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World J Surg OncolWorld Journal of Surgical Oncology1477-7819BioMed Central London 1477-7819-3-61568354410.1186/1477-7819-3-6ResearchResection of small plexiform neurofibromas in neurofibromatosis type 1 children Friedrich Reinhard E [email protected] Rainer [email protected] Melanie [email protected]ünsterer Carsten [email protected] Victor-F [email protected] Department of Maxillofacial Surgery, Universitätskrankenhaus Hamburg-Eppendorf, Martinistr. 52, 20246 Hamburg, Germany2 MRI Institute, Othmarscher Kirchenweg 166, 22763 Hamburg, Germany2005 31 1 2005 3 6 6 14 12 2004 31 1 2005 Copyright © 2005 Friedrich et al; licensee BioMed Central Ltd.2005Friedrich 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
Plexiform neurofibromas (PNF) are benign tumors of the peripheral nerve which mostly develop in patients with neurofibromatosis type 1 (NF1). Surgical interventions are usually not applied to children with small tumors. These are rather restricted to debulking of larger tumors in adults that cause clinical complications or aesthetic disfigurement. In most cases, a total resection of PNF is not possible due to the network-like growth of the tumors.
Patients and methods
Early surgical intervention was carried out for 9 small PNFs in 7 NF1 children. Tumor resection was performed following the graphical delineation of the affected skin and according the MRI findings.
Results
Total resection was achieved for all 9 PNF without causing any neurological or organic deficit. Annual magnetic resonance tomography over a period of four years did not reveal any relapse of the tumors.
Conclusions
Early surgical intervention for small superficial PNFs in NF1 children have various advantages and may especially be considered a strategy to prevent progression.
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Background
Plexiform neurofibromas (PNF) are benign tumors originating from nerve sheath cells, subcutaneous, or visceral peripheral nerves and can involve multiple fascicles [1]. PNF occur almost exclusively in patients with NF1, an autosomal dominant disorder caused by defect of one allele of the tumor suppressor gene, NF1 on 17q [2-5]. At least 30% of NF1 patients suffer from PNF [2,6,7], which are often present at birth and progress during the first years of life. The growth rate and pattern of PNF vary to a large extent and their growth spurts are unpredictable. PNF can arise in various parts of the body, for example as anterior mediastinal masses, sciatic nerve lesions with pelvic extension, or perirectal plexiform and uterine tumors, often leading to severe clinical complications [7]. Especially tumors occurring in the head and neck area often lead to facial disfigurement and functional deficits. Due to large size of the tumors and involvement of multiple fascicles of nerves and tissues, the risk of neurological and functional destruction upon tumor resection is high. Surgical interventions are thus commonly postponed as long as possible. In addition, most surgical interventions are limited to debulking and rests of tumors often re-grow afterwards leading to the requirement of repeated intervention [8-10].
Previously we reported that PNF can be distinguished into three growth categories using magnetic resonance imaging (MRI): superficial, displacing and invasive. Superficial PNF arise from subcutaneous or cutaneous nerves and may remain within the upper layer of the skin – usually not involving major nerves [10]. Subtotal and total resection without functional destruction is often possible for superficial PNF, as demonstrated in our recent study [11]. In contrast, invasive PNF infiltrate multiple tissue planes and are thus much more difficult or impossible to resect. Superficial PNF show progressive growth and it is unknown whether or not a superficial PNF may change to displacing or invasive types. Early resection of small superficial PNF may thus be considered as an advantageous treatment option.
In this study, we present the results of early intervention for 9 PNFs in 7 NF1 children aged 3 to 15 years.
Patients and methods
The 7 children were examined in our NF-Clinic in the Department of Maxillofacial Surgery, University Hospital Eppendorf, Hamburg. Diagnosis of NF1 was based on the NIH criteria [6]. Informed consent was obtained from parents of these children. All patients received dermatological, neurological and ophthalmological examinations as well as an ultrasound of abdominal organs. PNF were diagnosed based on the following indications: subcutaneous location on palpation, associated with thickening of the skin, local hypertrophy, hair excess and hyperpigmentation on inspection, and prepubertal occurrence from the medical report. Magnetic resonance image (MRI) was done for the tumor regions at 1.5 Tesla with T1- and T2- weighted sequences including a short-tau inversion-recovery (STIR) sequence. Ultra rapid half Fourier single-shot turbo spin-echo (HASTE) sequences were used for imaging the trunk. Intravenous contrast medium was given to all patients. Tumor resection was performed following the graphical delineation of the affected skin and according the MRI findings. Tumor resection included the epidermal and subcutaneous layer with safety margins of 1 cm in all directions. Exploration of the underlying muscles was mandatory.
Results
Seven NF1 children, five boys and two girls, aged 3 to 15 years were included in this study. All of them met the NIH diagnostic criteria for NF1 [6]. PNF was initially diagnosed clinically and further ascertained by MRI (Figs. 1, 2, 3, 4, 5, 6, 7). Five tumors were histologically confirmed as PNF (Fig. 8). Other four were reported as diffuse neurofibromas due to lack of nerve fascicle in the examined sections. However, these tumors were parts of PNF. Five PNF in four children exhibited hyperpigmentation while the other two had hair excess in the tumor area. Two children had two and the other five had one PNF each. Size of tumors varied from 2 cm to 8 cm in greatest diameter (table 1). All PNF were superficial based on MRI. The tumor location was variable (table 1). Neither functional deficit nor pain was caused by the tumors at the time of surgery. Neither was there significant aesthetic disfigurement caused by the tumors.
Figure 1 1A: Pre-surgical T2-weighted STIR-sequence, axial section: in right ventral chest wall bright superficial thickening of cutis and subcutis without involvement of muscles. 1B: Pre-surgical T2-weighted STIR-sequence, axial section: very bright, flat superficial cutaneous PNF in proximal part of right upper arm. 1C: Pre-surgical clinical frontal view of both PNF on right upper arm and thorax wall. 1D: Post-surgical T1-weighted sequence, axial section: small defect in cutis and subcutis, no PNF visible anymore. 1E: Post-surgical T2-weighted STIR-sequence, axial section: complete removal of tumor with hypointensive induration. 1F: Post-surgical clinical frontal view of both scars on right upper arm and thorax wall.
Figure 2 2A: Pre-surgical T2-weighted STIR-sequence, axial section: superficial tumor covering the laryngeal prominence. 2B: Pre-surgical clinical frontal view of PNF of ventral neck. 2C: Post-surgical T2-weighted STIR-sequence, axial section: scar tissue praelaryngeal visible. 2D: Post-surgical clinical frontal view of laryngeal scar.
Figure 3 3A: Pre-surgical T2-weighted STIR sequence of left ventral abdominal wall, paraumbilical. Bright plexiform neurofibroma with thickening of cutis without involvement of muscle. 3B: Pre-surgical T2-weighted STIR sequence, axial section of left ventral abdominal wall, costal margin. Small bright plexiform neurofibroma in cutis and subcutis ventral left. 3C: Pre-surgical clinical frontal view of abdomen with both superficial plexiform neurofibromas visible. 3D: Post-surgical MRI control from A. Complete removal of plexiform neurofibroma. 3E: Post-surgical MRI control from B. Complete removal of plexiform neurofibroma. 3F: Post-surgical clinical frontal view of abdomen. Only two visible scars left after surgery.
Figure 4 4A: Pre-surgical T2-weighted STIR-sequence, axial section: discrete signs of flat funicular, cutaneous and subcutaneous PNF near the left iliac crest with involvement of soft tissue, but without visible infiltration of abdominal muscles. 4B: Pre-surgical clinical view of PNF in the left flank. 4C: Post-surgical T2-weighted Haste-sequence: complete resection of tumor, only a smooth fibrous post-surgical induration and small scar can be identified. 4D: Post-surgical clinical view of hypertrophic scar.
Figure 5 5A: Pre-surgical T2-weighted STIR-sequence, axial section; small nodular hyperintensive PNF in the cutis and subcutis on left ventral chest wall. 5B: Pre-surgical clinical view of PNF in left chest wall, parasternal. 5C: Post-surgical T2-weighted Turbo Spin Echo-sequence, axial section: tumor no longer visible, only adipose tissue visible in the subcutis. 5D: Post-surgical clinical view of scar.
Figure 6 6A: Pre-surgical T2-weighted STIR-sequence, transversal section: bright, flat cutaneous and subcutaneous PNF of right back without involvement of abdominal wall and muscles. 6B: Pre-surgical clinical view of PNF on right back with hypertrichosis. 6C: Post-surgical T2-weighted Turbo Spin Echo-sequence, axial section: complete removal of PNF, thin scar, no subcutaneous fatty tissue visible in scan. 6D: Post-surgical clinical view of scar after tumor removal on back.
Figure 7 7A: Pre-surgical T2-weighted STIR-sequence, transversal section: Cutaneous and subcutaneous PNF of forearm, bright signal without involvement of muscles or fascia. 7B: Pre-surigcal clinical view of hyperpigmented PNF of left forearm. 7C: Post-surgical T2-weighted STIR-sequence, axial section: complete removal of tumor. 7D: Post-surgical clinical view of scar on left forearm.
Figure 8 Photomicrograph of PNF. Plexiform neurofibroma WHO grade I invading fascicles of a peripheral nerve. Tumor growth is primarily confined to the endoneurial space; the perineurium (arrow) forms a natural border for the tumor. Note the loose myoxid texture of the tumor tissue
Table 1 Clinical information
Patient number Sex Age at surgery Tumor location Hyper pigmentation hair growth Size (greatest diameter) Histology post-operative MRI Annual MRI follow up
1 f 5 upper arm right no no 4 cm PNF yes yes
5 thorax right yes no 4 cm PNF yes yes
2 m 15 Adams apple no no 5 cm PNF no yes
3 f 14 rib bow left no no 4 cm PNF no yes
14 paraumbilical left no no 3 cm PNF no yes
4 m 3 thigh left yes yes 7 cm PNF no yes
5 m 4 thorax left yes no 2 cm PNF yes yes
6 m 7 back right yes yes 8 cm PNF yes yes
7 m 11 lower arm left yes no 5 cm PNF no only 2003
In 2001, all seven children underwent surgical intervention for their nine PNF. During the mobilization of the underlying skin layers, three patients showed enlarged nerves running from subcutis to superficial muscle layers, which were identified and additionally resected. These enlarged nerves were proven to be PNF in all cases. Primary wound closure was achieved following the mobilization of the marginal skin. Healing followed without complications in all cases. The scars are relatively small and no hypertrophy was observed. The intervention was well tolerated by all children and recovery occurred within a few days.
Postoperative MRI was done for three children. Six children underwent follow-up examinations annually by MRI for three years. One child was only examined in 2003, two years after the operation. MRI revealed successful total resection for all 9 tumors (Figs. 1, 2, 3, 4, 5, 6, 7). So far, no tumor re-growth has been detected in any of the children.
Discussion
In this study we demonstrated that small superficial PNF can be completely resected, leaving scars without hypertrophy. Operation is relatively uncomplicated, allows healing by primary intention, requires only a few days of hospitalization and is thus no burden for even the youngsters. Within the clinical and radiological follow-up period of three years there was no re-growth of the tumors. However, it cannot be excluded that all tumor cells have been resected. Therefore those patients warrant further annual clinical examination.
The scars in some children may seem more obvious and disfiguring after the operation. However, in comparison to the complications the tumors may cause later, they are only of minor concern. Furthermore, these scars may be corrected later surgically.
Without resection, these small PNF are likely to grow continuously to a large or even very large size which often causes aesthetic disfigurement, functional deficits and pain. Resection of large tumors is much more difficult and total resection is usually not possible any more. Currently it is not clarified whether or not growth patterns of PNF might possibly change from superficial to displacing or to invasive types over time. Early surgical intervention of small superficial PNF may thus be considered as a preventive strategy for later disfigurement and functional deficits.
Adequate diagnosis of NF1 and thus small PNF in the pediatric age group is challenging. Children usually do not complain about subtle pain or discomfort in the affected skin region. Even in the presence of some symptoms parents are often not aware of the origin of the tumor. Only small PNF of the face and neck causing disfigurement in children tend to be recognized early. On the other hand, small PNF of the trunk and extremities which present with subtle hyperpigmentation, hair excess and palpable tumor tissue are frequently not noticed by the physicians. These tumors are rarely diagnosed correctly as PNF. In our cohort only one child received the diagnosis of a PNF correctly by the referring family physician. For better management and adequate treatment, efforts should be made to diagnose NF1 and PNF in their early stage.
Conclusions
Early surgical intervention of small superficial PNFs is uncomplicated, without burden for even the youngsters and enables total resection of the tumors. It may be considered as a preventive strategy for later disfigurement and functional deficits.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
REF and RS carried out the surgical intervention for the tumors and post-operational care of the patients.
CF carried out the MRI and was involved in the diagnosis of PNF.
MH and VFM did the diagnosis and were responsible for management and consulting of the patients.
REF and VFM designed the study and prepared the manuscript.
All authors read and approved the final version of the manuscript.
Acknowledgements
We thank Dr. L. Kluwe for helping preparing this manuscript. Written informed consent was obtained from parents of all the patients.
This study was supported by the Deutsche Krebshilfe project number: 70-3072-Ma4.
==== Refs
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| 15683544 | PMC549083 | CC BY | 2021-01-04 16:39:05 | no | World J Surg Oncol. 2005 Jan 31; 3:6 | utf-8 | World J Surg Oncol | 2,005 | 10.1186/1477-7819-3-6 | oa_comm |
==== Front
Mol CancerMolecular Cancer1476-4598BioMed Central London 1476-4598-4-91569138110.1186/1476-4598-4-9ResearchGlobal gene expression in neuroendocrine tumors from patients with the MEN1 syndrome Dilley William G [email protected] Somasundaram [email protected] Sulekha [email protected] J Perren [email protected] Jason M [email protected] Terry C [email protected] Department of Surgery, Washington University School of Medicine, St. Louis, MO, USA2 John Cochran Veterans Administration Medical Center, St. Louis, MO, USA2005 3 2 2005 4 9 9 11 11 2004 3 2 2005 Copyright © 2005 Dilley et al; licensee BioMed Central Ltd.2005Dilley 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
Multiple Endocrine Neoplasia type 1 (MEN1, OMIM 131100) is an autosomal dominant disorder characterized by endocrine tumors of the parathyroids, pancreatic islets and pituitary. The disease is caused by the functional loss of the tumor suppressor protein menin, coded by the MEN1 gene. The protein sequence has no significant homology to known consensus motifs. In vitro studies have shown menin binding to JunD, Pem, Smad3, NF-kappaB, nm23H1, and RPA2 proteins. However, none of these binding studies have led to a convincing theory of how loss-of-menin leads to neoplasia.
Results
Global gene expression studies on eight neuroendocrine tumors from MEN1 patients and 4 normal islet controls was performed utilizing Affymetrix U95Av2 chips. Overall hierarchical clustering placed all tumors in one group separate from the group of normal islets. Within the group of tumors, those of the same type were mostly clustered together. The clustering analysis also revealed 19 apoptosis-related genes that were under-expressed in the group of tumors. There were 193 genes that were increased/decreased by at least 2-fold in the tumors relative to the normal islets and that had a t-test significance value of p < = 0.005. Forty-five of these genes were increased and 148 were decreased in the tumors relative to the controls. One hundred and four of the genes could be classified as being involved in cell growth, cell death, or signal transduction. The results from 11 genes were selected for validation by quantitative RT-PCR. The average correlation coefficient was 0.655 (range 0.235–0.964).
Conclusion
This is the first analysis of global gene expression in MEN1-associated neuroendocrine tumors. Many genes were identified which were differentially expressed in neuroendocrine tumors arising in patients with the MEN1 syndrome, as compared with normal human islet cells. The expression of a group of apoptosis-related genes was significantly suppressed, suggesting that these genes may play crucial roles in tumorigenesis in this syndrome. We identified a number of genes which are attractive candidates for further investigation into the mechanisms by which menin loss causes tumors in pancreatic islets. Of particular interest are: FGF9 which may stimulate the growth of prostate cancer, brain cancer and endometrium; and IER3 (IEX-1), PHLDA2 (TSS3), IAPP (amylin), and SST, all of which may play roles in apoptosis.
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Background
Multiple Endocrine Neoplasia type 1 (MEN1, OMIM 131100) is an autosomal dominant disorder characterized by endocrine tumors of parathyroid, pancreatic islets and pituitary [1]. The prevalence of MEN1 is estimated to be 2–10 per 100,000 [2]. Based on loss of heterozygosity in tumors and Knudson's "two-hit" hypothesis, the MEN1 gene was classified as a tumor suppressor [2,3] and the gene was isolated in 1997 by positional cloning [4]. The MEN1 gene spans 9 kb of the genome, is comprised of 10 exons, and codes for a 610 amino acid protein termed menin [4]. More than 300 independent germline and somatic mutations have been identified [5]. Recently, five new germline mutations which affect splicing of pre-mRNA transcribed from MEN1 gene were identified in our laboratory [6]. The nature of all the disease-inducing mutations points to a loss of function of menin, which is characteristic of a tumor suppressor. Database analysis of menin protein sequence reveals no significant homology to known consensus protein motifs. Menin is widely expressed in both endocrine and non-endocrine tissues [4]. Menin is primarily localized in the nucleus and contains two nuclear localization signal sequences near the carboxyl terminus of the protein [7].
Studies on the function of menin have not yielded a clear picture as to the role of menin as a tumor suppressor; however, the results of these studies suggest some interesting possibilities. Two groups [8,9], based on yeast two-hybrid screening of a human adult brain library, reported that menin interacts with JunD (a member of the AP-1 transcription factor family) and represses JunD mediated transcription. Recently, Agarawal et al[10] reported that when JunD loses its association with menin it becomes a growth promoter rather than a growth suppressor. Other reports suggest some relevance of the menin-JunD interaction. JunD null male mice exhibit impaired spermatogenesis [11]. In postnatal mouse, Men1 was found to be expressed in testis (spermatogonia) at high levels [12]. Lemmens et al [13] by screening a 12.5 dpc mouse embryo library with menin, identified a homeobox-containing mouse protein, Pem. Interestingly, both menin and Pem showed a very similar pattern of expression, especially in testis and Sertoli cells. These findings along with the fact that some MEN1 patients have idiopathic oligospermia and non-motility of spermatozoa [14] suggest that menin-JunD and menin-PEM interactions may play a vital role in spermatogenesis. Kaji et al [15] observed that menin interacts with Smad3 and inactivation of the former blocks transforming growth factor beta (TGF-β) signaling in pituitary tumor derived cell lines. Recently, two more menin interacting proteins, NF-kappa B [16] and a putative tumor metastasis suppressor nm23 [17] have been identified. Interactions among AP-1 family members, Smad proteins and NF-kappa B have been documented [18-21] and such cross talk among signaling pathways is not uncommon.
Despite the above studies, a clear consensus of the molecular mechanisms leading to neoplasia, following the loss of menin, has not emerged. Very little is known about the gene expression changes in human neuroendocrine tumors following the loss of menin. Global gene expression analyses, using cDNA microarrays, have been used to classify other human tumors into clinically distinct categories [22-26]. Wu [27] has discussed the mathematical and statistical considerations for the use of DNA microarrays to identify genes of specific interest, and Harkin [28] has used expression profiling to identify downstream transcriptional targets of the BRCA1 tumor suppressor gene. Our objective was to identify genes that might be directly or indirectly over or under-expressed as a consequence of loss of menin expression.
Results
Patients and Controls
Eight neuroendocrine tumors from six MEN1 patients were included in this study. The patient ages were 19, 22, 42, 51, 57, and 57 years at the time of surgery (Table 1). One was female, and five were male. Two of the patients had clinical and laboratory findings consistent with insulinoma. Three tumors were analyzed from one of these patients. One patient had findings consistent with VIP-oma (vasoactive intestinal polypeptide secreting tumor). Two patients, with no specific symptoms, had non-functioning or pancreatic polypeptide secreting tumors. One patient had symptoms of gastrinoma from a duodenal tumor (not used for this analysis). A pancreatic tumor from this patient, found incidentally, was used in this study. Pathological examination of tumors from the 6 patients resulted in the classification of 3 insulinomas, 3 neuroendocrine tumors, 1 VIP-oma and 1 glucagonoma. The ages of the individuals donating normal pancreatic islets were 42, 52(2), and 56 years. Two were female, and two were male.
Table 1 Characteristics of patients and normal subjects.
Pt.# T # Age Sex Clinical LN Mets T Vol. (ml) Menin Defect [6]
1 1 19 F Insulinoma 0/1 8.28 Large Deletion, exon 1 & 2
2 2 42 M Neuroendocrine Tumor 0/14 18.75 Nonesense Mutation, exon 7
6 6 60 M VIP-oma 1/16 288 8 bp Deletion, exon 5
7 7 51 M Neuroendocrine Tumor 2/30 3.75 2 bp Deletion, exon 2
8 8–10 22 M Insulinoma 2/8 6.9 2 bp Deletion, exon 2
11 11 57 M Gastrinoma 1/1 0.5 4 bp Deletion, exon 3
N1 N1 52 M Normal NA NA NA
N2 N2 56 F Normal NA NA NA
N3 N3 52 F Normal NA NA NA
N4 N4 42 M Normal NA NA NA
Quality of Hybridization
The RNA isolated from 8 tumor specimens (6 patients) and 4 normal islet preparations was of acceptable quality for hybridization, as determined by preliminary small hybridizations on test chips. The dChip computer program returned data concerning the percent of genes judged to be present, and the percent of single and array outlier events (Table 2). The expression data from one normal islet preparation had 5.94% array outliers, which prompted dChip to issue a warning (a warning indicates more than 5% array outliers detected). However, since we had only four normal specimens, we elected to include all four in our analysis. The average level of gene expression was computed for each gene (Figure 1). The average gene expression level for all genes followed an exponentially decreasing pattern; the greatest number of genes had expression values less than 100, and only a few genes had expression levels greater than 4000.
Table 2 Overall statistics on the quality of each the processed GeneChips. One chip was used for each tumor/normal specimen. The "Median Intensity" refers to the overall brightness of the fluorescence of the genes. The "Present Call" refers to whether the gene was "present" or "absent".
Chip Name Median Intensity Present Call (%) Array outlier % Single outlier % Warning
T1 170 49.4 1.12 0.11
T2 107 46.2 1.54 0.15
T6 160 51.4 1.16 0.12
T7 132 47.7 0.50 0.08
T8 158 51.0 0.59 0.10
T9 114 48.9 0.66 0.10
T10 158 50.6 0.42 0.07
T11 121 46.1 3.34 0.30
N1 142 48.4 2.65 0.26
N2 179 49.7 2.72 0.24
N3 75 48.3 3.38 0.31
N4 73 33.2 9.50 0.63 *
Figure 1 Histogram showing the frequency of genes being expressed at levels between 50 and 7875 (arbitrary expression units).
Overall Consistency of Gene Expression
Average expression and standard deviation was computed for each gene in both the group of 4 normal islets, and the group of 8 islet tumors and expressed as the coefficient of variation (CV). Genes with average expression levels less than 50 were excluded from this analysis. Figure 2 shows that the average (11,416 genes and expressed sequences) CV in the group of 8 tumors was 30%. There was a linear regression of CV values as the average minimum expression level of the genes increased. Genes with an average minimum expression level of 7000 or more had an average CV level of 12.7%. The analysis of genes expressed in the normal islets gave similar results. However, when the tumors were combined with the normals, the CV was higher than either group alone. This was caused by the true differences in gene expression levels between the tumors and the normals.
Figure 2 Coefficient of variation (CV) of genes being expressed at levels between 50 and 6000. For each gene expressed at an average level of 50 or above, the CV was computed for the group of 8 tumors, for the group of 4 normals, and for the group of all 12 tumors and normals. As the lower limit of expression was increased, the number of genes represented in the CV decreased: there were 12,000 genes with expression levels of 50 or more, but only a few genes with expression levels of 6,500 or more.
Clustering
The experimental groups were clustered (figure 3) using a hierarchical clustering procedure [29,30]. This cluster was based on the inclusion of all genes which had 33% to 67% of "present" calls made by the GeneChip software. The assignment of tumor type was made on the basis of principal hormone messenger RNA levels that were consistent with the clinical and biochemical findings (Table 3). The principal bifurcation in the clustering occurred between the group that included the normal specimens and the three tumors with a predominance of insulin expression, on one hand, and the other tumor types on the other. The four normal islet preparations clustered together, separate from the tumors. Among the normal islets, the females clustered separately from the males. Among the tumors, all 3 insulinomas clustered together, separate from the VIP-oma, the glucagonoma and the PP-omas (pancreatic polypeptide producing tumors). It is also interesting that all the specimens clustered in a pattern of increasing malignancy going from normal at the bottom of the cluster to most malignant at the top.
Table 3 Gene expression levels of islet hormone mRNAs in tumors and normals. VIP: Vasoactive intestinal polypeptide; PP: Pancreatic polypeptide.
T1 T2 T6 T7 T8 T9 T10 T11 N1 N2 N3 N4
pre-Gastrin 864 530 678 392 600 383 209 395 1036 775 28 1192
Insulin 9990 13 179 401 10195 240 8971 1831 10010 9752 9580 8158
Glucagon 10 6482 2783 1198 10 8370 10 10 9037 8425 9043 7800
VIP 351 278 10243 374 334 276 362 202 806 436 334 389
PP 246 7257 577 5845 70 1805 211 8895 1897 7605 3598 1177
Figure 3 Clustering of tumors and normals according to overall gene expression patterns. The predominant type of hormone expression (Table 3) is noted for each tumor/normal specimen.
The genes were also clustered by the dChip software. A group of apoptosis-related genes was identified whose expression was significantly correlated with the Tumor/Normal assignment of the data. Twenty-four apoptosis-related genes represented by 26 different Affymetrix probes were identified in the overall hierarchical clustering. Nineteen of these genes were more highly expressed in the normal islets than in the islet tumors (Figure 4). Eighteen of the nineteen under expressed genes in the set of tumors had t-test p values (tumor vs. normal) <= 0.037. All five of the apoptosis-related genes, that were more highly expressed in the tumors, had t-test p values >0.05
Figure 4 Clustering of apoptosis-related genes in tumors (T) and normals (N). Pink indicates strong, white indicates moderate, and blue indicates weak expression.
Evaluation of Student's t-test
Since the Student's t-test was designed to compare only one parameter in two populations, the simultaneous measurement of multiple genes might lead to an excessive number of false positives. In order to empirically determine the potential false positive rate, we started with 923 genes which had a p value <=.05 and repeatedly scrambled the individual tests into groups 4 and 8 and then performed new t-tests. The average number of genes having a p value = < .05 in 20 such scrambles was 51 (5.5% of 923 genes). This was only slightly more than the 46 genes expected (0.05 × 923). We therefore concluded that there was little chance of excess false positives in repeatedly using the Student's t-test.
Hormone Expression Profiles
In order to obtain a better picture of the nature of the tumors and normal islets in this study, the expression levels of the principal hormone RNA of pancreatic islets was examined (Table 3). Tumors 1, 8, and 10 had high levels of insulin expression and came from patients with the clinical diagnosis of insulinoma. Tumor 6 had high levels of VIP and came from a patient with the clinical syndrome of VIP-oma. Tumors 2 and 7 had high levels of pancreatic polypeptide, and came from patients with only a diagnosis of neuroendocrine tumor. Tumor 9, which came from a patient with a clinical diagnosis of insulinoma had a high level of glucagon expression; the clinical diagnosis was apparently due to the other tumor (#8) which did have a high level of insulin expression. One other apparent discrepancy between the clinical diagnosis and hormone expression profile occurred with tumor 11, which had high a level of glucagon expression. This patient had an additional duodenal tumor that was responsible for the gastrin secretion and the clinical diagnosis. All the normal islet preparations had high levels of insulin and glucagon expression, as expected.
Comparison of tumor and normal gene expression
The reporting of differentially expressed genes was restricted to those in which the absolute ratio of Tumor to Normal was greater than or equal to 2, and which had a Student's t-test p value of less than or equal to .005. There were 193 genes that met the criteria. Expressed sequences with no known protein product were not included. There were 45 genes that were increased in the tumors relative to the normals, and 148 genes that were decreased. The fold-change in expression values ranged from +179 to -449. Genes were assigned to functional categories based on the Gene Ontology Consortium assignments . There were 16 genes related to cell growth, 13 genes related to signal transduction, and 16 genes related to other functions which were increased in the group of tumors relative to the group of normal islets (Table 4). There were 44 genes related to cell growth, 10 related to cell death, 10 related to embryogenesis, 5 related to nucleic acid binding, 21 related to cell signaling, and 58 related to other functions in the group of genes which were decreased in the islet tumors relative to the controls (Tables 5, 6, 7, 8).
Table 4 Genes significantly increased in tumors.
GeneBank Accession Gene Symbol Normal Mean Tumor Mean Fold Change P value
Cell Growth/Cycle
X16323 hepatocyte growth factor HGF 11 116 10.77 0.003305
AB017642 oxidative-stress responsive 1 OSR1 58 428 7.41 0.000819
AL078641 phorbolin-like protein APOBEC3G 15 92 6.21 0.000158
L17128 gamma-glutamyl carboxylase GGCX 64 346 5.37 0.000018
D21089 xeroderma pigmentosum, complementation group C XPC 292 1278 4.38 0.000284
AL050223 vesicle-associated membrane protein 2 VAMP2 360 1533 4.26 0.002196
D38145 prostaglandin I2 synthase PTGIS 29 121 4.09 0.000448
AF092563 structural maintenance of chromosomes 2-like 1 SMC2L1 58 185 3.21 0.002352
AF006087 actin related protein 2/3 complex, subunit 4 ARPC4 292 865 2.96 0.000565
AC004537 inhibitor of growth family, member 3 ING3 46 114 2.47 0.003976
AF013168 tuberous sclerosis 1 TSC1 35 86 2.45 0.001232
AJ236876 ADP-ribosyltransferase polymerase)-like 2 ADPRTL2 32 76 2.34 0.003874
Cell Death/Apoptosis
D38435 postmeiotic segregation increased 2-like PMS2L1 74 193 2.6 0.002976
M61906 phosphoinositide-3-kinase, regulatory subunit PIK3R1 43 104 2.4 0.004387
Signal Transduction
U26710 Cas-Br-M ectropic retroviral transforming sequence b CBLB 21 177 8.4 0.000082
AB010414 guanine nucleotide binding protein, gamma 7 GNG7 59 334 5.68 0.003835
U59913 mothers against decapentaplegic homolog 5 MADH5 14 73 5.22 0.004731
AB004922 Homo sapiens gene for Smad 3 MADH3 93 443 4.76 0.001024
L11672 zinc finger protein 91 ZNF91 428 2007 4.69 0.000376
D14838 fibroblast growth factor 9 FGF9 27 108 3.97 0.000752
W27899 member RAS oncogene family RAB6B 68 232 3.43 0.00501
U48251 protein kinase C binding protein 1 PRKCBP1 40 127 3.18 0.001999
U90268 cerebral cavernous malformations 1 CCM1 53 151 2.87 0.004392
AL050275 cysteine rich with EGF-like domains CRELD1 195 543 2.79 0.000828
AB014600 SIN3 homolog B, transcriptional regulator SIN3B 177 425 2.39 0.001924
M27691 cAMP responsive element binding protein 1 CREB1 107 229 2.15 0.003559
U85245 phosphatidylinositol-4-phosphate 5-kinase, type II, beta PIP5K2B 244 518 2.12 0.000441
W25793 ring finger protein 3 RNF3 163 326 2 0.004947
Nucleic Acid Binding
D50912 RNA binding motif protein 10 RBM10 96 443 4.6 0.001925
U41315 makorin, ring finger protein, 4 MKRN4 404 808 2 0.000262
Ligand Binding
X67155 kinesin-like 5 KIF23 64 368 5.76 0.001584
AB028985 ATP-binding cassette, sub-family A, member 2 ABC1 65 262 4.04 0.001234
Z48482 matrix metalloproteinase 15 MMP15 139 495 3.56 0.003946
Enzyme
X13794 lactate dehydrogenase B LDHB 396 1606 4.05 0.000845
X15334 creatine kinase, brain CKB 939 2083 2.22 0.002008
X60708 dipeptidylpeptidase IV DPP4 133 291 2.19 0.000697
AC004381 SA homolog SAH 283 599 2.11 0.000168
AF000416 exostoses-like 2 EXTL2 134 271 2.02 0.001314
Embryogenesis
U48437 amyloid beta precursor-like protein 1 APLP1 851 2433 2.86 0.001043
U66406 ephrin-B3 EFNB3 168 438 2.6 0.00309
D50840 UDP-glucose ceramide glucosyltransferase UGCG 85 211 2.5 0.002554
Other/Unknown
L48215 hemoglobin, beta HBB 12 2099 178.78 0.001299
J00153 hemoglobin, alpha 1 HBA1 15 1249 82.25 0.001889
U30521 P311 protein C5orf13 157 453 2.88 0.001431
AB011169 similar to S. cerevisiae SSM4 TEB4 140 300 2.15 0.00154
AL031432 GCIP-interacting protein P29 99 198 2 0.002036
Table 5 Genes significantly decreased in tumors.
GeneBank Accession Gene Description Symbol Normal Mean Tumor Mean Fold Change P value
Cell Growth/Division
D17291 regenerating protein I beta REG1B 6286 13 -499.46 0.000095
X67318 carboxypeptidase A1 CPA1 3928 121 -32.57 0.003205
AI763065 regenerating islet-derived 1 alpha REG1A 5641 334 -16.88 0.000001
D29990 solute carrier family 7, member 2 SLC7A2 2988 445 -6.72 0.002204
AB017430 kinesin-like 4 KIFF22 1223 316 -3.87 0.000177
Z25884 chloride channel 1 CLCN1 2511 655 -3.84 0.00013
X81438 amphiphysin AMPH 2686 752 -3.57 0.000002
L03785 myosin, light polypeptide 5 MYL5 207 59 -3.51 0.000233
W28062 guanine nucleotide-exch. Prot. 2 ARFGEF2 66 19 -3.46 0.003602
X52486 uracil-DNA glycosylase 2 UNG2 2555 756 -3.38 0.000514
M81933 cell division cycle 25A CDC25A 312 96 -3.25 0.000005
M69136 chymase 1 CMA1 360 115 -3.13 0.004413
U90543 butyrophilin BTN2A1 685 226 -3.04 0.000023
X69086 utrophin UTRN 1325 457 -2.90 0.000011
AF039241 histone deacetylase 5 HDAC5 1124 393 -2.86 0.000319
U49392 allograft inflammatory factor 1 AIF1 165 58 -2.82 0.000105
U81992 pleiomorphic adenoma gene-like 1 PLAGL1 330 118 -2.80 0.004717
L26336 heat shock 70kD protein 2 HSPA2 90 32 -2.79 0.000689
F27891 cytochrome c oxidase subunit VIa COX6A2 872 313 -2.79 0.000342
D87673 heat shock transcription factor 4 HSF4 1964 721 -2.73 0.000453
X97795 RAD54-like RAD54L 392 144 -2.72 0.001345
X92689 UDP-N-acetyl-alpha-D-galactosamine GALNT3 80 32 -2.50 0.000243
Y08683 carnitine palmitoyltransferase I CPT1B 1038 420 -2.47 0.000573
U40622 X-ray repair complementing defective repair 4 XRCC4 177 72 -2.45 0.000678
U64315 excision repair, complementation group 4 ERCC4 2122 868 -2.44 0.000045
AB020337 beta 1,3-galactosyltransferase B3GALT5 1489 635 -2.34 0.002613
U40152 origin recognition complex ORC1L 3671 1702 -2.16 0.001425
M10943 metallothionein 1F MT1F 5691 2653 -2.14 0.001707
X79882 major vault protein MVP 758 376 -2.02 0.001719
AF035960 transglutaminase 5 TGM5 3097 1542 -2.01 0.002951
Cell Death/Apoptosis
S81914 immediate early response 3 IER3 2209 480 -4.60 0.000307
D80007 programmed cell death 11 PDCD11 457 129 -3.55 0.002358
AF013956 chromobox homolog 4 CBX4 1599 492 -3.25 0.00034
U33284 protein tyrosine kinase 2 beta PTK2B 693 237 -2.93 0.000763
U90919 likely partner of ARF1 APA1 2687 1021 -2.63 0.000015
X57110 Cas-Br-M retroviral transforming CBL 1889 784 -2.41 0.000033
AL050161 pro-oncosis receptor PORIMIN 1178 497 -2.37 0.00031
U40380 presenilin 1 PSEN1 1301 569 -2.29 0.00012
D83699 harakiri, BCL2 interacting protein HRK 768 338 -2.27 0.001321
U07563 v-abl viral oncogene homolog 1 ABL1 1415 631 -2.24 0.000248
M95712 v-raf oncogene homolog B1 BRAF 338 157 -2.16 0.004207
M16441 lymphotoxin alpha LTA 2106 985 -2.14 0.000239
AF035444 pleckstrin homology-like domain, family A, member 2 PHLDA2 334 166 -2.01 0.001759
Table 6 Genes significantly decreased in tumors (continued).
GeneBank Accession Gene Description Symbol Normal Mean Tumor Mean Fold Change P value
Signal Transduction
J00306 somatostatin SST 7701 284 -27.09 0
AI636761 somatostatin SST 7224 598 -12.09 0.000001
AB011143 GRB2-associated binding protein 2 GAB2 2237 402 -5.57 0.001816
M93056 serine (or cysteine) proteinase inhibitor SERPINB1 505 105 -4.80 0.004637
X68830 islet amyloid polypeptide IAPP 2231 477 -4.68 0.001221
AB029014 RAB6 interacting protein 1 RAB6IP1 824 181 -4.56 0.000155
AI198311 neuropeptide Y NPY 610 154 -3.96 0.004817
M28210 member RAS oncogene family RAB3A 2566 672 -3.82 0.000048
J04040 glucagon GCG 8620 2351 -3.67 0.000396
AF030335 purinergic receptor P2Y P2RY11 2314 680 -3.40 0.000058
M29335 major histocompatibility complex HLA-DOA 906 268 -3.39 0.00159
L38517 Indian hedgehog homolog IHH 3013 897 -3.36 0.000055
U95367 gamma-aminobutyric acid A receptor, pi GABRP 668 202 -3.30 0.000837
W28558 pleiotropic regulator 1 PLRG1 704 216 -3.26 0.000068
L08485 gamma-aminobutyric acid A receptor, alpha 5 GABRA5 342 107 -3.20 0.000336
AF004231 leukocyte immunoglobulin-like receptor LILRB2 93 30 -3.08 0.001105
AF055033 insulin-like growth factor binding protein 5 IGFBP5 126 43 -2.96 0.000257
AJ010119 ribosomal protein S6 kinase RPS6KA4 1532 522 -2.94 0.000201
U46194 Human renal cell carcinoma antigen RAGE 2057 754 -2.73 0.000324
L13858 son of sevenless homolog 2 SOS2 964 354 -2.72 0.000268
Z29572 tumor necrosis factor receptor superfamily TNFRSF17 184 68 -2.69 0.000178
U01134 fms-related tyrosine kinase 1 FLT1 910 379 -2.40 0.003257
D78156 RAS p21 protein activator 2 RASA2 327 144 -2.26 0.002332
U77783 glutamate receptor GRIN2D 518 240 -2.15 0.001379
D49394 5-hydroxytryptamine receptor 3A HTR3A 197 98 -2.02 0.002493
Nucleic Acid Binding
Z30425 nuclear receptor subfamily 1, group I, member 3 NR1I3 1008 356 -2.83 0.000329
U18760 nuclear factor I/X NFIX 5796 2216 -2.62 0.000711
AI223140 purine-rich element binding protein A PURA 1137 506 -2.25 0.002448
AF015950 telomerase reverse transcriptase TERT 561 255 -2.20 0.002839
U40462 zinc finger protein, subfamily 1A, 1 ZNFN1A1 662 308 -2.15 0.001171
Z93930 X-box binding protein 1 XBP1 2223 1061 -2.09 0.000277
AB019410 PET112-like PET112A 1422 707 -2.01 0.001309
Ligand Binding
X00129 retinol binding protein 4, plasma RBP4 1517 68 -22.27 0.004809
AJ223317 sarcosine dehydrogenase SARDH 3844 1069 -3.60 0.000085
AB017494 LCAT-like lysophospholipase LYPLA3 906 326 -2.78 0.001131
U78735 ATP-binding cassette, sub-family A, member 3 ABCA3 1914 706 -2.71 0.000288
AF026488 spectrin, beta, non-erythrocytic 2 SPTBN2 1604 671 -2.39 0.00005
U83659 ATP-binding cassette, sub-family C, member 3 ABCC3 1287 551 -2.34 0.00244
R93527 metallothionein 1H MT1H 5093 2196 -2.32 0.002937
AA586894 S100 calcium binding protein A7 S100A7 507 221 -2.29 0.000537
U91329 kinesin family member 1C KIF1C 2981 1484 -2.01 0.000518
Table 7 Genes significantly decreased in tumors (continued).
GeneChip Accession Gene Description Symbol Normal Mean Tumor Mean Fold Change P value
Enzyme
M81057 carboxypeptidase B1 CPB1 4534 79 -57.09 0.001106
X71345 protease, serine, 4 PRSS3 3859 76 -51.11 0.004102
X01683 serine (or cysteine) proteinase inhibitor, clade A SERPINA1 2550 74 -34.64 0.004833
M24400 chymotrypsinogen B1 CTRB1 5158 207 -24.95 0.001744
M18700 elastase 3A, pancreatic ELA3A 7058 384 -18.37 0.000009
U66061 protease, serine, 1 PRSS1 7291 645 -11.31 0.000047
L22524 matrix metalloproteinase 7 MMP7 595 54 -11.03 0.002591
AI655458 5-oxoprolinase (ATP-hydrolysing) OPLAH 446 99 -4.52 0.004072
H94881 FXYD domain-containing ion transport regulator 2 FXYD2 3116 708 -4.40 0.000539
AL021026 flavin containing monooxygenase 2 FMO2 905 215 -4.21 0.000804
AC005525 plasminogen activator, urokinase receptor PLAUR 1779 566 -3.14 0.000031
U40370 phosphodiesterase 1A, calmodulin-dependent PDE1A 268 89 -3.03 0.004023
R90942 sialyltransferase 7D SIAT7D 3148 1052 -2.99 0.002319
M84472 hydroxysteroid (17-beta) dehydrogenase 1 HSD17B1 1196 440 -2.72 0.000991
X55988 ribonuclease, RNase A family, 2 RNASE2 480 203 -2.36 0.001314
AB003151 carbonyl reductase 1 CBR1 4538 1945 -2.33 0.000511
X08020 glutathione S-transferase M1 GSTM1 2766 1376 -2.01 0.000519
Embryogenesis
U15979 delta-like homolog SIGLEC5 3384 402 -8.41 0.002927
M60094 H1 histone family, member T HIST1H1T 976 230 -4.23 0.001639
U50330 bone morphogenetic protein 1 BMP1 3298 973 -3.39 0.001637
M74297 homeo box A4 HOXA4 501 176 -2.85 0.000477
AJ011785 sine oculis homeobox homolog 6 SIX6 530 190 -2.79 0.000286
U66198 fibroblast growth factor 13 FGF13 191 73 -2.61 0.001068
D31897 double C2-like domains, alpha DOC2A 1151 451 -2.55 0.000068
U12472 glutathione S-transferase pi GSTP1 3122 1524 -2.05 0.000237
Transcription
AL049228 pleckstrin homology domain interacting protein PHIP 257 33 -7.69 0.000782
M27878 zinc finger protein 84 ZNF84 54 15 -3.64 0.001108
U77629 achaete-scute complex-like 2 ASCL2 438 184 -2.38 0.000058
D50495 transcription elongation factor A, 2 TCEA2 1330 595 -2.23 0.000019
U49857 transcriptional activator of the c-fos promoter CROC4 542 259 -2.09 0.003894
Table 8 Genes significantly decreased in tumors (continued).
GeneBank Accession Gene Description Symbol Normal Mean Tumor Mean Fold Change P value
Other/Undefined
X72475 immunoglobulin kappa constant IGKC 1409 276 -5.11 0.000111
D17570 zona pellucida binding protein ZPBP 355 71 -5.02 0.001107
M90657 transmembrane 4 superfamily member 1 TM4SF1 592 141 -4.20 0.004537
AF063308 mitotic spindle coiled-coil related protein SPAG5 2015 502 -4.01 0.000588
U66059 T cell receptor beta locus TRB@ 3022 779 -3.88 0.000266
AL022165 carbohydrate sulfotransferase 7 CHST7 359 94 -3.82 0.001738
U10694 melanoma antigen, family A, 9 MAGEA9 1039 272 -3.82 0.000067
M73255 vascular cell adhesion molecule 1 VCAM1 80 22 -3.66 0.004179
U47926 leprecan-like 2 protein LEPREL2 1003 319 -3.15 0.00013
L05424 CD44 antigen CD44 1439 471 -3.05 0.001361
AI445461 transmembrane 4 superfamily member 1 TM4SF1 463 161 -2.88 0.002911
AF010310 proline oxidase homolog PRODH 1194 421 -2.84 0.000005
AF000991 testis-specific transcript, Y-linked 2 TTTY2 700 254 -2.76 0.000542
X57522 transporter 1, ATP-binding cassette, sub-family B TAP1 781 287 -2.72 0.000971
AA314825 trefoil factor 1 TFF1 1657 616 -2.69 0.000011
AB020880 squamous cell carcinoma antigen SART3 3228 1224 -2.64 0.000135
AF040707 homologous to yeast nitrogen permease NPR2L 1131 437 -2.59 0.001537
U47292 trefoil factor 2 TFF2 359 141 -2.54 0.000684
X69398 CD47 antigen CD47 350 144 -2.42 0.000853
U27331 fucosyltransferase 6 FUT6 1105 473 -2.34 0.000872
AI827730 cyclin M2 CNNM2 5863 2535 -2.31 0.000484
U05255 glycophorin B GYPB 1606 717 -2.24 0.00013
M34428 pvt-1 oncogene homolog, MYC activator PVT1 1231 550 -2.24 0.004423
U86759 netrin 2-like NTN2L 2039 937 -2.18 0.000204
D90278 CEA-related cell adhesion molecule 3 CEACAM3 4388 2024 -2.17 0.000902
L40400 ZAP3 protein ZAP3 1549 719 -2.15 0.000776
U48224 beaded filament structural protein 2, phakinin BFSP2 568 271 -2.10 0.000166
AI138834 deltex homolog 2 DTX2 311 148 -2.10 0.000687
M13755 interferon-stimulated protein, 15 kDa G1P2 1507 741 -2.03 0.001157
X52228 mucin 1, transmembrane MUC1 1523 756 -2.02 0.001707
Validation of GeneChip Data with Quantitative RT-PCR
In order to evaluate how accurately the GeneChip data was representing actual gene expression levels, eleven genes were tested with quantitative RT-PCR (Q-PCR). The results are shown in Table 9. The correlation coefficients ranged from 0.964 to 0.235 with an average of 0.655. The lower correlation coefficients were associated with genes with larger numbers of exons. There was some association of low correlation with low average numerical expression values. The lowest correlations were associated with very faint image intensity of the involved genes in the dChip visual representation. The correlation coefficients of 4 genes, identified as apoptosis-related, was examined in detail (Figure 5). IER3, IAPP, SST, and PHLDA2 all had good correlation between GeneChip and Q-PCR results. FGF9, a potential growth stimulating gene was also examined (Figure 6). Again, there was overall good correlation between the individual GeneChip and Q-PCR results.
Table 9 Correlation of GeneChip expression with quantitative RT-PCR.
Gene Symbol Correlation Probe Set Exons Gene Size (bp) Fold Change (T/N) P value GeneChip T vs. N
IER3 0.964 1237_at 1 1236 -4.6 0.0000
SST 0.925 37782_at 2 351 -12 0.0000
PHLDA2 0.909 40237_at 2 913 -2.01 0.0003
REG1B 0.875 35981_at 6 773 -499 0.0000
IAPP 0.823 37871_at 3 1462 -4.68 0.0033
REG1A 0.814 38646_s_at 6 808 -16.9 0.0000
FGF9 0.74 1616_at 3 1420 3.97 0.0031
CBLB 0.327 514_at 21 3923 3.01 0.0009
XPC 0.318 1873_at 16 3658 4.38 0.0018
HRK 0.273 34011_at 2 716 -2.27 0.0011
PTK2B 0.235 2009_at 38 4715 -2.94 0.0019
Average 0.655
Figure 5 The expression levels of 4 apoptosis-related genes are shown by GeneChip and quantitative RT-PCR: a) IER3; b) IAPP; c) SST; d) PHLDA2. Normals (N) and tumors (T) are shown. Solid bars represent GeneChip and open bars represent Q-PCR results.
Figure 6 FGF9 expression levels in tumors (T) and normals (N) by GeneChip and quantitative RT-PCR. Solid bars represent GeneChip and open bars represent Q-PCR results.
Discussion
Whether there were degradative processes acting on the tissues prior to or during or after the extraction of the RNA can be guessed by the quality of the RNA. Each RNA specimen in this study was tested on an Affymetrix test chip, and each was found to be acceptable. Additional quality assessment was made by the dChip software. Only one specimen, a normal control, had Array Outliers greater than 5%, suggesting that it was subnormal (Table 2). However, since the percent outliers was only 5.94, the chip was included in the analysis.
Although, only solid tumor was utilized, there were undoubtedly a small percentage of blood, blood vessel, and connective tissue elements intermixed with the tumor tissue. Rarely, there might be a small amount of exocrine tissue. In the case of the normal islets used as controls, microscopic examination showed that greater than 90% of the tissue was islet. Any contaminants would probably have the effect of reducing the discriminant power to differentiate tumor from normal. Thus, t-test p values and fold changes would tend to under-represented and some, otherwise significant, genes might be missed. The actual data, represented by the hierarchical specimen clustering (Figure 3), showed strong differential gene expression relating to group identity as would be expected if the overall gene expression levels were accurate. All the normals clustered together, separate from all the tumors. Within the normals, the two male specimens clustered in one group, and the two female in another. All the normal islet preparations, which are composed predominantly of beta cells, clustered closer to the insulinoma tumors than to the other neuroendocrine tumor types. The gene clustering results revealed 19 apoptosis-related genes whose expression was suppressed in the islet tumors relative to the normals. This suggests that apoptosis may play a significant role in the development of these tumors.
One might have expected more variation in the gene expression levels in the tumors than in the normal islets, since tumors are often heterogonous. However the data on the average CV of the genes in the normal and tumor groups suggested that there was no more variation in the tumors (average CV of 30%) than in the normals (average CV of 31%). The low CV in the tumors may relate to the single mode of tumor formation (induction by the loss of the menin tumor suppressor). However, there was increased variation noted when the tumors and normals were combined (Figure 2). This was probably the result of the differences in expression between the tumors and the normals.
Of particular interest was the high proportion (3/8) of tumors expressing principally PP hormonal RNA. This was entirely consistent with pathological studies showing the preponderance of PP containing tumors in the pancreas of MEN1 patients [31]. The fact that the clinical classification of two patients (9 and 11) was different than indicated by the hormone expression profile of the tumor analyzed was a consequence of the facts that those patients had multiple tumors secreting multiple hormones but only insulin and gastrin and sometime PP over secretion are likely to result in a clinical diagnosis.
The use of the Students t-test for comparison of multiple genes might be questioned because the test was designed for comparison of only two groups. In this study, we confirmed that comparison of 923 genes would not generate an excess number of false positive results. Nevertheless, in the group of 193 genes finally selected at a p < = .005, we can expect that 1 of those genes is a false positive.
This study suggests that the overall effect of loss of function of menin is the suppression of gene expression. Nevertheless, there were 86 genes that were over-expressed in the tumors relative to the normals. Although we associate tumorigenesis with increased rates of growth, only two of eleven Cell Cycle and Cell Proliferation genes were increased in the tumors. Since tumor growth may also be significantly affected by rates of cell death, it is perhaps significant that there were no Cell Death genes significantly increased in the tumors relative to the controls.
The correlation of GeneChip results with quantitative real-time PCR (Q-PCR, Table 9) was relatively good. However, there were some genes that correlated poorly (correlation coefficient less than 0.6). Interestingly, most of the genes with poor correlation coefficients had a large number of exons, whereas those with high correlation coefficients had a low number of exons. Since exhaustive testing of alternative primer pairs for Q-PCR was not made, it is possible that correlation coefficients of some genes could be improved by the use of other primers.
Four studies of global gene expression in pancreatic islets have been published recently [32-35]. Cardozo et al [32] have used microarrays to look for NF-kB dependent genes in primary cultures of rat pancreatic islets. Shalev et al [33] have measured global gene expression in purified human islets in tissue culture under high and low glucose concentrations. They noted that the TGFβ superfamily member PDF was down regulated 10-fold in the presence of glucose, whereas other TGFβ superfamily members were up regulated. In the current study, none of the TGFβ superfamily members were significantly different between tumor and normal. Scearce et al [34] have used a pancreas-specific micro-chip, the PanChip to analyze gene expression patterns in E14 to adult mice. Only a few specific genes were noted in the paper, and none of them had human homologs of significance to the current study. Maitra et al [35] conducted a study which in many ways was similar to the current one. They compared gene expression, using the Affymetrix U133A chip, in a series of sporadic pancreatic endocrine tumors with isolated normal islets. There was no overlap in the genes they identified (having a three-fold or greater difference in expression) with the genes we identified (having a two-fold or greater difference in expression). This is quite surprising, but perhaps suggests that sporadically arising tumors may have a quite different pattern of gene expression than tumors arising as a result of menin loss or dysfunction. Another possible cause of the differences may be the different Affymetrix GeneChips used in the two studies.
The question of which (if any) of the genes delineated in this study are a direct and necessary affect of loss-of-menin tumorigenesis cannot be determined by this study alone. Firstly, the activity of many genes are regulated both by their levels of expression and by post-translation modifications, such as phosphorylation. Secondly, the microchips used in this study represent only about 1/3 of the total number of human genes. Thirdly, it is not certain that the initiating gene changes caused by loss-of-menin are persistent in the tumors that develop. However, there were some genes, which because of their association with growth or apoptosis are of special interest. The general suppression of apoptosis related genes noted in this study (Figure 4) has been highlighted by the recent study of Schnepp et al, [36] who showed a loss of menin suppression of apoptosis in murine embryonic fibroblasts through a caspase-8 mechanism. Specific apoptosis-related genes which were suppressed in the tumors in the current study, and which were confirmed by Q-PCR include IER3, SST, PHLDA2, and IAPP. IER3 (IEX-1) is regulated by several transcription factors and may have positive or negative effects upon cell growth and apoptosis depending upon the cell-specific context [37]. Several studies have shown that it can be a promoter of apoptosis [38-40]. Somatostatin has shown a wide range of growth inhibitory activity in vitro and in vivo [41-57].PHLDA2 (TSSC3) is an imprinted gene homologous to the murineTDAG51 apoptosis-related gene [58], and may be involved in human brain tumors [59]. IAPP (amylin) is a gene which has contrasting activities and has been associated with experimental diabetes in rodents [60]. Amylin deposits were increased in islets of patients with gastrectomy-induced islet atrophy [61]. On the other hand, exposure of rat embryonic islets to amylin results in beta cell proliferation [62]. In contrast, amylin has been shown to induce apoptosis in rat and human insulinoma cells in vitro [63,64]. In contrast to the suppression of apoptosis-related genes, FGF9 (Figure 6), a growth promoting gene, was significantly increased in the neuroendocrine tumors. This protein has been reported to play roles in glial cell growth [65], chondrocyte growth [66], prostate growth [67], endometrial growth [68], and has been suggested to have a role in human oncogenesis [69].
A recent report by Busygina et al [70] suggested that loss of menin can lead to hypermutability in a Drosophila model for MEN1. The spectrum of mutation sensitivity suggested that there was a defect in nucleotide excision repair. Whether the defect was a direct or indirect effect of menin loss was not stated. In the current study, there was a 2.44-fold decrease, in the tumors, in the expression of ERCC4 (Table 5), a gene involved in nucleotide excision repair. In addition, XRCC4, a gene involved in double-strand break repair, was also decreased in the tumors in the current study.
Conclusion
This first study of global gene expression in neuroendocrine tumors arising in the pancreas of patients with the MEN1 syndrome has identified many genes that are differentially expressed, as compared with normal human islet cells. A number of these genes are strongly over/under expressed and are attractive candidates for further investigation into the mechanisms by which menin loss causes tumors in pancreatic islets. Of particular interest was a group of 24 apoptosis-related genes that were significantly differentially expressed (mostly underexpressed) in the group of neuroendocrine tumors. The underexpression of these apoptosis-related genes may be related to neoplastic development or progression in these MEN1-related neuroendocrine tumors.
Methods
Human Tissue Specimens
Tumor specimens were obtained from patients with the MEN1 syndrome who had undergone surgery for islet-cell tumors of the pancreas. The specific germline mutations in the menin tumor suppressor gene were identified and previously reported [6] for each of the patients. Six of the patients had frame-shift mutations and one had a nonsense mutation. Informed consent was obtained in advance, and tumor tissues not needed for pathological analysis were snap frozen in liquid nitrogen, and kept frozen at -70° prior to RNA extraction. Normal pancreatic islets (which were originally intended for human transplatation studies, but were not used) were isolated from brain-dead donors by a collagenase procedure, as previously described [71], and were then frozen until used for extraction of RNA. Human Studies Committee approval from Washington University School of Medicine was obtained for this study.
Isolation of RNA from Tissue Specimens
Approximately 50 mg of tissue was removed from each frozen tumor specimen and homogenized with a mortar and pestle (Qiagen, Qiashredder Kit), and RNA was extracted using the Rneasy Mini Kit (Qiagen, Inc.), and quantified by UV absorbance. RNA was similarly isolated from the normal human islet preparations.
GeneChip Hybridization and Analysis
The RNA was submitted to the GeneChip facility of the Siteman Cancer Center at Washington University School of Medicine. There, biotin labeled cRNA was prepared and hybridized to U95Av2 microarray chips (Affymetrix). The fluorescence of individual spots was then measured and the data returned on compact discs. We analyzed the gene expression data and made comparisons between groups using the dChip computer program [30]. Following normalization (to equalize the overall intensity of each chip), the expression of each gene was determined by statistical modeling procedure in the dChip software. Each gene was represented by an array of 10 perfect match oligonucleotide spots and 10 mismatch oligonucleotide spots on the U95Av2 chip. The dChip program examines all the spots on all the chips involved in the study, and by a statistical procedure determines single and array outliers. These outliers can be considered as "bad" readings, and removed from further consideration.
Quantitative RT-PCR
The same preparations of total RNA that were used to probe the GeneChips were also used to prepare c-DNA for quantitative RT-PCR analysis of gene expression. C-DNA was first prepared using Superscript II reverse transcriptase (Invitrogen, Inc.). Primers for each gene were designed to produce products of 100 to 150 bp that spanned exon boundaries (when possible). The primer pairs are shown in table 10.
Table 10 Gene Forward Primer Reverse Primer
CBLB cacgtctaaatctatagcagccagaac tgcactcccaagcctcttctc
FGF9 cggcaccagaaattcacaca aaattgtctttgtcaactttggcttag
HRK agctggttcccgttttcca cagtcccattctgtgtttctacgat
IAPP ctgctttgtatccatgagggttt gaggtttgctgaaagccacttaa
ER3 ccagcatctcaactccgtctgt caccctaaaggcgacttcaaga
SST cccagactccgtcagtttctg tacttggccagttcctgcttc
PHLDA2 tgcccattgcaaataaatcact ctgcccgcccattcct
PTK2B gtgaggagtgcaagaggcagat gccagattggccagaacct
REG1A cctcaagcacaggattccaga acatgtattttccagctgcctcta
REG1B gggtccctggtctcctacaagt catttcttgaatcctgagcatgaa
XPC gcccgcaagctggacat atcagtcacgggatgggagta
The Sybr Green technique on an Applied Biosystems model GeneAmp 5700 instrument was utilized. Relative quantitation using a standard c-DNA preparation from an in vitro islet tumor cell line was utilized.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
All authors contributed equally to this manuscript.
Acknowledgements
We would like to thank the Alvin J. Siteman Cancer Center at Washington University School of Medicine and Barnes-Jewish Hospital in St. Louis, Missouri, for the use of the Multiplexed Gene Analysis Core, which provided the GeneChip processing service. The Siteman Cancer Center is supported in part by an NCI Cancer Center Support Grant #P30 CA91842.
Portions of this work were supported by grant RPG-99-183-01-CCE (TCL) from the American Cancer Society and a Siteman Cancer Center Research Development Award.
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| 15691381 | PMC549185 | CC BY | 2021-01-04 16:36:36 | no | Mol Cancer. 2005 Feb 3; 4:9 | utf-8 | Mol Cancer | 2,005 | 10.1186/1476-4598-4-9 | oa_comm |
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BMC Public HealthBMC Public Health1471-2458BioMed Central London 1471-2458-5-131569399510.1186/1471-2458-5-13Research ArticleParental educational level and cardiovascular disease risk factors in schoolchildren in large urban areas of Turkey: Directions for public health policy Kocaoglu Bike [email protected] George [email protected] Maria [email protected] Maria [email protected] Yasar [email protected] Haydar [email protected] Osman [email protected] Yannis [email protected] Department of Nutrition & Dietetics, Harokopio University of Athens, 70, E. Venizelou Ave,17671 Kallithea, Athens, Greece2 Department of Tourism Administration, School of Applied Disciplines, Bogazici University, Istanbul, Turkey3 Department of Health Education, University of Marmara School of Health Education, Kartal Devlet Hastanesi Yani, Cevizli, Kartal, Istanbul, Turkey2005 4 2 2005 5 13 13 10 6 2004 4 2 2005 Copyright © 2005 Kocaoglu et al; licensee BioMed Central Ltd.2005Kocaoglu 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
It is widely accepted that the development of atherosclerosis starts at an early age. However, there are very few studies evaluating the prevalence of the common clinical and behavioral cardiovascular disease (CVD) risk factors among children, especially in developing countries. The aim of the present cross-sectional survey was to evaluate the distribution of blood lipid profile and various behavioral (i.e. dietary habits, physical activity status) factors related to CVD risk and its relationships to paternal (PEL) and maternal educational level (MEL) among primary schoolchildren in Turkey.
Methods
In three major metropolises in Turkey (Istanbul, Ankara and Izmir), a random sample of 1044 children aged 12 and 13 years old was examined. ANOVA was applied to evaluate the tested hypothesis, after correcting for multiple comparisons (Tukey correction).
Results
After controlling for energy and fat intake, physical activity status and Body Mass Index (BMI), it was found that mostly PEL had a significant positive effect for most of the subgroups examined (Lower vs. Higher and Medium vs. Higher) on TC and HDL-cholesterol and a negative effect on TC/HDL ratio for both genders. Furthermore, both boys and girls with higher PEL and MEL were found to have higher energy intake derived from fat and protein than their counterparts with Medium and Lower PEL and MEL, while the opposite was observed for the percentage of energy derived from carbohydrates.
Conclusions
Our study provides indications for a possible association between an adverse lipid profile, certain dietary patterns and Higher PEL and MEL among schoolchildren in Turkey. These findings underline the possible role of social status, indicated by the degree of education of both parents, in developing certain health behaviors and health indices among Turkish children and provide some guidance for Public Health Policy.
Educational levelparentsadolescentscholesteroldeveloping countrydietphysical activity
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Background
Cardiovascular disease (CVD) is the primary cause of mortality in developed countries and generates a major burden of morbidity throughout life [1,2]. Additionally, CVD emergencies have become the leading cause of death in developing countries as well [3,4]. Prospective and retrospective studies have shown that CVD risk factors, namely obesity, the lipid profile, unhealthy diets and sedentary lifestyle, have their roots in childhood and tend to track into adulthood [5-8]. Therefore, early identification and understanding of behavioral and physiological variables related to CVD are essential, so that appropriate interventions can be targeted to children, minimizing the risk of developing the disease later in life.
The continuing modernization and technological advancement of the developing world has brought about rapid lifestyle changes (e.g. fast-food culture, caloric dense diets, sedentary lifestyle), which are known to have a major impact on the development of CVD and other chronic diseases [8,9]. Many investigators have pointed out social and economic status differences, indicated either by the type of school attended (i.e. public vs. private), by the region of residence (i.e. rural vs. urban), or by the level of parental education (primary school vs. University) as important determinants that appear to influence the prevalence of CVD risk factors in both developed and developing world [10-12]. Currently conducted cross-sectional studies have indicated that various socioeconomic factors are inversely associated with CVD morbidity and mortality in developed countries [11,13], while in developing countries, existing data on socioeconomic conditions and the prevalence of CVD are inconsistent [14-16]. The way in which parental educational level seems to exert its effect on health indices and health behaviors differentiates and therefore, should not be considered constant over time and geographic regions [17]. Together health behaviors with social and economic status indices are the outcome of a dynamic and interactive process among several parameters such as education, income, wealth, local culture, beliefs and practices and since none of those parameters stay constant over time and region so do these indices and the way they influence health [18,19]. This observation indicates the need for periodic assessment of these conditions in each population in order to have a clear picture of the social and economic variables and their effects over the populations' health which could effectively guide Public Health Policy in achieving "health for all" and social justice [18].
As far as Turkey is concerned, the available data on the possible effect of parental educational level on the clustering of CVD risk factors among children are limited. Turkey, which has experienced rapid urbanization and industrialization in the past few decades, is a middle-income country, located between Europe and Asia and bordering the Mediterranean, Aegean and Black Seas. The purpose of the present study was to examine the influence of PEL and MEL on CVD risk factors, namely the lipid profile and behavioral indices, among children of Turkey. Expanding our knowledge and understanding on the interrelationship of all these parameters could effectively guide Public Health Policy in early prevention of CVD risk factors in childhood.
Methods
Sampling
The first phase of this cross-sectional study took place during March-May 2001 and the second phase during January-May 2002. The study population consisted of primary schoolchildren aged 12 and 13 years old, living in three urban areas of Turkey, namely Istanbul, Ankara and Izmir. Out of totally 1320 6th grade primary school children registered in the selected schools, 1044 pupils (510 from Istanbul, 289 from Ankara, 245 from Izmir, 49.2% males, 50.8% females) were finally examined. Inclusion of subjects was on a voluntary basis; prior to acceptance, children's parents or guardians were fully informed about the objectives and methods of the study and were asked to sign a consent form.
The study population was selected from nine primary schools (three from each city) using the multi-stage sampling method. Schools were selected taking into consideration the available records of the Ministry of National Education and the National Statistical Center of Turkey, in an attempt to obtain a representative sample from the overall population. In the case of Ankara and Izmir data were collected from three public schools respectively, while in the case of Istanbul sample came from one private and two public schools. All children in the same class were invited to participate in the study to avoid ethical problems.
Approval to conduct this survey was granted by the Ethical Committee of Marmara University and the Turkish Ministry of Education.
Data collection
Baseline data was collected during face-to-face interviews with children by a team of trained personnel. The data collected from the children consisted of physiological indices, namely biochemical and behavioral indices, such as dietary habits, estimation of energy and nutrient intake and physical activity assessment. These data are presented in more detail below.
Demographic characteristics
A coded questionnaire was developed and administered to the study participants, in order to obtain information on socioeconomic conditions and their personal characteristics, such as family size, parental academic qualifications, occupation and car ownership. Both Paternal (PEL) and Maternal Educational Level (MEL) were classified into three categories. "Lower" PEL and MEL corresponded to illiterate, literate with no formal education and to primary school graduates. "Medium" PEL and MEL was attributed to those parents, who had completed junior high school or high school, whereas the category of "Higher" PEL and MEL included parents who possessed a college or a university diploma.
Biochemical indices
Early morning venous blood samples were obtained from each child for biochemical screening tests, following a 12-h overnight fast. Professional staff performed venipuncture, using vacutainers to obtain 10 ml of whole blood. Blood was centrifuged for plasma separation at the local University Hospital and 1.5 ml aliquots were pipetted into plastic Eppendorf tubes and stored at -80°C. When blood collection from each city was completed, all samples were sent to Marmara University, Faculty of Health Education, where the actual biochemical analysis took place.
Total cholesterol (TC) was determined using Allain's method [20], while Fossati's method was used for triglycerides (TG) determination [21]. High Density Lipoprotein-cholesterol (HDL-C) was measured by the heparin-manganese precipitation method. Low Density Lipoprotein-cholesterol (LDL-C) was calculated as follows:
LDL-C = TC - (HDL-C + TG/5) [22].
Anthropometrical measurements
Body weight was measured using a digital scale (Seca) with an accuracy of ± 100 g. Subjects were weighed without shoes, in the minimum clothing possible, i.e. underwear. Standing height was measured without shoes to the nearest 0.5 cm with the use of a commercial stadiometer, with the shoulders in relaxed position and arms hanging freely [23]. Body Mass Index (BMI) was calculated by dividing weight (kg) by height squared (m2).
Dietary assessment
Food consumption of children was assessed by the 24-hour recall technique on three consecutive days. Dietary data was collected from children during a face-to-face interview with a trained dietician. Dieticians were trained as a group to minimize inter-observer variation. During the interview, food models and photos of common Turkish dishes of various portions, as well as household cups and measures were used to define amounts, in order to obtain as accurate information as possible, regarding the type and amount of food and beverages consumed during the previous day. Macronutrient and micronutrient intake were calculated using the food database available in Marmara University, Faculty of Health Education. This database contains Turkish food composition tables for all food, including cooked Turkish dishes. Information on processed foods was obtained from food companies and national as well as international fast food chains.
Physical activity assessment
Physical activity during school hours and leisure time was assessed using a standardized physical activity diary completed by the children for two consecutive weekdays and one weekend day. A member of the research team crosschecked diary information during daily interviews. The diary was constructed for searching various physical activities ranging from mild to vigorous [24], while the time spent for each type of activity was recorded in hours.
Activities were classified into two groups, namely Sedentary and Light Activities (< 4 METs) and Moderate to Vigorous Physical Activities (MVPA) (> 4 METs). Typical activities in the Sedentary and Light category were watching TV, board and computer games, studying and extra curricular classes (e.g. music, language), etc. The MVPA category included activities such as walking, bicycling, rhythmic-gymnastics, dancing, basketball, soccer, athletics, tennis, swimming, running up and down, jumping rope and general participation in active outdoors games. Given the age group, MVPA was defined as continuous vigorous activity causing sweating and heavy breathing for periods longer than 15 minutes, but with occasional breaks in intensity, rather than the strict aerobic definition of 20 continuous minutes appropriate for adults.
Statistical analysis
Descriptive statistics of continuous variables were expressed as the Mean ± standard deviation (s.d.), as well as median and 25th and 75th percentile for not normally distributed variables. The 2- sample Z test was used to compare proportions regarding values above normal range among the different categories of parental education for both genders. One- way analysis of variance (ANOVA) with a Tukey post- hoc analysis and multivariate analysis of variance (MANOVA) controlling for certain confounding factors, was conducted to determine whether differences derived from the comparison of continuous variables among the educational categories were statistically significant. For not normally distributed variables the non- parametric univariate Mann-Whitney test was used to verify the statistical significance of the existing differences among the three educational categories. All analyses were conducted using the SPSS 10.0 statistical software package for Windows. In all analyses a 5% significance level was used.
Results
Table 1 summarizes the mean serum lipid values determined for the study participants by gender and parental educational level, as well as the significant differences observed among the three educational level categories. According to these findings Higher PEL and MEL boys and girls were found to have significantly higher mean levels of TC and HDL-C, but lower mean TC to HDL-C ratio, compared to their Medium and Lower PEL and MEL peers. However, after adjusting for sex, energy intake, fat intake, BMI and MVPA some of the differences presented in Table 1 lost their significance (data not shown). More specifically, when PEL was used as a grouping variable HDL-C remained higher for Higher PEL boys and girls, compared to those of Medium PEL (p = 0.010 for boys and p < 0.001 for girls) as well as for Higher PEL girls compared to those of Lower PEL (p < 0.001). A similar observation applied for TC to HDL-C ratio, which remained lower for Lower PEL boys and girls, compared to Medium (p = 0.021 for boys and girls) and to Lower PEL ones (p = 0.022 for boys and p = 0.005 for girls). When mean serum lipid levels where compared on the basis of MEL categories, most of the differences observed in Table 1 lost their significance, since only HDL-C and LDL-C remained higher for Higher MEL boys, compared to Medium (p = 0.018) and to Lower MEL ones (p = 0.020) respectively.
Table 1 Biochemical indices by gender and parental educational level
Father's educational level (PEL) BOYS
Serum Lipids Lower (n = 174) Medium (n = 264) Higher (n = 95) p-value (ANOVA)
TC (mg/dl) 159.7 ± 30.2 167.6 ± 31.6a 169.3 ± 30.9b 0.007
HDL-C* (mg/dl) 53.8 ± 31.9 54.2 ± 14.7 60.3 ± 15.2b,c <0.001
LDL-C cholesterol (mg/dl) 90.3 ± 27.2 95.6 ± 30.0 96.2 ± 29.7 0.930
Triglycerides* (mg/dl)] 90.6 ± 49.0 85.3 ± 38.0 85.4 ± 43.4 0.568
TC/ HDL-C ratio 3.23 ± 0.85 3.28 ± 0.98 2.96 ± 0.86b,c 0.011
Mother's educational level (MEL)
Serum Lipids Lower (n = 276) Medium (n = 209) Higher (n = 46) p-value (ANOVA)
TC (mg/dl) 162.3 ± 32.1 168.9 ± 29.4a 168.8 ± 34.0 0.036
HDL-C* (mg/dl) 54.0 ± 15.9 53.7 ± 13.5 60.0 ± 18.0b,c 0.033
LDL-C cholesterol (mg/dl) 90.9 ± 28.6 97.2 ± 29.1a 99.6 ± 31.8 0.017
Triglycerides* (mg/dl)] 88.0 ± 45.2 87.2 ± 42.4 85.0 ± 39.1 0.851
TC/ HDL-C ratio 3.16 ± 0.83 3.34 ± 1.01 3.02 ± 0.97 0.023
Father's educational level (PEL) GIRLS
Serum Lipids Lower (n = 164) Medium (n = 281) Higher (n = 66) p-value (ANOVA)
TC (mg/dl) 168.9 ± 29.8 172.0 ± 34.2 175.5 ± 30.5 0.308
HDL-C* (mg/dl) 51.1 ± 11.5 52.9 ± 12.5 61.5 ± 20.0b,c <0.001
LDL-C cholesterol (mg/dl) 103.2 ± 85.4 99.9 ± 32.8 95.5 ± 31.9 0.609
Triglycerides* (mg/dl)] 95.3 ± 42.3 95.5 ± 49.6 98.1 ± 45.9 0.879
TC/ HDL-C ratio 3.44 ± 0.84 3.40 ± 0.92 3.06 ± 0.89b,c 0.008
Mother's educational level (MEL)
Serum Lipids Lower (n = 259) Medium (n = 227) Higher (n = 27) p-value (ANOVA)
TC (mg/dl) 168.4 ± 32.2 174.2 ± 32.7 179.7 ± 28.1b 0.046
HDL-C* (mg/dl) 51.6 ± 13.9 54.9 ± 12.8a 56.2 ± 13.7b 0.002
LDL-C cholesterol (mg/dl) 100.6 ± 72.0 99.8 ± 33.0 107.4 ± 26.3 0.799
Triglycerides* (mg/dl)] 95.2 ± 42.1 97.4 ± 51.9 81.5 ± 35.1 0.194
TC/ HDL-C ratio 3.41 ± 0.85 3.32 ± 0.93 3.38 ± 0.95 0.488
a p < 0.05 Medium SES vs. Low SES
b p < 0.05 High SES vs. Low SES
c p < 0.05 High SES vs. Medium SES
* Parameter was log transformed.
Table 2 presents the proportions of children with serum lipid levels above the cut-off points, proposed by the NCEP [25]. According to these findings the prevalence of children found to be in "borderline or high risk" according to their TC and LDL-C serum levels, was significantly higher in Higher PEL and MEL boys and girls, compared to their Medium and Lower PEL and MEL peers, respectively. Furthermore, the prevalence of children with HDL-C levels below 35 mg/dl was found to be lower in Higher PEL boys, compared to those of Medium and Lower PEL.
Table 2 Percentage of children characterized as "borderline or high risk" by gender and parental educational level.
Father's educational level (PEL) BOYS GIRLS
Borderline or High Risk Lower % (n = 174) Medium % (n = 264) Higher % (n = 95) Lower % (n = 164) Medium % (n = 281) Higher % (n = 66)
TC ≥ 170 32.0 43.6a 49.5b 45.4 50.2 60.6b
LDL-C ≥ 110 21.4 28.0 25.3 33.2 37.7 30.3
HDL-C<35 7.8 5.7 0.0b,c 6.1 4.5 3.0
TC/ HDL-C>4.5 9.7 9.1 5.3 10.7 10.9 9.1
Mother's educational level (MEL)
Borderline or High Risk Lower % (n = 276) Medium % (n = 209) Higher % (n = 46) Lower % (n = 259) Medium % (n = 227) Higher % (n = 27)
TC ≥ 170 36.2 45.7a 50.0 45.1 54.8a 70.4b
LDL-C ≥ 110 21.2 29.8a 32.6 32.5 38.0 40.7
HDL-C<35 5.8 6.5 0.0 6.8 4.9 5.7
TC/HDL-C>4.5 7.4 11.0 8.7 8.5 12.2 14.8
* Lipids cut-off points in mg/ dl (according to NCEP)
a p < 0.05 Medium SES vs. Low SES
b p < 0.05 High SES vs. Low SES
c p < 0.05 High SES vs. Medium SES
Dietary and physical activity characteristics of the under study population are reported in Tables 3 and 4. Both boys and girls with Higher PEL were found to have higher intakes of energy derived from fat and protein than Lower and Medium PEL boys (p = 0.002 and p = 0.021) and girls (p = 0.007 and p = 0.010) respectively. Regarding boys of Higher MEL, they were found to have lower total energy intake (p = 0.005) but higher percentages of energy derived from fat (p = 0.002) and protein (p = 0.001), compared to boys of Lower and Medium MEL. The percentage of energy derived from fat was also found to be higher for Medium and Higher MEL girls, compared to those of Lower MEL (p = 0.001). On the other hand the contribution of carbohydrates to the total daily energy intake was found to be higher for Lower MEL boys (p = 0.025) and girls (p = 0.001), compared to Medium and Higher MEL children. With the exception of MVPA, which was found to be higher only for Medium MEL boys, compared to Lower MEL ones (P < 0.05), no other statistically significant differences were observed.
Table 3 Energy and macronutrient intakes by gender and parental educational level.
Father's educational level (PEL) BOYS
Dietary Indices Lower (n = 171) Medium (n = 266) Higher (n = 99) p-value (ANOVA)
Energy Intake* (Kcal/ day) 2031.4 ± 556.1 2017.7 ± 603.5 1952.3 ± 642.9 0.373
Fat Intake (%) 29.7 ± 7.2 30.2 ± 6.3 32.4 ± 5.5b,c 0.002
Protein Intake (%) 13.3 ± 2.3 13.3 ± 2.6 14.1 ± 2.5b,c 0.021
CHO Intake (%) 40.0 ± 10.9 39.3 ± 10.5 39.9 ± 9.3 0.739
Mother's educational level (MEL)
Dietary Indices Lower (n = 274) Medium (n = 213) Higher (n = 46) p-value (ANOVA)
Energy Intake* (Kcal/ day) 2000.7 ± 546.9 2059.6 ± 650.8 1754.8 ± 557.5b,c 0.005
Fat Intake (%) 29.7 ± 6.6 30.6 ± 6.4 33.2 ± 6.9b,c 0.002
Protein Intake (%) 13.3 ± 2.4 13.4 ± 2.6 14.8 ± 2.8b,c 0.001
CHO Intake (%) 41.1 ± 8.6 40.6 ± 10.7 38.4 ± 10.2b 0.025
Father's educational level (PEL) GIRLS
Dietary Indices Lower (n = 157) Medium (n = 278) Higher (n = 73) p-value (ANOVA)
Energy Intake* (Kcal/ day) 1913.3 ± 562.9 1926.8 ± 585.8 1796,0 ± 413,0 0.414
Fat Intake (%) 30.5 ± 6.7 31.0 ± 6.3 33,2 ± 6,4b,c 0.007
Protein Intake (%) 12.9 ± 2.6 12.9 ± 2.5 13,8 ± 2,2b,c 0.010
CHO Intake (%) 38.4 ± 11.5 36.7 ± 10.4 36,6 ± 7,9 0.189
Mother's educational level (MEL)
Dietary Indices Lower (n = 260) Medium (n = 220) Higher (n = 31) p-value (ANOVA)
Energy Intake* (Kcal/ day) 1889,3 ± 554,7 1915.5 ± 533.4 1780.2 ± 609.5 0.404
Fat Intake (%) 30,2 ± 6,5 31.9 ± 6.5a 33.4 ± 6.5b 0.001
Protein Intake (%) 12,8 ± 2,4 13.0 ± 2.6 13.6 ± 2.3 0.260
CHO Intake (%) 38,8 ± 11,2 35.7 ± 9.6a 35.4 ± 10.0 0.001
a p < 0.05 Medium SES vs. Low SES,
b p < 0.05 High SES vs. Low SES,
c p < 0.05 High SES vs. Medium SES
* Parameter was log transformed
Table 4 Physical activity by gender and parental educational level.
Father's educational level (PEL) BOYS GIRLS
Physical Activity Lower (n = 174) Medium (n = 267) Higher (n = 94) Lower (n = 157) Medium (n = 281) Higher (n = 71)
MVPA (hours/week) Median (25th – 75th percentile) 6.7 (2.3–11.1) 7.0 (3.5–11.6) 7.0 (3.2–11.6) 2.3 (0.0–7.0) 3.5 (0.0–7.0) 1.2 (0.0–7.0)
Mean ± SD 7.3 ± 6.4 7.9 ± 6.1 7.6 ± 6.4 4.1 ± 4.4 4.2 ± 4.5 4.0 ± 5.3
Mother's educational level (MEL)
Physical Activity Lower (n = 273) Medium (n = 214) Higher (n = 45) Lower (n = 260) Medium (n = 222) Higher (n = 30)
MVPA (hours/week) Median (25th – 75th percentile) 5.8 (2.3–10.5) 8.1a (3.5–11.6) 5.8 (2.3–8.1) 2.3 (0.0–7.0) 3.5 (0.0–7.0) 0.6 (0.0–5.2)
Mean ± SD 7.2 ± 6.4 8.2 ± 6.1a 6.7 ± 5.8 3.8 ± 4.3 4.4 ± 4.8 3.5 ± 5.0
a p < 0.05 Medium SES vs. Low SES (Mann Whitney test).
Discussion
Despite the traditional notions of CVD as a Western disease of "affluence", more than three quarters of global CVD mortality now occurs in middle- and lower- income nations (WHO, 2001) [26]. Furthermore, progression of CVD as well as the risk factors and health behaviors leading to this medical condition seem to be related with various social and economic indices for both adults and children [11,27]. However, prevention seems to be the most effective way to treat CVD and since the roots of the disease are located in childhood, early detection and management of the related risk factors should begin at that age [27,28].
According to the findings of the current study there was a higher prevalence of "borderline or high risk", with respect to TC levels, for children with Medium and Higher parental educational level (Table 2). Several other investigators, who have conducted analogous epidemiological surveys in other developing nations, such as in Philippines, Costa Rica and Iran [29-31], have confirmed these alarmingly high prevalence rates among children living under the supervision and care of better educated parents. Furthermore, in contrast with Western populations where TC levels are often inversely associated with income and education [32,33], but in consistency with several other studies conducted in recent years in Turkey the findings of the current one indicated a positive effect of parental education on serum TC levels [34,35]. The same trend applied for HDL-C levels since, in consistency to the findings of Mahley et al. (2001) [34] for upper socioeconomic status prepubescent subjects, the present study showed that children with Medium and Higher PEL and MEL were found to have higher serum levels of this lipoprotein than those with Lower PEL and MEL.
The effect of diet on serum lipids and lipoproteins has been extensively studied in various clinical trials and epidemiological studies, and although dietary content is clearly an important determinant, several environmental and metabolic factors intervene to modulate the dietary effect (36). Previously conducted surveys in urban regions of Turkey have provided strong evidence that children coming from more affluent and/or well-educated families consumed diets higher in animal protein and fat, while the typical diet of less privileged children was rich in carbohydrates, including cereal grains and sugar (37). These findings, regarding the macronutrient content of the consumed diet, are in consistency with the current study, since children from Medium and Higher PEL and MEL were found to consume higher percentage of energy derived from fat and protein, while the opposite was observed for carbohydrate intake (Table 3). Based on the existing literature (38) we could safely speculate that higher intake of fat, especially saturated, and of protein, originating mostly from animal products, could explain the more unfavorable lipidemic profile, with respect to TC and LDL-C serum levels, among children with Higher PEL and MEL. Additionally the lower HDL-C levels and the higher TC to HDL-C ratio reported for children of Lower PEL and MEL could probably be attributed to the higher ratio of carbohydrates constituting their diet. Indeed the percentage of energy derived from carbohydrates has been inversely associated with HDL-C levels according to the results from several other studies [39,34].
Regarding physical activity, it is well established that higher levels of physical activity are associated with higher HDL-C and lower TC to HDL-C ratio values in both children and adolescents [40-42]. However the current study, in agreement to similar findings of Mahley et al (2001) [34], has not revealed any significant differences with respect to MVPA among children of different PEL and MEL. Still, of great interest are the differences observed in physical activity levels between genders. The present study in consistency with many other studies conducted in the developed world [43-45] revealed that boys were found to devote more time on MVPA than girls. This gender differentiation in physical activity levels should not be attributed to physiological differences between the two sexes but to social and cultural beliefs of parents and teachers as to the types of activities appropriate for boys and girls. Family and society have been shown to influence the level and type of physical activity, girls are engaged in and therefore may determine the lifetime habits with respect to habitual physical activity [45].
The findings of the current study are in agreement with previous surveys conducted in Turkey indicating that parental education, either as a single estimate of social status or combined with other social and/or economic indices, is a "reliable index" of socioeconomic status [34,46]. Both indices (PEL and MEL) utilized in the present study provided similar findings regarding the differences on children's serum lipid levels. These could probably be attributed to dietary differences, since no significant differences were reported for physical activity. Furthermore, higher percentage of energy derived from fat and protein recorded for Higher PEL and MEL children, compared to those with Lower PEL and MEL, in conjunction with the opposite finding regarding carbohydrates, is in agreement with previous studies indicating "limited" access to food by children of lower socioeconomic status [46]. These findings may provide some indication that less privileged children are not only under a greater risk of undernourishment but furthermore, by having a higher ratio of TC to HDL-C, that they combine, at the same time, a high prevalence of a health risk index of affluence. However, due to its cross sectional design the present study could not establish causal-effect relationships, but only generate hypothesis about the possible role of parental education on certain CVD risk factors. Another limitation that has to be considered is the fact that the study's focus was on certain biochemical and behavioral indices, since it has not included other important CVD risk factors such as fasting glucose, insulin, blood pressure and smoking habits.
The underlying influence of socio-economic status on health status is far more complex than diet and physical activity alone, since many other factors interact in producing the differences observed for serum lipids or other health indices. Based on the data provided by the current study it could be concluded that the differences regarding the lipidemic profile of children with different parental educational level could possibly be attributed to the differences observed on their dietary and macronutrient intake. Any attempt for the development and implementation of a health and education programme should consider these findings and set priorities accordingly. However further research is needed in order to develop an effective index for assessing socioeconomic level, as well as in better understanding its multidimensional role on public health. All these will help the public health authorities to develop effective strategies, which will efficiently tackle these health issues early in life.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
This study was supported with a research grant from Kellogg Europe and Bogazici University Research Fund.
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| 15693995 | PMC549186 | CC BY | 2021-01-04 16:28:55 | no | BMC Public Health. 2005 Feb 4; 5:13 | utf-8 | BMC Public Health | 2,005 | 10.1186/1471-2458-5-13 | oa_comm |
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BMC Womens HealthBMC Women's Health1472-6874BioMed Central London 1472-6874-5-11569400010.1186/1472-6874-5-1Research ArticleCorrelation of breast cancer risk factors with HER-2/neu protein overexpression according to menopausal and estrogen receptor status Tsakountakis Nikos [email protected] Elias [email protected] Efstathios [email protected] Maria [email protected] Nektaria [email protected] Vasilis [email protected] Dimitris D [email protected] Dept of Family and Social Medicine, Heraklion Medical School, University of Crete, Greece2 Dept of Surgical Oncology, Heraklion Medical School, University of Crete, Greece3 Dept of Pathology, Heraklion Medical School, University of Crete, Greece4 Dept of Biostatistics, Heraklion Medical School, University of Crete, Greece5 Dept of Medical Oncology, Heraklion Medical School, University of ≥Crete, Greece2005 4 2 2005 5 1 1 16 10 2004 4 2 2005 Copyright © 2005 Tsakountakis et al; licensee BioMed Central Ltd.2005Tsakountakis 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
Several researchers have claimed that classification of tumours on the basis of HER-2/neu overexpression or amplification may define a subset of breast cancer in which the net effect of a risk factor could be rather more obvious and its impact on breast cancer development more clear. We decided to investigate, in a group of patients from a geographical area with a low incidence of breast cancer, whether HER-2/neu positive tumours are correlated with established or suspected risk factors for breast cancer and thus to identify distinct subgroups of high risk women.
Methods
This study analysed data from patients who attended the Breast Unit at the University Hospital of Heraklion, Crete, Greece between 1996 and 2002. 384 women with primary invasive breast cancer were compared with 566 screened women who were referred to the Unit and had not developed breast neoplasm by the time the data were analysed. Risk factor data were obtained from each subject by personal interviews using a structured questionnaire. The detection and scoring of the HER-2/neu protein, estrogen and progesterone receptor expression were performed using immunochemistry. Odds ratios and 95% confidence intervals were determined by chi-square test and logistic regression analysis. Case-case odds ratios were calculated in order to measure the risk heterogeneity between HER-2/neu+ and HER-2/neu-tumours. Separate analyses were performed for premenopausal and postmenopausal women and according to estrogen receptor status.
Results
In multivariate analysis without HER-2/neu stratification, an increased breast cancer risk was associated with only four of the factors examined: use of oral contraceptives (OR = 4.40, 95%C.I: 1.46–13.28), use of HRT (OR = 7.34, 95%C.I: 2.03–26.53), an age at first full pregnancy more than 23 years (OR = 1.91, 95%C.I: 1.29–2.83) and body mass index more than 29 kg/m2 (OR = 3.13, 95%C.I: 2.02–4.84). Additionally, a history of abortion or miscarriage (OR = 0.56, 95%C.I: 0.38–0.82) was correlated with a decreased risk of breast cancer. In the case to case comparison only BMI >29 kg/m2 revealed a relative connection that was stronger with positive than with negative HER-2/neu tumours (ratio of OR's = 2.23, 95%C.I: 1.20–4.15, p = 0.011). This may indicate evidence of heterogeneity of a rather significant degree for this factor. In the ER negative group an age at first full pregnancy >23 years and a BMI >29 kg/m2 were associated with an increased risk in both HER-2/neu groups, but the association was significantly stronger for the latter factor in the positive HER-2/neu tumours (ratio of OR's = 2.46, 95%CI: 0.97–6.21).
Conclusions
Our study did not confirm that the established or putative hormonal breast cancer risk factors differ regarding their relations with HER-2/neu+ versus HER-2/neu-breast tumours, with the exception of increased BMI. Further innovative studies with larger sample sizes are needed to examine how the status of these potentially modifiable breast cancer risk factors interacts with biological markers such as HER-2/neu oncoprotein.
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Background
The HER-2/neu oncogene, also known as c-erb-B2, c-neu or ERBB2, is located in chromosome 17q11.2-12, encoding an EGFR-family like glycoprotein [1]. Its amplification, which is strongly correlated with protein overexpression, occurs in about 15–43% of breast tumours [1-10].
The observation that morphologically similar neoplasmatic lesions of the breast can exhibit different biology has necessitated the identification of biological parameters that might improve risk assessment; the evaluation of HER-2/neu expression is a typical example [11]. Indeed, several studies have demonstrated that HER-2/neu amplification represents a prognostic and predictive marker; its expression is associated with early disease recurrence, relative resistance to chemo- and/or hormonotherapy and short survival [2,10]. In addition it has been shown that genetic alterations of the HER-2/neu oncogene represent early events involved in breast carcinogenesis and tumour initiation, while their presence is observed in all stages of malignant development from in situ carcinomas to metastatic lesions [12]. As a result, some researchers have maintained that HER-2/neu amplification and/or protein overexpression may also represent not only an important marker of prognosis but also a key indicator of the aetiological heterogeneity of breast carcinogenesis. [3,7-9].
On the other hand, the contribution of even well established breast cancer risk factors to the aetiology of carcinogenesis in the breast remains obscure, ill-defined and tenuous, mostly because of the existence of different pathways for the initiation and the evolution of a breast tumour [13]. In order to explain this incompatibility, several researchers have claimed that classification of tumours on the basis of HER-2/neu overexpression or amplification may define a subset of breast cancer in which the net effect of a risk factor could be rather more obvious and its impact on breast cancer development more clear [3,7,8].
Thus, a close correlation of a risk factor with HER-2/neu overexpression could indicate either that a HER-2/neu alteration is the way that this risk factor evolves into the carcinogenesis or that there is a parallel interaction between them that leads to breast tumour initiation and development. Since the data in the literature supporting the above hypothesis are few and conflicting, we decided to investigate, in a group of patients from a geographical area with a low incidence of breast cancer, whether HER-2/neu positive tumours are correlated with established or suspected risk factors for breast cancer and thus to identify distinct subgroups of high risk women.
Methods
This study analysed data derived from the database of the Breast Unit of the Department of Surgical Oncology at the University General Hospital of Heraklion on the island of Crete, Greece. The study considered all women who were consecutively diagnosed with primary, invasive breast cancer in our unit from 1996 to 2002. Subjects of other races, ethnicity, with residence outside Crete or diagnosed with DCIS or LCIS were excluded. Finally, 384 women, all originating from the island of Crete, were eligible for analysis.
An age-stratified random sample of 566 women was used as a control group, derived from the Breast Unit's database of screened patients who had not developed breast cancer after a median follow up period of 40 months (range 12–92 months). Personal interviews were conducted with each woman during her first visit (both patients and controls) by a consultant or a senior resident. The interview followed a structured questionnaire, which did not change during the study period. Anthropometric measures were also made during the first visit.
Women were classified as postmenopausal if their menstrual cycles had ended naturally at least 12 months before the interview or from surgery or radiation therapy at any age. Those who reported not having menstrual cycles for the last 10 months were considered as perimenopausal and were combined with premenopausal women for the purpose of our analysis.
The following variables were analysed for all patients and controls: residence (rural/urban), age at interview (≤ 50 and >50 years), age at menarche (≤ 12 and >12 years old), age at first full birth (<23 vs. ≥ 23 years old), parity (nulliparous, 1 or 2, and >3), lactation (yes/no), use of medications to suppress lactation (yes/no), abortions and miscarriages (yes/no), age at menopause for postmenopausal women (≤ 50 and >50 years old), use of HRT for more than 2 months (yes/no), use of oral contraceptives for more than 2 months (yes/no), family history of breast cancer in a first degree relative (yes/no), history of benign breast disease (yes/no), obesity on the day of the interview (BMI ≤ 29 kg/m2 vs. BMI>29 kg/m2, median value for the study population) and radiation history of the chest (yes/no).
Immunohistochemical study
For this study, tumour blocks were successfully retrieved in 378 (98.4%) and in 377 (98.17%) of the 384 interviewed cases for the immunohistochemical detection of HER-2/neu protein and hormone-receptor expression, respectively.
Immunohistochemical detection and scoring of the HER-2/neu protein expression
Immunohistochemistry with the monoclonal antibody CB11 (NCLCB11, Novocastra Laboratories, UK 12 8EW), at a dilution of 1/50 with incubation period of 60 min, was performed using the OPTIMAX automated system with the Super Sensitive Link-Label Detection System RTU Multilink AP/Fast Red, QA200OXE (purchased from Biogenex Laboratories, San Ramon CA 94583 USA), following antigen retrieval by microwave pre-treatment at 500 Watts for 3 × 5 min in citrate buffer (0.01 M, pH 6). Sections from breast cancer of known positivity were used as positive controls. Negative controls were processed by omitting the primary antibody and substituting non-immune serum. Scoring was based on the criteria recommended by DAKO A/S for the HercepTest [14]. Only membrane staining pattern and intensity were scored using the 0–3+ scale: scores of 0–1+ were considered negative, score 2+ was considered weak positive-need for FISH, and score 3+ was considered (strongly) positive.
Immunohistochemical detection and scoring of estrogen and progesterone receptors
Three (3) μm-thick sections taken on negatively-charged (SuperFrostPlus) slides were dewaxed in xylene, and rehydrated through graded alcohols. Following antigen retrieval by microwave pre-treatment at 500 W for 3 × 5 min in citrate buffer (0.01 M, pH 6), estrogen receptor (ERa) and progesterone receptor (PR) expression was detected by immunohistochemistry using the same automated system and detection kit as above, and primary monoclonal antibodies to ERa (DAKO M7047) and PR (Biogenex code # MU 328-UC) at dilutions of 1/50 and 1/20, respectively, with incubation time 60', at room temperature. Positive and negative controls were processed as above. Positive nuclei counting was performed at a final magnification of 400× (Teaching double-headed NICON, ECLIPSE E400 microscope, equipped with CFI 10X/22 oculars). After scanning at a final magnification of 100× for locating the areas with highest density of ER+ or PR+ carcinoma cell nuclei (hot spots), a 40X/¥/0.17 WD 0.65 objective lens was used for cell counting. All carcinoma cells in three hot spots per immunostained slide were evaluated by two pathologists working simultaneously, though independently, and the mean of the two independent counts was considered the final counting value for each field and hot spot. The ratio of the ER+ or PR+ carcinoma cell nuclei was recorded separately for each of the hot spots. The final immunoreactivity index (score) was calculated as the mean percentage of ER+ or PR+ carcinoma cell nuclei in the three hot spots. Specimens were interpreted as positive for ER or PR if at least 10% of the cells demonstrated nuclear staining of any intensity of reactivity, from 1+ to 3+. Staining intensity was graded as negative (0), weak (1+), intermediate (2+) or strong (3+), and reported separately. A mean value of intensity was assigned for specimens in which the staining intensity varied from field to field, and/or from hot spot to hot spot.
Statistical analysis
Odds ratios (OR) and 95% CI (confidence intervals), as approximators of relative risk, were calculated to measure the association of the groups of breast cancer and the risk factors, using the chi-square (χ2) test. A p value <0.05 was defined as significant. The potential association between breast cancers stratified by HER-2/neu status and well known predisposing factors was further investigated by using a stepwise logistic regression analysis (backward LR), testing the independent effect of breast cancer risk factors (independent variables) on breast cancer (dependent variable) for all women and also separately for premenopausal and postmenopausal females. In addition, we undertook further stratification with estrogen receptor status by using the same multivariate logistic regression model. These patient-controls odds ratios helped us to detect the pattern of heterogeneity and to explore plausible aetiological correlations between patient subgroups. Additionally, case-case odds ratios were calculated in order to measure the risk heterogeneity between HER-2/neu+ and HER-2/neu-tumours. It seems that the departure of the OR from unity can reveal the degree of heterogeneity between these subgroups [15].
Results
Risk factor distributions in breast cancer patients and matched controls are presented in table 1. The mean age at interview was 56.30 years. When all patients were compared with matched controls, and after adjustment for confounding factors, an increased breast cancer risk was associated with only four of the factors examined: use of oral contraceptives (OR = 4.40, 95%C.I: 1.46–13.28), use of HRT (OR = 7.34, 95%C.I: 2.03–26.53), an age at first full pregnancy more than 23 years (OR = 1.91, 95%C.I: 1.29–2.83) and body mass index more than 29 kg/m2 (OR = 3.13, 95%C.I: 2.02–4.84). Additionally, a history of abortion or miscarriage (OR = 0.56, 95%C.I: 0.38–0.82) was correlated with a decreased risk of breast cancer. However, the number of oral contraceptive and HRT users was too small for reliable estimates of risk.
Table 1 Characteristics of the participants
Factors Cases N = 384 n(%) Controls N = 566 n(%) OR1 (95% CI) OR2 (95% CI)
Age at interview
≤ 50 years 138(36) 178(31) 1.00
>50 years 246(64) 388(69) 0.82(0.62–1.08) NS
Area of residence
rural 189(49) 292(52) 1.00
urban 195(51) 274(48) 0.91(0.70–1.18) NS
Menopausal status
Pre/perimenopausal 134(35) 170(30) 1.00
Postmenopausal 250(65) 396(70) 0.80(0.60–1.06) NS
Age at menopause3
≤ 50 years 144(59) 252(64) 1.00
>50 years 102(41) 140(36) 1.28(0.92–1.77) NS
Age of menarche
≤ 12 years 155(40) 150(27) 1.86(1.41–2.45)
>12 years 229(60) 412(73) 1.00 NS
Use of oral contraceptives
no 341(89) 548(97) 1.00 1.00
yes 43(11) 18(3) 3.84(2.18–6.77) 4.40(1.46–13.28)
Use of HRT3
no 231(92) 393(99) 1.00 1.00
yes 19(8) 3(1) 10.78(3.15–36.81) 7.34(2.03–26.53)
First degree family history
no 341(89) 522(92) 1.00
yes 43(11) 44(8) 1.5(0.96–2.33) NS
Age at first full pregnancy
<23 years 106(35) 239(50) 1.00 1.00
≥ 23 years 197(65) 242(50) 1.84(1.37–2.47) 1.91(1.29–2.83)
Parity
nulliparous 79(20) 78(14) 1.00
1–2 175(46) 255(45) 0.68(0.47–0.98) NS
3 plus 130(34) 233(41) 0.55(0.38–0.80) NS
Abortion or miscarriage
no 183(57) 247(50) 1.00 1.00
yes 138(43) 248(50) 0.75(0.57–0.99) 0.56(0.38–0.82)
Lactation
no 67(22) 84(17) 1.00
yes 238(78) 404(82) 0.74(0.52–1.06) NS
Medication to suppress lactation
no 273(90) 438(90) 1.00
yes 31(10) 50(10) 0.99(0.62–1.60) NS
Radiation to the chest
no 372(97) 550(97) 1.00
yes 12(3) 16(3) 1.11(0.52–2.37) NS
Body mass index
≤ 29 kg/m2 282(74) 498(88) 1.00 1.00
>29 kg/m2 97(26) 68(12) 2.52(1.79–3.55) 3.13 (2.03–4.84)
Benign breast disease
no 315(82) 472(83) 1.00
yes 69(18) 94(17) 1.10(0.78–1.55) NS
1Adjusted for age. -2Adjusted for age, residence, menopausal status, menopausal age, menarche age, use of OC, use of HRT, first degree family history, age at first full pregnancy, parity, abortion, lactation, medication to suppress lactation, radiation to the chest, body mass index and benign breast disease. -3Postmenopausal women only.
NS: non significant multivariate OR. Bold types: statistically significant values.
Tumour characteristics of breast cancer patients are shown in table 2. Thirty eight percent (145/378) of the tumours showed HER-2/neu protein overexpression. HER-2/neu positive tumours were not related with menopausal state, age at interview, tumour size, grade and stage, nodal and estrogen receptor status, but there was a modest positive association between HER-2/neu and progesterone negative tumours.
Table 2 Characteristics of the tumours of breast cancer patients1.
Tumour characteristics HER-2/neu + n = 145 (%) HER-2/neu- n = 233 (%) p value
Age at interview 0.533
≤ 50 years 55 (40) 81 (60)
>50 years 90 (37) 152 (63)
Staging 0.106
I 30 (45) 36 (55)
II 76 (35) 143 (65)
III 20 (34) 39 (66)
IV 2 (50) 2 (50)
Unknown 17 (57) 13 (43)
Tumour size 0.161
T1 55 (44) 71 (56)
T2 65 (35) 121 (65)
>T3 10 (29) 25 (71)
Unknown 15 (48) 16 (52)
Menopausal status 0.762
Pre/perimenopausal 52 (40) 80 (60)
Postmenopausal 93 (38) 153 (62)
Grading 0.577
I 7 (33) 14 (67)
II 64 (36) 113 (64)
III 60 (43) 80 (57)
Unknown 14 (35) 26 (65)
Node Status 0.119
Negative 55 (33) 112 (67)
Positive 89 (43) 118 (57)
Unknown 1 (25) 3 (75)
Estrogen receptor status 0.108
Er+ 60 (33) 120 (67)
Er - 85 (43) 112 (57)
Unknown 1
Progesterone receptor status 0.038
Pr+ 49 (49) 52 (51)
Pr- 96 (35) 180 (65)
Unknown 1
1Data for HER-2/neu status were missing for 6 of the 384 interviewed cases.
Menopausal status and estrogen receptor stratification
Subgroups of women stratified by menopausal status were further analysed by a multivariate stepwise logistic regression model adjusted for the remaining variables (table 3). In the premenopausal group of women, an increased risk for HER-2/neu-tumours was observed for those women who reported an age at first full pregnancy ≥ 23 years (OR = 3.56, 95%C.I: 1.70–7.46), a BMI>29 kg/m2(OR = 6.89, 95%C.I: 2.23–21.25), first degree family history (OR = 3.30, 95%C.I:1.10–9.96) or use of oral contraceptives (OR = 11.19, 95%C.I 3.70–33.84), while an age at menarche less than 12 years was the only factor which slightly increased the risk in premenopausal HER-2/neu+ patients (OR = 2.09, 95%C.I 0.99–4.42). Abortion played a less protective role (p = 0.068) for HER-2/neu-breast cancer in premenopausal than in postmenopausal women (p = 0.038). However, the intercase comparison in the premenopausal subgroup showed an evidence of heterogeneity only for the HER-2/neu+ women who had ever had an abortion (ratio of the OR's = 3.12, 95%C.I:1.18–8.24), while use of oral contraceptives (OR = 0.16, 95%C.I: 0.04–0.60, p = 0.007) and a positive first degree family history (OR = 0.09, 95%C.I: 0.01–0.85, p = 0.035) showed a stronger association for HER-2/neu negative tumours.
Table 3 Multivariate analysis of risk factors and HER-2/neu overexpression according to menopausal status
Risk Factors HER-2/neu+ Cases/controls OR (95% CI) HER-2/neu-Cases/controls OR (95% CI) Ratio of the OR's Cases+/cases- OR (95% CI)
PREMENOPAUSAL
Age at first full pregnancy(≥ 23 years) NS 3.56(1.70–7.46) NS
Body mass index(>29 kg/m2) NS 6.89(2.23–21.25) NS
Abortion or miscarriage(ever) NS 0.49(0.23–1.05) 3.12 (1.18–8.24)
First degree family history(positive) NS 3.30(1.10–9.96) 0.09 (0.01–0.85)
Use of oral contraceptives (ever) NS 11.19(3.7–33.84) 0.16 (0.04–0.60)
Age of menarche (≤ 12 years) 2.09 (0.99–4.42) NS NS
POSTMENOPAUSAL
Age at first full pregnancy(≥ 23 years) 2.19(1.23–3.91) 1.66(1.03–2.66) NS
Body mass index(>29 kg/m2) 4.83(2.75–8.49) 2.67(1.56–4.55) 2.23 (1.20–4.15)
Abortion or miscarriage(ever) 0.50(0.28–0.88) 0.62(0.39–0.97) NS
First degree family history(positive) NS 2.23(1.08–4.63) NS
Use of estrogens (ever) NS 10.70(2.71–42.31) 0.21 (0.04–1.08)
Use of oral contraceptives (ever) NS 6.47(1.89–22.16) NS
Age of menarche (≤ 12 years) NS 1.72(1.07–2.75) 0.54 (0.28–1.04)
ALL WOMEN
Age at first full pregnancy(≥ 23 years) 2.19(1.23–3.91) 1.66 (1.03–2.66) NS
Body mass index(>29 kg/m2) 4.83(2.75–8.49) 2.67(1.56–4.55) 2.23(1.20–4.15)
Abortion or miscarriage(ever) 0.50(0.28–0.88) 0.62(0.39–0.97) NS
First degree family history(positive) NS 2.23(1.08–4.63) NS
Use of estrogens (ever) NS 10.70(2.71–42.31) 0.21 (0.04–1.08)
Use of oral contraceptives (ever) NS 6.47(1.88–22.16) NS
Age of menarche (≤ 12 years) NS 1.72(1.07–2.75) 0.54 (0.28–1.04)
Adjusted for age, residence, menopausal status, menopausal age, menarche age, use of OC, use of HRT, first degree family history, age at first full pregnancy, parity, abortion, lactation, medication to suppress lactation, radiation to the chest, body mass index and benign breast disease.
NS: non significant.
The results of logistic regression were identical for all women and the postmenopausal groups of patients due to the large sample size. Patients with an age of menarche ≤ 12 years (OR = 1.72, 95%C.I: 1.07–2.75), first degree family history (OR = 2.23, 95%C.I:1.08–4.63), use of HRT (OR = 10.70, 95%C.I: 2.71–42.31) or OC (OR = 6.47, 95%C.I:1.89–22.16) were at increased risk of developing HER-2/neu-breast cancer only, although the significance of the latter two factors was of little value due to the limited sample size. On the other hand, an age at first full pregnancy ≥ 23 years and a BMI greater than 29 kg/m2 increased breast cancer risk independently of HER-2/neu status, while a history of abortion decreased risk in the same way. In the case to case comparison only BMI >29 kg/m2 revealed a relative stronger connection with positive than with negative HER-2/neu tumours (ratio of OR's = 2.23, 95%C.I: 1.20–4.15, p = 0.011) and this may indicate an evidence of heterogeneity of a rather significant degree for this factor. The stronger association between an age at menarche ≤ 12 years, use of HRT and negative as opposed to positive HER-2/neu status did not reach statistical significance (p = 0.067 and p = 0.062, respectively).
A different stratification pattern of our study's population is presented in table 4. This multivariate model, further stratified by estrogen receptor status, confirmed the observed tight connections between HER-2/neu positivity and obesity already shown in the analysis so far. In more detail, although BMI >29 kg/m2 elevated risk for both ER negative and positive tumours independently of HER-2/neu status, the association was significantly stronger for positive HER-2/neu tumours in the ER negative group (ratio of OR's = 2.46, 95%CI: 0.97–6.21). Additionally, in the same group an age at first full pregnancy >23 years revealed an increase of risk in both HER-2/neu groups, while first degree family history (OR = 2.72, 95%C.I: 1.05–7.07, p = 0.040), age at menopause >50 years (OR = 2.05, 95%C.I: 1.10–3.79, p = 0.023) and birth of 1–2 children (OR = 2.38, 95%C.I: 1.21–4.67, p = 0.012) elevated risk for HER-2/neu negative tumours only. In the ER+ group of women the direct comparison between cases revealed no associations with any factor at all, while abortion showed a protective pattern against breast cancer which expressed estrogen receptors independently of HER-2/neu status.
Table 4 Multivariate analysis of risk factors and HER-2/neu overexpression according to ER1 status.
Risk Factors HER-2/neu+ Cases/controls OR2 (95% CI3) HER-2/neu-Cases/controls OR (95% CI) Ratio of the OR's Cases+/cases- OR (95% CI)
ER + cases
Body mass index(>29 kg/m2) 5.59 (2.58–12.13) 2.84 (1.52–5.32) NS
Age at 1st pregnancy (≥ 23 years) 2.09 (0.97–4.53) NS NS
First degree family history (positive) NS 2.18 (0.92–5.14) NS
Abortion or miscarriage (ever) 0.44 (0.20–0.95) 0.56 (0.32–0.99) NS
ER – cases
Body mass index(>29 kg/m2) 5.33 (2.59–10.94) 2.41 (1.15–5.04) 2.46 (0.97–6.21)
Age at 1st pregnancy (≥ 23 years) 2.37 (1.08–5.18) 1.78 (0.93–3.42) NS
First degree family history (positive) NS 2.72 (1.05–7.07) NS
Age of menopause (>50 years) NS 2.05 (1.10–3.79) NS
Parity (1–2 children) NS 2.38 (1.21–4.67) NS
Adjusted for age, residence, menopausal status, menopausal age, menarche age, use of OC, use of HRT, first degree family history, age at first full pregnancy, parity, abortion, lactation, medication to suppress lactation, radiation to the chest, body mass index and benign breast disease.
1ER: estrogen receptor. NS: non significant.
Discussion
This epidemiological study, conducted in a low incidence Mediterranean population, [16] found that obesity was related with postmenopausal breast tumours that overexpress HER-2/neu oncoprotein. In fact, increased BMI elevated risk in both groups, but the comparison between HER-2/neu+ and HER-2/neu- tumours revealed a much stronger association with HER-2/neu+ breast cancers.
Very few studies have examined the possibility whether HER-2/neu status can help discriminate aetiologically distinct subgroups of breast cancer cases, and none of them has identified the effect of increased BMI with HER-2/neu positive tumours [3,5,7-9].
More specifically, in contrast with other investigators who have shown an elevated risk for HER-2/neu+ tumours with an early age at first full pregnancy, we found a strong elevated risk with a late age regardless of HER-2/neu protein expression [3]. Previous findings suggested an inverse relationship between abortion and HER-2/neu+ breast cancers, while we also found this inverse association but independently of HER-2/neu status [7]. Interestingly enough, abortion increased risk for HER-2/neu+ tumours only in the premenopausal group of women. Early contraceptive use has been positively associated with HER-2/neu+ breast cancer in two studies [7,8], but our findings were different, revealing a positive association with HER-2/neu negative tumours. However, because the number of oral contraceptive (and HRT) users in this study was small, this subgroup analysis was hindered by decreased power to detect associations of any magnitude. The slightly protective effect of parity found in the age-adjusted analysis was diminished after logistic regression and did not reveal any association with HER-2/neu status, in contrast with previous findings [7]. Breastfeeding was associated with increased risks for breast cancer in women with HER-2/neu positive tumours in one study while other investigators reported opposite results [3,9]. Although our study population showed a remarkable lactation incidence (almost 80% of the participants) we found no associations at all.
Our findings have similarities and differences with respect to previous reports that examined the associations of breast risk factors with HER-2/neu status. This inconsistency may reflect differences in study design, populations, and laboratory methodology. In this study we used immunochemistry (CB11 monoclonal antibody) to assess the HER-2/neu protein overexpression, which is highly correlated with gene amplification according to previous reports [2,4]. Also, the percentage of women with breast cancer and HER-2/neu protein overexpression found here was within the limits reported elsewhere [3,5-9].
This lack of relationship between HER-2/neu protein overexpression and most of the hormone-related breast cancer risk factors does not completely agree with several hypotheses which have maintained that combined estrogen and HER-2/neu activation is closely involved in the same pathway in breast cancer carcinogenesis [17,18].
The only hormone-related factor that was found to be related with HER-2/neu positive tumours in our study was high body mass index, which is an established risk factor that has an estrogen-mediated oncogenic effect on the mammary gland. More specifically, obesity is associated with higher breast cancer risk among postmenopausal women through greater lifetime exposure to higher levels of estrogens produced in adipose tissue and lower SHBG production [19,20]. Higher levels of circulating estrogens enhance the rate of cell division, and this hormone-induced cellular proliferation can result in somatic mutations and finally lead to a malignant change. These alterations involve many genes, including those concerned with hormone metabolism and transport, DNA repair, as well as tumour suppressor genes and oncogenes such as the HER-2/neu gene [18,21]. According to some investigators, circulating estrogens can stimulate breast cancer cell proliferation, not only through hormone receptors, but also through the HER-2/neu receptor, and so promote carcinogenesis through common means [4,17,18].
Numerous epidemiological and experimental studies have shown the strong relationship between HER-2/neu-positivity and lack of hormone receptor expression in breast tumours [2,10,18,22]. In our study, HER-2/neu positive tumours were weakly related with the absence of estrogen receptors, although this was not statistically significant (see table 2). Because different ER status can result in different correlations between risk factors and HER-2/neu+ breast cancer, it is always important to examine these interactions under ER stratification [8]. Since antiestrogens can lower HER-2/neu levels in ER negative tumours, it is possible that an excess of estrogens can stimulate HER-2/neu in these tumours [8,18]. This mechanism could explain the stronger association between obesity (a situation with an overload of estrogens as mentioned above) and HER-2/neu-positivity among ER negative patients that was found in the present study (see table 5).
The interview was conducted during the subjects' first visit to the unit and before clinical examination or any other intervention took place. This constitutes an advantage, because there was no chance that the subjects (both cases and controls) would be influenced by the diagnosis and might therefore falsely inflate the relative risk. Thus, the likelihood of recall bias is not high, improving the comparability of several covariates in both groups, and the selection bias is lessened since all subjects had taken the same route through the Breast Unit's standard routine procedures.
Since each case group was compared with the same control group, any selection bias would be expected to have a similar effect on the estimates in the tumour subgroups. Thus, it is extremely unlikely that recall bias issues would apply only to those cases in a specific HER-2/neu status subgroup. Some caution regarding our findings is related to the size of the study group. In the analyses stratified by HER-2/neu and menopausal or ER status numbers are quite small and for some risk estimates the confidence intervals are wide and the estimates of risk unstable.
Conclusions
In conclusion, our study did not confirm that the established or putative hormonal breast cancer risk factors differ regarding their relations with HER-2/neu+ versus HER-2/neu-breast tumours, with the exception of increased BMI. Further innovative studies with larger sample sizes are needed to examine how the status of these potentially modifiable breast cancer risk factors interacts with biological markers such as HER-2/neu oncoprotein. Their findings will provide us with greater insight into breast cancer aetiology and will help us identify any association that would help discriminate subgroups of women at higher risk.
Abbreviations
EGFR: epidermal growth factor receptor, HRT: hormone
replacement therapy, BMI: body mass index, SHBG: sex hormone-binding protein, ER: estrogen receptor, PR: progesterone receptor, OC: oral contraceptives.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
NT conceived the study, participated in its design and drafted the manuscript.
ES participated in the design of the study, assisted in writing and reviewed the final article.
EfS and KM scheduled and performed the laboratory analysis.
NA performed the statistical analyses.
VG and DDT participated in the design and coordination of the study and reviewed the final article.
All authors have read, discussed and approved the manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
None.
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Treurniet HF Rookus MA Peterse HL Hart AA van Leeuwen FE Differences in breast cancer risk factors to neu (c-erbB2) protein overexpression of the breast tumor Cancer Res 1992 52 2344 2345 1348449
Isola JL Chu S DeVries K Matsumura K Chew K Ljung BM Waldman FM Genetic Alterations in ERBB2-amplified Breast Carcinomas Clin Cancer Res 1999 5 4140 4145 10632352
Rosen PP Lesser ML Arroyo CD Cranor M Borgen P Norton L Immunohistochemical detection of HER2/neu in patients with auxiliary lymph node negative breast carcinoma Cancer 1995 75 1320 1326 7882282
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Gammon MD Hibshoosh H Terry MB Bose S Schoenberg JB Brinton LA Bernstein JL Thompson WD Oral contraceptive use and other risk factors in relation to HER-2/neu overexpression in breast cancer among young women Cancer Epidemiol Biomarkers Prev 1999 8 413 419 10350436
Huang WY Newman B Millikan RC Conway K Hulka BS Schell MJ Liu ET Risk of breast cancer according to the status of HER-2/neu oncogene amplification Cancer Epidemiol Biomarkers Prev 2000 9 65 71 10667465
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| 15694000 | PMC549187 | CC BY | 2021-01-04 16:30:35 | no | BMC Womens Health. 2005 Feb 4; 5:1 | utf-8 | BMC Womens Health | 2,005 | 10.1186/1472-6874-5-1 | oa_comm |
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BMC Med EducBMC Medical Education1472-6920BioMed Central London 1472-6920-5-51569848010.1186/1472-6920-5-5Research ArticleTeaching appropriate interactions with pharmaceutical company representatives: The impact of an innovative workshop on student attitudes Wofford James L [email protected] Christopher A [email protected] Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA2005 8 2 2005 5 5 5 27 2 2004 8 2 2005 Copyright © 2005 Wofford and Ohl; licensee BioMed Central Ltd.2005Wofford and Ohl; 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
Pharmaceutical company representatives (PCRs) influence the prescribing habits and professional behaviour of physicians. However, the skills for interacting with PCRs are not taught in the traditional medical school curriculum. We examined whether an innovative, mandatory workshop for third year medical students had immediate effects on knowledge and attitudes regarding interactions with PCRs.
Methods
Surveys issued before and after the workshop intervention solicited opinions (five point Likert scales) from third year students (n = 75) about the degree of bias in PCR information, the influence of PCRs on prescribing habits, the acceptability of specific gifts, and the educational value of PCR information for both practicing physicians and students. Two faculty members and one PCR led the workshop, which highlighted typical physician-PCR interactions, the use of samples and gifts, the validity and legal boundaries of PCR information, and associated ethical issues. Role plays with the PCR demonstrated appropriate and inappropriate strategies for interacting with PCRs.
Results
The majority of third year students (56%, 42/75) had experienced more than three personal conversations with a PCR about a drug product since starting medical school. Five percent (4/75) claimed no previous personal experience with PCRs. Most students (57.3%, 43/75) were not aware of available guidelines regarding PCR interactions. Twenty-eight percent of students (21/75) thought that none of the named activities/gifts (lunch access, free stethoscope, textbooks, educational CD-ROMS, sporting events) should be restricted, while 24.0% (8/75) thought that students should be restricted only from sporting events. The perceived educational value of PCR information to both practicing physicians and students increased after the workshop intervention from 17.7% to 43.2% (chi square, p = .0001), and 22.1% to 40.5% (p = .0007), respectively. Student perceptions of the degree of bias of PCR information decreased from 84.1% to 72.9% (p = .065), but the perceived degree of influence on prescribing increased (44.2% to 62.1% (p = .02)).
Conclusions
Students have exposure to PCRs early in their medical training. A single workshop intervention may influence student attitudes toward interactions with PCRs. Students were more likely to acknowledge the educational value of PCR interactions and their impact on prescribing after the workshop intervention.
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Background
Pharmaceutical company representatives (PCRs) influence the prescribing habits and professional behavior of physicians [1]. Despite the availability of guidelines regarding appropriate interactions with PCRs for practicing physicians [2-4], the skills for interacting with PCRs have not been included as part of the traditional medical school curriculum.
Physicians in training may be particularly susceptible to marketing strategies from PCRs. Restricting interactions between physician in training and PCRs is one approach to eliminating adverse effects of contacts with PCRs [5]. However, physicians in training will likely deal with such marketing influences once in practice. The provision of training or guided experiences in dealing with PCRs seems a more reasonable educational strategy for producing a physician who will be aware of the potential conflict of interest from the profit motive inherent in the pharmaceutical and other health related industries. To our knowledge, there is only one published study of an educational intervention targeting third year medical students on the subject of appropriate interactions with PCRs [6]. Furthermore, the best means of developing the skills and attitudes for interacting appropriately with PCRs is not well defined.
We sought to examine whether a single workshop intervention had immediate effects on the attitudes of third year medical students regarding interactions with PCRs. The goal of the workshop was to increase the student's knowledge and awareness of ethical issues surrounding the PCR encounter, and to improve the students' interactions with representatives by fostering discussion on the profit motive in pharmaceutical marketing, PCR marketing techniques, and appropriate interactions with the PCR, issues necessary for critical thinking about the potential conflict of interest. Unique to our intervention was the participation of a PCR who role played a typical PCR encounter and who offered a perspective on marketing from the perspective of industry. Our findings have implications for institutions considering strategies for controlling PCR interactions and for medical educators seeking to develop curricula for marketing in medicine.
Methods
During the ambulatory internal medicine clerkship of the third year medical school curriculum, students were required to attend a ninety minute workshop entitled "Appropriate Encounters with Pharmaceutical Representatives". These workshops took place three times during the calendar year 2001 for three different student groups. To the best of our knowledge, there were no other organized learning experiences in the medical school curriculum about interactions with pharmaceutical representatives, either before or during the study period. We did not seek approval by the institutional review board for ethical research practice at our institution, because at that time the study was conducted, approval of student education projects was considered unnecessary.
Two faculty members interested in the subject (JW, CO), and a regional manager of pharmaceutical representatives from a major pharmaceutical company facilitated the ninety minute workshop. The workshop began by soliciting student opinions regarding the characteristics of typical interactions with PCRs. After a list of characteristics was compiled, each characteristic was discussed in more detail and compared with previous personal experiences with PCRs. Salient points of the subsequent discussion included the usefulness of patient assistance programs, the use of samples and gifts in PCR marketing strategies, the validity and legal boundaries of information provided by the PCR, and the ethical and legal aspects of physician-industry relations. The final segment of the workshop involved two student volunteers who role played a typical PCR encounter in the office. After discussion of the first role play, a second role play between one faculty member (CO) and the PCR demonstrated desirable characteristics of the PCR encounter.
