | no | BMC Surg. 2005 Jun 25; 5:15 | utf-8 | BMC Surg | 2,005 | 10.1186/1471-2482-5-15 | oa_comm |
==== Front
BMC UrolBMC Urology1471-2490BioMed Central London 1471-2490-5-91590721510.1186/1471-2490-5-9Research ArticleNew chemolysis for urological calcium phosphate calculi – a study in vitro Xiang-bo Zhang [email protected] Wang [email protected] Duan [email protected] Lu [email protected] Ma [email protected] School of Life Sciences, LanZhou University, LanZhou, 730030, China2 Institute of Urology, the 2nd Hospital of LanZhou University, Cuiyingmen 80, LanZhou, 730030, China2005 22 5 2005 5 9 9 6 12 2004 22 5 2005 Copyright © 2005 Xiang-bo et al; licensee BioMed Central Ltd.2005Xiang-bo et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Advances in techniques have left very few indications for open surgical extraction of urinary stones currently. These advances notwithstanding, the search continues for medical approaches to urinary stone management. In this study, we perform an in vitro study analyzing the efficiency and prospect of two new complex solutions in urological calcium phosphate calculi dissolution.
Methods
Eighteen stones composed mainly of calcium phosphates were taken from patients who underwent kidney stone surgery. These stones were large enough (weight range 0.514–0.928 g) to be fragmented and matched equally into six groups. Chemolysis of phosphate stones was done with six different solvents and was repeated 3 times with 6 stones for each solution. At 24, 48 and 72 h, reduction in weight, percentage weight change, and dissolution rate; the dissolution rates at pH 5.0, 7.0 and 8.5 for each solution, using different cations (Na+, K+ or Ca2+), according to different dilutions (1:1, 1:2, 1:3, 1:4) of S1 and S2 were simultaneously determined.
Results
Calcium phosphate calculi were poorly dissolved by Phys and Art, and they had a low dissolution rate in pH 8.5 EDTA. The most effective solutions were S1, S2 and R, with 72 h mean dissolution rates: 5.75 ± 0.44 mg/hr (S1), 5.2 ± 0.63 mg/hr (S2), 4.55 ± 0.46 mg/hr (R) ( ± s, p < 0.01 R, S1 and S2 vs Phys, Art and EDTA; p < 0.05, S1 vs R, LSD-test). The mean percentage weight loss at 72 h was: 52.1 ± 15.75 % (S1), 44.4 ± 7.37 % (S2) and 40.5 ± 3.67 % (R) ( ± s, p < 0.01 R, S1 and S2 vs Phys, Art and EDTA, LSD-test). Diluted twice, S1 and S2 had even better effectiveness than their initial solution. The additive of Na+, K+ or Ca2+ greatly reduced the dissolution rates of S1, S2.
Conclusion
Our data indicate that test solutions S1 and S2 are effective solvents in the chemolysis of calcium phosphate stones. At twice dilutions, these solutions are even more useful in the treatment of stone disease.
==== Body
Background
The most important phosphate-containing calculi involved in urinary stone disease are carbonate apatite, brushite, and struvite. Overall, phosphate stones account for 12–20% of all urinary stones and rank first in the list of recurrent calculi [1]. The most definitive therapy involving any type of phosphate stone is calculus removal by shock-wave lithotripsy, percutaneous stone removal, or open surgery (especially in children). However, while technologies have successfully treated patients with phosphate calculi, they are associated with injury to the urinary tissue and retained stone fragments have resulted in recurrences.
Stone dissolution through chemolysis remains an option for urologists even in the advent of more sophisticated modalities in the treatment of urolithiasis. Chemolysis via acidification of the urine and antibiotic therapy (especially for infection stones) are important adjuvant modalities for phosphate calculi therapy. Hitherto, a many solutions have been tested in the quest for more effective dissolution agents. The most effective solution among them is Renacidin (R), which is a buffer consisting mainly of citrate and gluconate [2-4]. These solutions are delivered directly into the kidney by ureteric catheter or percutaneous nephrostomy, and are successful in the dissolution of struvite. But the injury to urothelium restrains their wide use. So, solutions with more dissolution efficiency and less side effects are needed urgently and may be used widely. Our in vitro study was designed to evaluate the effectiveness of two new complex solutions (using D-gluconic acid-lactone, D-gluconic-acid and other ingredients which makes them different from R) in the chemolysis of calcium phosphate stones.
Material and methods
Stones specimen preparation
Eighteen stones composed mainly of calcium phosphate were taken from 18 patients who underwent kidney stone surgery. These stones were large enough (weight range from 0.514–0.928 g) to be fragmented and matched equally into six groups. Each stone was analyzed using the Merckognost at Urinary Stone analysis Kit. The chemical composition of these stones was varied but there was a predominance of calcium phosphate in almost all the stones and calcium oxalate was less than 10% (Table 1, Table 2).
Table 1 Chemical analysis of 18 stones for stone dissolution. There was a predominance of calcium phosphate in almost all the stones and calcium oxalate was less than 10%.
Stone% Ca Oxalate NH4 PO4 Mg Uric Acid Tri-calcium phosphate Calcium oxalate Struvite
1. 45 2 2 57 7
2. 60 45 10 9
3. 60 10 4 55 10
4. 45 15 45 5 4
5. 35 5 35
6. 80 11 3 65 6
7. 50 10 60 6
8. 40 2 7 25 5 7
9. 5 5 45 15 20 8
10. 15 20 15 40 6
11. 45 5 3 45 10
12. 35 20 2 35
13. 50 20 5 25
14. 40 10 35 15
15. 45 15 35 9
16. 40 15 0.5 35 5
17. 75 5 15
18. 15 5 45 10 15
Table 2 Mean chemical composition of 18 stones, showing that there was a predominance of calcium phosphate in almost all the stones and calcium oxalate was less than 10%.
Composition ± s (%)
Ca++ 42.5 ± 20.7
Oxalate 9.6 ± 6.2
NH4 1.5 ± 2.1
PO4 40.1 ± 13.9
Mg 1.7 ± 4.9
Uric acid 3.3 ± 4.9
Cystine 0.0 ± 0.0
Ca++oxalate 3.4 ± 3.7
Preparation of solvent
Six different solvents were used for chemolysis of phosphate stones. The molecular formula and the molecular weights of some drugs used in these solvents are provided in Table 3.
Table 3 Molecular formulae and molecular weights of chemical drugs used in our experiment
Experimental drug Molecular formula Molecular weight
Citric acid C6H6O7·H2O 210.14
Sodium citrate Na3 C6H6O7·2H2O 294.11
D-Gluconic Acid Lactone C6H10O6 178.1
Magnesium citrate Mg3(C6H5O7)2·14H2O 703.4
Magnesium Carbonate (MgCO3)4·Mg(OH)2·5H2O 485.8
Disodium EDTA C10H14O8N2Na2·2H2O 372.24
Potassium citrate, tribasic K3C6H5O7·H2O 324.34
Potassium phosphate, monobasic KH2PO4 136.09
1. Physiologic sodium chloride solution (Phys).
2. Artificial urine (Art, pH5.7, according to Griffith et al [5]) consisting of urea (25 g/L), sodium chloride (4.6 g/L), potassium-dihydrogen-phosphate (2.8 g/L), sodium sulfate (2.3 g/L), potassium chloride (1.6 g/L), ammonium chloride (1.0 g/L), calcium chloride dehydrate (0.1 g/L), sodium oxalate (0.05 g/L), and sodium citrate (0.01 g/L), dissolved in 1000 ml. distilled water.
3. 0.03 M disodium ethylenediaminetetraacetic acid buffered to pH 8.5 with triethanolamine (EDTA, pH 8.5)
4. 10% Renacidin (R, pH 3.9), consisting of citric acid (28.2 g), gluconic acid (5.0 g), calcium carbonate (1.0 g), magnesium bicarbonate (14.5 g), citrate magnesium (2.5 g), dissolved in 1000 ml. distilled water.
5. Test solution 2 (S2, pH 4.0), prepared using citric acid (18.0 g), citrate magnesium (1.0 g), calcium carbonate (0.5 g), magnesium carbonate (7.5 g), D-gluconic acid-lactone (3.0 g), dissolved in 100 ml. distilled water. The solution was kept at 37? for 3 days, then diluted with 140 ml. distilled water. The concentrations of these ingredients are shown in Table 4.
Table 4 Concentrations of chemical drugs contained in S1 and S2
Chemical drug Concentration (mmol/L)
Citric acid 357.1
Magnesium citrate 5.9
Magnesium Carbonate 64.3
D-Gluconic Acid Lactone 70.2
Calcium carbonate 20.8
D-Gluconic Acid 63.8
Sodium citrate 302.7
Potassium citrate, tribasic 302.7
Calcium chloride, anhydrous 454.5
Calcium carbonate is difficult to be dissolved in water, but in acidic solutions of S1 or S2, it can be dissolved thoroughly. So we give the concentration of Calcium as above. In diluted solutions these cations were diluted correspondingly, such that their pH did not change.
6. Test solution 1 (S1, pH 3.9), prepared using citric acid (18.0 g), citrate magnesium (1.0 g), calcium carbonate (0.5 g), magnesium carbonate (7.5 g), D-gluconic-acid (3.0 g), dissolved in 100 ml. distilled water, and processed as described for S2. The concentrations of these ingredients are shown in Table 4).
We also altered the pH of these solutions to 4, 5, 7, and 8.5 to test their effectiveness and added different cations (Na+, by adding 302.7 mmol/L citrate sodium 10 ml. into 100 ml. of the initial solution; K+, by adding 302.7 mmol/L citrate potassium 10 ml. into 100 ml. of the initial solution; Ca2+, by adding 454.5 mmol/L calcium chloride anhydrous 10 ml. into 100 ml. of the initial solution). S1 and S2 were formulated according to different dilutions (1:1, 1:2, 1:3, 1:4). The pH of these changed solutions had no detectable variation. After stones were immersed in these solvents for 24, 48 and 72 h, reduction in weight, percentage weight loss, and dissolution rate were determined. Results were analyzed using the Multiple Comparisons Test with the alpha set at 0.05. Stones remaining after the dissolution period were weighed (gm), and final weights were applied to the following formula:
The formula used to determine the dissolution rate was:
Chemolysis
Every stone was placed in a vessel containing solvents, which were held at a constant temperature of 37? using a thermostat. Solvents were exchanged 2 times per day at 6 ml/100 mg per stone each time. The pH values were constantly controlled by a pH meter (Mettler Toledo 320-S, sensitivity 0.01). The weight of the calculus was measured continuously by Electronic Semi-micro-, Analytical and Precision Balances (Sartorius BP211D-OCE, sensitivity 0.01 mg) and documented online with a computer system (PC windows 486, Software Wedge for window, version 1.1). The analysis represents six stones for each experiment, repeated three independent times.
Results
Urological calcium phosphate calculi were poorly dissolved by Phys and Art, and they had a low dissolution rate in EDTA at pH 8.5. The most effective solutions were R, S1 and S2 with 24 h mean dissolution rates: 5.05 ± 0.15 mg/hr (S1), 4.52 ± 0.64 mg/hr (S2), 4.53 ± 0.46 mg/hr (R); 72 h mean dissolution rates: 5.75 ± 0.44 mg/hr (S1), 5.2 ± 0.63 mg/hr (S2) and 4.55 ± 0.46 mg/hr (R) ( ± s, P < 0.01, R, S1 and S2 vs Phys, Art and EDTA; P < 0.05, S1 vs R, LSD-test). The mean percentage weight loss at 72 h was: 40.5 ± 3.67 % (R), 52.1 ± 15.75 % (S1) and 44.4 ± 7.37 % (S2) ( ± s, p < 0.01 R, S1 and S2 vs Phys, Art and EDTA, LSD-test). Figure 1 shows the average dissolution rates of the 6 different solutions at the end of 72 h.
Figure 1 Dissolution rates of phosphate calculi in vitro at 24 and 72 h using different solutions. Phys = physiologic sodium chloride solution, pH 7.0. Art = artificial urine, pH 5.7. EDTA = 0.03 M disodium EDTA+TEA, pH 8.5. R = renacidin, pH 4.0. S1 = test solution 1, pH 4.0. S2 = test solution 2, pH 3.9. aP < 0.01 vs Phys and Art. bP > 0.05 vs EDTA, Phys and Art. cP < 0.05 vs R· ± s·n = 18 for each group. For statistics, see results section.
Table 5 Shows mean weight loss and mean percentage weight loss of stones dissolved by the 6 solutions at the end of 24 and 72 h. ( ± s, aP < 0.01 Phys, Art and EDTA vs R, S1 and S2; bP < 0.05 EDTA vs S1, S2 and R.cP < 0.05 R vs S1).
Table 5 Mean weight and percentage weight decrease after 24 and 72 h between groups dissolved with 6 different solutions. Phys = physiologic sodium chloride solution, pH 7.0. Art = artificial urine, pH 5.7. EDTA = 0.03 M disodium EDTA+TEA, pH 8.5. R = renacidin, pH 4.0. S1 = citrate complex 1, pH 4.0. S2 = citrate complex 2, pH 3.9. ± s, aP < 0.01 vs R, S1 and S2.bP < 0.05 vs S1, S2.cP < 0.05 vs S1. n = 18 for each group. For statistics, see results section.
Groups Weight loss (mg) Percentage weight loss (%)
24 h 72 h 24 h 72 h
Phys 3.52 ± 0.73a 18.15 ± 13.15a 0.00 ± 0.00a 1.33 ± 1.53a
Art 2.48 ± 0.37a 7.44 ± 1.9a 0.00 ± 0.00a 0.00 ± 0.00a
EDTA 43.78 ± 6.23ab 153.6 ± 20.84ab 4.67 ± 2.08ab 19.00 ± 5.19ab
R 114.4 ± 8.92c 346.14 ± 26.56c 13 ± 1.35c 40.5 ± 3.67c
S2 127 ± 23.09 408.11 ± 62.94 13.5 ± 2.76 44.4 ± 7.37
S1 138.5 ± 31.09 439.5 ± 102.00 5.77 ± 1.29 52.1 ± 15.75
The dissolution rates were pH dependent. Even Phys and Art were effective to some extent at pH 4. The addition of 1 mol/L sodium hydroxide 10 ml into S1 or S2 100 ml, though not enough to lead to a detectable pH rise, would make the solutions cloudy and greatly reduce their effectiveness. At pH 5.0 they were nearly ineffective, as also observed at pH 7.0, 8.5. However, the dissolution rate of EDTA increased at an elevated pH value. At pH 8.5, EDTA approached a maximum dissolution rate with 72 h mean 1.56 ± 0.05 mg/hr (Figure 2).
Figure 2 Effectiveness of six solvents at different pH (mg/hr). Phys = physiologic sodium chloride solution, Art = artificial urine, EDTA = 0.03 M disodium EDTA+TEA, R = renacidin, S1 = test solution 1, S2 = test solution 2.
The addition of Na+, K+ or Ca2+ (302.7 mmol/L Sodium citrate 10 ml, 302.7 mmol /L Potassium citrate 10 ml or 454.5 mmol/L Calcium chloride dihydrate 10 ml into initial solution 100 ml, respectively) caused no significant change in dissolution rate.
Diluted solutions demonstrated an interesting result. Diluted twice, S1 and S2 were more effective than their initial solutions with 72 h mean dissolution rates: 6.04 ± 1.36 mg/hr (S1), 5.60 ± 1.23 mg/hr (S2) ( ± s, P < 0.05, S1 and S2 vs R). The effectiveness of three times diluted S1 or S2 was the same as the initial solution. When diluted further, the effectiveness was reduced gradually until nearly 0 after solutions were diluted five times (Figure 3).
Figure 3 Concentration and effective of S1 and S2
Discussion
Chemolysis is useful for eliminating cystine stones as well as for cases in which lithotripsy or endourology is considered to be difficult or risky. It proved to be a useful method for reducing staghorn stones before performing lithotripsy [6]. The type of chemolytic solution is dependent upon the composition of the stone and must be regarded as an effective adjuvant treatment [7]. Calcium phosphate can be dissolved with Suby or R, but the treatment is often tedious and time consuming. Calcium oxalate, the major urinary stone component, cannot be dissolved by these solutions. EDTA and other strong calcium chelators cannot be used because of their local toxicity. Certain enzymes can digest the organic matrix of the stone [8]. The first attempts to dissolve calcium stones were done by Hellstrom and Albright in 1930. They used citric acid for phosphate calculi, but this proved irritating to tissues. Suby and Albright modified the solution by adding magnesium oxide and sodium carbonate (Suby's G solution) [9,10] to reduce injury to the rabbit bladder mucosa even though adding this cation reduced the speed of dissolution of struvite Mg (NH4) PO4. A contradictory conclusion was been made by a Dutch study [11] that magnesium in R promotes stone dissolution by cation exchange with calcium in apatite [12].
Our S1 and S2 solutions were similar to R although actual formulas were different. First, we added D-gluconic acid-lactone or D-gluconic-acid as new chelators which bind with calcium well by their special trait. Second, we used new ingredients and ingredients at different weights. The higher density of our solutions than R may be one of the factors which enhanced stone dissolution rates, but it may prevented further dissolution. When diluted twice, the solutions may have gained more space to accommodate cations than the initial solutions and achieve better effectiveness (P < 0.05, S1 and S2 vs R). The further diluted solutions had a lower concentration suggesting that less ingredient took part in the reaction thus accounting for a lower dissolution rate. So, we think twice diluted S1 and S2 may be more useful than their initial solutions.
The dissolution of the majority of the stones in this study can be attributed on the basis of their reaction equation:
3Ca+2 + 2 Citrate→CaCitrate→Ca2+ + CaCitrate
The citrate in the solution binds with the calcium component of the stone producing calcium citrate, thus preventing crystallization. The dissolution process may be brought about by the combination of the above reaction.
As the solubility of calcium phosphate is very pH dependent, the acidification of the urine by the incorporation of citric acid produce a pH between 3.0–4.0, the ideal pH for dissolution as described by Albright et al [9,10]. When the pH is elevated, the citrate will react with cations thus losing its effectiveness. On the other hand, excessive alkalization may lead to the formation of calcium phosphate calculi. Added minor quantities of cations (Na+, K+ or Ca2+) in S1 and S2 apparently causes no significant change to their dissolution rate.
Conclusion
The study has shown that solutions S1 and S2 can dissolve calcium phosphate stones effectively in vitro at a precise dilution of their chemical components. Based on these findings, it is suggested that S1 and S2 may become useful complements to modern techniques of stone fragmentation such as extracorporeal shock wave lithotripsy and percutaneous surgery. Their roles may be suited for the treatment of infectious stones with a CaOx content of less than 10%. However, their safety profiles should be further investigated in order to support their use in subsequent human trials.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
Xiang-bo Zhang participated in the design of the study, in the sequence alignment, carried out the experiment, performed the statistical analysis and drafted the manuscript. Zhi-ping Wang conceived of the study, and participated in its design and coordination and helped to draft the manuscript. All authors read and approved the final manuscript. Jian-min Duan, Jian-zhong Lu, Bao-liang Ma, participated in the sequence alignment.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
We are indebted to Zhi-ping Wang, Professor and director of the institute of urinary, the 2nd Hospital of LanZhou University, for his help in conducting the study and for reviewing the manuscript. We thank Jian-min Duan, Jian-zhong Lu, Bao-liang Ma, staff at the institute of urinary, the 2nd Hospital of Lanzhou University, for generously supplying the room for our experiment.
==== Refs
Leusmann DB Niggemann H Roth S von Ahlen H Recurrence rate and severity of urinary calculi Scand J Urol Nephrol Sep 1995 29 279 83
Nemoy NJ Stamey TA Use of hemiacidin in management of infection stones J Urol 1976 116 693 5 1003632
Blaivas JG Pais VM Spellman RM Chemolysis of residual stone fragments after extensive surgery for staghorn calculi Urology Dec 1975 6 680 6 10.1016/0090-4295(75)90794-3
Rodman JS Recker J Israel A Hemiacidrin irrigations to dissolve stone remnants after nephrolithotomy. Problems with solution flow Urology 1981 18 127 130 7269011 10.1016/0090-4295(81)90420-9
Griffith DP Muschel DM Itin C Urease-the primary cause of infection induced urinary stones Invest Urol 1976 13 346 350 815197
Dormia E Dormia G Malagola G Minervini S Experience with instrumental chemolysis for urolithiasis J Urol 2003 170 1105 10 14501702 10.1097/01.ju.0000090870.62281.95
Heimbach D Winter P Hesse A When is the indication of percutaneous chemolysis justified Urol Int 1995 54 157 61 7604459
Oosterlinck W Verbeeck R Chemolysis of calcium containing urinary calculi. A review Act Urol Belg 1994 62 31 7
Suby HI Suby RM Albright F Properties of organic acid solutions which determine their irritability to the bladder mucous membrane and the effect of magnesium ions in overcoming this irritability J Urol 1942 48 549
Suby HI Albright F Dissolution of phosphatic urinary calculi by the retrograde introduction of a citrate solution containing magnesium N Engl J Med 1943 228 81 91
Kroon A Baadenhuijsen H Froeling P Magnesium in citric acid and the dissolution of struvite and hydroxyapatite Urol Res 1984 12 41 42
Dretler SP Pfister RC Newhouse JH Renal stone dissolution via percutaneous nephrostomy N Engl J Med 1979 300 341 3 759894
| 15907215 | PMC1173122 | CC BY | 2021-01-04 16:30:02 | no | BMC Urol. 2005 May 22; 5:9 | utf-8 | BMC Urol | 2,005 | 10.1186/1471-2490-5-9 | oa_comm |
==== Front
Biomed Eng OnlineBioMedical Engineering OnLine1475-925XBioMed Central London 1475-925X-4-321590452110.1186/1475-925X-4-32ResearchThe effect of geometry and abduction angle on the stresses in cemented UHMWPE acetabular cups – finite element simulations and experimental tests Korhonen Rami K [email protected] Arto [email protected] Yrjö T [email protected] Seppo S [email protected] Reijo [email protected] Department of Applied Physics, University of Kuopio, P.O.Box 1627, FIN-70211 Kuopio, Finland2 Department of Medicine, Helsinki University Central Hospital, Biomedicum, P.O.Box 700, FIN-00029 Helsinki, Finland; ORTON Orthopaedic Hospital of the Invalid Foundation, FIN-00280 Helsinki, Finland; COXA Hospital for the Joint Replacement, FIN-33520 Tampere, Finland3 Department of Orthopaedics and Traumatology, University of Helsinki, P.O.Box 22, FIN-00014 Helsinki, Finland2005 17 5 2005 4 32 32 14 12 2004 17 5 2005 Copyright © 2005 Korhonen et al; licensee BioMed Central Ltd.2005Korhonen et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Contact pressure of UHMWPE acetabular cup has been shown to correlate with wear in total hip replacement (THR). The aim of the present study was to test the hypotheses that the cup geometry, abduction angle, thickness and clearance can modify the stresses in cemented polyethylene cups.
Methods
Acetabular cups with different geometries (Link®: IP and Lubinus eccentric) were tested cyclically in a simulator at 45° and 60° abduction angles. Finite element (FE) meshes were generated and two additional designs were reconstructed to test the effects of the cup clearance and thickness. Contact pressures at cup-head and cup-cement interfaces were calculated as a function of loading force at 45°, 60° and 80° abduction angles.
Results
At the cup-head interface, IP experienced lower contact pressures than the Lubinus eccentric at low loading forces. However, at higher loading forces, much higher contact pressures were produced on the surface of IP cup. An increase in the abduction angle increased contact pressure in the IP model, but this did not occur to any major extent with the Lubinus eccentric model. At the cup-cement interface, IP experienced lower contact pressures. Increased clearance between cup and head increased contact pressure both at cup-head and cup-cement interfaces, whereas a decreased thickness of polyethylene layer increased contact pressure only at the cup-cement interface. FE results were consistent with experimental tests and acetabular cup deformations.
Conclusion
FE analyses showed that geometrical design, thickness and abduction angle of the acetabular cup, as well as the clearance between the cup and head do change significantly the mechanical stresses experienced by a cemented UHMWPE acetabular cup. These factors should be taken into account in future development of THR prostheses. FE technique is a useful tool with which to address these issues.
==== Body
Background
Aseptic loosening is the most common cause for long-term failure of total hip replacement (THR). The success rate after revision surgery is much lower than that after the primary operation. Wear, which contributes to aseptic loosening [1-4], has been shown to correlate with the contact pressure of the UHMWPE acetabular cup [5,6]. An increase of the abduction angle of the acetabular cup has been shown to increase contact pressure and wear [7,8]. Different geometrical cup designs, polyethylene thicknesses and clearances between the cup and head have been demonstrated to modulate implant survival [2,7,9-15]. However, the combined effect of these parameters on polyethylene stress is still unclear. For instance, the different geometries of the acetabular cups may modify the contact pressure in different ways depending on the abduction angle. Parameters reducing contact pressure reduce plastic deformation and wear, and thus may diminish the risk for aseptic loosening.
Pre-clinical testing of hip implants prior to marketing is known to be important [16], since failure to perform proper testing may lead to unsatisfactory clinical results. Therefore, the geometries and orientations of acetabular cups should be optimized. Finite element (FE) modeling enables the evaluation of stress distribution throughout the THR prostheses [8,17] and an assessment of geometries and material properties which would be difficult or time-consuming to test experimentally.
In this study, two UHMWPE acetabular cups with different geometries and good long term clinical records, according to Scandinavian hip registers, were studied [18,19]. However, the cups belong to the same hip prosthesis system and their individual survivorships are not described separately in the registers. FE modeling and cyclic testing of hip implants in a simulator were used to test the hypotheses that the geometry, thickness and abduction angle of the cup, as well as the clearance between the femoral head and the cup could affect acetabular cup stress upon loading. Information from this study can be used for the future development of THR implants prior to their surgical installation.
Methods
Laboratory tests
Two UHMWPE acetabular cups* with different designs (Waldemar LINK GmbH & Co., Hamburg, Germany: IP, n = 4 and Lubinus eccentric (with a snap-fit primary locking mechanism), n = 8) were tested experimentally under a cyclic load [20]. Axial loading was used to investigate the plastic deformations occurring in the cups and to minimize wear.
Before the tests, the cups were fixed in stainless steel holders with bone cement (Palacos® R-40 cum Gentamicin, Schering-Plough Europe, Brussels, Belgium). To speed up the experimental tests, two combinations of head, cup and cement were tested at the same time which led overall to six tests (Table 1, Fig. 1). Testings were carried out using a dynamic tester (Instron 8874, Instron Corporation, Canton, MA) at a 5 Hz frequency for 5 million cycles. The load profile was a Paul gait curve with a peak load of 3 kN, and abduction angles of 45° and 60° were used. Diluted bovine serum supplemented with EDTA and antibacterial agents was used as lubricant [21]. The serum was filtered through a 0.2 μm filter and had a total protein content of 25 mg/ml. Temperature (37°C) and pH (7) were regularly recorded.
Table 1 Summary of the parameters obtained from experimental tests and numerical simulations.
Experimental tests Finite element analyses
IP Lubinus eccentric IP1 Lubinus eccentric IP2 Lubinus concentric
Compression (μm) 45° Mean: 115 (n = 1) Mean: 129 (n = 2) 98 132 - -
Range: 125–132
60° Mean: 123 (n = 1) Mean: 140 (n = 2) 107 133 - -
Range: 129–150
Penetration rate (μm/million cycles) 45° Mean: 11.8 (n = 2) Mean: 9.5 (n = 4) - - - -
Range: 11.6–11.9 Range: 8.9–10.2
60° Mean: 14.7 (n = 2) Mean: 11.2 (n = 4) - - - -
Range: 14.2–15.2 Range: 10.0–11.9
Von Mises stress 45° - - Fig. 3 Fig. 3 Fig. 3 Fig. 3
60° - - " " " "
Contact pressure and/or area 45° Fig. 6 Fig. 6 Figs. 4-8 Figs. 4-8 Figs. 4-8 Figs. 4-8
60° - - " " " "
45° and 60° refer to the abduction angle.
Experimental maximum compressions were analyzed from the initial loading cycles for two cup-cement combinations (12 acetabular cups, 6 experimental tests) at the same time (Fig. 1).
Penetration rates of the cups, i.e. plastic deformations, were calculated after 5 million loading cycles.
Figure 1 Hip implant simulator and tested acetabular cups. Two types of acetabular cups (up right, IP and Lubinus eccentric) were tested in a simulator (left) under cyclic axial loading. Two cups, fixed in a metal backing with bone cement, were tested at the same time.
During the tests, compressions of whole measurement systems, i.e. compressions of femoral heads into the cup-cement combinations during each cycle, were recorded. Maximum compression values during the initial cycle were used for the validation of the finite element models. As the compression was applied according to Fig. 1, the final value for one cup-cement combination was approximated to be half of the recorded value, and consequently six compression values were obtained (Table 1).
After 5 million cycles, the penetration rates (μm / million cycles) of the acetabular cups, i.e. plastic deformations, were analyzed using a coordinate tester Dea Global C 091508 (Dea, Tourin, Italy). The penetration rates were evaluated as the displacement of the center of the spherical surface of the cups, which were mathematically estimated after the cyclic tests.
Finite element modeling
The femoral head-acetabular cup-cement complexes, used in experimental tests, were processed for finite element analyses. In addition, two new designs were reconstructed to investigate the effect of clearance and polyethylene thickness on the contact pressure. Thus, altogether four 3-D meshes consisting of 15834 – 16072 hexahedral elements (Fig. 2) were created:
Figure 2 Finite element meshes of the present study. Four acetabular cups, cement mantle and femoral head were reconstructed by using hexahedral elastic elements.
1) Lubinus eccentric (inner diameter of acetabular cup = 28.5 mm, experimentally tested),
2) Lubinus concentric, (inner diameter of acetabular cup = 28.5 mm, virtual design),
3) IP1 (inner diameter of acetabular cup = 28 mm, experimentally tested),
4) IP2 (inner diameter of acetabular cup = 28.5 mm, virtual design).
The outer diameter of all acetabular cups was 52 mm and the diameter of the femoral head was 28 mm. Lubinus concentric was reconstructed to analyse differences between eccentric and concentric cups and, consequently, the effect of polyethylene thickness. The effect of clearance was studied by increasing the inner diameter of the IP cup (IP1 → IP2) to correspond to the diameter of Lubinus eccentric/concentric. Young's moduli (E) for femoral head, acetabular cups and bone cement, as determined experimentally, were 193 GPa, 0.69 GPa and 2.74 GPa, respectively. A friction coefficient of 0.05 was assumed for the contact between acetabular cup and femoral head [22]. The cup-cement interface was fixed and the boundary constaint was applied for the outer surface of the cement layer to simulate the metal backing used in the experimental tests.
First, the compressions of the femoral heads into the acetabular cup – cement combinations were analyzed using 3 kN loading force and compared with corresponding experimental findings. Second, the effect of abduction angle on the stresses of acetabular cups was investigated with different loading forces in order to simulate different body weights performing regular daily activities and exceptionally high impact loads. In addition to the experimentally used abduction angles of 45° and 60°, simulations were also conducted using an angle of 80°. Von Mises stress distributions in the cups and contact pressures both at cup-head and cup-cement interfaces were studied. Abaqus code (v6.3, Hibbitt, Karlsson & Sorenssen, Inc., Pawtucket, RI, USA) was used for the FE simulations.
Results
Experimentally, the maximum compressions of the femoral heads during the initial loading cycle using the IP and Lubinus eccentric acetabular cups were 115 μm and 129 μm, respectively, at the 45° abduction angle (Table 1). The corresponding values obtained in the FE simulations were 98 μm and 132 μm. At the abduction angle of 60°, experimental maximum compression values during the initial cycle using the IP and Lubinus eccentric cups were 123 μm and 140 μm, respectively. The corresponding values obtained in the FE simulations were 107 μm and 133 μm.
The measured penetration rates of the cups were 11.8 μm (11.6 – 11.9) and 9.5 μm (8.9 – 10.2) per million cycles for IP and Lubinus eccentric, respectively, at the abduction angle of 45° (Table 1). The corresponding values at the 60° angle, 14.7 μm (14.2 – 15.2) and 11.2 μm (10.0 – 11.9), were significantly higher (p < 0.05, Wilcoxon signed ranks test, n = 6 + 6). The penetration rates were significantly (p < 0.05, Mann-Whitney U-test, n = 4 + 8) higher for IP than for Lubinus eccentric.
FE simulations disclosed that there were different stress distributions (von Mises stress) in Lubinus eccentric and IP cups (Fig. 3). Due to the varying geometries, the direction of the stress was different. The decrease of the thickness of the Lubinus acetabular cup (eccentric versus concentric) did not affect the stress distribution, but the increase in the gap between the head and the IP cup had a major influence on the von Mises stresses.
Figure 3 Stress distribution in the acetabular cups. Von Mises stresses of a) Lubinus eccentric, b) IP1, c) Lubinus concentric and d) IP2 models at 45°, 60° abduction angles.
FE simulations showed that the abduction angle (45° – 80°) had only a minor influence on the contact pressure between the head and the Lubinus eccentric cup (Figs. 4a and 5a). In contrast, the contact pressure on the surface of IP cup increased notably as a function of the abduction angle (Figs. 4b and 5a). However, the larger contact area between the IP cup and head induced lower contact pressure at low loading forces on the surface of IP compared to the corresponding situation with Lubinus eccentric (Fig. 6). At high loads, the edge of the IP acetabular cup experienced very high contact pressures, especially at high abduction angles (60° and 80°). The difference in the contact pressure between the eccentric and concentric Lubinus models at the inner surface of the acetabular cup was not significant (Figs. 4a, c and 5). As the increase of the radius of the IP acetabular cup from 28 mm to 28.5 mm reduced the contact area, the peak contact pressure increased (Figs. 4b, d and 5).
Figure 4 Contact pressure at the inner surface of acetabular cups at 45° 60° and 80° abduction angles. a) Lubinus eccentric, b) IP1, c) Lubinus concentric and d) IP2.
Figure 5 Peak contact pressure at the cup-head interface as a function of loading force and abduction angle. a) Lubinus eccentric and IP1, b) Lubinus concentric and IP2.
Figure 6 Contact area between humeral head and acetabular cup. Experimentally analyzed (a) and numerically simulated (b) contact area between Lubinus eccentric and IP acetabular cup and femoral head. After cyclic tests of hip implants in a simulator, the surfaces of UHMWPE cups were covered with a thin layer of diluted colourant (Tuschierpaste blau, Emil Alberts GmbH, Gevelsberg, Germany), and femoral heads were positioned in contact with the acetabular cups in the loading direction. After removing the femoral heads, the presence of blue color indicated the contact area. The contact area in the FE-simulations was analyzed under 3 kN axial load which was the maximum load in the experimental cyclic tests.
At the interface between the acetabular cup and the cement, the contact pressure increased as a function of abduction angle in all models (Figs. 7 and 8). Due to the larger contact area between cup and head and the smaller deformation of the cup, the contact pressure remained lower on the outer surface of the IP cup at all abduction angles (Figs. 7a, b and 8a). A decreased thickness of the acetabular cup (Lubinus eccentric → concentric) (Figs. 7a,c and 8) and the increased clearance between IP cup and femoral head (Figs. 7b,d and 8) elevated contact pressures on the outer surfaces of the cups.
Figure 7 Contact pressure at the outer surface of acetabular cups at 45°, 60° and 80° abduction angles. a) Lubinus eccentric, b) IP1, c) Lubinus concentric and d) IP2
Figure 8 Peak contact pressure at cup-cement interface as a function of loading force and abduction angle. a) Lubinus eccentric and IP1, b) Lubinus concentric and IP2.
Discussion
In the present study, 3-D finite element analyses and experimental cyclic tests were used for the estimation of the combined effects of acetabular cup geometry and orientation on the stresses in cemented UHMWPE. It was found that IP and Lubinus eccentric acetabular cups, manufactured by Link®, were subjected to considerably different stress distributions and contact pressures both on the inner and outer surfaces of the cups. The abduction angle and thickness of the cup, as well as the clearance between the femoral head and the cup, contributed significantly to stress experienced by the acetabular cup.
Experimental and theoretical compressions during one loading cycle were consistent with each other. The slight discrepancies (2 – 15%) were probably due to the fact that the processing of UHMWPE induces uncertainties in the diameters of the cups, whereas in the finite element simulations, optimal diameters, supplied by the manufacturer, were used. On the other hand, the initial fit of the head-cup-cement complex may not have been perfect in all of the experimental configurations, and this may have induced higher compression values.
The experimentally determined penetration rates of the present study supported the conclusions based on the FE analyses. The experimental tests showed that the penetration rate increased significantly as a function of the abduction angle. This was consistent with the FE analyses which suggested that the contact pressure increased as a function of the abduction angle, even though this increase with the Lubinus model was relatively low. Even though the peak contact pressure remained lower on the inner surface of the IP acetabular cup compared to that on the Lubinus eccentric when simulating loading forces of less than 3 kN, the experimentally determined penetration rate was faster for the IP cup. The contact area between the IP cup and the femoral head was larger than that between Lubinus eccentric and the head (Fig. 6), which probably induced this discrepancy. The minor clearance and consequently high contact area have been shown to increase also volumetric wear [10,15]. Previously, in simulator tests, wear rates of Lubinus eccentric cups were lower than those of IP cups and some other models [23]. This advantageous effect might be due to the formation of a protective protein layer on the cup surface as a result of the more closed lubrication environment in the Lubinus eccentric design.
The behavior of contact pressure and penetration rate of the present study were consistent with earlier studies [8,9,12]. Jin et al. (1999) investigated contact pressure and area in eight combinations of femoral head and UHMWPE cup, and found similar behavior of contact pressure as a function of load as observed in the present study [9], although their model was 2-D axisymmetric and was not affected by the edge of the cup. Patil et al. (2003) studied the effect of abduction and anteversion angle of acetabular cup on the contact stress and wear of UHMWPE [8]. FE simulations of their study showed that peak contact stresses increased as a function of abduction angle, as was also found in the present study. Wear rates after testing in the hip simulator and linear head penetrations of the clinical study [8] as well as plastic deformations of the cups in the present study supported those findings. Some studies have suggested that the cup orientation plays minor role on the polyethylene wear, but more important is to determine the shape of the wear distribution [10,24]. In the present study, the distribution of von Mises stress and contact pressure were highly influenced by the cup geometry. In general, slight differences between the previous studies and the present study are probably due to differences in the acetabular cup geometries, material properties and the loading protocols used in the experimental tests and analytical or numerical analyses [8,25,26].
Abduction angle clearly differentiated the acetabular cups. Lubinus eccentric seemed to be relatively forgiving in dealing with the variations in the abduction angle, whereas at 60° and 80° abduction angles, the IP cup experienced high peak contact pressures, especially at high loading forces. Evidently, geometrical factors were behind this kind of behaviour. The snap-fit primary locking mechanism in Lubinus cup eliminated the effect of the abduction angle. In this model the contact area between the ball and cup did not change as a function of the abduction angle. This minimizes the variations in the contact pressure and indicates that the survival of Lubinus acetabular cup may not be so operation sensitive. On the other hand, even though the geometry of IP cup permits a large range of motion, the contact area between IP cup and head changed as a function of the abduction angle, modifying the contact pressure. Furthermore, the edge of the IP cup was the most critical area in elevating the contact pressure, pointing to an increased risk for the cup failure [27].
The thickness of the acetabular cup and the clearance between cup and femoral head may have significant clinical relevance [9-12,14,15]. For instance, in the present study, a 13% decrease of the thickness at the upper part of the acetabular cup (Lubinus eccentric versus concentric) increased the peak contact pressure at the cup-cement interface at a 45° abduction angle by 20% (3 kN load). Consequently, eccentricity may decrease the risk for cup rotation. The increase of the clearance between IP acetabular cup and femoral head from 0 to 0.25 mm elevated peak contact pressure at cup-head interface by 27% and at the cup-cement interface by 65% (3 kN load). Also earlier studies have shown that the increased clearance and decreased thickness raise peak contact pressure [9,12]. These percentual values suggest that rather minor changes in the geometrical parameters of UHMWPE acetabular cups may have significant consequences (e.g. rotation, wear, loosening) in long-term use.
In the present study, all of the materials and boundaries were kept similar to permit a comparative evaluation of acetabular cups with different geometrical designs. In the clinical setting, however, the bone support and joint capsule will affect the stresses to which the acetabular cups are subjected [28]. Also, the contact area between the ball and the cup increases during the so-called running-in period, which typically lasts less than a year [29]. The bearing surface of the polyethylene accommodates to the head radius through deformation, wear and creep, so that the effective clearance approaches zero. Therefore, the contact pressure and fracture risk decrease substantially. After the first year, the penetration rate of the head into the cup is fairly constant [29,30]. In long-term clinical use, this phenomenon may modify the behavior of the acetabular cups tested in the present study. Finally, cement fixation was assumed to extend up to the edge of the acetabular cups. However, in the clinical situation, the upper edge of the cup is not always fully supported by the cement mantle, especially at low abduction angles (<45°), inducing variations in the stress and wear concentrations of the cups.
A previous finite element model with elasto-plastic polyethylene cup proposed a perfect plastic yield after 8 MPa von Mises stress [15], which is lower than the maximum von Mises stress observed in the present study. However, the radiation-crosslinked UHMWPE tested in this study has a yield strength of 20 MPa or more (ASTM F648) [31] and the von Mises stress of IP cup at the abduction angles of 45° and 60° did not exceed 20 MPa under any load. In this study the cup was assumed to be elastic to enable analysis of potential peak stresses also at very high impact loads, not only during normal walking. Under low loads (< 3 MPa), the von Mises stress did not exceed 20 MPa in any cup design. In addition, if von Mises stresses are calculated for the IP acetabular cup at the 3 kN load, which was the maximum value used in the experimental tests of the present study, only approximately 8 MPa peak von Mises stress is reached at an abduction angle of 45°. Plasticity, nonlinear elasticity or viscoelasticity [8] of UHMWPE would have changed absolute pressure values, but not the conclusions of the present study.
FE modeling provides a rapid and inexpensive estimate of implant-related factors (e.g. geometry of the acetabular cup) and surgery-related factors (e.g. abduction angle of the implant), but the final judgement is based on laboratory tests and clinical data. The hip arthroplasty registers [18,19], used to obtain clinical reference data, do not differentiate between Lubinus eccentric and IP acetabular cups, but the present study points to differences in the performances of these cups. The results of this study indicate that it would be beneficial if cups of different designs were recorded separately in the registers, rather than combining cups from a single hip system. All experimental and numerical data presented in this study address the importance of optimizing the geometry and orientation of the acetabular cup before and during the operation, respectively. These are factors which may affect significantly failure of THR.
Conclusion
FE analyses of the present study showed that the geometrical design, thickness and abduction angle of acetabular cup, as well as the clearance between cup and head modify the mechanical stresses experienced by UHMWPE. These factors should be taken into account in the future development of THR and the FE technique is a powerful tool for this purpose.
Authors' contributions
RKK was involved in the design of the study, developed the FE models and calculated numerical predictions, as well as drafted the manuscript. AK participated in the design of the study, experimental tests and data analyses, as well as in the statistical analyses. YTK participated in the design of the study and coordination as well as helped in the manuscript preparation. SSS was involved in conceiving the study, coordination and manuscript preparation. RL participated in conceiving the study, coordination, experimental tests, FE model development and manuscript preparation. All authors have read and approved the final manuscript.
Note
*Partially cross-linked polyethylene cups are processed according to ISO 5834-II and ASTM F648 standards. Cups are compression molded and gamma irradiated in a vacuum to a level of 27 kGy.
Acknowledgements
Financial support from the Academy of Finland, Sigrid Jusélius Foundation, Helsinki, Finland, and the Invalid Foundation, Helsinki, Finland, is acknowledged. The authors thank MSc Petteri Väänänen for conducting the experimental measurements and Esa Miettinen for technical support.