A pre-intervention survey handed out and collected prior to the beginning of the workshop solicited information about the number of previous personal experiences with PCRs, and whether the student was previously aware of guidelines (medical school, federal government, or professional society) for appropriate interactions with PCRs. Using five point Likert scales, the survey solicited student attitudes about the educational value of PCR information for practicing physicians and for medical students, the degree of bias in PCR information, and the degree of influence of PCRs on prescribing habits. One additional question solicited the acceptability to students of specific gifts (lunch access, free stethoscope, textbooks, educational CD-ROMS, sporting events) from PCRs. A post-intervention survey with the same attitude questions was administered and collected as students left the workshop. The available data comes from three groups – the third, or last student group of academic year 2000–1 and the first two student groups of academic year 2001–2.
Students were characterized by gender, age, and number of previous personal contacts with PCRs (None, 1–3, 4–6, >6). For the purposes of understanding the Likert scale responses for student attitudes, we collapsed Likert scores into three categories – scale responses of 1 or 2 to signify disagreement, a scale response of 3 to signify neutral, and a response of 4 or 5 to signify agreement with the attitude question. We compared student attitudes toward the educational value of PCR detailing for medical students with the perceived value for practicing physicians using the Pearson chi square test.
The association between previous personal PCR experience and attitudes about the educational value of PCR detailing was explored using analysis of variance. We also compared attitudes before and after the workshop intervention using the Pearson chi square test and a dichotomous variable a response of 4 or 5 (versus 3 or lower) on the Likert scale.
Results
Student characteristics
A total of 75 students attended one of the three mandatory workshops on "Appropriate Encounters with PCRs". One student did not complete a post-intervention survey. The mean age of students was 26.4 (± 2.4), and males (56.1%, n = 41) outnumbered females. Fifty-six percent of students (42/75) had experienced more than three personal conversations about a pharmaceutical product with a PCR since starting medical school. Five percent (4/75) claimed no previous personal experience with PCRs. There was no association between the number of PCR contacts, and either gender, age or time of the academic year.
Student attitudes toward value of PCR interaction
The pre-intervention survey showed that PCR detailing was of educational value to 22.1% (18/75) of students with no perceived difference in educational value to medical students versus that to practicing physicians (chi square, p = .40). While students agreed that the degree of bias from PCR information was substantial (86.7%, 65/75), only 44.0% (33/75) of students felt that pharmaceutical representatives were influential with regard to physicians' prescribing habits. No relationship between number of previous personal PCR contacts and educational value to medical students was demonstrated (ANOVA p = .08)
Awareness of guidelines and attitudes toward gifts
Forty-three percent (32\75) of students reported awareness of available guidelines regarding PCR interactions. Fifty percent (16/32) of those students reported familiarity with medical school guidelines, 21.8% (7/32) with federal government guidelines, and 40.6% (13/32) with professional society guidelines. When asked which drug company sponsored activities/gifts targeting medical students should be restricted, 28.0% of students (21\75) thought that none of the named activities/gifts (lunch access, free stethoscope, textbooks, educational CD-ROMS, sporting events) should be restricted. Twenty-four percent (8/75) of students thought that only sporting events should be restricted.
Effect of workshop intervention on student attitudes
Figure 1 shows that the perceived educational value to both practicing and student physicians increased after the workshop intervention from 17.7% to 43.2% (chi square, p = .0001), and 22.1% to 40.5% (p = .0007), respectively. Fifty-eight percent of students (43/74) and 37.8% (28/74), respectively, changed their Likert scale response to the questions on educational value by at least one point after the workshop intervention (Table 1). Student perceptions of the degree of bias of PCR information decreased from 84.1% to 72.9% (p = .065), but the perceived degree of influence on prescribing increased (44.2% to 62.1% (p = .02)). The response to the question on the degree of bias in PCR detailing changed by at least one Likert scale point for 17 students (17/74, 23.0%) (Table 1). The response to the question on the influence of PCR detailing on prescribing practices changed by at least one Likert scale point for 34 students (34/75, 46.0%).
Figure 1 Student attitudes toward PCR detailing before and after workshop intervention. Student perception of the educational value of PCR interactions increased after the intervention at the same time that the perception that PCRs influenced prescribing increased. Student perception of the degree of bias decreased slightly after the workshop, but this decrease was not statistically significant.
Table 1 Student attitudes toward PCR detailing before and after workshop intervention
In your opinion, what is the educational value to practicing physicians offered by detailing from pharmaceutical representatives? (1 = No value at all, 5 = Extremely valuable)
Before-Not Valuable (<3) Before-Neutral (3) Before-Valuable (>3)
After-Not valuable (<3) 8 1 0 9
After-Neutral (3) 10 20 3 33
After-Valuable(>3) 2 18 12 32
20 39 15
In your opinion, what is the educational value to medical students offered by detailing from pharmaceutical representatives? (1 = No value at all, 5 = Extremely valuable)
Before-Not Valuable (<3) Before-Neutral (3) Before-Valuable (>3)
After-Not valuable (<3) 13 0 0 13
After-Neutral (3) 8 19 4 31
After-Valuable(>3) 6 10 14 30
27 29 18
What is you perception of the degree of bias in the information provided by pharmaceutical representatives detailing to practicing physicians? (1 = Not at all biased, 5 = Totally biased)
Before-Not Biased (<3) Before-Neutral (3) Before-Biased (>3)
After-Not biased (<3) 0 1 1 2
After-Neutral (3) 0 6 12 18
After-Biased(>3) 0 3 51 54
0 10 64
How influential are pharmaceutical representatives with regard to physicians' prescribing habits? (1 = Not at all influential, 5 = Very influential)
Before-Not Influential (<3) Before-Neutral (3) Before-Influential (>3)
After-Not influential (<3) 2 2 1 5
After-Neutral (3) 7 11 5 23
After- Influential (>3) 2 17 27 36
11 30 33
Discussion
Professional relationships with PCRs begin early in a physician's career. Because physicians typically underestimate the influence of pharmaceutical marketing on prescribing practices, countering this naivete early is warranted. Because students do not yet have prescribing privileges, the effect of PCR detailing on the prescribing decision is less relevant than how PCR contact shapes professional values [1]. Several studies have examined perceptions of the potential influence of PCRs on resident and practicing physicians [7-13]. However, fewer studies have examined the views of medical students [6,14,15].
Our data show that students have early exposure to PCRs, perhaps earlier than previously suspected. Only five percent of third year students at this institution had not yet experienced PCR detailing, and many had experienced greater than six such encounters. Although resident physicians understandably have more PCR contacts, on average at least three PCR encounters per month [11,16], to our knowledge, there are no studies of comparable data for medical students.
In this study few students were aware of existing guidelines for PCR interactions. Furthermore, students perceived information from PCRs to have educational value, and a value equivalent to that for practicing physicians. That students felt no more or less susceptible to marketing influence than practicing physicians is a marked contrast to the opinions of many educators that physicians in training need special protection from marketing influences [1,2,17].
Several interventions have been proposed for educating physicians-in-training about pharmaceutical marketing practices. Shaughnessy et al described a single brief seminar of marketing concepts followed by regular structured evaluation of PCR sales presentations throughout the following year [18]. Despite this well organized effort, meaningful educational outcomes were meager for the twelve residents evaluated. Hopper et al showed that a single elective forty minute lecture/discussion on ethical and marketing issues in pharmaceutical promotion was successful in improving attitudes and knowledge among residents and faculty [19]. They presented six vignettes to illustrate marketing techniques related to gifts, guidelines, and the yield of marketing for pharmaceutical companies. Vinson et al showed that a fifty minute lecture for first and second year medical students could have immediate effects on knowledge as measured by repeat anonymous survey six weeks later [15]. Palmisano et al described a ninety minute lecture and role-play with simulated PCRs to teach analysis of advertising copy and sales techniques, although no data on educational outcomes were offered [20]. Most similar to our intervention was this study by Wilkes and Hoffman who used pharmacists who were trained to portray PCRs during a one hour seminar targeting third year medical students [6]. Designed to promote critical thinking about appropriate physician-PCR interactions, the single workshop was successful in increasing the amount of uncertainty students felt about the accuracy and ethics of standard drug "detailing".
Similar to these interventions, our workshop intervention targeting third year medical students was a one time intervention and brief in duration. Our intervention differed in that the workshop (1) took place during the clinical clerkship year, (2) made use of practicing PCRs and physicians, and (3) encouraged a distanced but amicable relationship with the PCR. In contrast to many educators who oppose PCR contact for trainees, we encouraged respect for the individual PCR and the success of the pharmaceutical company's business model. We were concerned enough about the growing influence of pharmaceutical marketing on trainees to stage this workshop, but we were careful to remember our goals of encouraging critical thinking about the topic rather than simply condemning the PCR contact. As an example, we emphasized the legal limits regarding what the PCR could and could not say to the physician. This may explain, in part, why attitudes toward PCR information improved after the intervention, at the same time that perceived degree of influence on prescribing increased. Teaching students the "rules of the game" in PCR encounters may explain why students thought that PCR information had more educational value after the workshop.
The limitations of this study should be recognized. First, our survey took place at a single academic medical center affiliated with a private hospital. Student attitudes might be different at a state supported institution or at institutions where there are restrictions on the activities of PCRs. Second, students may have answered the post-intervention survey in a socially desirable manner. Respect for the PCR and the business model was presented as a balanced perspective toward marketing in medicine. Third, how immediate changes in student perceptions will ultimately translate into durable attitude changes and prescribing practices was not a goal of this study. We are not naïve enough to be certain that a one time intervention on any subject matter related to ethical issues will change student attitudes in a way that is durable. However, our goal as educators should be to make the students think critically, and demonstrating self-reported attitude changes is a necessary first step toward more durable change.
Some academic institutions have chosen to ban PCRs from the academic learning environment. McCormick et al showed that restricting access to PCRs during residency training was associated with less informational dependence on the PCR and a decreased frequency of PCR contact after training [5]. Underlying such a restrictive policy is the idea that trainees are not able and/or educable to resist the marketing tactics of PCRs. In contrast, our approach is based on the opinion that learning the skills for interacting appropriately with PCRs should not be delayed until a physician has entered practice, and that banning PCRs may simply extend the period of naivete for physicians in training [14]. Not only does such an omission in the curriculum miss the opportunity to teach physicians about professional relationships surrounding the business model. It also ignores the cost containment needs of the academic medical center and prospective employers.
The challenge for medical educators is how to incorporate this increasingly important knowledge domain into training programs. What aspects of marketing strategy need to be taught and how? The growing emphasis on social justice and professionalism should encourage the appropriate distance from and respect for marketing pressures in medicine and add support for this curricular element in medical education [21]. Our model suggests the possibility of a partnership between the pharmaceutical industry and educators in better preparing phsyicians in training for marketing in medicine. While pharmaceutical companies are the current target of criticism of commercialism in medicine, other services (durable medical equipment, herbal/nutritional supplements, new medical technologies) are all accompanied by marketing pressures that physicians will have to factor into clinical decision making.
Conclusions
Medical students have exposure to PCRs early in their medical education, at least in this setting. Students perceived information from PCRs to have moderate educational value, and a value equivalent to that for practicing physicians. A brief workshop intervention can have a measurable immediate effect on student attitudes.
List of abbreviations
PCR – pharmaceutical company representative
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
JW conceived of the study, participated in its design and coordination, and drafted the manuscript.
CO participated in design and coordination of the study, conducted the intervention, participated in data interpretation, and manuscript revision.
Both authors read and approved the final manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
The pharmaceutical company representative involved in the workshop intervention wished to remain anonymous, but we are still grateful for his efforts to educate medical students.
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BMC GenetBMC Genetics1471-2156BioMed Central London 1471-2156-6-41569400610.1186/1471-2156-6-4Research ArticleInfluence of language and ancestry on genetic structure of contiguous populations: A microsatellite based study on populations of Orissa Sahoo Sanghamitra [email protected] VK [email protected] National DNA Analysis Centre, Central Forensic Science Laboratory, 30, Gorachand Road, Kolkata-700 014 India2005 5 2 2005 6 4 4 5 7 2004 5 2 2005 Copyright © 2005 Sahoo and Kashyap; licensee BioMed Central Ltd.2005Sahoo and Kashyap; 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 have examined genetic diversity at fifteen autosomal microsatellite loci in seven predominant populations of Orissa to decipher whether populations inhabiting the same geographic region can be differentiated on the basis of language or ancestry. The studied populations have diverse historical accounts of their origin, belong to two major ethnic groups and different linguistic families. Caucasoid caste populations are speakers of Indo-European language and comprise Brahmins, Khandayat, Karan and Gope, while the three Australoid tribal populations include two Austric speakers: Juang and Saora and a Dravidian speaking population, Paroja. These divergent groups provide a varied substratum for understanding variation of genetic patterns in a geographical area resulting from differential admixture between migrants groups and aboriginals, and the influence of this admixture on population stratification.
Results
The allele distribution pattern showed uniformity in the studied groups with approximately 81% genetic variability within populations. The coefficient of gene differentiation was found to be significantly higher in tribes (0.014) than caste groups (0.004). Genetic variance between the groups was 0.34% in both ethnic and linguistic clusters and statistically significant only in the ethnic apportionment. Although the populations were genetically close (FST = 0.010), the contemporary caste and tribal groups formed distinct clusters in both Principal-Component plot and Neighbor-Joining tree. In the phylogenetic tree, the Orissa Brahmins showed close affinity to populations of North India, while Khandayat and Gope clustered with the tribal groups, suggesting a possibility of their origin from indigenous people.
Conclusions
The extent of genetic differentiation in the contemporary caste and tribal groups of Orissa is highly significant and constitutes two distinct genetic clusters. Based on our observations, we suggest that since genetic distances and coefficient of gene differentiation were fairly small, the studied populations are indeed genetically similar and that the genetic structure of populations in a geographical region is primarily influenced by their ancestry and not by socio-cultural hierarchy or language. The scenario of genetic structure, however, might be different for other regions of the subcontinent where populations have more similar ethnic and linguistic backgrounds and there might be variations in the patterns of genomic and socio-cultural affinities in different geographical regions.
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Background
Human society in a geographic area develops when colonizing populations bring along with them different languages, cultures and technological advancements over a period of time. As more populations migrate to settle in the same area, they are either eliminated, subjugated or absorbed [1]. In India, majority of incoming populations have been absorbed, forming heterogeneous and complex human societies. A few have subjugated the subservient cultures to establish a hierarchical caste system or have totally isolated some groups such as tribes, which still remain outside the social boundaries. This practice has enriched India with populations having varied socio-cultural and linguistic diversities that have flourished independently, nurtured by the vast geographical and ecological regime [2]. Studies based on various DNA markers on diverse populations occupying different geographical areas of the Indian subcontinent have revealed much about the presence of large extent of human genetic variation [3-10] and the distinct genetic difference between castes and tribal populations of India [11-13]. These studies, however fail to characterize the structure of populations in geographic contiguity, where populations with different language and social hierarchies cohabit together. Although distinct social demarcation between castes and tribes is well established, the origin of a few populations of India still remains controversial. Though many castes are known to have tribal origins [14], nevertheless their assessment with polymorphic DNA markers still remains incomplete.
This study aims to understand the genetic diversity of populations of Orissa and examines the role of language and genetic origin on structure of populations inhabiting the same geographic region and evaluates some of the suggested population histories from a molecular perspective. Orissa is a coastal state in the southeast region of India, which is occupied by population groups having varied ethnicity, belonging to different strata of the hierarchical caste system and speaking languages belonging to different linguistic families. Its strategic geographic location between Northern plains and peninsular Southern India and cultures assimilated during the 4th – 5th century B.C. from southeast Asian countries of Java, Sumatra, Brunei and Indonesia [15] have enriched the socio-cultural diversity of contemporary populations of Orissa. The extant populations of the region can be broadly classified into two major social groups; castes and tribes. Brahmin, Khandayat, Karan and Gope comprise a large section of Indo-European speaking caste populations of Orissa, whose position in hierarchical caste system is governed by occupation and where ancestry is patrilineal. Brahmins form the priestly class who occupy uppermost strata in the caste hierarchy, with historical accounts that trace their migration from upper Gangetic regions of north India. Next in hierarchy is the Kshatriyā – a warrior group comprising the Khandayats; followed by Karans (Kayasthā), record keepers and Gope are cattle-breeders who occupy the subsequent strata in caste system [16]. Other than caste groups, tribes constitute a large number of aboriginal Australoid populations of Orissa who are predominantly forest dwellers, most of them having their own dialects. Linguistically, the tribal groups of the region can be categorized into three of the four major language families spoken in India: Indo-European, Austro-asiatic and Dravidian. Kharia, Juang, Gadaba, Ho, Munda and Saora are among few of the most ancient tribes whose dialects belong to the Austro-asiatic linguistic family, while those of Paroja, Oraon and Kondh belong to the Dravidian linguistic group [16]. Of these populations, only a few (Paroja, Agharia, Gaud, Tanti) have been included in studies using DNA markers to get a perspective of the overall genetic diversity present in the country [8,11,12]. Hence, to understand the genetic constitution of these ethnically and linguistically diverse populations, we have used autosomal microsatellites, genetic markers with proven precision in deciphering genomic diversity and affinities of human populations [17].
Microsatellites or short tandem repeats (STRs) are most extensively used for elucidating the genetic diversity and evolution of human populations because of their abundance and prevalence in the genome, high level of polymorphism and amenability to automation [18-23]. High mutation rates of STR loci facilitate inferences to be drawn about population substructure and short-term evolutions and to make a more reliable and precise estimation of phylogenetic relationships among populations both at racial and continental levels [24-29]. Also, most questions of anthropological interest involve processes occurring over relatively short time periods, during which substantial genetic drift and migration may occur but fewer mutations get accumulated. These minor changes are easily detected using STR markers rather than bi-allelic markers, where mutations accumulate slowly through evolutionary time. STR markers are therefore markers of choice for this study, which involves closely related populations that share similar ethnicity, language, culture or history of origin.
In this study, we have examined variation at 15 autosomal STR loci in a sample of 404 individuals from Orissa (Table 1, Figure 1) and compared the results with previously published data from other regions of the Indian subcontinent. Our aim was (i) to assess the genetic diversity and relationship of populations of Orissa with other Indian populations, and (ii) to find out the role of language and ancestry, if any, on genetic structure of populations living in geographic contiguity. This study also allows a finer resolution of population history of the region than has hitherto been possible.
Table 1 Demographic characterization of the seven studied populations of Orissa
POPULATION CODE n SOCIAL HIERARCHY ETHNICITY LANGUAGE GROUP
1 ORIYABRAHMIN OB 57 Upper Caste Indo-Caucasoid Indo-European
2 KARAN KR 62 Middle Caste Indo-Caucasoid Indo-European
3 KHANDAYAT KY 62 Middle Caste Indo-Caucasoid Indo-European
4 GOPE GP 60 Lower Caste Indo-Caucasoid Indo-European
5 JUANG JU 50 Tribe Proto-Australoid Austro-Asiatic
6 SAORA SA 35 Tribe Proto-Australoid Austro-Asiatic
7 PAROJA PR 78 Tribe Proto-Australoid Dravidian
Figure 1 Geographical map of Orissa showing the location of sample collection
Results
Nature and extent of allelic diversity
The distribution of allele frequencies and tests of Hardy-Weinberg Equilibrium (HWE) on the seven populations of Orissa have been previously reported [30,31]. Except for Saora, all other studied populations were found to be in HWE. Saora showed significant departures from HWE at three analysed parameters (p < 0.05 for exact test and homozygosity test; p < 0.1 for log-likelihood ratio test) and a lower heterozygosity value (0.571) compared to the expected estimates of allele frequencies at D3S1358 locus. Number of alleles and most common alleles at the fifteen STR loci along with gene diversity of each of the studied seven populations are shown in Table 2a, 2b and 3. The most common alleles at each of the 15 STR loci were shared between 2–4 populations. These results agree with the analysis of 4 STR loci (CSF1Po, TPOX, THO1 and vWA) reported by Mukerjee et al, 1999 on three populations of Orissa (Agharia, Gaud and Tanti). The number of alleles observed in the studied population and heterozygosity values (0.615–0.967) indicate that the selected STR markers are highly polymorphic in all populations and that genetic variability within populations is significantly high across populations with mean gene diversity of 81%.
Table 2a Allelic Diversity at 8 of 15 STR loci describing the extent of variation within the populations of Orissa
D3S1358 THO1 D21S11 D18S51 D5S818 D13S317 D7S820 D16S539
Alleles MCA Alleles MCA Alleles MCA Alleles MCA Alleles MCA Alleles MCA Alleles MCA Alleles MCA
Oriya Brahmin 6 15 6 6 11 29 11 15 6 12 8 11 7 11 6 11
Khandayat 6 15 6 9 11 29 10 14 7 11 8 12 8 11 8 11
Karan 7 15 5 6 10 32 11 14 6 11,12 8 12 7 11 8 11
Gope 8 15 6 9 10 32 12 14 8 12 8 11 8 11 7 11
Juang 6 15 6 9 8 29 10 15 6 11 7 11 7 8 7 11
Paroja 6 15 6 9 9 32 11 15 6 11 8 8 6 11 7 12
Saora 6 16,17 6 9 8 30 11 9 6 11 6 8 7 11 6 12
* Alleles = No. of Alleles, MCA = Most Common Allele
Table 2b Allelic Diversity at 7 of 15 STR loci describing the extent of variation within the populations of Orissa
CSF1Po vWA D8S1179 TPOX FGA Penta E Penta D
Alleles MCA Alleles MCA Alleles MCA Alleles MCA Alleles MCA Alleles MCA Alleles MCA
Oriya Brahmin 7 12 7 17 11 14 6 8 13 24 14 11 6 11
Khandayat 7 12 8 17 9 10,15 7 11 16 24 14 12 8 11
Karan 7 12 7 16 9 10 5 11 13 22 15 11 9 11
Gope 8 12 7 17 8 14 5 11 11 24 17 11,12 9 9
Juang 6 12 6 17,18 8 15 5 11 11 19,22 13 12 8 10
Paroja 5 12 8 14 8 10 5 11 14 23 18 11 9 10
Saora 5 11 5 16 8 13 5 8 10 21 15 11 8 9
* Alleles = No. of Alleles, MCA = Most Common Allele
Table 3 Gene diversity estimated from 15 autosomal STR loci describing the total variation within the seven studied populations of Orissa
Population Gene Diversity
Oriya Brahmin 0.816 ± 0.017
Khandayat 0.811 ± 0.015
Karan 0.817 ± 0.018
Gope 0.815 ± 0.014
Juang 0.804 ± 0.015
Paroja 0.811 ± 0.013
Saora 0.810 ± 0.016
Extent of differentiation between populations
To quantify the amount of genetic diversity that exists among populations, FST was calculated separately for caste groups and tribes. The coefficient of gene differentiation was found to be significantly higher in tribes (0.014) than caste groups (0.004). Combining all seven populations yielded an FST of 1%, demonstrating low level of population differentiation within Orissa. All values of FST were significantly different from zero (p < 0.05). Analysis of molecular variance (AMOVA) presented in Table 4, revealed that as a single group, a large extent of genetic variation (98.98%) was present within the populations of the region. To determine how the residual genetic variance was compartmentalized, we grouped the populations into (i) caste and tribes, (ii) linguistic groups; Indo-European speaking caste populations (Oriya Brahmins, Karan, Khandayat, Gope), Austro-Asiatic speakers Juang and Saora and Dravidian speaking, Paroja and (iii) according to their origins as suggested by historical accounts. The genetic variance between the groups varied from 0.25% to 0.34% and was equally distributed in both ethnic and linguistic clusters, but statistically significant only in the ethnic apportionment.
Table 4 Variance in populations of Orissa due to ethnicity, language and history of origin at three different levels of hierarchy analysed with 15 autosomal STR loci
Basis Grouping Populations in group % of total variance (p values)
Within population Between population within group Between groups
Ethnicity Castes vs Tribes (OB, KY, KR, GP) vs (JU, PR, SA) 98.84 (0.00) 0.83 (0.00) 0.34 (0.03)
Language Indo-European vs Austro-Asiatic vs Dravidian (OB, KY, KR, GP) vs (JU, SA) vs (PR) 98.86 (0.00) 0.79 (0.00) 0.34 (0.05)
History of Origin European vs Austro-Asiatic vs Admixed Gene Pool (OB, KR) vs (JU, SA) vs (KY, GP, PR) 98.91 (0.00) 0.84 (0.00) 0.25 (0.06)
Because the amount of genetic variance between groups was found to be low, we also used clustering algorithm implemented in STRUCTURE analysis (Figure 2) to explore the population structure and relationship among these geographically contiguous but socially and linguistically disparate populations. When the populations were analysed assuming no admixture model and K varying from 1 to 7, only a single distinct genetic cluster could be found with the highest log likelihood value at K = 3. Most of the individuals of the seven populations clustered in cluster 1 and did not split into distinct clusters corresponding to their population affinities. A few of the individuals of Paroja and Khandayat were found in cluster 2 and 3 respectively.
Figure 2 Assignment of samples from seven populations of Orissa to genetic clusters inferred from the STRUCTURE analysis for K = 3.
Genetic relationship among populations
The inter-population genetic relationship among Brahmins, Khandayat, Karan, Gope, Juang, Saora and Paroja was determined using principal component analysis. The plot (Figure 3) of principal component (PC) depicts population configurations in accordance with their ethnic affiliations. Together, the first two principal coordinates described almost 99.9% of the variance in the distance matrix. The caste populations (Brahmins, Khandayat and Karan) and the three tribal populations of Juang, Saora and Paroja were distinctly separated by the first component of the distance matrix. All the caste populations were found to cluster in the upper right quadrant while the tribes distinctly occupied the lower right quadrant. The only discordance was position of Gope, where this population was genetically separate from the other studied caste populations in the PC plot.
Figure 3 PC plot for the seven populations of Orissa from centroid based on fifteen microsatellite loci
The Neighbour-Joining (NJ) tree (Figure 4) gives a graphical representation of genetic distance of Orissa populations from populations of Bihar [32,33], Uttar Pradesh [34], Maharastra [35,36] and Tamil Nadu [37], belonging to similar rank and occupational affiliation in the caste hierarchy. The genetic closeness exhibited by Brahmins of Orissa to those of North India (NJ tree; Figure 4) was clearly discernible, supported by moderately high bootstrap values. While Karan belonging to the next level of hierarchy in the caste system showed similarity to Maratha, a warrior group of Maharastra; Khandayats and Gope depicted affinity to the tribal populations (Figure 4). Paroja, a Dravidian linguistic group, demonstrated affinity with Gonds, and the two Austro-Asiatic speakers Juang and Saora distinctly branched out in the phylogenetic tree.
Figure 4 Neighbor-joining tree of genetic distances (DA) based on fifteen microsatellite loci among studied populations of India
Discussion
India is a remarkable representation of a large segmented society that harbours rich genetic diversity within its human populations and offers myriads of attributes to study the various factors influencing demographics of human populations. It is of particular interest to study patterns of genetic affinities among endogamous groups inhabiting small geographical regions within the subcontinent because of their diverse origins and interethnic admixtures.
We have typed a set of fifteen polymorphic autosomal microsatellite markers in linguistically and socially divergent populations with different histories of origin to elucidate the genetic diversities and affinities among them and to understand the role of genetic origin and language on the genetic structure of populations living in geographic contiguity. The most distinctive feature of our study was the clear delineation between castes and tribes, as was evident from both multivariate and phylogenetic analyses (Figure 3 and 4 respectively). The tribes seem to be the most unique and genetically isolated populations within Orissa. The two Austro-Asiatic tribes Juang and Saora were not significantly different from each other and both showed least number of alleles even at the most polymorphic STR loci such as, D21S11, D18S51, Penta E and FGA (Table 2a, 2b) and lowest heterozygosity values in as many as six loci as compared to the caste groups [30,31]. The tribal groups show relatively high between group differentiation that probably can be attributed to reproductive isolation and drift. This finding is consistent with similar studies carried on tribal populations of Central India [6]. The low heterozygosity estimate of tribes suggests that they have probably undergone some stochastic processes that have resulted from limitations in mating practices and socio-cultural differences in them.
The significantly low coefficient of differentiation among the seven populations (Fst: 0.010, p < 0.05), along with the number of alleles shared between them, confirms admixture and suggests an increased genetic affinity among populations residing in geographic proximity irrespective of their socio-cultural affiliation [3,38,39]. This is also substantiated with the AMOVA and Structure results, which showed that all the individuals of the studied populations cluster in one group and could not be subdivided further. The inability of STRUCTURE analysis to subdivide populations may be due to gene flow among groups or may be that more number of samples and loci are required to identify such close genetic subgroups.
Among the caste groups, Orissa Brahmin showed close affinity to the other upper caste populations of North India rather than to its geographic neighbors. The affinity between Bihar Brahmin and Orissa Brahmin was supported with moderate bootstrap values in the phylogenetic tree (Figure 4), which could be attributed to gene flow between them because of sharing same hierarchical status in the Hindu caste system [9]. This observation corroborates prevalent historical accounts, which suggests that the Brahmin populations of different parts of the subcontinent were natives of upper Gangetic region, who later dispersed to different parts of the country to propagate their cultural and religious ideologies and to explore better economic opportunities [15]. The phylogenetic tree (Figure 4) also clearly depicted that Khandayat and Gope are genetically more related to each other than to other occupationally similar populations (Rajput, Thakur, Maratha and Yadav) of adjoining regions. These results are in congruence with the observations of Majumder et al 1998, where populations studied from widely separated geographic areas were found to exhibit closer genomic affinities with their geographic neighbors than with those sharing similar social ranks. It also substantiates the suggested origin of Khandayat from skilled individuals drawn from peasantry and aboriginals of the region [14]. Because the natives were assimilated into the caste system, they adopted the language and culture of the expanding and dominant upper caste population as a consequence of 'elite-dominance'. Their gene pool, however, still remains closer to aboriginals of the region. Therefore, except Brahmins, other groups were probably pooled from the local people to serve the needs of upper castes in the brahminical society. Thus, two castes bearing similar names simply represent affiliation to the same profession, but have probably different genetic constitution in different geographical regions. When populations of diverse geographic regions were included, the genetic difference among populations of the Indian subcontinent increased. This can probably be ascribed to drift caused by limitations imposed on social mobility between groups due to differences in culture and language. Juang and Saora speak Austro-Asiatic languages while Paroja follow the Dravidian language, both of which are unrelated to Oriya and by itself is a branch of Indo-European linguistic family spoken largely by the caste groups. PC analysis (Figure 3) revealed distinct isolation of the tribes from the Oriya speaking caste populations. The position of Juang and Saora in the NJ tree suggests that they are genetically still separate from other populations and extent of admixture in them from neighboring caste groups is negligible. It is also discernible that genetic distance among tribes is more strongly correlated with their genetic origin, with Paroja forming a close cluster with Madia Gond, a Dravidian tribe of India. This also substantiates the historical account describing Paroja to be an offshoot of the Gonds, one of the largest tribal populations of India. The NJ tree clearly shows that ethnic affiliation (caste/ tribe) and genetic ancestry are the key factors in shaping the genetic variation and sub-structuring among populations in geographic contiguity.
Conclusions
Our study on linguistically distinct but geographically contiguous populations of Orissa using autosomal microsatellite markers reveals a significant amount genetic homogeneity in them. AMOVA results suggest that linguistic differences probably play a negligible role in the present day scenario in restricting gene flow between these populations. The middle-order caste groups shared genetic affinity with the local people of the area, while the Brahmins were similar to those from northern regions. Tribal populations, on the other hand, because of their long-term isolation and mating patterns, were well differentiated from the upper caste groups. This paper provides evidence that for populations living in geographic contiguity, ancestry is the governing factor in fine-tuning of genetic differentiation.
Methods
Population samples analyzed
Blood samples were collected from randomly chosen consenting volunteers, distributed across 17° -48' and 22° -34' North latitude and 81° -24' and 87° -29' East longitude of Orissa (Figure 1). A total of 404 individuals from seven populations, Brahmins (n = 57), Khandayat (n = 62), Karan (n = 62), Gope (n = 60), Juang (n = 50), Saora (n = 35), and Paroja (n = 78) were analyzed for the fifteen autosomal microsatellite loci. These populations were categorized based on ethnic and linguistic criteria (Table 1). The populations used for comparison in the study were selected on the basis of ethnicity, language and occupational similarity: Kanyakubj Brahmins (95), Bihar Brahmins (59), Kayastha (53), Yadav (44), Bhumihar (65), Rajput (58), Thakur (48), Irular (54), Maratha (65), Madia Gond (45), Katkari (72) and Pawara (51).
DNA typing
DNA was extracted from blood samples using standard phenol-chloroform procedure and amplified for fifteen autosomal microsatellite loci using primers multiplexed in the Powerplex 16 System (Promega Corp., Madison, Wisconsin). STR loci analyzed in the study included thirteen tetranucleotides D3S1358, THO1, D21S11, D18S51, D5S818, D13S317, D7S820, D16S539, CSF1PO, vWA, D8S1179, TPOX, FGA and two pentanuleotides, PentaD and PentaE.
Analysis of data
The genetic structure of the populations was analyzed at two hierarchical levels – within populations and among populations. The intrapopulation variability was estimated by analyzing the number of alleles and most common allele at individual loci and by estimating the average gene diversity [40] across the fifteen microsatellite loci. To understand the genetic variation among populations; FST estimates, genetic distance and the analysis of molecular variance [41] were calculated. Genetic relationships among populations were analyzed using the Principal Component Analysis [42]. Genetic distances were estimated by using the DA distance measure [43], and were used to construct neighbor-joining tree [44]. The degree of support for the branches was evaluated by bootstrap analysis. To test the correspondence of genetic clusters with linguistically labeled groups, we used STRUCTURE program [45] assuming that each individual had ancestry in all clusters, so that fractions of ancestry in various clusters could be estimated.
Authors' contributions
SS carried out laboratory experiments, statistical analysis and drafted the manuscript and VKK conceptualized the paper, provided important intellectual inputs in intrepretation of data and preparation of the manuscript. Both authors read and approved the final manuscript.
Acknowledgements
This research was supported by a financial grant to CFSL, Kolkata under the X Five Year Plan of the Govt. of India. We express our appreciation to the original donors who made this study possible. We thank Dr. R. Trivedi for providing helpful information and technical support; Ms. Sitalaximi T. for providing valuable suggestions. We profusely thank the two anonymous reviewers, whose critical suggestions have helped us to significantly improve inferences drawn from our study. SS is grateful to DFS, Ministry of Home Affairs for the Fellowship.
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| 15694006 | PMC549189 | CC BY | 2021-01-04 16:38:19 | no | BMC Genet. 2005 Feb 5; 6:4 | utf-8 | BMC Genet | 2,005 | 10.1186/1471-2156-6-4 | oa_comm |
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BMC Infect DisBMC Infectious Diseases1471-2334BioMed Central London 1471-2334-5-61568659410.1186/1471-2334-5-6Research ArticleA novel pancoronavirus RT-PCR assay: frequent detection of human coronavirus NL63 in children hospitalized with respiratory tract infections in Belgium Moës Elien [email protected] Leen [email protected] Els [email protected] Kalina [email protected] Sandra [email protected] Piet [email protected] Krzysztof [email protected] Ben [email protected] der Hoek Lia [email protected] Ranst Marc [email protected] Laboratory of Clinical & Epidemiological Virology, Department of Microbiology & Immunology, Rega Institute for Medical Research, University of Leuven, Belgium2 Department of Human Retrovirology, Academic Medical Center, University of Amsterdam, The Netherlands2005 1 2 2005 5 6 6 13 10 2004 1 2 2005 Copyright © 2005 Moës et al; licensee BioMed Central Ltd.2005Moës 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
Four human coronaviruses are currently known to infect the respiratory tract: human coronaviruses OC43 (HCoV-OC43) and 229E (HCoV-229E), SARS associated coronavirus (SARS-CoV) and the recently identified human coronavirus NL63 (HCoV-NL63). In this study we explored the incidence of HCoV-NL63 infection in children diagnosed with respiratory tract infections in Belgium.
Methods
Samples from children hospitalized with respiratory diseases during the winter seasons of 2003 and 2004 were evaluated for the presence of HCoV-NL63 using a optimized pancoronavirus RT-PCR assay.
Results
Seven HCoV-NL63 positive samples were identified, six were collected during January/February 2003 and one at the end of February 2004.
Conclusions
Our results support the notation that HCoV-NL63 can cause serious respiratory symptoms in children. Sequence analysis of the S gene showed that our isolates could be classified into two subtypes corresponding to the two prototype HCoV-NL63 sequences isolated in The Netherlands in 1988 and 2003, indicating that these two subtypes may currently be cocirculating.
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Background
Coronaviruses are large, enveloped, positive stranded RNA-viruses [1]. The viral RNA genome is 27–32 kb in size, capped, polyadenylated and encapsidated in a helical nucleocapsid. The envelope is studded with long, petal-shaped spikes, giving the virus particle a characteristic crown-like appearance. Three distinct groups of coronaviruses have been described based on serological affinity and genome sequence. Coronaviruses can infect humans and a variety of domestic animals and can cause highly prevalent diseases such as respiratory, enteric, cardiovascular and neurologic disorders [2,3].
Until recently only three human coronaviruses were thoroughly studied. Human coronavirus OC43 (HCoV-OC43; group 2) and human coronavirus 229E (HCoV-229E; group 1) were identified in the 1960s. They are responsible for 10–30% of all common colds, and infections occur mainly during winter and early spring [4-7]. A third novel human coronavirus, SARS-CoV, was identified as the causal agent during the 2002–2003 outbreak of severe acute respiratory syndrome (SARS) [8-10]. Phylogenetic analysis showed that the SARS-CoV does not closely resemble any of the three previously known groups of coronaviruses, and therefore a tentative fourth group of coronaviruses was suggested [11,12]. However, an early split-off of the SARS-CoV from the coronavirus group 2 lineage has also been suggested [13,14].
A new human coronavirus associated with respiratory illness, HCoV-NL63, was recently identified by a research team in The Netherlands [15]. The virus was isolated in January 2003 from a nasopharyngeal aspirate of a 7-month-old child suffering from bronchiolitis, conjunctivitis and fever. Screening of specimens from patients with respiratory symptoms identified seven additional HCoV-NL63 infected individuals, both children and adults, between December 2002 and February 2003. The complete viral genome sequence was determined. The characteristic genome organisation of coronaviruses can be observed: the 5' two-third of the genome contains two large open reading frames (ORF), ORF1a and ORF1b. In the 3' part of the genome, genes encoding four structural proteins are found: spike (S), envelope (E), membrane (M), and nucleocapsid (N). The hemagglutinin-esterase (HE) gene, characteristic for group 2 coronaviruses, is not present in HCoV-NL63. Sequence analysis demonstrated that HCoV-NL63 shares 65% sequence identity with HCoV-229E. Phylogenetic analysis confirmed that HCoV-NL63 is a new group 1 coronavirus, most closely related to HCoV-229E and porcine epidemic diarrhea virus (PEDV) [15]. Shortly after van der Hoek and colleagues published their discovery of the new human coronavirus HCoV-NL63, a second research group described the characterization of essentially the same virus [16]. The virus was isolated from a nose swab sample collected from an 8-month-old child suffering from pneumonia in The Netherlands in April 1988. Real-time RT-PCR assays were designed for screening of respiratory tract samples. Four additional HCoV-NL63 positive samples, from children aged 3 months to 10 years, were detected between November 2000 and January 2001.
HCoV-NL63 can be considered as a new important cause of respiratory illnesses and two different subtypes might be currently cocirculating in the human population [15]. In this study we wanted to explore the incidence of HCoV-NL63 infection in children diagnosed with respiratory tract infections in Belgium.
Methods
Isolates and patients
We studied 309 isolates from 279 patients with severe respiratory symptoms collected from January 2003 until March 2004 at the University Hospital in Leuven, Belgium. These isolates originated from bronchoalveolar lavages, pharyngeal swabs, nasopharyngeal aspirates, and sputum samples. Routine diagnostic testing was performed for respiratory syncytial virus (RSV), influenza virus, parainfluenza virus and adenovirus. No prior amplification by cell culture was performed. The results of diagnostic tests for RSV were negative for 244 isolates, while 65 isolates were positive for RSV. Patients ranged in age from 1 month to 16 years, with a mean age of 2 years. The temporal distribution of the isolates corresponded to the yearly RSV epidemic period: 236 samples were collected from January to June 2003 and 73 samples were recovered during the first trimester of 2004 (Figure 1A).
Figure 1 Detection of HCoV-NL63 and HCoV-OC43 in samples from patients suffering from severe respiratory symptoms. (A) Number of samples tested per month. (B) Patients infected with HCoV-NL63 and HCoV-OC43. A single HCoV-229E positive sample was isolated in April 2003 (not shown).
Pancoronavirus RT-PCR assay
RNA was extracted from the collected specimens by using the QIAamp Viral RNA Mini kit (QIAGEN, Westburg, The Netherlands) according to instructions of the manufacturer. Screening of the samples was performed by amplifying a 251 bp fragment of the polymerase gene using the following primer set: Cor-FW (5'-ACWCARHTVAAYYTNAARTAYGC-3') and Cor-RV (5'-TCRCAYTTDGGRTARTCCCA-3') (Figure 2). These one-step RT-PCR assays (OneStep RT-PCR kit; QIAGEN) were undertaken in a 50 μl reaction volume containing 10 μL RNA-extract, 10 μl 5x QIAGEN OneStep RT-PCR Buffer, 2 μl dNTP mix (final concentration of 400 μM of each dNTP), 1.8 μl QIAGEN OneStep RT-PCR Enzyme Mix (a combination of Omniscript and Sensiscript reverse transcriptase and HotStarTaq DNA polymerase), 4 μM of each primer, and RNase-free water to 50 μl. The reaction was carried out with an initial reverse transcription step at 50°C for 30 min, followed by PCR activation at 95°C for 15 min, 50 cycles of amplification (30 sec at 94°C; 30 sec at 48°C; 1 min at 72°C), and a final extension step at 72°C for 10 min in a GeneAmp PCR system 9600 thermal cycler (Applied Biosystems, Foster City, CA, USA). PCR-products were run on a polyacrylamide gel, stained with ethidium bromide, and visualized under UV-light.
Figure 2 Selection of primers for the novel pancoronavirus RT-PCR. Shown is the alignment of 14 coronaviral sequences of a conserved region of the polymerase gene. The forward (Cor-FW) and reverse (Cor-RV) primer sequences are shown at the bottom (Y = C/T, W = A/T, V = A/C/G, R = A/G, H = A/T/C, N = A/C/T/G). The coordinates of Cor-FW and Cor-RV are 14017 and 14248, respectively, in the HCoV-NL63 complete genome sequence. The 14 coronavirus sequences used here are available from GenBank under the following accession numbers: HCoV-NL63, AY567487; HCoV-229E, AF304460; infectious bronchitis virus (IBV), Z30541; SARS-CoV, AY313906; HCoV-OC43, AY391777; PEDV, AF353511; bovine coronavirus (BCoV), AF391541; transmissible gastroenteritis virus, AF304460; MHV, X51939; PHEV, AF124988; sialodacryoadenitis virus (SDAV), AF124990; turkey coronavirus (TCoV), AF124991; canine respiratory coronavirus (CRCV), AY150273; feline infectious peritonitis virus (FIPV), AF124987.
RT-PCR assays for HCoV-NL63
Samples that were found positive for HCoV-NL63 were confirmed using one-step RT-PCR assays, which amplified four different regions of the HCoV-NL63 genome. Amplification of a 314-bp gene fragment in the nucleocapsid region was performed with two specific HCoV-NL63 primers: N5-PCR1 (5'-CTGTTACTTTGGCTTTAAAGAACTTAGG-3', nt 26695-nt 26721) and N3-PCR1 (5'-CTCACTATCAAAGAATAACGCAGCCTG-3', nt 26982-nt 27008). Secondly a 237-bp fragment in ORF1b was amplified using the primers repSZ-1 and repSZ-3 described by van der Hoek and colleagues [15]. A third RT-PCR assay was carried out on the HCoV-NL63 positive samples amplifying a 839-bp fragment with ORF1a specific primers: SS5852-5P and P4G1M-5-3P [15]. These one-step RT-PCR assays were performed essentially as described above. They were carried out using 5 μL RNA-extract and 0.6 μM of each primer. Only 45 cycles of amplification were run and annealing temperature was set at 50°C. Furthermore a 663 bp fragment of the spike gene was amplified using a RT-nested PCR. The outer primer set SINL5 (5'-GAGTTTGATTAAGAGTGGTAGGTTG-3', nt 20391-nt 20415) and SINL3 (5'-AACAGTGTAGTTAACTACACGG-3', nt 21068-nt 21089) were used in a one-step RT-PCR, performed as described above, using 10 μl of RNA-extract and an annealing temperature of 48°C. A nested PCR was carried out with the inner primer set SINL5n (5'-GGTTGTTGTTACGCAATAATGGTCGT-3', nt 20411-nt 20436) and SINL3n (5'-ACACGGCCATTATGTGTGGTGAC-3', nt 21051-nt 21073). The nested reaction mix was composed of 1 unit Taq polymerase, 1 μl of a 25 mM dNTP-mix, 10 μl 5X buffer C (PCR Optimizer Kit, Invitrogen, The Netherlands), and 30 pmol of forward and reverse primer in a 50 μl reaction volume. As template 10 μl of the outer PCR product was added. The cycling conditions were as follows: an initial denaturation at 94°C for 5 min, followed by 40 cycles of amplification (45 sec at 94°C, 45 sec at 54°C, 1 min at 72°C), and a final extension of 5 min at 72°C. PCR-products were run on a polyacrylamide gel, stained with ethidium bromide, and visualized under UV-light. The amplicons were purified using the QIAquick PCR purification kit (QIAGEN) and sequenced with the respective primer pairs using the ABI PRISM BigDye Terminator Cycle Sequencing Reaction kit (version 3.1) on an ABI PRISM 3100 DNA sequencer (Applied Biosystems) according to the manufacturer's instructions. Positive and negative controls were included in each PCR experiment. The HCoV-NL63 positive control was RNA isolated from a HCoV-NL63 culture.
Sequence analysis and phylogenetic analysis of the amplicons
Chromatogram sequencing files were inspected with Chromas 2.2 (Technelysium Pty Ltd, Helensvale, Australia), and contigs were prepared using SeqMan II (DNASTAR, Madison, WI, USA). The obtained consensus sequences were compared with the prototype HCoV-NL63 sequences available in GenBank database release 142.0 using BLAST analysis (NCBI BLAST server). Multiple sequence alignments were prepared using CLUSTAL X version 1.82 [26], and manually edited in the GeneDoc Alignment editor [27]. Phylogenetic analysis was conducted using MEGA version 2.1 [28].
Nucleotide sequence accession numbers
The sequences determined in this study have been deposited in the GenBank sequence database under accession numbers AY758276 to AY758301.
RT-PCR assays for HCoV-OC43 and HCoV-229E
Our collection of samples was also screened using the pancoronavirus RT-PCR assay for the presence of HCoV-OC43 and HCoV-229E. Positive results were confirmed by one-step RT-PCR using HCoV-OC43 and HCoV-229E specific primer pairs located in the membrane glycoprotein region (OC43-FW: 5'-GGCTTATGTGGCCCCTTACT-3', nt 28580-nt 28599; OC43-RV: 5'-GGCAAATCTGCCCAAGAATA-3', nt 28894-nt 28913; 229E-FW: 5'-TGGCCCCATTAAAAATGTGT-3', nt 24902-nt 24921; 229E-RV: 5'-CCTGAACACCTGAAGCAAT-3', nt 25456-nt 25475) [18]. One-step RT-PCR and sequence analysis were performed essentially as described above. Annealing conditions during the RT-PCR assay were modified: the annealing temperature was set at 55°C.
Results
Pancoronavirus RT-PCR assay
A pancoronavirus RT-PCR assay is a usefull tool to test for all coronaviruses in a clinical sample. Besides quick screening for several pathogens in one assay, it supplies the possibility to identify previously unknown coronaviruses. The consensus RT-PCR assay as described by Stephensen et al., designed to amplify all known coronaviruses, is not able to detect HCoV-NL63 because of several mismatches with the primer sequences [15,17]. We modified these consensus primers based on an alignment of the HCoV-NL63 prototype sequence and 13 other coronavirus sequences (Figure 2). To determine whether the newly designed pancoronavirus RT-PCR assay efficiently amplifies a broad range of coronaviruses the RT-PCR assay was tested on cell culture supernatant of the four known human coronaviruses and three animal coronaviruses: HCoV-NL63, HCoV-OC43, HCoV-229E, SARS-CoV, feline infectious peritonitis virus (FIPV), porcine hemagglutinating encephalomyelitis virus (PHEV), and murine hepatitis virus (MHV). Amplification of the expected 251 bp region was observed for all tested coronaviruses (Figure 3). The sensitivity of the pancoronavirus RT-PCR assay was assessed by testing tenfold dilutions of HCoV-NL63 and HCoV-OC43 RNA. While 50 copies of HCoV-OC43 RNA copies per μl nasopharyngeal aspirate could be detected, the sensitivity for HCoV-NL63 was a bit lower i.e. 5 × 103 RNA copies per μl nasopharyngeal aspirate.
Figure 3 Gel electrophoresis after pancoronavirus RT-PCR assay. The indicated band of 251 bp corresponds with the expected amplicon size. As a marker Molecular Weight Marker VI was used (Boehringer Mannheim, Germany).
Detection of HCoV-NL63 in clinical specimens
The pancoronavirus RT-PCR assay was used for screening of specimens from hospitalized patients with respiratory symptoms collected between January 2003 and March 2004. Samples, from which a 251 bp fragment could be amplified, were further identified by sequencing using the pancoronavirus primers. We studied 309 specimens with a temporal distribution that corresponded with the yearly RSV epidemic period (Figure 1A). A total of 244 samples were found negative for RSV by diagnostic testing. The 279 patients in this study comprised of 211 patients aged <2 years (75.6%), 68 aged 2–16 years (24.4%). We detected HCoV-NL63 in 7 samples (2.3%). One positive sample was collected at the end of January 2003 and coinfection with RSV type B was present. Five of the positive samples were collected within a ten-day period at the end of February 2003, and one positive sample was collected at the end of February 2004, which showed coinfection with adenovirus and parainfluenza virus (Figure 1B, Table 1). The seven positive samples were obtained from one patient aged 1 month, four patients of 1 year, one patient of 2 years, and one patient of 16 years. The patient files showed that all subjects suffered from respiratory tract illness and some had underlying disease (Table 1).
Table 1 Patients hospitalized with respiratory tract illness associated with HCoV-NL63 infection
Patient nr. Age Sex Symptoms Underlying disease Specimen Sample date
1153a 1 year male URTI: fever, coughing, wheezing, rhinitis, diarrhoea none NPA 27 Jan 2003
33545 16 years male LRTI: fever, coughing, respiratory distress, pharyngitis Smith-Lemli-Opitz syndrome NPA 14 Feb 2003
21596 1 year female LRTI: fever, coughing, respiratory distress Vater syndrome, epilepsy NPA 20 Feb 2003
53887 1 month female URTI: fever, rhinitis, two siblings have URTI none NPA 20 Feb 2003
40001 1 year male LRTI: respiratory distress, cardiac arrest, rotavirus-positive diarrhoea epilepsy NPA 21 Feb 2003
64880 2 years male URTI: fever, coughing, wheezing neurofibromatosis NPA 24 Feb 2003
70688b 1 year female LRTI: pneumonia, fever, cyanosis, diarrhoea none PS 25 Feb 2004
apositive for RSV type B; bpositive for adenovirus and parainfluenza virus
LRTI, lower respiratory tract illness; URTI, upper respiratory tract illness; PS, pharyngeal swab; NPA, nasopharyngeal aspirate
The seven HCoV-NL63 positive respiratory samples were confirmed by alternative RT-PCR assays. Amplification of a fragment of the nucleocapside gene and ORF1b was carried out. Sequence analysis of the N gene fragments and the ORF1b fragments showed 98–100% similarity to the prototype HCoV-NL63 sequences available in the GenBank database (AY567487, AY518894). A third one-step RT-PCR was carried out for each positive sample to amplify part of the ORF1a gene. Sequence analysis of the ORF1a PCR-products revealed 99% sequence identity with both HCoV-NL63 prototype sequences available in GenBank. A neighbor-joining phylogenetic tree was constructed based on an alignment of the ORF1a nucleotide sequences from the HCoV-NL63 positive samples and the available HCoV-NL63 sequences in GenBank. HCoV-229E was used as an outgroup. The dendrogram shows that all HCoV-NL63 sequences cluster together, but two subclusters can be observed (Figure 4).
Figure 4 Phylogenetic analysis of the partial ORF1a nucleotide sequences. Accession numbers: HCoV-NL63, AY567487; HCoV-NL, AY518894; HCoV-229E, AF304460; NL-p466, AY567488; NL-p246, AY567489; NL-p251, AY567490; NL-p496, AY567491; NL-p223; AY567492; NL-p248, AY567493; NL-p72, AY567494; CAN39, AY675541; CAN52, AY675542; CAN57, AY675543; CAN140, AY675544; CAN146, AY675545; CAN214, AY675546; CAN449, AY675547; CAN470, AY675548; CAN483, AY675549; CAN495, AY675550; CAN528, AY675551; CAN531, AY675552; CAN543, AY675553.
Inspection of the two full genome HCoV-NL63 sequences available in GenBank demonstrates that especially the aminoterminal region of the Spike protein can be very divergent. Therefore we decided to amplify this region to investigate the variability of these region in our patients. An RT-nested PCR assay was used to amplify part of the S gene. These partial spike sequences showed 98% similarity with the HCoV-NL63 prototype strains. An alignment of the S gene sequences from the Belgian samples, partial spike sequences from the positive samples identified in The Netherlands (data not shown), and the prototype HCoV-NL63 sequences, was used to constitute a neighbor-joining phylogenetic tree. The neighbor-joining tree was evaluated by 500 bootstrap pseudoreplicates. Two clusters can again be observed (Figure 5).
Figure 5 Phylogenetic analysis of the partial S gene nucleotide sequences based on an alignment of the Belgian spike sequences, spike sequences from the positive samples identified in The Netherlands, and the prototype HCoV-NL63 sequences available in GenBank. Accession numbers: HCoV-NL63, AY567487; HCoV-NL, AY518894. PEDV was used as an outgroup.
Detection of HCoV-OC43 and HCoV-229E
Screening of our sample collection for the presence of HCoV-OC43 and HCoV-229E was also performed. We detected HCoV-OC43 in 7 of 309 samples (2.3%) and HCoV-229E in one sample (0.3%). The seven HCoV-OC43 positive samples were collected during the winter and early spring of 2003 and 2004. The sample in which we detected HCoV-229E was collected in April 2003. The positive samples were confirmed by RT-PCR using specific HCoV-OC43 and HCoV-229E primer pairs that amplify part of the M gene [18]. The HCoV-OC43 and HCoV-229E partial membrane sequences of the contemporary Belgian strains showed 97–99% similarity with the HCoV-OC43 and HCoV-229E prototype sequences in GenBank.
Discussion
RSV, influenza viruses, adenoviruses, and parainfluenzaviruses are probably the most important viral agents of severe respiratory diseases. However, a substantial part of respiratory tract infections can not be attributed to any known pathogen. Underlying conditions and immunosuppression largely determine the impact of respiratory viruses on individuals [19]. The common cold viruses HCoV-OC43 and HCoV-229E have also been associated with more severe lower respiratory tract conditions in infants and immunocompromised patients [20-23]. The clinical symptoms associated with HCoV-NL63 infections still need to be determined, but there are some indications that HCoV-NL63 can cause severe respiratory illnesses in children and immunocompromised adults [15,16]. We detected HCoV-NL63, using a pancoronavirus RT-PCR, in patients suffering from relatively severe respiratory diseases necessitating hospitalization. These positive samples were collected from children aged 1 month to 16 years. Two patients suffered from severe underlying disease: one patient suffered from Smith-Lemli-Opitz syndrome, a rare autosomal recessive disorder due to a primary enzymatic defect in the cholesterol metabolism. A second patient was diagnosed with VATER, a syndrome characterized by the sporadic association of specific birth defects or abnormalities such as vertebrae and vascular anomalies, anal atresia, trachea and esophagus problems and renal anomalities. All HCoV-NL63 infected patients established a complete recovery from their respiratory symptoms. One-step RT-PCR assays were used to detect and confirm these positive samples.
Results from epidemiological surveys conducted in the 1970's have led to the conclusion that human coronaviruses are distributed worldwide and circulate during seasonal outbreaks [22]. Our results indicate that HCoV-NL63 is the causal agent in a significant portion of respiratory diseases of unknown etiology. We detected HCoV-NL63 in respiratory samples collected in February 2003, with a frequency of 7.1%, and during February 2004, with a frequency of 2.5%. These results seem to support the tendency of human coronaviruses to circulate mainly during the winter season [7,24]. However, in this study, sampling was only performed from January to May during the yearly RSV epidemic period, while no samples from the summer and autumn months were screened. The first publication on HCoV-NL63 showed that the virus circulated in Amsterdam during the winter months of 2002/2003 [15]. More recently another set of Amsterdam samples was screened, obtained during the winter of 2001/2002 and 2003/2004. HCoV-NL63 was found in one trachea sample obtained in February 2002, and in two oropharyngeal aspirates from December 2003 and January 2004, respectively (data not shown). Combined with the data that we present here from Belgium, these findings confirm that HCoV-NL63 reappears each winter season similar to the previously known respiratory viruses. Recently, research teams from Australia, Japan and Canada, have submitted partial HCoV-NL63 sequences to the GenBank database (AY600442-AY600446, AY662694-AY662698, AY675541-AY675553). This indicates that this newly discovered human coronavirus has a worldwide distribution.
Sequence analysis of the highly conserved nucleocapsid region showed that the Belgian isolates are similar to the two prototype HCoV-NL63 complete genome sequences in GenBank isolated in the Netherlands in 1988 and 2003. Furthermore, phylogenetic analysis of part of the ORF 1a region of our patients showed the same subclusters of HCoV-NL63 that were described previously [15] (Figure 4). This finding supports the suggestion that several HCoV-NL63 subtypes with distinct molecular markers are cocirculating, also in Belgium. A large insert in the 5' part of the S gene of HCoV-NL63 compared with HCoV-229E has been described [15,16]. Both HCoV-NL63 complete genome sequences show only 89% sequence identity in this spike insert region, which implies that there are at least two different HCoV-NL63 subtypes. Sequence analysis of this spike insert region revealed that our samples show similarity to both prototype HCoV-NL63 subtypes, which was confirmed by phylogenetic analysis. The partial S gene sequences cluster together with the two prototype HCoV-NL63 sequences in two different groups (Figure 5). This confirms that the HCoV-NL63 subtypes first isolated in 1988 and 2003 are cocirculating. When analysing the dendrograms based on ORF1a and S gene sequences, a discordance in the clustering pattern of some HCoV-NL63 isolates (e.g. HCoV-NL and NL-p223) can be observed, suggesting a possible recombination event. Further research of complete genome sequences of these isolates is required. Drawing conclusions based on phylogenetic analysis of one single gene therefore requires caution as the true phylogeny can only be demonstrated by analysing complete genome sequences.
Screening of our sample collection for the presence of HCoV-OC43 and HCoV-229E revealed seven HCoV-OC43 positive samples and only one HCoV-229E positive sample. All positive samples were isolated during winter and early spring, which is concordant with the results of previous epidemiological studies. HCoV-OC43 infected samples were mainly identified during February 2003 and February 2004 (Figure 1B). These data show that the epidemic seasons of HCoV-OC43 and HCoV-NL63 coincide. The positive samples were collected from children aged 1 to 12 years, whom all suffered from respiratory symptoms. The very low detection rate of HCoV-229E compared with the frequent detection of HCoV-NL63, might imply that HCoV-NL63, closely related to HCoV-229E, is currently more important as a causal agent of respiratory diseases. At the moment, there are no data concerning cross-neutralization between HCoV-229E and HCoV-NL63. In theory, such cross-neutralization might be possible, since both viruses are relatively closely related species belonging to coronavirus group 1. Antigenic cross-reactivity has already been demonstrated between SARS-CoV and group 1 coronaviruses TGEV, FIPV and CCoV [25].
The development of a pancoronavirus RT-PCR assay using a primer set that matches all known coronaviruses might be useful for the identification of new coronaviruses. This pancoronavirus RT-PCR-assay can also be used as a diagnostic tool to detect any of the four currently known human coronaviruses in clinical samples.
Conclusions
Human coronavirus NL63 is a new important respiratory pathogen that can cause severe respiratory infections in children. Sequence analysis of the HCoV-NL63 isolates detected in our study demonstrates that our Belgian isolates can be classified into two subtypes corresponding to the two prototype HCoV-NL63 sequences isolated in The Netherlands in 1988 and 2003. Our findings indicate that these two subtypes may currently be cocirculating.
Competing interests
The author(s) declare that they have no competing interests.
Author's contributions
EM conceived of the study and designed it together with LV, EK, and MVR. EM developed the pancoronavirus RT-PCR and performed the RT-PCR and sequencing reactions. EM and LV drafted the manuscript. KZ assembled the respiratory samples. SL performed the RT-PCR sensitivity assays. PM was responsible for the graphical support of the manuscript. LVDH, KP and BB developed the HCoV-NL63 RT-PCRs and helped with the design of the study and the writing of the manuscript. All authors contributed to the final version of the manuscript, read and approved it.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
We would like to thank all the colleagues of the laboratory of Clinical & Epidemiological Virology, Department of Microbiology & Immunology, Rega Institute for Medical Research, University of Leuven, Belgium, and the Department of Retrovirology, Academic Medical Center, University of Amsterdam, The Netherlands, for helpful comments and discussion. This work was supported by a fellowship of the Flemish Fonds voor Wetenschappelijk Onderzoek (FWO) to Leen Vijgen, and by FWO-grant G.0288.01.
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| 15686594 | PMC549190 | CC BY | 2021-01-04 16:28:14 | no | BMC Infect Dis. 2005 Feb 1; 5:6 | utf-8 | BMC Infect Dis | 2,005 | 10.1186/1471-2334-5-6 | oa_comm |
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BMC GenetBMC Genetics1471-2156BioMed Central London 1471-2156-6-31568354610.1186/1471-2156-6-3Research ArticleTransient expression analysis of allelic variants of a VNTR in the dopamine transporter gene (DAT1) Mill Jonathan [email protected] Philip [email protected] Ian [email protected]'Souza Ursula M [email protected] Institute of Psychiatry, MRC Social, Genetic, and Developmental Psychiatry (SGDP) Centre, De Crespigny Park, Denmark Hill, London, SE5 8AF, UK2005 31 1 2005 6 3 3 1 9 2004 31 1 2005 Copyright © 2005 Mill et al; licensee BioMed Central Ltd.2005Mill 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 10-repeat allele of a variable number tandem repeat (VNTR) polymorphism in the 3'-untranslated region of the dopamine transporter gene (DAT1) has been associated with a range of psychiatric phenotypes, most notably attention-deficit hyperactivity disorder. The mechanism for this association is not yet understood, although several lines of evidence implicate variation in gene expression. In this study we have characterised the genomic structure of the 9- and 10-repeat VNTR alleles, and directly examined the role of the polymorphism in mediating gene expression by measuring comparative in vitro cellular expression using a reporter-gene assay system.
Results
Differences in the sequence of the 9- and 10- repeat alleles were confirmed but no polymorphic differences were observed between individuals. There was no difference in expression of reporter gene constructs containing the two alleles.
Conclusions
Our data suggests that this VNTR polymorphism may not have a direct effect on DAT1 expression and that the associations observed with psychiatric phenotypes may be mediated via linkage disequilibrium with other functional polymorphisms.
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Background
The dopamine transporter (DAT) mediates uptake of dopamine into presynaptic neurons, and is a major target for various pharmacologically active stimulants such as cocaine. Genetic association studies provide considerable evidence that a variable number tandem repeat (VNTR) polymorphism in the 3'-untranslated region (UTR) of the dopamine transporter gene (DAT1) is associated with a range of psychiatric phenotypes. In particular, the 10-repeat allele of this polymorphism has been widely associated with attention deficit hyperactivity disorder (ADHD) (e.g. [1,2]), although there have been several non-replications reported (e.g. [3,4]). The mechanism for this association is not yet understood, although several lines of evidence implicate variation in gene expression [5]. The VNTR polymorphism consists of a 40 bp sequence that most frequently occurs as 9 or 10 tandem repeat units, although 3 through to 11 repeats are also observed. Its location within the transcribed 3'-UTR is interesting since these regions have been shown to play an important role in the regulation of transcription efficiency, mRNA stability or mRNA sub-cellular localization [6].
Several in vivo studies using single photon emission computed tomography (SPECT) show an increased density of DAT in ADHD probands compared to controls [7-10], although such findings are not ubiquitous [11]. In addition, several studies suggest there may be an association between VNTR genotype and DAT density [e.g. [12,13]]. Furthermore, methylphenidate, which is used as a treatment for ADHD, has been shown to lower levels of DAT in the brain [9]. Finally, the most thorough investigation of methylphenidate response in relation to DAT1 genotype suggests that the 10-repeat allele is associated with a positive response to the drug [14] as would be expected if the density of the DAT, to which methylphenidate binds, is increased in individuals with the 10-repeat allele. Two smaller studies also report an effect of the DAT1 VNTR on methylphenidate response, although they find poor response is associated with the 10-repeat allele [15,16]. Previously, we measured DAT1 messenger RNA (mRNA) levels in cerebellum, temporal lobe and lymphocytes and observed that increased levels of DAT1 expression were associated with the number of 10-repeat alleles [17]. These data suggested that the VNTR or another polymorphism in linkage disequilibrium (LD) with the VNTR is involved in regulating expression of this gene.
A number of groups have investigated the functional role of the DAT1 VNTR in vitro, although the results from these studies are inconclusive. Michelhaugh et al demonstrated that the human DAT1 9-repeat VNTR enhances transcription in SN4741 cells, obtained from a mouse-embryonic substantia nigra-derived cell line [18]. However, their study did not compare the effect of the 10- versus the 9-repeat. Furthermore, their constructs contained the repeat region inserted upstream of the reporter gene promoter, and not in the 3'UTR of the gene itself. Thus the position of the repeat did not mirror that seen in the wild-type DAT1 gene. It has been postulated that large repeat motifs in the 3'UTR of genes may alter mRNA stability, but such effects would not be detected in the research presented by Michelhaugh et al. Furthermore, it has been shown that the enhancing effect of sequence elements is largely determined by their relative location [19]. Fuke et al examined the effect of the VNTR polymorphism on gene expression using the luciferase reporter system in COS-7 cells [20]. They found that luciferase expression was significantly higher in cells transfected with vectors containing the 10-repeat allele compared to the 7-repeat or 9-repeat alleles. However, they used a monkey cell-line that may not be representative of endogenous human cells and did not employ an internal transfection control for the numerous forms of experimental variability that could affect their data. Miller and Madras concluded that the 9-repeat allele was correlated with increased expression in HEK-293 cells compared with the 10-repeat, but that expression was further mediated by a SNP also located in the 3'UTR of DAT1 [21]. Again, this study did not utilise the dual-luciferase assay system and thus their data could be skewed by experimental variability. Inoue-Murayama et al investigated the functional effect of DAT1 VNTR alleles from several primate species transfected into the human neuroblastoma cell-line, SK-N-SH [22]. They found that the VNTR sequences of nonhuman primates show higher reporter-gene activity compared to human alleles, and a general trend for longer VNTR alleles to reduce transcription. Finally, Greenwood & Kelsoe found no effect on transcription of the 9- and 10-repeat alleles in SN4741 cells, but found that introns 9, 12, and 14 may contain enhancer elements capable of increasing expression ~2-fold [23]. They conclude that it may be the particular combination of polymorphisms in a haplotype across the gene that ultimately effects DAT1 gene expression.
The aim of this study was to examine directly the role of the VNTR polymorphism in mediating gene expression by measuring comparative in vitro cellular expression implementing a reporter-gene assay system in which the VNTR has been inserted in an appropriate 3' configuration, and using human cell-lines known to express DAT1. Analysis was limited specifically to the VNTR sequence itself, so that any functional effect detected could be attributed solely to this candidate polymorphism. Another aim of this study was to fully characterise the genomic structure of the DAT1 VNTR. It is possible that any functional effects of the VNTR are not mediated by repeat length, but instead by variation in the actual sequence of the repeat units. Recent work on the DRD4 exon III VNTR sequence has demonstrated that there can be considerable variation within the sequence of large VNTRs [24]. Such variation, if present, could confound analyses of gene expression and negate associations with disease based solely on repeat length.
Results
Sequence analysis of the DAT1 VNTR
Differences were found between repeat motifs (the individual repeat units making up the total VNTR), and nine variants (labelled A-I) were detected in total (see Figure 1). Interestingly, although differences were found between the orders of motifs in 9- and 10-repeat alleles, they were identical for all examples of each allele size. The order of motifs in the 10-repeat VNTRs was found to be A-A-B-C-D-E-F-D-G-H, and the order in 9-repeat alleles was found to be A-A-B-C-D-I-F-D-H. These sequences are identical to those reported by Fuke et al in a Japanese sample [20]. Furthermore, aligning these sequences up against those available on the NCBI database (accession numbers NM_001044 and AF119117.1) also suggested a lack of between-individual polymorphisms within the VNTR. Interestingly, the 'I' motif (seen in the 9-repeat VNTR but not the 10-repeat) appears to be a combination of the 'E' and 'G' motifs (seen in the 10-repeat VNTR but not in the 9-repeat). The 'F' motif, which occurs in both the 9- and 10-repeat alleles, is also interesting in that it contains 45 base-pairs rather than 40. Furthermore, almost all the between-motif variation occurs within the first (1–24 bp) section of each sequence, before the location of the 5 bp insertion in motif 'F'.
Figure 1 Alignment of the repeat motifs in the 9 and 10 repeat VNTR alleles. Blue letters highlight deviations from the 'A' sequence motif. These sequences are identical to those observed in a Japanese population by Fuke et al [20].
Luciferase activity from transiently transfected cells
Table 1 shows the luciferase transcriptional activity of the seven transfected pGL3 plasmid constructs in SH-SY5Y and HEK-293 cells. Plasmids containing the VNTR insert produced slightly less transcriptional activity than the original pGL3-promoter and pGL3-control plasmids in both cell-lines, although this difference was not statistically different. No statistical difference in transcriptional activity was detected between constructs containing the 9 or 10-repeat DAT1 VNTR sequence in either the SH-SY5Y cells or the HEK-293 cells, although a slight decrease in expression was noticed with increasing repeat length (no insert > 9-repeat insert > 10-repeat insert). Some slight differences were noted between the two cell lines: in both SH-SY5Y cells and HEK-293 cells, the pGL3-basic plasmid, which contains neither promoter nor enhancer sequences, generated the lowest transcriptional activity as expected. In the SH-SY5Y cells, control plasmids containing both an enhancer and promoter showed significantly higher levels of transcriptional activity than the promoter plasmids, although this difference was not seen in the HEK-293 cells.
Table 1 Luciferase transcriptional activity of the DAT1 VNTR constructs in SH-SY5Y and HEK-293 cells.
pGL3 Construct Luciferase/Renilla ratio (95%CI)
SH-SY5Y HEK-293
pGL3-Basic 0.0033 (0.0026–0.0041) 0.1811 (0.1197–0.2424)
pGL3-Control 1.0407 (0.8464–1.2350) 1.7432 (1.1692–2.3172)
pGL3-Control-9rpt 0.7400 (0.6018–0.8781) 1.4963 (1.0416–1.951)
pGL3-Control-10rpt 0.5557 (0.4598–0.6515) 1.2098 (0.8637–1.5559)
pGL3-Promoter 0.1624 (0.0853–0.2396) 2.3461 (1.246–3.4462)
pGL3-Promoter-9rpt 0.1350 (0.1053–0.1646) 1.5967 (1.0963–2.0972)
pGL3-Promoter-10rpt 0.1172 (0.0929–0.1416) 1.2916 (0.925–1.6583)
Discussion
The aims of this study were twofold: first to characterise the genomic structure of the DAT1 VNTR; and second to investigate the effect of the 9- and 10-repeat VNTR alleles on levels of transcription. It is possible that any effects, both on behavioural phenotype or levels of DAT1 expression, commonly associated with the VNTR are due to polymorphisms within the repeat rather than the actual length of the VNTR itself. This theory has often been postulated to explain cases of non-replication of association studies with complex disorders. Recent work on the DRD4 exon III VNTR polymorphism has highlighted the existence of both within individual and between individual variation in repeat motif sequence [24]. In other words the 1st and 2nd repeat motifs within a certain length DRD4 VNTR allele may differ in sequence in a single individual, but there is also variation within the 1st motif between different individuals. We sequenced the DAT1 VNTR in individuals homozygous for either the 9- or 10-repeat allele. Differences were found between repeat motifs in both the 9- and 10-repeat alleles, and nine variants were detected in total. Interestingly, although differences were found between the 9- and 10-repeat alleles, the order of the motifs was identical for all examples of each allele size. Given that not one variation in these sequences was observed in the 60 chromosomes sequenced, it can be concluded that any between individual variations that do occur are extremely rare and unlikely to be the cause of common disorders such as ADHD.
Previously, Ueno et al screened the DAT1 3'UTR for novel polymorphisms in a Japanese population, but only detected a G>A SNP located upstream of the VNTR at position 2319 [25]. Fuke et al have also sequenced the DAT1 VNTR in a small number of Japanese subjects with results identical to those we describe [20]. Miller et al report a SNP that abolishes a DraI restriction site, which they claim to be within the 10-repeat allele [26]. Closer inspection of their paper, however, shows that this polymorphism is located outside of the repeat region and thus their conclusion that they have found a 'novel variant of the 10-repeat allele' is technically incorrect. It is possible, however, that either this polymorphism or that discovered by Ueno et al [25] may be the real risk variant, and associations reported for the VNTR polymorphism may be a result of LD relationships with either of these SNPs.
The lack of between-individual variation in the sequence of the DAT1 VNTR is perhaps surprising given the number of polymorphisms seen in other large VNTRs (e.g. [24]). VNTRs are often mutation hotspots with a high level of genetic recombination due to misaligned repeat units that can cause variations in sequence as well as length [27-29]. Furthermore, according to several estimates of SNP frequency across the genome (e.g. [30]), the average total repeat length of ~400 bp might be expected to contain at least one SNP, especially as it is not located in a highly-conserved coding-region of the gene. The fact that there appears to be no between-individual variations within the 9- and 10-repeat VNTR sequences suggests that it may be subjected to some form of selective pressure, and perhaps have an important functional role. A clue to the importance of the DAT1 VNTR may come from its location within the 3'UTR of the gene. Sequence motifs in the 3'UTR have been shown to have important roles in translation, mRNA stability, subcellular localization, and polyadenylation [6]. Alternatively, given that the between-motif variations seen within the VNTR are ubiquitous, it is possible that they are relatively ancient and have been pushed towards fixation within the population via demographic and random genetic drift.
The second aim of this study was to examine in vitro possible functional consequences of the DAT1 VNTR polymorphism. We made constructs containing the 9- and 10-repeat alleles of the DAT1 VNTR and the luciferase reporter gene, and transiently transfected them into SH-SY5Y and HEK-293 cells. Constructs containing the VNTR alleles gave slightly lower levels of luciferase activity compared to vectors without the inserts. Although these differences were not statistically significant, they appear to go against the conclusions of a previous study in which the VNTR sequence acted as a strong enhancer of transcription [18]. However, the trend of our results do agree with data presented by Fuke et al who found that vectors containing the VNTR polymorphism gave lower luciferase expression levels compared to positive control vectors having no VNTR inserted [20]. Furthermore, Greenwood & Kelsoe found no evidence to suggest that the VNTR sequence acts as a transcriptional enhancer [23]. The discrepancies between these results may be explained by the different methodological strategies employed. Michelhaugh et al utilised GFP as a reporter gene [18], which does not have the sensitivity or specificity associated with the luciferase reporter system, and is generally used in qualitative detection assays. Furthermore, they cloned the VNTR sequence upstream of the SV40 promoter, in a location not analogous to the 3'UTR location of the polymorphism in the DAT1 gene. The importance of the location of regulatory elements has been well-documented [19] and so it is possible that the enhancing effect reported by Michelhaugh et al [18] is specific to the location of the VNTR in their particular experimental design. Additionally, it is possible that the VNTR polymorphism has an important role in mediating processes such as mRNA stability – such effects will have been missed by Michelhaugh et al, as their insert is not transcribed.
We found no significant differences in luciferase activity between constructs containing the 9- or 10-repeat DAT1 VNTR alleles. Other transient expression studies that have compared the VNTR alleles have provided mixed results. Fuke et al found that luciferase expression was significantly higher in cells transfected with vectors containing the 10-repeat allele compared to the 7-repeat or 9-repeat alleles [20]. Their study used a different cell-line, COS-7, which is derived from African Green Monkey kidney. Miller and Madras, on the other hand, concluded that the 9-repeat allele was correlated with increased expression in HEK-293 cells, but that expression was further mediated by a SNP also located in the 3'UTR of DAT1 [21]. Finally, our data is in agreement with that of Greenwood & Kelsoe, who also found no effect on transcription of the 9- and 10-repeat alleles in SN4741 cells, but found that introns 9, 12, and 14 may contain enhancer elements capable of increasing expression ~2-fold [23].
Therefore, our data suggest that the VNTR polymorphism itself may not be functional. Unlike the studies of Fuke et al and Miller & Madras [20,21], our inserts contained no flanking sequence and were restricted to specifically the VNTR itself. There is considerable evidence that there is a functional polymorphism in the vicinity of the 3'UTR of the DAT1 gene. Genetic association studies with ADHD, SPECT brain imaging studies, and correlations with levels of DAT protein and DAT1 mRNA all suggest that a variant associated with DAT1 expression is present in this region. Given that in each of these associations, the VNTR has been nominated as the causative polymorphism, it is likely that the real risk variant is in strong LD with it. Ueno et al and Miller et al both report novel SNPs located within the 3'UTR and close to the VNTR [25,26]. It is possible that either of these SNPs, or another polymorphism yet to be characterised, is mediating expression of DAT1 and is the real risk variant.
There are several obvious limitations to this study. First, it is not known how well in vitro studies of gene expression reflect patterns seen in vivo. Future work could employ animal models to characterise more realistically the effect of the VNTR on DAT1 expression. Second, while we ensured that we used cell-lines that naturally express DAT1, and inserted the VNTR into the correct 3'UTR location of the luciferase reporter gene, our constructs could have been improved by using a homologous DAT promoter. Third, we only cloned a very small portion of the DAT1 gene. Even though this was necessary to examine functional effects specific to the VNTR, the fact that the majority of the DAT1 gene was absent means that it is likely that several cis-acting regulatory elements were not present in the constructs and thus the observed expression may not reflect the actual regulation of the gene. Finally these studies have only analysed DAT1 gene expression in the basal state, and complexities such as the induction of expression by factors such as cellular signals would thus be missed. Future work should focus on systematically characterising the remainder of the 3'UTR to discover the functional effects of other polymorphisms in this candidate region.
Conclusion
In this study we have characterised the genomic structure of the 9- and 10-repeat DAT1 VNTR alleles, and directly examined the role of the polymorphism in mediating gene expression by measuring comparative in vitro cellular expression using a reporter-gene assay system. No expression differences were observed between the 9- and 10-repeat alleles suggesting that this polymorphism may not have a direct effect on DAT1 function.
Methods
Sequence analysis of the DAT1 VNTR polymorphism
Before cloning the DAT1 VNTR and performing expression analyses it was imperative to characterise fully its structure. If there was variation within the VNTR between individuals who have repeats of the same length, then these variants could confound expression analyses based simply upon length. Thirty individuals of predominantly Caucasian ethnicity, homozygous for either the 9- or 10-repeat allele of the VNTR, were selected for sequencing. The VNTR region was amplified on an MJ PTC-225 thermal cycler (MJ Research, Massachusetts, USA) using the primers 5'- TGT GGT GTA GGG AAC GGC C-3' and 5'- CAT TCG CAA ACA TAA AAA CTG TTG T-3' using a standard PCR protocol with a proofreading polymerase and an annealing temperature of 58°C. PCR products were run on a 2% agarose gel stained with ethidium bromide, and then purified using the QIAquick Gel Extraction Kit (Qiagen, Crawley, UK). Purified fragments were sequenced using an ABI BigDye Terminator (v3.0) Cycle Sequencing kit (PE Applied Biosystems, Foster City, CA, USA) and electrophoresed on an ABI 3100 Genetic Analyzer (PE Applied Biosystems). Sequencing traces were analysed using Sequencher software (Gene Codes Corporation, Ann Arbor, MI, USA) and multiple samples aligned to aid mutation detection.
Cloning the DAT1 VNTR into pGL3 gene expression vectors
The pGL3 expression vector family (Promega, UK) contains an Xba I restriction site (TCTAGA) immediately downstream from the luciferase reporter gene, enabling inserts to be cloned into the 3'UTR. Primers were designed to directly flank the DAT1 VNTR and to both of these an Xba I restriction site, along with three extra bases of DAT1 sequence, were added. The primer sequences used were: 5'-TGT TCT AGA TTG TGG TGT AGG GAA CGG C-3' and 5'-AGG TCT AGA AGA GTG TTG GTC TGC AGG CT-3'. The aim of this project was to concentrate solely on the functional significance of the VNTR, so flanking regions around the VNTR were kept as small as possible. Using these primers, the VNTR was amplified in individuals homozygous for the 9- and 10-repeat alleles using standard PCR conditions with an annealing temperature of 55°C. The PCR products were isolated from a 2% agarose gel as described above. The purified fragments were cloned into pCRII TA cloning vectors (Invitrogen, UK), which were then transformed into TOP10F E. Coli cells (Invitrogen, UK) following the manufacturers protocol. Colonies containing recombinant plasmids were identified using X-gal and IPTG. DNA from colonies containing recombinant plasmids was prepared using a Qiagen Midi-prep kit (Qiagen, UK), and the presence of insertions was verified using Xba I restriction enzyme digestion and further checked using direct plasmid sequencing. The Xba I digested 9- and 10-repeat VNTR inserts were run on a 2% agarose gel and purified as described above. The fragments were cloned into pGL3-Control and pGL3-Promoter vectors. The pGL3-Control vector contains both SV40 promoter and enhancer sequences whereas the pGL3-Promoter vector contains only an SV40 promoter. Additionally the pGL3-Basic vector which lacks eukaryotic promoter and enhancer elements was tested on its own without any insert, for transcriptional activity and served as a negative control. Five colonies from each of the four cloning reactions (pGL3-Control-9rpt, pGL3-Promoter-9rpt, pGL3-Control-10rpt, and pGL3-Promoter-10rpt) were selected. Following plasmid DNA preparation, the presence and orientation of the inserts was again verified by Xba I digestion and fluorescent sequencing. New DNA stocks for each of the 8 plasmids to be used in subsequent transfection experiments (pGL3-Control, pGL3-Promoter, pGL3-Basic, pRLSV40, pGL3-Control-9rpt, pGL3-Promoter-9rpt, pGL3-Control-10rpt, and pGL3-Promoter-10rpt) were prepared, and tested again by Xba I digestion.
Cell culture, transient transfections, and luciferase assays
SH-SY5Y and HEK-293 cells were purchased from ATCC (VA, USA). The SH-SY5Y cell line is a thrice-cloned subline of the neuroblastoma cell line SK-N-SH. The HEK-293 cell line is derived from human embryonic kidney. A problem with many in vitro studies of gene expression using reporter genes is that the cell-lines used do not naturally express the gene of interest (i.e. DAT1). Before we transfected our constructs into the SH-SY5Y and HEK-293 cell lines they were tested for DAT1 expression using quantitative RT-PCR. Both cell lines were found to naturally express DAT1 making them suitable for our experiments (data not shown). In addition previous in vitro studies have shown regulation of the DAT1 gene in both the HEK-293 and SH-SY5Y cell lines [31,32], suggesting endogenous expression of the gene in these cell types.
Both cell lines were cultured in 6-well tissue culture plates containing Minimun essential medium Eagle (ATCC) supplemented with 10% foetal bovine serum (Invitrogen, UK). Cells were grown at 37°C in a humidified atmosphere containing 5% CO2. Transfection of the SH-SY5Y cells was carried out using a calcium phosphate transfection kit (Invitrogen, UK). The two different transfection methods used were found to be optimal for each line respectively. The HEK-293 cell line was transiently transfected using Lipofectamine 2000 (Invitrogen, UK). Transfection efficiencies were normalised by the co-transfection of the Renilla vector, pRL-SV40 (Promega, UK). Following transfection, the cells were allowed to grow for 48 hours. The cells were then washed and 500 μl cell lysis buffer (Invitrogen, UK) was added to each well. The firefly luciferase and Renilla luciferase assays were carried out using the Dual-Luciferase Assay System (Promega, UK) following the manufacturers protocol. All transfections were done in triplicate, and repeated at least three times. All comparisons between constructs were analysed by one-way analysis of variance (ANOVA), followed by Tukey post-hoc analysis for pairwise comparisons between specific plasmids.
Authors contributions
JM carried out the molecular genetic studies, participated in the sequence alignment and drafted the manuscript. UD participated in the overall design and co-ordination of the study with supervision of cell culture techniques. PA/IC contributed to the interpretation of findings and general points of the experimental design. All authors read and approved the final manuscript
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| 15683546 | PMC549191 | CC BY | 2021-01-04 16:38:18 | no | BMC Genet. 2005 Jan 31; 6:3 | utf-8 | BMC Genet | 2,005 | 10.1186/1471-2156-6-3 | oa_comm |
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BMC Musculoskelet DisordBMC Musculoskeletal Disorders1471-2474BioMed Central London 1471-2474-6-51569399610.1186/1471-2474-6-5Research ArticleEffect of urbanization on bone mineral density: A Thai epidemiological study Pongchaiyakul Chatlert [email protected] Tuan V [email protected] Vongsvat [email protected] Nipa [email protected] Somsri [email protected] Rajata [email protected] Division of Endocrinology, Department of Medicine, Faculty of Medicine, Khon Kaen University, Thailand2 Bone and Mineral Research Program, Garvan Institute of Medical Research, Sydney, Australia3 Institute of Nutrition, Salaya Campus, Mahidol University, Thailand4 Division of Endocrinology, Department of Medicine, Ramathibodi Hospital, Mahidol University, Thailand2005 4 2 2005 6 5 5 6 7 2004 4 2 2005 Copyright © 2005 Pongchaiyakul et al; licensee BioMed Central Ltd.2005Pongchaiyakul 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 incidence of fractures in rural populations is lower than in urban populations, although the reason for this difference is unclear. This cross-sectional study was designed to examine the difference in bone mineral density (BMD), a primary predictor of fracture risk, between urban and rural Thai populations.
Methods
Femoral neck and lumbar spine BMD was measured by dual-energy X-ray absorptiometry (GE Lunar, Madison, WI) in 411 urban and 436 rural subjects (340 men and 507 women), aged between 20 and 84 years. Body mass index (BMI) was calculated from weight and height.
Results
After adjusting for age and body weight in an analysis of covariance model, femoral neck BMD in rural men and women was significantly higher than those in urban men and women (P < 0.001), but the difference was not observed at the lumbar spine. After stratifying by sex, age group, and BMI category, the urban-rural difference in femoral neck BMD became more pronounced in men and women aged <50 years and with BMI ≥ 25 kg/m2.
Conclusions
These data suggest that femoral neck BMD in rural men and women was higher than their counterparts in urban areas. This difference could potentially explain part of the urban-rural difference in fracture incidence.
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Background
Osteoporosis and its ultimate consequence of low traumatic fracture pose a major public health problem, because it incurs significant costs and increased risk of mortality [1-3]. Osteoporosis is sometimes considered a "consequence" of modernization, because the incidence of fractures in urban regions is often higher than in rural regions [4-10], although the underlying reason for this trend is largely unknown.
Measurement of bone mineral density (BMD) is considered the primary predictor of fracture risk [11]. Therefore, it could be hypothesized that the urban-rural difference in fracture incidence is partly explained by the urban-rural difference in BMD. However, such a difference has not been well documented due to limited data available [12-14]. Some previous studies reported that rural subjects had higher BMD or bone mineral content (BMC) than those urban subjects [12,13], but another study found no such difference [14].
The pace of urbanization in developing countries is more pronounced than in developed countries. Therefore, developing countries are ideal settings for studying the urban-rural difference in BMD. The aim of this study was to examine the difference in BMD between an urban population and a rural population in Thailand.
Methods
Setting and subjects
The present study was designed as a cross-sectional, population-based investigation. The setting was Bangkok city and Khon Kaen province in Thailand. Bangkok is the capital city with a population of 5.7 million and Khon Kaen is a rural province, located 445 km northeast of Bangkok with a population of 1.8 million and is largely an agricultural community. Further details of this study have been described elsewhere [15]
The study included 872 Thai men and women, aged between 20 and 84 years, of whom 422 subjects were from Bangkok and 450 subjects from Khon Kaen. In Khon Kaen, subjects were recruited from 2 villages in the Muang district. There were 14 hamlets in the two villages. In each hamlet, a full list of subjects was obtained, from which 40 subjects were randomly selected by the village's administrator. The selected subjects were then sent a letter of invitation to participating in the study. The response rate was 80.3%. In Bangkok, subjects were recruited via a media campaign, and the sampling technique was similar to the scheme used in Khon Kaen, where subjects were randomly selected from 5 districts within the city of Bangkok.
All Khon Kaen subjects were farmers, while Bangkok subjects were office workers, factory workers or house workers. Twenty-one subjects were excluded from analysis because of bone disorders, chronic diseases, history of taking medications that are deemed to affect calcium and bone metabolism, such as the use of steroids or thyroid hormone; and 4 women were excluded on the basis of pregnancy, lactation, delivery or abortion within the previous 3 months, previous history of oophorectomy and premature menopause. The study was conducted in accordance with the Helsinski Declaration in 1975 and as revised in 1983 and was approved by the Ethics Committee of Faculty of Medicine Ramathibodi Hospital Mahidol University (Bangkok) and Khon Kaen University (Khon Kaen), and written informed consent was obtained from all subjects.
Measurements
BMD at the femoral neck and lumbar spine (L2-4) in g/cm2, was measured by dual-energy X-ray absorptiometry with a Lunar DXP-IQ densitometer (GE Lunar Radiation Corp, Madison, WI, USA). The two study sites (Bangkok and Khon Kaen) used the same model of the DXA machine and the same protocol of measurements. The radiation dose with this method is < 0.1 μGy. The coefficient of variation of BMD for normal subjects is 0.96 and 0.98 at proximal femur and lumbar spine, respectively.
Body weight (including light indoor clothing) was measured using an electronic balance (accuracy 0.1 kg) and standing height (without shoes) with a standiometer (nearest 0.1 cm). Body mass index (BMI) was calculated as ratio of weight (in kg) over height (in meter squared).
Statistical analyses
Descriptive statistics were computed for each residential region and sex separately. In order to test for difference between urban and rural regions, an analysis of covariance (ANCOVA) model was performed. In this model, BMD was treated as outcome variables; age and weight (or BMI) were treated as covariates; and residence (urban or rural) was the factor. Interactions between age and BMI or age and residence variable were also considered in the model. Estimates of the model parameters were based on the least square method via the SPSS version 9.0 (SPSS, Inc, Chicago).
Results
Demographic characteristics
After excluding 25 subjects, data from 847 subjects (340 men and 507 women) were analysed. There was no significant difference between urban and rural subjects with respect to age or sex distribution. The mean age was 49 and 50 years old in men and women, respectively. However, urban men had higher weight and greater height than rural men (P < 0.001), whereas urban women had a greater height (P < 0.001) but equivalent weight (P = 0.72) compared with rural women (Table 1).
Table 1 Characteristics of study subjects
Urban (Bangkok) Rural (Khon Kean) Mean Difference (95% CI) P value
Men
Number of Subjects 159 181
Age (years) 49.6 ± 17.5 49.1 ± 17.1 0.5 (-3.2, 4.2) 0.800
Body weight (kg) 64.3 ± 11.1 58.2 ± 8.8 6.1 (3.0, 8.1) <0.001
Height (cm) 165.5 ± 6.3 161.2 ± 5.9 4.3 (3.0, 5.6) <0.001
Body Mass Index (kg/m2) 23.4 ± 3.6 22.4 ± 2.8 1.0 (0.3, 1.7) 0.003
Bone Mineral Density (g/cm2)
Femoral neck 0.87 ± 0.16 0.96 ± 0.18 -0.09 (-0.13, 0.05) <0.001
Lumbar spine 1.12 ± 0.17 1.11 ± 0.16 0.01 (-0.03, 0.04) 0.64
Women
Number of Subjects 252 255
Age (years) 50.4 ± 15.1 50.6 ± 15.9 -0.2 (-2.9, 2.4) 0.853
Body weight (kg) 55.5 ± 8.9 55.9 ± 10.5 -0.4 (-2.0, 1.4) 0.718
Height (cm) 154.7 ± 5.4 152.1 ± 5.2 2.6 (1.6, 3.5) <0.001
Body Mass Index (kg/m2) 23.2 ± 3.8 24.1 ± 4.0 -0.9 (-1.5, -0.1) 0.017
Bone Mineral Density (g/cm2)
Femoral neck 0.79 ± 0.13 0.87 ± 0.19 -0.08 (-0.11, -0.05) <0.001
Lumbar spine 1.05 ± 0.18 1.01 ± 0.21 0.04 (-0.11, 0.08) 0.16
All values are shown in mean ± standard deviation (SD).
In the entire sample, higher weight was associated with higher BMD in men (r = 0.13, P = 0.017 for femoral neck, and r = 0.37, P < 0.001 for lumbar spine) and in women (r = 0.33, P < 0.001 for femoral neck, and r = 0.33, P < 0.001 for lumbar spine). On the other hand, advancing age was associated with a significant reduced BMD in men (r = -0.53, P < 0.001 for femoral neck, and r = -0.15, P = 0.007 for lumbar spine) and women (r = -0.63, P < 0.001 for femoral neck, and r = -0.60, P < 0.001 for lumbar spine).
However, the strength of relationship between age and BMD in urban subjects was less pronounced than in rural subjects, such that rural women had a higher cross-sectional "rate of bone loss" than urban women, particularly at the femoral neck. For example, in women, each 5-year increase in age was estimated to associate with a 2.1% and 1.2% decrease in femoral neck BMD for rural and urban group, respectively; in men, the respective rate of decrease was 1.3% and 0.8%. As a result, among those aged 50+ years, BMD in rural subjects tended to be lower than (or converged to) BMD in urban subjects (Figure).
Figure 1 Interaction effects of age and residence variable on bone mineral density at the femoral neck in men (A) and women (C), and at the lumbar spine in men (B) and women (D).
Urban-rural difference in BMD
In both sexes, after adjusting for age and weight, BMD in rural individuals was significantly higher than in urban individuals. For instance, femoral neck BMD in rural men and women was 0.22 and 0.23 g/cm2 significantly higher (P < 0.001) than in urban men and women, respectively; but the difference was lower for the lumbar spine BMD (0.12 g/cm2 in men, P = 0.017 and 0.05 g/cm2 in women, P = 0.293). The statistical significance of the age-by-residence interaction term in the ANCOVA model suggested that the urban-rural difference in BMD decreased with advancing age (Table 2).
Table 2 Effects of age, weight and residence on bone mineral density: estimates of parameters of the analysis of covariance stratified by sex and BMD site
Effect Estimate ± SE P value
Men
Femoral neck BMD
Age (+5 yr) -0.020 ± 0.003 <0.001
Weight (+5 kg) 0.015 ± 0.004 <0.001
Residence (Rural) 0.222 ± 0.046 <0.001
Age × Residence (Rural) -0.012 ± 0.004 0.008
Lumbar spine BMD
Age (+5 yr) -0.001 ± 0.003 0.874
Weight (+5 kg) 0.030 ± 0.004 <0.001
Residence (Rural) 0.122 ± 0.051 0.017
Age × Residence (Rural) -0.010 ± 0.004 0.048
Women
Femoral neck BMD
Age (+5 yr) -0.026 ± 0.002 <0.001
Weight (+5 kg) 0.026 ± 0.003 <0.001
Residence (Rural) 0.233 ± 0.034 <0.001
Age × Residence (Rural) -0.015 ± 0.003 <0.001
Lumbar spine BMD
Age (+5 yr) -0.033 ± 0.003 <0.001
Weight (+5 kg) 0.031 ± 0.003 <0.001
Residence (Rural) 0.047 ± 0.045 0.293
Age × Residence (Rural) -0.009 ± 0.004 0.036
SE, Standard Error.
Notes: Since height was not a significant factor in the analysis of covariance model, it was removed from the final model with no significant change of the results.
Further analyses stratified by sex, age group, and BMI category indicated that the urban-rural difference in femoral neck BMD was more pronounced in the younger age group (< 50 years old) and higher BMI (≥ 25 kg/m2). This trend was consistent for men and women. However, for lumbar spine BMD, no significant urban-rural difference was observed in most subgroups, with the exception of women aged ≥ 50 years and BMI < 25 kg/m2 in whom BMD was lower in the rural group compared to the urban group (Table 3).
Table 3 Bone mineral density in urban and rural men and women by age group and body mass index
(a) Lumbar spine BMD
Sex Age (years) BMI (kg/m2) Bone mineral density (g/cm2)
Urban Rural Mean difference and 95% CI
Men < 50 < 25 0.94 ± 0.16 1.05 ± 0.16 -0.11a (-0.16, -0.06)
≥ 25 0.89 ± 0.12 1.04 ± 0.17 -0.15b (-0.26, -0.03)
≥ 50 <25 0.80 ± 0.15 0.86 ± 0.15 -0.06b (-0.12, -0.01)
≥ 25 0.83 ± 0.11 0.92 ± 0.15 -0.09b (-0.17, -0.01)
Women < 50 < 25 0.85 ± 0.11 0.97 ± 0.13 -0.12a (-0.16, -0.09)
≥ 25 0.92 ± 0.11 1.04 ± 0.13 -0.12b (-0.20, -0.05)
≥ 50 <25 0.70 ± 0.11 0.71 ± 0.15 -0.01 (-0.05, 0.03)
≥ 25 0.76 ± 0.11 0.82 ± 0.15 -0.06b (-0.11, -0.01)
(b) Femoral neck BMD
Sex Age (years) BMI (kg/m2) Bone mineral density (g/cm2)
Urban Rural Mean difference and 95% CI
Men < 50 < 25 1.12 ± 0.14 1.13 ± 0.15 -0.01 (-0.06, 0.04)
≥ 25 1.11 ± 0.09 1.14 ± 0.16 -0.03 (-0.13, 0.08)
≥ 50 < 25 1.05 ± 0.18 1.06 ± 0.16 -0.01 (-0.07, 0.05)
≥ 25 1.21 ± 0.19 1.19 ± 0.20 0.02 (-0.11, 0.14)
Women < 50 < 25 1.14 ± 0.13 1.13 ± 0.14 0.01 (-0.04, 0.04)
≥ 25 1.21 ± 0.15 1.15 ± 0.13 0.06 (-0.02, 0.15)
≥ 50 < 25 0.92 ± 0.14 0.83 ± 0.19 0.09b (0.03, 0.14)
≥ 25 1.02 ± 0.17 0.97 ± 0.21 0.05 (-0.01, 0.13)
Statistical significance at aP < 0.001 and bP < 0.05. Statistical significance is indicated by bold-faced letters.
Discussion
Osteoporosis has emerged as one of the most common diseases in the aged population, and represents one of the most significant public health problems in Asia [2,16,17]. A consistent trend in osteoporosis is that the incidence of fracture is higher in developed countries than in developing countries; and in any country, the incidence is higher in urban than in rural communities [5-11]. While many factors are hypothesized to be responsible for this trend, BMD is thought to be a primary determinant, because it is the most consistent and robust predictor of fracture risk [1,11].
In the present population-based study, we have shown that BMD in a rural Thai population was significantly higher than in urban population, particularly at femoral neck. The magnitude of difference was more than 1 standard deviation which is clinically relevant. It is difficult to compare the present study's results to previous studies' due to differences in methodology and study design. For instance, Sundberg et al [12] reported that lumbar spine BMD (measured by DXA) in rural adolescents was significantly higher than that in urban adolescents, but there was no significant difference in femoral neck BMD. Furthermore, a study from Southern Sweden suggested that bone mass at the forearm (measured by single-photon absorptiomety) in rural population was significantly higher than in urban population and the difference was more pronounced when comparing a true urban population who had lived their entire life in a city with a true rural population who had never lived in a city [13]. A study from Eastern Poland found that the mean lumbar spine BMD values in every age range were higher in rural population than in urban population, but the difference was not statistically significant [14]. Taken together, these results including ours, suggest that rural subjects tend to have higher BMD than in urban subjects.
The present study's data and design can not elucidate any underlying factors that are responsible for the difference but some propositions could be put forward. The urban-rural difference in femoral neck BMD could be due to the difference in the peak of bone mass levels. In this study, both rural men and women aged between 20 and 30 years had significantly higher BMD than urban counterparts. For example, young rural men and women had significantly higher than urban subjects (1.17 vs. 1.03 g/cm2, [95% CI: 0.07–0.22] in men and 1.02 vs. 0.86 g/cm2, [95% CI: 0.10–0.22] in women). This finding was partially consistent with a previous study [12] and could be explain the fact that the urban-rural difference was mainly found in younger age groups.
This study also found that the urban-rural difference in femoral neck BMD decreased with advancing age. The difference may be attributed to the difference in physical activity between the two populations. Rural populations were generally more physically active than urban populations [18,19]. The rural population in this study was mainly farmers who spend most of their time in rice field long hours of physical activity.
However, the difference was sex- and site- dependent. The difference in femoral neck BMD was much more pronounced than that in lumbar spine and this was more transparent before the age of 50 in men and before the menopause in women. After this age the difference was no longer significant. The data suggested that the rate of bone loss in rural population may be more rapid than in urban population. However, this finding was not consistent with a previous study which demonstrated that the rate of bone loss was higher in urban population compared with rural population [13]. The reason(s) for the higher rate of bone loss in rural population in this study is unknown, but low dietary calcium intake could be a contributory factor [20-22].
The present findings must be interpreted in the context of a number of potential strengths and weaknesses. The data were obtained from a large and well-defined rural vs. urban area, which allowed the rural and urban difference to be reliably delineated. The study subjects were Thai, among whom, cultural backgrounds and environmental living conditions are different from Western populations. Thus care should be taken when extrapolating these results to other populations.
Conclusions
These data have demonstrated that femoral neck BMD in rural men and women was higher than their counterparts in urban areas. This difference could potentially explain part of the urban-rural difference in fracture incidence.
List of abbreviations
All abbreviations are defined in the text.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
Chatlert Pongchaiyakul had an active role in the conduct of this study, obtained and analysed data, and drafted the manuscript. Tuan V Nguyen was involved in the conceptual discussion of this study, and had an active role in data analysis, drafting of the manuscript. Vongsvat Kosulwat, Nipa Rojroongwasinkul, and Somsri Charoenkiatkul had an active role in the study design, and was involved in the conceptual discussion. Rajata Rajatanavin conducted and established this study. All authors contributed to the last version of the manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgments
The study was supported by Thailand Research Fund. The first author would like to acknowledge the Faculty of Medicine, Khon Kaen University for grant to Garvan Institute of Medical Research. We also thank Mrs. Ratchanee Chotmongkol, RN and Mrs. Choowong Pongchaiyakul, RN for data collection. TVN is supported by a Australian National Health and Medical Research Council grant.
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| 15693996 | PMC549192 | CC BY | 2021-01-04 16:32:05 | no | BMC Musculoskelet Disord. 2005 Feb 4; 6:5 | utf-8 | BMC Musculoskelet Disord | 2,005 | 10.1186/1471-2474-6-5 | oa_comm |
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BMC NeurosciBMC Neuroscience1471-2202BioMed Central London 1471-2202-6-61568659810.1186/1471-2202-6-6Research ArticleThe progressive nature of Wallerian degeneration in wild-type and slow Wallerian degeneration (WldS) nerves Beirowski Bogdan [email protected] Robert [email protected] Diana [email protected] Daniela S [email protected] Klaus [email protected] Richard R [email protected] Michael P [email protected] Center for Molecular Medicine Cologne (CMMC) and Institute for Genetics, University of Cologne, Zuelpicher Strasse 47, D-50647 Cologne, Germany2 Department of Anatomy I, University of Cologne, Joseph-Stelzmann Strasse 9, D-50931 Cologne, Germany3 Division of Neuroscience, University of Edinburgh, 1 George Square, Edinburgh, EH8 9JZ, UK4 Babraham Institute, Babraham, Cambridge CB2 4 AT, UK2005 1 2 2005 6 6 6 29 9 2004 1 2 2005 Copyright © 2005 Beirowski et al; licensee BioMed Central Ltd.2005Beirowski 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 progressive nature of Wallerian degeneration has long been controversial. Conflicting reports that distal stumps of injured axons degenerate anterogradely, retrogradely, or simultaneously are based on statistical observations at discontinuous locations within the nerve, without observing any single axon at two distant points. As axon degeneration is asynchronous, there are clear advantages to longitudinal studies of individual degenerating axons. We recently validated the study of Wallerian degeneration using yellow fluorescent protein (YFP) in a small, representative population of axons, which greatly improves longitudinal imaging. Here, we apply this method to study the progressive nature of Wallerian degeneration in both wild-type and slow Wallerian degeneration (WldS) mutant mice.
Results
In wild-type nerves, we directly observed partially fragmented axons (average 5.3%) among a majority of fully intact or degenerated axons 37–42 h after transection and 40–44 h after crush injury. Axons exist in this state only transiently, probably for less than one hour. Surprisingly, axons degenerated anterogradely after transection but retrogradely after a crush, but in both cases a sharp boundary separated intact and fragmented regions of individual axons, indicating that Wallerian degeneration progresses as a wave sequentially affecting adjacent regions of the axon. In contrast, most or all WldS axons were partially fragmented 15–25 days after nerve lesion, WldS axons degenerated anterogradely independent of lesion type, and signs of degeneration increased gradually along the nerve instead of abruptly. Furthermore, the first signs of degeneration were short constrictions, not complete breaks.
Conclusions
We conclude that Wallerian degeneration progresses rapidly along individual wild-type axons after a heterogeneous latent phase. The speed of progression and its ability to travel in either direction challenges earlier models in which clearance of trophic or regulatory factors by axonal transport triggers degeneration. WldS axons, once they finally degenerate, do so by a fundamentally different mechanism, indicated by differences in the rate, direction and abruptness of progression, and by different early morphological signs of degeneration. These observations suggest that WldS axons undergo a slow anterograde decay as axonal components are gradually depleted, and do not simply follow the degeneration pathway of wild-type axons at a slower rate.
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Background
Wallerian degeneration, the characteristic degeneration sequence of nerve fibres separated from their cell bodies, was described by Waller in 1850 [1,2]. Following various forms of axon injury this rapid degeneration process begins with degradation of axoplasm and axolemma accompanied by development of axonal and myelin debris that is subsequently removed by Schwann cells and invading macrophages. In recent years it became apparent that Wallerian degeneration is initiated by an active process intrinsic to the axon that shares some principles with apoptosis [3-7]. These discoveries were firmly established by studies on the slow Wallerian degeneration (WldS) mutant mouse, in which this active process seems to be turned off. Accordingly, this mutant shows a tenfold delay in Wallerian degeneration and synapse breakdown after experimental nerve injury [8,9]. The delay of Wallerian degeneration is an intrinsic property of the axon suggesting that glial cell and macrophage changes are secondary events [3]. The underlying trait is carried by the autosomal dominant mutation WldS that arose by spontaneous mutation [6,10]. Genetic analysis has shown that the WldS mutation on mouse chromosome 4 comprises a stable 85-kb tandem triplication [11,12] encoding the N-terminal 70 amino acids of the multiubiquitination factor Ube4b fused in frame to the nuclear NAD producing enzyme nicotinamide mononucleotide adenylyltransferase 1 (Nmnat 1). Correspondingly, WldS mice express a novel chimeric protein (WldS protein) in neuronal nuclei that has full Nmnat 1 activity but seemingly no Ube4b function since the expressed N-terminus lacks ability for multi-ubiquitination within the ubiquitin-proteasome system (UPS) [13,14], the molecular machinery responsible for a major pathway of cellular protein catabolism. Either only one or both parts of the nuclear WldS protein could be responsible for the phenotype through a nuclear process that has an indirect effect on the axon although recent results foster that the WldS mechanism is likely to involve a gain of function of NAD synthesis [15]. However, inhibition of a specific step of the ubiquitin proteasome system or another modifying role of the N-terminal domain of the WldS protein remains a possibility [16,17].
From a clinical point of view not only traumatic disorders such as nerve, spinal cord or head injury result in Wallerian degeneration [18] but it is now broadly accepted that Wallerian degeneration is mechanistically related to axon loss in many neurodegenerative disorders such as amyotrophic lateral sclerosis, Charcot-Marie-Tooth disease, toxic neuropathy, multiple sclerosis, and possibly Alzheimer's Disease and Parkinson's Disease [7,14,19-23]. Protection from neurodegenerative disorders by WldS is currently under intense investigation. The neuroprotective mutation alleviates diverse PNS axon disorders, including dysmyelination and dying back neuropathy in P0-/- mutants [24], motor neuropathy in pmn mutants [25] and axon degeneration in Vincristine and Taxol toxicity [26-28]. More recently WldS was reported to attenuate pathology in acute CNS lesions caused by stroke [29], Parkinson's disease [30], and in gracile axonal dystrophy (gad) mice, a CNS axonal spheroid pathology [31]. A better understanding of the biological mechanism of delayed axon degeneration in neurological diseases would help to develop therapeutic methods to target axon degeneration.
Despite research extending over more than 150 years and its frequent use as tool to detect interneuronal connections in the CNS since the time of Cajal, fundamental issues of Wallerian degeneration remain unresolved and controversial even on a purely morphological level. Among these is the spatiotemporal pattern of Wallerian degeneration along the separated nerve stump. Understanding the exact pattern of spread should provide additional insights into the mechanisms of axon death and may indicate strategies to alter Wallerian degeneration in neurological disease. Shortly after the pioneering investigations of Waller, and in the following decades, there has been much debate as to whether degeneration occurs in an anterograde direction, a retrograde direction or simultaneously along the separated nerve stump axons (reviewed historically in [32-34]).
The controversy over the directionality of Wallerian degeneration has arisen partly because appropriate methods to follow axons over considerable distances did not exist until recently but also because the course of Wallerian degeneration varies with many experimental factors. Thus, spatiotemporal evolution of Wallerian degeneration depends on the laboratory animals used [32,34-36], on the age of the animals [32,37], on the neuroanatomical locus of study (CNS vs. PNS) [35,38,39], on the type of fibre analyzed (e.g. myelinated vs. unmyelinated, thick vs. thin axons) [34,39,40], on the type of lesion (axotomy, crush, ligature, intoxication etc.) [34,41,42], on the length of the remaining distal nerve stump [32,43-45], on the criteria used for identification of fibre degeneration (e.g. myelin breakdown, axon disintegration, decay of electrophysiological activity) [32,33,39], on environmental factors (e.g. temperature) [6,32,34,36] and many more. For example, in more modern experimentation from the last decades, Lubinska [46] demonstrated with the help of the teased fibre technique on myelinated fibres of the rat phrenic nerve that axonal breakdown into myelin ovoids spreads anterogradely along axons separated from their cell bodies at velocities correlated with fibre diameter and internodal length. George and Griffin [47] also found anterograde spread of axonal disintegration along dorsal columns of the rat following L4L5L6 radiculotomy. Contrary to these views, Lunn and colleagues [48] showed by means of silver-stained wholemount preparations from the peripheral nerve stump that degeneration after crushing proceeds in a retrograde direction. They also proposed a retrograde progression after sectioning, freezing or ligaturing, although this was less clear because degeneration was more complete at the time-point sampled. Electrophysiological approaches suggested that the spread of failure of conduction in degenerating mammalian nerves runs from proximal to distal after nerve transection [49]. In cell culture studies using dorsal root ganglions (DRG) explants membrane beading, blebbing, fragmentation and Annexin V staining progressed along interrupted neurites in an anterograde direction with a rate comparable to that of slow axonal transport [50]. Taking secondary changes after axon disintegration into consideration, Bendszus and colleagues [51] tracked an anterograde spatiotemporal course of macrophage infiltration after acute peripheral nerve injury in rats. While most of the above mentioned investigators concluded a progressive nature of Wallerian degeneration from the appearance of degeneration gradients along injured nerves other authors did not observe any evidence for an anterograde or retrograde pattern of axonal degeneration [52,53].
In view of the contradictions and anomalies in the previous literature, we have reassessed the directionality of Wallerian degeneration using a recently introduced technique to visualize individual fluorescent axons over cm-long distances during degeneration [54]. This was made possible by using nerves from transgenic mice expressing Yellow Fluorescent Protein (YFP) in representative subsets of axons, which presents a simplified image of peripheral nerve [55]. No method existed until recently to follow up individual axons undergoing Wallerian degeneration over a considerable length. Here we compared the progression of Wallerian degeneration along single axons traced over lengths of approximately 2.5 cm. Specifically, we have tested a key prediction of all progressive models: that it should be possible to image axons degenerated at one end but not at the other. We detected such axons and showed that Wallerian degeneration in wild-type peripheral nerve is a rapid, asynchronous, progressive and wave-like process that can change its orientation depending on the lesion type.
To our knowledge there have been no reports about the spatiotemporal pattern of the much-delayed axon degeneration in peripheral WldS nerves that could yield important clues for understanding classic Wallerian degeneration. Therefore, we also report a detailed characterisation of injury-induced axon degeneration in slow Wallerian degeneration mutant mice in order to determine whether axons degenerate with a similar spatial evolution to that in wild-type mice, but in "slow motion", or whether the process is fundamentally distinct. We report a series of differences between axon degeneration in wild-type and WldS mice, suggesting that irreversible injury in axons where Wallerian degeneration is blocked eventually leads to a different pathway of degeneration.
Results
YFP labelled wild-type axons fragment abruptly and asynchronously after a latent phase of approximately 36–44 h
In preliminary experiments we used conventional light and electron microscopy to investigate whether Wallerian degeneration is progressive in wild-type mouse peripheral nerves. We were never able to find any significant gradients of degeneration along injured nerves that were processed with these traditional methods (data not shown). We then looked for signs of progression in localised observations of degenerating YFP-H nerves because fragmentation of YFP-labelled axons from these mice corresponds to granular disintegration of axoplasm as well as myelin ovoid formation and YFP positive axons represent the whole myelinated axon population [54]. Axonal fragmentation was first detected at both the proximal and distal ends of the distal nerve stump 37 h after transection (Fig. 1A, B) and 40 h after crush injury (Fig. 1C, D). 42 h after transection (Fig. 1E, F) and 44 h following crush lesion (Fig. 1G, H) the majority of axons in both locations were fragmented by assessment with conventional fluorescence microscopy. By direct comparison of the separate images of proximal and distal sites in the distal nerve stumps excised at all further time points no apparent difference was visible in the proportion of fragmented axons (data not shown).
Figure 1 After a latency period Wallerian degeneration following cut and crush injury starts abruptly in single axons and involves total fragmentation of axons within few hours A-D: Conventional fluorescence micrographs of a ~2.5 cm long peripheral nerve stump (sciatic-tibial nerve segment) wholemount preparation at the proximal (A) and distal site (B) 37 h after cut injury with few individual fluorescent axons broken into fragments. A small number of axons fragmented at the proximal (C) and distal site (D) of a peripheral nerve stump wholemount preparation could also be detected 40 h following crush injury. E-H: Conventional fluorescence micrographs of a ~2.5 cm long peripheral nerve stump (sciatic-tibial nerve segment) wholemount preparation at the proximal (E) and distal site (F) 42 h after cut injury with most YFP labelled axons fragmented. A similar picture with a majority of axons degenerated is evident at the proximal (G) and distal end (H) of a peripheral nerve stump wholemount preparation 44 h after crush injury. YFP fluorescence has been pseudo-coloured green with the applied imaging software (MetaVue, Universal Imaging Corporation). Magnification: 100 ×
Wallerian degeneration in wild-type nerves progresses anterogradely after nerve transection and retrogradely after nerve crush
The failure to observe any gradient of degeneration in the above experiment does not mean that Wallerian degeneration is not progressive. It could propagate so rapidly that it was not detectable by this method, or a gradient might not be detectable because of the considerable statistical noise of the highly asynchronous process. In order to investigate these possibilities we turned to confocal tracing of individual axons in long wholemount YFP-H nerve segments. At 37 h after transection we found 2.0 % of fluorescent axons with extensive proximal fragmentation and intact distal regions indicating an anterograde gradient of Wallerian degeneration in these axons (Fig. 2A). Around 40 h the proportion of distal axon stumps degenerated at their proximal but not distal ends peaked at 9.3%. An example is presented in Fig. 3. Of the remaining axons, 77.5 % were intact and 13.2 % were entirely fragmented without an apparent gradient. 42 h after cut injury the proportion of partially fragmented axons decreased to 4.4 % and after 48 h we only found axons that were fragmented over the whole length. In summary, at all investigated time points partially degenerated axons (mean: 5.3 %) always exhibited an anterograde spread of Wallerian degeneration after nerve transection.
Figure 2 Quantification of fluorescent axons in wholemount YFP-H peripheral nerve stumps after cut and crush injury at different time points. Depending on the extent of fragmentation, YFP positive axons from peripheral nerve stumps were assigned to the group "intact", "entirely fragmented", "fragmented with anterograde gradient" or "fragmented with retrograde gradient". The chart presents means and standard deviations. A: All partially fragmented axons that could be identified at the time points between 37 h and 42 h after cut injury were fragmented at the proximal end of the distal axon stump but not further distal, indicating an anterograde gradient of Wallerian degeneration ("fragmented with anterograde gradient"). A maximum of 9.3 % YFP positive axons with anterograde fragmentation appeared 40 h after cut injury. B: All partially fragmented axons that could be identified at the time points between 40 h and 44 h after crush injury were fragmented at their distal ends but not further proximal indicating a retrograde gradient of Wallerian degeneration ("fragmented with retrograde gradient"). A maximum of 7.2 % of YFP positive axons with retrograde fragmentation appeared 44 h after crush injury.
Figure 3 Wallerian degeneration proceeds in anterograde direction along individual axons after cut injury. Confocal composite picture showing seven consecutive lengths (from top to bottom in overview) of the proximodistal course of an individual YFP labelled axon within a distal nerve stump 40 h after transection demonstrating an anterograde progression of axon fragmentation. Note that this axon has fragmented in its proximal end (upper inset) but not in its distal end (lower inset). Axonal fragments are clearly demarcated by fluorescence interruptions (arrows in upper inset). YFP fluorescence has been pseudo-coloured yellow with the applied confocal imaging software (Biorad LaserSharp 2000). Scale bar: 500 μm
In contrast, all partially fragmented axons after crush injury at all investigated timepoints were fragmented in distal tibial nerve but not at the proximal end of the distal stump (Fig. 2B). Once again, only a small minority (mean: 5.0%) could be detected in this state at any one time. Partially fragmented axons first appeared at 40 h (1.6 % of axons) and the proportion peaked at 44 h (7.2 %). A representative example is shown in Fig. 4. The remaining 92.8 % of YFP labelled axons at 44 h was entirely fragmented without an apparent gradient. At all earlier investigated time points axons with a retrograde gradient of fragmentation were also observed but in lower proportions and after 48 h we only found axons that were fragmented over the whole length.
Figure 4 Wallerian degeneration proceeds in retrograde direction along individual axons after crush injury. Confocal composite picture showing seven consecutive lengths (from top to bottom in overview) of the proximodistal course of an individual YFP labelled axon within a peripheral nerve stump 44 h after crush injury displaying a retrograde progression of axon fragmentation. Note that this axon has fragmented in its distal end (lower inset) but not in its proximal end (upper inset). Axonal fragments are clearly demarcated by fluorescence interruptions (arrows in lower inset). YFP fluorescence has been pseudo-coloured yellow with the applied confocal imaging software (Biorad LaserSharp 2000). Scale bar: 500 μm
Summarising all these quantification results of cut and crush lesions at time points where partially fragmented fibres were observed, on average 94.8 % of all axons were either completely intact or fragmented and 5.2 % showed a gradient of Wallerian degeneration, whose orientation depended on the lesion type.
A wave of axonal fragmentation propagates rapidly along individual wild-type axons and the axon population degenerates asynchronously
To study further the gradients of axonal fragmentation both after cut and crush injury (Fig. 3, 4) we quantified the number of axonal breaks along partially and totally fragmented axons. Firstly, this was a way to distinguish between a locally restricted wave of fragmentation such that entirely intact lengths of axon suddenly change into entirely fragmented lengths, and a more gradual fragmentation process that would result in a few interruptions that become more frequent further along the axon. Secondly, by this approach we tried to get insight on the question of whether axons assigned into the group "entirely fragmented" continue to break into smaller fragments leading to a gradient of fragment size along the nerve.
Concerning the first question we found that Wallerian degeneration progresses as a wave, with the wave front defining the point to which fragmentation had spread along the axon. In partially fragmented axons separated from the cell body by transection or proximally compressed by crush lesion, axon regions with no features of degeneration abruptly change into segment lengths with marked breakdown within a transition zone of less than one millimeter (Fig. 5, 6). A short region of intact axon immediately ahead of the wavefront becomes increasingly vacuolated as the wave front approaches, and a newly formed break appears as though a vacuole has filled the entire axon diameter, completely interrupting it (Fig. 5). The degeneration wave sequentially affects adjacent regions of the fibre and different lesions cause this wave to progress in different directions.
Figure 5 Wave front of Wallerian degeneration in a YFP labelled wild-type axon after crush lesion A: The partially degenerated axon that is bracketed was identified in a 44 h crushed wild-type nerve. All more distal regions of this axon are fragmented and all more proximal regions are intact (data not shown). B-D: higher magnification of this axon from (A) around the transition point between intact and fragmented regions. (D) shows the most proximal breakpoint in this nerve and the inferred retrograde direction of propagation of Wallerian degeneration. Immediately proximal to the breakpoint severe vacuolation occupies almost the entire axon thickness. Slightly further proximal in (C), there are also severe YFP negative vacuoles and fragmentation appears imminent at two points (asterisks). Further proximal still in (B), the degree of vacuolation decreases. YFP fluorescence has been pseudo-coloured green with the applied confocal imaging software (Zeiss LSM Software Release 3.2). Scale bars: 50 μm (A) and 10 μm (B, C, D)
Figure 6 Axonal fragmentation progresses asynchronously as a localised wave along individual axons in a anterograde or retrograde direction A-D: Graphs showing the number of axonal breaks along individual YFP labelled axons with anterograde gradient of fragmentation in relation to the distance in mm from the transection point 37 h (A), 40 h (B), 41 h (C) and 42 h (D) after cut lesion. Note that with increasing distance from the transection, axon lengths with marked fragmentation abruptly change into lengths with no or just a few axonal breaks, indicating that Wallerian degeneration progresses with a localised fragmentation wave front. Additionally note the variable localisation of the fragmentation wave front along different axons at one timepoint representing the asynchronity of Wallerian degeneration among the axon population. E-H: Graphs showing the number of axonal breaks along individual YFP labelled axons with retrograde gradient of fragmentation in relation to the distance in mm from the crush point 40 h (E), 42 h (F), 43 h (G) and 44 h (H) after crush lesion. Note that with increasing distance from the crush point axon lengths without any features of fragmentation abruptly change into lengths containing axonal breaks. Asynchronity of progression of Wallerian degeneration along individual axons is also apparent after crush lesion.
In order to determine whether the anterograde and retrograde fragmentation wave runs at the same velocity along the axon we next estimated the rate of progression. As the average axon length measured was 24 mm and the majority of axons must have entirely fragmented between 41 h and 42 h after transection (significant difference between percentage of entirely degenerated axons at 42 h and entirely plus partially degenerated axons at 41 h in Student t-test) (Fig. 2A), the minimal velocity for the degeneration wave is 24 mm/h. Analogously, after crush lesion the calculated velocities of the retrograde degeneration wave is also at least 24 mm/h (Fig. 2B), as the majority of axons fragmented between 43 h and 44 h after the lesion (significant difference between entirely degenerated axons at 44 h and entirely plus partially degenerated axons at 43 h in Student t-test). Thus, the rates of Wallerian degeneration progression are similar or possibly even equal in these opposite directions, but with a faster initiation of the fragmentation wave after transection.
We then tested whether our crush lesions interrupted axon continuity as in nerve transection, because a failure to do so could underlie the different direction of propagation in crushed nerves (see Discussion). In fluorescent wholemount preparations of crushed nerve segments we found continuous longitudinal YFP signals across the crush site, and in teased fibre bundles of osmificated nerve segments after crush injury, a majority of fibres remained continuous across the crush site (see additional data file Add Fig 1.pdf). These data are consistent with the axonal membrane remaining intact after 30 sec nerve crush, unlike that of a transected nerve.
The observation that at early time points after cut and crush injury some axons had already fragmented or started to fragment while the majority is still intact (Fig. 1, 2) together with the variable localisation of the fragmentation wave front along different axons at one time point (Fig. 6) indicates that Wallerian degeneration is asynchronous among the population of axons in a peripheral nerve. This probably reflects both differences in the timing of onset of degeneration and varying velocities of propagation in axons of different thickness that cannot be distinguished by our imaging approaches. Furthermore, the observation that the transition between intact and degenerated regions can be 19–21 mm distal to the crush within 44 h rules out regeneration as a possible source of error.