==== Refs
Amstutz HC Campbell P Kossovsky N Clarke IC Mechanism and clinical significance of wear debris-induced osteolysis Clin Orthop Relat Res 1992 276 7 18 1537177
Bono JV Sanford L Toussaint JT Severe polyethylene wear in total hip arthroplasty. Observations from retrieved AML PLUS hip implants with an ACS polyethylene liner J Arthroplasty 1994 9 119 125 8014641 10.1016/0883-5403(94)90059-0
Hozack WJ Mesa JJ Carey C Rothman RH Relationship between polyethylene wear, pelvic osteolysis, and clinical symptomatology in patients with cementless acetabular components. A framework for decision making J Arthroplasty 1996 11 769 772 8934315 10.1016/S0883-5403(96)80175-6
Petersilge WJ D'Lima DD Walker RH Colwell CWJ Prospective study of 100 consecutive Harris-Galante porous total hip arthroplasties. 4- to 8-year follow-up study J Arthroplasty 1997 12 185 193 9139101 10.1016/S0883-5403(97)90065-6
Maxian TA Brown TD Pedersen DR Callaghan JJ Adaptive finite element modeling of long-term polyethylene wear in total hip arthroplasty J Orthop Res 1996 14 668 675 8764879 10.1002/jor.1100140424
Rostoker W Galante JO Contact pressure dependence of wear rates of ultra high molecular weight polyethylene J Biomed Mater Res 1979 13 957 964 511863 10.1002/jbm.820130612
D'Lima DD Chen PC Colwell CWJ Optimizing acetabular component position to minimize impingement and reduce contact stress J Bone Joint Surg Am 2001 83-A Suppl 2 Pt 2 87 91 11712840
Patil S Bergula A Chen PC Colwell CWJ D'Lima DD Polyethylene wear and acetabular component orientation J Bone Joint Surg Am 2003 85-A Suppl 4 56 63 14652394
Jin ZM Heng SM Ng HW Auger DD An axisymmetric contact model of ultra high molecular weight polyethylene cups against metallic femoral heads for artificial hip joint replacements Proc Inst Mech Eng [H] 1999 213 317 327 10466363 10.1243/0954411991535158
Raimondi MT Santambrogio C Pietrabissa R Raffelini F Molfetta L Improved mathematical model of the wear of the cup articular surface in hip joint prostheses and comparison with retrieved components Proc Inst Mech Eng [H] 2001 215 377 391 11521761 10.1243/0954411011535966
Akasaki K Long-term results of rotational total hip arthroplasty: radiological analysis J Orthop Sci 2004 9 126 134 15045540 10.1007/s00776-003-0762-3
Jin ZM Dowson D Fisher J A parametric analysis of the contact stress in ultra-high molecular weight polyethylene acetabular cups Med Eng Phys 1994 16 398 405 7952678
Puolakka TJ Keranen JT Juhola KA Pajamaki KJ Halonen PJ Nevalainen JK Saikko V Lehto MU Jarvinen M Increased volumetric wear of polyethylene liners with more than 3 years of shelf-life time Int Orthop 2003 27 153 159 12679893 10.1007/s00264-003-0495-0
Saikko VO Wear of the polyethylene acetabular cup. The effect of head material, head diameter, and cup thickness studied with a hip simulator Acta Orthop Scand 1995 66 501 506 8553815
Teoh SH Chan WH Thampuran R An elasto-plastic finite element model for polyethylene wear in total hip arthroplasty J Biomech 2002 35 323 330 11858807 10.1016/S0021-9290(01)00215-9
Huiskes R Failed innovation in total hip replacement. Diagnosis and proposals for a cure Acta Orthop Scand 1993 64 699 716 8291421
Stolk J Maher SA Verdonschot N Prendergast PJ Huiskes R Can finite element models detect clinically inferior cemented hip implants? Clin Orthop Relat Res 2003 409 138 150 12671496 10.1097/01.blo.0000058882.03274.5e
The Swedish National Hip Arthroplasty Register. Annual Report 2003 Göteborg, Sweden, Sahlgrenska University Hospital
Finnish Arthoplasty Register. The 2000-2001 implant yearbook on orthopaedic endoprostheses 2003 Helsinki, Finland, National Agency for Medicines
Vaananen P Koistinen A Santavirta SS Korhonen RK Lappalainen R Simulator study on the effect of abduction angle on the performance of cemented UHMWPE acetabular cup of THR 5th Combined Meeting of Orthopaedic Research Societies of Canada, USA, Japan and Europe 2004 216
Clarke IC Chan FW Essner A Good V Kaddick C Lappalainen R Laurent M McKellop H McGarry W Schroeder D Selenius M Shen MC Ueno M Wang A Yao J Multi-laboratory simulator studies on effects of serum proteins on PTFE cup wear Wear 2001 250 188 198 10.1016/S0043-1648(01)00656-1
Lappalainen R Anttila A Heinonen H Diamond coated total hip replacements Clin Orthop Relat Res 1998 352 118 127 9678039 10.1097/00003086-199807000-00014
Selenius M Santavirta SS Lappalainen R Simulation studies of the five most commonly used THR implants in Finland 7th World Biomaterials Congress 2004 1145
Del Schutte HJ Lipman AJ Bannar SM Livermore JT Ilstrup D Morrey BF Effects of acetabular abduction on cup wear rates in total hip arthroplasty J Arthroplasty 1998 13 621 626 9741436
Chen PC Pinto J D'Lima DD Colwell CW Polyethylene material properties: stress relaxation 6th World Biomaterials Congress 2000 1469
D'Lima DD Chen PC Pinto J Colwell CW Finite element model of UHMWPE 6th World Biomaterials Congress 2000 133
Yew A Jagatia M Ensaff H Jin ZM Analysis of contact mechanics in McKee-Farrar metal-on-metal hip implants Proc Inst Mech Eng [H] 2003 217 333 340 14558645 10.1243/095441103770802496
Stewart KJ Pedersen DR Callaghan JJ Brown TD Implementing capsule representation in a total hip dislocation finite element model Iowa Orthop J 2004 24 1 8 15296198
Santavirta S Bohler M Harris WH Konttinen YT Lappalainen R Muratoglu O Rieker C Salzer M Alternative materials to improve total hip replacement tribology Acta Orthop Scand 2003 74 380 388 14521286 10.1080/00016470310017668
Oonishi H Kadoya Y Wear of high-dose gamma-irradiated polyethylene in total hip replacements J Orthop Sci 2000 5 223 228 10982661 10.1007/s007760050155
Muratoglu OK Bragdon CR O'Connor DO Jasty M Harris WH Gul R McGarry F Unified wear model for highly crosslinked ultra-high molecular weight polyethylenes (UHMWPE) Biomaterials 1999 20 1463 1470 10458559 10.1016/S0142-9612(99)00039-3
| 15904521 | PMC1173123 | CC BY | 2021-01-04 16:37:37 | no | Biomed Eng Online. 2005 May 17; 4:32 | utf-8 | Biomed Eng Online | 2,005 | 10.1186/1475-925X-4-32 | oa_comm |
==== Front
Biomed Eng OnlineBioMedical Engineering OnLine1475-925XBioMed Central London 1475-925X-4-341590452310.1186/1475-925X-4-34ResearchInvestigation of non-uniform airflow signal oscillation during high frequency chest compression Sohn Kiwon [email protected] Warren J [email protected] Yong W [email protected] Jongwon [email protected] James E [email protected] Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, USA2 Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA2005 19 5 2005 4 34 34 10 3 2005 19 5 2005 Copyright © 2005 Sohn et al; licensee BioMed Central Ltd.2005Sohn et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
High frequency chest compression (HFCC) is a useful and popular therapy for clearing bronchial airways of excessive or thicker mucus. Our observation of respiratory airflow of a subject during use of HFCC showed the airflow oscillation by HFCC was strongly influenced by the nonlinearity of the respiratory system. We used a computational model-based approach to analyse the respiratory airflow during use of HFCC.
Methods
The computational model, which is based on previous physiological studies and represented by an electrical circuit analogue, was used for simulation of in vivo protocol that shows the nonlinearity of the respiratory system. Besides, airflow was measured during use of HFCC. We compared the simulation results to either the measured data or the previous research, to understand and explain the observations.
Results and discussion
We could observe two important phenomena during respiration pertaining to the airflow signal oscillation generated by HFCC. The amplitudes of HFCC airflow signals varied depending on spontaneous airflow signals. We used the simulation results to investigate how the nonlinearity of airway resistance, lung capacitance, and inertance of air characterized the respiratory airflow. The simulation results indicated that lung capacitance or the inertance of air is also not a factor in the non-uniformity of HFCC airflow signals. Although not perfect, our circuit analogue model allows us to effectively simulate the nonlinear characteristics of the respiratory system.
Conclusion
We found that the amplitudes of HFCC airflow signals behave as a function of spontaneous airflow signals. This is due to the nonlinearity of the respiratory system, particularly variations in airway resistance.
==== Body
Background
High Frequency Chest Compression (HFCC) [6,9,19,29] is a useful and popular therapy for clearing bronchial airways of excessive or thick mucus since it does not require patients to do any directed efforts for respiration while therapy is given, unlike other airway clearance techniques such as active cycle of breathing or autogenic drainage [17]. A HFCC machine pumps air into an inflatable jacket worn by patient. By means of a surrogate piston, sine waveform compression pulses with frequencies ranging from ~5 Hz to ~21 Hz are supplied to the thorax of a patient through the jacket. These pulses squeeze and vibrate the patient's thorax at prescribed frequencies. These actions help in the evacuation of mucus through changing the rheological property of the mucus and airflow oscillation. King et al. [13], Krumpe et al. [15], and Tomkiewicz at al. [28], showed that HFCC pulses decrease the viscosity of mucus and helps evacuation. A more important consequence is the respiratory airflow oscillated during use of HFCC, which results from variation of intrapleural pressure. Lapin [17] and Warwick [30] pointed out that airflow is the most important factor for mucus transport since airflow produces the shear stresses for evacuation of mucus.
Although several models have been developed to simulate respiration by other researchers and their models successfully worked for their own purposes, these models are not appropriate for HFCC simulation because these models were either linearized [7,8] or because they assumed that respiration was driven by a mechanical ventilator at the mouth [5,20]. The model presented in this paper provides reliable simulation results on fast change of intrapleural pressure (Ppl) altered by HFCC because this model is described with nonlinear equations and Ppl is selected as the driving force of respiration. The nonlinear characteristics of the respiratory system are not easily noticed during quiet tidal breathing, but the airflow signal oscillation measured at the mouth during use of HFCC is a strong indicator of the nonlinear characteristics of the respiratory system.
In this study, we simulated the respiratory system with a computational model that carefully reflected its nonlinear characteristics. The model is an electrical circuit analogue, in which nonlinear resistors (R's), capacitors (C's), and inductors (L's) represent airway resistance, lung capacitance, and inertance of air, respectively. Just like in a living organ, the driving force of this model is Ppl which is a superposition of HFCC pulses on the spontaneous breathing effort. We compared the simulation data to the in vivo data to demonstrate and understand the characteristics of airflow signal oscillation.
Methods
Conceptual model of the respiratory system
Our modelling and simulation for reproducing airflow signals required simplification of airway structure in the lung. The geometrical and dimensional structures of the airways were proposed by several researchers, among which Horsefield et al. [10] and Weibel [31] dissected and measured the human lungs and airways, and more recently, and Tawhai et al. [11] and Kitaoka et al. [14] proposed algorithmic approaches for reconstructing the branching structure. We employed Weibel's morphometry of the lung, which provides the geometries and the dimensions based on the symmetric dichotomous structure of airway branching when the lung volume is assumed to be 75% of the total lung capacity (TLC). According to his morphometry, the trachea is defined as airway generation 0 and it is separated into two geometrically identical daughter branches. Each daughter is repeatedly branched up to 22 times, thus the lung is considered to have 24 (0–23) airway generations and the number of airway branches total ~1.7 × 107. In each airway generation, there are 2z (z is a generation number) identical branches whose lengths and radii are provided and the dimensions of airway branches in each generation differ from generation to generation. He also suggested that airway generations 0–16 comprise the conducting zone, whereas airway generations 17 – 23 make up the respiratory zone in which gases are exchanged.
Based on Weibel's morphometry of the lung, we simplified the geometry of the airways. For airway generation Z in conducting zone, a bundle of 2z identical airway branches are considered as the big tube whose cross sectional area equals to 2z times the cross sectional area of a single airway branch. The tubes for each airway generation are represented by RCL T-networks shown in fig. 1 (b), and evaluation of the R's, C's, and L's in the RCL T-network are explained in equations (4) – (6). Meanwhile, the respiratory zone is considered as a big lump, the alveolar space, since alveolar ducts and sacs are scattered throughout the respiratory zone [8]. Although the upper airway is not presented in Weibel's morphometry, it is one of the chief sites for airway resistance.
Figure 1 (a) The conceptual model based on Weibel's morphometry of the lung [31]. The lung and airways are comprised of five regions, namely, the alveolar space, the conducting airway zone, the pleural cavity, the thorax outside the lung, and outside the thorax. (b) RCL T-network that represents a region (airway generation) in the conducting airway zone. (c) Electrical circuit analogue converted from (a). For acronyms in the figure, see list of abbreviations.
Our conceptual model as a summary of the simplification, 'the upper airway + 17 conducting airway generations + the alveolar space', is demonstrated in fig. 1 (a), and circuit analogue converted from fig. 1 (a) is shown in fig. 1 (c).
Dimensions of airway branches
Since the dimensions of every single airway branch in the lung vary during respiration, it is crucial to track them to extract proper values of R's, C's, and L's. The radii of the airway branches in airway generation Z are determined by transmural pressure (PtmZ), pressure difference between the pleural cavity and inside airway generation Z. In order to determine PtmZ, we need to rely on the study about transpulmonary pressure (Ptp), pressure difference between the pleural cavity and alveolar space. According to Salizar et al. [26], Ptp is a function of lung volume (LV) and TLC. With given LV, Ptp is obtained by,
Ptp = -log (1 - LV / TLC) × 7.22. (1)
If LV is functional residual capacity (FRC) and no airflow exists in the airways, the lung is at rest. In this situation, air pressure at any site is the same and atmospheric (zero), therefore PtmZ and Ptp are the same. Our simulation begins with assuming that the lung was at rest. The equation of Lambert et al., or Lambert's tube law [16], is a function of PtmZ, and gives the ratio of the cross sectional area (AZ) to the maximum cross sectional area of an airway branch (AmaxZ) in airway generation Z. That is,
AZ / Amax Z = 1.0 - (1.0 - α0)(1.0 - PtmZ / P0)-N (2)
where α0, α0' and N are constants for each airway generation given from Lambert's tube law, and P0 = (α0-1)N/α0'. As mentioned earlier, the dimensions of the airway branches provided by Weibel's morphometry are based on 75 % of TLC. Let AZ75 be Weibel's cross sectional areas in airway generation Z. By using
AmaxZ for each airway generation can be found. Since AmaxZ does not change whether or not the lung is at rest, the equation is valid to find out AZ during respiration.
The length of an airway branch is assumed to vary in away that;
lz / lFRC = rz / rFRC (3)
where lz and rz are the length and the radius of an airway branch in airway generation Z, respectively. lFRC and rFRC are the length and the radius on FRC, respectively.
Equivalent circuit elements modelling
The RCL T-network consists of two resistors (RgZ), two inductors (LgZ), a capacitor (CgZ), and a DC voltage source (Ptm_ini). RgZ and LgZ are the airway resistance and the inertance of air in the entire airway generation Z, respectively. CgZ, the airway capacitance of the entire airway generation Z, represents inflation and deflation of the non-rigid airway wall during respiration. Ptm_ini is the initial value of PtmZ. This initial pressure counterbalances Ppl, which is negative when the lung is at rest.
The values of the circuit elements in the RCL T-network of airway generation Z can be obtained by totalling the 2z airway branches. Therefore, RgZ is given by
Similarly, Lgz is given by
and CgZ is
CgZ = CsZ × Nz [ml/cmH2O], (6)
where RsZ, LsZ, and CsZ indicate the values of a single airway branch in airway generation Z. Nz is 2z, the number of airway branches in generation Z.
RsZ depends on the classic Poiseuille equation and the Zeta correction factor proposed by Pedley et al. [21]. The Zeta correction factor is given by
and
Re is Reynolds number , V is air velocity, ρ is the density of air, and η is the viscosity of air.
Because electric current flows at the speed of light in an electrical circuit, it is necessary to compensate for the incomparably slower behaviour of airflow in the airways by placing inductors. Inertance of air in a single airway branch (LsZ) depends on the dimension of the airway branch [5] and it is given by
To compute the values for CsZ in equation (2), relation between AZ and PtmZ in airway generation Z, is used again. That is,
The alveolar space is represented by a capacitor in the circuit analogue. Alveolar capacitance (Cas) is the ratio of the alveolar volume (ΔAV) to ΔPtp. Lung volume (LV) consists of airway volume and alveolar volume, and airway volume is negligible compared to alveolar volume. Therefore,
which implies that represents Cas. It can be obtained by equation (1); however, the equation did not consider the hysteresis of Ptp-volume curves that is caused by several proposed reasons [1]. To overcome this, we defined Cas as *k (k<0), and k was continuously changed over the time course of the simulation. The values of k were empirically determined to achieve the acceptable shape of the hysteresis, which is shown in fig. 2.
Figure 2 Ptp-volume curves of the lung model during use of HFCC. Although the initial LV (FRC) is 2700 ml, LV during use of HFCC is smaller. The curves became jagged due to HFCC pulses.
A resistor and an inductor characterize the upper airway, from the nasal/oral cavity to larynx. The equations for the resistance of the upper airway (Rua) that Jackson et al. [12] validated are described below:
where Fua is the airflow rate in the upper airway. As Marchal et al. [18] estimated, the value of the inductor that represents inertance of air is 0.00003 [cmH2O·s2/ml].
Numerical methods for nonlinear circuit analogue
Although the number of elements is manageable and the structure of circuit is fairly simple, analysis of the circuit analogue in fig. 1 (c) is not trivial since the values of all the energy-storing (C's and L's) elements as well as resistive elements (R's) change at every sequence of the simulation time-step. To exemplify a general idea of numerical methods for the nonlinear circuit analogue, analysis of a simple nonlinear second-order system in fig. 3 was demonstrated. The system of fig. 3 is described by an equation:
Figure 3 A nonlinear second-order system in the form of an electrical circuit. i is electrical current, and vC is voltage difference between each end of C. The value of the resistor (R) in this figure is dependant on i as well as vC whereas the capacitor (C) and the inductor (L) are dependent only on vC. Vin(t) is a voltage source for this simple circuit system. Nonlinear circuit elements in this circuit imply the nonlinearity of fig. 1 (c).
where vC is the voltage difference between each end of the capacitor. Note that R(•) is a function of i and vC, and L(•) and C(•) are functions of vC just like in fig. 1 (c). Using backward Euler approximation [22], equation (14) is converted to a difference equation:
where Δt is time difference between sequence [n] and [n-1]. Equation (15) is the same as
By the definition of backward Euler approximation, the current of the circuit . Then equation (16) can be restated as an equation;
In equation (17), the right hand side consists of all known values, and the left hand side is a function of vC[n]. Suppose that vC[n] is x, equation (17) can be expressed as
f(x) = c, (18)
where c is a constant. Equation (18) can be easily solved using an iteration method [24]. To do this computation, MATLAB (Mathworks, Natick, MA) codes were written.
Protocols for measurement airflow signals
In this study, The Vest™ (Advanced Respiratory, St.Paul, MN, USA; now named Hill-Rom Co.,Inc.), which delivers sine waveform compression pulses, was used for application of HFCC to a subject for measuring and recording the airflow signals at the mouth. The general usage of HFCC device was early described in the review of Hansen et al. [9] and the typical respiratory airflow during use of HFCC is shown in fig. 4.
Figure 4 (a) The airflow and (b) the oesophageal pressure measured by Fink et al. [6] (modified with the permission), which shows typical respiratory airflow during use of HFCC. The positive numbers of airflow rate represent inspiration and the negative numbers represent expiratory airflow. Oesophageal pressure reflects the intrapleural pressure (Ppl) that is altered by HFCC pulses (tiny peaks).
The subject sat upright on a chair for measuring and recording the airflow signals at the mouth with an in-house built electronic spirometer. The subject worn a nose clip and breathed through a mouthpiece. After the HFCC device is properly set up, the compression pulses were applied and then the subject made several slow and large, but not to TLC, breaths. During the breaths the subject hold his glottis open until data collection was completed. This protocol was followed for the low (5 Hz), high (21 Hz), and medium frequencies (15 Hz) of HFCC pulses. Before each frequency recording of airflow signals, the subject rested for one minute. To ensure that the subject had adapted to HFCC pulses and had reached a steady state, only the last ten seconds of the one- minute breathing were recorded and analyzed for our study.
Results
For the simulation, the parameters of the lung were determined to represent a normal healthy lung. The TLC, FRC, and RV of the model lung are 6000 ml, 2700 ml, and 1000 ml, respectively. The ambient atmospheric pressure is assumed to be zero, and the air density and viscosity are 0.00113 g/cm3 and 0.00019 g/cm·s, respectively. It was assumed that there would be no airflow in the airways and that initially the LV would be the same as the FRC. Change of Ppl is the primary driving force of respiration and is initially -4.32 cmH2O, which is the counterbalance to initial Ptp given by equation (1).
Fig. 4 is the airflow the oesophageal pressure measured by Fink et al. [6], which shows typical respiratory airflow during use of HFCC. Fig. 5 shows the subject's airflow signals during ten seconds at the three different frequencies. In this figure, each airflow signal is also viewed as the low-pass filtered and the high-pass filtered curves. The high-pass filtered curve indicates the fast airflow signal oscillation generated by HFCC pulses (HFCC airflow signal) whereas the low-pass filtered curve is the airflow during the spontaneous breathing effort (spontaneous airflow signal) of the subject. We divided one cycle of the respiration into four phases. Phase I is the portion of the inspiration phase when the spontaneous airflow signal is greater than the amplitudes of HFCC airflow signal. In this phase LV increases. During phase II, the spontaneous airflow signal stays within the amplitudes of the HFCC airflow signal. Phase II is the pause before expiration begins. The amplitudes of HFCC airflow signals change considerably as the phase moves from I to II. To emphasize the difference of HFCC airflow signals, phase II were consciously prolonged and they are longer than phase II in fig. 6. In phase III, passive or active expiration begins and the amplitudes of HFCC airflow signals decrease to about phase I amplitudes. The low-pass curve gets greater to the negative direction curve than the high-pass curve. The next and last phase is phase IV. Phase IV is the resting period before inspiration, begins. During this phase the amplitudes of HFCC airflow signals again become greater than the spontaneous airflow signal. To reproduce similar airflow signals, a cycle of respiration from phase IV to phase IV was simulated using our computational model. The simulation results with the three frequencies are shown in fig. 6.
Figure 5 The airflow signals measured at the mouth of the subject, the high-pass filtered (HFCC airflow signal) and the low-pass filtered (spontaneous airflow signal) curves. The subject was using HFCC with (a) 5 Hz, (b) 15 Hz, and (c) 21 Hz. Regardless of the frequencies, larger spontaneous airflow signals result in smaller HFCC airflow signals. Since it is difficult to breathe hard during 21 Hz, spontaneous airflow signals in (c) are smaller than in (a) and (b). Phase I is the portion of the inspiration phase when spontaneous airflow signals are greater than the amplitudes of HFCC airflow signals. During phase II, spontaneous airflow signals stay within the amplitudes of HFCC airflow signals. In phase III, expiration begins, and the amplitudes of airflow oscillation decrease to about the amplitudes during phase I. Spontaneous airflow signals get greater to the negative direction than HFCC airflow signals. Finally phase IV, the resting period before inspiration, begins, and the amplitudes of HFCC airflow signals again become greater than spontaneous airflow signals. To emphasize the difference of HFCC airflow signals, phase II were consciously prolonged and they are longer than phase II in fig. 6.
Figure 6 Simulated respiration, spontaneous airflow signals and HFCC airflow signals. The frequencies of HFCC were set (a) 5 Hz, (b) 15 Hz, and (c) 21 Hz. Definitions for Phases I, II, III, and IV in this figure are the same as those in the text and fig. 5.
From the measured values and the simulation of airflow signals at the mouth, we could observe two important phenomena during respiration pertaining to the airflow signal oscillation generated by HFCC. First, the amplitudes of HFCC airflow signals in phases I and III were smaller than those in phases II and IV. Second, the amplitudes in phases I and III became even smaller as the spontaneous airflow signal became greater.
We used the simulation results to investigate how the nonlinearity of airway resistance, lung capacitance, and inertance of air characterized the respiratory airflow. The simulation was repeated after setting one of the three properties as a linear constant value. Fig. 7 compares the linear values with the nonlinear values of the three properties. The linear values are means of the nonlinear values during the simulation. Fig. 8 presents the simulation results of the lung model under the imaginary assumptions. Fig. 8 (a) is normal respiratory airflow at 15 Hz, and fig. 6 (b) and fig. 8 (a) are from the same simulation data. Fig. 8 (b) demonstrates the predicted airflow signals at the mouth with linear airway resistance, which indicates the amplitudes of HFCC airflow signals do not vary significantly. Fig. 8 (c) is the airflow when lung capacitance is set to a linear value. Just like fig. 8 (a), HFCC airflow signals are the largest when spontaneous airflow signals are close to zero. Therefore, it can be presumed that the nonliearity of lung capacitance does not play a role in the non-uniformity of HFCC airflow signals. And neither is inertance of air. Fig. 8 (d), which shows the simulation data with linear inertance of air, is almost identical to fig. 8 (a). This indicates that the inertance of air is also not a factor in the non-uniformity of HFCC airflow signals. Fig. 9 shows the HFCC airflow signals as a function of spontaneous airflow signals based on the same simulation data shown in fig. 8. Fig. 8 (a), (c), and 8 (d) indicate that larger spontaneous airflow signals result in smaller oscillations of HFCC airflow signals whereas HFCC airflow signals do not seem to be related to spontaneous airflow signals in fig. 8 (b).
Figure 7 (a) Airway resistance, (b) lung capacitance, and (c) inertance of air during the simulation used for fig. 8. The linear (fixed) values are the mean values of each nonlinear (varying) value.
Figure 8 Simulated spontaneous airflow signals and HFCC airflow signals, (a) when the values of airway resistance, lung capacitance, and inertance of air are nonlinear (varying), (b) when the value of airway resistance is linear (fixed), (c) when the value of lung capacitance is linear (fixed), and (d) when the value of inertance is linear (fixed). The frequencies of each plot are 15 Hz, so (a) is the same as fig. 6 (b). In (b), the amplitudes of HFCC airflow signals almost do not vary.
Discussion
The number of the airway branches is estimated to be about 17 million [31], and the dimensions of each airway branch vary while the lung is being inflated and deflated during respiration. To reduce the computational burden, models of the respiratory system are often simplified by ignoring the nonlinear natures of the respiratory system [7,8]. Linearization entails considerable flexibility in numerical analysis since linear circuits are computationally much cheaper than nonlinear circuits, either on a time-domain or a frequency-domain basis. However, even during the slowest breathing, airway resistance, lung capacitance, and inertance of air change due to the variation of airway dimensions as well as turbulence. In particular, increase of the airway resistance due to turbulence is so drastic that inaccurate evaluation of airway resistance may result in a misleading simulation result. Our simulation results demonstrated that such errors are more likely when HFCC intervention is applied. Evidence for this was that the result from a linear model was significantly different from that from a nonlinear model (fig. 8 and 9). As parts of the respiratory system, lung capacitance and inertance of air are also nonlinear although it was observed that their nonlinearity did not cause the non-uniform amplitudes of HFCC airflow signals. However, this does not imply that the nonlinear characteristics of lung capacitance and inertance of air have no role in the simulation of the respiratory system. Dimensional changes of the airway branches in the lung are responsible for the nonlinearity of lung capacitance and inertance of air. When dimensions of the airways are involved for simulation and prediction, the nonlinearity is very important for accurate results. For example, in the study of Sohn et al. [27], our model is used for estimation of air velocity, which is airflow rate ÷ cross sectional area. Since the cross sectional areas of airway branches do not vary linearly, lung capacitance and inertance of air also should not be linear in order to avoid discrepancy.
Ideally, studies about airflow in the airways would be best resolved by CFD (Computational Fluid Dynamics), however, using a CFD approach in this study presents several problems that cannot be overcome by modern technology. First, the turbulence mechanism is not completely known [23]. Even during the slowest breathing manoeuvre, turbulence exists in the proximal airways, and ignoring turbulence would not give true simulation results. Another obstacle is that the whole lung cannot be taken into consideration even with the latest supercomputing power. A CFD approach to simulate dynamics of airflow interacting in a huge number of airway branches in the lung requires extremely massive computation. There is no way to deal with it, if any, its computation time would be incredibly long. It should be also pointed out that CFD techniques for airflow in non-rigid wall tubes are not yet mature. Although not perfect, our circuit analogue model allows us to effectively simulate the nonlinear characteristics of the respiratory system.
It is well known that respiratory system impedance consists of airway impedance and chest wall (tissue) impedance [2-4]. Since the driving force of airflow in our model is the intrapleural pressure altered by HFCC pulses transferred from the body surface, our model does not necessarily incorporate chest wall (tissue) impedance. However, it is not clear how effectively the chest wall transfers HFCC pulses to the pleural cavity. Other factors should also be considered for impedance between the jacket of HFCC and the pleural cavity – such as clothes, posture, and tightness of the jacket. Currently, based on observations of Milla et al. [19], we assume that HFCC pulses on the body surface are transferred to the pleural cavity without any distortion of pulsation waveforms although some attenuation may exist.
The HFCC device was initially developed only for cystic fibrosis patients who normally have healthy lungs [29]; consequently we modelled a healthy lung as the first step of the research. As this medical treatment becomes widely applicable to other lung diseases, we are planning to develop models that can be used to simulate HFCC on various lung diseases in the future.
Figure 9 HFCC airflow signals are demonstrated as a function of spontaneous airflow signals based on the same simulation data shown in fig. 8. Nonlinear airway resistance (a, c, and d) produces the non-uniform amplitudes of HFCC airflow signals.
Conclusion
In this study, the airflow signals measured at the mouth during use of HFCC are viewed as a composite of two causes: the spontaneous breathing effort and HFCC pulses. However, since the respiratory system is nonlinear, airflow signals at the mouth are not a mere superposition of the effects from these two causes. In laboratory measurements, the amplitudes of the airflow signal oscillation varied considerably despite the uniformity of the HFCC pulses. After confirming that the simulation results matched up with the observations, we analyzed the simulation data to explain the observed inconsistency in the HFCC airflow signal amplitudes. We found that the amplitudes of HFCC airflow signals behave as a function of spontaneous airflow signals. This is due to the nonlinearity of the respiratory system, particularly variations in airway resistance.
The findings in this paper may not be immediately applicable for HFCC therapy, but they do lead to ways to better prescribe HFCC therapy. Most importantly, the usefulness of our computational simulation and the model-based approach as a tool to understand clinical observations of HFCC was well demonstrated in this paper.
List of abbreviations
HFCC: High Frequency Chest Compression
FRC: Functional Residual Capacity
TLC: Total Lung Capacity
RV: Residual Volume
LV: Lung volume
AV: Alveolar volume
R: resistor
C: capacitor
L: inductor
AZ: Airway cross sectional area in airway generation Z
AmaxZ: Maximum Airway cross sectional area in airway generation Z
AZ75: Airway cross sectional area in airway generation Z when LV is 75% of TLC
Cas: Alveolar capacitance
Cgz: Total airway capacitance in airway generation Z
CsZ: Single airway capacitance in airway generation Z
FinZ: Incoming airflow in airway generation Z
FoutZ: Outgoing airflow in airway generation Z
Fua: Airflow in the upper airway
Lgz: Total inductance (inertance of air) in airway generation Z
LsZ: Single inductance (inertance of air) in airway generation Z
lZ: The length of an airway branch in airway generation Z
NZ: Number of airway branches in airway generation Z
Palv: Alveolar pressure
PawZ: Airway pressure in airway generation Z
Ppl: Pleural pressure or intrapleural pressure
Ptm_ini: The initial value of transmural pressure
PtmZ: Transmural pressure in airway generation Z
Ptp: Transpulmonary pressure
Ptp_ini: The initial value of transmural pressure
Rgz: Total airway resistance in airway generation Z
RsZ: Single airway resistance in airway generation Z
rz: The radius of an airway branch in airway generation Z
Authors' contributions
KS designed all the necessary computational and experimental procedures, analysed data to reach the conclusion, and also prepared the texts and figures in the manuscript. WJW conceived this study, helped organizing the manuscript, and advised all aspects of physiology and medicine for this study. YWL and JL helped measuring the respiratory airflow. JEH advised all aspects of technology and engineering for this study.
==== Refs
Axe JR Abbrecht PH Analysis of the pressure-volume relationship of excised lungs Ann Biomed Eng 1985 13 101 117 4003874
Black LD Dellaca R Jung K Atileh H Israel E Ingenito EP Lutchen KR Tracking variations in airway caliber by using total respiratory vs. airway resistance in healthy and asthmatic subjects J Appl Physiol 2003 95 511 518 12692146
Dellaca RL Aliverti A Lutchen KR Pedotti A Spatial distribution of human respiratory system transfer impedance Ann Biomed Eng 2003 31 121 131 12627819 10.1114/1.1541012
Dellaca RL Black LD Atileh H Pedotti A Lutchen KR Effects of posture and bronchoconstriction on low-frequency input and transfer impedances in humans J Appl Physiol 2004 97 109 118 14966017 10.1152/japplphysiol.00721.2003
Elad D Shochat A Shiner RJ Computational model of oscillatory airflow in a bronchial bifurcation Respir Physiol 1998 112 95 111 9696286 10.1016/S0034-5687(98)00005-X
Fink JB Mahlmeister MJ High-frequency oscillation of the airway and chest wall Respir Care 2002 47 797 807 12088550
Gillis HL Lutchen KR How heterogeneous bronchoconstriction affects ventilation distribution in human lungs: a morphometric model Ann Biomed Eng 1999 27 14 22 9916756 10.1114/1.161
Golden JF Clark JW JrStevens PM Mathematical modeling of pulmonary airway dynamics IEEE Trans Biomed Eng 1973 20 397 404 4754311
Hansen LG Warwick WJ Hansen KL Mucus transport mechanisms in relation to the effect of high frequency chest compression (HFCC) on mucus clearance Pediatr Pulmonol 1994 17 113 118 8165037
Horsfield K Dart G Olson DE Filley GF Cumming G Models of the human bronchial tree J Appl Physiol 1971 31 207 217 5558242
Howatson Tawhai M Pullan AJ Hunter PJ Generation of an anatomically based three-dimensional model of the conducting airways Ann Biomed Eng 2000 28 793 802 11016416 10.1114/1.1289457
Jackson AC Milhorn HT Jr Digital computer simulation of respiratory mechanics Comput Biomed Res 1973 6 27 56 4487654 10.1016/0010-4809(73)90061-X
King M Rubin BK Takishima T, Shimura S Physiological bases for the control of mucous hyper-secretion Airway secretion 1994 NY: Marcel Dekker, Inc
Kitaoka H Takaki R Suki B A three-dimensional model of the human airway tree J Appl Physiol 1999 87 2207 2217 10601169
Krumpe PE Evrensel CA Hassan AA Superimposed oscillation enhance the clearance of mucus stimulant at low air flows in a rigid tracheal model ASME International Mechanical Engineering Congress & Exposition 2002 437 438
Lambert RK Wilson TA Hyatt RE Rodarte JR A computational model for expiratory flow J Appl Physiol 1982 52 44 56 7061277
Lapin CD Airway physiology, autogenic drainage, and active cycle of breathing Respir Care 2002 47 778 785 12088548
Marchal F Haouzi P Peslin R Duvivier C Gallina C Mechanical properties of the upper airway wall in children and their influence on respiratory impedance measurements Pediatr Pulmonol 1992 13 28 33 1589309
Milla CE Hansen LG Weber A Warwick WJ High-frequency chest compression: effect of the third generation compression waveform Biomed Instrum Technol 2004 38 322 328 15338841
Nucci G Suki B Lutchen K Modeling airflow-related shear stress during heterogeneous constriction and mechanical ventilation J Appl Physiol 2003 95 348 356 12651864
Pedley TJ Schroter RC Sudlow MF Flow and pressure drop in systems of repeatedly branching tubes J Fluid Mech 1971 46 365 383
Pillage TL Rohrer RA Visweswariah C Electronic circuit and system simulation methods 1995 McGrow-Hill
Rajagopal KR On some unresolved issues in non-linear fluid dynamics Russ Math Surv 2003 58 319 330 10.1070/RM2003v058n02ABEH000612
Robinson RC An introduction to dynamical systems: Continuous and discrete 2004 NJ: Pearson Prentice Hall
Rodarte JR Rehder K Dynamics of respiration Handbook of Physiology 1986 2 Bethesda, MD: American Physiological Society
Salazar E Knowles JH An Analysis of Pressure-Volume Characteristics of the Lungs J Appl Physiol 1964 19 97 104 14104296
Sohn K Holte JE Phillips JR Warwick WJ Modeled velocity of airflow in the airways during various respiratory patterns the 26th Annual International Conference of the IEEE-EMBS; San Francisco, CA 2004 3925 3928
Tomkiewicz RP Biviji A King M Effects of oscillating air flow on the rheological properties and clearability of mucous gel simulants Biorheology 1994 31 511 520 7833454
Warwick WJ Hansen LG Chest compression apparatus US Patent 4 838 263 June 13, 1989
Warwick WJ Mechanisms of mucous transport Eur J Respir Dis Suppl 1983 127 162 167 6578055
Weibel ER Morphometry of the human lung 1963 Berlin: Springer
| 15904523 | PMC1173124 | CC BY | 2021-01-04 16:37:36 | no | Biomed Eng Online. 2005 May 19; 4:34 | utf-8 | Biomed Eng Online | 2,005 | 10.1186/1475-925X-4-34 | oa_comm |
==== Front
Biomed Eng OnlineBioMedical Engineering OnLine1475-925XBioMed Central London 1475-925X-4-371595524410.1186/1475-925X-4-37Book ReviewReview of "The Physical Measurement of Bone", Edited by C.M. Langton and C.F. Njeh Gefen Amit [email protected] Department of Biomedical Engineering, Faculty of Engineering, Tel Aviv University, Tel Aviv 69978, Israel2005 14 6 2005 4 37 37 The Physical Measurement of Bone .
Langton CM and Njeh CF , editors. Bristol and Philadelphia: Institute of Physics Publishing . 2003 . ISBN 0-7503-0838-9, xxvi+612 pages. US$180 (Hardback). 9 6 2005 14 6 2005 Copyright © 2005 Gefen; licensee BioMed Central Ltd.2005Gefen; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
==== Body
This book is intended for biologists, medical physicists, biomechanical engineers and clinicians who are involved in bone studies. For these practitioners, the book is a comprehensive review of physical measurement techniques applied to bone, with useful emphasis on practical aspects such as protocols of measurement, sample preparation and sources of errors. Chapters were written by leading scientists in the relevant fields, and overall, the outcome is a well-written, comprehensive and useful textbook that will definitely serve the biomedical community.
The book contains 18 chapters classified into four major sections: Introduction, Invasive Techniques, Ionizing Radiation Techniques, and Non-Ionizing Techniques. As typically occurs with books that are collections of chapters from several authors, the quality is not uniform throughout. For example, while some figures are clear and illustrative, other figures suffer poor quality or were reproduced at a too low resolution. The important points of strength and weakness are summarized below.
The introduction includes a comprehensive review of bone anatomy and physiology, in which each skeletal component – bone cells, matrix and mineral – is separately addressed. It would have been useful here to also refer to tissues that connect to bone (tendons, ligaments, cartilage) and produce mechanical loads which act on bone (muscles) and particularly, to the interfaces between bone and these soft tissues. A review of the pathophysiology, etiology, epidemiology, and economic impact of osteoporosis follows, but other, less common bone diseases are only briefly mentioned. A useful chapter on biology safety considerations, with focus on bone studies, is also included in the introduction. I found this chapter particularly helpful as a guide for students or laboratory technicians who become involved in preparing bone sections for histopathology or mechanical testing. Typically, the information on how to avoid accidents such as when dealing with bone saws, chemicals for demineralizing, fixing and staining bone samples, radiation, and biological waste, is posted in internal laboratory or institutional regulations. This is the first textbook chapter that integrates this information specifically for experiments with bone, and I will certainly make it an obligatory reading material for those involved in bone studies in my laboratory. The last chapter in the introduction concerns instrument evaluation. While appreciating the important information provided on measurement errors, precision, and accuracy, I found this chapter to be too general in nature, and was not convinced that it should have been included in a textbook that focuses on bone measurements. For example, the classical Bland and Altman paper in Lancet (1986) [1] which is discussed in detail as related to bone mineral density measurements, originally referred to flow and oxygen saturation measurements, and can be generalized for bone as for any other application. Accordingly, this chapter could have fit a textbook on biomedical instrumentation, but it does not contain contents that are specific enough for bone studies.
The second section, on invasive techniques, puts heavy emphasis on the chapter which concerns mechanical testing of bone. Unfortunately, the contents of this chapter substantially overlap information already provided in the Bone Mechanics Handbook [2] which is a classic in this field. I was disappointed to find out that the tabulated data of mechanical properties for cancellous bone, cortical bone and individual trabeculae mostly summarize publications from the 1970's and 1980's (with few references to publications from the 1990's). Publications from 2000's (e.g. [3,4]) are not covered. I would have expected this new book to cover a more recent literature than that covered in the Bone Mechanics Handbook published on 2001 [2] or in Prof. J.D. Currey's book "Bones: structure and mechanics" published on 2002 [5], particularly because of the growth in attention to bone mechanical properties as osteoporosis becomes a major epidemic. The issue of bone viscoelasticity, which is discussed in detail in [2], is only briefly mentioned here in terms of the dependence of the elastic modulus of cortical bone on the strain rate. On the contrary, I found the subsequent chapters on bone histomorphometry, microscopy and related techniques very useful, specifically because these chapters include detailed procedures for bone histological staining as well as for immunohistochemistry, immunofluorescence, confocal microscopy and scanning electron microscopy analyses.
The third section concerns ionizing radiation techniques and specifically, absorptiometric methods to asses bone mineral density such as DXA, quantitative CT, peripheral QCT and micro-CT. Again, the parts which describe the fundamentals of radiation physics, interactions of x-rays with matter and radiological instrumentation may be too general for this type of book, but the applications to assessment of bone quality in humans and animal models are useful. A remarkable drawback in this section is that nearly all attention is given to bone mineral density, and very little information is provided on morphological parameters of bone that are demonstrated by the CT-based imaging modalities. Specifically, measurements of trabecular separation, trabecular thickness, bone volume fraction, trabecular number, trabecular connectivity etc., and accuracy of these measurements using clinical QCT and micro-CT are not addressed. Relations between these morphologic parameters, which are important characteristics of cancellous bone, are also not mentioned. Although the chapter on MRI that is included in the fourth section (non-ionizing techniques) partially concerns these issues, the reader is lacking information on morphological parameters that can be measured specifically by CT-based methods, and on the relation of accuracy to CT resolution for each morphological parameter.
The last section is dedicated to non-ionizing techniques for bone studies. These include imaging methods such as MRI and ultrasound, as well as finite element and animal models. The chapter on ultrasound measurements of bone is particularly worth mentioning as a well-written review on the technological aspects, accuracy and precision and clinical applications. The chapter on finite element analysis covers up-to-date modeling approaches based on CT cross-sectional images at the whole bone level, or based on micro-CT or micro-MR images at the trabecular level. Geometrical model reconstructions from cross-sectional images and bone mechanical properties relevant to structural modeling are described in adequate detail, but meshing techniques and the effect of mesh density and element selection on the predicted stresses and deformations in bone were not addressed (qualitatively or quantitatively). This may disappoint a reader who was hoping to use this chapter as a practical, rather than a theoretical guide for model development. A second drawback relates to the discussion on models at the trabecular levels, where generic models of the trabecular architecture are ignored. Generic modeling of trabecular bone, which utilizes the theory of cellular solid mechanics, is a complementary modeling approach to specimen-specific (micro-CT or micro-MR image based) modeling. Generic models allow to study the mechanics of 'typical' trabecular bone samples [6,7], as opposed to specimen-specific models which may include abnormalities or anatomical variations that are specific to the studied specimens [7]. The concluding chapter in the last section concerns animal models to study bone, and particularly, osteoporosis. I found this chapter to be extremely useful for experimentalists who weigh alternative models for an experimental design of an animal study of osteoporosis.
Having considered the points of strength and weakness in the different sections of this book as discussed above, I certainly recommend individual researchers and laboratories who deal with bone studies to hold a copy of this book. It should be noted that for those investigators focused on biomechanics of bone, it is not a substitute for the classics "Bone Mechanics Handbook" [2] and "Bones" [5], but rather, a complimentary book with particular added value in biology-oriented topics of safety considerations, microscopical techniques and animal model specifications. Bioengineering students, medical physics students and perhaps biology students at the graduate levels will also find this book useful for obtaining insight into the broad field of bone analysis.
Abbreviations
DXA = dual x-ray absorptiometry
CT = computed tomography
QCT = quantitative computed tomography
MRI = magnetic resonance imaging
MR = magnetic resonance
==== Refs
Bland JM Altman DG Statistical methods for assessing agreement between two methods of clinical measurement Lancet 1986 8476 307 310 2868172
Cowin SC Ed Bone Mechanics Handbook, 2001 CRC Press, Boca Raton, FL
Brown SJ Pollintine P Powell DE Davie MW Sharp CA Regional differences in mechanical and material properties of femoral head cancellous bone in health and osteoarthritis Calcif Tissue Int 2002 71 227 234 12170373 10.1007/s00223-001-2102-y
Homminga J McCreadie BR Ciarelli TE Weinans H Goldstein SA Huiskes R Cancellous bone mechanical properties from normals and patients with hip fractures differ on the structure level, not on the bone hard tissue level Bone 2002 30 759 764 11996916 10.1016/S8756-3282(02)00693-2
Currey JD Bones: Structure and Mechanics, 2002 Princeton University Press, Princeton, NJ
Kim HS Al-Hassani ST A morphological model of vertebral trabecularbone J Biomech 2002 35 1101 1114 12126669 10.1016/S0021-9290(02)00053-2
Dagan D Be'ery M Gefen A Single-trabecula building-block for large-scale finite element models of cancellous bone Medical & Biological Engineering & Computing 2004 42 549 556 15320466
| 0 | PMC1173125 | CC BY | 2021-01-04 16:37:37 | no | Biomed Eng Online. 2005 Jun 14; 4:37 | utf-8 | Biomed Eng Online | 2,005 | 10.1186/1475-925X-4-37 | oa_comm |
==== Front
Cerebrospinal Fluid ResCerebrospinal Fluid Research1743-8454BioMed Central London 1743-8454-2-31598241110.1186/1743-8454-2-3ResearchExpansion of antibody reactivity in the cerebrospinal fluid of multiple sclerosis patients – follow-up and clinical implications Petereit Hela-Felicitas [email protected] Dirk [email protected] Department of Neurology, University of Cologne, Kerpener Str. 62, D-50924 Cologne, Germany2005 27 6 2005 2 3 3 7 1 2005 27 6 2005 Copyright © 2005 Hela-Felicitas and Reske; licensee BioMed Central Ltd.2005Hela-Felicitas and Reske; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
An intrathecal polyspecific antibody response is a well known finding in multiple sclerosis. However, little is known about the evolution of intrathecal antibodies over time and their impact on the disease progress. Therefore, we focused in this study on the intrathecal polyspecific antibody response in multiple sclerosis.
Methods
Here we present a follow-up study of 70 patients with multiple sclerosis over 1 to 106 months. Serum and cerebrospinal fluid sample pairs were obtained from 1 to 5 consecutive lumbar punctures. CSF cell count, the IgG index, local IgG synthesis, oligoclonal bands and the antibody index for measles, rubella or varicella zoster were calculated. Results were analysed with regard to clinical characteristics of the patients.
Results
Once an intrathecal antibody response was established, it persisted. De novo antibody response against measles virus developed in 7% of the patients between the first and the second spinal tap. In two of seven patients where 5 consecutive CSF samples were available, the intrathecal antibody response expanded from one to three antigens. Furthermore, an intrathecal measles antibody production was associated with a rapid progression of the disease.
Conclusion
These data stress the importance of activated B cells for the disease process and the clinical outcome in multiple sclerosis.
==== Body
Background
An elevated immunoglobulin G (IgG) index and the presence of oligoclonal bands (OCB) in the cerebrospinal fluid (CSF) are a hallmark of multiple sclerosis (MS) [1,2]. Although this finding is not specific for MS, 72 % percent of patients present with an elevated IgG index and even 98 % show an oligoclonal distribution of IgG bands exclusively in the CSF [3,4]. Intrathecal IgG is thought to be the product of B lymphocytes residing in the brain of MS patients after they have crossed the blood brain barrier in an activated state with the help of various co-stimulatory signals [5]. Instead of undergoing apoptosis, the B cells expand clonally within the central nervous system (CNS) giving rise to a persistent antibody production [6]. Despite intense investigations, no single antigen against which the antibodies might be directed has been isolated so far. In contrast, the intrathecal antibody response covers a large number of CNS and non-CNS antigens as well as various pathogens [7-14], including the viral antigens such as measles, rubella and varicella zoster [15]. In up to 96 % of MS patients an intrathecal antibody production against at least one of the three antigens has been found [3,16]. Little is known, however, about the clinical significance of these findings. Previous studies attempting to evaluate the long-term evolution of intrathecal viral antibodies were hampered by technical shortcomings such as few sensitive detection methods and an absence of correction for blood-CSF-barrier disturbance [17,18]. Hence, the findings of these preliminary studies were partially contradictory with regard to the stability of the CSF antibody production [17,18]. Furthermore, no correlation to the clinical course could be demonstrated [17,18]. Here we report the results of a follow-up study on 70 MS patients from which at least two CSF analyses including cell count, IgG index, local IgG synthesis, antibody specific index and oligoclonal bands were available. The clinical implications of the immunological findings are discussed.
Methods
Patients
The study used 70 consecutive patients with definite MS according to the criteria of Poser [19] and a primary relapsing course. All patients had at least two spinal taps, mostly during disease exacerbations. Three lumbar punctures (LP) were performed in 26 patients, four in 12 patients and five in 7 patients. Patients were characterized clinically by age, sex, disease duration, course of the disease and the expanded disability status scale (EDSS), documented at the time of the first LP. Furthermore, the progression index was calculated as the ratio of the EDSS and the disease duration for each patient. Patients with corticosteroid treatment in the last four weeks or with immunomodulatory or immunosuppressive therapy in the last 3 months prior to the first LP were excluded. Cerebrospinal fluid and serum sample pairs were analyzed for cell count in the CSF, oligoclonal bands in serum and CSF, local IgG synthesis, IgG index and antibody index for the following antigens: measles, rubella and varicella zoster virus. We focused only on these specific antigens because of the frequent detection of these antigens within CSF in the case of MS described in prior studies [3].
Cell count
The CSF cell count was determined immediately after LP. For this purpose, 90 μl of CSF were stained with 10 μl dye containing 20% crystal violet solution, 20 % glacial acetic acid and 60% H2O. Cells were enumerated in a Fuchs-Rosenthal counting chamber.
IgG index
The intrathecal IgG production was quantitated by the IgG index. For this purpose, albumin and IgG were measured in matched serum and CSF pairs by nephelometry according to the manufacturer's instructions using commercially available kits (antiserum against human albumin or IgG, respectively) and the BN 100 nephelometer (both Dade Behring GmbH, Marburg, Germany). The IgG index was calculated according to the following formula: (CSF IgG × serum albumin) / (serum IgG × CSF albumin). An IgG index above 0.7 was indicative of an intrathecal IgG synthesis [20].
Local IgG synthesis
We quantitated the local IgG synthesis within the CSF with the help of a method described by Reiber and colleagues [3]. Therefore, we used the following formula: Igloc = [QIg - Qlim (Ig)] × Ig(serum) (Q = quotient CSF: serum). Details of the calculation have been described previously [21].
Oligoclonal bands (OCB)
All samples were analyzed directly after performing the LP without freezing, to minimize post-sampling changes. The presence of oligoclonal bands in the CSF indicated an intrathecal IgG production. For detection of OCB, isoelectric focusing was performed on matched serum and CSF sample pairs. The serum and CSF samples were diluted to the same IgG concentration and run on polyacrylamide gel precoated with ampholytes (pH between 4.5 and 10.0) at increasing voltage according to the manufacturer's instructions (Servalyt Precotes, Serva Electrophoresis GmbH, Heidelberg, Germany). Subsequently, a silver staining with commercially available reagents was done as indicated by the manufacturer (Serva Electrophoresis GmbH). The patterns were interpreted qualitatively by comparing the presence or absence of OCB in the serum and CSF.
Antibody specific index (AI)
During the whole study period, antibody production against measles, rubella and varicella zoster virus was analysed in matched serum and CSF pairs by commercially available, specific enzyme immune assays (Enzygnost by Dade Behring) on an ELISA II processor using the alpha-method (Dade Behring). The AI was calculated according to the following formula: AI = Q spec. / Q lim. with Q spec. = CSF antibodies / serum antibodies and Q lim. being calculated from the CSF / serum albumin ratio according to the Reiber formula [21]. AI larger than 1.4 indicate an intrathecal antibody synthesis against the given antigen.
Statistical analyses
This study was carried out as retrospective case-control study. The mean values of cell count, IgG index, local IgG synthesis and AI were compared for the whole group at the different time points (LP 1 to 5) by non-parametric tests for dependent samples (Friedman test). The percentage of patients positive for OCB or with a positive AI against measles at the 1st and 2nd LP, respectively, was compared with the Fisher's Exact test.
Different clinical subgroups, i.e. those with a high or low EDSS, were analyzed for their mean measles AI with the help of a median split. The mean measles AI in the subgroups was compared with a non-parametric test for independent samples (Mann Whitney U test).
Results
Patient characteristics
A total of 70 patients, 45 women and 25 men, were included in this study. The mean age of the patients was 38 years (range 21 to 67 years). All patients had a primary relapsing course of the disease. The mean disease duration was 4.5 years with a range of one to 37 years. The mean EDSS at study entry was 2.9 (standard deviation SD 1.33). The mean time from the first LP to the second was 15 months with a range from 1 to 81 months. The mean time from the first to the last LP was 22 months (range: 1 to 106 months) in all patients. In 30 patients the range between the first and second LP was at least 12 months. In 24 patients the time between these LPs was less than 6 months. At the occasion of the second LP, 22 patients received an immunomodulatory or immunosuppressive treatment (interferon beta, glatiramer acetate, intravenous immunoglobulin, azathioprine). It has to be stressed that the study population is inhomogeneous. If the LPs were sorted by the follow-up years in which they had been arranged, no new information could be observed. This might be due to the wide range of time between the different LPs in this patient cohort (1 to 106 months). The data are not shown.
Mean IgG index, local IgG synthesis and AI
There was no significant change of the mean IgG index, local IgG synthesis or AI for any of the viral antigens investigated over time (p = 0.414 for IgG index, p = 0.578 for local IgG synthesis, p = 0.673 for measles AI, p = 0.984 for rubella AI, p = 0.941 for varicella zoster AI, Friedman test). The data are summarized in Table 1. In addition, there was no significant change in the mean cell count (p = 0.291, Friedman test, data not shown).
Table 1 Mean and SD of IgG index, local IgG synthesis (Igloc) and antibody index (AI) for measles, rubella and varicella zoster virus at each successive lumbar puncture (LP). The number of patients in each category of serial LP is given. All included patients received at least two serial LPs (first and second). Additional LPs were only obtained in the mentioned number of patients.
LP no. No. of patients with the respective LP IgG index Igloc (mg/L) AI measles AI rubella AI varicella zoster
1. 70 1.3 ± 0.75 33 ± 5,0 3.4 ± 3.29 4.6 ± 7.11 3.6 ± 5.86
2. 70 1.3 ± 1.58 25 ± 4,1 3.5 ± 3.67 4.8 ± 7.67 3.6 ± 5.85
3. 26 1.4 ± 0.99 46 ± 1,1 3.9 ± 5.59 5.4 ± 9.28 4.7 ± 7.28
4. 12 1.2 ± 0.73 28 ± 0,9 2.8 ± 2.09 6.7 ± 14.78 4.4 ± 8.74
5. 7 1.0 ± 0.39 19 ± 4,8 2.1 ± 0.89 1.9 ± 1.28 1.9 ± 1.46
OCB and AI positive patients
As expected, the presence of OCB in the CSF was more sensitive in the detection of an intrathecal IgG production than a positive IgG index [22,23]. For instance, at the 1st LP 94% of patients had positive oligoclonal CSF bands whereas 88% of patients had a positive IgG index. Once positive the OCB bands remained positive during the follow-up. The percentage of patients who were positive for oligoclonal bands in the CSF increased after the 1st LP from 94 to 100 %. Likewise, the relative number of patients with an intrathecal antibody synthesis against measles virus increased significantly over time (Figure 1). No obvious change in rubella and varicella zoster antibody positive patients over time was observed. This significant increase in patients with an intrathecal antibody production against measles was seen in both patient subgroups irrespective of whether or not they were treated with any immunomodulatory treatment mentioned above at the 2nd LP or not (Table 2).
Figure 1 Percentage of patients with an intrathecal antibody synthesis against measles, rubella, and varicella zoster virus at five successive spinal taps (LP, n = 70 for LP 1 and 2, n = 26 for LP 3, n = 12 for LP4 and n = 7 for LP5). There was a significant increase (p <0.05) in patients positive for antibody synthesis against measles virus over time. There were no significant changes in rubella or varicella zoster antibody synthesis.
Table 2 Percentage of patients who had oligoclonal bands in the CSF or a positive AI for measles at the respective lumbar puncture (LP).
1st LP 2nd LP p value
Untreated patients OCB 96 100 not done
measles AI 68 73 0.013
Treated patients OCB 91 100 not done
Measles AI 55 68 0.001
All patients OCB 94 100 not done
Measles AI 64 71 <0.001
Individual long-term follow-up studies
In 7 patients, data from 5 consecutive spinal taps were available. Except for patient no. 57, all data were derived from patients with a secondary progressive course of the disease and collected over a period of 1 to 6 years. Although the AI for the various antigens was not identical, 4 of the patients were stable over time with regard to their status as antibody producers (patients no. 16, 21, 41, 52). Of these patients, one was positive for measles alone, one for measles and rubella, one for all three viral antigens and one patient was antibody negative. The introduction of an immunomodulatory or immunosuppressive treatment at the 2nd LP (interferon beta patients 16, 21 and 41, azathioprine patient no. 52) had no impact on the antibody production. Two additional patients experienced an expansion of their antibody response from one (rubella virus in both cases) to three antigens, despite treatment initiated at the 2nd LP (interferon beta in patient no. 5 and azathioprin in patient no. 34).
Correlation with clinical features
There was no significant difference in the mean AI against measles in patients with high or low disability (p = 0.995, Mann Whitney U test) at the 1st LP. High disability was defined as an EDSS score above the median of 3.0. Furthermore, there was no difference in the mean measles AI in patients with long and short disease duration (median 2 years, p = 0.304). The EDSS scale and disease duration was used to calculate the progression index for each patient. A progression index of more than 1 (median), indicating an increase of at least 1 point on the EDSS scale per year was regarded as high. The mean AI against measles was significantly higher in patients with a high progression index than in those with a low progression index (p = 0.038). In the subgroup with a high progression index the mean measles AI was 4.2, whereas in the low progression index group a mean measles AI of 2.6 was measured. In the low progression index subgroup 53% of patients had an intrathecal antibody production against measles, but almost 74% were positive for measles in the high progression index subgroup. There were no significant differences in the local IgG synthesis when comparing the groups with high or low disability at the 1st LP or the groups with a high or low progression index (p = 0.71, p = 0.962, respectively). In these respective groups, the IgG index was not changed (p = 0.165 high disability group; p = 0.828 high progression index).
Discussion
There are three main findings of our study: i) Once an intrathecal antibody production is established it is maintained over time; ii) For the first time we provide evidence for an expansion of antibody reactivity in the CSF of MS patients; and iii) disease progression and B cell activation may be linked.
Persistent IgG production
In our study patients positive for oligoclonal IgG bands in the CSF remained positive at the follow-up. These findings are in accordance with previous data indicating a clonally stable IgG production in the CSF over long periods [24]. This was true despite the introduction of immunomodulatory or immunosuppressive treatment. In 132 MS patients serial CSF analysis before and after 2 years of interferon beta treatment or placebo failed to reveal differences in the IgG index or OCB in either treatment group [25]. Even after autologous hematopoietic stem cell transplantation identical OCB compared to pre-treatment CSF analysis were found [26,27]. Similarly in our study, there was no effect of treatment on IgG production as documented by the IgG index or on the local IgG synthesis in the CSF. In addition to the well-known finding of a stable OCB production, we demonstrated for the first time that the intrathecal antibody production is stable over time as well. This means, once an intrathecal antibody response against measles, rubella or varizella zoster virus was established it persisted at the follow-up analyses for at least 4 years.
Although persistent IgG and antibody production is a well-known phenomenon in multiple sclerosis, the mechanisms remain unknown. It has been demonstrated recently in an experimental model of B cell migration over the blood brain barrier that activated human B cells readily cross the blood brain barrier with the help of adhesion molecules and chemokines [5]. Longevity of B cells and plasma cells is a common feature [28], and the microenvironment of MS lesions promotes the persistence and activation of B cells [29]. Although repeated antigenic stimulation favors longevity of B cells, persistance of antigen is not required for the survival of B cells [30]. Instead, high expression of anti-apoptotic proteins may be involved in the survival of B cells. Interestingly, increased expression of the apoptosis-inhibitory proteins Bcl-2 and FLIP were detected in B cells of MS patients [6]. Alltogether, microenvironment and antiapoptotic signaling might explain in part the persisting IgG and antibody production in the CSF of MS patients even in the absence of persistent antigen exposure.
Expansion of antigen response
More intriguing was the finding that the number of patients positive for intrathecal OCB increased over time from 94 to 100%. It has been assumed that in early disease activated B cells might not yet have become resident in the CNS. Progression from a monoclonal to an oligoclonal CSF pattern has been reported in multiple sclerosis patients [31]. An increase in CNS clones after the initial stage of the disease has been suggested as a possible explanation. Further evidence for an expanding B cell activity during the course of the disease comes from a CSF analysis in which the prevalence of mature plasma cells was found to be higher in patients with longer disease duration [32].
In our study, an increasing number of patients showed a newly established intrathecal antibody response against measles virus: whereas 64% of patients were positive for measles at the 1st LP, 71% became positive at the 2nd and 86% at the 5th LP. Furthermore, in two out of seven patients with repeated CSF analysis, there was an expansion of the B cell response from one to three viral antigens by the 5th LP. To our knowledge, this is the first follow-up report on intrathecal polyspecific antibody production in multiple sclerosis patients. This follow-up for the first time provides evidence for an expansion of antibody reactivity over time in multiple sclerosis patients. However, this expansion of antibody is in contrast to the stable local IgG synthesis over time.
One possible explanation for a polyspecific intrathecal antibody production might be a bystander activation of B cells with a given antibody reactivity. This is possible in the presence or absence of T cells. If certain cytokines -namely tumor necrosis factor alpha- is present, IgG secretion by activated B cells may occur even in the absence of T cells [33]. Why preferentially measles, rubella, varicella zoster and to a lesser extent other virus reactive B cells become activated during the disease process remains unclear.
Association between B cell activity and clinical aspects of MS
Although the evidence of B cell activity in the CNS is a common feature in MS, its clinical significance remains to be elucidated. Early studies on fluctuations in the CSF antibody production failed to show an association between antibody titers and the clinical course, possibly due to methodological shortcomings [17,18]. In contrast, a recent publication revealed an association between a very high IgG index and a rapidly progressing course of the disease [34]. Further evidence for an impact of B cell products on disease severity comes from a publication by Villar and colleague. They found an intrathecal IgM synthesis to be associated with a worse clinical outcome [35]. Accordingly, a predominance of B cells over T cells and macrophages in the CSF has been shown to be associated with a more rapid disease progression, but not with a longer disease duration or a higher disability score [36]. Interestingly, when our patients were divided into two subgroups according to the rate of disease progression, there were more measles positive patients in the rapidly progressive subgroup. Furthermore, the AI for measles was significantly higher in those with a rapid progression of disability.
Conclusion
In summary, our data indicate that once an intrathecal antibody production has been established it is stable over time. Furthermore, an expansion in antibody specifity occurred in a proportion of patients. The presented data support the hypothesis that a strong B cell activation is associated with a worse clinical outcome in MS.
List of abbreviations
AI – antibody specific index
CNS – central nervous system
CSF – cerebrospinal fluid
EDSS – expanded disability status scale
Ig – immunoglobulin
LP – lumar pucture
MS – multiple sclerosis
OCB – oligoclonal bands
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
H-FP gave the idea of this study and participated in the design of the study. The statistical analysis and the design of the study was performed by DR. Both authors read and approved the final manuscript.
==== Refs
Laterre EC Collewaert A Heremans JF Sfaello Z Electrophoretic morphology of gamma globulins in cerebrospinal fluid of multiple sclerosis and other diseases of the nervous system Neurology 1970 20 982 90 4097237
Link H Muller R Immunoglobulins in multiple sclerosis and infections of the nervous system Arch Neurol 1971 25 326 44 4999855
Reiber H Ungefehr S Jacobi C The intrathecal, polyspecific and oligoclonal immune response in multiple sclerosis Mult Scler 1998 4 111 7 9762657 10.1191/135245898678909448
Wurster U Zettl UK, Lehmitz R, Mix E Elektrophoreseverfahren Klinische Liquordiagnostik 2003 Berlin: De Gruyter Verlag 207 36
Alter A Duddy M Hebert S Determinants of human B cell migration accross brain endothelial cells J Immunol 2003 170 4497 505 12707326
Seidi OA Sharief MK The expression of apoptosis-regulatory proteins in B lymphocytes from patients with multiple sclerosis J Neuroimmunol 2002 130 202 10 12225903 10.1016/S0165-5728(02)00222-9
Cross AH Trotter JL Lyons JA B cells and antibodies in CNS demyelinating disease J Neuroimmunol 2001 112 1 14 11108928 10.1016/S0165-5728(00)00409-4
Walsh MJ Murray JM Dual implication of 2',3'-cyclic nucleotide 3' phosphodiesterase as major autoantigen and C3 Complement-binding protein in the pathogenesis of multiple sclerosis J Clin Invest 1998 101 1923 31 9576757
Sellebjerg F Jensen CV Christiansen M Intrathecal IgG synthesis and autoantibody-secreting cells in multiple sclerosis J Neuroimmunol 2000 108 207 15 10900355 10.1016/S0165-5728(00)00292-7
Xiao BG Linington C Link H Antibodies to myelin-oligodendrocyte glycoprotein in cerebrospinal fluid from patients with multiple sclerosis and controls J Neuroimmunol 1991 31 91 6 1991822 10.1016/0165-5728(91)90014-X
Warren KG Catz I Relative frequency of autoantibodies to myelin basic protein and proteolipid protein in optic neuritis and multiple sclerosis cerebrospinal fluid J Neurol Sci 1994 121 66 73 7510787 10.1016/0022-510X(94)90158-9
Genain CP Canella B Hauser SL Raine CS Identification of autoantibodies associated with myelin damage in multiple sclerosis Nat Med 1999 5 170 5 9930864 10.1038/5532
Williamson RA Burgoon MP Owens GP Anti-DNA antibodies are a major component of the intrathecal B cell response in multiple sclerosis PNAS 2001 98 1793 8 11172030 10.1073/pnas.031567598
Sindic CJ Monteyne P Laterre EC The intrathecal synthesis of virus-specific oligoclonal IgG in multiple sclerosis J Neuroimmunol 1994 54 75 80 7523446 10.1016/0165-5728(94)90233-X
Felgenhauer K Reiber H The diagnostic significance of antibody specificity indices in multiple sclerosis and herpes virus induced diseases of the nervous system Clin Investig 1992 70 28 37 1318123 10.1007/BF00422934
Felgenhauer K Beuche W Labordiagnostik neurologischer Erkrankungen 1999 Stuttgart: Thieme Verlag
Reunanen M Arstila P Hakkarainen H Nikoskelainen J Salmi A Panelius M A longitudinal study on antibodies to measles and rubella viruses in patients with multiple sclerosis. A preliminary report Acta Neurol Scand 1976 54 366 70 973556
Arnadottir T Reunanen M Meurman O Salmi A Panelius M Halonen P Measles and rubella virus antibodies in patients with multiple sclerosis. A longitudinal study of serum and CSF specimens by radioimmunoassay Arch Neurol 1979 36 261 5 444095
Poser CM Paty DW Scheinberg L New diagnostic criteria for multiple sclerosis: Guidelines for research protocols Ann Neurol 1983 13 227 31 6847134 10.1002/ana.410130302
Reiber H Zettl UK, Lehmitz R, Mix E Quantitative Proteindiagnostik, Quotientendiagramme und krankheitsbezogene Datenmuster Klinische Liquordiagnostik 2003 Berlin: De Gruyter 177 200
Reiber H External quality assessment in clinical neurochemistry: survey of analysis for cerebrospinal fluid (CSF) proteins based on CSF/serum quotients Clin Chem 1995 41 256 63 7874779
Reiber H Cerebrospinal fluid – physiology, analysis and interpretation of protein patterns for diagnosis of neurological diseases Mult Scler 1998 4 99 107 9762655 10.1191/135245898678909439
Lunding J Midgard R Vedeler CA Oligoclonal bands in cerebrospinal fluid: a comparative study of isoelectric focusing, agarose gel electrophoresis and IgG index Acta Neurol Scand 2000 102 322 5 11083510 10.1034/j.1600-0404.2000.102005322.x
Walsh MJ Tourtelotte WW Temporal invariance and clonal uniformity of brain and cerebrospinal IgG, IgA, and IgM in multiple sclerosis J Exp Med 1986 163 41 53 3941297 10.1084/jem.163.1.41
Rudick RA Cookfair DL Simonian NA Cerebrospinal fluid abnormalities in a phase III trial of Avonex (IFNβ-1a) for relapsing multiple sclerosis J Neuroimmunol 1999 93 8 14 10378864 10.1016/S0165-5728(98)00174-X
Saiz A Carreras E Berenguer J MRI and CSF oligoclonal bands after autologous hematopoietic stem cell transplantation in MS Neurology 2001 56 1084 9 11320183
Openshaw H Lund BT Kashyap A Peripheral blood stem cell transplantation in multiple sclerosis with busulfan and cyclophosphamide conditioning: report of toxicity and immunological monitoring Biol Blood Marrow Transplant 2000 6 563 75 11071262
McHeyzer-Williams MG Ahmed R B cell memory and the long-lived plasma cell Curr Opinion Immunol 1999 11 172 9 10.1016/S0952-7915(99)80029-6
Archelos JJ Storch MK Hartung HP The role of B cells and autoantibodies in multiple sclerosis Ann Neurol 2000 47 694 706 10852535 10.1002/1531-8249(200006)47:6<694::AID-ANA2>3.0.CO;2-W
Zubler RH Naïve and memory B cells in T-cell-dependent and T-independent responses Springer Semin Immunopathol 2001 23 405 19 11826617 10.1007/s281-001-8167-7
Davies G Keir G Thompson EJ Giovannoni G The clinical significance of an intrathecal monoclonal immunoglobulin band. A follow-up study Neurology 2003 60 1163 6 12682325
Zeman D Adam P Kalistova H Sobek O Andel J Andel M Cerebrospinal fluid cytologc findings in multiple sclerosis. A comparison between patient subgroups Acta Cytol 2001 45 51 59 11213505
Hodgkin PD Basten A B cell activation, tolerance and antigen-presenting function Curr Opin Immunol 1995 7 121 9 7772275 10.1016/0952-7915(95)80037-9
Izquierdo G Angulo S Garcia-Moreno JM Intrathecal IgG synthesis: marker of progression in multiple sclerosis patients Acta Neurol Scand 2002 105 158 63 11886357 10.1034/j.1600-0404.2002.1o009.x
Villar LM Masjuan J González-Porqué P Intrathecal IgM synthesis is a prognostic factor in multiple sclerosis Ann Neurol 2003 53 222 226 12557289 10.1002/ana.10441
Cepok S Jacobsen M Schock S Patterns of cerebrospinal fluid pathology correlate with disease progression in multiple sclerosis Brain 2001 124 2169 76 11673319 10.1093/brain/124.11.2169
| 15982411 | PMC1173126 | CC BY | 2021-01-04 16:37:38 | no | Cerebrospinal Fluid Res. 2005 Jun 27; 2:3 | utf-8 | Cerebrospinal Fluid Res | 2,005 | 10.1186/1743-8454-2-3 | oa_comm |
==== Front
Clin Mol AllergyClinical and molecular allergy : CMA1476-7961BioMed Central London 1476-7961-3-61590720510.1186/1476-7961-3-6ResearchResearch Upregulation of CD23 (FcεRII) Expression in Human Airway Smooth Muscle Cells (huASMC) in Response to IL-4, GM-CSF, and IL-4/GM-CSF Belleau Joseph T [email protected] Radha K [email protected] Holly M [email protected] D Betty [email protected] Department of Pediatrics, Children's Foundation Research Center at the Le Bonheur Children's Medical Center, University of Tennessee Health Science Center, 50 North Dunlap Street, Rm401, WPT, Memphis, TN 38103, USA2005 20 5 2005 3 6 6 30 8 2004 20 5 2005 Copyright © 2005 Belleau et al; licensee BioMed Central Ltd.2005Belleau et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Airway smooth muscle cells play a key role in remodeling that contributes to airway hyperreactivity. Airway smooth muscle remodeling includes hypertrophy and hyperplasia. It has been previously shown that the expression of CD23 on ASMC in rabbits can be induced by the IgE component of the atopic serum. We examined if other components of atopic serum are capable of inducing CD23 expression independent of IgE.
Methods
Serum starved huASMC were stimulated with either IL-4, GM-CSF, IL-13, IL-5, PGD2, LTD4, tryptase or a combination of IL-4, IL-5, IL-13 each with GM-CSF for a period of 24 h. CD23 expression was analyzed by flow cytometry, western blot, and indirect immunofluorescence.
Results
The CD23 protein expression was upregulated in huASMC in response to IL-4, GM-CSF, and IL-4/GM-CSF. The percentage of cells with increased fluorescence intensity above the control was 25.1 ± 4.2% (IL-4), 15.6 ± 2.7% (GM-CSF) and 32.9 ± 13.9% (IL-4/GMCSF combination)(n = 3). The protein content of IL-4/GMCSF stimulated cells was significantly elevated. Expression of CD23 in response to IL-4, GM-CSF, IL-4/GM-CSF was accompanied by changes in cell morphology including depolymerization of isoactin fibers, cell spreading, and membrane ruffling. Western blot revealed abundant expression of the IL-4Rα and a low level expression of IL-2Rγc in huASMC. Stimulation with IL-4 resulted in the phosphorylation of STAT-6 and an increase in the expression of the IL-2Rγc.
Conclusion
CD23 on huASMC is upregulated by IL-4, GM-CSF, and IL-4/GM-CSF. The expression of CD23 is accompanied by an increase in cell volume and an increase in protein content per cell, suggesting hypertrophy. Upregulation of CD23 by IL-4/GM-CSF results in phenotypic changes in huASMC that could play a role in cell migration or a change in the synthetic function of the cells. Upregulation of CD23 in huASMC by IL-4 and GM-CSF can contribute to changes in huASMC and may provide an avenue for new therapeutic options in asthma targeting ASMC.
==== Body
Background
Chronic inflammation and airway smooth muscle dysfunction are consistent features of asthma responsible for disease progression and airway remodeling [1]. The increase in bronchial smooth muscle, both hypertrophy [2] and hyperplasia [3], plays a critical role in the development of airway hyperreactivity (AHR), the hallmark of asthma. Airway smooth muscle cells (ASMC) may also play a secretory or immunomodulatory role by producing pro-inflammatory cytokines, chemokines, polypeptide growth factors, extracellular matrix proteins, cell adhesion receptors, and co-stimulatory molecules, which perpetuate submucosal inflammation [4,5]. These mediators may act on the ASM itself in an autocrine manner as well to further contribute to the asthma phenotype [6]. Therefore, smooth muscle itself may be capable of initiating and maintaining airway inflammation. Also, ASMC have been shown to undergo cell migration, which could contribute to airway remodeling [7]. Thus, regulation of airway smooth muscle hypertrophy and migration may be a new target for treatment of asthma [7,8].
It is well known that IgE plays a critical role in the pathogenesis of asthma in the early and late phases by interacting with its two receptors, the high affinity receptor (FcεRI) and the low affinity receptor (FcεRII) [9]. IgE plays a key role in bronchial hyperresponsiveness and smooth muscle hyperreactivity [8]. Crosslinking of the high affinity IgE receptor (FcεRI) on mast cells leads to cellular degranulation and the release of various proinflammatory mediators and cytokines contributing to bronchoconstriction. The low affinity IgE receptor (CD23) (FcεRII) has been identified on B cells, monocytes, follicular dendritic cells, Langerhan's cells, eosinophils, and platelets [10]. Upregulation of the CD23 receptor is thought to increase allergic responses in the bronchial mucosa through the enhancement of antigen uptake and presentation [8]. The receptor has two isoforms that differ only in their cytoplasmic domains [11]. CD23a is constitutively expressed on B cells and is associated with endocytosis of IgE coated particles, and CD23b is induced by IL-4 and is also found on non- B cells such as T cells, Langerhan's cells, monocytes, macrophages, platelets, and eosinophils [12,13]. IL-4 causes CD23 induction on B cells through CD40 [12]. CD23b mediates phagocytosis of soluble IgE complexes. An autocatalytic process involving cleavage of membrane bound CD23 by a matrix metalloprotease yields a series of soluble elements (sCD23) which increase IgE production via the CD21 receptor on B cells [13,14].
The CD23 receptor has been shown to be upregulated on monocytes and alveolar macrophages in a T helper cell type 2 (TH2) environment and may contribute to chronic inflammation in asthma through this mechanism [15]. It has been shown that IL-4 and GM-CSF induce CD23 expression on monocytes, and GM-CSF primes monocytes for cellular activation and secretion of IL-1 upon subsequent exposure to IgE-containing immune complexes [8]. CD23 is also involved in antigen presentation to B cells as well as cellular interactions between B and T cells [12].
In previous studies, Hakonarson et al. [16] demonstrated the expression of CD23 (FcεRII) messages and a low level of the protein in airway smooth muscle cells. In two patients who died of status asthmaticus, CD23 expression was also markedly upregulated on ASMC. The CD23 expression was inducible with human atopic sera or IgE immune complexes in naïve (control) ASMC, and this upregulation was blocked when pretreated with anti-CD23 blocking antibody. The authors concluded that IgE coupled activation of CD23 contributes largely to its upregulation [5,14]. In a corresponding experiment with rabbit ASMC subjected to control and atopic serum, they were able to demonstrate, through Western blot analysis, a markedly enhanced expression of CD23 in the ASMC sensitized with atopic serum or IgE immune complexes. They were able to achieve significant inhibition of upregulation by pretreatment with anti-CD23 mAb. They hypothesized that IgE was responsible for the upregulation of the low affinity IgE receptor [17]. Hakonarson, et al. have also demonstrated that ASMC in vitro exposed to human atopic sera results in an initial increase in TH2 cytokines including IL-5 and GM-CSF followed hours later by production of IL-1 and TH1 cytokines [18,19]. Recently, phase I trials have been completed on IDEC-152, an IgG1 anti-CD23 antibody, for patients with mild to moderate persistent asthma. The drug was well tolerated by participants, and a dose-dependent decrease in mean IgE values was reported [20].
T helper cell type 2 (TH2) mediated inflammatory cytokines, such as IL-4, IL-13, and IL-5, as well as other enzymes and chemokines are active in the asthmatic patient. GM-CSF has been shown to be involved in asthma pathogenesis and in vivo can induce TH2 differentiation independent of IL-4 [21]. Tryptase and prostagladin D2 (PGD2) were chosen as major mast cell mediators, and more recently the PGD2 receptor gene (PTGDR) has been shown to be an asthma susceptibility gene [22-24]. It is possible that many factors are responsible for the upregulation of the low affinity IgE receptor in addition to and independent of IgE. The purpose of this study was to identify specific mediators released in the asthmatic patient that are responsible for the upregulation of CD23 on human airway smooth muscle cells independent of IgE.
Methods
Cell culture and flow cytometry
Alpha-smooth muscle isoactin positive Human ASMC (Cambrex, Walkersville, MD) in T-75 flasks were starved for 24 hours in 0.1% (vol/vol) fetal bovine serum (FBS) containing medium M199 (Cellgro, Herndon, VA) supplemented with 1% (vol/vol) antibiotic/antimycotic solution (Sigma Chemical Co., St Louis, MO). The cells were then stimulated with either vehicle (bovine serum albumin, BSA, vehicle for cytokines (1 mg/ml), in M199; ethanol (EtOH), vehicle for LTD4 (6% final concentration) and PGD2 (0.001–0.01% final concentration); M199, vehicle for tryptase), an individual mediator, or a mediator in combination with GM-CSF at their optimum concentrations for 24 hours. The doses of cytokines used were up to four time ED50 including: IL-4 (0.04–1 nM), GM-CSF (0.07–0.8 nM), IL-13 (0.4 nM), IL-5 (0.01–0.07 nM), IL-13 (0.3–2.2 nM), PGD2 (1–10 μM), LTD4 (1–10 μM), tryptase (30 nM, a concentration sufficient to induce ASMC proliferation) (Sigma). Dose ranging studies were performed to determine the optimum concentration of IL-4 and GM-CSF on the expression of CD23, and the doses chosen were IL-4 (0.5 nM) and GM-CSF (0.4 nM) (Figure 1). All cytokines were obtained from R & D Systems Inc. Minneapolis, MN except GM-CSF which was obtained from Sigma. The cells were then harvested with a soft rubber edged scraper, centrifuged for 5 minutes at 1000 rpm (200 g), washed and resuspended in 1% BSA in phosphate buffered saline (PBS) and fixed with 70% ETOH. After washing twice more, the cells were resuspended in 1% BSA in PBS. Finally, they were filtered through a 40 μm nylon mesh to obtain single cell suspension and stained with (20 μl) of PE (phycoerythrin)-CD23 (EBVCS-5, BD Biosciences, San Jose, CA) or PE-mouse IgG1 for 15 minutes in the dark to facilitate staining for flow cytometry.
Figure 1 Upregulation of CD23 by IL-4 and GM-CSF. Dose-ranging studies were performed to determine the optimum concentrations of IL-4 and GM-CSF. Alpha-smooth muscle isoactin positive Human ASMC (Clonetics) in T-75 flasks were starved for 24 h in 0.1% FBS containing medium M199. The cells were then stimulated with BSA (1 μg/ml), IL-4 (0.125. 0.25, 0.5, or 1.0 nM) or GM-CSF (0.1, 0.2, 0.4, or 0.8 nM) for 24 h. The cell lysates in RIPA buffer were subjected to western blot analysis for CD23. Mouse anti-human CD23 monoclonal antibody (clone M-L233, BD Biosciences, 1 μg/5 ml) was used as the primary antibody and anti-mouse horseradish peroxidase linked antibody as the secondary antibody (Amersham). The immunoreactive protein bands were detected by enhanced chemiluminescence light (ECL) (Amersham).
Protein analysis
A commercially available bicinchoninic acid (BCA) kit (Pierce, Rockford, IL) was used for protein analysis according to the manufacturer's instructions. The optical densities were read using a Bio-Kinetics EL-312 Microplate reader.
Indirect immunofluorescence
Indirect immunofluorescence stainings were performed with anti-smooth muscle-α isoactin antibody (Sigma) and anti-human CD23 antibody (M-L233, 1 μg/ml, BD Biosciences), which are specific monoclonal antibodies and either a FITC or TRITC fluorochrome, conjugated second antibody. Fixed huASMC were incubated with the above antibodies diluted in PBS with 3% BSA for 60 min at room temperature. The cells were then washed three times with PBS for 10 minutes for each wash. Non-specific binding was blocked by incubating cells with 3% BSA in PBS for 60 minutes. The blocking solution was then removed and cells were incubated with FITC- or TRITC- fluorochrome conjugated antibody for 45 minutes in the dark to facilitate staining. Cells were then washed with PBS three times. Finally, one drop of Fluoromount-G (Southern Biotechnology Inc., Birmingham, AL) was added.
Western blot
Standard Western blot analyses were performed to detect anti-STAT6 (1:500, Calbiochem, San Diego, CA) polyclonal rabbit, anti-p-STAT-6 (1:500, Calbiochem) polyclonal rabbit. Human ASMC lysates in radio-immunoprecipitation assay (RIPA) buffer were transferred onto Hybond-ECL nitrocellulose membranes and were immunoblotted with monoclonal anti-human CD23 (1:500 dilution, clone M-L233, 1 μg/5 ml, BD Biosciences), polyclonal anti-IL-4Rα (1:500 dilution, Santa Cruz), monoclonal anti-IL-2Rγc (1:250 dilution, R&D Systems, Inc.). The nitrocellulose membranes were incubated with a 1:1,000 dilution of anti-rabbit or anti-mouse horseradish peroxidase linked whole antibody (Amersham, Piscataway, NJ) in PBS-T for 1 hour at room temperature. Paxillin monoclonal antibody (1:500 dilution, Transduction Laboratories) was used as a positive isotype control for CD23, and fibronectin polyclonal antibody (1:250, Sigma) was used as a positive control for the remaining antibodies. The immunoreactive protein bands were detected by enhanced chemiluminescence light (ECL) (Amersham).
Statistical analysis
Data were analyzed with Prism 4 software (GraphPad, San Diego, CA). One-way analysis of variance (ANOVA) was used. Results are expressed as mean ± SEM. A P value less than 0.05 was considered statistically significant.
Results
CD23 protein expression is upregulated in huASMC by IL-4, GM-CSF, or IL-4/GM-CSF
Previous studies have shown that IgE immune complexes in atopic serum caused an increase in CD23 expression in ASMC [16]. To determine if other humoral factors in atopic serum effect CD23 expression in human ASMC, we have tested the effect of the relevant cytokines, arachidonic acid metabolites, and the mast cell enzyme tryptase. Flow cytometry was performed to evaluate differences in cell populations after stimulation of the huASMC for 24 hours with either individual mediators IL-4 (0.5 nM), GM-CSF (0.4 nM), IL-13 (0.4 nM), IL-5 (0.4 nM), PGD2 (10 μM), LTD4 (10 μM), tryptase (30 nM) or a combination of IL-4, IL-5, and IL-13 each with GM-CSF. Within the huASMC stimulated by IL-4, GM-CSF or the combination of IL-4/GM-CSF, two populations of cells were detected distinguishable by cell size. While the smaller cells did not show a significant expression of CD23, many of the larger cells showed increased expression of CD23. In the example in Figure 2, 66% of the larger cells (gate D) showed an increase in cell expression of CD23 when compared to the controls. As stated previously, the functions of ASMC are heterogeneous including proliferation and synthesis. Previous studies have shown, on flow cytometry of ASMC stimulated in vitro with IL-1β and TNF-α, only 20–60% of ASMC produce GM-CSF. The ASMC producing GM-CSF include some which also have increased proliferative properties. This suggests that considerable heterogeneity exists in the phenotypic expression of the ASMC in culture [25].
Figure 2 Upregulation of CD23 by IL-4, GM-CSF and IL-4/GM-CSF. Alpha-smooth muscle isoactin positive Human ASMC (Clonetics) in T-75 flasks were starved for 24 h in 0.1% FBS containing medium M199. The cells were then stimulated with IL-4 (0.5 nM)/GM-CSF (0.4 nM) for 24 h. The FACS analysis showed that the smaller cells passed through Gate A and larger cells passed through Gate D. Background noise was eliminated using the BSA-stimulated control cells that were labeled with PE-anti-CD23 (EBVCS), represented by C in Gate A, and F in Gate D. The FACS results of a representative experiment showed 66% of the larger cells (Gate D) had an increase in cell expression of CD23 when compared to the controls.
In addition to the combination of IL-4/GM-CSF inducing increased expression of CD23, both IL-4 and GM-CSF alone independently increased the expression of CD23 in huASMC. The percentage of cells with increased fluorescence intensity above the control was 25.1 ± 4.2% (IL-4), 15.6 ± 2.7% (GM-CSF) and 32.9 ± 13.9% (IL-4/GM-CSF combination). On the other hand, IL-5, IL-13, cysteinyl leukotrienes, and tryptase did not induce CD23 expression (Table 1).
Table 1 Il-4, GM-CSF, and IL-4/GM-CSF Increase CD23 Expression on ASMC (n = 3)
Cytokine (24 hours) #Cells in Gate D
(n = 3) %Cells with Increased CD23
Expression Above the Control
BSA (1 μg/ml) 1,343 ± 122 0
IL-4 (0.5 nM) 1,413 ± 197 25.1 ± 4.2*
GM-CSF (0.4 nM) 1,346 ± 243 15.6 ± 2.7*
IL-4/GM-CSF (0.4/0.5 nM) 1,324 203 32.9 ± 13.9*
IL-5 (0.4 nM) 1,130 ± 251 0
IL-13 (0.4 nM) 1,316 ± 269 0
PGD2 (1 μM) 1,521 ± 123 0
PGD2 (10 μM) 1,159 ± 204 0
LTD4 (10 μM) 2,037 ± 375 0
Ethanol (6% vol/vol) 2,507 ± 200 0
Tryptase (10 μM) 2,385 ne ± 405 0
Alpha-smooth muscle isoactin positive Human ASMC (Clonetics) in T-75 flasks were starved for 24 h in 0.1% FBS containing medium M199. The cells were then stimulated with BSA (1 μg/ml), IL-4 (0.5 nM), GM-CSF (0.4 nM), IL-4 (0.5 nM)/GM-CSF (0.4 nM), IL-13 (0.4 nM), IL-5 (0.4 nM), PGD2 (10 μM), LTD4 (10 μM), tryptase (30 nM) for 24 h. Results are mean ± SEM of the percentage of cells with an increased fluorescence intensity above the control (n = 3). Control values: BSA-stimulated, PE-anti-CD23 labeled, 10.9 ± 1.4 %; BSA-stimulated, PE-mouse IgG1, non-immune, 0.5 ± 0.1 % (n = 3). *denotes significant increase in CD23 expression above the BSA control value.
Expression of CD23 in response to IL-4, GM-CSF, IL-4/GM-CSF is accompanied by changes in huASMC morphology
Western blot analysis of huASMC stimulated with IL-4, GM-CSF, or Il-4/GM-CSF for 24 h showed an increase in CD23 expression compared to BSA vehicle control (Figure 3). Indirect immunofluorescence was used also to identify any morphological changes associated with the cytokine stimulation and upregulation of CD23 (Figure 4A–D). Those cells stimulated with the combination of IL-4/GM-CSF demonstrated CD23 expression along with changes in cell morphology including depolymerization of isoactin fibers, cell spreading, and membrane ruffling (Figure 4B). These changes in phenotype are consistent with flow cytometry results in that the larger cells expressed CD23 (Figure 4D). In contrast, the control BSA stimulated population showed no changes in cell cytoskeletal structure and morphology (Figure 4A) or specific staining for CD23 (Figure 4C).
Figure 3 Western blot analysis of CD23 after stimulation of IL-4, GM-CSF, IL-4/GM-CSF. Alpha-smooth muscle isoactin positive huASMC (Clonetics) in T-75 flasks were starved for 24 h in 0.1% FBS containing medium M199. The cells were then stimulated with BSA (1 μg/ml) (vehicle control), IL-4 (0.5 nM), GM-CSF (0.4 nM), or IL-4/GM-CSF (0.5 nM/0.4 nM) for 24 h. The cell lysates in RIPA buffer were subjected to western blot analysis for CD23. Mouse anti-human CD23 monoclonal antibody (clone M-L233, BD Biosciences, 1 μg/5 ml) was used as the primary antibody and anti-mouse horseradish peroxidase linked antibody as the secondary antibody (Amersham). The immunoreactive protein bands were detected by enhanced chemiluminescence light (ECL) (Amersham). Paxillin mouse monoclonal IgG1 (Transduction Laboratories) was used as an irrelevant isotype control.
Figure 4 Expression of CD23 in response to IL-4/GM-CSF is accompanied by changes in huASMC morphology. Alpha-smooth muscle isoactin positive huASMC (Clonetics) in T-75 flasks were starved for 24 h in 0.1% FBS containing medium M199. The cells were then stimulated with either BSA or IL-4 (0.5 nM)/GM-CSF (0.4 nM) for 24 h, and stained with either anti-smooth muscle-isoactin (A & B) or anti-CD23 antibody (C & D). Those cells stimulated with the combination of IL-4/GM-CSF demonstrated CD23 expression (D) and changes in cell morphology including depolymerization of isoactin fibers, cell spreading, and membrane ruffling (B). Cells stimulated with BSA (vehicle for IL-4/GM-CSF) alone did not increase the expression of CD23 (C) nor changes in phenotype (A). These findings were confirmed by three independent observers.