Quantification of axonal breaks along entirely fragmented axons (Fig. 7) revealed that fragmentation is homogenously dispersed through the whole fibre distance and no gradient is detectable. Thus, once fragmentation begins it is rapidly completed. All these findings obtained in YFP-H mice are summarized schematically in Fig. 13.
Figure 7 The Wallerian degeneration wave runs through individual axons and leaves uniformly degenerated fibres without gradients of fragmentation A: Confocal composite picture showing six consecutive lengths (from top to bottom in overview) of the proximodistal course of an individual completely fragmented YFP labelled axon within a peripheral nerve stump 42 h after transection injury without any features of a degeneration gradient. Note that this axon has fragmented in its proximal (upper inset) and distal (lower inset) site equally. Axonal fragments are clearly demarcated by fluorescence interruptions (arrows in insets). YFP fluorescence has been pseudo-coloured yellow with the applied confocal imaging software (Biorad LaserSharp 2000). Scale bar: 500 μm B, C: Graphs showing the number of axonal breaks along 10 YFP labelled axons without apparent gradient of fragmentation in relation to the distance in mm from the cut point 37 h to 42 h after cut lesion. Means and standard deviations are presented in (B). Note that axonal breaks and therefore fragmentation is homogenously dispersed through the axon lengths. D, E: Graphs showing the number of axonal breaks along 10 YFP labelled axons without apparent gradient of fragmentation in relation to the distance in mm from the crush point 40 h to 44 h after crush lesion. Means and standard deviations are presented in (E). Note that axonal breaks and therefore fragmentation is homogenously dispersed through the axon lengths.
Figure 13 Schematic illustration depicting the spatiotemporal pattern of axon degeneration after cut and crush injury of a wild-type and a WldS peripheral nerve. Each yellow line represents an individual YFP positive axon in wild-type (A, B) and WldS (C, D) peripheral nerves. Accounting for wild-type peripheral nerves, firstly, both after transection (A) and crush injury (B) axonal fragmentation progresses as a localised wave quickly within a matter of few hours over the individual axon. Thereby, the abrupt shift between preserved and fragmented axon distances along partially fragmented axons represents the wave front. The processes differ only in direction with an anterograde course after cut and a retrograde course after crush lesion. Secondly, axonal fragmentation in the YFP positive axon population is asynchronous with some intact and others entirely or partially fragmented in one nerve at one time point. Thirdly, axonal breaks are dispersed homogenously along totally fragmented fibres. In contrast, in WldS peripheral nerves, firstly, both after transection (C) and crush (D) injury axonal degeneration progresses in anterograde direction with a velocity similar to that of slow axonal transport. Secondly, the gradients of axon degeneration are uniform with gradual decrease of degenerative changes along the axon from proximal to distal. Thirdly, degeneration happens broadly synchronously among the population of WldS axons. Fourthly, formation of end bulbs with subsequent swellings at the proximal ends of WldS axons can be observed especially after crush lesion but also occasionally after transection lesion.
In contrast to wild-type nerves injured WldS sciatic and tibial nerves degenerate anterogradely independent of the lesion type
We then extended these studies to WldS axons, already known to survive 14 days after transection lesion [13], using light and electron microscopy after prolonged lesion times of 15, 20, 25 and 30 days. In contrast to the analogous experiment in wild-type mice, a significant difference in axon preservation rate was immediately apparent between the proximal sciatic nerve and distal tibial nerve. 20 days after high sciatic nerve transection, 28.1 % of myelinated axons were structurally preserved a few millimetres distal to the lesion site in light and electron microscopy (Fig. 8A, B, C) but the most distal part of the tibial nerve showed ultrastructural preservation in 85.0 % of axons (Fig. 8A, D, E). Likewise, at all further time points beside 20 days (15, 25 and 30 days) after transection lesion we found more intact axons in distal tibial nerve than in proximal sciatic nerve close to the point of injury (Fig. 8A). Overall, these results clearly indicate anterograde progression of axon degeneration along transected WldS peripheral nerves.
Figure 8 Light and electron microscopy revealed an exclusively anterograde gradient of axon degeneration in transected and crushed WldS sciatic/tibial nerves after prolonged lesion times A, F: Quantification of axon preservation at proximal and distal ends of the peripheral nerve stump after transection (A) and crush (F) injury exposed exclusively anterograde gradients of axon degeneration after 15 to 30 days following injury (15 d lesion time-point only after transection injury). Differences in the number of protected axons between the proximal and distal end of the stump were maximum after 20 days and more moderate prior or later to that, correspondingly. Remarkably, after 30 days following crush lesion considerable numbers of totally intact axons could be counted (63.5 % in distal tibial nerve) pointing to a weaker effect of compression over transection and generally to the longevity of distal WldS axons. B-E: Light microscopic images (B, D) and corresponding electron micrographs (C, E) taken from the proximal (B, C) and distal (D, E) end of the peripheral nerve stump after 20 days following transection lesion. At the proximal end (sciatic nerve) 28.1 % myelinated axons were structurally preserved while at the distal end (tibial nerve) we could observe 85.0 % preserved axons pointing to an anterograde gradient of axon degeneration. G-J: Light microscopic images (G, I) and corresponding electron micrographs (H, J) taken from the proximal (G, H) and distal (I, J) end of the peripheral nerve stump after 20 days following compression lesion. Similar to the transection lesion also here we identified a clear anterograde degeneration gradient with 70.0 % intact axons at the proximal end and 94.8 % preserved axons at the distal end of the nerve stump. Magnification of light microscopy is 630 × and electron microscopy is 3400 ×
Remarkably, in view of data reported in wild-type mice, a crush injury of the proximal sciatic nerve also resulted in anterograde progression in WldS sciatic/tibial nerve that was evident with a more moderate gradient after 20–30 days. Twenty days after sciatic nerve crush 70.0 % of all myelinated axons were preserved a few millimetres distal to the lesion (Fig. 8F, G, H) while 94.8 % of these fibres were preserved at the distal tibial nerve more than 20 millimetres away from the point of lesion (Fig. 8F, I, J). Similarly, 25 and 30 days after crush lesion we observed an increase in preserved axon numbers from proximal to distal along the sciatic-tibial nerve distance (Fig. 8F). Even 30 days after transection or crush lesion there were many protected distal axons in tibial nerve (Fig. 8A, F). By contrast, the degeneration of all distal fibres in wild-type mice was complete within two days (see above). Thus, while axon degeneration in more proximal regions is delayed approximately tenfold by WldS after a lesion, the delay in more distal regions is at least twenty fold. In summary, quantification of axon preservation assessed by light and electron microscopy is sufficient to indicate a marked anterograde direction of axon degeneration both after transection and crush injury of peripheral WldS nerves.
Anterograde degeneration of individual YFP labelled WldS axons is slowly progressive
In order to exclude nerve branching as an explanation for the observations above, we carried out detailed longitudinal analysis of individual degenerating WldS axons labelled with the YFP-H transgene as described previously [54]. Following transection or crush lesions to the sciatic nerve, long-range confocal YFP axon tracing was performed in 2–3 cm wholemount nerve segments. 15 days after transection almost all (96.4 ± 3.4 %) YFP labelled WldS axons showed a homogeneous anterograde gradient of degenerative changes along the sciatic and tibial nerve (Fig. 9). An example is presented in Fig. 10. In contrast to partially degenerated wild-type axons after transection lesion, where there were clear interruptions between markedly demarcated YFP-positive fragments, axon fragmentation in proximal WldS nerves after 15 days was mostly incomplete. Instead of interruptions, there were many constrictions of short regions of the axon or thin axoplasmatic bridges between thicker regions (inset 1 + 2 in Fig. 10). Occasionally we observed small swellings (bulbs) at the proximal ends (data not shown). Distal areas of the same WldS axon lacked these degenerative changes (inset 3 + 4 in Fig. 10). The remaining 3.6 % of WldS axons appeared to be completely intact without any discernible signs of degeneration (Fig. 9). 20 days after transection, proximal regions of individual WldS distal axon stumps were more completely fragmented (inset 1 in Fig. 11). However, some millimetres distal the fragments became gradually less frequent and again were often joined by YFP positive material indicating incomplete fragmentation (inset 2 in Fig. 11). At this time point such incomplete fragmentation with axonal narrowing occasionally continued up to distal regions of the fluorescent WldS axons (inset 3 in Fig. 11). Altogether at 20 days post operation all axons showed anterograde gradients of complete or incomplete fragmentation (Fig. 9). Additionally, we analyzed individual axons that were separated for 12.5, 17.5 and 22.5 days from their parent cell body and found that with increasing lesion time proportionally more axons displayed anterograde degeneration gradients. The gradients became structurally clearer through more marked demarcation of axonal fragments (data not shown). Thus, the initial morphological events in the degeneration of WldS axons are constrictions or atrophy, followed only considerably later by complete interruptions of the axon.
Figure 9 Quantification of fluorescent WldS axons in whole-mounted peripheral nerve stumps from triple heterozygote mice after transection and crush injury at different time points. Partially degenerated YFP positive WldS axons that could be identified 15 and 20 days either after transection or crush injury showed axonal constrictions or interruptions in their proximal site but not further distal indicating an anterograde gradient of degeneration. They were assigned to the group "fragmented with anterograde gradient". Few entirely preserved fluorescent WldS axons could be only seen 15 days after transection and crush injury. They were assigned to the group "intact". The chart presents means and standard deviations.
Figure 10 Anterograde degeneration of transected WldS axons initially involves proximal axonal atrophy with occasional interruptions. Confocal composite picture showing eight consecutive lengths (from top to bottom in overview) of the proximo-distal course of an individual YFP labelled WldS axon within a peripheral triple heterozygote nerve stump 15 days after transection injury displaying an anterograde progression of axon degeneration. Note that this axon shows predominantly narrowings (red asterisks) and occasionally interruptions (white arrows) in its most proximal end (inset 1) with a gradual decrease of this degeneration signs over a few millimetres more distal (inset 2) while at its distal parts almost no degeneration can be identified (inset 3 and 4). YFP fluorescence has been pseudo-coloured yellow with the applied confocal imaging software (Biorad LaserSharp 2000). Scale bar: 500 μm
Figure 11 Anterograde degeneration of transected WldS axons eventually continues with complete proximal fragmentation. Confocal composite picture showing six consecutive lengths (from top to bottom in overview) of the proximo-distal course of an individual YFP labelled WldS axon within a peripheral triple heterozygote nerve stump 20 days after transection injury demonstrating a clearer anterograde progression of axon degeneration than in Fig. 10. Note that this isolated axon shows complete break-up (white arrows) with clearly demarcated fragments in its most proximal part among a minority of axonal narrowings (red asterisks) (inset 1). Moving further distal fragmentation accompanied by axonal constrictions becomes gradually weaker (inset 2, 3) while at its most distal end almost no degeneration can be identified (inset 4). YFP fluorescence has been pseudo-coloured yellow with the applied confocal imaging software (Biorad LaserSharp 2000). Scale bar: 500 μm
We then followed up the earlier EM experiments using crushed nerves from WldS/YFP-H double mutant mice to study the directionality of axon degeneration in WldS nerves using this very different method. Once again, the spatio-temporal pattern of axon degeneration after crush injury in WldS mice was very similar to that after transection injury, contrasting with wild-type mice where directionality depends on lesion type. Correspondingly, 15 days after crush lesion we counted 84.60 % of all YFP labelled WldS axons with an anterograde gradient of degenerative changes (Fig. 9). An example of such an individual axon is shown in the additional data file Add Fig 2.pdf. However, crushed WldS axons more frequently showed end bulbs at the proximal end of the distal stump, which were often very large, (red arrow in overview of Add Fig 2.pdf) and subsequent multiple axonal swellings (inset 1 in Add Fig 2.pdf). This feature was far more prominent in crushed WldS axons than in the transection experiment where we observed end bulbs just occasionally. Further distally these swellings disappear with remaining axonal constrictions and breaks (inset 2 in Add Fig 2.pdf) representing incomplete fragmentation. As in transected nerves, distal parts of the crushed WldS axon were free of degeneration signs (inset 3 and 4 in Add Fig 2.pdf). Compared to transection lesion, more axons at 15 days remained entirely intact (15.4 %) (Fig. 9). By 20 days after nerve crush of WldS axons, proximal fragmentation became more prominent with fully separated fragments (inset 1 in additional data file Add Fig 3.pdf) while more distal regions of the same axons were again incompletely fragmented (inset 2 in Add Fig 3.pdf) and further distal still lacked any degeneration signs (insets 3 + 4 in Add Fig 3.pdf). The proximal end bulbs and localised swellings were larger than at 15 days (red arrow in overview of Add Fig 3.pdf), possibly due to continued accumulation of retrogradely transported material.
In summary, quantification 20 days after crush lesion revealed that all axons showed anterograde gradients of complete or incomplete fragmentation (Fig. 9). Thus, the YFP-H studies confirmed our light and electron microscopy observations that delayed degeneration in individual WldS axons is directional with an exclusively anterograde pattern both after transection and crush injury. This pattern of degeneration is qualitatively different from that in wild-type mice, which shows asynchronous, bidirectional fragmentation and degeneration.
WldS axons show a continuous gradient of axon degeneration that moves with a velocity similar to that of slow axonal transport
In the above experiments we noted the gradual change from degenerated regions to intact regions in WldS axons. In contrast to our observations in wild-type mice, there was no clearly delineated boundary or wave front separating degenerated and fully intact regions. In order to quantify this, we counted the number of axonal constrictions and breaks along the length of YFP positive WldS axons following injury. At all post-lesion time-points randomly chosen axons showed gradually decreasing signs of degeneration (constrictions or interruptions) along their length (Fig. 12). This markedly contrasts with the wave-like degeneration observed in wild-type mice where a sharp boundary divided preserved regions of the axon from completely fragmented regions. The closely superimposed curves shown in Fig. 12A, C, E, G also indicate that anterograde axon degeneration is more synchronous among the axon population in WldS nerves at both 15 and 20 days following transection or crush injury. Only rarely could we observe morphologically normal WldS axons adjacent to axons with anterograde gradients of degeneration (Fig. 9). This quantification allowed us to estimate the rate at which anterograde degeneration progresses along single WldS axons. Between 15 and 20 days the equivalent stage of degeneration has advanced up to 11 mm further along the nerve (sometimes less), giving a maximum velocity of WldS degeneration progression of 11 mm / 5 days = 2.2 mm/day. This is similar to the reported velocity of slow axonal transport (0.1–3.0 mm/day) [56-59]. All findings concerning topology of axonal degeneration in WldS peripheral nerves are summarized schematically in Fig. 13.
Figure 12 Progression of axon degeneration in shape of a continuous degeneration gradient appears roughly synchronous along individual WldS axons A-H: Graphs showing the number of axonal constrictions and breaks along individual YFP labelled WldS axons with an anterograde gradient of degeneration in relation to the distance in mm from the transection point 15 days (A, B) and 20 days (C, D) after transection lesion or from the crush point 15 days (E, F) and 20 days (G, H) after crush lesion. Means and standard deviations are presented in B, D, F, H. Note that with increasing distance from the transection and crush point degeneration signs decrease uniformly characterized by the steady decline of the curves. Moreover, degeneration in different WldS fibres is broadly synchronous as shown by the good superimposition of individual curves in A, C, E, G.
Discussion
We have shown that the fragmentation of axons undergoing Wallerian degeneration in a mixed wild-type peripheral nerve is a rapid, asynchronous and progressive process. By using a recently developed method to visualise individual axons over cm-long distances, and by targeting a short critical period during which nearly all axons degenerate, we have made the first observations in vivo of partially fragmented individual axons and thus determined the directionality and the wave-like nature of Wallerian degeneration, as well as estimating its velocity. Furthermore, we have shown that nerves of WldS mutant mice undergo a fundamentally distinct process rather than simply following the same pathway in slow motion.
Lesioned wild-type axons remain morphologically normal for a latency period of ca. 36–44 hours, which depends on lesion type and individual axonal properties [38,39,44,46,60]. Each axon then undergoes a catastrophic process in which at least 24 mm of the distal stump fragments entirely within an hour. The propagation rate of at least 24 mm/h is considerably faster than reported in rat dorsal column (3 mm/h) [47], rat phrenic nerve (up to 10.4 mm/h) [46] and in primary culture (ca. 0.4 mm/h) [50], probably reflecting differences in neuronal subtype and context. For example, slower propagation of Wallerian degeneration in the CNS is suggested by the observation of an anterograde spread in the gracile tract following a dorsal root lesion, whereas the spread of degeneration within the root itself was too short-lived to be resolved by the methods used [47]. Wallerian degeneration may also propagate more slowly in longer axons, which could account for differences between mice and rats [44,45], and there may be many reasons why the propagation rate in vitro could differ from that in vivo. Nevertheless, while the propagation rate may differ, the anterograde degeneration after axon transection is a consistent feature of each of these studies.
We have shown that Wallerian degeneration in wild-type nerves is a wave-like process that can travel in either direction along the axon, depending on lesion type. 29 partially fragmented axons were observed, and all showed a sharp boundary between fragmented and non-fragmented zones, such that all axon regions up to the wavefront were degenerated and all regions beyond it remained intact. Fragmentation had reached different points along the nerve in different individual axons (Fig. 6), reflecting asynchronicity of the onset and rate of degeneration. The wave-like propagation of Wallerian degeneration has been proposed before [44,46,47,49,61], and especially Lubinska [44,46] has shown that Wallerian degeneration of the distal stump progresses centrifugally by jumping from one internode to another, but this is the first time the wavefront has actually been observed. Of the 29 partially fragmented axons, 17 transected axons were fragmented only at their proximal ends and 12 crushed axons were fragmented only at their distal ends (Fig. 2, 3, 4). Differences between cut and crushed nerves have been suggested before [48,53] and axons cut at both ends also exhibit a retrograde degeneration component [44], but this is the first demonstration that two different lesions at the same site in the same nerve cause different directions of degeneration. The mechanistic basis of this surprising observation remains unknown, but some models are outlined below.
We discuss here two models to explain the wave-like propagation of Wallerian degeneration in wild-type nerves: one based on fast axonal transport and the other based on calcium influx (see also Fig. 14). Numerous reports have proposed that the clearance of a supportive or trophic factor by fast axonal transport processes underlies the anterograde direction of Wallerian degeneration after transection [33,44,46,47,62] based on the observation that anterograde fast axonal transport of proteins continues after axotomy in the peripheral nerve stump in a wavelike manner. Such a factor could be an inhibitor of an axonal destruction programme, likely to be stabilised or upregulated by a downstream effector of the WldS protein. The fastest reported components of axonal transport move at around 14–25 mm/h, but it is reasonable to expect that some minor, thus far undetected, components may move faster [63,64]. This is just compatible with the spread of the fragmentation wave at a minimum of 24 mm/h that we observe. However, Wallerian degeneration could progress even faster, too fast to be accounted for by fast axonal transport, and anterograde clearance of a factor inhibiting Wallerian degeneration could not explain the retrograde degeneration that we found in crushed nerves.
Figure 14 Two models to account for the progressive nature of Wallerian degeneration after transection lesions in wild-type axons. (A) A putative inhibitor of intrinsic self-destruction machinery is constantly delivered from the cell body to the unlesioned wild-type axon (top). After axon transection the inhibitor is no longer supplied and is cleared first from proximal regions of the distal stump by fast axonal transport. This leads to a wave of fragmentation moving proximal to distal along the isolated axon stump. (B) In an alternative model, the wave of fragmentation is propagated not by directional removal of a putative inhibitor but by rapid localised influx of calcium ions beginning at the most vulnerable part of the axon. Once inside, calcium ions not only activate calpains to degrade the local axoplasm, but also diffuse and exceed the threshold of calpain activation in the immediately adjacent region. This leads to further axoplasmic and membrane breakdown and further calcium influx. The pattern is repeated to generate a wave of fragmentation moving along the axon. Model (A) has the attraction that the putative inhibitor would be a good candidate for mediating of the WldS phenotype (e.g., it could be overexpressed in WldS), while model (B) more easily explains why the directionality is reversed in a crush lesion. The calcium influx and diffusion wave could spread also retrogradely (not shown) if the distal end were the first to disintegrate. In model (A), however, it is hard to see how retrograde axonal transport could explain the depletion of an inhibitor that ultimately has to come from the cell body (see text for more details).
Thus, we consider also an alternative model in which short regions of the axon membrane become permeabilised to calcium ions and this feature moves rapidly as a wave along the axon. Fibre degeneration requires accumulation of axoplasmic calcium [65,66], which probably activates the cystein protease calpain [67-70]. Once inside the axon, calcium ions could diffuse to the immediately neighbouring axoplasm and activate calpain, leading to degradation of axoplasmic and membrane proteins, and thus permeabilisation of the next segment. Such a membrane associated Ca2+ influx hypothesis was proposed by Schlaepfer for the first time [71,72] and developed further involving calcium channels in more modern studies [73,74]. LoPachin and Lehning [75] reported calcium entry linked to membrane depolarisation through reverse Na2+-Ca2+-exchange, leading to a steady rise in intra-axonal calcium and calcium accumulation has been observed beneath Schmidt Lantermann clefts at distal sites 4 h after injury [76]. Once the threshold for calpain activation is exceeded, a wave of degeneration could be initiated and then propagate rapidly in either direction as outlined above.
There are several possible reasons why degeneration may begin proximally in a transected nerve but distally in a crushed nerve. The proximal end of a transected distal stump is especially vulnerable because of the exposure of the axoplasm to the external ionic environment, and because all extra-axonal structures that normally support the axon have been totally disrupted, e.g., blood vessels, Schwann cells, extracellular matrix, perineurium. One of these factors may cause a calcium entry wave to begin at this point. In contrast, intact endoneural blood vessels can be found close to a nerve crush [77,78], the epi- and perineurium tubes are maintained at the site of crush [78-81], and some nerve crush protocols do not break axon continuity [82-85], so that Wallerian or Wallerian-like degeneration occurred only many days after compression or not at all. More specifically, even application of longer high pressure injuries with a minimum of shear forces may squeeze out axoplasm into adjacent parts of the axon rather than interrupting the axolemma preserving nerve conduction monitored electrophysiologically [82]. In our nerves we observed continuous longitudinal YFP signals across crush sites immediately after lesioning, indicating that at least some axons were not transected by the direct effect of crushing. We also observed many preserved fibres crossing the crush site when we fixed and then partially teased crushed nerves to generate small bundles where individual fibres were easily identifiable (see additional data file Add Fig 1. pdf). Thus, the proximal end of the distal stump may be less vulnerable than after transection, and fragmentation may begin instead at the distal end because this is the hardest part to supply with everything the axon needs to survive.
We observed a series of differences in the pattern of Wallerian degeneration in WldS nerves that are incompatible with delayed axon degeneration following a similar mechanism to Wallerian degeneration in wild-type nerves, only slower. The spread of degeneration along WldS nerves is around 100-fold slower, axon degeneration is more synchronous, at least relative to how long it takes to occur, it progresses in a proximal to distal direction in crushed nerves as well as transected nerves, there is a continuous gradient of degeneration along the length of the axon rather than an abrupt change at a boundary, and the first sign of axon degeneration is a constriction rather than a complete interruption. We therefore propose that the ultimate degeneration of axons in WldS mice be termed "slow anterograde axon decay" rather than Wallerian degeneration as summarised schematically in Fig. 13.
Based on these differences, we propose that injured WldS axons eventually undergo a passive process of atrophy, rather than an active process of self-destruction similar to apoptosis that appears to take place in wild-type axons [5,7,15,16,86]. It is likely that preserved axonal proteins will eventually be degraded by catabolic processes and may not be replaced by significant new synthesis, even if Wallerian degeneration is completely prevented. A direct indication of this is our observation in primary neuronal cultures of significant atrophy of distal neurites when their degeneration is delayed by WldS (data not shown). Even the fact that some proteins are synthesised locally in axons [57,87-89] may not be sufficient to prevent the eventual depletion of protein in severed WldS axons, as it remains unclear which proteins are made there and in what quantities.
We discuss two models to explain the slow anterograde progression of degeneration along WldS axons: one based on slow axonal transport and the other on a temperature gradient along the limb. The gradual nature of axonal atrophy in WldS makes it difficult to be precise about the rate at which it progresses along the axon, but it is certainly not incompatible with the velocity of slow axonal transport of 0.1–3.0 mm/day [56-58,90]. Clearance of structural proteins by slow anterograde transport, added to their gradual depletion by protein turnover, could cause the protein content at the proximal end of the distal stump to drop below the threshold level needed to maintain axon integrity. Bidirectional transport of cytoskeletal components continues in transected WldS nerves, leading to localised neurofilament-depleted constrictions and terminal and intermediate swellings containing disorganised neurofilaments [91,92]. We have made similar observations in YFP labelled WldS axons, and additionally report a gradient of such features along the nerve. A net anterograde movement of cytoskeletal proteins could therefore underlie the anterograde gradient of axonal atrophy in WldS axons injured for many days.
Alternatively, a proximal-distal decreasing gradient of temperature along the limb could underlie the observed difference in degeneration rate at different points in the WldS nerve. A decrease in temperature has been shown to delay degeneration both in wild-type and WldS axons after injury [52,74,93-96]. In wild-type nerves, a temperature gradient explains neither the different directions of propagation after transection and crush injury, nor the sharp boundary between intact and degenerated regions. However, in WldS axons there is a proximal to distal gradient of degeneration regardless of lesion type and the change from intact to degenerated is a gradual one. Thus, a temperature gradient could play a more important role here.
The extremely long survival of distal tibial nerve following injury in WldS is in marked contrast to the presynaptic nerve terminal at the neuromuscular junction, which is the first structure to degenerate in both wild-type and WldS nerves [2,8,46]. Intramuscular nerve also degenerates early, at least in WldS heterozygotes (L. Fan and R.R. Ribchester, unpublished). This supports the hypothesis of compartmentalised degeneration mechanisms of axons and synapses [97] and suggests that a clear boundary exists between the two domains. The location and nature of this boundary could hold important clues for determining the mechanism of both Wallerian degeneration and synapse degeneration.
Finally, the methods we report here could now be applied to study spontaneous nerve degeneration in 'dying-back' disease. The 'dying-back' model also predicts the transitory existence of partially degenerated axons, but as in Wallerian degeneration such axons have never been directly observed and there is no indication of the speed of 'dying-back' of individual axons [98,99]. There are interesting parallels between axon degeneration after nerve crush and 'dying-back', as both can be delayed by the WldS gene and the direction of degeneration is also shared [24]. Thus, it is an intriguing possibility that the speed of propagation is equally rapid and asynchronous. If it is a similarly catastrophic event, what can stop it progressing back to the cell body leading to neuron death? In some cases neuronal death does appear to be the outcome [25,100], whereas in others, proximal axons and their cell bodies somehow survive [101] and it is important to find out why. Future prospects include direct observation of the progression of a degeneration boundary along YFP labelled axons in vivo after nerve lesion or in disease, once methods for in vivo imaging of single axons become more refined and more readily available, e.g., Cell ViZio, Mauna Kea Technologies [102].
Conclusions
In summary, we report the first direct observation of partially degenerated single axons in lesioned nerves undergoing Wallerian degeneration, indicating that Wallerian degeneration propagates in wild-type nerves as a wave whose speed is at least as fast as the highest reported rate of fast axonal transport. It could be faster still in mouse sciatic and tibial nerve. The direction of degeneration is proximal to distal after a cut, but the reverse after a crush. For now the mechanism remains unknown, but these observations will ultimately need to be explained in any comprehensive model of the Wallerian degeneration mechanism. Injury-induced axon degeneration in WldS nerves is also progressive, but differences in the topographic pattern and morphology of degeneration indicate a fundamentally different process from that in wild-type nerves. We propose that WldS axons ultimately undergo atrophy, in a passive process similar to that which Wallerian degeneration was once thought to be.
Methods
Crossbreeding and genotyping of transgenic mice
Crossbreeding and genotyping of the YFP-H line [55] and triple heterozygote mice carrying the original WldS mutation, the transgenic WldS mutation (tg-WldS) [13] and the YFP-H gene was performed as previously described [54]. Triple heterozygote mice rather than WldS/YFP-H mice were used purely for reasons of convenience in their breeding. They express similar levels of WldS protein as homozygous natural mutant WldS mice and display a similar retarded time-course of axon degeneration. They additionally express YFP in approximately 3% of myelinated motor and sensory fibres in the PNS, equal to the original YFP-H line obtained from the Jackson Laboratories.
Sciatic nerve lesions
Six- to 10-week-old mice from the YFP-H line and triple heterozygote mice for the second part of the study were anaesthetised by intraperitoneal injection of Ketanest (5 mg/kg; Parke Davis) and Rompun (100 mg/kg; Bayer), sciatic nerves were transected or crushed firmly close to the Foramen intrapiriforme and the wound was closed with a single suture. Complete nerve transection was performed with conventional surgical scissors and crush lesion was achieved with fine watchmaker's forceps (model: micrscopic forceps bent No. 7, Aesculap BD 333R, Germany) for 30 seconds. The continuity of the sciatic nerve was always preserved after crush lesion as checked in situ. For light and electron microscopy we removed distal ~2.5 centimeter long nerve stumps after 15 (transection only), 20, 25 and 30 days in triple heterozygote mice following intracardial perfusion. The first 2 millimeters of the distal nerve stump were discarded to reduce artifacts, and the next 2 mm from the most proximal and distal end of the peripheral nerve stump was prepared for Durcupan embedding and electron microscopy.
For conventional fluorescence microscopy and confocal tracing of individual YFP labelled wild-type axons after 34 h, 37 h, 40 h, 41 h, 42 h and 48 h following cut lesion and 37 h, 40 h, 42 h, 43 h, 44 h and 48 h following crush lesion the operated YFP-H mice were sacrificed by cervical dislocation and nerve segments prepared as follows.
For confocal tracing of individual YFP labelled WldS axons from triple heterozygote mice we dissected sciatic-tibial nerve segments after 12.5 d (transection only), 15d, 17.5 d (transection only), 20 d and 22.5 d (transection only). For each investigated time-point 2 – 3 YFP-H or triple heterozygote mice were operated.
Assessment of axonal continuity in crushed YFP-H nerve segments
Sciatic nerves of mice from the YFP-H line were crushed as described in the paragraph above and the short nerve segment containing the crush site immediately removed after lesion, freed from surrounding connective tissue and subsequently either prepared for wholemount fluorescence embedding as described previously [54] or for tissue osmification. For the latter the crushed segment was immersion-fixed for four hours in 10% PFA in 0.1 M PBS, washed three times in 0.1 M PBS for 10 minutes and osmificated in aqueous osmium-tetroxide (1 %) solution for 90 minutes. After rinsing in fresh 0.1 M PBS individual axon bundles were teased from the crushed segment using fine syringe needles (Neoject 26 G × 1/2, Dispomed WITT, Germany) and mounted on conventional glass slides. Fluorescence imaging of crushed YFP-H nerve segments and light microscopy of osmificated fibre bundles was carried out using an Olympus IX 81 inverted microscope coupled to a Olympus U-TV0.5XC digital camera system.
Intracardial perfusion for light and electron microscopy of semithin and ultrathin preparations
After sternotomy under deep anaesthesia mice were killed by cardiac puncture and instantly intracardially perfused first with a solution containing 10 000 i.e./l heparin (Liquemin N 25 000, Hoffmann-La Roche) and 1 % procainhydrochloride in 0.1 M PBS for 30 s and then with fresh half-strength Karnovsky's fixative (4 % paraformaldehyde, 2 % glutardialdehyde in 0.1 M sodium cacodylate, pH 7.3).
Light and electron microscopy
Nerve samples for light and electron microscopy were embedded in Durcupan and further processed for examination with a Zeiss Axiophot light microscope and Zeiss EM 902 electron microscope as described previously [54].
Morphological quantification of axon preservation in light and electron micrographs
The percentage of preserved myelinated axons in proximal and distal ends of peripheral nerve stumps from triple heterozygote mice after transection and crush injury was determined as described previously [13,54].
Conventional fluorescence microscopy and confocal tracing of individual YFP labelled axons after various lesion times
In both YFP-H and triple heterozygote mice after cut or crush lesion the entire nerve distances from the proximal sciatic to the distal tibial nerve were carefully excised, the perineurium and the branch of the commune fibular nerve removed and the remaining ~2.5 centimeter long stumps treated for wholemount fluorescence preparation using Vectashield Mounting Medium (Vector Laboratories) as described previously [54]. For rough orientation the wholemount preparations were photomicrographed at the proximal and distal end of the excised nerve segment using a Zeiss Axiophot microscope connected to a digital camera system (Universal Imaging Corporation). High resolution confocal composite presentation of the entire intra-nerve course of individual degenerating YFP-labelled wild-type or WldS axons running through the excised stumps over their whole length was achieved as described previously [54]. Single images were obtained with LaserSharp 2000 software connected to a Biorad Radiance 2000 laser scanning system (Hemel Hempsted, UK) and composite pictures on a black background were created using Adobe Photoshop.
Imaging of restricted transition zones dividing intact and fragmented axon regions in YFP-H nerves was performed under highest possible resolution with a Zeiss LSM 510 META confocal system (LSM Software Release 3.2) coupled to a Zeiss Axiovert 200 microscope.
Quantification of intact and degenerated YFP labelled wild-type and WldS axons in peripheral nerve stumps after cut and crush injury
For the first part of the study focusing on sciatic/tibial nerves from the YFP-H line in each wholemount preparation (2 – 3 nerve preparations per time point) YFP labelled wild-type axons running continuously through the excised peripheral nerve stump after cut and crush injury were traced individually with the laser scanning confocal microscope under high resolution and divided into four groups: axons without any features of axonal disintegration were assigned to the group "intact". Axons that showed fragmentation of the longitudinal YFP signal over the whole length of the fibre were assigned to the group "entirely fragmented". Axons without any sign of fragmentation at one end but clear axon breakdown at the other end were assigned either into the group "fragmented with anterograde gradient" or "fragmented with retrograde gradient" depending whether the fragmentation appeared close to the lesion point or at the most distal point of the tibial nerve segment. For the second part of the study dealing with triple heterozygote mice YFP labelled WldS axons in wholemount peripheral nerve stumps (2–3 nerve preparations for each timepoint) after transection and crush injury were equally traced individually with the BioRad Radiance 2000 laser scanning confocal microscope under high resolution, and divided into two groups: axons without any features of axonal disintegration were counted and assigned to the group "intact". Fibres that showed degeneration signs like constrictions or interruptions of the longitudinal YFP signal at the proximal site were associated into the group "fragmented with anterograde gradient". Means and standard deviations for all experiments were calculated using Microsoft Excel.
Quantification of axonal degeneration signs along YFP positive axons
The length of degenerated YFP labelled wild-type and WldS axons was measured during the tracing process with the confocal laser scanning microscope and the distribution of axonal interruptions (both in wild-type and WldS axons) and/or constrictions (only in WldS axons) was graphed against the distance in mm from the cut or crush point. Means and standard deviations were calculated using Microsoft Excel.
Animal experiments
All animal experiments were carried out under appropriate German licences: Tierschutzgenehmigung K 13, 11/00 and Anzeige K30/99.
Authors' contributions
MPC (corresponding author) and BB jointly conceived of the design for this study, interpreted the experimental results and wrote the manuscript; BB carried out preliminary light and electron microscopy experiments, confocal imaging of YFP labelled axons, axon quantification and statistical analysis; RA: collaborated on the set up of the experiments, improvement of histological techniques and interpretation of results, performed teased fibre experiments, assisted in writing the manuscript; DW and DSG: provided excellent technical assistance in many parts of the experiments, performed sciatic nerve cut lesions and carried out routine work; KA: contributed to the discussion of the experimental results, preliminary light and electron microscopy work was done in his lab; RRR: contributed to the interpretation of the experiments and writing of the manuscript; confocal microscopy of YFP axons was mostly done in his lab; MPC: performed sciatic nerve crush lesions and partially confocal imaging, supervised all aspects of the study and main work was done in his lab.
All authors read and approved the final manuscript.
Supplementary Material
Additional File 1
Many nerve fibres are unbroken directly after a 30 second crush as shown in YFP-H wholemount nerves and osmificated teased fibre preparations.A-C: Sciatic nerves crushed for 30 seconds at maximum pressure and then immediately fixed and imaged by osmium staining (A, B) or YFP fluorescence (C). D: YFP-H nerve crushed for 5 seconds at maximum pressure. Nerves in (A) and (B) were partially teased apart after staining, leading to accidental breakage of a few fibres. However, the majority of fibres clearly cross the crush site unbroken. YFP signal (identifying the axoplasm) at the crush site in (C-D) is weak, probably due to squeezing of the axoplasm longitudinally out of the crush site, or quenching of fluorescence by the crushed tissue, or both. To compensate, the photographs are deliberately overexposed. There is no sign of YFP positive axoplasm escaping laterally into the extracellular space, as would be expected if the axolemma were broken. Instead, some YFP positive axons clearly cross the crush site unbroken. In (C) the overexposure would prevent any broken axons from being identified, but in (D) the signal from most or all axons fades gradually as the axon enters the crush site, rather than stopping abruptly as one would expect if the axon were broken. Scale bars: 20 μm (A, B) and 50 μm (C, D).
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Additional File 2
Degeneration of individual crushed WldS axons proceeds anterogradely beginning with the formation of end bulbs and axonal swellings at the most proximal end and accompanying proximal axonal atrophy. Confocal composite picture showing seven consecutive lengths (from top to bottom in overview) of the proximo-distal course of an individual YFP labelled WldS axon within a peripheral triple heterozygote nerve stump 15 days after crush injury displaying an anterograde gradient of axon degeneration. This axon exhibits an end bulb at the most proximal end (red arrow in overview) and subsequent multiple axonal swellings delimited by constrictions (red asterisks) (inset 1). Further distally these swellings disappear with remaining constrictions (red asterisks) and sporadic breaks (white arrow) (inset 2). Distal parts of the crushed WldS axon are free of degeneration signs (inset 3 and 4). Scale bar: YFP fluorescence has been pseudo-coloured yellow with the applied confocal imaging software (Biorad LaserSharp 2000). 500 μm
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Additional File 3
Anterograde degeneration with formation of massive end bulbs of compressed WldS axons finally includes complete proximal fragmentation. Confocal composite picture showing six consecutive lengths (from top to bottom in overview) of the proximo-distal course of an individual YFP labelled WldS axon within a peripheral triple heterozygote nerve stump 20 days after crush injury demonstrating a clearer anterograde progression of axon degeneration than in Add Fig 2.pdf. Likewise after 15 days following crush injury this picture shows a massive end bulb at the most proximal end of the distal stump (red arrow in overview) and subsequent multiple axonal swellings and constrictions. Complete axonal fragmentation is evident in inset 1 (white arrows mark axonal breaks) and gradually gives way to incomplete breakup with axonal constrictions (red asterisks) (inset 2). Distal parts of the crushed WldS axon lack degeneration signs (inset 3 and 4). YFP fluorescence has been pseudo-coloured yellow with the applied confocal imaging software (Biorad LaserSharp 2000). Scale bar: 500 μm
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Acknowledgements
This study was supported by the Federal Ministry of Education and Research (FKZ: 01 KS 9502), Center for Molecular Medicine (CMMC), University of Cologne (BB, RA, DW, DSG and MCP), the Koeln Fortune Program / Faculty of Medicine, University of Cologne (BB), ALS Association (USA) Grant 167 (RA) and a Wellcome Trust Biomedical Collaboration Grant (RRR and MPC).
We thank Dr. Simon Walker (The Babraham Institute) and Adrian Thomson (Division of Neuroscience, University of Edinburgh) for assistance and technical advice on confocal microscopy.
The work forms part of the doctoral thesis of Bogdan Beirowski (University of Cologne).
==== Refs
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| 15686598 | PMC549193 | CC BY | 2021-01-04 16:39:09 | no | BMC Neurosci. 2005 Feb 1; 6:6 | utf-8 | BMC Neurosci | 2,005 | 10.1186/1471-2202-6-6 | oa_comm |
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BMC PsychiatryBMC Psychiatry1471-244XBioMed Central London 1471-244X-5-71569137410.1186/1471-244X-5-7Research ArticleNarrative Exposure Therapy as a treatment for child war survivors with posttraumatic stress disorder: Two case reports and a pilot study in an African refugee settlement Onyut Lamaro P [email protected] Frank [email protected] Elisabeth [email protected] Verena [email protected] Michael [email protected] Maggie [email protected] Thomas [email protected] vivo Uganda, Mbarara, Uganda2 Mbarara University of Science and Technology, Mbarara, Uganda3 University of Konstanz, Centre for Psychiatry Reichenau, Haus 22, Feursteinstr. 55, D-78479 Reichenau-Lindenbühl, Germany2005 3 2 2005 5 7 7 13 9 2004 3 2 2005 Copyright © 2005 Onyut et al; licensee BioMed Central Ltd.2005Onyut 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
Little data exists on the effectiveness of psychological interventions for children with posttraumatic stress disorder (PTSD) that has resulted from exposure to war or conflict-related violence, especially in non-industrialized countries. We created and evaluated the efficacy of KIDNET, a child-friendly version of Narrative Exposure Therapy (NET), as a short-term treatment for children.
Methods
Six Somali children suffering from PTSD aged 12–17 years resident in a refugee settlement in Uganda were treated with four to six individual sessions of KIDNET by expert clinicians. Symptoms of PTSD and depression were assessed pre-treatment, post-treatment and at nine months follow-up using the CIDI Sections K and E.
Results
Important symptom reduction was evident immediately after treatment and treatment outcomes were sustained at the 9-month follow-up. All patients completed therapy, reported functioning gains and could be helped to reconstruct their traumatic experiences into a narrative with the use of illustrative material.
Conclusions
NET may be safe and effective to treat children with war related PTSD in the setting of refugee settlements in developing countries.
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Background
In the wars and armed conflicts of the past decades, children have been among the survivors who have been exposed to war or conflict-related violence. The United Nations High Commissioner for Refugees (UNHCR) recently stated that 43% of its population of concern are children under the age of 18 [1]. Mental health experts are also becoming more aware that war and conflict-related event types are among those that may result in children developing disorders of the stress spectrum, including posttraumatic stress disorder (PTSD) [2-5].
An increasingly important field of research addresses the wide-ranging negative sequelae that children and adolescents in modern post-conflict populations such as in Iraq, Kuwait, Bosnia, Rwanda, Croatia, South Africa and others may develop consequent to war and conflict violence [6-17]. Current research emphasis is now more than ever being placed on developing appropriate interventions that address the needs of survivors experiencing a range of symptoms after trauma exposure [18-29].
Given the pervasiveness of war and conflict-related trauma, especially in resource poor countries, interventions tailored to suit the circumstances of the overwhelming number of such survivors are especially in demand. However, treatment outcome studies in this field are still few. Many such interventions are derived from interventions initially developed for adults, such as cognitive behavioural therapy. Cognitive-behavioural interventions have been successfully used with school children exposed to violence, after single-incident stressors, after natural disasters as well as to treat sexually abused children [18,30-33].
Other interventions currently in use with children include psycho-pharmacological treatments, play therapy, psychological debriefing and testimony therapy [17,20,23,26,34-39]. It is notable that most approaches have not yet been tested within post-conflict populations of children and adolescents living in non-industrialized countries.
Narrative Exposure Therapy (NET) is a treatment approach that was developed for the treatment of PTSD resulting from organized violence. vivo developed Narrative Exposure Therapy as a standardized short-term approach based on the principles of cognitive behavioural exposure therapy by adapting the classical form of exposure therapy to meet the needs of traumatized survivors of war and torture [40-42]. In exposure therapy, the patient is requested to repeatedly talk about the worst traumatic event in detail while re-experiencing all emotions associated with the event. In the process, the majority of patients undergo habituation of the emotional response to the traumatic memory. In addition to the reconstruction of the traumatic memory, this habituation consequently leads to a remission of PTSD symptoms.
As most victims of organized violence have experienced many traumatic events, it is often impossible to identify the worst event before treatment. To overcome this difficulty in NET, the patient constructs a narration of his whole life from early childhood up to the present date while focusing on the detailed report of traumatic experiences. The focus of NET is therefore two-fold. As with exposure therapy, one goal is to reduce the symptoms of PTSD by 1) confronting the patient with memories of the traumatic event. However, recent theories of PTSD and emotional processing suggest that the habituation of the emotional processes is only one of the mechanisms that improve symptoms [43]. Other theories suggest that the distortion of the explicit autobiographic memory of traumatic events leads to a fragmented narrative of the traumatic memories. Thus, 2) the reconstruction of autobiographic memory and a consistent narrative should be used in conjunction with exposure therapy. Emphasis is put on the integration of emotional and sensory memory within the autobiographic narrative. Narrative Exposure Therapy was initially developed for adults, but has been adapted for use with children older than 8 years [43,44].
In narrative exposure procedures, children are asked to describe what happened to them in great detail, paying attention to what they experienced in terms of what they saw, heard, smelled, felt, the movements they recall and how they felt and thought at the time. Initially, the session is distressing, but as it is long enough to allow habituation, distress levels diminish towards the end and more and more details are recalled. After only four sessions of exposure, scores on intrusion and avoidance may drop significantly [43].
This study investigated the effectiveness of NET when applied to child refugees. The investigation was carried out in the context of the Nakivale mental health project, which aimed at the examination of mental health symptoms as well as the evaluation of different treatment approaches in the Nakivale refugee settlement in Uganda [45].
The first aim of this paper is to present and illustrate the procedure of KIDNET as a child-friendly treatment approach for traumatized children in post-conflict populations. In addition, we present the results of a small sample pilot test to allow the examination of the feasibility and potential efficacy of the method in a field context.
Methods
Ethical approval
The study protocol was approved by the Ethical Review Board of the University of Konstanz and by the Ugandan National Council for Science and Technology, Kampala.
Participants
Six child refugees (ages 13 – 17 years; 3 girls and 3 boys) of Somali ethnic origin screened as having PTSD from a larger epidemiological survey in Uganda's Nakivale refugee settlement [45].
Instruments and procedure
As instruments need to go through a work-intensive process of translation and validation and interpreters as well as interviewers need extensive training so that instruments are properly applied, we used the same already-validated instruments as in the adult epidemiological survey [45]. The Posttraumatic Diagnostic Scale (PDS) and the Hopkins Symptom Checklist-25 (HSCL) were administered face-to-face by trained, local, non-professional interviewers as assisted self-report interviews in order to screen for posttraumatic stress disorder and co-morbid depression [46,47]. The six children were identified as having PTSD according to the PDS. These diagnoses for both PTSD and depression were validated using the Composite International Diagnostic Interview (CIDI) version 2.1 [48] Sections K and E respectively, administered by expert clinicians with the help of extensively trained interpreters within two weeks of the initial interview.
This was done within the context of a clinical interview during which the clinicians clarified the questions for the children. The clinicians employed child-appropriate language to make sure the children understood the questions. In all six cases, the initial diagnosis was confirmed.
All six were assigned to a Narrative Exposure Therapy (KIDNET) treatment group, with treatment being offered by expert clinicians experienced in the use of NET. The post-tests were also conducted by expert clinicians and trained interpreters, again using the CIDI.
All six child patients gave verbal assent for the screening. They were then formally offered individual treatment after diagnosis, along with a brief psycho-education describing the nature and prevalence of PTSD symptoms, and what treatment would entail. A standard written rationale that has been developed for this purpose was used, the goal being to explain that PTSD-related symptoms and dysfunction are frequently consequent to multiple traumatic experiences. All six gave their assent for treatment, which only began after informed consent from the parents or guardians was granted. It was made clear that both assessment and treatment would be entirely voluntary, and no monetary or food-item inducements would be offered. In all cases, both the patients and their parents or guardians were relieved that treatment was offered.
The patients were tested again with the CIDI approximately four weeks (post-test) and nine months (follow-up) after the end of treatment.
Treatment modality
Narrative Exposure Therapy treatment sessions lasted between 4 to 6 sessions, of between 1 – 2 hours in duration. The treatment involved one-to-one sessions with a clinician attending to an single child patient at a time. At the beginning of Session 1, the patient was requested to draw any picture that came into their minds, as the very first step. Next, the patient was given a lifeline (length of rope) and a selection of stones of varying characteristics and sizes, as well as fresh flowers of varying sizes and colours. He or she was then asked to construct his lifeline, outlining the major events using flowers for positive events and stones for negative events in a chronological order.
When he or she was quite sure about the sequence and magnitude of events, the patient was then asked to make a drawing of this lifeline, with brief titles for each event. The narrative session then began, with the patient narrating the events of his or her life starting with his or her birth, with the aid of the lifeline and the drawings. The patient used a representative object, which he or she moved at will to indicate where he or she had reached on the lifeline.
In the following narration procedure, the participant constructed a detailed chronological account of his own biography in cooperation with the therapist. The therapist's task was to document the patient's autobiography, which was corrected with each subsequent reading. Special focus of the therapy was on the transformation of the generally fragmented report of traumatic experiences into a coherent chronological narrative, and working through emotions, sensations and reactions relevant to the traumatic events. During the discussion of the traumatic life experiences, the therapist asked for current emotional, physiological, cognitive and behavioural reactions, while accompanying the patient back into the details and emotions surrounding each event, and helping the patient to reconstruct the trauma memory. The participant was encouraged to relive these reactions and emotions while reporting the events. The discussion of a traumatic event was not terminated until a habituation of the emotional reactions presented and reported by the patient occurred.
During the session and in subsequent sessions, the testimony was read back to the patients, who was asked to correct, modify or add to it until a complete document has been made of the patient's experiences. During the last session, the participant received a complete written document of his biography. The precepts of Narrative Exposure Therapy are described in detail in a manual [43].
The main innovation of KIDNET as compared to the adult version of NET is the use of illustrative material such as a lifeline (usually a length of rope or string), stones and flowers, as well as coloured drawings and role-play, to help the child reconstruct the memories of his or her experiences. Unlike with adult NET thus far, the patients were encouraged to extend the narration beyond the present, to describe their hopes and aspirations for the future, mainly with the use of flowers. This is done at the end of therapy. These hopes and aspirations were included in the drawings, lifeline and narrations as an integral part of the document. The therapist also highlighted the length of rope still left over, to illustrate opportunities and possibly improved life circumstances, despite negative past experiences. The patient was requested to construct his or her lifeline at the beginning of each session, after which narration was resumed. The therapist was also alert to detect any connection between the initial picture and the traumatic events in the storyline, especially the worst-ever event. As a final task, the therapist requested the child to draw any picture that came to their minds after handing over the document to the patient at the end of the last session, in order to compare this with the initial picture drawn.
Results
Two cases of Narrative Exposure Therapy
Case one AWH
AWH is a very slim young person of middle height, with active uneasy eyes that never rest. He was interviewed in March 2003 when he was 15 years old by a locally trained interviewer using the PDS. This PTSD diagnosis was confirmed within a two-week period by an expert using the CIDI, after which AWH was invited for therapy. He was very shy when he came. In fact, he approached the house then ran back into the street. After some time, he slowly approached again. Both the therapist and the interpreter put in a lot of effort to make him feel welcome and comfortable. As we later learnt, he lost both parents during the civil war in Somalia. This was without question his "worst event".
He has lived by himself since the age of 14 in the camp, but fended for himself since the age of 9. He had no family in the camp or anywhere else, as far as he knew. At the time of his parent's death in Somalia, he recalled a younger brother and sister, but he had never heard of them again. He has been a registered refugee in Uganda since 1998.
His initial drawing at the beginning of therapy shows the tiny lonely figure of a child, placed in the middle of the large white sheet of paper, nothing else. He named it " a boy".
The beginning of NET was challenging, since he seemed to recall very little of his early years as a child in Somalia. He was also very economical with words and upon being asked to place flowers for good events in his life, he found there was no event that would deserve a flower. He simply placed two stones on his lifeline, one for the day his parents were shot in front of him, one for the time he reached Nairobi as a refugee, a time when he had to struggle hard to stay alive in the absence of any aid.
After NET 1 (session 1), he did recall his early years in quite some detail and even remembered some joyful events; for one of which he later placed a flower: 'the time I used to play football with my dad in the evenings in our compound'.
After having witnessed the death of his parents and being able to escape through the back of the house, he was completely on his own. He escaped Mogadisho with a group of strangers, survived Nairobi by himself, eating left-overs at hotel garbage dumps and finally smuggled himself into Uganda by hiding in the back of a bus.
Excerpts of his story read:
I was born in Mogadisho, Somalia. I do not know my exact birthyear, I think it is 1986. I grew up with both my parents. I have a sister who is 2 years younger called Halimo and a 4 years younger brother called Mohamed. We lived in a part of town called ...
My mother had fair brown hair and skin. She was young and I loved her a lot. I was her first-born and her favourite. She even told me so. My father was of darker complexion. He was also a young man in those days. He was hard working. He had a shop close by in the market. He would usually leave in the morning and return home in the evening. Sometimes when he came home, he played with us in the evening. We played football together. Those were good times. I do not know how old I was then; I just remember that I was very young...
When I remember those days I get sad. All these memories come back and I only know what I have lost. The years went by and I used to live like this until the war broke out. I don't remember the year, but I was still young... One day we fled from home in the late afternoon...We went with a car to a place called Bal'aad, about 30 km out of town...
Eventually we went back home to Mogadisho. I must have been about 10 years by then. A few months later, the war reached us again. It was early in the morning. A group of about 10 civilian men reached came to our house. They were armed with guns...
I stood very near to my parents. I was so scared. Suddenly I heard the sound of bullets. One of the soldiers had started shooting. The moment I saw that he pulled the trigger and heard the first bullet, I panicked. I started running. I felt such great fear. I ran inside the house and tried to hide myself behind a door in one of the rooms. I was shivering, fearing, thinking, they will also come for me, they will come and kill me'. I still have a heart beat now, when I recall that moment. After some time it went quiet outside. I still stood behind the door, silent, not moving. After a while I slowly moved towards the window and peeped out. What I saw was terrible. My mother and my father had been hit by the bullets. They were both lying on the ground. My mother had fallen on top of my father. They both had blood on their clothes. My mother had blood on her face and her stomach. They were not moving anymore, they had died. Until that day, I had never seen a dead person. I felt horror. I was so afraid of them, shocked by what I saw. I only thought of running away, leaving this place. I escaped through the back of the house and jumped over the fence. This was the last time I have seen my parents and also the last time I had been in our home in Mogadisho...
While fleeing, I joined strangers in the street. So many people were trying to flee. I simply ran with them. When these people reached their destination, they branched off from the road. It was night time by then. I was alone. I hated my life. I followed the road and finally fell asleep under a bush. I had given up about life by then. I felt like I had died as well. I knew about the danger of wild animals and lions, but I did not care...
This is how I came to Uganda. When we reached Kampala I saw a group of Somalis and went to greet them. They took me in and I lived with them for a few weeks. They also showed me how to register as a refugee with UNHCR. I remember the day I came to Nakivale Refugee Camp. I was so surprised how people can live in a place like this. I stayed with the Somali family that found me in Kampala for about two years in the camp. Finally, Red Cross helped me to build my own house in 2000, I was about 14 years then. Since then I live alone. I started going to school when I came to Nakivale. I will graduate from P7 at the end of this year. I have learnt how to live by myself; I can do everything by myself. I never ask for help. No one can help me anyway. I have never heard about my brother and sister again. Whether they are still alive and if so, where I could find them. But now I am ready to look for them.
As mentioned before, he has been surviving on his own since the age of 9 years. This has probably led to his enormous shyness but also an amazing sense of self-reliability. 'I can do everything by myself. I never ask for help. Anyway who could help me?' There is also a strong feeling of sadness and loneliness around him that is very moving. Our local translator Haji, who is also trained as a NET therapist, was moved to free flowing tears at several moments of AWH's life recall, specially when he spoke about his loneliness and desperation.
AWH is a smart boy, so he frequently challenged the concept of therapy in the beginning. 'It won't make my parents come back, and it won't change my life situation'. AWH has never really entered a state of expressing strong emotions like crying or anger during therapy. He said he could not cry, also not by himself. There were however visible signs of emotional processing like tears and strong heartbeat especially during NET 1 and 2.
AWH reported having strong PTSD symptoms when he started therapy, especially continuous nightmares and flashbacks, mainly related to the day his parents were killed. Re-experiencing actually increased, he said, once therapy was started. After NET 4 he talked of having fewer symptoms. In his last session AWH talked about wanting to try and trace his family with the help of the Red Cross. He was especially interested in finding his two younger siblings.
When the sum of symptoms were counted according the CIDI-K section, AWH had a sum score of 12 in the CIDI pre-test. This had decreased to 8 in the CIDI post-test immediately after the end of therapy, and 9 at the nine-month follow-up. At the nine-month follow-up, AWH was looking well-dressed, and had put on both height and weight. He had completed his primary school education at the camp primary school and spoke confidently of his plans. He had also joined the camp soccer team and played along with the group now every evening, a significant behavioural change, given that he previously would not even talk or socialize with others. He was not more friendly than usual, but admitted significant symptom reduction to an expert evaluator who had never seen him before.
Case two – UG
UG was a pretty seventeen-year old girl in March 2003 when she was interviewed by a locally trained interviewer. She looked, however, visibly ill and strained -quite unlike a normal happy young woman. She complained of constant headache and pain in her eyes. UG's PTSD diagnosis was confirmed within a two-week period by an expert using the CIDI.
UG did not wait to be offered treatment, but came herself to the project centre and requested for help. In her own words, "I have been to all the doctors but they have done nothing for me. All they give me are painkillers. I had to drop out of school because of my headaches and pain in my eyes." When the treatment protocol was explained to her, she was enthusiastic about relating her experiences and readily gave her assent. Her mother was quick to give her consent. She said she would try anything that would help her daughter. In her own words, ' My daughter has not been her real self for a long time.'
At the beginning of NET 1, UG drew a picture of the Somali flag. Asked to explain, she said she loved her homeland and hoped to go back there one day when there was peace. While laying her lifeline, UG included a happy family life in Somalia till the age of 4, her arrival in Uganda after a long and difficult flight itinerary and being accepted as a refugee by the UNHCR as the flowers in her life. The stones in her life represented the worst event, when her older brother was killed, her sister was severely injured and her two younger brothers were lost, never to be seen again, to date. Other stones symbolised flight difficulties such as extreme hunger, and a failure to access a solution for her headaches and eye pain, which she has had since the worst event.
In subsequent NET sessions, UG talked in detail about these events. Excerpts from her story read:
I was born on August 26th 1986 in Mogadishu.... I had six brothers, two younger than me and two sisters older than me. We were a very happy family. As a big family, we conversed a lot and made jokes. We were very happy with our father. He made us laugh and brought us presents whenever he went anywhere. This was a happy time till I was 4 years old...
One day,... we heard guns and bullets firing and we were excited. My father ran from work and picked up the other children from school and came back home with them. Some people came to chase us away from our house because we were a minority clan (Madiban). They were from the Hawie (Habrigidir). They were men, very many. They told us to leave everything and flee from the house. They did not beat us. I was still a child, with a soft head. I heard the bullets and started vomiting and fell down. My mother picked me up and put me on her back. We all left the house...
On the way, we met very many militia men dressed as army men. They told us to lie down on the ground. I was still crying. The rest were silent. One of them knocked me with the butt of the gun on the soft part of my head. Then I kept quiet. They wanted to kill everyone...
They put us in a house for security purposes. A heavy gun was shot near the house. There was another house near our house. They shot this house and the fragments reached our house. Some people were killed in our group, including my brother. He was older than me. He was called Mahad. He was in his school uniform. He fell down on his stomach. I did not see him fall but I saw the blood. My sister Khadija was lying down when the fragments hit her. I did not see any blood, but the fragments went into her stomach and she was hurt in her stomach. My father thought she was dead, but people said she was still alive and she was still talking. He went to her and told her to get up. She could not get up. My father carried her to the hospital. Two of my brothers, Abdirahman aged four years, and Abdirasaq aged three years, disappeared in that group as everyone ran away. They were my two younger brothers. My dead brother Mahad was left there. We never saw my two brothers who disappeared again. So many other people died as well...
After one year, we came back to Mogadishu. We found our father and sister in the hospital. They first stayed in the hospital for some time, then moved to a house. My sister had been operated on. My father had become a bit deaf because of the gunshot.
We decided to leave Somalia and go somewhere else more secure. We left Somalia with nothing. My mother, my father, my injured sister Khadija, and the other six children...
We went to Kampala. My mother was advised to go to the UNHCR and got a mandate. My sister Shamso and my cousin sister Fardosa also got separate mandates.... In 1997, we were resettled in Nakivale camp...
I hit my head down and I felt the pain of the gun again. I was not hurt but I got a terrible headache for three days. I went to the doctor but I did not get any assistance except Panadols and eyedrops. Since then, I was unable to go to school because the headaches increased. My eyes had begun paining from birth, but they increased with the headaches.
I am still here but I hope for a better future and a happier life e.g. to be resettled elsewhere, to have an education, to have a happy family of my own and to make contact with my lost loved ones.
Among her hopes and aspirations for the future, UG hoped to trace her missing brothers under the auspices of the Red Cross, as well as re-enter the education system. She also hoped to one day have a happy family of her own
In the final picture at the end of therapy, she drew a happy family inside a nice house, living in peace.
UG had a CIDI pre-test sum-score of 16; immediately after treatment, this reduced to 12 in the CIDI post-test and 1 at the nine-months follow-up. The nine months follow-up found UG no longer in the camp but in Kampala, the capital city of Uganda. She looked happy and cared about her appearance. She said she had no more headaches, and little eye problems. In her own words, "I feel like a newborn child," she told the blind evaluator. She had moved away from the camp to explore possibilities for further education, resettlement and to seriously try to trace her brothers. She also reported joining other adolescents when they were out to socialize. "My biggest dream is to play soccer myself, but as a girl, I would never be allowed. But at least I go and cheer to the boys when they play." She says her family members, especially her mother, have all noticed the difference in her and keep commenting on the improvements she has made. She is more like any healthy young woman.
Pilot study
All the patients accepted and completed treatment. Two patients were unavailable for the post-test as they had left the settlement after treatment. At the 9-months follow-up, all children could be tested again, as the investigation included a testing in other regions to which Somali refugees had moved. At baseline, all six had moderate to severe PTSD according to the CIDI (M = 14.3, SD = 1.9). Scores dropped to M = 9.0 (SD = 2.2) at post-test and again to M = 6.2 (SD = 3.3) at 9-months follow-up (see Figure 1 and Table 1). A mixed model (random factor: Subject, fixed factor: Time, missing data: restricted maximum likelihood), that allows the inclusion of all six cases in the analysis, indicated a significant reduction of symptoms across time; F (2,5) = 15.45, p < 0.01. This result was confirmed by a Friedman-test using row-wise-exclusion of the two missing cases: χ2 (df = 2) = 6.50, p = 0.039. The analysis at individual level showed that the symptom scores of each individual patient decreased in the period between the pre-test and the follow-up period.
Figure 1 Scatterplot of the sum of PTSD symptoms as recorded by the CIDI-K section across therapy. Both a mixed model ANOVA and a Friedman test confirmed a significant reduction of symptoms between time intervals.
Table 1 The participants' individual scores on the PTSD section of the Composite International Diagnostic Interview at the timepoints pre-treatment, post-treatment and 9-months follow-up.
Code Age Sex CIDI pre CIDI post CIDI follow-up
AMA 16 female 12 9 7
ABJ 15 male 16 6
HI 13 female 15 7 4
DMM 16 male 15 10
AWH 15 male 12 8 9
UG 17 female 16 12 1
M (SD) 15.3 (1.4) 14.3 (1.9) 9.0 (2.2) 6.2 (3.3)
After nine months, four of the six patients no longer met the criteria for PTSD. The remaining two both had borderline scores.
Before treatment, four of the six patients presented with clinically significant depression as they fulfilled DSM-IV criteria for major depression according to CIDI interview. None of the subjects met the criteria for clinically significant depression according to the CIDI at the post-test or the 9-months follow-up.
Discussion
In this pilot trial we tried to get a first impression on the efficacy and safety of KIDNET, a short-term treatment approach for the therapy of traumatized adolescents.
Results showed an important reduction in posttraumatic symptoms, as early as the post test. At the 9-months follow-up, 2 of the 6 patients still fulfilled PTSD criteria, but now at borderline levels and with less functional impairment. Clinically significant depression has remitted to non-clinical levels in all four adolescents who had presented with depression in the pre-test.
This study presents with the limitations of pilot studies with small sample size. Symptom changes cannot be causally attributed to treatment, but might also be caused by spontaneous remission. Nevertheless, given the cross-sectional data available, in particular, the high prevalence of PTSD in the Somali refugee population (with nearly 50% [45]), it seems unlikely that spontaneous remission has occurred at this rate. Otherwise, the high prevalence would be difficult to explain, as the PTSD should have remitted earlier.
Neither the clinical impression nor the symptom scores indicated a worsening of the symptoms in any of the patients. Therefore, this pilot study suggests that NET might be used effectively as a short-term treatment with child patients even in the unsafe conditions of a refugee camp in an African country. A possible adjustment would be to allocate more sessions where needed, such as where traumatic events were particularly severe or numerous.
The case reports illustrated that the child patients were able and willing to narrate their traumatic experiences, especially with the aid of illustrative material. There is also evidence that children can recall details of traumatic events that occurred when they were younger. Teenaged children are also able to comply with short-term treatment approaches such as the version of NET presented here.
It is noteworthy that this group of children had multiple and very severe war events and yet showed a clear benefit from treatment with NET. This encourages research into the effectiveness of KIDNET with other child trauma populations such as child PTSD after single stressors, after natural disasters or after accidents. More pressing of course, are randomized controlled trials comparing KIDNET to existing therapies for children. Any such comparisons between different groups of children has to await further research.
It is often a matter of survival that mental function is restored to an extent that the survivor can cope with the daily stressors and that children actively take advantage of scholastic opportunities and ultimately strive for finding ways out of the camp.
In this study, the therapies were carried out by highly trained experts. Given the large numbers of possibly traumatised youth in post-conflict low-income areas worldwide, treatment costs would be prohibitive unless further research can increase the ease with which non-professional paramedics can acquire adequate therapy skills through rigorous short-term training and supervision.
Conclusions
KIDNET proved to be a feasible method for the treatment of traumatized children in an African refugee settlement. The clinical observations and the assessed reduction in symptoms should approve KIDNET to be tested in further controlled trials.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
The study was designed by LPO, FN, MO, MS and TE. PLO, VE, and ES carried out the treatments and the assessments, FN and MS supervised the treatments. Data was analyzed by FN and LPO. LPO drafted the manuscript, all authors revised the manuscript and approved the final version.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
Research was supported by the Deutsche Forschungsgemeinschaft, and the NGO vivo . We would like to thank Martie Hoogeeven for assistance in treatment and data acquisition.
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| 15691374 | PMC549194 | CC BY | 2021-01-04 16:33:03 | no | BMC Psychiatry. 2005 Feb 3; 5:7 | utf-8 | BMC Psychiatry | 2,005 | 10.1186/1471-244X-5-7 | oa_comm |
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BMC Health Serv ResBMC Health Services Research1472-6963BioMed Central London 1472-6963-5-121568659910.1186/1472-6963-5-12Research ArticleHome injuries and built form – methodological issues and developments in database linkage Newcombe Robert G [email protected] Ronan A [email protected] Sarah J [email protected] Joanne [email protected] Department of Epidemiology, Statistics and Public Health, Cardiff University, Heath Park, Cardiff CF14 4XN, UK2 The Clinical School, University of Wales Swansea, Grove Building, Singleton Park, Swansea SA2 8PP, UK3 Welsh School of Architecture, Cardiff University, Bute Building, King Edward VII Avenue, Cardiff, CF10 3NB, UK2005 2 2 2005 5 12 12 30 4 2004 2 2 2005 Copyright © 2005 Newcombe et al; licensee BioMed Central Ltd.2005Newcombe 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 aim of this body of research is to determine whether injuries in the home are more common in particular types of housing. Previous home injuries research has tended to focus on behaviours or the provision of safety equipment to families with young children. There has been little consideration of the physical environment. This study reports methodological developments in database linkage and analysis to improve researchers abilities to utilise large administrative and clinical databases to carry out health and health services research.
Methods
The study involved linking a database of home injuries obtained from an emergency department surveillance system with an external survey of all homes in an area and population denominators for home types derived from a health service administrative database. Analysis of injury incidence by housing type was adjusted for potential biases due to deprivation and distance to hospital. For non-injured individuals data confidentiality considerations required the deprivation and distance measures be imputed. The process of randomly imputing these variables and the testing of the validity of this approach is detailed.
Results
There were 14,081 first injuries in 112,248 residents living in 54,081 homes over a two-year period. The imputation method worked well with imputed and observed measures in the injured group being very similar. Re-randomisation and a repeated analysis gave identical results to the first analysis. One particular housing type had a substantially elevated odds ratio for injury occurrence, OR = 2.07 (95% CI: 1.87 to 2.30).
Conclusions
The method of data linkage, imputation and statistical analysis used provides a basis for improved analysis of database linkage studies.
==== Body
Background
Home injuries are frequent and result in greater mortality and morbidity than road traffic injuries[1]. It is evident that the risks of some types of injuries, such as falls or injuries resulting from fire, could well be related to the built form of the home. Nevertheless the availability of robust evidence based on large numbers of cases is quite limited[2]. Previous home injuries research has tended to focus on behaviours or the provision of safety equipment to families with young children. There has been little consideration of the physical environment. Linkage of existing large datasets has the potential to yield substantial evidence.
The present study was designed to utilise three such datasets relating to all residential properties in a defined geographical area in the United Kingdom, the resident population, and their attendances at local hospital emergency departments (EDs). These datasets could not be linked comprehensively at individual level on account of constraints on identifiability of individuals. This article describes the novel challenges that result, and the methodology used to obviate them.
Methods
This study was carried out as part of the wider Housing and Neighbourhood and Health (HANAH) project[3]. This is a long-term partnership between academia and local authorities to elucidate the relationship between the social and built environment and health and to develop interventions to improve health. Data from an injury surveillance system on injury events in residents of the Neath-Port Talbot County Borough Council area was linked to a register of property types and denominator data. Ethical permission for the study was granted by the Morgannwg Local Research Ethics Committee.
All properties in the study area were viewed externally. Domestic properties were classified into categories based on floor area (four groups), five period groups, and five build types, viz. detached, semi-detached, flat conversions, purpose-built flats, and terraced housing. Ninety-four of the 100 combinations of the three housing type variables were found in the study area. Analysis was carried out at individual property level: analysis at postcode or zip code level was not possible because very few postcodes (13%) comprised a single property type. Postcodes contained an average of 14 properties.
Data on injuries treated at EDs were obtained for the period 1999 – 2000 from the All Wales Injury Surveillance System (AWISS) which routinely obtains individual level data from EDs surrounding the study area and is described in detail elsewhere[4]. Briefly, the data comprises the patient's address, age, sex, date of occurrence, type and anatomical site of injury (up to three diagnoses and three sites can be coded), and includes a code indicating whether the injury occurred at home or not. No information on precipitating factors such as falls, fires or drug abuse is included.
To obtain denominator data for each property type we used the National Health Service Administrative Register (NHSAR), a list of all people registered with the free-to-use primary care health service in Wales. Data on this system are highly confidential and denominator population profiles were obtained by providing a list of all properties in the ninety four different groups to the NHSAR staff who then matched these with their system and obtained the number of people in each of the property types, subdivided by age and sex. This system has previously been used to obtain small area population data[5].
In analysing data on injury attendance at hospital EDs it is important to take into account the potential confounders of deprivation and access, which are known to be strongly related to injury occurrence and ED attendance respectively[6]. For each of the injured individuals it was possible to assign an exact value for the Townsend Index of Material Deprivation and distance to hospital by road as the individual addresses were available[7]. The Townsend Index is a small area based deprivation index, commonly used in epidemiological studies in the UK, and derived from four census variables: home ownership, overcrowding, access to a car, and unemployment. It has been shown to be strongly related to the incidence of specific types of injuries[5,6]. For non-injured individuals this was not possible due to confidentiality constraints described above – only data aggregated at groups of address level was available. Linkage had to be performed in an indirect manner because a small number of properties in a single electoral division meant that data on age/sex compilation could be considered potentially identifiable and so could not be released.
During 1999 and 2000, 14,171 out of 112,248 residents made one or more emergency department visits for a home injury. We sought to combine three files comprising individual-level injuries data from an emergency department surveillance system; an external assessment of the built form in all 54,801 homes in the area; and denominator populations for each of ninety-four property types delivered from a health service registration system. Application of logistic regression to model injury risk on built form, property size and age, subject age, sex, deprivation and distance from emergency department jointly necessitates construction of a single linked data file. The objective was to construct an appropriately linked database and hence determine whether injuries occur more commonly in different types of home.
The study population of 112,248 individuals made 16,358 ED attendances for home injuries during the study period. The vast majority (99.5%, n = 16,277) of these attendance records included adequate data on age, gender, proximity and Townsend score. These 16,277 attendances involved 14,171 residents of the study area. Thus the average number of visits during the study period among those who ever visited the ED was 1.15, in other words 15% of the visits were repeat visits. The main analyses were constructed to compare the 14,171 first injury records identified as the subject's first attendance at ED for a home injury during the study period with those of the remaining 98,077 subjects. This has the effect of identifying all subjects who had one or more ED attendance for home injury during the study period.
The other datasets to be linked were the population distribution by housing group, age and sex (112,248 subjects, no missing data) and a file listing 54,913 properties, of which we restrict attention to the 54,801 with complete data. Table 1 shows how the three sets of data include different subsets of the variables. It is not possible to construct a comprehensively linked dataset at individual level enabling comparison of 14,171 injured and 98,077 uninjured subjects, because individuals in the latter group lack deprivation and proximity data.
Table 1 Variables included in the 3 datasets to be linked.
Variable Included in dataset for
Injuries Properties Population
Housing type (build type, period, floor area) Y Y Y
Sex Y N Y
Age Y N Y
Townsend score Y Y N
Proximity to hospital Y Y N
Type of injury (3 variables) Y N N
Anatomical site of injury (3 variables) Y N N
Following discussion of preliminary results it was decided to use actual deprivation and proximity scores for the injured, and to impute values randomly according to property type for the uninjured. This is appropriate because risk scores for the remaining variables, age and sex taken together as a forty two category categorical variable, were uncorrelated with risk scores for all other variables (see later), hence imputing according to property type alone and disregarding age and sex is a reasonable strategy.
The process of randomly imputing property records, and hence Townsend and proximity scores, to the 112,248 population according to housing type is not trivial. Using ordinary stratified sampling does not work, simply because the number of residents is larger than the number of properties. The overall occupancy ratio was 112,248 residents in 54,801 properties, i.e. 2.05 individuals per property, but this figure varied widely between the 94 property types. For example, for property type 1 there were just under 2 people per property, 114 properties and 226 population. We then choose randomly 114 of the 226 population to match one-to-one to the 114 properties in a random order, leaving the remaining 112 to be matched to a random sample of the 114 properties also in a random order. This simply achieves a maximal degree of representativity with an appropriate degree of randomness. A multi-stage randomisation and linkage process (further details available from the authors) successfully linked the vast majority (14,081/14,171) of first attendances with the merged population-properties file. This has the effect of producing a merged data file in which the deprivation and distance scores randomly imputed to the uninjured both incorporate the correct means to produce an appropriate degree of adjustment for confounding, and also the correct amount of variation to produce appropriate logistic regression coefficients to perform the adjustment.
The resulting linked file, comprising reconstructed data for all 112,248 residents, containing elements originating in population, properties and events files, has complete data for demographics, property type and randomly imputed Townsend and proximity measures. Among the 112,248 subjects, 14,081 are identified as having had one or more attendances for injuries following home accidents. Actual Townsend and proximity measures and the code for injury type 1 are available for each of the 14,081 injured individuals.
The actual and imputed Townsend and proximity values were summarised for the injured and uninjured and compared. This was done by t-test, paired or unpaired as appropriate, rather than by non-parametric methods which were associated with a serious loss of power due to the gross discreteness of the small area based, randomly imputed Townsend score. Associations between random and actual Townsend and proximity scores were characterised by Spearman rank correlations. Examination of these results, together with the low correlations of a risk score for age and sex with those for property type variables, Townsend and proximity, suggested it was appropriate to include in the logistic regression model composite Townsend and proximity scores, defined as the actual value in the injured and the randomly imputed value in the uninjured. Property size, age and build type were entered as categorical variables. Preliminary analyses indicated that Townsend score should be included as a continuous variable, but distance from hospital discretised into five categories. On account of the known marked sex-age interaction, sex and subject's age were entered together as a 42-group categorical variable, age being discretised into groups under 1, 1–4, 5–9, ..., 90–94 and 95 and over.
The main analysis proceeded as above, using the 14,081 who were ever injured during the study period as the group with the outcome of interest. Both univariate analyses for each explanatory variable in turn and a multivariate analysis were produced.
Also, the main analysis was repeated after re-running the randomisation parts of the linkage process. This step is more radical than might appear. In particular, due to the small amount of missing data, the randomised matching program does not pick up exactly the same set of 14,081 events records on both occasions. Essentially, the process draws 14,081 out of 14,114 potentially matchable events.
Results
Table 2 shows summary statistics for actual and randomly imputed Townsend score and proximity. The summary statistics for the randomly imputed Townsend and proximity scores based on all 112,248 subjects are very similar but not identical to those for the 54,801 properties, from which they have been drawn. The mean randomly imputed Townsend score for the injured is very similar to the mean actual score in the 14,081 injured subjects, 0.85 (p = 0.78). Conversely, the randomly imputed distance measures are similar in injured and uninjured (p = 0.12), but the randomly imputed values are significantly greater than the actual ones in the 14,081 injured (p < 0.001). For the Townsend score, the randomly imputed scores are highly significantly higher (i.e. more deprived) for the injured (mean 0.86) than the uninjured (mean 0.70, p < 0.001). For Townsend score and distance alike, the difference between the actual mean in the injured and the mean of randomly imputed values in those not injured is approximately correct to adjust for in the subsequent multivariate analysis, and the process incorporates the appropriate degree of variation at individual level.
Table 2 Summary statistics (mean and SD) for actual and randomly imputed Townsend score and proximity to hospital.
Basis Series n Townsend score Distance (km)
All properties 54,801 +0.74 (2.75) 8.33 (5.06)
Randomly imputed All 112,248 +0.72 (2.77) 8.36 (5.05)
Not injured 98,167 +0.70 (2.77) 8.37 (5.06)
Injured 14,081 +0.86 (2.76) 8.30 (5.03)
Actual Injured 14,081 +0.85 (2.77) 7.73 (4.87)
Table 3 gives Spearman rank correlations between random and actual Townsend and proximity measures. While all of these are statistically significant (p < 0.001), most are quite small. The correlation of nearly 0.2 between random and actual Townsend scores reflects the unsurprising, substantial variation in Townsend score between property types.
Table 3 Spearman rank correlations between random and actual Townsend and proximity measures.
Within groups between variables N Spearman rank correlation 95% confidence interval
Townsend v. distance
Randomly imputed 112,248 0.107 0.101 to 0.113
Actual 14,081 0.051 0.034 to 0.067
Randomly imputed v. actual
Townsend 14,081 0.193 0.177 to 0.209
Distance to ED 14,081 0.055 0.039 to 0.072
The effect of the random imputation process was explored in the main logistic regression model. In the final model the effect of age and sex jointly was dominant, followed by build type, then distance, property age, Townsend score (all p < 0.001) and floor area (p = 0.007). Table 4 shows the univariate and adjusted results with regard to build type, the housing variable with the clearest association with the proportion of subjects who ever attended for a home injury. Adjustment for the confounding effects of the other variables made some difference to the odds ratios, but the doubled risk of injury in build type D remained essentially unaltered.
Table 4 Main logistic regression model results. All first injuries (14,081 subjects out of 112,248). Odds ratios and X2 tests for effect of build type on proportion of subjects ever injured (a) unadjusted; (b) adjusted for other factors after random imputation of deprivation and distance scores to the uninjured; and (c) adjusted for other factors after re-randomisation.
Build type Number of residents Univariate model Adjusted for other factors, original random imputation Adjusted for other factors, re-randomisation
Odds ratio Odds ratio (95% CI) Odds ratio (95% CI)
A 15,877 0.790 (0.746–0.837) 0.890 (0.831–0.954) 0.892 (0.832–0.955)
B 35,791 1.049 (1.009–1.091) 1.108 (1.055–1.165) 1.109 (1.055–1.166)
C 280 1.003 (0.703–1.431) 1.106 (0.768–1.592) 1.113 (0.774–1.600)
D 2,695 2.046 (1.863–2.247) 2.074 (1.870–2.301) 2.074 (1.869–2.301)
E 57,605 1.000 1.000 1.000
X2 (4 df) 327.5 254.5 254.1
p-value <0.001 <0.001 <0.001
Distance to ED (km)
4.26 and below 1.431 (1.352–1.514) 1.469 (1.384–1.560) 1.467 (1.381–1.557)
4.27 – 5.57 1.288 (1.211–1.369) 1.413 (1.317–1.516) 1.409 (1.314–1.512)
5.58 – 8.69 1.385 (1.308–1.467) 1.356 (1.276–1.440) 1.352 (1.273–1.437)
8.70 – 13.25 1.168 (1.100–1.240) 1.243 (1.166–1.325) 1.248 (1.170–1.330)
13.26 and above 1.000 1.000 1.000
X2 (4 df) 194.8 (p < 0.001) 179.9 (p < 0.001) 176.9 (p < 0.001)
Townsend score 1.020 (1.014–1.027) 1.016 (1.008–1.024) 1.016 (1.008–1.024)
X2 (1 df) 36.8 (p < 0.001) 15.4 (p < .0.01) 15.9 (p < 0.01)
The results of the main multiple logistic regression model in table 4 were used to construct risk scores for each individual representing age and sex, the three property variables, and the composite distance measure. Table 5 shows parametric correlations of the risk score for sex and age with those for the three property variables and the composite distance measure, and the composite Townsend score. (This is, of course, equivalent to using a risk score based on it as it is entered as a linear factor in the model). Even though all but one of these correlations is highly significant, all of them are sufficiently small that we can regard the random imputation process as reasonable.
Table 5 Parametric correlations of risk scores for age and sex with those for other factors.
Parametric correlation of risk score for age and sex with: 95% confidence interval
Risk score for floor area +0.027 +0.021 to +0.033
Risk score for age of property -0.020 -0.026 to -0.014
Risk score for type of property +0.028 +0.022 to +0.034
Townsend score working +0.026 +0.020 to +0.031
Risk score for distance -0.003 -0.009 to +0.003
Discussion
The main methodological finding of the study is that the random imputation process developed here is a reasonable one. This approach enabled us to base analyses on a very large dataset notwithstanding confidentiality issues precluding comprehensive linkage directly at individual level. It is feasible to incorporate randomisation into the linkage process, even when the target group is larger than the source. The reasonableness of the imputation process can be judged by comparison of the actual and imputed variables for the injured population. For the Townsend score the actual and imputed scores are essentially identical in distribution, thus showing that the methodology does not produce a biased result. For the distance variable the mean imputed value is 7.4% higher than the actual distance. Whilst this difference is statistically significant the magnitude of the effect on residual confounding cannot be large, given the odds ratios for attendance rates by distance in Table 4, which indicate that a 1% change in distance produces around a 1% change in the odds ratio for attendance.
The low correlation between randomly imputed and actual values, for distance from hospital and Townsend score, could result in attenuated regression coefficients and hence underadjustment for the confounding effect of these variables. For distance, which is by far the more influential of the two variables, a logistic regression in which the entire population of 112,248 is assumed to have the same distribution into the 5 distance groups as applies to the 54,801 properties gives odds ratios 1.469, 1.318, 1.445, 1.200 for the first 4 distance categories relative to the 5th (most distant) one. These figures are similar to those obtained in the univariate logistic regression based on the composite distance measure, and suggest that the latter regression coefficients, and hence also those in the multiple regression, may be attenuated by around 10% only.
Of primary importance to the validity of the methodology set out here, the results obtained after a second randomisation were almost identical. The unadjusted analyses for age-sex and housing type were unaltered, as these variables do not come from the random imputation. The analyses for deprivation and proximity and the results of multivariate analyses for build type and other variables were altered, but only to a very minor degree. These results provide considerable reassurance that the random element that was necessary in order to achieve the linkage process introduced very little additional uncertainty into the final analyses.
It appears that injured people tend to live in property types more associated with deprivation than the uninjured. Their actual Townsend scores are in line with what we would expect from their property types. On the composite data, i.e. when we replace random by actual Townsend scores for the injured only, there is a substantial difference in mean Townsend score, 0.85 v. 0.70, and all the 0.15 points difference is attributable to a real effect of deprivation on risk.
Conversely, the injured and uninjured tend to live in property types equally distanced from hospital. The actual distance is less for the injured than the randomly imputed distance, which is in line with the known tendency for hospital attendance for less serious types of injury to be related to proximity(6). On the composite data (with means 7.73 v. 8.37 km), nearly the whole of the difference (0.57 out of 0.64 km) is attributable to this self-selection effect.
Conclusions
This process is an important methodological development to increase the power of linkage studies when all individual data elements are not available for all individuals. As a result the analysis was based on 112,248 subjects and not on ninety-four groups. Thus, the power to detect important differences is substantially enhanced.
Further work is continuing in the relationship between specific features of built type and injury occurrence, using the methodology described in this paper.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
All authors contributed to the design of the study. RGN devised the conceptual design of the data imputation and carried out the statistical analysis. All authors read and approved the final manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
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Lyons RA Jones SJ Deacon T Heaven M Socio-economic variation in injury in children and older people: population based study Injury Prevention 2003 9 33 37 12642556 10.1136/ip.9.1.33
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| 15686599 | PMC549195 | CC BY | 2021-01-04 16:31:52 | no | BMC Health Serv Res. 2005 Feb 2; 5:12 | utf-8 | BMC Health Serv Res | 2,005 | 10.1186/1472-6963-5-12 | oa_comm |
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BMC CancerBMC Cancer1471-2407BioMed Central London 1471-2407-5-151570307010.1186/1471-2407-5-15Research ArticleUse of a recombinant Salmonella enterica serovar Typhimurium strain expressing C-Raf for protection against C-Raf induced lung adenoma in mice Gentschev Ivaylo [email protected] Joachim [email protected] Andreas [email protected] Tamara [email protected] Jakob [email protected] Werner [email protected] Ulf R [email protected] Institut für Medizinische Strahlenkunde und Zellforschung (MSZ), University of Wuerzburg, D-97078 Wuerzburg, Germany2 Daniel-Swarovski-Research Laboratory, Department of General and Transplant Surgery, Innsbruck Medical University, Innsbruck, Austria3 Department of Microbiology, University of Wuerzburg, D-97074 Wuerzburg, Germany2005 9 2 2005 5 15 15 15 9 2004 9 2 2005 Copyright © 2005 Gentschev 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
Serine-threonine kinases of the Raf family (A-Raf, B-Raf, C-Raf) are central players in cellular signal transduction, and thus often causally involved in the development of cancer when mutated or over-expressed. Therefore these proteins are potential targets for immunotherapy and a possible basis for vaccine development against tumors. In this study we analyzed the functionality of a new live C-Raf vaccine based on an attenuated Salmonella enterica serovar Typhimurium aroA strain in two Raf dependent lung tumor mouse models.
Methods
The antigen C-Raf has been fused to the C-terminal secretion signal of Escherichia coli α-hemolysin and expressed in secreted form by an attenuated aroA Salmonella enterica serovar Typhimurium strain via the α-hemolysin secretion pathway. The effect of the immunization with this recombinant C-Raf strain on wild-type C57BL/6 or lung tumor bearing transgenic BxB mice was analyzed using western blot and FACS analysis as well as specific tumor growth assays.
Results
C-Raf antigen was successfully expressed in secreted form by an attenuated Salmonella enterica serovar Typhimurium aroA strain using the E. coli hemolysin secretion system. Immunization of wild-type C57BL/6 or tumor bearing mice provoked specific C-Raf antibody and T-cell responses. Most importantly, the vaccine strain significantly reduced tumor growth in two transgenic mouse models of Raf oncogene-induced lung adenomas.
Conclusions
The combination of the C-Raf antigen, hemolysin secretion system and Salmonella enterica serovar Typhimurium could form the basis for a new generation of live bacterial vaccines for the treatment of Raf dependent human malignancies.
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Background
The Raf proteins (A-Raf, B-Raf, C-Raf) are located upstream of MEK and downstream of Ras and represent an essential part of the mitogenic cascade [1-3]. Interestingly, Raf kinases are not only central players in cellular signal transduction, but are often causally involved in the development of cancer. Recently, B-Raf was found to be mutated in a broad range of malignancies including melanoma (more than 65%), and colon cancer [4]. In addition, overexpression of C-Raf was found in many tumors [5,6]. Therefore, these proteins are potential targets for immunotherapy as well as immunoprevention of tumors.
Here we describe the development of a C-Raf vaccine on the basis of an attenuated Salmonella enterica serovar Typhimurium aroA strain. Such recombinant live vaccines have been shown to efficiently elicit both, humoral and cellular immune responses against a variety of heterologous antigens [7,8]. In order to achieve stable expression of C-Raf we used the E. coli α-hemolysin (HlyA) secretion system which is fully active in Salmonella [9]. This transport machinery is the prototype of type I secretion systems and consists of three different components, namely HlyB, HlyD and TolC. The HlyA carries at its C-terminus a secretion signal of about 50–60 amino acids in length (HlyAs), which is recognized by the HlyB/HlyD/TolC-translocator, leading to direct secretion of the entire protein into the extracellular medium without the formation of periplasmic intermediates. In addition, fused to the C-terminus of heterologous proteins, the HlyAs leads to efficient secretion of such proteins by the recombinant bacteria. In our case, the whole C-Raf antigen fused to the C-terminal secretion signal of hemolysin was efficiently expressed and secreted by an attenuated Salmonella enterica serovar Typhimurium aroA strain. The effects of this recombinant vaccine were assessed in wild-type C57BL/6 or tumor bearing transgenic BxB mice.
Methods
Bacterial strains, plasmids, cell lines and mice
The bacterial strains, plasmids, cell lines and mice used in this study are listed in Table 1.
Plasmid transformation in Salmonella enterica serovar Typhimurium SL7207
The plasmids pMOhly1 and pMOhly-Raf were first transformed in competent Salmonella enterica serovar Typhimurium LB5000 (Tab. 1), a restriction-negative and modification-proficient strain by a standard transformation protocol for E. coli [10,11]. Subsequently, the plasmids purified from Salmonella enterica serovar Typhimurium LB5000 were introduced into Salmonella enterica serovar Typhimurium SL7207 by electroporation using a Bio-Rad Gene Pulser (Hercules, CA, USA) at 2.5 kV, 25 microfarads (μF), and 200 Ohm in a 0.1 cm electroporation cuvette.
Construction of the plasmid pMOhly-Raf
Sense primer 5' Raf: 5'-ATGGAGCACATACATGCATCTTGGAAG-3' and antisense primer 3'Raf: 5'-CAACTAGAATGCATGCAGCCTCGGGGA-3' were used to amplify by PCR a 1950 bp DNA fragment representing the entire craf gene from plasmid pUC13-c-raf-1 [12]. PCRs were performed in a Thermal Cycler 60 (Biometra, Göttingen, Germany) for 30 cycles of 94°C for 1 min, 55°C for 1 min, and 72°C for 90 s. After purification with the GeneClean Kit (Bio101, La Jolla, Ca) and digestion with the NsiI restriction enzyme, the DNA fragment carrying the craf gene was inserted into the single NsiI site of the export vector pMOhly1 [13]. The resulting plasmid pMOhly-Raf was isolated from E. coli DH5α (Invitrogen), analyzed and transformed in S. typhimurium SL7207 (Tab. 1) by electroporation.
Western blot analysis
Salmonella enterica serovar Typhimurium strains harbouring the recombinant plasmids pMOhly1 or pMOhly-Raf were cultivated at 37°C in BHI medium with 100 μg/ml ampicillin. Cells at the exponential growth phase (OD600 of 1) were centrifuged at 5000 × g at 4°C for 5 min. The supernatant proteins were precipitated with 10% (V/V) trichloroacetic acid (TCA) for 1 h on ice, collected by centrifugation and resuspended in SDS sample buffer. The supernatant proteins were separated on 10% gels by SDS-PAGE [14]. For immunodetection of Raf-HlyA proteins the rabbit polyclonal anti-Raf antibody SP-63 (diluted 1:1,000, Rapp Laboratory) and donkey anti-rabbit immunoglobulins linked to horseradish peroxidase (Amersham Pharmacia Biotech) diluted 1:1,000 as secondary antibodies were used. Blots were developed by enhanced chemiluminescence (ECL reagents; Amersham Biosciences, UK) and exposed on X-ray film (Kodak, XO-MAT-AR) for 1 min.
Immunization of mice with Salmonella enterica serovar Typhimurium SL7207 strains
Oral/intravenous prime boost protocol (p.o./i.v.)
In order to achieve a broad immune response encompassing both, the mucosal and systemic immunity against C-Raf, we combined oral immunization (p.o.) with an intravenous (i.v.) boost. In these experiments, seven weeks old C57BL/6 or BxB23 mice were immunized, first p.o. three times with 5 × 109 bacteria/100 μl phosphate-bufferd saline (PBS) at 5-day intervals. At day 45 after the start of the vaccination, these mice were boosted intravenously (i.v.) with a single-dose of 5 × 105 bacteria/100 μl PBS. The BxB23 mice received a second i.v. boost of 5 × 105 bacteria at day 90 after the start of the vaccination. Induction of Raf-specific immune responses were analyzed at day 50 for C57BL/6 or at day 95 for BxB23 respectively.
Intranasal Immunization (i.n.)
Seven weeks old BxB23 mice were immunized i.n. four times with 1 × 107bacteria/30 μl phosphate-buffered saline (PBS) at 14-day intervals. The vaccine was applied using a micropipette onto the nares of mice under anesthesia.
Induction of Raf-specific immune responses were analyzed at day 70.
I. n. Immunization of BXB11 mice with Salmonella enterica serovar Typhimurium SL7207/pMOhly-Raf
Four months old BXB11 mice were immunized i.n. three times with 1 × 108salmonellae in 10 μl PBS at 14-day intervals. The vaccine was applied using a micropipette into the nares of mice without anesthesia.
Construction of a C-Raf overexpressing EL-4 cell line
In order to create tools for analysis of C-Raf specific T cells we first constructed a C-Raf overexpressing EL-4 cell line (ELRaf). The EL4 tumor cell line is a murine thymoma cell line of the H-2b haplotype (Tab. 1). 10 μg purified DNA of plasmid pDNA3craf was introduced into EL4 cells by electroporation with the Bio-Rad Gene Pulser (Hercules, CA) at 0.25 kV, 960 μFD, in a 0.4-cm electroporation cuvette. The transformed cells were grown RPMI 1640 medium (Invitrogen) supplemented with 5% (vol/vol) FCS (PAN Systems) and 600 μg/ml G418 (Sigma). C-Raf is highly expressed in ELRaf cells (data not shown).
Flow cytometric detection of specific CD8+ T-cells
Isolation of spleen cells
Animals were sacrificed and a single cell suspension of splenocytes was prepared by passage of the spleen through a sieve into RP 10 medium [RPMI medium (Life Technologies) supplemented with glutamine (1%), 50 μM β-mercaptoethanol (ROTH, Wuerzburg), penicillin (10 U/ml, GIBGO), streptomycin (100 U/ml, GIBGO) and 10% fetal calf serum (PAN™, BIOTECH GmbH).
The cell suspension was centrifuged and resuspended in 3 ml lysis buffer (5 mM Tris-HCl, 140 mM NH4Cl, pH 7.3) for the lysis of erythrocytes. After 2 minutes, 10 ml RP 10 medium was added to stop lysis. After centrifugation, cells were resuspended in 2 ml RP 10 medium and counted.
Restimulation
In 6 ml FACS tubes and a total volume of 100 μl RP 10 medium in the presence of 30 U/ml recombinant IL-2 and 10 μg/ml Brefeldin A at 37°C, 5% CO2, 1 × 106 spleen cells were incubated for 5 hours with 5 × 105 C-Raf overexpressing EL-4 cells (EL-Raf) or 5 × 105 EL-4 cells or with the addition of 10 ng/ml of phorbol myristyl acetate (PMA; Sigma) and 500 ng/ml of ionomycin (Sigma) or with medium alone.
Staining
After restimulation, cells were washed with PBS-0.1% bovine serum albumin (BSA; P-B buffer) and incubated with 1 μl of anti-CD8-CyChrome (Pharmingen Nr. 01082A) in a volume of 100 μl PBS-0.1% BSA for 20 min on ice. Subsequently, cells were washed and fixed for 20 min at room temperature with PBS-2% paraformaldehyde (Sigma). After washing with PBS-0.1% (BSA), cells were permeabilized with PBS-0.1% BSA-0.5% saponin (Sigma, P-B-S) buffer. After incubation for 5 min at room temperature, cells were washed with P-B-S buffer and incubated in a volume of 100 μl at room temperature with polyclonal rat immunoglobulin G (IgG) antibodies (JacksonImmunoResearch) to block nonspecific binding and 1 μl anti-IFN-γ-FITC (AN18.17.24; XMG1.2 Rat IgG1; Pharmingen) for 20 min. After incubation, cells were washed twice with P-B-S buffer and another time with P-B buffer. Cells were resuspended in 400 μl PBS-PFA 0,5% and kept at 4°C until analysis.
Analysis
Cells were analyzed by flow cytometry in a FACS Calibur flow cytometer (Becton Dickinson) using CellQuest 3.0 software (Becton Dickinson). Lymphocytes were chosen according to their size and granularity in a forward/side – scatter diagram. Numbers are expressed as percent IFN-γ positive CD8+ cells.
Statistical analysis
The statistical significance of differential findings between experimental groups was determined by Student's t test. Findings were regarded as significant, if P values were <0.05. Survival curves were compared using a log rank test.
Results
Creation of a C-Raf vaccine on the basis of the attenuated Salmonella enterica serovar Typhimurium strain SL7207
The construction of the attenuated Salmonella enterica serovar Typhimurium aroA strain SL7207 secreting the C-Raf antigen was achieved by cloning the human craf cDNA from pUC13-c-raf-1 [12] into the vector plasmid pMOhly1 [13] as described in materials and methods. The resulting plasmid pMOhly-Raf carried the craf-hlyAs fused gene and the functional hlyB and hlyD genes required for its secretion (Fig. 1). The S. typhimurium SL7207/pMOhly-Raf strain efficiently expressed and secreted the hybrid C-Raf protein, as shown by immunoblotting with polyclonal antibodies raised against C-Raf (Fig. 2). The amount of secreted C-Raf was 2–3 μg protein/ml supernatant under the experimental conditions.
Raf-specific responses of mice after immunization with recombinant SL7207/pMOhly-Raf
The efficacy of the recombinant bacterial strain to induce a Raf-specific immune response was analyzed using wild-type C57BL/6 and transgenic BxB23 mice. Groups of five C57BL/6 and BxB23 mice at the age of 7 weeks were immunized p.o./i.v or i.n. with recombinant Salmonella enterica serovar Typhimurium SL7207 secreting C-Raf antigen (SL7207/pMOhly-Raf) and with Salmonella enterica serovar Typhimurium SL7207 as control in order to test the induction of Raf-specific immune responses. The data showed that 20% of the sera of BxB23 mice immunized with SL7207/pMOhly-Raf contained Raf-specific antibodies (Fig. 3; supplementary Fig. 1 [see Additional file 1]). In contrast, no Raf-specific IgG response was detectable in the sera of BxB23 mice immunized with SL7207 alone (data not shown). Similar data were obtained after immunization of C57BL/6 mice with SL7207/pMOhly-Raf and SL7207 (data not shown).
To assess the induction of Raf-specific T-cell responses, mice were sacrificed and Raf specific T-cell responses were assessed using intracellular IFN-γ staining followed by FACS analysis. For this purpose, T-cells were restimulated with C-Raf overexpressing EL-4 cells. Using this technique, we could detect Raf specific CD8+ T-cell response in C57BL/6 animals immunized p.o./i.v. with SL7207/pMOhly-Raf only but not in mice immunized i.n. or with the control strain SL7207 (Fig. 4). In immunized BxB23 mice, but not naïve BxB23 mice, a high background and variability of CD8+ IFN-γ positive cells even with non-specific stimulation was observed in two independent experiments. Therefore it was not possible to assess specific T-cell responses in this setting. Interestingly, the level of T-cells which responded to polyclonal stimulation by PMA / ionomycin was also reduced about 4 fold in comparison to C57BL/6 mice (data not shown).
Salmonella enterica serovar Typhimurium SL7207/pMOhly-Raf strain induced partial protection against lung cancer in transgenic mouse models of Raf oncogene-induced lung adenomas
To test the protective capacity of the immune responses induced by the recombinant Salmonella strains, groups of 6 to 10 heterozygous BxB23 mice at the age of 7 weeks were immunized p.o./i.v. or i.n. with recombinant Salmonella enterica serovar Typhimurium strain (SL7207/pMOhly-Raf) or with SL7207 as control. BxB23 mice normally show an induction of lung adenomas with short latency and at 100% incidence [15,16]. The development of lung adenomas in the vaccinated BxB23 mice was assessed for 13 months. Our analysis revealed a significantly delayed tumor growth (reduction of lung weight) in mice immunized i.n. or p.o./i.v. with SL7207/pMOhly-Raf compared to control mice (Fig. 5).
In order to confirm these data we repeated the protection experiments using BxB11, another craf transgenic strain, which develop lung adenomas after a shorter latency period compared to BxB23 mice [15]. In this case, 66% of the mice immunized with SL7207/pMOhly-Raf survived at least three months longer than the control mice (Fig. 6).
These results suggest that the immunization with the vaccine strain SL7207/pMOhly-Raf can achieve a partial protection against tumor growth in the BxB mouse model.
Discussion
The major problems for vaccine development against cancer are the heterogeneity of the tumor cells and the fact that all tumor antigens are self-antigens. Therefore specific T-cells might be anergic or tolerant [17,18].
However, despite these problems, several cancer vaccines have already reached clinical trials [19]. The success of these vaccines seems to be dependent on the target antigen and on the tumor type.
Here we describe a new strategy for achieving an anti-tumor immune response with a C-Raf vaccine on the basis of an attenuated Salmonella enterica serovar Typhimurium aroA strain as a "live vaccine". In general, recombinant aroA salmonellae are efficient live bacterial vectors that stimulate strong mucosal immunity, humoral and cell-mediated responses with a great potential as live vaccine carriers in both humans and animals [7,20]. Advantages of live attenuated aroA Salmonella vaccines include their safety and easy administration [21,22]. In addition aroA Salmonella enterica serovar Typhimurium strains were already successfully used as carriers for DNA vaccines against cancer in mice [23].
In this study the C-Raf antigen was delivered in secreted form by attenuated Salmonella enterica serovar Typhimurium aroA strain using the E. coli hemolysin secretion system. This system allows an efficient antigen secretion and presentation, which are necessary for an optimal immune response against the given heterologous antigen [9]. In fact, immunization of mice with the Salmonella enterica serovar Typhimurium aroA strain SL7207 secreting C-Raf resulted in the induction of a humoral immune response, manifested by the presence of Raf-specific antibodies in some of the vaccinated mice. In addition, C57BL/6 mice immunized with Salmonella enterica serovar Typhimurium SL7207/pMOhly-Raf developed a Raf-specific CD8+ T-cell response. The C-Raf vaccine thus is able to break the peripheral tolerance of the immune system towards C-Raf and to induce a specific immune response. Although the transgenic model is closer to the human setting in comparison to challenge models with tumor cell lines, we can not formally exclude that lung specific expression of the transgene in our BxB model is not sufficient for the induction of peripheral tolerance. Furthermore, side effects due to autoimmunity might occur in humans who have a more generalized expression pattern. However, the lung tissue does not belong to immunoprivileged sites and we have never observed any signs of lung pathology in immunized animals which strongly suggests that the data could, in principle, be translated into the human setting.
We demonstrated also a partial tumor protection both in BxB23 and in BxB11 mice after immunization with recombinant Salmonella enterica serovar Typhimurium SL7207/pMOhly-Raf. However, we were not able to assess Raf specific CTL responses in these mice due to the high variability and background and therefore we cannot conclude whether protection is really due to cytotoxic T-cells or might be the result of other effects, e.g. an increased intratumoral level of IFN-γ produced by Raf specific CD4+ T-cells. Interestingly, the observed variation occurred only in treated BxB23 mice, not in naïve BxB23 mice. Therefore, the observed effect might be due to a spontaneous induction of an immune response mediated by tumor infiltrating bacteria. It is interesting to note that spontaneous Raf specific immune responses also occur in the human context, which we have recently demonstrated B-Raf V599E specific CTL and B-Raf /B-Raf V599E specific humoral responses in melanoma patients [24,25].
Most importantly, the lack of B-Raf V599E mutations in metastases of melanoma patients with strong B-Raf V599E CD8 response [24] supports the notion that CD8+ T-cells are effective in eliminating antigen positive tumor cells. The combined data thus provide proof of concept for the development of Raf-based anti-cancer vaccines.
This is the first example demonstrating that the E. coli hemolysin secretion system is a versatile tool for the delivery of cancer antigens in Salmonella enterica serovar Typhimurium. Moreover, we have recently shown that this secretion system is also fully active in Salmonella enterica serovar Typhi Ty21a, the only Salmonella vaccine strain registered for human use [26]. Therefore, the combination of the hemolysin secretion system and S. typhi Ty21a could form the basis for a new generation of live bacterial vaccines against cancer.
Conclusions
Taken together we have demonstrated that the C-Raf antigen can be successfully expressed and secreted by the attenuated Salmonella enterica serovar Typhimurium aroA SL7207 strain via the E. coli hemolysin secretion system. In addition, the immunization of wild-type C57BL/6 or tumor bearing transgenic mice with this C-Raf secreting Salmonella strain provoked specific C-Raf antibody and T cell responses. Most importantly, the vaccine strain induced partial protection against lung cancer in two transgenic mouse models of Raf oncogene-induced lung adenomas.
The approach may provide a new strategy for the rational design of cancer therapies.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
IG, JF and JT designed the study. IG drafted the manuscript. JF was also involved in writing the report. AS and JF did the FACS analyses. JT constructed the EL4Raf cell line. TP, AS, JF and IG carried out the immunization of mice and the Western blot analyses. WG and URR were involved in providing the conceptual framework for this study. All authors approved the final version of the manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Supplementary Material
Additional File 1
Supplementary figure 1: C-Raf-specific IgG in sera of p.o/i.v. (A) or i.n (B) immunized BxB23 mice (serum dilution 1:1000) demonstrated by western blotting. Supplementary figure with WESTERN Blot analysis of positive C-Raf sera.
Click here for file
Acknowledgements
We would like to thank G. Dietrich and J.C. Becker for helpful discussions and Z. Sokolovic and H. Drexler for critical reading of the manuscript. This work was supported by grants from the Bavarian Research Cooperations Abayfor (Forimmun T3), Theraimmune GmbH (Wuerzburg) and the Fond der Chemischen Industrie.
Figures and Tables
Figure 1 Restriction map of plasmid pMOhly-Raf The plasmid pMOhly-Raf contains the intact structural genes hlyC, hlyB and hlyD of the hemolysin operon and the c-raf-hlyA fusion hybrid gene. All genes are transcribed from the original cis-acting expression sites in front of hlyC [27]. Abbreviations: ori – origin of replication, bla – ampicillin resistance cassette
Figure 2 Identification of the Raf-HlyAs fusion protein by immunoblotting. Cultures of Salmonella enterica serovar Typhimurium SL7207 carrying the plasmids pMOhly1 (lanes 1 and 3) or pMOhly-Raf (lanes 2 and 4) were grown in BHI medium to a density of 5 × 108 cells per ml (optical cell density OD600 = 1). Supernatant proteins precipitated from 1.5 ml of bacterial culture were loaded in lanes 1 and 2; cellular proteins from 0.15 ml of culture were loaded in lanes 3 and 4. The immunoblot was developed with polyclonal anti C-Raf antibodies. The samplers were prepared as described in Materials and Methods.
Figure 3 Raf-specific IgG in sera of i.n (A) or p.o/i.v. (B) immunized BxB23 mice (serum dilution 1:200) demonstrated by western blotting. Proteins of 106 lysed SF9 cells expressing recombinant C-Raf [28] (lanes marked with +) or proteins of 106 lysed SF9 cells (– lanes) as control were loaded per lane.
Figure 4 Increased frequency of IFN-γ-secreting CD8+ T cells after p.o./i.v. Salmonella infection of C57BL/6 mice (n = 3). For each group, 1 mouse was assessed individually and the remaining splenocytes from 2 mice were pooled in an equivalent proportion. 1 × 106 spleen cells restimulated with either wild-type EL-4 (EL-4) or C-Raf overexpressing EL-4 cell (EL-Raf) and not stimulated (NST) were used. Production of IFN-γ was determined by flow cytometry after CD8 surface staining and intracellular IFN-γ staining. Each data point represents the proportion of IFN-γ positive cells for one individual mouse or two pooled mice respectively. Intracellular staining with an FITC-conjugated isotype control mAb always resulted in <0.05% positive cells.
Figure 5 Effect of immunization on reduction of lung weight. Reduction of lung weight is a mark for a delayed tumor growth. Lung weight of 12–13-month-old BxB23 mice immunized with SL7207/pMO-Raf (i.n., n = 10), SL7207/pMO Raf (p.o./i.v., n = 8), SL7207 (i.n or p.o./i.v., n = 6) and naive (n = 6). Bars represent means and standard deviation of the mice per group. Differences in lung weight (tumor weight) between experimental groups treated with SL7207pMO-Raf (i.n and p.o./i.v.) and all control groups were statistically significant * (P < 0.05), as determined by Student's t test. n – number of the mice
Figure 6 Survival of naive BxB11 (■) or BxB11 mice immunized intranasally with SL7207 pMOhly-Raf (▲) in period of one year.
Table 1 Bacterial strains, plasmids (ApR-ampicillin-resistant), cell lines and mice
Name Relevant characteristics/sequence Source or reference
Bacterial strains:
E. coli DH5α F-, ø80dlacZΔM15, Δ(lacZYA-argF)U169 deoR, recA1, endA1, hsdR17(rk-, mk+), phoA, supE44, λ-, thi-1, gyrA96, relA1 Takaba
Salmonella enterica serovar
Typhimurium aroA SL7207 hisG46, DEL407 [aroA544::Tn10 (Tcs)] Stocker, B. A. D.
Salmonella enterica serovar
Typhimurium LB5000 rk-, mk+ Stocker, B. A. D.
Plasmids:
pUC13-c-raf-1 c-raf cDNA in pUC13 [12]
pcDNA3 pCMV, ApR, Neomycin, SV 40, ColE Invitrogene
pcDNA-craf craf cDNA in pcDNA3 Troppmair, J
pMOhly1 ApR, hlyR, hlyC, hlyAs (encoding the hemolysin secretion signal), hlyB, hlyD [13]
pMOhly-Raf ApR, hlyR, hlyC, raf-hlyAs (encoding a C-Raf-hemolysin fusion), hlyB, hlyD this study
Cell lines:
EL-4 spontaneous murine lymphoma ATCC(Rockville, MD, USA)
EL-4Raf pcDNA-craf transfected EL-4 cells this study
SF9 insect cell line Gibco
SF9 Raf craf transfected SF9 cells [28]
Mice:
C57BL/6JolaHsd wild-type (H-2b) Harlan-Winkelmann, Borche, Germany
BxB23 [(C57BL/6 × DBA-2)F1] expressing an oncogenically activated NH2-terminal deletion mutant c-Raf-1-BxB under the control of human SP-C promoter [15]
BxB11 [(C57BL/6 × DBA-2)F1] expressing an oncogenically activated NH2-terminal deletion mutant c-Raf-1-BxB under the control of human SP-C promoter [15]
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| 15703070 | PMC549196 | CC BY | 2021-01-04 16:03:07 | no | BMC Cancer. 2005 Feb 9; 5:15 | utf-8 | BMC Cancer | 2,005 | 10.1186/1471-2407-5-15 | oa_comm |
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BMC Mol BiolBMC Molecular Biology1471-2199BioMed Central London 1471-2199-6-31569137510.1186/1471-2199-6-3Research ArticleRole of Leishmania (Leishmania) chagasi amastigote cysteine protease in intracellular parasite survival: studies by gene disruption and antisense mRNA inhibition Mundodi Vasanthakrishna [email protected] Ashwini S [email protected] Lashitew [email protected] Department of Biological Sciences, University of Calgary, Calgary AB T2N1N4, Canada2005 3 2 2005 6 3 3 21 9 2004 3 2 2005 Copyright © 2005 Mundodi et al; licensee BioMed Central Ltd.2005Mundodi 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 parasitic protozoa belonging to Leishmania (L.) donovani complex possess abundant, developmentally regulated cathepsin L-like cysteine proteases. Previously, we have reported the isolation of cysteine protease gene, Ldccys2 from Leishmania (L.) chagasi. Here, we have further characterized this cysteine protease gene and demonstrated its role during infection and survival of Leishmania (L.) chagasi within the U937 macrophage cells.
Results
The amastigote specific Ldccys2 genes of L. (L.) chagasi and L. (L.) donovani have identical gene organization, as determined by southern blots. In vivo expression analyses by Northern blots showed that Ldccys2 is amastigote specific. Western blot using anti-Ldccys2 antibody confirmed the amastigote specific protein expression. Recombinant expression of Ldccys2, a 30 kDA protein, was functionally active in a gelatin assay. Results from Ldccys2 heterozygous knockout mutants showed its role during macrophage infection and in intra-macrophage survival of the parasites. Since attempts to generate null mutants failed, we used antisense RNA inhibition to regulate Ldcccys2 gene expression. Not surprisingly, the results from antisense studies further confirmed the results from heterozygous knockout mutants, reiterating the importance of amastigote specific cysteine proteases in Leishmania infection and pathogenesis.
Conclusions
The study shows that Ldccys2 is a developmentally regulated gene and that Ldccys2 is expressed only in infectious amastigote stages of the parasite. The collective results from both the heterozygous knockout mutants and antisense mRNA inhibition studies shows that Ldccys2 helps in infection and survival of L. (L.) chagasi amastigotes within the macrophage cells. Finally, antisense RNA technique can be used as an alternate approach to gene knockout, for silencing gene expression in L. (L.) chagasi, especially in cases such as this, where a null mutant cannot be achieved by homologous recombination.
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Background
Leishmania are the etiological agents of a variety of disease manifestations, collectively termed as leishmaniasis. Visceral leishmaniasis caused by Leishmania (L.) donovani and Leishmania (L.) chagasi is a serious health problem in many tropical and subtropical countries [1-3]. During the digenetic life cycles of Leishmania, it alternates between gut of sand fly vector as an extra cellular promastigote and in the acidic phagolysosome of macrophage as an intracellular amastigote. However, the most intriguing question is the capacity of Leishmania to withstand the hydrolytic conditions of the macrophages, the mechanism of which is still unclear. Thus, identifying the genes expressed specifically in the amastigote stage of the parasites and elucidating their biological function is very important as it would provide new insights into the role of these gene products in the intracellular life cycle of the parasites. Further, this will also help in designing specific drugs and identifying vaccine candidates.
Cysteine proteases play an important role in the infection, replication, development and metabolism of protozoan parasites [4,5]. They have been implicated in the invasion of human erythrocyte by Plasmodium falciparum [6] and considered as virulence factors in the pathogenesis of Entamoeba histolytica [7]. Cysteine protease activity is necessary for the survival of Leishmania (L.) mexicana [8,9] and related protozoan, Trypanosoma cruzi, within the macrophages, in vitro [10]. Knockout studies in L. (L.) mexicana have shown that cysteine proteases not only are virulence factors but also act as modulators of host immune responses [11,12]. Thus, cysteine proteases have become a potential target for chemotherapy and a candidate for vaccine development. Initial studies have confirmed the efficacy of cysteine protease inhibitors in treatment of T. cruzi, P. falciparum and L. (L.) major [13-15]. Immunization with the hybrid protein vaccine, consisting of L. (L.) major cysteine proteases CPB and CPA, partially protected against leishmaniasis [16]. So far, functionally well characterized cysteine proteases are from the New World species of Lesihamania causing the cutaneous forms of leishmaniasis. The members of L .(L.) donovani complex also possess multiple classes of cysteine proteases, which are developmentally regulated [17,18] and are not functionally well characterized. Therefore, there is a need to study the function of these proteases and their role in visceral leishmaniasis.
Studies aimed at defining the function of protozoan parasite components have often used gene disruption approach by homologous recombination. Recently an alternative antisense RNA method was followed that may easily and rapidly answer the complex biological questions. Anti sense RNA approach has been used to study the functions of certain gene products in Entamoeba and Leishmania, to elucidate the functions of cysteine protease [19,20], A2 protein [21] and gp63 [22]. Previously, we have isolated and characterized two distinct cysteine protease cDNA clones Ldccys1 and Ldccys2 from promastigote and amastigote specific cDNA libararies of L. (L.) chagasi [17]. Ldccys1, a member of multi gene family was characterized both in L. (L.) chagasi (Ldccys1) and L. (L.) donovani (Lddcys1) parasites [18]. In the present study, we have characterized the functional role of amastigote specific cysteine protease gene (Ldccys2) of L. (L.) chagasi. We have generated Ldccys2 heterozygous knockout mutants of L. (L.) chagasi by homologous recombination. As an alternative approach, antisense mRNA expression was also employed. Results obtained from both, gene disruption and antisense mRNA expression shows that Ldccys2 plays an important role in the survival of amastigotes within the U937 macrophages.
Results
Ldccys2 is a single copy gene
From our earlier studies it is known that Ldccys2 is a single copy gene in L. (L.) chagasi. In order to compare the genomic organization of Ldccys2 gene in L. (L.) donovani and L. (L.) chagasi, the members of L. (L.) donovani complex, Southern analysis of genomic DNA was performed. Genomic DNA was digested with different restriction enzymes as shown in Figure 1A and probed with Ldccys2 coding region as a probe. Identical hybridizing bands were present in both L. (L.) chagasi and L. (L.) donovani (Figure 1A). PCR amplification and sequencing of Ldccys2 coding region from L. (L.) donovani genomic DNA showed identical nucleotide sequences, indicating that L. (L.) chagasi and L. (L.) donovani had identical Ldccys2 cysteine protease genes.
Ldccys2 gene is differentially expressed
To study the expression of Ldccys2 cysteine protease genes, Northern blot analysis was performed using L. (L.) chagasi total RNA from log and stationary phase promastigotes and amastigotes. The 3'UTR region of Ldccys2 used as a probe, hybridized to a 2.5 kb transcript in amastigote (Figure 1BI) unlike the cysteine protease, Ldccys1, which is predominantly expressed in promastigote stages of the parasite (Figure 1 BII). The α-tubulin gene expression was used as an internal control (Figure 1 BIII). Ldccys2 showed similar pattern of expression in L. (L.) donovani (data not shown). It is important to note that this result is in contrast to the earlier report (17), wherein Ldccys2 was identified as promastigote specific cysteine protease gene and Ldccys1 was thought to be amastigote specific. We have confirmed the expression pattern and rectified this error in the following publication (18).
To further confirm the amastigote expression of Ldccys2, Western blot analysis was carried out using extracts from both promastigotes and U937 infected amastigotes of L. (L.) chagasi. The anti-Ldccys2 antibody detected a 30 kDa band in amastigotes alone (Figure 1C, lane 3).
However, a single 46 kDa band seen in log and stationary phase promastigotes (Figure 1C, lanes 1 and 2) represents promastigote specific cysteine protease Ldccys1, due to the cross-reactivity of the antibody. Taken together, the above results show that Ldccys2 is expressed only in the amastigote stage of L. (L.) chagasi.
Recombinant Ldccys2 expressed in insect cells is functionally active
In order to determine the cysteine protease activity encoded by Ldccys2, the predicted coding region was cloned into pIE1/153A.jhe (6hep) vector and transfected into High Five insect cells (invitrogen). The supernatant was harvested and analyzed for the presence of recombinant protein by Western blot analysis using JHE and Ldccys2 antibodies. Western blot analyses with α-JHE antibody (Figure 2A, lane3) detected a band of 96 kDa, corresponding to the fusion protein. The lower molecular mass bands are due to the processed products as a result of autocatalytic activity. Anti- Ldccys2 antibody however, could not detect the recombinant fusion protein (Figure 2B lane 3). The processed products were detected instead, which may be because of inaccessibility of the epitope in the fusion protein. Both the antibodies did not give any background with the negative control (cell extract, Figure 2B and 2C, lane1). Protease activity determined by gelatin SDS-PAGE, showed a band of approximately 30 kDa (Figure 2C, lane 3), confirming the protease activity. Cysteine protease activity was completely inhibited by a specific inhibitor, E-64 at 20 μM concentration (data not shown).
Ldccys2 single allele gene replacement by homologous recombination
In order to investigate the function Ldccys2 gene, we have performed gene replacement by disrupting a 500 bp coding region of the gene with hyg and dhfr-ts cassette as shown in figure 3A. Following transfection, hygromycin B resistant parasites (Ldccys2KO, heterozygous knockout mutants) were selected for further analysis. The PstI restriction enzyme digested genomic DNA from wild type L. (L.) chagasi and Ldccys2 KO were subjected to Southern analysis and results are presented in figure 3B. The disrupted Ldccys2 allele had an additional PstI site that is present within the hyg gene. As shown in the figure 3B, 5' and 3'probes (probes a and b) hybridized to a single 3.5 kb band with wild type genomic DNA. In Ldccys2KO, probe-a hybridized to two bands (3.5 kb and 2.8 kb) and probe-b hybridized to 3.5 kb and 3.0 kb bands. As expected, one of the bands corresponds to the wild type allele whereas the other band corresponded to the disrupted allele. The hyg specific probe-c resulted in no hybridizing band with PstI digested wild type genomic DNA, while in Ldccys2KO, two bands (2.8 kb and 3.0 kb) corresponding to the disrupted allele were detected (Figure 3B, probe c). These results clearly indicate that one of the alleles of the Ldccys2 gene has been replaced by hygromycin gene. Similarly, a second cassette using neomycin gene was used in order to replace the second allele of Ldccys2 gene. Despite numerous attempts, we were unable to obtain a null mutant of Ldccys2. We then checked for any events of rearrangements or change in ploidy levels in the heterozygous mutants. No such detectable events were detected (data not shown).
Ldccys2 single allele knock-out mutants had reduced mRNA and protein levels
In order to compare the expression of Ldccys2 gene in wild type and heterozygous knockout mutants (Ldccys2 KO), amastigote RNA was isolated from U937 cells infected with wild type as well as Ldccys2KO mutant L. (L.) chagasi promastigotes. Northern blot analysis with Ldccys2 coding region probe detected a single transcript of 2.5 kb from wild type as well as Ldccys2 KO amastigotes (Figure 4A, panel 1). However, the transcript level of Ldccys2 in the Ldccys2KO amastigotes was reduced by 64% compared to that in the wild type L. (L.) chagasi. There was no change in the level of α-tubulin expression either in the Ldccys2KO or in the wild type amastigotes (Figure 4A, panel 2).
The effect of Ldccys2 single allele disruption at protein level was studied using western blot analysis. Equal amounts of lysates from wild type and Ldccys2KO L. (L.) chagasi amastigotes were analyzed using antiserum raised against Ldccys2 protein. Wild type L. (L.) chagasi amastigotes showed a major band of 30 kDa (Figure 4B, panel 1), while Ldccys2KO amastigotes showed an identical sized band, but there was a reduction in amounts by 45%, based on the quantitation of bands. The antibody did not pick up any signal from the negative control (U937 cells). Figure 4B, panel 2 indicates the equal loading of proteins. These results once again, confirm the deletion of one of the alleles of Ldccys2.
Ldccys2 heterozygous knockout mutants exhibit reduced infectivity and intra-macrophage survival of amastigotes
In order to study the effect of Ldccys2 heterozygous knockout mutants on parasite growth, a growth curve analysis was performed. No significant differences were observed between the wildtype parasites and the Ldccys2KO (data not shown). Next, we performed an infection assay with differentiated U937 macrophage cells using with wild type and Ldccys2KO L. (L.) chagasi promastigotes. Interestingly, twelve hours after infection, the number of amastigotes in Ldccys2KO infected macrophages were reduced by half as compared to that of wild type infected macrophage cells. This trend remained same at all the time intervals tested (24, 36 and 48 hours post infection), indicating that the intracellular amastigotes were not able to multiply efficiently (Figure 4C). The percentage of infected macrophages in the wildtype and Ldccys2KO were similar at 12, 24, 36 and 48 hours post infection (Figure 4D), however, there was a clear decrease in the initial infection in case of Ldccys2KO, as compared to the wildtype parasites. The above data suggests that Ldccys2 heterozygous knockout has resulted in reduced levels of Ldccys2 expression and furthermore, has decreased the ability of the amastigotes to infect the macrophages and survive inside the macrophage cells. Taken together, these results suggest that Ldccys2 gene has a significant role in the infection and intramacrophage survival of amastigotes.
Antisense mRNA inhibition of Ldccys2 resulted in reduced macrophage infection and poor amastigote survival within the macrophages
We were unable to generate a complete knock out mutant of Ldccys2 and the heterozygous knockout mutants only partially inhibited the gene expression. Therefore, we used an alternative approach of antisense mRNA inhibition to silence the Ldccys2 gene and to confirm the conclusions derived from Ldccys2 heterozygous knockout mutants studies. Plasmid constructs containing the Ldccys2 antisense and sense sequences were transfected into L. (L.) chagasi promastigotes. The presence of plasmids in these transfectants was confirmed by Southern analysis with Ldccys2 probes (data not shown). Northern blot analyses of amastigotes expressing different plasmid constructs were carried out using specific sense and antisense probes. As expected, Ldccys2 antisense mRNA was expressed only in amastigotes with antisense constructs (Figure 5A, panel 1), and these amastigotes showed a 74% decrease in the Ldccys2 mRNA levels (Figure 5A, panel 2). The amastigotes containing either the sense plasmid or the control plasmid did not show any change in the levels of Ldccys2 mRNA (Figure 5A, panel 2). The stained agarose gel indicates the equal amounts of RNA used in the Northern blots (Figure 5A, panel 3). These results clearly demonstrate that the episomal expression of Ldccys2 antisense mRNA reduces the levels of endogenous Ldccys2 mRNA.
We next performed Western blot analysis of transfectants expressing sense and antisense Ldccys2 mRNA using α-Ldccys2 antibody. Amastigotes expressing antisense mRNA showed a significant reduction (by 76%) in the levels of Ldccys2, however, the expression of sense mRNA did not increase the levels of Ldccys2 compared to amastigotes containing the control plasmid (Figure 5B, panel1). Equal loading of the protein is depicted by the Coomassie stained gel (Figure 5B, panel 2). The results further confirm that Ldccys2 antisense mRNA expression does inhibit the endogenous levels of Ldccys2.
Survival of L. (L.) chagasi amastigotes within the macrophages was assessed in vitro, using U937 cells. Results from three individual experiments are pooled and the collective data is presented in figure 5C. Results showed that the amastigotes carrying either the control plasmid (P6.5) or expressing Ldccys2 sense mRNA did not have any effect on their capacity to infect and survive inside the macrophages. The number of amastigotes per macrophage cell remained the same at initial stages of infection (data not shown). However, amastigotes expressing Ldccys2 antisense mRNA showed significant reduction (by almost 50%) in terms of the initial infection and intra macrophage survival starting from 12 hours post infection and remained consistent up to 48 hours after infection (Figure 5D). The percentage of total infected macrophages is shown in figure 5D. Consistent with the results from the heterozygous knockout mutants, the Ldccys2 antisense transfectants had reduced levels of infection when compared to that of the wildtype and control plasmids. These results further underline the importance of Ldccys2 in infection of macrophages and subsequent survival of amastigotes within the macrophage cells. Taken together, these results indicate that the amastigote specific cysteine protease, Ldccys2 plays an important role in intramacrophage survival of L. (L.) chagasi amastigotes.
Discussion
In this study, we have shown that amastigote cysteine protease, Ldccys2 necessary for macrophage infection and for survival of L. (L.) chagasi amastigotes inside the macrophage cells using two different approaches, gene disruption and antisense mRNA expression. Leishmania (L.) chagasi cysteine protease, Ldccys2 is a single copy gene [18] and is expressed only in amastigote stage of the parasite. L. (L.) donovani also possesses an identical gene. Expression studies performed demonstrates that Ldccys2 is expressed only in amastigotes of L. (L.) chagasi and L. (L.) donovani. A similar single copy gene in L. (L.) mexicana (Lmcpa) has a significant sequence identity (80%) to Ldccys2. Lmcpa gene of L. (L.) mexicana which is the closest homolog of Ldccys2 is differentially expressed in amastigotes [23], whereas the Ldccys2 gene of L. (L.) chagasi is expressed specifically in the amastigote stage. In addition, the major amastigote specific cysteine proteinase gene of L. (L.) mexicana, cpb2.8 is a multicopy gene, located within the lmcpb cluster [24] and there is no significant sequence identity (34%) between Ldccys2 and lmcpb2.8. Therefore, gene organization and expression of amastigote specific cysteine proteases in L. (L.) mexicana and L. (L.) donovani complex are not identical. Interestingly, Llacys1, an amastigote specific cysteine protease from L. (L.) amazonensis was identified recently, which has high homology (88%) with Ldccys2 and like Ldccys2, is only expressed in amastigote stages [25]. In order to confirm the protease activity of amastigote cysteine protease, full-length Ldccys2 was expressed as JHE-fusion protein in an insect cell expression system. The recombinant protein hydrolysed gelatin in activity gels.
Recently, functions of many genes have been established in Leishmania by following gene disruption approach [26,27]. To study the biological role of Ldccys2 cysteine protease, we have followed targeted gene disruption using hyg gene as the selectable marker. Genomic Southern analyses of the hygromycin B resistant clones using specific probes confirmed the replacement of 500 bp region within the ORF of the Ldccys2 by hyg/dhfr-ts. Northern and Western blot analyses Ldccys2KO amastigotes showed a clear decrease in the endogenous levels of Ldccys2 compared to that of wild type L. (L.) chagasi amastigotes (Figure 4), demonstrating the disruption of one of the Ldccys2 alleles. Despite our repeated effort using different selectable marker genes, we failed to create a null mutant of Ldccys2 in L. (L.) chagasi. Since gene amplification and increase in ploidy level has been reported for Leishmania species [28], we analyzed for changes in ploidy level and or gene amplification and found no such events occurring in these heterozygous knockout mutants. This suggests that Ldccys2 is an important gene necessary for the initiation of macrophage infection and survival of amastigotes within the macrophages. Therefore we used the Ldccys2 heterozygous knockout parasites for further functional studies. The U937 macrophage cells infected with Ldccys2 heterozygous knockout mutants showed a significant decrease in the initial infection and survival within the macrophage cells, compared to wild type (Figure 4). This trend remained consistent from 12 hours up to 48 hours after infection. The decrease in initiation of infection and subsequent survival of amastigotes may explain the role of Ldccys2 in amastigote metabolism and its survival inside the macrophages [4]. Consistent with our results, null mutants of the lmcpb cluster in L. (L.) mexicana exhibited reduction in macrophage infectivity and survival [23]. However, lack of Ldccys2 null mutant prevented us from a detailed study on the role of Ldccys2 in survival and pathogenesis, using animal models.
The lack of Ldccys2 null mutants prompted us to use an alternative approach of antisense mRNA inhibtion in order to confirm the results obtained from Ldccys2 heterozygous knockout studies. Using antisense RNA technique it has become possible to investigate the contribution of cysteine proteases to virulence mechanism of E. histolytica [19,20] and A2- protein in the survival of L. (L.) donovani amastigotes in macrophages [21]. Furthermore, episomal expression of sense and anti sense mRNA of L. (L.) amazonensis gp63using Leishmania- specific P6.5 vector provided evidence for a role both in binding of macrophages and the intracellular survival and replication [22]. Not surprisingly, L. (L.) chagasi amastigotes expressing Ldccys2 antisense mRNA has clearly down regulated the endogenous Ldccys2 mRNA levels (Figure 5). However, a small amount of Ldccys2 mRNA is still present in antisense transfectants, which may be due to the incomplete suppression, which is inherent to this approach. Infection of U937 macrophage cells with transfectants expressing Ldccys2 antisense mRNA showed a significant decrease in amastigote survival inside the macrophage cells, as compared to amastigotes expressing either sense Ldccys2 mRNA or the control plasmid (Figure 5). This is in agreement with the results obtained from Ldccys2 heterozygous knockout mutants, reaffirming the role of Ldccys2 in initiation of intracellular infection, and subsequent survival and multiplication of amastigotes. However, the actual effect of antisense mRNA expression may be greater, since reversal of antisense effects is expected from the release of the selective pressure necessary to avoid drug toxicity to macrophages [21]. This is especially true in the assay for intracellular survival and replication, since it requires prolonged period of incubation. The transient nature of the antisense suppression in the absence of selection prevented us from taking up animal studies that also require prolonged infection with these transfectants.
The out come of this study shows that Ldccys2 is expressed only in amastigote stage of the parasite. Both the heterozygous knockout mutants and antisense mRNA expression shows that Ldccys2 is important for infection of macrophages and survival of L. (L.) chagasi amastigotes inside the macrophage cells. Based on the data obtained in this study, there is a clear justification for targeting the Ldccys2 gene in L (L.). chagasi and carrying out further studies in animal models. Currently, we are working towards generating null mutants of Ldccys2 in L. (L.) chagasi and to further understand the role of this protein in the pathogenesis of L. (L.) chagasi parasites.
Methods
Parasite culture
L. (L.) chagasi strain MHOM/BR/74/PP75 promastigotes were grown in HOMEM, pH 7.4 (Gibco BRL) supplemented with 10% (v/v) heat inactivated calf serum, at 26°C. Promastigote cultures were seeded at 1 × 106parasites/ml and harvested in logarithmic or stationary growth phase, as defined by cell concentration. L. (L.) chagasi promastigotes were transformed to axenic amastigotes using the standardized protocol as described earlier [29]. All the transfectants were periodically converted to amastigotes by infecting U937 macrophage cells in order to ensure the property of virulence.
RNA isolation and northern hybridization
Total RNA was isolated using trizol (GibcoBRL) as recommended by the manufacturer. Promastigote RNA was obtained from logarithmic and stationary growth phase parasites of L. (L.) chagasi. To isolate amastigote RNA, human macrophage cell line (U937, ATCC) was infected with promastigote parasites, which were subsequently converted into intracellular amastigotes [29]. RNA (10 μg/lane) was separated on 1.2% (w/v) formaldehyde agarose gels and transferred onto Hybond N+ membrane (Amersham Pharmacia). Standard procedures were followed to perform Southern and Northern blot hybridizations. Using Quick Prime Labeling Kit (Amersham Pharmacia Biotech), probes representing specific region of Ldccys2 cDNA clone was labeled with [α32P] dCTP. The sense and antisense probes were generated by 5'end-labeling the specific sense and antisense oligonuecleotide primers with γ-32P ATP, using T4 polynucleotide kinase according to the standard protocol.
Polyclonal antibody production against Ldccys2
Direct DNA immunization [30] was used to generate antibody against Ldccys2. Briefly, the pro-mature region of the gene was PCR amplified from the Ldccys2 cDNA clone using specific 5' (5'CAGACAGGATCCG CGGCCGCCATGGACGACTTCATTGCC 3') and 3' primers (5' GGCCGCGGATCCGCG GCCGCCTATGAGGTGTTGGAGTCGTC 3') and the PCR product was sub-cloned into BamHI site of pcDNA 3.1 (Invitrogen). After confirmation by sequencing the plasmid constructs were amplified in E. coli and DNA was isolated using endotoxin free maxi prep kit (Qiagen). 50 μg of plasmid DNA in 100 μl of saline was injected into the hind limb quadriceps muscles of BALB/c mice. All the mice were boosted after 14 days and tested for antibody response seven days after the boost. Mice with positive response were boosted one more time and after a week sera was collected and stored at -20°C for further use.
Western blot analysis
Denaturing gel electrophoresis was carried out according to the standard protocols. Following SDS-PAGE, proteins were transferred onto to Hybond P membrane (Amersham Pharmacia Biotech) using semi-dry transblot apparatus (BioRad). Membranes were blocked for 2 hours with 5% (w/v) skim milk solution and probed overnight at 4°C with 1:200 dilution of anti-Ldccys2 antiserum. Membranes were washed three times with phosphate buffered saline containing 0.1% (v/v) Tween and incubated with 1:5000 dilution of anti-mouse horseradish peroxidase linked secondary antibody (Molecular Probes). Enhanced chemiluminescent kit (Amersham Pharmacia Biotech) was used for detection.
Expression of cysteine protease genes
In order to express Ldccys2 cysteine protease gene, the coding region was amplified by PCR. The digested PCR product was cloned in-frame into unique NotI site of pIE1/153A.jhe (6hep) vector [31] and confirmed by sequencing. The fusion of the Cysteine proteases to the c-terminus of Juvenile hormone esterase (JHE) directs the secretion into the culture supernatant of transfected insect cells. Culture of insect cells and procurement of samples containing recombinant protein from transfected insect cells are described earlier [32]. Briefly, High Five insect cells (Invitrogen) were seeded into6-well culture plates (35 mm diameter) at a density of 5 × 105 cells/ml (2 ml/well) and transfected for 5 h with 0.5 ml of transfection solution containing 30 μg/ml lipofectin (Life Technologies) and 6 μg/ml total plasmid DNA in basal IPL-41 medium. Then the transfection solution was removed, the cells were rinsed with basal media and 2 ml IPL-41 + 10% FBS was added and incubated for sixty hours. The supernatant was then harvested and stored at -20°C for analysis. Enzyme activity was analyzed on gelatin SDS-PAGE containing 0.2% gelatin and 8% (w/v) acrylamide as described previously [17]. For inhibition studies, gels were pre-incubated with 20 μM E-64 (Sigma), a Cysteine protease specific inhibitor. Gels were stained with Coomassie Brilliant Blue for half hour and destained with 30% Methanol for 2 hours, to visualize the bands. Bands were photographed using Diamed apparatus (Bio-Rad).
Ldccys2 gene disruption by homologous recombination
Gene replacement vector, pXLdccys2-HygKO was designed to replace 500 bp mature region of Ldccys2 coding region and constructed as outlined below (Figure 2b). The sense primer Ldccys2 HindIII (5' GCTCTCAAGCTTGCTCACGCATCCGCCGC-3') and the antisense primer Ldccys2 Xho I (5'GAAGGCCTCGAGCGAGCCGCACATTCCCTG-3') were used to amplify a 500 bp region from Ldccys2 cDNA and cloned between HindIII – XhoI sites in pX63-Hyg (kindly provided by Dr. S. M. Beverley) for the 5' end homologous recombination. A 450 bp 3' end homologous recombination fragment was amplified using the sense primer Ldccys2 SmaI (5'CCGGAGCCCGGGCCCACGGCGCTTGTGCAG-3') and antisense primer Ldccys2 BglII (5' ACTGTCAGATCTGCTGTGCGCCAGATCGCG-3') and cloned between SmaI and BglII sites of pX63-Hyg. The plasmid construct pXLdccys2-HygKO was confirmed by sequencing and digested with HindIII and BglII. The resulting 3.8 kb linear fragment containing hygromycin phospotransferase/dihydrofolate reductase-thymidylate synthase (hyg/dhfr-ts) gene sequence and the homologous recombination fragment was purified and used for transfection.
Episomal expression of Ldccys2 specific sense and antisense mRNA
The Ldccys2 cDNA clone was isolated from an amastigote specific cDNA library of L. (L.) chagasi. Ldccys2 was earlier reported as promastigote specific cDNA clone [17]. However, it was further verified to be amastigote specific gene (18). The coding region (1 kb) of Ldccys2 was inserted at BamHI site of Leishmania specific vector P6.5 [22], a kind gift from Dr. K.P.Chang. Cloning was done in both sense and antisense orientations with reference to that of N-acetylglucosamine 1-phosphate transferase (nagt), which was used as the selective marker for tunicamycin resistance. Plasmid constructs were confirmed by sequencing. P6.5 plasmid and the sense and antisense plasmid constructs were amplified in E. coli and isolated with a DNA maxi prep kit (Qiagen) and the purified DNA samples were used for transfection.
DNA transfection
All the transfections were carried out using L. (L.) chagasi promastigotes. Briefly, 4 × 107 log phase promastigotes were pelleted, washed twice with phosphate buffered saline and resuspended in 0.4 ml of electroporation buffer in a 0.2 cm cuvette. Twenty-five microgram of P6.5 plasmid DNA constructs was used for episomal expression, whereas for homologous recombination 5 μg of linearized DNA fragment was transfected. DNA was electroporated using BioRad Gene Pulser Unit at 0.45 kV, capacitance of 25 μF and resistance of 250 ohms. Following electroporation, cells were resuspended in drug-free media for 24 hours. Parasites with P6.5 plasmid DNA constructs were selected for tunicamycin resistance at 5, 10 and 20 μg/ml tunicamycin (Sigma). Parasites transfected with DNA fragment for homologous recombination were selected for hygromycin B (GibcoBRL) resistance at 100 μg/ml.
In vitro assay for intra macrophage survival
The U937 macrophage cells were infected with L. (L.) chagasi stationary promastigotes at a host to parasite ratio of 1:10 [33]. Briefly, U937 suspension cells (10 6 cells/ml) in 10 ml RPMI 1640 medium supplemented with 10% (v/v) heat inactivated fetal bovine serum, 2 mM L-glutamine and 50 μg gentamycin (Gibco BRL) were allowed to grow at 37°C for 3 days in 10% (v/v) CO2. The cells were then induced to adhere with 7.5 ng/ml of phorbol myristate acetate (PMA) and allowed to recover for 72 hours. The macrophage cells were then infected with stationary phase promastigotes and allowed to infect for 6 hours. The unbound parasites were washed away with RPMI medium and the infected macrophage cells were fed with fresh RPMI medium and left for 4 days. At every 12 hours interval up to 72 hours, cells were scraped and Diff-Quick stained slides were prepared for microscopic counting,
Abbreviations
Hyg, hygromycin; JHE, juvenile hormone esterase; kb, kilobase; KO, knock-out; ORF, open reading frame; UTR, untranslated region
Authors' contributions
VM carried out all the plasmid constructs for gene disruption and antisense mRNA inhibiton studies and performed the Southern and Northern blot analyses shown in Figures 1, 3, 4 & 6; wrote parts of the manuscript. ASK performed all the transfections, western blots and macrophage assays shown in Figures 1, 2, 4, 5, 6 and 7; wrote parts of the manuscript. LG supervised the experiments and gave laboratory support, and critically read the manuscript. All authors read and approved the final manuscript.
Acknowledgements
This investigation received financial support from the Natural Sciences and Engineering Council (NSERC) of Canada, Canadian Institute of Health Research (CIHR) and UNDP/World Bank/WHO Special Program for Research and Training in Tropical Diseases to L.G. We would like to thank Dr. K.P. Chang, Chicago Medical School for providing the Leishmania specific P6.5 plasmid.
Figures and Tables
Figure 1 Ldccys2 is a single copy gene and is expressed only in amastigotes. (A) Southern blot hybridization of digested genomic DNA from L. (L.) chagasi (Lc) and L. (L.) donovani (Ld). 5 μg of genomic DNA was digested with restriction enzymes as mentioned in the figure and blotted onto Hybond-N membranes. The blot was probed with coding region pf Ldccys2 cDNA clone. (B) Northern blot analyses of L. (L.) chagasi total RNA. Total RNA (10 μg/lane) from promastigotes of logarithmic (lane 1), stationary (lane 2) growth phase, U937 cells (human macrophage cell line) infected with promastigotes for 96 h (lane 3) and uninfected U937 cells (lane 4) were separated on 1.2% (w/v) formaldehyde agarose gel and transferred on to Hybond N+ membrane. Blot was hybridized with PCR amplified DNA fragment containing 3'UTR from Ldccys2 (panel I), Ldccys1 (154 bp, near the polyA region, panel II), and coding region of α-tubulin from L. (L.) chagasi, a kind gift from Dr. M.E. Wilson (panel IV). (C) Western blot analysis of L. (L.) chagasi promastigotes and amastigotes. Equal amounts of proteins from promastigotes of logarithmic (lane 1), stationary (lane 2) phase, U937 cells infected with promastigotes (lane 3) and uninfected U937 cells (lane 4) were separated on 10% (w/v) SDS-PAGE and blotted on to Hybond – P membrane. Western blot analysis was carried out using α-Ldccys2 antibody.
Figure 2 Expression of recombinant Ldccys2 using insect cell expression system. Western blots showing recombinant expression of Ldccys2 using anti-JHE antibody (A) and duplicate blot probed with anti-Ldccys2 antibody (B). The lanes are labeled appropriately. 5 μg of supernatant from the insect cells expressing recombinant plasmids or the control were separated on 8% SDS-PAGE, blotted onto to PVDF membranes and probed with 1:500 dilution of anti-JHE or 1:100 dilution of anti-Ldccys2 antibody. A horseradish peroxidase conjugated anti-mouse secondary antibody was used and the blot was developed by using ECL chemiluminescent kit. (C) Gelatin assay showing cysteine protease activity of the recombinant protein. The supernatant was separated on a gelatin gel and incubated in a reducing buffer. The gel was then stained with Coomassie Blue to visualize the clearing of gelatin on the gel indicating cysteine protease activity.
Figure 3 Ldccys2 single allele gene replacement. (A) Schematic representation of the wild type and hyg/dhfr-ts targeted alleles of Ldccys2. The location of the PstI sites used to characterize the hygromycin B resistant recombinants is shown by arrows. The bold lines labelled a, b and c represents the location of different probes used in Southern analyses. (B) Southern analyses of Ldccys2 heterozygous knockout mutants. Genomic DNA (2 μg/lane) from wild type L. (L.) chagasi (WT) and Ldccys2 heterozygous knockout mutants (KO) were digested with PstI and separated on a 0.9% (w/v) agarose gel. The DNA was blotted on to Hybond N+ membrane and hybridized with probes a (i), b (ii) and c (iii). Asterisks: 1- represents wild type allele of Ldccys2 (3.5 kb), 2 and 3- represent disrupted allele (3.0 kb and 2.8 kb). The grey lines indicate the size of expected bands upon PstI digestion.
Figure 4 Characterization of L. (L.) chagasi heterozygous knockout mutant amastigotes and intra macrophage survival of Ldccys2KO amastigotes in vitro. (A) Northern blot analysis. Total RNA (10 μg/lane) from U937 cells infected with wild type promastigotes, Ldccys2KO and uninfected U937 cells were separated on 1.2% (w/v) formaldehyde agarose gel and transferred on to Hybond N+ membrane. Blot was hybridized with Ldccys2 coding region DNA probe (1) and α-tubulin gene from L. (L.) chagasi (2). (B) Western blot analysis. Equal amount of lysates from U937 cells infected with wild type promastigotes, Ldccys2KO promastigotes and uninfected U937 cells were separated on 10% (w/v) SDS-PAGE, blotted on to Hybond P membrane. Panel 1 represents the membrane that was probed with α-Ldccys2 antibody and panel 2 is the duplicate gel stained with Coomassie blue. (C) Bar graph showing the number of intracellular amastigotes. U937 macrophage cells were infected at a macrophage to parasite ratio of 1:10. The survival of the amastigotes within the macrophages was evaluated every 12 hours by cytospin and Diff-Quick staining. (D) Graph showing the percent of total macrophages infected at the given time points. For each treatment, 100 infected macrophages were counted. Values represent means ± SEM from three independent experiments.
Figure 5 Expression of sense and antisense Ldccys2 transcripts in L. (L.) chagasi and survival of wild type, sense and antisense Ldccys2 expressing amastigotes in macrophages. (A) Northern blot analyses of amastigotes expressing sense and antisense transcripts. Total RNA (10 μg/lane) isolated from axenic amastigotes of wildtype parasites, transfectants with P6.5/Ldccys2 sense plasmid and P6.5/Ldccys2 antisense plasmid were separated on 1.2% (w/v) formaldehyde agarose gel and blotted on to Hybond N+ membrane. Blots were probed with probes specific for antisense (panel 1) and sense (panel 2) transcripts. Panel 3 represents ethidium bromide stained gel. (B) Western blot analysis of sense and antisense Ldccys2 expressing amastigotes. Equal amounts of total protein extracted from axenically transformed amastigotes with P6.5/Ldccys2 sense plasmid and P6.5/Ldccys2 antisense plasmid and wildtype parasites were separated on 10% (w/v) SDS-PAGE and blotted on to Hybond P membrane. The blot was probed with α-Ldccys2 antibody (panel 1) and a duplicate gel was stained with Coomassie blue (panel2). (C) Bar graph showing total number of amastigotes within the macrophage cells. U937 macrophage cells were infected at a macrophage to parasite ratio of 1:10. The survival of the amstigotes within the macrophages was evaluated every 12 hours by cytospin and Diff-Quick staining.(D) Graph showing the percent of total macrophages infected at the given time points. For each treatment, 100 infected macrophages were counted. Values represent means ± SEM from three independent experiments.
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| 15691375 | PMC549197 | CC BY | 2021-01-04 16:22:25 | no | BMC Mol Biol. 2005 Feb 3; 6:3 | utf-8 | BMC Mol Biol | 2,005 | 10.1186/1471-2199-6-3 | oa_comm |
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BMC NeurosciBMC Neuroscience1471-2202BioMed Central London 1471-2202-6-71568923710.1186/1471-2202-6-7Research ArticleDysregulation of Na+/K+ ATPase by amyloid in APP+PS1 transgenic mice Dickey Chad A [email protected] Marcia N [email protected] Donna M [email protected] Donna L [email protected] Melissa J [email protected] Dave [email protected] Alzheimer's Disease Research Laboratory, Department of Pharmacology, University of South Florida, Tampa, USA2005 2 2 2005 6 7 7 8 10 2004 2 2 2005 Copyright © 2005 Dickey 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 pathology of Alzheimer's disease (AD) is comprised of extracellular amyloid plaques, intracellular tau tangles, dystrophic neurites and neurodegeneration. The mechanisms by which these various pathological features arise are under intense investigation. Here, expanding upon pilot gene expression studies, we have further analyzed the relationship between Na+/K+ ATPase and amyloid using APP+PS1 transgenic mice, a model that develops amyloid plaques and memory deficits in the absence of tangle formation and neuronal or synaptic loss.
Results
We report that in addition to decreased mRNA expression, there was decreased overall Na+/K+ ATPase enzyme activity in the amyloid-containing hippocampi of the APP+PS1 mice (although not in the amyloid-free cerebellum). In addition, dual immunolabeling revealed an absence of Na+/K+ ATPase staining in a zone surrounding congophilic plaques that was occupied by dystrophic neurites. We also demonstrate that cerebral Na+/K+ ATPase activity can be directly inhibited by high concentrations of soluble Aβ.
Conclusions
The data suggest that the reductions in Na+/K+ ATPase activity in Alzheimer tissue may not be purely secondary to neuronal loss, but may results from direct effects of amyloid on this enzyme. This disruption of ion homeostasis and osmotic balance may interfere with normal electrotonic properties of dendrites, blocking intraneuronal signal processing, and contribute to neuritic dystrophia. These results suggest that therapies aimed at enhancing Na+/K+ ATPase activity in AD may improve symptoms and/or delay disease progression.
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Background
Alzheimer's disease (AD) has several well-characterized post-mortem pathological markers that include both gliosis and dystrophic neurites surrounding extracellular amyloid plaques. In addition, intracellular tangles of hyper-phosphorylated tau and massive neurodegeneration are seen later in the disease process. Mutated forms of both amyloid precursor protein (APP) and presenilin 1 (PS1) lead to an increased rate of amyloid deposition and therefore an earlier onset of the dementia associated with AD [1]. Doubly transgenic mice expressing these human mutants of the APP [2] and PS1 [3] genes (APP+PS1 mice; [4] exhibit a large amount of amyloid deposition and gliosis without the formation of tangles or neuron loss, and yet they still develop anterograde amnesia as they age, similar to what is seen in the early stages of AD [5]. Memory deficits without the loss of neurons indicate that amyloid-associated disruption of some step in neural processing can result in memory deficits.
Previously we have described decreased expression of genes critical for learning and memory and impaired induction of several immediate early genes (IEGs) in aged, memory deficient APP+PS1 mice [6,7]. Increased neural activity during learning is argued to be a primary inducing stimulus for these IEGs [8]. One possible mechanism to describe this phenomenon would be that amyloid is diminishing the ability of neurons to facilitate sufficient electrical signaling to induce changes in synaptic plasticity essential for memory consolidation. Here we present evidence that in addition to decreased expression of Na+/K+ ATPase mRNA as previously described [6,7], the activity of this enzyme is significantly decreased in the APP+PS1 hippocampus but not in the amyloid-free cerebellum. Perhaps not surprisingly ouabain, an Na+/K+ ATPase inhibitor, has been shown to impair memory consolidation [9,10]. We decided to investigate further the interactions of Aβ and Na+/K+ ATPase activity to understand better the potential role of this enzyme in AD and memory dysfunction.
Results
We used the APP+PS1 transgenic mouse model to better understand how the deposition of amyloid contributes to the consistent memory loss seen in these animals [11-14]. Specifically, we have found that Na+/K+ ATPase, a protein critical for not only brain function, but survival, is adversely affected by the presence of amyloid and this interaction may be driving a major pathological event in the progression of amyloid-associated dementia.
In order to determine if our early observation regarding reduced mRNA for Na+/K+ ATPase was functionally meaningful, we measured total and ouabain-sensitive ATPase activity in APP+PS1 brain homogenates compared to those from non-transgenic littermates using a standard colorimetric assay. Using ouabain as a selective inhibitor of Na+/K+ ATPase, we demonstrated that the specific enzymatic activity was significantly reduced by ~25% in the hippocampi of aged, memory-deficient APP+PS1 mice compared with non-transgenic littermates (Figure 1B). The percent reduction in total ATPase activity was similar to that of specific Na+/K+ ATPase activity, suggesting that inhibition of is selective for Na+/K+ ATPase (Figure 1A &1B). In addition, approximately 40% of all the ATP hydrolysis found in the homogenate was ouabain sensitive, confirming that this enzyme is likely the largest single site of ATP hydrolysis in brain. The specific activity values measured here were consistent with those reported 3 decades ago by Stefanovic et al. [15], testifying to the robustness of the assay method. Upon analysis of the cerebellum of these mice, we found that the specific enzyme activity in APP+PS1 transgenics remained equivalent to that in non-transgenic littermates (Figure 1B); however the overall activity of Na+/K+ ATPase in this region was only one fifth of that in the hippocampus (Figure 1A &1B). Western blot analyses of cortical homogenates demonstrated a trend for reduced protein expression, a finding that would be expected based upon the mRNA analyses (Figure 1C).
Immunohistochemical staining for the Na+/K+ ATPase αIII subunit was performed using saggital sections from non-transgenic and APP+PS1 mice. Specific staining was observed throughout the forebrain. The specificity of the Na+/K+ ATPase α subunit antibody used for immunochemistry was determined by pre-incubation of the antibody with purified Na+/K+ ATPase protein, which dramatically reduced apparent immunostaining (Figure 2B) compared with normal staining (Figure 2A; amyloid plaques stained with Congo red dye appear red). Positive reaction product appeared to be localized to the periphery of cellular profiles in CA3 of the hippocampus (Figure 3A) and the insular cortex (Figure 3B), consistent with the enzyme's membrane-association. Throughout the brain, the white matter regions appeared to have less intense staining, than the neuropil, consistent with the larger numbers of ions crossing the membrane in post-synaptic potentials than action potentials (thus requiring more ionic pumping to maintain ionic equilibrium). Additionally, regions with high densities of neuronal somata also appeared to have less dense staining, reflecting the greater density of membrane area in dendritic than somatic regions of neuropil. Similar observations have been made using [3H] ouabain to mark Na+/K+ ATPase distribution in brain [16] Another striking observation from images of the hippocampus in non-transgenic mice (Figure 3C) demonstrate a decreased intensity of staining along the dentate granule cell projection pathways within the hilus and along the mossy fiber projections to CA3 (Figure 3A). This can also be observed at higher magnification in figure 3A, where there is reduced staining to the left of the somatic staining in the inner molecular layer. Although not commented upon, this too can be observed in micrographs of [3H] ouabain autoradiography [17].
Cortical staining (Figure 3D) revealed a fairly uniform pattern, with the exclusion of white matter. The difference in Na+/K+ ATPase staining between non-transgenic and APP+PS1 forebrain areas is the absence of staining where amyloid plaques are present in the APP+PS1 mice (Figure 3E &3F). Subsequent Congo red staining of these amyloid plaques confirmed that the loss of Na+/K+ ATPase staining was not only present in the center of the plaque, but also in a penumbral zone immediately surrounding the congophilic material, resulting in a "halo" (Figure 2A, 3G, 3H &4A). Higher power magnification clearly demonstrated the lack of Na+/K+ ATPase staining surrounding the congophilic plaques (Figure 4A and 4B).
These findings led us to postulate that the osmotic imbalance brought on by an absence or inhibition of Na+/K+ ATPase may contribute to the swelling associated with dystrophic neurites found in the vicinity of congophilic plaques in APP+PS1 mice and AD patients. We designed a dual immunostain utilizing immunohistochemical methods for Na+/K+ ATPase and immunofluorescence methods for phosphorylated neurofilament, a dystrophic neurite marker we evaluated earlier [12]. Using this assay, we were able to demonstrate that the dystrophic neurites were almost exclusively present within the zone surrounding the congophilic plaque that lacked Na+/K+ ATPase staining. This is represented in a triple staining overlay of the fluorescent neurites from figure 4C onto the bright field image of Na+/K+ ATPase and Congo red staining from figure 4B (Figure 4D). The arrows in figure 4C demarcate where dystrophic neurites are present.
Finally, to determine whether amyloid could inactivate Na+/K+ ATPase activity, we measured the activity of purified cerebral Na+/K+ ATPase after exposure to various concentrations of Aβ 1–42 peptide in a DMSO+water suspension or a DMSO+neutralized HCl suspension. Figure 5 demonstrates that increasing concentrations of the DMSO+water Aβ soluble preparation dose-dependently reduced Na+/K+ ATPase activity, whereas the fibrillar Aβ preparation suspended in DMSO+neutralized HCl did not demonstrate the same effect. There were significant reductions in Na+/K+ ATPase activity at the lower concentrations of 112 and 225 μg/ml compared to vehicle, but maximal reductions were at the highest concentration of the DMSO+water Aβ suspension (450 μg/ml).
Discussion
Over the past 6 years, our group has characterized various aspects of the APP+PS1 transgenic mice including their pathology, behavior, and gene expression. With age, these mice progressively develop more amyloid plaques surrounded by dystrophic neurites, activated microglia and astrocytes [12]. With increasing amyloid burden, aged animals consistently develop memory deficits in the radial arm water maze (RAWM; [13,18,19], and, there is as yet no evidence for neuronal or synaptic loss. [6,20,21]. We have also demonstrated that several genes critical for synaptic plasticity and memory consolidation are down-regulated in these mice exclusively in those brain regions which accumulate amyloid [6] and the induction of a subset of immediate-early genes is impaired when the transgenic mice are introduced to a novel environment [7].
Here, we show that Na+/K+ ATPase has decreased enzyme activity in the amyloid-containing hippocampus of APP+PS1 transgenic mice. We have also demonstrated by immunohistology that Na+/K+ ATPase protein expression is reduced in the immediate vicinity of congophilic plaques, a zone where dystrophic neurites are most prevalent, suggesting that disrupted ionic homeostasis may contribute to their formation. Additionally, high concentrations of Aβ 1–42 directly inhibit the activity of Na+/K+ ATPase. This suggests that in the area surrounding amyloid plaques, where the local Aβ concentration is likely high, Na+/K+ ATPase activity may be locally inhibited.
From previous gene expression studies, we found that the mRNA for the Na+/K+ ATPase αIII subunit was consistently down-regulated ~30% in the hippocampi of APP+PS1 mice compared to non-transgenic littermates and to the amyloid-free cerebella [6]. These reductions were also demonstrated in human Alzheimer's disease samples, consistent with data from previous investigations [6,22]. Using a sensitive colorimetric assay to measure activity of Na+/K+ ATPase modified from Ellis et al. [23], we were able to demonstrate that in the APP+PS1 hippocampus, the specific activity of ouabain-sensitive ATPase was significantly reduced (figure 1B) while Na+/K+ ATPase activity in the amyloid-free cerebellum remained unperturbed with respect to genotype. Cerebellar activity was substantially lower than that seen in the non-transgenic hippocampal tissue, perhaps indicative of the abundant white matter found in this region, where Na+/K+ ATPase activity is low. These data demonstrate that the function of Na+/K+ ATPase is perturbed in a brain region that contains high overall concentrations of Aβ.
Previous investigations have shown that Na+/K+ ATPase protein levels are decreased in AD tissue but not in normal aged tissue [24,25], but it is difficult to dissociate the loss due to neuronal death from any loss caused directly by Aβ inhibition. This demonstration that reduced activity along with a trend for reduced protein levels can be determined in homogenates from animal models of amyloid deposition argues that at least some of this loss in AD brain is associated with direct actions of Aβ. In vitro data suggests that Na+/K+ ATPase activity can be blocked directly by various Aβ peptide fragments in cultured neurons [26] and that even the purified enzyme can be inhibited by high concentrations of Aβ (Figure 5).
When we immunostained transgenic mouse tissue to visualize the distribution of Na+/K+ ATPase alpha III subunits we found that in areas where congophilic plaque staining was apparent, Na+/K+ ATPase staining was absent, and more specifically, there appeared to be no or little Na+/K+ ATPase staining in a penumbral zone surrounding the plaques stained with Congo red (Figures 3E–H and 4A–B). While most immunostaining protocols detect voids at the sites where congophilic plaques are located, these areas appeared somewhat larger in the Na+/K+ ATPase immunostained sections. This led us to speculate about that a reduction in the activity of this extremely important enzyme may have severe impacts on the functions of neurons in the vicinity of the deposits.
We knew from previous studies that dystrophic neurites could be visualized surrounding amyloid plaques in the APP+PS1 mice. And we have demonstrated previously that proteins such as synaptophysin and APP are in fact increased in dystrophic neurites [12]. Therefore, we decided to stain sections for Na+/K+ ATPase and dystrophic neurites, along with amyloid plaques using Congo red, to determine whether Na+/K+ ATPase was absent from these neurites and in their immediate vicinity. We found empirically that staining the ATPase with a peroxidase label and the phosphorylated neurofilament with a fluorescein label to detect dystrophic neurites was the most effective way to see both markers on the same section along with the Congo red stained plaques. Imaging of these sections revealed that dystrophic neurites are in the circumferential area surrounding the congophilic amyloid plaques where Na+/K+ ATPase staining is absent (Figure 4D).
One possible explanation for this putative relationship would be that Aβ associated inhibition of Na+/K+ ATPase activity would result in osmotic imbalance and cause the neurites to begin swelling. In addition to the loss of electronic properties and accompanying dysregulation of neuronal signaling, these changes might even feedback to influence gene expression. Indeed, Huang et al. demonstrated that cells exposed to ouabain have reduced Na+/K+ ATPase αIII subunit mRNA expression [27]. An alternative pathway may involve interactions of Aβ with surface proteins, such as integrins [28,29]. and focal adhesion proteins [30] leading to activation of signal transduction cascades that mediate tyrosine phosphorylation [31]. Bozulic et al. reported that the tyrosine kinase, Lyn, can phosphorylate Na+/K+ ATPase resulting in its removal from the membrane [32]. These findings suggest that either direct inhibition of Na+/K+ ATPase by amyloid or its removal due to amyloid-mediated activation of a signaling cascade, could contribute to the formation of dystrophic neurites due to osmotic and/or ionic imbalances.
Aβ has been shown to bind various cell surface proteins [26,33,34]. and induce neuro-toxicity in vitro [35-37]. To determine the effect of Aβ 1–42 on Na+/K+ ATPase activity, we pre-incubated purified Na+/K+ ATPase with Aβ then colorimetrically measured enzyme activity. Although both preparations of Aβ did suppress activity at 112 μg/ml (~10 μM) and 225 μg/ml (~50 μM), it was the highest concentration (450 μg/ml or ~100 μM) of the soluble Aβ suspension that precipitated the largest reduction in activity compared to vehicle, nearly rendering it completely inactive (Figure 5). The fibrillar Aβ preparation did not exact the same precipitous decline in activity, demonstrating that it is not simply an artifact caused by high concentrations of a peptide that reduced activity. Further investigations will be required to determine which physicochemical form of Aβ is causing the reduced activity. This suggests that the Aβ can directly bind to the Na+/K+ ATPase and decrease its activity. Mark et al. suggests that the 25–35 amino acid region of the Aβ peptide induces oxidative stress thereby impairing Na+/K+ ATPase activity [26], and the findings presented herein are consistent with this earlier work.
Conclusions
These data indicate that Aβ deposition in transgenic mice is associated with reduced activity of Na+/K+ ATPase. In vitro studies suggest that high concentrations of Aβ can quickly inactivate the enzyme activity. One area in the brain that might harbor Aβ concentrations sufficient to suppress the activity of Na+/K+ ATPase would be the micro-domain near and immediately around the plaques. This is the area demonstrated to have reduced immunostaining for Na+/K+ ATPase, while exhibiting increased phosphorylated neurofilament staining consistent with dystrophic neurites. These results lead to the possibility that one factor contributing to the formation of dystrophic neurites is loss of ionic homeostasis. Such changes might explain the "swollen" nature of these neuronal processes in the vicinity of plaques. It might also lead to sufficient disruption of electro-chemical properties as to disrupt normal information processing and lead to memory dysfunction. If these suggestions are correct, drugs targeted at activating Na+/K+ ATPase and maintaining ionic balance in these neurons may benefit Alzheimer's patients by delaying the onset of neuritic dystrophia and memory dysfunction.
Methods
Tissue preparation
Mice were bred in our facility and genotyped using previously described methods [19] The working memory performance of the APP+PS1 mice used in these studies was impaired when compared to non-transgenic littermates as published previously [14]; untreated groups were studied here). For tissue collection, 17–18 month old mice were deeply anesthetized with pentobarbital (100 mg/kg) and perfused transcardially with phosphate buffered saline. Brains were removed and bisected into right and left hemispheres. The right hemisphere was immediately dissected into regions that were immediately frozen on dry ice, while the left hemisphere was post-fixed in 4% para-formaldehyde for 24 hours and subsequently processed through a cryo-protection schedule of 10, 20 and 30% sucrose. Frozen brains were sectioned horizontally on a sliding microtome at 25 μm and stored in Dulbecco's phosphate buffered saline plus azide at 4°C.
Na+/K+ ATPase activity assay and amyloid preparation
An assay to detect specific activity of Na+/K+ ATPase by measuring the release of phosphate was developed using a variation of the method described by Ellis et al. [23]. Freshly frozen dissected hippocampi, cortex and cerebella (20–30 mg tissue weight) from APP+PS1 and non-transgenic littermates were homogenized using a rotor-stator homogenizer in 1 ml of cold suspension buffer containing 85 mM sodium chloride (NaCl), 20 mM potassium chloride (KCl), 4 mM magnesium chloride (MgCl), 0.2 mM EGTA and 30 mM histidine pH 7.2. Saponin was added to the samples to a final concentration of 20 μg/ml. They were then incubated at 37°C for 15 minutes. Protein concentration was measured by Bradford assay and concentrations were adjusted to 10 mg/ml.
In a 96-well plate, 60 μl of ATP buffer containing 140 mM NaCl, 20 mM KCl, 3 mM MgCl, 30 mM histidine and 3 mM ATP were added to wells. Two sets of samples were included, one with ATP buffer only and the other with 100 μM of the Na+/K+ ATPase selective inhibitor ouabain added to the ATP buffer. Subsequently, 10 μl of protein homogenates were added to the ATP buffer ± ouabain, which were then mixed by pipetting and incubated at 37°C for 30 minutes. The reaction was stopped by adding 120 μl of an acid molybdate solution consisting of 0.5 g ammonium molybdate (Sigma, St. Louis, MO) in 0.5 M sulfuric acid. After mixing, 10 μl of Fiske Subbarow Reducer (Sigma, St. Louis, MO) was added and wells were mixed again. The plate was allowed to incubate covered at room temperature for 10 minutes and then measured spectrophotometrically at 660 nm. A standard curve of phosphoric acid dilutions was used to calculate the specific activity of the ouabain sensitive ATP hydrolysis and converted to μmols of inorganic phosphate (Pi) liberated/mg protein/ hour. All reactions were performed in triplicate, which were then averaged to produce the single value for the sample. Differences between APP+PS1 and non-transgenic mice were analyzed for significance using one-way ANOVA. Aβ used for these studies was generated by resuspending 1 mg of commercially available recombinant Aβ 1–42 peptide (rPeptide, Athens, GA) in 221 μl of 1,1,1,3,3,3-Hexafluoro-2-propanol (HFIP, Sigma, St. Louis, MO) to generate 45 μg Aβ 1–42 films. These films were resuspended in 2 μl of anhydrous DMSO, followed by agitation and subsequent addition of either 48 μl of cold water followed by overnight incubation at 4°C (for soluble Aβ preparation) or 10 mM HCl followed by overnight incubation at 37°C (for fibrillar Aβ preparation). The acid was neutralized the following day by the addition of NaOH. These preparations yielded approximately 900 μg/ml suspensions of Aβ.
For analysis of activity inhibition by both preparations of Aβ, purified Na+/K+ ATPase (from brain; Sigma, St. Louis, MO) was pre-incubated for 2 hours in a 37°C orbital shaker separately with 112.5, 225 and 450 μg/ml of either a DMSO+water Aβ suspension or a DMSO+neutralized HCl Aβ suspension. Vehicle alone was also used for each preparation and sample values are indicated as a percentage of the "vehicle only" values. Activity was then measured using the same activity assay as above and significance was measured using one-way ANOVA comparing activity between vehicle treated and Aβ treated.
Western blot
Brain homogenate from cortical tissue was equilibrated to 10 μg of total protein. This homogenate, along with 1 μg of purified cerebral Na+/K+ ATPase, was diluted 1:1 with loading buffer containing 4% SDS and 5% β-mercaptoethanol, heated to 95°C for 5 minutes and loaded onto a 7.5% Tris-glycine gel which was electrophoresed at 100 mV for one hour in the presence of SDS. The protein was subsequently transferred onto an Immobilon membrane (Millipore, Billerica, MA) for one hour at 100 mV. The blot was rinsed with borate saline + 0.05% Tween-20 (BST) and blocked overnight at 4°C in 5% non-fat dry milk (NFDM). The following day, a 1:2000 dilution of rabbit anti-rat Na+/K+ ATPase αIII antibody (Upstate Biotech, Lake Placid, NY) in 0.5% NFDM+BST was applied to the blot for 1 hour, followed by washing and a subsequent 1 hour incubation with a 1:5000 dilution of hrp-labeled anti-rabbit IgG (Sigma, St. Louis, MO) in 0.5% NFDM+BST. After washing, the blot was developed for chemiluminescence using a luminol substrate kit (Santa Cruz Biotech, Santa Cruz, CA). Band density was quantified using the SoftMax Pro program and one-way ANOVA was used to determine significance.
Histology
Immunohistochemical and immunofluorescence analyses for Na+/K+ ATPase αIII and phosphorylated neurofilament, respectively, were performed on the same 25 μm free-floating hippocampal sections. Sections were treated 15 minutes with 10% methanol, 3% hydrogen peroxide and 80% phosphate buffered saline (PBS) to block endogenous peroxidase activity, and then washed 3 times with PBS. Sections were subsequently treated with sodium borohydride for 15 minutes to reduce background auto-fluorescence [38] followed by washing with PBS. Sections were then permeabilized for 30 minutes with 100 mM lysine, 0.2% triton x-100, 2% goat serum and 2% horse serum in PBS, and washed 3 times with PBS. Because one antibody was murine being used on mouse tissue, endogenous mouse IgG was first blocked with a 1:300 dilution of goat F (ab') 2 anti-mouse IgG (overnight; Protos Immunoresearch, Burlingame, CA). Sections were washed the following day and co-incubated with a 1:5000 dilution of a rabbit anti-rat Na+/K+ ATPase αIII IgG (Upstate Biotech, Lake Placid, NY) and a 1:10,000 dilution of a mouse monoclonal IgG1 ascites pool specific for phosphorylated forms of neurofilament (SMI-312; Sternberger Monoclonals, Lutherville, MD) in 2% goat serum and 2% horse serum in PBS. The following day, sections were washed, and then co-incubated in both a 1:3000 dilution of anti-rabbit biotinylated secondary antibody (Vector Laboratories, Burlingame, CA) and a 1:100 dilution of anti-mouse fluorescein conjugated secondary antibody (Vector Labs, Burlingame, CA) for 2 hours. After washing, the tissue was incubated with Vectastain® Elite® ABC kit (Vector Labs, Burlingame, CA). The tissue was then washed and stained with a diaminobenzidine: peroxide system plus nickel enhancement (DAB/Ni2+), followed by final washes. Compact amyloid plaques were visualized using Congo red staining after sections were slide mounted and dried [19]. Briefly, slides were incubated in alkaline alcoholic saturated sodium chloride (AASSC), followed by 0.2% Congo red in AASSC, then dehydrated and cover-slipped with xylene-free Vectamount (Vector Labs, Burlingame, CA). Other mounting media were tested, but only Vectamount was suitable for combined immunohistochemistry, immunofluorescence and Congo red staining. The extent of nonspecific binding was assessed in the absence of primary antibodies for all assays. Specificity of the Na+/K+ ATPase antibody was confirmed by reduced staining following a 2 hour pre-incubation of the antibody with purified cerebral Na+/K+ ATPase at a 1 antibody to 4 enzyme molecule ratio. Both immunostains were characterized individually before the co-incubation procedure was implemented.
Authors' contributions
C D contributed to the design the study, developed the activity assay, generated the Aβ preparations, performed the histology and western blotting, and drafted the article. M G was responsible for maintenance of the animals used in the study, prepared the tissue for subsequent analysis, and assisted in the design. Both D W and D H participated in the histology and contributed to the coordination of the study. M B facilitated the investigations and assisted with histology. M F performed the genotyping of the mice. D M conceived of the study, and contributed to its design and coordination, along with helping to draft the manuscript. All authors read and approved the final manuscript.
Acknowledgements
This work was supported by AG15490 and AG18478 from NIH.
Figures and Tables
Figure 1 Reduced activity and protein levels of the Na+/K+ ATPase enzyme in APP+PS1 mice. Activity of total (A) and ouabain-sensitive (B) ATPase was assayed colorimetrically in APP+PS1 mice tissue (n = 8, open bars) and non-transgenic littermate tissue (n = 8, solid bars), presented here as μmols of phosphate liberated by ATPase per mg of protein per hour. In the amyloid-containing hippocampus, there was a significant decrease in the specific activity of ouabain-sensitive ATPase in APP+PS1 mice compared to non-transgenic mice, but there was no decrease in cerebellar Na+/K+ ATPase activity. Cerebellar activity was 20% of that seen in non-transgenic hippocampus. Panel C shows the quantitation of the optical density of bands corresponding to the molecular weight of Na+/K+ ATPase using standard Western blot technique. This reveals a trend for decreased protein levels. *** indicates significant differences between APP+PS1 mice and non-transgenic littermates (p < 0.001) when measured by one-way ANOVA.
Figure 2 Verification of Na+/K+ ATPase αIII antibody specificity by immunohistochemistry following pre-incubation with purified protein and Western blotting. Horizontal sections were immunostained for Na+/K+ ATPase αIII with (Panel B) and without (Panel A) pre-incubation with 70 μunits of purified enzyme followed by Congo red staining. The pre-incubation significantly decreased staining, confirming antibody specificity. Scale bar = 50 μm.
Figure 3 Hippocampal and cortical immunohistochemistry for Na+/K+ ATPase in APP+PS1 mice and non-transgenic littermates. Horizontal hippocampal and cortical sections were immunostained for Na+/K+ ATPase αII. The left panels depict hippocampus, while the right panels encompass the cerebral cortex. Panels A & B: high power magnification (Scale bar = 8.33 μm) revealed membrane-localized staining for Na+/K+ ATPase in the insular cortex (Panel B) and CA3 of the hippocampus (Panel A) of non-transgenic mice. Panel C: hippocampal staining of non-transgenic mice showed a ubiquitous distribution of Na+/K+ ATPase throughout the neuropil, while less staining was apparent along the pyramidal layer of Ammon's horn, the hilus and the granular layer of the dentate gyrus. Panel D: cortical staining was also substantial with slight lightening in layers 1 and 2. White matter in both structures remained unstained. A similar staining pattern was observed in the APP+PS1 mice with the exception of focal non-stained areas in the gray matter, presumably where amyloid plaques are located (Panel E [hippocampus] & F [cortex]). Immunostaining followed by Congo red histochemistry confirmed that the Na+/K+ ATPase staining was absent not only immediately where amyloid was located, but also in a zone surrounding the plaque (Panels G [hippocampus] & H [cortex]). Scale bar for panels C-H = 120 μm.
Figure 4 Dual Immunostaining of Na+/K+ ATPase αIII and dystrophic neurites. Horizontal sections were immunostained for Na+/K+ ATPase using DAB with nickel intensification followed by Congo red staining for Aβ plaques. A discernable circumferential void in ATPase staining surrounding the plaque was observed (Panel A, scale bar = 50 μm; Panel B, scale bar = 16.67 μm). Immunofluorescent staining of dystrophic neurites using the anti-phosphorylated neurofilament antibody SMI-312 followed by Congo red staining demonstrate a close relationship between amyloid plaques and dystrophic neurites (Panel C; white arrows demarcate the neurites). Congo red yellow fluorescence was digitally suppressed to more clearly reveal the green-stained neurites (scale bar = 16.67 μm). Panel D is a digital overlay of the fluorescein-labeled dystrophic neurite image onto the bright field peroxidase-labeled Na+/K+ ATPase + Congo red image which demonstrates that dystrophic neurites are present predominantly in the zone devoid of Na+/K+ ATPase staining surrounding the congophilic plaques (scale bar = 16.67 μm).
Figure 5 Amyloid-beta 1–42 peptide inhibits Na+/K+ ATPase activity. Purified cerebral Na+/K+ ATPase was pre-incubated with vehicle or Aβ 1–42, and enzyme activity percentages of the vehicle (20 μmols Pi/mg protein/hour) are presented (mean ± SEM). "◊" indicates the values for the soluble (DMSO+water) Aβ suspension. "○" indicates the values for the fibrillar (DMSO+neutralized HCl) Aβ suspension. At the highest concentrations, the soluble preparation dramatically reduces Na+/K+ ATPase activity compared to both vehicle and the fibrillar Aβ preparation. * (p < 0.05) and *** (p < 0.001) indicates significant differences between Aβ and vehicle alone when measured by one-way ANOVA.
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| 15689237 | PMC549198 | CC BY | 2021-01-04 16:03:47 | no | BMC Neurosci. 2005 Feb 2; 6:7 | utf-8 | BMC Neurosci | 2,005 | 10.1186/1471-2202-6-7 | oa_comm |
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BMC BioinformaticsBMC Bioinformatics1471-2105BioMed Central London 1471-2105-6-221569846910.1186/1471-2105-6-22Research ArticleProteins with two SUMO-like domains in chromatin-associated complexes: The RENi (Rad60-Esc2-NIP45) family Novatchkova Maria [email protected] Andreas [email protected] Birgit [email protected] Frank [email protected] Gregor Mendel-Institut GMI, Austrian Academy of Sciences, Vienna Biocenter, A-1030 Vienna, Austria2 Research Institute of Molecular Pathology, Dr. Bohr-Gasse 7, A-1030 Vienna, Austria3 Max Planck Institute for Plant Breeding Research, Carl-von-Linné-Weg 10, D-50829 Cologne, Germany2005 7 2 2005 6 22 22 21 7 2004 7 2 2005 Copyright © 2005 Novatchkova 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
Post-translational modification by Small Ubiquitin-like Modifiers (SUMO) has been implicated in protein targeting, in the maintenance of genomic integrity and in transcriptional control. But the specific molecular effects of SUMO modification on many target proteins remain to be elucidated. Recent findings point at the importance of SUMO-mediated histone NAD-dependent deacetylase (HDAC) recruitment in transcriptional regulation.
Results
We describe the RENi family of SUMO-like domain proteins (SDP) with the unique feature of typically containing two carboxy-terminal SUMO-like domains. Using sequence analytic evidence, we collect family members from animals, fungi and plants, most prominent being yeast Rad60, Esc2 and mouse NIP45 . Different proteins of the novel family are known to interact directly with histone NAD-dependent deacetylases (HDACs), structural maintenance of chromosomes (SMC) proteins, and transcription factors. In particular, the highly non-trivial designation of the first of the two successive SUMO-domains in non-plant RENi provides a rationale for previously published functionally impaired mutant variants.
Conclusions
Till now, SUMO-like proteins have been studied exclusively in the context of their covalent conjugation to target proteins. Here, we present the exciting possibility that SUMO domain proteins, similarly to ubiquitin modifiers, have also evolved in a second line – namely as multi-domain proteins that are non-covalently attached to their target proteins. We suggest that the SUMO stable fusion proteins of the RENi family, which we introduce in this work, might mimic SUMO and share its interaction motifs (in analogy to the way that ubiquitin-like domains mimic ubiquitin). This presumption is supported by parallels in the spectrum of modified or bound proteins e.g. transcription factors and chromatin-associated proteins and in the recruitment of HDAC-activity.
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Background
Among ubiquitin-related proteins, containing at least one domain with a ubiquitin-like fold, one can distinguish ubiquitin-like modifiers (UBLs) and ubiquitin domain proteins (UDPs) [1].
UBLs can be covalently attached to target proteins analogously to ubiquitin. Unlike ubiquitin, UBLs mostly do not directly target proteins for degradation [2], although functional links can exist. One of the most heavily researched single domain UBLs, the small ubiquitin-related modifier (SUMO), is known to act on transcription factors, chromatin associated proteins, nuclear body proteins and septins [2].
In contrast to UBLs, UDPs are not conjugated to other proteins and lack the C-terminal double glycine motif characteristic for ubiquitin and ubiquitin-like modifiers. They are a heterogeneous class of usually multi-domain proteins, which are unrelated outside of their ubiquitin-like domain [1]. In several cases, it has been demonstrated that the ubiquitin-domain within those proteins likely fulfills its cellular role by functionally mimicking ubiquitination [3,4].
The biological relevance of non-conjugatable multi-domain proteins having a domain with clear relationship to UBLs like SUMO, rather than ubiquitin, is yet unknown. Here, we present a detailed sequence analysis of a family of SUMO-like domain proteins (SDPs) containing one or two SUMO-like domains. Members of the proposed RENi family act as factors in transcriptional regulation, chromatin silencing and genomic stability.
Results
Sequence architecture of Drosophila melanogaster CG4449
During the study of the predicted nuclear subset of the Drosophila proteome, we encountered the unknown 424 amino acids long protein CG4449 (NP_651134). Initial analysis of its sequence complexity shows that the disordered N-terminal half of the protein is followed by a likely globular segment (predicted using Pdisorder by Softberry, Inc). Indeed, a compositionally biased, polar low-complexity region (LCR) spans almost the entire N-terminal 220 amino acids (AA) as reported by CAST (region 47–165, lysine-rich) [5] and SEG (regions 46–77 and 133–178, parameters 25/3.0/3.3) [6].
The C-terminal half of CG4449 turns out to contain an internally repeated segment identifiable with RADAR [7] (region 270–309 matching 368–407). In an attempt to confirm this repeat, we queried the protein against the conserved domain database using RPS-BLAST [8]. Thereby, we could define a similarity to SUMO-like domains overlapping with the second repeat-element (see Table 1 for details), while no significant hits emerged for the first of the repeat-constituents. Using profile-profile comparison, however, segment 220–325 is shown to possess a distant, yet significant similarity to SUMO sequences and, therefore, to share the SUMO fold (Table 1).
In conclusion, we found that the Drosophila protein CG4449 (NP_651134) has a tripartite architecture: with a N-terminal LCR followed by two globular domains with a SUMO-like fold (termed SD1 and SD2). Whereas SD2's similarity to single domain SUMO-like sequences can be easily detected with BLAST tools, the identification of SD1 is non-trivial (Table 1). For both SD1 and SD2, a carboxy-terminal double-glycine motif, as it is known and necessary for the covalent attachment of SUMO proteins, is missing. This finding is remarkable as SUMO proteins are discussed in the scientific community solely as polypeptides that become covalently bonded to various targets [9]. Here, we present cases of non-conjugatable poly-SUMO fusion protein.
Collecting animal NIP45-related proteins characterized by two SUMO-like domains
A PSI-BLAST search started with the globular C-terminal half of CG4449 (220–424) including the two SUMO-like domains, collects a family of animal proteins with the same tripartite organization in C. briggsae (CAE71155.1, E = 0.001 round 2), H. sapiens (NP_116204.2, E = 0.003 round 2), M. musculus (NP_035030, E = 1e-39 round 3) and C. elegans (NP_497960, E = 2e-12 round 3). All these proteins contain a LCR at the N-terminus followed by two SUMO-like domains, the first of which has mostly diverged away beyond recognition thresholds using traditional sequence-profile searches (Table 1). The human and the mouse homologs correspond to the studied nuclear factor NIP45 (NF-AT interacting protein) [10]. All sequences and original database search results can be found at the RENi homepage [11].
Distant NIP45 homologs in fungi, other lower eukaryotes and plants
Indications on the existence of NIP45 homologs in lower eukaryotes and plants
A multiple sequence alignment of the globular C-terminal half of D. melanogaster CG4449 (220–424) and the corresponding sequences derived from A. gambie, X. laevis, C. elegans, C. briggsae, M. musculus and H. sapiens (Figure 1) was used to generate a Hidden Markov Model (HMM; in the global alignment mode). The protein family was enlarged using the HMMER2 tool [12] in searches against single model organism proteomes. These searches retrieved as best hits in the respective proteomes the likely homologs in D. discoideum (Sanger proteome identifier- JC3V1_0C0008_11033, 0.00059) A. thaliana (At1g68185.1, NP_564924.1, E = 0.00076), O. sativa (NP_917594.1, E = 0.0019), S. pombe (NP_595995.1, E = 0.00073), S. cerevisiae (NP_010650.1, E = 0.11), Y. lipolytica (CAG82446, E = 0.00087), C. glabrata (CAG57776, E = 0.52) and in other recently published fungi proteomes [13]. The S. cerevisiae and S. pombe homologs correspond to the studied Rad60 and Esc2 proteins, respectively [14,15]; the remaining proteins are uncharacterized.
These HMM-search results suggest the most likely plant and lower eukaryote orthologues to the animal NIP45-like proteins. For establishing the orthology relationship, these initial results need to be confirmed by reciprocal searches independently performed for fungal and plant proteins. Further below, we present this evidence for the homology between the C-terminal part of the proteins found in the various taxonomic groups.
Confirming fungal family members in reciprocal searches
The set of fungal RENi proteins can be autonomously collected using a BLASTP search started with the C. glabrata representative (CAG57776) and retrieving the best and significant hits in the proteomes of S. cerevisiae, S. pombe, K. lactis, C. albicans, Y. lipolytica, D. hansenii, A. nidulans [11]. The domain architecture of these fungal homologs is likely also tripartite (Figure 1, Table 1). It differs from the animal representatives by a longer sequence separating the two SUMO-like domains (many dozens of residues compared with ~10 in the case of animal proteins), which is typically of highly helical content (determined using NPL consensus secondary structure prediction [16]). A HMM was generated from a multiple sequence alignment of the SUMO-domain containing C-terminal half of the listed fungal homologs, where gap only columns replaced the compositional biased helical region between the two SUMO domains. A search with this HMM retrieved as best hits in the respective proteomes the RENi proteins in M. musculus (NP_035030, E = 0.005), A. thaliana (NP_564924, E = 0.016), C. elegans (NP_497960, E = 0.0012).
Confirming plant family members in reciprocal searches
Potential plant RENi homologs, derived in a full-length TBLASTN search with A. thaliana (At1g68185.1, NP_564924.1) against the TIGR Gene indices of barley, maize, rice, potato and soybean [17], show a length of 210–240 AA and are thus around 100 AA shorter than the shortest animal homolog from worm. The domain organization seems also to be distinct. A 100 AA N-terminal, very polar region (with two conserved motifs E [ED]LEPLFDY [SR]RVQP and DWLPPPP found with MEME [18]) is followed by ~40 AA with predicted strong helical preference (using NPL [16]) and a clear C-terminal SUMO-like domain (Table 1). There are no indications for another SUMO-like domain at the N-terminal side of the ~40 AA helical region. Further confirmation of the relationship between the listed RENi proteins of the Viridiplantae and Fungi/Metazoan group comes from the analysis of the reciprocal genomic best hits of A. thaliana in Y. lipolytica (At vs Yl 1e-07, Yl vs At 6e-04) and H. sapiens proteomes (At vs Hs 3e-05, Hs vs At 8e-05) [11].
Definition of the Rad60-Esc2-NIP45 (RENi) protein family
We propose to name the collected group of protein sequences the RENi-family after its most studied members Rad60, Esc2 and NIP45. All representatives have a similar sequence architecture involving a N-terminal low complexity region with many polar and (positively) charged residues and a C-terminal globular part with one (plant proteins) or two (all others) SUMO-like domains.
The use of a model representing the complete globular region of RENi proteins was essential for the successful collection of the family. A global HMM spanning the SD1 and SD2 domains tests for homology in the whole globular part and, correspondingly, directly collects the RENi family. In contrast, when using the C-terminal half of various RENi family members as query sequence in PSI-BLAST [19], the searches are invaded by SUMO proteins (hitting only the segment of SD2) before the RENi family can be collected. This means that the SD2 domain sequence segments of the RENi group and the family of single-domain SUMO proteins are not well separated in sequence space (Figure 3). For this reason, the similarity of NIP45, Esc2 and Rad60 could previously only been defined transitively via the similarity of their SD2 segment to SUMO proteins and their similar length [20].
Discussion
The SUMO-like domains in proteins of the Rad60-Esc2-NIP45 (RENi) family
While RENi proteins of the fungal, metazoan and mycetozoan taxa contain two C-terminal SUMO-like domains (SD1 and SD2), only the second one can be clearly defined in plant representatives (Table 1, Figure 4). This very C-terminal SD2 domain, shares several features discriminating SUMO proteins from other ubiquitin-like modifiers, as for example the large negative charged cluster, seen in the alignment 5–15 residues from the very C-terminus (Figure 1). The negative surface patch formed by these residues has been suggested to shape a SUMO-typical interaction surface [21]. RENi proteins lack conservation of the carboxy-terminal double-glycine motif required for covalent attachment of SUMO to its substrates. Thus, they are likely linear non-cleavable SUMO fusions, which cannot be conjugated to target proteins, and have to be classified as UDPs.
The SD1 SUMO-like domain contained in fungi, metazoa and mycetozoa, has sequentially diverged away from SUMO proteins, but structural prediction suggest its resemblance to SUMO (Table 1). The low sequence conservation of this domain does not understate a possible functional conservation in that region, as it has been shown that the structure rather than sequence is important for the function of ubiquitin-like domains (UD). For example, replacing the UD of the UDP Rad23 with ubiquitin renders a functional protein variant [1].
Indications on the functional importance of the first SUMO-like domain in RENi proteins come from the two fungal representatives of the family. The fission yeast rad60-1 (K263E) [15] and rad60-3 (F272V) [20] mutants, which are defective in the rad60 function of double strand break repair, contain a point-mutation within this first SUMO-like domain (SD1). The sequence alignment to human SUMO-1 (structure 1A5R, see Figure 1) indicates that both mutations most likely affect structurally important positions. They align to residues within human SUMO-1 (1A5R) (Gln55 and Phe66) that have been listed by Bayer et al. [21] among the contacts contributing with parts of their side chain to the formation of the hydrophobic core of the fold (Figure 1 and Figure 2). In the budding yeast Esc2p, the region containing the first SUMO-domain SD1 together with a 80 AA low-complex N-terminal segment can be defined as a sufficient fragment supplying its function in targeted silencing (residues 115–389 in Esc2p) [14].
A graph representation of the pair-wise similarity relationship for SD1 and SD2 sequences to other known ubiquitin-like domains (Figure 3, created with the program Clans [22]) illustrates that both are most closely related to SUMO domains. From our analysis of sequence similarity, we suggest that, at least, the very C-terminal SUMO-like domain (SD2) in RENi proteins is able to mimic SUMO and potentially shares its interaction partners. On the other hand, the available experimental data confirms the functional importance of the SUMO-like domain SD1 preceding it.
The N-terminal polar low complexity region in proteins of the Rad60-Esc2-NIP45 (RENi) family
The occurrence of a N-terminal low complexity region with an excess of polar/charged residues is a characteristic element of the RENi protein architecture. Most likely, this is a conformationally flexible segment without inherent structural preference [23,24]. The molecular function of this region remains unknown. It should also be noted that homology considerations are not applicable to such compositionally biased regions for functional prediction.
Boddy et al. [20] discussed the possible existence of coiled coils in the domain architecture of Rad60, Esc2 and NIP45. We found that the COILS [25] tool generates hits only in few representatives of the RENi family. They are positionally not conserved relative to the two SUMO-like domains. It is known that the COILS tool produces a considerable number of false-positive hits, especially in regions with many polar/charged residues, for example, as is likely the case for a glutamic-acid-rich part in Rad60.
Experimentally verified functions of RENi proteins
Functional information about RENi family members is restricted to the fungal Esc2, Rad60 and the metazoan NIP45 proteins. Here, unfortunately most of the existing data relates to the full-length sequences. Nevertheless, the quite divergent set of functions known for RENi proteins shows considerable overlap with the established cellular roles of SUMO proteins in genome replication and regulation of gene expression.
The fission yeast Rad60 protein was shown to be essential in DNA double-strand break repair, and to be critical also for normal growth [15]. It physically and genetically interacts with the Smc5/6 complex, a complex with a housekeeping role in the genome [20]. Interestingly, the Smc5/6 complex [26] also includes Nse2, a protein containing a zf-MIZ domain commonly found in E3-like SUMO ligases (Pfam-search E = 0.0074). In addition, Rad60 is known to bind the replication checkpoint kinase Cds1 [20].
S. cerevisiae Esc2 (establishment of silent chromatin 2) is involved in chromatin silencing via the recruitment or stabilization of the Sir (silent information regulators) complex [27,28]. It is known to interact with Sir2, a histone NAD-dependent deacetylase (HDAC-class III) of the Sir complex, which is well conserved from bacteria to human [29] and, thus, might be an interaction partner of other RENi proteins as well. Similarly to other HDACs, Sir2 proteins are recruited to chromatin by DNA-bound factors [30] and act by deacetylating histones [31] as well as transcription factors such as p53 and forkhead transcription factor (shown for hSIR2) [29,32]. With respect to a possible intersection with known Rad60 functions, it is interesting that Sir2 is not only involved in heterochromatic gene silencing and euchromatic repression [30] but also in DNA double-strand break repair mediated by end-joining [33].
NIP45, the one studied RENi in metazoa, has been implied in gene regulation, where it needs its DNA-binding partner NFATp for this activity [34]. Strikingly, the NFAT family member NFAT1 that interacts with NIP45 [10] was independently shown to be sumoylated [35]. NFAT1 sumoylation acts in nuclear retention, regulation of transcriptional activity and recruitment to nuclear SUMO-1 bodies [35]. This analysis might suggest a potential role for SUMO-like NIP45 in its complex with NFAT proteins.
Possible functional role of the SUMO-like domains in RENi proteins
There is little experimental data on the importance of the predicted SUMO-like domains in RENi proteins. Nevertheless, all listed functions of RENi proteins conform with the known role of SUMO in transcriptional regulation and the control of genome integrity [36]. In the context of transcriptional repression, SUMO-modification has been suggested to recruit class I and II HDACs to promoter sites. Regarding genome stability, SUMOylation in DNA-repair proteins is thought to target these to DNA damage foci. The following parallels in RENi proteins become obvious: 1) HDAC recruitment has also been suggested for the fission yeast Esc2p [27,28]. 2) Mammalian NIP45 binds to transcription factors that can also be modified by SUMO [35]. 3) RENi and SUMO share a functional context in double-strand break repair and transcriptional regulation. On the basis of functional overlaps of SUMO and RENi proteins, we can speculate that RENi proteins act as SUMO stable fusion proteins "mimicking" SUMO and that they might have common interaction partners.
Conclusions
In this report, we use sequence-analytical methods to infer the homology relationships between RENi family members and determine their tripartite (bipartite for plant homologs) domain architecture. A N-terminal polar low-complexity segment and two consecutive SUMO-like domains in the C-terminal half characterize the functionally described fungal and metazoan RENi proteins. While the more C-terminal SD2 is easily detectable, it is the particularly divergent SD1 that was shown in fungi to be essential for the assayed molecular functions. Due to the likely limited sequential- (as opposed to structural-) requirements, this SUMO-like domain is difficult to detect and has been missed in previous analyses of individual family members. The identification of the more N-terminal SUMO-like domain SD1 helps rationalizing experimental findings for mutant fungal RENi family members.
Methods
RPS-BLAST [8] and FFAS [37] algorithms were used to search the COG [38], SCOP [39] and SMART databases [40]. SEG [6] and CAST [5] were applied in identifying low-complexity regions. Structural similarity was determined using the fold prediction methods FFAS [37] and BIOINBGU [41]. T-coffee was used for initial multiple sequence alignment [42]. CLANS [22] generated the pairwise similarity graph. VMD [43] was used for molecular visualization and POV-ray for the follow-up image rendering.
Authors' contributions
The sequence analytic work was executed by MN. All authors (MN, AB, BE, FE) contributed to evaluating the results and making the discoveries reported here. MN prepared all the figures and, together with FE, the manuscript text. All authors read and approved the final manuscript.
Acknowledgements
The authors thank D. Schweizer for support and assistance. This project has been partly funded by the Austrian Academy of Science, Boehringer Ingelheim, by the Fonds zur Förderung der wissenschaftlichen Forschung Österreichs (FWF P15037) and by the Austrian Gen-AU bioinformatics integration network sponsored by BM-BWK.
Figures and Tables
Figure 1 Multiple Sequence Alignment of Rad60-Esc2-NIP45 (RENi) members. The alignment is CLUSTAL colored [44]. The organism from which a sequence has been derived is indicated by a 2 letter code preceding the database accession numbers: An Aspergillus nidulans, Ag Anopheles gambiae, At Arabidopsis thaliana, Ce Caenorhabditis elegans, Dd Dictyostelium discoideum, Dm Drosophila melanogaster, Gz Gibberella zeae, Hs Homo sapiens, Mm Mus musculus, Os Oryza sativa, Sc Saccharomyces cerevisiae, Sp Schizosaccharomyces pombe, Xl Xenopus laevis, Zm Zea mays. All accession numbers can be found in the NCBI non-redundant database, except 1) the ones of Xl, Zm and Os, which correspond to the TIGR Contig identifiers from which a presumptive translation was derived 2) the Dd protein which is included in the Sanger protein set with the accession JC3V1_0C0008_11033 3) the Ag protein was derived using FGENESH on a segment from Anopheles gambiae str. PEST chromosome 2L (accession AAAB01008810) 4) IL2N, 1A5R are entries from the PDB. The two alignment blocks correspond to the two distinct SUMO-like domains in RENi proteins. Only the second block includes plant representatives, which seem to miss the first SUMO-like domain. The SUMO sequences IL2N, 1A5R have been aligned to both blocks and the secondary structure elements below the alignment are derived from the PDBsum entries for both of these. Triangles mark positions reported to be involved in maintaining the ubiquitin-fold of human SUMO-1 [21]. These are also highlighted in the structural representation in Figure 2. Black encycled red-colored residues in NP_595995 point at the mutations in the rad60-1 (K263E) [15] and rad60-3 (F272V) [20] variants.
Figure 2 Ribbon diagram of the human SUMO-1 protein structure [21]. The displayed region corresponds to the segment shown in the alignment in Figure 1. The core residues L24, I34, F36, F64, F66, I88 located in the beta-strands and L44, L47, K48, Y51, Q55 in the helix form critical contacts in the helix-sheet interface of the SUMO core. These residues are shown in the stick mode (in purple). The highlighted Q55 and F66 residues align with residues mutated in the rad60-1 (K263E) [15] and rad60-3 (F272V) [20] variants (see also Figure 1).
Figure 3 Graph representation of pair-wise sequence similarities for known ubiquitin-like domains plus SD1 and SD2 domains. SD1 and SD2 domains cluster with SUMO proteins. The graph was generated using CLANS [22] and shows all pairwise interactions based on HSP P-values calculated using all-against-all BLASTP. The sequence file used as an input is available on the homepage [11]. Analysis of a more extensive assembly of ubiquitin-fold proteins [45] leads to the same conclusion, but a less well readable graph (not shown). AGP8 – autophagy 8 like proteins, AGP12 – autophagy 12 like proteins, URM1 – ubiquitin related modifier 1, UBP6 - Ubiquitin-specific processing protease 6, RUB1 – Related to ubiquitin 1.
Figure 4 Domain architecture of RENi proteins. Red boxes: SUMO-related domains (labeled SD1 and SD2 respectively), black thick lines: low complexity regions. Species code and accession numbers as in Figure 1. Black waves indicate long helical regions (>20 AA), conserved among close relatives.
Table 1 Representative search hits supporting the SUMO relationship of globular segments in RENi family members. RENi family members (column 1) have been initially split into likely globular segments (column 2). These sequences have been submitted to sequence-based domain and fold-recognition methods (RPS-BLAST [8], FFAS03 [37], column 3) as well as a structure-based similarity method (INBGU [41]) (column 4). For FFAS03 scores below -9.5 are considered significant, for the Fischer fold prediction method (INBGU) it is a score of 12 and above. The following database identifiers correspond to the tabulated domains: COG5227 for the SMT3 domain in COG, smart00213 for UBQ (ubiquitin and ubiquitin-like) in SMART. The mentioned PDB identifiers represent structures of the following molecules: 1A5R Sumo-1 in human, 1L2NA Smt3, the SUMO homolog in budding yeast, 1EUVB Smt3 in budding yeast. The sequence-only similarity methods can be ordered with increasing sensitivity as: (i) RPS-BLAST, (ii) FFAS03 against a sequence database (COG), and (iii) FFAS03 against a structure database (SCOP). Only the significant hit with the lowest sensitivity method is reported for each sequence.
Species/Accession Segment Method/DB/Hit/E-value Hit/Score
D. melanogaster/ NP_651134 220–325 FFAS03/COG/SMT3/-10.400 1A5R/27.1
1L2NA/13.6
325–424 RPS-BLAST/COG/SMT3/9e-04 1L2NA/42.4
1A5R/24.4
S. pombe/ NP_595995 200–315 FFAS03/scop165/1euvb/-11.4 1L2NA/26.4
1A5R/19.7
315–406 FFAS03/COG/SMT3/-16.3 1A5R/16.1
1L2NA/15.2
S. cerevisiae/ NP_010650 330–456 FFAS03/COG/SMT3/-36.6 1A5R/89.7
1L2NA/35.0
C. elegans/ NP_497960 115–225 FFAS03/COG/SMT3/-11.8 1A5R/27.2
225–328 FFAS03/COG/SMT3/-15.3 1A5R/38.5
1L2NA/17.6
M. musculus/ NP_035030 220–320 RPS-BLAST/SMART/UBQ/3e-05
FFAS03/COG/SMT3/-11 1L2NA/24.3
1A5R/19.9
320–412 RPS-BLAST/COG/SMT3/1e-04 1L2NA/89.4
1A5R/71.6
A. nidulans/ EAA62889 160–300 FFAS03/COG/SMT3/-8.3 1A5R/22.5
300–404 RPS-BLAST/SMART/UBQ/3e-04
FFAS03/COG/SMT3/-39.100 1A5R/87.4
1L2NA/30.6
A thaliana/ NP_564924 130–213 RPS-BLAST/COG/SMT3/4e-06 1L2NA/119.1
1A5R/51.4
D discoideus/ JC3V1_0C0008_11033 230–340 RPS-BLAST/COG/SMT3/0.001 1A5R/141.9
1L2NA/57.0
340–449 FFAS03/COG/SMT3/-33.600 1A5R/51.3
1L2NA/39.4
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| 15698469 | PMC549199 | CC BY | 2021-01-04 16:02:52 | no | BMC Bioinformatics. 2005 Feb 7; 6:22 | utf-8 | BMC Bioinformatics | 2,005 | 10.1186/1471-2105-6-22 | oa_comm |
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BMC BioinformaticsBMC Bioinformatics1471-2105BioMed Central London 1471-2105-6-141566378910.1186/1471-2105-6-14Methodology ArticleA robust two-way semi-linear model for normalization of cDNA microarray data Wang Deli [email protected] Jian [email protected] Hehuang [email protected] Liliana [email protected] Marcelo Bento [email protected] Biostatistics and Bioinformatics Unit, Comprehensive Cancer Center, the University of Alabama at Birmingham, Birmingham, AL 35294, USA2 Department of Statistics and Actuarial Science, and Program in Public Health Genetics, the University of Iowa, Iowa City, IA 52242, USA3 Department of Pediatrics, the University of Iowa, Iowa City, IA 52242, USA4 Departments of Biochemistry, Orthopaedics, Physiology and Biophysics, the University of Iowa, Iowa City, IA 52242, USA2005 21 1 2005 6 14 14 18 8 2004 21 1 2005 Copyright © 2005 Wang 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
Normalization is a basic step in microarray data analysis. A proper normalization procedure ensures that the intensity ratios provide meaningful measures of relative expression values.
Methods
We propose a robust semiparametric method in a two-way semi-linear model (TW-SLM) for normalization of cDNA microarray data. This method does not make the usual assumptions underlying some of the existing methods. For example, it does not assume that: (i) the percentage of differentially expressed genes is small; or (ii) the numbers of up- and down-regulated genes are about the same, as required in the LOWESS normalization method. We conduct simulation studies to evaluate the proposed method and use a real data set from a specially designed microarray experiment to compare the performance of the proposed method with that of the LOWESS normalization approach.
Results
The simulation results show that the proposed method performs better than the LOWESS normalization method in terms of mean square errors for estimated gene effects. The results of analysis of the real data set also show that the proposed method yields more consistent results between the direct and the indirect comparisons and also can detect more differentially expressed genes than the LOWESS method.
Conclusions
Our simulation studies and the real data example indicate that the proposed robust TW-SLM method works at least as well as the LOWESS method and works better when the underlying assumptions for the LOWESS method are not satisfied. Therefore, it is a powerful alternative to the existing normalization methods.
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Background
Microarray technology has become a useful tool for quantitatively monitoring gene expression patterns and has been widely used in functional genomics [1,2]. In a cDNA microarray experiment, cDNA segments representing a collection of transcripts and Expressed Sequence Tags (ESTs) are amplified by PCR and spotted in high density on glass microscope slides using a robotic system to produce cDNA microarrays. Each microarray contains thousands of such PCR products, named cDNA probes, which serve as reporters for the expression of the respective transcripts that represent the collection of genes or ESTs. The cDNA microarrays are queried in a co-hybridization assay using two fluorescently labeled biosamples derived from RNA obtained from the cell populations of interest. One sample is labeled with fluorescent dye Cy5 (red), and another with fluorescent dye Cy3 (green). Hybridization is assayed using a confocal laser scanner to measure fluorescence intensities, allowing simultaneous determination of the relative expression levels of all the genes represented on the slide [3].
A basic question in analyzing cDNA microarray data is normalization, the purpose of which is to remove systematic bias in the observed expression values by establishing a normalization curve across the whole dynamic range. A proper normalization method ensures that the normalized intensity ratios provide meaningful measures of relative expression levels. Normalization is needed because many factors, including different efficiency of dye incorporation, difference in the amount of RNA labeled between the two channels, uneven hybridizations, difference in the printing pin heads, among others, may cause bias in the observed expression values. Therefore, proper normalization is a critical component in the analysis of microarray data and can have important impact on higher level analysis such as detection of differentially expression genes, classification, and cluster analysis.
Many normalization methods have been proposed in the literature. The earliest normalization method for cDNA microarray data goes back to Chen et al. [4] who proposed a ratio-based method. Yang et al. [5] summarized several normalization methods for cDNA microarray data such as global normalization, dye-swap normalization, block-wise normalization, and scale normalization. They also proposed a locally weighted scatter plot smoothing (LOWESS [6]) method for intensity dependent normalization. Quackenbush [7] and Bilban et al. [8] provided good reviews on normalization methods for cDNA microarray data. Tseng et al. [9] proposed using a rank based procedure to first select a set of invariant genes that are likely to be constantly expressed and then carrying out LOWESS normalization using this set of genes. But as pointed out by Tseng et al., selected invariant genes may not cover the whole dynamic range of the expression values, and extrapolation is needed to fill in the gaps that are not covered by the invariant genes. Kepler et al. [10] also first estimated a set of "constantly expressed genes" and then used the LOWESS method. Wang et al. [11] proposed an iterative normalization method for cDNA microarray data by estimating a normalization coefficient and identifying control genes. Workman et al. [12] used array signal distribution analysis for a robust non-linear method of normalization. Park et al. [13] compared a number of normalization methods, including global, linear and LOWESS normalization methods. Wolfinger et al. [14] used a mixed model for normalization. They proposed a normalization model for normalization and a gene model for inference and these two models are related by the residual terms in the normalization model. A constant normalization factor assumption is needed in this method. Fan et al. [15] considered a Semi-linear-In-slide Model (SLIM) method using within-array replications. The SLIM method requires replication of a subset of the genes in an array. If the number of replicated genes is small, the expression values of the replicated genes may not cover the entire dynamic range or reflect spatial variation in an array. Fan et al. [16] generalized the SLIM method to account for across-array information, resulting in an aggregated SLIM, so that replication within an array is no longer required. Huang et al. [17] proposed a two-way semi-linear model (TW-SLM) for normalization of cDNA microarray data. They used the least squares method for estimating the normalization curves based on B-splines. This method does not require the assumptions required by the LOWESS normalization method, i.e. (i) a small fraction of genes are differentially expressed or (ii) there is symmetry in the expression levels of up- and down-regulated genes.
It is well known that the least squares method is not resistant to outliers which arise often in cDNA microarray experiments because of many sources of variations. In this paper, we propose a robust method for normalization in the framework of the TW-SLM. We conduct simulation studies and use a real cDNA microarray data set to compare the proposed method with the LOWESS normalization method.
Results
Simulation study
Simulation was conducted to compare the mean square errors (MSE) and biases of estimated gene expression levels between the proposed robust TW-SLM and LOWESS normalization methods, between the proposed method and the TW-SLM using OLS. The MSE for the jth gene is calculated as the following:
that is, , where N is the total number of replicates for each simulation, J is the number of unique genes, βj is the true gene expression level (base two log scale) for gene j, is the estimated value for βj, is the mean of for N replicates, j = 1, 2,..., J, where J is the total number of genes. The data simulation procedure is based on the method proposed by Balagurunathan et al. [18]. In each simulation, we generated 10 slides with twelve blocks in each, and 500 genes in each block. We repeated 100 times for each simulation. The simulation procedure can be summarized in the following steps:
1. Simulate true signal intensity for each gene j using the exponential distribution with the mean of 3,000, i.e. Ij ~ exp(λ = 1/3000), for j = 1,..., J;
2. Simulate fluorescent intensity for the Cy5 channel and the Cy3 channel with the normal distribution, respectively. Suppose the coefficients of variation for intensity in the Cy5 channel and the Cy3 channel are αrj and αgj, respectively, then the fluorescent intensity on the two channels can be generated by the normal distribution with mean Ij and standard deviations αrjIj and αgjIj for the red channel and the green channel, respectively. Let Rj and Gj represent simulated fluorescent intensity for the Cy5 channel and the Cy3 channel for gene j, respectively;
3. Simulate differentially expressed genes. Suppose γ × 100% genes are differentially expressed in the whole simulated gene set, then the ratio of the expression level for gene j can be generated by tj = 10±b with b ~ Beta(1.7,4.8). The sign ± will determine if the gene is up- or down-regulated. The probability of the up-regulated genes within those γ × 100% differentially expressed genes is given as an input parameter. For the genes that are not differentially expressed, the b takes value zero;
4. Incorporate the tj into signal intensity of gene j. The Rj and Gj will be adjusted by adding the simulated expression ratio tj through the following formulae: for j = 1,..., J;
5. Simulate a fluorescent system with the imperfect response characteristics. Due to various reasons, such as the unequal amount of mRNA for the two channels, different labeling efficiencies, or uneven laser powers at the scanning stage [18], actual intensity in the two channels are not exactly the same. More over, fluorescent intensity is not necessarily linearly related to the expression levels. Balagurunathan et al. proposed the following functional family,
to distort the response characteristic functions of observed fluorescent intensity for the two channels, which are expressed as and , respectively. So four parameter values need to be determined for each channel before simulation. Different parameter values in the two channels will control the shape of the ratio vs. signal intensity plots (R-I plots);
6. Simulate background noise for each channel. The mean of background noise is determined by one input parameter: the signal to noise ratio (SNR) and the true mean of signal. The SNR is the ratio between the true mean of the signal and the true mean of background noise. The SNR controls variability of background noise. The normal distribution with a given mean value is used in simulating background noise. Variance of background noise will be controlled by the input parameters αbr and αbg for the Cy5 channel and the Cy3 channel, respectively. These two parameters are the ratios between the mean and the standard deviations of background noise for the two channels, respectively. Simulated signal intensity for the two channels, and , are adjusted by subtracting background noise in each channel. Let and still denote background adjusted signal intensity for the two channels;
7. Add noise to the signal intensity for each channel. Finally, the signal intensity of each channel is generated by
with , where α1 ~ U (a1, b1), α2 ~ U (c1, d1), α3 ~ U (a2, b2), α4 ~ U (c2, d2). The a1, b1, c1, d1, a2, b2, c2, d2 are given as input parameters to control variability of fluorescent signal intensity.
We simulated two situations, one is the no-dye bias case and another one is the shape case (dye bias exists). R-I plots of twelve blocks on one slide for two simulated cases are shown in Figures 2 and 3, respectively. We considered five different percentage levels of differentially expressed genes: 1%, 5%, 10%, 20%, and 40%. The ratio of the up-regulated genes to the down-regulated genes takes three values, i.e., 1:1, 3:1, and 9:1 at each percentage level of differentially expressed genes. In addition, based on the suggestion of a reviewer, we simulated an extreme case for the scenario in Figure 3, in which 70% genes are all up-regulated and the remaining ones are not differentially expressed.
The trend of MSEs and biases of estimated gene expression levels are similar between the robust TW-SLM and the LOWESS normalization methods across different levels of the ratios between the up-regulated genes and the down-regulated genes. This trend also exists in the extreme case. We present the results of the following two scenarios: (a) a 9:1 ratio between the number of the up-regulated genes and that of the down-regulated genes and, (b) the extreme case. Tables 1 and 3 present MSEs, Tables 2 and 4 show biases of estimated gene expression levels. MSEs and biases for the extreme case (70% of the genes are up-regulated) are presented in the bottom of Tables 3 and 4, which are displayed in Figures 6 and 7, respectively. The robust TW-SLM method has smaller means of MSEs than the LOWESS normalization method and the TW-SLM using OLS, respectively. Also the ranges of MSEs for the proposed method are also smaller than those using the LOWESS method and the TW-SLM with OLS, respectively.
Comparing the different robust weight functions, means of MSEs are slightly smaller using Tukey's weight function than that using Huber's weight function. These results are observed across different percentage levels of differentially expressed genes. Biases for estimated gene expression levels distributed similarly between the proposed method and the LOWESS normalization method. But the ranges of the biases for the proposed method are smaller than those of the LOWESS normalization method and the TW-SLM using OLS, respectively. These observations are true in both simulated situations.
The extreme case is an example where the proposed method does better than the LOWESS method (Tables 3 and 4, Figures 6 and 7). Estimates using the LOWESS method are downward biased in this case. This is what we would expect because the LOWESS method fits normalization curves through the majority of genes, which are mostly up-regulated here. In contrast, the TW-SLM method does not need the either of the two assumptions needed by the LOWESS method, neither of which is satisfied here.
The distributions of MSEs and biases between the TW-SLM using OLS and the LOWESS method are similar for cases where there is a relatively small percentage of differentially expressed genes. However, the TW-SLM with OLS performs better than the LOWESS when a larger proportion of genes are differentially expressed. It appears that the more deviation from the two assumptions required by the LOWESS, the better the TW-SLM performs. This trend is consistent with findings in our previous work [17].
An example
In this section, a real data set was analyzed to compare consistency of the LOWESS normalization method and the proposed robust TW-SLM method. A collection of human placenta cDNAs comprising 7,042 clones was identified and used as the probe set for cDNA microarray fabrication in this study [19].
Three kinds of RNA samples were used which include: (i) a common reference RNA obtained by in vitro transcription from a pool of cDNAs in equal amount comprising the entire probe set (PS); (ii) the "Universal Human Reference RNA" from Stratagene, a pool of RNAs derived from 10 different cell lines; and (iii) human full-term placenta RNA. The original goal of the study was to evaluate the performance of the PS RNA as a reference RNA in comparison with that of Stratagene's universal reference RNA.
In this study, the Universal Human Reference RNA and the human placenta RNA were treated as two experimental samples. The PS RNA was used as the reference against which the two other bio-samples were compared. In the simple direct comparison, gene expression values were obtained through direct hybridizations between the human placenta RNA and the Universal Human Reference RNA. In the indirect comparison using the PS set as the common reference, hybridizations were performed between the human placenta RNA and the PS reference RNA, and between the Universal Human Reference RNA and the PS reference RNA. The design of this experiment is depicted in Figure 1.
After hybridization, slides were scanned with the Axon instruments 4000B scanner. The 633 and 532 lasers are used for excitation of the Cy5 and Cy3 fluorophores, respectively. For each of the three types of hybridizations (i.e., the human placenta vs. the universal reference, the human placenta vs. the PS reference, and the universal reference vs. the PS reference), there are four slides, including two dye-swapped slides. Each clone was printed three times on different blocks on each slide. Background adjusted medians for the Cy5 and Cy3 channels were used as expression levels. We removed negative controls including "Human Cot1", "PolyA" and "Empty" in the analysis.
To evaluate the proposed method, we compare it with the LOWESS method by examining which method produces more consistent results between the direct comparison and the indirect comparison of human placenta and universal human reference RNA samples as described above (see also Figure 1). The rationale is that the results from the direct comparison design and the indirect comparison design should be similar, because the same RNA samples are compared in both designs, albeit the indirect comparison is through a third common reference. Therefore, a better normalization method is the one that yields more consistent results between the direct and indirect comparison experiments.
The data were normalized using the LOWESS normalization method and the robust TW-SLM with Tukey's robust weight function separately. Significance analysis was carried out for the normalized data for each method by comparing gene expression levels in the human placenta tissue relative to the universal reference. One sample t-test was used for the direct comparison and two-sample t-test was used for the indirect comparison. We used 10-5 and 10-3 as cutoff points for p-values to determine if clones are statistical significant or not. Consistency of estimated relative gene expression levels was compared between the direct design and the indirect design for each method. We also compared overlap between the LOWESS normalization method and the robust TW-SLM for each design. The results are presented in Figures 4 and 5.
We used 10-5 as a cutoff point for p-values in Figure 4. Using the robust TW-SLM normalization and the t-tests, there are 2,907 genes with p-value less than 10-5 in the direct comparison and 2,791 in the indirect comparison. There are 1,713 genes common in these two sets of genes with p-value less than 10-5, which account for about 59% (1713/2907) in the direct comparison and about 61% (1713/2791) in the indirect comparison.
In comparison, using the LOWESS normalization and the t-tests, there are 1,447 genes with p-value less than 10-5 in the direct comparison and 1,045 in the indirect comparison. The number of overlapping genes with p-value less than 10-5 is 467, which is around 32% (467/1447) in the direct comparison and about 44% (467/1045) in the indirect comparison. It is clear that the proposed method performs more consistent between the direct comparison and the indirect comparison.
We also examined overlap between the LOWESS and robust TW-SLM methods for the two comparisons. In the direct comparison, about 79% (1141/1447) of the genes found to be significant based on the LOWESS method are also found to be significant based on the robust TW-SLM method. But they only account for about 40% (1141/2907) of the significant genes detected based on the robust TW-SLM method. In the indirect comparison, about 71% (738/1045) of the significant genes based on the LOWESS method are also found to be significant based on the robust TW-SLM method. But they only account for about 26% (738/2791) significant genes detected based on the robust TW-SLM method.
In our analysis, we used background adjusted intensity values. How to adjust background is an important issue in microarray data analysis. To evaluate if background affects our conclusions, we repeated the comparison analysis without adjusting background for the intensity values in both channels, the results are presented in Tables 5 and 6. We see from these tables that the overall results are similar to those using background adjusted intensity values in normalization. This is what we would expect because of low and uniform distributed background noise in all arrays in this example (data description is not shown).
Therefore, the robust TW-SLM method yields more consistent results between the direct comparison and the indirect comparison with the human placenta and the universal human reference RNA samples. In addition, the robust TW-SLM method detects more significant genes for a given cutoff p-value. This makes sense biologically because most of the 7,042 genes specifically discovered from human placenta are expected to have differential expressions relative to the universal reference RNAs. We would expect that the similar comparison results will be got if we compare the TW-SLM using OLS or Huber's weight function with the LOWESS method because the normalization curves for the TW-SLMs (TW-SLM:OLS, TW-SLM:Huber, TW-SLM:Tukey) are similar, but all these three curves are different from the LOWESS normalization curve (Figure 8).
Discussion
We have proposed a robust TW-SLM normalization method for cDNA microarray data. It is interesting to compare the proposed normalization method with the existing methods, such as the widely used LOWESS normalization proposed by Yang et al. (2001) [5] and further discussed by Tseng et al. (2001) [9]. In the LOWESS method, normalization is done separately by first fitting a separate curve for each slide through the R-I plot of log-intensity ratios versus log-intensity products. In comparison, the proposed method uses all the slides in estimating each normalization curve, using the gene effects βj as the thread linking these slides. In addition, in the proposed method, the normalization curves φi and gene effects βj are estimated simultaneously. With this approach, there is no need to assume that the percentage of genes with differential expression levels is small or the expression levels of up- and down-regulated genes are symmetric, or when one of these assumptions is not satisfied, to use dye-swap normalization, which in turn requires the assumption that the two normalization curves are symmetric. (However, we note that dye-swap as a design strategy is useful to balance the experimental conditions and reduce bias due to different dye incorporation efficiencies.) An underlying condition required for the proposed method is independence of arrays, which is satisfied in a typical microarray experiment. Further theoretical conditions for the TW-SLM can be found in the paper by Huang et al. [17].
We have only considered the proposed robust TW-SLM method for the simple direct comparison design described in the Methods section. We can easily extend the method to more complicated designs. For example, we can adapt the proposed robust method to the TW-SLM that accommodates the design where a gene is printed multiple times. Such a design is helpful for improving the precision and for assessing the quality of an array using the coefficient of variation (Tseng et al. 2001 [9]). We can also adapt the robust TW-SLM to incorporate control genes with known concentration ratios in estimating the normalization curves. Model (1) can be easily extended to block-wise normalization by treating different blocks as separate arrays and normalization can be carried out as what we did here. Block-wise normalization considers spatial variation within an array. We did block-wise normalization on the data sets in the example and compared the results with that using the LOWESS method (Tables 5 and 6). The proposed method still outperforms the LOWESS method if we use block-wise normalization in this example.
Conclusions
In our simulation studies, the proposed method performs better than the LOWESS normalization method in terms of MSEs of estimated gene effects in the simulation models we considered. Analysis of the probe set reference data set [19] shows that the proposed method yields more consistent results between the direct and indirect comparisons than the LOWESS normalization method. In addition, the proposed method is more sensitive in detecting differentially expressed genes than the LOWESS method. Therefore, we believe that the proposed robust TW-SLM method is a powerful alternative to the existing normalization methods. We have coded the proposed method in an R package which is available from the corresponding authors.
Methods
We first describe the TW-SLM. For simplicity, we focus on the case of comparing two cell populations, in which two cDNA samples from the respective cell populations are competitively hybridized on the same array. Let n be the number of slides, and J be the number of genes in the study. Let Rij represent background corrected signal intensity from the Cy5 channel and Gij the background corrected signal intensity from the Cy3 channel, and let yij = log2(Rij/Gij), xij = (1/2) log2(Rij × Gij), for gene j on slide i. We assume that there is only one spot for each gene on each slide. The TW-SLM [17] is
yij = φi (xij) + βj + ∈ij, i = 1,..., n, j = 1,..., J (1)
In this model, the observed log intensity ratio is decomposed into three components. The first component is φi which is the intensity dependent normalization curve for slide i, the second component is βj which represents the relative expression value of the jth gene after normalization, the last one is the residual error term. Let be a robust estimator of the ith normalization curve φi based on this model described above. The normalized data are
Huang et al. (2004) [17] considered the least squares method for estimating φi and βj in the TW-SLM. However, it is well known that least squares estimates are not robust against outliers which often arise in microarray experiments. Therefore, we propose to use the robust method [20] for estimating φi and βj. This is done by minimizing the objective function
where ρ is an appropriately chosen function for robust estimation, λ is the collection of the coefficients in the spline representations of φi described below, σ is the scale parameter, and α is a constant to be described below. We note here that estimation of φi, βj are done jointly and uses data from all the arrays. This is different from the LOWESS normalization method in which estimation of normalization curves are done array by array.
We consider two ρ functions: Huber's ρ function and Tukey's biweight function. Huber's ρ function is
Tukey's biweight function is
Two other usefull functions derived from ρ, ψ and χ, will be used repeatedly in the description of the algorithm below. They are defined as
ψ(x) = ρ'(x), χ(x) = xψ(x) - ρ(x). (4)
The expressions of these functions are given in the Appendix. We choose commonly used constants in the literature for Huber's and Tukey's functions, i.e., H = 1.345 and k = 4.685. The influence of the choice of these constants on normalization methods is beyond the scope of this study.
We use the cubic B-splines [21,22] to approximate the normalization curves φi. Specifically, let b1,..., bK be K B-spline basis functions. We approximate φi by
where b(x) = (1, b1(x),..., bK(x))' and λi = (λi0, λi1,..., λiK)'.
We estimate the parameters in model (1) by minimizing objective function (3) using an iterative procedure. Two steps, a location step and a scale step, will be used in the computation.
Location step
We use the following vector and matrix notations in describing the location step:
Bi = (b(xi1), b(xi2),..., b(xiJ))',
yi = (yi1, yi2,..., yiJ)'.
Let
and let
for i = 1,..., n. Given the scale parameter σ, and satisfy the equations:
where and because of identifiability requirement in the TW-SLM. We can solve these equations iteratively to obtain and . The derivations of these equations are given in the Appendix.
Scale step
According to Huber's proposal [23], the estimation equation for σ is
where rij = yij - b'(xij) , and N is the total number of observations in the data set. In general, equation (8) does not have an explicit solution. So we use the following updating equation to compute the estimated scale parameter σ,
In order to obtain the consistent scale estimator at the normal distribution and obtain the classic estimates when using the least squares objective function, i.e., , we used the constant suggested by Huber [23],
where EΦ denotes expectation with respect to the standard normal distribution function Φ.
The procedure described above is called an iterative reweighted least squares (IWLS) algorithm that is used in many non-least squares estimation problems. The implementation of the IWLS algorithm can be carried out using the following steps:
1. Initialize for j = 1,..., J and σ(0) = 1, , for i = 1,..., n, j = 1,..., J;
2. Calculate according to equation (6) given β(m-1), σ(m-1) and for i = 1,..., n, j = 1,..., J, m = 1,...;
3. Check convergence of λi, β, and σ. If the convergence criteria is met, then stop, otherwise continue;
4. Update σ(m) by equation (9) given , , σ(m-1), and , and set σ(m-1) = σ(m);
5. Calculate weight given β(m-1), and σ(m) according to equation (5), and set ;
6. Calculate β(m) given σ(m-1) and using equation (7), and set ;
7. Go to step 2 and iteratively update the estimators of parameters and the weights between steps 2 and 6 until convergence.
Authors' contributions
DW devised and implemented the procedure described in the paper, drafted and finalized the manuscript. JH helped with writing and revising the manuscript. JH and MBS supervised and provided support for this work. HX and LM conducted the experiment that generated the data set used in the example.
Appendix
Derivation of and
We derive estimation equations for location parameters presented in the Methods section in this appendix. Again the notations from the Methods section:
b(x) = (1, b1(x),..., bK(x))',
λi = (λi0, λi1,..., λiK)'.
φi(xij) can be approximated by a linear combination of B-spline basis functions, i.e. b'(xij)λi, where bk(xij) is the kth B-spline basis function of xij. Let A = (a1, a2,..., an)', C = (c1, c2,..., cn)', and define
Given scale parameter σ, the first partial derivatives of S(λ, β, σ) (3) with respect to λ and β can be expressed in the matrix form as
where Bi; = (b(xi1), b(xi2),..., b(xiJ))', yi = (yi1, yi2,..., yiJ)', ψ(x) = ρ'(x). As defined in equation (5)
and
Wi = diag(wi1, wi2,..., wiJ),
Plugging Wi into equations (10) and (11) and setting them to zeros, and solving these two equations and yielding estimation equations for in equation (6) and in equation (7). They are
Let
then equation (7) can also be expressed as
= (Z'WZ)-1 Z'W(y - B).
The solution of (Z'WZ)-1 can be explicitly calculates using the following matrix,
where , and for j = 1,..., J. We can get the explicit solution of after doing some linear algebra. It is
for j = 2,..., J. And because of identifiability requirement in model (1).
Derivation of scale parameter estimator
The ψ and χ functions derived from Huber's ρ(z) function are
The related weight function has the form
where H is a constant.
The constant α used in the scale step for Huber's robust estimation can be calculated as the following
where Φ is the distribution function of the standard normal distribution, N is the total number of observations in the dataset, and p is the total number of parameters in the model.
The ψ and χ functions derived from Tukey's ρ(z) function are
The associated weight function has the form
where k is a constant and the constant a in the scale step takes value
where is the Chi-square probability function with n degrees of freedom evaluated at s.
When Tukey's weight function is used, equation (8) is solved directly for the estimator of σ instead of iteratively updating equation (9) in our R program. It can be shown that equation (8) for Tukey's χ(z) function has an unique real root. This real root is just the solution for the estimator of σ. Let n* be the total number of observations that satisfy the second case of Tukey's χ function, i.e. | z | >k, let J* be the total number of clones that satisfy the first case of the χ, i.e. | z | ≤ k. Replacing z by and plugging Tukey's χ into equation (8), we get
where
Let
Then equation (12) becomes
ax3 + bx2 + cx + d = 0. (13)
Let x = y - b/3a, divided by a in the both sides of equation (13), and plugs x into equation (13), then we get the Cardan's cubic equation
Let p = c/a - b2/3a2, q = d/a - bc/(3a2) + 2b3/(27a3), the above equation becomes
y3 + py + q = 0. (15)
The determinant for Cardan's equation (15) is
It can be shown that the determined function Δ must be positive. The first term in the determinant equation must be positive because of the square function and q cannot be zero. If we can show that the p is greater or equal to zero, then the Δ must be positive. Because
So the Δ is positive if only if 3ac - b2 is non-negative. We can see that
According to the Cauchy inequality [24], we have
Therefore, the p must be non-negative and the Δ must be positive. Thus there is only one real root for equation (15), that is
Then the solution for σ in equation (12) is
Acknowledgements
This work is supported in part by grant HL72288 from the National Heart, Lung and Blood Institute.
Figures and Tables
Figure 1 Study designs for cDNA microarray experiments among the human placenta, the universal reference, and the Probe Set.
Figure 2 An example of R-l plots for twelve blocks of slide one with no-dye bias for two channels, 10% genes are differentially expressed.
Figure 3 An example of shaped R-l plots for twelve blocks of slide one with the dye bias for two channels, 10% genes are differentially expressed.
Figure 4 Consistency analysis based on cutoff p-value 10-5. Both x and y axes are estimated log intensity ratios. (a)-(b) between the direct design and the indirect design for the robust TW-SLM and the LOWESS normalization method, respectively; (c)-(d) between the LOWESS method and the robust TW-SLM for the direct design and the indirect design, respectively.
Figure 5 Consistency analysis based on cutoff p-value 10-3. Both x and y axes are estimated log intensity ratios. (a)-(b) between the direct design and the indirect design for the robust TW-SLM and the LOWESS normalization method, respectively; (c)-(d) between the LOWESS method and the robust TW-SLM for the direct design and the indirect design, respectively.
Figure 6 A boxplot for comparing mean square errors among normalization methods for the case that 70% genes are all up-regulated (Table 3).
Figure 7 A boxplot for comparing biases among normalization methods for the case that 70% genes are all up-regulated (Table 4).
Figure 8 Slide-wise normalization curves based on different methods for one slide of the human placenta vs. the probe set hybridization in the example.
Table 1 The mean square errors (MSE) of estimated gene expression levels (up:down = 9:1) for simulated cDNA microarray data with the R-I plots similar to Figure 2.
Percentage of DEG Descriptive Statistics
Method Mean Minimum 25% Quantile Median 75% Quantile Maximum
1% OLS 0.0837 0.0243 0.0474 0.0614 0.1074 1.7586
Huber 0.0510 0.0106 0.0235 0.0312 0.0703 1.1750
Tukey 0.0481 0.0101 0.0215 0.0291 0.0675 0.8684
LOWESS 0.0849 0.0197 0.0485 0.0642 0.1085 1.7488
5% OLS 0.0984 0.0197 0.0487 0.0648 0.1128 2.1413
Huber 0.0605 0.0117 0.0246 0.0331 0.0740 1.5012
Tukey 0.0556 0.0110 0.0226 0.0305 0.0712 1.2406
LOWESS 0.0990 0.0234 0.0493 0.0677 0.1145 2.1275
10% OLS 0.1198 0.0259 0.0519 0.0695 0.1244 1.7445
Huber 0.0749 0.0118 0.0266 0.0371 0.0830 1.1705
Tukey 0.0673 0.0111 0.0241 0.0340 0.0795 1.0206
LOWESS 0.1196 0.0232 0.0514 0.0722 0.1264 1.7935
20% OLS 0.1545 0.0239 0.0601 0.0855 0.1482 2.2914
Huber 0.0983 0.0121 0.0322 0.0497 0.0994 1.4550
Tukey 0.0854 0.0112 0.0285 0.0451 0.0932 1.1777
LOWESS 0.1530 0.0244 0.0602 0.0900 0.1612 2.1958
40% OLS 0.2099 0.0287 0.0835 0.1293 0.2086 2.3221
Huber 0.1365 0.0155 0.0465 0.0827 0.1428 1.6918
Tukey 0.1164 0.0135 0.0395 0.0735 0.1296 1.4402
LOWESS 0.2220 0.0345 0.1153 0.1665 0.2491 2.8279
DEG: differentially expressed genes. OLS: the TW-SLM using the ordinary least squares.
Huber: the robust TW-SLM using Huber's weight function. Tukey: the robust TW-SLM using Tukey's weight function.
Table 2 Bias of estimated gene expression levels (up:down = 9:1) for simulated cDNA microarray data with the R-I plots similar to Figure 2.
Percentage of DEG Descriptive Statistics
Method Mean Minimum 25% Quantile Median 75% Quantile Maximum
1% OLS 0.0000 -1.2716 -0.0212 -0.0033 0.0154 1.2441
Huber 0.0000 -1.0330 -0.0161 -0.0020 0.0115 0.9925
Tukey 0.0001 -0.8617 -0.0153 -0.0014 0.0112 0.8462
LOWESS -0.0017 -1.2685 -0.0226 -0.0047 0.0137 1.2367
5% OLS 0.0000 -0.8941 -0.0412 -0.0209 0.0019 1.4051
Huber 0.0000 -0.7785 -0.0326 -0.0167 0.0007 1.1751
Tukey 0.0000 -0.7195 -0.0299 -0.0146 0.0017 1.0581
LOWESS -0.0005 -0.8995 -0.0384 -0.0182 0.0008 1.3993
10% OLS 0.0000 -1.1402 -0.0705 -0.0441 -0.0125 1.2574
Huber 0.0000 -0.9240 -0.0578 -0.0353 -0.0096 1.0326
Tukey 0.0000 -0.8245 -0.0521 -0.0313 -0.0064 0.9551
LOWESS -0.0050 -1.1332 -0.0666 -0.0429 -0.0207 1.2736
20% OLS 0.0000 -1.4381 -0.1108 -0.0742 -0.0336 1.3336
Huber 0.0000 -1.1569 -0.0927 -0.0607 -0.0247 1.1176
Tukey 0.0000 -1.0430 -0.0841 -0.0540 -0.0175 0.9757
LOWESS -0.0325 -1.4180 -0.1352 -0.1009 -0.0634 1.2991
40% OLS 0.0000 -1.4475 -0.1943 -0.1348 0.1870 1.3258
Huber 0.0000 -1.2461 -0.1620 -0.1061 0.1474 1.1159
Tukey 0.0000 -1.1429 -0.1460 -0.0907 0.1294 0.9800
LOWESS -0.1488 -1.6159 -0.3340 -0.2603 0.0182 1.1444
DEG: differentially expressed genes. OLS: the TW-SLM using the ordinary least squares.
Huber: the robust TW-SLM using Huber's weight function. Tukey: the robust TW-SLM using Tukey's weight function.
Table 3 The mean square errors (MSE) of estimated gene expression levels (up:down = 9:1) for simulated cDNA microarray data with the R-I plots similar to Figure 3.
Percentage of DEG Descriptive Statistics
Method Mean Minimum 25% Quantile Median 75% Quantile Maximum
1% OLS 0.0370 0.0116 0.0258 0.0323 0.0410 2.2092
Huber 0.0248 0.0112 0.0195 0.0223 0.0255 1.7156
Tukey 0.0238 0.0109 0.0191 0.0217 0.0247 1.5648
LOWESS 0.0375 0.0119 0.0251 0.0321 0.0419 2.2162
5% OLS 0.0489 0.0126 0.0265 0.0333 0.0422 1.5836
Huber 0.0324 0.0110 0.0198 0.0228 0.0263 1.1765
Tukey 0.0299 0.0108 0.0194 0.0222 0.0254 1.0278
LOWESS 0.0493 0.0125 0.0255 0.0325 0.0429 1.6134
10% OLS 0.0692 0.0124 0.0285 0.0359 0.0464 1.6907
Huber 0.0455 0.0098 0.0210 0.0245 0.0288 1.1667
Tukey 0.0404 0.0102 0.0204 0.0236 0.0276 1.0175
LOWESS 0.0692 0.0119 0.0270 0.0349 0.0461 1.6846
20% OLS 0.0961 0.0137 0.0324 0.0428 0.0570 1.8614
Huber 0.0632 0.0124 0.0235 0.0282 0.0354 1.2969
Tukey 0.0547 0.0127 0.0225 0.0266 0.0329 1.0525
LOWESS 0.0950 0.0154 0.0325 0.0431 0.0580 1.8834
40% OLS 0.1439 0.0147 0.0493 0.0665 0.1007 2.5021
Huber 0.0960 0.0134 0.0330 0.0446 0.0673 1.9988
Tukey 0.0821 0.0136 0.0305 0.0401 0.0602 1.6771
LOWESS 0.1562 0.0187 0.0832 0.1121 0.1418 3.0480
*70% OLS 0.1530 0.0138 0.0554 0.1146 0.1882 1.2717
Huber 0.1040 0.0121 0.0366 0.0791 0.1267 0.9153
Tukey 0.0901 0.0115 0.0337 0.0700 0.1098 0.7778
LOWESS 0.4082 0.0350 0.1651 0.3563 0.6331 1.0816
DEG: differentially expressed genes. *: all DEG are up-regulated. OLS: the TW-SLM using the ordinary least squares.
Huber: the robust TW-SLM using Huber's weight function. Tukey: the robust TW-SLM using Tukey's weight function.
Table 4 Bias of estimated gene expression levels (up:down = 9:1) for simulated cDNA microarray data with the R-I plots similar to Figure 3.
Percentage of DEG Descriptive Statistics
Method Mean Minimum 25% Quantile Median 75% Quantile Maximum
1% OLS 0.0000 -0.8219 -0.0173 -0.0043 0.0094 1.4229
Huber 0.0000 -0.6011 -0.0146 -0.0034 0.0080 1.2449
Tukey 0.0000 -0.4942 -0.0137 -0.0031 0.0079 1.1431
LOWESS 0.0017 -0.8382 -0.0155 -0.0018 0.0116 1.4261
5% OLS 0.0000 -1.1839 -0.0307 -0.0151 0.0009 1.1853
Huber 0.0000 -1.0325 -0.0258 -0.0118 0.0016 0.9497
Tukey 0.0000 -0.9366 -0.0240 -0.0107 0.0024 0.8284
LOWESS 0.0028 -1.1707 -0.0257 -0.0123 0.0015 1.1979
10% OLS 0.0000 -1.2366 -0.0567 -0.0351 -0.0108 1.2074
Huber 0.0000 -1.0440 -0.0477 -0.0297 -0.0078 1.0073
Tukey 0.0000 -0.9654 -0.0444 -0.0270 -0.0056 0.9112
LOWESS 0.0034 -1.2259 -0.0467 -0.0310 -0.0151 1.2333
20% OLS 0.0000 -1.2168 -0.0922 -0.0677 -0.0368 1.3011
Huber 0.0000 -0.9445 -0.0771 -0.0568 -0.0286 1.0866
Tukey 0.0000 -0.8220 -0.0707 -0.0510 -0.0241 0.9765
LOWESS -0.0089 -1.2455 -0.0953 -0.0765 -0.0537 1.3045
40% OLS 0.0000 -1.5360 -0.1722 -0.1230 0.1383 1.3821
Huber 0.0000 -1.3680 -0.1451 -0.1030 0.1192 1.1008
Tukey 0.0000 -1.2384 -0.1328 -0.0934 0.1114 0.9741
LOWESS -0.1418 -1.7047 -0.2937 -0.2553 -0.0205 1.2253
*70% OLS 0.0000 -0.5137 -0.2925 -0.0519 0.2306 1.0736
Huber 0.0000 -0.4227 -0.2466 -0.0429 0.1947 0.9327
Tukey 0.0000 -0.3924 -0.2259 -0.0390 0.1802 0.8543
LOWESS -0.5203 -1.0007 -0.7719 -0.5651 -0.3230 0.5017
DEG: differentially expressed genes. *: all DEG are up-regulated. OLS: the TW-SLM using the ordinary least squares.
Huber: the robust TW-SLM using Huber's weight function. Tukey: the robust TW-SLM using Tukey's weight function.
Table 5 Consistency analysis with and without background adjustment under slide-wised and block-wised normalization strategies (the cutoff p-value is 10-5)
Normalization Strategy Normalization Method Direct comparison Indirect comparison Common genes1
With background subtraction
Slide-wised LOWESS 1447(32.27)a(78.85)b 1045(44.69) (70.62) 467
TW-SLM 2907(58.93)(39.25) 2791(61.38)(26.44) 1713
Common2 1141 738 -
Block-wised LOWESS 1551(37.91)(76.47) 1464(40.16)(59.84) 588
TW-SLM 2545(48.84) (46.60) 2267(54.83) (38.64) 1243
Common2 1186 876 -
Without background subtraction
Slide-wised LOWESS 1240(37.98) (86.05) 1599(29.46) (77.42) 471
TW-SLM 1924(72.77)(55.46) 3237(43.25)(38.25) 1400
Common2 1067 1238 -
Block-wised LOWESS 1357(46.13)(82.68) 2099(29.82) (69.46) 626
TW-SLM 1904(59.51)(58.93) 2872(39.45) (50.77) 1133
Common2 1122 1458 -
Common1: intersection between the direct and the indirect comparison given the same method.
Common2: intersection between the LOWESS and the TW-SLM given the same comparison.
a: consistency between the comparisons expressed as the percentage. .
b: the percentage of Common2 for each method. .
Table 6 Consistency analysis with and without background adjustment under slide-wised and block-wised normalization strategies (the cutoff p-value is 10-3)
Normalization Strategy Normalization Method Direct comparison Indirect comparison Common genes1
With background subtraction
Slide-wised LOWESS 2563(44.52)a(79.05)b 2234(51.07)(73.23) 1141
TW-SLM 4330(68.45) (46.79) 4055(73.09) (40.35) 2964
Common2 2026 1636 -
Block-wised LOWESS 2731(49.40)(78.58) 2700(49.96) (66.74) 1349
TW-SLM 4085(61.32)(52.53) 3645(68.72) (49.44) 2505
Common2 2146 1802 -
Without background subtraction
Slide-wised LOWESS 2440(52.50) (82.99) 3024(42.36) (79.27) 1281
TW-SLM 3615(77.01)(56.02) 4400(63.27) (54.48) 2784
Common2 2025 2397 -
Block-wised LOWESS 2694(57.24) (79.62) 3495(44.12)(74.91) 1542
TW-SLM 3530(67.39) (60.76) 4190(56.79)(62.48) 2379
Common2 2145 2618 -
Common1: intersection between the direct and the indirect comparison given the same method.
Common2: intersection between the LOWESS and the TW-SLM given the same comparison.
a: consistency between the comparisons expressed as the percentage. .
b: the percentage of Common2 for each method. .
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Kepler TB Crosby L Morgan KT Normalization and analysis of DNA microarray data by self-consistency and local regression Genome Biol 2002 3 1 12 10.1186/gb-2002-3-7-research0037
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| 15663789 | PMC549200 | CC BY | 2021-01-04 16:02:49 | no | BMC Bioinformatics. 2005 Jan 21; 6:14 | utf-8 | BMC Bioinformatics | 2,005 | 10.1186/1471-2105-6-14 | oa_comm |
==== Front
BMC BioinformaticsBMC Bioinformatics1471-2105BioMed Central London 1471-2105-6-201568659310.1186/1471-2105-6-20SoftwareGeneNotes – A novel information management software for biologists Hong Pengyu [email protected] Wing H [email protected] BioX program, Department of Statistics and HRP, Stanford University, Stanford, CA 94305-4065, USA2 BioX program, Department of Statistics and HRP, Stanford University, Stanford, CA 94305-4065, USA2005 1 2 2005 6 20 20 10 11 2004 1 2 2005 Copyright © 2005 Hong and Wong; 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
Collecting and managing information is a challenging task in a genome-wide profiling research project. Most databases and online computational tools require a direct human involvement. Information and computational results are presented in various multimedia formats (e.g., text, image, PDF, word files, etc.), many of which cannot be automatically processed by computers in biologically meaningful ways. In addition, the quality of computational results is far from perfect and requires nontrivial manual examination. The timely selection, integration and interpretation of heterogeneous biological information still heavily rely on the sensibility of biologists. Biologists often feel overwhelmed by the huge amount of and the great diversity of distributed heterogeneous biological information.
Description
We developed an information management application called GeneNotes. GeneNotes is the first application that allows users to collect and manage multimedia biological information about genes/ESTs. GeneNotes provides an integrated environment for users to surf the Internet, collect notes for genes/ESTs, and retrieve notes. GeneNotes is supported by a server that integrates gene annotations from many major databases (e.g., HGNC, MGI, etc.). GeneNotes uses the integrated gene annotations to (a) identify genes given various types of gene IDs (e.g., RefSeq ID, GenBank ID, etc.), and (b) provide quick views of genes. GeneNotes is free for academic usage. The program and the tutorials are available at: .
Conclusions
GeneNotes provides a novel human-computer interface to assist researchers to collect and manage biological information. It also provides a platform for studying how users behave when they manipulate biological information. The results of such study can lead to innovation of more intelligent human-computer interfaces that greatly shorten the cycle of biology research.
==== Body
Background
In a genome-wide profiling project, researchers usually select many sets of genes (or ESTs) for further investigation based on the computational analyses of the experimental data. For example, a set of genes is selected because they are clustered together based on their mRNA levels. To generate or support biologically meaningful hypotheses, researchers need to selectively and systematically collect information about the genes/ESTs from various sources. For example, huge amount of gene annotations have been accumulated over decades in distributed databases. In addition, there are plenty of online computational tools (e.g., BLAST [1], TMHMM [2], MEME [3], etc.) that can be customized to generate invaluable information complementary to the local computational analyses of researchers. Most databases and online computational tools require a direct human involvement. Sometimes, it is extremely difficult, if not impossible, to perform further computational analyses on the collected information. For example, a cellular image often contains large amount of important information that can be easily understood by human but is beyond the capability of existing computational tools. Therefore, the timely integration and interpretation of the collected information still relies heavily on the sensibility of biologists. However, it is a challenging task to effectively collect and manage various types of information of interest. Researchers often feel overwhelmed by not only vast amount of information but also the great diversity of information types. To facilitate this task, we developed GeneNotes that provides an integrated environment for surfing the Internet, recording information, annotating genes, and retrieving information in the form of text, HTML, image, PDF, word file, and so on.
Implementation
Architecture
We maintain a server (Figure 1) that integrates gene annotations from many major databases (e.g., HGNC [4], MGI [5], RGD [6], FlyBase [7], WormBase [8], PlasmoDB [9], SGD [10], KEGG pathway DB [11], etc.). The integrated gene annotations are stored as XML files, which are updated every two weeks. GeneNotes runs locally on users' computers and uses the integrated gene annotations to identify genes given various types of IDs (e.g., RefSeq ID, GenBank ID, UniGene ID, LocusLink ID, etc.). There is one menu in GeneNotes that allows the user to update the annotation files from the server. Once a gene is identified, GeneNotes can visualize Gene Ontology annotation of the gene, list its other annotations (e.g., name/symbol/synonyms/products, RefSeq ID, GenBank ID, UniGene ID, LocusLink ID, Model Organism database ID, protein information, etc.), and generate hyperlinks to major databases (e.g., Swiss-Prot [12], UCSC Genome DB [13], KEGG pathway DB [11], etc.) for the user to jump around those databases easily. GeneNotes also supports Affymetrix probe sets given the corresponding GeneChip® annotation files, which can be downloaded from the web site of Affymetrix.