To confirm activity of protein synthesis, the protein content of the control and the experimental groups of cells were compared using a BCA protein analysis kit. Human ASMC were starved for 24 hours in 0.1% FBS containing medium M199 and then stimulated with BSA (1 μg/mL), IL-4 (0.5 nM), GM-CSF (0.4 nM), or IL-4 (0.5 nM)/GM-CSF (0.4 nM) for 24 hours. The protein content was increased by 19% in the IL-4/GM-CSF treated cells above that of the control (Table 2). The increase in protein concentration with IL-4 alone was not statistically significant.
Table 2 IL-4/GM-CSF Combination Increases Protein Content in huASMC.
Cytokine (nM) mg/106 cells (n = 3)
BSA (vehicle) 1.17 ± 0.08
IL-4 (0.5) 1.18 ± 0.01
GM-CSF 1.12 ± 0.03
IL-4 (0.5)/GM-CSF (0.4) 1.39 ± 0.02 *
Alpha-smooth muscle isoactin positive huASMC (Clonetics) in T-75 flasks were starved for 24 h in 0.1% FBS containing medium M199. The cells were then stimulated with BSA (1 μg/ml)), IL-4 (0.5 nM), GM-CSF (0.4 nM), or IL-4/GM-CSF (0.4/0.5 nM) for 24 h. The cell lysates in RIPA buffer were analyzed for protein content using a commercially available BCA kit (Pierce). The optical density was read using a Bio-Kinetics EL-312 Microplate reader. Results are mean ± SEM (n = 3). *denotes value significantly different from the BSA vehicle treated control.
Stimulation of huASMC with IL-4 induces phosphorylation of STAT-6 and expression of IL-2Rγc
IL-4 binds the IL-4R with high affinity, and signaling through IL-4 causes enhanced expression of IL-4R [21]. The induction of these genes is mediated through signal transduction molecules including signal transducer activator of transcription (STAT-6). The binding of IL-4 to its receptor complex induces the formation of an IL-4 receptor complex which consists of IL-4Rα and the common gamma chain (γc) of the receptors for IL-2, IL-4, IL-7, IL-9, IL-15, and IL-21 [21]. It has not been previously reported that airway smooth muscle cells express the IL-2Rγc, the signaling unit of the IL-4 receptors.
Western blot analysis of IL-4Rα and IL-2Rγc in huASMC lysates showed the presence of these receptor components on huASMC. Figure 5 shows abundant expression of IL-4Rα and a low level expression of IL-2Rγc protein on huASMC. After stimulation of huASMC with IL-4 (0.4 nM) for 24 h, a two fold increase in γc expression was observed compared to the BSA vehicle control (Figure 6).
Figure 5 IL-4Rα and IL-2Rγc Expression in huASMC. A: IL-4Rα and IL-2Rγc expression in huASMC at baseline. Unstarved huASMC lysates were subjected to western blot analysis for IL-4Rα and IL-2Rγc using polyclonal anti-IL-4Rα (1:500 dilution, Santa Cruz), or monoclonal anti-IL-2Rγc (1:125 dilution, R&D Systems, Inc.). The nitrocellulose membranes were incubated with a 1:1,000 dilution of anti-rabbit or anti-mouse horseradish peroxidase linked whole antibody (Amersham). The immunoreactive protein bands were detected by ECL (Amersham). IL-2Rγc is minimally expressed in huASMC while IL-4Rα is expressed abundantly in huASMC.
Figure 6 Upregulation of IL-2Rγc Expression in huASMC by IL-4 and IL-4/GM-CSF. Alpha-smooth muscle isoactin positive Human ASMC (Clonetics) in T-75 flasks were starved for 24 h in 0.1% FBS containing medium M199. The cells were then either stimulated with BSA (vehicle) (1 μg/ml), IL-4 (0.5 nM), GM-CSF (0.4 nM), or IL-4/GM-CSF (0.5 nM/0.4 nM) for 24 hours. The IL-4 and IL-4/GM-CSF stimulated cells had increased IL-2Rγc expression compared to the BSA (vehicle) group. Fibronectin polyclonal rabbit antibody (Sigma) (1:250) was used as an irrelevant isotype control.
To confirm that IL-4 was activating the IL-4Rα during the stimulation of huASMC, we examined the phosphorylation of downstream STAT-6 by western blot. Human ASMC were starved for 24 h and then stimulated with IL-4 (0.4 nM) for fifteen minutes. Results of Western blot revealed an approximately a four fold increase in intensity of the band for phosphorylated-STAT-6 in IL-4 stimulated cells when compared to BSA control (Figure 7). This supports the role of an IL-4 mediated signal transduction pathway involvement in CD23 upregulation in huASMC.
Figure 7 Phosphorylation of STAT-6 by IL-4 and IL-4/GM-CSF in huASMC. Starved huASMC were incubated with either BSA vehicle control (1 μg/ml), IL-4 (0.5 nM), GM-CSF (0.4 nM), or IL-4/GM-CSF (0.5 nM/0.4 nM) for 15 minutes. Standard Western blot analyses were performed to detect STAT-6 and phosphorylated-STAT-6 (p-STAT-6) using a anti-STAT-6 polyclonal rabbit antibody (Calbiochem) and anti-p-STAT-6 polyclonal rabbit antibody (Calbiochem). Anti-rabbit horseradish peroxidase linked antibody was used as the secondary antibody. Protein bands were detected by ECL. STAT-6 was abundantly expressed by all four groups, while p-STAT-6 was only expressed in the IL-4 and IL-4/GM-CSF groups. Fibronectin polyclonal rabbit antibody (Sigma) was used as an irrelevant isotype control and was abundantly expressed in all four groups.
Discussion
In our study, we have demonstrated that CD23, the low affinity IgE receptor, is upregulated on human airway smooth muscle cells by the cytokines IL-4, GM-CSF, and the combination of IL-4/GM-CSF. This upregulation of CD23 by the combination of IL-4 and GM-CSF was accompanied by an increase in cell volume and protein content, cytoskeletal depolymerization, cell spreading and membrane ruffling. Because ASMC require a doubling time of 48 hours, the increase in protein content could not be attributed to an increase in cell number. Also, the increase in cell number in gate D seen with LTD4 was likely secondary to the effects of ethanol (Table 1). Stimulation of huASMC by IL-4 caused an activation of STAT-6 and an increase in γc expression. Collectively, our findings suggest that CD23 expression can be stimulated by IL-4 and GM-CSF cytokines independent of IgE in huASMC and the upregulation of CD23 may play a role in cell migration and hypertrophy.
Previous studies have demonstrated an increase in CD23 expression in alveolar monocytes after stimulation with IL-4 and GM-CSF [10]. In that study, the use of the individual mediators alone did not increase the CD23 levels to that of asthmatic patients suggesting a possible synergistic role between IL-4 and GM-CSF. Our findings are consistent with these in that the combination of IL-4 and GM-CSF was most effective in upregulating CD23 in huASMC. Not all TH2 cytokines are involved in this process; IL-5 (0.4 nM) and IL-13 (0.4 nM) had no effect on CD23 expression. Cysteinyl leukotriene LTD4 (10 μM), prostaglandin PGD2 (10 μM) and tryptase (30 nM) did not induce CD23 expression on huASMC [26].
We evaluated the effect of stimulation of huASMC with IL-4 on phosphorylation of STAT-6 via the IL-4R which would confirm the presence of the receptor in huASMC. STAT-6 is a critical mediator of IL-4 stimulated gene activation, and it is regulated by both tyrosine and serine kinases [27]. It has been shown in a mouse model that STAT-6 binds the CD23a murine promoter, and STAT -/- mice stimulated with IL-4 are unable to upregulate CD23. This suggests STAT-6 is a critical mediator for IL-4 induced upregulation of CD23 [28]. IL-4 along with CD40 mediated signals are responsible for upregulation of CD23 on B cells [14]. In this study, we have confirmed the expression of the IL-4Rα and a low level of common gamma chain in huASMC and that after stimulation of huASMC with IL-4, there was a two fold increase in γc chain expression (Figure 6). Phosphorylation of STAT-6 after stimulation with IL-4 for 15 min confirms that IL-4 has bound and activated the IL-4 receptor complex (Figure 7). It has been shown that the common gamma chain is a functional β chain of the IL-4 receptor complex in certain cells [27], and our data suggest that this is the case in huASMC. Interestingly, IL-13 (4 nM, a concentration sufficient to simulate huASMC proliferation, unpublished observation) did not upregulate CD23. For proliferation of ASMC by IL-13, IL-4Rα and IL-13Rα1 are required for signal transduction and downstream activation of p44/42 extracellular regulated kinases (ERK, unpublished data). Apparently, IL-4Rα and IL-13Rα1 engagement is not sufficient for CD23 expression, further supporting the role of γc chain in CD23 expression by IL-4. The signs of signal transduction in response to IL-4, and the increase in protein content of the cell in response to IL-4 and GM-CSF combination (Table 2) represent activation of transcription and translation of CD23 in this case. Coupling of GM-CSF and its receptor complex is known to activate ERK that may have contributed to the synergistic effect of GM-CSF on CD23 expression.
CD23 expression was associated with changes in cell morphology including depolymerization of isoactin fibers, cell spreading, and membrane ruffling (Figure 4B &4D). Actin in ASMC is in a dynamic state and undergoes polymerization-depolymerization during the contraction-relaxation cycle [29,30]. Membrane ruffling and cell migration involve signaling pathways including PI3-kinase, Rac and other Rho family G protein members in a variety of cell types, including vascular smooth muscle cells. Rac has an essential role in cell migration and regulation of the actin cytoskeleton [31,32]. Moreover, ASMC are capable of switching their phenotypes from contractile to synthetic phenotype that is mediated by Rho kinases [32,33].
In summary, we have demonstrated that the low affinity IgE receptor can be induced on huASMC by specific cytokines including IL-4, GM-CSF, and the combination of IL-4/GM-CSF. The combination of IL-4/GM-CSF also induced morphologic changes in the ASMC that may contribute to the synthetic function or migration. In addition, IL-4 and IL-4/GM-CSF stimulation of huASMC increased the protein content of the cell, suggesting hypertrophy.
Conclusion
T helper type 2 cytokines including IL-4 have major role in asthma pathogenesis. GM-CSF is a hemopoetic growth factor, mostly released by activated monocytes and T cells. Additional sources of GM-CSF include epithelium of asthmatic airways [34] and human airway smooth muscle cells [6,35]. Therefore, the effect of GM-CSF on CD23 expression can be both via paracrine and autocrine mechanisms. Previous studies by Hakonarson et al. [16,17] have shown that upregulation of the CD23 receptor has been associated with proasthmatic changes in agonist-mediated ASM constrictor and relaxant responsiveness. Our study suggests that CD23 expression is associated with elements of hypertrophy (i.e. an increase in cell volume and protein content), thus consistent with their findings. Inhaled corticosteroids, the mainstay in treatment of asthma, effectively reduce inflammation and remodeling of the epithelium and basement membrane. However, no agents have been proven effective in reducing smooth muscle mass in asthmatic patients. Recent study results on anti-CD23 therapy showed decrease in serum IgE. Further studies to intervene the upregulation of CD23 expression by cytokines IL-4 and GM-CSF may open a new avenue to target smooth muscle hypertrophy, an important element of severe asthma [2].
Competing interests
The author(s) declare that they have no competative intrests.
List of abbreviations
huASMC: Human airway smooth muscle cells
FceRI: High-affinity receptor for IgE
FceRII (CD23): Low-affinity receptor for IgE
AHR: Airway hyperreactivity
PGD2: Prostaglandin D2
LTD4: Leukotriene D4
PE: Phycoerythrin
FBS: Fetal bovine serum
BSA: Bovine serum albumin
PBS: Phosphate bufferred saline
BCA: Bicinchoninic acid
FITC: Fluorescein Isothiocyanate
TRITC: Tetramethyl Rhodamine Iso-Thiocyanate
RIPA: Radio-immunoprecipitation assay
ECL: Enhanced chemiluminescence light
Rα: Receptor alpha
γc: Common gamma chain
FACS: Fluorescent Activated Cell Sorter
STAT: Signal Transducer Activator of Transcription
TH2: T helper cell type 2
ERK: Extracellular regulated kinases
Authors' contributions
JTB participated in designing experiments and performing CD23 analysis by flow cytometry.
RKG carried out flow cytometry, immunofluorescence studies, and drafted the manuscript.
HM carried out western blot analyses.
DBL supervised all aspects of the project.
All authors have read and approved the final manuscript.
Acknowledgements
This work was supported in part by the grant from the Le Bonheur Children's Medical Center, NIH-HL56812, Children's Foundation Research Center, Molecular Resource Center, and American Academy of Allergy, Asthma and Immunology. The authors would like thank Jan Aldrich for her technical assistance.
==== Refs
Vignola AM Effects of inhaled corticosteroids, leukotriene receptor antagonists, or both, plus long-acting beta2-agonists on asthma pathophysiology: a review of evidence Drugs 2003 63 35 51 14984079
Benayoun L Druihe A Dombret M-C Aubier M Pretolani M Airway structural alterations selectively associated with severe asthma Am J Respir Crit Care Med 2003 167 1360 8 12531777 10.1164/rccm.200209-1030OC
Woodruff PG Dolganov GM Ferrando RE Donnelly S Hays SR Solberg OD Carter R Wong HH Cadbury PS Fahy JV Hyperplasia of smooth muscle in mild to moderate asthma without changes in cell size or gene expression Am J Respir Crit Care Med 2004 169 1001 6 14726423 10.1164/rccm.200311-1529OC
Hirst SJ Regulation of airway smooth muscle cell immunomodulatory function: role in asthma Respir Physiol Neurobiol 2003 137 309 26 14516734 10.1016/S1569-9048(03)00155-1
Busse W Banks-Schlegel S Wenzel S Pathophysiology of severe asthma, Nihlbi workshop summary J Allerg Clin Immunol 2000 106 1033 42 10.1067/mai.2000.111307
Hakonarson H Grunstein M Autocrine regulation of airway smooth muscle responsiveness Respir Physiol & Neurobiol 2003 137 263 76 14516731 10.1016/S1569-9048(03)00152-6
Madison M Migration of airway smooth muscle cells: Am J Respir Cell Mol Biol 2003 29 8 11 12821446 10.1165/rcmb.F272
Schmidt D Rabe K Immune mechanisms of smooth muscle hyperreactivity in asthma J Allerg Clin Immunol 2000 105 673 83 10.1067/mai.2000.105705
Broide D Novel therapies in allergic disease: molecular and cellular mechanisms of allergic disease J Allerg Clin Immunol 2001 108 65 71 10.1067/mai.2001.116436
Matz J Williams J Rosenwasser L Borish L Granulocyte-macrophage colony-stimulating factor stimulates macrophages to respond to IgE via the low affinity IgE receptor (CD23) J Allerg Clin Immunol 1994 93 650 7
Visan I Goller M Berberich I Kneitz C Tony HP Pax-5 is a key regulator of the B cell restricted expression of the CD23a isoform Eur J Immunol 2003 33 1163 1173 12731041 10.1002/eji.200323747
Novak N Kraft S Bieber T IgE receptors Curr Opinion in Immunol 2001 13 721 6 10.1016/S0952-7915(01)00285-0
Ewart MA Ozanne BW Cushley W The CD23a and CD23b proximal promoters display different sensitivities to exogenous stimuli in B lymphocytes Genes Immunol 2003 3 158 64 10.1038/sj.gene.6363848
Oettgen H Geha R IgE regulation and roles in asthma pathogenesis J Allerg Clin Immunol 2001 107 429 40 10.1067/mai.2001.113759
Harkins MS Moseley PL Iwamoto GK Regulation of CD23 in the chronic inflammatory response in asthma: a role for interferon-gamma and heat shock protein 70 in the TH2 environment Ann Allergy Asthma Immunol 2003 6 567 74 14700442
Hakonarson H Carter C Kim C Grunstein M Altered expression and action of the low-affinity IgE receptor FCRII (CD23) in asthmatic airway smooth muscle J Allerg Clin Immunol 1999 104 575 84
Hakonarson H Grunstein MM Autologously up-regulated Fc receptor expression and action in airway smooth muscle mediates its altered responsiveness in the atopic asthmatic sensitized state Proc Nat Acad Sci 1998 95 5257 62 9560263 10.1073/pnas.95.9.5257
Hakonarson H Maskeri N Carter C Grunstein M Regulation of TH1- and TH2-tye cytokine expression and action in atopic asthmatic sensitized airway smooth muscle J Clin Invest 1999 103 1077 87 10194481
Hakonarson H Maskeri N Kim C Grunstein M Autocrine interaction between IL-5 and IL-1 mediates altered responsiveness of atopic asthmatic sensitized airway smooth muscle J Clin Invest 1999 104 657 67 10487780
Rosenwasser L Busse W Lizambri R Olejnik T Totoritis Allergic asthma and anti-CD23 mAb (IDEC-152): Results of a phase 1, single-dose, dose-escalating clinical trial J Allerg Clin Immunol 2003 112 563 70 10.1016/S0091-6749(03)01861-X
Ritz SA Cundall M Gajewska B Alvarez D Gutierrez-Ramos J Coyle A McKenzie A Stampfli M Jordana M Granulocyte macrophage colony-stimulating factor-driven respiratory mucosal sensitization induces Th2 differentiation and function independently of interleukin-4 Am J Respir Cell Mol Biol 2002 27 428 435 12356576
Schwartz LB Bradford TR Regulation of tryptase from human lung mast cells by heparin. Stabilization of the active tetramer J Biol Chem 261 7372 9 1986 Jun 5 3519608
Brightling CE Bradding P Symon FA Holgate ST Wardlaw AJ Pavord ID Mast-cell infiltration of airway smooth muscle in asthma: N Engl J Med 346 1699 705 2002 May 30 12037149 10.1056/NEJMoa012705
Oguma T Palmer LJ Birben E Sonna LA Asano K Lilly CM Role of prostanoid DP receptor variants in susceptibility to asthma: N Engl J Med 351 1752 63 2004 Oct 21 15496624 10.1056/NEJMoa031785
Sukkar MB Stanley AJ Blake AE Hodgkin PD Johnson PR Armour CL Hughes JM 'Proliferative' and 'synthetic' airway smooth muscle cells are overlapping populations Immunol Cell Biol 2004 82 471 8 15479432 10.1111/j.0818-9641.2004.01275.x
Brown JK Jones CA Rooney LA Caughey GH Hall IP Tryptase's potent mitogenic effects in human airway smooth muscle cells are via nonproteolytic actions Am J Physiol Lung Cell Mol Physiol 2002 282 L197 206 11792624
Jiang H Harris M Rothman P IL-4/IL-13 signaling beyond JAK/STAT J Allerg Clin Immunol 2000 105 1063 70 10.1067/mai.2000.107604
Tinnell SB Jacobs-Helber SM Sterneck E Sawyer ST Conrad DH STAT6, NF-kappaB and C/EBP in CD23 expression and IgE production: Int Immunol 1998 10 1529 38 9796920 10.1093/intimm/10.10.1529
Gunt SJ Tang DD Saez AO Cytoskeletal remodeling of the airway smooth muscle cell: a mechanism for adaptation to mechanical forces in the lung Respir Physiol Neurobiol 2003 137 151 168 14516723 10.1016/S1569-9048(03)00144-7
Hirshman CA Zhu D Panettieri RA Emala CW Actin depolymerization via beta-adrenoreceptor in airway smooth muscle cells: a novel PKA-independent pathway Am J Physiol Cell Physiol 2001 281 C1468 76 11600409
Halayko AJ Solway J Molecular mechanisms of phenotypic plasticity in smooth muscle cells J Appl Physiol 2001 90 358 68 11133929
Nishiyama T Sasaki T Takaishi K Kato M Yaku H Araki K Matsuura Y Takai Y rac p21 is involved in insulin-induced membrane ruffling and rho p21 is involved in hepatocyte growth factor- and 12-O-tetradecanoylphorbol-13-acetate (TPA)-induced membrane ruffling in KB cells Mol Cell Biol 1994 14 2447 56 8139548
Okamoto H Takuwa N Yokomizo T Sugimoto N Sakurada S Shigematsu H Takuwa Y Inhibitory Regulation of Rac Activation, Membrane Ruffling, and Cell Migration by the G Protein-Coupled Sphingosine-1-Phosphate Receptor EDG5 but Not EDG1 or EDG3 Mol Cell Biol 2000 20 9247 61 11094076 10.1128/MCB.20.24.9247-9261.2000
Fish J Peters S Airway remodeling and persistent airway obstruction in asthma J Allerg Clin Immunol 1999 104 509 16
Oltman U Issa R Sukkar MB John M Chung KF Role of c-jun N-terminal kinase in the induced release of GM-CSF, RANTES and IL-8 from human airway smooth muscle cells Br J Pharmacol 2003 139 1228 34 12871843 10.1038/sj.bjp.0705345
| 15907205 | PMC1173127 | CC BY | 2021-01-04 16:36:25 | no | Clin Mol Allergy. 2005 May 20; 3:6 | utf-8 | Clin Mol Allergy | 2,005 | 10.1186/1476-7961-3-6 | oa_comm |
==== Front
Clin Mol AllergyClinical and molecular allergy : CMA1476-7961BioMed Central London 1476-7961-3-81597210110.1186/1476-7961-3-8Case ReportSecondary prevention of allergic symptoms in a dairy farmer by use of a milking robot Korinth Gintautas [email protected] Horst Christoph [email protected] Wolfgang [email protected] Hans [email protected] Institute and Outpatient Clinic of Occupational, Social and Environmental Medicine, University Erlangen-Nuremberg, Schillerstrasse 25/29, D-91054 Erlangen, Germany2 Department of Medical Informatics, Biometry and Epidemiology, University Erlangen-Nuremberg, Waldstrasse 6, D-91054 Erlangen, Germany2005 22 6 2005 3 8 8 26 8 2004 22 6 2005 Copyright © 2005 Korinth et al; licensee BioMed Central Ltd.2005Korinth et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Animal-derived allergens include lipocalins which play an increasing role in occupational respiratory sensitizations. The prevention of sensitization in stock farming is often difficult due to intense exposure, with traditional milking still requiring close animal contact. Complete avoidance of allergen exposure is only possible if stock farming is abandoned. This is, however, often not feasible in small dairy plants because of the resulting loss of income.
Case presentation
In a 37-year-old female farmer daily asthmatic complaints appeared, associated with cow dust-derived allergen exposure by milking with a conventional device. Respiratory symptoms increased during a period of 12 years. Allergic bronchial asthma was diagnosed, caused by sensitization against cow dust-derived allergens, as demonstrated by positive skin prick test and by detection of IgE antibodies. In a separate specific inhalation challenge test using a 10% extract of cow dust-derived allergens a 330% increase of airway resistance was detected. To enable further dairy farming, a milking robot was installed in 1999, i.e., an automatic milking system. The novel milking technique reduced the daily exposure from over 2 hours to approximately 10 min. The clinical course after the installation of the milking robot was favourable, with less frequent allergic and asthmatic symptoms. Furthermore, asthma medication could be reduced. Improvement was noted also in terms of lung-function and decreased total serum IgE.
Conclusion
The case presented and the evidence from the literature indicates that the strategy of exposure minimization to allergens at workplaces can be an effective alternative to total elimination. In farmers with cow dust allergy a milking robot is an appropriate technical measure to minimize allergen-exposure.
==== Body
Background
Allergic asthma ranks in Germany among frequent occurred occupational diseases. Cow hair allergy in Finland is one of the most frequent reasons for the development of occupational asthma [1], but epidemiologically in Germany still insufficiently explored. The prevalence of respiratory complaints in Finnish farmers with cow husbandry is 27% for rhinitis respectively 12% for asthma in consequence of occupational exposure [2,3]. Until now there is only limited insight into the risk factors with regard to this disease. The prevention of sensitization in stock farming to cow hair and epithelial allergens including lipocalins is often difficult due to intense exposure, with traditional milking still requiring close animal contact.
The German Professionals insurance laws require a complete elimination of allergens for the recognition of an allergic airway disease as a compensable occupational disease. Complete avoidance of occupational exposure of cow hair allergens is only possible if stock farming is abandoned. This is, however, often not feasible in small dairy plants because of the resulting loss of income.
In the present case report we discuss the efficiency of the strategy of exposure minimization to allergens by the use of a milking robot, i.e., an automatic milking system (AMS) as an alternative measure to total elimination of allergens for the prevention of occupational asthma caused by cow hair allergy.
Case presentation and discussion
A 37-year-old female farmer reported to suffer from daily asthmatic complaints by milking of cows with a conventional device. Exposure associated respiratory symptoms increased continuously during a period of 12 years. Allergic bronchial asthma, caused by sensitization against cow dust-derived allergens, was diagnosed by a positive skin prick test (Bencard®) and by the detection of IgE antibodies against Bos d 2 at 74.9 kIU/l (Pharmacia, UniCAP®). Moreover, nonspecific bronchial hyperresponsiveness was verified by a positive histamine inhalation challenge test. The diagnosis of occupational asthma was confirmed by a separate specific inhalation challenge test using a 10% extract of cow hair allergens which led to a 330% increase of airway resistance (Raw).
The German Professionals insurance laws require complete elimination of allergen exposures for the compensation of occupational allergic asthma as occupational disease [4]. Legal consequence would usually be to abandon dairy farming. However, in our case presented, dairy farming substantially contributed to family-income and the compensation offered would be insufficient for subsistence. Hyposensitization is the most effective measure in the prevention of allergic symptoms in patients with asthma. In that farmer the hyposensitization was not feasible due to permanent exposure to allergens. This farmer did not wear a helmet during the milking process because of claustrophobic panic attacks (fear of suffocation). Moreover an immunotherapy with recombinant lipocalins is currently not available.
Respirator helmets have been predominantly used as effective measures for prevention of the inhalation of fumes and dusts [5]. Investigations about the effectiveness of respirator helmets against high-molecular allergens to prevent allergic asthma are rare. Taivainen et al. (1998) demonstrated that due to the use of a dust respirator helmet with a P2-class filter, dairy farmers with occupational asthma induced by cow dander showed less rhinitic symptoms and an improved peak flow rate [6]. However, workers using respirator helmets were not prevented against a progressive behavior of occupational asthma [7,8]. Thus it is to doubt whether respirator helmets are efficient in farmers with occupational asthma to provide a complete protection against allergens [9].
To enable further dairy farming, the farmer installed a milking robot in 1999, i.e., an automatic milking system (AMS). At present circa 1300 AMS are installed, predominantly in the Netherlands, followed by Germany. AMS were developed in the course of increasing automation of the agricultural production. AMS consist of a milking box with the milking equipment and an electronic controlling system, an automatically operating dosing unit of a specific food-concentrate as well as a software controlled management system. The cows are decoyed from a specific food-concentrate to enter the milking box. A transponder, fixed on the cow neck, initiates milking operations automatically controlled by software and laser. The milking robot operates in the cowshed, which is air-shielded from the control-centre. After the installation of AMS the farmer was involved only in terms of monitoring the milking process. Figure 1 shows the job and the current exposure situation of the farmer. It is apparent that the novel milking technique reduced exposure significantly by some 90% (from over 2 hours to approx. 10 min.) without a decline of milk production. Beyond allergen exposure reduction, the physical workload was lessened and the time available for activities to improve coping was increased – these factors are increasingly recognized as relevant for the prognosis of asthma [10]. Table 1 shows the influence of the AMS technique on the current occupational exposure of the farmer. According to German Professionals insurance laws all conceivable measures must be taken into account even AMS is an expensive technical device to prevent occupational asthma.
Figure 1 Milking process monitoring by an air-shielded control-centre.
Table 1 Parameters influenced by automatic milking system (AMS)
Parameter Power of parameter Influence of AMS
Daily exposure period ↓↓↓ Drop of more than 2 hours to approx. 10 min. (> 90%)
Exposure intensity ↓↓↓ Increasing space to cow
Physical workload ↓↓ Monitoring tasks
Timing flexibility ↑↑ • No commitment to fixed milking times
• Free working plan
Quality of life ↑ More time available for other activities
Explanation: ↓ = reduction of power, ↑ = improvement of power
After installation of the milking robot the farmer reported significantly less frequent allergic and asthmatic symptoms. Asthma medication was reduced and required only once daily in the evening. Improvement was noted also in terms of lung-function and decreased total serum IgE: serum IgE decreased from 1332 IU/ml before milking robot installation to 572 and 474 IU/ml two and three years after installation, respectively. FEV1 improved by 20% and vital capacity by 11%, comparing values one year before with two years after installation. A CAP-RAST score "5" versus Bos d 2 was determined after the intervention. Preceding EAST-Test results vs. Bos d 2 were not suitable for comparison.
Current discussions address threshold limit values for allergens that may prevent allergic symptoms [11]. These have been proposed also for the cow dust-derived allergen Bos d 2 [12]. Table 2 shows examples for successful measures of exposure minimization at workplaces to reduce sensitizations. Recent studies have already demonstrated that allergen exposure reduction at workplaces is successful in reducing sensitizations, e.g., to latex proteins [13,14], laboratory animals [15] or acid anhydrides [16].
Table 2 Examples for successful measures of exposure minimization at workplaces in reducing of sensitizations
Exposure areas Allergen Measure of exposure minimization Study
Hospitals Latex proteins Replacement of powdered gloves through powder-free gloves Edelstam et al. 2002, Tarlo et al. 1994
Animal research laboratories Allergens to laboratory animals Technical improvement of housing cabinets for animals Thulin et al. 2002
Electrical industry Acid anhydrides Installation of a closed system in the production of epoxy resin Drexler et al. 1999
Conclusion
The case presented and the evidence obtained from the literature indicates that the strategy of exposure minimization to allergens at workplaces can be an effective alternative to total elimination, which may not be feasible for economical reasons. In farmers with cow dust allergy a milking robot is an appropriate technical measure to minimize allergen-exposure particularly with regard to the reduced animal contact. Independently from this, such milking robots also increasingly used to enhance productivity (usually in herds comprising more than 50 animals). The efficacy of milking robots in terms of primary and secondary prevention should be evaluated also epidemiologically in a suitable cohort study, preferably in countries with intensive dairy farming.
List of abbreviation
AMS; Automatic milking system
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
GK was the principal investigator. GK examined the patient, performed the investigations and drafted the manuscript. HCB revised the manuscript. WU revised the manuscript and evaluated the epidemiological aspects. HD conceived the case report. All authors read and approved the final manuscript.
==== Refs
Ylönen J Mäntyjärvi R Taivainen A Virtanen T IgG and IgE antibody responses to cow dander and urine in farmers with cow-induced asthma Clin Exp Allergy 1992 22 83 90 1551038
Virtanen T Vilhunen P Husman K Happonen P Mäntyjärvi R Level of airborne bovine epithelial antigen in Finnish cowsheds Int Arch Occup Environ Health 1988 60 355 360 3384493 10.1007/BF00405670
Virtanen T Vilhunen P Husman K Happonen P Mäntyjärvi R Sensitization of dairy farmers to bovine antigens and effects of exposure on specific IgG and IgE titers Int Arch Allergy Appl Immunol 1988 87 171 177 3192304
Merget R Schultze-Werninghaus G Occupational asthma: definition – epidemiology – etiologic substances – prognosis – prevention – diagnosis – expert assessment aspects [in German] Pneumologie 1996 50 356 363 8710819
Kongerud J Rambjor O The influence of the helmet respirator on peak flow rate in aluminum potroom Am Ind Hyg Assoc J 1991 52 243 248 1858666
Taivainen AI Tukiainen HO Terho EO Husman KR Powered dust respirator helmets in the prevention of occupational asthma among farmers Scand J Work Environ Health 1998 24 503 507 9988093
Slovak AJ Orr RG Teasdale EL Efficacy of the helmet respirator in occupational asthma due to laboratory animal allergy (LAA) Am Ind Hyg Assoc J 1985 46 411 415 4050677
Cote J Kennedy S Chan-Yeung M Outcome of patients with cedar asthma with continuous exposure Am Rev Respir Dis 1990 141 373 376 1689129
Müller-Wening D Neuhauss M Protective effect of respiratory devices in farmers with occupational asthma Eur Respir J 1998 12 569 572 9762781 10.1183/09031936.98.12030569
Bergmann KC Fischer J Schmitz M Petermann F Petro W Inpatient pneumologic rehabilitation of adults: goals – diagnostic and therapeutic standards – research needs [in German] Pneumologie 1997 51 523 532 9265157
Baur X Are we closer to developing threshold limit values for allergens in the workplace? Ann Allergy Asthma Immunol 2003 90 11 18 12772945
Zeiler T Taivainen A Mäntyjärvi R Tukiainen H Rautiainen J Rytkönen-Nissinen M Virtanen T Threshold levels of purified natural Bos d 2 for inducing bronchial airway response in asthmatic patients Clin Exp Allergy 2002 32 1454 1460 12372125 10.1046/j.1365-2745.2002.01499.x
Edelstam G Arvanius L Karlsson G Glove powder in the hospital environment – consequences for healthcare workers Int Arch Occup Environ Health 2002 75 267 271 11981661 10.1007/s00420-001-0296-y
Tarlo SM Sussman G Contala A Swanson MC Control of airborne latex by use of powder-free latex gloves J Allergy Clin Immunol 1994 93 985 989 8006320
Thulin H Björkdahl M Karlsson AS Renström A Reduction of exposure to laboratory animal allergens in a research laboratory Ann Occup Hyg 2002 46 61 68 12005134 10.1093/annhyg/mef022
Drexler H Schaller KH Nielsen J Weber A Weihrauch M Welinder H Skerfving S Efficacy of measures of hygiene in workers sensitised to acid anhydrides and the influence of selection bias on the results Occup Environ Med 1999 56 202 205 10448330
| 15972101 | PMC1173128 | CC BY | 2021-01-04 16:36:25 | no | Clin Mol Allergy. 2005 Jun 22; 3:8 | utf-8 | Clin Mol Allergy | 2,005 | 10.1186/1476-7961-3-8 | oa_comm |
==== Front
Cost Eff Resour AllocCost effectiveness and resource allocation : C/E1478-7547BioMed Central London 1478-7547-3-41589007010.1186/1478-7547-3-4ResearchCost-analysis of different management policies for patients with mild hepatitis A virus infection in Kazakhstan Yassin Abdiaziz S [email protected] Michael [email protected] Edmond [email protected] Ramses [email protected] Aliya [email protected] Victor [email protected] Tatiana [email protected] Terence [email protected] Division of International Health, Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, USA2 CDC Central Asian Regional Office, Almaty, Republic of Kazakhstan3 Division of HIV/AIDS Prevention, CDC, Atlanta, Georgia, USA4 Almaty City Sanitary and Epidemiological Stations, Ministry of Health, Almaty, Republic of Kazakhstan2005 12 5 2005 3 4 4 6 1 2005 12 5 2005 Copyright © 2005 Yassin et al; licensee BioMed Central Ltd.2005Yassin et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Objective
For patients with mild hepatitis A virus (HAV) infection, this study compared estimates of total costs associated with managing cases under a policy of mandatory hospitalization in the Republic of Kazakhstan and estimates of total costs associated with managing cases in outpatient settings. Costs were estimated both from the perspective of the Ministry of Health and from a broader societal perspective.
Methods
Data were collected by using a standardized structured questionnaire. For cases of mild HAV infection, medical records were obtained from 200 patients managed by hospitalization and from 251 patients managed in an outpatient setting. Personal interviews were also conducted to collect information on productivity losses and out-of-pocket expenses.
Results
Nationally, we estimated about 21,600 cases of mild HAV infection annually. The mean annual treatment costs in hospital for mild HAV infection was estimated at US$3.39 million (2001 US$) (95% confidence interval [CI] = [US$3.26 million – US$3.52 million]). The total annual mild HAV infection cost to the society, including direct medical and nonmedical costs and productivity losses due to 721,440 lost work days, was estimated at US$6.26 million (95% CI [US$6.05 million – US$6.47 million]). In sensitivity analyses, the total annual cost of mild HAV infection ranged from US$4.37 million to US$24.66 million. The survey results showed that a relatively minor change in the current policy of mandatory hospitalization could result in an estimated total annual savings of US$4.62 million (2001 US$) in Kazakhstan.
Conclusion
Adoption of an outpatient management policy for cases of mild HAV infection would generate substantial cost savings to the Ministry of Health and society.
==== Body
Background
The average annual incidence rate of hepatitis A virus (HAV) infection varies significantly worldwide ranging from 9.1 per 100,000 in the United States and Europe to 500 per 100,000 in the Central Asian Republics [1,2]. According to the latest available data, the incidence of HAV infection remains as high as 150 cases per 100,000 population in the Central Asian Republics and Kazakhstan in 2001 [3,4]. Although HAV infection incidence has decreased slightly compared to the figures for the last decade, the persistence of high incidence in Kazakhstan is mainly due to problems related to poor supplies of good-quality drinking water, sanitation and hygiene practices [1,5,6]. It has been documented that the incidence of HAV infection is closely linked to poor socio-economic living conditions [3].
HAV infection is usually a mild illness, but can be severe if it occurs concurrently with other diseases or comorbid conditions [7-10]. In Britain, and North America, a patient with HAV infection is hospitalized only if (a) (s)he is too sick with diarrhea, nausea, and vomiting to be managed appropriately with antiemetics and oral rehydration at home, (b) (s)he has hepatic and/or renal failure (sometimes seen with HAV-infection in persons with underlying alcoholic liver disease or with chronic hepatitis caused by other viral agents) [11], or (c) (s)he has a clinical presentation that is truly anomalous (e.g., meningoencephalitis has been reported in association with HAV infection but is exceedingly rare [12]). However, in many republics of the former Soviet Union, HAV infection has been a cause for routine hospitalization, as mandated in administrative directives. The premise on which many such patients are hospitalized should be reconsidered because relatively few patients with HAV infection become seriously ill, no treatment to influence the underlying course of the disease exists, and neither admission to hospital nor isolation from others in the home lessens the spread of the infection [13].
Because HAV infection is neither a severe illness nor one with important sequelae, it has been observed that the rates of infection of family members of patients with mild HAV managed at home or in hospital were similar [13-15]. Previous studies using data from the region reported that the hospitalization of patients after the appearance of jaundice was unjustified, and that the quality of treatment between inpatient and outpatient settings would be similar [13,14]. However, in severe cases (<10% of HAV infections), patients are more likely to be managed in a hospital and to receive more intensive treatment, including ultrasound and computerized tomography exams, as well as liver biopsies [7,8,10]. In such cases, the assumption of similar quality of inpatient and outpatient treatment does not hold.
Using data gathered from patients with mild HAV infection in Almaty, Kazakhstan, we conducted a cost-comparison analysis of the policy of mandatory hospitalization and an alternative policy of outpatient management for patients with mild HAV infection. The purposes of this study were (a) to determine the mean treatment costs associated with managing cases of mild HAV infection in an inpatient setting under a policy of mandatory hospitalization, (b) to compare those costs with costs of treating patients with mild HAV infection using outpatient management, assuming a similar quality of treatment under inpatient and outpatient conditions, and (c) to determine total direct medical and nonmedical costs as well as productivity losses associated with mild HAV infection and then compare these costs both from the perspective of the resource-allocating authority (i.e., the Ministry of Health) and from a broader societal perspective.
Materials and methods
Data sources
Data were collected using survey questionnaires that involved interviews with patients and medical practitioners between November 2000 and February 2001. Information was collected on patient's age, sex, principal diagnosis, duration of illness, use of services, and cost data. Patients were interviewed to collect information regarding out-of-pocket and direct nonmedical expenses, such as expenses paid for transportation to outpatient clinics and indirect costs associated with the number of days absent from work. Interviews with medical personnel and hospital administrators were conducted to determine the costs and quantify the amount of health and nonhealth staff time spent per day in caring for patients with mild HAV infection.
A sample size of 451 subjects (200 inpatients and 251 outpatients) was used to conduct a cost-comparison analysis. We enrolled patients presenting to either of two hospitals in Almaty, Kazakhstan, in a geographical area where mandatory hospitalization for mild HAV infection was still practiced. We also enrolled patients in 19 outpatient clinics in geographical areas where mandatory hospitalization was no longer practiced. Patients selected for the study included members of both sexes, all age groups, and varied in ethnicity.
Case definition
A case of mild HAV infection was defined as a clinical presentation with manifestations of acute hepatitis and serologic confirmation of HAV infection in a person who reported to one of the selected hospitals or outpatient clinic sites. The clinical manifestations of HAV infection included sudden onset of fever, anorexia, fatigue, and/or abdominal discomfort followed within a few days by jaundice and hepatomegaly [16-18]. Serologic confirmation of mild HAV infection was determined by elevated alanine serum transferase (AST) not in excess of 5 times the upper limit of normal of the reference value, and by presence of detectable IgM anti-HAV
Criteria for inclusion in this analysis were (a) having mild HAV infection as a primary or sole diagnosis confirmed by laboratory; (b) being between 1 and 65 years of age and being either hospitalized or managed at one of the study sites by a health care worker during the study period; and (c) providing voluntarily signed consent that included permission to review medical records. Persons who had multiple concurrent diseases or comorbid conditions and those who had not been diagnosed and tested positive for mild HAV infection more than 30 days before the study period were excluded from the study.
Cost description
Costs for direct medical and non-medical services provided for patients with mild HAV infection were calculated based on interviews with medical providers, hospital administrators, health officials and patients. Units of direct medical services recorded included the number of days spent in hospital, health staff time allocated to treatment, and costs for those services specifically identified as part of the management of patients with mild HAV infection in hospital and outpatient clinics. Time spent by health care personnel was obtained based on reviews of medical records. Costs were based on estimates of costs for time spent by hospital- or clinic-personnel per day in caring for patients with mild HAV infection: in hospital, physicians spent approximately 54 minutes (min.), nurses approximately 89 min., and nonhealth staff about 40 min.; in the outpatient clinics, physicians spent approximately 26.4 min., nurses approximately 18 min., and nonhealth staff a negligible amount of time. In this analysis, we are considering only the base salary for the health care personnel; physicians are paid US$15.84 per 8-hour workday, US$4.8 per day for nurses, and US$2.4 per day for nonhealth staff obtained from the budget of each health facility and based on the national contract for health personnel. Although physicians earn more than their base salary through various bonus payments and through informal payments from patients, consistent estimates of these payments could not be captured and were not included in this analysis [6,19,20]. Since an estimated 80% to 90% of physician income is obtained informally [20], it is difficult to track the flow of incomes for doctors, and we were able to use only the base salary for our estimates.
The cost per patient-hospital day included the costs of purchase and repair of medical equipment and buildings, administrative and operational costs in the hospitals allocated to the treatment of mild HAV patients. To cover the full capital and recurrent cost, cost per patient-hospital day was determined based on average national estimates provided by hospital administrators [21-23]. Although hospital costs cover capital and recurrent costs such as the cost of building and medical equipment, laboratory services, health and nonhealth personnel, and hospital administrative costs, we estimated separately the costs for laboratory and personnel services for managing patients in hospital based on medical records and interviews with medical practitioners. Costs for hospital meals and prescription drugs were obtained based on patient self-reported out-of-pocket expenses. The cost of hospital meals was estimated for the respective number of inpatient hospital days. The number of hospital days was determined based on patient medical records. Because all patients paid for hospital meals and prescription drug charges where incurred, we calculated the cost of hospital meals and prescription drugs separately.
Total treatment costs were calculated as the sum of direct medical and non-medical costs which included hospital costs, costs for time spent with patients by physicians, nurses, and other staff, laboratory and prescription drug costs, as well as non-medical costs such as hospital meals and transport. Because there are no long-term sequelae of mild HAV infection [7,10], no home care was needed for such patients; therefore, the cost of home care was not calculated. Productivity losses were calculated as indirect costs associated with lost workdays due to illnesses of HAV infection. The number of lost workdays were determined based on self-reports of missed work. The exchange rate used was US$1 = 148 Kazakhstan Tenge (KZT), a rate that has not varied more than 15% since January 2001. As of May 5, 2005, the exchange rate was US$1 = 131 KZT.
Treatment outcome
Having measured the direct medical and nonmedical costs, as well as productivity losses of managing mild HAV infection, we defined effective treatment or management for a mild HAV infection as an episode of care (which included all services provided) that led to a complete recovery. As has been observed epidemiologically elsewhere, we assumed that the rates of infection of family members of patients with mild HAV infection managed at home or in hospital were similar [13,15].
Statistical analyses
We completed our analyses in five stages: First, we estimated the mean annual treatment cost per case of mild HAV infection when managed in inpatient and outpatient settings. Using SAS statistical programs, comparison between inpatient and outpatient groups were made using PROC TTEST of the null hypothesis of equal group variances, and we determined the difference in mean treatment cost per case using t tests of differences in means. The confidence interval (CI) for the difference between two sample means was obtained using a "pooled" estimate of the standard deviation [24].
Second, we stratified the samples by four different age groups, given significant differences in mean age between the two groups. We categorized patients into four age groups: ≤ 18, 19 – 26, 27 – 34, and ≥ 35 years to estimate the mean annual treatment cost per case of mild HAV infection by age group. We used PROC GLM to conduct one-way analysis of variance (ANOVA) using Bonferroni t tests of pair of means within age groups to test the null hypothesis of equality of the group means among different age groups.
Third, we estimated the number of lost workdays for both inpatient and outpatient group. We calculated the productivity losses by multiplying the number of lost workdays by employed patients aged 18 – 64 years or by adult parents or guardians of children with mild HAV infection, and by daily urban wage rates. In this analysis, we did not consider replacement costs for unemployed patients.
Fourth, we estimated the total annual cost of mild HAV infection as the sum of the annual treatment costs consisting of direct medical and nonmedical costs as well as productivity losses resulting from lost workdays.
Finally, we conducted sensitivity analyses to determine which parameters exert the greatest influence on the results of this analysis and establish the range of total annual cost of mild HAV infection. A p-value ≤ 0.05 was considered to be statistically significant. Epi Info software [25] was used for data entry. Data from questionnaire forms were entered twice into a computer database to reduce the chances of data-entry errors and were analyzed using SAS statistical programs [26].
Results
Table 1 presents sociodemographic characteristics of the inpatient and outpatient groups. The mean age of the inpatient group was 22 years; the mean age of the outpatient group was 12 years. The inpatient group reported a higher annual household income of US$898.2 (2001 US$) compared with US$502.3 for the outpatient group. Several other comparisons reflected disparities in age of the two sample groups: 26.5% of the inpatient group was employed, compared with 6.7% of the outpatient group; 21% of the inpatient group were married, compared with 8.9% of the outpatient group; 32% of the inpatient group smoked cigarettes, compared with 9.9% of the outpatient group. The average wage rate per patient in urban areas was 14,617 KZT (US$98.76) per month compared to 5000 KZT (US$33.78) per patient in rural areas. There were 27.21 lost workdays for employed inpatients and 6.19 lost workdays for family members caring for minor patients in hospital; employed outpatients had an average of 15.73 lost workdays (lost workdays: 33.40 vs. 15.73). The average length of hospital stay for a patient with mild HAV infection was 9.7 days, compared with 3.4 visits per patient in the outpatient group.
Table 1 Sociodemographic characteristics of patients with mild HAV infection, Almaty, Kazakhstan, 2001
Variables All patients (n = 451) Inpatients (n = 200) Outpatients (n = 251)
Gender (%)
Male 50.9 50.0 51.4
Female 49.1 50.0 48.6
Marital status (%)
Married 17.8 21.0 8.9
Unmarried 85.2 79.0 91.1
Education level (%)
Never attended or kindergarten 13.2 0.5 23.4
School 1–8 years 55.8 72.0 42.7
Grades 9–11 years 16.3 27.5 17.3
High school graduate 1.1 - 2.0
College 1–3 years or graduate 13.6 - 14.5
Ethnicity (%)
Kazakhs 40.6 36.0 44.2
Russians 49.2 54.5 45.0
Uzbek 2.4 2.0 2.8
Others 7.8 7.5 8.0
Employment status (%)
Employed 16.4 26.5 6.7
Unemployed 83.6 73.5 93.3
Tobacco use (%)
Smoker 20.3 32.0 9.9
Nonsmoker 79.7 68.0 90.1
Urban status (%)
Urban 99.8 100.0 99.6
Rural 0.2 - 0.4
Home ownership (%)
Owned 98.2 99.5 97.2
Rented 1.8 0.5 2.8
Age group (%)
≤ 18 66.3 37.5 89.2
19 – 26 22.6 42.5 6.8
27 – 34 6.7 12.5 2.0
≥ 35 4.4 7.5 2.0
Mean Age (years) (SE) ¶ 17 (0.41) 22 (0.49) 12 (0.43)
Mean household income (US$) (SE)¶ 886.6 (60.03) 898.2 (61.65) 502.3 (28.38)
¶ Standard error (SE) are values in parenthesis.
Table 2 presents the mean treatment costs per patient with mild HAV infection in inpatient and outpatient settings. The mean total direct medical and nonmedical cost of managing mild HAV infection was estimated at US$157.4 (2001 US$) per inpatient (95% CI = US$151 – 163), compared with US$22.5 per outpatient (95% CI = US$21 – 23). The hospital costs (US$81) were calculated by taking the product of the average number of hospital days (9.7 days) and the cost per HAV patient-hospital day (US$8.4) obtained from the survey. Of the US$81 of hospital costs, as much as 40% (US$32) of the hospital costs was allocated to the costs for the purchase and repair of medical equipment and buildings and 60% (US$49) was spent on recurrent hospital administrative and operational costs including overhead and utilities. Laboratory costs accounted for 6.9% (US$11.0) of the mean treatment costs for inpatients compared with 35.6% (US$8.0) of those costs for outpatients. We estimated that about 19% (US$30) of the mean treatment costs were allocated to hospital meals.
Table 2 Mean treatment costs of managing cases of mild HAV infection for inpatient and outpatient settings, Almaty, Kazakhstan (2001 US$)
Inpatient Outpatient
Cost items (US$) Mean SE† 95% CI‡ Mean SE† 95% CI‡
Hospital cost 81.0 1.78 (89.0, 96.0) - - -
Physicians' time 18.0 0.49 (17.0, 19.0) 3.0 0.08 (2.80, 3.20)
Nurses' time 9.0 0.17 (8.7, 9.30) 1.6 0.07 (1.46, 1.70)
Non-health staff 2.0 0.04 (1.92, 2.10) - - -
Laboratory 11.0 0.35 (10.0, 12.0) 8.0 0.11 (7.8, 8.2)
Prescription drugs 6.4 0.21 (6.19, 7.01) 5.9 0.33 (5.25, 6.55)
Hospital meals 30.0 0.57 (29.0, 31.0) - - -
Transport - - - 4.0 0.20 (3.60, 4.40)
Total inpatient/outpatient 157.4 3.04 (151.0, 163.0) 22.5 0.42 (21.0, 23.0)
Productivity losses¶ 150.9 2.12 (146.7,155.1) 71.5 4.75 (66.8, 76.3)
Total societal cost§ 308.3 4.90 (298.7, 317.9) 94.0 4.28 (85.6, 102.4)
Note: Data may add exactly due to rounding
†Standard error (SE)
‡95% Confidence interval (95% CI)
¶Productivity losses calculated based on the number of lost workdays reported and average urban wage rate.
§ Total societal costs include treatment costs and productivity losses
From the perspective of the Ministry of Health, the mean direct medical costs of managing mild HAV infection was estimated at US$127.4 per patient in hospital, compared with US$18.5 in an outpatient setting. From the societal perspective, the mean total cost of direct medical and nonmedical services as well as of productivity losses was estimated at US$308.3 per patient in hospital compared with US$94.0 per patient in an outpatient setting. Of the US$157.4 total for direct medical and nonmedical services, a patient in hospital paid approximately US$36.4 out of pocket costs for drugs and hospital meals, compared with US$9.9 for such costs paid by a patient in an outpatient setting.
Results from the PROC TTEST indicated that the difference between the mean treatment costs for management of mild HAV infection among the inpatient and outpatient groups was US$134.6 (2001 US$), 95% CI = (US$ 128.0 – 140.0) and statistically significant at (p ≤ 0.0001). When we controlled for the effect of age on medical cost by stratifying the samples by age group, we found that the mean treatment costs in the outpatient setting was still considerably lower than those in the inpatient setting. For example, the mean treatment costs of managing cases of mild HAV infection for outpatients aged 19 to 26 years was estimated at 13.9% of that for the inpatients of the same age. The one-way ANOVA analysis indicated that the mean treatment costs per inpatient decreased as age increased (Figure 1). The mean treatment cost per inpatient for the age group ≥ 35 years was estimated at US$144 compared with US$163 for the age group ≤ 18 years (F-value = 1.40; p = 0.25). Results from this analysis indicated that although there were differences in population means among different age groups, these differences were not statistically significant. We also noted that the mean treatment cost per outpatient in the age group ≥ 35 years was estimated at US$28 versus US$22 for the age group ≤ 18 years (F-value = 2.05; p = 0.10). Again, results from this analysis indicated that although there were differences in population means, these differences were not statistically significant. Mean treatment costs as well as productivity losses per outpatient increase slightly as age increases (Table 3).
Figure 1 Mean treatment costs per mild HAV inpatient by age group
Table 3 Mean, median total cost and standard error of managing mild HAV infection, by age group and treatment setting (inpatient vs. outpatient), Almaty, Kazakhstan (2001 US$)
Total cost* per inpatient Total cost* per outpatient
Age (years) n§ Mean (SE†) Median cost n§ Mean (SE†) Median cost
≤ 18 75 320 (32.42) 319 224 92 (8.64) 97
19 – 26 85 303 (6.72) 304 17 96 (4.75) 97
27 – 34 25 302 (11.25) 304 5 111 (11.60) 111
≥ 35 15 290 (12.88) 292 5 93 (12.95) 101
All 200 308.3 (4.90) 304 251 94 (4.28) 98
* Note the total cost includes the treatment costs as well as productivity losses
§ Sample size
†Standard error (SE)
Nationally, we estimated about 21,600 cases of mild HAV infection occurred during 2001. Of these cases, an estimated 19,008 employed patients with HAV infection would report lost workdays due to illness considering the 12% unemployment rate in Kazakhstan [6]. Assuming no replacement costs of unemployed sick workers, we calculated the productivity losses by multiplying the average lost wages of US$150.9 per inpatient by the cases of employed inpatients. We estimated the productivity losses at US$2.87 million (95% CI = US$2.79 million – US$2.95 million). Using 21,600 cases of mild HAV infection, an average of 9.7 hospital days and 33.4 lost workdays per inpatient, we calculated a total of 209,520 hospital days and 721,440 lost workdays. Annual mild HAV infection treatment costs for inpatients were estimated at US$3.39 million (95% CI = US$3.26 million – US$3.52 million). These costs could be lowered by managing patients with mild HAV infection in an outpatient setting for as low as US$486,000 (95% CI = US$453,600 – US$496,800).
From the societal perspective, the annual total cost of mild HAV infection for patients treated in hospital was estimated at US$6.26 million, 95% CI = (US$6.05 – US$6.47). The treatment costs represent 51% of the total costs whereas productivity losses account for 49% of the total costs. The total cost of managing mild HAV infection in an outpatient was estimated at US$1.85 million, 95% CI= (US$1.72 – US$1.95). The annual total cost of mild HAV infection could be reduced by almost 70% from US$6.26 million to US$1.85 million by encouraging patients with mild HAV infection to be treated in outpatient rather than in inpatient settings. Using an average saving (US$214) per inpatient and 21,600 cases of mild HAV infection, the potential savings at the national level from changing the treatment setting from inpatient to outpatient would be about US$4.62 million (2001 US$) per year.
Discussion
Our findings suggest that the mean treatment costs per patient managed in hospital were almost seven times the costs per patient in an outpatient setting. Our results were consistent with previous reports that inpatient care is more expensive than outpatient care settings [6]. Even though no other study has directly estimated the costs of mild HAV infection in Kazakhstan, we observed how expensive the inpatient setting in the region was, relative to the outpatient setting. Health systems in the Central Asian Republics, including Kazakhstan, have not been designed and managed with attention to the criteria of technical efficiency (the production of a defined set of services at the lowest cost within the health system; also known as operational efficiency) or allocative efficiency (the distribution of resources across varied range of services in an optimum manner). These health systems have tended to overinvest services provided in inpatient settings; hospitals utilize approximately 75% of the Kazakhstan health budget compared to 10% of the budget for outpatient care [6]. Many disease entities managed with outpatient treatments in European Union countries (including viral hepatitis and tuberculosis) are managed on an inpatient basis in Kazakhstan [6]. In order to provide optimal care within the budget limits imposed by the allocation of hospital resources to various emerging infectious diseases like human immunodeficiency virus (HIV) infection, health authorities should consider choosing health care practices known to be beneficial on the basis of evidence of cost-effectiveness [27]. Inefficiency in the use of public funds has resulted in the increasing practice of informal or 'under-the-table' payments in the health system [6].
Informal out-of-pocket expenses are increasingly required due to declining funds for the health sector. In the late 1990s, a 65% reduction in government revenues resulted in insufficient health sector funding that led to delays in wage payments and shortage of medical supplies [20]. Although the benefit package in Kazakhstan has covered inpatient drug costs, many hospitals in practice cannot afford to supply them. Therefore, patients often pay for food and drugs while they are in hospital [6]. These expenditures are informal payments that patients are asked to pay out-of-pocket. Our results were consistent with the findings of Ensor and Savelyeva, that estimates of patient per capita payment for prescription drugs in hospital range between US$ 8.5 and US$10.4 [20,28,29]. In Kazakhstan, private practice has been permitted since 1991, and more physicians are becoming semi-autonomous practitioners in group practices funded through a patient capitation fund. Many local health authorities permit health facilities to establish charge departments in order to obtain additional revenue [20]. User charges for medical services by public sector health organizations were legalized in 1995. Now, health care facilities charge for services, and as a result, outpatients make official co-payments for the treatment [6].
In addition to these official charges, recent surveys indicated that informal payments to health care practitioners continue to exist, ranging from US$5 for consultations to thousands for an operation [6,20,30,31]. In this paper, estimates of out-of-pocket expenses were obtained by interviewing patients. Higher costs in inpatient settings may reflect unnecessary use of hospital resources. Other factors that contributed to higher costs in inpatient services may be due to the decrease in government revenues that used to subsidize the hospital services, low official salaries of health care staff, and growth in private health care services [6]. Because of these latter factors, medical practitioners seek augmentation of income via the informal payments [20]. User fees for those who can afford them or cost-sharing strategies could address the problems of under-funding in health systems, stabilize these informal payments, and free up public funds. By balancing the mix of resources and increasing the proportion of spending on services managed in outpatient settings, Ministries of Health in Central Asia might be able to achieve optimal allocation of resources in the health care system.
Our findings may be conservative for three reasons. First, in estimating mean treatment costs, we did not consider informal payments to health care staff. Second, our estimates of productivity losses were based on 264 working days per year (22 working days per month) and did not include the value of housekeeping productivity losses. Third, we used lower estimates of the number of patients with mild HAV as 150 per 100,000; the upper estimates of this figure could be as high as 500 per 100,000.
This study has some limitations. First, we did not evaluate post-treatment health outcomes after hospital discharge, including completion of outpatient visits. However, there is a wealth of literature that has demonstrated a lack of long-term health outcome differences between persons restricted to bedrest or institutionalized and persons forced to exercise or allowed to engage in activities ad libitum when symptomatic with acute HAV infection [32,33]. Second, because of lack of reliable data, we were unable to obtain the capital costs of outpatient facilities including the cost of space, maintenance for facility and medical equipment, overhead, and utilities associated with the treatment of mild HAV infection; therefore, our cost estimates for the outpatient might be biased toward the lower end. Despite these potential concerns, these limitations would not invalidate the findings of this study.
In sensitivity analyses, we varied some parameters to establish the range of annual cost estimates of mild HAV infection. We observed that annual cost estimates are sensitive to the following four variables: value of medical services, number of lost workdays, average wage rates, and incidence of HAV infection cases. In these analyses, the annual cost estimates of mild HAV infection varied from US$4.37 to US$24.66 million (Table 4). Considering patients with multiple concurrent diseases or patients diagnosed with severe HAV, cost of medical services can vary significantly.
Table 4 Total annual cost estimates of mild HAV infection for inpatients in sensitivity analysis, Kazakhstan, (2001 US$) in millions
Analysis Treatment cost Productivity losses Total cost
Base case assumption 3.39 2.87 6.26
Value of medical services † 4.89 2.87 7.76
Rural wage rate (KZT 5000 per month) § 3.39 0.98 4.37
Greater adjustment of hepatitis A under-reporting¶ 12.59 12.07 24.66
Note the total cost includes the treatment costs as well as productivity losses
†an estimated informal payment is included. When 80–90% informal payment is taken into account, the treatment costs were estimated at US$226.2 per inpatient.
§ reported wage rate based on the survey results
¶ annual incidence of hepatitis A as high as 500 per 100,000 (reported in the Central Asia Republics in 1998)
Future research should consider conducting cost-effectiveness analyses (CEA) taking into account the quality of post-treatment outcomes rather than assuming similar treatment outcomes among inpatients and outpatients. In conducting these analyses, researchers should consider two possible scenarios: (a) the treatment outcome for the inpatient setting is better than that for the outpatient setting (in this case, the inpatient setting is more costly and more effective than the outpatient setting, so an incremental cost-effectiveness analysis should be conducted); and (b) the treatment outcome for the outpatient setting is as good as or better than that for the inpatient setting (thus, because the cost of managing mild HAV infection for outpatients is lower than for inpatients, cost savings should be calculated).
Conclusion
From a societal perspective, the annual total treatment costs and productivity losses associated with mild HAV infection ranged from US$6.05 million to US$6.47 million for inpatients compared to a range of US$1.72 million to US$1.95 million for patients in the outpatient setting. The results of this study show that compliance with a change in the policy of hospitalization for patients with mild HAV infection could produce savings of US$4.62 million at the national level in Kazakhstan.
Appendix
Before beginning this study, we obtained institutional review board (IRB) approval (Protocol No. 2708) from the Centers for Disease Control and Prevention (CDC) Assurances-Human Subjects Office. In addition to CDC IRB approval, we also obtained an approval letter from the Ethics Committee Review from the Ministry of Health in Kazakhstan. Prior to administering questionnaires and interviews with patients, we explained the purposes of the study and obtained informed consent forms signed by all adult patients with mild HAV infection. Parents or guardians of all child participants with mild HAV infection under 18 years of age signed the informed consent forms for children. This study was conducted in collaboration with the Data for Decision Making and Policy Branch of the Division of International Health (DIH), Epidemiology Program Office (EPO) of CDC, the CDC Central Asian Regional Office (CDC/CAR), and the Almaty City Sanitary and Epidemiological Stations of the Ministry of Health in Almaty, Kazakhstan.
Acknowledgements
The authors thank colleagues at CDC, the CDC Central Asian Regional Office, and the Ministry of Health and health care practitioners in the Republic of Kazakhstan for their support in collecting the data. The study was conducted entirely at the Division of International Health, Epidemiology Program Office, Centers for Disease Control and Prevention.
The opinions expressed in this article do not necessarily represent those of the agencies of the United States Government
==== Refs
World Health Organization (WHO) Highlights on health in Kazakhstan 1999 Copenhagen: WHO Available online at: Accessed April 2005
Berge JJ Drennan DP Jacobs RJ Jakins A Meyerhoff AS Stubblefield W Weinberg M The cost of hepatitis A infections in American adolescents and adults in 1997 Hepatology 2000 31 469 73 10655272 10.1002/hep.510310229
World Health Organization (WHO) Protocol on water and health to the 1992 convention on protection and use of transboundary waters and international lakes progress report 1999–2004 Document No EUR/04/5046267/BD/6 2004 [Presented at the Fourth Ministerial Conference on Environment and Health, held in Budapest, Hungary, 23–25 June 2004].
Dzhumagulova AB Dzhumagulova SK Favorov M Necessity of quality control introduction for infectious diseases diagnostic laboratories in the Kazakhstan Republic From evidence to action Global strategies for public health in the new millennium, Training Program in Epidemiology and Public Health Intervention Network (TEPHINET) 1st International Conference April 17–21, 2000 2000 Ottawa, Canada: TEPHINET
Nurgalieva ZZ Malaty HM Graham DY Almuchambetova R Machmudova A Kapsultanova D Osato MS Hollinger FB Zhangabylov A Helicobacter pylori infection in Kazakhstan: effect of water source and household hygiene Am J Trop Med Hyg 2002 67 201 6 12389948
World Health Organization (WHO) European observatory on health care systems: health care systems in transition Kazakhstan Copenhagen: WHO Regional Office for Europe 1999 AMS 5001888 CARE 04 01 03 Target 19
Lesnicar G A prospective study of viral hepatitis A and the question of chronicity Hepatogastroenterology 1988 35 69 72 3371849
Dienstag JL Hepatitis A virus: virologic, clinical, and epidemiologic studies Human Pathology 1981 12 1097 106 6277764
Lee SD Asian perspective on viral hepatitis A Journal of Gastroenterology and Hepatology 2000 15 G94 9 11101002 10.1046/j.1440-1746.2000.02239.x
Palmovic D [Hepatitis A: results of the analysis of 3,111 hospitalized patients] Lijecnicki Vjesnik 1989 111 194 7 2796573
Lemon SM Type A viral hepatitis: epidemiology, diagnosis, and prevention Clinical Chemistry 1997 43 1494 9 9265900
Bromberg K Newhall PN Peter G Hepatitis A and meningoencephalitis Journal of the American Medical Association 1982 247 815 6276580 10.1001/jama.247.6.815
Zubkov I Shakhgil'dian IV Iashina TL [Prevalence of hepatitis A markers in families of patients treated at home and in hospitals] Voprosy Virusologii 1990 35 29 30 2363272
Shakhgil'dian IV Onishchenko GG Schastnyi EI Khukhlovich PA Doroshenko NV Stakhanova VM The current problems in the epidemiology and prevention of enteric viral hepatitis in Russia Zh Mikrobiol Epidemiol Immunobiol 1994 5 20 5 7879475
Contu P Masia G Scarpa B [Epidemiology of hepatitis A in Sardinia: mathematical model] Annali di igiene : medicina preventiva e di comunita 1989 1 1157 62 2483898
Delpech V Habib M Lin M McAnulty J Epireview: hepatitis A in New South Wales, 1991 – 2000 New South Wales (NSW) Public Health Bulletin 2001 12 255 258
Tong MJ el-Farra NS Grew MI Clinical manifestations of hepatitis A: recent experience in a community teaching hospital Journal of Infectious Diseases 1995 171 S15 8 7876641
Chin J Control of communicable diseases. Manual An official report of the American Public Health Association (APHA) 2000 17 Washington DC: APHA
European Expertise Service Kazakhstan economic trends October – December 1998 Government of the Republic of Kazakhstan and the European Commission Tacis Program 1998 Almaty: European Expertise Service
Ensor T Savelyeva L Informal payments for health care in the Former Soviet Union. Some evidence from Kazakhstan Health Policy and Planning 1998 13 41 49 10178184 10.1093/heapol/13.1.41
World Bank Project appraisal document on a proposed loan in the amount of US$ 42.50 million equivalent to the Republic of Kazakhstan for a health project in support of the first phase of a health reform program Europe and Central Asia Region The World Bank Report No 19007 World Bank, Washington, DC 1999
Ministry of Health Medical Statistical Bulletin Ministry of Health and Regions of Kazakhstan 1997 Committee for Statistics and Analysis. Kazakhstan
Ministry of Health, Education and Sports Medical Statistical Bulletin Health Committee and Statistical Press-bulletin 1998 Committee for Statistics and Analysis. Kazakhstan
Gardner MJ Altman DG Confidence intervals rather than p values: estimation rather than hypothesis testing British Medical Journal 1986 292 746 750 3082422
Dean AD Dean JQ Coulombier D Brendel KA Smith DC Burton AH Epi Info. [A word-processing, database and statistics program for epidemiology on microcomputers]. Version 6 1994 Atlanta: Centers for Disease Control and Prevention
SAS Institute, Inc SAS language and procedures Usage version 6 Cary (NC): SAS Institute Inc 1989 1
University of York Project preparation for the Kazakhstan health sector project: final report Centre for Health Economics 1998 University of York, UK
Ensor T Ryder S Thompson R Hospital resource utilization in Kazakhstan: a methodology for change Report to Know How Fund 1996
Ensor T Rittman J Thompson R, Ensor T, Rittman J Pilot health insurance initiatives Health care reform in Kazakhstan A compendium of papers prepared for the World Bank health reform technical assistance project 1995
Caravan "If you don't grease, you won't go" Caravan newspaper 19 April Almaty 1996
United Nations Development Programme (UNDP) Human development report 1997 UNDP. Kazakhstan
Chalmers TC Eckhardt RD Reynolds WE Cigarroa JG JrDeane N Reifenstein RW Smith CW Davidson CS The treatment of acute infectious hepatitis: controlled studies of the effects of diet, rest, and physical reconditioning on the acute course of the disease and incidence of relapses and residual abnormalities Journal of Clinical Investigation 1955 34 1163 235 14392230
Flanagan KT Lister J Infectious hepatitis in a village community Br Med J 1962 5301 376 378 13893428
| 15890070 | PMC1173129 | CC BY | 2021-01-04 16:39:14 | no | Cost Eff Resour Alloc. 2005 May 12; 3:4 | utf-8 | Cost Eff Resour Alloc | 2,005 | 10.1186/1478-7547-3-4 | oa_comm |
==== Front
Curr Control Trials Cardiovasc MedCurrent Controlled Trials in Cardiovascular Medicine1468-67081468-6694BioMed Central 1468-6708-6-71594387810.1186/1468-6708-6-7ResearchSymptomatic relief precedes improvement of myocardial blood flow in patients under spinal cord stimulation Diedrichs Holger [email protected] Carsten [email protected] Peter [email protected] Michael [email protected] Athanassios [email protected] Harald [email protected] Robert HG [email protected] Department III of Internal Medicine, University of Cologne, Cologne, Germany2 Clinic for Stereotactic and Functional Neurosurgery, University of Cologne, Cologne, Germany3 Department of Nuclear Medicine, University of Cologne, Cologne, Germany2005 19 5 2005 6 1 7 7 30 3 2005 19 5 2005 Copyright © 2005 Diedrichs et al; licensee BioMed Central Ltd.2005Diedrichs et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Spinal cord electrical stimulation (SCS) has shown to be a treatment option for patients suffering from angina pectoris CCS III-IV although being on optimal medication and not suitable for conventional treatment strategies, e.g. CABG or PTCA. Although many studies demonstrated a clear symptomatic relief under SCS therapy, there are only a few short-term studies that investigated alterations in cardiac ischemia. Therefore doubts remain whether SCS has a direct effect on myocardial perfusion.
Methods
A prospective study to investigate the short- and long-term effect of spinal cord stimulation (SCS) on myocardial ischemia in patients with refractory angina pectoris and coronary multivessel disease was designed. Myocardial ischemia was measured by MIBI-SPECT scintigraphy 3 months and 12 months after the beginning of neurostimulation. To further examine the relation between cardiac perfusion and functional status of the patients we measured exercise capacity (bicycle ergometry and 6-minute walk test), symptoms and quality of life (Seattle Angina Questionnaire [SAQ]), as well.
Results
31 patients (65 ± 11 SEM years; 25 male, 6 female) were included into the study. The average consumption of short acting nitrates (SAN) decreased rapidly from 12 ± 1.6 times to 3 ± 1 times per week. The walking distance and the maximum workload increased from 143 ± 22 to 225 ± 24 meters and 68 ± 7 to 96 ± 12 watt after 3 months. Quality of life increased (SAQ) significantly after 3 month compared to baseline, as well. No further improvement was observed after one year of treament. Despite the symptomatic relief and the improvement in maximal workload computer based analysis (Emory Cardiac Toolbox) of the MIBI-SPECT studies after 3 months of treatment did not show significant alterations of myocardial ischemia compared to baseline (16 patients idem, 7 with increase and 6 with decrease of ischemia, 2 patients dropped out during initial test phase). Interestingly, in the long-term follow up after one year 16 patients (of 27 who completed the one year follow up) showed a clear decrease of myocardial ischemia and only one patient still had an increase of ischemia compared to baseline.
Conclusion
Thus, spinal cord stimulation not only relieves symptoms, but reduces myocardial ischemia as well. However, since improvement in symptoms and exercise capacity starts much earlier, decreased myocardial ischemia might not be a direct effect of neurostimulation but rather be due to a better coronary collateralisation because of an enhanced physical activity of the patients.
Angina pectorisspinal cord stimulationmyocardial ischemiaexercise capacityMIBI-SPECT
==== Body
Introduction
In spite of continuous improvements in revascularization techniques, there remain patients ineligible for coronary artery bypass graft surgery (CABG) and coronary angioplasty. Those patients frequently suffer from severe angina, CCS (Canadian Cardiovascular Society) class III to IV; their complaints may not be managed even with optimized drug treatment. An estimated 0.5–1% of catheterized patients belongs to this category. Taking into account the above numbers of catheterizations, in Germany alone there are up to 6000 patients per year suffering from angina-related pain without an option for revascularization.
Those patients master their daily lives only by an excessive use of short-acting nitrates and avoiding physical activity. Regular use of morphine is not uncommon. A vicious circle is established: The pain limits physical activity thus inducing further decrease of physical fitness. Frequent hospitalizations, visits to the attending physician and the need for intensive care (when a myocardial infarction is suspected) cause immense costs for the health care system.
Based on the "gate control theory" [1] Wall and Sweet [2] were the first to use electric stimulation of spinal nerves or dorsal roots in treating chronic pain. This new technique called spinal cord stimulation (SCS) caused a significant decrease in ischemia-related pain and an increased perfusion of capillaries in skeletal muscle and skin through stimulating different types of neurons and fibers in the spinal cord.
In recent years the number of studies showing decreasing symptoms, improved quality of life and less signs of myocardial ischemia (mostly measured by ECG) in SCS-treated patients rose continuously [3-13]. However, the exact mode of action and the influence on myocardial perfusion are yet unknown. Very recently Jessurun and co-workers could demonstrate an improved myocardial perfusion in TENS (transcutaneous electric neurostimulation) treated patients with syndrome X after 4 weeks [14]. Besides a study with 9 patients and a 6 week follow up [15], there exist no long-term data about myocardial ischemia under SCS in patients with coronary artery disease. In our trial, we therefore investigated not only the development of symptoms, quality of life and exercise capacity but also the myocardial perfusion measured by MIBI-SPECT (single photon emission computer tomography) in a one year follow up of 31 patients with CAD and intractable angina.
Materials and methods
Patients
Between March 1999 and May 2003 31 patients were included in the study. Criteria for accepting a patient was a refractory angina CCS III-IV in spite of optimized medical therapy (ACE inhibitors, aspirin, β-blockers, statins, calcium channel blockers, nitrates). All patients had a coronary angiogram in the last 3 months before screening and were discussed in detail for possibility of CABG and/or PCI (percutaneus coronary intervention) by a specialized team of cardiologists and heart surgeons. Only if none of these revascularization techniques was considered as suitable was the patient included in the trial. Since relieving of pain is the main aim of SCS treatment we only included patients with angina CCS III-IV without relevant symptoms of heart failure. Hence, patients with a left ventricular ejection fraction less than 40% or a NYHA class greater than II were excluded from the study. All inclusion and exclusion criteria are listed in table 1.
Table 1 Inclusion and exclusion criteria
Inclusion criteria
Chronic coronary artery disease (CAD)
Evidence of ischemia in MIBI-SPECT examination
Coronary angiogram in the last 3 months
Angina pectoris, CCS III-IV
Optimal medical treatment (Beta-blocker, ACE-inhibitor or AT1-antagonist, Ca2+-antagonist, ASS, CSE-inhibitor, long-acting nitrate [LAN])
Not suitable for percutaneous coronary intervention (PCI) or aortocoronary bypass surgery (CABG) after discussion with a team of specialists (cardiologists and heart surgeons)
Exclusion criteria
Myocardial infarction or unstable in the last 3 months
Pacemaker with unipolar electrode
Relevant valvular heart disease
Symptomatic heart failure > NYHA II
Left ventricular ejection fraction (LVEF) < 40%
Implantation of the electrode
The electrode was placed in the epidural space at the level of Th4-5 through a small skin incision under local anesthesia, and then it was moved up to C7-Th1 subcutaneously. Correct placement was defined by test-stimulation and interviewing the patient. Patients should experience paraesthesia in the same dermatome normally affected by angina. After final placement, the electrode was connected to an external stimulator, which allowed the patient to test the effects of SCS for 3–4 days. Afterwards the final stimulator (Medtronic Itrel III) was implanted subcutaneous in the lateral abdomen and connected to the electrode. The stimulator was controlled through an external device by the patient allowing to change the amplitude of the stimulus or to switch it on/off.
During the course of the study, examinations were scheduled after four weeks, three months (with MIBI-SPECT and SAQ), twelve month (with MIBI-SPECT and SAQ) and whenever wished by the patients.
Exercise capacity
The bicycle ergometry protocol began at a workload of 25 Watt and increases in 25 Watt increments every 2 minutes. Exercise was terminated by the patient, when angina pectoris occurred or he was exhausted. Criteria for early termination of exercise were ischemic ST-segment depression > 2 mm; ventricular or supraventricular tachycardia; and a decrease or abnormal elevation in systolic blood pressure. In our study in none of the patients termination was necessary because of tachycardia or abnormal blood pressure.
The six-minute walk test was performed using an internal hallway with a marked distance of 50 meters. Patients were instructed to walk the distance at their own pace but to cover as much ground as possible. They were allowed to stop and rest during the test if needed.
Nitrate intake and Seattle Angina Questionnaire (SAQ)
The SAQ is a self-administered, disease-specific measure for patients with CAD that has previously been demonstrated to be valid, reproducible, and sensitive to clinical change [16-18]. The SAQ measures five dimensions of coronary artery disease: patients' physical limitations caused by angina, the frequency of and recent changes in their symptoms (angina frequency and angina stability), their satisfaction with treatment and the degree to which they perceive their disease to affect their quality of life. Each scale is transformed to a score of 0 to 100, where higher scores indicate better function (e.g. less physical limitation, less angina, and better quality of life).
The amount of short acting nitrates (SAN) during one week was reported by the patients at every visit in the clinic. For our analysis we used average SAN consumption after 3 and 12 months.
Myocardial scintigraphy (MIBI-SPECT)
SPECT- examinations were run on two days, one day under resting conditions, the second day after stress, using 740 MBq 99-Technetium-MIBI. Stress was induced either by physical exercise (bicycle ergometry) or by dobutamine injection (10, 20, 30, 40 μg per /kg/ min). Scanning was run one hour after the injection in the stress examinations and two hours after resting-conditions. To compare conditions before SCS implantation and during follow up stress scans were made at a comparable rate pressure product.
The camera was a three-head gamma camera with a LEHR- (low-energy-high-resolution) -collimator (prism 3000, Picker/Philips; matrix 128 × 128, 40 steps with 3° each, 20 seconds per step). For generating tomograms in short and long axis views, a filtered backprojection technique with additional semiquantitative polarmap analysis was used. SPECT examinations took place prior to the implantation of the SCS system as well as three and twelve months after.
Myocardial scintigraphy is usually used to access regional perfusion, e.g. after a heart attack or PCI. However, if the total myocardial perfusion in one patient is to be examined over a course of time, one frequently encounters the reduction of ischemia in one area combined with increased ischemia in another, e.g. improved perfusion in the anterior myocardium with reduced perfusion in the posterior myocardium. This makes it difficult to judge whether conditions have improved or actually worsened. To meet this problem, results were interpreted with the „Emory Cardiac Toolbox“ (Emory Medical Device Group). This software compares the perfusion found in the patient to a virtual normal perfusion, setting the normal nuclide distribution- that is the normal perfusion- as 1. If a patient has a score of 0.5 (50% of normal radionuclide distribution and myocardial perfusion) in the initial scan and reaches a score of 0.8 (80% of normal radionuclide distribution and myocardial perfusion) in follow-up examinations this means total perfusion has improved, even if perfusion of some areas has decreased. The score is not determined in direct comparison of two SPECT-scans, but by comparing each scan to virtual normal results. This software makes it possible to monitor the development of myocardial perfusion over a course of time.
In spite of this method, accessing the total perfusion remains more complex than judging regional perfusion (e.g. after PCI or heart attack). We therefore decided to limit our interpretation of data on the development of myocardial perfusion in the course of the study as follows: A score improved at least 0.2 was judged an improvement; a score lowered by 0.2 was regarded as a worsened state. A score of ± = 0.1 was defined as unchanged. We left out any semi-quantitative scores with standard deviation as we felt they would over-interpret the data.
Statistical analysis
Data are presented as mean ± 95 % confidence interval. Differences among groups were compared by an unpaired t-test. Significance was assigned to a value of p < 0.05.
Results
Patients
The mean age was 65 years (± 11). As angina is more common in men, there were more men (n = 26) than women (n = 5) enrolled. 26 Patients suffered from a 3-vessel coronary artery disease, 5 from a 2-vessel disease. All patients had undergone bypass surgery (n = 24) and/or PCI (stent) (n = 28); five patients already underwent transmyocardial laser revascularization. Detailed patient characteristics are presented in table 2. Drug therapy had been optimized; apart from morphine intake it was not changed significantly during the trial's course (see table 3).
Table 2 Patient characteristics at baseline
Gender: male/female 26 / 5
Mean Age (range), years 65 (35–79)
Diagnosis
3-vessel coronary artery disease 26 (84%)
2-vessel coronary artery disease 5 (16%)
History, number of patients and percentage
Myocardial infarction 23 (74%)
Heart Failure >NYHA II 0 (0%)
Previous coronary intervention (PTCA/Stent) 28 (90%)
Previous CABG 24 (77%)
TMLR 5 (16%)
Cerebrovascular Disease (stroke and TIA) 5 (16%)
Symptomatic peripheral vascular disease 4 13%)
Hypertension 16 (52%)
Diabetes mellitus 7 (23%)
Hyperlipoproteinemia 23 (74%)
Adipositas (BMI >30) 8 (26%)
Nicotine abuse past/current 24 / 6 (77% / 19%)
NYHA = New York Heart Association, PTCA = percutaneous transluminal coronary angioplasty, CABG = coronary artery bypass graft, TMLR = transmyocardial laser revascularization, TIA = transitoric ischemic attack, BMI = body mass index
Table 3 Medication of the patients at baseline and one year follow up
Baseline (n = 31) 1 Year (n = 27)
Beta-blocker 31 (100%) 27 (100%)
ACE-Inhibior/AT1-Antagonist 29 (94%) 26 (96%)
Ca++-Antagonist 26 (84%) 24 (89%)
CSE-inhibitor 31 (100%) 27 (100%)
Long-acting nitrate 31 (100%) 25 (93%)
Morphine derivate 12 (39%) 1 (4%)
Medication of the patients at baseline (n = 31) and one year follow up (n = 27). Before one year follow up SCS device was explanted in 3 patients (2 during test phase, one after 8 months). One patient died before last visit.
2 patients did not feel a positive effect of SCS on their symptoms in the test period (after implantation of the electrodes and using the external stimulator) and therefore dropped out during the initial phase of the study. SCS device was explanted in another patient after 8 months because of a lack of anti-anginal effect, too. Unfortunately, after explantation of the SCS device none of the 3 patients joined further follow up visits or MIBI-SPECT examinations. One patient died because of a liver cell cancer one month before one year visit. Cancer was not known at time of inclusion in the study.
Exercise capacity
The physical fitness of patients improved as measured by six-minute walk test and bicycle ergometry already after 3 months (142.74 ± 22.13 vs. 224.83 (± 23.96) meters and 67.50 ± 7.11 vs. 96.43 ± 11.74 watt) and maintained at this level after one year (250.56 ± 25.24 meters; 98.08 ± 8.12 watt, see table 4). The 3 months follow up was finished by 29, the one year follow up by 27 patients (see above).
Table 4 SAN consumption per week and results of bicycle ergometry and 6-minute walk test at baseline and follow up
Baseline 3 Months 1 Year
SAN Consumption amount/week 12.35 (± 1.6) 3.38 (± 0.96)* 2.78 (± 0.90)*
Bicycle Ergometry watt 67.50 (± 7.11) 96.43 (± 11.74)* 98.08 (± 8.12)*
6-Minute Walk meters 142.74 (± 22.13) 224.83 (± 23.96)* 250.56 (± 25.24)*
* = p < 0.05 compared to baseline. Results are listed in mean ± 95% confidence interval.
Symptoms, nitrate intake and Seattle Angina Questionnaire (SAQ)
Apart from the three patients who decided to have the electrodes explanted as they felt no relieve in symptoms, all other patients felt a significant decrease of symptoms due to treatment with SCS (28 out of 31).
Eleven out of twelve patients treated with morphine at baseline no longer needed morphine at all; one patient was at least able to reduce the dose from 60 mg morphine sulphate (MST®) to 20 mg per day. Two patients no longer needed long-acting nitrates (see table 3). The use of short-acting nitrates (SAN) was lowered significantly, as well (12.35 ± 1.6 vs. 3.38 ± 0.96 and 2.78 ± 0.90 times per week, see table 4).
The Seattle Angina Questionnaire showed a significant increase in quality of Life after 3 months under SCS treatment (SAQ score 39 at baseline vs. 73). After one year the improved quality of life maintained (score 75). Scores for physical limitation 33 vs. 47 [3 months] and 48 [1 year]), angina stability (30 vs. 51 and 53) and frequency (26 vs. 53 and 54) improved significantly, as well (see figure 1).
Figure 1 Results from the Seattle Angina Questionnaire (SAQ). * = p < 0.05 compared to baseline. Results are in mean ± 95% confidence interval (error indicator).
Myocardial perfusion (MIBI-SPECT)
As described above, data were interpreted with the „Emory Cardiac Toolbox“ software. The examinations 3 months after SCS implantation (n = 29) showed unchanged SPECT results in most patients (n = 16). Only 6 patients showed a better myocardial perfusion while in 7 ischemia worsened (figure 2). Interestingly, a shift towards an improved myocardial perfusion could be found after one year. Of 27 examined patients a worsened situation compared to baseline was found only in one patient. 16 patients showed clearly less myocardial ischemia. Results of the MIBI-SPECT analysis with the "Emory Cardiac Toolbox" software are shown in figure 2. Black arrows indicate the shift of the patients between the three groups (worse, equal or improved myocardial perfusion) during 3 and 12 months follow up. An exemplary scintigram prior to and twelve months after implantation is shown in figure 3.
Figure 2 Results of the MIBI-SPECT analysis with the "Emory Cardiac Toolbox" software. Black arrows indicate the shift of the patients between the three groups (worse, equal or improved myocardial perfusion) during 3 and 12 months follow up.
Figure 3 Scintigram of one patient prior to (left) and twelve months after (right) implantation. Each first line shows a stress scan, the second line the appendant rest scan. The third line shows again a stress scan etc. After one year clearly reduced hibernation resp. prolonged ischemia of the anterior LV wall (arrows vertical long axis views). Less pronounced reduction of the ischemia of the lateral LV wall (arrow heads short axis views).
Complications
No serious complications were caused by the implantation of the neurostimulators. Neither injuries of the spinal cord nor infections occurred. The major problem in the beginning were a dislocation of the electrodes (n = 4). This could be remedied without any difficulties by surgical re-intervention. As the operating surgeons became more experienced, electrode dislocations requiring surgical intervention did not happen any longer. Small dislocations could be handled easily by re-programming the stimulation parameters.
Discussion
This is the first clinical report with a long term follow up of myocardial perfusion measured by MIBI-SPECT in patients with multivessel coronary artery disease under spinal cord stimulation (SCS). Like in prior investigations we additionally measured symptoms, quality of life and exercise capacity of the patients, as well.
There was an early reduction of angina related symptoms under SCS treatment. Patients showed not only a significant reduction of SAN consumption (table 4) but also less use of morphine derivates already in the first weeks under neurostimulation therapy (table 3). The analysis of the self-administered Seattle Angina questionnaire (SAQ) resulted in improved scores for physical limitation, angina frequency, angina stability and quality of life after 3 months with unchanged results after one year (figure 1).
In opposite to the early functional improvement of the patients (symptoms, physical activity, quality of life), myocardial ischemia measured by MIBI-SPECT was not decreased after 3 months. 22 patients showed unchanged or even more ischemia compared to baseline before SCS implantation (figure 2). After one year – while functional parameters (exercise capacity, quality of life etc.) did not show a further change – myocardial perfusion was remarkable improved in many patients (16 of 27). Only one patient still had more cardiac ischemia than in baseline examination (figure 2). Interestingly, the score for physical limitation (SAQ) of this patient did not improve very much, as well (55 [baseline), 62 [3 months], 58 [1 year]).
Since a direct effect of SCS on myocardial perfusion should be established early after beginning of the neurostimulation, one would have expected to see alterations in the MIBI-SPECT after 3 months. The improved myocardial perfusion found after one year might therefore be due to the development of collateral vessels associated with increased physical fitness.
Two recent studies reported alterations in myocardial blood flow already after 4 or 6 weeks [22,23]. Both found a homogenization of myocardial perfusion measured by positron emission tomography (PET) in patients with multivessel disease or syndrome X. They suggested that the change in myocardial blood flow can be denoted as a steal phenomenon at the microcirculatory level eventually mediated by a direct effect of SCS on coronary vasomotion. However, they could not find an improved resting myocardial blood flow in their studies, as well. Hautvast and co-workers even found a decreased flow reserve under dipyridamole stress [22]. Thus, our study is the first to show that myocardial perfusion can improve under neurostimulation in patients with coronary multivessel disease. Since we applied a different method to measure myocardial ischemia, we cannot provide data regarding a possible homogenization of cardiac blood flow in the early phase of spinal cord stimulation. But our data suggest that the main effect of SCS treatment is anti-symptomatic and changes in myocardial ischemia are rather secondary and might be due to increased physical activity. This hypothesis is supported by data of Belardinelli and co-workers, who demonstrated that moderate exercise training improved myocardial perfusion measured by thallium scintigraphy in patients with chronic coronary artery disease [19]. If this decrease of myocardial ischemia does also improve the prognosis of the patients cannot be answered yet.
Nevertheless, the impressive improvement of angina-related symptoms, the exercise ability and last but not least the increase in quality of life of 90% (28/31) of our patients in a one year follow up supports the data of other studies which treated patients with CAD and refractory angina with spinal cord stimulation.
In a recent study, which included 32 patients with a follow up of 65 months, SCS relieved angina effectively also after long-term treatment without development of tolerance. SAQ scores still were improved after years [20]. Maintenance of increased exercise ability for years might be an ongoing stimulus for coronary collateralization.
In conclusion electrical spinal cord stimulation is a valuable therapeutic option for the treatment of refractory angina pectoris in patients not suitable for coronary revascularization procedures. Additionally, the symptomtic relief may allow more physical activity which might induce coronary collateralization resulting in an improved myocardial perfusion.
Study limitations
Since it is difficult to conduct placebo-controlled trials with electrical neuromodulation, because there is no alternative for the paraesthesia induced by the neurostimulators, our study has -like others- no placebo group. However, measurement of myocardial perfusion with MIBI-SPECT is an objective parameter not impressionable by the patient [21,22]. As placebo effect is generally believed to decrease with time [23-26] the sustained relief of symptoms over one year in this study seem to contradict the estimation that placebo effects are the major mode of action of SCS treatment. To finally prove whether the altered myocardial perfusion is due to direct SCS effects or increased exercise ability with improved collateralization a control group without SCS but with exercise training would be necessary.