GeneNotes manages information by projects (Figure 2). Each project contains a note database and several lists of genes/ESTs. The gene/EST lists are selected by users and can be edited anytime via the GUI of GeneNotes. Each gene/EST can have many notes that contain multimedia information. For example, a note could be a segment of text, an image, a PDF file, a word file, a local copy of a web page, and so on.
Create, collect, and manage notes
GeneNotes offers many useful functions. The most attractive feature to biologists is the function for creating, collecting, and managing notes for genes/ESTs. Basically, there are three ways for creating/collecting notes. First, GeneNotes has an embedded Web browser, which allows the user to surf the Internet. The user can selectively record useful information segments shown in the Web browser or save a web page as a note. Saving a web page as a note is especially useful when the web page contains the non-text results (e.g., images, logos, etc.) generated by a remote computational server. GeneNotes automatically stores the sources of notes and allows users to trace back to the sources of notes later. Second, users can create text notes to summarize their thoughts/comments about genes/ESTs. Finally, users can create notes linked to local files (e.g., images, PDF files, word files, etc.). The user can directly modify a text note and add annotations to non-text notes. Each note has an editable title. A meaningful title helps the user recall what information the note contains. When the number of notes is large, it may become difficult for users to browse and locate notes. GeneNotes allows users to organize notes into directories, which can be defined by categories.
Note database
Currently, GeneNotes runs on Microsoft Windows 2000/XP and uses Microsoft Data Access Components (MDAC) 2.7 to manipulate the note database. MDAC 2.7 provides the same Data Access core components as Windows XP SP1. Windows 2000 users need to download and install MDAC 2.7 or the latest version of MDAC, which are free at the web site of Microsoft. We are considering developing a platform independent version of GeneNotes and using other free database software such as MySQL [14].
GUI
The GUI of GeneNotes is flexible and user friendly. It contains the following main windows: project explorer, gene list window, note window, gene property window, Gene Ontology visualization window, and web browser window. The project explorer displays the content of a project, e.g., gene lists, the note database file, Affymetrix GeneChip® annotation files, etc. It allows users to edit the project, e.g., add/delete gene lists, create/change the note database, add/delete Affymetrix GeneChip® annotation files, etc. The user can select a gene list in the project explorer. The selected gene list will be displayed in the gene list window. When a gene is selected in the gene list window, its properties (e.g., name/symbol/synonyms, RefSeq IDs, GenBank IDs, UniGene ID, etc.) will be displayed in the gene property window and its Gene Ontology annotation will be visualized in the Gene Ontology visualization window. The gene property window also displays a set of hyperlinks that are linked to the records of the selected gene in remote biological databases (e.g., HGNC [4], MGI [5], RGD [6], FlyBase [7], WormBase [8], PlasmoDB [9], SGD [10], Swiss-Prot [12], UCSC Genome DB [13], KEGG pathway DB [11], etc.). Once a hyperlink is clicked, GeneNotes will display the corresponding URL in the web browser window. The web browser window allows user to surf the Internet freely.
All windows are dockable. Users can configure of the interface by dragging and dropping the window to virtually wherever they want. If a window is set as auto-hide, it will hide itself when it is inactive so that the computer screen can be used to display other windows.
Discussion and conclusions
GeneNotes provides a novel human-computer interface for researchers to effectively and efficiently manage multimedia biological knowledge. There are many online databases (e.g., Entrez Gene [15], GeneCards [16], etc.) providing pre-compiled information about genes/ESTs. GeneNotes has different purposes. It gives users freedom to selectively collect information and create their own databases to store heterogeneous biological information. At the same time, GeneNotes allows users to make full usage of those online databases. GeneNotes stores notes locally so that the notes are accessible when computers are offline. GeneNotes organizes information in the order of project, gene/EST list, and notes. This not only makes it easier for researchers to switch from one gene/EST to another one but also helps researchers obtain global view about the ongoing status of the project. We are currently pursuing the direction to innovate more intelligent human-computer interface to help biologists collect and manage information by observing how biologists using GeneNotes.
Availability and requirements
Project name: GeneNotes
Project home page: .
Operating system(s): Windows 2000/XP
Programming language: C#
License: Free for non-commercial usage.
Authors' contributions
PH was responsible for the conception, design, implementation, and testing of the GeneNotes program. WHW was responsible for its conception, design, and testing and provided overall project coordination. Both authors have read and approved the final manuscript.
Acknowledgements
The work of Pengyu Hong is supported by NIHGM67250. The work of Wing H. Wong is supported by NIH-HG02341. We acknowledge Dr. Storch and members of the Perrimon Lab and the McMahon Lab for testing GeneNotes and many helpful suggestions.
Figures and Tables
Figure 1 The server integrates gene annotations from many major biological databases.
Figure 2 GeneNotes organizes information by projects.
==== Refs
BLAST
TMHMM server for predicting Transmembrane helices in proteins
MEME
HUGO Gene Nomenclature committee
Mouse Genome Informatics
Rat Genome Database
FlyBase
WormBase
The Plasmodium Genome Resource
Saccharomyces Genome Database
Kyoto Encyclopedia of Genes and Genomes
Swiss-Prot Protein Knowledgebase
UCSC Genome Bioinformatics
MySQL
Entrez Gene
GeneCards
| 15686593 | PMC549201 | CC BY | 2021-01-04 16:02:51 | no | BMC Bioinformatics. 2005 Feb 1; 6:20 | utf-8 | BMC Bioinformatics | 2,005 | 10.1186/1471-2105-6-20 | oa_comm |
==== Front
BMC BioinformaticsBMC Bioinformatics1471-2105BioMed Central London 1471-2105-6-191567607010.1186/1471-2105-6-19Methodology ArticleGraph-representation of oxidative folding pathways Ágoston Vilmos [email protected] Masa [email protected]án László [email protected] Sándor [email protected] Bioinformatics Group, Biological Research Center, Hungarian Academy of Sciences, Temesvári krt. 62, 6726 Szeged, Hungary2 Protein Structure and Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, Area Science Park, 34012 Trieste, Italy3 Institute for Molecular Bioscience, University of Queensland, St. Lucia 4072, QLD, Australia2005 27 1 2005 6 19 19 20 10 2004 27 1 2005 Copyright © 2005 Ágoston 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 process of oxidative folding combines the formation of native disulfide bond with conformational folding resulting in the native three-dimensional fold. Oxidative folding pathways can be described in terms of disulfide intermediate species (DIS) which can also be isolated and characterized. Each DIS corresponds to a family of folding states (conformations) that the given DIS can adopt in three dimensions.
Results
The oxidative folding space can be represented as a network of DIS states interconnected by disulfide interchange reactions that can either create/abolish or rearrange disulfide bridges. We propose a simple 3D representation wherein the states having the same number of disulfide bridges are placed on separate planes. In this representation, the shuffling transitions are within the planes, and the redox edges connect adjacent planes. In a number of experimentally studied cases (bovine pancreatic trypsin inhibitor, insulin-like growth factor and epidermal growth factor), the observed intermediates appear as part of contiguous oxidative folding pathways.
Conclusions
Such networks can be used to visualize folding pathways in terms of the experimentally observed intermediates. A simple visualization template written for the Tulip package can be obtained from V.A.
==== Body
Background
The process of protein folding whereby a linear polypeptide chain reaches its native structure has been one of the most intensely studied biomolecular problems over the past 50 years (for current reviews see [1-3]). Folding of a protein is usually pictured as a search for the native conformation within the conformational space of all possible conformational states, each characterized by a set of parameters. Even though most of the conformational states are not accessible to experiment, graphic representations of the potential energy surface have played pivotal roles in explaining how the conformational space is gradually restricted during the process folding [4]. Key concepts such as folding pathways [5] are also best explained by graphic representations.
The particular kind of folding that this article is concerned with is oxidative folding, which is the fusion of native disulfide bond formation with conformational folding [6-8]. This complex process is guided by two types of interactions: first, non-covalent interactions giving rise to secondary and tertiary structure, and second, covalent interactions between cysteine residues, which ultimately transform into native disulfide bridges. The process of disulfide formation is a simple chemical reaction in which two SH groups join to form a disulfide link (Figure 1A). If the SH groups are on a polypeptide chain, the in vitro reaction can be promoted by an external redox system such as a mixture of oxidized and reduced glutathione, or cysteine and cystine, respectively. In vivo, the oxidative power comes from specific agents such as the molecular chaperones protein disulfide isomerases[9].
The underlying chemical mechanism is disulfide interchange (Figure 1B). In this scheme there are two kinds of reactions: i) in a redox reaction a protein disulfide bond is created (or abolished), i.e. the oxidative state of the polypeptide is changed. This is the case when one of the participants of the reaction (say RSH) is not part of the protein. ii) In a shuffling reaction both participants of the reaction are protein-bound, so the oxidative state of the polypeptide does not change. In view of these possibilities it becomes obvious that there are a great many ways in which disulfide bridges can form and rearrange during the folding process. Today it is generally accepted that non-covalent interactions guide the process of folding and formation of disulfide bridges will lock the protein into the right conformation. The advantage of oxidative folding as opposed to general protein folding is that disulfide intermediates can be chemically isolated and studied using such techniques as acid trapping of the intermediates and analysis of the disulfide bridges using a combination of enzymatic cleavage and mass spectrometry. There is a body of literature in describing the pathways of oxidative folding in terms of disulfide intermediates [6-8], and our goal is show how graph theory can be used to visualize them.
Graph theory has been applied to many aspects of protein research (for a recent review see [10]). The applications followed two broad avenues:
i) First, protein structure itself can be considered as a graph consisting of various interactions (such as covalent bonds, hydrogen bonds, spatial vicinities, contacts etc.) as edges, the nodes being atoms or residues of the protein. For instance, one of the classical definitions of protein secondary structures is based on main/chain H-bond contacts between residues [11]. Structural neworks have been used in folding research as well. It was found, among others, that the so-called contact order, i.e. the average sequence distance between residues in atomic contact, seems to be a key determinant of folding speed [12]. Another line of research concentrates on characteristic networks of inter-atomic contacts that may form stabilization centres in protein structures and can be the reason of the differential stability of various proteins [13,14]. It was found that populated conformations seen in molecular dynamics simulations contain characteristic networks of residues [15,16].
ii) In the network descriptions of the folding space, on the other hand, the folding states are the nodes, and transitions are the edges between them. This approach was fostered by the finding that the robustness and stability of networks may be the result of simple topological properties that are invariant throughout various technical as well as biological systems [17]. In the following years the network topology of a large number of systems have been described, and it was found that some topology classes, such as those characterized by a scale-free distribution of the number of links at each node, or the so called "small world models" that are characterized by densely connected subnetworks loosely linked between each other, are indeed found in various systems within and without biology (for reviews see [18]). The various network types were described in terms of simple measures borrowed from graph theory, such as the clustering coefficient, the diameter of the graph etc [19]. Scala and associates described the folding states of short peptides using Monte Carlo simulation on lattice models [20]. They found that that the geometric properties of this network are similar to those of small-world networks, i.e. the diameter of the conformation space increases for large networks as the logarithm of the number of conformations, while locally the network appears to have low dimensionality. Shakhnovich and co-workers analysed the folding states of proteins during molecular dynamics simulations. It was found that the folding space is reminiscent of scale-free network, characterized by a majority of less populated states as well as some highly populated states reminiscent of "hubs" seen in other systems [21].
Our purpose is to describe the folding space of the oxidative folding process using graph representations. This is an intriguing task since, in contrast to "ordinary" protein folding, the number of states defined in terms of disulfide links is not exceedingly high, moreover the actual disulfide intermediates can be isolated and studied. We will approach the problem in two steps as: i) We will use graph theory to describe the disulfide intermediates, and to enumerate the states of the folding space. ii) Then we will represent the folding space as a network (graph) of all possible intermediates. We show with few examples that experimentally observed intermediates mapped onto this network appear as contiguous folding pathways.
Results and discussion
Graph representation of oxidative folding intermediates
The disulfide topology of a protein is unequivocally defined by describing which cysteines are connected to each other. For example, a topology "1–3, 2–4" means that a protein with four cysteines has two disulfide bridges that connect cysteines (1,3) and cysteines (2,4) respectively. Cysteines can be labelled by their sequence position, or – as in the previous example – in a serial order from the N-terminus (Figure 2).
The number of fully oxidised (disulfide bonded) isomers in a protein chain with n disulfide bonds (2n cysteines) can be deduced from simple combinatorial considerations as (2n)!/(n!*2n). According to this formula proteins with two disulfide bridges have 3 fully oxidized isomers, 3-disulfide proteins have 15 and 4-disulfide proteins have 105. In other words, the number of intermediates increases very fast as a function of the number of constituent cysteines.
For a complete description of the folding process we have to consider both fully oxidized intermediates as well as the ones with free cysteine residues. For this purpose we will use a formal description of the intermediates as undirected graphs, with cysteines as nodes and disulfide bridges as edges (the main chain will not be represented). For the majority of naturally occurring protein structures the resulting graphs will be extremely simple. If the protein has n cysteines, the n × n adjacency matrix of the graph is symmetrical; it will contain a value of 1 if two cysteines form a disulfide bond and zero otherwise. As one cysteine can form only one disufide bridge, each column and each row will have at most one value of 1. Examples are shown in Figure 3.
Description of the oxidative folding space as graphs
The transitions between folding intermediates can be conveniently described by comparing the adjacency matrices of the two states. For the enumeration of the transition reactions we introduce a few simple variables. NB is the number of disulfide bonds, calculated as the sum of the elements of the adjacency matrix.
The sum of elements in the i-th column plus the i-th row,
is 1 if the i-th cysteine is part of a disulfide bridge and zero otherwise. The sum of the differences calculated between the Si measures of two adjacency matrices,
shows how many cysteines gain or loose a bond as the molecule passes from one state to the other. Here we are interested only in the two kinds of elementary reactions depicted in Figure 1B. In shuffling reactions, the number of disulfide bridges NB remains the same by definition, and it is easy to show that SD will differ exactly by 2. In redox steps in which one disulfide bridge is established or lost, NB and SD will increase or decrease by one and two, respectively.
On the above basis one can easily draw a network of all possible oxidative folding pathways. For a protein of n cysteines, we first generate the graphs (adjacency matrices) of all possible intermediates, i.e. those with 0,1...(i ≤ n/2) disulfide bridges. Then we compare all pairs of intermediates in terms of the above parameters. A shuffling edge will be drawn between two intermediate states if |SD| = 2 and ΔNB = 0; redox edges will be drawn if |SD| = 2 and ΔNB = 1. If the values of |SD| and ΔNB are different from these two combinations, no edge will be drawn.
The graph characteristics of a few systems are summarized in Table 1. The results show that as the number of cysteines increases, the clustering coefficient of the system decreases. While the average path length increases. Both findings are consistent with the intuitive view that the folding space of peptides with many cysteines may be too complex and thus the systems may be unable to fold fast enough.
The pathways can also be graphically represented, and in order to simplify the resulting picture, we chose a 3D representation wherein the states (species) are grouped according to the number of disulfide bridges (Figure 4). Species with the same number of disulfide bridges are placed on the same plane, so shuffling reactions, which do not change the number of disulfide bridges are represented as edges within the same plane. It is noted that on each of the separate planes we find a regular graph. This is not surprising: exhaustive enumeration of theoretical states, such as Eigen's quasi-species [22], can produce highly connected regular graphs. On the contrary, reactions in which a disulfide bridge is gained or lost, are represented as edges between two neighbouring planes. The fully reduced state (zero disulfide bridges) is on top, the fully oxidized species, one of which is the native state, is on the bottom.
Panel B shows a peptide with an odd number cysteines, such as granulocyte-colony stimulating-factor [23,24] in which the native state contains one free cysteine residue. In this case there are shuffling edges even in the lowest plane in the figure, so the native state (one of the states in the lowest plane) can be subject to shuffling transitions. On the contrary, if the number of cysteines is an even number (i.e. in the majority of known proteins), the fully oxidized DISs can not interconvert into each other in one step. In some cases however an additional cysteine is in fact used to facilitate the process of oxidative folding: the propeptide of BPTI contains an additional free cysteine that seems to significantly speed up the in vitro folding of the molecule [25]. In vivo, the propeptide is subsequently cleaved, and in this way the structure is locked into the native disulfide configuration.
In principle, the oxidative folding pathways can be pictured as routes within the full network, starting at the fully reduced species and ending at the native state. In the literature there are a few well-studied examples in which folding intermediates have been determined. The experimentally observed disulfide intermediates of three examples, bovine pancreatic trypsin inhibitor, insulin-like growth factor and epidermal growth factor, are shown in Table 2 and Figure 5, respectively. It is noted that experimental methods do not necessarily reveal all possible intermediates; some of the intermediates may be too short-lived or not abundant enough so as to be noticed an isolated. In spite of these limitations, the folding pathways appear as connected subgraphs within the network of all possible intermediates, showing that the experimental techniques actually identified states that can interconvert into one another. Only in EGF do we see an "isolated" intermediate, which suggests that some intermediates of the pathway were not observed experimentally.
Conclusions
The oxidative folding space of polypeptides can be represented as networks in which the nodes are the disulfide intermediates while the edges are transitions between them. A simple visualization tool written was developed to draw 3D pictures of such networks in which the states having the same number of disulfide bridges are placed on separate planes. These pictures provide a simple method for the visualization of oxidative folding pathways as studied by experimental methods. In the case of bovine pancreatic trypsin inhibitor, insulin-like growth factor and epidermal growth factor, the folding pathways appear as a small network of contiguous routes that connect the fully reduced state to the native state. A further plausible extension of this method would include colouring of the folding states by quantitative properties and look for correlations between the coloured areas of the network and the experimentally determined folding pathways.
Even though the topology of the theoretically complete folding space appears to be highly regular, data currently available are insufficient to draw general conclusions on the topology of the experimentally observed folding pathways. Experimentalists find folding intermediates as a series of chromatographic peaks, and usually the disulfide bridges of more abundant species are analysed first. The question whether or not all the relevant intermediates have been analyzed is difficult to answer, and mapping the intermediates onto the graphs presented here may help one to decide whether or not the pathways found are contiguous.
Authors' contributions
V.A. designed and implemented the algorithms and carried out the calculations. M.C. helped to compile the experimental data and to draft the manuscript. L.K. designed the representation of folding intermediates. The project was coordinated by S.P.
Acknowledgements
The authors are grateful for the comments of Drs. István Simon (Institute of Enzymology, Hungarian Academy of Sciences, Budapest) and Alessandro Pintar (ICGEB, Trieste). The work was supported by the Hungarian Office of Research and Development (OMFB-01887/2002, OMFB-00299/2002). S. P. is recipient of the Szent-Györgyi Award for teaching at the Department of Genetics and Molecular Biology, University of Szeged.
Figures and Tables
Figure 1 A. Thiol-disulfide exchange mechanism: in the pH range above 8, cysteine thiols are readily converted to thiolate anions (RS-), which are potent nucleophiles. RS- anions attack a disulfide bond, displacing one sulfur atom and forming a new bond with the other sulfur atom (nucleophilic substitution). The rate-determining step of this concerted process is the formation of a transition state with a partial transfer of the negative charge (δ-) over the three sulfur atoms. B. The formation of a disulfide bond on the polypeptide chain (solid curve) with the help of a small molecule reagent (thiol form: RSH, disulfide form: RSSR). The two steps both proceed via a thiol-disulfide exchange reaction. The first step shown is intermolecular and the second intramolecular. The rate of the intramolecular step is relevant to protein folding, since it also involves conformational changes.
Figure 2 Nomenclature for disulfide topologies. Disulfides can be labeled by the sequence positions, or simply by the sequential number of the cysteine residues they connect (1–3, 2–4 topology). Alternatively, it is customary to alphabetically label the disulfide bridges, and and to assign bridge label to the cysteines, starting from the N terminus (abab topology).
Figure 3 Adjacency matrices of two disulfide topologies of a peptide with two disulfide bridges
Figure 4 Three dimensional representation of the oxidative folding space of polypeptides with 4, 5 and 6 cysteine residues (A, B and C, respectively). The nodes represent intermediates, the number of disulfide bridges is indicated with numbers on the left of each panel. The edges indicate disulfide exchange transitions. Zero indicates the fully reduced state, nodes in the lowest plane are the fully oxidized intermediates, one of which is usually the native state. Edges within the same plane indicate shuffling reactions (interchange between two protein-bound disulfides), edges between planes are redox transitions in which a disulfide bridge is created or abolished. A simple visualization tool written for the Tulip package can be obtained from V.A. [email protected]
Figure 5 The oxidative folding pathways of bovine pancreatic trypsin inhibitor (BPTI), insulin-like growth factor (IGF) and epidermal growth factor (EGF). The disulfide connectivity of the intermediates is sumarized in Table 2. Asterisk denotes the native state.
Table 1 Parameters of oxidative folding networks*
N of cysteines N of intermediates (nodes) Redox transitions Shuffling transitions Total no of transitions (edges) Clustering coefficient C Average path length
1 1 0 0 0 1.000 0.000
2 2 1 0 1 1.000 1.000
3 4 3 3 6 1.000 1.000
4 10 12 12 24 0.400 1.467
5 26 40 60 100 0.410 1.810
6 76 150 240 390 0.247 2.293
7 232 546 1050 1596 0.253 2.640
8 764 2128 8736 10864 0.181 3.149
9 2620 8352 19152 27504 0.182 3.550
10 9496 34380 83520 117900 0.142 3.977
*Oxidative folding networks represent the entire folding space that comprise all possible intermediates. Folding pathways, on the other hand, include only the experimentally observed intermediates.
Table 2 Disulfied intermediates experimentally observed in the oxidative folding of various proteins
Protein Disulfide intermediates1 Ref.
Bovine pancreatic trypsin inhibitor (BPTI) 3–5; 1–6; 3–5, 1–2;
3–5, 1–4; 3–5, 2–4;
1–6, 2–4; 3–5, 1–6;
1–6, 3–5, 2–4; [26, 27]
Insulin-like growth factor (IGF) 2–6; 2–6, 3–5; 2–6, 1–4;
2–6, 4–5; 2–6, 1–3;
2–6, 1–3, 4–5; 1–4, 2–6, 3–5; [28-30]
Epidermal growth factor (EGF) 2–3; 1–2; 4–6; 5–6;
3–4; 2–4, 5–6; 2–5, 3–4;
1–6, 2–5, 3–4; 1–2, 3–4, 5–6;
1–3, 2–4, 5–6; [31]
1The intermediates are described with the notation given in Figure 2. The native disulfide connectivity is in bold, the fully reduced species is not included.
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| 15676070 | PMC549202 | CC BY | 2021-01-04 16:02:51 | no | BMC Bioinformatics. 2005 Jan 27; 6:19 | utf-8 | BMC Bioinformatics | 2,005 | 10.1186/1471-2105-6-19 | oa_comm |
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BMC BioinformaticsBMC Bioinformatics1471-2105BioMed Central London 1471-2105-6-171567346810.1186/1471-2105-6-17Research ArticleEvaluating concentration estimation errors in ELISA microarray experiments Daly Don Simone [email protected] Amanda M [email protected] Susan M [email protected] Kevin K [email protected] Richard C [email protected] Statistical and Mathematical Sciences, Pacific Northwest National Laboratory, PO Box 999, Richland, WA, USA2 Biological Sciences, Pacific Northwest National Laboratory, PO Box 999, Richland, WA, USA2005 26 1 2005 6 17 17 24 6 2004 26 1 2005 Copyright © 2005 Daly 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
Enzyme-linked immunosorbent assay (ELISA) is a standard immunoassay to estimate a protein's concentration in a sample. Deploying ELISA in a microarray format permits simultaneous estimation of the concentrations of numerous proteins in a small sample. These estimates, however, are uncertain due to processing error and biological variability. Evaluating estimation error is critical to interpreting biological significance and improving the ELISA microarray process. Estimation error evaluation must be automated to realize a reliable high-throughput ELISA microarray system.
In this paper, we present a statistical method based on propagation of error to evaluate concentration estimation errors in the ELISA microarray process. Although propagation of error is central to this method and the focus of this paper, it is most effective only when comparable data are available. Therefore, we briefly discuss the roles of experimental design, data screening, normalization, and statistical diagnostics when evaluating ELISA microarray concentration estimation errors.
Results
We use an ELISA microarray investigation of breast cancer biomarkers to illustrate the evaluation of concentration estimation errors. The illustration begins with a description of the design and resulting data, followed by a brief discussion of data screening and normalization. In our illustration, we fit a standard curve to the screened and normalized data, review the modeling diagnostics, and apply propagation of error.
We summarize the results with a simple, three-panel diagnostic visualization featuring a scatterplot of the standard data with logistic standard curve and 95% confidence intervals, an annotated histogram of sample measurements, and a plot of the 95% concentration coefficient of variation, or relative error, as a function of concentration.
Conclusions
This statistical method should be of value in the rapid evaluation and quality control of high-throughput ELISA microarray analyses. Applying propagation of error to a variety of ELISA microarray concentration estimation models is straightforward. Displaying the results in the three-panel layout succinctly summarizes both the standard and sample data while providing an informative critique of applicability of the fitted model, the uncertainty in concentration estimates, and the quality of both the experiment and the ELISA microarray process.
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Background
Proteomic approaches are resulting in the identification of large numbers of proteins that can potentially be used as disease markers or drug targets. Unfortunately, proteomic approaches currently lack the throughput or quality metrics necessary to evaluate hundreds or thousands of samples that may be required to determine clinical usefulness of a biomarker [1]. Traditionally, candidate biomarkers have been commonly evaluated using a 96-well enzyme-linked immunosorbent assay (ELISA). However, this approach is not suited for analyzing more than a few proteins when sample volumes are limited, as is commonly the case for early tumor samples. For this reason, we and others are developing ELISA microarray systems to evaluate 20 to 50 proteins using only a few microliters of sample in an efficient and quantitative manner [2,3].
Processing a ELISA microarray experiment produces large volumes of data of wide variety and high complexity. Similar to traditional 96-well ELISA data, ELISA microarray data often are perturbed by processing error [4-7]. Processing errors are introduced by unintended variation in sample preparation, slide or pin arrangement, printing, imaging, and estimation of spot summary statistics. The specific role of concentration error estimates and the general role of statistical diagnostics is to reveal process accuracy and precision. This evaluation then enables an insightful interpretation of the biological significance, an informative critique of the current experiment, and insights to improve the accuracy and precision of future experiments. In a high-throughput ELISA microarray system, there is a need to not only quickly and accurately generate the standard curves and estimate concentrations from the sample data, but also to quickly evaluate the quality of those estimates. The resulting information can be used in both the development stage for optimizing assay conditions and in the production phase for ensuring that the overall analytic process is working well on a day-to-day basis.
Statistically evaluating ELISA microarray concentration estimation errors depends upon both the availability of the appropriate set of comparable measurements and the choice of data analysis methods. Sufficient replication within and across arrays is key to making precise estimates of both concentrations and errors [8]. Hence, evaluating concentration estimation errors in an ELISA microarray experiment begins with the design of the experiment. Evaluation of these estimation errors also depends on the recording of the pedigree, or history, of each result from probe preparation and array printing through sample preparation and spot intensity estimation [9-12]. Screening for anomalous results and normalizing within and across arrays may significantly reduce obscuring variation and improve homogeneity [13-15]. Although the mathematical statistics and algorithms are quite sophisticated, software makes actual estimation and application of the standard curve and the concentration error function straightforward. This is true also for the presentation of modeling results for diagnostic purposes.
In this paper, we describe and illustrate a methodology for calculating the concentration estimation error of each assay in an ELISA microarray experiment based on a statistical analysis of the most likely sources of error. We expect the resulting data analysis algorithms to be a key component in a bioinformatics package for evaluating ELISA microarray data.
Methods
Making concentration estimates and estimating their errors in our ELISA microarray studies involve a sequence of steps beginning with the layout of the ELISA microarray and design of the experiment. Following execution of the analytical components of the experiment, the statistical analysis proceeds with data screening, normalization, and model identification. Estimation and evaluation of the standard curves and error estimation functions come next. Finally, the standard curves and error estimation functions are applied and then evaluated using a modeling diagnostic.
Layout of the ELISA microarray and design of the experiment
To estimate errors in concentration estimates, it is necessary to carefully lay out the microarray and design the experiment. Our layout features several distally separate replicates of each assay spot on each microarray to evaluate local processing effects. Our design addresses selection and application of treatments – in particular, replicate treatments – to a collection of arrays. This replication facilitates adjustments for the sources of variability that lead to ambiguous concentration estimates [16,17]. In array experiments featuring relatively small numbers of assays, usually 50 or fewer analytes, thoughtful design is critical to normalization, calibration, and estimation of concentrations due to the significant lack of technical replicates found in arrays with thousands of assays. With regard to error estimation, the major consideration in the design of the experiments is replication of treatments across arrays to capture the effects of process error.
To illustrate our technique for evaluating estimation errors in an ELISA microarray experiment, we used a subset of data from an ELISA microarray investigation of breast cancer biomarkers. The ELISA microarray experiments were performed as previously described [2,3]. Briefly, capture antibodies were covalently attached to an aminosilanated glass slide surface (Sigma, St. Louis, Missouri, USA) using a Microgrid 2 robot from Genomic Solutions (Ann Arbor, Michigan, USA) equipped with ChipMaker2 split pins from TeleChem (Sunnyvale, California, USA). As demonstrated previously, these spots are typically uniform in shape with a reasonable homogenous distribution of protein across the spot [1-3]. That is, "donut" formation is not normally observed. These spatially confined antibodies bind a specific antigen from a sample overlaying the array. A second, biotinylated antibody that recognizes the same antigen as the first antibody but at a different epitope is then used for detection. Detection of the second antibody is based upon streptavidin (which binds biotin) and an enzymatic signal enhancement method known as tyramide signal amplification (TSA). The resultant fluorescence was detected at 10-micron scan resolution using a ScanArray 3000 from General Scanning (Billerica, Massachusetts, USA). The experiment used 94 arrays printed in pairs on 47 slides. Each array contained 4 (2 × 2) replicate subarrays of 25 (5 × 5) spots. A subarray contained 21 unique assays, 1 positive control and 3 negative control spots. A set of 7 known standard concentrations and a buffer blank was assembled by performing a three-fold dilution series of a single mixture of all the standards. Each standard concentration was applied to duplicate slides. The remaining 39 slides were treated with serum samples from women with or without breast cancer. These sera were encoded to prevent knowledge of the study group during sample processing. The treated microarrays were imaged with a ScanArray microarray scanner (PerkinElmer, Boston, Massachusetts, USA). The spot fluorescence estimates were calculated with custom array-image-analysis software that was developed in-house.
Data screening, normalization and model identification
Data screening, an exploratory data analysis, serves several purposes – identifying outliers, anomalous values, and experimental design shortcomings; identifying data transforms to improve curve-fitting and application; identifying measurement trends and other processing effects; and suggesting an appropriate functional form for the standard curve [6,18-21]. This exploratory analysis combines simple summary statistics and graphical displays. For instance, graphs of control spot intensities versus processing variables such as array print order or pin number may reveal variability due to processing. These processing trends can be made more apparent with locally weighted regression, or loess, a statistical technique to fit a smooth curve through the scatterplot [22,23]. These graphs can be used as the basis for modifying the process or for data normalization.
Because our protein arrays feature fewer spots per array than do typical gene expression microarrays, a different approach to normalization, suitable for low spot-frequency arrays, is required. This normalization is critical, given that array-to-array processing error is common and that standard curves are estimated from reference spot intensities calculated from one set of arrays and then applied to sample spot intensities estimated from a separate set of arrays.
A scatterplot of intensity estimates of standard spots versus concentration is particularly useful. First, outliers and anomalies may be readily apparent. Second, the spacing between concentration values may be assessed. If standard concentrations follow from a dilution series, then the separation between concentrations decreases significantly with the decrease in concentration. This results in spot intensities measured at higher concentrations having much more leverage on the fit of the model than may be desirable. It should also be apparent whether the variability in spot intensity is increasing with mean spot intensity. Both increasing spacing in the concentrations and heteroskedasticity in the measured intensities affect the model fit and follow-on statistical inferences [24]. These may be minimized with loge transformations of both concentrations and spot intensities.
A scatterplot of raw or transformed standard spot intensity versus concentration also provides an indication of the appropriate model for the data. In particular, data following a sigmoid curve favor the logistic curves while data apparently lacking the horizontal asymptotes of a sigmoid curve favor a linear or power law model. Although several models may be fit and one selected based on a goodness-of-fit statistic (see next section), the scatterplot is a useful visual check on this selection.
Several plots provide useful information about the quality of the fitted model. Of special importance are the scatterplot of residuals versus concentration and the scatterplot of residuals versus estimated intensity. In both cases, the variability of the residuals should be centered about zero and constant across concentration or intensity. Model bias is indicated by a systematic drift of residuals to one side of the zero line. Heteroskedasticity is indicated by a systematic change in the variation of the residuals. Both may indicate that a better model is necessary before proceeding to estimation of sample concentrations and estimation of concentration errors.
Standard curves and estimation errors
An ELISA standard curve expresses protein concentration as a function of spot intensity. One standard curve is required for each assay. In an ELISA microarray experiment, the standard data are collected by fixing a set of concentrations and measuring spot intensities via imagery of the treated arrays. A standard curve is estimated by fitting an appropriate function to the set of (concentration, intensity) measurement pairs [25]. This equation is then inverted to obtain the standard curve.
Common parametric choices for standard curve models are multiparameter logistic functions and power law functions. For an ELISA microarray, a strictly monotone model is consistent with the belief that a monotone change in concentration should result in a monotone change in spot intensity.
We estimate standard curves with both logistic and power law parametric models. The four-parameter logistic model [26], expressing intensity I as a function of concentration C and parameters P1, P2, P3 and P4, is defined as
The two-parameter power law model [27] expressing intensity I as a function of concentration C and parameters P1 and P2, in loge terms, is
loge (I) = P1 + P2 loge (C) + ε
We assume the errors, denoted by the term ε, are independent and normally distributed with mean 0 and variance σ2. With either of these parametric models, concentration estimation errors may be estimated using propagation of error, also known as the delta method.
To choose between competing candidate models, a number of measures exist for evaluating model fit when replicate observations of each assay are available. These include partitioning the mean squared error, or MSE, into components representing pure error and lack of fit [28], and penalized measures such as Akaike (AIC) and Bayesian (BIC) information criteria [29]. We also examine the PRESS statistic, a direct measure of the predictive capability of each candidate model [30].
To calculate the PRESS statistic for each candidate model, suppose we exclude each poin (xj, yj) in turn and fit the model to the remaining points. We predict the value at the excluded point xj and calculate the PRESS residual defined by ej, - j = yj - . Then, the PRESS statistic is the sum of the squared PRESS residuals
The candidate model with the lowest PRESS score as the best predictive model to estimate concentrations.
The basic approach to estimating concentration errors with the propagation of error method has three steps [31]. First, fit intensity as a function of concentration and estimate the covariance among model parameter estimates. Next, solve the fitted function for concentration as a function of intensity. Finally, propagate error estimates from the fitted model through the inverted model and combine with the error estimate of the sampled spot intensity to estimate the concentration estimation error.
Let C(I|), with , denote the inverted N parameter model expressing concentration C as a function of intensity I and the parameter estimates Suppose is the NxN parameter covariance matrix estimated by fitting I as a function of C, say I(C|P). Now, let Cs be the estimated concentration from the sample intensity estimate IS, say CS = C(IS/P) and be the corresponding estimated standard error of IS. Then, the propagation of error estimate for the concentration estimate CS is the square root of the product of , the sample covariance matrix augmented with , and the Jacobian matrix J evaluated at IS and the parameter estimates . In this application, the Jacobian is the matrix of partial derivatives of C(I|P) with respect to the intensity I and the parameters P. Hence, the concentration estimation error of C(I|P) is the square root of the concentration estimation variance V(C(I|P))
V(C(I|P)) = J(C(I|P))T ΣJ(C(I|P))
where the Jacobian is
J(C(I|P))T = [∂C/∂I, ∂C/∂P1,..., ∂C/∂PN]
and the augmented covariance matrix is
Hence, the formula for estimated standard error of CS is
For a given intensity estimate IS and standard error , the estimated concentration and approximate 95% confidence interval (C95%L, C95%U) are
CS = C(IS)
C95%L = CS - 2SE[CS] (2)
and
C95%U = CS + 2SE[CS] (3)
For example, consider the four parameter logistic model, Eqn. 1. The concentration estimation equation is obtained by solving this equation for C in terms of I and the four parameters
The Jacobian matrix is obtained by taking the partial derivatives of the inverted four-parameter logistic function of C (Eqn. 4) with respect to I and the parameters P1, P2, P3 and P4
Diagnostic visualizations
A three-panel display combining a histogram of normalized sample spot intensities for a given antigen, its corresponding standard curve, and the graph of the concentration coefficient of variation, or relative error, versus concentration provides pertinent information about the conduct of the current experiment as well as information to improve future experiments. The standard curve panel presents a scatterplot of normalized standard spot intensities versus standard concentrations. The scatterplot is overlain with the estimated standard curve expressing concentration as a function of spot intensity. This panel also includes approximate 95% confidence intervals. These intervals summarize the uncertainty in concentration estimates due to both the uncertainty in estimating the standard curve and the uncertainty in the sample spot intensity estimate. Finally, a highlighted region helps distinguish concentration estimates s with acceptable errors from concentration estimates with possibly less than acceptable errors.
The segment of the standard curve corresponding to acceptable concentration errors may be determined using the 95% confidence intervals. The lower and upper endpoints of this segment, (IL, CL) and (IU, CU), are the two points such that the confidence intervals begin to increase significantly in length. This segment generally corresponds to the linear segment of a standard curve. We identify the intensity IL of the lower pair as the smallest intensity such that 95% UB(IL) is less than 95% UB(I) for intensity values I less than IL. Similarly, we identify IU as the largest intensity such that 95% LB(IU) is greater than 95% LB(I) for intensity values I greater than IU. We define CL and CU to be CL = C(IL) and CU = C(IU), respectively. We believe that this is a conservative approach to identifying intensities that generate concentration estimates with acceptable errors.
An informative visualization of acceptable concentration estimates may be generated using the points (IL, CL) and (IU, CU). Consider the union of the two rectangular regions defined by the two sets of vertices [(IL, 0), (IL, CL), (IU, CU), (IU, 0)], and [(0, CL), (0, CU), (IU, CU), (IU, CLU)]. This union defines an L-shaped region covering the standard curve segment and bound at its extremes by the intensity and concentration segments. From this visualization, one can quickly grasp the dynamic range of acceptable intensities and the potential range of acceptable concentration estimates.
In regard to this first panel, two notable aspects of this propagation of error methodology are noteworthy. First, the error bands are computed pointwise and provide reasonable error estimates for a small number of concentrations. As the number of concentration estimates grows, the impact of the multiple testing problem grows [32]. This a problem in any biomedical testing that features numerous simultaneous tests and has spawned considerable debate and research. The second aspect of note is the divergence of the error bands from the estimated standard curve as the standard curve approaches a horizontal asymptote. We see this apparent deficiency in the method as a plus. This divergence is a clear indicator that concentration estimates in the segment of a standard curve approaching a horizontal asymptote are highly suspect.
The second panel in this display shows the concentration coefficient of variation – that is, %CCV = 100 * SE(C|I)/C(I), or relative error of a concentration estimate – as a function of concentration. This provides an alternative view of the error in concentration estimation over the concentration range covered by the concentration estimation equation. A standard curve modeled with a four-parameter logistic function generally will have a bathtub shape due to the increasing uncertainty in concentration estimates at the two ends of the concentration range where the curve approaches horizontal asymptotes.
The third panel in this display features an annotated histogram of sample spot intensity estimates on the intensity axis opposite the scatterplot. In this representation, it is easy to see the extent of overlap between the distribution of sample intensity estimates and the range of intensities that result in concentration s estimates with acceptable errors.
Results and discussion
To evaluate concentration estimation errors in the example analysis, we attempted to quantify or understand those errors that we can and minimize those errors that we cannot. We began with data screening. The most significant anomaly uncovered during this exploratory analysis of the cancer biomarker data was a decreasing trend in control spot intensity as a function of array print order (Figure 1). The trend was quantified using loess, a flexible, nonparametric method to fit a smooth curve through a scatterplot to uncover trends in data [22,23]. This trend suggests that 1) normalizing across arrays would improve precision; 2) in future experiments, assigning study groups to arrays should address array print order; and 3) array printing should be monitored and, if possible, modified to reduce this source of obscuring variation. In this case, we normalized for slide-level processing errors by subtracting from each spot's loge(fluorescent intensity) the difference between the mean of its slide's control spot loge (intensities) and the corresponding loess estimate.
Our evaluation addressed the selection and fitting of an acceptable concentration estimation model. To that end, we examined two plots. The first displays the fluorescent intensities of the standards as a function of concentration (Figure 2A). Two characteristics of the data that significantly affect selecting and fitting the model and then interpreting the results in a statistically meaningful way are apparent.
The first is heteroskedasticity, or the increasing variation in fluorescent intensity with increasing concentration. Meaningful statistical inferences about concentration estimation errors depend upon correct modeling assumptions. To apply propagation of error when estimating and then interpreting the approximate 95% confidence intervals, we rely on normal distribution theory and require that the random variability in spot intensities be homogeneous across concentrations [28]. In this case, a loge transformation of the intensity estimates stabilizes the variability across concentrations (Figure 2B).
The second characteristic is the undue leverage of data at high concentrations due to the increasing separation between standard concentrations with increasing concentration. Although both are expected (the first due to the randomness generally observed when counting photons, and the second due to the use of a concentration dilution series in the design), each must be addressed to achieve the best fit of the standard curve and resulting concentration estimation inferences. A loge transformation of the concentrations standardizes the separation in concentrations (Figure 2B).
With the heteroskedasticity and undue leverage addressed, we estimated a standard curve by selecting one of two models: a four-parameter logistic model (Eqn. 1) and a power curve model (Eqn. ??). We chose the logistic model as the model that fits the data best visually and in terms of the PRESS statistic (Figure 3). The logistic curve more closely follows the data points, while the power curve is too high in the lower concentrations and too low in the higher concentrations. We confirmed our choice with a review of the modeling diagnostics. In this case, we examined graphs of the standardized residuals as a function of concentration and the estimated intensities (Figure 4). In both graphs, the residuals show no significant systematic trends or deviations from the zero line and vary uniformly. Further, the preponderance of standardized residuals falls between -2 and 2, indicating that a statistical interpretation of the 95% confidence intervals is warranted.
Figure 5 presents the three-panel diagnostic visualization for the HER-2 data. HER-2 belongs to the family of epidermal growth factor receptors and has been used as a serum biomarker for the detection of breast cancer. This figure illustrates how data from a large study measuring HER-2 levels in the serum of women with and without breast cancer can be visualized using this statistical approach. A standard curve of HER-2 was generated, and the concentration of HER-2 in 39 samples was determined. To estimate manually the concentration for a sample HER-2 spot intensity, say I, locate I on the vertical axis, then scan across horizontally to the standard curve and 95% confidence intervals (Figure 5A). Scan down from these points to find the appropriate estimated concentration and lower and upper 95% concentration confidence bounds. In this manner, the estimated concentration and confidence interval can be determined.
In the standard curve panel (Figure 5A), we see that near the asymptotes of the standard curve, the uncertainty grows much more quickly than the curve, causing the concentration confidence bounds to diverge. Although this divergence is due to the approximation (Eqns 2 and 3), it is true that near the asymptotes, the uncertainty of the estimated concentration increases greatly. For this reason we have defined our optimal region of this curve to be the range of spot fluorescence values such that both the upper and lower bounds are monotonically increasing in intensity. The boundaries of this range are indicated by the shaded area and the dashed red lines, which also show the concentration values corresponding to the acceptable fluorescence range. Our optimal concentration range spans approximately two orders of magnitude.
The histogram (Figure 5B) shows the fluorescence values of the sample spots for which this curve may best be used to estimate concentration. The plot shows that many of the sample values lie outside our optimal region. The researcher must then decide if too many of these values lie outside this range and, if so, what can be done to fix this problem. Nevertheless, we were able to compare the HER-2 concentrations and found a 3.5-fold increase in HER-2 protein levels in women with stage Ill/stage IV breast cancer (7 samples) compared to women without breast cancer (12 samples).
The concentration coefficient of variation, or the ratio of the concentration estimation error to the corresponding estimated concentration, offers an alternative expression to a confidence interval as a means to evaluate concentration estimation error. A graph of this estimation error as a function of concentration offers a comprehensive summary of the variation in the concentration coefficient of variation over the concentration range (Figure 5C).
Presenting the results in this type of plot allows us to immediately look for several potential problems. First, does the fitted curve seem reasonable, given the data points to which we are fitting? We also can determine whether most of the unknown sample data fall within the acceptable range of the curve. The usable concentration range is made clear and, if it is too limited in range, it is immediately apparent. If problems are identified, several fixes are available, including changing the settings on the imager or using a different concentration range to create the standard curves.
Conclusions
Evaluation of errors in estimating concentrations is important to establishing confidence in protein concentration estimates. Propagation of error provides a straightforward approach to estimating concentration estimation errors in ELISA microarray experiments. When presented in a simple multi-panel visualization, the propagated errors provide valuable information about individual concentration estimates, the applicability of the estimated standard curve, quality of the experiment, and the conduct of the ELISA microarray processing. The visualization provides a rapid assessment of the quality of the data, particularly in regard to the goodness of fit of the estimated standard curve and its capability to estimate concentrations over the observed range of intensities of biological samples.
Authors' contributions
DSD framed evaluation of ELISA microarray concentration estimation errors as a statistical problem. KKA suggested the use of propagation of error and outlined the initial derivation. DSD and AMW derived the appropriate propagation of error equations, developed the algorithms, and designed the diagnostic visualizations. AMW encoded the algorithms, analyzed the microarray imagery, and produced the statistical results. SMV designed and printed the arrays and then carried out the ELISA microarray experiments. RCZ conceived the study, designed it with SMV, and then coordinated all our efforts. All authors submitted comments on drafts, then read and approved the final manuscript.
Acknowledgements
This research was supported by the Biomolecular Systems Initiative at the Pacific Northwest National Laboratory, a multiprogram national laboratory operated by Battelle for the U.S. Department of Energy under Contract DE-AC05-76RL01830.
Figures and Tables
Figure 1 Control spot fluorescence and slide print order We expect control spot intensity to be constant across slide print order. The trend, estimated with loess regression, indicates a processing effect due to printing order. In this case, the decrease in control spot intensity, coupled with knowledge of the printing process, suggests that the quantity of printed material is decreasing over a printing run.
Figure 2 Spot fluorescence and standard concentration A graph of spot fluorescence as a function of standard concentration (A) shows that both the difference in concentration and the variability in spot fluorescence increase with concentration. Both negatively affect model fitting and subsequent statistical inferences due to the excessive leverage of the larger concentrations and the heteroskedasticity of the spot intensities. In this case, loge transforms of both concentration and spot fluorescence reduce the excessive leverage and improve the homogeneity (B). The log transformation is consistent with the featured concentration dilution series and is a common transformation of chemical measurements that often are assumed log normally distributed.
Figure 3 Candidate standard curves A review of the graphs of a four-parameter logistic curve (A) and a power law curve (B) suggests that the former shows higher fidelity to the data and is a better choice for the standard curve in this case.
Figure 4 Modeling diagnostics The points in graphs of the standardized residuals versus the loge standard concentrations (A) and the standardized residuals versus the estimated loge spot intensities (B) are reasonably well behaved, showing no strong systematic trends or deviations from the zero line. These indicate that the four-parameter logistic model is acceptable, that subsequent statistical inferences are reasonable, but that a better model may exist in another model family.
Figure 5 Three-panel diagnostic summary The standard curve panel (A) of the three-panel diagnostic summary features a scatterplot of the data, the estimated standard curve (black line), the 95% confidence intervals (blue lines), and the region of acceptable errors (grey). For this example, the acceptable segment of the standard curve (i.e., the segment with concentration estimation errors acceptable to us) covers spot intensities from about 1000 to 7500 intensity units and concentrations from about 25 to 500 pg/ml. The histogram of sample intensities (B) suggests that about one-fifth of the sample spot intensities is below the detection limit of about 1000 units, about three-fifths will produce estimated concentrations in the acceptable range, and one-fifth exceeds the acceptable range. With regard to remeasuring the standards in this experiment or imaging in future experiments, the three-panel graph suggests that it may be worthwhile to attempt to extend the acceptable range. It also suggests that the normalization between the standards measurements and sample measurements should be revisited. The graph of the concentration coefficient of variation as function of concentration (C) offers an alternative summary of the estimation errors over the range of concentrations.
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| 15673468 | PMC549203 | CC BY | 2021-01-04 16:02:51 | no | BMC Bioinformatics. 2005 Jan 26; 6:17 | utf-8 | BMC Bioinformatics | 2,005 | 10.1186/1471-2105-6-17 | oa_comm |
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BMC BioinformaticsBMC Bioinformatics1471-2105BioMed Central London 1471-2105-6-81564933210.1186/1471-2105-6-8Research ArticleStructural comparison of metabolic networks in selected single cell organisms Zhu Dongxiao [email protected] Zhaohui S [email protected] Bioinformatics Program, University of Michigan, Ann Arbor, MI 48109, USA2 Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA3 Department of Statistics, University of Michigan, Ann Arbor, MI 48109, USA2005 14 1 2005 6 8 8 20 7 2004 14 1 2005 Copyright © 2005 Zhu and Qin; 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 has been tremendous interest in the study of biological network structure. An array of measurements has been conceived to assess the topological properties of these networks. In this study, we compared the metabolic network structures of eleven single cell organisms representing the three domains of life using these measurements, hoping to find out whether the intrinsic network design principle(s), reflected by these measurements, are different among species in the three domains of life.
Results
Three groups of topological properties were used in this study: network indices, degree distribution measures and motif profile measure. All of which are higher-level topological properties except for the marginal degree distribution. Metabolic networks in Archaeal species are found to be different from those in S. cerevisiae and the six Bacterial species in almost all measured higher-level topological properties. Our findings also indicate that the metabolic network in Archaeal species is similar to the exponential random network.
Conclusion
If these metabolic network properties of the organisms studied can be extended to other species in their respective domains (which is likely), then the design principle(s) of Archaea are fundamentally different from those of Bacteria and Eukaryote. Furthermore, the functional mechanisms of Archaeal metabolic networks revealed in this study differentiate significantly from those of Bacterial and Eukaryotic organisms, which warrant further investigation.
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Background
Classification of biological organisms is of fundamental importance to evolutionary studies. It is commonly believed that there are three domains of life: Archaea, Bacteria and Eukaryote. Currently, the most popular classification method is the so called "molecular approach", in which polymorphism information in DNA or protein sequence is exploited to assess the phylogenetic relationships among species [1,2]. To a large extent, this is a "local" approach since the choice of sequence for comparison greatly affects the final result, "lateral gene transfer" (LGT) and thus the resulting "genome chimerism" further complicates the situation [3]. A new "system" approach that takes "global" properties of each organism into consideration serves as a potential alternative to overcome this shortcoming. Indeed, recent advances in system biology and increasingly available genomic databases have made it possible to rebuild biological networks from genomic data and have offered opportunity for such a "system" approach [4].
Podani and co-workers [5] proposed classifying organisms based on two kinds of network indices: the Jaccard index, which measures proportions of common sets of nodes in two networks, and Goodman-Kruskal γ function, which measures the similarity between rankings of nodes in two networks. They studied metabolic and information network structures of 43 organisms using these two measures under the hypothesis that network structure and the network design principle(s) behind them contain phylogenetic information. Ma and Zeng [6] conducted a more extensive phylogenetic classification study on 82 fully sequenced organisms based on different cellular function systems (enzyme, reaction, and genes) at the genomic level. They constructed phylogenetic tree based on Jaccard index and Korbel's definition, and concluded that in general, the classification based on network indices are in good agreement with the one obtained by analyzing the 16S rRNA using molecular approach. These studies seem to support the notion that significant differences in the network design principle(s) exist among the three domains of life [7]. These differences may reflect on the different approaches that organisms take to organize their entire systems to serve their special needs in the environment they live during the evolutionary history. Motivated by these encouraging results, in this manuscript, we went on to conduct a thorough comparison of network structural properties which provide further and more compelling evidences that significant differences exist among the network design principle(s) in organisms from the three domains of life.
Restricted by the theoretical network structural studies, there are not many deterministic and informative topological measurements available [8-11]. The established measurements can be roughly divided into two categories: higher-level (global) properties and low-level (local) properties. The difference between the two is that one needs to know the whole network in order to calculate the higher-level property measures (e.g. average path length) while the low-level properties can be worked out locally (e.g. marginal degree of individual node) [9]. We use three groups of topological measurements (both low and higher-level) that address different aspects of the network structure. The first group contains network indices such as average clustering coefficient, average path length [12]. The second group is composed of degree distributions (both marginal and bivariate joint degree distributions) [8-11,13]. The third group is composed of network motif profiles that are recently shown to represent the network design principle(s) and global statistical properties of the network when aggregating together [14-16]. These measurements have been well studied in the network literatures, and are able to capture most aspects of network degree information.
Single cell model organisms such as E. coli and S. cerevisiae have been studied intensively in biochemistry, cell biology and genetics; hence the rebuilt networks in those organisms present the best chance to approximate the true underlying network. Moreover, single cell organisms are less likely to have experienced the Whole Genome Duplication (WGD), which might drastically change the network structure [17,18]. As a result, we selected eleven single cell organisms to study their network structural properties: one Eukaryote: S. cerevisiae; six Bacteria: E. coli, V. cholerae, R. solanacearum, B. subtilis, L. lactis, S. coelicolor; and four Archaea: S. solfataricus, S. tokodaii, M. acetivorans, T. acidophilum.
There are three main types of intracellular networks: the protein-protein interaction network, the transcriptional regulation network and the metabolic network. The first two are rebuilt by using high throughput techniques such as yeast two-hybrid system, in vivo pull down assay or DNA microarray, which are subject to high uncertainties, and the resulting networks may not be good approximation to biological complexity [19-22]. On the other hand, the metabolic network is derived from metabolic pathways, many of which are inferred from biochemical experiment-defined stoichiometries of many reactions [23]. It is well known that central pathways contain "hub nodes" of the whole metabolic network [24,25] and are also main building blocks of the so-called Giant Strongly Connected Component (GSCC) and Giant Weakly Connected Components (GWCC) [26]. The former is defined as the largest cluster of nodes within which any pair of nodes is mutually reachable from each other, and the latter is defined as the largest cluster of nodes within which each pair of nodes is connected in the underlying undirected graph [10]. Therefore, our high confidence in the structure of GSCC and GWCC, based on experimentally verified pathways, guarantees high confidence in whole network structure. The long history of biochemical studies of enzymes ensures relatively low false positive and low false negative rates of connections. Therefore, we decided to use metabolic networks in single cell organisms to compare network topological properties in the three domains of life.
Results
In constructing metabolic networks, Ma and Zeng [28] argued that connections through "current metabolites", which is referred to as cofactors in biochemistry such as ATP, ADP, H2O, should be removed from metabolic networks. We followed their suggestions by removing such "current metabolites" before conducting the following analysis.
Group I measures: network indices
Before checking different types of network topological measurements, we visually compared different metabolic networks (Fig. 1). Metabolic networks in S. cerevisiae and the six Bacterial species appear much more heterogeneous than Archaeal metabolic networks. It is well known that the so-called exponential random network (marginal degree distribution follows a Poisson distribution, see Methods for details) appears homogeneous while scale-free network (marginal degree distribution follows a power-law distribution, see Methods for details) appears more heterogeneous and modular [9].
Calculations of the two classic network indices, average clustering coefficient and average betweenness (see Methods for definition) also indicate that the metabolic networks in S. cerevisiae andthe six Bacterial species are more clustered and modular than those in the four Archaeal species (Table 1, Fig. 2). From Table 1 and Fig. 2, it is evident that the Clustering Coefficient (C) and Betweenness (B) did a better job in separating Archaeal species from non-Archaeal species than Average Path Length (L) and Diameter (D). Note that since we removed connections through "current metabolites" when constructing metabolic networks, our average path lengths are much longer than those reported in Jeong et al. [25] but similar to those reported in Ma and Zeng [28].
To avoid the confounding effects stemming from different network sizes, we calculated the so-called concentrations (number of appearances of subgraphs divided by the number of nodes with edges or arcs (directed edges), see Methods for details) of three-node subgraphs and four-node subgraphs. The concentration of subgraphs is an objective measure of the extent of clustering and modularity of the network [8,9]. It is observed that the concentrations of subgraphs in S. cerevisiae and the six Bacterial metabolic networks are much higher than those in Archaeal metabolic networks (Fig. 3).
Group II measures: degree distributions
Marginal degree distributions
Recently, a variety of real-life networks are found to share the "scale-free" property, i.e. the marginal degree distribution follows a power-law distribution [25,29-31]. Our analysis demonstrates that the outgoing and incoming marginal degree distributions in metabolic networks also follow the power-law distribution. A simple linear model fits the log-transformed data well (except for the incoming degree distributions for most of the Archaea) which indicates that in general, the power-law model is appropriate to capture the structure of degree data (Fig. 4). Parameters were estimated using the Least Square method. The results together with goodness of fit measure R2 and 95% individual confidence intervals are summarized in Table 2 and Table 3. The estimated power-law index γ is around -0.3 in all cases and the estimated log-transformed scaling parameter α ranges within 2.0 to 2.5. These indicate that marginal degree distribution, which is a low-level (local) topological property measure, although showed some distinction, is not enough to effectively differentiate networks from different domains. Overall, metabolic networks in most of the species we studied seem to follow the power-law distributions and thus are "scale-free". The fact that the incoming degree distributions of most Archaeal species we studied do not follow power-law well (Fig. 4B) suggests that networks in Archaeal species tend to be less "scale-free" and more "random-like" compared to those of the non-Archaeal species.
As we have shown, marginal degree distribution alone does not reveal the fundamental network structural differences between the Archaeal species and the non-Archaeal species. Simulation studies have shown that randomized networks preserving marginal degree distribution can be quite different in terms of global (higher level) topological properties such as average clustering coefficient [9]. In metabolic networks, we are unable to determine the preferred types of reactions based on just marginal substrate or product degree distributions. Since the metabolic network is rebuilt from chemical reactions, joint behavior of substrate and product in reactions should be more informative than disjoint behavior of metabolites. Therefore, we calculate the joint degree distributions hoping to gain more insight into the network organization.
Joint degree distributions
Joint degree distribution measures and describes correlation between connectivities of neighboring nodes. N(K0, K1) is defined as the number of edges connecting nodes of connectivity K0 to those of connectivity K1. For metabolic networks, which are directed, N(Kout, Kin) is used to measure the number of arches where substrate (node) with out-connectivity Kout transforms to product with in-connectivity Kin. This quantity reflects intrinsic properties of the network and can be used to distinguish different types of networks. For instance, we can test whether N(Kout, Kin) of a particular network differs significantly from that of the random network. To be specific, we calculate , where (Kout, Kin) represents the mean of random variable N(Kout, Kin) in a large number (say, 1000) of random networks simulated by an edge-rewiring algorithm proposed by Maslov and Sneppen [13], (Kout, Kin) denotes the estimated standard deviation of N(Kout, Kin). The p-value can then be obtained by compare Z to a standard normal distribution. Comparing with "properly" randomized network ensembles allows us to concentrate on those statistically significant patterns of the complex network that are likely to reflect the design principle(s) [13].
We calculated statistically significant correlation profiles (Z-score profiles, see Methods for details) for the metabolic network in each organism (Fig. 5). The Z-score profiles of the four Archaeal species are similar to each other but quite different from those in S. cerevisiae and the six Bacterial species. Although the dark red regions of the Z-score profiles in Archaeal species are quite different in scale, they all seem to differ significantly from the random network preserving the corresponding marginal degree distribution in a similar way (p-value < 0.1). Looking into the correlation profiles more carefully, we found that the number of statistically significant positive (Kout, Kin) increases in the order of S. cerevisiae, the six Bacterial species and the four Archaeal species. The significant Z-score of certain observation N(Kout, Kin) implies that the chemical reaction between substrates with out-degree Kout and products with in-degree Kin are statistically significant. We define substrates whose Kout >= 2 or products whose Kin >= 2 as versatile metabolites. Thus, the above trend implies that the preference to employ reactions involving versatile metabolites increases in the order of S. cerevisiae, the six Bacterial species and the four Archaeal species. Correspondingly, the variety of metabolites decreases in the above order and so does the number of distinct enzymes or variety of enzymes because of the high specific binding of metabolites and enzyme. This is consistent with the biological facts that S. cerevisiae (Eukaryote) encodes a greater variety of enzymes than Bacterial and Archaeal species.
Group III measure: Network Motif
The network motif is defined to be recurring and non-random building blocks of the network [14,15]. Just like sequence motif, which is an over-represented and biologically meaningful DNA or protein sub-sequence, network motif is an over-represented and biologically meaningful subgraph.
Network motif has been shown to be informative of network design principle(s) and network structure. It was found that over 80% of the nodes in the E. coli transcription regulation network are covered by network motifs [14]. Dobrin et al. [16] recently discovered that in the E. coli transcriptional regulatory network, "individual motifs aggregate into homologous motif clusters and a supercluster forming the backbone of the network and play a central role in defining its global topological organization." More importantly, network motifs capture the information that is likely to be missed by the correlation profiles because motif actually describes the number of appearances of certain configurations of multiple nodes, and therefore nicely complement with the correlation profiles [9]. One might argue that there are certain amount of overlaps between the information they capture but the motif profile does not capture the degree information of the connecting nodes, which may be the most powerful feature of the correlation profiles.
We searched for all of the 13 three-node subgraphs and all of the 199 four-node subgraphs in the metabolic networks of eleven species. The results showed that the three-node motif profiles found in S. cerevisiae and the six Bacterial species are identical while there is no three-node motif found in any of the four Archaeal networks (Fig. 6). Also there is no common four-node motif shared by Archaeal species and S. cerevisiae/Bacterial species while two four-node motifs (id4702, id4950) are shared by the latter (Additional file 1). Among all the 13 possible three-node subgraphs, six of them have one pair of nodes not directly connected. Abundance of such subgraphs will lower the extent of clustering and modularity of the network. As expected, we found that all three-node motifs identified in S. cerevisiae and the six Bacterial species form triangles (Fig. 6). It may explain our main finding that metabolic networks in non-Archaeal species are more clustered and modular than those in Archaeal species.
Discussion
Based on our comparison of network structural properties beyond network indices, we were able to gain more insight into the structural differences across the three domains of life. Having shown that the metabolic network is "scale-free", we further showed that metabolic networks in the four Archaeal species are closer to "exponential random network" [9:Ch2, [11]] than those in S. cerevisiae and the six Bacterial species. The reasons are the following:
First, the Archaeal metabolic networks are visually more homogeneous among themselves compared to their counterparts in the non-Archaeal species. In random networks, any pair of nodes is equally likely to be connected. The network topology should look homogeneous given that the size of network is large enough. The "scale-free" network, on the other hand, features a highly modular and heterogeneous topology since the marginal degree is power-law distributed [8,9]. Moreover, the marginal degree distributions of the metabolic networks in non-Archaeal species fit the power-law model better than Archaeal species (Table 2 and Table 3).
Second, the average clustering coefficient and average betweenness of Archaeal metabolic networks are much smaller than those in S. cerevisiae and the six Bacterial species. The same is true for the concentrations of three-node and four-node subgraphs. As pointed out by Watts and Strogatz, real-life networks show strong clustering or network transitivity while exponential random network does not [12].
Third, there is no three-node motif and fewer four-node motifs found in Archaeal metabolic networks compared to non-Archaeal metabolic networks. In particular, the ubiquitous feed-forward loop (FFL) motif found in networks from biology (including metabolic networks in S. cerevisiae and the six Bacteria species in this study) to neurology and engineering fields was not found in any of the four Archaeal metabolic networks (Fig. 6). Since motifs are statistically significant subgraphs compared to "properly" randomized network ensembles, no motif or fewer than usual motifs found in a real-life network indicates that the network structure is closer to that of a random network. It has been shown by Milo et al. [15] that concentration of FFL motif is insensitive to the network size within E. coli transcription regulation network, but diminishes to zero in increasingly larger random networks. This also supports that Archaeal metabolic networks are closer to randomized network ensembles than other real-life networks.
The metabolic networks in Archaea are both "random-like" and "scale-free", which might exert profound influences on their adaptability to the hostile environment. Archaeal species are typically restricted to marginal habitats such as hot springs or areas of low oxygen concentration and can assimilate different kinds of inorganic carbon and nitrogen sources. Indeed, the chemical structure and component of the macromolecules such as protein and lipid make significant contributions to the organism's adaptability to the environment. The seemingly ad hoc network organization (both "random-like" and "scale-free") in Archaeal species might also enabled them to survive in those extreme physiological conditions. Archaeal species might employ some biologically significant subgraphs (rather than statistically significant motifs) which can not be detected by current motif searching algorithm [15]. This makes the Archaeal metabolic networks appear random in statistical sense (not statistically significantly different from random networks) but not in biological sense.
Our comparison results showed that many network structural properties measured in Archaeal species are different from those of non-Archaeal species. However, the hidden anthropomorphic factors might account for some of the differences observed. Specifically, the drastic differences of topological profiles between the metabolic networks of Archaeal species and non-Archaeal species may be partially explained by the fact that significantly less extensive metabolic pathway studies have been conducted in Archaeal species [32]. Robustness of topological profiles against random perturbations can alleviate the impact to a certain extent but is unable to eradicate it [9].
Conclusions
Our network analysis results showed that in most of higher-level (global) topological properties measured, metabolic networks in the four Archaeal species are similar to each other but significantly different from those in S. cerevisiae and the six Bacterial species. This provides further evidence that the metabolic network structures and consequently the design principle(s) in the four Archaeal species are very different from those in S. cerevisiae (Eukaryote) and the six Bacterial species. Our finding that the metabolic networks in Archaeal species possess many properties of the exponential random network begs for better understanding of the design principle(s) in biological networks, which may be revealed by further systematic analyses. For example, locate and align conservative pathways such as glycosis between E. coli or S. cerevisiae and Archaeal species to understand the functional mechanisms of Archaeal metabolic networks.
Methods
Data source
Chemical reaction data was obtained from metabolic database in Ma and Zeng [28], which consists of five related tables: reaction, enzyme, react, connect and organism. We compiled a new table from this database excluding any inconsistent or redundant connections between metabolites (details below). SQL was used to query the database.
Identify and remove inconsistency
Inconsistent connections refer to pairs of metabolites that have conflicting reversibility annotation. It is caused by the fact that a pair of metabolites can be in more than one reaction and the reversibility of these reactions can be different. For example, NAD+ and Nicotinamide is a pair of metabolites in two reactions: 1) NAD+ + L-Arginine = Nicotinamide + N2 (ADP-D-ribosyl)-L-arginine 2) NAD+ + H2O ->Nicotinamide + ADPribose. (Note that here the role of NAD+ is NOT "current" metabolite, and hence connections established through it should NOT be removed). Reaction 1 is a reversible reaction while reaction 2 is not. We annotated an edge between the two metabolites as long as there was at least one reversible reaction that both of them were involved. For example, the type of connection between NAD+ and Nicotinamide is edge (undirected connection). This step could be summarized as "edge ← edge + arc".
Identify and remove redundancy
There are also numerous redundant connections where the same pair of metabolites switch their roles between substrate and product in two or more different irreversible reactions. For example: 1) UDPglucose + N-Acylsphingosine = UDP + Glucosylceramide 2) Glucosylceramide + H2O = D-Glucose + N-Acylsphingosine. (N-Acylsphingosine and Glucosylceramide is a pair of metabolites that switch their roles in two irreversible reactions). In case of redundancy, we annotated an edge between the pair of metabolites rather than the two arcs because they could be converted to each other through two reactions. This step could be summarized as "edge ← arc + arc".
Definitions of some network topological measurements
Clustering coefficient (C)
We define two kinds of clustering coefficients for each node in the directed metabolic networks, i.e. Cin and Cout. Cin measures the average clustering coefficient of the node representing the product that can be generated from its first-order "nearest neighbors" through chemical reactions. Cout measures the average clustering coefficient of the node that generate its first-order "nearest neighbors" through chemical reactions. The larger the coefficients, the more clustered and modular the network appears to be.
Betweenness (B)
The betweenness for any node ni in the network is defined as , where gjk is the number of shortest paths between node j and node k. gjk(ni) is the number of shortest path between node j and node k containing node ni, g is the total number of nodes with edges/arcs. CB(ni) needs to be multiplied by two in the case of directed network [27]. The average betweenness is defined as: . Higher value of betweenness indicates the network is more clustered and modular.
Average path length (L)
Watts and Strogatz [12] defined the average path length as , where d(j, k) is the shortest path length between node j and node k (distance), V represents the set of all nodes with edges/arcs of the graph, and g is the number of nodes with edges/arcs.
Diameter (D)
The diameter of the directed graph G is the longest geodesic between any pairs of nodes. The geodesic is the shortest path between a pair of nodes. Pajek [33] was used to calculate the average betweenness, average path length and diameter.
Concentration of subgraphs (S)
Wasserman and Katherine [27] defined the subgraph as follows: A graph Gs is a subgraph of G if the set of nodes of Gs is a subset of the set of nodes of G, and the set of lines in Gs is a subset of the lines in the graph G. Let M be the number of subgraphs, and N be the number of nodes with edges or arcs. Then the "concentration of subgraph" is defined as C = M/N. A high value of C indicates the network is more clustered and modular. Mfinder1.1 [15] was used to calculate both M and N.
Marginal degree distribution calculations
The marginal degree distribution of each network is calculated from the Boolean adjacency matrix A, a matrix of 0 or 1. Zero means there is no connection between nodes, and 1 the opposite. The outgoing degree of the node i, kout(i) is defined as , where . The incoming degree of the node i, kin(i) is defined as .
Simple regression analyses of marginal degree distributions
The power-law degree model was first log transformed into linear model, i.e. log P(Ki) = γ log(Ki) + log(α) + εi (i = 1,2,...,n), γ and α are parameters, εi is the residual. Ki is the degree and P(Ki) is the corresponding probability. Based on the fitted linear model, we made statistical inference including parameter estimation and individual confidence intervals on the estimates using the Least Square method.
Correlation profile calculations
Statistically significant correlation profiles were calculated using Matlab code downloaded from Dr. Maslov's website [34]. The adjacency matrix of the network is the input.
Motif profiles calculations
According to Milo et al.[15] , a subgraph is referred to as a motif if the following criteria are met: 1) Its empirical p-value is smaller than a pre-specified threshold, e.g. 0.01. 2) The number of appearances in real networks with distinct sets of nodes is larger than another pre-specified cut-off value, e.g. 4. 3) The number of appearances in real networks is significantly larger than that in randomized networks, i.e. . Nreal and Nrand represent the number of certain subgraphs detected in real-life network and randomized networks, respectively. This is to avoid the situation where some common subgraphs are detected as motifs that have only slight differences in Nreal and Nrand but have a narrow spread of distribution in randomized networks [14,15]. Motif profiles are generated using the Mfinder program. This program and the motif dictionary were downloaded from Dr. Uri Alon group's website [35].
Authors' contributions
DZ and ZSQ conceived and designed the study; DZ wrote the computer code, analyzed the data and draft the manuscript. Both authors read and approved the final manuscript.
Supplementary Material
Additional File 1
Four-node motifs found in the metabolic networks in different species. The number of connecting nodes for each network is shown. For each motif, the numbers of appearances in real networks (Nreal) and in randomized networks (Nrand ± SD, all values rounded) are shown. The p-values of all motifs are less than 0.01, as determined by comparing to 1000 randomized networks. Each motif occurs at least four times in one network. Other restrictions apply. Motifs were detected and generated using program found in Milo et al. [15] and the motif dictionary therein.
Click here for file
Acknowledgements
We thank Drs. Hong-Wu Ma and An-Ping Zeng for their compiled metabolic database; Dr. Kerby A. Shedden for valuable discussion and the two anonymous reviewers for their constructive comments
Figures and Tables
Figure 1 Visualizations of metabolic networks in the eleven organisms. In each graph, green lines represent arc and red lines represent edge. The numbers of distinct metabolites that are involved in at least one reaction are noted. All graphs are drawn with Pajek [33] using the layout optimization algorithm Kamada-Kawai.
Figure 2 Five network indices (Clustering Coefficients (Cout, Cin), Betweenness (B), Average Path Length (L) and Diameter (D)) of the metabolic networks in the eleven organisms.
Figure 3 Concentrations (number of appearances divided by number of nodes with edges/arcs) of three-node and four-node subgraphs.
Figure 4 (A) Log transformed marginal outgoing degree distributions (B) Log transformed marginal incoming degree distributions in the eleven organisms
Figure 5 Statistical significance of correlation (Z-scores) present in the metabolic networks. To improve statistics, the connectivities in all eleven panels of this figure were logarithmically binned into two bins per decade. Statistically significant correlation profiles are generated using the Matlab program developed by Maslov and Sneppen [13].
Figure 6 Three-node motifs found in the metabolic networks in different species. The number of connecting nodes for each network is shown. For each motif, the numbers of appearances in real networks (Nreal) and in randomized networks (Nrand ± SD, all values rounded) are shown. The p-values of all motifs are less than 0.01, as determined by comparing to 1000 randomized networks. Each motif occurs at least four times in one network. Motifs were detected and generated using program developed by Milo et al. (2002) and the motif dictionary therein [15].
Table 1 Descriptive statistics of metabolic networks in the eleven organisms.
DOMAIN, KINGDOM AND PHYLUM ORGANISM NUM NODES NUM EDGES SINGLE EDGES MUTUAL EDGES COUT CIN B L D
Eukarya S. cerevisiae 748 1072 396 338 0.066 0.062 0.053 12.147 49
Bacteria Proteobacteria gamma E. coli 893 1365 459 453 0.060 0.070 0.070 9.281 30
V. cholerae 738 1076 370 353 0.057 0.055 0.045 8.236 23
beta R. solanacearum 864 1238 406 416 0.044 0.044 0.049 10.358 43
Firmicutes Bacillales B. subtilis 787 1151 401 375 0.061 0.063 0.047 10.020 29
Lactobacillales L. lactis 545 778 280 249 0.044 0.043 0.068 9.277 27
Actinobacteria S. coelicolor 814 1154 406 374 0.046 0.047 0.047 15.062 66
Archaea Euryarchaeota M. acetivorans 489 633 209 212 0.029 0.033 0.026 11.350 35
T. acidophilum 458 593 197 198 0.034 0.036 0.030 10.597 33
Crenarchaeota S. solfataricus 586 730 256 237 0.022 0.021 0.018 8.053 26
S. tokodaii 522 651 229 211 0.021 0.024 0.017 8.424 27
The column marked "Num nodes" lists the number of metabolites that are involved in at least one chemical reaction in the organism. The column marked "Num edges" lists the number of all directed chemical reactions in the organism. Note that this number consists of two parts: The number of irreversible reactions, i.e. "Single edges"; and the number of reversible reactions, i.e. "Mutual edges", where "Num edges" = "Single edges" + 2 × "Mutual edges". The column marked "Cout" lists the average clustering coefficient calculated from the nearest neighbors in out-component. The column marked "Cin" lists the average clustering coefficient calculated from the nearest neighbors in in-component. Column marked "B" lists the average betweenness of the network, the column "L" lists average path length of the network and column marked "D" lists diameter of the network.
Table 2 Parameter estimates of γ and logα in the outgoing degree distribution model.
R2 γ, 95% C.I. logα, 95% C.I.
S. cerevisiae (748) 0.96 -0.39, [-0.46, -0.31] 2.53, [2.29, 2.78]
E. coli (893) 0.92 -0.36, [-0.43, -0.28] 2.51, [2.29. 2.74]
V. cholerae (738) 0.91 -0.36, [-0.44, -0.28] 2.45, [2.22, 2.68]
R. solanacearum (864) 0.96 -0.37, [-0.43, -0.31] 2.50, [2.32, 2.68]
B. subtilis (787) 0.92 -0.36, [-0.44, -0.28] 2.46, [2.23, 2.68]
L. lactis (545) 0.95 -0.38, [-0.45, -0.31] 2.39, [2.20, 2.58]
S. coelicolor (814) 0.95 -0.36, [-0.43, 0.30] 2.47, [2.29, 2.65]
S. solfataricus (586) 0.92 -0.33, [-0.43, -0.23] 2.17, [1.86, 2.49]
S. tokodaii (445) 0.94 -0.34, [-0.42, -0.25] 2.15, [1.88, 2.42]
T. acidophilum (458) 0.97 -0.37, [-0.44, -0.31] 2.25, [2.05, 2.45]
M. acetivorans (489) 0.86 -0.33, [-0.46, -0.20] 2.13, [1.73, 2.53]
Model: log P(Ki) = γ log(Ki) + log(α) + εi (i = 1,2,...,n). Parameters are estimated using Least Square Method.
Table 3 Parameter estimates of α and γ in the incoming degree distribution model.
R2 γ, 95% C.I. logα, 95% C.I.
S. cerevisiae (748) 0.95 -0.35, [-0.42, -0.29] 2.38, [2.18, 2.59]
E. coli (893) 0.90 -0.35, [-0.42, -0.28] 2.50, [2.29, 2.70]
V. cholerae (738) 0.91 -0.36, [-0.44,-0.28] 2.45, [2.22, 2.68]
R. solanacearum (864) 0.96 -0.37, [-0.42, -0.31] 2.50, [2.32, 2.68]
B. subtilis (787) 0.92 -0.36, [-0.43, -0.28] 2.46, [2.23, 2.68]
L. lactis (545) 0.95 -0.38, [-0.45, -0.31] 2.40, [2.20, 2.58]
S. coelicolor (814) 0.95 -0.36, [-0.43, -0.30] 2.47, [2.29, 2.65]
S. solfataricus (586) 0.45 -0.24, [-0.41, -0.07] 2.21, [1.76, 2.68]
S. tokodaii (445) 0.46 -0.25, [-0.42, -0.08] 2.21, [1.76, 2.65]
T. acidophilum (458) 0.89 -0.30, [-0.41, -0.20] 2.00, [1.69, 2.32]
M. acetivorans (489) 0.46 -0.25, [-0.43, -0.08] 2.20, [1.75, 2.65]
Model: log P(Ki) = γ log(Ki) + log(α) + εi (i = 1,2,...,n). Parameters are estimated using Least Square Method.
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| 15649332 | PMC549204 | CC BY | 2021-01-04 16:35:47 | no | BMC Bioinformatics. 2005 Jan 14; 6:8 | utf-8 | BMC Bioinformatics | 2,005 | 10.1186/1471-2105-6-8 | oa_comm |
==== Front
BMC CancerBMC Cancer1471-2407BioMed Central London 1471-2407-5-141570117610.1186/1471-2407-5-14Research ArticleQuantitative evaluation and modeling of two-dimensional neovascular network complexity: the surface fractal dimension Grizzi Fabio [email protected] Carlo [email protected] Piergiuseppe [email protected] Barbara [email protected] Eldo E [email protected] Everardo [email protected] Maurizio [email protected] Scientific Direction, Istituto Clinico Humanitas, Via Manzoni 56 – 20089 Rozzano, Milan, Italy2 "Michele Rodriguez" Foundation-Institute for Quantitative Measures in Medicine, Via Ludovico Di Breme 79 – 20100 Milan Italy3 Department of Pathology, Istituto Clinico Humanitas, Via Manzoni 56 – 20089 Rozzano, Milan, Italy4 Department of Surgery, Texas Tech University Health Science Center and the Southwest Cancer Treatment and Research Center, 79430 Lubbock, Texas, USA5 Department of Internal Medicine, Texas Tech University Health Science Center and the Southwest Cancer Treatment and Research Center, 79430 Lubbock, Texas, USA6 Department of Microbiology and Immunology, Texas Tech University Health Science Center and the Southwest Cancer Treatment and Research Center, 79430 Lubbock, Texas, USA2005 8 2 2005 5 14 14 15 10 2004 8 2 2005 Copyright © 2005 Grizzi 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
Modeling the complex development and growth of tumor angiogenesis using mathematics and biological data is a burgeoning area of cancer research. Architectural complexity is the main feature of every anatomical system, including organs, tissues, cells and sub-cellular entities. The vascular system is a complex network whose geometrical characteristics cannot be properly defined using the principles of Euclidean geometry, which is only capable of interpreting regular and smooth objects that are almost impossible to find in Nature. However, fractal geometry is a more powerful means of quantifying the spatial complexity of real objects.
Methods
This paper introduces the surface fractal dimension (Ds) as a numerical index of the two-dimensional (2-D) geometrical complexity of tumor vascular networks, and their behavior during computer-simulated changes in vessel density and distribution.
Results
We show that Ds significantly depends on the number of vessels and their pattern of distribution. This demonstrates that the quantitative evaluation of the 2-D geometrical complexity of tumor vascular systems can be useful not only to measure its complex architecture, but also to model its development and growth.
Conclusions
Studying the fractal properties of neovascularity induces reflections upon the real significance of the complex form of branched anatomical structures, in an attempt to define more appropriate methods of describing them quantitatively. This knowledge can be used to predict the aggressiveness of malignant tumors and design compounds that can halt the process of angiogenesis and influence tumor growth.
==== Body
Background
The term "angiogenesis" defines the fundamental process of the development and growth of new blood vessels from the pre-existing vasculature, and is essential for reproduction, development and wound repair [1]. Under these conditions, it is highly regulated: i.e. "turned on" for brief periods of time (days) and then completely inhibited.
The cyclic nature of the microvascular bed in the corpus luteum provides a unique experimental model for examining the discrete physiological steps of angiogenesis in the life cycle of endothelial cells which, together with pericytes (supportive vascular smooth muscle cells), carry all of the genetic information necessary to form tubes, branches and entire capillary networks.
However, many human diseases (including solid tumors) are driven by persistently up-regulated angiogenesis [1]. In some non-malignant processes, such as pyogenic granuloma or keloid formation [2], angiogenesis is prolonged but still self-limited; however, this is not true of tumor angiogenesis which, once begun, continues indefinitely until the entire tumor is eradicated or the host dies. Without blood vessels, tumors cannot grow beyond a critical size (1–2 mm) or metastasize to another organ.
Angiogenesis is one of the most complex dynamic processes in biology, and is highly regulated by a balance of pro- and anti-angiogenic molecules. It is now widely accepted that the "angiogenic switch" is "off" when the effects of pro-angiogenic molecules is balanced by that of anti-angiogenic molecules, and "on" when the net balance is tipped in favor of angiogenesis [1,3]. Pro- and anti-angiogenic molecules can be secreted from cancer cells, endothelial cells, stromal cells, blood, and the extra-cellular matrix [4,5], the relative contributions of which are likely to change with tumor type and site, as well as with tumor growth, regression and relapse [1].
Although considerable advances have been made in our molecular and cellular knowledge of the promotion, mediation and inhibition of angiogenesis, very little is known about its underlying complex dynamics. Vasculature and more generally tubular organs develop in a wide variety of ways involving many cell processes [6-8].
In mathematical terms, angiogenesis is a non-linear dynamic system that is discontinuous in space and time, but advances through qualitatively different states. The word state defines the configuration pattern of the system at any given moment, and a dynamic system can be represented as a set of different states and a number of transitions from one state to another over a certain time interval [9,10].
At least seven critical steps have so far been identified in the sequence of angiogenic events on the basis of sprout formation: a) endothelial cells are activated by an angiogenic stimulus; b) the endothelial cells secrete proteases to degrade the basement membrane and extra-cellular matrix; c) a capillary sprout is formed as a result of directed endothelial cell migration, d) grows by means of cell mitoses and migration, and e) forms a lumen and a new basement membrane; f) two sprouts come together to form a capillary loop; and g) second-generation capillary sprouts begin to form [1,11,12] (Fig. 1).
The progression of these states generates a complex ramified structure that irregularly fills the surrounding environment (Fig. 2). The main feature of the newly generated vasculature is the structural diversity of the vessel sizes, shapes and connecting patterns.
Tumor vessels are structurally and functionally abnormal [1,3]: unlike normal vessels, they are highly disorganized, tortuous and dilated, and have uneven diameters, and excessive branching and shunts. This may be mainly due to the heterogeneous distribution of angiogenic regulators, such as vascular-endothelial growth factor (VEGF), basic fibroblastic growth factor (bFGF) and angiopoietin [5,13], leading to chaotic tumor blood flow, and hypoxic and acidic tumoral regions [5,14-16]. Moreover, although it is commonly believed that the endothelial cells making-up tumor vessels are genetically stable, diploid cells (and thus different from genetically unstable neoplastic cells), tumor vasculature seems to be much more unpredictable [17].
These conditions all reduce the effectiveness of treatments, modulate the production of pro- and anti-angiogenic molecules, and select a subset of more aggressive cancer cells with higher metastatic potential [1].
A large number of clinical trials of anti-angiogenic therapies are being conducted throughout the world, but investigators are still concerned about how to achieve the maximum benefit from them and how to monitor patient response. There are currently no markers of the net angiogenic activity of a tumor that can help investigators to design specific anti-angiogenic treatment strategies [5,18], but it is reasonable to resume that the quantification of various aspects of tumor vasculature may provide an indication of angiogenic activity.
One often-quantified element of tumor vasculature is microvessel density (MVD), which is used to allow a histological assessment of tumor angiogenesis. The results of studies carried out over the last decade have suggested the value of using tumor MVD as a prognostic index in a wide variety of solid cancers, and it has also recently been assumed that MVD may reveal the degree of angiogenic activity in a tumor. On the basis of these assumptions, the quantification of MVD is thought to be a surrogate marker of the efficacy of anti-angiogenic agents as well as a means of assessing which patients are good candidates for anti-angiogenic therapy. However, MVD has a number of substantial limitations, mainly due to the complex biology characterizing tumor vasculature [17], and the highly irregular geometry that the vascular system assumes in real space, which cannot be measured using the principles of Euclidean geometry because it is only capable of interpreting regular and smooth objects that are almost impossible to find in Nature.
However, quantitative descriptors of its geometrical complexity can be usefully abstracted from the fractal geometry introduced by Benoit Mandelbrot in 1975 [20,21]. We here discuss the surface fractal dimension (DS) as a quantitative index of the 2-D geometrical complexity of vascular networks and their behavior during computer-simulated changes in vessel density and distribution.
Geometrical properties of a vascular network
The human vascular system can be geometrically depicted as a complex fractal network of vessels that irregularly branch with a systematic reduction in their length and diameter [19].
Fractal objects are mainly characterized by four properties: a) the irregularity of their shape; b) the self-similarity of their structure; c) their non-integer or fractal dimension; and d) scaling, which means that the measured properties depends on the scale at which they are measured [22].
One particular feature of fractal objects is that the schemas defining them are continuously repeated at decreasing orders of magnitude, and so the form of their component parts is similar to that of the whole [20,21]: this property is called self-similarity. Unlike geometrical self-similarity, which only concerns mathematical fractal objects in which every smaller piece is an exact duplicate of the whole (e.g. Koch's snowflake curve, Sierpinski's triangle and Menger's sponge), statistical self-similarity concerns all complex anatomical systems, including tumor vasculature. The smaller pieces constituting anatomical entities are rarely identical copies of the whole, but more frequently "similar" to it and, in such systems, the statistical properties of the pieces are proportional to the statistical properties of the whole [23].
Dimension is a numerical attribute of an object that does not depend on its process of generation, and has been defined in two ways. The first is the topological or Euclidean dimension (Fig. 3), which assigns an integer to every point or set of points in Euclidean space (E): 0 to a point (defined as that which has no part); 1 to a straight line (defined as a length without thickness), 2 to a plane surface (defined as having length and thickness, but no depth); and 3 to three-dimensional figures (a volume defined by length, thickness and depth). The second was introduced by the mathematicians Felix Hausdorff and Abram S. Besicovitch, who attributed a real number to every natural object in E lying between the topological dimensions 0 and 3 (Fig. 3).
Benoit Mandelbrot uses the symbol Dγ to indicates the topological dimension, and the symbol D to indicate that of Hausdorff-Besicovitch (also called the fractal dimension). The Dγ and D of all Euclidean figures are coincident (Dγ = D), but this is not true of fractal objects in which D is always >Dγ.
As no anatomical entity corresponds to a regular Euclidean figure, their dimension is always expressed by a non-integer number falling between two integer topological dimensions. In our case (Fig. 2), the vascular network has a dimension lying between 2 (plane surface) and 3 (volume), and any two-dimensional section of a vascular system (as in the case of a histological section) has a dimension lying between 0 (the dimension of a single isolated point) and 2 when the sectioned vessels entirely fill a plane surface (Figs. 3 and 4).
Anatomical structures are also hierarchical systems that operate at different spatial and temporal scales, and different patterns can change, appear or disappear depending on the scale of magnification [22]. A fundamental characteristic is that the process operating at a given scale cannot be important at higher or lower scales [23].
The irregularity and self-similarity underlying scale changes are the main attributes of the architectural complexity of both normal and pathological biological entities [22-26]. In other words, the shape of a self-similar object does not change when the scale of measure changes because every part of it is similar to the original object; however, the magnitude and other geometrical parameters (e.g. the outline perimeter) of an irregular object differ when inspected at increasing resolutions that reveal an increasing number of details [25]. Over the last decade, accumulating experimental evidence has shown that the fractal patterns or self-similar structures of biological tissues can only be observed within the scaling window of an experimentally established measure of length ε1-ε2 (Fig. 4), within which experimental data sets follow a straight line with a slope (1-D): i.e. the fractal dimension remains invariant at different magnifications [20-27].
Methods
Computer-aided modeling of two-dimensional vascular tree complexity
We have developed a computer model to simulate the geometrical complexity of a histological two-dimensional section of a tumor vascular tree that automatically generates an unlimited number of images with a changeable density of vessels irregularly distributed on a planar surface.
In order to simplify the model, we considered all of the vessels as rounded, unconnected objects of equal magnitude (Fig. 5). As the parameters of a model must be as few as possible and it is necessary to reduce mathematical complexity [28-30], we included only two variables: a) the number of vessels; and b) their distribution in the surrounding environment. The vessel distribution patterns were randomly generated using different time-dependent seeds for random number function generation.
One thousand images were automatically generated for each vessel density (from five to 50 vessels, with the number being increased by five in each group), and their DS were estimated using the box-counting method [22].
DS was automatically estimated using the equation:
where ε is the side-length of the box, and N(ε) the smallest number of boxes of side ε required to completely contain the irregular object (Fig. 4).
As the zero limit cannot be applied to biological images, DS was estimated by means of the equation:
(2) DS = d
where d is the slope of the graph of log [N(ε)] against log (1/ε), in a fixed range of side-lengths (ε 1-ε 2) empirically evaluated by visualization [20-29].
Statistical analysis
All of the data are expressed as mean values ± standard deviation, and the results were analysed using the Statistica software package (StatSoft Inc. Tulsa, USA). Unvaried analysis was performed by means of the Student t as required for parametric variables. p values of less than 0.05 were considered statistically significant.
Results
The computer-aided simulations showed that different DS values can be obtained for images with the same vessel density (Fig. 6). As the only variable in these images is the vessel distribution pattern, DS depends on the irregular arrangement of the vessels in the surrounding environment. DS also significantly increased (p <0.05) when higher vessel densities were considered in the system (Fig. 6) because of the greater space filled by the vascular component (as shown in Fig. 3); the increased density of the vessels reduces the variability in their space-filling properties, and thus the standard deviation (Fig. 6).
Discussion and conclusions
One of the most important and distinctive characteristics of biological systems is the complexity of their shape (geometrical or spatial complexity) and functions (behavioral complexity). Complexity is a real quality of organized biological matter that is mainly manifested in the living world as diversity and organization. No two anatomical systems are exactly alike because of the enormous variability not only between the different members of a population, but also between the component parts of an organism. The word complexity has long been used descriptively in order to describe, for example, a large number of genes or cellular interconnections [33], but complexity can also reside in the structure of a system (i.e. an intricate architecture or the existence of many different component parts with varying interactions) or its non-linear functions (i.e. physiological rhythms are rarely strictly periodic but fluctuate irregularly over time) [34].
The vascular system is a complex network consisting of branched tubes of different sizes that are irregularly settled in the surrounding environment [6,7]. This geometrical characteristic highlights the complexity of its generating process in space and time, and greatly biases any quantitative method that tends to idealize it as a smooth and regular Euclidean object.
However, both normal and tumor vasculature can more properly be considered fractal objects because of their irregular shape (spatial conformation), self-similar structure, non-integer dimension and dependence on the scale of observation (scaling effect) [19,35-37].
We here discuss the estimate of DS as a quantitative index of the 2-D spatial complexity of the vascular tree, in order to provide a closer-to-reality measure of this complex anatomical entity (Figs. 3 and 4).
The theory underlying DS was abstracted from fractal geometry, which is also called the geometry of irregularity [20,21]. The concept of spatial conformation has played a fundamental role in the study of biological macromolecules in chemistry (particularly biochemistry) since the early 1950s. However, it has only been introduced in the science of morphology as theoretical morphology, which studies extant organismal forms (complex structures of interdependent and subordinate elements whose relationships and properties are largely determined by their function in the whole) as a subset of the range of theoretically possible morphologies [32].
The significance of DS also comes from the fact that, like any other complex biological system, the vascular tree cannot be correctly quantified by measuring its individual properties (i.e. micro-vessel density, MVD). DS is a parameter that depends on: a) the number of vessels; b) the spatial relationships between the vascular components; and c) the interactions between the vascular components and the surrounding environment. In other words, its estimate is "ecologically" important because it provides a quantitative index of the "habitat structure".
As computer models are crucial for scientific procedures, and the modeling process itself represents the hypothetical-deductive approach in science [30-32], we developed a simple computer-aided model capable of generating an unlimited number of 2-D images of a simulated vascular network. The model was simplified by using a minimum amount of mathematical complexity and only two variables: the number of vessels and their pattern of distribution. A total of 10,000 images showing a different number of unconnected vessels irregularly distributed on a planar surface were automatically generated (Fig. 5) and, interestingly, it was found that DS increased with the number of vessels making up the system (Fig. 6); furthermore, its value changed when the same number of vessels were differently distributed in the surrounding environment.
In other words, it is plausible that an equal number of vessels may have different space-filling properties depending on their distribution pattern. These results suggest the usefulness of this model when comparing real vasculature configurations in order to explore the morphological variability that can be produced in nature, as it is now well known that aberrant vascular architectures in tumors may affect the uniform delivery of specific drugs to all cancer cells [15].
The model also suggests that:
a) Ds can be an estimate of the 2-D geometrical complexity of the vascular system. As 2-D vascular complexity depends on the number of vessels and their distribution pattern, the use of MVD quantification alone to measure the angiogenic dependence of a tumor is strongly biased because the number of vessels does not reflect the number of tumor cells that can be supported by a vessel. Moreover the metabolic needs of cancer cells vary with the tissue of origin and change with tumor progression [18].
b) DS depends on the degree of vessel contiguity and continuity. These two geometrical properties determine what is called the intercapillary distance, and are not only involved in the spatial complexity of tumor vasculature, but also reflect the inviolable demand of a growing tumor for sufficient levels of nutrition and oxygen exchange. Inter-capillary distances are locally defined by the net balance between pro- and anti-angiogenic molecules in each microtissue region, as well as by non-angiogenic factors such as the oxygen and nutrient consumption rates of tumor cells. In normal tissue, vessel density fairly accurately reflects cell metabolic demands because evolutionary pressures have led to close and efficient coupling between vascular supply and metabolic needs. In tumors, the close coupling between vascular density and oxygen or nutrient consumption (i.e. the environment) may be loosened [18], thus altering not only the number of vessels but also the whole vascular architecture [15,38].
c) DS falls between 0 (corresponding to the Euclidean dimension of a point) and 2 (the dimension of a plane). The more DS tends towards 2, the more the analyzed vascular configuration tends to fill a 2-D space and the greater its geometrical complexity.
In conclusion, the present study indicates that the complex geometry of tumor vasculature and its well-known biological characteristics [18] mean that vascular network cannot be measured on the basis of MVD estimates alone. These findings also support the findings of various authors who have shown the uselessness of MVD as a predictor of anti-angiogenic treatment efficacy or for stratifying patients in therapeutic trials [14,39-41].
Scientific knowledge develops through the evolution of new concepts, and this process is usually driven by new methodologies that provide previously unavailable observation. The potential broad applicability of the proposed quantitative index makes it possible to explore the range of the morphological variability of vasculature that can be produced in nature, thus increasing its diagnostic importance in cancer research.
Abbreviations
Ds, Surface fractal dimension; 2-D, two-dimensional; VEGF, Vascular-endothelial growth factor; bFGF, basic fibroblastic growth factor; MVD, microvessel density.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
FG conceived, coordinated and designed the study and drafted the manuscript; CR, PC, BF, EEF, EC, MCI participated in designing the study and drafting 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:
Figures and Tables
Figure 1 Angiogenesis is a complex dynamic process that evolves through different states and a number of transitions between two successive states. At least seven critical steps have so far been identified in the sequence of angiogenic events on the basis of sprout formation.
Figure 2 The space-filling property of the vascular system is quantified by the fractal dimension (D), which falls between two topological integer dimensions. A. A Euclidean three-dimensional space (i.e. a cube) can contain a branching structure (i.e. the vascular system) without this entirely filling its internal space. B. Two-dimensional sectioning of the vascular network makes it possible to identify a variable number of vessels depending on the geometrical complexity of the system at any particular level of sectioning. C. The geometrical complexity of a 2-D section (s1, s2, s3) of the vascular network depends in the number of sectioned vessels and their distribution pattern.
Figure 3 Fractal dimensioning of the 2-D complexity of a vascular network. The figure shows four idealized cross-sectioned vascular patterns that not only have a different number of vessels, but also clearly different distributions: the geometrical complexity arising from these two variables determines the value of the surface fractal dimension.
Figure 4 Computer-aided estimate of the surface fractal dimension (Ds) of a vascular network in 2-D biopsy sections. A. Hepatocellular carcinoma section stained with antibodies raised against CD31 (Dako, Milan, Italy) that specifically react with vessels. B. Image segmentation: immunopositive vessels are specifically selected on the basis of the similarity of the color of adjacent pixels. C. Determination of Ds using the box-counting algorithm. Briefly, the method counts the number of boxes of length ε required to cover the object being measured, indicated as N(ε). D. Prototypical curve obtainable using the box-counting method that highlights the so-called fractal windows ranged by box size ε1 and ε2, and represents the appropriate region in which to estimate the dimension. Box sizes of more than ε2 approach the size of the image until one box covers it completely, at which point N(ε) = 1 and the slope = 0. Box sizes smaller than ε1 approach a single pixel or the resolution of the image: in this region, box counting simply gives the area of the image.
Figure 5 Computer-aided procedure used to quantify the surface fractal dimension of a simulated two-dimensional image of the vascular system. Prototypical 2-D simulated microscopy images of the vascular system with different vessel numbers and distribution were automatically generated, and their Ds was determined.
Figure 6 The behavior of Ds during a simulated increase in vessel density. The graph shows that different Dsvalues can be obtained for images with the same vessel density. As the only variable in these images is their distribution pattern, Ds depends on the irregular arrangement of the vessels in the surrounding environment (note the standard deviation of each cell density group). Ds also increases significantly when a higher vessel density is introduced into the system because of the greater space filled by the vascular component. The increase in vessel density reduces the variability of their space-filling properties, thus reducing the standard deviation.
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| 15701176 | PMC549205 | CC BY | 2021-01-04 16:03:07 | no | BMC Cancer. 2005 Feb 8; 5:14 | utf-8 | BMC Cancer | 2,005 | 10.1186/1471-2407-5-14 | oa_comm |
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BMC BiolBMC Biology1741-7007BioMed Central London 1741-7007-3-21567989010.1186/1741-7007-3-2Research ArticleComparative analysis of protein coding sequences from human, mouse and the domesticated pig Jørgensen Frank Grønlund [email protected] Asger [email protected]øj Henrik [email protected] Christian [email protected] Merete [email protected] Mikkel Heide [email protected] Department of Ecology and Genetics, University of Aarhus, Aarhus C, Denmark2 Bioinformatics Research Center (BiRC), University of Aarhus, Arhus C, Denmark3 Department of Genetics and Biotechnology, Danish Institute of Agricultural Sciences, Tjele, Denmark4 Department of Animal Science and Animal Health, KVL, Frederiksberg C, Denmark2005 28 1 2005 3 2 2 5 11 2004 28 1 2005 Copyright © 2005 Jørgensen 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 abundant sequence data from key model organisms has made large scale studies of molecular evolution an exciting possibility. Here we use full length cDNA alignments comprising more than 700,000 nucleotides from human, mouse, pig and the Japanese pufferfish Fugu rubrices in order to investigate 1) the relationships between three major lineages of mammals: rodents, artiodactyls and primates, and 2) the rate of evolution and the occurrence of positive Darwinian selection using codon based models of sequence evolution.
Results
We provide evidence that the evolutionary splits among primates, rodents and artiodactyls happened shortly after each other, with most gene trees favouring a topology with rodents as outgroup to primates and artiodactyls. Using an unrooted topology of the three mammalian species we show that since their diversification, the pig and mouse lineages have on average experienced 1.44 and 2.86 times as many synonymous substitutions as humans, respectively, whereas the rates of non-synonymous substitutions are more similar. The analysis shows the highest average dN/dS ratio in the human lineage, followed by the pig and then the mouse lineages. Using codon based models we detect signals of positive Darwinian selection in approximately 5.3%, 4.9% and 6.0% of the genes on the human, pig and mouse lineages respectively. Approximately 16.8% of all the genes studied here are not currently annotated as functional genes in humans. Our analyses indicate that a large fraction of these genes may have lost their function quite recently or may still be functional genes in some or all of the three mammalian species.
Conclusions
We present a comparative analysis of protein coding genes from three major mammalian lineages. Our study demonstrates the usefulness of codon-based likelihood models in detecting selection and it illustrates the value of sequencing organisms at different phylogenetic distances for comparative studies.
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Background
Large scale sequencing projects of many different species allow us to investigate phylogenetic issues in much more detail and to identify whether certain genes have had an extraordinary evolution in one or more species and thus gain insight into the actions of natural selection. Despite the sequencing of an increasing number of mammalian genomes and the implementation of more sophisticated evolutionary models using maximum likelihood and Bayesian methodology, the branching order within the mammalian phylum is still not completely resolved. The main reason for this uncertainty is that the diversification of these orders occurred over a short period of time, making the inference of branching order a difficult problem. One of the highly debated issues concerns the relative order of branching among primates, artiodactyls and rodents [1-9]. Here, the Japanese pufferfish Fugu rubrices is used as an outgroup to estimate the branching order of the three species relative to each other.
Codon based models [10,11] allow for powerful analysis of protein coding nucleotide sequences. Evolutionary hypotheses may be tested using likelihood ratio tests between nested models. For an introduction to the practical use of these models see [12], for a more thorough review of the methodology see [13]. The parameter of primary interest is the ratio of nonsynonymous to synonymous substitutions (ω), also known as the dN/dS ratio. The dN/dS ratio measures the relative importance of evolutionary forces that have shaped a particular protein. A dN/dS ratio significantly larger than one strongly suggests that positive Darwinian selection has acted on the protein. Different extensions to the basic codon model exist, and these can be divided into three main categories: (1) Lineage-specific models that average ω over sites but differentiate between lineages [14]; (2) site-specific models that average ω over lineages but differentiate over sites [15]; (3) branch-site specific models that combine the two previous extensions by allowing ω to vary over sites in all background lineages, but allow for a different value of ω in one or more pre-specified lineages [16]. The models we use here and their relationships are shown in Table 1. Numerous studies have shown the ability of the site-specific and the branch-site specific models to detect positive selection in cases where the branch-specific models did not, indicating that averaging over sites is generally a more serious problem than averaging over lineages and that in many cases using a branch-site specific model increases the power to detect positive selection [17-22].
In a recent study of cDNA trios of human, mouse and chimpanzee a codon based branch-site specific model was used to search for human genes that have undergone positive selection since our divergence from other primates [23]. Here, a similar search is done on a different phylogenetic level using a collection of porcine genes. While the study by Clark and colleagues concentrates on the divergence between humans and chimpanzees (branch a in Figure 1) our study searches for genes that have undergone positive selection since the divergence of primates, artiodactyls and rodents. Several recent studies have shown that some of the branch-site specific models under certain conditions might have a high false positive rate when used to detect positively selected sites [24,25]. This problem has recently been addressed by Yang and colleagues with the implementation of a new Bayes empirical Bayes (BEB) method for predicting positively selected sites. This new method is much better at avoiding false positives while still retaining a high sensitivity (Z. Yang, pers. comm.). Here we use the new and improved BEB version of the branch-site specific model originally presented in [23] to detect genes that may have been influenced by positive selection.
Results
The distribution of sequence lengths of the 1120 three-species alignments is shown in Figure 2. Since the full length cDNAs were assembled from random ESTs, there is a bias towards assembling relatively short genes. Therefore the subset of genes used in this analysis is not a random sample from the pig genome. This decreases the power of our evolutionary tests, since short alignments have less power when testing for positive selection, but we do not anticipate any other systematic bias in our results.
Mammalian phylogeny
The relative branching order of the three mammalian species was investigated with the individual genes as well as with a concatenated super gene. Using the empirical amino acid substitution model of Whelan and Goldman [26] we maximized the likelihood under the three conflicting topologies shown in Figure 3a–c. In 123 of the 988 alignments all amino acids are identical in the three mammalian species giving us no information to discriminate between the three topologies. Of the remaining 865 alignments 245 favour topology A, while 440 and 180 favour topology B and topology C respectively. A concatenated super gene of all 988 alignments clearly favoured topology B over topology A, which again has a higher likelihood than topology C, consistent with the results from the individual gene comparisons (Table 2.).
We used the baseml program of PAML to compare the three topologies in a nucleotide based framework. Different nucleotide based substitution models were used to maximize the likelihood on the three topologies for each of the three codon positions separately. The results of using different models of nucleotide evolution were highly similar so here we only discuss the results obtained with the HKY85 model [27]. The results based on the third codon position shows that Fugu is too distantly related to the three mammals to be informative in placement of the root of the mammals (results not shown). The first and second codon positions do not show such saturation and should therefore be useful in comparing the three topologies. Consistent with the results based on the amino acid substitution model we see that topology B is favoured in most genes, followed by topology A and topology C, respectively. The actual numbers from the second codon position are 215, 386 and 179 in favour of topology A, topology B and topology C respectively and 208 alignments are uninformative. The corresponding numbers for the first codon position are 215, 545, 175 and 53 (Table 2.).
The internal branch is rather short in all cases. Therefore in the remaining analyses we treat the mouse, human, pig split as a trifurcation. Depending on which topology is actually the right one, the only bias introduced by treating the topology as a star tree, as shown in Figure 3d, is a minor overestimation of the branch length of the species that actually roots the other two.
The rates of evolution
The three-species alignments were used to estimate the synonymous and nonsynonymous substitution rates of the three branches under the free ratio model, see Table 3. Figure 4a–f shows the distribution of the synonymous and nonsynonymous branch lengths for each gene in all three species. The synonymous rates are significantly different between the three species. The average synonymous substitution rate, estimated using the concatenated super gene, is approximately 2.86 times larger in mouse compared to pig, and approximately 1.44 times larger in pig than in human. The nonsynonymous rates are more similar among the three species. The corresponding values for the nonsynonymous rates are 2.08 and 1.17 respectively. Table 3 shows the mean, median and variance of both the synonymous and nonsynonymous rate distributions as well as the values obtained from the concatenated super gene. The average values from the individual genes are highly similar to the results obtained from the concatenated super gene.
Positive Darwinian selection
The dN/dS ratios on the three different lineages were estimated under the free ratio model (Figure 4g–i). Most genes in all three species have an average dN/dS ratio very close to zero with the average dN/dS ratio higher in human than in pig, which again is higher than in the mouse lineage.
The one ratio model averages over sites and lineages, which makes this an extremely conservative method of detecting positive selection. Only four of the 1120 three-species alignments have an average dN/dS ratio larger than one, see Table 4, and of those only one is significantly larger than one (XM_165930). The free ratio model allows each lineage to have its own dN/dS ratio. This model has slightly more power than the one ratio model due to its ability to find lineage specific signals. The likelihood ratio test (LRT) of these two models should not be considered as a stringent test for positive selection, but more as a test for different selective forces among lineages. The LRT shows that 154 genes have significantly different dN/dS ratios among lineages at the 5% significance level, 73 at 1% and 41 at the 0.1% level of significance. Table 5 shows the 24 genes that have a dN/dS ratio larger than one in one or more lineages as well as the result from each gene of a LRT that tests whether the estimated value of ω is significantly larger than one. As with the one ratio model only one gene shows a result significantly larger than one. The gene is the same one as reported with the one ratio model (XM_165930) and the lineage with a dN/dS ratio significantly larger than one is the lineage leading to pig.
Several studies have shown that averaging over sites is more conservative when searching for positive selection than is averaging over lineages. The branch-site specific model A and model B [16] were originally designed to search for genes where only a small fraction of codons in a specific foreground lineage has evolved under positive selection. Several studies have shown that the original models are prone to predicting false positives under certain conditions, and one should therefore be very careful drawing conclusions from studies based on those models. Here we use a new and improved version of a branch-site model developed for the analyses of human, chimpanzee and mouse gene trios [23]. The new model we use here is implemented in PAML v. 3.14 and uses the new and improved Bayes empirical Bayes approach to predict which sites have evolved under positive selection in the foreground lineage. Likelihood ratio tests were done separately with human, pig and mouse as the predefined foreground lineage. The LRT when contrasting the neutral model with the branch-site model has two degrees of freedom. By using the human lineage as foreground lineage we find 288 genes that show signals of positive selection (dN/dS in the foreground lineage is larger than one). In 58 of those genes the branch-site model fits the data significantly better than the neutral model at the 5% significance level. We find 34 and 15 genes at the 0.01 and 0.001 levels of significance respectively. The corresponding numbers of genes using pig as foreground lineage are 314, 55(0.05), 23(0.01) and 5(0.001). Using mouse as foreground lineage results in 352, 67(0.05), 25(0.01) and 4(0.001). The genes found to be under positive selection in any of the three species with a LRT significance level of 0.001 are shown in Table 6.
The molecular function of the genes predicted to be under positive selection was determined using the Panther server [28] and the NCBI server using the newest build of the human genome. Both annotation servers are updated on a regular basis when new information becomes available. During the course of this study the annotation of several genes changed. Of our 1120 alignments 188 are currently not annotated as functional genes indicating that they might possibly be pseudogenes in human; see the Discussion for more details on this subject. The proportion of genes that we report to have undergone positive selection in the human lineage at the 5% level of significance can therefore be viewed as either 58/1120 ~5.2% or 43/931 ~4.6%, indicating that possible pseudogenes are only slightly overrepresented in the genes predicted to have undergone adaptive evolution. The genes predicted to have been under positive selection in the pig and mouse lineage show a similar trend.
Several different models have been developed that allow for heterogeneity of ω over sites in an alignment. We used the M4 model [15] which allows each codon to fall into one of 5 categories corresponding to ω equal to 0, 1/3, 2/3, 1 and 3. The first category represents the fraction of codons that have evolved under strong purifying selection allowing no nonsynonymous changes to occur. The next two categories represent different intensities of purifying selection. The category with ω = 1 represents neutrally evolving sites, while the last category with ω = 3 represents codons that have evolved under positive selection. The results of this analysis on the concatenated super gene can be seen in Table 7. Only 1.6 % of all codons appear to have evolved under positive selection, and approximately 69 % have been under strong functional constraints.
Codon usage bias
The concatenated super gene was also used to investigate the patterns of codon usage in the three species; the results of this investigation are summarized in Table 8. A test for equal codon distributions is rejected in all three pair wise comparisons (P < 0.0001, 60 d.f.). Using nucleotide frequencies to estimate the codon equilibrium frequencies fits the data poorly, so does the equal frequency model (Table 9). For a description of the codon equilibrium frequency models, see the Methods. The F3 × 4 model was extended with one extra parameter that accounts for CpG avoidance at the second and third codon position. Since all changes in the second position of a codon are nonsynonymous, the frequency of NCG codons is expected to be lower than under the F3 × 4 model. The extra parameter introduced improves the log likelihood by approximately 1236 units (~44%). This can be compared to the approximately 321 units per extra parameter introduced when going from the F3 × 4 model to the codon table model. When analysing the super gene it is still better to use the actual codon frequencies, but with individual genes the number of codons can sometimes be so small that the use of actual codon counts can be problematic. We also implemented a similar model that incorporated the avoidance of CG in first and second position by introducing an additional parameter but this does not improve the fit of the model significantly (results not shown). This is probably caused by the fact that all four codons with CG in the first and second position code for the same amino acid, Arginine. Arginine has six different codons and the two codons without a CG pair (AGA and AGG) are generally favoured over the other four (Table 8), but this tendency is apparently accounted for when modelling nucleotide frequencies at the three codon positions, so here we only present the model that accounts for CpG avoidance at the second and third codon position. Table 9 shows that the choice of codon equilibrium frequency model has detectable effects on the parameter estimates. Most striking is the apparent overestimation of the transition/transversion ratio and the dN/dS ratio when the model is less parameter-rich.
Discussion
The phylogeny of the early mammalian radiation has been extensively debated over the last two decades. The classical view based on fossil evidence states that all major orders of placental mammals first appear right after the Cretaceous-Tertiary (KT) boundary approximately 65 million years ago [29]. This sudden appearance of all major placental orders is known as the mammalian radiation. With the use of molecular data this late radiation has been challenged and it is now widely accepted that the radiation of the placental orders probably occurred many million years before the KT boundary [29-31]. Molecular data have also been used to investigate the relative branching orders of many of the larger clades of placental mammals [1-7,9,30]. One of the issues that have been debated extensively is the placement of Rodentia in the placental tree. Some studies favour a basal placement of the rodents [1,3-5,32,33] while other studies favour a sister relationship between primates and rodents [6-8]. Recently strong evidence based on insertions, deletions and ancient transposable elements in favour of a sister relationship of primates and rodents has been reported [2,34].
The incongruence of single gene phylogenies was investigated in a recent study of eight yeast species [35]. The phylogeny commonly believed to be correct is completely resolved when concatenating 20 or more randomly chosen genes to form a super gene. A concatenated multi gene approach was also shown to resolve single gene incongruences in a recent study on green algae [36]. Here we use 988 full cDNA alignments comprising 672,918 nucleotides to investigate the branching order of the three mammalian species. We present results based on both single gene phylogenies and a concatenated super gene. All genes including the concatenated super gene were analysed with both nucleotide and amino acid based substitution models. All methods favour a primate-artiodactyls clade with rodents as an outgroup but with a relatively short internal mammalian branch, indicating that the mammalian radiation happened within a short period of time. The different methods used in this study have very different assumptions but they all show the same general results. The HKY85 model takes into account differences in nucleotide frequencies and transition/transversion biases and allows for differences in substitution rates among the lineages. However, it is still possible that complexities unaccounted for such as non-stationarity and irreversibility of the substitution process have created biases that lead to long-branch attraction of Fugu and Mouse and an erroneous conclusion. Furthermore, the incongruence between our analysis and many recent studies is also affected by the following. (1) The choice of outgroup; bony fishes are believed to have diverged approximately 450 million years ago [31], making saturation effects in synonymous sites a real problem. We are therefore forced to only consider nonsynonymous sites or amino acid replacements in the phylogenetic analyses. The recently completed genome sequence of the chicken (Gallus gallus) shows that the average value of dS between human and chicken genes is approximately 1.66 [37], which indicates that many genes may still be too distantly related for synonymous sites to avoid problems with saturation. A marsupial species would provide a much better outgroup when available [3,32]. (2) Taxon sampling; by only using three species the variance of the parameter estimates can be quite high and the power to discriminate between two conflicting topologies quite low. The sequencing of more species will lessen this problem. (3) Overly simplistic evolutionary models; here we use only nucleotide and amino acid based models. If a more closely related outgroup was available the use of more complex codon based models could be beneficial in resolving the apparent conflict. Several extensions have been made to the codon models during the past few years. One obvious extension to the codon models is a model that incorporates CG avoidance within and over codon boundaries. This will clearly improve the fit of the data to the model and therefore give more accurate parameter estimates. Including context dependencies over codon boundaries and information about protein structure have also been shown to increase the fit of the models to protein coding data and therefore should result in better parameter estimates [38,39]. (4) Gene trees and species trees can be different; the split between the three groups probably occurred within a very short period of time, allowing for the possibility that different genes actually have different phylogenies due to ancient polymorphisms at the time of the speciation. Using even larger number of genes and a sufficiently sophisticated model should lessen this problem [35,36].
The rate of synonymous substitution was estimated to be almost three times higher in rodents than in other mammals, in agreement with previous investigations that also showed an elevated rate in rodents [40-42]. This has historically often been explained by a generation time effect. Species that have short generation times experience more generations in the time span we consider and consequently they will experience more neutral substitutions over time. The fact that the pig, which has a generation time intermediate between mouse and humans, has an intermediate rate of synonymous substitutions, seems to agree with this theory. For a more thorough discussion of the generation time hypothesis in mammals see [43]. The nearly neutral theory of molecular evolution predicts that the generation time effect should be smaller for non-synonymous substitutions [42,44,45]. The simple argument is that animals with short generation times such as rodents often have a very large effective population size. In a population with a large effective population size slightly deleterious mutations will be removed from the gene pool more effectively than in a population with a small effective population size, where genetic drift will reduce the efficiency of natural selection. Figure 4g–h shows the distribution of the dN/dS ratio in the three lineages. The average dN/dS ratio is highest in humans suggesting a small effective population size, while it is smallest in mouse suggesting a larger effective population size.
Previous studies of the occurrence of positive selection based on pair wise comparisons have revealed a very low occurrence of positive selection. In a study of 3595 alignments only 17 genes showed evidence of positive selection [46]. The branch specific models used here only find one gene where the dN/dS ratio is significantly larger than one. The gene reported is XM_165930. XM_165930 was originally annotated as being similar to cold shock domain protein A, but it has recently been removed from Genbank as a result of standard genome annotation processes.
Codon based branch-site models similar to the ones used here were used in a paper based on a three way comparison among chimpanzees, humans and mice [23]. They report that approximately 1.6 % of all the genes studied have been undergoing positive selection in the lineage leading to modern humans. Using a similar criterion our study indicates that approximately 3.0 % of the genes studied have been undergoing positive selection on the lineage leading to humans; the corresponding numbers for pig and mouse are 2.0 % and 2.2 % respectively. When comparing these two studies it is important to consider the following three things: (1) the relatively short average length of the genes studied here decreases the power of the models to detect positive selection; (2) the use of the new BEB method for detecting positively selected sites should reduce the number of false positives, making our estimates more conservative and more accurate; (3) our study deals with a completely different phylogenetic level, covering a much longer time span than the study by Clark and colleagues.
The multiple testing and the small number of taxa used in a study like this imply that the results presented should not be taken as conclusive evidence for positive selection, but more as an approach to searching among the thousands of genes to look for genes that may have evolved in a biologically interesting manner. Comparative approaches such as the one we use here can only be a first step towards showing that positive Darwinian selection may be a key part in the evolution of many different gene families. Further experimental and computational analyses must then be used to investigate the suggested candidates more thoroughly.
During the course of our investigation a large fraction of the genes were re-annotated as putative pseudogenes: 188/1120 ~16.8%. However, all these genes have uninterrupted reading frames in all three species; only a tiny fraction of all codons seems to have evolved in a neutral-like fashion (ω~1), and the distributions of the synonymous as well as the nonsynonymous rates of these putative pseudogenes are almost identical to the distributions of the remaining genes (results not shown). The only difference is a slight increase in the dN/dS ratio in the human lineage, which is actually due to a few genes that experience an unusually high dN/dS ratio. Omitting these genes from the analysis removes the observed differences completely. Thus, if all these genes are indeed pseudogenes in human, the loss of function must have occurred quite recently and they may not be pseudogenes in pig and mouse.
Conclusions
The collection of a large set of pig cDNA sequences has enabled us to study long term evolutionary trends in mammalian genes. Our results indicate that the codon models are able to detect evolutionary signals indicating adaptive evolution in several genes. Our phylogenetic investigation of the primate, rodent, artiodactyl split disagree with most recent findings in favouring a primate, artiodactyl clade with rodents as an outgroup. Our study indicates that several genes that are not classified as genes in the most recent human annotation might after all be real genes; or at least they have become pseudogenes very recently, and the orthologous genes in mouse and pig might still be functional. This shows the potential of comparative methods in identifying functional regions of the genome.
Methods
cDNA alignment
Complete cDNA from the domesticated pig Sus scrofa was assembled at the Danish Institute of Agricultural Sciences (DIAS) from cDNA libraries from 100 different tissues constructed at DIAS and the Royal Veterinary and Agricultural University in the following way. Total RNA was purified from selected tissues using Rneasy (Qiagen) or Tri ReagentR and poly(A+) mRNA was selected using Oligotex (Qiagene) or PolyATract (Promega). Directional cloneable cDNA was synthezised from Poly(A+) mRNA using the cDNA Synthesis Kit (Stratagene) and was ligated into Eco RI/Xho I digested pTrueBlue (GenomicsOne) or pBluescript (Stratagene) followed by electrotransformation into E. coli XL1-Blue MRF' (Stratagene). 5'-EST sequencing was performed using standard protocols (Applied Biosystem). The sequences were trimmed to the longest open reading frame and the termination codons were removed.
Homologues sequences from human, mouse and the Japanese pufferfish Fugu rubrices were obtained with the blastall program with default parameters; the E-score was set to 10-8. We constructed two different datasets, one with and one without Fugu rubrices. Individual alignments were made using ClustalW version 1.83 with default parameters [47]. We kept the pig reading frame intact in the alignments by removing any columns where the alignment gave rise to gaps in the pig sequence. Alignments that resulted in premature stop codons, or were shorter than 30 codons, were removed. We used the one ratio model to estimate the total branch length of the tree as well as the synonymous branch lengths. These distributions were used to detect peculiar genes where one or more sequences might not be a true orthologue, and all outliers were thereafter removed from the dataset. This analysis gave 1120 alignments of mouse, human and pig, and of these 988 also included Fugu. The 1120 original cDNAs from Sus scrofa have been deposited in Genbank with the following accession numbers: AY609387-AY610506.
Phylogeny and rates of evolution
Nine hundred and eighty-eight four-species alignments were concatenated into a super gene. The three topologies were compared using the super gene as well as each individual gene. Both nonsynonymous nucleotide substitutions and amino acid substitutions were investigated with PAML v. 3.14 [48]. The nonsynonymous substitutions were represented by the first and second codon positions of all codons, and the three different topologies were investigated with baseml using the HKY85[27] model (model = 4) of nucleotide substitutions. The likelihood was then maximized under the three different topologies using all the individual genes as well the concatenated super gene. The codeml program with the codons translated to amino acids (seqtype = 3) were also used to investigate the three topologies. We used different models of amino acid evolution to maximize the likelihood under the three topologies and since the results were highly similar we only present the results from the empirical method of Whelan and Goldman (model = 2, aaratefile = wag.dat)[26].
Using the 1120 three species alignments, the synonymous and nonsynonymous rates of evolution were estimated with the codeml program (seqtype = 1) using the free ratio model (model = 2) with the transition/transversion ratio estimated from the data (fix_kappa = 0).
Investigation of selection
The different tests for positive Darwinian selection are all based on extensions of the basic codon based likelihood model [11]. Likelihood ratio tests (LRTs) were used to compare nested models where one allows for positive selection and the other does not. The probability that a codon i substitutes into another codon j during the time interval t is determined by the rate matrix Q = (qij) with entries
for i ≠ j, with corresponding substitution probability matrix given by exp(Qt). Here πj is the equilibrium codon frequency of codon j, κ is the transition/transversion ratio and ω is the dN/dS ratio. All parameters are estimated independently for each gene. The star topology of the three species is used to estimate the branch lengths (τhuman, τpig, τmouse) for synonymous and non-synonymous substitutions.
Positive selection was tested in two different ways. Test 1 averages over sites but differentiates among lineages. The LRT compares the free ratio model where all three lineages have a different value of ω estimated from the data with the one ratio model where all three lineages share a common value of ω [14]. We note that this test is more a test of variable dN/dS ratios among lineages than a test for positive selection. The free ratio model has three parameters for ω and the one ratio model only one. The LRT statistic is calculated as 2 times the differences in maximum log likelihood and is asymptotically distributed as a χ2 distribution with 2 degrees of freedom. The genes found in one or more lineages evolving with a dN/dS ratio > 1 are compared to a nested model where the dN/dS ratio is fixed at 1 in the lineages shown to have a dN/dS ratio larger than one to see whether the result can be attributed to natural selection or just relaxation of selective pressures.
Test 2 is based on a new and improved version of the branch-site method presented in [23]. We will refer to this model as model A. The LRT is based on a comparison of the neutral model and model A. The neutral model assumes two categories of sites, a proportion p1 of sites where ω1 are estimated from the data and is forced to lie between 0 and 1, and a proportion p2 of neutrally evolving sites where ω1 = 1 (p1 + p2 = 1). Model A furthermore allows a pre-specified branch to have a proportion of sites that evolve with a different value of ω estimated from the data. This value cannot be smaller than 1. The LRT follows a χ2 distribution with 2 degrees of freedom. If the value of ω in the foreground lineage is estimated to be equal to one the model collapses to the neutral model.
PAML v. 3.14 [48] was used to estimate likelihood and parameters under each model. Codon equilibrium frequencies can be estimated from data using either simple proportions in the full data set (the CT model with 60 parameters), assuming equal frequencies (Fequal model), multiplying overall counts of nucleotide frequencies (F1 × 4 model, 3 parameters) or counts of nucleotide frequencies for each codon position (F3 × 4 model, 9 parameters). The codon table (CT) was used for analysis of the concatenated super gene and the F3 × 4 model was used on the individual genes.
CpG Extension of the codon models
A simple extension of the F3 × 4 codon equilibrium frequency model can incorporate CpG avoidance by adding an extra parameter that penalizes a C followed by a G in the second and third codon position. The new model is parameterised as follows
Here πi11 represents the frequency of nucleotide i1, at codon position 1, and ψ(0 < ψ < 1) is a CpG penalizing parameter. The scaling factor cψ ensures that the codon frequencies sum to one.
Authors' contributions
FGJ carried out the analyses and was the primary writer of the text. AH and FGJ together implemented some of the analysis tools. FGJ, AH and MHS together developed the ideas and discussed the interpretation of the results. MF and CB gathered the EST data used. HHJ assembled the cDNAs and carried out Blast searches. All authors read and approved the final manuscript.
Acknowledgments
We would like to thank Andrew Clark, Rasmus Nielsen, Nick Goldman, Thomas Bataillon, Ole Fredslund Christensen, and two anonymous reviewers for many valuable comments on previous versions of this manuscript.
We acknowledge the Sino-Danish Pig Genome Sequencing Consortium that has generated the pig data used. The data are part of a much larger data set of one million ESTs, which is under publication.
The Sino-Danish Pig Genome Consortium consists of The Danish Veterinary and Agricultural University (KVL), Denmark, the Danish Institute of Agricultural Sciences (DIAS), Denmark, and the Beijing Genomics Institute/James D. Watson Institute of Genome Sciences (BGI/WIGS), China, in collaboration with Institute of Human Genetics, University of Aarhus, Denmark.
In particular we acknowledge the construction of cDNA libraries by Susanna Cirera with the help of Milena Sawera, Trine Green and Bente Juul Nielsen at KVL as well as Jakob Hedegaard with the help of Lone Bruhn Madsen, Bo Thomsen, Xuegang Wang and Miao Zhu at DIAS and Lin Li and Bin Liu at BGI/WIGS.
Figures and Tables
Figure 1 Phylogenetic tree of key mammalian species. A schematic drawing showing the topologies considered in our study compared to a recent study on human, chimpanzee and mouse trios [23]. Branch a shows the branch considered in the study by Clark et al (2003) while branch a+b represents the evolutionary time scale studied here.
Figure 2 Distribution of sequence alignment lengths. Histogram showing the distribution of sequence lengths in the three species alignments.
Figure 3 Conflicting mammalian phylogenies. A schematic drawing of the three conflicting bifurcating topologies (a-c) as well as a multifurcating alternative (d). The divergence times shown in (a) are million years from present [31].
Figure 4 Evolutionary rates. Histograms of key parameters in the codon models. (a-c) The rate of synonymous substitutions per synonymous site (dS) in the pig, human and mouse lineage respectively. (d-f) The rate of nonsynonymous substitutions per nonsynonymous site (dN) in the pig, human and mouse lineage respectively. (g-h) The ratio of nonsynonymous substitutions to synonymous substitutions (dN/dS ratio) in the pig, human and mouse lineage respectively. The horizontal line represents the mean of the distributions.
Table 1 Overview of the codon models used in the analyses.
Model NP Parameters
Lineage specific models
M0: One Ratio 5 κ, τpig, τhuman, τmouse, ω
M1a: Free Ratio 7 κ, τpig, τhuman, τmouse, ωpig, ωhuman, ωmouse
Site specific models
M1b: Neutral 6 κ, τpig, τhuman, τmouse, p0 (p0 + p1 = 1), ω[0;1[
Branch-Site specific models
M2a: Model A 8 κ, τpig, τhuman, τmouse, p0(p0 + p1 = 1), p2, ω[0;1[, ωforeground
The parameters used are (κ) transition / transversion ratio, (τ) branch length, (ω) dN/dS ratio, (p) fraction of codons that fall into the specified ω category.
Table 2 Comparison of topologies.
Log likelihood Branch lengths
Topology No. genes Super gene Pig Human Mouse Internal Fugu
Amino Acids
A 245 -921354 0.0227 0.0280 0.0554 0.0083 0.3294
B 440 -920090 0.0292 0.0281 0.0403 0.0171 0.3229
C 180 -921703 0.0292 0.0241 0.0555 0.0055 0.3304
1. codon pos.
A 215 -570181 0.0189 0.0235 0.0524 0.0088 0.2692
B 386 -568900 0.0265 0.0237 0.0341 0.0195 0.2600
C 208 -570504 0.0264 0.0190 0.0525 0.0058 0.2708
2. codon pos.
A 215 -498689 0.0124 0.0156 0.0323 0.0053 0.1680
B 545 -498005 0.0167 0.0157 0.0229 0.0102 0.1642
C 175 -498925 0.0167 0.0130 0.0324 0.0034 0.1687
Top (A-C) refers to the three different topologies shown in Figure 3a–c. No. genes is the number of individual genes that favour each topology. The likelihood and the branch lengths shown are based on the concatenated super gene of the 988 individual four-species alignments; the average values of the branch lengths from the individual genes are highly similar to these results. Branch lengths are shown in number of substitutions per site.
Table 3 The rates of evolution.
Super gene Synonymous substitutions Nonsynonymous substitutions
dS dN Mean Median Variance Mean Median Variance
Human 0.115 0.017 0.126 0.118 0.003 0.018 0.010 0.0006
Pig 0.165 0.020 0.183 0.176 0.006 0.020 0.011 0.0005
Mouse 0.329 0.035 0.365 0.360 0.015 0.035 0.023 0.0013
Estimated rates of evolution on the super gene and the individual alignments. (dS) synonymous substitutions per codon, (dN) nonsynonymous substitutions per codon.
Table 4 Genes where all branches have ω > 1 based on the one ratio model.
Branch length Number of substitutions
Gene L Pig Mouse Human Kappa Omega P(N) P(S) M(N) M(S) H(N) H(S)
NM_031268 72 0.096 0.102 0.128 2.844 1.481 5.7 1.3 6.0 1.3 7.6 1.6
NM_032353 97 0.105 0.269 0.104 3.183 1.206 7.6 2.6 19.5 6.6 7.5 2.6
XM_165930a 102 0.231 0.370 0.162 8.593 2.127 20.5 3.1 32.8 4.9 14.4 2.2
XM_168460a 74 0.176 0.527 0.132 2.665 1.121 8.7 4.3 26.1 12.9 6.5 3.2
Three-species alignments where the average dN/dS ratios over sites and lineages are larger than one. (Gene) Genbank accession number of the human gene. (L) Length of sequence alignment in codons, P(N) number of nonsynonymous substitutions in pig, P(S) number of synonymous substitutions in pig, M(N), M(S) and H(N), H(S) represents the mouse and human lineage respectively. (a)Possible pseudogene in human lineage.
Table 5 Genes with branches where ω > 1 based on the free ratio model.
Omega Number of substitutions Significance
Gene L Pig Mouse Human P(N) P(S) M(N) M(S) H(N) H(S) ω > 1
NM_001866 80 2.130 0.434 0.535 9.8 1.9 11.5 11.0 12.0 9.3 0.4775
NM_004085 97 1.088 0.053 0.000 2.0 0.5 4.9 24.1 0.0 8.8 0.9863
NM_004549 122 0.570 0.276 1.615 15.2 10.2 25.7 35.5 28.9 6.8 0.4229
NM_004891 65 0.092 0.116 2.560 2.9 11.6 8.1 25.1 10.1 1.4 0.5318
NM_006607 187 0.261 0.281 2.117 24.6 38.0 54.7 78.4 31.0 5.9 0.3625
NM_012198 216 0.341 0.073 1.849 24.9 26.5 18.3 91.6 29.4 5.8 0.3888
NM_017425 147 0.594 0.424 1.110 33.5 18.7 39.3 30.8 21.2 6.3 0.8750
NM_022978 60 0.228 0.143 1.102 2.8 4.4 3.3 8.0 38.9 12.5 0.8547
NM_031268 72 1.307 1.009 2.307 5.5 1.3 5.6 1.8 8.2 1.1 0.4009
NM_032353 97 0.539 2.100 0.964 5.71 4.3 22.0 4.3 7.1 3.0 0.1606
NM_032731 123 1.576 0.299 0.146 12.5 2.9 27.9 33.6 5.6 13.8 0.6854
XM_003044a 118 1.022 0.172 0.042 22.1 9.1 21.7 53.1 1.6 15.6 0.9743
XM_016532 155 0.000 0.125 1.193 0.0 34.0 16.0 49.0 11.4 3.6 0.8863
XM_041680a 168 0.415 0.186 1.079 29.4 25.5 33.1 64.0 6.7 2.2 0.9673
XM_062742a 110 0.000 0.011 1.661 0.0 19.0 1.0 36.4 22.9 5.4 0.5119
XM_069411 187 0.085 0.058 1.108 3.7 15.9 5.5 34.9 119.9 39.6 0.6943
XM_092681 81 0.187 0.040 1.167 5.3 10.0 3.0 26.0 15.9 4.8 0.8551
XM_165930a 102 ∞ 2.061 0.691 24.7 0.0 32.9 5.1 10.2 4.7 0.0020*
XM_166695a 190 0.235 0.067 1.183 19.8 30.9 12.5 38.3 79.6 24.7 0.6657
XM_168460a 74 2.672 0.848 1.085 10.4 2.3 23.9 15.6 6.6 3.4 0.9234
XM_172026a 72 0.035 0.042 2.213 0.9 8.8 2.1 17.3 30.1 4.7 0.2564
XM_172342a 143 0.000 0.032 1.320 0.0 3.0 2.0 20.3 27.3 6.6 0.6075
XM_172363a 77 0.139 0.132 1.077 8.7 21.0 8.6 22.0 14.4 4.5 0.9422
Three-species alignments where one or more lineages have a dN/dS ratio larger than one. (Gene) Genbank accession number of the human gene. (L) Length of sequence alignment in codons, P(N) number of nonsynonymous substitutions in pig, P(S) number of synonymous substitutions in pig, M(N), M(S) and H(N), H(S) represents the mouse and human lineage respectively. (a)Possible pseudogenes in human lineage. (ω > 1) If more than one branch have ω > 1 only the significance of the branch with the largest value of ω is shown. (*) LRT (ω > 1) significant at 0.01 level.
Table 6 Genes predicted to be under positive selection with the branch-site models.
Genbank Acc. ω P Human gene annotation
Human lineage
NM_001785 3.8 0.27 Cytidine deaminase
NM_001867 5.3 0.20 Cytochrome c oxidase subunit VIIc
NM_004846 10.7 0.05 Eukaryotic translation initiation factor 4E-like 3
NM_006607 27.9 0.23 Pituitary tumor-transforming 2
NM_012198 4.8 0.32 Grancalcin, EF-hand calcium binding protein
NM_021167 6.9 0.13 Ocular development-associated gene (Interim)
NM_022978 22.0 0.28 Small EDRK-rich factor 1B (centromeric)
NM_080915 28.1 0.12 Deoxyguanosine kinase
XM_039644 49.5 0.02 Unclassified
XM_059906 8.2 0.07 Unclassified
XM_062742 2.0 0.84 Unclassified
XM_069411 6.8 0.38 Similar to RIKEN cDNA 1300003K24 (Interim)
XM_166695 6.9 0.31 Unclassified
XM_167131 3.8 0.28 Unclassified
XM_172026 16.9 0.38 Unclassified
Pig lineage
NM_000509 2.4 0.13 Fibrinogen, gamma polypeptide
NM_000520 10.3 0.06 Hexosaminidase A (alpha polypeptide)
NM_002979 2.0 0.15 Sterol carrier protein 2
NM_003142 3.1 0.14 Sjogren syndrome antigen B (autoantigen La) *
NM_016489 2.4 0.32 5'-nucleotidase, cytosolic III
Mouse lineage
NM_005731 8.6 0.074 Actin related protein 2/3 complex, subunit 2, 34 kDa
NM_013342 1.3 0.152 TCF3 (E2A) fusion partner (in childhood leukaemia)
NM_023935 3.0 0.171 Chromosome 20 open reading frame 116
XM_007076 2.5 0.248 Unclassified
Genes shown here all have a significant LRT at the 0.001 level. (ω) the predicted dN/dS ratio in the foreground lineage. (p) the proportion of sites predicted to be under positive selection.
Table 7 Heterogeneity in dN/dS ratios over sites.
Fraction of codons Branchlength
Model ω = 0 ω = 1/3 ω = 2/3 ω = 1 ω = 3 Pig Mouse Human Kappa
CT 0.691 0.238 0.055 8 × 10-5 0.016 0.221 0.418 0.163 2.494
F3 × 4 0.681 0.245 0.058 1 × 10-5 0.017 0.219 0.410 0.162 2.658
The concatenated super gene is used to estimate the distribution of dN/dS ratios over sites. Each codon is allowed to fall into one of the five predefined dN/dS ratio classes. The branch lengths are expressed as number of substitutions per codon.
Table 8 Codon usage in the three mammalian species.
Frequency Frequency Frequency Frequency
Codon H M P Codon H M P Codon H M P Codon H M P
TTT(F) 2.16 2.00 2.06 TCT(S) 1.43 1.44 1.38 TAT(Y) 1.61 1.40 1.48 TGT(C) 1.03 0.99 0.97
TTC 1.85 2.01 1.93 TCC 1.30 1.40 1.37 TAC 1.48 1.64 1.60 TGC 0.92 0.97 0.96
TTA(L) 0.98 0.81 0.89 TCA 1.12 1.01 1.04 TAA(*) 0 0 0 TGA(*) 0 0 0
TTG 1.50 1.42 1.46 TCG 0.33 0.39 0.40 TAG(*) 0 0 0 TGG(W) 1.24 1.23 1.23
CTT 1.53 1.40 1.44 CCT(P) 1.66 1.62 1.60 CAT(H) 1.17 1.05 1.07 CGT(R) 0.53 0.49 0.51
CTC 1.55 1.67 1.70 CCC 1.35 1.37 1.48 CAC 1.15 1.31 1.25 CGC 0.79 0.80 0.83
CTA 0.83 0.78 0.74 CCA 1.63 1.58 1.53 CAA(Q) 1.30 1.18 1.19 CGA 0.75 0.79 0.76
CTG 3.32 3.60 3.48 CCG 0.47 0.55 0.54 CAG 3.03 3.17 3.13 CGG 0.99 1.02 1.06
ATT(I) 2.16 1.90 2.01 ACT(T) 1.42 1.30 1.32 AAT(N) 2.05 1.73 1.88 AGT(S) 1.18 1.12 1.13
ATC 2.06 2.24 2.20 ACC 1.53 1.61 1.62 AAC 1.76 1.99 1.86 AGC 1.39 1.52 1.44
ATA 0.92 0.84 0.88 ACA 1.64 1.59 1.50 AAA(K) 3.35 2.95 3.23 AGA(R) 1.46 1.40 1.42
ATG(M) 2.22 2.20 2.22 ACG 0.47 0.56 0.58 AAG 3.74 3.98 3.65 AGG 1.04 1.14 1.08
GTT(V) 1.49 1.37 1.41 GCT(A) 2.21 2.22 2.11 GAT(D) 2.93 2.59 2.79 GGT(G) 1.32 1.23 1.26
GTC 1.33 1.50 1.43 GCC 2.35 2.43 2.54 GAC 2.35 2.70 2.51 GGC 1.95 2.08 0.06
GTA 0.99 0.84 0.88 GCA 1.89 1.77 1.81 GAA(E) 3.77 3.44 3.62 GGA 2.05 1.95 1.97
GTG 2.66 2.82 2.75 GCG 0.63 0.75 0.73 GAG 3.51 3.79 3.66 GGG 1.28 1.35 1.34
The frequencies are expressed as a percentage of the 240,048 codons in each of the three species. Human(H), Mouse(M), Pig(P). Stop codons are not allowed in the analyses (*).
Table 9 Evaluation of the choice of codon equilibrium frequencies.
Estimated Branch Lengths
Model df Human Mouse Pig κ ω lnL X2
FQ 1 0.136 0.340 0.178 2.862 0.125 -1502578 249354
F1 × 4 3 0.134 0.335 0.175 2.776 0.122 -1500436 231560
F3 × 4 9 0.136 0.343 0.178 2.692 0.119 -1495232 133363
F3 × 4 + CpG 10 0.138 0.351 0.181 2.593 0.114 -1493996 74214
Codon Table 60 0.136 0.348 0.179 2.497 0.113 -1478877 0
The values are estimated with the concanated gene comprising 240,048 codons using the one ratio model. (df) Number of parameters (κ) Transition/transversion ratio. (ω) dN/dS ratio. (X2) A chi square test statistic comparing the expected frequencies of each codon to the observed codon counts.
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| 15679890 | PMC549206 | CC BY | 2021-01-04 16:02:56 | no | BMC Biol. 2005 Jan 28; 3:2 | utf-8 | BMC Biol | 2,005 | 10.1186/1741-7007-3-2 | oa_comm |
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BMC Musculoskelet DisordBMC Musculoskeletal Disorders1471-2474BioMed Central London 1471-2474-6-31567988410.1186/1471-2474-6-3Research ArticleAssessing stability and change of four performance measures: a longitudinal study evaluating outcome following total hip and knee arthroplasty Kennedy Deborah M [email protected] Paul W [email protected] Jean [email protected] Jeffrey D [email protected] Dianne [email protected] School of Rehabilitation Science, McMaster University, Hamilton, ON, Canada2 Centre for Studies of Physical Function, Orthopaedic and Arthritic Institute of Sunnybrook and Women's College Health Sciences Centre. Department of Physical Therapy, University of Toronto, Toronto, ON, Canada3 Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada4 Division of Orthopaedic Surgery, Orthopaedic and Arthritic Institute of Sunnybrook and Women's College Health Sciences Centre. Department of Surgery, Faculty of Medicine, University of Toronto, Toronto, ON, Canada2005 28 1 2005 6 3 3 28 6 2004 28 1 2005 Copyright © 2005 Kennedy et al; licensee BioMed Central Ltd.2005Kennedy 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
Physical performance measures play an important role in the measurement of outcome in patients undergoing hip and knee arthroplasty. However, many of the commonly used measures lack information on their psychometric properties in this population. The purposes of this study were to examine the reliability and sensitivity to change of the six minute walk test (6MWT), timed up and go test (TUG), stair measure (ST), and a fast self-paced walk test (SPWT) in patients with hip or knee osteoarthritis (OA) who subsequently underwent total joint arthroplasty.
Methods
A sample of convenience of 150 eligible patients, part of an ongoing, larger observational study, was selected. This included 69 subjects who had a diagnosis of hip OA and 81 diagnosed with knee OA with an overall mean age of 63.7 ± 10.7 years. Test-retest reliability, using Shrout and Fleiss Type 2,1 intraclass correlations (ICCs), was assessed preoperatively in a sub-sample of 21 patients at 3 time points during the waiting period prior to surgery. Error associated with the measures' scores and the minimal detectable change at the 90% confidence level was determined. A construct validation process was applied to evaluate the measures' abilities to detect deterioration and improvement at two different time points post-operatively. The standardized response mean (SRM) was used to quantify change for all measures for the two change intervals. Bootstrapping was used to estimate the 95% confidence intervals (CI) for the SRMs.
Results
The ICCs (95% CI) were as follows: 6MWT 0.94 (0.88,0.98), TUG 0.75 (0.51, 0.89), ST 0.90 (0.79, 0.96), and the SPWT 0.91 (0.81, 0.97). Standardized response means varied from .79 to 1.98, being greatest for the ST and 6MWT over the studied time intervals.
Conclusions
The test-retest estimates of the 6MWT, ST, and the SPWT met the requisite standards for making decisions at the individual patient level. All measures were responsive to detecting deterioration and improvement in the early postoperative period.
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Background
Osteoarthritis, the most common reason for total hip (THA) and knee arthroplasty (TKA), accounts for more difficulty with climbing stairs and walking than any other disease [1,2]. Physical performance measures, therefore, play an important role in the measurement of outcome in patients undergoing total joint arthroplasty. Although the past two decades have seen considerable development and evaluation of self-report functional status measures [3-7] these advances have not been paralleled to the same extent in performance measures.
Information about customary or normal values often exists for performances measures, however, information concerning sensitivity to change and clinically important change are rarely available [8]. This gap is exemplified in the case of commonly used performance measures in the assessment of patients post TKA and THA. Measures such as self-paced walk tests (SPWTs) [9-11], the timed up and go test (TUG) [9,12,13], stair measures (STs) [9-11,14] and the six minute walk test (6MWT) [14-18] lack information on responsiveness in this population [8]. Although the literature contains varied definitions of responsiveness, in this case, it is used to indicate the ability of a measure to detect change [19].
A few studies have examined the responsiveness of the 6MWT and STs in patients following arthroplasty. Kreibich et al [15] investigated the responsiveness of six outcome measures using paired t tests and found that the 6MWT was more responsive than a thirty-second stair climb, yet not as responsive as the two disease specific measures studied. Parent et al [14] compared the responsiveness of 3 locomotor tests and 2 questionnaires using 4 different responsiveness statistics and recommended the 6MWT and the Physical Function subscale of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) for assessment in the early recovery period after TKA. No studies were found that examined the responsiveness of the SPWT and TUG. Several studies used performance test components in other tools, however, they were not reported in their original format [20,21].
Responsiveness statistics such as the standardized response mean (SRM) and effect size (ES) are important for making relative comparisons between measures. However, clinicians still require estimates to quantify the error in patients' scores and to determine if change has truly occurred. In the absence of population specific benchmarks, clinicians and researchers apply the results available from other populations. For example, Mahon et al [17] used the 6MWT as one outcome measure to examine the association between waiting time and postoperative health-related quality of life in patients undergoing THA. They considered a change of greater than 30 meters in the 6MWT to be clinically important, based on the work of Guyatt et al [22] in respiratory patients. Enhancing the interpretability of commonly used performance measures in the end stage OA-arthroplasty population would assist clinicians and researchers to better quantify decline and recovery.
The importance of determining THA and TKA population specific benchmarks is further underlined when one considers the growing number of North Americans requiring total joint arthroplasty [23,24]. In Canada alone, the number of THR and TKR increased 31.7% from 1994/1995 to 1999/2000 [25]. The purposes of this study were therefore to examine the reliability and sensitivity to change of the SPWT, TUG, ST and the 6MWT in patients with end-stage hip or knee osteoarthritis (OA) who subsequently underwent a total joint arthroplasty.
Methods
Subjects
The sample consisted of patients with a diagnosis of OA who were scheduled to undergo primary, unilateral THA or TKA and was part of a larger, observational, longitudinal study. A sample of convenience was chosen and included one hundred fifty consecutive, eligible patients (69 hips, 81 knees) investigated over the one-year period, November 2001 to 2002. Eligibility criteria included the following: diagnosis of OA, scheduled for primary total joint arthroplasty; sufficient language skills to communicate in written and spoken English; and absence of neurological, cardiac, psychiatric disorders or other medical conditions that would significantly compromise physical function. Patients were excluded if they were scheduled for revision, bilateral or staged arthroplasties. All of the surgeries took place at a specialized, orthopaedic tertiary care hospital in Toronto.
The characteristics of the patients with respect to age, height, weight, and body mass index (BMI) are reported in Table 1. All patients provided informed consent and the study received approval from the institution's research and ethics review board.
Table 1 Sample Characteristics
n = 150 Mean, SD Quartiles
Age (yr) 63.7, 10.7 57, 64, 72
Height (m) 1.69, 0.09 1.62, 1.68, 1.76
Weight (kg) 85.5, 15.4 74.3, 83.3, 94.2
Body mass index (kg/m2) 30.0, 4.9 26.3, 28.9, 33.4
n, Number of subjects
Yr, year
M, meter
Kg, kilogram
SD, standard deviation
Outcome measures
As noted earlier, patients completed four timed performance measures; the fast SPWT, TUG, ST, and 6MWT, at each assessment point. Time was measured on a stopwatch to the nearest 1/100 of a second. The order of testing was as follows: SPWT, TUG, ST, and 6MWT with a 10 minute rest between the ST and 6MWT. Standardized guidelines for performing the SPWT, TUG, and ST have been reported previously for a similar patient population [9,11]. In terms of the fast SPWT, patients were timed while they walked two lengths (turn excluded) of a 20-m indoor course in response to the instruction: "walk as quickly as you can without overexerting yourself." The ST required patients to ascend and descend 9 stairs (step height, 20 cm) in their usual manner, and at a safe and comfortable pace. To complete the TUG, patients were required to rise from a standard arm chair, walk at a safe and comfortable pace to a tape mark 3-m away, then return to a sitting position in the chair [26]. During the performance of the 6MWT, patients were instructed to cover as much distance as possible during the 6 minute time frame with opportunity to stop and rest if required. The test was conducted on a pre-measured, 46 meter unobstructed, uncarpeted, rectangular circuit. The course was marked off in meters and the distance traveled by each subject was measured to the nearest meter. As encouragement has been shown to improve performance [27], standardized encouragement, "You are doing well, keep up the good work" was provided at 60 second intervals. During the administration of each of the four performance measures, patients were permitted to use their regular walking aids.
Study design
As noted previously, the data for this study represent a subset from a larger ongoing study that examines recovery profiles using a number of self-report and physical performance measures. The study has two arms, in Phase 1 patients are recruited from the caseload of two orthopaedic surgeons with high volumes and long waiting lists to examine the impact of waiting time on recovery profiles. In phase 2, patients are recruited from all of the orthopaedic surgeons' lists at their preoperative visit to the hospital's standardized patient orientation program, which is scheduled one to two weeks prior to surgery. There are no differences in the postoperative follow-up for both of the Phases and all patients receive standardized treatment, following either a primary total hip or knee care pathway. To provide an accurate model of change over time, patients' follow-up measurements are scheduled at different intervals. The format is that of an observational repeated measures' design (Figure 1).
Figure 1 Study Design
Test-retest reliability was assessed preoperatively in a sub-sample of 21 patients from Phase 1. These 21 patients represented individuals who had progressed to surgery and follow-up by the time of this analysis. Data from patients' initial consultations with the surgeon, an intermediate assessment, and then again at patients' preoperative orientation visits contributed to the reliability analysis. Although the median interval between the first and second assessments was 91 days (1st, 3rd quartiles: 72, 133 days) and between the first and third assessments was 178 days (1st, 3rd quartiles: 140, 204 days), there is evidence to suggest that the amount of change in function while on the waiting list is minimal [28]. A second strategy was also employed to examine the stability of the twenty-one patients' measures over the aforementioned time period using data from the larger study on the Lower Extremity Functional Scale (LEFS). Previous research has determined the LEFS minimal detectable change at a 90% confidence level (MDC90) to be 9 LEFS points [29]. Using this benchmark, data from only 17 of the 21 patients were retained for the reliability analysis.
It is important when assessing responsiveness that a research design be employed in a period where change is expected. Based on the results of prior work [9], it was recognized that the early period following joint arthroplasty would provide such a framework in which the measures' abilities to detect deterioration and improvement could be determined. A construct validation process was therefore applied to evaluate the measures' abilities to detect change at two different time points post-operatively. The first postoperative assessment occurred within 15 days of surgery. The median interval between the preoperative and first postoperative assessment was 8 days (1st, 3rd quartiles: 7, 9 days). It was theorized that patients' lower extremity functional status, as represented by either the time to complete a task or the distance covered in the case of the 6-minute walk test, would demonstrate deterioration compared to their preoperative values [9]. Next it was theorized that patients' lower extremity functional status would improve over the interval between the first and second postoperative assessments with the minimum interval between these assessments set to 20 days. The median interval between these postoperative assessments was 38 days (1st, 3rd quartiles: 32, 46 days).
Analysis
Descriptive statistics including the mean, standard deviation, and quartiles were applied to summarize the data. Shrout and Fleiss Type 2,1 intraclass correlation coefficients (ICC) were used to describe the measures' test-retest reliabilities [30]. Standard errors of measurement (SEMs) were used to quantify the measurement error in the same units as the original measurement [31]. The 95% confidence intervals for all ICCs and SEMs [30,31] were calculated. In addition, the error associated with a measured value (i.e., 90% confidence interval) and the minimal detectable change at the 90% confidence level (MDC90) was calculated [19]. The error calculation for a measured value was obtained by multiplying the point estimate for the SEM by the z-value associated with the 90% confidence interval (z = 1.65). To calculate MDC90, the value obtained from the error calculation was multiplied by the square root of two (i.e. MDC90 = SEM × 1.65 × ). The interpretation of MDC90 is that 90% of truly stable patients will demonstrate random variation of less than this magnitude when assessed on multiple occasions. A change greater than MDC90 is often interpreted as a true change.
The standardized response mean (SRM) was used to quantify change [3] and SRMs were calculated for all measures for the two change intervals. A minus sign was applied to all SRMs that represented deterioration in functional status. For example, a decrease in distance, and an increase in time were assigned negative values. Although sample values of the SRM for the measures represent estimates of the population parameters for these measures, it is impossible to directly ascertain their sampling distributions. We applied a bootstrap procedure to obtain approximate representations of the sampling distributions for the measures' SRMs and to estimate their 95% confidence intervals [32]. Bootstrapping involves sampling with replacement. Specifically, 1000 samples of size n – where n equaled the number of observations for the specific analysis of interest – were selected with replacement. Estimates of SRMs were ordered from lowest to highest; accordingly, the 25th and 975th observations from the bootstrap samples represented the 95% confidence limits. This method provides a distribution free estimate of the confidence limits.
Results
Figures 2, 3, 4, 5 provide the distributions of preoperative scores for each of the performance measures. Table 2 provides a summary of the reliability analyses and estimates of SEM and MDC90. There was no systematic difference between the test and retest assessments for any of the measures (p > 0.05). All of the estimates were greater or equal to 0.90 with the exception of the TUG. Table 3 summarizes the measured performance values (means and quartiles) for the three assessment points and Table 4 presents a summary of the change scores and SRMs. The number of patients in Tables 3 and 4 differ as a result of the pattern of missing values. The results presented in Tables 3 and 4 provide consistent evidence that lower extremity functional status, as represented by the time/distance concept, deteriorates between the preoperative and first postoperative assessment. The measures demonstrated uniform improvement from the first to second postoperative assessments: time decreased, and distance for the 6-minute walk increased. As apparent in Table 4, the SRMs were greatest for the ST and 6MWT over the two measured time intervals. Table 5 provides an accounting of the missing data. It is evident from this table that a substantial number of patients were unable to complete the ST and 6MWT when administered within 16 days of surgery. Independent t-tests were performed to test if the preoperative values differed for patients who were and were not able to complete the ST and 6MWT at the first postoperative visit. No significant differences (p > 0.05) in the preoperative ST or 6MWT were observed for patients in the two groups.
Figure 2 Distribution of Times to Complete the Fast Self-Paced Walk Test
Figure 3 Distribution of Preoperative Stair Test Times
Figure 4 Distribution of Preoperative Timed Up and Go Test Times
Figure 5 Distribution of Preoperative 6 Minute Walk Test Distances
Table 2 Reliability Coefficients and Minimal Level of Detectable Change
Measure R (95% CI) SEM (95% CI) Confidence in Score (90% CI) MDC90
Fast Self-paced Walk Time (completed over 40 meters) 0.91 (0.81, 0.97) 1.73 (1.39, 2.29) ± 2.86 s 4.04 s
Stair Time 0.90 (0.79, 0.96) 2.35 (1.89, 3.10) ± 3.88 s 5.49 s
Timed Up and Go Time 0.75 (0.51, 0.89) 1.07 (0.86, 1.41) ± 1.76s 2.49 s
Six Minute Walk Test Distance 0.94 (0.88, 0.98) 26.29 (21.14, 34.77) ± 43.37 m 61.34 m
R, Reliability Coefficient
SEM, Standard Error of Measurement
MDC90, Minimal detectable change at the 90% confidence Level
s, seconds
m, meters
Table 3 Mean and Quartile Scores of the Performance Measures across Time
Measure Preop
Mean, SD
Quartiles
n = 150 Postop 1
<16 Days Postop
Mean, SD, n
Quartiles Postop 2
>20 Days From Postop 1
Mean, SD, n
Quartiles
Self-paced Walk Time (seconds) 31.7, 9.2
25, 30, 36 85.7, 62.7, 115
53, 66, 93 33.7, 10.9, 92
26, 32, 38
Stair Time (seconds) 17.1, 8.2
11, 15, 22 40, 12, 87
29, 39, 48 20.0, 9.7, 91
12, 18, 27
Timed Up and Go Time (seconds) 9.8, 3.2
7, 9, 11 24.7, 14.2, 116
15, 21, 31 10.3, 4.2, 91
7, 9, 12
Six minute Walk Test Distance (meters) 412, 123
329, 412, 508 193, 87, 82
120, 194, 263 408, 116, 91
328, 393, 477
SD, Standard Deviation
n, Number of subjects
Table 4 Change Scores and Standardized Response Means
Measure Preop to First Postop Interval Mean Change*, SD, n SRM* (95% CI) First to Second Postop Interval Mean Change*, SD, n SRM* (95% CI)
Self-paced Walk Time (seconds) -54.8, 61.6, 115
-0.89 (-1.42, -0.68) 47.7, 60.7, 89
0.79 (0.66, 1.45)
Stair Time (seconds) -23.8, 13.8, 87
-1.74 (-2.13, -1.45) 20.59, 10.40, 73
1.98 (1.68, 2.42)
Timed Up and Go Time (seconds) -14.9, 13.8, 116
-1.08 (-1.38, -0.92) 13.57, 13.04, 89
1.04 (0.84, 1.61)
Six minute Walk Test Distance (meters) -232, 133, 82
-1.74 (1.60, 1.97) 207, 109, 61
1.90 (1.46, 2.39)
* Negative sign indicates a worsening in the measured value; positive sign indicates an improvement in the measured value
SD, Standard Deviation
SRM, Standardized Response Mean
n, Number of subjects
CI, Confidence Intervals
Table 5 Missing Values Details
Measure Time 2
Eligible n = 119 Time 3
Eligible n = 93
Self-paced Walk
Completed Test 115 92
Unable to Complete Test 4 0
Missing 0 1
Stair Test
Completed Test 87 91
Unable to Complete Test 29 1
Missing 3 1
Timed Up and Go Test
Completed Test 116 91
Unable to Complete Test 3 0
Missing 0 2
Six minute Walk Test
Completed Test 82 87
Unable to Complete Test 33 1
Missing 4 5
Discussion
This study has provided information concerning the measurement properties of four performance measures used to complement information concerning lower extremity functional status in patients with advanced OA undergoing THA or TKA. The test-retest reliability component of this study was conducted over a median interval of 178 days, which is a longer period than would typically be chosen to assess stability. This extended reassessment interval was chosen to accommodate the fact that random measurement error is often time dependent, and in practice, the period between clinical visits is often greater than several months [33]. A potential concern when applying a reassessment of this duration is that true change in the sample will occur; however, in this study the LEFS MDC90 was applied to further define a stable patient sample. The reliability coefficients (Table 2) for the time and distance components of the tests met or exceeded 0.90 with the exception of the TUG. They are believed to represent conservative estimates of the reliability likely to be associated with most clinical reassessment intervals.
It is important to remember that the reliability of a measure intended for individual patient application must be greater than the reliability of a measure designed for group use [34]. Different authors have advocated different standards for individual patient use, Nunnally [34] recommended 0.95, Kelley [35] 0.94 and Weiner and Stewart suggested 0.85 [36]. Although the reliability of the TUG at 0.75 would meet the standards for group application, it would not meet the aforementioned standards for individual patient use. The SPWT, ST and 6MWT would meet one or all of these standards.
In reviewing the mean and quartile scores of the performance measures preoperatively (Table 3), the scores indicate higher function than those reported in other studies [14,16,17], including the findings from our own prior work which examined a large dataset of over 1800 patients [11]. One potential explanation for these findings may have been the age of our sample, 25% of the patients were 57 or younger. As noted in the Canadian Joint Replacement Registry, the numbers of THA and TKA in the 45–54 year age group has increased between 1994/1995 to 1999/2000 [25]. A second factor potentially accounting for the preoperative scores is the nature of the study. Individuals who could not complete all the performance measures preoperatively would not be included, thereby filtering out the individuals with the highest disability.
To be useful in clinical practice, the scores obtained on outcome measures must have meaning to clinicians. In this study, the SEM was used to identify the error associated with a patient's reported score and to estimate the value of MDC90. Because the SEM is reported in scale points, it enhances the interpretability of a patient's score and change score. To the authors' knowledge this is the first study to provide estimates for MDC90 for each of the four physical performance measures in the hip/knee end stage OA-arthroplasty population. These benchmarks will assist clinicians to more effectively monitor change in these types of patients.
Using a different methodology, Redelmeier et al [37] determined the smallest difference in the 6MWT associated with a noticeable difference in perceived walking ability for COPD patients to be a distance of 54 meters. Using this as a benchmark in arthroplasty patients would underestimate the distance required to be confident that a change had truly occurred. This illustrates the importance of population specificity when determining MDC90.
Many studies assessing change have focused on improvement only; the current investigation assessed deterioration and improvement [14,21,38,39]. Based on prior work, it was hypothesized that surgical intervention would induce a reduction in lower extremity functional status when assessed within 16 days of surgery [9]. All time/distance performance measures demonstrated deterioration over this interval. Subsequently all of the measures demonstrated significant improvements between the first and second postoperative visits. These findings suggest that the four performance measures are adept at assessing both types of change. The greatest changes were associated with the ST and 6MWT. Examination of the SRMs for these two tests demonstrated similar responsiveness over the studied time intervals.
This parallels the findings in the study by Parent et al [14] examining early recovery after TKA using locomotor tests, including gait speed, stair ascent cycle duration, and the 6MWT. Of these measures, the authors found the 6MWT to be most responsive over the study's three time points, ranging from preoperatively to 4 months postoperatively. Of interest, the stair ascent cycle duration, measured using a 2-dimensional biomechanical analysis system was least responsive and the authors recommended evaluating the responsiveness of a timed stair measure, which has been accomplished in this study.
In addition to providing information concerning the psychometric properties of the performance measures, our results also offer insights into the clinical application of these measures. The TUG was originally developed to easily evaluate the risk of falls using balance and basic functional mobility [8]. Tested in the frail elderly population, scores under 10 seconds were associated with individuals who were functionally independent [26]. Considering this benchmark and normative values reported for community dwelling elders [40], the patients' mean TUG score, in this sample, did not demonstrate much disability. Consequently, there would not be as much opportunity for detecting change. However, the usefulness of the TUG in an elderly orthopaedic population, including patients post THA and TKA, has been reported. [13].
In considering the SPWT and the 6MWT, it is not surprising that the 6MWT demonstrated greater responsiveness in this study, as it was measured over a longer distance and duration. Unlike the SPWT, which in this study was used to determine fast walking speed, the 6MWT has both speed and endurance components. However, as apparent in Table 5, the TUG and SPWT tests might be preferred if the goal was measurement in the early acute post-operative phase when patients deteriorate and may be unable to perform the ST or 6MWT. This was the case for over 25% of the current study's sample when assessed within 16 days of surgery. Therefore, the time period of administration and the patient's preoperative level of disability can serve as useful guides for clinicians faced with the decision of choosing the most informative measures.
This study has several limitations. As apparent in the tables, different numbers of patients were assessed at postoperative assessment one and two. This is partially a reflection of the study design, as mentioned earlier, not all patients were assessed at the same time points due to the goals of the larger ongoing observational study. However, some patients were also missed at both time points due to unexpected changes in appointments without communication to the investigators. Referral bias might also be a potential concern due to the nature of the institution being a specialized tertiary care facility. This must be balanced against the fact that it is one of the largest joint arthroplasty centers in Canada and draws from a wide catchment area. Considering the higher preoperative function of the patients in this sample, it will be important to replicate the current study's findings in different settings with other samples of arthroplasty patients. In addition, as responsiveness is a highly contextualized attribute [19], it would be informative to study the results over additional time points in the postoperative continuum.
Conclusions
This study has examined selected psychometric properties in four commonly used performance measures to assess change in the end-stage OA-arthroplasty population. The test-retest reliability estimates of the SPWT, ST and 6MWT met the requisite standards for making decisions at the individual patient level. All of the measures were responsive to detecting deterioration and improvement in the early postoperative time period following arthroplasty. The time period of administration and the patient's preoperative level of disability can serve as useful guides for clinicians faced with the decision of choosing the most informative measures. Estimates of MDC90 have been reported for each of the performance measures to assist clinicians in assessing change.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
DMK conceived and designed the study, assisted with the statistical analysis and prepared the manuscript.
PWS assisted with the design, performed the statistical analysis and assisted with the manuscript preparation.
JW consulted in the conception and design of the study and assisted with the manuscript preparation.
JDG assisted with the design and execution of the study and manuscript preparation.
DP assisted in the coordination of the study, data collection and assisted with the manuscript preparation.
All authors read and approved the final manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgments
We are grateful to each of the orthopaedic surgeons at the Orthopaedic and Arthritic Institute for their support and provision of patients for this study. Special thanks is extended to Anne Marie Macleod, Chief Operating Officer of the Orthopaedic and Arthritic Institute of Sunnybrook and Women's College Health Sciences Centre and also to Charmaine Newland (MS, PT) and Research Assistant Neil Reid for their dedication to these projects.
A Research Grant from the Orthopaedic and Arthritic Foundation supported this research.
Deborah Kennedy was supported by a Studentship Award from the Provincial Rehabilitation Research Program, funded by the Ministry of Health and Long Term Care and the Toronto Rehabilitation Institute Foundation, at the time of the study.
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| 15679884 | PMC549207 | CC BY | 2021-01-04 16:32:04 | no | BMC Musculoskelet Disord. 2005 Jan 28; 6:3 | utf-8 | BMC Musculoskelet Disord | 2,005 | 10.1186/1471-2474-6-3 | oa_comm |
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Biomed Eng OnlineBioMedical Engineering OnLine1475-925XBioMed Central London 1475-925X-4-51564932710.1186/1475-925X-4-5ResearchDesign and testing of low intensity laser biostimulator Valchinov Emil S [email protected] Nicolas E [email protected] Department of Medical Physics, University of Patras, Patras 26500, Greece2005 13 1 2005 4 5 5 11 11 2004 13 1 2005 Copyright © 2005 Valchinov and Pallikarakis; licensee BioMed Central Ltd.2005Valchinov and Pallikarakis; 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 non-invasive nature of laser biostimulation has made lasers an attractive alternative in Medical Acupuncture at the last 25 years. However, there is still an uncertainty as to whether they work or their effect is just placebo. Although a plethora of scientific papers published about the topic showing positive clinical results, there is still a lack of objective scientific proofs about the biostimulation effect of lasers in Medical Acupuncture. The objective of this work was to design and build a low cost portable laser device for stimulation of acupuncture points, considered here as small localized biosources (SLB), without stimulating any sensory nerves via shock or heat and to find out a suitable method for objectively evaluating its stimulating effect. The design is aimed for studying SLB potentials provoked by laser stimulus, in search for objective proofs of the biostimulation effect of lasers used in Medical Acupuncture.
Methods
The proposed biostimulator features two operational modes: program mode and stimulation mode and two output polarization modes: linearly and circularly polarized laser emission. In program mode, different user-defined stimulation protocols can be created and memorized. The laser output can be either continuous or pulse modulated. Each stimulation session consists of a pre-defined number of successive continuous or square pulse modulated sequences of laser emission. The variable parameters of the laser output are: average output power, pulse width, pulse period, and continuous or pulsed sequence duration and repetition period. In stimulation mode the stimulus is automatically applied according to the pre-programmed protocol. The laser source is 30 mW AlGaInP laser diode with an emission wavelength of 685 nm, driven by a highly integrated driver. The optical system designed for beam collimation and polarization change uses single collimating lens with large numerical aperture, linear polarizer and a quarter-wave retardation plate. The proposed method for testing the device efficiency employs a biofeedback from the subject by recording the biopotentials evoked by the laser stimulus at related distant SLB sites. Therefore measuring of SLB biopotentials caused by the stimulus would indicate that a biopotential has been evoked at the irradiated site and has propagated to the measurement sites, rather than being caused by local changes of the electrical skin conductivity.
Results
A prototype device was built according to the proposed design using relatively inexpensive and commercially available components. The laser output can be pulse modulated from 0.1 to 1000 Hz with a duty factor from 10 to 90 %. The average output power density can be adjusted in the range 24 – 480 mW/cm2, where the total irradiation is limited to 2 Joule per stimulation session. The device is controlled by an 8-bit RISC Flash microcontroller with internal RAM and EEPROM memory, which allows for a wide range of different stimulation protocols to be implemented and memorized. The integrated laser diode driver with its onboard light power control loop provides safe and consistent laser modulation. The prototype was tested on the right Tri-Heater (TH) acupuncture meridian according to the proposed method. Laser evoked potentials were recorded from most of the easily accessible SLB along the meridian under study. They appear like periodical spikes with a repetition rate from 0.05 to 10 Hz and amplitude range 0.1 – 1 mV.
Conclusion
The prototype's specifications were found to be better or comparable to those of other existing devices. It features low component count, small size and low power consumption. Because of the low power levels used the possibility of sensory nerve stimulation via the phenomenon of shock or heat is excluded. Thus senseless optical stimulation is achieved. The optical system presented offers simple and cost effective way for beam collimation and polarization change. The novel method proposed for testing the device efficiency allows for objectively recording of SLB potentials evoked by laser stimulus. Based on the biopotential records obtained with this method, a scientifically based conclusion can be drawn about the effectiveness of the commercially available devices for low-level laser therapy used in Medical Acupuncture. The prototype tests showed that with the biostimulator presented, SLB could be effectively stimulated at low power levels. However more studies are needed to derive a general conclusion about the SLB biostimulation mechanism of lasers and their most effective power and optical settings.
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Background
Nowadays lasers are widely used in therapy and diagnostics. They have been adapted to many medical procedures ranging from surgery, oncology, physiotherapy, dentistry, dermatology and biostimulation. The non-invasive nature of laser biostimulation have made lasers an attractive alternative in Medical Acupuncture at the last 25 years. Unfortunately, there is still an uncertainty as to whether they work or their effect is just placebo. Although a plethora of scientific papers published about the topic showing positive clinical results, there is still a lack of objective scientific proofs about the biostimulation effect of lasers in Medical Acupuncture.
The properties of acupuncture points, considered here as small localized biosources (SLB), have been extensively studied over the past 50 years. Research has shown SLB to be small area body regions, which exhibit unique, electrical, physiological and anatomical properties (e.g. high density of gap junctions, relatively low impedance etc.). They are considered to form groups, each group being arranged along a line, called meridian and related to an internal organ [1-4]. SLBs appear to be highly sensitive to mechanical, thermal, electrical or electromagnetic stimulation and are found to take place from the epidermis to a maximum depth of 2 cm [5-8]. It has been shown that with proper laser wavelength, intensity and collimation, low-level laser energy could be effectively delivered to SLB up to a 10 mm beneath the skin surface [9].
The objective of this work was to design and build a low cost portable laser device for effectively stimulation of SLB without exciting sensory nerves, and to find out a suitable method for objectively evaluating its efficiency. The attempt to define the optimal device parameters was based on the SLB properties, data about existing devices for low level laser therapy and on preliminary measurements performed in our laboratory. The latter suggest that the effect of SLB stimulation is also dependent on the polarization of the coherent emission in addition to its intensity, wavelength and modulation frequency. Therefore the device should provide a polarization adjustment, wide range of modulation frequencies, precise power settings and to have minimum size and cost.
Methods
Basic design and operating principle
The block diagram of the proposed biostimulator design is shown in Fig. 1. A laser diode is used as a coherent source of radiation because of its high brightness, efficiency, low cost and possibility for direct modulation. The emission wavelength is chosen in the visible range for minimum water absorption and haemoglobin reflection. The diode is driven by a microcontroller through an integrated driver and digital-to-analog converter (DAC). The user interface includes a liquid crystal display (LCD) and control buttons. The connection with the programmer is optional and is used only for in-circuit serial programming (ICSP). The optical system serves for beam collimation and polarization adjustment. Each stimulation session contains certain number of consecutive sequences of laser emission, where every sequence consists of continuous or pulse modulated laser emission as shown in Fig. 2. There are two main operational modes: program mode and stimulation mode, and two output polarization modes: linearly and circularly polarized laser emission. In program mode, a set of different user-defined stimulation protocols can be created and memorized according to the requirements of the specific study.
Figure 1 Block diagram of the of the laser biostimulator.
Figure 2 Time diagram of pulse modulated laser output.
The variable parameters of the laser output are: average output power, pulse width, pulse period, and sequence duration and repetition period. After each input parameter is selected, the total energy that would be delivered at the end of the stimulation session is automatically calculated and displayed. When defining the stimulation protocol, the software program reads the selected parameter value and automatically re-calculates the possible set of the other parameters, so that the user could not select inconsistent values or ones that would result in a total energy delivered that exceeds a certain safety limit. In stimulation mode the laser stimulus is applied according to the pre-programmed protocol.
A quarter-wave retardation plate realizes the laser output polarization change, as shown in Fig. 3. Within the retarder plane, the crystalline optic axis and the axis normal to it are also called fast or slow axis, depending on whether the uniaxial crystal is positive or negative. By rotating the retarder slightly about one of these axes, the retardation amount or the phase shift is varied. If the electric field vector of the incident linearly polarized beam and the quarter-wave retarder principal plane coincide, the emergent beam polarization remains the same as shown in Fig. 3a. If the angle θ between the electric field vector of the incident linearly polarized beam and the quarter-wave retarder principal plane is +45 degrees, the emergent beam is circularly polarized as shown in Fig. 3b. Reversing θ to -45 degrees reverses the sense of the circular polarization. The output from a single cavity laser diode is mainly linearly polarized, parallel to the laser junction. Although, spontaneous emission with a random polarization and with a polarization perpendicular to the laser junction is also present. For a diode operating near its maximum power the polarization ratio is typically greater than 100:1 but when operating near the threshold point, the ratio is considerably lower as spontaneous emission becomes more significant. Therefore a collimating lens followed by a linear polarizer is used since the retarder requires linearly polarized and normally incident light upon its plate over the whole power range. A single collimating lens, with good anti-reflection coating and large numerical aperture to efficiently capture the widely divergent perpendicular axis of the laser diode, is the most efficient and cost effective solution for the current application. Polarizers typically utilize birefringence, dichroism, optical activity, and polarization by reflection or by a metallic thin film [10]. For low-power and visual applications like the current one, sheet-type polarizers utilizing dichroism are normally used. Dichroic sheet polarizers subject one of the two orthogonal polarizations to strong absorption. They offer large apertures and acceptance angles, excellent extinction ratios and are simple to mount.
Figure 3 Polarization change principle.
The application can tolerate an elliptical beam shape and waveform aberrations, so circularization of the laser beam or correction of the waveform aberrations is not required.
Method for testing the device efficiency
The best way for testing the device efficiency is to obtain a biofeedback from the site of stimulation. A suitable non-invasive method is to measure the surface biopotential of the irradiated SLB site. However simultaneous stimulation and biopotential recording from a single SLB is technically difficult and inadequate, since the record may contain sham potentials due to local changes of the electrical conductivity of the irradiated skin. So a new method is proposed to avoid this problem. The method uses separate stimulation and measurement sites. Thus the laser stimulus is applied at SLB situated at the beginning of the meridian (e.g. the first point), where biopotential records are obtained from all the other easily accessible SLB lying distantly on the same meridian (see Fig. 4). Therefore measuring of SLB biopotentials caused by the stimulus would indicate that a biopotential has been evoked at the irradiated site and has propagated to the measurement sites, rather than being caused by local changes of the electrical skin conductivity. Extra electrodes have to be placed at non-SLB sites at close proximity to individual or group of closely spaced SLB recording electrodes, as a control. Due to the low intensity of the biostimulator output, even after prolonged irradiation, the subject has no thermal or tactile sensation and remains unaware of the application of the stimulus. Further more, there should be no visual, auditory or tactile cues that may indicate the activation of the laser.
Figure 4 Method for testing the device efficiency.
Practical biostimulator circuit
The schematic of the practical biostimulator circuit, built according to the proposed design is shown in Fig. 5. The microcontroller is implemented with the 8-bit RISC Flash microcontroller PIC16F84 with built in RAM and EEPROM memory [11]. It operates in HS oscillator mode with an 8 MHz crystal resonator. Power-on reset (POR), power-up timer and the oscillator start-up timer are enabled to allow for the power supply to rise to an acceptable level. The input/output ports are configured as follows:
Figure 5 Practical biostimulator circuit.
• RA0-RA2 – outputs used as LCD control signals
• RA3-RA4 – outputs, used as DAC control signals
• RB0-RB3 – either inputs or outputs, shared between the input control buttons B1-B4 and the LCD data bus DB4-DB7
• RB4-RB6 – outputs, used as control signals for the laser diode driver
The LCD is implemented with the dot matrix alphanumeric character module U4 (Seiko Instruments L1682). It features low power consumption, high contrast, wide viewing angle, on-board controller and LSI driver (Samsung S6A0069). All functions required for the LCD drive are internally provided on the chip. Its internal operation is determined by signals sent from the microcontroller. These signals include:
• Register select – RS
• Read/Write – R/W
• Data bus – DB4-DB7 (configured as inputs)
• Read/Write Enable – E
When ports RB0-RB3 are configured as inputs, the LCD data inputs DB4-DB7 have no practical influence on the logic levels set by push buttons B1-B4. LCD operation is also not affected since DB4-DB7 content is read only on logic high at E (U4-pin 6), set by the microcontroller [12]. When ports RB0-RB3 are configured as outputs, input buttons B1-B4 cannot alter their output logic levels because of resistor R2 connecting B1-B4 to common. Connector J1 is used for the microcontroller ICSP.
The laser diode driver is implemented with the highly integrated circuit U1 (Analog Devices AD9660), which combines a very fast output current switch with onboard analog light power control loops. It gets feedback current from the laser diode built-in photo detector (U1-pin 8), feeds it to a transimpedance amplifier (TZA) and then to two analog feedback loops where the bias and the active power levels of the laser are set [13]. The two levels are proportional to the analog input voltage at the bias level input (U1-pin 14) and at the active level input (U1-pin 3). These inputs drive track and hold amplifiers with hold capacitors C4 and C5. The input voltage range on both inputs ranges from Vref to Vref + 1.6 V, requiring an offset of Vref to be created for common based signals. The bias level is chosen to be equal to Vref, where the active level is determined by the circuit realized with op-amp U5. It performs the level shift and scales the DAC output from Vref to Vref + 1.6 V. This solution is attractive because both DAC and op-amp can run off a single 5 V supply, and the op-amp does not have to swing rail-to-rail. The op-amp U5 output voltage level is given by:
Since the monitor current is proportional to the laser diode light power, the feedback loops effectively control the laser power to a level proportional to the analog inputs. The bias control loops is periodically calibrated via U1-pin 15, where the active control loop is continuously calibrated via U1-pin 1. Resistors R3 and R4 are used to avoid floating of inputs U1-pin 15 and U1-pin 2 when microcontroller ports are in a high impedance mode. The laser pulse modulation is done by switching between the bias and the active power levels according to the logic level at U1-pin 2, where logic high turns the modulation current on. The gain resistor R5 matches the feedback loop transfer function to the laser/photo diode D1. Capacitor C6 optimizes the TZA response, with larger values to slow TZA response. Lower values increase TZA bandwidth but may cause oscillations. When input U1-pin 16 is logic high, the onboard disable circuit turns off the output drivers and returns the light power control loops to a safe state. It is used during initial power up of U1 and when the laser is inactive. In case that input U1-pin 16 floats (after POR or other reset conditions) the driver is disabled. When U1 is re-enabled the control loops are recalibrated.
The DAC is implemented with the single 8-bit voltage output MAX517 (U3). It is controlled by the microcontroller via 2-wire serial interface (U3-pin 3, U3-pin 4), operates from a single power supply and swings rail-to-rail. POR ensures the DAC output is at zero volts when power is initially applied. It uses the power supply Vdd as reference (U3-pin 8) filtered by R12 and C9. The DAC's full-scale output voltage ranges from 0 to Vdd. Special attention was paid to the PCB layout design to minimize the crosstalk between analog inputs and digital outputs.
The drawing of the practical optical system assembly is shown in Fig. 6. It includes an aluminium housing, collimating lens, linear polarizer and a quarter-wave retarder. Turning manually the polarization adjustment cap, clockwise or anti-clockwise at 45°, changes the polarization from linear to circular left or right-handed. The laser source used is a high power AlGaInP (Mitsubishi ML1412R) laser diode, which provides a stable, single transverse mode oscillation with a typical emission wavelength of 685 nm and a maximum continuous output power of 30 mW. The diode is matched with a single collimating lens with a relatively large numerical aperture (NA) and a single layer of anti-reflection coating (MgF2), optimized for 670 nm. The polarizer used is a linear polarizing film produced by aligning long chain polymers, which is then laminated in cellulose acetate butyrate (CAB) for durability and stiffness [14]. The quarter-wave retarder is implemented with polyvinyl-alcohol film supported by CAB.
Figure 6 Optical system assembly.
Results
A prototype device was built according to the proposed design using inexpensive and commercially available components. Its optical and electrical characteristics are given in Table 1. The microcontroller's internal RAM and EEPROM memory allows for a wide range of different stimulation protocols to be implemented and memorized. The integrated laser diode with its onboard light power control loop provides safe and consistent laser modulation. Because the application of the stimulus throughout the stimulation session is entirely controlled by the microcontroller, once the procedure is started, both subject and operator are unaware of whether the stimulus is active or not, except if intentionally staring the stimulated location. Thus true double-blind studies can be performed. The optical system presented, offers simple and cost effective way for beam collimation and polarization change. With the power levels used the possibility of sensory nerve stimulation via shock or heat is excluded.
Table 1 Device specifications.
Parameter Value
Beam dimensions (-3dB) D┴ D\\
3.12 mm 1.7 mm
Average output power 1–20 mW
Average output power density 24–480 mW/cm2
Maximum irradiation per stimulation session 2 Joule
Collimating lens coupling efficiency (685 nm, f = 4.6 mm, NA = 0.53) 96 %
Polarizer transmittance (685 nm, optic axis parallel to the diode junction) 75 %
Quarter-wave retarder transmittance, (685 nm) 93 %
Total optical system transmittance (685 nm) 67 %
Output polarization linear/circular
Laser class IIIb
Pulse modulation 0–10 000 Hz
Duty factor 10–90 %
Pulse sequence duration 1–30 sec
Pulse sequence repetition period 1–5 min
Number of pulse sequences 1–20
Maximum power consumption (5 V) 600 mW
The biostimulator was tested on the right Tri-Heater (TH) meridian of ten subjects according to the proposed method (see Fig. 4). The laser stimulus was applied at point TH-1, where recording electrodes were placed along the same meridian on points TH-3, 4, 5, 6, 7, 8, 9, 13, 15, 16, 17, 18, 21, 22 and 23, which were relatively easily accessible (see Fig. 7). Additional control electrodes were placed at non-SLB sites, approximately 2 cm apart from each SLB electrode, and the reference was positioned at the right ear lobe. Sample records of unprocessed real time SLB laser evoked potentials obtained from points TH-8, TH-15, TH-17 and their controls are shown in Fig. 8. These signals were recorded with an active electrode amplifier [15] from one subject and are responses to the same stimulation, where the biostimulator settings used are given in Table 2. The SLB evoked potentials appear like periodical spikes with a repetition rate from 0.05 to 10 Hz and amplitude range 0.1 – 1 mV. The preliminary results suggest that the repetition rate of the evoked SLB signals is proportional to the total energy delivered by the stimulus.
Figure 7 Photo of the electrodes placement and stimulus application during a preliminary measurement.
Figure 8 Evoked biopotentials acquired from points TH-8, TH-15, and TH-17 and their controls.
Table 2 Device settings used during the preliminary measurements.
Parameter Value
Average output power 10 mW
Average output power density 240 mW/cm2
Pulse modulation 2000 Hz
Duty factor 50 %
Pulse sequence duration 10 sec
Pulse sequence repetition period 1 min
Number of pulse sequences 10
Output polarization Circular
The noise present in the signals is mainly composed of electromyographic signals and noise from the electrode-skin interface. The first two signal records (TH-8 and control) contain ECG artifacts and additional electromyographic noise since those two electrodes were positioned relatively distant from the reference electrode. The frequency bandwidth was limited to 200 Hz by sixth order low-pass Bessel filter and the signals were sampled with 1 kHz.
Recording to the EU regulation (Medical Device Directive 93/94) this device falls under class IIb in order to obtain the CE mark. The biostimulator prototype was categorized as Class IIIb laser product according to the International Standard for the Safety of Medical Laser Products IEC 601-2-22, as stated in Table 1.
Discussion
The best solution for building a compact hand held biostimulator would be to design a custom made integrated circuit, but the cost would be much higher. We found a good alternative in using surface mount technology (SMT), commercially available integrated laser diode driver and a RISC Flash microcontroller. This solution resulted in a reduction in parts, size and power consumption. The proposed method for testing the device efficiency is very sensitive to precise electrode and stimulus positioning. Even a deviation of 3 mm from the exact SLB location may prevent the recording electrode from capturing signals from the source. The same deviation of the stimulus position also results of ineffective excitation of the targeted SLB and thus no SLB evoked potentials can be recorded. The method is also susceptible to the electrode-skin pressure, but not only due to its strong influence on the contact impedance. It was observed that the excessive electrode-skin pressure led to diminishing or even disappearing of the SLB signal, although the contact impedance was lower. This is most probably due to the pressure exerted on the SLB source that may affect the signal generation or transduction. Alternatively insufficient electrode-skin pressure led to excessive contact impedance and noise from the electrode-skin interface. The preliminary results suggest that a circularly polarized laser emission is most effective when used on the so-called Yang acupuncture meridians but not on Yin types. However more studies are needed to validate or disprove this observation.
Conclusions
The specifications of the prototype, built according to the proposed design, were found to be better or comparable to those of other existing devices. It features small size and low component count and power consumption. Because of the low power levels used the possibility of sensory nerve stimulation via the phenomenon of shock or heat is excluded. Thus senseless optical stimulation is achieved. The optical system presented offers simple and cost effective way for beam collimation and polarization change. The novel method proposed for testing the device efficiency allows for objectively recording of SLB potentials evoked by laser stimulus. Based on the biopotential records obtained with this method, a scientifically based conclusion can be drawn about the effectiveness of the commercially available devices for low level laser therapy used in Medical Acupuncture. The prototype tests showed that with the biostimulator presented, SLB could be effectively stimulated at low power levels. However more studies are needed to derive a general conclusion about the biostimulation mechanism of lasers in Medical Acupuncture and their most effective power and optical settings.
Authors' contributions
The authors contributed equally to this work
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| 15649327 | PMC549208 | CC BY | 2021-01-04 16:37:33 | no | Biomed Eng Online. 2005 Jan 13; 4:5 | utf-8 | Biomed Eng Online | 2,005 | 10.1186/1475-925X-4-5 | oa_comm |
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Curr Control Trials Cardiovasc MedCurrent Controlled Trials in Cardiovascular Medicine1468-67081468-6694BioMed Central 1468-6708-6-11569138410.1186/1468-6708-6-1ReviewMethodological considerations in the design of trials for safety assessment of new drugs and chemical entities Pater Cornel [email protected] Cornel Pater, Hannover, Germany2005 3 2 2005 6 1 1 1 22 11 2004 3 2 2005 Copyright © 2005 Pater; licensee BioMed Central Ltd.2005Pater; 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.
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Introduction
Assessment of the QT interval started to receive increased regulatory attention in the late 1980s.
The heightened safety concern was precipitated by repeated reports on torsade de pointes (TdP) and other arrhythmias occurring in patients treated with an antihistamine drug (terfenadine) [1]. ECG measurements performed during the clinical development process by cardiologists (allegedly using "eyeball/calliper" techniques), have failed to identify drug-related QT prolongation. The false-negative conclusions consequently provided have resulted in a number of serious adverse events and, ultimately in the removal of terfenadine from the US market [2].
Similarly, in early 1990s, attempts to decrease sudden cardiac death by novel antiarrhythmic drugs (Cardiac Arrhythmia Suppression Trial – CAST), have demonstrated that a certain degree of arrhythmia suppression was paralleled by a proarrhythmic effect, translated in 3-fold increase in mortality rate among patients treated with encainide or flecainide [3].
Awareness about the potential risk of drug-induced QT prolongation and subsequent risk of malignant arrhythmias has increased gradually since then and, particularly during the past years, regulatory requirements for short- and long-term safety of any new chemical entities have become more stringent. For example, after CAST, the FDA changed its advice regarding antiarrhythmic drugs and required evidence showing minimally, that a new antiarrhythmic agent did not cause death in patients.
The first regulatory guidelines regarding clinical evaluation of the QT/QTc interval prolongation in the context of new drug development were issued in 1997 by the Committee for Proprietary Medicinal Products (CPMP) [4]. Most recently, the FDA has issued its 4th draft document on the matter, clarifying the specific safety issues related to QT/QTc prolongation [5].
Congenital Long QT Syndrome
The frequency of congenital long QT syndrome (LQTS) is unknown, but appears to be a common cause of sudden and unexplained death in children and young adults. It is much more common than previously thought – possibly as frequent as 1 in 5,000, and may cause 3,000 – 4,000 sudden deaths in children and young adults each year in US [6]. It is present in all races and all ethnic groups, but it is not certain if the frequency is the same in all races.
Clinically, the diagnosis of LQTS is suggested by the occurrence of syncope, cardiac arrest or sudden death [7]. The diagnosis is established on the basis of prolonged QT interval on the ECG. A clearly prolonged QT interval is present in 60% to 70% of affected persons, but the QT is normal or only borderline prolonged in 30–40% of those affected. Overall, about 12% of LQTS patients have a normal QT interval on their baseline, resting ECG.
Torsade de pointes (TdP) tends to appear during exercise (especially swimming) or psychological stress in LQT1, during stress or startle (particularly auditory stimuli) in LQT2 and during rest in LQT3 [8]. Studies on transmural dispersion of repolarization (TDR) in experimental models have shown it to be linked to the genesis of TdP. TDR has different features in the three different forms of LQT referenced as LQT1, LQT2 and LQT3 [9].
Diurnal and sex-related pattern of QT interval
The maximal QT interval over 24 hours in normal subjects is longer than thought so far (440 ms). Both QT and QTc intervals are longer during sleep. The QT interval and QTc variability reach peak shortly after awakening, which may reflect increased autonomic instability during early waking hours. The time of the peak value corresponds to the period of reported increased vulnerability to ventricular tachycardia and sudden cardiac death. These findings have implications regarding the definition of QT prolongation and its use in predicting arrhythmias and sudden death [10].
At rest, the surface ECG in women displays longer QT interval [11], lower T wave amplitude [12] and less QT dispersion [13]. The QT interval displays greater shortening during exercise as compared to men, as a consequence [14]. Women are also known to have a greater propensity towards developing TdP when treated with agents belonging to class III antiarrhythmic drugs [15,16]. Besides, women are more susceptible to development of malignant arrhythmias in various settings of QT prolongation [12]. The basis for sex differences in repolarization appear to be, at least in part, influenced by sex hormones [17].
However, most recent data derived from a novel, automated QT-analysis algorithm, indicate that there are also sex differences in the dynamics of the QT interval during exercise and recovery in healthy subjects [18]. Women exhibited greater QT-interval shortening during accelerating heart rates and greater QT-interval prolongation during decelerating heart rates than in men. These results suggest that women might have a greater QT interval-rate adaptation, contributing to the greater prevalence of drug-induced TdP episodes in women as compared to men.
In this context, the currently 20 ms sex difference in the rate-adjusted QT interval, recommended by the regulatory agencies, might need to be revised.
Acquired forms of Long QT interval in diseased patients
It is estimated that more than 50 marketed agents and an equivalent number of drugs under development have been found to block potassium channels, to prolong the QT interval and induce, in some individuals, malignant arrhythmias. TdP is, however, a relatively rare event with a rate of 2–3% for some drugs [19]. Drugs which prolong the QT interval exist in every therapeutic class [20]. An international registry for cases of drug-induced arrhythmias associated with QT prolongation can be found on the web [21].
The pathophysiology of the TdP
Prolongation of the QT interval on the ECG is caused by increased duration of the action potential (AP) of the ventricular myocytes. Inhibition or activation of the potassium channels in the cells belonging to the different myocardial layers (Purkinje cells, subendocardial myocytes, mid-myocardial M cells and subepicardial myocytes) [22], interferes with the normal repolarization process and triggers different patterns of AP duration. The M cells for example, are characterised by prolonged repolarization in comparison with the epicardial or the endocardial layers.
The potassium channels are of particular importance in drug-related QT changes, most notably the rapid component of the delayed rectifier potassium current (IKr) channel. Blockage of the channel caused by the human ether-a-go-go-related gene (HERG) protein, the gene encoding for the IKr, has been implicated in many of the drug-induced changes.
The model used to explain the increased propensity toward malignant arrhythmias secondary to prolonged QT interval is based on extraneously induced, altered depolarization process with occurrence of "early after-depolarization" action potentials (EADs), which register on the surface ECG as prolonged QT interval [23].
In the drug-induced model, any drug, normally used for therapeutic purposes, but which interferes with the inward/outward ion currents across the cell membrane is leading to a prolongation of the action potential duration (APD) and thereby delayed repolarization. Certain drugs have the property to block the potassium channels (IKr) in order to achieve a desired antiarrhythmic effect. These types of changes facilitate additional inward Ca++ currents that further prolong the action potential. Consequently, the AP not only fails to repolarize but also depolarizes again, creating characteristics "humps" which, actually are EADs (Fig. 1A) [24].
Figure 1A "Humps" on the terminal part of the T-wave reflecting early ADPs. Figure 1b EAD degenerating in tachycardia.
Genetic defects of the Na+ or of the K+ channels lead to lengthening of QT interval and EADs which may trigger ventricular extrasystoles (VES). Occurrence of burst-like, repetitive EADs may degenerate in a tachycardia (see Fig. 1B) with particular features, termed torsade de pointes [25]. The French term torsade de pointes, suggests a rapid polymorphic tachycardia in which the QRS axis rotates 360 degrees over a sequence of 5 to 20 complexes [15].
Such early EADs also occur in a multitude of cases such as: bradycardia, diuretic-induced hypokalemia or hypomagnesemia, treatment with natrium or calcium channel blockers.
Preferential prolongation of the action potential duration in the M cells is thought to underlie QT prolongation, the phenotypic appearance of abnormal T-waves, the pathologic U-wave, and the development of TdP.
It is generally accepted that a focal activity initiates the onset of TdP, whereas functional re-entry is responsible for its maintenance [26].
Results from more recent research (27) suggest that changes in a new variable termed "T-wave peak to T-wave end" interval (TPE) would predict increased risk in subjects with LQT1 and LQT2. These changes would reflect the dynamicity of the transmural dispersion of repolarization (TDR) in clinical setting, in LQTS patients. Increased TPE interval may show to be the electrophysiological substrate for TdP. Modulation of the TPE interval magnitude seems to be a property of the Iks and Ikr (rapidly respectively slowly activating delayed rectifier potassium current) defects. The TPE interval, as an index of TDR, has been proved to be clinically useful in assessing arrhythmic risk [28-31].
Current regulatory recommendations. Objectives and Scope
Drugs with significant effects on repolarization must be identified and their risk quantified in preclinical and clinical development. Risk-benefit assessment of drugs under development, with particular emphasis to their propensity to prolong repolarization should be individualized to their pharmacokinetic and pharmacodynamic profile as well as to their safety characteristics. The following major aspects need to be addressed:
• Rigorous assessment of the agent's effects on the QT/QTc interval.
• Assessment of the QT/QTc prolongation-related safety risks of the particular drug against its potential benefits.
The above-mentioned issues should be taken into account in any of the following circumstances:
• Development of a novel agent (with non-antiarrhythmic properties).
• A marketed agent for which new dose or route is being developed (with consequent potential increases in pharmacokinetic parameters – Cmax, AUC values).
• A marketed agent for which a new indication or new target patient population is pursued.
• A marketed agent belonging to a chemical or pharmacological class in which any other drug may have been associated with any of the following events: QT/QTc prolongation, TdP or sudden death during postmarketing surveillance.
The "thorough QT/QTc study" – General Considerations
The "thorough QT/QTc study" is about to emerge as the comprehensive "clinical data set" fully complying with current regulatory requirements, as opposed to "non-clinical" testing that may, or may not generate sufficient information considered to preclude risk of QT/QTc prolongation. Judgement is required on a case-to-case basis on whether the "clinical data set" following completed non-clinical testing [32,33] is still necessary or not, with correspondent adjustment of study design variables.
Being considered a biomarker of proarrhythmic risk, the QT/QTc interval is the pharmacodynamic (PD) parameter which is explored to assess drug induced changes in heart rate (HR) and ECG parameters as correlated to plasma drug concentrations (PK). The PK/PD analysis implies a standardized collection of blood samples for determination of PK parameters (Cmax, Tmax, AUC) and recording of 12-lead ECGs for measurement and computation of specific ECG parameters (PR, QRS, QT/QTc). All of these measurements can be expected to show exposure-response relationships that enhance comparison of the investigated drug with its comparator (placebo or active), primarily with respect to its safety.
In early phase I studies, when the PK profile of the drug is eventually still unknown, a traditional PK study should be performed with the aim to determine the plasma concentration-time profiles (see Fig. 2B). This allows not only calculation of AUC but also determination of concentration versus time profiles over a dosing interval for each individual, as well as for the population. This approach yields relatively detailed exposure information that can be correlated to the observed responses in individuals. The exposure-response relationship based on concentration-time profiles can provide time-dependent information that cannot be derived from AUC or Cmin.
Figure 2A 12-lead ECG sampling pattern in the run-in period (baseline). Minimum number of recordings are highlighted at 8, 14 and 20 hours. Figure 2B Plasma concentration-time profiles (PK/PD analysis).
Within the bounds of maintained safety and tolerability, the QT/QTc evaluation should also be performed on ECGs recorded at substantial multiples of the maximum therapeutic exposure (multiples of Tmax – see Fig. 2B – samplings at 8, 12, 16, 20 and 24 hours from Tmax).
Knowledge of "concentration increases" that might occur due to drug-drug or drug-food interactions require specifically adjusted study designs. Likewise, in instances where increased plasma concentrations and ensuing QT/QTc prolongation effects may occur due to a metabolite with different pharmacokinetic profile from that of the parent drug (see Fig. 3A and 3B), a tailored study design will be needed.
Figure 3A Plasma concentration-time profile of parent drug. Figure 3B Plasma concentration-time profile of metabolite.
When the "through QT/QTc study" assessment is intended to be performed in drugs with well known pharmacokinetic profile (known optimal dose and therapeutic window), the sampling plan for both blood collection and ECG recordings will be spaced to match the known peak plasma concentration (Cmax – for single doses of the formulations) or the attained "steady state" after multiple dosing. Importantly, there can be large interindividual variability in the time to peak concentration with differences in the PK profile (e.g., Tmax, time to Cmax) due to demographics, disease states, etc., compelling to closely spaced samplings to account for these differences.
Study design – Methodological Considerations
The study design needs to be adjusted to the individual drug's pharmacokinetics and safety characteristics. Both the crossover and the parallel designs have specific advantages and relative disadvantages that need to be taken into account in the particular case at hand (see Additional file 1). However, as a rule, regardless of the design alternative chosen, the study should be randomised, double-blind and controlled.
Primary objectives
To quantify the dose-, concentration-, and time-relationships of the drug on the QT/QTc interval in the target population at therapeutic and supra-therapeutic plasma concentrations.
Secondary objectives
Collection of (serious) adverse events such as:
• Absolute QT/QTc prolongation: - QTc > 500 ms and/or
- QTc > 60 ms increase as compared to baseline
• Events suggestive of arrhythmia:- TdP
- Cardiac arrest/Sudden death
- VT/VF
- Syncope
- Dizziness
- Seizures
- Palpitations
Selection of control
Selecting a control for the purpose of demonstrating safety of a product in terms of "no risk for QT/QTc prolongation effect" is inevitably facing the question of whether an active control or a placebo should be used. The basic assumption is however, that the largest time-matched mean (baseline subtracted) difference between the drug and control (placebo or active control) for the QT interval is ≤ 5 ms, with a one-sided 95% CI that excludes an effect at <8 ms.
Placebo-controlled trials are still used to demonstrate effectiveness of new drugs and, for circumstance in which no increased risk for patients is foreseen, use of placebo seems appropriate and ethical, provided that the patients are fully informed and that they give written, informed consent [34-36].
At closer scrutiny, use of placebo in the particular case of demonstrating safety of a drug is not, by far, so much ethically charged as usually, as the subjects supposed to receive it are, in fact, exposed to a lesser degree of risk by QT prolongation. On the other hand, the "placebo-induced changes" are a reflection of underlying variability of the QT/QTc, an otherwise a well-known phenomenon. With other words, use of placebo-control in these cases is fully justifiable.
Use of an active control, while extensively advocated currently, due to its considerable credibility as compared with placebo, may raise troublesome methodological issues, typical for equivalence trials, such as the rigorous choice of control agent with special emphasis to essay sensitivity, etc.[34]. Commonly, the primary objective of an equivalence/noninferiority trial is to demonstrate that the efficacy of a new treatment matches that of the control treatment while, in the "thorough QT/QTc study", the goal is to demonstrate that the safety of the new drug is equal or at least not worse than that of the control agent. This translates into the need to demonstrate that the new agent doest not prolong the QT/QTc by more than 5 ms on average, as compared to the control. That is to say that the "equivalence margin" is set to 5 ms, although, a definite prolongation effect will be stated if the upper bound of the one-sided 95% CI would exceed 8 ms [5].
The 5 ms value, as an average threshold for demonstrating non-inferiority of the tested drug versus a comparator, might be a too ambitious cut-off point (i.e., too low). With the technique currently available, this level of accuracy may possibly be attained by some highly skilled analysts, but it might be difficult to be maintained as an average level for an entire group of analysts. A more reasonable and practically attainable average value would be 10 ms. Individual subjects displaying prolongation in excess of 10 ms would, however, need to be given careful scrutiny.
Target patient population
These studies are generally performed in normal, healthy, adult volunteers. The subject population should be selected carefully to minimize inter-subjects variations.
Restrictive eligibility criteria are recommended in early phase studies (I and II) of compounds known to have APD or QT prolonging effects, with subsequent widening of criteria in later phase studies (II and III).
It is estimated that ECGs should be generated in at least 100 volunteers (including females and males), for NCE with no pre-clinical evidence of QT prolongation [37], and in at least 200 volunteers (including females and males) for NCE with pre-clinical evidence of prolonged action potential duration or prolonged QT/QTc [37].
The test and the reference products are usually administered to the subjects in the fasting state (overnight fast for at least 10 hours). These subjects should not take any other medication for one week prior to the study or during the study. Identical test conditions must be used for the two group subjects with respect to: foods, fluid intake, physical activity, posture, etc. and, the physical characteristics of the subjects should be standardized (age, height, weight, and health) [38].
Clinical studies in later phases of development (phase III) and after market approval (phase IV) are supposed to have enlarged inclusion criteria to encompass female and elderly patients, patients with associated comorbidities and with concomitant treatment. Exposure to the relative new treatment of a heterogeneous population, to mimic the real population anticipated to be the end-user of the drug in the future, is meant to create a "worst case scenario" for drugs that in the pre-clinical and clinical development stages have shown effects on the QT/QTc interval. Establishing with confidence the behaviour of the QT/QTc interval in these patients, while exposed to the peak effect (Cmax/steady state) of the drug, is not only an effective risk management tool but also a highly ethical issue.
Timing of ECG recordings
Baseline ECG sampling
For NCE with suspected, or known from previous clinical studies, effects on the HR and/or APD, 10 to 20 baseline ECGs are required (see Fig. 2A). For agents administered intermittently, repeated baseline ECG assessments may be needed prior to each new treatment period. Carry-over effects should be carefully taken into consideration when cross-over design is employed.
During the run-in period of later phase trials (II-III), at least three baseline ECGs should be recorded [39].
"On-treatment" ECG sampling
The pattern of ECG sampling should match the planned blood sample collections for PK assessment (see Fig. 2B). There will be a few or up to 20 ECGs recorded during 24 hours period, depending on how the PK/PD analysis has been planned to be performed, on the amount of knowledge regarding the agent's pharmacokinetics as well as on the information generated by previous pre-clinical studies.
However, regardless of the study design, whenever possible, ECGs should be recorded at the same time of the day during both baseline period and after randomisation (during "on-treatment") to minimize the confounding effects of diurnal variations and postprandial effects [37].
For drugs with known metabolite(s), the ECG recordings should cover the prolonged blood sampling for the plasma concentration-time profile of the metabolite (see Fig. 3B).
Whenever ethically justifiable, for the case of inadvertent over-dosage or metabolic inhibition, it is recommendable that ECGs should be recorded at substantial multiples of the maximum therapeutic exposure, even in excess of the upper bound of the anticipated therapeutic range (see Fig. 2B – sampling at 28 hours).
Measurement of QT interval
Quality of ECG recordings is of paramount importance for the reliability of the data generated. Poor quality traces due to artefacts or lead misplacement should be avoided through appropriate training of the staff in charge with acquisition of ECGs. Whether these people are professionals or temporary research staff, all are supposed to have a high level of expertise in ECG acquisition technique and be able to validate tracings that are analysable or not.
Standard 12-lead ECGs should be taken in supine, after at least 5 minutes rest with default calibration of the recording device at 1 mV, speed at 50 mm/s.
Currently, standard lead II is chosen for measurement of RR and PR interval, QRS complex and the QT interval, on at least three cardiac cycles. Two additional precordial leads may be used for performance of the same measurements (e.g., V3-V4). Means are computed consequently, from one or three leads.
Manual measurement of different ECG parameters is charged with problems of accuracy and reproducibility due to the inter- and intra-observer variability inherent in such highly demanding tasks while, interpretation of ECG tracings is known to vary from one clinician to another [40].
However, ICH-GCP-compliant quality control and quality assurance SOPs, as well as systematic performance analyses applied to the individual analysts/technicians and their output data, employed nowadays in certain core laboratories, ensure the prospective clients of minimized inter- and intra-observer variability regarding the measurements performed and of high level of accuracy of the output results in the range of ± 10 ms, around a selected/agreed "gold standard" [41].
In order to ensure an overall high level of performance within a group of technicians/analysts who perform the factual measurements on ECG tracings, performance analysis applied to the group and each individual member of the group, should be run at six months interval. Deviation in the measurements performed of more than ± 10 ms should be addressed speedily and corrective measures implemented. Such quality-assurance performance analyses may maintain a high level of measurements' homogeneity and ensure a high quality of the data provided.
Likewise, ECG tracings as well as summary data are subject to interpretation and reporting by qualified cardiologist(s) [4].
Fig. 4 depicts a normal ECG with the most common parameters measured in the process of exploring any new NCE's effects on the QT/QTc interval. Apparently, measuring the QT interval should be a quite straightforward task, however, in practice there are a number of pitfalls and difficulties [30,31].
Figure 4 Normal ECG highlighting the common parameters measured when assessing the QT/QTc interval.
The beginning of the QRS complex is best determined in a lead with an initial "q" wave – commonly standard lead I or II, and leads aVL, V5 and V6. Sometimes, the "q" wave may be missing (the initial part of the QRS complex is isoelectric) due to its incorporation within the PR interval.
Determining the precise end of the T wave may be simple, when a tangent line to the steepest part of the descending portion of the T wave is drawn and the intercept between the tangent and the isoelectric line is indicating the end of T wave. At times, however, the T wave may be obscured by a superimposed U wave or, in the case of sinus tachycardia, by the ensuing P wave, making the positioning of the fiducial point difficult.
The U wave deflection is usually minimal or isoelectic in lead aVL. The aVL lead is therefore a useful for QT measurement since the end of the T wave is least likely to be obscured by a U wave.
TU morphology assessment
Different repolarization properties among the epicardium, M cells, and endocardium, as well as their interplay, are responsible for various morphologies of the T-wave and the pathologic U-waves. The T-wave is a symbol of the transmural dispersion of repolarization.
Several hypotheses have been proposed to explain the genesis of the U-wave, which represents the last repolarization component of the ventricules [42] however, the hypothesis that the Purkinje network is responsible for the physiologic U-wave seems most plausible.
Morphology changes of the T and U-wave should be interpreted as warning signs of TdP. Sometimes, a clear demarcation between the two waves is very difficult, exposing to the risk of underestimating the QT interval and, ultimately, to missing the clinical significance of the changes per se. Clearly, both qualitative and quantitative assessments of the repolarization changes occurring with different degrees of merger between the T and the U-wave are subject to a certain degree of subjectivity of the assessor. Therefore, it is recommendable that TU-wave morphology assessment to be made by qualified cardiologist(s) according to a standardised methodology. Additional file 2 captures the possible changes that may be encountered in the T-waves, U-waves and different forms of TU mergers in a particular individual. Additional file 3 summarizes the frequency distribution of TU morphology changes across two groups compared.
Given the high level of subjectivity inherent in this type of assessments, with considerable discrepancies between two assessors, even when identical data are assessed, an overall, reasonable conclusion on the TU morphology changes can be provided by use of a visual analogue scale (see Fig. 5). The degree of normality/abnormality in a particular case is estimated on a scale from 1 to 10, on which: "1" – is definite abnormal and "10" – is unquestionably normal. As an example, the flat-to-small negative T-waves in V5/V6 in the early phase of hypertension could be scaled as "7", whereas the large negative T-waves in the same leads, in the case of severe aortic stenosis, would be scaled as "1". A classical "borderline" change would be given a "5".
Figure 5 Visual Anlogues Scale to assist in reconciliating the inter-observer assessment of TU morphology.
QT dispersion (QTD)
Increased dispersion on the QT interval of the electrocardiogram has been proposed as a marker for increased risk of arrhythmias in patients with hypertrophic cardiomyopathy [48], long QT intervals [44], and sustained ventricular arrhythmias [45]. Most of the studies exploring QT dispersion were small and, thereby could not provide accurate data for the sensitivity and specificity of the method to be derived. One study has assessed different cut-off values for QT dispersion by employing ROC analysis, however, the QT dispersion analysed was essentially developed on the basis of a training set [46]. The average normal value of QT dispersion in normal subjects was ≤ 40 ms in 13 studies and ≥ 40 ms in eight studies [47]. The Rotterdam study reported QTc dispersion > 60 ms in apparently healthy subjects aged ≥ 55 years in whom a two-fold increase in sudden death was registered subsequently [48].
Despite sophisticated methods of computerised measurements of QT dispersion [49,50], the reliability of both manual and automatic measurement of QT dispersion is low and the method is considered a crude measure of the abnormalities during the whole course of repolarization [51]. However, more recent studies [52,53] indicated that dispersion in repolarization may arise from differences in the action potential durations between cells situated in difference myocardial layers and that heterogeneity in repolarization might be linked to induction of ventricular fibrillation [42].
The analysis of repolarization variability is commonly based on methods that evaluate spatial and temporal QT dispersion. Recent experimental studies [54] in arterially perfused canine left ventricular wedge preparations, suggest that the second part of the T wave represents the arrhythmogenic substrate and that the peak-to-end interval of the T wave is the trasmural dispersion of the repolarization. The TPE interval of the T wave is postulated to reflect the transmural dispersion in humans (as measured in V5) and might become a parameter to be routinely measured in the future. It is claimed that TPE correlates better than the QT-dispersion with TdP and that a TPE > 280 msec may be useful in predicting risk of TdP in acquired LQTS.
Heart rate correction of QT interval
The length of the QT interval varies inversely with heart rate and therefore shortens as the heart rate increases. Due to the known substantial inter-subject variability of the QT/RR interval relation, there is no mathematical formula to fit every individual. A formula that performs well in one healthy individual may not do so in another, resulting in over- or undercorrection of the QT interval.
Several correction formulas exist. The Bazett formula (square root – QTcB = QT/RR1/2) [55,56], most commonly used, is known to overcorrect at high heart rates and undercorrect at low heart rates [57,58]. The Fridericia formula (cubic root – QTcF = QT/RR1/3) [59] is considered to reflect a more accurate correction factor in subjects with tachycardia.
A more recent formula is the Framingham linear correction (QTcL = QT + 0.154 × [1 - RR]) known to be derived from a large patient population and thereby to be considered the most rigorous from an epidemiological perspective [60,61].
The main limitation in the aforementioned formulas is that each of them attempts to correct for heart rate only, while leaving into play a number of other known confounders (diurnal variability, effect of physical exercise, etc.). Disappointingly, analysis done on ECGs sampled from periods of stable heart rate provided no better results [62]. According to Malik et al., the relation between QT interval and heart rate is highly individual [63]. Using a parabolic heart rate correction formula (QTc = QT/RRα) they demonstrated a large variability of the α exponent (range: 0.233 – 0.485) in 50 healthy subjects. The same parameter in Fridericia's and Bazett's formulas is 0.33 and 0.50 respectively. Malik and colleagues concluded that correction of QT interval by heart rate may be misleading, regardless of the method used.
QT/RR regression models [64,65] can be used for computing the "right formula for the right data" in experimental situation, however, for practical purposes the Bazett and Fridericia as well as the linear corrections are preferred at present (from regulatory point of view).
Reporting of measurement results
Reporting of results becomes mostly informative if tabular frequency distribution and frequency histograms are used to display PR, QRS and QTc data (QTcB, QTcF, QTcL) for individuals and/or groups. For the hypothetic example captured in Fig. 2B, tabular representation of the data might be used to illustrate the frequency distribution of a number of parameters (PR, QRS, QTcB, QTcF, QTcL) matching the PK sampling (see Additional file 4). Summary data for the same parameters (Min, Max, Mean) as compared to baseline can be displayed for individual subjects and/or group of subjects (see Additional file 5). The relevant normal ranges for all parameters are given in Additional file 6.
Additional file 7 captures the baseline, mean and mean maximum values for all parameters measured/computed for one group (PR, QRS, QT, QTcB, QTcF and QTcL) and displays the difference (D1) between the mean value of each parameter "on-treatment" and the corresponding mean value at baseline. Given that a D2 value is to be computed for the second group (comparator), their difference (D2 – D1), for all parameters and the resulting p value (Bomferoni adjusted) could be displayed in Additional file 8.
Risk assessment as related to prolonged QT/QTc interval
Risk-benefit assessment with respect to a drug's propensity to prolong the QT/QTc interval entails a careful judgement of the frequency and magnitude of QT changes encountered in the preclinical and/or clinical program and balancing the potential risks against the drug's benefit.
The large variability in the prolonged QT/QTc behaviour as to the potential risk for a TdP ensuing, makes this task difficult and requires individual characterisation of a specific drug's effects on repolarization.
Amiodarone, for example, is known to prolong repolarization but to cause rarely TdP. Sotalol which prolongs repolarization through the same mechanism of action as Amiodarone (blockade of the IKr channel) causes a more frequent occurrence of TdP [66].
Some agents may cause slight QTc prolongation but when combined with other drugs that inhibit the metabolism of the suspected drug (e.g., terfenadine and cisapride), marked prolongation can occur [67]. A typical example is dofetilide, a potent QT-prolonging class III antiarrhythmic agent indicated for atrial fibrillation. Concomitant administration of cimetidine with dofetilide was shown to enhance the QT-prolonging effect resulting in a dose-dependent, baseline-related QTc increase of 22% and 33% with 100 mg and 400 mg of cimetidine respectively [68].
It is estimated that about 40–50% of the cases of drug-induced QT interval prolongation and/or TdP, result from drug-drug interactions with metabolic inhibitors (as in the example of dofetilide-cimetidine) and that only 10% are associated with electrolyte imbalance, some 10% with concurrent use of other QT-prolonging drugs and approximately 10–20% of cases have no obvious risk factors [69].
As a general rule, it is recommended that any prolongation should be considered as a potential toxicity [36]. In this context, it has become a widespread consensus that outliers with QTc > 500 ms or a baseline-related increase of QTc > 60 ms are better predictors than the mean QTc values [44]. In such instances, a careful screening for associated underlying risk factors or concomitant drugs is recommended, in order to determine the best course of action. Small QT prolongations (<10 ms) are acceptable as long as there are no associated risk factors. Longer QTc, however, requires individual monitoring and withdrawal from study should be considered, while further elective investigation should be scheduled on a case-to-case basis (see Additional file 9).
Risk management for marketed products
Ideally, therapy should be individualized on the basis of patient's genotype/phenotype determined through pharmacogenetic studies performed in the early stages of a drug's development and through application of that information while exploring the drug's pharmacokinetic and pharmacodynamic properties, its drug interaction potential as well as when ethnical-based bridging data is generated.
While genotyping of individual cases, where prior informed consent is obtained, based on strong suspicion of genetic substrate having caused substantial QT/QTc prolongation is highly recommendable (such as, outliers in phase I-III studies, patients withdrawn from study due to lack of efficacy or due to type A adverse events), large-scale genotyping in early stages of drug development or pre-prescription genotyping are still controversial.
Consequently, the clinical and scientific community is facing the need to apply classical "individualizing therapy" approaches [70] in reducing the clinical risk of QT/QTc-related adverse events (TdP, VT/VF, sudden death, etc.).
Obviously, the most elementary requirement in this respect is that prescribing physicians should fully comply with contraindications regarding co-prescription of interacting drugs and with the recommendation on appropriate monitoring of targeted patients. More specifically, attention should be given to pharmacokinetic and pharmacodynamic factors that constitute important risk factors [4].
Liver and/or renal diseases act as risk factors at pharmacokinetic level. Likewise, a multitude of metabolic inhibitors (see Additional file 10), when temporarily co-administered, develop high plasma concentration of the parent drugs, exposing them to high-dose pharmacology of the drugs concerned [4].
Pharmacodynamic risk factors include diseases that are associated with QT interval prolongation (see Additional file 11).
Obviously, appropriate monitoring is a sine qua non condition for preventing SAE in patients known to be treated with QT-prolonging drugs. QT interval should be monitored in these patients: (i) at baseline; (ii) at steady-state post-dose and at each incremental dose; (iii) when there is an inter-current change in level of risk, and (iv) if the patient develops symptoms of tachycardia or impaired cerebral circulation [4]. Treatment should be discontinued if QTc ≥ 500 ms and appropriate measures instituted based on the clinical picture at hand.
Occurrence of typical AE suggestive of eventual QT-prolongation, should prompt careful investigation of this possibility even in cases where initial QT/QTc assessment has shown to be negative. In such instances, it is recommended that screening for risk factors shall be employed and genotyping performed after receipt of informed consent. Furthermore, consideration should be give to "re-challenge" with the investigational drug under appropriate monitoring conditions, with the aim of obtaining an accurate assessment of the situation at hand as well as for getting useful information on dose- and concentration-response relationship.
Conclusions
Compelling evidence has accrued during the past years on the potential of several cardiac and non-cardiac drugs to prolong cardiac repolarization (reflected as prolonged QT on surface ECG) and to predispose to life-threatening arrhythmias.
This evidence has a major impact on the risk-benefit ratio of any drug, currently carefully considered from early stages of clinical drug development by pharmaceutical companies, by ethics committees as well as by regulatory agencies.
The broad spectrum of risk factors that may interplay in the increased propensity toward malignant arrhythmias of any new chemical entity is just increasing (congenital LQTS, genetic substrate, comorbidities, concomitant treatment) and adding to the complexity of the problem.
This calls for standardized methodologies to deal with the multifaceted aspects that the QT/QTc prolongation poses in practice, meant to ensure that drugs awarded market approval have undergone appropriate quality assurance scrutiny and, where necessary, further post-marketing surveillance is systematically planned and reported on, in a timely manner.
Competing interests
The author(s) declare that they have no competing interests.
Supplementary Material
Additional File 1
Frequency distribution of TU morphology changes across two groups.
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Additional File 2
TU morphology changes in individual subjects.
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Additional File 3
Frequency distribution of TU morphology changes across two groups.
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Additional File 4
Frequency distribution of the PR/QRS/QTc(B/F/L) data matching PK sampling (for individuals and/or groups).
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Additional File 5
Summary of PR/QRS/QTc(B/F/L) data (for individuals and/or groups).
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Additional File 6
Normal ranges for the PR/QRS/QTc(B/F/L) data and for the QTc(B/F/L) relative changes to baseline.
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Additional File 7
Frequency distribution of the baseline and on-treatment values pertaining the PR, QRS, QT, QTcB, QTcF and QTcL parameters as well as the D1 difference.
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Additional File 8
Summary of outcome differences between the two groups regarding key ECG parameters.
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Additional File 9
Alert criteria based on ECG findings (measurements) and rational for subject withdrawal from study.
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Additional File 10
Characteristics of the cross-over and parallel study designs.
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Additional File 11
Disease associated with prolonged QT/QTc interval.
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Additional File 12
Abbreviations (Not mentioned in the text!)
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Nutr Metab (Lond)Nutrition & Metabolism1743-7075BioMed Central London 1743-7075-2-21565691210.1186/1743-7075-2-2ResearchAn evaluation of the metabolic syndrome in the HyperGEN study Kraja Aldi T [email protected] Steven C [email protected] James S [email protected] Richard H [email protected] Gerardo [email protected] Cora E [email protected] DC [email protected] Michael A [email protected] Division of Biostatistics, Washington University School of Medicine, St. Louis, MO., USA2 Department of Medicine, University of Utah School of Medicine, Salt Lake City, UT., USA3 Division of Epidemiology, University of Minnesota, Minneapolis, MN., USA4 Department of Neurology, Boston Medical Center, MA., USA5 Department of Epidemiology, University of North Carolina, Chapell Hill, NC., USA6 Division of Preventive Medicine, University of Alabama, Birmingham, AL., USA2005 18 1 2005 2 2 2 16 9 2004 18 1 2005 Copyright © 2005 Kraja et al; licensee BioMed Central Ltd.2005Kraja 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 2001 the National Cholesterol Education Program (NCEP) provided a categorical definition for metabolic syndrome (c-MetS). We studied the extent to which two ethnic groups, Blacks and Whites were affected by c-MetS. The groups were members of the Hypertension Genetic Epidemiology Network (HyperGEN), a part of the Family Blood Pressure Program, supported by the NHLBI. Although the c-MetS definition is of special interest in particular to the clinicians, the quantitative latent traits of the metabolic syndrome (MetS) are also important in order to gain further understanding of its etiology. In this study, quantitative evaluation of the MetS latent traits (q-MetS) was based on the statistical multivariate method factor analysis (FA).
Results
The prevalence of the c-MetS was 34% in Blacks and 39% in Whites. c-MetS showed predominance of obesity, hypertension, and dyslipidemia. Three and four factor domains were identified through FA, classified as "Obesity," "Blood pressure," "Lipids," and "Central obesity." They explained approximately 60% of the variance in the 11 original variables. Two factors classified as "Obesity" and "Central Obesity" overlapped when FA was performed without rotation. All four factors in FA with Varimax rotation were consistent between Blacks and Whites, between genders and also after excluding type 2 diabetes (T2D) participants. Fasting insulin (INS) associated mainly with obesity and lipids factors.
Conclusions
MetS in the HyperGEN study has a compound phenotype with separate domains for obesity, blood pressure, and lipids. Obesity and its relationship to lipids and insulin is clearly the dominant factor in MetS. Linkage analysis on factor scores for components of MetS, in familial studies such as HyperGEN, can assist in understanding the genetic pathways for MetS and their interactions with the environment, as a first step in identifying the underlying pathophysiological causes of this syndrome.
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Background
Metabolic and physiologic disorders for cardiovascular disease (CVD) and type 2 diabetes (T2D), including abdominal obesity, insulin resistance, hyperglycemia, dyslipidemia, and hypertension often cluster. This cluster is frequently identified as the "metabolic syndrome" (MetS). Reaven [1] related MetS to the presence of resistance to insulin-mediated glucose disposal, glucose intolerance, hyperinsulinemia, increased triglycerides, decreased high-density lipoprotein cholesterol, and hypertension. Later, the definition of MetS was extended to include obesity, inflammation, microalbuminuria, and abnormalities of fibrinolysis and of coagulation [2-4]. Clearly, insulin resistance is not considered equivalent to MetS [5,6]. Grundy et al. [7], at a recent National Heart, Lung, and Blood Institute (NHLBI) /American Heart Association (AHA) National Conference, concluded that abdominal obesity is strongly associated with MetS. Sonnenberg et al. [8] have hypothesized that increased adipose tissue mass contributes to the development of MetS by triggering an increase in proinflammatory adipokines, especially the tumor necrosis factor-α, which may play a role in the pathogenesis of dyslipidemia, insulin resistance, hypertension, endothelial dysfunction, and atherogenesis. Although several studies have targeted MetS, its genetic determination and its pathophysiology remain unclear [9].
Different definitions and multivariate statistical approaches have been applied to characterize the increasing high-risk MetS premorbid state. Recently, special attention has received the categorical definition of metabolic syndrome (c-MetS) of the National Cholesterol Education Program Adult Treatment Panel III (NCEP) [2]. The NCEP definition (see Material and Methods) has especially two components, its usefulness in the clinical diagnosis of MetS and its association with recommendations for its therapeutic treatment. Based on the NCEP c-MetS definition, it is reported that 20 to 25 percent of the U.S. adult population has MetS. This represents a high prevalence of the syndrome in the general population [10,11]. In addition, employing the multivariate statistical method factor analysis (FA) different studies in different sampled populations have documented the underlying latent traits of MetS [4,12-17]. Meigs [3] has reported that FA in different studies has yielded on average 2 to 4 latent traits (factors) of MetS. Different studies have found different numbers of latent factors, depending on the type and number of the original risk factors analyzed, sampled population(s), methods utilized, including the statistical rotation method, and decisions about how many factors appeared statistically meaningful.
The objective of this study was to exemplify important facets of the MetS in the HyperGEN study. Two MetS aspects were assessed: a. The trait characterized as the categorical MetS (c-MetS) was studied according to the NCEP definition; b. The underlying (latent) traits or clusters of MetS (q-MetS) were evaluated by performing FA with and without Varimax rotation on 11 risk factors. All data were grouped by ethnicity and gender. Subgroups were created by excluding T2D participants, under the assumptions that T2D individuals may have a different pattern of glucose and insulin levels. Finally, our goal was to compare the expression of c-MetS and q-MetS in the Hypertension Genetic Epidemiology Network (HyperGEN) study.
Results
Sample size and relationships among original risk factors
For c-MetS the sample sizes varied from 2,025 observations for fasting triglycerides (TG) to 2,300 for high density lipoprotein (HDL) cholesterol in Blacks, and from 2,171 observations for TG to 2,471 for HDL in Whites. In the HyperGEN study, a high percentage of individuals have body waist (WAIST) and systolic blood pressure (SBP) / diastolic blood pressure (DBP) above the NCEP thresholds (Figure 1). Whites tended to have greater percentages of participants with TG and HDL beyond the NCEP thresholds than Blacks. The prevalence of c-MetS was 34 and 39 percent in Blacks and Whites, respectively.
Figure 1 Categorical MetS (c-MetS) in the HyperGEN Study
For q-MetS, the sample sizes and variables studied are summarized in Table 1 (the statistics were similar when T2D subjects were excluded, results not shown). After participants with missing data for any of the 11 original variables were excluded, this resulted in a sample of 1,422 Blacks and 1,470 Whites with complete data. The samples reduced to 1,173 Blacks and 1,322 Whites when T2D participants were excluded.
Table 1 Original Data Included in Factor Analysis
Blacks (N = 1422) Whites (N = 1470)
Variable Units Kurtosis Skewness Mean Std Dev Kurtosis Skewness Mean Std Dev
BMI kg/m2 0.51† 0.72 32.04‡ 7.54 0.67 0.77 28.86 5.57
GLUC mg/dl 0.68 0.70 107.37 44.06 1.43 -0.55 100.80 26.38
INS μU/ml 0.34 0.06 10.55 9.24 0.42 0.23 7.45 5.90
LDL mg/dl 0.31 0.33 118.89 36.63 0.36 0.26 116.41 31.56
HDL mg/dl 0.46 0.22 53.58 15.17 0.17 0.18 48.70 14.09
TG mg/dl 0.41 0.35 101.32 56.03 0.17 0.20 144.77 75.24
SBP mm Hg 0.46 0.68 128.45 21.78 0.44 0.62 120.50 18.33
DBP mm Hg 0.85 0.60 74.08 11.59 0.42 0.44 68.96 9.94
WAIST cm 0.51 0.64 102.05 17.78 0.74 0.71 99.22 15.48
WHR ratio 0.11 0.10 0.90 0.08 0.17 0.05 0.92 0.09
%BF % 0.44 0.17 40.00 12.06 0.33 0.57 33.41 9.29
†Kurtosis and skewness are reported after the data were transformed (where necessary) and adjusted (see Material and Methods); ‡number of observations, mean, and standard deviations represent measures from the final sample in factor analysis
In terms of the participants with complete data, the age at clinic visit had a mean of 46 and a standard deviation of 13 years in Blacks, and a mean of 51 and a standard deviation of 14 years in Whites. Overall, when compared to Whites, Blacks tended to have a higher body mass index (BMI), fasting plasma glucose (GLUC), fasting insulin (INS), HDL, SBP, DBP, WAIST, and percent body fat (%BF), similar low density lipoprotein (LDL) cholesterol and waist to hip ratio (WHR), and lower TG. Kurtosis after adjustments varied from 0.11 for WHR to 0.85 for DBP in Blacks, and 0.17 for WHR to 1.43 for GLUC in Whites, which demonstrates normal distributions for the traits in study and also for the factors created by performing FA (see Material and Methods).
Pearson correlations among the 11 adjusted and normally distributed variables are presented in Table 2. The lower triangle correlations correspond to all data, whereas the upper triangle refers to the data excluding T2D participants. In both ethnicities, strong correlations were observed among BMI, WAIST, %BF, INS, and WHR. GLUC correlated significantly with INS (inversely, because GLUC was inversely squared transformed). HDL cholesterol had a significantly negative correlation with TG and INS. SBP was significantly correlated with DBP. Interestingly, WAIST correlated higher with BMI (about 0.9) than with WHR (about 0.7) in all groups. These inter-correlations determine the structure of the factors.
Table 2 Correlation Matrix of the Variables Included in Factor Analysis
Variables ** Blacks: Upper Triangle: All Data Excluding T2D
(N = 1422 / 1173) BMI INS GLUC LDL HDL TG SBP DBP WAIST WHR %BF
Lower Triangle:All Data BMI 0.56‡ - 0.33‡ 0.15‡ - 0.22‡ 0.15‡ 0.18‡ - 0.04 0.91‡ 0.45‡ 0.78‡
INS 0.51‡ - 0.50‡ 0.16‡ - 0.37‡ 0.32‡ 0.04 - 0.08† 0.57‡ 0.44‡ 0.49‡
GLUC - 0.29‡ - 0.40‡ - 0.16‡ 0.25‡ - 0.26‡ - 0.06 0.03 - 0.33‡ - 0.26‡ - 0.28‡
LDL 0.13‡ 0.11‡ - 0.11‡ - 0.18‡ 0.23‡ - 0.00 - 0.05 0.14‡ 0.11† 0.17‡
HDL - 0.20‡ - 0.35‡ 0.23‡ - 0.16‡ - 0.41‡ 0.02 0.06 - 0.25‡ - 0.25‡ - 0.20‡
TG 0.17‡ 0.32‡ - 0.31‡ 0.20‡ - 0.41‡ 0.05 - 0.01 0.20‡ 0.28‡ 0.16‡
SBP 0.17‡ 0.02 - 0.07* 0.02 0.05 0.06 0.76‡ 0.16‡ 0.12† 0.06
DBP - 0.04 - 0.08† 0.04 - 0.02 0.08† - 0.00 0.74‡ - 0.03 0.03 - 0.06
WAIST 0.90‡ 0.52‡ - 0.32‡ 0.14‡ - 0.23‡ 0.22‡ 0.15‡ - 0.03 0.70‡ 0.75‡
WHR 0.44‡ 0.42‡ - 0.32‡ 0.10† - 0.25‡ 0.30‡ 0.11‡ 0.02 0.69‡ 0.407‡
%BF 0.76‡ 0.44‡ - 0.24‡ 0.16‡ - 0.18‡ 0.16‡ 0.03 - 0.06* 0.74‡ 0.37‡
Variables Whites: Upper Triangle: All Data Excluding T2D
(N = 1470 / 1322) BMI INS GLUC LDL HDL TG SBP DBP WAIST WHR %BF
Lower Triangle:All Data BMI 0.55‡ - 0.30‡ 0.01 - 0.21‡ 0.20‡ 0.19‡ 0.07* 0.89‡ 0.46‡ 0.77‡
INS 0.52‡ - 0.30‡ - 0.01 - 0.35‡ 0.34‡ 0.22‡ 0.15‡ 0.52‡ 0.36‡ 0.45‡
GLUC - 0.32‡ - 0.31‡ - 0.08* 0.13‡ - 0.16‡ - 0.12† - 0.09* - 0.30‡ - 0.25‡ - 0.26‡
LDL 0.02 - 0.02 - 0.05 - 0.04 0.08* 0.05 0.07 0.04 0.08* 0.07*
HDL - 0.22‡ - 0.37‡ 0.21‡ - 0.02 - 0.43‡ 0 0.01 - 0.20‡ - 0.21‡ - 0.12†
TG 0.20‡ 0.33‡ - 0.21‡ 0.06* - 0.45‡ 0.13† 0.09† 0.22‡ 0.23‡ 0.20‡
SBP 0.17‡ 0.19‡ - 0.13‡ 0.04 0.00 0.10† 0.70‡ 0.15‡ 0.13‡ 0.09†
DBP 0.03 0.09† 0.00 0.06 0.01 0.06 0.67‡ 0.06 0.09† 0.03
WAIST 0.89‡ 0.49‡ - 0.33‡ 0.04 - 0.21‡ 0.23‡ 0.14‡ 0.02* 0.70‡ 0.77‡
WHR 0.46‡ 0.35‡ - 0.25‡ 0.06 - 0.23‡ 0.25‡ 0.11† 0.07* 0.69‡ 0.44‡
%BF 0.76‡ 0.43‡ - 0.25‡ 0.08† - 0.12‡ 0.18‡ 0.11† 0.01 0.76‡ 0.43‡
*p < 0.05 † < 0.01 ‡ < 0.0001
**Variables were adjusted for age and center within ethnicity and gender (see Material and Methods)
A negative correlation between GLUC and INS is result of the inverse squared transformation of the original GLUC
FA with no rotation identified a factor (Factor 1) that was loaded mostly by central obesity, obesity risk factors and INS (Table 4, see Additional file 1 ). It explained 21 percent to 32 percent of the variance of the original risk factors. Three other factors, "Obesity," "Blood pressure," and "Lipids," were identified. In Blacks, the "Obesity" factor was primarily loaded by BMI, INS, WAIST, and %BF. In Whites, exclusion of T2D participants led to a similar pattern. However, in all data in Whites, the first factor represented a stronger mixture of central obesity, obesity and INS, leaving the fourth factor with mainly WHR loading. In order to distinguish the second factor from the first one, we labeled the first as "Central obesity" factor and the second as "Obesity" factor. In both ethnicities, blood pressure (BP) gave rise to a separate factor. Also the "Lipids" remained as a separate factor and was dominated mainly by HDL and TG. INS was associated mostly with the "Obesity" and "Lipids" factors.
In the case of FA with Varimax rotation, again, 4 distinct factors explained about 60 percent of the variance in the original variables (Table 4, see Additional file 1). We are labeling them as "Obesity," "BP," "Lipids," and "Central obesity". Factor loadings less than 0.1 were not listed in Tables 3 and 4 (see Additional file 1). The first factor alone explained 23 percent to 25 percent of the variance in the original risk factors, while the fourth factor explained 7 percent to 9 percent of the variance. The "Obesity" factor (Factor 1) loaded mainly BMI, WAIST, WHR, %BF, and INS. SBP and DBP loaded separately. A distinct factor ("Lipids") loaded mainly HDL cholesterol, TG, INS and GLUC in Blacks and HDL cholesterol, TG and INS in Whites. The fourth factor contained a higher loading for WHR than for WAIST. Similar factor loadings were present in the samples when T2D participants were excluded (Table 4, see Additional file 1).
Table 3 Factors, Loadings, and Sums of Squared Loadings in All Data (Males (M) and Females (F)), and by Gender (M, F) (Varimax Rotation)
Factor 1 (Obesity) Sample BMI* %BF WHR WAIST INS GLUC SBP DBP LDL HDL TG SS Loadings
Blacks M+F (1422) 0.95† 0.71 0.32 0.86 0.42 -0.20 0.13 2.49
M (483) 0.92 0.71 0.65 0.95 0.46 -0.15 0.11 0.11 -0.21 0.14 2.91
F (939) 0.96 0.71 0.23 0.84 0.40 -0.22 0.14 2.43
Whites M+F (1470) 0.94 0.77 0.40 0.86 0.46 -0.26 0.14 -0.11 0.11 2.69
M (721) 0.94 0.76 0.55 0.93 0.48 -0.26 -0.13 0.16 2.99
F (749) 0.94 0.81 0.31 0.84 0.46 -0.28 0.18 -0.11 0.11 2.69
Factor 2 (BP) Sample BMI %BF WHR WAIST INS GLUC SBP DBP LDL HDL TG SS Loadings
Blacks M+F (1422) 0.99 0.76 1.58
M (483) 0.13 0.83 0.83 1.42
F (939) 0.99 0.77 1.59
Whites M+F (1470) 0.13 0.88 0.76 1.39
M (721) 0.14 0.87 0.80 1.41
F (749) 0.12 -0.14 0.98 0.65 0.11 1.45
Factor 3 (Lipids) Sample BMI %BF WHR WAIST INS GLUC SBP DBP LDL HDL TG SS Loadings
Blacks M+F (1422) 0.22 0.19 0.31 0.24 0.52 -0.43 0.27 -0.57 0.64 1.49
M (483) 0.17 0.12 0.29 0.18 0.48 -0.19 -0.72 0.65 1.37
F (939) 0.18 0.11 0.29 0.21 0.49 -0.41 0.32 -0.55 0.59 1.32
Whites M+F (1470) 0.23 0.17 0.27 0.21 0.51 -0.27 -0.68 0.64 1.41
M (721) 0.14 0.41 -0.18 -0.18 -0.75 0.61 1.20
F (749) 0.25 0.19 0.24 0.23 0.5 -0.34 0.11 0.22 -0.70 0.60 1.44
Factor 4 (Central Obesity) Sample BMI %BF WHR WAIST INS GLUC SBP DBP LDL HDL TG SS Loadings
Blacks M+F (1422) 0.90 0.40 0.15 -0.13 0.11 1.03
M (483) -0.19 0.37 0.11 0.2
F (939) 0.93 0.44 0.15 -0.16 0.11 1.13
Whites M+F (1470) 0.16 0.69 0.47 -0.10 0.76
M (721) 0.11 0.57 0.27 -0.11 0.13 0.45
F (749) 0.92 0.44 0.14 1.10
* Variables were adjusted for age and center within ethnicity and gender (see Material and Methods)
GLUC negative loadings are result of inverse squared power transformation of the original GLUC;† Loadings ≥ 0.4 are in bold
FA with Varimax rotation was performed also by gender (Table 3). Between genders, the factors loaded in a similar fashion in Blacks and Whites. WHR and WAIST reflected gender differences in their loadings in factors 1 and 4.
Discussion
The fact that MetS is more prevalent in the HyperGEN study as compared to the average of the US adult population [10,11], is probably due to selection bias arising from the hypertension selection criterion applied in HyperGEN (see Material and Methods). Although BP was an important contributor to the categorical definition of the MetS (c-MetS), other risk factors such as WAIST, HDL and TG were also important. The HyperGEN Whites had a higher prevalence of c-MetS than the Blacks. Blacks had a higher percentage of participants with WAIST, BP, and GLUC beyond the NCEP thresholds.
In this study, FA of 11 potential risk factors for CVD and T2D yielded 4 latent factors, explaining about 60 percent of the variance in the original risk factors. Using the maximum likelihood estimation (MLE) method in S-PLUS (Insightful Corporation software), we found that the model p-values were significant, suggesting that additional factors may exist. However, although additional factors must exist to explain approximately 40 percent of the variance in the original variables, none of the remaining factors individually can explain more than about 5 percent of the variance. Therefore, we concluded that the quantitative structure of MetS can be described in terms of three to four factors when no rotation was performed, and four factors with Varimax rotation. One may even argue whether the fourth factor in the Varimax rotation is very meaningful. We chose to retain the "Central Obesity" factor particularly because it tends to reflect the well-known gender asymmetry (Table 3). FA without and with Varimax rotation can be useful in different settings. We believe that FA without any rotation makes more sense when investigating the pattern of risk factor clustering in the MetS. On the other hand, gene finding studies can be enhanced with Varimax rotation because, it is easier to find genes each of which influences a different (uncorrelated) factor. Therefore, depending on the goals of a study, rotation may or may not be used. We regard this flexibility as strength of the FA method.
We tested the pattern of the factors between genders only for FA with Varimax rotation. This pattern was stable among ethnicities between genders (Table 3). WHR on Factors 1 and 4 and WAIST on Factor 4 had statistically different loadings in males and females.
Another characteristic of the HyperGEN study was that at least two participants in each sibship had hypertension. A large proportion of the hypertensive participants have used anti-hypertensive and anti-cholesterol medications. Maison et al. [13] have compared medicated and unmedicated groups to see any implications of the medication use in FA. They applied FA to 9 risk factor changes over time, and separated data into groups of treated and untreated for hypertension and dyslipidemia. They found 3 and 4 factors respectively in males and females, the "BP", "Glucose," "Lipid," and "BMI, WHR, INS and TG" factors, which were similar between treated and untreated groups.
It is a common belief that T2D participants may have a different expression of INS and GLUC, therefore it may influence also the factors pattern in the MetS analysis. In the present study, we found a consistency of the factors before and after removing type 2 diabetics. This finding is supported also by Hanson et al. [17] who studied two samples of Pima Indians classified as T2D and non-T2D. They identified consistently 4 latent factors out of 10 risk factors in the two samples, with a relative variation only on insulin loadings. They found that the "Insulinemia" factor explained 30 percent of the original variance, "Body size" 20 percent, "BP" 15 percent, and "Lipids" 14 percent. In our study, the INS variable loaded with BMI, WAIST, %BF, and also with lipids. INS was present mainly in 2 and sometimes in 3 factors with loadings mostly in the "Obesity" and "Lipids" factors.
Other studies have provided similar results about the latent traits of MetS [4,16,17]. FA studies cited here, and other studies described by Meigs [3], have elements in common with our study: 2 to 4 factors were identified; BMI, INS, WHR and WAIST are major contributing risk factors; SBP and DBP load in a separate factor; INS was associated with more than one factor and mainly with obesity and lipids.
Our study and several others have shown that FA is a useful method for studying the underlying traits of MetS. Nevertheless this methodology has not passed without been criticized. Lawlor et al. [18] reviewed 22 published studies of the MetS, all based on FA. None of the studies had clearly identified whether they used FA for exploratory analysis or for hypothesis testing purposes. Such ambiguous use was regarded by Lawlor et al [18] as a major misuse of FA in the study of the metabolic syndrome. In fact exploratory FA and the hypothesis-testing (confirmatory) FA are two distinct methods. Basically, the two analyses use different constraints and different approaches in the analytical software. The exploratory FA is driven by the data (example is our study). On the other hand, the hypothesis-testing FA is only performed with some prior knowledge of possible loadings for different risk factors. One applies confirmatory FA on the data to test if the factor structure of the hypothesized model specifying the interrelationships among the original variables and the latent factors included in the model is true or not. A detailed example of the confirmatory FA of the metabolic syndrome is provided by Shen et al. [16].
If c-MetS and q-MetS are explaining the same disorder in two different aspects in the HyperGEN study, can FA contribute to MetS gene finding? MetS is recognized as a precursor for cardiovascular disease and type 2 diabetes [19]. There are several studies that have used FA for understanding the complexity of the MetS. Our study brings in more evidence that FA provides not only insights about the latent factor traits for MetS, but it produces factor scores for each of the MetS domains at the same time. Can factor scores be used in genetic analysis, such as in linkage analysis? The concept of a latent factor has much (intellectual) parallel with the concept of a latent gene. Much like a latent gene might have pleiotropic effects on several correlated phenotypes (original risk factors), several correlated risk factors load onto a latent factor. This makes FA very attractive from a genetic analysis point of view since, unlike individual risk factors each of which may entail several genes, each factor is likely to involve only a few genes which simplify their discovery. We believe that FA is useful for complex disease gene finding. In a near future motivated from this analysis we plan in the HyperGEN study to perform linkage analysis on the trait established by c-MetS and also on factor scores created by q-MetS, for identifying essential MetS putative genes / QTLs.
Conclusions
These analyses demonstrated that obesity and hypertension were the most important factors contributing to the MetS in the HyperGEN Study. Three to four distinct factor domains were identified depending on the FA rotation applied and decisions made. Results support the hypothesis that MetS is a compound phenotype, where obesity and its relationship to lipids and insulin are clearly the driving force of MetS. Insulin may play a connecting role between obesity and lipid domains.
In genetic analysis, it is well known that categorical data, especially a complex trait such as MetS, encounter reduced power as compared to quantitative variables. Therefore, we suggest that genetic analysis should be performed on specific combinations of traits that belong to a factor. It is possible that some common genes may exist in the pathways for the factors identified. Linkage analysis investigating putative quantitative trait loci for MetS factor domains can be a first step which may help discover the underlying mechanisms, or generate new hypotheses, in finding the causes of MetS.
Material And Methods
Data collection and MetS definition
The sample represents data from the HyperGEN network, part of the Family Blood Pressure Program, supported by the NHLBI as described by Williams et al. [20] and Province et al. [21]. The ethnicity was recorded as a self-reported demographic category. In the HyperGEN study sibships were recruited, each with at least 2 members who were hypertensive before age 60. Also, parents and offspring of some of the hypertensive sibs, as well as random samples of unrelated Blacks and Whites, were recruited, totaling 4,781 participants. Insulin measurements are not available in a part of the sample and therefore the sample size was smaller for FA. Also, participants with missing values for any of the quantitative risk factors used in the definition of MetS were excluded. A detailed account is provided in the Results section.
A participant was classified as having T2D if (s)he had a fasting plasma glucose value ≥ 126 mg/dl, or is a current user of hypoglycemic medication or insulin that was documented at examination in the clinic, or if diabetes was reported in the HyperGEN questionnaire. Also, an age at diagnosis ≥ 40 years was required for T2D individuals [22].
c-MetS according to the NCEP definition, was identified in participants by the simultaneous presence of 3 or more of the following conditions: WAIST > 102 cm in men, and > 88 cm in women; TG ≥ 150 mg/dl; high density lipoprotein (HDL) < 40 mg/dl in men, and < 50 mg/dl in women; systolic blood pressure (SBP) ≥ 130 mm Hg and/or diastolic blood pressure (DBP) ≥ 85 mm Hg or using antihypertensive medications; GLUC ≥ 110 mg/dl or on treatment for diabetes [2].
Factor analysis was founded on 11 variables: BMI expressed as the ratio of body weight divided by body height squared (in kg/m2); WAIST measured at the level of the umbilicus in cm; WHR defined as waist circumference divided by hip circumference; GLUC in mg/dl; INS in μU/ml (where fasting time was defined as ≥ 12 hours before blood draw); LDL in mg/dl; HDL in mg/dl; TG in mg/dl; Sitting SBP in mm Hg; DBP in mm Hg (SBP and DBP were measured three times after the subject was asked to sit for five minutes, with the mean of the second and third measurements of each variable being used in the analysis); %BF derived from the bioelectric impedance measurements based on the Lukaski formula [23].
Statistical Analysis
TG and INS had skewed distributions. A relatively skewed distribution was also present for HDL. Log transformation brought these variables distributions to approximately normal. GLUC and %BF were highly kurtotic. Using Box-Cox transformation, it was found that the inverse of the squared transformation of GLUC (1/GLUC2) and the squared transformation of %BF (%BF2) reduced the excess kurtosis considerably. The procedure transreg in SAS (version 9 for PC) was employed for finding power transformations.
There were two field centers recruiting Blacks and four field centers recruiting Whites. Accordingly, dummy (0,1) field center variables, one for Blacks and three for Whites, were created. All 11 risk factors were adjusted within ethnicity and gender for age, age2, age3, and field center effects using stepwise regression analysis within ethnicity and gender by employing SAS (SAS version 8.2 for Linux). Any variables with outliers beyond ± 4 standard deviations (SD) were also adjusted for heteroscedasticity of the variance. After the adjustments for each variable, outliers beyond ± 4 SD were eliminated. Each final adjusted variable was standardized to a mean 0 and variance 1.