==== Refs
Melzack R Wall PD Pain mechanisms: a new theory Science 1965 150 971 979 5320816
Wall PD Sweet WH Temporary abolition of pain in man Science 1967 155 108 109 6015561
Mannheimer C Augustinsson LE Carlsson CA Epidural spinal electrical stimulation in severe angina pectoris Br Heart J 1988 59 56 61 3257701
Sanderson JE Epidural neurostimulators for pain relief in angina Br Heart J 1990 63 141 3 2183856
de Jongste M Haustvat R Hillege H Efficacy of spinal cord stimulation as adjuvant therapy for intractable angina pectoris: a prospective, randomised clinical study J Am Coll Cardiol 1994 23 1592 7 8195519
Sanderson JE Brooksby P Waterhouse D Epidural spinal electrical stimulation for severe angina: a study of its effects on symptoms, exercise tolerance and degree of ischemia Eur Heart J 1992 13 628 33 1618204
Mannheimer C Eliasson T Andersson B Effects of spinal cord stimulation in angina pectoris induced by pacing and possible mechanisms of action Br Med J 1993 307 477 80 8400930
de Jongste M Haaksma J Haustvay R Effects of spinal cord stimulation on myocardial ischemia during daily life in patients with severe coronary artery disease Br Heart J 1994 71 413 18 8011403
Eliasson T Jern S Augustinsson LE Mannheimer C Safety aspects of spinal cord stimulation in severe angina pectoris Coron Artery Dis 1994 5 845 50 7866604
Sanderson J Ibrahim B Waterhouse D Spinal electrical stimulation for intractable angina: long-term clinical outcome and safety Eur Heart J 1994 15 810 14 8088270
Andersen C Hole P Oxhoj H Does pain relief with spinal cord stimulation conceal myocardial infarction? Br Heart J 1994 71 419 21 8011404
Eliasson T Augustinsson LE Mannheimer C Spinal cord stimulation in severe angina pectoris: presentation of current studies, indications and practical experience Pain 1996 65 169 79 8826504 10.1016/0304-3959(95)00238-3
Jessurun G Vaarwerk I de Jongste M Sequelae of spinal cord stimulation for refractory angina pectoris: reliability and safety profile of long-term clinical application Coron Artery Dis 1997 8 33 8 9101120
Jessurun G Hautvast RWM Tio RA deJongste MJL Electrical neuromodulation improves myocardial perfusion and ameliorates refractory angina pectoris in patients with syndrome X: fad or future? Eur J Pain 2003 7 507 512 14575663 10.1016/S1090-3801(03)00022-3
Hautvast RWM Blanksma PK DeJongste MJL Effect of spinal cord stimulation on myocardial blood flow assessed by positron emission tomography in patients with refractory angina pectoris Am J Cardiol 1996 77 462 7 8629585 10.1016/S0002-9149(97)89338-1
Spertus JA Winder JA Dewhurst TA Development and evaluation of the Seattle Angina Questionnaire: a new functional status measure for coronary artery disease J Am Coll Cardiol 1995 25 333 341 7829785 10.1016/0735-1097(94)00397-9
Spertus JA Winder JA Dewhurst TA Monitoring the quality of life in patients with coronary artery disease Am J Cardiol 1994 74 1240 1244 7977097 10.1016/0002-9149(94)90555-X
Hofer S Benzer W Schussler G Health-related quality of life in patients with coronary artery disease treated for angina: validity and reliability of German translations of two specific questionnaires Qual Life Res (Netherlands) 2003 12 2 199 212 10.1023/A:1022272620947
Belardinelli R Georgiou D Ginzton L Giovanni Cianci G Purcaro A Effects of moderate exercise training on thallium uptake and contractile response to low-dose dobutamine of dysfunctional myocardium in patients with ischemic cardiomyopathy Circulation 1998 97 553 561 9494025
Ekre O Norrsell H Währborg P Eliasson T Mannheimer C Temporary cessation of spinal cord stimulation in angina pectoris – effects on symptoms and evaluation of long-term effect determinants Coron Artery Dis 2003 14 323 327 12826932 10.1097/00019501-200306000-00008
Schafers M Bull U Bengel F Comparing apples with addled pears. The need to optimize study protocols to compare imaging modalities for assessing myocardial perfusion Nuklearmedizin 2004 43 105 106 15316575
Cholewinski W Stefaniak B Poniatowicz-Frasunek E Tarkowska A Reduction of the LVEF measured with gSPECT after 1–3 hours after physical exercise in CAD Nuklearmedizin 2004 43 150 157 15480503
Kienle GS Kiene H The powerful placebo effect: fact or fiction? J Clin Epidemiol 1997 50 1311 1318 9449934 10.1016/S0895-4356(97)00203-5
Brown WA The placebo effect Sci Am 1998 278 90 95 9418301
Boissel JP Philippon AM Gauthier E Schbath J Destors JM Time course of long-term placebo therapy effects in angina pectoris Eur Heart J 1986 7 1030 1036 3104043
Hrobjartsson A Gotzsche PC Is the placebo powerless? N Engl J Med 2001 344 1594 1602 11372012 10.1056/NEJM200105243442106
| 15943878 | PMC1173130 | CC BY | 2021-01-04 16:47:32 | no | Curr Control Trials Cardiovasc Med. 2005 May 19; 6(1):7 | utf-8 | Curr Control Trials Cardiovasc Med | 2,005 | 10.1186/1468-6708-6-7 | oa_comm |
==== Front
Emerg Themes EpidemiolEmerging Themes in Epidemiology1742-7622BioMed Central London 1742-7622-2-21590453810.1186/1742-7622-2-2CommentaryAuthor's response to comments on "Epidemiologic Measures and Policy Formulation" Greenland Sander [email protected] Departments of Epidemiology and Statistics, University of California, Los Angeles, USA2005 19 5 2005 2 2 2 1 5 2005 19 5 2005 Copyright © 2005 Greenland; licensee BioMed Central Ltd.2005Greenland; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
==== Body
I see no important disagreement between me and the commentators, but disagreement does exist on these topics. I would classify opposing views into two major categories. On one side, some writers assert that causal inference can and should be done without counterfactuals. In my view, Dawid [1,2] is a moderate on that side, as he deploys devices that are isomorphic to counterfactuals, so the difference seems mostly one of labeling and emphasis (which is not always unimportant). More radical counterfactual deniers include Shafer [3], who appears mostly upset because counterfactual models continue to weave into the foundation of statistics, econometrics, sociology, and health sciences, while his approach [4] appears destined for the dustbin, along with other truly noncounterfactual theories of causation. Pearl [5] gives a succinct account of the failings of these theories (reference 5, section 7.5), noting (as do Greenland and Brumback [6]) that the causal models entering into scientific teaching and application (including causal graphs, causal "pies," and structural equations) have mappings into counterfactual formalisms.
The target of my article was the other side, those who take counterfactuals uncritically or superficially, without paying enough attention to what these hypothetical quantities are supposed to mean. My article originated as a chapter in a WHO volume [7]. This volume arose from a conference which seemed a festival of counterfactual abuse, rife with talk of cause-of-death removal as if it were an intervention. It is disheartening if not frightening to witness discussion of global health policy framed in such terms. In this context, the concerns expressed by Dawid [1,2] about counterfactuals seem reserved.
Counterfactual abuse can be diminished by connecting potential outcomes to interventions. Susser and Schwartz [8] point out that this connection is needed for lifestyle risk factors (smoking, physical inactivity, etc.) just as for social factors. I agree; risk-factor epidemiology could better serve public health if it addressed what could be done, rather than estimating effects of the unattainable (like removal of all tobacco exposure), without regard to how change is brought about.
Becoming more realistic involves more than just operationalizing the exposure (right-hand) side of the structural equation; one also needs to expand the left-hand side to consider the full spectrum of intervention effects, such as all effects of smoking cessation (e.g., weight gain, depression). The traditional narrow focus on a few prominent endpoints (like cancer and cardiovascular disease), encouraged by the case-control viewpoint, has discouraged grappling with the multivariate complexity of outcomes as well as exposures. Worse, in the smoking context, there may be a bias against acknowledging that one of our most damaging population exposures (tobacco) may bring worthwhile benefits to a non-negligible portion of the population – not just medical benefits like Parkinsonism prevention, but also psychologic benefits like enhanced sense of well-being, which are hard to measure and weigh against costs. If we really believe in informed consent, then we must inform the public about how lifestyle choices are not just about lifespan maximization, but are also choices of how to live and die. This view will not sit well with those for whom good sensations are evil if the sensations do not come from sanctified sources like religious faith, licensed entertainment, or prescription drugs.
==== Refs
Dawid AP Causal inference without counterfactuals (with discussion) J Am Stat Assoc 2000 95 407 448
Dawid AP Comment on Maldonado GM, Greenland S, "Estimating causal effects." Int J Epidemiol 2002 31 421 438 10.1093/ije/31.2.429
Shafer G Comment on Maldonado GM, Greenland S, "Estimating causal effects." Int J Epidemiol 2002 31 421 438 10.1093/ije/31.2.434
Shafer G The art of causal conjecture 1996 Cambridge, MA: MIT Press
Pearl J Causality: models, reasoning and inference 2000 Cambridge: Cambridge University Press, UK
Greenland S Brumback B An overview of relations among causal modelling methods Int J Epidemiol 2002 31 1030 7 12435780 10.1093/ije/31.5.1030
Murray CJL Salomon JA Lopez AD (eds) Summary measures of population health 2002 Cambridge, MA: Harvard University Press / World Health Organization
Susser S Schwartz S Are social causes so different from all other causes? A comment on Sander Greenland Emerg Themes Epidemiol 2005
| 15904538 | PMC1173131 | CC BY | 2021-01-04 16:38:27 | no | Emerg Themes Epidemiol. 2005 May 19; 2:2 | utf-8 | Emerg Themes Epidemiol | 2,005 | 10.1186/1742-7622-2-2 | oa_comm |
==== Front
Filaria JFilaria Journal1475-2883BioMed Central London 1475-2883-4-41593263610.1186/1475-2883-4-4ResearchDiethylcarbamazine activity against Brugia malayi microfilariae is dependent on inducible nitric-oxide synthase and the cyclooxygenase pathway McGarry Helen F [email protected] Leigh D [email protected] Mark J [email protected] Filariasis Research Laboratory, Molecular and Biochemical Parasitology, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool L3 5QA, UK2005 2 6 2005 4 4 4 28 10 2004 2 6 2005 Copyright © 2005 McGarry et al; licensee BioMed Central Ltd.2005McGarry et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Diethylcarbamazine (DEC) has been used for many years in the treatment of human lymphatic filariasis. Its mode of action is not well understood, but it is known to interact with the arachidonic acid pathway. Here we have investigated the contribution of the nitric oxide and cyclooxygenase (COX) pathways to the activity of DEC against B. malayi microfilariae in mice.
Methods
B. malayi microfilariae were injected intravenously into mice and parasitaemia was measured 24 hours later. DEC was then administered to BALB/c mice with and without pre-treatment with indomethacin or dexamethasone and the parasitaemia monitored. To investigate a role for inducible nitric oxide in DEC's activity, DEC and ivermectin were administered to microfilaraemic iNOS-/- mice and their background strain (129/SV). Western blot analysis was used to determine any effect of DEC on the production of COX and inducible nitric-oxide synthase (iNOS) proteins.
Results
DEC administered alone to BALB/c mice resulted in a rapid and profound reduction in circulating microfilariae within five minutes of treatment. Microfilarial levels began to recover after 24 hours and returned to near pre-treatment levels two weeks later, suggesting that the sequestration of microfilariae occurs independently of parasite killing. Pre-treatment of animals with dexamethasone or indomethacin reduced DEC's efficacy by almost 90% or 56%, respectively, supporting a role for the arachidonic acid and cyclooxygenase pathways in vivo. Furthermore, experiments showed that treatment with DEC results in a reduction in the amount of COX-1 protein in peritoneal exudate cells. Additionally, in iNOS-/- mice infected with B. malayi microfilariae, DEC showed no activity, whereas the efficacy of another antifilarial drug, ivermectin, was unaffected.
Conclusion
These results confirm the important role of the arachidonic acid metabolic pathway in DEC's mechanism of action in vivo and show that in addition to its effects on the 5-lipoxygenase pathway, it targets the cyclooxygenase pathway and COX-1. Moreover, we show for the first time that inducible nitric oxide is essential for the rapid sequestration of microfilariae by DEC.
==== Body
Background
Diethylcarbamazine citrate (DEC) has been used in the treatment and control of lymphatic filariasis (caused by the nematodes Wuchereria bancrofti, Brugia malayi and B. timori) since 1947 and it continues to play an important role, being one of the drugs used in the Global Programme for the Elimination of Lymphatic Filariasis [1]. However, despite this long period of use, DEC's mode of action is still poorly understood. Particularly intriguing is the marked contrast between its rapid action in vivo and the lack of significant activity in vitro. In vivo, the response is rapid: within a few minutes of treatment, peripheral blood microfilariae counts drop dramatically [2]. The poor in vitro activity indicates that DEC probably requires some host factor for its activity, and previous work has highlighted the role of the innate immune system and leucocytes independent of T cells and complement in the activity of DEC [3,4].
DEC also has anti-inflammatory properties, as a result of its interference with arachidonic acid metabolism [4]. The products of the arachidonic acid metabolic pathway, eicosanoids, have a number of biological effects, including inhibition of platelet aggregation; regulation of leucocyte activation and adherence; mediation of granulocyte chemotaxis and degranulation; and promotion of vasodilatation [5]. It is well known that DEC inhibits enzymes of the 5-lipoxygenase pathway, leukotriene synthases [6,7]. Additionally, in vitro, DEC blocks endothelial cell production of the cyclooxygenase (COX) pathway products prostaglandin (PG) E2, prostacyclin (PGI2) and thromboxane A2 but has no effect on platelet prostanoid production [8]. In addition, the drug increases the rate and degree of microfilariae adherence to granulocytes, with eosinophil adhesion in particular being augmented [9-11]. Nevertheless, a role for some of these activities has yet to be demonstrated in vivo and so we have used a mouse model to identify the host factors responsible for the rapid efficacy of DEC.
The arachidonic acid pathway includes lipoxygenase and cyclooxygenase enzymes. The COX pathway has similarities with the nitric oxide (NO) pathway, since both have constitutive and inducible isoforms of their enzymes and are key regulators of inflammatory responses [12,13]. The COX and NO pathways are known to interact with each other, with there being 'cross-talk' between NO/PGE2 and iNOS/COX which is generally stimulatory but may also be inhibitory [14,15]. Therefore, we have used a combination of pharmacological inhibitors and gene-knockout technology to elucidate the role of these two pathways in DEC's activity in vivo.
Materials and methods
Parasites and mice
Microfilariae of Brugia malayi were obtained from TRS Laboratories (Georgia, USA), suspended in RPMI 1640 with 5% FCS, and 300000 parasites in a volume of 200 μl were injected intravenously into mice. Systemic parasitaemia was allowed to equilibrate for 24 hours, then heparinised blood samples were taken by tail bleeding and parasitaemia was measured. Mice were allocated into age- and size-matched groups and treated as described below. All animals were kept in the Biological Services Unit of the University of Liverpool in accordance with Home Office regulations and were fed and watered ad libitum. BALB/c mice were kept under standard conditions, and the 129/SV and targeted knockout of the iNOS gene (iNOS-/-, kindly provided by Prof. F.Y. Liew, University of Glasgow) strains in filter-top cages.
Action of DEC against microfilariae in vivo in mice
Three BALB/c mice infected with B. malayi microfilariae were treated with a single, oral dose of DEC 100 mg/kg [3] (Sigma, U.K) in distilled water and the parasitaemia monitored from five minutes to two weeks post treatment. To investigate the role of the arachidonic acid metabolic pathway in the mode of action of DEC, indomethacin (10 mg/kg in 1% ethanol), water-soluble dexamethasone (3 mg/kg in water, both obtained from Sigma, U.K.), or vehicle was given by intra-peritoneal (i.p.) injection to microfilaraemic male BALB/c mice 30 minutes before oral DEC administration (100 mg/kg, three mice per treatment group). One animal was kept as an untreated control. Heparinised blood samples were taken at intervals post treatment for measurement of parasitaemia. Experiments were repeated three times.
The requirement for inducible NO in DEC's efficacy was determined in iNOS-/- mice. DEC (100 mg/kg) or vehicle were administered orally to three female iNOS-/- mice or their background strain, 129/SV. Mice were tail-bled at regular intervals post-treatment for evaluation of parasitaemia. To test the efficacy of another anti-filarial drug, ivermectin, in these mice, ivermectin phosphate (1 mg/kg in 1% DMSO) was administered by i.p. injection. This experiment was repeated three times.
Expression of COX-1, COX-2 and iNOS in DEC-exposed peritoneal exudate cells
Male 129/SV and iNOS-/- mice were injected i.p. with 10 mg/kg DEC in endotoxin-free water or 100 μl of endotoxin-free water (three mice in each group). After 30 minutes, peritoneal exudate cells were collected in sterile PBS with 1 g/L glucose, 1% bovine serum albumin and 1 U/ml heparin. The cells were pelleted and lysed in 1 ml TRI reagent (Sigma, U.K.) then protein extracted according to the supplied protocol.
For Western blot analysis, 10 μg of each protein were separated on a 7.5 % denaturing SDS polyacrylamide gel and blotted on to 0.45 μM pore size PVDF membrane (Immobilon P, Micropore, U.K.). After blocking overnight at 4°C in block buffer (1% casein in PBS/0.1% Tween) and washing in PBS/0.1% Tween, membranes were incubated for 1 hour in rabbit anti-mouse COX-1, COX-2 or iNOS polyclonal IgG (Cayman Chemical Co., Alexis Corporation, U.K.) diluted to 1 in 5000 in block buffer. The anti-COX antibodies showed no cross-reactivity with the opposite isoform, whilst the anti-iNOS antibody showed only 5% cross-reactivity against nNOS and none against eNOS. Membranes were then washed and incubated for 1 hour in goat anti-rabbit IgG conjugated to horse radish peroxidase (Nordic, The Netherlands) diluted to between 1 in 20000 and 1 in 100000, depending on the primary antibody, followed by further washing. The electrochemiluminescent reagent SuperSignal West (Pierce Perbio, U.K.) was used to visualise the bands on X-ray films.
Statistical analysis
Parasitaemia data were expressed as mean percentage of pretreatment microfilariae or as a percentage of untreated control microfilaraemias per 100 μl of blood and were analysed by the two-tailed Student's t-test. P values of < 0.05 were considered to be significant.
Results
Action of DEC against microfilariae in vivo in mice
In BALB/c mice treated with DEC alone, microfilaraemia levels were reduced by five minutes with a sustained reduction for at least 60 minutes post-treatment (Fig. 1). However, by 24 hours after treatment, microfilarial levels had partially recovered and two weeks later they had returned to levels approaching those pre-treatment (Fig. 1). Subsequent experiments focused on the rapid activity of DEC over the first one to two hours. Neither vehicle, indomethacin nor dexamethasone by itself had any effect on microfilaraemia in BALB/c mice (data not shown). However, in mice pre-treated with indomethacin or dexamethasone, microfilaraemias were reduced by only 11% (dexamethasone) or 44% (indomethacin) of untreated controls at 60 minutes post DEC administration (Fig. 2). The differences from the DEC-only group were statistically significant for all time points for indomethacin (P < 0.004) and for 15 and 30 minutes post-treatment for dexamethasone (P < 0.017) pre-treatments.
Figure 1 DEC causes rapid sequestration of B. malayi microfilariae in BALB/c mice. BALB/c mice intravenously injected with B. malayi microfilariae were dosed orally with 100 mg/kg DEC and microfilaraemia monitored from 5 to 60 minutes post treatment, then at 24 hours and two weeks.
Figure 2 Indomethacin or dexamethasone pre-treatment reduces efficacy of DEC in BALB/c mice infected with B. malayi microfilariae. Indomethacin (10 mg/kg), dexamethasone (3 mg/kg) or vehicle was administered 30 minutes before oral dosing with DEC (100 mg/kg). Symbols are means of three mice for the DEC plus dexamethasone group (triangles), seven mice for the DEC plus indomethacin group (white circles) and four mice for the DEC-only group (black circles). Significantly different results from the DEC-only group are denoted by * (P < 0.017), ** (P = 0.001) or *** (P = 0.000).
DEC administration also rapidly reduced microfilaraemias in 129/SV mice but, in contrast, had no effect on microfilariae levels in iNOS-/- mice, in which microfilaraemia was maintained at pre-treatment levels for at least 2 hours (Fig. 3a), with no significant differences from untreated iNOS-/- controls (P > 0.887 for all time points). In contrast, ivermectin was effective in both 129/SV and iNOS-/- mice (Fig. 3b), although it had a slower onset of action than DEC. However, by 24 hours no microfilariae were detected in either strain of mouse given ivermectin.
Figure 3 DEC is ineffective against B. malayi microfilariae in the absence of iNOS. Efficacy of (a) a single, oral dose of DEC (100 mg/kg) or (b) a single, i.p. dose of ivermectin phosphate (1 mg/kg) in 129/SV and iNOS-/- mice infected with B. malayi microfilariae. Black symbols represent 129/SV mice, white symbols iNOS-/-. Squares indicate DEC administration, triangles ivermectin administration and circles untreated controls. Symbols represent mean results from at least three or four mice, except in the case of those treated with ivermectin (two animals) from two combined experiments which were representative of a further repeat. Significantly different microfilaraemias between 129/SV and iNOS-/- mice after DEC administration are denoted by * (P = 0.001) or ** (P = 0.000).
Expression of COX-1, COX-2 and iNOS in DEC-exposed peritoneal exudate cells
Thirty minutes after administration of endotoxin-free water to 129/SV and iNOS-/- mice, peritoneal exudate cells were expressing COX-1 protein, whereas those from DEC-exposed animals contained markedly less COX-1 (Fig. 4). Interestingly, there seemed to be a higher level of COX-1 remaining in the iNOS-/- than the 129/SV macrophages after DEC treatment. Neither COX-2 nor iNOS protein was detected in any of the 129/SV or iNOS-/- groups (not shown).
Figure 4 Western blot detection of COX-1 protein from peritoneal exudate cells. COX-1 protein was detected in 129/SV and iNOS-/- peritoneal exudate cells thirty minutes after i.p. injection of endotoxin-free water (control) or DEC (10 mg/kg). Proteins (10 μg) were separated on a 7.5% denaturing SDS polyacrylamide gel, transferred to PVDF membrane, incubated with rabbit anti-mouse COX-1, then goat anti-rabbit IgG-horse radish peroxidase conjugate and detected by chemiluminescence.
Discussion
Here we have used a murine model to elucidate the processes within the mammalian host that contribute to DEC's rapid in vivo action. The involvement of two interacting pathways, the cyclooxygenase and inducible nitric oxide pathways, were shown to mediate the activity of DEC in vivo.
Treatment of mice with DEC resulted in a rapid reduction in microfilaraemia. This reduction, however, was transient and microfilaraemia began to recover 24 hours after treatment, with almost full restoration to pre-treatment levels two weeks after treatment. This has been previously observed in other models [16,17] and suggests that the disappearance of the microfilariae from the peripheral circulation and their sequestration in the central vascular system occur independently of parasite killing. A prolonged course of DEC treatment of B. malayi-infected mice led to sustained reductions in circulating microfilariae for at least 30 days [18].
Our results confirm previous findings showing that an important target for DEC is the arachidonic acid metabolic pathway. Inhibition at the first stage in the pathway by dexamethasone, which inhibits phospholipase A2, almost completely abolished the activity of DEC, whereas inhibition of the cyclooxygenase enzymes COX-1 and COX-2 by indomethacin reduced its efficacy by 56%, indicating that in addition to its well documented inhibition of the 5-lipoxygenase pathway [6,7], DEC acts on the cyclooxygenase pathway. We have shown that at least one way it does this in vivo is by the loss of COX-1 protein within 30 minutes of administration.
The lack of activity of DEC in mice deficient in iNOS identifies a novel enzyme system involved in the in vivo activity of DEC. Previously we have shown that B. malayi microfilariae are susceptible to nitric oxide in vitro [19]. However, we found no evidence that DEC itself up-regulated iNOS activity either in vitro (not shown) or in vivo, in agreement with Rajan et al. [20], who did not find any induction of NO release from murine macrophages or rat endothelial cells treated with DEC. It therefore seems probable that iNOS exerts an effect on DEC activity via its interaction with cyclooxygenases, an idea supported by the reduced loss of COX-1 protein in peritoneal exudate cells derived from iNOS-/- mice. Several studies have shown that NO and iNOS interact with COX enzymes to cause an increase in enzymatic activity [21] and consequently increased prostaglandin synthesis [22-25], although large amounts of endogenous NO inhibited COX expression and activity in murine macrophages [26]. One explanation of the differential effects of NO on COX activity may relate to effects on different COX isoforms. For example, NO can activate COX-1 in fibroblasts but inhibit COX-2 in the same cell [15]. Although our studies do not distinguish between the role of COX-1 and COX-2 in DEC's activity, the rapid activity of DEC sequestration and the depletion of COX-1 protein suggest a role for COX-1. COX-1 but not COX-2 is essential for the early production of prostaglandins from macrophages and mast cells [27,28]. Further studies on mice deficient in COX isoforms or the use of isoform-specific pharmacological inhibitors could address this question. Several polymorphisms in the human iNOS gene have been described that are associated with a variety of diseases, including malaria [29-31] and hypertension [32]; it would be interesting to know if these or other polymorphisms affected responsiveness to DEC therapy.
Our findings could help expand our understanding of the mechanisms involved in the cellular processes leading to sequestration and the subsequent killing of parasites. In addition to the elevation of granulocyte adherence, platelets have also been shown to bind to and kill microfilariae [33]. In view of the well know effects of NO and prostaglandins on platelet function and evidence to suggest the presence of inducible NO in human platelets [34,35], the role of platelets in parasite sequestration and killing should be re-evaluated in vivo.
Filarial parasites also produce and release prostanoids, including PGE2, PGI2 and PGD2 [36-41], which result in inhibition of platelet aggregation [40], vasodilatation of the blood vessels and immune suppression, and may contribute to the long persistence of these parasites in their natural hosts [41]. This prostanoid production is also inhibited by DEC [8]. Significantly, they do not produce thromboxane A2 [36]. In contrast to mammalian systems, in which eicosanoid formation is often in response to agonist-induced stimulation, microfilariae produce prostanoids constitutively [36], but the mechanisms by which they do so have not yet been described in detail, although a glutathione S-transferase of O. volvulus synthesizes PGD2 from PGH2 [39]. It is not clear if DEC acts predominantly against the prostanoids of the worm or of the host. The lack of any direct effect of dexamethasone and indomethacin on microfilaraemia suggests that these drugs either do not influence parasite prostaglandins in vivo or that if they do, they are not involved in DEC-mediated sequestration. Further studies that involve inhibition of the key parasite enzymes would be required to determine the role of parasite-derived prostanoids in DEC activity. Recent studies have reported a direct activity of DEC against Wuchereria bancrofti microfilariae that results in exsheathment, organelle damage and cytolysis [42], which occur both in vitro and in vivo and suggest that DEC may have a direct effect on worms in addition to its interaction with host-derived pathways as reported here.
Much remains to be discovered of the mode of action of DEC. What mechanisms lead to parasite killing following sequestration in the central vasculature; and how does this relate to the paradoxical appearance of microfilariae in the peripheral circulation following the 'DEC provocative test'? What is the role of host immunity and effects on adult worms in the long-term efficacy of DEC? This model should be a powerful tool to address these questions and others to further unravel the mysteries of this elusive drug.
Conclusion
Inducible nitric oxide synthase and the cyclooxygenase pathway were found to be essential for DEC's activity in vivo. Along with its well-documented activity on the lipoxygenase pathway, DEC administered in vivo reduced the amount of the host's COX-1. Further elucidation of DEC's mechanism of action with this murine model could provide a clearer understanding of the interaction of the nitric oxide and cyclooxygenase pathways and the cellular and molecular events at the site of sequestration.
List of abbreviations
DEC, diethylcarbamazine citrate; COX, cyclooxygenase; i.p., intra-peritoneal; PG, prostaglandin; PGI2, prostacyclin; NO, nitric oxide; iNOS, inducible nitric-oxide synthase.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
HFM assisted with the in vivo experiments, performed the Western blot detection, analysed and interpreted the results, conducted statistical analysis and wrote the manuscript. LDP collected the parasitaemia data and assisted with the in vivo experiments. MJT conceived the study, performed the in vivo experiments, interpreted the results and advised on the manuscript. All authors read and approved the final manuscript.
Acknowledgements
MJT is supported by a Senior Wellcome Trust Fellowship in Basic Biomedical Science. LDP was funded by the University of Liverpool Research Development Fund. We thank Prof. F.Y. Liew (University of Glasgow) for providing the iNOS-/- mice.
==== Refs
Molyneux DH Bradley M Hoerauf A Kyelem D Taylor MJ Mass drug treatment for lymphatic filariasis and onchocerciasis Trends Parasitol 2003 19 516 522 14580963 10.1016/j.pt.2003.09.004
Hawking F Laurie W Action of hetrazan on filariasis and onchocerciasis Lancet 1949 2 146 147 10.1016/S0140-6736(49)90993-9
Vickery AC Nayar JK Tamplin ML Diethylcarbamazine-mediated clearance of Brugia pahangi microfilariae in immunodeficient nude mice Am J Trop Med Hyg 1985 34 476 483 3890576
Maizels RM Denham DA Diethylcarbamazine (DEC): immunopharmacological interactions of an anti-filarial drug Parasitol 1992 105 S49 S60
Needleman P Turk J Jakschik BA Morrison AR Lefkowith JB Arachidonic acid metabolism Ann Rev Biochem 1986 55 69 102 3017195 10.1146/annurev.bi.55.070186.000441
Bach MK Brashler JR Inhibition of the leukotriene synthetase of rat basophil leukemia cells by diethylcarbamazine, and synergism between diethylcarbamazine and piriprost, a 5-lipoxygenase inhibitor Biochem Pharmacol 1986 31 2129 2132
Mathews WR Murphy RC Inhibition of leukotriene biosynthesis in mastocytoma cells by diethylcarbamazine Biochem Pharmacol 1982 31 2129 2132 6288051 10.1016/0006-2952(82)90435-X
Kanesa-Thasan N Douglas JG Kazura JW Diethylcarbamazine inhibits endothelial and microfilarial prostanoid metabolism in vitro Mol Biochem Parasitol 1991 49 11 20 1775151 10.1016/0166-6851(91)90125-P
King CH Greene BM Spagnuolo PJ Diethylcarbamazine citrate, an antifilarial drug, stimulates human granulocyte adherence Antimicr Ag Chemo 1983 24 453 456
Rácz P Tenner-Rácz K Büttner DW Albiez EJ Ultrastructural evidence for eosinophil-parasite adherence (EPA) reaction in human onchocercal lymphadenitis in the early period following diethylcarbamazine treatment Tropenmed Parasitol 1982 33 213 218 7164163
Medina-De la Garza CE Brattig NW Tischendorf FW Jarrett JMB Serum-dependent interaction of granulocytes with Onchocerca volvulus microfilariae in generalized and chronic hyper-reactive onchocerciasis and its modulation by diethylcarbamazine Trans R Soc Trop Med Hyg 1990 84 701 706 2278077 10.1016/0035-9203(90)90155-8
Clancy RM Abramson SB Nitric oxide: a novel mediator of inflammation Proc Soc Exp Biol Med 1995 210 93 101 7568290
Sano H Hla T Maier JAM Crofford LJ Case JP Maciag T Wilder RL In vivo cyclooxygenase expression in synovial tissues of patients with rheumatoid arthritis and osteoarthritis and rats with adjuvant and streptococcal cell wall arthritis J Clin Invest 1992 89 97 108 1729286
Salvemini D Regulation of cyclooxygenase enzymes by nitric oxide Cell Mol Life Sci 1997 53 576 582 9312403 10.1007/s000180050074
Clancy R Varenika B Huang W Ballou L Attur M Amin AR Abramson SB Nitric oxide synthase/COX cross-talk: nitric oxide activates COX-1 but inhibits COX-2-derived prostaglandin production J Immunol 2000 165 1582 1587 10903767
Horii Y Aoki Y Plasma levels of diethylcarbamazine and their effects on implanted microfilariae of Brugia pahangi in rats J Vet Med Sci 1997 59 961 963 9362054 10.1292/jvms.59.961
Denham DA Suswillo RR Rogers R McGreevy PB Studies with Brugia pahangi 17. The anthelmintic effects of diethylcarbamazine J Parasitol 1978 64 463 468 26737
Neill M Kazura JW The effect of diethylcarbamazine in a murine model of Brugia malayi microfilaraemia Bull WHO 1979 57 329 330 312165
Taylor MJ Cross HF Mohammed AA Trees AJ Bianco AE Susceptibility of Brugia malayi and Onchocerca lienalis microfilariae to nitric oxide and hydrogen peroxide in cell-free culture and from IFNτ-activated macrophages Parasitol 1996 112 315 322
Rajan TV Shultz LD Babu S Doukas J Greiner D Porte P Diethylcarbamazine (DEC) does not induce nitric oxide (NO) synthesis Exp Parasitol 1998 88 217 222 9562425 10.1006/expr.1998.4247
Salvemini D Misko TP Masferrer JL Seibert K Currie MG Needleman P Nitric oxide activates cyclooxygenase enzymes Proc Natl Acad Sci USA 1993 90 7240 7244 7688473
Salvemini D Seibert K Masferrer JL Misko TP Currie MG Needleman P Endogenous nitric oxide enhances prostaglandin production in a model of renal inflammation J Clin Invest 1994 93 1940 1947 7514189
Salvemini D Settle SL Masferrer JL Seibert K Currie MG Needleman P Regulation of prostaglandin production by nitric oxide; an in vivo analysis Br J Pharmacol 1995 114 1171 1178 7542531
Devaux Y Seguin C Grosjean S de Talancé N Camaeti V Burlet A Zannad F Meistelman C Moertes P-M Longrois D Lipopolysaccharide-induced increase of prostaglandin E2 is mediated by inducible nitric oxide synthase activation of the constitutive cyclooxygenase and induction of membrane-associated prostaglandin E synthase J Immunol 2001 167 3962 3971 11564815
Marnett LJ Wright TL Crews BC Tannenbaum SR Morrow JD Regulation of prostaglandin biosynthesis by nitric oxide is revealed by targeted deletion of inducible nitric-oxide synthase J Biol Chem 2000 275 13427 13430 10788454 10.1074/jbc.275.18.13427
Swierkosz TA Mitchell JA Warner TD Botting RM Vane JR Co-induction of nitric oxide synthase and cyclo-oxygenase: interactions between nitric oxide and prostanoids Br J Pharmacol 1995 114 1335 1342 7541688
Reddy ST Tiano HF Langenbach R Morham SG Herschman HR Genetic evidence for distinct roles of COX-1 and COX-2 in the immediate and delayed phases of prostaglandin synthesis in mast cells Biochem Biophys Res Comm 1999 265 205 210 10548515 10.1006/bbrc.1999.1658
Bozza PT Payne JL Morham SG Langenbach R Smithies O Weller PF Leukocyte lipid body formation and eicosanoid generation: cyclooxygenase-independent inhibition by aspirin Proc Natl Acad Sci USA 1996 93 11091 11096 8855314 10.1073/pnas.93.20.11091
Hobbs MR Udhayakumar V Levesque MC Booth J Roberts JM Tkachuk AN Pole A Coon H Kariuki S Nahlen BL Mwaikambo ED Lal AL Granger DL Anstey NM Weinberg JB A new NOS2 promoter polymorphism associated with increased nitric oxide production and protection from severe malaria in Tanzanian and Kenyan children Lancet 2002 360 1468 1475 12433515 10.1016/S0140-6736(02)11474-7
Kun JF Mordmuller B Perkins DJ May J Mercereau-Puijalon O Alpers M Weinberg JB Kremsner PG Nitric oxide synthase 2 (Lambarene) (G-954C), increased nitric oxide production, and protection against malaria J Inf Dis 2001 184 330 336 11443559 10.1086/322037
Ohashi J Naka I Patarapotikul J Hananantachai H Looareesuwan S Tokunaga K Significant association of longer forms of CCTTT microsatellite repeat in the inducible nitric oxide synthase promoter with severe malaria in Thailand J Inf Dis 2002 186 578 581 12195390 10.1086/341779
Rutherford S Johnson MP Curtain RP Griffiths LR Chromosome 17 and the inducible nitric oxide synthase gene in human essential hypertension Hum Genet 2001 109 408 415 11702222 10.1007/s004390100565
Cesbron JY Capron A Vargaftig BB Lagarde M Pincemail J Braquet P Taelman H Joseph M Platelets mediate the action of diethylcarbamazine on microfilariae Nature 1987 325 533 6 3808054 10.1038/325533a0
Chen LY Mehta JL Further evidence of the presence of constitutive and inducible nitric oxide synthase isoforms in human platelets J Cardiovasc Pharmacol 1996 27 154 8 8656650 10.1097/00005344-199601000-00024
Mehta JL Chen LY Kone BC Mehta P Turner P Identification of constitutive and inducible forms of nitric oxide synthase in human platelets J Lab Clin Med 1995 125 370 7 7534807
Liu LX Serhan CN Weller PF Intravascular filarial parasites elaborate cyclooxygenase-derived eicosanoids J Exp Med 1990 172 993 996 2117642 10.1084/jem.172.3.993
Liu LX Buhlmann JE Weller PF Release of prostaglandin E2 by microfilariae of Wuchereria bancrofti and Brugia malayi Am J Trop Med Hyg 1992 46 520 523 1599045
Kaiser L Lamb VL Tithof PK Gage DA Chamberlin BA Watson JT Williams JF Dirofilaria immitis : do filarial cyclooxygenase products depress endothelium-dependent relaxation in the in vitro rat aorta? Exp Parasitol 1992 75 159 167 1516664 10.1016/0014-4894(92)90175-A
Sommer A Rickert R Fischer P Steinhart H Walter RD Liebau E A dominant role for extracellular glutathione S-transferase from Onchocerca volvulus is the production of Prostaglandin D2 Infect Immun 2003 71 3603 3606 12761146 10.1128/IAI.71.6.3603-3606.2003
Liu LX Weller PF Intravascular filarial parasites inhibit platelet aggregation. Role of parasite-derived prostanoids J Clin Invest 1992 89 1113 1120 1313445
Liu LX Weller PF Arachidonic acid metabolism in filarial parasites Exp Parasitol 1990 71 496 501 2226710 10.1016/0014-4894(90)90076-O
Peixoto CA Rocha A Aguiar-Santos A The effects of diethylcarbamazine on the ultrastructure of microfilariae of Wuchereria bancrofti in vivo and in vitro Parasitol Res 2004 92 513 517 15007641 10.1007/s00436-004-1081-0
| 15932636 | PMC1173132 | CC BY | 2021-01-04 16:38:25 | no | Filaria J. 2005 Jun 2; 4:4 | utf-8 | Filaria J | 2,005 | 10.1186/1475-2883-4-4 | oa_comm |
==== Front
Health Qual Life OutcomesHealth and Quality of Life Outcomes1477-7525BioMed Central London 1477-7525-3-321587173810.1186/1477-7525-3-32ResearchThe two-year impact of first generation protease inhibitor based antiretroviral therapy (PI-ART) on health-related quality of life Eriksson Lars E [email protected] Göran A [email protected]öm Eric [email protected]öm Gun [email protected] Department of Nursing, Karolinska Institutet, 23300, SE-141 83 Huddinge, Sweden2 Department of Venhälsan, South Stockholm General Hospital, SE-118 83 Stockholm, Sweden3 Department of Virology, Swedish Institute for Infectious Disease Control, SE-171 82 Solna, Sweden2005 4 5 2005 3 32 32 16 12 2004 4 5 2005 Copyright © 2005 Eriksson et al; licensee BioMed Central Ltd.2005Eriksson et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
Protease inhibitor based antiretroviral therapy (PI-ART) was introduced in 1996 and has greatly reduced the incidence of HIV-related morbidity and mortality in the industrialised world. PI-ART would thus be expected to have a positive effect on health-related quality of life (HRQL). On the other hand, HRQL might be negatively affected by strict adherence requirements as well as by short and long-term adverse effects. The aim of this study was to assess the influence of two years of first generation PI-ART on HRQL in patients with a relatively advanced state of HIV-infection. Furthermore, we wanted to investigate the relation between developments in HRQL and viral response, self-reported adherence and subjective experience of adverse effects in patients with PI-ART.
Methods
HRQL was measured by the Swedish Health-Related Quality of Life Questionnaire (SWED-QUAL). Sixty-three items from the SWED-QUAL forms two single-item and 11 multi-item dimension scales. For this study, two summary SWED-QUAL scores (physical HRQL composite score and emotional HRQL composite score) were created through a data reduction procedure. At the 2-year follow-up measurement (see below), items were added to measure adherence and subjective experience of adverse effects. Demographic and medical data were obtained from specific items in the questionnaires and from the medical files. Seventy-two patients who were among the first to receive PI-ART (indinavir or ritonavir based) responded to the questionnaire before the start of PI-ART. Of these, 54 responded to the same instrument after two years of treatment (13 had died, four had changed clinic and one did not receive the questionnaire).
Results
The main findings were that the emotional HRQL deteriorated during two years of PI-ART, while the physical HRQL remained stable. Multiple linear regression analyses showed that experience of adverse effects contributed most to the deterioration of emotional HRQL.
Conclusion
In this sample of patients with relatively advanced state of HIV-infection, our data suggested that a negative development of physical HRQL had been interrupted by the treatment and that the emotional dimension of HRQL deteriorated during two years after start of PI-ART. Subjective experience of adverse effects made a major contribution to the decrease in emotional HRQL. The results underline the importance of including HRQL measures in the evaluation of new life prolonging therapies.
==== Body
Background
Protease inhibitor based antiretroviral therapy (PI-ART), defined as the combination of at least two nucleoside analogues with at least one protease inhibitor (PI) [1], was introduced in 1996 and has greatly reduced the incidence of HIV-related morbidity and mortality in the industrialised world [2,3]. PI-ART would thus be expected to have a positive effect on health-related quality of life (HRQL). On the other hand, HRQL might be negatively affected by strict adherence requirements as well as by short and long-term adverse effects [4,5].
Several studies (cross-sectional or longitudinal) have focused on the HRQL of HIV-positive individuals in different stages of the HIV infection and under different treatment regimes. The results have varied but in general HIV infection affects several physical, psychological and social dimensions of HRQL and patients with symptomatic disease and/or an AIDS-defining complication are more severely affected than those with other comparable chronic diseases [6-8]. HRQL has been shown to be related to the CD4 value, viral load and symptoms, so that patients with a more advanced state of HIV infection reported poorer HRQL [9-15]. Moreover, symptoms, physical function, role function and sexual function deteriorated over time, while emotional domains were unchanged or improved [9,10,16]. Only a few studies on the influence of long-term (>1 year) PI-ART on the quality of life have yet been published. Nieuwkerk et al. [17] compared the development of HRQL during three different PI based regimes and concluded that in terms of HRQL, patients with higher CD4 values at start experienced less benefit from the treatment. Burgoyne et al. [18,19] followed HRQL in 41 patients with different treatment status over a period of four years and found no overall change of HRQL and that HRQL was less sensitive to CD4 changes than to symptom changes as well as that change in HRQL was somewhat related to change in social support.
The main aim of the present study was to investigate HRQL before and after two years of first generation PI-ART. The following research questions were addressed: (a) Does HRQL change during two years of PI-ART? (b) Do viral response, adherence, subjective experience of adverse effects and initial CD4 count predict changes in HRQL during two years of PI-ART?
Methods
Data collection
Subjects
The study was performed at the Department of Venhälsan at South Stockholm General Hospital, Sweden. A convenient sample of 72 subjects (70 men and 2 women) in an advanced state of HIV infection and who were among the first patients to receive PI-ART in Sweden responded to the HRQL instrument described below before the start of PI-ART (pre PI-ART). HIV infection was documented by at least two laboratory tests (two repeated ELISA tests or one ELISA test and one Western Blot). The patients were treated according to best clinical practice and the participant's physician chose the drug combination of the PI-ART (at least 2 nucleoside analogue reverse transcriptase inhibitors and either indinavir (n = 55) or ritonavir (n = 17) at start). Approximately two years after the introduction of PI-ART (follow-up; mean 25.1 months, standard deviation (SD) 2.8 months, post initiation), 54 of the 72 subjects (75 %) completed the follow-up measure. Thirteen patients had died, four had changed clinic and one did not receive the follow-up questionnaire.
The Swedish Health-Related Quality of Life Questionnaire (SWED-QUAL)
The patients completed the SWED-QUAL at the pre PI-ART and two-year follow-up visits. SWED-QUAL was developed by Brorsson et al. [20] from the measures used in the US Medical Outcomes Study (MOS) [21-24]. The questionnaire, which is designed to measure HRQL, consists of 70 items, of which 63 forms two single-item and 11 multi-item dimension scales of Likert type: physical functioning (7 items), mobility (1 item), satisfaction with physical ability (1 item), role limitations due to physical health (3 items), pain (6 items), emotional well-being: positive affect (i.e. positive feelings; 6 items), emotional well-being: negative affect (i.e. negative feelings; 6 items), role limitations due to emotional health (3 items), sleep problems (7 items), satisfaction with family life (relations with parents, siblings, children etc.; 4 items), relation to partner (6 items), sexual functioning (4 items) and general health perception (9 items). In the present study, the relation to partner section was slightly modified to make it suitable for the investigated group (i.e. the word "spouse" was replaced by "partner"). Each scale is transformed into a 0–100 index; the higher the score, the better the perceived HRQL. In a general population sample, the internal-consistency reliability coefficients (Cronbach's α) ranged from 0.79 to 0.89 [20]. Brorsson et al. have also reportedpreliminary support for the construct validity [20]. The instrument has been used in our previous study of HIV-positive subjects in Sweden [25].
A factor analysis (see below) was performed on a merged material from three groups of patients: (a) the group described above at pre PI-ART (n = 72), (b) a previously described group of protease inhibitor naïve HIV patients (n = 73) [25] and (c) an unpublished material of 164 HIV-negative men who have sex with men visiting our information and screening clinic for sexually transmitted diseases (own unpublished data).
Adherence/adverse effects
At the follow-up, the patients' adherence and drug-related adverse effects were examined. Adherence was assessed by asking the following question, modified from Morisky et al. [26]: "How many times during the last month did you skip doses of your HIV medication for the following reasons: because you felt so good that it did not matter, because you felt worse due to the medication or because you forgot?" For each of the three given reasons the patients were asked to rate the number of missed doses on a scale with five alternatives (1 = 0 doses, 2 = 1–2 doses, 3 = 3–5 doses, 4 = 6–9 doses or 5 = >9 doses). Patients were classified as non-adherent if they indicated >9 missed doses in at least one of the three mentioned categories (i.e. indicating 90% adherence or less) or if they indicated missed doses in all three categories.
The subjective experience of medication-related adverse effects was addressed in one question, which asked the patients to rate their global experience of adverse effects during the past month on a 10 cm visual analogue scale (VAS) ranging from "none at all" to "severe".
Laboratory measures
Lymphocyte subsets were determined, using routine flow cytometry [27], at least every 3–4 months. The level of HIV-1 RNA in plasma was quantified at the Swedish Institute for Infectious Disease Control by a commercially available reverse transcriptase polymerase chain reaction (PCR)-based assay (HIV Monitor; Roche Diagnostic Systems, Branchburg New Jersey, USA). The level of quantification at the time of the study was 500 viral copies ml-1.
Viral outcome
On the basis of the participants' long-term virologic outcome to PI-ART, they were subdivided into viral responders and viral non-responders. Viral responders were defined as participants who, after the first 3 months of PI-ART, had either HIV RNA less than 500 copies ml-1 in more than 75% of the analysed samples or a continuous decrease in HIV RNA to below 500 copies ml-1 before 18 months. All other participants were regarded as viral non-responders [28].
Demographic and medical data
Demographic and medical data were obtained from specific items in the questionnaires and from the medical files.
Statistical methods
Statistical calculations were performed with the assistance of the personal-computer program SPSS for Windows, version 11.0.0. The criterion for statistical significance was p < 0.05. Since some parameters did not fulfil the assumptions of a normal distribution, the Wilcoxon signed ranks test [29] was used to compare differences between two related groups (i.e. pre PI-ART versus follow-up).
In order to achieve data reduction to create composite scores for use in multiple regression analyses of the material, a rotated component matrix analysis [30] was performed on the scores from ten of the 13 SWED-QUAL scales (i.e. those measuring physical and emotional health). The following scales were used in the factor analysis: physical functioning, mobility, satisfaction with physical ability, role limitations due to physical health, pain, emotional well-being: positive affect, emotional well-being: negative affect, role limitations due to emotional health, sleep problems and sexual functioning. The analysis resulted in two factors: (a) physical HRQL composite score, i.e. PCS, comprising the averaged scores of the SWED-QUAL scales physical functioning, mobility, satisfaction with physical ability, pain, role limitations due to physical health and sexual functioning, and (b) emotional HRQL composite score, i.e. ECS, comprising the averaged scores of the SWED-QUAL scales role limitations due to emotional health, positive affect, negative affect and sleep problems (Table 1). These two factors explained 65 % of the total variance.
Table 1 Rotated factor loading (varimax) of the principal component analysis (n = 309)
Rotated factor loadings
PCS ECS
SWED-QUAL Scale
Physical functioning 0.92 0.07
Mobility 0.83 0.04
Satisfaction with physical ability 0.79 0.24
Pain 0.56 0.45
Role limitations due to physical health 0.66 0.46
Sexual functioning 0.63 0.32
Role limitations due to emotional health 0.33 0.75
Emotional well-being, positive affect 0.08 0.81
Emotional well-being, negative affect 0.08 0.85
Sleep problems 0.32 0.70
PCSPhysical HRQL composite score; ECSEmotional HRQL composite score
A set of hierarchical multiple linear regression analyses [31] were performed to investigate whether the initial CD4 value, viral response, adherence and subjective experience of adverse effects predicted the change in HRQL. The two analyses (one for PCS and one for ECS) were conducted in two forced steps with the follow-up PCS and ECS as dependent variables. The pre PI-ART PCS and ECS, respectively, were entered in the first step, while the three variables viral response, adherence and subjective experience of adverse effects were entered in the second step together with the initial CD4 value.
Ethical approval
The study was approved by the Local Ethical Committee at Huddinge University Hospital. Information about the study was given to the subjects in connection with an ordinary, scheduled visit to the clinic.
Results
Demographic and medical data
At pre PI-ART, the mean age of the 72 patients was 41 (SD 9, range 23 – 65) years, 59 were of Swedish origin, 61 had prior antiretroviral treatment with only nucleoside analogue reverse transcriptase inhibitors, 32 had a CD4 count of <200 × 106 cells l-1 and 28 had an AIDS diagnosis. Further demographic and medical data are shown in Table 2.
Table 2 Demographic and medical data regarding a Swedish sample of HIV-infected persons before the start of PI-ART (n = 72)
No. of subjects Percentage
Mode of transmission
Male to male 69 96
Female to male/male to female 3 4
Working status
Full or part time work/studies 36 50
Sick leave or disability pension 31 43
Not stated 5 7
Education
Compulsory school 13 18
Upper secondary school/high school 27 38
University studies 27 38
Not stated 5 7
Having a partner:
Yes/no 30/41 42/57
not stated 1 1
CD4 count, cells × 106 l-1: median 127
range 1–660
HIV RNA, log10 copies ml-1: median 4.87
range 2.70–6.18
Time since first start of antiretroviral treatment, months: mean 33
SD 31.6
PI-ARTProtease inhibitor based antiretroviral therapy; SDStandard deviation
Changes from pre PI-ART to follow-up
From the pre PI-ART to the follow-up, the CD4 count of the surviving patients increased from a median (Md) of 150 (range 1 – 660) × 106 cells l-1 to 325 (range 5 – 840) × 106 cells l-1 (p < 0.001) and the HIV-1 RNA level decreased from 4.90 (range 2.70 – 6.00) log10 copies ml-1 to 2.70 (range 2.70 – 6.31) log10 copies ml-1 (p < 0.001). Thirty patients had switched PI during the first two years of PI-ART. A total of 36 subjects were classified as viral responders and 18 as viral non-responders.
The patients' emotional well-being deteriorated during the first two years of PI-ART
The pre PI-ART and follow-up results of the composite scores and the single SWED-QUAL scales are shown in Table 3. The ECS decreased from pre PI-ART to follow-up (Md 71.2, interquartile range (IQR) 47.1 – 86.9 versus Md 63.6, IQR 41.0 – 77.3; p < 0.01;). A comparison of the single SWED-QUAL scales at pre PI-ART with the same scales at follow-up revealed statistically significant decreases in the SWED-QUAL scales role limitations due to emotional health (pre PI-ART Md 88.9, IQR 66.7 – 100 versus follow-up Md 77.8, IQR 50.0 – 100; p < 0.05) and emotional well-being: negative affect (pre PI-ART Md 62.5, IQR 37.5 – 94.8 versus follow-up Md 50.0, IQR 25.0 – 75.0; p < 0.01; Table 3). The effect sizes of the change were 0.34 for the PCS, 0.36 for role limitations due to emotional health and 0.37 for emotional well-being: negative affect.
Table 3 The Swedish Health-Related Quality of Life Questionnaire (SWED-QUAL) results before and after 2 years of protease inhibitor based antiretroviral therapy (pre PI-ART and follow-up respectively). The higher the score the better the health-related quality of life (n = 54)
Score
Pre PI-ART Median (IQR) Follow-up Median (IQR) P-valuea
Physical HRQL composite score (PCS) 79.3 (64.5–92.5) 77.2 (58.4–92.9) NS
Emotional HRQL composite score (ECS) 71.2 (47.1–86.9) 63.6 (41.0–77.3) <0.01
Physical functioning 95.2 (81.0–95.2) 95.2 (84.5–100) NS
Mobility 100 (66.7–100) 100 (66.7–100) NS
Satisfaction with physical ability 66.7 (33.3–83.3) 66.7 (33.3–100) NS
Pain 100 (53.8–100) 100 (84.7–100) NS
Role limitations due to physical health 66.7 (55.6–100) 88.9 (50.0–100) NS
Sexual functioning 75.0 (41.7–91.7) 58.3 (41.7–91.7) NS
Role limitations due to emotional health 88.9 (66.7–100) 77.8 (50.0–100) <0.05
Emotional well-being, positive affect 72.9 (47.9–83.3) 62.5 (37.5–83.3) NS
Emotional well-being, negative affect 62.5 (37.5–94.8) 50.0 (25.0–75.0) <0.01
Sleep problems 67.9 (39.3–87.5) 57.1 (36.6–75.0) NS
Satisfaction with family life 72.9 (49.5–90.6) 72.9 (55.7–85.4) NS
Relation to partner 87.5 (75.0–100) 79.2 (52.1–95.8) NS
General health perception 55.6 (36.1–75.0) 63.9 (38.9–80.6) NS
aWilcoxon signed ranks test, change from pre PI-ART to follow-up; NSNon significant; IQRInterquartile range; HRQLHealth-related quality of life
Subjective experience of adverse effects contributed to deteriorated emotional HRQL at follow-up
Forty-seven (87 %) of the 54 patients were classified as adherent and seven (13 %) as non-adherent. The mean VAS score for subjective experience of adverse effects at follow-up was 3.39 (SD 2.95, Md 2.57, IQR 0.79 – 5.84) cm on a 10 cm scale.
Two hierarchical multiple regression analyses were performed to investigate whether the change in physical and emotional HRQL composite scores could be predicted by initial CD4 count, viral response, adherence and subjective experience of adverse effects (Table 4). Only the ECS model showed a statistically significant R2 change; that is, the subjective experience of adverse effects predicted a decrease in the emotional HRQL.
Table 4 Hierarchical multiple linear analyses of the influence of initial CD4 value and the variables viral response, subjective experience of adverse effects and adherence on the change in PCS and ECS from before start (pre PI-ART) to after two year of treatment (follow-up)
Follow-up PCS Follow-up ECS
Step 1 Partial correlationa Partial correlationa
Pre PI-ART PCS 0.722*** -
Pre PI-ART ECS - 0.681***
R2 0.605*** 0.456***
F 78.26 42.72
d.f. (regression;residual) 1;51 1;51
Step 2 Partial correlation Partial correlation
Viral response 0.202 0.076
Adherence 0.167 0.235
Adverse effects 0.091 -0.366*
Pre PI-ART CD4 value -0.043 -0.024
R2-change 0.028 0.128*
F-change 0.91 3.63
d.f. (regression;residual) 4;47 4;47
PCSPhysical HRQL composite score; ECSEmotional HRQL composite score; PI-ARTProtease inhibitor based antiretroviral therapy; apartial correlation of the final model (step 2); *p < 0.05; ***p < 0.001
Internal consistency of the SWED-QUAL scales
Cronbach's α reliability estimates for the 11 SWED-QUAL multi-item scales for the pre PI-ART and follow-up ranged between 0.74 and 0.92 indicating good internal consistency. The internal consistency for the two HRQL composite scores was for the PCS α 0.88 and 0.85 (pre PI-ART and follow-up, respectively) and for the ECS α 0.91 and 0.89 (pre PI-ART and follow-up, respectively).
Discussion
In this study we used the SWED-QUAL instrument to investigate the HRQL of 54 relatively advanced HIV patients before and after two years of first generation PI-ART in a setting where protease inhibitors were introduced. We also studied the patients' viral outcome, self reported adherence and subjective experience of adverse effects and the relationship between these variables and the development in HRQL. To minimise multiple comparisons, a set of linear regression models were used. To increase the power to detect relations as a result of these models, we created two SWED-QUAL composite scores (PCS and ECS) through a data reduction procedure.
The main findings from the present study were that the physical HRQL remained stable while the emotional HRQL deteriorated for two years of first generation PI-ART and that subjective experience of adverse effects was the strongest predictor of the deterioration in emotional HRQL ratings.
The present study thus suggests that first generation PI-ART interrupted the progressive negative development of the physical domain of HRQL that has been reported in studies performed before the introduction of PI-ART [9,10,16,32,33]. Our findings are consistent with those of Goujard et al. [34] and Burgoyne et al. [18] who also failed to detect any changes in HRQL after one and a half and four years, respectively, when monitoring patients in a period after PI-ART had become available.
The somewhat surprising decrease in emotional health found in the present study has, to our knowledge, not been reported in other longitudinal studies of PI-ART. Longitudinal studies performed before the introduction of PI-ART have, in general, showed stable or improved mental/emotional health over time [9,10,16,35]. We also found stable scores in the emotional domain of HRQL in a previous pre PI-ART era study, where patients with no or only single drug antiretroviral therapy were followed for two years (own unpublished data). However, a study investigating the HRQL of patients receiving didanosine monotherapy or in combination with delavirdine (not approved in Europe due to side effects) showed slightly declining mental health scores for up to two years after the start of the trial [33]. After the introduction of PI-ART, improvements in depressive symptoms and mental health was reported in a shorter time period, i.e. after up to one year following the addition of a PI to existing antiretroviral therapy [36,37]. Similarly, Rabkin et al. [38] found a reduction in psychological distress and clinical depression during a two-year period when PI-ART became widely available. In the latter study, however, PI-ART was introduced to the cohort continuously during the follow-up, resulting in a mean time with PI-ART shorter than two years (i.e. the analysis did not evaluate patients before and after start of PI-ART in a consistent manner). From a longer term perspective, however, emotional HRQL was found to be stable over a four-year period [18].
When we further investigated the relation between the change in HRQL and the variables viral response, adherence, subjective experience of adverse effects and baseline CD4 value, our study showed that it was the subjective experience of adverse effects that contributed most to the deterioration in the emotional HRQL. It should be stressed that our measure of adverse effects was a global single item, where the patients were asked to rate their total perception of adverse effects during the previous month and that we did not sub-analyse this experience further into different symptoms. However, the negative impact of perceived side effects/symptoms on HRQL, is confirmed in a great number of quantitative investigations [12,18,37-42]. Also, the results from our quantitative study agreed with those of a qualitative study that aimed to elicit the patients' real-life descriptions of their experience of combination therapy. Erlen & Mellors [43] found that side effects were one of the major problems associated with the therapy. Furthermore, symptoms or adverse events have been shown to be related to medication adherence [44,45]. In order to improve HRQL and adherence, it is therefore crucial to find treatment combinations and strategies that minimise these negative effects and to individualize treatment. The simplified and less toxic treatment regimes available today, with antiretroviral therapy based on three nucleoside analogue reverse transcriptase inhibitors or nucleoside analogues combined with non-nucleoside analogue reverse transcriptase inhibitors or ritonavirboosted PIs once or twice daily [1], may be less liable to have a negative impact on HRQL. This was indicated in a randomised study comparing two nucleoside analogue reverse transcriptase inhibitors combined with either a PI or efavirenz, over a one year period and where the combination with efavirenz had a better influence on HRQL than the combination with the PI [46]. Similarly, Carrieri et al. [37] found a positive development of HRQL in patients switching to a non-PI-containing therapy, as compared to patients continuing stable PI-ART. However, these aspects need to be further investigated and there is a need for further study of the effect of different treatment regimes on HRQL, in experienced as well as naïve patients.
Certain study limitations should be emphasized when interpreting the present results. Firstly, the small sample may mean that the study failed to detect further relations between the investigated variables. Secondly, a large proportion of the investigated patients were in an advanced state of their HIV infection and many had previous experience of antiretroviral monotherapy. The inferences drawn from this study may not be applicable to ART naïve patients starting antiretroviral therapy in a less advanced state of the disease. Today treatment is started when certain laboratory criteria are fulfilled and before symptoms, including AIDS-defining disease, are at a high risk of appearing. Thirdly, our study population may not be totally representative of all patients receiving PI-ART. The majority of our patients were well-educated males with a homosexual route of transmission. The influence on HRQL may be different for female patients or patients with other educational status or routes of transmission. It should be noted that we chose to consider viral outcome of the treatment in a longitudinal context, i.e. viral response defined by repeated HIV RNA measures over up to 18 months. The impact on the development of HRQL might have been different if only one single measure of viral load at follow-up had been taken into account.
Conclusion
In this sample of mainly advanced patients, the emotional dimension of HRQL had deteriorated for two years after the start of first generation PI-ART, and the subjective perception of adverse effects made a major contribution to this decrease.
The results of the present study show the importance of studying HRQL in a situation where there is a desperate need for life-saving new therapies. Therefore, consistently taking HRQL into account when treating HIV patients is of the utmost importance. Finding treatment combinations and strategies with the least negative long-term influence on HRQL is essential at a time when those having access to antiretroviral combination therapy have a dramatically increased life span. Furthermore, considering the current numerous treatment options together with the fluctuations in HRQL over time, further short and long-term investigations of HRQL in patients receiving antiretroviral therapy are of the utmost importance.
Authors' contributions
LEE, ES and GN conceived of the study. All authors made substantial contributions to conception, planning and design. LEE participated in the coordination, carried out the statistical analysis and interpretation of data and drafted the manuscript. GAB participated the coordination and acquisition of the study and helped draft the manuscript. ES participated in the acquisition of the study and helped draft the manuscript. GN participated in the interpretation of data and helped draft the manuscript. All authors read and approved the final manuscript.
Acknowledgements
We would like to thank the nurses and physicians at the Department of Venhälsan, South Stockholm General Hospital for their help in administering the instruments to the participants, Eva-Lena Fredriksson, Department of Venhälsan, South Stockholm General Hospital for her great assistance in the co-ordination of the study and J. Petter Gustavsson, Department of Nursing, Karolinska Institutet for helpful discussions. We would also like to acknowledge the assistance of the participants, who gave time and effort to respond to the questionnaires.
This study was supported by grants from the Board of Research for Health and Caring Sciences at Karolinska Institutet.
==== Refs
British HIV Association Writing Committee British HIV Association (BHIVA) guidelines for the treatment of HIV-infected adults with antiretroviral therapy HIV Med 2003 4 1 41 14511246
Palella FJ JrDelaney KM Moorman AC Loveless MO Fuhrer J Satten GA Aschman DJ Holmberg SD Declining morbidity and mortality among patients with advanced human immunodeficiency virus infection. HIV Outpatient Study Investigators N Engl J Med 1998 338 853 860 9516219 10.1056/NEJM199803263381301
Mocroft A Katlama C Johnson AM Pradier C Antunes F Mulcahy F Chiesi A Phillips AN Kirk O Lundgren JD AIDS across Europe, 1994–98: the EuroSIDA study Lancet 2000 356 291 296 11071184 10.1016/S0140-6736(00)02504-6
Safrin S Grunfeld C Fat distribution and metabolic changes in patients with HIV infection AIDS 1999 13 2493 2505 10630518 10.1097/00002030-199912240-00002
Carr A Cooper DA Adverse effects of antiretroviral therapy Lancet 2000 356 1423 1430 11052597 10.1016/S0140-6736(00)02854-3
Ragsdale D Morrow JR Quality of life as a function of HIV classification Nurs Res 1990 39 355 359 2092309
Wu AW Rubin HR Mathews WC Ware JE Brysk LT Hardy WD Bozzette SA Spector SA Richman DD A health status questionnaire using 30 items from the Medical Outcomes Study Med Care 1991 29 786 798 1875745
Wachtel T Piette J Mor V Stein M Fleishman J Carpenter C Quality of life in persons with human immunodeficiency virus infection: Measurement by the Medical Outcomes Study Instrument Ann Intern Med 1992 116 129 137 1727616
Holzemer WL Wilson HS Quality of life and the spectrum of HIV infection Annu Rev Nurs Res 1995 13 3 29 8527253
Wu AW Rubin HR Approaches to health status assessment in HIV disease overview of the conference Psychol Health 1994 9 1 18
Call SA Klapow JC Stewart KE Westfall AO Mallinger AP DeMasi RA Centor R Saag MS Health-related quality of life and virologic outcomes in an HIV clinic Qual Life Res 2000 9 977 985 11332226 10.1023/A:1016668802328
Lorenz KA Shapiro MF Asch SM Bozzette SA Hays RD Associations of symptoms and health-related quality of life: findings from a national study of persons with HIV infection Ann Intern Med 2001 134 854 860 11346321
Murri R Fantoni M Borgo CD Visona R Barracco A Zambelli A Testa L Orchi N Tozzi V Bosco O Wu AW Determinants of health-related quality of life in HIV-infected patients AIDS Care 2003 15 581 590 14509872 10.1080/0954012031000134818
Ichikawa M Natpratan C Quality of life among people living with HIV/AIDS in northern Thailand: MOS-HIV Health Survey Qual Life Res 2004 13 601 610 15130024 10.1023/B:QURE.0000021319.73865.5a
Kemmler G Schmied B Shetty-Lee A Zangerle R Hinterhuber H Schüssler G Mumelter B Quality of life of HIV-infected patients: psychometric properties and validation of the German version of the MQOL-HIV Qual Life Res 2003 12 1037 1050 14651421 10.1023/A:1026114004548
de Boer JB van Dam FSAM Sprangers MAG Health-related quality-of-life evaluation in HIV-infected patients. A Review of the literature Pharmacoeconomics 1995 8 291 304 10155671
Nieuwkerk PT Gisolf EH Reijers MHE Lange JMA Danner SA Sprangers MAG Long-term quality of life outcomes in three antiretroviral treatment strategies for HIV-1 infection AIDS 2001 15 1985 1991 11600827 10.1097/00002030-200110190-00011
Burgoyne RW Rourke SB Behrens DM Salit IE Long-term quality-of-life outcomes among adults living with HIV in the HAART era: the interplay of changes in clinical factors and symptom profile AIDS Behav 2004 8 151 163 15187477 10.1023/B:AIBE.0000030246.19577.fb
Burgoyne R Renwick R Social support and quality of life over time among adults living with HIV in the HAART era Soc Sci Med 2004 58 1353 1366 14759681 10.1016/S0277-9536(03)00314-9
Brorsson B Ifver J Hays RD The Swedish Health-Related Quality of Life Survey (SWED-QUAL) Qual Life Res 1993 2 33 45 8490616 10.1007/BF00642887
Stewart AL Hays RD Ware JE The MOS Short-form General Health Survey: Reliability and validity in a patient population Med Care 1988 26 724 735 3393032
Tarlov AR Ware JE Greenfield S Nelson EC Perrin E Zubkoff M The Medical Outcomes Study. An application of methods for monitoring the results of medical care JAMA 1989 262 925 930 2754793 10.1001/jama.262.7.925
Stewart AL Sherbourne CD Hays RD Wells KB Nelson EC Kamberg CJ Rogers WH Berry SH Ware JE Stewart AL, Ware JE Summary and discussion of MOS measures Measuring Functioning and Well-Being The Medical Outcomes Study Approach 1992 Duram, NC: Duke University Press 345 371
Ware JE Sherbourne CD The MOS 36-Item Short-Form Health Survey (SF-36). I. Conceptual framework and item selection Med Care 1992 30 473 483 1593914
Eriksson LE Nordström G Berglund T Sandström E The health-related quality of life in a Swedish sample of HIV-infected persons J Adv Nurs 2000 32 1213 1223 11115007 10.1046/j.1365-2648.2000.01592.x
Morisky DE Green LW Levine DM Concurrent and predictive validity of a self-reported measure of medication adherence Med Care 1986 24 67 74 3945130
1994 revised guidelines for the performance of CD4+ T-cell determinations in persons with human immunodeficiency virus (HIV) infections. Centers for Disease Control and Prevention. MMWR Recom Rep 1994 43 1 21
Hejdeman B Lenkei R Leandersson A-C Hultström AL Wahren B Sandström E Bratt G Clinical and immunological benefits from highly active antiretroviral therapy in spite of limited viral load reduction in HIV type 1 infection AIDS Res Hum Retroviruses 2001 17 277 286 11242515 10.1089/08892220150503654
Shott S Statistics for health professionals 1990 Philadelphia: W.B. Saunders Company
Fayers PM Machin D Quality of life: assessment, analysis, and interpretation 2000 West Sussex, England: John Wiley & Sons Ltd
Cohen J Cohen P Applied multiple regression/correlation analysis for the behavioral sciences 1983 Second Hillsdale, NJ: Lawrence Erlbaum Associates, Inc
Wu AW Rubin HR Mathews WC Brysk LM Bozzette SA Hardy WD Atkinson JH Grant I Spector SA McCutchan JA Richman DD Functional status and well-being in a placebo-controlled trial of zidovudine in early symptomatic HIV infection J Acquir Immune Defic Syndr 1993 6 452 458 8483109
Weinfurt KP Willke RJ Glick HA Freimuth WW Schulman KA Relationship between CD4 count, viral burden, and quality of life over time in HIV-1-infected patients Med Care 2000 38 404 410 10752972 10.1097/00005650-200004000-00007
Goujard C Bernard N Sohier N Peyramond D Lançon F Chwalow J Arnould B Delfraissy J-F Impact of a patient education program on adherence to HIV medication J Acquir Immune Defic Syndr 2003 34 191 194 14526208
Lubeck DP Fries JF Changes in quality of life among persons with HIV infection Qual Life Res 1992 1 359 366 1299468 10.1007/BF00704430
Low-Beer S Chan K Yip B Wood W Montaner JSG O'Shaughnessy MV Hogg RS Depressive symptoms decline among persons on HIV protease inhibitors J Acquir Immune Defic Syndr 2000 23 295 301 10836751
Carrieri P Spire B Duran S Katlama C Peyramond D Francois C Chene G Lang JM Moatti JP Leport C Health-related quality of life after 1 year of highly active antiretroviral therapy J Acquir Immune Defic Syndr 2003 32 38 47 12514412
Rabkin J Ferrando S Lin S Sewell M McElhiney M Psychological effect of HAART: a 2-year study Psychosom Med 2000 62 413 422 10845355
Blanch J Rousaud A Martinez E Lazzari ED Milinkovic A Peri J-M Blanco J-L Jaen J Navarro V Massana G Gatell J-M Factors associated with severe impact of lipodystrophy on the quality of life of patients infected with HIV-1 Clin Infect Dis 2004 38 1464 1470 15156486 10.1086/383573
Hudson A Kirksey K Holzemer W The influence of symptoms on quality of life among HIV-infected women West J Nurs Res 2004 26 9 23 14984639 10.1177/0193945903259221
Préau M Leport C Salmon-Ceron D Carrieri P Portier H Chene G Spire B Choutet P Raffi F Morin M APROCO Study Group Health-related quality of life and patient-provider relationships in HIV-infected patients during the first three years after starting PI-containing antiretroviral treatment AIDS Care 2004 16 649 661 15223534 10.1080/09540120410001716441
Tramarin A Parise N Campostrini S Yin DD Postma MJ Lyu R Grisetti R Capetti A Cattelan AM Di Toro MT Mastroianni A Pignattari E Mondardini V Calleri G Raise E Starace F Palladio Study Group Association between diarrhea and quality of life in HIV-infected patients receiving highly active antiretroviral therapy Qual Life Res 2004 13 243 250 15058804 10.1023/B:QURE.0000015282.24774.36
Erlen JA Mellors MP Adherence to combination therapy in persons living with HIV: balancing the hardships and the blessings J Assoc Nurses AIDS Care 1999 10 75 84 10394562
Holzemer WL Corless IB Nokes KM Turner JG Brown MA Powell-Cope GM Inouye J Henry SB Nicholas PK Portillo CJ Predictors of self-reported adherence in persons living with HIV disease AIDS Patient Care STDS 1999 13 185 197 10375267
Stone VE Jordan J Tolson J Miller R Pilon T Perspectives on adherence and simplicity for HIV-infected patients on antiretroviral therapy (HAART) regimens in predicting adherence J Acquir Immune Defic Syndr 2004 36 808 816 15213564
Fumaz CR Tuldrà A Ferrer MJ Paredes R Bonjoch A Jou J Negredo E Romeu J Sirera G Tural C Clotet B Quality of life, emotional status, and adherence of HIV-1-infected patients treated with efavirenz versus protease inhibitor-containing regimens J Acquir Immune Defic Syndr 2002 29 244 253 11873073
| 15871738 | PMC1173133 | CC BY | 2021-01-04 16:38:14 | no | Health Qual Life Outcomes. 2005 May 4; 3:32 | utf-8 | Health Qual Life Outcomes | 2,005 | 10.1186/1477-7525-3-32 | oa_comm |
==== Front
Int J Health GeogrInternational Journal of Health Geographics1476-072XBioMed Central London 1476-072X-4-111590452410.1186/1476-072X-4-11MethodologyA flexibly shaped spatial scan statistic for detecting clusters Tango Toshiro [email protected] Kunihiko [email protected] Department of Technology Assessment and Biostatistics, National Institute of Public Health, 3–6 Minami 2 chome Wako, Saitama 351-0197 Japan2005 18 5 2005 4 11 11 14 4 2005 18 5 2005 Copyright © 2005 Tango and Takahashi; licensee BioMed Central Ltd.2005Tango and Takahashi; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
The spatial scan statistic proposed by Kulldorff has been applied to a wide variety of epidemiological studies for cluster detection. This scan statistic, however, uses a circular window to define the potential cluster areas and thus has difficulty in correctly detecting actual noncircular clusters. A recent proposal by Duczmal and Assunção for detecting noncircular clusters is shown to detect a cluster of very irregular shape that is much larger than the true cluster in our experiences.
Methods
We propose a flexibly shaped spatial scan statistic that can detect irregular shaped clusters within relatively small neighborhoods of each region. The performance of the proposed spatial scan statistic is compared to that of Kulldorff's circular spatial scan statistic with Monte Carlo simulation by considering several circular and noncircular hot-spot cluster models. For comparison, we also propose a new bivariate power distribution classified by the number of regions detected as the most likely cluster and the number of hot-spot regions included in the most likely cluster.
Results
The circular spatial scan statistics shows a high level of accuracy in detecting circular clusters exactly. The proposed spatial scan statistic is shown to have good usual powers plus the ability to detect the noncircular hot-spot clusters more accurately than the circular one.
Conclusion
The proposed spatial scan statistic is shown to work well for small to moderate cluster size, up to say 30. For larger cluster sizes, the method is not practically feasible and a more efficient algorithm is needed.
==== Body
Background
The question of whether disease cases are clustered in space has received considerable attention in the literature [1-4]. Although many statistical tests for disease clusters have been proposed, most tests suffer from multiple testing problems due to one or two unknown parameters that must be set prior to their applications. For example, Cuzick and Edwards's procedure [5] has an unknown number k of nearest-neighbours and Besag and Newell's method [6] has an unknown number of cases k for the size of the cluster. As far as we know, the spatial scan statistic proposed by Kulldorff [7,8] and Tango's maximized excess events test [9,10] are exceptions and take multiple testing into account in the sense that we have only to specify the maximum possible cluster size. Especially, Kulldorff's circular spatial scan statistic has been applied to a wide variety of epidemiological studies for cluster detection (for example, see [11-13]). In recent power comparisons of disease clustering tests, his scan statistic has been shown to be the most powerful for detecting localized clusters [14,15]. It should be noted, however, that the power estimates provided reflect the "power to reject the null hypothesis for whatever reason" and that the probability of both rejecting the null hypothesis and detecting the true cluster correctly is a different matter.
As the circular spatial scan statistic uses a "circular window" with variable size to define the potential cluster area, it is difficult to correctly detect noncircular clusters such as those along a river. Most geographical areas are noncircular. Furthermore, in our experience in applying SaTScan program [16] to various data, even if the null hypothesis is rejected, the circular spatial scan statistic tends to detect a larger cluster than the true cluster by absorbing surrounding regions where there is no elevated risk. It should be noted that although Kulldorff originally made no assumptions about the shape of the scanning window in his paper [8], a circular scanning window has been used in almost all purely spatial applications especially for the availability of software and computational speed.
Recently, Patil and Taillie [17] and Duczmal and Assunção [18] proposed non-circular spatial scan statistics based on the likelihood ratio test formulated in the same way as in the circular spatial scan statistic. To avoid undertaking computationally infeasible searches, they considered different approaches. Patil and Taillie [17] used the notion of "upper level set" to reduce the size of windows to be scanned and proposed "upper level set scan statistic". However, they do not discuss how to select the level g which defines the upper level set and do not provide any illustrations of their method nor any results of comparison with the circular scan statistic. Duczmal and Assunção [18], on the other hand, have applied a simulated annealing method in which they try to examine only the most promising windows using a graph-based algorithm to obtain the local maxima of a certain likelihood function over a subset of the collection of all the connected regions. Their method seems to be very complicated but they do not show any programmable procedure of their method. In our experience using their program (personal communication to Professor Duczmal via email) which is executable with the Borland C++ Builder 6, their scan statistic, in most cases, detected a cluster of peculiar shape that was much larger than the true cluster by absorbing not only surrounding regions with non-elevated risk but also faraway regions with non-elevated risk. An example of such properties of Duczmal and Assunção's procedure is shown later in comparison with the circular spatial scan statistic and the proposed flexible spatial scan statistic. That is why we did not include both the Patil and Taille method and Duczmal and Assunção's procedure in our simulation for comparison.
In this paper, we propose an alternative flexibly shaped spatial scan statistic ('flexible spatial scan statistic' hereafter) in which the detected cluster is allowed to be flexible in shape while at the same time the cluster is confined within relatively small neighborhoods of each region. The performance of the flexible spatial scan statistic is compared with that of the circular spatial scan statistic using Monte Carlo simulation. In comparing performance we examined not only the usual power but also the newly introduced bivariate power distribution classified by the number of regions detected as the most likely cluster and the number of hot-spot regions included in the most likely cluster. The proposed flexible spatial scan statistic is illustrated with some simulated disease maps for the Tokyo Metropolitan area.
Methods
Consider the situation where an entire study area is divided into m regions (for example, county, enumeration districts, etcetera). The number of cases in the region i is denoted by the random variable Ni with observed value ni, i = 1, ..., m. Under the null hypothesis H0 of no clustering, the Ni are independent Poisson variables such that
H0 : E(Ni) = ξi, Ni ~ Pois(ξi), i = 1, ..., m (1)
where Pois(e) denotes Poisson distribution with mean e and the ξi are the null expected number of cases in the region i. To specify the geographical position of each region, we will use the coordinates of the administrative population centroid.
Under this situation, the circular spatial scan statistic imposes a circular window Z on each centroid. For any of those centroids, the radius of the circle varies from zero to a pre-set maximum distance d or a pre-set maximum number of regions K to be included in the cluster. If the window contains the centroid of a region, then that whole region is included in the window. In total, a very large number of different but overlapping circular windows are created, each with a different location and size, and each being a potential cluster. Let Zik, k = 1,..., K, denote the window composed by the (k - 1)-nearest neighbours to region i. Then, all the windows to be scanned by the circular spatial scan statistic are included in the set
Z1 = {Zik | 1 ≤ i ≤ m, 1 ≤ k ≤ K} (2)
A flexible scan statistic we propose, on the other hand, imposes an irregularly shaped window Z on each region by connecting its adjacent regions. For any given region i, we create the set of irregularly shaped windows with length k consisting of k connected regions including i and let k moves from 1 to the pre-set maximum K. To avoid detecting a cluster of unlikely peculiar shape, the connected regions are restricted as the subsets of the set of regions i and (K - 1)-nearest neighbours to the region i where K is a pre-specified maximum length of cluster. In total, as in the circular spatial scan statistic, a very large number of different but overlapping arbitrarily shaped windows are created. Let Zik(j), j = 1,..., jik denote the j-th window which is a set of k regions connected starting from the region i, where jik is the number of j satisfying Zik(j) ⊆ Zik for k = 1,..., K. Then, all the windows to be scanned are included in the set
Z2 = {Zik(j) | 1 ≤ i ≤ m, 1 ≤ k ≤ K, 1 ≤ j ≤ jik} (3)
In other words, for any given region i, the circular spatial scan statistic consider K concentric circles, whereas the flexible scan statistic consider K concentric circles plus all the sets of connected regions (including the single region i) whose centroids are located within the K-th largest concentric circle. So, the size of Z2 is far larger than that of Z1 which is at most mK. Details of the algorithm that we adopted to find all these arbitrarily shaped windows within a pre-specified maximum length K are given in the Appendix.
Under the alternative hypothesis, there is at least one window Z for which the underlying risk is higher inside the window when compared with outside. In other words, we are considering the following hypothesis:
H0 : E(N(Z)) = ξ(Z), for all Z, H1 : E(N(Z)) > ξ(Z), for some Z (4)
where N() and ξ() denote the random number of cases and the null expected number of cases within the specified window, respectively. For each window, it is possible to compute the likelihood to observe the observed number of cases within and outside the window, respectively. Under the Poisson assumption, the test statistic, which was constructed with the likelihood ratio test [8], is given by
where Zc indicates all the regions outside the window Z, and n() denotes the observed number of cases within the specified window and I() is the indicator function. The window Z* that attains the maximum likelihood is defined as the most likely cluster (MLC). To find the distribution of the test statistic under the null hypothesis, Monte Carlo hypothesis testing [19] is required. In this paper, p-value of the test is based upon the null distribution of likelihood ratio test statistic with a large number (we used 999) of Monte Carlo replications of the data set generated under the null hypothesis. It should be noted that, in the same manner as the circular spatial scan statistic, the flexible spatial scan statistic is also able to locate secondary clusters that do not overlap the most likely cluster but are still statistically significant.
Results
Illustrations and powers
In this section, we will compare the flexible spatial scan statistic with the circular spatial scan statistic. As an entire study population, we will use m = 113 regions comprising the wards, cities and villages in the area of Tokyo Metropolis and Kanagawa prefecture in Japan (Figure 1). The variability of regional populations for m = 113 regions is: 25 percentile = 56, 704, median = 142, 320 and 75 percentile = 200, 936.
Figure 1 An entire study population for simulation studies. The 113 regions comprising wards, cities and villages in the area of Tokyo Metropolis and Kanagawa prefecture in Japan. The region number used in the text is shown. Especially, The region numbers of four hot-spot clusters A-D are A = {14, 15, 20}, B = {14, 15, 20, 26}, C = {14, 15, 26, 27}, and D = {73, 74, 75, 76, 78}, respectively.
Hot-spot clusters
We will consider the following four hot-spot clusters where the expected total number of cases is set to be 200 under the null hypothesis.
1. Cluster A = {14, 15, 20}
2. Cluster B = {14, 15, 20, 26}
3. Cluster C = {14, 15, 26, 27}
4. Cluster D = {73, 74, 75, 76, 78}
where the region included in a hot-spot cluster is called a "hot-spot region" (hot-spot region numbers are shown in Figure 1). The relative risk within any cluster R is set to three, i.e.,
H1 : N(R) ~ Pois(θξ(R)), θ = 3.0 (6)
The cluster A is considered here as an example of a circular cluster that can be in the set of the circular windows and is expected to be identified by the circular spatial scan statistic more often than by the flexible spatial scan statistic. The other clusters are examples of noncircular clusters that are not in the set of the circular windows and thus cannot be identified correctly by the circular spatial scan statistics. For example, consider the region i0 = 15 as the starting region and the set of (K - 1)-nearest neighbours to the region 15, which is listed as follows in the ascending order of distance from the region 15:
15, 14, 20, 12, 4, 26, 13, 27, 16, 40, 19, 42, 10,...,
In this case, circular windows are {15}, {15, 14}, {15, 14, 20}, {15, 14, 20, 12}, ... When the starting region is 14 or 20, the corresponding set of (K - 1)-nearest neighbours is
14, 15, 20, 4, 16, 13, 19, 12, 5, 1, 17, 10, 26, 3, 27,...,
and
20, 14, 15, 19, 16, 4, 17, 26, 40, 13, 5, 12, 1, 27,...,
respectively. In both cases, cluster B and C are easily found to be not in the set of circular windows. The cluster D is considered as an example of a long and narrow cluster as is shown in Figure 1.
Illustrative example
As an illustration, we will apply the circular spatial scan statistic, the flexible spatial scan statistic and Duczmal and Assunção's spatial scan statistic to the disease map shown in Figure 2 which is a random sample of n = 235 cases assuming the cluster model C. Circles are drawn only for the regions whose observed-expected ratio (standardized risk ratio) is statistically significantly larger than 1 at α = 0.05. The radius of the circles is set inversely proportional to the upper tail p-value. The number shown in Figure 2 indicates the region number. Figure 2 obviously suggests the clusters occurring in the area including regions {14, 15, 26, 27, 33}.
Figure 2 A random sample from cluster model C. Dots describe the centroids of regions with some cases. Circles are drawn only for the regions whose standardized risk ratios are statistically significantly larger than 1 at α = 0.05 and the region number is placed in stead of dot. The radius is set inversely proportional to the tail probability.
Before applying the three spatial scan statistics, we have to specify a common maximum length K for the most likely cluster. This makes comparisons to a certain extent fair. In this example, we chose two kinds of maximum length K = 15 and K = 20 since it is not unreasonable to assume that an actual cluster size will be less than one third or one fourth of the size of the whole study area.
Irrespective of the value of K, the circular spatial scan statistic detected the regions {14, 15} as MLC with log likelihood ratio = 20.1, p = 1/(999 + 1) = 0.001 and the estimated relative risk is = 3.47. This is shown in Figure 3(a). The flexible spatial scan statistic, regardless of the value K, detected the regions {14, 15, 26, 27, 33} as MLC with log likelihood ratio = 29.7, p = 0.001 and the estimated relative risk is = 3.41. This is shown in Figure 3(b). Duczmal and Assunção's method, on the other hand, detected a cluster of peculiar shape that is much larger than the true cluster. In the case of K = 15, their scan statistic detected an area consisting of K = 15 connected regions {14, 15, 24, 26, 27, 31, 32, 33, 48, 54, 69, 77, 78, 90, 110 } as MLC with log likelihood ratio = 31.8, p = 0.001 and the estimated relative risk is = 2.40. This is shown in Figure 4(a). Figure 4(b) shows the most likely cluster {14, 15, 26, 27, 31, 32, 33, 48, 60, 61, 62, 67, 69, 77, 78, 80, 89, 90, 108, 110 } detected by Duczmal and Assunção's scan statistic for K = 20 where the length of MLC is also the same as K = 20 and log likelihood ratio = 36.0, p = 0.001 and the estimated relative risk is = 2.26. In the case of K = 15, the results of the three scan statistics are summarized in Table 1. Although the most likely cluster detected by Duczmal and Assunção's scan statistic has the largest log likelihood ratio among three scan statistics, it has detected MLC surprisingly larger than the true cluster.
Figure 3 The most likely cluster detected by the circular and the flexible spatial scan statistic. (a) Detected by the circular spatial scan statistic for both K = 15 and K = 20 and (b) by the flexible spatial scan statistic for both K = 15 and K = 20, when applied to a random sample from the cluster model C = {14, 15, 26, 27}.
Figure 4 The most likely cluster detected by the Duczmal and Assunção's scan statistic. (a) Detected for K = 15 and (b) for K = 20, when applied to a random sample from the cluster model C = {14, 15, 26, 27}.
Table 1 Regions detected as the most likely cluster by three procedures. Regions detected as the most likely cluster by the circular scan, the flexible scan and Duczmal and Assunção's scan, with the maximum length of cluster set to be K = 15 for the simulated random sample from the cluster model C where the hot spot cluster is assumed to be the set of connected four regions {14, 15, 26, 27} with the assumed relative risk θ = 3.0. For details, see text.
region no. population observed no. cases expected no. cases relative risk estimated (true) Log likelihood ratio (LLR) and estimated relative risk for the most likely cluster
Circular Flexible Duczmal et al.
14 319,687 14 3.794 3.69 (3.0) * * *
15 529,485 21 6.283 3.34 (3.0) * * *
LLR = 20.1
= 3.47
26 139,077 6 1.650 3.64 (3.0) * *
27 165,564 6 1.964 3.05 (3.0) * *
33 105,899 4 1.257 3.18 (1.0) * *
LLR = 29.7
= 3.41
24 466,347 8 5.534 1.44 (1.0) *
31 197,677 3 2.346 1.27 (1.0) *
32 349,050 5 4.142 1.20 (1.0) *
48 58,635 1 0.696 1.43 (1.0) *
54 3,808 1 0.045 22.12(1.0) *
69 119,575 3 1.419 2.11 (1.0) *
77 177,742 5 2.109 2.37 (1.0) *
78 125,127 2 1.485 1.34 (1.0) *
90 194,866 5 2.312 2.16 (1.0) *
110 21,535 1 0.256 3.91 (1.0) *
LLR = 31.8
= 2.41
Using a PC(Windows XP, CPU pentium 4, 3.2 GHz), the execution time of the flexible spatial scan statistic in this example is 14 seconds for K = 15 and 379 seconds for K = 20 which is certainly greater than that for the circular spatial scan statistic (less than 1 second for both K = 15 and K = 20).
Power comparison
In the power comparison, we chose K = 15. To compare the power of the flexible spatial scan statistic with that of the circular spatial scan statistic based upon Monte Carlo simulation, we will introduce a new bivariate power distribution P(l, s) classified by the length l of the significant MLC and the number s of hot-spot regions included in the most likely cluster:
where l ≥ 1 and s ≥ 0. Based on P(l, s), we examined the following powers,
1. the usual power, i.e., P(+,+) = ∑l≥1 ∑s≥0 P(l, s),
2. the joint power P(l, s), especially P(s*, s*) where s* is the length of the hot-spot cluster assumed in the simulation.
3. the marginal power distribution of s(≥ 0), P(+, s) = ∑l≥1 P(l, s) and its conditional power P(+, s)/P(+,+),
4. the marginal power distribution of l(≥ 1), P(l, +) = ∑s≥0 P(l, s).
The powers are calculated for tests of nominal α levels of 0.05 and for the expected total number of cases 200 under the null hypothesis, which are based on Monte Carlo simulation using Poisson random numbers. For each simulation, 1,000 trials were carried out. The resultant power distribution P(l, s) × 1000 is shown in Tables 2, 3, 4, 5 for each of the four cluster models, respectively, in the form of cross table classified by l ("length" in tables) and s ("include" in tables).