Prevalence of c-MetS was estimated with the FREQ procedure of SAS. The multivariate method of factor analysis was employed for reducing a group of risk factors to a subset of latent factors. The primary goal of FA is to identify the interrelationships among a set of variables. In this study FA was used for exploratory analysis, because there was no a priori information about the structure underlying the variables. FA can be used also for a confirmatory analysis, when validation (or refutation) of a postulated structure is sought. In either case, FA seeks parsimony by summarizing a large group of interrelated variables (risk factors for a complex disease such as MetS) in terms of a small number of latent factors, thereby reducing the dimensionality. Theoretical statistical descriptions of FA can be found in the literature [24-26]. FA was performed with S-PLUS 6.0.1 software by using the factanal function, in which the MLE was employed. FA evaluated latent factors underlying the 11 original variables.
FA was performed with and without the Varimax rotation. "No rotation" achieves the simplest latent factor structure, in the extreme case loading any variable in one of the factors and almost negligible loadings in the rest of the factors. That is the reason why some studies (extracting factors with no rotation) find a concentration of the major variables' loading on the first factor. This is also the reason why some investigators named the first factor in their studies as the "Metabolic syndrome" factor [3,27]. Conversely, when Varimax rotation is applied, the objective is to maximize the independence of the clusters for variables that load onto factors. This is achieved by loading in separate factors distinct combinations of the interrelated risk factors. A loading of 0.4 or larger was considered as a significant contribution of an original variable to a factor.
List of abbreviations used
MetS, metabolic syndrome; c-MetS, categorical MetS; q-MetS, latent traits of MetS; FA, Factor analysis; MLE, maximum likelihood estimate; T2D, type 2 diabetes; CVD, cardiovascular disease; BMI, body mass index; INS, fasting insulin; GLUC, fasting glucose; WHR, waist to hip ratio; SBP, systolic blood pressure; DBP, diastolic blood pressure; BP, blood pressure; TG, fasting triglycerides; LDL, low density lipoprotein cholesterol; HDL, high density lipoprotein cholesterol; %BF, percent body fat.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
All authors were equally involved in designing the MetS study, evaluating statistics, interpreting the data, writing the manuscript, and organizing the figure and tables.
Supplementary Material
Additional File 1
Table 4. This table contains information on factor loadings result of FA with and without rotation performed on 11 risk factors
Click here for file
Acknowledgments
We are thankful for the support of all the HyperGEN participants and to the efforts of the:
Primary Centers and Investigators of HyperGEN
University of Utah (Network Coordinating Center, Field Center, and Molecular Genetics Lab).
Steven C. Hunt, Ph.D. (Network Director and Field Center P.I.); Mark F. Leppert, Ph.D. (Molecular Genetics P.I.); Jean-Marc Lalouel, M.D., D.Sc; Robert B. Weiss, Ph.D.; Paul N. Hopkins, M.D., M.S.P.H.; Hilary Coon, Ph.D.; Roger R. Williams, M.D. (late); Janet Hood.
Boston University (Field Center): R. Curtis Ellison, M.D. (P.I.); Richard H. Myers, Ph.D.; Luc Djoussé, M.D., D.Sc.; Yuqing Zhang, M.D.; Jemma B. Wilk, D.Sc.; Greta Lee Splansky, M.S.
University of Alabama (Field Center): Albert Oberman, M.D., M.P.H. (P.I.); Cora E. Lewis, M.D., M.S.P.H.; Michael T. Weaver, Ph.D.; Phillip Johnson; Susan Walker; Christie Oden.
University of Minnesota (Field Center and Biochemistry Lab): Donna K. Arnett, Ph.D. (Field Center P.I.); John H. Eckfeldt, M.D., Ph.D. (Biochemistry Lab P.I.); James S. Pankow, Ph.D.; Michael B. Miller, Ph.D.; Anthony A. Killeen, M.D., Ph.D.; Kim Weis, M.P.H.; Greg Rynders; Catherine Leiendecker-Foster, M.S.; Gregory Feitl; Barbara Lux; Jean Bucksa.
University of North Carolina (Field Center): Gerardo Heiss, M.D., Ph.D. (P.I); Barry I. Freedman, M.D.; Kari E. North, Ph.D.; Kathryn Rose, Ph.D.; Amy Haire.
Washington University (Data Coordinating Center): D.C. Rao, Ph.D. (P.I.); Michael A. Province, Ph.D.; Aldi Kraja, Ph.D.; Ingrid B. Borecki, Ph.D.; Charles Gu, Ph.D.; Treva Rice, Ph.D; Mary Feitosa, Ph.D; Jun Wu, M.D.; Karen L. Schwander, M.S.; Derek Morgan; Stephen Mandel; Shiping Wang M.S.; Brandon Pierce.
National Heart, Lung and Blood Institute: Susan E. Old, Ph.D.; Cashell Jaquish, Ph.D.; Dina Paltoo, Ph.D.
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| 15656912 | PMC549210 | CC BY | 2021-01-04 16:37:46 | no | Nutr Metab (Lond). 2005 Jan 18; 2:2 | utf-8 | Nutr Metab (Lond) | 2,005 | 10.1186/1743-7075-2-2 | oa_comm |
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Biomed Eng OnlineBioMedical Engineering OnLine1475-925XBioMed Central London 1475-925X-4-61566765410.1186/1475-925X-4-6ResearchLife-threatening ventricular arrhythmia recognition by nonlinear descriptor Sun Yan [email protected] Kap Luk [email protected] Shankar Muthu [email protected] Bioinformatics Institute, 138671 Singapore2 Biomedical Engineering Research Center, School of Electrical and Electronic Engineering, Nanyang Technological University, 639798 Singapore2005 24 1 2005 4 6 6 8 9 2004 24 1 2005 Copyright © 2005 Sun et al; licensee BioMed Central Ltd.2005Sun 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
Ventricular tachycardia (VT) and ventricular fibrillation (VF) are ventricular cardiac arrhythmia that could be catastrophic and life threatening. Correct and timely detection of VT or VF can save lives.
Methods
In this paper, a multiscale-based non-linear descriptor, the Hurst index, is proposed to characterize the ECG episode, so that VT and VF can be recognized as different from normal sinus rhythm (NSR) in the descriptor domain.
Results
This newly proposed technique was tested using MIT-BIH malignant ventricular arrhythmia database. The relationship between the ECG episode length and the corresponding recognition performance was studied. The experiments demonstrated good performance of the proposed descriptor. An accuracy rate as high as 100% was obtained for VT/VF to be recognized from NSR; for VT and VF to be recognized from each other, the recognition accuracy varies from 84.24% to 100%. In addition, the results were compared favorably against those obtained using Complexity measure.
Conclusions
There is strong potential for using the Hurst index for malignant ventricular arrhythmia recognition in clinical applications.
==== Body
Introduction
If a life-threatening ventricular tachycardia (VT) or ventricular fibrillation (VF) is detected promptly, a high energy electrical shock can be delivered to the heart, in an attempt to return the heart to a normal sinus rhythm (NSR). If a normal sinus rhythm is misinterpreted as VT or VF, leading to delivering of an unnecessary shock, it can damage the heart, causing fatal consequences to the patient. Therefore, correct and prompt detection of VT or VF is of great importance. However, the detection of these life-threatening cardiac arrhythmia is difficult because the waveform and frequency distribution of these life-threatening arrhythmia changes with the prolonged duration [1]. Furthermore, practical problems such as poor contact, movement, interference, etc, can produce artifacts that mimic these rhythms [2].
Till now, many linear techniques for VT/VF detection have been developed, such as the probability density function method [3], rate and irregularity analysis [4], analysis of peaks in the short-term autocorrelation function [5], sequential hypothesis testing algorithm [6,7], correlation waveform analysis [8], four fast template matching algorithms [9], VF-filter method [2,10], spectral analysis [1], and time-frequency analysis [11]. However, these methods exhibit disadvantages, some being too difficult to implement and compute for automated external defibrillators (AED's) and implantable cardioverter defibrillators (ICD's), and some only successful in limited cases. For example, the linear techniques [5,11] using the features of amplitude or frequency have shown their limits, since the amplitude of ECG signal decreases as the VF duration increases, and the frequency distribution changes with prolonged VF duration. Therefore, more sophisticated signal processing techniques are needed to fully describe and characterize VT and VF and facilitate the development of new detection schemes with high correct detection rate, or equivalently, with low false-positive and false-negative performance statistics.
Recent studies [12,13] have shown that the cardiac dynamics are complex and non-linear. Even if they could be described by a set of differential equations, they would be of high dimensionality. Normally, each heart beat is initiated by a stimulus from pacemaker cells in the SA node in the right atrium. The activation wave then spreads through the atria to the AV junction. Following activation of the AV junction, the cardiac impulse spreads to the ventricular myocardium through a specialized network, the His-Purkinje system. This branching structure of the conduction system is a self-similar tree with finely scaled details on a microscopic level. The spread of the depolarization wave is represented by the QRS complex in ECG. Spectral analysis of the waveform reveals a broadband of frequencies. To explain the inverse power-law spectrum, West has conjectured that the repetitive branches of the His-Purkinje system represent a fractal set in which each generation of the self-similar tree imposes greater detail onto the system [14]. The effect of the finely branching fractal network is to subtly decorrelate the individual pulses that superpose to form the QRS complex. The distribution in path lengths resulting from the fractal nature of the branches give rise to a distribution of decorrelation time. Some methods developed based on the theory of non-linear dynamics have been highlighted for the analysis of the signals generated from non-linear system [15]. Due to the complex and non-linear dynamical behavior of the cardiac conduction system, non-linear dynamics or non-linear mathematical models are considered to be suitable tools for the analysis of ECG signals. Non-linear techniques have been proven to be major cornerstones for understanding the ECG signals [13,16,17].
Some non-linear techniques [18-20] have been developed for life-threatening ventricular arrhythmia recognition. However, there are still many problems requiring solution. The computational demands for most of the existing algorithms are considerably high and a long ECG episode duration is needed. In order to strike a balance between lower computational burden and reliable recognition performance, a non-linear descriptor, the Hurst index, is proposed as a new tool in this study for recognition of the life-threatening ventricular arrhythmia. The Hurst index is defined in the multiscale domain as a feature to quantify the non-linear dynamical behavior (such as, self-similarity, roughness and irregularity) of the ECG signal for detecting the life-threatening ventricular arrhythmia.
ECG episodes with VT and VF from MIT-BIH malignant arrhythmia database [21] are tested for cardiac abnormality recognition. The data also included some NSR signals to check on the validity of the algorithm. Experimental results are compared with those obtained by a typically used non-linear technique, the Complexity measure, which has been shown to perform well for life-threatening ventricular arrhythmia recognition [20]. In this paper, the complexity measure is Zheng's complexity measure without exception. Detailed description of Zheng's complexity measure technique can be find in [20].
The present paper is organized as follows. Mathematical background on the proposed non-linear descriptor is given in Section. Methodology for the recognition of ventricular arrhythmia is described in Section. Section covers the experimental results and discussions. Lastly, a conclusion of the proposed study is given in Section.
Multiscale-based non-linear descriptor
Multiscale analysis is a useful framework for many signal processing tasks. Wavelet transform is a good tool for multiscale analysis, which allows the expansion of a signal from the time domain into the time-frequency domain. In this paper, the Hurst index, defined in multiscale space, is proposed for the characterization of ECG episodes.
The Hurst index, H, is a single scalar parameter describing the fractal Brownian motion (fBm) model, which is a useful model for nonstationary stochastic self-similar processes with long term dependencies over wide ranges of frequencies [22]. fBm is an extension of the ordinary Brownian motion, and is a zero-mean Gaussian nonstationary stochastic process BH(t), t ∈ ℝ, 0 <H < 1, [23]. Self-similarity is inherent to the fBm structure. The fractal dimension D is a commonly used parameter for measuring self-similarity. The relationship between the fractal dimension, D, and the Hurst index H is: D = S - H, where S is the topology dimension. For a one-dimensional signal, S = 2; for a two-dimensional image, S = 3 [24]. The fBm model has following features:
• It is non-stationary, which necessitates some time-dependent analysis.
E(BH(t)BH(s)) = σ2/2(|t|2H + |s|2H - |t - s|2H) (1)
where E(·) represents the expectation operator, σ is the standard deviation, t is a time variable, s is a time lag variable. Based on Equation (1), the variance of fBm, is computed as var(BH(t)) = σ2|t|2H.
• It is self-similar, which necessitates some scale-dependent analysis.
{BH(at)} ≜ aH BH(t), a ∈ ℝ+ (2)
where ℝ+ is the set of positive real numbers. ≜ means equality in distribution, which means that the fBm has stationary increments, and the probability properties of the process BH(t + s) - BH(t) only depend on the lag variable s. The scalar index H of fBm is related to the complexity and roughness of fBm samples.
Consider a discrete orthogonal wavelet decomposition of a given fBm, BH(t).
For any given resolution 2J, the wavelet mean-square representation of fBm is:
Computing the corresponding wavelet coefficients amounts to evaluating the following approximate coefficients aj[n] and detail coefficients dj[n]:
where φ(t) is the corresponding smooth function of wavelet ψ(t).
Flandrin et al. in [22] have deduced the following theorem: When normalized according to
Wavelet coefficients of fBm give rise to:
where Vψ(H) is constant, which depends on both the chosen wavelet and the fBm index H. It follows the power-law behavior of the wavelet coefficients' variance:
log2(var(dj[n])) = (2H + 1)j + constant (9)
Therefore, the fBm index H (and hence the associated fractal dimension D = 2 - H) can be easily obtained from the slope of this variance plotted as a function of scale in a log-log plot.
Life-threatening ventricular arrhythmia recognition by Hurst index
For each testing ECG episode, the following steps are performed:
• Perform wavelet decomposition and computation of its detail coefficients at different scales.
• Compute the Hurst index H according to Equation (9).
• Detect the life-threatening ventricular arrhythmia in the feature space of H.
In this study, the wavelet used is a quadratic spline wavelet with compact support and one vanishing moment. It is a first derivative of a smooth function [25], whose discrete Fourier transform is:
The low-pass and high-pass filters L(ω) and G(ω) are respectively:
The dyadic wavelet transform (WT) of a digital signal f(n) can be calculated with Mallat's algorithm [26] as follows:
where is a smoothing operator. is the wavelet transform of digital signal f(n). lk|k ∈ Z and gk|k ∈ Z are coefficients of a low-pass filter L(ω) and a high-pass filter G(ω), respectively, and, L(ω) = Σk∈Zlke-ikω, G(ω) = Σk∈Zgke-ikω. Based on the frequency analysis of the ECG characteristic waves [27], scale 2j (j = 1 to 4) are selected. For each experimental episode, its wavelet transform coefficient sets d1, d2, d3 and d4 corresponding to different scales 21, 22, 23, 24 are computed. The Hurst index H is then computed according to Equation (9). Smaller Hurst index corresponds to larger fractal dimension and more irregular signal.
Comparative Experimental Results and Discussions
Description of the test data
The database used in this study is the MIT-BIH malignant ventricular arrhythmia database [21] with a sample frequency of 250 Hz. Typical waveforms of VT and VF as well as NSR are shown in Figure 1 to 3. Selected ECG episodes with different lengths are tested for evaluating the performance of the life-threatening ventricular arrhythmia recognition using the Hurst index. Each ECG episode is characterized by the Hurst index H, computed by Equation (9). The statistical distribution of the Hurst indexes for characterizing different types of episodes is studied so that VT and VF can be recognized in the feature domain of the Hurst index. Recognition performance is measured by Sensitivity (SE), Specificity (SP) and Accuracy (ACR). They are defined as: Sensitivity = ; Specificity = ; Accuracy = . Where TP is true positive, the abnormal case being correctly recognized as abnormal one; FN is false negative, the abnormal case being wrongly recognized as normal one; TN is true negative, the normal case being correctly recognized as normal one; and FP is false positive, the normal case being wrongly recognized as abnormal one. Lastly, results are compared with that of Complexity measure technique.
Figure 1 Typical life-threatening ECG waveform of NSR
Figure 2 Typical life-threatening ECG waveform of VT
Figure 3 Typical life-threatening ECG waveform of VF
In this study, about 5076 ECG episodes are tested for performance evaluation of life-threatening ventricular arrhythmia recognition using the proposed Hurst index. Among them, 2588 cases are NSR episodes, 1390 cases are VT episodes, and 1098 are VF episodes. In order to explore the effect of the time series lengths on the recognition performance using the proposed Hurst index, analyzing was conducted using different lengths of ECG episodes from 1 sec to 5.5 sec with a difference of 0.5 sec. For each length, the whole dataset was randomly divided into two equal parts for training and testing, respectively. From a clinical point of view, it is essential to recognize and diagnose malignant ventricular arrhythmia as soon as possible. This calls for detection with as short a length of the time series as possible.
The statistical results, viz, the means and standard deviations for characterizing NSR, VT and VF episodes using the Hurst index are given in Table 1. As a comparison, the results by the complexity measure technique, are given in Table 2. Graphical descriptions of the results listed in Tables 1 and 2 are shown in Figure 4 and 5 respectively.
Table 1 Statistical results of Hurst index for episode characterization
Episode Length Hurst index
NSR VT VF
Mean SD Mean SD Mean SD
1 sec 0.6099 0.0981 0.8117 0.0775 0.8567 0.0579
1.5 sec 0.6206 0.0805 0.8269 0.0671 0.8597 0.0501
2 sec 0.6317 0.0619 0.8373 0.0558 0.8618 0.0438
2.5 sec 0.6349 0.0549 0.8398 0.0509 0.8682 0.0419
3 sec 0.6389 0.0458 0.8445 0.0409 0.8766 0.0399
3.5 sec 0.6389 0.0458 0.8445 0.0409 0.8766 0.0399
4 sec 0.6395 0.0436 0.8452 0.0403 0.8794 0.0395
4.5 sec 0.6398 0.04 0.8455 0.0397 0.8797 0.0392
5 sec 0.6399 0.035 0.8458 0.0391 0.8799 0.0387
5.5 sec 0.6399 0.035 0.8458 0.0388 0.8799 0.0386
Table 2 Statistical results of Hurst index for episode characterization
Episode Length Complexity measure
NSR VT VF
Mean SD Mean SD Mean SD
1 sec 0.1674 0.0433 0.2775 0.0428 0.2798 0.0498
1.5 sec 0.1476 0.0403 0.2562 0.0428 0.2601 0.0498
2 sec 0.1319 0.037 0.2413 0.0335 0.2454 0.0432
2.5 sec 0.1245 0.0366 0.2311 0.0335 0.239 0.0432
3 sec 0.1192 0.0363 0.2229 0.0349 0.2351 0.037
3.5 sec 0.1129 0.0348 0.2168 0.0349 0.2298 0.037
4 sec 0.1095 0.0332 0.2149 0.0342 0.2242 0.0343
4.5 sec 0.1071 0.0321 0.2136 0.0342 0.2205 0.0343
5 sec 0.1056 0.0315 0.2129 0.0342 0.2187 0.0341
5.5 sec 0.1056 0.0313 0.2129 0.0339 0.2187 0.0341
Figure 4 The mean and standard deviation values for characterizing NSR, VT and VF episodes using the Hurst index
Figure 5 The mean and standard deviation values for characterizing NSR, VT and VF episodes using the Complexity measure
From the results shown in Figure 4 and 5, the following observation can be made.
• As the episode length increases, the mean of Hurst index for every type of rhythm basically increases and tends to approach a relatively stable value, while the standard deviation decreases gradually.
• For a particular episode length, from NSR to VT then to VF, the corresponding Hurst index increases gradually. The increase from NSR to VT is more than the increase from VT to VF.
• As the episode length increases, the mean of Complexity measure for every type of rhythm basically decreases and tends to approach a relatively stable value, while the standard deviation decreases gradually.
• For a particular episode length, from NSR to VT then to VF, both the Hurst index and the Complexity measure increase gradually, in which, the increase from NSR to VF is far more than the increase from VT to VF.
• The mean values of Hurst index vary slower than those of Complexity measure as the episode length increases from 1 sec to 5.5 sec. It is concluded that the Hurst index is more stable than the Complexity measure with respect to episode lengths.
Using the Hurst index for VT or VF recognition from NSR with different episode lengths, there is no false detection, meaning that the VT/VF can be totally correctly recognized from NSR without exception. For the Complexity measure, when the length of ECG episode is longer than 1 sec, it has as good performance as the Hurst index; when the length of the ECG episode is 1 sec, there is 6 false negatives and 27 false positives; when the length of the ECG episode is 1.5 sec, there is 1 false negatives and 5 false positives. The statistical values of SE, SP and ACR for VT/VF recognition from NSR using the Hurst index are all 100%. Hence, the Hurst index can be used to detect VT and VT earlier.
As for VF differentiation from VT, the statistical values of SE, SP and ACR for different episode lengths using the Hurst index and the Complexity measure, are shown in Table 3. The computational time of the Hurst index and the Complexity measure for different ECG episode length are presented in Table 4. From Table 3, the following conclusions can be obtained:
Table 3 Statistical values of SE, SP and ACR for VF differentiation from VT
Episode Length Hurst index Complexity measure
SE SP ACR SE SP ACR
1 sec 0.8351 0.8482 0.8424 0.8242 0.8302 0.8275
1.5 sec 0.8780 0.8698 0.8734 0.8689 0.8597 0.8637
2 sec 0.9080 0.8834 0.8942 0.9007 0.8798 0.8890
2.5 sec 0.9408 0.9158 0.9268 0.9381 0.9194 0.9277
3 sec 0.9608 0.9439 0.9513 0.9654 0.9489 0.9562
3.5 sec 0.9754 0.9669 0.9707 0.9818 0.9734 0.9771
4 sec 0.9854 0.9849 0.9851 0.9918 0.9885 0.9899
4.5 sec 0.9936 0.9914 0.9924 1 0.9986 0.9992
5 sec 1 0.9978 0.9988 1 1 1
5.5 sec 1 1 1 1 1 1
Table 4 Computation time comparison in seconds
Length of episode Hurst index Complexity measure Length of episode Hurst index Complexity measure
1 sec 0.0546 0.0654 1.5 sec 0.0697 0.0824
2 sec 0.0794 0.1143 2.5 sec 0.0933 0.1538
3 sec 0.1168 0.2176 3.5 sec 0.1401 0.2991
4 sec 0.1885 0.4003 4.5 sec 0.2407 0.609
5 sec 0.2803 0.6833 5.5 sec 0.3122 0.7792
• The performance on differentiating VT and VF is worse than the performance of VT/VF recognition from NSR, for both the Hurst index and the Complexity measure.
• The recognition performance by either descriptors improves as the length of ECG episode increases.
• When the length of ECG episode is less than or equal to 2 sec, the recognition performance for the Hurst index is better. When the length of ECG episode is longer than 2 sec and less than 5 sec, the recognition performance for the Complexity measure is better. When the length of ECG episode is longer than 5 sec, VT and VF can be 100% differentiated with either descriptor, the recognition performance for both descriptors are same.
According to Table 4, the computational time for the Hurst index is less than that for the Complexity measure. These two algorithms are programmed using MATLAB 5.3 running on a SUN SPARC-333MHz workstation. The computational burden for the Hurst index is O(N log2 N), while the computational burden for the complexity is O(N2), where N is the length of ECG episode. It is noted that with more powerful computer programming in C, the computational speed will be further improved.
Time is an important factor for saving lives in clinical situations, therefore, algorithm with less computational burden is obviously preferred. In addition, using short ECG episode length is preferred for earlier detection of arrhythmia (such as VT/VF). Based on the experimental results, it is observed that the Hurst index has a better potential for clinical adaptation than the Complexity measure.
Conclusions
In this paper, a new technique based on multiscale analysis and non-linear dynamics was presented for VT and VF recognition. Hurst index defined across multiscale was proposed for characterizing ECG episode so that life-threatening arrhythmia can be recognized. Furthermore, upon applying to the MIT-BIH malignant ventricular arrhythmia database, the performance for malignant arrhythmia recognition using Hurst index was compared with that using Zheng's complexity measure. The Hurst index requires less computation and is more reliable in detecting VT and VF with short ECG episode. There is strong potential for using the Hurst index for malignant ventricular arrhythmia recognition in clinical applications.
Authors' contributions
SY conceived the study, performed data analysis and drafted the manuscript. CKL and KSM guided the study, helped the analysis and interpretation of the results, and critically reviewed the manuscript. All authors read and approved the final script.
Acknowledgments
The authors wish to extend their sincere appreciation to Nanyang Technological University, Singapore for supporting the present work. The authors also acknowledge the clinical collaboration from Singapore General Hospital.
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| 15667654 | PMC549211 | CC BY | 2021-01-04 16:37:34 | no | Biomed Eng Online. 2005 Jan 24; 4:6 | utf-8 | Biomed Eng Online | 2,005 | 10.1186/1475-925X-4-6 | oa_comm |
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Theor Biol Med ModelTheoretical Biology & Medical Modelling1742-4682BioMed Central London 1742-4682-2-31569847810.1186/1742-4682-2-3ResearchIn vitro bioassay as a predictor of in vivo response Barnard Ross [email protected] Konstantin G [email protected] Department of Biochemistry, The University of Queensland, Brisbane, Qld 4072, Australia2 UNESCO Chair in healthy life for sustainable development, Moscow State University of Medicine and Dentistry, Delegatskay ulitsa, 20/1, 103473, Moscow, Russian Federation2005 7 2 2005 2 3 3 24 11 2004 7 2 2005 Copyright © 2005 Barnard and Gurevich; licensee BioMed Central Ltd.2005Barnard and Gurevich; 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 is a substantial discrepancy between in vitro and in vivo experiments. The purpose of the present work was development of a theoretical framework to enable improved prediction of in vivo response from in vitro bioassay results.
Results
For dose-response curve reaches a plateau in vitro we demonstrated that the in vivo response has only one maximum. For biphasic patterns of biological response in vitro both the bimodal and biphasic in vivo responses might be observed.
Conclusion
As the main result of this work we have demonstrated that in vivo responses might be predicted from dose-effect curves measured in vitro.
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Background
In vitro bioassay is very useful in biomedical experiments. It has the potential to yield very important data about molecular mechanism of action of any biologically active compounds. However, the major challenge for such experiments is extrapolation to in vivo responses. Unfortunately, there is a substantial discrepancy between in vitro and in vivo experiments, and there is a paucity of work directed to prediction of in vivo response from in vitro bioassay. So, the purpose of the present work was development of a theoretical framework to enable improved prediction of in vivo response from in vitro bioassay results.
Results
A survey of literature revealed that most cases of dose-effect curves for in vitro experiments fall into three classes. They are:
• monophasic response;
• biphasic pattern;
• bimodal or polymodal dose-effect curve.
MONOPHASIC RESPONSE is the form most commonly reported in articles on in vitro bioassay. In these cases, with increasing dose of biologically active substance (BAS), the cellular response increases to a maximum (dose-response curve reaches a plateau). The most general schemes exhibiting this class of response can be classified as 3 classes:
(I) BAS regulation of enzyme activity,
(II) Ligand interaction with one type of receptor, and
(III) Ligand interaction with negatively cooperative receptors.
We will consider these three classes:
(I): BAS might regulate enzyme activity. It might be:
• substrate:
E+S ←→ ES → E+P → cell response, (scheme 1)
where E is enzyme, S is substrate, ES is enzyme-substrate complex, P is product. Cellular response is suggested to be proportional to product concentration.
Scheme (2) approximates the classic Michaelis scheme [1].
• enzyme activator (A)
E+S ←→ ES → E+P → cell response
E+A ←→ EA (scheme 2)
EA+S ←→ EAS → EA+P → cell response increasing,
Scheme (3) is characteristic of many BAS. The majority of these groups are vitamins and minerals, which are known to be enzyme cofactors and serve to increase enzyme activity.
• enzyme inhibitor (I)
E+S ←→ ES → E+P → cell response
E+I ←→ EI → no cell response, (scheme 3)
For example, there is the large class of drugs, whose action can be described with the help of scheme (4). This class is called "inhibitors of angiotensin-converting enzyme". These drugs are commonly used for hypertension treatment and prevention [2].
(II) Ligand interaction with one type of receptors:
L+R ←→ LR → cell response (scheme 4)
where L is ligand (BAS), R is receptor, LR is ligand-receptor complex.
Scheme (4) is "classic" receptor theory as described by Clark (1937) [3].
For example, kinetic schemes of such type were proved in the case of estrogen regulation of gene expression [4], apolipoprotein AI, CII, B and E synthesis [5].
(III) Ligand interaction with negative cooperative receptors
L+R ←→ LR
L+LR ←→ L2R → cell response (5)
where L2R is complex ligand-receptor complexes.
Scheme (5) is characteristic for insulin receptors [6].
Kinetic equations for schemes (1)–(5) are well known [7]. They include "classic" Michaelis [1] and Clark [3] equations. It can be shown, due to the first order Taylor series, equations for the schemes (1)–(4) can be re-formulated from particle counter theory as:
y = B*x/(1+A*x) (6)
and for scheme (5):
y = B*x2/(1+A*x2) (7)
where x is incoming signal (x is BAS concentration). For scheme (1) x is substrate concentration, for scheme (2) it is activator concentration, for scheme (3) it is inhibitor concentration, for schemes (4) and (5) it is ligand concentration. y is cellular response for the in vitro system. A and B are scaling coefficients.
The BAS concentration in the whole organism changes as a function of time according to equation (14) (see Methods.) i.e.
x(t) = C(t) = C0[exp(-kelγt)-exp(-k1t)] (8)
We used equation (8) as the incoming signal, substituted this into equations (6) and (7) and solved analytically using Math Cad 8 graphing software (MathSoft Inc., Cambridge, MA, USA) to predict in vivo responses for monomodal in vitro dose-effect curves for schemes (1)–(5). We used illustrative values from works [8,9] and demonstrated that for such in vitro dose-effect curves, the in vivo response has only one maximum (fig. 1).
Figure 1 In vivo response for monophasic dose-effect curves measured in vitro. B = 1. a) equation (6), b) equation (7). kel = 0.0714 1/min, k1 = 0.0277 1/min, C0 = 1 nM, γ = β. Illustrative values for fig. 1, 2, 4 taken from Veldhuis et al., (1993) [8] and similar to those measured by Baumann et al., (1987)9 for the clearance of growth hormone (GH).
We define β (degree of conjugation) as the proportion of BAS that is free of binding proteins and is available to interact with cognate receptors. The larger is β, the larger the proportion of "free" BAS (see Methods). For equation (6) the value of this maximum is increasing as β increases; for equation (7) this value is maximum for mid-range β values.
BIPHASIC PATTERNS OF BIOLOGICAL RESPONSE
In this case, in in vitro experiments the low doses of BAS stimulate cellular response, and the high doses inhibit it. So, a maximum is observed on the dose-response curve. The most common kinetic schemes for such response are:
• Negative back loop (substrate and product inhibition):
a) E+S ←→ ES → E+P → cellular response
ES+S ←→ ES2 (9)
b) E+S ←→ ES → E+P → cellular response
ES + P ↔ ESP
Such schemes are characteristic of glucose metabolism [1].
• Presence of two receptor types: one type stimulates cellular response, another type inhibits it.
L+R ←→ LR → "positive" cellular response
L+R' ←→ LR' → "negative" cellular response (10)
where R are receptors of the first type, R' are receptors of the second type, LR, LR' are ligand-receptor complexes with different receptor types.
This mechanism has been proven for estrogen regulation of nitric oxide synthase (activity in the rat aorta [10]; protein pS2 expression in hormone-dependent tumors [11] and so on.
• Desensitization of cellular receptors
L+R ←→ LR → positive cellular response
LR → decrease in receptor number (11)
It has been suggested, that mechanism (11) is basic for drug tolerance [7]. For example, this mechanism was described for uretal cell stimulation by 17-β-estradiol. Before estradiol treatment, expression of estrogen receptors mRNA in cells was much higher then after 12-days estradiol administration [12]. It is well known that endogenous opioid receptors become down regulated after chronic exposure to exogenous opioids [13] and receptor down-regulation has often been observed to follow acute exposure to hormones including growth hormone [14].
• Change of effector's molecule conformation:
"Active" conformation + ligand suplus ←→ "Passive" conformation (12)
Scheme (12) was suggested by Bootman and Lipp (1999) [15] for Ca++ regulation of 1,4,5-trisphosphate activity. The authors suggested that Ca++ surplus induces a change in Ca++-channel conformation from "open" or "active" to "closed" or "passive" [15].
For schemes (9)–(12), due to the first order Taylor series, this kinetic equation can be derived:
y = A*x*exp(-B*x) (13)
Using equation (13), we obtained a prediction of in vivo biphasic dose-effects curves (fig. 2). As is apparent from the figure, the magnitude and the analytical appearance of in vivo response is affected by the dose of BAS and its degree of conjugation (β). Both the bimodal and biphasic in vivo responses might be observed for biphasic dose-effect curves. Changes of dose of BAS concentration or its conjugation with blood proteins (or their concentration) might dramatically change the form of in vivo response. For the simulations shown in Figure 2 we used values for kel and k1 and blood volume (4.9 liters) based on measurements by Baumann et al. (1987) [9] and Veldhuis et al. (1993) [8] for growth hormone secretion, clearance and pulsatility. Polymodal biological responses are commonly observed in biological systems. It has been demonstrated, that in some experimental systems, administration of a single, bolus dose of hormone produces a polymodal response [16].
Figure 2 In vivo response for biphasic dose-effect curves measured in vitro. B = 1. a) variation of β, C0 = 1 nM, b) variation of C0, β = .388. kel = 0.0714 1/min, k1 = 0.0277 1/min, γ = β.
Bimodal dose-effect curves are usually observed for BAS with regulatory activity [17,18]. The mechanism of their formation is still unclear. From our point of view, bimodal dose-response curve might be described by superposition of two biphasic dose-effect curves with different B value. This might be observed in cascade system of signal transduction and amplification. If x regulate intermediate z formation in biphasic way with B1, and z has biphasic response on y formation with B2, then if B1<B2, summary dose-effect curve (y concentration from x) is bimodal (fig. 3). Differences in B1 and B2 value define the maximum points. For example, with B2 increasing, the interpeak distance will also increase.
Figure 3 Possible mechanism of bimodal dose-effect curve formation for in vitro systems. a) intermediate z formation as function of x concentration, B1 = 1, b) final product y formation as function of z concentration, B2 = 5, c)summary dose-response curve. See comments in the text of the article.
For systems, which have bimodal dose-effect curve in vitro, the polymodal response in vivo is observed (fig. 4). The form of this response might be change to "seems constant" due to BAS concentration of β value. The differences of maximum values are observed, this differences is time-dependent: the highest maximum is observed with the longest observation. It might be demonstrated, that with change of B2 value to 20, only bimodal in vivo response will be observed. So, the form and the value of maximums are dependent from the dose of BAS and degree of conjugation.
Figure 4 In vivo response for bimodal dose-effect curves measured in vitro. B1 = 1, B2 = 5. a) variation of β, C0 = 1 nM, b) variation of C0, β = .388. kel = 0.0714 1/min, k1 = 0.0277 1/min, γ = β.
Discussion
Analogues of hormones are commonly used in medicine for hormone replacement therapy (for example in post-menopausal women), for oral contraception, as anabolic drugs, for asthma therapy and so on [2]. But engineered modifications of hormones, growth factors or their analogs are likely to differ from the native analogues in their affinity for binding proteins. In view of this, an important practical consequence of our simulations results are that the testing of newly designed hormones in in vivo systems (with endogenous binding proteins) will require measurements of acute biological response at multiple concentration and time points. For longer-term responses requiring protein synthesis (such as a secretion of body mass or longitudinal bone growth), it could be argued that such multiple time point studies would not be as important. However, in so far as long term biological responses are the consequence of critical initial events which may require threshold concentrations of free hormone, or repeated patterns of hormone exposure over prolonged periods [16,19], this assumption may not be justified.
Another application of our work may be the study of hormone functions in glandular tumour disorders. With these disorders, there is usually serious metabolic or hormonal dysfunction. From our point of view, it may be not only due to gland biosynthesis of abnormal hormone. Tumour-produced hormones may not differ structurally from their normal analogues. The dysfunctional occurs due to abnormal concentrations of hormones, which are synthesised by tumours. As it follows from our results, changes in concentrations can dramatically change the form and value of biological response. On the other hand, in many tumour disorders the concentrations of binding proteins are changed. For example, in ovarian carcinoma the changes of sex binding protein and ratio free/bound sex hormones (β) are observed [20]. As follows from our results, this can dramatically change the biological response to such hormones, i.e. apparent biological functions. So with testing in vitro such hormones seems to be normal (and they may be normal), but in vivo they may have abnormal effects due to changes of their binding protein concentration, or ratio free/bound hormone.
Conclusion
So, as a result of this work we have demonstrated that in vivo responses might be predicted from dose-effect curves measured in vitro. For monophasic curves, in vivo response is proportional to BAS concentration. For the most complex in vitro curves, the value and the form of in vivo response depends in a predictable way on the dose of BAS and its degree of conjugation.
Methods
To obtain the discussed results we used linear pharmacokinetics model:
where: m1(t) mass of biologically active substance (BAS) in the place of infusion, m2(t) mass of BAS in compartment (blood), k1,kel constants of hormone diffusion from place of infusion to blood and excretion form blood (accordingly).
Many of biologically active substances are conjugate into complexes with blood proteins (for example: GH, nerves growth factor, IGF-1):
B+P ⇔K HP (15)
where B is BAS, P is blood protein, BP is BAS-protein complex, K is dissociation constant.
For many BAS, concentration of free (not bound with blood proteins) BAS is equal to:
[B] ≈β [B0] (16)
where β is constant ("degree of conjugation"), [B] is concentration of free BAS, [B0] is initial concentration of BAS. If β = 1 then BAS dose not conjugate with protein. If β = 0 then all BAS is in conjugate form.
It may be that only conjugate BAS (for example, bilirubin), or only unconjugated BAS can be excreted form the blood (for example, sex hormones). This means that for scheme (14) the law of mass action will be written in the next way:
dm1/dt = -k1m1, m1(0) = M
dm2/dt = k1m1 - γkelm2, m2(0) = 0 (17)
where γ is a constant. γ = 1-β if only conjugate form of BAS can be excreted and γ = β if only unconjugated form is excreted.
But γ is a constant with respect to t: γ = const(t). This means that solution of system (17) is:
C(t) = C0[exp(-kelγt)-exp(-k1t)] (18)
where C(t) is BAS concentration in the blood compartment (C = m2/V, V = const (about 5 liters) is blood volume), C0 is seems initial BAS concentration (C0 = M/V).
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| 15698478 | PMC549212 | CC BY | 2021-01-04 16:39:26 | no | Theor Biol Med Model. 2005 Feb 7; 2:3 | utf-8 | Theor Biol Med Model | 2,005 | 10.1186/1742-4682-2-3 | oa_comm |
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BMC GenomicsBMC Genomics1471-2164BioMed Central London 1471-2164-6-91567606610.1186/1471-2164-6-9Research ArticleInter-species horizontal transfer resulting in core-genome and niche-adaptive variation within Helicobacter pylori Saunders Nigel J [email protected] Prawit [email protected] John F [email protected] Stephen A [email protected] Bacterial Pathogenesis and Functional Genomics Group, The Sir William Dunn School of Pathology, University of Oxford, South Parks Road, Oxford, OX1 3RE, UK2 Department of Computer Science, University of Warwick, Coventry, CV4 7AL,UK3 Oxford University Bioinformatics Centre, Sir William Dunn School of Pathology, University of Oxford, South Parks Road, Oxford, OX1 3RE, UK2005 27 1 2005 6 9 9 11 6 2004 27 1 2005 Copyright © 2005 Saunders et al; licensee BioMed Central Ltd.2005Saunders 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
Horizontal gene transfer is central to evolution in most bacterial species. The detection of exchanged regions is often based upon analysis of compositional characteristics and their comparison to the organism as a whole. In this study we describe a new methodology combining aspects of established signature analysis with textual analysis approaches. This approach has been used to analyze the two available genome sequences of H. pylori.
Results
This gene-by-gene analysis reveals a wide range of genes related to both virulence behaviour and the strain differences that have been relatively recently acquired from other sequence backgrounds. These frequently involve single genes or small numbers of genes that are not associated with transposases or bacteriophage genes, nor with inverted repeats typically used as markers for horizontal transfer. In addition, clear examples of horizontal exchange in genes associated with 'core' metabolic functions were identified, supported by differences between the sequenced strains, including: ftsK, xerD and polA. In some cases it was possible to determine which strain represented the 'parent' and 'altered' states for insertion-deletion events. Different signature component lengths showed different sensitivities for the detection of some horizontally transferred genes, which may reflect different amelioration rates of sequence components.
Conclusion
New implementations of signature analysis that can be applied on a gene-by-gene basis for the identification of horizontally acquired sequences are described. These findings highlight the central role of the availability of homologous substrates in evolution mediated by horizontal exchange, and suggest that some components of the supposedly stable 'core genome' may actually be favoured targets for integration of foreign sequences because of their degree of conservation.
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Background
Helicobacter pylori is a bacterial pathogen associated with gastritis, peptic ulcers, gastric adenocarcinoma, and rare lymphomas [1]. It has a highly panmictic population structure in which homologous recombination makes the predominant contribution to sequence differences within a highly diverse population structure [2]. The acquisition of genes from other strains and species is by far the most rapid evolutionary process. This occurs frequently without loss of existing functions, is central to the evolution of niche-adaptive and pathogenic characteristics of bacteria, and greatly influences inter-strain differences in gene complement [3-5]. In this context, it is notable that none of the traits typically used to differentiate E. coli from Salmonella can be attributed to point mutation genes but are broadly attributable to horizontal exchange [6]. H. pylori is relatively unusual in that it is a naturally transformable Gram-negative species that does not appear to have a species-specific DNA uptake sequence and appears to rely upon its niche separation as a transformation barrier [7]. Disease associated H. pylori strains have been divided into two types, type I being those that carry the cag pathogenicity island [8] (cag PAI), which has a foreign species origin, and are associated with more severe disease.
Dinucleotide composition is highly stable within a genome and can distinguish between sequences from different species. Based upon its constancy the species composition is referred to as a 'genome signature' [9,10]. This characteristic has been applied to assessments of DNA metabolic processes such as methylation and base conversion, DNA structure, and evolutionary relationships. It has also become established as a method for the identification of sequences that have been acquired by inter-species horizontal transfer. For example, lateral transfer has recently been shown using these methods for a tryptophan pathway operon [11], the gain of additional metabolic functions in Pseudomonas putida [12], a determination that many gain of function genes have been acquired by E. coli rather than lost from S. typhi [13], and more recently developed Bayesian methods based upon similar premises have been used to assess global signatures and determine the origins of some lateral transfer events [14,15]. However there are problems associated with this and other methods that use progressive 'walking windows', and the larger the window the greater the problems. These result from the inclusion of intergenic sequence, the inability to distinguish divergences due to a single highly divergent gene from that from a cluster of less divergent ones, and an inability to identify the limits of the abnormal regions. In practice additional features are necessary to determine the ends of such regions, such as the location of repeats typical of pathogenicity islands in H. pylori [16], or comparisons with other sequences as in N. meningitidis strain MC58 [17]. In addition, divergence scores are influenced by the size of the sampling window used such that sampling effects limit analysis of sequences shorter than about 800 bp (data not presented), and the need to use fixed window sizes prevents gene by gene studies.
We describe the use of a linear implementation of signature analysis that can efficiently address a range of walking window sizes using dinucleotide signatures (DNS) and longer signatures. In addition, use of a new approach based upon classical text analysis that allows analysis of genomes gene-by-gene is described. Analysis of H. pylori sequences, combined with comparisons of the identified genes between genomes, reveals complex changes that influence both niche-adaptive and core functions illustrating a previously unpredicted range of functions which are continuously undergoing variation and selection.
Results and discussion
Genes were ranked on the basis of their divergence from the mean genome composition. The degree of divergence that is indicative of acquisition from other species is not an absolute. The frequency with which genes are acquired, the untypicality of the donated material, and the rate at which they are ameliorated to the host sequence composition influence it. Strains J99 and 26695 had 53 (Table 1) and 60 (Table 4) genes respectively with DNS that were >2 SD from the mean. Those with annotated functions included genes from the cag pathogenicity island (6 and 5), vac and related toxins (3 and 4), and restriction-modification genes (2 and 4). On the basis of the similarities determined in the H. pylori strain J99 sequence annotation, 7 of the most divergent genes as determined by DNS are not present in strain 26695. Likewise, 2 of the 50 most divergent genes in strain 26695 are not present in strain J99. This is consistent with the identification of genes acquired from other species that have not extended to both sequenced strains. It also suggests that a significant proportion of the 6 to 7% of genes unique to one or other strain [18] are inherent to the Helicobacter gene pool, but are variably present in different strains rather than reflecting recent foreign origins. Comparisons of a selection of identified orthologous genes in the two strains are shown in Figure 1.
Table 1 The 53 most divergent (>2 SD) genes in H. pylori strain J99 by DNS showing their ranking in strain 26695 and in TNS and HNS analysis
DNS order JHP # annotation 26695 # 26695 DNS order TNS order HNS order
1 JHP0952 hypothetical protein HP0427 14 3 1355
2 JHP0476 cag pathogenicity island protein (cag7) HP0527 1 2 2
3 JHP0556 vacuolating cytotoxin (vacA) paralog HP0609/10 4/13 5 4
4 JHP0274 vacuolating cytotoxin (vacA) paralog HP0289 2 6 5
5 JHP0305 hypothetical protein HP0322 3 8 10
6 JHP0942 hypothetical protein HP0996 5 13 27
7 JHP0856 vacuolating cytotoxin (vacA) paralog HP0922 6 9 6
8 JHP0050 hypothetical protein HP0058 88 7 84
9 JHP1300 hypothetical protein HP1408 15 1 1
10 JHP1044 hypothetical protein HP1116 8 14 8
11 JHP0928 hypothetical protein NAH - 12 9
12 JHP0074 hypothetical protein HP0080 9 32 125
13 JHP0440 hypothetical protein HP0488 7 16 17
14 JHP1042 hypothetical protein HP1115 20 25 694
15 JHP1321 histidine and glutamine-rich metal-binding protein HP1432 46 4 49
16 JHP0934 hypothetical protein NAH - 15 95
17 JHP0495 cag island protein (cagA) HP0547 31 20 12
18 JHP0931 topoisomerase I (topA 3) NAH - 18 20
19 JHP0693 hypothetical protein HP0756 24 59 1490
20 JHP0632 N-methylhydantoinase HP0696 19 44 36
21 JHP0471 cag pathogenicity island protein (cag3) HP0522 11 35 62
22 JHP0438 outer membrane protein HP0486 26 67 145
23 JHP0026 hypothetical protein HP0030 45 36 64
24 JHP1084 outer membrane protein (omp26) HP1157 34 17 24
25 JHP0481 cag island protein (cagT) HP0532 23 70 558
26 JHP0052 hypothetical protein HP0059 43 24 120
27 JHP0336 hypothetical protein HP1089 12 51 54
28 JHP1426 iron(III) dicitrate transport protein (fecA) HP1400 32 78 111
29 JHP0174 hypothetical protein HP0187 / 8 / 6 47&1127&596 88 90
30 JHP1297 type III restriction enzyme (res) NAH - 63 28
31 JHP0953 hypothetical protein NAH - 26 1463
32 JHP0067 urease beta subunit (urea amidohydrolase) (ureB) HP0072 21 37 70
33 JHP0941 integrase/recombinase (xerD) HP0995 25 100 541
34 JHP0548 flagellin A (flaA) HP0601 33 40 154
35 JHP0299 hypothetical protein HP061/2 230&765 11 275
36 JHP1033 hypothetical protein HP1106 59 262 342
37 JHP1409 type II restriction enzyme (methyltransferase) NAH - 55 15
38 JHP0626 iron(III) dicitrate transport protein (fecA) HP0686 62 89 47
39 JHP0940 hypothetical protein NAH - 53 393
40 JHP1253 hypothetical protein HP1333 40 75 384
41 JHP0132 cytochrome oxidase (cbb3 type) (fixN) HP0144 27 206 209
42 JHP0842 hypothetical protein HP0906 42 29 21
43 JHP0925 hypothetical protein NAH - 130 990
44 JHP0613 hypothetical protein HP0669 69 42 33
45 JHP0565 DNA mismatch repair protein (mutS) HP0621 22 227 82
46 JHP1363 DNA polymerase I (polA) HP1470 30 81 46
47 JHP0489 cag island protein (cagH) HP0541 71 137 398
48 JHP1260 siderophore-mediated iron transport protein (tonB) HP1341 85 1260 402
49 JHP0492 DNA transfer protein (cagE) HP0544 104 95 50
50 JHP1121 DNA-directed RNA polymerase, beta subunit (rpoB) HP1198 84 23 16
51 JHP1434 DNA repair protein (recN) HP1393 35 177 160
52 JHP0491 cag island protein (cagF) HP0543 82 170 828
53 JHP0191 hypothetical protein HP0205 57 33 7
Genes with > 2 SD divergence indicated in bold
NAH indicates No Annotated Homologue in the other sequence
Table 4 Top 60 most divergent (>2 SD) genes by DNS in H. pylori strain 26695 plus those additional genes in the top 50 genes from TNS and HNS
DNS order annotation HP# J99 # J99 DNS order TNS order HNS order
1 cag pathogenicity island protein (cag7) HP0527 JHP0476 2 1 1
2 vacuolating cytotoxin (vacA) paralog HP0289 JHP0274 4 2 4
3 poly E-rich hypothetical protein HP0322 JHP0305 5 8 5
4 hypothetical protein HP0609 JHP0556* 3 6 9
5 hypothetical protein HP0996 JHP0942 6 14 46
6 vacuolating cytotoxin (vacA) paralog HP0922 JHP0856 7 5 3
7 hypothetical protein HP0488 JHP0440 13 10 12
8 hypothetical protein HP1116 JHP1044 10 11 13
9 hypothetical protein HP0080 JHP0074 12 18 122
10 hypothetical protein HP0489 JHP0441 115 36 582
11 cag pathogenicity island protein (cag3) HP0522 JHP0471 21 48 100
12 hypothetical protein HP1089 JHP0336 27 67 59
13 vacuolating cytotoxin (vacA) paralog HP0610 JHP0556* 3 12 17
14 hypothetical protein HP0427 JHP0952 1 3 737
15 hypothetical protein HP1408 JHP1300 9 4 738
16 type III restriction enzyme R protein (res) HP0592 NAH - 30 35
17 hypothetical protein HP0119 NAH - 7 2
18 vacuolating cytotoxin (vacA) HP0887 JHP0819 59 25 34
19 N-methylhydantoinase HP0696 JHP0632 20 35 43
20 hypothetical protein HP1115 JHP1042 14 33 866
21 urease beta subunit (urea amidohydrolase) (ureB) HP0072 JHP0067 32 38 87
22 DNA mismatch repair protein (MutS) HP0621 JHP0565 45 137 64
23 cag island protein (cagT) HP0532 JHP0481 25 87 693
24 hypothetical protein HP0756 JHP0693 19 71 1548
25 integrase/recombinase (xerD) HP0995 JHP0941 33 39 448
26 outer membrane protein HP0486 JHP0438 22 147 142
27 cytochrome oxidase (cbb3 type) (fixN) HP0144 JHP0132 41 102 168
28 type IIS restriction enzyme R and M protein (ECO57IR) HP1517 NAH - 42 14
29 DNA transfer protein (cagE) HP0441 JHP0492 49 51 22
30 DNA polymerase I (polA) HP1470 JHP1363 46 77 54
31 cag island protein (cagA) HP0547 JHP0495 17 15 7
32 iron(III) dicitrate transport protein (fecA) HP1400 JHP1426 28 99 129
33 flagellin A (flaA) HP0601 JHP0548 34 40 180
34 outer membrane protein (omp26) HP1157 JHP1084 24 17 25
35 DNA repair protein (recN) HP1393 JHP1434 51 154 207
36 type I restriction enzyme R protein (hsdR) HP0464 NAH - 90 26
37 cell division protein (ftsK) HP1090 JHP0335 67 181 90
38 hypothetical protein HP1003 NAH - 61 170
39 histidine-rich, metal binding polypeptide (hpn) HP1427 NAH - 26 1449
40 hypothetical protein HP1333 JHP1253 40 53 296
41 hypothetical protein HP0788 JHP0725 68 72 256
42 hypothetical protein HP0906 JHP0842 42 22 16
43 hypothetical protein HP0059 JHP0052 26 21 320
44 GMP reductase (guaC) HP0854 JHP0790 107 169 451
45 hypothetical protein HP0030 JHP0026 23 24 39
46 histidine and glutamine-rich metal-binding protein HP1432 JHP1321 15 9 1432
47 hypothetical protein HP0186 JHP0174 29 130 276
48 fucosyltransferase HP0651 JHP0596 105 43 75
49 translation elongation factor EF-Tu (tufB) HP1205 JHP1128 81 64 166
50 virulence associated protein homolog (vacB) HP1248 JHP1169 79 164 160
51 hypothetical protein HP0449 NAH - 81 449
52 type III restriction enzyme R protein HP1371 JHP1285 55 119 23
53 virB4 homolog (virB4) HP0459 NAH - 49 28
54 2',3'-cyclic-nucleotide 2'-phosphodiesterase (cpdB) HP0104 JHP0096 56 73 68
55 hypothetical protein HP1479 JHP1372 135 153 127
56 RNA polymerase sigma-70 factor (rpoD) HP0088 JHP0081 62 55 31
57 hypothetical protein HP0205 JHP0191 53 78 8
58 hypothetical protein HP1143 JHP1071 78 29 41
59 hypothetical protein HP1106 JHP1033 36 272 277
60 cag pathogenicity island protein (cag13) HP0534 JHP0482 71 225 1021
63 DNA topoisomerase I (topA) HP0440 NAH - 149 24
68 outer membrane protein (omp3) HP0079 JHP0073 796 45 99
69 hypothetical protein HP0669 JHP0613 44 60 42
74 cag pathogenicity island protein (cag8) HP0528 JHP0477 72 50 27
75 hypothetical protein HP0453 NAH - 58 10
84 DNA-directed RNA polymerase, beta subunit (rpoB) JHP1121 50 23 19
91 hypothetical protein HP1142 JHP1070 60 19 6
97 multidrug resistance protein (spaB) HP0600 JHP0547 75 41 30
103 type I restriction enzyme R protein (hsdR) HP1402 JHP1424 195 86 21
109 adenine/cytosine DNA methyltransferase HP0054 NAH - 120 20
119 preprotein translocase subunit (secA) HP0786 JHP0723 159 176 49
121 hypothetical protein HP0058 JHP0051 394 16 53
122 hypothetical protein HP0513 JHP0462 104 28 15
125 type I restriction enzyme M protein (hsdM) HP1403 JHP1423 299 340 44
132 hypothetical protein HP0731 JHP0668 110 80 32
139 hypothetical protein HP0508 JHP0458 84 32 77
142 hypothetical protein HP1187 JHP1113 274 31 38
167 hypothetical protein HP1520 NAH - 20 33
179 hypothetical protein HP0118 JHP0110 64 27 36
195 type III restriction enzyme R protein (res) HP1521 JHP1410 161 210 18
209 outer membrane protein (omp17) HP0725 JHP0662 257 47 101
224 hypothetical protein HP0733 JHP0670 769 222 48
230 hypothetical protein HP0611 JHP0299 35 37 1129
249 hypothetical protein HP0345 NAH - 46 1338
283 hypothetical protein HP0120 NAH - 44 50
291 translation initiation factor IF-2 (infB) HP1048 JHP0377 330 332 45
297 DNA polymerase III alpha-subunit (dnaE) HP1460 JHP1353 509 219 47
342 type I restriction enzyme R protein (hsdR) HP0846 JHP0784 244 101 37
363 adenine specific DNA methyltransferase (mod) HP1522 JHP1411 857 207 11
410 secreted protein involved in flagellar motility HP1192 JHP1117 614 13 1256
593 hypothetical protein HP1516 NAH - 34 1090
631 hypothetical protein HP0586 JHP0534 577 163 29
1080 type II restriction enzyme (methyltransferase) HP0478 JHP0430 953 220 40
* probably frame shifted components of the same vacA related gene
Genes with > 2 SD divergence in each analysis are indicated in bold
NAH indicates No Annotated Homologue in the other sequence
Figure 1 Comparisons using LAlign between a representative selection of orthologous genes with divergent DNA present in both H. pylori strains J99 and 26695 (presented in descending order of divergence as determined in strain J99).
It cannot be assumed that all genes identified in this manner have been recently acquired. It is necessary to assess the nature of the sequence to determine if its divergence might be accounted for on the basis of features of the encoded protein. For example, JHP0476/HP0527, JHP1300/HP1408 and JHP0074/HP0080 include repetitive sequences likely to account for their DNS divergence. This type of analysis cannot be used to determine the possible foreign origin of such genes. Notably, the most divergent cag PAI gene (the 1st and 2nd most divergent gene in the whole genomes of strain 26695 and J99 respectively, JHP0476/HP0527) has a highly complex repetitive structure and the size of the large divergent peak associated with this island using previous methods is largely due to the presence of this gene.
While a significant proportion of the genes identified in this analysis are associated with regions including several such genes and which share characteristics of islands of horizontal transfer or pathogenicity islands, this is far from universally true. There are many instances of single genes or small numbers of genes that are present that are not associated with any features that might otherwise have been used as indicators of horizontal acquisition such as transposases and flanking repeats.
Our initial goal was to identify recently acquired and exchanged genes as candidates likely to be important in niche-adaptation, host interactions, and alterations in bacterial fitness. It has been argued that essential genes are unlikely to be transferred successfully since recipient taxa would already bear functional orthologues, which would have experienced long-term co-evolution with the rest of the cellular machinery. In contrast, it is proposed that those under weak or transient selection – like those associated with nonessential catabolic processes, new operons, and those providing new niche-adaptive changes are likely to be successfully transferred and retained [19]. This leads to a model in which a stable 'core genome' comprised of essential metabolic, regulatory, and cell division genes provides a stable context for the more labile non-essential and niche adaptive genes. On this basis such genes are used for phylogenetic studies and are thought to provide a relatively constant background in which species evolution occurs. Many of the genes identified for which functions are known affect virulence or niche adaptive genes, including: the vacuolating cytotoxin and related toxins (2 and 3), urease and flagellar components, and genes involved in iron acquisition. However, we also find clear evidence, confirmed by differences between the two genome sequences, that recent, and therefore relatively frequent, horizontal transfer is not limited to genes associated with niche adaptation and virulence. Amongst the core function genes identified were mutS, ftsK, xerD, and polA. The comparisons of the latter three between the sequence strains are shown in Figure 1f,g &1j. These comparisons support the results suggesting that these genes have been the substrates for horizontal exchange between species.
Tetranucleotide composition has been used for the consideration of the presence of palindromic sequences that might be substrates for restriction systems and Chi sites and the presence of unstable repeats mediating phase variation [10], but the use of longer component signatures has not been used to identify horizontally acquired regions in bacterial genomes. Following analysis of eukaryotic sequences it was concluded that DNS captures most of the departure from randomness in DNA sequences and that longer component lengths correlate highly with the DNS results [20]. Also, analysis of dinucleotides separated by no, one, or two other nucleotides showed that separated pairs are more nearly random than adjacent pairs and were concluded to be relatively uninformative [9]. However, in preliminary analyses, while results using the typically long walking windows gave concordant results as previously reported, we found that the use of smaller walking windows generated progressively more different patterns of divergence with other length components. Using tetranucleotide (TNS) and hexanucleotide (HNS) signature analysis we find that, while in some instances there is significant overlap between the genes identified using the different component lengths, there are substantial differences that indicate additional horizontally transferred genes not identified by DNS alone (Tables 2 to 6).
Table 2 Top 50 most divergent genes by TNS in H. pylori strain J99 plus those additional genes > 2 SD greater than the mean by DNS and the 50 most divergent by HNS
TNS order Annotation JHP # 26695 # DNS order HNS order
1 hypothetical protein JHP1300 HP1408 9 1
2 cag pathogenicity island protein (cag7) JHP0476 HP0527 2 2
3 hypothetical protein JHP0952 HP0427 1 1355
4 histidine and glutamine-rich metal-binding protein JHP1321 HP1432 15 49
5 vacuolating cytotoxin (vacA) paralog JHP0556 HP0609/10 3 4
6 vacuolating cytotoxin (vacA) paralog JHP0274 HP0289 4 5
7 hypothetical protein JHP0050 HP0058 8 84
8 hypothetical protein JHP0305 HP0322 5 10
9 vacuolating cytotoxin (vacA) paralog JHP0856 HP0922 7 6
10 type I restriction enzyme (hsdS) JHP1422 NAH 319 3
11 hypothetical protein JHP0299 HP061/2 35 275
12 hypothetical protein JHP0928 NAH 11 9
13 hypothetical protein JHP0942 HP0996 6 27
14 hypothetical protein JHP1044 HP1116 10 8
15 hypothetical protein JHP0934 NAH 16 95
16 hypothetical protein JHP0440 HP0488 13 17
17 outer membrane protein (omp26) JHP1084 HP1157 24 24
18 topoisomerase I (topA 3) JHP0931 NAH 18 20
19 hypothetical protein JHP0318 NAH 286 293
20 cag island protein (cagA) JHP0495 HP0547 17 12
21 hypothetical protein JHP0110 HP0118 64 19
22 hypothetical protein JHP1208 HP1288 91 830
23 DNA-directed RNA polymerase, beta subunit (rpoB) JHP1121 HP1198 50 16
24 hypothetical protein JHP0052 HP0059 26 120
25 hypothetical protein JHP1042 HP1115 14 694
26 hypothetical protein JHP0953 NAH 31 1463
27 hypothetical protein JHP1070 HP1142 60 14
28 hypothetical protein JHP1113 HP1187 274 39
29 hypothetical protein JHP0842 HP0906 42 21
30 type II restriction enzyme JHP0630 NAH 173 588
31 histidine-rich, metal binding polypeptide (hpn) JHP1320 HP1427 70 1404
32 hypothetical protein JHP0074 HP0080 12 125
33 hypothetical protein JHP0191 HP0205 53 7
34 hypothetical protein JHP0376 HP1049 235 1128
35 cag pathogenicity island protein (cag3) JHP0471 HP0522 21 62
36 hypothetical protein JHP0026 HP0030 23 64
37 urease beta subunit (urea amidohydrolase) (ureB) JHP0067 HP0072 32 70
38 hypothetical protein JHP0939 HP0991 116 156
39 multidrug resistance protein (spaB) JHP0547 HP0600 75 18
40 flagellin A (flaA) JHP0548 HP0601 34 154
41 hypothetical protein JHP1071 HP1143 78 61
42 hypothetical protein JHP0613 HP0669 44 33
43 hypothetical protein JHP0623 HP0682 231 1186
44 N-methylhydantoinase JHP0632 HP0696 20 36
45 hypothetical protein JHP1049 NAH 278 470
46 vacuolating cytotoxin (vacA) JHP0819 HP0887 59 38
47 putative restriction enzyme JHP0164 NAH 88 43
48 type I restriction enzyme R protein (hsdR) JHP0784 HP0846 244 35
49 hook assembly protein, flagella (flgD) JHP0843 HP0907 103 175
50 hypothetical protein JHP0458 HP0508 84 44
51 hypothetical protein JHP0336 HP1089 27 54
53 hypothetical protein JHP0940 NAH 39 393
54 hypothetical protein JHP0462 HP0513 104 11
55 type II restriction enzyme (methyltransferase) JHP1409 NAH 37 15
58 hypothetical protein JHP1285 HP1371 55 25
59 hypothetical protein JHP0693 HP0756 19 1490
62 cag pathogenicity island protein (cag8) JHP0477 HP0528 72 31
63 type III restriction enzyme (res) JHP1297 NAH 30 28
64 hypothetical protein JHP0668 HP0731 110 32
67 outer membrane protein JHP0438 HP0486 22 145
70 cag island protein (cagT) JHP0481 HP0532 25 558
71 RNA polymerase sigma-70 factor (rpoD) JHP0081 HP0088 62 37
75 hypothetical protein JHP1253 HP1333 40 384
78 iron(III) dicitrate transport protein (fecA) JHP1426 HP1400 28 111
81 DNA polymerase I (polA) JHP1363 HP1470 46 46
85 type I restriction enzyme (hsdS) JHP0414 NAH 275 30
88 hypothetical protein JHP0174 HP0187/8/6 29 90
89 iron(III) dicitrate transport protein (fecA) JHP0626 HP0686 38 47
95 DNA transfer protein (cagE) JHP0492 HP0544 49 50
100 integrase/recombinase (xerD) JHP0941 HP0995 33 541
104 type III restriciton enzyme (mod) JHP1411 HP1522 857 13
105 type I restriction enzyme R protein (hsdR) JHP0416 HP0464 63 29
122 adenine specific DNA methyltransferase (mod) JHP0244 HP0260 236 48
130 hypothetical protein JHP0925 NAH 43 990
137 cag island protein (cagH) JHP0489 HP0541 47 398
138 type I restriction enzyme (hsdR) JHP1424 HP1402 195 22
158 hypothetical protein JHP0540 NAH 674 26
170 cag island protein (cagF) JHP0491 HP0543 52 828
177 DNA repair protein (recN) JHP1434 HP1393 51 160
190 type III restriction enzyme (mod) JHP1296 NAH 121 34
196 role in outermembrane permeability (imp) JHP1138 HP1215/6 208 45
206 cytochrome oxidase (cbb3 type) (fixN) JHP0132 HP0144 41 209
227 DNA mismatch repair protein (mutS) JHP0565 HP0621 45 82
230 hypothetical protein JHP0534 HP0586 577 40
258 type III restriction enzyme (res) JHP1410 HP1521 161 23
262 hypothetical protein JHP1033 HP1106 36 342
281 translation initiation factor IF-2 (infB) JHP0377 HP1048 330 42
290 type II restriction enzyme (methyltrasferase) JHP1284 NAH 750 41
1260 siderophore-mediated iron transport protein (tonB) JHP1260 HP1341 48 402
Genes with > 2 SD divergence in each analysis are indicated in bold
NAH indicates No Annotated Homologue in the other sequence
Table 3 Top 50 most divergent genes by HNS in H. pylori strain J99 plus those additional genes >2 SD greater than the mean by DNS and top 50 by TNS
HNS order J99 annotation JHP # 26695 # DNS order TNS order
1 hypothetical protein JHP1300 HP1408 9 1
2 cag pathogenicity island protein (cag7) JHP0476 HP0527 2 2
3 type I restriction enzyme (hsdS) JHP1422 NAH 319 10
4 vacuolating cytotoxin (vacA) paralog JHP0556 HP0609/10 3 5
5 vacuolating cytotoxin (vacA) paralog JHP0274 HP0289 4 6
6 vacuolating cytotoxin (vacA) paralog JHP0856 HP0922 7 9
7 hypothetical protein JHP0191 HP0205 53 33
8 hypothetical protein JHP1044 HP1116 10 14
9 hypothetical protein JHP0928 NAH 11 12
10 hypothetical protein JHP0305 HP0322 5 8
11 hypothetical protein JHP0462 HP0513 104 54
12 cag island protein (cagA) JHP0495 HP0547 17 20
13 type III restriciton enzyme (mod) JHP1411 HP1522 857 104
14 hypothetical protein JHP1070 HP1142 60 27
15 type II restriction enzyme (methyltransferase) JHP1409 NAH 37 55
16 DNA-directed RNA polymerase, beta subunit (rpoB) JHP1121 HP1198 50 23
17 hypothetical protein JHP0440 HP0488 13 16
18 multidrug resistance protein (spaB) JHP0547 HP0600 75 39
19 hypothetical protein JHP0110 HP0118 64 21
20 topoisomerase I (topA 3) JHP0931 NAH – check 18 18
21 hypothetical protein JHP0842 HP0906 42 29
22 type I restriction enzyme (hsdR) JHP1424 HP1402 195 138
23 type III restriction enzyme (res) JHP1410 HP1521 161 258
24 outer membrane protein (omp26) JHP1084 HP1157 24 17
25 hypothetical protein JHP1285 HP1371 55 58
26 hypothetical protein JHP0540 NAH 674 158
27 hypothetical protein JHP0942 HP0996 6 13
28 type III restriction enzyme (res) JHP1297 NAH 30 63
29 type I restriction enzyme R protein (hsdR) JHP0416 HP0464 63 105
30 type I restriction enzyme (hsdS) JHP0414 NAH 275 85
31 cag pathogenicity island protein (cag8) JHP0477 HP0528 72 62
32 hypothetical protein JHP0668 HP0731 110 64
33 hypothetical protein JHP0613 HP0669 44 42
34 type III restriction enzyme (mod) JHP1296 NAH 121 190
35 type I restriction enzyme R protein (hsdR) JHP0784 HP0846 244 48
36 N-methylhydantoinase JHP0632 HP0696 20 44
37 RNA polymerase sigma-70 factor (rpoD) JHP0081 HP0088 62 71
38 vacuolating cytotoxin (vacA) JHP0819 HP0887 59 46
39 hypothetical protein JHP1113 HP1187 274 28
40 hypothetical protein JHP0534 HP0586 577 230
41 type II restriction enzyme (methyltrasferase) JHP1284 NAH 750 290
42 translation initiation factor IF-2 (infB) JHP0377 HP1048 330 281
43 restriction enzyme JHP0164 NAH 88 47
44 hypothetical protein JHP0458 HP0508 84 50
45 role in outermembrane permeability (imp) JHP1138 HP1215/6 208 196
46 DNA polymerase I (polA) JHP1363 HP1470 46 81
47 iron(III) dicitrate transport protein (fecA) JHP0626 HP0686 38 89
48 adenine specific DNA methyltransferase (mod) JHP0244 HP0260 236 122
49 histidine and glutamine-rich metal-binding protein JHP1321 HP1432 15 4
50 DNA transfer protein (cagE) JHP0492 HP0544 49 95
54 hypothetical protein JHP0336 HP1089 27 51
62 cag pathogenicity island protein (cag3) JHP0471 HP0522 21 35
64 hypothetical protein JHP0026 HP0030 23 36
70 urease beta subunit (urea amidohydrolase) (ureB) JHP0067 HP0072 32 37
82 DNA mismatch repair protein (mutS) JHP0565 HP0621 45 227
84 hypothetical protein JHP0050 HP0058 8 7
90 hypothetical protein JHP0174 HP0187/8/6 29 88
95 hypothetical protein JHP0934 NAH 16 15
111 iron(III) dicitrate transport protein (fecA) JHP1426 HP1400 28 78
120 hypothetical protein JHP0052 HP0059 26 24
125 hypothetical protein JHP0074 HP0080 12 32
145 Outer membrane protein JHP0438 HP0486 22 67
154 flagellin A (flaA) JHP0548 HP0601 34 40
160 DNA repair protein (recN) JHP1434 HP1393 51 177
209 cytochrome oxidase (cbb3 type) (fixN) JHP0132 HP0144 41 206
275 hypothetical protein JHP0299 HP061/2 35 11
342 hypothetical protein JHP1033 HP1106 36 262
384 hypothetical protein JHP1253 HP1333 40 75
393 hypothetical protein JHP0940 NAH 39 53
398 cag island protein (cagH) JHP0489 HP0541 47 137
402 siderophore-mediated iron transport protein (tonB) JHP1260 HP1341 48 1260
541 integrase/recombinase (xerD) JHP0941 HP0995 33 100
558 cag island protein (cagT) JHP0481 HP0532 25 70
694 hypothetical protein JHP1042 HP1115 14 25
828 cag island protein (cagF) JHP0491 HP0543 52 170
990 hypothetical protein JHP0925 NAH 43 130
1355 hypothetical protein JHP0952 HP0427 1 3
1463 hypothetical protein JHP0953 NAH 31 26
1490 hypothetical protein JHP0693 HP0756 19 59
Genes with > 2 SD divergence in each analysis are indicated in bold
NAH indicates No Annotated Homologue in the other sequence
Table 5 Top 50 most divergent genes by TNS in H. pylori strain 26695 plus those additional genes > 2 SD greater than the mean by DNS and the 50 most divergent by HNS
TNS order annotation HP# J99 # DNS order HNS order
1 cag pathogenicity island protein (cag7) HP0527 JHP0476 1 1
2 vacuolating cytotoxin (vacA) paralog HP0289 JHP0274 2 4
3 hypothetical protein HP0427 JHP0952 14 737
4 hypothetical protein HP1408 JHP1300 15 738
5 vacuolating cytotoxin (vacA) paralog HP0922 JHP0856 6 3
6 hypothetical protein HP0609 JHP0556* 4 9
7 hypothetical protein HP0119 NAH 17 2
8 poly E-rich hypothetical protein HP0322 JHP0305 3 5
9 histidine and glutamine-rich metal-binding protein HP1432 JHP1321 46 1432
10 hypothetical protein HP0488 JHP0440 7 12
11 hypothetical protein HP1116 JHP1044 8 13
12 vacuolating cytotoxin (vacA) paralog HP0610 JHP0556* 13 17
13 secreted protein involved in flagellar motility HP1192 JHP1117 410 1256
14 hypothetical protein HP0996 JHP0942 5 46
15 cag island protein (cagA) HP0547 JHP0495 31 7
16 hypothetical protein HP0058 JHP0051 121 53
17 outer membrane protein (omp26) HP1157 JHP1084 34 25
18 hypothetical protein HP0080 JHP0074 9 122
19 hypothetical protein HP1142 JHP1070 91 6
20 hypothetical protein HP1520 NAH 167 33
21 hypothetical protein HP0059 JHP0052 43 320
22 hypothetical protein HP0906 JHP0842 42 16
23 DNA-directed RNA polymerase, beta subunit (rpoB) HP1198 JHP1121 84 19
24 hypothetical protein HP0030 JHP0026 45 39
25 vacuolating cytotoxin (vacA) HP0887 JHP0819 18 34
26 histidine-rich, metal binding polypeptide (hpn) HP1427 NAH 39 1449
27 hypothetical protein HP0118 JHP0110 179 36
28 hypothetical protein HP0513 JHP0462 122 15
29 hypothetical protein HP1143 JHP1071 58 41
30 type III restriction enzyme R protein (res) HP0592 NAH 16 35
31 hypothetical protein HP1187 JHP1113 142 38
32 hypothetical protein HP0508 JHP0458 139 77
33 hypothetical protein HP1115 JHP1042 20 866
34 hypothetical protein HP1516 NAH 593 1090
35 N-methylhydantoinase HP0696 JHP0632 19 43
36 hypothetical protein HP0489 JHP0441 10 582
37 hypothetical protein HP0611 JHP0299 230 1129
38 urease beta subunit (urea amidohydrolase) (ureB) HP0072 JHP0067 21 87
39 integrase/recombinase (xerD) HP0995 JHP0941 25 448
40 flagellin A (flaA) HP0601 JHP0548 33 180
41 multidrug resistance protein (spaB) HP0600 JHP0547 97 30
42 type IIS restriction enzyme R and M protein (ECO57IR) HP1517 NAH 28 14
43 fucosyltransferase HP0651 JHP0596 48 75
44 hypothetical protein HP0120 NAH 283 50
45 outer membrane protein (omp3) HP0079 JHP0073 68 99
46 hypothetical protein HP0345 NAH 249 1338
47 outer membrane protein (omp17) HP0725 JHP0662 209 101
48 cag pathogenicity island protein (cag3) HP0522 JHP0471 11 100
49 virB4 homolog (virB4) HP0459 NAH 53 28
50 cag pathogenicity island protein (cag8) HP0528 JHP0477 74 27
51 DNA transfer protein (cagE) HP0441 JHP0492 29 22
53 hypothetical protein HP1333 JHP1253 40 296
55 RNA polymerase sigma-70 factor (rpoD) HP0088 JHP0081 56 31
58 hypothetical protein HP0453 NAH 75 10
60 hypothetical protein HP0669 JHP0613 69 42
61 hypothetical protein HP1003 NAH 38 170
64 translation elongation factor EF-Tu (tufB) HP1205 JHP1128 49 166
67 hypothetical protein HP1089 JHP0336 12 59
71 hypothetical protein HP0756 JHP0693 24 1548
72 hypothetical protein HP0788 JHP0725 41 256
73 2',3'-cyclic-nucleotide 2'-phosphodiesterase (cpdB) HP0104 JHP0096 54 68
77 DNA polymerase I (polA) HP1470 JHP1363 30 54
78 hypothetical protein HP0205 JHP0191 57 8
80 hypothetical protein HP0731 JHP0668 132 32
81 hypothetical protein HP0449 NAH 51 449
86 type I restriction enzyme R protein (hsdR) HP1402 JHP1424 103 21
87 cag pathogenicity island protein (cag12) HP0532 JHP0481 23 693
90 type I restriction enzyme R protein (hsdR) HP0464 NAH 36 26
99 iron(III) dicitrate transport protein (fecA) HP1400 JHP1426 32 129
101 type I restriction enzyme R protein (hsdR) HP0846 JHP0784 342 37
102 cytochrome oxidase (cbb3 type) (fixN) HP0144 JHP0132 27 168
119 type III restriction enzyme R protein HP1371 JHP1285 52 23
120 adenine/cytosine DNA methyltransferase HP0054 NAH 109 20
130 hypothetical protein HP0186 JHP0174 47 276
137 DNA mismatch repair protein (MutS) HP0621 JHP0565 22 64
147 outer membrane protein HP0486 JHP0438 26 142
149 DNA topoisomerase I (topA) HP0440 NAH 63 24
153 hypothetical protein HP1479 JHP1372 55 127
154 DNA repair protein (recN) HP1393 JHP1434 35 207
163 hypothetical protein HP0586 JHP0534 631 29
164 virulence associated protein homolog (vacB) HP1248 JHP1169 50 160
169 GMP reductase (guaC) HP0854 JHP0790 44 451
176 preprotein translocase subunit (secA) HP0786 JHP0723 119 49
181 cell division protein (ftsK) HP1090 JHP0335 37 90
207 adenine specific DNA methyltransferase (mod) HP1522 JHP1411 363 11
210 type III restriction enzyme R protein (res) HP1521 JHP1410 195 18
219 DNA polymerase III alpha-subunit (dnaE) HP1460 JHP1353 297 47
220 type II restriction enzyme (methyltransferase) HP0478 JHP0430 1080 40
222 hypothetical protein HP0733 JHP0670 224 48
225 cag pathogenicity island protein (cag13) HP0534 JHP0482 60 1021
272 hypothetical protein HP1106 JHP1033 59 277
332 translation initiation factor IF-2 (infB) HP1048 JHP0377 291 45
340 type I restriction enzyme M protein (hsdM) HP1403 JHP1423 125 44
* probably frame shifted components of the same vacA related gene
Genes with > 2 SD divergence in each analysis are indicated in bold
NAH indicates No Annotated Homologue in the other sequence
Table 6 Top 50 most divergent genes by HNS in H. pylori strain 26695 plus those additional genes > 2 SD greater than the mean by DNS and the 50 most divergent by HNS
HNS order annotation HP# J99 # DNS order TNS order
1 cag pathogenicity island protein (cag7) HP0527 JHP0476 1 1
2 hypothetical protein HP0119 NAH 17 7
3 vacuolating cytotoxin (vacA) paralog HP0922 JHP0856 6 5
4 vacuolating cytotoxin (vacA) paralog HP0289 JHP0274 2 2
5 poly E-rich hypothetical protein HP0322 JHP0305 3 8
6 hypothetical protein HP1142 JHP1070 91 19
7 cag island protein (cagA) HP0547 JHP0495 31 15
8 hypothetical protein HP0205 JHP0191 57 78
9 hypothetical protein HP0609 JHP0556* 4 6
10 hypothetical protein HP0453 NAH 75 58
11 adenine specific DNA methyltransferase (mod) HP1522 JHP1411 363 207
12 hypothetical protein HP0488 JHP0440 7 10
13 hypothetical protein HP1116 JHP1044 8 11
14 type IIS restriction enzyme R and M protein (ECO57IR) HP1517 NAH 28 42
15 hypothetical protein HP0513 JHP0462 122 28
16 hypothetical protein HP0906 JHP0842 42 22
17 vacuolating cytotoxin (vacA) paralog HP0610 JHP0556* 13 12
18 type III restriction enzyme R protein (res) HP1521 JHP1410 195 210
19 DNA-directed RNA polymerase, beta subunit (rpoB) HP1198 JHP1121 84 23
20 adenine/cytosine DNA methyltransferase HP0054 NAH 109 120
21 type I restriction enzyme R protein (hsdR) HP1402 JHP1424 103 86
22 DNA transfer protein (cagE) HP0441 JHP0492 29 51
23 type III restriction enzyme R protein HP1371 JHP1285 52 119
24 DNA topoisomerase I (topA) HP0440 NAH 63 149
25 outer membrane protein (omp26) HP1157 JHP1084 34 27
26 type I restriction enzyme R protein (hsdR) HP0464 NAH 36 90
27 cag pathogenicity island protein (cag8) HP0528 JHP0477 74 50
28 virB4 homolog (virB4) HP0459 NAH 53 49
29 hypothetical protein HP0586 JHP0534 631 163
30 multidrug resistance protein (spaB) HP0600 JHP0547 97 41
31 RNA polymerase sigma-70 factor (rpoD) HP0088 JHP0081 56 55
32 hypothetical protein HP0731 JHP0668 132 80
33 hypothetical protein HP1520 NAH 167 20
34 vacuolating cytotoxin HP0887 JHP0819 18 25
35 type III restriction enzyme R protein (res) HP0592 NAH 16 30
36 hypothetical protein HP0118 JHP0110 179 27
37 type I restriction enzyme R protein (hsdR) HP0846 JHP0784 342 101
38 hypothetical protein HP1187 JHP1113 142 31
39 hypothetical protein HP0030 JHP0026 45 24
40 HP0478 JHP0430 1080 220
41 hypothetical protein HP1143 JHP1071 58 29
42 hypothetical protein HP0669 JHP0613 69 60
43 N-methylhydantoinase HP0696 JHP0632 19 35
44 type I restriction enzyme M protein (hsdM) HP1403 JHP1423 125 340
45 translation initiation factor IF-2 (infB) HP1048 JHP0377 291 332
46 hypothetical protein HP0996 JHP0942 5 14
47 DNA polymerase III alpha-subunit (dnaE) HP1460 JHP1353 297 219
48 hypothetical protein HP0733 JHP0670 224 222
49 preprotein translocase subunit (secA) HP0786 JHP0723 119 176
50 hypothetical protein HP0120 NAH 283 44
53 hypothetical protein HP0058 JHP0051 121 16
54 DNA polymerase I (polA) HP1470 JHP1363 30 77
59 hypothetical protein HP1089 JHP0336 12 67
64 DNA mismatch repair protein (MutS) HP0621 JHP0565 22 137
68 2',3'-cyclic-nucleotide 2'-phosphodiesterase (cpdB) HP0104 JHP0096 54 73
75 fucosyltransferase HP0651 JHP0596 48 43
77 hypothetical protein HP0508 JHP0458 139 32
87 urease beta subunit (urea amidohydrolase) (ureB) HP0072 JHP0067 21 38
90 cell division protein (ftsK) HP1090 JHP0335 37 181
99 outer membrane protein (omp3) HP0079 JHP0073 68 45
100 cag pathogenicity island protein (cag3) HP0522 JHP0471 11 48
101 outer membrane protein (omp17) HP0725 JHP0662 209 47
122 hypothetical protein HP0080 JHP0074 9 18
127 hypothetical protein HP1479 JHP1372 55 153
129 iron(III) dicitrate transport protein (fecA) HP1400 JHP1426 32 99
142 outer membrane protein HP0486 JHP0438 26 147
160 virulence associated protein homolog (vacB) HP1248 JHP1169 50 164
166 translation elongation factor EF-Tu (tufB) HP1205 JHP1128 49 64
168 cytochrome oxidase (cbb3 type) (fixN) HP0144 JHP0132 27 102
170 hypothetical protein HP1003 NAH 38 61
180 flagellin A (flaA) HP0601 JHP0548 33 40
207 DNA repair protein (recN) HP1393 JHP1434 35 154
256 hypothetical protein HP0788 JHP0725 41 72
276 hypothetical protein HP0186 JHP0174 47 130
277 hypothetical protein HP1106 JHP1033 59 272
296 hypothetical protein HP1333 JHP1253 40 53
320 hypothetical protein HP0059 JHP0052 43 21
448 integrase/recombinase (xerD) HP0995 JHP0941 25 39
449 hypothetical protein HP0449 NAH 51 81
451 GMP reductase (guaC) HP0854 JHP0790 44 169
582 hypothetical protein HP0489 JHP0441 10 36
693 cag island protein (cagT) HP0532 JHP0481 23 87
737 hypothetical protein HP0427 JHP0952 14 3
738 hypothetical protein HP1408 JHP1300 15 4
866 hypothetical protein HP1115 JHP1042 20 33
1021 cag pathogenicity island protein (cag13) HP0534 JHP0482 60 225
1090 hypothetical protein HP1516 NAH 593 34
1129 hypothetical protein HP0611 JHP0299 230 37
1256 secreted protein involved in flagellar motility HP1192 JHP1117 410 13
1338 hypothetical protein HP0345 NAH 249 46
1432 histidine and glutamine-rich metal-binding protein HP1432 JHP1321 46 9
1449 histidine-rich, metal binding polypeptide (hpn) HP1427 NAH 39 26
1548 hypothetical protein HP0756 JHP0693 24 71
* probably frame shifted components of the same vacA related gene
Genes with > 2 SD divergence in each analysis are indicated in bold
NAH indicates No Annotated Homologue in the other sequence
The 50 most divergent J99 ORFs by HNS included 26 (52%) that were not in the 53 (>2 SD) most divergent by DNS, these included 11 restriction-modification system genes and 6 others that were not annotated within the strain 26695 genome sequence. The identification of genes of a type known to be horizontally exchanged, and different between the gene complements of the strains, is strong corroboration for the foreign origin of the additional genes identified by HNS. In several instances (Tables 2 to 6) the DNS did not detect these genes at all e.g. restriction enzymes that were the 3rd, 13th and 41st most divergent genes by HNS, were 319th, 857th and 750th most divergent by DNS, respectively. In some instances the TNS gave intermediate results and in others identified other genes as more divergent than the other methods. The TNS was most sensitive for the detection of rpoB (HP1198 / JHP1121) which is associated with a significantly different gene length in the two strains (Figure 1h). One explanation for this observation is that while the DNS may initially be the most sensitive indicator of horizontal exchange it may become ameliorated to the new sequence characteristics more rapidly that the longer component features, which are probably detecting qualitatively different sequence characteristics.
The differences in the analyses using different length components, and a comparison of the results from the two sequenced strains, suggest a complex evolutionary history for the cag pathogenicity island. These suggest that it probably has mosaic structure including sequences from more than one species background, in addition to sequence that is entirely typical of H. pylori.
It is normally impossible to determine the chronology of events to distinguish insertions and deletions when comparing strains. In strain 26695 there are two open reading frames that are both good candidate coding sequences. There is only one gene in this location in strain J99 composed of the 5' gene from strain 26695 and the 3' end of the subsequent gene. This could have arisen from either a deletion or an insertion event. However, the normal DNS of the J99 gene (JHP0073, 799th in divergence) and the 5' 26695 gene (HP0079, 751st in divergence), and the high divergence of the 3' 26695 gene (HP0078, 68th in divergence), indicate that the most likely event is an insertion into strain 26695 (Figure 1l). Likewise HP0119 is likely to contain an insertion and JHP1113 probably reflects the original sequences (Figure 1k).
The inclusion of two DNA metabolism genes associated with recombination and repair is notable. Both mutS and recN were identified in both strains (22nd and 35th, and 45th and 51st most divergent genes by DNS in strains 26695 and J99 respectively). When the homologous genes were compared between the strains, extensive divergences were evident between more than one region of each protein. That these genes have divergent signatures in both strains suggests that neither has a wholly native composition. This observation is consistent with the models of rapid evolution which suggest that transient competitive advantages are enjoyed by organisms that are hypermutators under conditions of environmental stress and transitions, and that these states which can be produced by mutations in DNA repair genes [21-26]. However, such states have to be reversed so that an unsustainable mutational burden is not attained, and it has been proposed that this reversal is mediated by repair following horizontal transfer and homologous recombination, and that such strains are hyper-recombinogenic [27-29]. The untypicality of mutS and recN suggest that H. pylori is another species that can make use of this strategy for diversification under stressful conditions.
The identification of RNA polymerase genes, with associated differences between the strains, is striking. The divergence of phylogenetic trees based upon different sequences has been highlighted, and particularly the differences between the trees associated with RNA polymerase genes and rRNA [30,31]. It has been argued that RNA polymerase is as essential to cell function as is rRNA and that there is no compelling reason to chose rRNA as the more reliable marker [32]. While the DNS analysis does not address the stability of rRNA (and specifically excludes the rRNA sequences because their differing coding requirements and evolutionary pressures generate a divergent signature for other reasons), it does indicate that RNA polymerase can be a substrate for horizontal transfer, and that trees based upon this gene, or other essential genes, need not necessarily be considered a challenge to rRNA based phylogenies.
Conclusions
The spectrum of recently horizontally acquired sequences identified emphasizes the two driving forces of horizontal exchange: the transfer of a phenotype which alters or enhances bacterial fitness resulting in increased competitive fitness or altered niche adaptation, and the presence of a substrate for homologous recombination. Because of the focus upon, and relative ease of identifying, large islands associated with readily identifiable features and phenotypes, the importance of the latter component has perhaps been underestimated. The genes that have been considered to code for 'core metabolic' 'house-keeping' functions are amongst those most likely to be changed by horizontal transfer events because of the presence of homologous substrates, and changes are likely to persist even when the change is phenotypically neutral. Equally, changes in the genes involved in core functions such as gene expression and DNA metabolism may have pleotropic effects and there may be significant differences in strain behaviour, that are not simply the consequence of differences in their respective gene complements. The selection of genes for phylogenetic analysis on the basis of their coding for conserved core functions is also problematic because these are also frequently the genes most likely to share the high homology that facilitates recombination and horizontal exchange.
Methods
A traditional nucleotide signature is generated by segmenting a sequence of DNA into k equal-sized subsequences (or 'windows'). The mathematical basis for the signature is an odds ratio – pi – calculated by dividing the frequency of a length-L oligonucleotide by its expected frequency. The odds ratios for each of the 4L oligonucleotides in each window (w) are compared with the odds ratios for the overall sequence (s) [9,10,33]. The normalized difference δ is plotted and thus a nucleotide signature consists of a k-length sequence of δ values: δ(w,s) = (1/4L)Σ(4L,i:x)|pi(w) - pi(s)|, where x is the set of all permutations of length L and i is one such permutation.
There are interesting parallels between signature-style genome analysis and stylometric techniques previously used to determine the authorship of controversial literary texts. This is analogous with the biological problem and it is from this that our method is derived. Rather than using a fixed-window signature, signature scores are calculated for each coding open reading frame (ORF) and weighted with variance estimates so that the scores for shorter ORFs confer with their longer counterparts. Bissell's weighted cusum (cumulative sum) [34], , is modified so that n denotes the number of ORFs in the genome, Xi the number of oligonucleotides in ORF i, and wi the number of nucleotides in ORF i. The results are scaled according to ORF size using the standard error σ = √(*#ORF). In this way false positives are abrogated by normalizing for over-representation of lower order peptides.
The method is implemented in Java and efficiency is maintained through an O(N) (N = sequence length) refinement: probabilities for the complete sequence are calculated in O(N) steps for any length-L oligonucleotide, and maintain O(N) when 4L>N through a hashing function; the second part of the program calculates σ for each ORF using a loop flattening technique, thereby avoiding the program having to recalculate overlapping sub-expressions. The program is available from and .
Sequence alignments, as shown in Figure 1, were performed and displayed using the programs: Lalign and viewed using Lalignview [35].
Abbreviations
ORF, Open Reading Frame; DNS, Dinucleotide Signature; TNS, tetranucleotide signature; HNS, hexanucleotide signature.
Authors' contributions
NJS initiated the project, performed the genome sequence analyses, compared the two strains, interpreted the results, and prepared the biological aspects of the manuscript. PB was a DPhil student who worked on the coding aspects of the new methodology. JFP contributed to the bioinformatics discussions and planning stage of this project. SAJ directed and primarily developed the analysis strategy and the implementation of the new computational basis of the methodology, and prepared the computational aspects of the manuscript.
Acknowledgements
At the time most of this study was performed NJS was supported by a Wellcome Trust Advanced Research Fellowship.
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| 15676066 | PMC549213 | CC BY | 2021-01-04 16:39:32 | no | BMC Genomics. 2005 Jan 27; 6:9 | utf-8 | BMC Genomics | 2,005 | 10.1186/1471-2164-6-9 | oa_comm |
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BMC NeurosciBMC Neuroscience1471-2202BioMed Central London 1471-2202-6-91569138710.1186/1471-2202-6-9Research ArticleNucleus accumbens core lesions retard instrumental learning and performance with delayed reinforcement in the rat Cardinal Rudolf N [email protected] Timothy HC [email protected] Department of Experimental Psychology, University of Cambridge, Downing Street, Cambridge CB2 3EB, UK2 Psychopharmacology Section, Division of Psychiatry, B Floor, Medical School, Queen's Medical Centre, Nottingham NG7 2UH, UK2005 3 2 2005 6 9 9 25 11 2004 3 2 2005 Copyright © 2005 Cardinal and Cheung; licensee BioMed Central Ltd.2005Cardinal and Cheung; 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
Delays between actions and their outcomes severely hinder reinforcement learning systems, but little is known of the neural mechanism by which animals overcome this problem and bridge such delays. The nucleus accumbens core (AcbC), part of the ventral striatum, is required for normal preference for a large, delayed reward over a small, immediate reward (self-controlled choice) in rats, but the reason for this is unclear. We investigated the role of the AcbC in learning a free-operant instrumental response using delayed reinforcement, performance of a previously-learned response for delayed reinforcement, and assessment of the relative magnitudes of two different rewards.
Results
Groups of rats with excitotoxic or sham lesions of the AcbC acquired an instrumental response with different delays (0, 10, or 20 s) between the lever-press response and reinforcer delivery. A second (inactive) lever was also present, but responding on it was never reinforced. As expected, the delays retarded learning in normal rats. AcbC lesions did not hinder learning in the absence of delays, but AcbC-lesioned rats were impaired in learning when there was a delay, relative to sham-operated controls. All groups eventually acquired the response and discriminated the active lever from the inactive lever to some degree. Rats were subsequently trained to discriminate reinforcers of different magnitudes. AcbC-lesioned rats were more sensitive to differences in reinforcer magnitude than sham-operated controls, suggesting that the deficit in self-controlled choice previously observed in such rats was a consequence of reduced preference for delayed rewards relative to immediate rewards, not of reduced preference for large rewards relative to small rewards. AcbC lesions also impaired the performance of a previously-learned instrumental response in a delay-dependent fashion.
Conclusions
These results demonstrate that the AcbC contributes to instrumental learning and performance by bridging delays between subjects' actions and the ensuing outcomes that reinforce behaviour.
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Background
Animals learn to control their environment through instrumental (operant) conditioning. When an animal acts to obtain reward or reinforcement, there is often a delay between its action and the outcome; thus, animals must learn instrumental action-outcome contingencies using delayed reinforcement. Although such delays impair learning, animals can nevertheless bridge substantial delays to acquire instrumental responses [1]. Little is known of the neural basis of this process. However, abnormalities in learning from delayed reinforcement may be of considerable clinical significance [2]. Impulsivity is part of the syndrome of many psychiatric disorders, including mania, drug addiction, antisocial personality disorder, and attention-deficit/hyperactivity disorder [3]. Impulsive choice, one aspect of impulsivity [4], is exemplified by the tendency to choose small rewards that are available immediately instead of larger rewards that are only available after a delay [5,6], and may reflect dysfunction of reinforcement learning systems mediating the effects of delayed rewards [5,7].
The nucleus accumbens (Acb) responds to anticipated rewards in humans, other primates, and rats [8-15], and is innervated by dopamine (DA) neurons that respond to errors in reward prediction in a manner appropriate for a teaching signal [16-19]. The Acb may therefore represent a reinforcement learning system specialized for learning with delayed reinforcement [20,21]. If this is the case, then damage to the Acb should not interfere with reinforcement learning in all circumstances, but should produce selective impairments in learning when reinforcement is delayed. This prediction has not previously been tested. However, lesions of the AcbC cause rats to prefer small immediate rewards (a single food pellet delivered immediately) to large delayed rewards (four pellets delivered after a delay); that is, AcbC-lesioned rats exhibit impulsive choice [22,23]. The reason for this is not clear. It might be that AcbC-lesioned rats exhibit steeper temporal discounting, such that the subjective utility (value) of future rewards declines more rapidly than normal as the reward is progressively delayed [24,25]. It might also be that AcbC-lesioned rats are less good at representing the contingency between actions and their outcomes when the outcomes are delayed, so that they choose impulsively because they are less certain or less aware that their choosing the delayed reward does in fact lead to that reward being delivered [24,25]. Both explanations would reflect a problem in dealing with delayed reinforcement in AcbC-lesioned rats. However, there might be a simpler explanation for the impulsive choice exhibited by AcbC-lesioned rats: they might perceive the size (magnitude) of rewards differently. For example, if they do not perceive the delayed reward to be as large, relative to the immediate reward, as normal rats did, then they might choose impulsively despite processing the delays to reward normally, simply because the delayed reinforcer is not subjectively large enough to compensate for the normal effects of the delay [24-26].
To investigate whether the AcbC is a reinforcement learning system specialized for delayed reinforcement, we first determined the ability of AcbC-lesioned rats to detect instrumental contingencies across a delay. The ability of AcbC-lesioned rats to acquire instrumental responding with delayed reinforcement was compared to that of sham-operated controls; each subject was allowed to respond freely on two levers, one of which produced reinforcement after a delay of 0, 10, or 20 s (Figure 1). We report that AcbC lesions only retarded instrumental learning when reinforcement was delayed, demonstrating a role for the AcbC in bridging action-outcome delays during learning. Subsequently, to establish whether AcbC-lesioned rats perceive reward magnitude abnormally, we assessed these subjects' sensitivity to reinforcer magnitude by measuring their relative preference for two different reinforcers using concurrent interval schedules of reinforcement. We report that reinforcer magnitude discrimination in AcbC-lesioned rats in this task was at least as good as in sham-operated controls, consistent with previous evidence of reinforcer magnitude discrimination following lesions of the whole Acb e.g. [27,28]. Together, these results suggest that the impulsive choice seen in AcbC-lesioned rats [22] is due to a problem in processing delayed reward, not in processing the magnitudes of the reward alternatives. Finally, to establish whether the AcbC is required for the performance of an instrumental response for delayed reinforcement, as well as for the learning of such a response, we trained naïve rats to respond for delayed reinforcement (Figure 1) before destroying the AcbC. We report that such lesions also impaired performance of a previously-learned instrumental response only when reinforcement was delayed, indicating that the AcbC makes an enduring contribution to bridging delays between subjects' actions and the ensuing outcomes.
Figure 1 Task schematic: free-operant instrumental responding on a fixed-ratio-1 (FR-1) schedule with delayed reinforcement Subjects are offered two levers; one (the active lever) delivers a single food pellet for every press (an FR-1 schedule) and the other (the inactive lever) has no programmed consequence. Food can either be delivered immediately (a) or after a delay (b) following responses on the active lever. The levers remain available throughout the session (hence, free-operant responding: animals are free to perform the operant at any time). Events of interest are lever presses, delivery of food pellets, and collection of food by the rat (when it pokes its nose into the food alcove following food delivery). To obtain food, the hungry rat must discriminate the active from the inactive lever, which is more difficult when the outcome is delayed. In these examples, the rat's response patterns (active and inactive lever presses, and collection of food) are fictional, while food delivery is contingent upon active lever pressing.
Results
In Experiment 1, rats received excitotoxic lesions of the AcbC or sham lesions, and were then tested on an instrumental free-operant acquisition task with delayed reinforcement (Experiment 1A; see Methods) and subsequently a reinforcer magnitude discrimination task (Experiment 1B). In Experiment 2, naïve rats were trained on the free-operant task for delayed reinforcement; AcbC lesions were then made and the rats were retested.
Histology
In Experiment 1, there were two postoperative deaths. Histological analysis revealed that the lesions were incomplete or encroached significantly on neighbouring structures in four subjects. These subjects were excluded; final group numbers were therefore 8 (sham, 0 s delay), 6 (AcbC, 0 s delay), 8 (sham, 10 s delay), 7 (AcbC, 10 s delay), 8 (sham, 20 s delay), and 7 (AcbC, 20 s delay). In Experiment 2, one rat spontaneously fell ill with a colonic volvulus during preoperative training and was killed, and there were three postoperative deaths. Lesions were incomplete or too extensive in seven subjects; final group numbers were therefore 7 (sham, 0 s delay), 5 (AcbC, 0 s delay), 8 (sham, 10 s delay), 4 (AcbC, 10 s delay), 8 (sham, 20 s delay), and 5 (AcbC, 20 s delay).
Lesions of the AcbC encompassed most of the core subregion; neuronal loss and associated gliosis extended in an anteroposterior direction from approximately 2.7 mm to 0.5 mm anterior to bregma, and did not extend ventrally or caudally into the ventral pallidum or olfactory tubercle. Damage to the ventromedial caudate-putamen was occasionally seen; damage to AcbSh was restricted to the lateral edge of the dorsal shell. Schematics of the lesions are shown in Figure 2. Photomicrographs of one lesion are shown in Figure 3, and are similar to lesions with identical parameters that have been presented before [29,30].
Figure 2 Schematic of lesions of the AcbC Black shading indicates the extent of neuronal loss common to all subjects; grey indicates the area lesioned in at least one subject. Coronal sections are (from top to bottom) +2.7, +2.2, +1.7, +1.2, and +0.7 mm relative to bregma. Diagrams are modified from reference [83]. Panels a-c correspond to Experiment 1, in which lesions were made before training; panels d-f correspond to Experiment 2, in which lesions were made after initial training. Panels a & d show groups trained with no delays; panels b & e show groups trained with 10 s delays; panels c & f show groups trained with 20 s delays.
Figure 3 Photomicrographs of lesions of the AcbC Lesions of the AcbC: photomicrographs of sections ~1.2 mm anterior to bregma, stained with cresyl violet. (a) Sham-operated rat, low-magnification view, right hemisphere (medial to the left). LV, lateral ventricle; CPu, caudate/putamen; AcbSh, nucleus accumbens shell; AcbC, nucleus accumbens core; ac, anterior commissure. The box marks the area magnified in (b). (b) Sham-operated rat, high-magnification view. Cresyl violet is basic and stains for Nissl substance, primarily nucleic acids (DNA and RNA); it therefore stains cytoplasmic rough endoplasmic reticulum, nuclei, and nucleoli. Individual neuronal nuclei are visible (circles ~10 μm in diameter). (c) AcbC-lesioned rat, low-magnification view. Dotted lines show the approximate extent of the lesion. There is some tissue collapse within the lesion and the lateral ventricle is slightly expanded. The box marks the area magnified in (d). (d) AcbC-lesioned rat, high-magnification view. In the region of the lesion, neurons have been replaced by smaller, densely-staining cells, indicating gliosis. (e) Coronal diagram of the rat brain at the same anteroposterior level [83], with scale. The light grey box indicates approximately the region shown in (a) and (c); the dark grey box indicates approximately the region shown in (b) and (e).
Acquisition of instrumental responding (Experiment 1A)
The imposition of response-reinforcer delays retarded the acquisition of free-operant lever pressing, in sham-operated rats and in AcbC-lesioned rats (Figure 4). AcbC-lesioned rats responded slightly more than shams on both the active and inactive levers in the absence of response-reinforcers delays, but when such delays were present, AcbC lesions retarded acquisition relative to sham-operated controls (Figure 5).
Figure 4 Effects of delays to reinforcement on acquisition of free-operant responding under an FR-1 schedule Data plotted to show the effects of delays. All groups discriminated between the active and the inactive lever, and delays retarded acquisition of the active lever response in both groups. (a) Responding of sham-operated control rats, under all three response-reinforcer delay conditions. (b) Responding of AcbC-lesioned rats under all delay conditions. The next figure replots these data to show the effect of the lesion more clearly.
Figure 5 Effect of AcbC lesions on acquisition of free-operant responding with delayed reinforcement Data plotted to show the effects of AcbC lesions (same data as in the previous figure). There was a delay-dependent impairment in AcbC-lesioned rats, who learned less well than shams only when reinforcement was delayed. (a) With a delay of 0 s, AcbC-lesioned rats learned just as well as shams; in fact, they responded more on the active lever than shams did. (b) With a 10 s delay, AcbC-lesioned rats were impaired at learning compared to shams. (c) With a 20 s delay, the impairment in AcbC-lesioned rats was larger still.
An overall ANOVA using the model lesion2 × delay3 × (session14 × lever2 × S) revealed multiple significant interactions, including lever × delay × lesion (F2,38 = 5.17, p = .01) and session × lever × delay (F6.0,229.1 = 5.47, = .464, p < .001), justifying sub-analysis. All six groups learned to respond more on the active lever than the inactive lever (p ≤ .002, main effect of lever or session × lever interaction for each group alone).
For sham-operated rats, delays reduced the rate of acquisition of the active lever response and reduced the asymptotic level of responding attained (Figure 4a; delay: F2,21 = 11.7, p < .001; = .276, p < .001; session × delay: F7.2,75.3 = 2.46, = .276, p = .024). The presence of a delay also increased responding on the inactive lever slightly (delay: F2,21 = 4.06, p = .032), though not systematically (the 10 s group differed from the 0 s group, p = .036, but no other groups differed, p ≥ .153).
There was a further, delay-dependent impairment in AcbC-lesioned rats, who responded more than shams at 0 s delay but substantially less than shams at 10 s and 20 s delay. As in the case of sham-operated controls, delays reduced the rate of acquisition and the maximum level of responding attained in AcbC-lesioned rats (Figure 4b; delay: F2,17 = 54.6, p < .001; delay × session: F6.9,58.7 = 2.64, = .266, p = .02). Responding on the inactive lever was not significantly affected by the delays (maximum F15.8,134.2 = 1.65, = .607, p = .066). At 0 s delay, AcbC-lesioned subjects responded more than shams on the active lever (Figure 5a; lesion: F1,12 = 5.30, p = .04) and the inactive lever (lesion: F1,12 = 9.12, p = .011). However, at 10 s delay, AcbC-lesioned rats responded significantly less than shams on the active lever (Figure 5b; lesion: F1,13 = 9.04, p = .01); there was no difference in responding on the inactive lever (F < 1, NS). At 20 s delay, again, AcbC-lesioned rats responded significantly less than shams on the active lever (Figure 5c; lesion: F1,13 = 9.87, p = .008) and there was no difference in responding on the inactive lever (F < 1, NS).
Experienced response-delivery and response-collection delays (Experiment 1A)
For every reinforcer delivered, the active lever response most closely preceding it in time was identified, and the time between that response and delivery of the reinforcer (the 'response-delivery delay') was calculated. This time can therefore be equal to or less than the programmed delay, and is only relevant for subjects experiencing non-zero programmed response-reinforcer delays. The response-to-reinforcer-collection ('response-collection') delays were also calculated: for every reinforcer delivered, the response most closely preceding it and the nosepoke most closely following it were identified, and the time between these two events calculated. This time can be shorter or longer than the programmed delay, and is relevant for all subjects.
AcbC-lesioned rats experienced the same response-delivery delays as shams when the programmed delay was 10 s, but experienced longer response-delivery delays when the programmed delay was 20 s (Figure 6a). Similarly, AcbC-lesioned rats experienced the same response-collection delays as shams when the programmed delay was 0 s, slightly but not significantly longer response-collection delays when the programmed delay was 10 s, and significantly longer response-collection delays when the programmed delay was 20 s (Figure 6b). These differences in the mean delay experienced by each rat were reflected in differences in the distribution of response-delivery and response-collection delays when the programmed delay was non-zero (Figure 6c,d). Since AcbC-lesioned rats experienced slightly longer delays than sham-operated rats, it was necessary to take this into account when establishing the effect of delays on learning, as follows.
Figure 6 Programmed and experienced delays to reinforcement AcbC-lesioned rats experienced slightly longer response-delivery delays (the delay between the most recent active lever press and pellet delivery) than shams in the 20 s condition, and slightly longer response-collection delays (the delay between the most recent active lever press and pellet collection) in the 10 s and 20 s conditions. (a) Mean experienced response-delivery delays (one value calculated per subject). When the programmed delay was 0 s, reinforcers were delivered immediately so no data are shown. There was a lesion × programmed delay interaction (F1,26 = 12.0, p = .002): when the programmed delay was 10 s, the experienced delays did not differ between groups (F < 1, NS), but when the programmed delay was 20 s, AcbC-lesioned rats experienced longer response-delivery delays (one-way ANOVA, F1,13 = 19.0, ** p = .001). (b) Mean experienced response-collection delays (one value calculated per subject). There was a lesion × programmed delay interaction (F2,38 = 7.14, p = .002): AcbC-lesioned rats did not experience significantly different delays when the programmed delay was 0 s (F < 1, NS) or 10 s (F1,13 = 4.52, p = .053), but experienced significantly longer response-collection delays when the programmed delay was 20 s (F1,13 = 15.4, ** p = .002). (c) Distribution of experienced response-delivery delays. All experienced delays for a given subject were aggregated across all sessions, and the proportion falling into different 2 s ranges were calculated to give one value per range per subject; the graphs show means ± SEMs of these values. The interval notation '[a, b)' indicates that a given delay x falls in the range a ≤ x <b. There were no differences in the distribution of delays experienced by AcbC-lesioned and sham rats in the 10 s condition (lesion and lesion × range, Fs < 1, NS), but in the 20 s condition AcbC-lesioned rats experienced slightly fewer short delays and slightly more long delays (lesion × range, F2.1,27.7 = 6.60, = .213, p = .004). (d) Distribution of experienced response-collection delays, displayed in the same manner as (c). There were no differences in the distribution of delays experienced by AcbC-lesioned and sham rats in the 0 s condition (lesion and lesion × range, Fs < 1, NS). In the 10 s condition, AcbC-lesioned rats experienced a slightly higher proportion of long response-collection delays and a slightly lower proportion of short response-collection delays (lesion, F1,13 = 6.36, p = .036, though the lesion × range interaction was not significant, F2.6,34.3 = 1.74, = .139, p = .181). Similarly, in the 20 s condition, AcbC-lesioned rats experienced a slightly higher proportion of long response-collection delays and a slightly lower proportion of short response-collection delays than shams (lesion × range, F4.2,54.8 = 6.65, = .222, p < .001).
Effect of delays on learning (Experiment 1A)
There was a systematic relationship between the acquisition rate and the programmed delay of reinforcement, and this was altered in AcbC-lesioned rats. Figure 7a replots the rates of responding on the active lever on session 10 of acquisition [1]. Despite the comparatively low power of such an analysis, lever-pressing was analysed for this session only using the model lesion2 × delay3. This revealed a significant lesion × delay interaction (F2,38 = 12.6, p < .001), which was analysed further. Increasing delays significantly reduced the rate of responding in this session for shams (F2,21 = 17.3, p < .001) and AcbC-lesioned rats (F2,17 = 54.4, p < .001). AcbC-lesioned rats responded more than shams at zero delay (F1,12 = 8.52, p = .013) but less than shams at 10 s delay (F1,13 = 4.71, p = .049) and at 20 s delay (F1,13 = 17.3, p = .001).
Figure 7 Learning as a function of programmed and experienced delays to reinforcement The imposition of response-reinforcer delays systematically retarded the acquisition of free-operant instrumental responding, and this relationship was altered in AcbC-lesioned rats, even allowing for differences in experienced response-collection delays. (a) The rate of responding on the active lever in session 10 is plotted against the programmed response-reinforcer delay. AcbC-lesioned rats responded more than shams at zero delay (* p = .013), but less than shams at 10 s (* p = .049) and 20 s delay (*** p = .001). (b) Responding on the active lever in session 10 plotted against the experienced response-to-reinforcer collection delays for sessions 1–10 (vertical error bars: SEM of the square-root-transformed number of responses in session 10; horizontal error bars: SEM of the experienced response-collection delay, calculated up to and including that session). The gradients of the two lines differed significantly (### p = .001; see text), indicating that the relationship between experienced delays and responding was altered in AcbC-lesioned rats.
Since the AcbC group experienced slightly longer response-delivery and response-collection delays than shams when the programmed delay was non-zero (Figure 6), it was important to establish whether this effect alone was responsible for the retardation of learning, or whether delays retarded learning in AcbC-lesioned rats over and above any effect to increase the experienced delay. The mean experienced response-collection delay was calculated for each subject, up to and including session 10. The square-root-transformed number of responses on the active lever in session 10 was then analysed using a general linear model of the form lesion2 × experienced delaycov. Unlike a standard analysis of covariance, the factor × covariate interaction term was included in the model. This confirmed that the lesion retarded the acquisition of responding in AcbC-lesioned rats, compared to controls, in a delay-dependent manner, over and above the differences in experienced delay (Figure 7b; lesion × experienced delay: F1,40 = 12.4, p = .001).
Experienced delays and learning on the inactive lever (Experiment 1A)
No such delay-dependent effects were observed for the inactive lever. Experienced inactive-response-delivery delays (calculated across all sessions in the same manner as for the active lever) were much longer and more variable than corresponding delays for the active lever, because subjects responded on the inactive lever so little. Means ± SEMs were 250 ± 19 s (sham, 0 s), 214 ± 29 s (AcbC, 0 s), 167 ± 23 s (sham, 10 s), 176 ± 33 s (AcbC, 10 s), 229 ± 65 s (sham, 20 s), and 131 ± 37 s (AcbC, 20 s). ANOVA of these data revealed no effects of lesion or programmed delay and no interaction (maximum F1,38 = 1.69, NS). Experienced inactive-response-collection delays were 252 ± 19 s (sham, 0 s), 217 ± 29 s (AcbC, 0 s), 169 ± 23 s (sham, 10 s), 179 ± 33 s (AcbC, 10 s), 231 ± 65 s (sham, 20 s), and 136 ± 37 s (AcbC, 20 s). Again, ANOVA revealed no effects of lesion or programmed delay and no interaction (maximum F1,38 = 1.61, NS). When the square-root-transformed number of responses on the inactive lever in session 10 was analysed with the experienced delays up to that point as a predictor, using the model lesion2 × experienced inactive-response-collection delaycov just as for the active lever analysis, there was no lesion × experienced delay interaction (F < 1, NS).
Discrimination of relative reinforcer magnitude (Experiment 1B)
Relative preference for two reinforcers may be inferred from the distribution of responses on concurrent variable interval schedules of reinforcement [31-33]. According to Herrnstein's matching law [31], if subjects respond on two concurrent schedules A and B delivering reinforcement at rates rA and rB respectively, they should allocate their response rates RA and RB such that RA/(RA+RB) = rA/(rA+rB). Overmatching is said to occur if subjects prefer the schedule with the higher reinforcement rate more than predicted by the matching law; undermatching is the opposite. Both sham-operated and AcbC-lesioned rats were sensitive to the distribution of reinforcement that they received on two concurrent random interval (RI) schedules, altering their response allocation accordingly. Subjects preferred the lever on which they received a greater proportion of reinforcement. In general, subjects did not conform to the matching law, but exhibited substantial undermatching; this is common [33]. AcbC-lesioned rats exhibited better matching (less undermatching) than shams (Figure 8), suggesting that their sensitivity to the relative magnitudes of the two reinforcers was as good as, or better than, shams'.
Figure 8 Discrimination of reinforcer magnitude: matching of relative response rate to relative reinforcement rate AcbC-lesioned rats exhibited better sensitivity to the difference between 1 and 4 food pellets than shams did. Subjects responded on two concurrent RI-60-s schedules, designated A and B, and the reinforcer magnitude for each schedule was varied. Data from the last session of each condition are plotted (sessions 11, 19, and 27; see Table 1); programmed reinforcement ratios were 0.2 (1 food pellet on schedule A and 4 pellets on schedule B), 0.5 (1:1 pellets), and 0.8 (4:1 pellets). The abscissa (horizontal axis) shows experienced reinforcement ratios (mean ± SEM); the ordinate (vertical axis) shows response allocation (mean ± SEM). Both groups exhibited substantial undermatching (deviation away from the predictions of the matching law and towards indifference). However, neither group was indifferent to the reinforcement ratio: the sham and AcbC groups both adjusted their response allocation towards the lever delivering the reinforcer with the greater magnitude (*** p < .001). Matching was better in AcbC-lesioned rats than in shams (lines of different gradient, # p = .021), suggesting that they were more sensitive to the difference between 1 and 4 food pellets.
Table 1 Training and testing schedule for reinforcer magnitude matching task (Experiment 1B) Subjects were trained to respond on two levers (designated A and B) separately and then concurrently under interval schedules of reinforcement. In sessions 8–27, their preference for reinforcers of different magnitudes was assessed. The third column, labelled 'fA', indicates the fraction of responses that would be allocated to lever A [i.e. A/(A+B)] were the subject to obey the matching law [31]. All concurrent (two-lever) schedules were subject to a 2 s changeover delay (COD), described in the Methods.
Day Condition fA Lever A Lever B
1 One-lever training -- RI-2s, 1-pellet reinforcer absent
2 One-lever training -- absent RI-2s, 1-pellet reinforcer
3 One-lever training -- RI-15s, 1-pellet reinforcer absent
4 One-lever training -- absent RI-15s, 1-pellet reinforcer
5 One-lever training -- RI-30s, 1-pellet reinforcer absent
6 One-lever training -- absent RI-30s, 1-pellet reinforcer
7 Two-lever training 0.5 RI-30s, 1-pellet reinforcer RI-30s, 1-pellet reinforcer
8–11 1:1 magnitude 0.5 RI-60s, 1-pellet reinforcer RI-60s, 1-pellet reinforcer
12–19 4:1 magnitude 0.8 RI-60s, 4-pellet reinforcer RI-60s, 1-pellet reinforcer
20–27 1:4 magnitude 0.2 RI-60s, 1-pellet reinforcer RI-60s, 4-pellet reinforcer
To analyse these data, the proportion of pellets delivered by lever A (see Methods), and the proportion of responses allocated to lever A, were calculated for each subject for the last session in each of the three programmed reinforcement distribution contingencies (session 11, programmed reinforcement proportion 0.5; session 19, programmed proportion 0.8; session 27, programmed proportion 0.2; see Table 1). The analysis used a model of the form response proportion = lesion2 × (experienced reinforcer distributioncov × S); the factor × covariate term was included in the model. Analysis of sham and AcbC groups separately demonstrated that both groups altered their response allocation according to the distribution of reinforcement, i.e. that both groups discriminated the two reinforcers on the basis of their magnitude (effects of reinforcer distribution; sham: F1,47 = 16.6, p < .001; AcbC: F1,39 = 97.2, p < .001). There was also a significant lesion × reinforcer distribution interaction (F1,86 = 5.5, p = .021), indicating that the two groups' matching behaviour differed, with the AcbC-lesioned rats showing better sensitivity to the relative reinforcer magnitude than the shams (Figure 8). These statistical conclusions were not altered by including counterbalancing terms accounting for whether lever A was the left or right lever (the left having been the active lever previously in Experiment 1A), or whether a given rat had been trained with 0, 10, or 20 s delays in Experiment 1A.
Switching behaviour during concurrent schedule performance (Experiment 1B)
Because switching behaviour has the potential to influence behaviour on concurrent schedules e.g. [34], we also analysed switching probabilities. AcbC-lesioned rats were less likely than shams to switch between levers when responding on two identical concurrent RI schedules with a changeover delay (COD) of 2 s. Responses on the left and right levers were sequenced for sessions 8–11 (concurrent RI-60s schedules, each delivering a one-pellet reinforcer; see Methods and Table 1), and the probabilities of switching from one type of response to another, or repeating the same type of response, were calculated. The switch probabilities were analysed by one-way ANOVA; this revealed an effect of lesion (F1,42 = 8.88, p = .005). Mean switch probabilities (± SEMs) were 0.41 ± 0.02 (AcbC) and 0.49 ± 0.01 (sham).
Effects of AcbC lesions on performance of a previously-learned instrumental response for delayed reinforcement (Experiment 2)
Due to mechanical faults, data from four subjects in session 10 (preoperative) and data from one subject in session 22 (postoperative) were not collected. Both sessions were removed from analysis completely, and data points for those sessions are plotted using the mean and SEM of the remaining unaffected subjects (but not analysed).
Preoperatively, the groups remained matched following later histological selection. Analysis of the last 3 preoperative sessions, using the model lesion intent2 × delay3 × (session3 × lever2 × S), indicated that responding was affected by the delays to reinforcement (delay: F2,31 = 5.46, p = .009; delay × lever: F2,31 = 19.5, p < .001), but there were no differences between the groups due to receive AcbC and sham lesions (terms involving lesion intent: maximum F was for session × lever × lesion intent, F2,62 = 1.844, NS). As expected, delays reduced the rate of responding on the active lever (F2,31 = 15.6, p < .001) and increased responding on the inactive lever (F2,31 = 8.12, p = .001) preoperatively.
AcbC lesions selectively impaired performance of instrumental responding only when there was a response-reinforcer delay. There was no effect of the lesion on responding under the 0 s delay condition, but in the presence of delays, AcbC lesions impaired performance on the active lever (Figure 9; Figure 10). These conclusions were reached statistically as follows.
Figure 9 Postoperative performance under an FR-1 schedule for delayed reinforcement Data plotted to show the effects of delays. All groups discriminated between the active and the inactive lever, and delays retarded acquisition of the active lever response in both groups. Postoperatively, shams' performance was unaltered, as was that of AcbC-lesioned rats in the 0 s delay condition. However, active lever responding was impaired postoperatively in AcbC-lesioned rats in the 10 s and 20 s conditions. (a) Responding of sham-operated control rats, under all three response-reinforcer delay conditions. The vertical black line indicates the time of surgery, between testing sessions 14 and 15. (b) Responding of AcbC-lesioned rats under all delay conditions. The next figure replots these data to show the effect of the lesion more clearly.
Figure 10 Effect of AcbC lesions on performance of free-operant responding for delayed reinforcement Data plotted to show the effects of AcbC lesions (same data as in the previous figure). There was a delay-dependent impairment in AcbC-lesioned rats, who were impaired by the lesion only when reinforcement was delayed. (a) With a delay of 0 s, AcbC-lesioned rats performed just as well as shams postoperatively. The vertical black line indicates the time of surgery, between testing sessions 14 and 15. (b) With a 10 s delay, AcbC-lesioned rats were impaired postoperatively compared to shams. (c) With a 20 s delay, the postoperative impairment in AcbC-lesioned rats was larger still, to the extent that their discrimination between active and inactive levers was no longer significant.
Subjects' responding on the relevant lever in the last preoperative session (session 14) was used as a covariate to increase the power of the analysis [35]. As expected, there were no significant differences in the covariates themselves between groups due to receive AcbC or sham surgery (terms involving lesion intent for the active lever: Fs < 1, NS; for the inactive lever, lesion intent: F1,31 = 2.99, p = .094; lesion intent × delay: F < 1, NS). Analysis of the postoperative sessions, using the model lesion2 × delay3 × (session17 × lever2 × session-14-active-lever-responsescov × S), revealed a near-significant lesion × delay × session × lever interaction (F22.4,335.5 = 1.555, = .699, p = .054). Furthermore, analysis of postoperative responding on the active lever, using the model lesion2 × delay3 × (session17 × session-14-active-lever-responsescov × S), revealed a session × delay × lesion interaction (F17.3,259.5 = 1.98, = .541, p = .013) and a delay × lesion interaction (F2,30 = 3.739, p = .036), indicating that the lesion affected responding on the active lever in a delay-dependent manner. In an identical analysis of responding on the inactive lever (using inactive lever responding on session 14 as the covariate), no terms involving lesion were significant (maximum F: lesion, F1,30 = 1.96, p = .172), indicating that the lesion did not affect responding on the inactive lever.
Postoperatively, response-reinforcer delays continued systematically to decrease responding on the active lever, both in shams (Figure 9a; delay: F2,20 = 11.78, p < .001; session × delay: F12.4,124.1 = 2.36, = .388, p = .008) and in AcbC-lesioned rats (Figure 9b; delay: F2,11 = 13.9, p = .001). Shams continued to discriminate between the active and inactive lever at all delays (lever: all groups p ≤ .002; lever × session: all groups p ≤ .003). AcbC-lesioned rats continued to discriminate at 0 s and 10 s (lever: p ≤ .011; lever × session: p ≤ .036), but AcbC-lesioned subjects in the 20 s condition failed to discriminate between the active and inactive levers postoperatively (lever: F1,4 = 1.866, p = .244; lever × session: F < 1, NS).
Lesioned subjects responded as much as shams at 0 s delay, but substantially less than shams at 10 s and 20 s delay (Figure 10). Again, analysis was conducted using responding on the relevant lever in session 14 (the last preoperative session) as a covariate. At 0 s, the lesion did not affect responding on the active lever (lesion: F < 1, NS; lesion × session: F16,144 = 1.34, NS). However, at 10 s, AcbC-lesioned rats responded significantly less than shams on the active lever (lesion: F1,9 = 7.08, p = .026; lesion × session: F15.0,135.3 = 3.04, = .94, p < .001). Similarly, at 20 s, AcbC-lesioned rats responded less than shams on the active lever (lesion: F1,10 = 6.282, p = .031). There were no differences on responding on the inactive lever at any delay (Fs ≤ 1.31, NS).