Table 2 Comparison of the circular and the flexible spatial scan statistic for the cluster model A. Comparison of bivariate power distribution P(l, s) × 1000 between the circular spatial scan statistic and the flexible spatial scan statistic for the hot-spot cluster A = {14, 15, 20}. Nominal α-level is set as 0.05 and 1000 trials are carried out. For more details, see text.
Flexible (K = 15) Circular (K = 15)
Length l Include s
hot-spot regions Total Length l Include s
hot-spot regions Total
0 1 2 3 0 1 2 3
1 0 0 0 1 0 0 0
2 0 0 0 0 2 1 0 0 1
3 0 0 0 142 142 3 0 0 0 738 738
4 0 0 0 116 116 4 0 0 0 134 134
5 0 0 0 137 137 5 0 0 0 39 39
6 0 0 0 149 149 6 0 0 0 12 12
7 0 0 0 165 165 7 0 0 0 9 9
8 0 0 0 131 131 8 0 0 0 1 1
9 0 0 0 84 84 9 0 0 2 3 5
10 0 0 0 27 27 10 0 0 0 2 2
11 0 0 0 11 11 11 0 0 0 4 4
12 0 0 0 2 2 12 0 0 0 12 12
13 0 0 0 0 0 13 0 0 0 14 14
14 0 0 0 0 0 14 0 0 0 3 3
15 0 0 0 0 0 15 0 0 0 6 6
Total 0 0 0 964 964 Total 1 0 2 977 980
usual power = 0.964 usual power = 0.980
Table 3 Comparison of the circular and the flexible spatial scan statistic for the cluster model B. Comparison of bivariate power distribution P(l, s) × 1000 between the circular spatial scan statistic and the flexible spatial scan statistic for the hot-spot cluster B = {14, 15, 20, 26}. Nominal α-level is set as 0.05 and 1000 trials are carried out. For more details, see text.
Flexible (K = 15) Circular (K = 15)
Length l Include s
hot-spot regions Total Length l Include s
hot-spot regions Total
0 1 2 3 4 0 1 2 3 4
1 0 0 0 1 0 0 0
2 0 0 0 0 2 0 0 0 0
3 0 0 0 0 0 3 0 0 0 523 523
4 0 0 0 0 127 127 4 0 0 0 65 0 65
5 1 0 0 0 157 158 5 0 0 0 23 0 23
6 0 0 0 0 205 205 6 0 0 0 7 66 73
7 0 0 0 2 198 200 7 0 0 0 0 15 15
8 0 0 0 1 151 152 8 0 0 0 0 32 32
9 0 0 0 5 85 90 9 0 0 0 1 15 16
10 0 0 0 1 24 25 10 0 0 0 0 7 7
11 0 0 0 0 17 17 11 0 0 0 2 3 5
12 0 0 0 0 5 5 12 0 0 0 2 63 65
13 0 0 0 0 0 0 13 0 0 0 0 96 96
14 0 0 0 0 0 0 14 0 0 0 0 30 30
15 0 0 0 0 0 0 15 0 0 0 0 22 22
Total 1 0 0 9 969 979 Total 0 0 0 623 349 972
usual power = 0.979 usual power = 0.972
Table 4 Comparison of the circular and the flexible spatial scan statistic for the cluster model C. Comparison of bivariate power distribution P(l, s) × 1000 between the circular spatial scan statistic and the flexible spatial scan statistic for the hot-spot cluster C = {14, 15, 26, 27}. Nominal α-level is set as 0.05 and 1000 trials are carried out. For more details, see text.
Flexible (K = 15) Circular (K = 15)
Length l Include s
hot-spot regions Total Length l Include s
hot-spot regions Total
0 1 2 3 4 0 1 2 3 4
1 0 0 0 1 1 0 1
2 0 0 0 0 2 0 0 351 351
3 0 0 0 0 0 3 2 0 4 0 6
4 0 0 0 0 138 138 4 0 0 3 0 0 3
5 0 0 0 3 147 150 5 2 0 2 0 0 4
6 1 0 0 2 200 203 6 1 0 0 0 0 1
7 0 1 0 4 147 152 7 0 0 0 81 0 81
8 0 0 2 9 107 118 8 0 0 10 18 38 66
9 0 0 0 10 71 81 9 0 0 2 0 26 28
10 1 0 2 5 28 36 10 0 0 0 29 3 32
11 0 0 0 0 10 10 11 0 0 1 13 1 15
12 0 0 0 0 2 2 12 0 0 2 4 60 66
13 0 0 0 0 0 0 13 0 0 0 5 62 67
14 0 0 0 0 0 0 14 0 0 0 10 27 37
15 0 0 0 0 0 0 15 0 0 0 6 37 43
Total 2 1 4 33 850 890 Total 6 0 375 166 254 801
usual power = 0.890 usual power = 0.801
Table 5 Comparison of the circular and the flexible spatial scan statistic for the cluster model D. Comparison of bivariate power distribution P(l, s) × 1000 between the circular spatial scan statistic and the flexible spatial scan statistic for the hot-spot cluster D = {73, 74, 75, 76, 78}. Nominal α-level is set as 0.05 and 1000 trials are carried out. For more details, see text.
Flexible (K = 15) Circular (K = 15)
Length l Include s
hot-spot regions Total Length l Include s
hot-spot regions Total
0 1 2 3 4 5 0 1 2 3 4 5
1 0 0 0 1 6 0 6
2 1 0 0 1 2 3 5 0 8
3 0 0 0 0 0 3 0 0 0 14 14
4 1 0 0 1 0 2 4 1 0 4 5 0 10
5 0 1 0 3 1 242 247 5 0 0 2 1 0 0 3
6 1 0 0 1 2 162 166 6 1 0 0 1 363 0 365
7 2 3 0 5 5 93 108 7 0 0 1 0 56 0 57
8 1 2 1 6 7 53 70 8 0 0 2 2 28 0 32
9 0 2 0 1 5 38 46 9 0 0 2 2 10 0 14
10 0 2 0 1 1 18 22 10 1 0 0 3 3 0 7
11 0 0 0 2 2 5 9 11 0 0 0 0 3 11 14
12 0 0 1 0 0 1 2 12 0 0 0 2 3 8 13
13 0 0 0 0 0 0 0 13 0 0 0 1 1 16 18
14 0 0 0 0 0 0 0 14 0 0 1 0 0 5 6
15 0 0 0 0 0 0 0 15 0 1 0 0 1 7 9
Total 6 10 2 20 23 612 673 Total 12 6 12 31 468 47 576
usual power = 0.673 usual power = 0.576
1) Usual power
Both tests have the same size 0.043 (distribution of length of significant MLC is omitted) and are shown to have high powers for the hot-spot clusters considered here. The flexible spatial scan statistic generally has higher power except for the model A (circular cluster) where, however, the difference is small.
2) Joint powers at (s*, s*) and at its neighbours
Table 2 shows the good characteristics of the circular spatial scan statistic. Namely, the circle-based scan statistic could detect circular hot-spot cluster A with length s* = 3 considerably more accurately with power 738/1000 compared to 142/1000 of the flexible spatial scan statistic. Tables 3, 4, 5, on the other hand, show that the power of the circular spatial scan statistic in detecting exactly noncircular hot-spot clusters is 0/1000 due to the circular window. However, the circular spatial scan statistic is seen to be able to include some of the hot-spot regions into MLC reasonably well. For example, when applied to the noncircular cluster B with length s* = 4, three or four regions including three hot-spot regions can be detected as the most likely cluster with relatively high power (523 + 65)/1000 = 0.588 (Table 3). When applied to the model D with length s* = 5, the similar high power 363/1000 can be observed at (l, s) = (6, 4) (Table 5). The flexible spatial scan statistic, on the other hand, has no such high power at a single point (l, s) near (s*, s*). However, the characteristic of the flexible spatial scan statistic is that the support of the power distribution is distributed in a relatively narrow range of / on the line s = s*,i.e, we have s* ≤ l ≤ 12 in the four cluster models considered here.
3) Marginal power P(+, s) and its conditional marginal power P(+, s)/P(+, +)
Regarding the marginal power P(+, s*) at s = s*, the flexible spatial scan statistic is shown to have much higher power than the circular spatial scan statistic for the case of noncircular clusters (Tables 3, 4, 5). Furthermore, the conditional marginal power P(+, s)/P(+, +) of the flexible spatial scan statistic is 964/964 = 1.000, 969/979 = 0.990, 850/890 = 0.955 and 612/673 = 0.909 for the cluster A-D, respectively. These results indicate that the identified MLC by the flexible spatial scan statistic includes the hot-spot cluster with quite high probability. For the noncircular clusters, the mode of P(+, s) of the circular spatial scan statistic is around s = s* - 1 or s = s* - 2.
4) Marginal power distribution P(l, +)
For the flexible spatial scan statistic, the probability that the length of significant MLC is less than s = s* is shown to be zero or quite small and the maximum length is around 10 to 12. the circular spatial scan statistic, on the other hand, tends to detect a much longer cluster than expected from the hot-spot cluster assumed in the simulation. For example, the probability that the length of MLC for the cluster B with length s* = 4 is greater than or equal to 12 is 213/1000 = 0.213 compared with 5/1000 = 0.005 for the flexible spatial scan statistic. The probability that the length of MLC for the cluster C with length s* = 4 is greater than or equal to 12 is 213/1000 = 0.213 compared with 2/1000 = 0.002 for the flexible spatial scan statistic. This tendency is shown even in the circular cluster A where the same probabilities are 0.035 vs. 0.002.
Cost comparison
Based upon the bivariate power function P(l, s), we can compute the following expected total cost incurred by incomplete identification of the true cluster:
C = C2{rE(s* - S) + E(L - S)}, r = C1/C2 (8)
where C1 and C2 denote the average cost of missing one region in the true cluster and that of incorrectly detecting one region not in the true cluster, respectively. L and S denote the random variable of l and s, respectively. Two expected numbers E(s* - S) and E(L - S) for four kinds of clusters A-D are shown in Table 6. In general, we can assume r > 1. For example, the ratio C/C2 is shown for the case of r = 1 and r = 2, respectively, in Table 6. However, in this example, irrespective of the value of r(> 1), the circular spatial scan statistic is shown to have lower cost for detecting circular cluster A but to have higher cost for detecting non-circular clusters B-D.
Table 6 Cost comparison Expected number of undetected regions included in the true cluster E(s* - S), expected number of detected regions not in the true cluster E(L - S) and the ratio of costs C/C2 (r = 1, 2) incurred by incomplete identification of the true cluster. The spatial scan statistic with low values is better.
Hot-spot Cluster Scan statistic E(s* - S) E(L - S) the ratio C/C2
r = 1 r = 2
A = {14, 15, 20} Flexible (K = 15) 0.108 2.951 3.059 3.167
Circular (K = 15) 0.065 0.722 0.787 0.852
B = {14, 15, 20, 26} Flexible (K = 15) 0.097 2.548 2.645 2.742
Circular (K = 15) 0.735 2.525 3.260 3.995
C = {14, 15, 26, 27} Flexible (K = 15) 0.492 2.243 2.735 3.227
Circular (K = 15) 1.736 3.153 4.889 6.625
D = {73, 74, 75, 76, 78} Flexible (K = 15) 1.774 1.088 2.862 4.636
Circular (K = 15) 2.770 1.709 4.479 7.249
Limitations of current work
Needless to say, the results derived here are based upon a small Monte Carlo simulations study and thus the characteristic observed in the current work could change a little bit depending on the cluster model adopted. We assumed here only one hot spot cluster and did not consider the case of several hot spot clusters. Therefore, we need a further simulation study to compare the performance of the two spatial scan statistics under several different clusters.
Regarding the algorithm adopted for the flexible spatial scan statistic, we set the restriction that irregularly shaped windows Z with length k(≤ K) are constructed from members of the (K - 1)-nearest neighbours to the starting region. It seems that this restriction plays an important role in preventing the flexible spatial scan statistic from reaching out for and absorbing faraway regions with non-elevated risk. However, to avoid undertaking computationally infeasible searches, the flexible spatial scan statistic has to be set with an upperbound for K. This depends on the disease map under study and the capability of the computer. The current practical upperbound is around K = 30 for the reason that the execution time of our current algorithm will take more than a week if K > 30 for the number of regions m = 200 ~ 300. However, it seems to be unlikely that the length of the true cluster would be larger than 10 ~ 15 percent of the total number of regions. So, we think that our current algorithm can be applied to many epidemiological studies with small to moderate cluster sizes. However, for larger cluster sizes, a more sophisticated algorithm to increase the upperbound for K is needed.
Regarding data type, the proposed spatial scan statistic can only be applied to regional count data whereas the circular spatial scan statistic can be applied to not only count data but also individual point data. However, at least in disease surveillance, most of the data that people analyze is aggregated, so the method covers most real-world situations.
Finally, one of the reviewers commented that using small areas as basis for clustering without any attempt to incorporate heterogeneity in background rates is a fundamental flaw of all existing scanning methods. In general, we know that disease risks over study regions are heterogeneous to a certain extent and the null hypothesis of complete spatial randomness is not true. However, statistical hypothesis testing is based upon the null hypothesis which is not true. Likewise, we will use complete spatial randomness as the null hypothesis as indicated in equation (1) since we are interested in rejecting the null hypothesis and detecting the local clusters with excess risk. If we are interested in estimating a clustering mechanism, we should use some modeling approach rather than spatial scan statistics.
Discussion
In this paper, we proposed a flexibly shaped spatial scan statistic to detect arbitrarily shaped clusters by amalgamating administrative units. The flexible spatial scan statistic is, via Monte Carlo simulation, shown to have reasonably high powers compared with the circular spatial scan statistic when examined by a newly introduced bivariate power distribution P(l, s). The simulation reveals that the circular spatial scan statistics shows a high level of accuracy in detecting circular clusters exactly and reasonably good power for including some hot-spot regions into the most likely cluster. The flexible spatial scan statistic exhibits no such high power regarding exact identification of clusters but the support of the power distribution is shown to be concentrated in a relatively narrow range of length l on the line s = s*, indicating that an observed significant most likely cluster contains the true cluster with quite high probability. The circular spatial scan statistic, on the other hand, is shown to have zero powers for detecting exactly noncircular clusters that cannot be captured by any circular window. The circular spatial scan statistic is also shown to have a tendency to detect a larger cluster than the true cluster assumed in the simulation even for the case when the true cluster is circular. Furthermore, by introducing the two kinds of cost due to incomplete detection of the true cluster, we could summarize these characteristics in terms of minimizing expected total cost. One of the reviewers suggested a similar cost comparison using the number of people that are incorrectly classified rather than the number of regions since the cost of misclassifying a large region is at least for disease surveillance purposes higher than that of misclassifying a region with smaller population. We think that would be an interesting additional simulation study worth conducting. However, since it can be expected that the result of such a cost comparison strongly depends on the spatial configuration of regions with different population size in the neighborhood of and within the true cluster and thus it requires careful design for creating suitable cluster models from which we can intuitively infer the result to a certain extent, we would like to leave such a simulation study in our future work.
The surprising result that Duczmal and Assunção's scan statistic detected quite large and unlikely peculiar shaped clusters that had the largest likelihood ratio among the three scan statistics might cast a doubt on the validity of the model selection based upon maximizing the likelihood ratio (5). Such a doubt can also be seen in some simulation results of the circular spatial scan statistic that had non-negligible probabilities of detecting much longer clusters than the true cluster. The flexible spatial scan statistic, on the other hand, is shown not to detect such an unexpected long cluster probably because it has the restriction that our windows are constructed only from members of the (K - 1)-nearest neighbours to the starting region. Nevertheless, these undesirable properties produced by maximum likelihood ratio might suggest the use of a different criterion for model selection. For example, we might consider a penalized likelihood where we consider a penalty for the complexity of the cluster shape, which is also worth future research.
All the computations and simulations have been conducted on a PC with Windows XP. For users who are interested in applying the flexible spatial scan statistic, we can provide the software FleXScan [20].
Conclusion
The circular spatial scan statistics shows a high level of accuracy in detecting circular clusters exactly and reasonably good power for including some hot-spot regions into the most likely cluster. The proposed flexible spatial scan statistic is shown to have good usual powers plus the ability to detect the noncircular hot-spot clusters more accurately than the circular spatial scan statistic. However, the proposed spatial scan statistic work well for small to moderate cluster size, say up to 30. For larger cluster sizes, the method is not practically feasible and a more efficient algorithm is needed.
Appendix: algorithm to find the set Z2 defined in equation (3)
There are probably several procedures to find the set Z2 that is defined as the set of arbitrarily shaped windows Z within a pre-specified maximum length K. The algorithm that we used is described as follows:
Step 1. First we set an m × m matrix A = (aij) such as
and set Z2 = φ and i0 = 0
Step 2. Let i0 ← i0 + 1 and i0(= 1, 2,..., m) be the starting region. Then we create the set consisting of (K - 1)-nearest neighbours to the starting region i0 and i0 itself, i.e.,
= {i0, i1, i2,..., iK - 1},
where ik is the k-th nearest to i0.
Step 3. We consider all the set Z ⊂ , which includes the starting region i0. For any given such set Z, repeat the following steps 4–7.
Step 4. We divide the set Z into two disjoint sets: Z0 = {i0} and Z1 which contains the other regions of Z.
Step 5. We make two new sets and . consists of the regions of Z1 that are connected to some regions of Z0. On the other hand, consists of the regions of Z1 that are not connected to any regions of Z0. Then we replace Z0 and Z1 by and , respectively.
Step 6. We repeat the step 5 recursively until either Z0 or Z1 becomes null first.
Step 7. We make a decision as follows. Z is said to be "connected" when Z1 becomes null first and "disconnected" when Z0 becomes null first. If we can find Z "connected", Z is added to the set Z2. If we find Z "disconnected", Z is discarded.
Step 8. Repeat the steps 2–7 until we finally get the set Z2 consisting of arbitrarily shaped windows Z whose maximum length is K.
Now we shall give an example using regions in the Tokyo Metropolitan area shown in Figure 1. Let the starting region i0 = 14. Then, the regions in the set of (K - 1)-nearest neighbours to the region 14 are listed as follows in the ascending order of distance to the region 14, i.e.,
W14 = {14, 15, 20, 4, 16, 13, 19, 12, 5,...}.
Suppose that we take a subset Z = {14, 15, 20, 26}. In the first step, we have
Z0 = {14}, Z1 = {15, 20, 26}.
Since a14,15 = a14,20 = 1 and a14,26 = 0, we then have
Z0 = {15, 20}, Z1 = {26}.
Further, because a15,26 = a20,26 = 1, these sets are replaced by
Z0 = {26}, Z1 = φ.
So, we can find that the set Z = {14, 15, 20, 26} is "connected" and can be a member of Z2.
If we take a subset Z = {14, 15, 20, 5}, we can find Z is "disconnected" because a14,5 = a15,5 = a20,5 = 0, Z0 = φ and Z1 = {5} at the final stage.
Authors' contributions
TT proposed the flexibly shaped spatial scan statistic and the bivariate power distribution. KT considered the algorithm given in the appendix, programmed the C++ code and carried out the power simulations. TT wrote the first draft of the manuscript. Both authors interpreted the results and wrote the final version of the paper.
Acknowledgements
This research was supported in part by Grant-in-Aid for Scientific Research (Grant No. 16300091) from the Ministry of Education, Culture, Sports, Science and Technology of Japan.
==== Refs
Marshall RJ A review of the statistical analysis of spatial patterns of disease Journal of Royal Statistical Society, Series A 1991 154 421 441
Lawson A Biggeri A Böhning D Lesaffre E Viel JF Bertollini R (Eds) Disease Mapping and Risk Assessment for Public Health 1999 London: John Wiley & Sons
Lawson A Denison D Spatial Cluster Modelling 2002 Boca Raton: CRC Press
Waller LA Gotway CA Applied Spatial Statistics for Public Health Data 2004 New York: John Wiley & Sons
Cuzick J Edwards R Spatial clustering for inhomogeneous populations (with discussion) Journal of the Royal Statistical Society, Series B 1990 52 73 104
Besag J Newell J The detection of clusters in rare diseases Journal of the Royal Statistical Society, Series A 1991 154 143 155
Kulldorff M Nagarwalla N Spatial disease clusters: detextion and inference Statistics in Medicine 1995 14 799 810 7644860
Kulldorff M A spatial scan statistic Communications in Statistics 1997 26 1481 1496
Tango T A class of tests for detecting 'general' and 'focused' clustering of rare diseases Statistics in Medicine 1995 14 2323 2334 8711272
Tango T A test for spatial disease clustering adjusted for multiple testing Statistics in Medicine 2000 19 191 204 10641024 10.1002/(SICI)1097-0258(20000130)19:2<191::AID-SIM281>3.0.CO;2-Q
Viel JF Arveux P Baverel J Cahn JY Soft-tissue sarcoma and non-Hodgkin's lymphoma clusters and a municipal solid waste incinerator with high dioxin emission levels American Journal of Epidemiology 2000 152 13 19 10901325 10.1093/aje/152.1.13
Sankoh OA Ye Y Sauerborn R Muller O Becher H Clustering of childhood mortality in rural Burkina Faso International Journal of Epidemiology 2001 30 485 492 11416070 10.1093/ije/30.3.485
Perez AM Ward MP Torres P Ritacco V Use of spatial scan statistics and monitoring data to identifyclustering of bovine tuberculosis in Argentina Preventive Veterinary Medicine 2002 56 63 74 12419600 10.1016/S0167-5877(02)00124-1
Kulldorff M Tango T Park PJ Power comparisons for disease clustering tests Computational Statistics and Data Analysis 2003 42 665 684 10.1016/S0167-9473(02)00160-3
Song C Kulldorff M Power evaluation of disease clustering tests International Journal of Health Geographics 2003 2 1 8 12556244
Kulldorff M Information Management Services Inc SaTScan v4.0: Software for the spatial and space-time scan statistics 2004
Patil GP Taillie C Upper level set scan statistic for detecting arbitrarily shaped hotspots Environmental and Ecological Statistics 2004 11 183 197 10.1023/B:EEST.0000027208.48919.7e
Duczmal L Assunção R A simulated annealing strategy for the detection of arbitrarily shaped spatial clusters Computational Statistics & Data Analysis 2004 45 269 286 10.1016/S0167-9473(02)00302-X
Dwass M Modified randomization test for nonparametric hypotheses Annals of Mathematical Statistics 1957 28 181 187
Takahashi K Yokoyama T Tango T FleXScan: Software for the flexible spatial scan statistic 2004 National Institute of Public Health, Japan
| 15904524 | PMC1173134 | CC BY | 2021-01-04 16:39:06 | no | Int J Health Geogr. 2005 May 18; 4:11 | utf-8 | Int J Health Geogr | 2,005 | 10.1186/1476-072X-4-11 | oa_comm |
==== Front
J Circadian RhythmsJournal of Circadian Rhythms1740-3391BioMed Central London 1740-3391-3-81592707410.1186/1740-3391-3-8ResearchIntermittent long-wavelength red light increases the period of daily locomotor activity in mice Hofstetter John R [email protected] Amelia R [email protected] Amanda M [email protected] Aimee R [email protected] Roudebush VA Medical Center, 1481 W. 10th St., Indianapolis, IN, 46202, USA2 Berry College, P.O. Box 491640, Mt. Berry, GA 30149-1640, USA3 Richmond-upon-Thames College, Egerton Road, Twickenham, Middlesex, UK2005 31 5 2005 3 8 8 28 3 2005 31 5 2005 Copyright © 2005 Hofstetter et al; licensee BioMed Central Ltd.2005Hofstetter et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background
We observed that a dim, red light-emitting diode (LED) triggered by activity increased the circadian periods of lab mice compared to constant darkness. It is known that the circadian period of rats increases when vigorous wheel-running triggers full-spectrum lighting; however, spectral sensitivity of photoreceptors in mice suggests little or no response to red light. Thus, we decided to test the following hypotheses: dim red light illumination triggered by activity (LEDfb) increases the circadian period of mice compared to constant dark (DD); covering the LED prevents the effect on period; and DBA2/J mice have a different response to LEDfb than C57BL6/J mice.
Methods
The irradiance spectra of the LEDs were determined by spectrophotometer. Locomotor activity of C57BL/6J and DBA/2J mice was monitored by passive-infrared sensors and circadian period was calculated from the last 10 days under each light condition. For constant dark (DD), LEDs were switched off. For LED feedback (LEDfb), the red LED came on when the mouse was active and switched off seconds after activity stopped. For taped LED the red LED was switched on but covered with black tape. Single and multifactorial ANOVAs and post-hoc t-tests were done.
Results
The circadian period of mice was longer under LEDfb than under DD. Blocking the light eliminated the effect. There was no difference in period change in response to LEDfb between C57BL/6 and DBA/2 mice.
Conclusion
An increase in mouse circadian period due to dim far-red light (1 lux at 652 nm) exposure was unexpected. Since blocking the light stopped the response, sound from the sensor's electronics was not the impetus of the response. The results suggest that red light as background illumination should be avoided, and indicator diodes on passive infrared motion sensors should be switched off.
==== Body
Introduction
One of the earliest observations in the study of circadian rhythms was that continuous light (LL) lengthens circadian period in most nocturnal animal species [1]. "Aschoff's Rule" posits that there is a positive log-linear relationship between the LL intensity and period [2-5]. In all these studies LL was white light, in one study full-spectrum light [4]. However, we found that mice had slightly longer circadian periods when the monitoring device was a passive infrared (ir) proximity sensor compared to a system using ir beams that crossed the cage. The only obvious difference between the systems was that the proximity sensor had a small, red light-emitting diode (LED) that came on immediately after discerned motion and stayed on for several seconds after motion was not discernable.
The first question to be raised is whether a dim red LED can affect the circadian system of mice. The circadian rhythm of locomotor activity in rats is entrained by red light [6]. However, several studies which examined the spectral sensitivity of the photoreceptors in mice suggest little or no response to red light. The peak sensitivity of the photoreceptors that mediate phase shifts in pigmented inbred mouse strains is between 500 nm [7] and 511 nm [8] (blue-green light). The sensitivity of the photoreceptors drop sharply and is vanishingly small at wavelengths above 600 nm (orange light) [7-9]. In mice lacking rods and cones, the peak sensitivity for phase-shifting is 481 nm, and sensitivity drops to zero at less than 600 nm [9]. In pigmented mice, electroretinographic responses to a flickering monochromatic light and the behavioral responses to a forced-choice discrimination task peak at 510 nm [10]. The light sensitivity in both tests drops sharply as the wavelength approaches 600 nm. Melanopsin, in combination with the classical rod and cone photoreceptors, accounts for the transduction of photic information to the circadian system. We are unaware of studies of the Aschoff effect in rodless and coneless mice, but melanopsin knockout mice have an attenuated Aschoff effect compared to wild-type mice [11,12].
The second question is whether light presented only in response to activity can lengthen period in mice. Pittendrigh and Daan suggested that light pulses during the photosensitive portion of an animal's circadian cycle mimic the effect of LL on period [13]. Ferraro and McCormack (1986) confirmed this in rats using feedback lighting (LDfb) [14]. In their LDfb apparatus, the lighting in each rodent's cage was controlled by each rodent's own locomotor activity. When wheel revolutions reached a certain rate, the cage lighting came on. The lights went out 2 minutes after wheel-running tapered off below the target rate. They compared LL to LDfb at 0.1, 1 and 100 lux of light. They found that circadian period under LDfb obeyed Aschoff's rule, and feedback lighting increased circadian period by the same amount as an equivalent irradiance of continuous light.
In earlier studies we showed that C57BL/6 and DBA/2 mice differed in their Aschoff affect comparing constant dark to constant full-spectrum LL. At 10 lux, the C57BL/6 mice had an increase in period of 1.20 hours but the period of the DBA/2 mice increased only 0.20 hours [4]. Consequently we predicted that the C57BL/6 mice would have a greater increase in period under the LD feedback regimen than DBA/2 mice.
This study tests the hypotheses that a dim red LED provided as feedback to activity elicits an increase in circadian period of locomotor activity and that C57BL/6 and DBA/2 mice have a differential response to the red light stimulus.
Methods
General housing and care
Mice were housed singly in optically clear polycarbonate cages (L × H × W: 11 × 8 × 7 in) with approximately 250 ml of Sani-chip® (Harlan Teklad) bedding. They were acclimated under alternating 200 lux light and dark of 12 hours each (LD 12:12) for at least two weeks prior to the start of the study. Food (Teklad 7001 Mouse & Rat Diet 4%) and water were continuously available throughout the study. All animals were maintained in facilities fully accredited by the Association for the Assessment and Accreditation of Laboratory Animal Care. All research protocols and animal care were approved by the Institutional Animal Care and Use Committee in accordance with the guidelines of the Guide for the Care and Use of Laboratory Animals (Institute of Laboratory Animal Resources, Commission on Life Sciences, National Research Council, 1996).
Experimental housing and care
For measurement of circadian period, all test mice were kept in a sound attenuating, ventilated room at a constant temperature (23°C) and under continuous darkness (DD). Sound attenuating, opaque dividers were placed between the test cages. Caretakers wore a Pelican Versabrite headlamp fitted with a red safelight beam diffuser. The diffuser/filter transmitted light greater than 600 nm only. Care in the darkroom consisted of ten min per day and each mouse was inspected for less than a minute. Daily visits occurred at random times between 8 am and 5 pm.
Locomotor activity assessment
Daily locomotor activity of the mice was monitored with passive infrared detectors (Ademco, Syosset, NY) mounted over each cage. The passive infrared (ir) proximity sensor works by emitting pulses of ir light, and then measuring the distance to objects from the flight time of the reflected signal. Whenever the distance changes, the detector opens or closes a switch. All detectors were tested to ensure response uniformity. Each detector had a red LED that switched on when motion was detected, then switched off 3 to 5 seconds after movement was no longer sensed. The LED could be disabled with a switch mounted on the motion sensor circuit board.
Spectral analysis
The irradiance spectra of the LEDs were determined using an S.I. Photonics fiber optic spectrophotometer (Tucson, AZ). The distance between the fiber optic input probe and the LED was 18 cm (the depth of the mouse cage). A random sample of eight of the 16 motion sensors used in the study was assessed. A hand-held light meter (UDT Instruments, Baltimore, MD) was used to measure illuminance produced by the LED at about 5 cm from the bottom of the cage and 13 cm from the LED. The test was repeated with the LEDs covered with black electrician's tape.
Assessment of circadian period of locomotor activity
Activity events were grouped into 5-minute bins by the Stanford Chronobiology Systems' (Stanford, CA) data processing and automatic storage system integrated into a Dell computer. Clocklab, the biological rhythm analysis software (Actimetrics, Evansville, IL), was used to calculate the period of locomotor activity of each mouse using linear regression through activity onsets of the last 8 to 10 days of each treatment.
Experiment 1: Hypothesis – LEDfb changes circadian period compared to DD
Mouse husbandry
C57BL/6 mice were bred in our facility from mice purchased from Jackson Laboratory (Bar Harbor, ME). Two male and six female C57BL/6 mice between the ages of 185 to 295 d were studied.
Experimental protocol
Four mice were put under motion sensors with the LED enabled (LEDfb), and four were put under sensors with the LED disabled (DD). The locomotor activity of the mice was monitored for two weeks (Stage 1). Then treatment was switched, and activity of the mice was monitored for another two weeks (Stage 2). The circadian period for each stage was calculated from the last 8 to 10 days under a given condition.
Statistical analysis
A factorial ANOVA (SAS ver. 9.1) tested for effect of sex, age, lighting condition (LEDfb compared to DD) and sequence of light treatment (LEDfb first compared to DD first). A post-hoc Tukey's Studentized Range test compared periods under different lighting protocols.
Experiment 2: Hypothesis – The effect of LEDfb on circadian period can be eliminated by blocking the light source
Mouse husbandry
Twelve male C57BL/6 mice aged 30 d were purchased from Jackson Laboratory and housed singly.
Experimental protocol
Following acclimation to our facility in LD 12:12 for two weeks, they were moved into DD. All mice were put under motion sensors with the LED enabled (LEDfb), but black electrician's tape covered the LEDs of six motion sensors (taped LED) for two weeks. For Stage 2, all the LEDs were turned off for two weeks of DD. For Stage 3, the treatment condition of Stage 1 was switched, i.e. all LEDs were enabled but the LEDs previously covered by tape were uncovered and the previously uncovered LEDs were covered. Mouse activity was monitored continuously throughout the experiment.
Statistical analysis
A one-way ANOVA tested for effect of lighting condition (DD compared to LEDfb and taped LED), with a post-hoc Tukey's Studentized Range test.
Experiment 3: Hypothesis – C57BL/6 and DBA/2 mice have different response to LEDfb
Mouse husbandry
Eight male C57BL/6 mice and eight male DBA/2 mice were purchased from Jackson Laboratory, age 4 weeks.
Experimental protocol
Following acclimation to our facility in LD 12:12 for two weeks, mice were moved into DD. Four mice of each strain (DBA/2 and C57BL/6) were put under motion sensors with the LED enabled (LEDfb), and four of each strain were put under sensors with the light disabled (DD). At the end of Stage 1, they were moved to LD 12:12 for one week. When mice returned to the assessment room under DD, the treatment condition was switched. Activities of all mice were monitored for another two weeks.
Statistical analysis
A two-factor ANOVA tested for effect of strain and lighting condition (LEDfb compared to DD) with a post-hoc Tukey's Studentized Range test. The change in period from LEDfb compared to DD (Δτ) was calculated for each mouse and compared by a t-test.
Results
Light measurements
The irradiance spectrum of the LED for a sample of 8 proximity sensors was a narrow band centered on 652 nm. Figure 1 shows a representative spectrum. The illuminance of the LED was one lux. The illuminance of the LED covered with black electrician's tape was zero.
Figure 1 The irradiance spectrum of a red LED integrated into the passive-infrared motion sensor circuitry.
Experiment 1: LEDfb changes circadian period compared to DD
Representative actograms of C57BL/6 mice under DD and dim red LEDfb are shown in Figure 2. The mean period in DD was 24.05 ± 0.04 h, and under red light LEDfb it was 24.21 ± 0.04 h. A factorial ANOVA testing for effect of sex, age, lighting condition (LEDfb compared to DD) and sequence of light treatment showed no effect of sex, age or sequence but an effect of lighting condition on period [F1,5 = 7.72, p = 0.039]. A post hoc Tukey's test showed longer period with LEDfb compared to DD (p = 0.0095). Figure 3 shows the effects of LEDfb on the circadian period of locomotor activity.
Figure 2 Double-plotted actograms of C57BL/6 mice under DD and dim red LEDfb. Lighting conditions are shown to the right of each actogram.
Figure 3 The circadian period of C57BL/6 mice is longer under dim red LEDfb than DD conditions (p = 0.0095). Lines show the mean period for each group.
Experiment 2: The effect of LEDfb on circadian period can be eliminated by blocking the light source
Representative actograms of C57BL/6 mice under DD, dim red LEDfb, and LEDs coved with black tape are shown in Figure 4. The mean period of 12 mice in DD was 23.96 ± 0.03 h; under taped LEDs, it was 23.93 ± 0.03 h; and, under LEDfb, it was 24.07 ± 0.03 h. There was a significant effect of lighting condition by one-way ANOVA [F2,33 = 7.02, p = 0.0029]. A post-hoc Tukey's test showed a longer period under the uncovered LED than under the tape-covered LED (p < 0.01) or DD (p < 0.025), as summarized in Figure 5. Periods did not differ between DD and tape-covered LED.
Figure 4 Double-plotted actograms of C57BL/6 mice under DD, dim red LEDfb, and LEDs covered with black tape. Lighting conditions are shown to the right of each actogram. Arrows show onset of new lighting conditions.
Figure 5 Circadian period of C57BL/6 mice is longer under dim red LEDfb than when the light source is covered by black tape (p < 0.01) or DD (p < 0.025). Lines show the mean period for each group.
Experiment 3: C57BL/6 and DBA/2 mice do not have different responses to LEDfb
Representative actograms of DBA/2 and C57BL/6 mice under DD and dim red LEDfb are shown in Figure 6. For C57BL/6 mice, the mean period under DD was 23.85 ± 0.07 h; the mean period under LEDfb was 24.00 ± 0.07 h. For DBA/2 mice, the mean period under DD was 23.46 ± 0.14 h; the mean period under LEDfb was 23.78 ± 0.08 h. A two-factor ANOVA testing for effect of strain and lighting condition (LEDfb compared to DD) showed a significant effect of both strain [F1,14 = 7.73, p = 0.0147] and lighting condition [F1,14 = 10.99, p = 0.0051] but no interaction. A post-hoc Tukey's test showed longer period with LEDfb compared to DD (p < 0.025). The C57BL/6 mice had different periods from the DBA/2 mice by post-hoc Tukey's test (p < 0.01). Figure 7 shows the effects of LEDfb on the circadian period of locomotor activity in the two strains of mice.
Figure 6 Double plotted actograms of DBA/2 and C57BL/6 mice under DD (top) and dim red LEDfb (bottom). The actograms at top and bottom are from one DBA/2 mouse (left) and one C57BL/6 mouse (right). Lighting conditions were separated by two weeks of LD 12:12.
Figure 7 The circadian period of both DBA/2 and C57BL/6 mice under DD (filled symbols) and dim red LEDfb (open symbols). Lines show the mean period for each group. Overall, mice had longer period under LEDfb than DD (p < 0.025), and C57BL/6 mice had longer periods than DBA/2 mice (p < 0.01).
The mean increase in period with LEDfb (period under LEDfb minus period under DD, Δτ) for C57BL/6 mice was 0.15 ± 0.05 h. For DBA/2 mice, Δτ was 0.32 ± 0.13 h. The increase in period with LEDfb did not differ between strains by t-test (p = 0.26).
In summary, circadian period was significantly longer under LEDfb (a small, red LED whose intensity was about 1 lux which came on only when a mouse was active) than that under DD in both C57BL/6 and DBA/2 strains of mice. The LEDs gave off red light in a narrow band centered on 652 nm. Covering the LED with black tape blocked the effect of the dim red light. Furthermore, there was no difference in this effect between the two strains.
Discussion
This study suggests that the circadian system in mice is responsive to long wavelength red light. The result is surprising because recent studies suggest that melanopsin, in combination with the classical rod and cone photoreceptors, account for the transduction of photic information to the circadian system. There are no studies of spectral sensitivity of the Aschoff effect in mice. However, the spectral sensitivity of photoreceptors mediating circadian phase-shifts in mice is vanishingly small at wavelengths above 600 nm [7-9]. In most organisms, circadian period under LL is a function of both intrinsic period and photic inputs. The Aschoff effect is understood to result from the cumulative phase-shifting effect of LL on the pacemaker [5,13,15]. Thus an effect of red light on circadian period is unexpected.
One possible explanation is that there is another photopigment present in mammals that is sensitive to far-red light and affects period rather than phase. It cannot be excluded that period and phase are affected by different light receptors or light receptive pathways. It seems more likely that low sensitivity to red light via the known circadian photopigments has a cumulative period-lengthening effect on the pacemaker. The timing of light exposure could have amplified this effect. Under LEDfb mice received light between circadian time (CT 12) and CT 24, during their active phase. The period-response curves (τRC) of mice have period-shortening between CT 4 and CT 16 and period-lengthening between CT 16 and CT 4 [16]. LEDfb should cause substantial period-lengthening, with minimal period-shortening.
This study has several limitations. Only the Aschoff effect was investigated, and this was not under the usual protocol of constant light. Nevertheless, the increase in circadian period of mice under LEDfb was consistent with a prior activity feedback study in rats, where wheel-running triggered full-spectrum illumination resulting in lengthened circadian period [14].
Covering the LED with black tape blocked the effect of the dim red light. We conclude that ultrasound from the LEDs or the electronics associated with their illumination did not produce the effect. Mice emit ultrasonic cries and this is important in maternal behavior [17-19]. However, it is unlikely that covering the lights with black tape would block ultrasound. Although this remains a possibility, we are aware of no instances in the literature where ultrasound causes either a phase response or a change in circadian period.
The C57BL/6 and DBA/2 mice did not differ in the amount period increased with 1 lux red light LEDfb. This is in contrast to an earlier study where C57BL/6 mice had a greater increase in period with 10 lux full-spectrum LL vs DD than DBA/2 mice [4]. One possible explanation is that DBA/2 mice are more sensitive to period-lengthening effects of red light than of full-spectrum light. Another possibility is that the shape of the τRC differs between the two strains, so that for C57BL/6 mice more of the period-lengthening portion of the τRC lies outside of the time when they received light during LEDfb than for the DBA/2 mice. In this case, constant LL would have more period-lengthening effect than LEDfb.
The results of this study suggest that investigators cannot use continuous dim red light to simulate DD, and must be judicious in using red "safe" lights for animal care in DD. Further studies are needed to determine whether constant red light of this output spectra and intensity lengthens period more than LEDfb, and whether it can phase-shift the circadian rhythms in mice.
Conclusion
Mice under a dim, long-wavelength red light that came on intermittently when the animals were active had a circadian period that was long compared to their free-running period under DD. Covering the light with black tape blocked the response. Furthermore, under the conditions described, the magnitude of the mean circadian period increase in DBA/2 and C57BL/6 strains of mice was indistinguishable.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
JRH conceived of the study, participated in its design and statistical analysis and drafted the manuscript.
ARH carried out experiment 1, designed and carried out experiment 3, and wrote the Methods section.
AMH participated in the statistical analysis and designed and set up experiment 2.
ARM carried out experiment 2, participated in the statistical analysis and assisted in drafting the manuscript.
All authors read and approved the final manuscript.
Acknowledgements
This work was supported by a Merit Grant to Dr. Mayeda from the Department of Veterans Affairs.
==== Refs
Aschoff J Exogenous and endogenous components in circadian rhythms Cold Spr Harbor Symp Quant Bio 1960 25 11 28
Pittendrigh CS Aschoff J Circadian systems: Entrainment Handbook of Behavioral Neurobiology 1981 14 New York, Plenum Press 95 124
Possidente B Hegmann JP Gene differences modify Aschoff's rule in mice Physiol Behav 1982 28 199 200 7200614 10.1016/0031-9384(82)90126-3
Hofstetter JR Mayeda AR Possidente B Nurnberger JIJ Quantitative trait loci (QTL) for circadian rhythms of locomotor activity in mice Behav Genet 1995 25 545 556 8540893
Daan S Pittendrigh CS A functional analysis of circadian pacemaker in nocturnal rodents: III. Heavy water and constant light: homeostasis of frequency? J Comp Physiol 1976 106 267 290 10.1007/BF01417858
McCormack CE Sontag CR Entrainment by red light of running activity and ovulation rhythms of rats Am J Physiol 1980 239 R450 R453 7435660
Yoshimura T Ebihara S Spectral sensitivity of photoreceptors mediating phase-shifts of circadian rhythms in retinally degenerate CBA/J (rd/rd) and normal CBA/N (+/+)mice J Comp Physiol [A] 1996 178 797 802 8667293
Provencio I Foster RG Circadian rhythms in mice can be regulated by photoreceptors with cone-like characteristics Brain Res 1995 694 183 190 8974643 10.1016/0006-8993(95)00694-L
Hattar S Lucas RJ Mrosovsky N Thompson S Douglas RH Hankins MW Lem J Biel M Hofmann F Foster RG Yau KW Melanopsin and rod-cone photoreceptive systems account for all major accessory visual functions in mice Nature 2003 424 75 81 10.1038/nature01761
Jacobs GH Neitz J Deegan JF Retinal receptors in rodents maximally sensitive to ultraviolet light Nature 1991 353 655 656 1922382 10.1038/353655a0
Ruby NF Brennan TJ Xie X Cao V Franken P Heller HC O'Hara BF Role of Melanopsin in Circadian Responses to Light Science 2002 298 2211 2213 12481140 10.1126/science.1076701
Panda S Sato TK Castrucci AM Rollag MD DeGrip WJ Hogenesch JB Provencio I Kay SA Melanopsin (Opn4) Requirement for Normal Light-Induced Circadian Phase Shifting Science 2002 298 2213 2216 12481141 10.1126/science.1076848
Pittendrigh CS Daan S A functional analysis of circadian pacemakers in nocturnal rodents: IV. Entrainment: pacemaker as clock J Comp Physiol 1976 106 291 331 10.1007/BF01417859
Ferraro JS McCormack CE Minimum duration of light signals capable of producing the Aschoff effect Physiol Behav 1986 38 139 144 3786494 10.1016/0031-9384(86)90144-7
Pickard GE Tang WX Pineal photoreceptors rhythmically secrete melatonin Neurosci Lett 1994 171 109 112 8084468 10.1016/0304-3940(94)90617-3
Weinert D Kompauerova V Light-induced phase and period responses of circadian activity rhythms in laboratory mice of different age Zoology 1998 101 45 52
D'Amato FR Scalera E Sarli C Moles A Pups Call, Mothers Rush: Does Maternal Responsiveness Affect the Amount of Ultrasonic Vocalizations in Mouse Pups? Behav Genet 2005 35 103 112 15674537 10.1007/s10519-004-0860-9
Gourbal BE Barthelemy M Petit G Gabrion C Spectrographic analysis of the ultrasonic vocalisations of adult male and female BALB/c mice Naturwissenschaften 2004 91 381 385 15278217 10.1007/s00114-004-0543-7
Liu RC Miller KD Merzenich MM Schreiner CE Acoustic variability and distinguishability among mouse ultrasound vocalizations J Acoust Soc Am 2003 114 3412 3422 14714820 10.1121/1.1623787
| 15927074 | PMC1173135 | CC BY | 2021-01-04 16:39:14 | no | J Circadian Rhythms. 2005 May 31; 3:8 | utf-8 | J Circadian Rhythms | 2,005 | 10.1186/1740-3391-3-8 | oa_comm |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.