Experienced response-delivery and response-collection delays (Experiment 2)
As in Experiment 1, AcbC-lesioned rats experienced the same response-delivery delays as shams when the programmed delay was 10 s, but experienced longer response-delivery delays when the programmed delay was 20 s (Figure 11a). Similarly, AcbC-lesioned rats experienced the same response-collection delays as shams when the programmed delay was 0 s, slightly but not significantly longer response-collection delays when the programmed delay was 10 s, and significantly longer response-collection delays when the programmed delay was 20 s (Figure 11b).
Figure 11 Programmed and experienced delays to reinforcement following AcbC lesions made after initial training AcbC-lesioned rats experienced slightly longer response-delivery and response-collection delays than shams in the 20 s condition. Lesions were made after initial training; postoperative experienced delays are plotted. (Compare Figure 6, in which rats had no preoperative experience of the task.) (a) Mean experienced response-delivery delays (one value calculated per subject). When the programmed delay was 0 s, reinforcers were delivered immediately so no data are shown. There were main effects of lesion (F1,21 = 9.14) and delay (F1,21 = 87.5, p < .001) but no lesion × delay interaction (F1,21 = 1.91, NS). When the programmed delay was 10 s, the experienced delays did not quite differ significantly between groups (F1,10 = 4.61, p = .057), but when the programmed delay was 20 s, AcbC-lesioned rats experienced longer response-delivery delays (F1,11 = 6.29, * p = .029). (b) Mean experienced response-collection delays (one value calculated per subject). There was a lesion × delay interaction (F2,31 = 3.85, p = .032), as well as main effects of lesion (F1,31 = 11.9, p = .002) and delay (F2,31 = 171, p < .001). AcbC-lesioned rats did not experience significantly different delays when the programmed delay was 0 s (F1,10 = 1.74, NS) or 10 s (F1,10 = 1.49, NS), but experienced significantly longer response-collection delays when the programmed delay was 20 s (F1,11 = 13.7, ** p = .003).
Relationship between experienced delays and performance (Experiment 2)
There was a systematic relationship between the postoperative response rate and the programmed delay of reinforcement, and this was altered in AcbC-lesioned rats. Figure 12a replots the rates of lever-pressing on session 24, the 10th postoperative session (compare Figure 7). An analysis using the model lesion2 × programmed delay3 revealed a significant lesion × delay interaction (F2,31 = 5.09, p = .012). In this session, there was no significant effect of delays on shams' performance (F2,20 = 2.15, p = .143), though there was for AcbC-lesioned rats (F2,11 = 9.01, p = .005). There were no significant differences in responding on this session between shams and AcbC-lesioned rats in the 0 s condition (F1,10 = 3.10, p = .109) or the 10 s condition (F < 1, NS), but AcbC-lesioned rats responded less at 20 s delay (F1,11 = 6.74, p = .025).
Figure 12 Performance as a function of delays to reinforcement in animals trained preoperatively Response-reinforcer delays systematically lowered the rate of free-operant instrumental responding, and this relationship was altered in AcbC-lesioned rats, even allowing for differences in response-collection delays experienced postoperatively. Lesions were made after initial training; postoperative experienced delays and response rates are plotted. (Compare Figure 7, in which rats had no preoperative experience of the task.) (a) The rate of responding on the active lever in session 24 (the 10th postoperative session; compare Figure 7) is plotted against the programmed response-reinforcer delay. AcbC-lesioned rats responded significantly less than shams in the 20 s delay condition (* p = .025). (b) Responding on the active lever in session 24 (the 10th postoperative session) plotted against the experienced response-to-reinforcer-collection delays for postoperative sessions up to and including session 24 (vertical error bars: SEM of the square-root-transformed number of responses in session 24; horizontal error bars: SEM of the experienced response-collection delay). The gradients of the two lines differed significantly (# p = .015; see text), indicating that the relationship between experienced delays and responding was altered in AcbC-lesioned rats, compared to sham-operated controls.
Since the AcbC group experienced slightly longer response-delivery and response-collection delays than shams when the programmed delay was non-zero (Figure 11), as before, the rate of responding in session 24 was analysed as a function of the delays experienced postoperatively. The mean experienced response-collection delay was calculated for postoperative sessions up to and including session 24; the square-root-transformed number of lever presses in session 24 was then analysed using a general linear model of the form lesion2 × experienced delaycov, with the factor × covariate interaction term included in the model. This confirmed that the lesion affected responding in AcbC-lesioned rats, compared to controls, in a delay-dependent manner, over and above the postoperative differences in experienced delay (Figure 12b; lesion × experienced delay: F1,33 = 6.53, p = .015).
Locomotor activity and body mass
AcbC-lesioned animals were hyperactive compared to sham-operated controls, and gained less mass then shams across the experiments (Figure 13), consistent with previous results [22,29,36].
Figure 13 Locomotor activity in a novel environment and body mass AcbC-lesioned rats were significantly hyperactive compared to sham-operated controls, and gained less weight, in both Experiments 1 & 2. (a) Locomotor activity in Experiment 1. Analysis using the model lesion2 × (bin12 × S) revealed effects of lesion (F1,42 = 5.12, * p = .029), reflecting hyperactivity in the AcbC group, with additional effects of bin (F5.7,237.9 = 13.3, = .515, p < .001), reflecting habituation, and a lesion × bin interaction (F5.7,237.9 = 2.52, = .515, # p = .024). (b) Locomotor activity in Experiment 2. The same patterns were observed (data from five subjects were not recorded due to a mechanical error; lesion: F1,37 = 9.155, ** p = .004; bin: F9.3,345.2 = 13.5, = .848, p < .001; lesion × bin: F9.3,345.2 = 3.18, = .848, ## p = .001). (c) Preoperative and final body mass in both experiments. Preoperatively, masses did not differ between groups (Experiment 1: F < 1, NS; Experiment 2: F1,42 = 1.008, NS), but in both cases, AcbC-lesioned subjects gained less mass than controls (Experiment 1: lesion × time: F1,41 = 95.9, ### p < .001; group difference at second time point: F1,42 = 88.4, *** p < .001; Experiment 2: lesion × time: F1,42 = 13.53, ## p = .001; group difference at second time point: F1,42 = 7.37, ** p = .01).
Discussion
These results establish that the AcbC contributes to learning of actions when the outcome is delayed. Lesions of the AcbC did not impair instrumental learning when the reinforcer was delivered immediately, but substantially impaired learning with delayed reinforcement, indicating that the AcbC 'bridges' action-outcome delays during learning. Lesions made after learning also impaired performance of the instrumental response in a delay-dependent fashion, indicating that the AcbC also contributes to the performance of actions for delayed reinforcement. Finally, the lesions did not impair the perception of relative reward magnitude as assessed by responding on identical concurrent interval schedules for reinforcers of different magnitude, suggesting that the impulsive choice previously exhibited by AcbC-lesioned rats [22] is attributable to deficits in dealing with delays to reinforcement.
Effect of delays on instrumental learning in normal animals
Delays have long been known to retard instrumental learning [1,37]. Despite this, normal rats have been shown to acquire free-operant responding with programmed response-reinforcer delays of up to 32 s, or even 64 s if the subjects are pre-exposed to the learning environment [1]. Delays do reduce the asymptotic level of responding [1], though the reason for this phenomenon is not clear. It may be that when subjects learn a response with a substantial response-reinforcer delay, they never succeed in representing the instrumental action-outcome contingency fully. Alternatively, they may value the delayed reinforcer slightly less; finally, the delay may also retard the acquisition of a procedural stimulus-response habit and this might account for the decrease in asymptotic responding. It is not presently known to what degree responses acquired with a response-reinforcer delay are governed by declarative processes (the action-outcome contingency plus a representation of the instrumental incentive value of the outcome) or procedural mechanisms (stimulus-response habits), both of which are known to influence instrumental responding [38,39]; it is similarly not known whether the balance of these two controlling mechanisms differs from that governing responses learned without such a delay.
Effect of AcbC lesions on instrumental learning and performance with or without delays
In the absence of response-reinforcer delays, AcbC-lesioned rats acquired an instrumental response normally, responding even more than sham-operated controls. In contrast, blockade of N-methyl-D-aspartate (NMDA) glutamate receptors in the AcbC has been shown to retard instrumental learning for food under a variable-ratio-2 (VR-2) schedule [in which P(reinforcer | response) ≅ 0.5] [40], as has inhibition or over-stimulation of cyclic-adenosine-monophosphate-dependent protein kinase (protein kinase A; PKA) within the Acb [41]. Concurrent blockade of NMDA and DA D1 receptors in the AcbC synergistically prevents learning of a VR-2 schedule [42]. Once the response has been learned, subsequent performance on this schedule is not impaired by NMDA receptor blockade within the AcbC [40]. Furthermore, infusion of a PKA inhibitor [41] or a protein synthesis inhibitor [43] into the AcbC after instrumental training sessions impairs subsequent performance, implying that PKA activity and protein synthesis in the AcbC contribute to the consolidation of instrumental behaviour. Thus, manipulation of Acb neurotransmission can affect instrumental learning. However, it is also clear that excitotoxic destruction of the AcbC or even the entire Acb does not impair simple instrumental conditioning to any substantial degree. Rats with Acb or AcbC lesions acquire lever-press responses on sequences of random ratio schedules [in which P(reinforcer | response) typically declines from around 1 to 0.05 over training] at near-normal levels [44,45]. In such ratio schedules, where several responses are required to obtain reinforcement, there is no delay between the final response and reinforcement, but there are delays between earlier responses and eventual reinforcement. It is therefore of interest that when differences between AcbC-lesioned rats and shams have been observed, AcbC-lesioned animals have been found to respond somewhat less than shams on such schedules late in training, when the ratio requirement is high [44,45], consistent with our present results. However, lesioned rats are fully sensitive to changes in the instrumental contingency [27,44,45]. Our present results indicate that when AcbC-lesioned rats are exposed to a FR-1 schedule for food [P(reinforcer | response) = 1] in the absence of response-reinforcer delays, they acquire the response at normal rates.
In contrast, when a delay was imposed between responding and reinforcement, AcbC-lesioned rats were impaired relative to sham-operated controls, in a systematic and delay-dependent fashion. The observation that learning was not affected at zero delay rules out a number of explanations of this effect. For example, it cannot be that AcbC-lesioned rats are in some way less motivated for the food per se, since they responded normally (in fact, more than shams) when the food was not delayed. Thus although the Acb and its dopaminergic innervation are clearly very important in motivating behaviour e.g. [23,46-48], this is not on its own a sufficient explanation for the present results. An explanation in terms of a rate-dependent impairment is also not tenable, since the AcbC-lesioned rats were capable (in the zero-delay condition) of responding at a level greater than they exhibited in the non-zero-delay conditions. Depletion of Acb DA also impairs rats' ability to work on high-effort schedules, where many, or very forceful, responses are required to obtain a given amount of food [47,48]. However, in the present experiments the ratio requirement (one response per reinforcer) and the force required per press were both held constant across delays, so this effect cannot explain the present results. Similarly, although AcbC lesions are known to impair the control over behaviour by Pavlovian conditioned stimuli e.g. [23,29,49-52], there was no Pavlovian stimulus that was differentially associated with delayed as opposed to immediate reinforcement in this task, so this cannot explain the present results.
Our results also indicated that when there were programmed delays to reinforcement, AcbC-lesioned animals experienced longer response-reinforcer collection delays, partly due to their failure to collect the reinforcer as promptly as shams. These additional experienced delays probably retarded learning. However, in addition to this effect, there was a further deficit exhibited by AcbC-lesioned rats: even allowing for the longer response-collection delays that they experienced, their instrumental learning was impaired more by delays than that of sham-operated controls. Deficits in learning with delayed reinforcement may account for some of the variability in the effect of AcbC lesions or local pharmacological manipulations on instrumental learning across different schedules.
The fact that pre-exposure to the context improves instrumental learning in normal rats [1] suggests one possible mechanism by which AcbC lesions might retard learning when delays are present. When a reinforcer arrives, it may be associated either with a preceding response, or with the context. Therefore, in normal animals, pre-exposure to the context may retard the formation of context-reinforcer associations by latent inhibition, or it might serve to retard the formation of associations between irrelevant behaviours and reinforcement. Similarly, non-reinforced exposure to the context forces the subjects to experience a zero-response, zero-reinforcer situation, i.e. P(outcome | no action) = 0. When they are then exposed to the instrumental contingency, such that P(outcome | action) > 0, this prior experience may enhance their ability to detect the instrumental contingency ΔP = P(outcome | action) - P(outcome | no action). In one aversive Pavlovian conditioning procedure in which a conditioned stimulus (CS) was paired with electric shock, AcbC lesions have been shown to impair conditioning to discrete CSs, but simultaneously to enhance conditioning to contextual (background) CSs [53], though not all behavioural paradigms show this effect [54,55]. It is therefore possible that enhanced formation of context-reinforcer associations may explain the retardation of response-reinforcer learning in AcbC-lesioned rats in the presence of delays.
The instrumental task used requires animals either to associate their response with the delayed food outcome (an action-outcome association that can be used for goal-directed behaviour), or to strengthen a stimulus-response association (habit) when the reinforcer eventually arrives [38,39]. Both mechanisms require the animal to maintain a representation of their past action so it can be reinforced (as a habit) or associated with food when the food finally arrives. This mnemonic requirement is not obviated even if the animal learns to predict the arrival of food using discriminative stimuli, and uses these stimuli to reinforce its responding (conditioned reinforcement): in either case, since the action precedes reinforcement, some trace of past actions or stimuli must persist to be affected by the eventual delivery of food.
A delay-dependent impairment was also seen when AcbC lesions were made after training. This indicates that the AcbC does not only contribute to the learning of a response when there is an action-outcome delay: it also contributes to the performance of a previously-learned response. Again, AcbC-lesioned rats were only impaired when that previously-learned response was for delayed (and not immediate) reinforcement. Of course, learning of an instrumental response depends upon the animal being able to perform that response; preventing an animal from pressing a lever (a performance deficit) would clearly impair its ability to learn an instrumental response on that lever to obtain food. In the present set of experiments, it is clear that AcbC-lesioned rats were just as able to perform the response itself (to press the active lever and to discriminate it physically from the inactive lever) as controls, as shown by their normal performance in the zero-delay condition, so it is not clear whether the delay-dependent impairments in learning and performance can be attributed to the same process. Again, since responding was unaffected in the zero-delay condition, many alternative interpretations (such as a lack of motivation to work for the food) are ruled out. It may be that AcbC-lesioned rats are impaired at representing a declarative instrumental action-outcome contingency when the outcome is delayed, or in forming or executing a procedural stimulus-response habit when the reinforcing event does not follow the response immediately. It may also be that they represent the action-outcome contingency normally but value the food less because it is delayed, and that this affects responding in a free-operant situation even though there is no alternative reinforcer available.
Discrimination of reinforcer magnitude in AcbC-lesioned rats
Excitotoxic lesions of the whole Acb do not prevent rats from detecting changes in reward value (induced either by altering the concentration of a sucrose reward or by changing the deprivational state of the subject) [27]. Such lesions also do not impair rats' ability to respond faster when environmental cues predict the availability of larger rewards [28], and nor does inactivation of the Acb with local anaesthetic or blockade of AMPA glutamate receptors in the Acb [56]; the effects of intra-Acb NMDA receptor antagonists have varied [57,58]. AcbC-lesioned rats can still discriminate large from small rewards [24,25]. Similarly, DA depletion of the Acb does not affect the ability to discriminate large from small reinforcers [59-61], and systemic DA antagonists do not affect the perceived quantity of food as assessed in a psychophysical procedure [62]. Our study extends these findings by demonstrating that excitotoxic AcbC lesions do not impair rats' ability to allocate their responses across two schedules in proportion to the experienced reinforcement rate, even when the two schedules are identical except in the magnitude of the reinforcements they provide, thus demonstrating their sensitivity to reinforcer magnitude is quantitatively no worse than shams'. In this experiment, there was substantial undermatching, but this is common [33,63] see also [64,65]; differential cues signalling the two rewards might have improved matching but were not used in the present experiments since it is known that AcbC lesions can themselves affect rats' sensitivity to cues signalling reinforcement [23,29,49-52]. Given that AcbC-lesioned subjects showed a reduced probability of switching between two identical RI schedules, it may be the case that an enhanced sensitivity to the COD accounts for the better matching exhibited by the AcbC-lesioned rats [34]. Alternatively, the lesion may have enhanced reinforcer magnitude discrimination or improved the process by which behaviour allocation is matched to environmental contingencies. In summary, the present results suggest that AcbC damage leads to pathological impulsive choice (preferring a small, immediate reinforcer to a large, delayed reinforcer) [22] not through any relative lack of value of large reinforcers, but through a specific deficit in responding for delayed reinforcement.
Contribution of the AcbC to reinforcement learning
The term 'reinforcement learning' simply means learning to act on the basis of reinforcement received; it is a term used in artificial intelligence research [66] that does not specify the mechanism of such learning [67,68]. Our present results indicate that the AcbC is a reinforcement learning structure that is critical for instrumental conditioning when outcomes are delayed, consistent with electrophysiological and functional neuroimaging evidence indicating that the ventral striatum responds to recent past actions [10,15] and to predicted future rewards [8-15], and with computational models suggesting a role for the striatum in predicting future primary reinforcement [20,21]. However, when reward is certain and delivered immediately, the AcbC is not necessary for the acquisition of instrumental responding. The delay-dependent role of the AcbC indicates that it plays a role in allowing actions to be reinforced by bridging action-outcome delays through a representation of past acts or future rewards. Acb lesions have also produced delay-dependent impairments in a delayed-matching-to-position task [69,70]; their effects on the delayed-matching-to-sample paradigm have also been studied, but a more profound and delay-independent deficit was observed, likely due to differences in the specific task used [71]. Finally, the AcbC is not alone in containing neurons that respond to past actions and future rewards. The dorsal striatum is another such structure [10,15,72,73]; expression of stimulus-response habits requires the dorsal striatum [74,75], and the rate at which rats learn an arbitrary response that delivers electrical stimulation to the substantia nigra is correlated with the degree of potentiation of synapses made by cortical afferents onto striatal neurons, a potentiation that requires DA receptors [76,77]. The prelimbic area of rat prefrontal cortex is important for the detection of instrumental contingencies and contributes to goal-directed, rather than habitual, action [78,79]. Similarly, the orbitofrontal cortex and basolateral amygdala encode reinforcement information and project to the AcbC, and lesions of these structures can produce impulsive choice see [24,80-82]. It is not yet known whether lesions of these structures also impair learning with delayed reinforcement.
Conclusions
We have demonstrated that excitotoxic lesions of the AcbC do not prevent rats from learning a simple instrumental response when the reinforcing outcome follows their action immediately. However, AcbC lesions impair rats' ability to learn the same instrumental response when the outcome is delayed. The lesions also impair performance of an instrumental response that was learned preoperatively, but again only when response-reinforcer delays were present. These results suggest that the AcbC makes a specific contribution to reinforcement learning and instrumental performance when reinforcing outcomes do not arrive immediately but are delayed. AcbC dysfunction, which is known to promote impulsive choice, appears to cause rats to be temporally short-sighted, learning preferentially about the proximal consequences of their actions and preferring immediate over delayed rewards.
Methods
Overview of experiments
Experiment 1A: Effects of AcbC lesions on acquisition of instrumental responding with delayed reinforcement
Fifty naïve rats received excitotoxic lesions of the AcbC (n = 26) or sham lesions (n = 24). Two died postoperatively. Subjects were next trained in a task in which they had continuous access to two identical levers; one lever delivered a single food pellet each time it was pressed, and the other lever had no effect. For some rats, the food pellet was delivered immediately after the lever press (0 s condition; n = 8 AcbC-lesioned rats and 8 shams). For others, each pellet was delayed by either 10 s (8 AcbC, 8 sham) or 20 s (8 AcbC, 8 sham). Subjects were trained for 14 sessions.
Experiment 1B: Effects of AcbC lesions on the ability to match response distribution to reinforcer magnitude distribution
After the same rats had their locomotor activity assessed, they moved on to a task testing their ability to judge differences in the magnitude of two reinforcers. They were again offered two levers, but this time both levers delivered reinforcement on a variable-interval schedule, which provides reinforcement in an intermittent and temporally unpredictable fashion. Reinforcers consisted of either 1 or 4 sucrose pellets. Over sessions, the levers' roles changed so that the ratio of the sizes of the reinforcers available on the two levers was 4:1, 1:1, or 1:4. Subjects' responding was measured to establish their ability to judge the relative differences in reinforcer magnitudes and to allocate their responses according to the matching law [31-33]. Finally, they were killed and perfused for histology.
Experiment 2: Effects of AcbC lesions on performance of a previously-learned instrumental response for delayed reinforcement
A further 48 naïve rats were trained to acquire an instrumental response as before, with delays to reinforcement of 0 s (n = 16), 10 s (n = 16), or 20 s (n = 16). One rat spontaneously fell ill with a colonic volvulus and was killed. Once the subjects had been trained for 14 sessions, they were allocated to receive either AcbC lesions or sham surgery (0 s: 8 AcbC, 7 sham; 10 s: 8 AcbC, 8 sham; 20 s: 8 AcbC, 8 sham). Sham and AcbC groups were matched for performance preoperatively: within each delay condition, rats were ranked by their rates of responding on the active lever at the end of training, and rats with equivalent levels of performance were randomized to receive sham or AcbC lesion surgery. They were then retested postoperatively on the same task for a further 18 sessions (giving 32 sessions in total), with each rat experiencing the same delay as it had preoperatively. These rats then had their locomotor activity assessed, and were killed and perfused for histology.
Subjects and housing conditions
Subjects were male Lister hooded rats (Harlan-Olac UK Ltd) housed in a temperature-controlled room (minimum 22°C) under a 12:12 h reversed light-dark cycle (lights off 07:30 to 19:30). Subjects were approximately 15 weeks old on arrival at the laboratory and were given a minimum of a week to acclimatize, with free access to food, before experiments began. Experiments took place between 09:00 and 21:00, with individual subjects being tested at a consistent time of day. Subjects had free access to water. During behavioural testing, they were maintained at 85–90% of their free-feeding mass using a restricted feeding regimen. Feeding occurred in the home cages at the end of the experimental day. All procedures were subject to UK Home Office approval (Project Licences PPL 80/1324 and 80/1767) under the Animals (Scientific Procedures) Act 1986.
Excitotoxic lesions of the nucleus accumbens core
Subjects were anaesthetized with Avertin (2% w/v 2,2,2-tribromoethanol, 1% w/v 2-methylbutan-2-ol, and 8% v/v ethanol in phosphate-buffered saline, sterilized by filtration, 10 ml/kg i.p.) and placed in a Kopf or Stoelting stereotaxic frame (David Kopf Instruments, Tujunga, California, USA; Stoelting Co., Wood Dale, Illinois, USA) fitted with atraumatic ear bars. The skull was exposed and a dental drill was used to remove the bone directly above the injection and cannulation sites. The dura mater was broken with the tip of a hypodermic needle, avoiding damage to underlying venous sinuses. Excitotoxic lesions of the AcbC were made by injecting 0.5 μl of 0.09 M quinolinic acid (Sigma, UK) through a glass micropipette at coordinates 1.2 mm anterior to bregma, ± 1.8 mm from the midline, and 7.1 mm below the skull surface at bregma; the incisor bar was 3.3 mm below the interaural line [83]. The toxin had been dissolved in 0.1 M phosphate buffer (composition 0.07 M Na2HPO4, 0.028 M NaH2PO4 in double-distilled water, sterilized by filtration) and adjusted with NaOH to a final pH of 7.2–7.4. Toxin was injected over 3 min and the micropipette was left in place for 2 min following injections. Sham lesions were made in the same manner except that vehicle was infused. At the end of the operation, animals were given 15 ml/kg of sterile 5% w/v glucose, 0.9% w/v sodium chloride intraperitoneally. They were given a week to recover, with free access to food, and were handled regularly. Any instances of postoperative constipation were treated with liquid paraffin orally and rectally. At the end of this period, food restriction commenced or was resumed.
Behavioural apparatus
Behavioural testing was conducted in one of two types of operant chamber of identical configuration (from Med Associates Inc, Georgia, Vermont, USA, or Paul Fray Ltd, Cambridge, UK). Each chamber was fitted with a 2.8 W overhead house light and two retractable levers on either side of an alcove fitted with an infrared photodiode to detect head entry. Sucrose pellets (45 mg, Rodent Diet Formula P, Noyes, Lancaster, New Hampshire, USA) could be delivered into the alcove. The chambers were enclosed within sound-attenuating boxes fitted with fans to provide air circulation. The apparatus was controlled by software written by RNC in C++ [84] using the Whisker control system [85].
Instrumental conditioning with delayed reinforcement
A variety of free-operant schedules may be used to assess instrumental acquisition with delayed reinforcement [1]. We used the simplest possible free-operant schedule: each response scheduled a reinforcer after the programmed delay (Figure 1). In such a schedule, if the subject responds during the delay, the experienced response-reinforcer delay will not match the programmed delay (as the second response is temporally close to the first reinforcer). However, this schedule has the advantage that the response-reinforcer contingency is constant (every response does in fact cause the delivery of reinforcement) and the reinforcement rate is not constrained [1]. So that responding could be attributed to the instrumental response-reinforcer contingency, rather than the effects of general activity or reinforcement itself, responding on the active lever was compared to responding on a control lever that had no programmed consequence. Different groups of lesioned and sham-operated subjects were trained using different delays; the delay was consistent for every subject. Delays of 0, 10, and 20 s were used.
Alternative free-operant schedules for this purpose exist, such as one in which the first response sets up reinforcement, and a subsequent response made before the reinforcer is delivered postpones reinforcement, in order to keep the delay between the last response and the reinforcer constant (known as a tandem fixed-ratio-1 differential-reinforcement-of-other-behaviour or FR-1-DRO schedule). However, the tandem FR-1-DRO schedule constrains the maximum rate of reinforcement, which also decreases as the delay being used increases. Furthermore, it does not hold constant the probability of reinforcement given a response, and it introduces two opposing contingencies: some responses make reinforcement more likely, while others (those during the delay) make it less likely [1]. Therefore, we did not use this schedule. Similarly, the acquisition of instrumental responding with delayed reinforcement may be assessed with discrete-trial tasks. For example, two levers could be presented in trials occurring at fixed intervals, the levers could be retracted when a response had been made, and responding on one lever could be reinforced after a delay, taking care to avoid a differential Pavlovian contingency between presentation or retraction of one lever and reinforcement, since responding might then be due to Pavlovian conditioning autoshaping; [86,87] rather than the instrumental contingency. However, this discrete-trial schedule would also divide up the session explicitly into response-food delays and food-response (intertrial) times, a process that might aid learning and/or be affected by the lesion. Furthermore, there is prior evidence that AcbC lesions impair rats' ability to choose a delayed reward over an immediate reward in the discrete-trial situation [22]. Therefore, to address the more general question of whether the AcbC is required to acquire instrumental responding with delayed reinforcement, we chose instead to use a free-operant schedule; this seemed to us to mimic best the real-life problem of relating actions to their outcomes with no explicit demarcation of when a response had been made or when a response was permissible.
Immediately after subjects were placed in the operant chamber, the sessions began. The houselight was illuminated, and remained on for each 30-min session. Two levers were extended into the chamber. All lever responses were first 'debounced' to 10 ms (i.e. if a response occurred within 10 ms of a previous valid response it was attributed to mechanical bounce and ignored). Other than this, all lever presses and nosepokes into the food alcove were recorded. Responding on the left (active) lever caused a single pellet to be delivered following a delay, under a fixed-ratio-1 (FR-1) schedule (Figure 1). To attribute acquisition of a lever-press response to the instrumental contingency, it is also necessary to control for the effects of reinforcer delivery itself [1]; therefore, responding on the active lever was compared to responding on the right (inactive) lever, which had no programmed consequence. To minimize any potential contribution of conditioned reinforcement to the task, no explicit signals were associated with pellet delivery other than the noise of the pellet dispenser apparatus.
Locomotor activity in a novel environment
Since general activity levels might influence instrumental responding, locomotor activity was also measured, using wire mesh cages, 25 (W) × 40 (D) × 18 (H) cm, equipped with two horizontal photocell beams situated 1 cm from the floor that enabled movements along the long axis of the cage to be registered. Subjects were placed in these cages, which were initially unfamiliar to them, and their activity was recorded for 2 h. All animals were tested in the food-deprived state. Locomotor hyperactivity and reduced weight gain have previously been part of the phenotype of AcbC-lesioned rats, though without alterations in the consumption of the reinforcer used in the present experiments [22,29,36].
Matching of response distribution to reinforcer magnitude distribution on a concurrent schedule
Subjects were trained in 30-min sessions to respond on both levers separately under interval schedules of reinforcement. The two levers were designated A and B; these were counterbalanced left/right (thus, for half the subjects in each group, lever A was the lever reinforced previously in the delay task; for the other half, it was the lever previously unreinforced). As before, responses were debounced to 10 ms. Training and testing proceeded according to Table 1. Random-interval-x-second (RI-x) schedules were implemented by having a clock tick once a second; each tick set up reinforcement with a probability p = 1/x. Once reinforcement had been set up for a schedule, the next response caused reinforcement to be delivered. Multiple pellets were delivered 0.5 s apart. For concurrent RI schedules, a 2 s changeover delay (COD) was imposed to discourage frequent switching between schedules [32-34,88]. The COD was implemented as follows: if a subject pressed lever B, it could only be reinforced if more than 2 s had elapsed since it last pressed lever A (and vice versa). The RI schedules could still set up reinforcement during the COD, but the subject could not earn that reinforcement until the COD had elapsed.
Histology
Rats were deeply anaesthetized with pentobarbitone sodium (200 mg/ml, minimum of 1.5 ml i.p.) and perfused transcardially with 0.01 M phosphate-buffered saline (PBS) followed by 4% paraformaldehyde in PBS. Their brains were removed and postfixed in paraformaldehyde before being dehydrated in 20% sucrose for cryoprotection. The brains were sectioned coronally at 60 μm thickness on a freezing microtome and every third section mounted on chromium potassium sulphate/gelatin-coated glass microscope slides and allowed to dry. Sections were passed through a series of ethanol solutions of descending concentration (3 minutes in each of 100%, 95%, and 70% v/v ethanol in water) and stained for ~5 min with cresyl violet. The stain comprises 0.05% w/v aqueous cresyl violet (Raymond A. Lamb Ltd, Eastbourne, UK), 2 mM acetic acid, and 5 mM formic acid in water. Following staining, sections were rinsed in water and 70% ethanol before being differentiated in 95% ethanol. Finally, they were dehydrated and delipidated in 100% ethanol and Histoclear (National Diagnostics, UK) before being cover-slipped using DePeX mounting medium (BDH, UK) and allowed to dry. The sections were used to verify cannula and lesion placement and assess the extent of lesion-induced neuronal loss. Lesions were detectable as the absence of visible neurons (cell bodies of the order of 100 μm in diameter with a characteristic shape and appearance), often associated with a degree of tissue collapse (sometimes with consequent ventricular expansion when the lesion was adjacent to a ventricle) and gliosis (visible as the presence of smaller, densely-staining cells).
Data analysis
Data collected by the chamber control programs were imported into a relational database (Microsoft Access 97) for case selection and analysed with SPSS 11. Figures were created with SigmaPlot 2001/v7 and Adobe Illustrator 8. All graphs show group means and error bars are ± 1 standard error of the mean (SEM) unless otherwise stated. Count data (lever presses and locomotor activity counts), for which variance increases with the mean, were subjected to a square-root transformation prior to any analysis [35]. Homogeneity of variance was verified using Levene's test [89]. General linear models are described as dependent variable = A2 × Bcov × (C5 × Dcov × S) where A is a between-subjects factor with two levels, B is a between-subjects covariate, C is a within-subjects factor with five levels, and D is a within-subjects covariate; S denotes subjects in designs involving within-subjects factors [90]. For repeated measures analyses, Mauchly's test of sphericity of the covariance matrix was applied [91] and the degrees of freedom corrected to more conservative values using the Huynh-Feldt epsilon for any terms involving factors in which the sphericity assumption was violated [92].
List of abbreviations used
, Huynh-Feldt epsilon
Acb, nucleus accumbens
AcbC, nucleus accumbens core
AcbSh, nucleus accumbens shell
AMPA, α-amino-3-hydroxy-5-methyl-4-isoxazolpropionate
ANCOVA, analysis of covariance
ANOVA, analysis of variance
COD, changeover delay
DA, dopamine
DRO, differential reinforcement of other behaviour
FR, fixed ratio
i.p., intraperitoneal
h, hour
min, minute
NMDA, N-methyl-D-aspartate
P(A), probability of event A occurring
P(A | B), probability of A occurring, given that B has occurred
PBS, phosphate-buffered saline
PKA, protein kinase A (cyclic-adenosine-monophosphate-dependent protein kinase)
RI, random interval
SEM, standard error of the mean
VR, variable ratio
v/v, volume per unit volume
w/v, weight per unit volume
Authors' contributions
RNC conceived and designed the studies, supervised THCC, wrote the software, and drafted the manuscript. THCC participated in the design of the studies and tested the animals. The work contributed to THCC's MPhil thesis. Both authors performed surgery, processed histological material, analysed the results, and read and approved the final manuscript.
Acknowledgements
The authors thank Anthony Dickinson, Trevor Robbins, John Parkinson and Barry Everitt for helpful discussions, and Caroline Parkinson and Mercedes Arroyo for skilled technical assistance. Supported by a Wellcome Trust programme grant (to Trevor W. Robbins, Barry J. Everitt, Angela C. Roberts, and Barbara J. Sahakian); conducted within the UK Medical Research Council (MRC) Cambridge Centre for Behavioural and Clinical Neuroscience. Competing interests: none declared.
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| 15691387 | PMC549214 | CC BY | 2021-01-04 16:39:09 | no | BMC Neurosci. 2005 Feb 3; 6:9 | utf-8 | BMC Neurosci | 2,005 | 10.1186/1471-2202-6-9 | oa_comm |
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BMC Dev BiolBMC Developmental Biology1471-213XBioMed Central London 1471-213X-5-21569400110.1186/1471-213X-5-2Research ArticlePathophysiologic consequences following inhibition of a CFTR-dependent developmental cascade in the lung Cohen J Craig [email protected] Janet E [email protected] Louisiana State University Health Sciences Center, Departments of Medicine, Biochemistry, and Genetics, School of Medicine, New Orleans, LA 70112, USA2 Ochsner Children's Research Institute, Ochsner Clinic Foundation, New Orleans, LA 70121, USA2005 4 2 2005 5 2 2 13 8 2004 4 2 2005 Copyright © 2005 Cohen and Larson; licensee BioMed Central Ltd.2005Cohen and Larson; 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
Examination of late gestation developmental genes in vivo may be limited by early embryonic lethality and compensatory mechanisms. This problem is particularly apparent in evaluating the developmental role of the cystic fibrosis transmembrane conductance regulator (CFTR) gene in the cystic fibrosis (CF) phenotype. A previously described transient in utero knockout (TIUKO) technology was used to address the developmental role of CFTR in the rat lung.
Results
Rat fetuses transiently treated with antisense cftr in utero developed pathology that replicated aspects of the human CF phenotype. The TIUKO CF rat developed lung fibrosis, chronic inflammation, reactive airway disease, and the CF Antigen (MRP8/14), a marker for CF in human patients, was expressed.
Conclusions
The transient in utero antisense technology can be used to evaluate genes that exhibit either early lethality or compensating gene phenotypes. In the lung CFTR is part of a developmental cascade for normal secretory cell differentiation. Absence of CFTR results in a constitutive inflammatory process that is involved in some aspects of CF pathophysiology.
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Background
The in utero gene transfer technology devised in this laboratory [1] was originally developed to circumvent the inflammatory response seen after birth with adenoviral-mediated gene transfer. During the course of these experiments it was discovered that the in utero transfer of the gene for cystic fibrosis transmembrane conductance regulator (cftr) to normal rat fetuses resulted in phenotypic changes in the neonatal lungs [2]. At the time of gene transfer the targeted epithelial cells were undifferentiated multipotential cells [3]. Administration of cftr to this epithelium using an adenovirus vector system resulted in persistent phenotypic changes in cells although the expression of the transgene was transient. These data provided the first insight that CFTR expression during the fetal period could permanently alter the differentiation of lung epithelial cells. The permanent functional changes in the in utero cftr-treated rats included an enhanced resistance to pulmonary bacterial infection three months after birth [2].
At the same time, other laboratories were examining the temporal and tissue-specific expression of CFTR. CFTR lung expression is greatest during the fetal period where it is localized to airway epithelial undifferentiated multipotential cells [4-9]. As these multipotential cells differentiate, the expression of CFTR dissipates and the adult lung expresses only a fraction of that expressed during the fetal period. Thus, CFTR resembles other developmentally important genes in its expression at specific times during organogenesis [10-12].
In addition to its role as a chloride channel in the mature lung, CFTR's expression in undifferentiated epithelial cells suggested another role (or roles) during development. Moreover, this raised the question of how much of CF disease pathology could be attributed specifically to the lack of CFTR expression during differentiation and how much could be attributed to lack of a chloride channel in the mature lung.
These questions prompted further experiments by this laboratory in the CF knockout mouse. Reversal of the lethal phenotype of the CF (cftr -/-) mouse following transient in utero expression of cftr [13] confirmed the role of this gene in gut development. Because of the rapid cell turnover, the human CFTR transgene was detected in the fetal gut for up to 72 hours post-treatment but not after birth. The in utero gene therapy did not permanently replace the CFTR-encoded cAMP-dependent chloride channel but rescued the mice from the disease phenotype and reversed biochemical markers specific to the knockout phenotype [14]. These data established that extra uterine expression of CFTR was not required for the correction of the intestinal obstruction in cftr -/- mice.
Additional insight into the role of CFTR in secretory cell development was obtained when we began to examine the effects of CFTR following in utero over expression in homozygous normal mouse pups and discovered that over expression resulted in a lethal phenotype due to epithelial cell hyperplasia [11]. Characterization of the secretory epithelium following CFTR over expression during fetal development has now demonstrated accelerated lung epithelial cell differentiation in the rat, mouse and nonhuman primate [2,14-16].
Experiments examining the developmental role of CFTR relied on either a knockout mouse model that poorly mimicked human lung disease or over expression studies in normal animals. At this point it seemed that only two research approaches were available to determine which aspects of CF pathology were due to the lack of CFTR expression during development. Reversal of human CF by transient in utero gene therapy is currently under consideration by our laboratory, but is many years from practical therapeutic consideration. Alternately, one could attempt to transiently inhibit in animals models CFTR production in utero to induce aspects of the adult CF disease phenotype in the presence of normal adult levels of CFTR.
The in utero gene transfer method developed by this laboratory uses small quantities of recombinant adenovirus at times during gestation when the lung and intestine epithelium is largely composed of undifferentiated multipotential cells [1]. Recombinant adenoviruses at 108 pfu/ml of amniotic fluid have been transferred to mice, rats, and rhesus monkeys [2,14-16]. The high transfer efficiency and absent immune response suggested that it was possible to use recombinant adenoviruses to transfer antisense genes to the lung and intestinal epithelium and transiently inhibit gene expression. Because undifferentiated multipotential cells were targeted, transfer of the antisense analog of a developmentally active gene would have the potential to significantly affect the developmental cascades in the lung and intestines. Recently, we developed a transient in utero knockout (TIUKO) technology to inhibit expression of specific genes in the fetal lung and intestine [17]. In this paper the TIUKO technology is applied to the question of the developmental role of CFTR in the cystic fibrosis phenotype.
Results
Inhibition of CFTR expression using TIUKO
An adenovirus was constructed from a ATCC plasmid containing exons 1–6 of cftr included in the [18] cloned into a recombinant adenovirus in the 3'-5', antisense direction (AdCMVAScftr). This virus was used for in utero gene transfer into fetal rats at 16 days gestation.
Sprague-Dawley rats were used in these experiments. There were 75 rats from 7 litters in the control group and 114 rats from 11 litters in the TIUKO group. The rats were treated with AdCMVAScftr at 16 days gestation and were evaluated daily from 18–22 days gestation and up to 1 year following birth.
The choice of controls for these experiments was a primary consideration. We showed in several publications that over expression of CFTR in normal mice and rats results in altered lung morphology. Thus, neither cftr constructs nor any sense portion of this gene could be used as a control. An adenovirus with exons 1–6 in the sense direction would not express a truncated product and thus its expression could not be detected as a control. The adenovirus constructs with beta-galactosidase (AdCMVlacZ) and green fluorescent protein (AdCMVgfp) were used in previous experiments in several hundred individual fetuses with no effect on the viability, structure, or function of the lung [1,15,16]. Thus, these two adenoviruses with reporter genes were used as negative controls for normal organogenesis.
The effects of AdCMVAScftr on CFTR expression in rat tissues was compared to control (AdCMVlacZ-treated) lungs at 24 and 72 hours post antisense therapy by fluorescent immunohistochemistry. As shown in Fig. 1A, deconvolution microscopic analysis readily detected CFTR in the normal embryonic lungs. The specificity of the immunohistochemistry was shown by the blocking of all fluorescence using specific blocking peptides (Fig. 1C). Comparison of control (Fig. 1B) and antisense CFTR treated (Fig. 1D) revealed decreased expression of CFTR in antisense treated lungs.
Figure 1 Inhibition of CFTR expression in rats treated in utero with antisense c ftr . Sprague-Dawley rats at 16 days of age were treated with either AdCMVlacZ (Panel A, B, C) or AdCMVAScftr (Panel D). At 19 days gestation lungs were harvested and CFTR expressing cells visualized by fluorescent microscopy with an Alexa 568 (RED) secondary and a goat anti-CFTR primary antibody. Nuclei were stained with DAPI (BLUE). Original Magnification Panels A & C 100×; Panels B & D 400×.
Reduction of the antisense transgene expression is difficult to measure, because at a maximum only 108 cells would be affected if one achieved 100% infection efficiency. Transfection efficiency via the amniotic fluid is less than 10% so only between 106–7 cells are affected in the tissue. Thus, real time PCR, northern blots, and western blots lack the sensitivity to detect these changes as shown in our previous publication on the TIUKO c-myc mouse [17]. Thus, the only method available to quantitate reduction in target gene expression in the TIUKO method is image analysis of random sections from multiple, independently treated lungs. As shown in Fig. 2, image analyses of the relative levels of CFTR expressed per cell in the AdCMVAScftr-treated tissues were performed.
Figure 2 Quantitation of CFTR expression following infection with AdCMVAScftr. Fetuses were treated at 16 days gestation with either AdCMVlacZ (control) or AdCMVAScftr and lungs harvest at 24 and 72 hours post-gene transfer. Lungs from 5 animals were cryo-sectioned and CFTR visualized by immunohistochemistry. Image analysis on the deconvoluting microscope was performed and the results standardized for the number of cells by nuclear staining with DAPI
Statistically significant reduction in CFTR levels was observed at 24 (p = 0.014) and 72 hours (p = 0.005) post-TIUKO cftr therapy. Thus, as in our previously published TIUKO c-myc model, the TIUKO cftr therapy decreases expression of the target gene at a critical time in lung development.
Airway and parenchymal changes in the CF TIUKO rat
Focal areas of fibrosis are seen in the lungs of congenic CF mice as well as humans at autopsy [19]. Rats were followed sequentially for lung histological examination to determine if they would develop any chronic lung changes that mimicked CF lung pathology. Both the airways and parenchyma were examined.
Comparison of the histology of lungs from control and AdCMVAScftr-treated animals during the neonatal period revealed little or no gross structural pathology (data not shown). Development of pulmonary histopathology became apparent in adult rats by 100 days of age following the in utero antisense cftr treatment.
The most notable histologic change was in the airways, which appeared thickened and fibrosis. Morphometric analysis was used to quantitate airway wall dimensions on lung sections from 100 day old rats following staining with hematoxylin and eosin [20,21]. The wall area was determined by digitizing the area excluding airway epithelium and cartilage. The corresponding segment of sub epithelial basement membrane was digitized and used as a reference length to normalize airway wall area[21]. As shown in Table 1, there was a significant increase in airway wall thickness in the in utero antisense cftr treated animals as compared to their aged-matched controls. The average internal airway circumference was not statistically different between the treated and control group. These measurements insured that similar sized airways were compared between the two groups.
Table 1 Morphometric analysis of fibrosis and airway thickness in control and AdCMVAScftr treated lungs at 100 days of age
Sample Average Internal Circumference (I) N = 20/group Average area (A) Average A/I Average airway Protein (V) N = 24/group average collagen (C) average C/V
AdCMVgfp-treated 101.8 452.1 4.49 6595 ± 1829 2921 ± 810 0.5251
AdCMVAScftr-treated 114.7 833.9 7.27* 6965 ± 911 11665 ± 1829 1.6648**
* p = .023 ** p < 0.001
Masson's Trichrome was used to differentiate collagen from smooth muscle and elastin surrounding the airways to better visualize and quantitate the extent of airway fibrosis. Collagen following this stain was visualized as a dense bluish-tinged material as shown surrounding the membranous airways in Figure 3. There was increased collagen in both the small (Fig. 3C) and large airways (Fig. 3D) of the AdCMVAScftr-treated rats when compared to control airways of the same size (Fig. 3A &3B). Morphometric quantitation of airway collagen was performed using image analysis [20]. Airway collagen was increased significantly (p < 0.001) in the antisense treated animals as determined by an increased collagen/protein ratio (Table 1). Total lung collagen was also quantitated using image analysis [22]. As shown in Figure 4, statistically significant (p = 0.0029) increase in total collagen was confirmed.
Figure 3 Airway fibrosis following in utero AdCMVAScftr therapy. Lung sections were stained with Masson's Trichrome to visualize collagen (blue) in 100 day old rats. There was increased collagen in both the small (Panel C) and large airways (Panel D) of the AdCMVAScftr-treated rats when compared to control airways of the same size (Panels A and B). The morphometric quantitation of this fibrosis (Table 1) confirmed that these changes were consistent throughout the lung fields examined. Original magnifications 100×.
Figure 4 Collagen in rat lungs following in utero antisense cftr gene transfer. Rat fetuses at 16 days gestation were treated with either AdCMVlacZ (control; black) or AdCMVAScftr (ASCFTR; red). At 120 days of age 5 animals in each group were harvested and 5 random sections were analyzed for total collagen following Mason trichome staining using image analysis as described in Methods
Chronic inflammation is another feature of CF lung pathology in humans [23]. At 100 days of age, prominent inflammatory cell infiltrate was present in the lung parenchyma of the AdCMVAScftr treated rats (Fig. 5B &5D) that was not present in the AdCMVgfp-treated control animals (Fig. 5A &5C). We have previously demonstrated that in utero adenoviral-mediated transgene expression decreases rapidly in the 30 days post-transfer [2]. Thus, the adult rat lung pathology progressed in the absence of significant antisense cftr expression. In addition, although these animals were not kept in a germ free environment, repeated bacterial challenge was not required for the induction of either lung inflammation or fibrosis. All animals greater than 60 days of age thus far examined (n = 12) have had significant pulmonary inflammatory infiltrate.
Figure 5 Chronic inflammation following in utero AdCMVAScftr therapy. Lung fields from rats at 100 days were examined for inflammation following hematoxylin and eosin staining (Panels A & B). Prominent areas of inflammatory cell infiltrate surrounding membranous airways were demonstrated in AdCMVAScftr treated rats (Panel B) and were not found in AdCMVgfp control animals (Panel A). Staining of the areas of inflammatory cell infiltrate with Masson's Trichrome demonstrated interstitial fibrosis associated with the inflammation (Panels C and D). Original magnification Panels A, B and C-100×; Panel D-400×.
Expression of CF-specific proteins following TIUKO cftr
MRP8 and 14 are proteins previously used as clinical markers of cystic fibrosis. These proteins are calcium binding proteins that form a heterodimer, are produced in neutrophils, and are associated with wound healing. Importantly, MRP8 was originally called "CF antigen" because it was found to be elevated in the serum of CF patients. The protein was subsequently found to be a heterodimer of MRP8 and MRP14. It was used to identify CF affected individuals as well as heterozygous carriers prior to the discovery of the cftr gene. Because of their significance the expression levels of these proteins were confirmed by western blot analysis in both mice and rats following AdCMVAScftr gene therapy.
To determine if MRP8/14 expression was directly associated with the inhibition of CFTR expression, and not induced by post-natal events, western blot analysis of expression was followed sequentially over the first 96 hours post antisense cftr therapy in utero . Minimally detected levels of MRP 8 were expressed in control fetuses (Fig. 6; AdCMVgfp-treated animals). In the AdCMVAScftr -treated rats, a gradual increase in MRP 8 expression was documented over 96 hours post-therapy. Similar results were obtained with MRP 14 (data not shown). Thus, increased CF Antigen expression was correlated with the decreased expression of CFTR following antisense cftr gene therapy.
Figure 6 Western analysis of MRP 8 (CF Antigen) expressions in rat lungs following in utero antisense cftr therapy. Western blots were performed on protein (20 μg) from lungs using MRP8 or actin specific antibodies. Protein was extracted from either AdCMVgfp (control) or fetuses (n = 6) treated at 16 days gestation with AdCMVAScftr (n = 6) and fetal rat lungs harvested at 18–20 days gestation
Altered airway reactivity in antisense cftr-treated rats
In cystic fibrosis patients, alteration in airway reactivity was previously documented [24,25]. To evaluate the effect of in utero antisense cftr on the airway development rats treated at 16 days gestation with AdCMVAScftr or AdCMVlacZ were maintained in filtered cages and analyzed for airway reactivity to acetylcholine at 6–13 months of age. As shown in Fig. 7, control animals challenged with nebulized acetylcholine showed only small changes in airway resistance (Raw) at 3.125 and 12.5 mg/ml concentrations. In contrast, age-matched, antisense cftr treated animals were highly reactive to the low concentrations of acetylcholine. In addition, maximal stimulation at 50 mg/ml in the TIUKO CF rats was over twice that observed in control animals. The differences between control and TIUKO CF rats was highly significant (p < 0.0001)
Figure 7 Airway reactivity in AdCMVAScftr-treated rats. Fetuses at 16 days gestation were treated with either AdCMVlacZ (black; n = 5) or AdCMVAScftr (red; n = 5). Animals were maintained in filtered cages to minimize exposure to environmental pathogens. At 6–12 months of age, changes in airway resistance (Raw) were determined in response to nebulized saline and acetylmethylcholine at concentrations of 3.125, 12.5, and 50 mg/ml.
Discussion
The development of the TIUKO procedure permits the examination of mid-gestation developmentally required genes in the absence of both early lethality and compensatory mechanisms that ameliorate the final disease phenotype. Previously, transient expression of the antisense to a known growth factor c-myc [17] demonstrated its requirement for normal cell expansion in both the lungs and intestines. The key element in the TIUKO method is the targeting of multi-potential, undifferentiated cells. Because the lung is developing rapidly at the time, organogenesis can be dramatically affected by inhibition of genes involved in a developmental cascade. Thus, inhibition of c-myc gave rise to severely hypoplastic lungs and stunted villi formation in the intestines, even though fewer than 107 cells were affected by the antisense transgene. This method can be used to dissect the developmental pathway of different epithelial cell types in these organs.
One caveat with the TIUKO method, however, is the difficulty in measuring the decrease in expression of the target gene. Because the population of affected multipotential, undifferentiated cells represent a small proportion of the total, rapidly expanding lung population, it is impossible to detect the changes in gene expression via real time PCR, northern blots, or western blots. However, as shown previously two independent methods, antisense and ubiquitin targeted, down regulation of C-MYC [17] yielded identical phenotypes and immunofluorescent quantitated decrease of the target transgene,. In this paper, all conclusions are based only immunofluorescent quantitation of target gene down regulation following transient antisense CFTR in utero .
Cystic fibrosis is a pleiotropic disease. The seemingly unrelated phenotypic effects of CFTR are largely unexplained by the hypothesis that CF pathology results from the lack of continuous chloride channel expression. Beginning with the reversal of the CF knockout mouse phenotype with transient in utero cftr gene therapy using a recombinant adenovirus [9], this laboratory proposed that CF was also a disease of secretory cell differentiation and that the protein's many functions, including that of a chloride channel, were required for multipotential cell differentiation. Results supporting this hypothesis were obtained in mice, rats and non-human primates. Thus, some of the altered functions observed in CF tissues are due to incomplete development and malfunctioning secretory cells.
As shown recently [5], CFTR is highly expressed in the lung during the pseudoglandular phase of development and begins to decline during the cannalicular phase of development where it remains low at birth. This early phase of lung development correlates with that used for in utero gene therapy and reversal of the knockout mouse phenotype [5,13]. These data also suggested that the transient, selective, inhibition of CFTR expression should recapitulate the human CF phenotype without species-specific compensatory mechanisms interference. The development of the TIUKO method permitted such experiments.
The selective, transient CFTR expression inhibition in a small number (<107) of undifferentiated multipotential cells was performed in using a recombinant adenovirus with a cftr fragment cloned in the 3'-5', antisense, direction. As shown in immunohistochemical examinations of lung tissues (Figure 1, 2), specific inhibition of CFTR expression occurred to the extent of that obtained previously with antisense c-myc [17].
In the lungs of TIUKO CF rats, significant changes in lung structure were not readily apparent at birth. As the animals aged, however, airway thickening and fibrosis were found morphologically. Changes in the airways were confirmed with morphometric analysis (Fig. 3, 4; Table 1) and pulmonary function tests (Fig 7). Thus, the TIUKO CF rats reproduced many aspects seen in lung disease of human.
Elevated serum levels of MRP8 were used to identify CF affected individuals and heterozygous carriers prior to the cloning of the cftr gene. The gene for the cystic fibrosis antigen (MRP8) was cloned in 1987 by Dorin et al. [20]. Because intermediate levels of the protein were expressed in clinically unaffected heterozygotes it was hypothesized at that time that its expression was closely related to the basic defect of cystic fibrosis. Work on this protein lost momentum when the cftr gene was cloned and confirmed to be a chloride channel and also when MRP 8 expression was not found in the preliminary survey of adult and fetal CF lung [26]. Because MRP8/14 is highly expressed in polymorphonuclear leukocytes, the high levels of MRP8/14 in CF patients were explained as a result of inflammation rather than a potential source of it. In addition to elevated levels of MRP8/14 protein in human CF serum, mRNA expression has been found in tracheal gland cells obtained from normal and cystic fibrosis patients. A significant increase in these mRNAs was shown in the cells of CF origin [27]. The increased expression of this protein in the fetal lung following antisense cftr gene transfer (Fig. 6) is consistent with human CF and the knockout mouse.
Reversal of the CF phenotype by in utero gene therapy and the developmental changes following CFTR over expression studies in mice, rats, and non-human primates are consistent with a developmental paradigm for this disease. As summarized in Table 2, the TIUKO CF rats demonstrate that faulty differentiation of secretory cell may be associated with many of the features of the CF lung disease phenotype [28].
Table 2 Comparison of cystic fibrosis disease phenotypes between human and animal models
HUMAN DISEASE PHENOTYPE CFTR KNOCKOUT MOUSE MODEL PHENOTYPE TIUKO CF RAT PHENOTYPE
LUNG FIBROSIS FIBROSIS AND INFLAMMATION PRESENT BY 100 DAYS OF AGE
MRP8/14 ELEVATED DETECTED IN G551D MOUSE INCREASED PRENATALLY
AIRWAY REACTIVITY NOT DETECTED INCREASED WITH AGE
CHRONIC INFLAMMATION DETECTED IN CONGENIC MICE PRESENT BY 100 DAYS OF AGE
Several recent papers illustrate the potential role of the developmental requirement of CFTR in CF pathophysiology and lung growth Groman and co-workers [29] found a subset of patients with the CF phenotype and no mutation in the cftr coding sequence. This finding is consistent with the role in CF of other genes in a common secretory cell pathway that includes cftr as only one of many components. In addition, transplant of human fetal CF lung tissues into SCID mice resulted in lung inflammation [30]. These data are consistent with our prenatal elevation of the MRP8/14 (Figure 6) and suggest that developmental interference with secretory cell differentiation results in a constitutive inflammatory response.
Until recently, no distinctive changes in lung structure and function were found in the CFTR knockout mouse. However, recent evaluation by our laboratory of lung function in cftr+/+, cftr+/-, and cftr-/- mice, showed distinct phenotypes for each genotype [31]. Thus, normal lung development in mouse is affected in a dose response manner by CFTR. The TIUKO rat is distinct genetically from a heterozygous animal. In heterozygous animals, one maintains a single functional copy of the transgene in all multipotential, undifferentiated cells of the developing fetal lung. So in the mature, heterozygous lung altered pulmonary function but normal structure is observed. In contrast, in the TIUKO CF fetal lung, multipotential, undifferentiated cells infected with the antisense gene have a total deficiency of CFTR (Fig 1). The developing TIUKO CF rat lung is a mosaic of normal (cftr+/+) and CFTR deficient (essentially cftr-/-). Thus, as shown in this paper, the TUIKO CF rat exhibited a CF-related phenotype while a CFTR heterozygous does not show any CF features.
We propose that CFTR is part of a developmental cascade for secretory cells in the lung, intestines, pancreas and other secretory organs (Fig. 8A). Disruption of this pathway could occur by either a cftr mutation, or as suggested by Groman et al's [29] work, other mutations of genes in this cascade. This would lead to incomplete differentiation of secretory cells and loss of function (Fig. 8B). In addition, the failure of secretory cell differentiation leads to a constitutive expression of cytokines that function in development as agents of differentiation. Once the immune system matures postnatally, however, these same cytokines assume a proinflammatory role, leading to chronic inflammation and fibrosis. The TIUKO CF rats may be used to identify these other genes involved in human lung epithelial cell differentiation and diseases resulting from their dysfunction. Finally, the TIUKO CF rat provides an animal model for the development of pharmacologic agents to disrupt the constitutional inflammatory processes in the CF affected tissues.
Figure 8 Developmental Paradigm for Cystic Fibrosis Lung Fibrosis Based on TIUKO CF Rat and Developmental Studies in Mice, Rats, and Non-human Primates. In Panel A CFTR is shown as one member of a developmental cascade required for normal secretory epithelium development. Included in this pathway are other cytokines, possibly MRP8/14. In normal development in the presence of CFTR feedback mechanisms either completely inhibit or at least decrease the expression of these developmentally active cytokines. In the absence of CFTR, Panel B, the secretory epithelium fails to differentiate properly. Failed development leads to an immature epithelium that does not exhibit the feedback function necessary for inhibition of developmentally required cytokines. Expression of these cytokines in the permanent, developmental immature, CF lung leads to activation of inflammatory cells once the immune system matures post-natal. Constitutive, chronic inflammation would explain the lung fibrosis and inflammatory disease seen in CF patients
Conclusions
Transient inhibition of CFTR expression in the lungs results in many features of cystic fibrosis in the mature animal. Increased fibrosis, chronic inflammation, increased airway reactivity, and elevation of CF antigen were observed. These data are consistent with a CFTR requirement for normal lung development.
Methods
Recombinant adenoviruses
A 920 bp human CFTR cDNA that included exons 1–6 (ATCC 61123; [18]) was gel-purified and subsequently subcloned into the plasmid pShuttle-CMV (Quantum Biotechnologies, Montreal, Canada). Recombinant adenoviruses were generated by homologous recombination in the E. coli strain BJ5183, according to the protocol of He et al [32]. Recombinants were confirmed for overall size by restriction endonuclease digestion and propagated in DH5a. Linear recombinant adenoviral DNA was used to transfect 911 packaging cells by Ca2PO4 precipitation to produce the virus AdCMVAScftr. Recombinant adenoviruses with the lacZ (AdCMVlacZ) and green fluorescent protein (GFP; AdCMVgfp) were provided by Dr. J. Kolls (LSHHSC, New Orleans, LA). All viruses were CsCl or HPLC purified.
In utero gene transfer
Timed pregnant Sprague-Dawley Rats were induced (5%) and sedated (2%) with inhaled Isoflurane. A laparotomy was performed exposing the uterine horns. The individual amniotic sacs of the fetuses were visualized and injected with fine gauge needle containing adenoviral particles in 10% of the amniotic fluid volume. The recombinant adenoviruses in Dulbecco's Minimal Essential Medium delivered final concentrations of 108 pfu/ml to the amniotic fluid.
Histochemistry and morphometry
At the time of sacrifice all animals received a number. This code was used for identification of all histologic and biochemical studies.
All tissues were fixed in methanol-free, 4% buffered paraformaldehyde and either mounted in paraffin or OCT for sectioning. Fluorescent immunohistochemistry was performed with goat polyclonal IgG (Santa Cruz) specific for CFTR carboxy (sc-8911) and amino terminal (sc-8909) sequences. Secondary donkey anti-goat ALEXA (Molecular Probes) antibodies were used. All tissues were visualized on a deconvoluting, Lieca, light microscope. Hematoxylin and eosin stain and Masson's Trichrome stain were performed with kits (Sigma Chemical Co) and tissues examined by standard light microscopy.
Morphometry was performed with the identification numbers and treatment groups unidentified by two blinded investigators. Airway thickness was determined following staining with hematoxylin and eosin in 100 day old rats. The area of the wall between the sub epithelial basement membrane and parenchymal epithelium was digitized excluding airway epithelium and cartilage. The corresponding segment of sub epithelial basement membrane was digitized and used as a reference length to normalize airway wall area [21]. Quantitation was performed using Scion Image [13,14].
Image analysis based morphometry was performed with the identification numbers and treatment groups unidentified. Morphometric analysis was performed by two blinded investigators. Digitalized images were analyzed for airway thickness using Scion Image [13,14] or for collagen using PHOTOSHOP imaging software [22,33]. Deconvoluting microscopy and image analysis was performed on a Lieca inverted microscope with Xenon light source and SLIDEBOOK imaging software.
Western blots
Polyacrylamide gel electrophoresis was performed on 18% Tris-HCl gels (Biorad) and transferred to PVDF membranes (Amersham) [34,35]. Polyclonal antibodies to MRP8, MRP14, and actin (Santa Cruz) were used in the concentrations of 1:1000 (all antibodies). The secondary HRP-labeled anti-goat antibody (Santa Cruz) was incubated at a concentration of 1:8000. Detection was performed using ECL-plus (Amersham).
Pulmonary function tests
Rats at 12–14 months of age were anesthetized with intra-peritoneal pentobarbital (90 mg/kg), and the trachea was dissected free of surrounding tissue and cannulated with a 20-gauge cannula. The rat was then connected to a small animal ventilator (flexiVent, SCIREQ Inc. Montreal, PQ, Canada) and ventilated with a tidal volume (Vt) of 10 ml/kg; inspiratory:expiratory ratio (I:E) of 66.67%, respiratory rate of 150 breaths/minute, and maximum pressure of 30 cmH20. Positive end-expiratory pressure (PEEP) was controlled by submerging the expiratory limb from the ventilator into a water trap. Each animal was paralyzed with pancuronium bromide (0.5 mg/kg) and allowed to equilibrate on the ventilator until spontaneous breathing ceased (5 minutes). Zrs measurements at a PEEP level of 3. Data were statistically evaluated using paired t-test.
Respiratory mechanics
To measure the input impedance of the respiratory system (Zrs), mechanical ventilation was interrupted and the animal was allowed to expire against the set level of PEEP for 1 s. We then applied an 8 second broad-band volume perturbation signal was then applied to the lungs with the flexiVent, after which ventilated was resumed. A PEEP of 3 cmH2O was used. The volume perturbation signal consisted of the superposition of 18 sine waves having frequency spaced roughly evenly over the range 0.25 Hz to 19.625 Hz. Zrs was calculated from the displacement of the ventilator's piston and the pressure in its cylinder as described previously [36,37]. Correction for gas compressibility as well as resistive and accelerative losses in the flexiVent, connecting tubing and the tracheal cannula were performed as described previously [38]using dynamic calibration data obtained by applying volume perturbations through the tubing and tracheal cannula first when it was completely closed and then when it was open to the atmosphere.
We interpreted the measurement of Zrs in terms of the constant phase model [39]
where Raw is a frequency independent Newtonian resistance reflecting that of the conducting airways [40], Iaw is airway gas inertance, G characterizes tissue damping, H characterizes tissue stiffness (elastance), i is the imaginary unit, α links G and H, and f is frequency. We also calculated a quantity known as hysteresivity (η = G/H), which is believed to increase when regional heterogeneities develop in the lung [41].
Acetylmethylcholine challenge
After rats were equilibrated on the respiratory, sequential 30 second challenges with nebulized physiologic saline, 3.125, 12.5 and 50 mg/ml acetylmethylcholine dissolved in physiologic saline were performed. Between each challenge, 18 broad-band volume perturbations were produced by the ventilator at 10 second intervals between each perturbation. Raw was calculated for each perturbation.
Abbreviations
CFTR – Cystic fibrosis transmembrane conductance regulator; CF – cystic fibrosis
Author contributions
Both authors were equally responsible for both the laboratory work and design of experiments
Acknowledgement
This work as supported entirely by the Ochsner Clinic Foundation and a grant from the Dean's Fund at Louisiana State University, School of Medicine. Authors wish to thank Daisy Dunn for her technical assistance.
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| 15694001 | PMC549215 | CC BY | 2021-01-04 16:40:17 | no | BMC Dev Biol. 2005 Feb 4; 5:2 | utf-8 | BMC Dev Biol | 2,005 | 10.1186/1471-213X-5-2 | oa_comm |
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BMC Health Serv ResBMC Health Services Research1472-6963BioMed Central London 1472-6963-5-131569399710.1186/1472-6963-5-13Research ArticleSimplicity within complexity: Seasonality and predictability of hospital admissions in the province of Ontario 1988–2001, a population-based analysis Upshur Ross EG [email protected] Rahim [email protected] Eric [email protected] Lori [email protected] Muhammad [email protected] Department of Family and Community Medicine, University of Toronto, 263 McCaul Street, Toronto, ON M5T 1W7, Canada2 Department of Public Health Sciences, University of Toronto, McMurrich Building, 12 Queen's Park Crescent W., Toronto, ON M5S 1A8, Canada3 Primary Care Research Unit, Sunnybrook and Women's College Health Sciences Centre, 2075 Bayview Ave., #E-349, Toronto, ON M4N 3M5, Canada4 Institute of Clinical Evaluative Sciences, 2075 Bayview Avenue, Toronto, ON M4N 3M5, Canada5 Faculty of Pharmacy, University of Toronto, 19 Russell Street, Toronto, ON M5S 2S2, Canada2005 4 2 2005 5 13 13 12 8 2004 4 2 2005 Copyright © 2005 Upshur et al; licensee BioMed Central Ltd.2005Upshur 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
Seasonality is a common feature of communicable diseases. Less well understood is whether seasonal patterns occur for non-communicable diseases. The overall effect of seasonal fluctuations on hospital admissions has not been systematically evaluated.
Methods
This study employed time series methods on a population based retrospective cohort of for the fifty two most common causes of hospital admissions in the province of Ontario from 1988–2001. Seasonal patterns were assessed by spectral analysis and autoregressive methods. Predictive models were fit with regression techniques.
Results
The results show that 33 of the 52 most common admission diagnoses are moderately or strongly seasonal in occurrence; 96.5% of the predicted values were within the 95% confidence interval, with 37 series having all values within the 95% confidence interval.
Conclusion
The study shows that hospital admissions have systematic patterns that can be understood and predicted with reasonable accuracy. These findings have implications for understanding disease etiology and health care policy and planning.
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Background
Health care is a complex human endeavor constituted by the interaction of multiple professions, organizations, industries, technologies and the public. Health itself is also a complex concept, with multiple determinants including genetic, socio-cultural, economic and environmental influences [1]. At the centre of this complex system is the hospital. Arguably, after a physician visit, the hospital admission represents the key event in the delivery of health care.
Do hospital admissions have consistent patterns? While individual diseases are extensively studied, there is a paucity of systematic approaches to the study of health care events. Epidemiology is not regarded as a science with the predictive accuracy and explanatory power of the physical sciences [2]. Health services research is in its scientific infancy and is directed towards policy and practice, however, recent trends in theoretical epidemiology have focused on more powerful computational approaches [3].
Using time series analysis, our research program investigates seasonality in the occurrence of health care events. Seasonality is an important aspect of disease manifestation as well as a clue to the etiology of disease. Our initial studies explored seasonality in hospital admissions in discrete disease categories including asthma [4], falls [5] and aortic aneurysms [6]. Subsequently, we hypothesized and confirmed that the hospital admissions in the system considered in totality also demonstrated consistent seasonal effects [7].
Consistent seasonal behavior suggests the possibility of predictable behavior. To the best of our knowledge, there are no studies systematically evaluating the seasonality and predictability of multiple hospital admissions using health services data. We therefore assessed the seasonality and predictability of the most common causes of hospital admission in the province of Ontario, Canada.
Methods
We conducted a retrospective, population-based study to assess temporal patterns in hospitalisations for the 52 most common admission discharge diagnoses from April 1, 1988 to December 2001. Approximately 14 million residents of Ontario eligible for universal healthcare coverage during this time were included for analysis. The Canadian Institute for Health Information Discharge Abstract Database was used to obtain information on the most responsible diagnosis. This database records discharges from all Ontario acute care hospitals, documenting a scrambled patient identifier, date of admission and discharge, up to 16 diagnoses as coded by the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM), and up to 10 procedures.
Researchers using these databases have found that diagnoses and surgical procedures are coded with a high degree of accuracy. There is very little missing information in the Ontario databases; other studies have similarly found that less than 1 percent of the basic information on patients is missing in various provincial databases [8-10].
The 52 most common discharges diagnoses over the 10 years were identified by summing all admissions and calculating in rank order the frequencies of admission. Owing to the influence of obstetric related admissions, we limited obstetric codes to the consideration of singleton births. Categories of closely related health conditions (such as myocardial infarction) were combined.
Numerator data consisted of the total number of discharges for each month for each of the most responsible diagnoses. Denominator data was derived from annual census data for each age group for residents of Ontario provided by Statistics Canada. Monthly population estimates were derived through linear interpolation. All transfers from within one acute care hospital to another within this study group were excluded from the analysis. To take into account the population changes over time we analyzed monthly admission rates per 100,000.
Analytic method
This study employed time series methods to assess the presence of statistically significant seasonality, the strength of the seasonal effect and the predictability of the time series. A time series can be decomposed as the sum or product of trend, seasonality, and random components. Trend is the long term movement of the series which is a systematic component that changes over time and generally does not repeat itself within the time range of the available data. If we eliminate the trend then the time series will consist of seasonal and random components.
Assessment of seasonality
Analysis of the data involved the use of the following statistical techniques in identical fashion to each series in order to assess statistical significance of seasonal patterns and the consistency and magnitude of seasonal effect. Spectral analyses were conducted to detect statistically significant seasonality. Spectral analysis detects periodicity in time series, by plotting the periodogram or spectral density of the series against the period or frequency [11]. The data series was de-trended using moving averages prior to conducting spectral analysis. Two tests for the null hypothesis that the series is strictly white noise were conducted. The Fisher Kappa (FK) Test is designed to detect one major sinusoidal component buried in white noise, whereas the Bartlett Kolmogorov Smirnov (BKS) Test accumulates departures from the white noise hypothesis over all frequencies [12]. Finally, R-squared autoregression coefficients (R2Autoreg) were calculated. Autoregression uses the coefficient of determination of the autoregressive regression model fitted to the data, and can be used for quantifying the strength of the seasonality within a set of serially correlated observations as occurs with time series data [13]. The R2Autoreg is interpreted the same way as the coefficient of determination in classic regression: values from 0 to less than 0.4 represent non-existent to weak seasonality, 0.4 to less than 0.7 moderate to strong seasonality, and 0.7 to 1 strong to perfect seasonality. The magnitude of the R2Autoreg shows how well the next value can be predicted when the seasonal component is the only predictor. In other words it shows the contribution of seasonality in the total variation of the data. Thus 1-R2Autoreg would be the variance that remains unexplained [13]. When the autoregression procedure is applied to observed data, it is important to validate the stationarity of the series as the R2Autoreg may be underestimated when the seasonal variation is non-stable. To account for this, data transformations were conducted where appropriate, to stabilize the seasonal variations [13]. All statistical analyses were performed using SAS (v8.2).
Predictive modeling
Of the 160 monthly observations for each series, the first 148 (April 1988 to December 2000) were used for fitting the model and estimating the parameters. We set aside the last 12 observations (January to December 2001) for assessing the performance of the suggested model and used the rest for fitting the model and estimating the parameters. We applied the first order differencing to eliminate the trend [14] and then used a very simple regression model to predict 12 new monthly observations for each series. We compared the observed 12 observations with the corresponding predicted values. Then we checked to see which observed value falls outside the 95 percent confidence interval.
Suppose n monthly observations x1, x2, ..., xn are available and we are interested in predicting the next k unobserved data points xx+1, xx+2,..., xx+k using the n observed data points. Here we will assume that the time series is an additive composition of trend, seasonality, and random components. The multiplicative case can be converted to additive by simply taking the log transformation. The time plot of the series did not indicate large changes in the variations of the amplitude of either seasonal or irregular components of the series whereas the level of the trend increased or decreased. Thus an additive model is appropriate. The first component we should deal with is trend. Visual inspection of the time plots of the 52 series indicate different trend patterns ranging from simple linear to more complex nonlinear patterns. We did not attempt to model the trend component parametrically as estimating the pattern of the trend components globally by a closed mathematical function of time may severely misestimate the true trend beyond the range of fitting period. Instead we decided to use the first order differencing to eliminate the trend component. The first order differencing of a time series xt, t = 1,2, ..., n is the series wt, t = 2,3, ..., n where wt = xt - xt-1 [14]. Visual inspection of the time plots of the differenced series showed elimination of the trend components. For monthly rates of hospitalization data it is reasonable to anticipate seasonal components of order 12 and 6 due to seasonal variation of the weather or administration (e.g. winter, Christmas, and vacation season). This was confirmed in spectral analysis. By modifying the components of the following regression equation we can model the series at different seasonal orders.
In the regression model we included for seasonal factors of period 12 and 6. Thus the regression model takes the following form
where βi's can be estimated through linear regression framework. Having fitted the model, one can substitute t = n + 1, n + 2, ..., n + k to estimate the next k differenced observations with their corresponding confidence intervals. The predicted differenced data points can be converted to raw data points by applying the following simple transformation:
xn+j = wn+j + xn+j-1, j = 1,2, ..., k
Confidence intervals can be transferred in a similar manner. For j > 1we can substitute the predicted values for xn+j-1.
Results
A total of 6,560,210 million admissions were included in the analysis. Figures 1 and 2 provide examples of the heterogeneity of the time series. There is visual evidence of non-linearity and clear seasonality in the time plot graphs.
Figure 1 Time plots (rates per 100,000 population) of highly seasonal hospital admission patterns: Chronic obstructive pulmonary disease and bronchiolitis.
Figure 2 Time plots (rates per 100,000 population) of moderately seasonal and non-linear trend in hospital admission patterns: Coronary atherosclerosis and dehydration.
Table 1 provides the Fisher Kappa and BKS and R2Autoreg test statistics for each diagnosis, rank ordered by R2Autoreg, and the number of predictions that fall outside the 95 percent confidence interval. The R2Autoreg values range from a high of 0.95 (bronchiolitis) to a low of 0.11 (infantile cataract). Fourteen series showed evidence of strong seasonality (R2Autoreg greater than 0.7), nineteen series showed evidence of moderate seasonality (R2Autoreg between 0.4 and 0.69) and eleven showed evidence of weak seasonality (R2Autoreg less than 0.4). Time series with strong seasonal effects by R2Autoreg also showed consistent statistical evidence of seasonality by BKS and Fisher Kappa tests. Those with moderate and weak evidence of seasonality by R2Autoreg showed inconsistent statistical evidence of seasonality by BKS and Fisher Kappa tests.
Table 1 Statistical summary of seasonality and predictability of the 52 admission time series
Health Outcome R2Autoreg Fisher Kappa (p-value)1 BKS (p-value)1 # outside 95% CI2
Acute bronchiolitis 0.95 76.56 (<0.01) 0.77 (<0.01) 0
Non-infectious gastroenteritis 0.91 66.28 (<0.01) 0.65 (<0.01) 0
Pneumonia/influenza 0.88 68.64 (<0.01) 0.68 (<0.01) 0
Osteoarthritis 0.86 49.81(<0.01) 0.37 (<0.01) 0
Appendicitis 0.84 52.99 (<0.01) 0.50 (<0.01) 0
Uterine fibroids 0.83 40.05 (<0.01) 0.27 (<0.01) 0
Congestive heart failure 0.82 44.14 (<0.01) 0.42 (<0.01) 0
Previous C-section 0.82 44.52 (<0.01) 0.39 (<0.01) 0
Prostatic hyperplasia 0.80 36.49 (<0.01) 0.31 (<0.01) 0
Singleton birth 0.76 39.20 (<0.01) 0.37 (<0.01) 0
Croup 0.75 47.84 (<0.01) 0.56 (<0.01) 0
Diverticulosis 0.75 29.57 (<0.01) 0.33 (<0.01) 0
Excessive menstruation 0.72 34.02 (<0.01) 0.26 (<0.01) 0
Chronic obstructive pulmonary disease 0.71 50.14 (<0.01) 0.50 (<0.01) 0
Urinary tract infection 0.69 52.24 (<0.01) 0.48 (<0.01) 3
Coronary atherosclerosis 0.69 31.60 (<0.01) 0.21 (<0.01) 0
Kidney stones 0.67 40.21 (<0.01) 0.35 (<0.01) 0
Breast cancer 0.67 39.47 (<0.01) 0.24 (<0.01) 0
MyocardiaI infarction 0.67 32.48 (<0.01) 0.30 (<0.01) 1
Gall bladder 0.66 34.69 (<0.01) 0.27 (<0.01) 0
Prostate cancer 0.62 33.42 (<0.01) 0.26 (<0.01) 3
Senile cataract and cataract unspecified 0.60 26.09 (<0.01) 0.27 (<0.01) 0
Acute pancreatitis 0.60 25.30 (<0.01) 0.18 (<0.05) 0
Threatened premature labour 0.59 26.74 (<0.01) 0.19 (<0.01) 1
Gall bladder w/acute cholecystitis 0.57 20.08 (<0.01) 0.15 (NS) 0
Convulsions 0.54 22.46 (<0.01) 0.21 (<0.01) 0
Trochanteric fracture 0.53 22.62 (<0.01) 0.14 (NS) 0
Chronic tonsillitis 0.51 20.82 (<0.01) 0.24 (<0.01) 0
Recurrent manic depression (depressed phase) 0.51 25.43 (<0.01) 0.20 (<0.01) 0
Premature rupture of membrane 0.50 32.01 (<0.01) 0.25 (<0.01) 1
Displacement of inter-lumbar disc 0.50 26.38 (<0.01) 0.18 (<0.01) 1
Dehydration 0.50 55.40 (<0.01) 0.58 (<0.01) 2
Syncope and collapse 0.48 22.57 (<0.01) 0.18 (<0.05) 5
Uncomplicated diabetes 0.48 22.54 (<0.01) 0.23 (<0.01) 0
Lung cancer 0.46 19.41 (<0.01) 0.12 (NS) 0
Depressive disorder 0.45 12.28 (<0.01) 0.14 (NS) 1
Fractured femur 0.44 12.72 (<0.01) 0.10 (NS) 3
Unilateral inguinal hernia 0.43 16.52 (<0.01) 0.18 (<0.01) 0
Abdominal pain 0.43 19.15 (<0.01) 0.26 (<0.01) 0
Transient cerebral ischemia 0.41 18.42 (<0.01) 0.12 (NS) 2
Acute but ill defined cardiovascular disease 0.40 14.69 (<0.01) 0.19 (NS) 0
Angina 0.40 11.72 (<0.01) 0.14 (NS) 0
Unspecified intestinal obstruction 0.38 10.80 (<0.01) 0.15 (<0.05) 0
Other acute ischaemic heart disease 0.36 17.08 (<0.01) 0.15 (<0.05) 1
Recurrent manic depression (manic phase) 0.35 13.77 (<0.01) 0.10 (NS) 4
Fetal distress 0.34 20.24 (<0.01) 0.26 (<0.01) 0
Spontaneous abortion unspecified 0.33 10.95 (<0.01) 0.12 (NS) 0
Stroke 0.31 10.32 (<0.01) 0.14 (NS) 0
Chest pain (nonspecific) 0.29 11.34 (<0.01) 0.14 (NS) 4
Gastrointestinal bleed 0.26 7.84 (<0.05) 0.14 (NS) 0
Other IHD 0.17 6.24 (NS) 0.12 (NS) 0
Infantile cataract 0.11 4.85 (NS) 0.28 (<0.01) 0
1 NS = not significant (p > 0.05)
2 95% CI = 95% confidence interval
In total, 96.5 percent of the predictions fell within the 95 percent confidence interval (602/624). In terms of complete series, the performance of the proposed predictive model is very good. Overall 37 (37/52 = 73 percent) had all 12 observed values falling within 95 percent prediction intervals, 10 series had only 1 observed value outside prediction limits and 4 series had 2 observed values outside 95 percent prediction intervals. For the worst case, only 1 series had 4 out of 12 observed values falling outside the 95% prediction intervals. The standard deviations for the confidence intervals of the predicted values are within 2 admissions per 100,000 for 48 of the 52 series (data not shown).
Discussion
Hospital admissions in the province of Ontario show remarkable consistency and predictability of occurrence. A heterogeneous group of health conditions are represented in the sample including surgical and medical conditions, acute and chronic diseases, communicable and non-communicable diseases. The performance of the proposed model for predicting the one-year ahead number of hospital admissions in the province of Ontario is excellent for the 52 most frequent hospital admissions series considered in this study.
Are these results of significance? We believe so. Most health care planning is based on what could be termed the 'invariance principle' that holds that all events are equally likely to happen and therefore hospitals should be staffed and managed accordingly [15]. Our study indicates that demand for hospital services varies, can be predicted with a high degree of accuracy and therefore planning and resource allocation could possibly be reorganized to reflect this knowledge. Furthermore, there are significant seasonal fluctuations to at least one third of the series analyzed, indicating that planning could be tailored to predictable demands. Understanding such seasonal patterns also promises to shed light on disease causality as not all highly seasonal conditions can be explained by infectious diseases known to have seasonal occurrence.
Our study is limited to the context of Ontario, and is applicable at a population level. Focusing on the most responsible diagnosis may bias the account of seasonal occurrence, although this bias is likely to be non-differential. In this study we focused on total counts for each most responsible diagnosis, which may obscure significant variation in rates between age and gender.
The proposed methods enjoy simplicity and stability. The prediction approach does not require model selection or any other sophisticated statistical methods. Selecting an appropriate seasonal model can be a challenging task in time series analysis. For example, the Box Jenkins approach is popular for selecting linear time series models. In this approach sometimes the analyst has to select a model subjectively from among several potentially appropriate models. Our proposed regression model does not require model selection.
The first order differencing eliminates trend; sin and cosine terms estimate the seasonal factors. The simple regression model works well for highly seasonal to non-seasonal data. Although the seasonal factors of some of the series are changing over time, the simple first order differencing in conjunction with the regression model forecast the future observations within the 95 percent confidence bounds. The confidence intervals around the predicted values are tight, reflecting the accuracy of the projections. This attenuates concerns expressed about the robustness of predictive models in epidemiology [16].
Conclusion
The results of this study demonstrate a simplicity underlying the complexity of hospital admissions. We believe these results are promising and can lead to more rational planning of hospital resources and open up areas of exploration for understanding the determinants of disease causation, specifically in those conditions with moderate to strong seasonality. Further research is necessary to look at whether more complex models have greater predictive power, and whether the analytic approach is robust at different time and space aggregations.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
RU conceived the study and wrote the first draft. RM contributed the statistical analysis. MM, LK and EC made substantial contributions to the design and interpretation of the data. All authors contributed to subsequent drafts, have read and approve of the content of the final submitted manuscript.
All authors have access to all data in the study and they hold final responsibility for the decision to submit for publication.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgments
This study was funded by an operating grant No. MOP-57928 from the Canadian Institutes of Health Research. Dr. Upshur is supported by a New Investigator Award from the Canadian Institutes of Health Research and a Research Scholar Award from the Department of Family and Community Medicine, University of Toronto. We would particularly like to thank Shari Gruman for her expert assistance in the preparation of the manuscript.
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| 15693997 | PMC549216 | CC BY | 2021-01-04 16:31:52 | no | BMC Health Serv Res. 2005 Feb 4; 5:13 | utf-8 | BMC Health Serv Res | 2,005 | 10.1186/1472-6963-5-13 | oa_comm |
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RetrovirologyRetrovirology1742-4690BioMed Central London 1742-4690-2-61569847510.1186/1742-4690-2-6ResearchHIV-1 Tat interacts with LIS1 protein Epie Nicolas [email protected] Tatyana [email protected] Tamar [email protected] Yaroslav [email protected] William S [email protected] Willie [email protected] Orly [email protected] Sergei [email protected] Center for Sickle Cell Disease, Howard University, Washington DC 20059, USA2 Department of Microbiology, Howard University College of Medicine, 520 W Street N.W., Washington, DC 20059, USA3 Department of Biochemistry and Molecular Biology, Howard University College of Medicine, 520 W Street N.W., Washington, DC 20059, USA4 Department of Molecular Genetics, The Weizmann Institute of Science, 76100, Rehoboth, Israel5 Harvard Microchemistry Facility, 16 Divinity Ave., Cambridge MA 02138, USA2005 7 2 2005 2 6 6 9 12 2004 7 2 2005 Copyright © 2005 Epie et al; licensee BioMed Central Ltd.2005Epie 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
HIV-1 Tat activates transcription of HIV-1 viral genes by inducing phosphorylation of the C-terminal domain (CTD) of RNA polymerase II (RNAPII). Tat can also disturb cellular metabolism by inhibiting proliferation of antigen-specific T lymphocytes and by inducing cellular apoptosis. Tat-induced apoptosis of T-cells is attributed, in part, to the distortion of microtubules polymerization. LIS1 is a microtubule-associated protein that facilitates microtubule polymerization.
Results
We identified here LIS1 as a Tat-interacting protein during extensive biochemical fractionation of T-cell extracts. We found several proteins to co-purify with a Tat-associated RNAPII CTD kinase activity including LIS1, CDK7, cyclin H, and MAT1. Tat interacted with LIS1 but not with CDK7, cyclin H or MAT1 in vitro. LIS1 also co-immunoprecipitated with Tat expressed in HeLa cells. Further, LIS1 interacted with Tat in a yeast two-hybrid system.
Conclusion
Our results indicate that Tat interacts with LIS1 in vitro and in vivo and that this interaction might contribute to the effect of Tat on microtubule formation.
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Background
HIV-1 Tat protein is the viral transactivator encoded in the HIV-1 genome of infected cells [1-3]. Tat stimulates formation of full-length transcripts from the HIV-1 promoter by promoting efficient transcript elongation (reviewed in [4]). Tat interacts with the bulge of transactivation response (TAR) RNA, a hairpin-loop structure at the 5'-end of all nascent viral transcripts [5-7]. Tat induces elongation of HIV-1 transcription by recruiting transcriptional co-activators that include Postive Transcription Elongation Factor b (P-TEFb), an RNA polymerase II C-terminal domain kinase [8-10] and histone acetyl transferases [11-13]. Whereas P-TEFb induces HIV-1 transcription from non-integrated HIV-1 template [8-10], histone acetyl transferases allow induction of integrated HIV-1 provirus [11-13]. Tat may also increase initiation of HIV-1 transcription by enhancing phosphorylation of SP1, a transcription factor involved in the basal HIV-1 transcription [14]. In addition to its function in HIV-1 transcription, Tat may contribute to HIV-1 pathogenesis by regulating signal transduction in endothelial cells [15,16]; functioning as a secreted growth factor for Kaposi sarcoma and endothelial cells [17]; and inducing apoptosis in T-cells by binding to microtubules and delaying tubulin depolymerization [18,19]. Tat induces apoptosis through BIM, a pro-apoptotic protein of the Bcl-2 family that antagonizes Bcl-2 anti-apoptotic proteins [18]. The effect of Tat is similar to the effect of Taxol, a drug that stabilizes microtubules and induces apoptosis [18]. Mutations in the glutamine-rich region of Tat protein (residues 60–72) were found to correlate with rapid progression of HIV disease, and with induction of apoptosis and binding to tubulin [20]. We previously showed that microtubules polymerization is facilitated by LIS1 protein [21], a causative factor for Lissencephaly [22], a severe brain disorder resulted from inefficient neuronal migration during early stages of brain development [23]. LIS1, a 45 kDa protein, contains seven repeating units called WD (Trp-Asp) repeats [24] that form antiparallel sheets making up a toroidal propeller structure [25]. WD repeats containing proteins are confined to eukaryotes and participate in protein-proteins interactions [24]. In addition to being a microtubule binding protein, LIS1 is also a subunit of platelet-activating factor acetyl hydrolase (PAF-AH) [26]. LIS1 interacts with dynein motor, NudC and Dynactin, a complex that regulates microtubule dynamics [27,28]. LIS1 in addition associates with Nudel [29], also a component of the dynein motor complex, and this interaction affects dephosphorylation of microtubules by protein phosphatase 2A (PP2A) [30]. Thus, LIS1 may function as a scaffold that help to assemble dynein motor and serve to regulate proper microtubule dynamics.
In the present paper, we fractionated extracts of Jurkat T-cells using HIV-1 Tat as an affinity bait and RNAPII CTD activity of the Tat-associated proteins as a selection criteria. We identified by mass-spectrometry and immunoblotting components of the partially purified protein fraction and found LIS1, CDK7, cyclin H, and MAT1. We analyzed interaction of Tat with the identified individual proteins and found that Tat interacts with LIS1. We confirmed this finding by co-immunoprecipitating Tat and LIS1 from HeLa cells that were expressing Tat. And we also confirmed binding of Tat to LIS1 in a yeast two-hybrid system. Our results indicate that HIV-1 Tat interacts directly with LIS1, and therefore this interaction might contribute to the effect of Tat on microtubules formation in the cells.
Results
LIS1, CDK7, cyclin H, and MAT1 co-purify with Tat-associated RNAPII CTD kinase activity
We reported previously that HIV-1 Tat associates with two distinct protein kinase complexes purified from mitogenically stimulated human primary T-lymphocytes; one complex containing CDK2 and the other one CDK7 [31]. The CDK2-containing protein complex was previously purified and characterized by us [32,33] and we showed that CDK2 regulates HIV-1 transcription [34]. In the present paper, we purify and characterize the CDK7-containing protein elution peak. Whole-cell lysate from Jurkat T cells was prepared and subjected to (NH4)2SO4 fractionation as described previously [32]. In accord with our previous report [32], the 40% (NH4)2SO4 cut contained Tat-associated CTD kinase activity (Fig. 1A). The 40% (NH4)2SO4 cut was subsequently fractionated on DEAE-Sepharose (Fig. 1B). As we previously reported, separation of the ammonium sulphate cut on DEAE-Sepharose resulted in the appearance of Tat-associated CTD hyperphosphorylating activity (Fig. 1B, fractions 34 to 36). Hyperphosphorylated CTD (CTDo) migrated on SDS-PAGE with a high degree of retardation, because of SDS repelling effect. Immunoblotting of the DEAE-Sepharose fractions 34 to 36 showed the presence of CDK7, CDK9 and a PSTAIRE-motif containing kinase, but not TFIIH (See Additional File 1) in accordance with our previous observations [32]. Further resolution of DEAE fractions 34–36 on SP-Sepharose column showed that part of the Tat-associated CTD kinase activity was retained by the column and we previously identified this activity as containing CDK2 [32]. The other part of the Tat-associated CTD kinase activity was not retained by the column and was eluted as a flow-through fraction (Fig. 1C, flow through fraction). This fraction was collected and further resolved on Hi-Trap heparin column (Fig. 1D). Immunoblotting of the Hi-Trap heparin fractions showed that Tat-associated kinase activity co-eluted with CDK7 and also with cyclin H, but not with CDK9 or a PSTAIRE-motif containing kinase (Fig. 2A). Silver staining of the Hi-Trap heparin fractions showed that fractions 22 and 24 contained three protein bands of 35, 40, and 50 kDa which co-eluted with the Tat-associated CTD kinase activity (Figure 2B; fractions 22 and 24, protein bands marked by stars). The Hi-Trap heparin fractions 22 to 24 were further analyzed on Sephacryl S-300 gel filtration column to determine whether CDK7, cyclin H and unknown protein bands comigrate as a single macromolecular mass. Following gel filtration on Sephacryl S-300, the Tat-associated CTD kinase activity was found in the fractions corresponding to the eluted proteins with a mass of 350 kDa (Fig. 3A, fraction 16–18). Immunoblotting analysis showed that CDK7, cyclin H (Fig. 3A) and MAT1 (not shown) co-eluted with the Tat-associated CTD kinase activity. Fractions 16–18 contain 32, 35, 40, 50 and 60 kDa protein bands (Fig. 3B, protein bands marked by stars). To determine composition of unknown protein bands, fractions 22 to 24 were combined, concentrated on Centricon-10 spin column (Amicon), recovered in SDS-loading buffer and resolved on 12% SDS-polyacrylamide gel. Following staining with colloidal Coumassie blue, only two protein bands of 35 and 50 kDa were visualized and subjected to tryptic digestion and nanoelectrospray MS (described in Experimental procedure section). The 35 kDa protein contained peptides vpflPGDSDlDqltr and YPilENPEilr (lower case letters indicate residues observed with less than full confidence) with sequence identity to CDK7 and cyclin H, respectively. The 50 kDa protein contained a peptide VWDYETGDfER with sequence identity to LIS1.
Figure 1 Purification of Tat Associated CTD Kinase. A, Ammonium sulfate fraction of T-cell extract. Whole cell extract of Jurkat T cells was fractionated by ammonium sulfate added sequentially to 10%, 20%, 40% and 80% saturation as described in Experimental procedures. Fractions were analyzed for Tat-associated CTD kinase activity as described in the Experimental procedures section. A portion of each fraction was bound to GST-Tat 72 immobilized on glutathione-agarose beads and then incubated with [γ-32P] ATP and recombinant GST-CTD. Phosphorylated GST-CTD was resolved on SDS/10%-(w/v)-PAGE. B, DEAE-Sepharose column-chromatographic elution profile. Jurkat T-cell extract 40%-(NH4)2SO4 cut was applied to a DEAE-Sepharose column. Fractions were analyzed for Tat-associated CTD kinase activity as described above. C, SP-Sepharose column-chromatographic elution profile. DEAE-fractions 32 to 36 containing hyperphosphorylating CTD kinase activity were combined and applied to SP-Sepharose column. D, heparin-agarose column-chromatographic elution profile. SP-Sepharose flow-through fraction was collected and further fractionated on Hi Trap heparin column. Fractions 22 to 24 (labelled as purified complex) contained Tat-associated CTD hyperphosphorylating activity. Positions of CTDa and CTDo are shown. The figure is an autoradiogram.
Figure 2 Analysis of protein composition of heparin-agarose purified fraction of Tat-associated CTD kinase. A, Heparin-agarose-purified fraction contains CDK7 but not CDK9. Fractions from the heparin-agarose column fractionation shown in Fig. 1 were analyzed by Western blotting with antibodies against CDK7, Cyclin H, PSTAIRE and CDK9. Fractions 22 to 24 which contain Tat-associated CTD hyperphosphorylating activity also contain CDK7 and cyclin H, but not CDK9 or PSTAIRE-like kinase. B, Tat-associated CTD kinase co-purifies with 35, 40 and 50 kDa protein bands. Fractions from the heparin-agarose column fractionation were resolved on 12% SDS PAGE and stained with silver. Protein bands of 35, 40, and 50 kDa that co-purify with the CTD kinase activity are marked by stars.
Figure 3 CDK7 and cyclin H co-migrate as a 350 kDa complex. Hi-Trap heparin fractions 22 to 24 were analyzed on Sephacryl S-300 gel filtration column. A, Tat-associated CTD kinase activity co-purify with CDK7 and cyclin H. Fractions from the Sephacryl S-300 column fractionation were analyzed for Tat-associated CTD kinase activity and also by Western blotting with antibodies against CDK7 and Cyclin H. B, Fractions from Sephacryl S-300 column fractionation were resolved by 12% SDS PAGE and stained with silver.
HIV-1 Tat interacts with WD domains of LIS1 in vitro
Next we analysed which one of the identified proteins in the elution complex might interact with Tat. We expected that CDK7 might bind to Tat as their interaction was previously reported [35]. We incubated fractions 18 to 24 with GST-fused Tat 1–72, then precipitated GST-Tat with glutathione-agarose beads and analysed associated proteins on SDS-PAGE followed by a silver staining. We found that a 50 kDa protein associated with GST-Tat in fractions 20 and 22 (see Additional file 2, lanes 3 and 4). We then asked whether LIS1, a candidate for a 50 kDa Tat-interacting protein, binds to Tat. We translated LIS1 and also translated as controls CDK7, cyclin H and MAT1, in reticulocyte lysate (Fig. 4A) and performed GST pull down assays using GST-fused Tat 1–72 (Fig. 4B). LIS1 bound to Tat (Fig. 4B, lane 4). In contrast, almost no binding was detected for CDK7, cyclin H or MAT1 (Fig. 4B, lanes 1 to 3). These results contrasted with the previous report in which recombinant Tat interacted with CDK7 immunopurified from reticulocyte lysate [35]. The main difference of our study was that we used programmed lysates rather than purified proteins. Immunoaffinity analysis showed that reticulocyte lysate contains substantial amount of endogenous LIS1 which is comparable to the amount of LIS1 in the LIS1-programmed lysate (see Additional file 3, compare lanes 1–3 to lane 4). Thus the excess of LIS1 might compete for the binding to Tat and prevent CDK7 interaction with Tat. To analyze whether WD domains of LIS1 might associate with Tat, we expressed each of WD domain, except domain 2 as well as the N-terminal part of LIS1, which contains a coiled-coiled motif and which is devoid of WD domains. The WD domain 1, 4, 5 or 7 bound to Tat (Fig. 4B, lanes 6 to 11). Also the N-terminal portion of LIS1 bound weakly to Tat (Fig. 4B, lane 5). To analyze specificity of the binding and to determine a domain of Tat that binds LIS1, several Tat mutants were utilized including Tat 1–72, Tat 1–48, and Tat 37–72 and also GST as a control (Fig. 5). Full length LIS1 bound with equal efficiency to a full length Tat, Tat 1–48 or Tat 37–72 but not to GST alone (Fig. 5, lanes 2 to 5). In contrast, isolated WD5 domain of LIS1 bound most efficiently to the full length Tat 1–72 and less efficiently to Tat 1–48 or to Tat 37–72 (Fig. 5, lanes 6 to 9). The isolated N-terminal domain of LIS1 bound strongly to GST (Fig. 5, lane13), and thus its weak binding to GST-Tat (Fig. 5, lane 12) is likely to be mediated by the binding to the GST moiety.
Figure 4 LIS1 binds to HIV-1 Tat in vitro. Individual protein components of Tat-associated complex were translated in reticulocyte lysate containing [35S]methionine as described in the Experimental procedures section. A, Input lysates, resolved on 12% SDS-PAGE. Lane 1- CDK7; Lane 2-Cyclin H; Lane 3-MAT1; Lane 4-LIS1; Lane 5-the N-terminal domain of LIS1 (LIS NT); Lane 6- WD7; Lane 7-WD6; Lane 8 – WD5; Lane 9 – WD4; Lane 10- WD3; and Lane 11- WD1. B, programmed reticulocyte lysates from panel A precipitated with GST-Tat 72 immobilized on glutathione-agarose beads, and resolved on 12% SDS-PAGE.
Figure 5 WD5 domain of LIS1 interact with HIV-Tat. LIS1, WD5 domain of LIS1 (WD5) and N-terminal portion of LIS1 (LIS1 NT) were translated in reticulocyte lysate containing [35S] methionine as described in the Experimental procedures section. Lysates were precipitated with GST-fused Tat 1–72, Tat 1–48, Tat 37–72 or GST alone, immobilized on glutathione-agarose beads, and resolved on 12% SDS-PAGE. Lanes 1, 6 and 11 – Input; Lanes 2, 7 and 12 – precipitation of LIS1, WD5 or LIS1 NT with Tat 1–72; Lanes 3 and 8 – precipitation of LIS1 and WD5 with Tat 1–48; Lanes 4 and 9 – precipitation of LIS1 and WD5 with Tat 37–72; Lanes 5, 10 and 13 – precipitation of LIS1, WD5 or LIS1 NT with GST alone. The figure is an autoradiogram.
Tat co-immunoprecipitates with LIS1 from HeLa cellular extracts
To analyze interaction of Tat with LIS1 in cultured cells, co-immunoprecipitation analysis was performed. Tat was expressed in HeLa cells infected with adenovirus vector expressing Flag-tagged Tat [36]. Tat expression in the extract was verified by immunoblotting analysis with anti-Flag antibodies (Fig. 6A, compare lane 2 to lane 1) and also with anti-Tat antibodies (not shown). LIS1 was expressed equally in control cells without Tat and in the cells expressing Flag-Tat (Fig. 6B, lanes 1 and 2). Tat co-precipitated with LIS1 when LIS1 was immunoprecipitated with LIS1-specific monoclonal antibodies, resolved by 12% Tris-Tricine PAGE and immunoblotted with anti-Flag antibodies (Fig. 6A, lane 3). No Tat was detected in the control immunoprecipitation (Fig. 6A, lane 4). Similar, LIS1 co-precipitated with Tat when Flag-Tat was immunoprecipitated with anti-Tat polyclonal antibodies, resolved by 10% Tris-Tricine PAGE and immunoblotted with anti-LIS1 antibodies (Fig. 6B, lane 3). No LIS1 was detected in the control immunoprecipitation (Fig. 6B, lane 4). These results indicate that Tat associates with LIS1 in cultured cells.
Figure 6 Co-immunoprecipitation of HIV-1 Tat with LIS1 from HeLa cells. HeLa whole cell extracts, with and without Flag-Tat, were prepared from uninfected and Adeno-Tat infected cells as described in the Experimental procedures section. A, LIS1 was immunoprecipitated with monoclonal anti-LIS1 antibodies, resolved by 10% Tris-Tricine gel and immunoblotted with anti-Flag antibodies to detect Flag-Tat. B, Flag-Tat was immunoprecipitated with polyclonal anti-Flag antibodies, resolved by 12% Tris-Tricine gel and probed with monoclonal anti-LIS1 antibodies to detect LIS1.
Tat binds to LIS1 in yeast two-hybrid system
To analyze whether Tat interacts with LIS1 directly and not through another protein, we utilized LexA-based yeast two hybrid system (Clontech, see details in Experimental procedures). EGY48 yeast cells pretransformed with pSH18–34 reporter plasmid (-Ura selection) were further transformed with different combinations of pJG-LIS1 or pJG4–5 empty vector (-Trp selection) and pLexA Tat or pLexA empty vector (-His selection). Colonies grown on-His/-Trp/-Ura media with glucose were plated on Galactose/Raffinose His /-Trp/-Ura plates, to induce LIS1 and Tat production. The plates also contained 5-Bromo-4-Chloro-3-Indolyl-β-D-galactopyranoside (X-Gal) substrate for β-galactosidase. Tat interacted with LIS1 as it was detected by development of blue color upon conversion of X-gal (Fig. 7D). In contrast Tat did not interact with the acid activation domain alone (Fig. 7C). Also no interaction was detected for LexA DNA binding domain and acid activation domain (Fig. 7A) or LexA DNA binding domain and LIS1 (Fig. 7B).
Figure 7 LIS1 interacts with Tat in yeast two-hybrid assay. EGY48 yeast cells were transformed, as described in Experimental procedures, with pSH18–34 reporter and combinations of pLexA and pJG4–5 empty vectors (panel A); pLexA and pJG LIS1 (panel B); pLexA Tat and pJG 4–5 (panel C); pLexA Tat 86 and pJG LIS1 (panel D). Six independent colonies from each transformation were cultured on plates containing Galactose/Raffinose to induce Tat and LIS1 synthesis and X-Gal substrate to detect β-galactosidase.
Taken together, these results indicate that LIS1 directly and specifically binds to Tat in vivo.
Discussion
In this study, we show that HIV-1 Tat protein associates with LIS1 protein. LIS1, a microtubule binding protein [21] contains WD repeats [24] that are likely to participate in protein-protein interactions [24]. LIS1 regulates microtubule dynamics by interacting with dynein motor, NudC and Dynactin [27,28] and also with Nudel [29]. A yeast homologue of LIS1, NudF associates with NudC to regulate dynein and microtubule dynamics [37,38]. Thus, interaction of Tat with LIS1, a scaffold that assembles dynein motor, may affect microtubule dynamics.
We purified several candidate proteins that might interact with Tat, and found CDK7, cyclin H, MAT1 and LIS1. We expected that CDK7 might bind to Tat as previously it was shown to interact directly with Tat [35]. In contrast, analysis of the binding of individually translated proteins showed that LIS1 and not CDK7 bound to Tat. We hypothesized that WD domain(s) of LIS1 might bind Tat, as these domains form a planar surface. Correspondingly, domains WD1, WD4, WD5 and WD7 were found to bind Tat but not the N-terminal part of LIS1 that contains coil-coil region, and which is devoid of WD domains. We analyzed whether a particular domain of Tat binds LIS1 or WD5 domain of LIS1. Full length Tat 1–72 was most efficient in binding of either LIS1 or WD5 domain of LIS1. It would be interesting to determine whether CDK7 also binds to LIS1, and whether LIS1 promotes activation of the kinase activity of CDK7 by Tat. Although LIS1 is a cytoplasmic protein, it may be required for initial assembly of a protein complex containing CDK7. Our results contrasted with the previous report in which Tat binds to purified CDK7 [35]. We hypothesize that under our experimental conditions, excess of endogenous LIS1 present in the reticulocyte lysate might compete with interaction of Tat with CDK7. Interestingly, Gaynor an colleagues only detect specific interaction of Tat with TFIIH but not with of CDK7 or CAK alone [39]. Therefore, it is possible that in a complex protein mixture Tat interacts with CDK7 indirectly through another protein such as LIS1.
To explore interaction of Tat and LIS1 in cultured cells, Flag-tagged Tat was expressed in HeLa cells and then immunoprecipitated with anti-Flag-antibodies. LIS1 was found to co-immunoprecipitate with Tat. Correspondingly, when LIS1 was immunoprecipitated with anti-LIS1 monoclonal antibodies, Flag-Tat was found in the immunoprecipitates. These results suggest that Tat associates with LIS1 in cultured cells. To confirm that LIS1 and Tat interact in vivo, we used yeast two-hybrid system, in which Tat was expressed as a bait and LIS1 as a prey. Again, we found that LIS1 and Tat interacted in this system. Taken together, our in vitro and in vivo results demonstrate that HIV-1 Tat binds to LIS1 and that this binding is likely to occur through one of the WD domains of LIS1.
Tat contains several functionally important regions, including the N-terminal region I (residues 1–21); cystein-rich region II (residues 22–37); core region III (residues 38–48); basic region IV (residues 49–59); glutamine-rich region V (residues 60–72); and C-terminal region VI [20,40]. Zhou and his colleagues showed that Tat interacts with microtubules through parts of region II (residues 35–37) and region III (residue 38) [18]. More recently, Loret and his colleagues showed that the glutamine-rich region of Tat may also interact with microtubules and promote apoptosis in T cells [20]. In a following study which will appear in the same issue of Retrovirology, Loret and his colleagues show that Tat residues 38–72 are sufficient to enhance microtubule polymerization and that the extent of the enhancement correlates with the severity of Tat-induced apoptosis[41]. Taken together these studies indicate that residues 35–38 of regions II and III and glutamine-rich region of Tat may interact with microtubules. These results correlate well with our finding that full length Tat binds LIS1 better than the isolate domains of Tat. Whether LIS1, a cellular structural protein and also an enzymatic subunit of PAF-AH, plays a role in Tat-induced apoptosis remained to be determined. As Tat-associated proteins include CDK7, Cyclin H, MAT1 and LIS1, it is possible that interaction of Tat with LIS1 might promote binding of CDK7 and ultimately affect viral gene expression through a direct activation of CDK7 or indirectly through activation of a down stream kinase, CDK2, by CDK7. As Tat is shuttling between nucleus and cytoplasm, its interaction with LIS1 and CDK7-containing protein complex might allow a temporary activation/modulation of the CDK7 activity. It is remained to be determined whether such interaction has an effect on Tat-induced transcription of HIV-1 genes. LIS1 may also function as an adaptor that brings HIV-1 Tat to microtubules that may release microtubules-associated BIM-1 protein and induce apoptosis [18]. A more detailed future study will address the questions of the regulation of HIV-1 transcription and Tat-mediated apoptosis by LIS1.
Methods
Materials
Jurkat T-cells were purchased from National Cell Culture Center (CELLEX BIOSCIENCES, MN). DEAE-Sepharose (FF), SP-Sepharose (FF), Hi Trap heparin columns, [γ-32P] ATP (6000 Ci/mmol) and (35S)-labeled Methionine were purchased from Amersham Pharmacia Biotech (Piscataway, NJ). Econo-Pac CHT-II Cartridge (ceramic hydroxyapatite) was from Bio-Rad (Hercules, CA). Glutathion-agarose was from Sigma (Atlanta, GA). GST-CTD was expressed in Escherichia coli and purified as we described [32]. The Tat expression plasmids GST-Tat (1–72), GST-Tat (1–48), GST-Tat (37–72) were obtained from AIDS Research and Reference Reagents Program (NIH), expressed in Escherichia coli and purified on Glutathione-agarose beads as described [31]. CDK7, cyclin H and MAT1 expression vectors were kindly provided by Dr. Marcel Doreé (CNRS, Montpellier, France). Coupled transcription/translation system based on rabbit reticulocyte lysate was purchased from Ambion (Austin, TX). Protein (G) and protein (A) agarose were purchased from Sigma (Atlanta, GA).
Antibodies
Anti-Tat rabbit polyclonal (HIV-1 BH10 Tat antiserum) and monoclonal (NT3 2D1.1) antibodies were received from AIDS Research and Reference Reagents Program (NIH). Anti-Flag antibodies were purchased from Sigma (Atlanta, GA). Polyclonal antibodies to CDK7, and PSTAIRE were purchased from Santa Cruz Biochemical (Santa Cruz, CA). Polyclonal antibody to CDK9 (PITALRE) were purchased from Biodesign Company (Saco, ME). Monoclonal antibodies for LIS1 were as described [21].
Tat-associated CTD kinase assay
Tat-associated kinase activity was assayed as described previously [32]. Briefly, portions of eluted fractions (about 1/1000 of the total amount) from each chromatography column were incubated with 10 μg of GST-Tat (1–72) immobilized on glutathione-agarose beads for 1 hour at 4°C. The beads were washed with the buffer B containing 20 mM HEPES (pH 7.9), 250 mM NaCl, 1% NP-40, 5 mM EDTA, 0.5 mM DTT, 0.5 mM PMSF and 10 μg/ml aprotinin, followed by washing with the kinase buffer (50 mM HEPES (pH 7.9), 10 mM MgCl2, 6 mM EGTA and 2.5 mM dithiothreitol). Tat-associated CTD kinase activity was assayed by incubating the kinase-bound beads with 100 ng GST-CTD in kinase buffer containing 50 μM ATP and 10 μCi of (32p)ATP for 10 min at room temperature. Phosphorylated GST-CTD was resolved on 10% SDS-PAGE and subjected to autoradiography and quantification with PhosphorImager Storm 860 (Molecular Dynamics).
Purification of Tat-associated CTD kinase
Purification of Tat-associated CTD kinase from Jurkat T-cells was carried as previously described [32]. Briefly, 100 liters of Jurkat T cell culture at concentration of 5 × 105 cells/ml were centrifuged, washed and Dounce-homogenized in Buffer A (50 mM HEPES [pH 7.9], 5 mM EDTA, 0.5 mM DTT, 0.5 mM PMSF, 10 μg/ml aprotinin and 10% glycerol) supplemented with 0.1% NP-40. The whole cell extract was prepared and fractionated by ammonium sulfate precipitation. Ammonium sulfate was added to 10% saturation to extract nuclei. After centrifugation, the supernatant, containing approximately 10 g of protein, was further fractionated with ammonium sulfate added to 20%, 40% and 80% saturation. The 40% ammonium sulfate fraction (about 3.5 g of protein) was found to contain the major part of Tat-associated CTD kinase activity. This fraction was diluted with Buffer A until the conductivity was equivalent to 50 mM KCl and then loaded on a DEAE-Sepharose column (about 500 mg of protein per 50 ml column). The column was eluted with a linear gradient of KCl (0.1 to 1 M) in Buffer A. Fractions were assayed for Tat-associated CTD kinase activity as described above. A peak of Tat-associated CTD kinase activity was collected, diluted with Buffer A until conductivity was equivalent to 50 mM KCl and loaded on a 10 ml SP-Sepharose column which was eluted with linear gradient of KCl (0.1 to 1 M) in Buffer A. A flow-through fraction containing Tat-associated CTD kinase activity was further fractionated on Hi Trap heparin columns (1 ml, three in series). Fractions were collected and analyzed for the Tat-associated CTD-kinase activity as described above, as well as by immunoblotting. Fractions containing Tat-associated CTD kinase activity TTK were resolved on 12% SDS-PAGE (20 × 20 cm) stained with colloidal Coumassie Blue and subjected to protein microsequencing.
NanoLC ion trap mass spectrometry and peptide sequencing
The procedure for peptide sequencing was performed as described previously. Protein bands visible after colloidal Coomassie blue staining and corresponding to the peak of CTD hyperphosphorylating activity after the heparin-agarose column were subjected to in-gel reduction, carboxyamidomethylation and tryptic digestion (Promega, Madison, WI). Multiple peptide sequences were determined in a single run by microcapillary reverse-phase chromatography directly coupled to a Finnigan LCQ quadrupole ion trap mass spectrometer equipped with a custom nanoelectrospray source. The column was packed in-house with 5 cm of C18 support into a New Objective one-piece 75 um I.D. column terminating in a 15 μm tip. Flow rate was 190 nanoliters/min. The ion trap was programmed to acquire successive sets of three scan modes consisting of full scan MS over alternating ranges of 395–800 m/z or 800–1300 m/z, followed by two data dependent scans on the most abundant ion in those full scans. These data dependent scans allowed the automatic acquisition of a high resolution (zoom) scan to determine charge state and exact mass, and MS/MS spectra for peptide sequence information. MS/MS spectra were acquired with a relative collision energy of 30%, an isolation width of 2.5 Dalton and recurring ions dynamically excluded. Interpretation of the resulting MS/MS spectra of the peptides was facilitated by programs developed in the Harvard Microchemistry Facility and by database correlation with the algorithm SyQuest [42].
In vitro proteins synthesis
Proteins were transcribed/translated as described previously [32]. Briefly, the CDK7, cyclin H and MAT1, LIS1 and different domains of LIS1 were transcribed/translated in a coupled rabbit reticulocyte system according to manufacturer recommendations (Ambion, Austin, TX). Proteins were resolved on 12% SDS-PAGE. The gel was treated with Amplify solution (Amersham Pharmacia Biotech, Piscataway, NJ), dried and exposed to X-ray film with intensifying screen at -70°C.
Co-immunoprecipitation and Western blot
HeLa cells were infected with adenovirus vector expressing Flag-tagged Tat protein as we previously described [36]. HeLa whole cell extracts were prepared as described previously [43]. Cell extracts were also prepared from non-infected HeLa cells and used as a control. About 100 μg of whole cell extract was supplemented with 5 μg of anti-Flag or anti LIS1 antibodies. Then protein G-agarose beads preblocked with 5% BSA and suspended in TNN buffer (50 mM Tris-HCl (pH 7.5), 0.5% NP-40, 150 mM NaCl) buffer were added and the reaction was incubated in TNN buffer at 4°C for 2 h with rocking. The beads were precipitated and washed once with TNN buffer and once with the kinase buffer (50 mM HEPES-KOH (pH-7.9), 10 mM MgCl2, 6 mM EGTA, 2.5 mM DTT). The pellet was then resuspended in a 30 μl of 1X SDS loading buffer (4% SDS, 10% glycerol, 5% 2-mecarpthaethanol, 0.002% bromophenol blue) and heated at 90°C for 3 minutes. The proteins were resolved on SDS Tris-Tricine PAGE, 10%, to detect LIS1, or 12%, to detect Tat, and immunoblotted with anti-LIS1 or anti-Flag antibodies.
Yeast two-hybrid system
The parent yeast cells EGY48 (LexA 2H) genotype (MATα, ura3, his3, tryp1, LexAop (x6) -LEU2), auxotrophic for tryptophan (Trp), uracil (Ura), histidine (His), with LEU2 as a reporter gene. Yeast were transformed by electroporation as follow. One colony of the yeast cells was resuspended into 10 ml of appropriate selective media and grown at 30°C overnight. Cells were collected at 3000 rpm for 10 min, washed twice with HEPES/Sorbitol (20 mM HEPES pH 7.9, 1 M Sorbitol), resuspended in 200 μl of HEPES/Sorbitol and supplemented with 1 μg of a plasmid DNA. The mixture was pulsed with 2500 V in 0.4 cm cuvette, then 1 ml of appropriate selective media was added and cells were shaken at 30°C for 2 hours. The cells were collected by centrifugation, resuspended into 250 μl of HEPES/Sorbitol and plated on appropriate selective plates. EGY48 cells were transformed with pSH18–34 vector containing Lac Z reporter under the control of LexAop(x8) and also URA3 and ampr genes as selection markers. The transformed yeast cells (EGY48-lacZ) were selected on Uracyl deficient media. HIV-1 Tat first exon was subcloned into pLexA in frame with the LexA(1–202), the DNA binding domain to create the bait vector (pLexA-Tat). LIS1 was subcloned into pJG 4–5 (ampr) in frame with the acid activation domain to create pJG-LIS1 carrying hemagglutinin (HA) tag (Trp selectable marker). The EGY48-lacZ yeast cells were transformed with pLexA-Tat vector, and selected for growth on uracyl and histidine deficient media. The Tat expressing yeast cell growing on Uracyl, Histidine deficient plates were then transformed with pJG-LIS1. To detect interaction between Tat and LIS1 interaction, yeast cells were plated on galactose/raffinose-containing plates to allow expression of Tat and LIS1, and production of β-galactosidase was visualized with 5-bromo-4-chloro-3-indolyl-β-D-galactoside (X-gal) substrate.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
NE carried out studies of LIS1 and Tat interaction in vitro and in vivo and participated in the writing and assembling of the manuscript. TA carried out yeast two-hybrid assays. YV provided technical help. WSL performed protein sequencing. WT participated in the design and discussion of the study. TS and OR created vectors for expression of LIS1 and participated in the design of the study. SN purified LIS1 containing protein complex for protein sequencing, performed general control and coordination of the study. All authors read and approved the manuscript.
Supplementary Material
Additional File 1
Analysis of protein composition of DEAE-Sepharose purified fraction of Tat-associated CTD kinase. Fractions from the DEAE-Sepharose column fractionation shown in Fig. 1B were analyzed for Tat-associated CTD kinase activity and also by Western blotting with antibodies against CDK7, CDK9, p62 subunit of TFIIH and PSTAIRE.
Click here for file
Additional File 2
HIV-Tat interacts with a 50 kDa protein from purified Tat-associated CTD kinase. GST-fused Tat 1–72, immobilized on glutathione-agarose beads, was incubated without (lane 1), or with fraction 18 (lane 2), fraction 20 (lane 3), fraction 22 (lane 4), or fraction 24 (lane 5) from the heparin-agarose, shown in Fig. 2B. Precipitated
Click here for file
Additional File 3
Endogenous LIS1 is present in reticulocyte lysates. Individual protein components of Tat-associated complex were translated in reticulocyte lysate. The lysates were resolved on 12% SDS-Tris-Tricine gel and immunoblotted with anti-LIS1 monoclonal antibodies. Lane 1- CDK7; Lane 2-Cyclin H; Lane 3-MAT1; and Lane 4-LIS1-programmed lysate.
Click here for file
Acknowledgements
This work was supported by NIH Grants AI 156973-01 and AI 056973-01S1, and by NHLBI Research Grant UH1 HL03679 from the National Institutes of Health and The Office of Research on Minority Health. The work was also supported in part by "The Nella and Leon Benoziyo Center for Neurological Diseases". O.R. is an Incumbent of the Berstein-Mason professorial chair of Neurochemistry. The authors would like to thank Dr. Victor Gordeuk, the director of the Research Scientist Program of Howard University for his continuous support and members of his laboratory at the Center for Sickle Cell Disease of Howard University for valuable discussions.
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| 15698475 | PMC549217 | CC BY | 2021-01-04 16:36:40 | no | Retrovirology. 2005 Feb 7; 2:6 | utf-8 | Retrovirology | 2,005 | 10.1186/1742-4690-2-6 | oa_comm |
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Nutr JNutrition Journal1475-2891BioMed Central London 1475-2891-4-51570307710.1186/1475-2891-4-5ReviewSweet proteins – Potential replacement for artificial low calorie sweeteners Kant Ravi [email protected] Institute of Bioinformatics and Applied Biotechnology, ITPL, Bangalore-560066, India2005 9 2 2005 4 5 5 1 12 2004 9 2 2005 Copyright © 2005 Kant; 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.
Exponential growth in the number of patients suffering from diseases caused by the consumption of sugar has become a threat to mankind's health. Artificial low calorie sweeteners available in the market may have severe side effects. It takes time to figure out the long term side effects and by the time these are established, they are replaced by a new low calorie sweetener. Saccharine has been used for centuries to sweeten foods and beverages without calories or carbohydrate. It was also used on a large scale during the sugar shortage of the two world wars but was abandoned as soon as it was linked with development of bladder cancer. Naturally occurring sweet and taste modifying proteins are being seen as potential replacements for the currently available artificial low calorie sweeteners. Interaction aspects of sweet proteins and the human sweet taste receptor are being investigated.
Sweet proteinSweet taste receptorSweetenerT1R2-T1R3Diabetes
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Sweet and taste modifying proteins
The prevalence of obesity and diabetes has increased dramatically in recent years in the United States, with similar patterns seen in several other countries including India [1] as well. Diabetes mellitus is a chronic disease caused by inherited or acquired deficiency in production of insulin by the pancreas or by the ineffectiveness of the insulin produced [2]. Artificial sweeteners like Saccharin, Aspartame, Cyclamate and AcesulfameK are used world-wide as low calorie sweeteners by patients affected by diseases linked to the consumption of sugar, e.g. diabetes, hyperlipemia, caries, obesity etc. but they have side effects such as psychological problems, mental disorders, bladder cancer, heart failure and brain tumors [3-7]. Sweet proteins have the potential to replace these artificial sweeteners, by acting as natural, good, low calorie sweeteners, as we know that proteins do not trigger a demand for insulin in these patients whereas sucrose does.
In humans, the sweet taste is mainly due to the recently discovered T1R2-T1R3 receptor [8-10], two of the three members of the T1R class [8-10] of taste-specific proteins hypothesized to function in combination as a heterodimer. The human T1R2-T1R3 receptor recognizes natural and synthetic sweetness and T1R1-T1R3 recognizes umami taste [11,12]. So far there are seven known sweet and taste-modifying proteins, namely Brazzein [13], Thaumatin [14], Monelin [15], Curculin [16], Mabinlin [17], Miraculin [18] and Pentadin [19]. Properties and characteristics of these proteins are illustrated in Table 1. The key residues on the protein surface responsible for biological activity have not yet been identified with certainty for any of these proteins [20]. Monellin was found to be 100000 times sweeter than sucrose on a molar basis [21], followed by Brazzein and Thaumatin which are 500 times [13] and 3000 times sweeter then sucrose [14] respectively (the latter two on a weight basis). All of these proteins have been isolated from plants that grow in tropical rainforests. Although most of them share no sequence homology or structural similarity, Thaumatin shares extensive homology with certain non-sweet proteins found in other plants [15].
The potential industrial applications of these proteins are the low calorie sweetener industry and the cola, snacks, food and chocolate industries.
Brazzein
Brazzein is the smallest, most heat-stable [13] and pH-stable member of the set of proteins known to have intrinsic sweetness. The protein, consisting of 54 amino acid residues, is reported to be between 500 and 2000 times sweeter than sucrose [22] and represents an excellent alternative to available low calorie sweeteners. It was originally isolated from the fruit of an African plant Pentadiplandra brazzeana Baillon [23]. Heat and pH stability of the protein make it an ideal system for investigating the chemical and structural requirements of a sweet-tasting protein. Based on the wild-type brazzein, 25 mutants were produced to identify critical regions important for sweetness. To assess their sweetness, psychophysical experiments were carried out with 14 human subjects. First, the results suggest that residues 29–33 and 39–43, plus residue 36 between these stretches, as well as the C-terminus are involved in the sweetness [24]. Second, charge plays an important role in its interaction with the sweet taste receptor [24].
Thaumatin
The thaumatins are a class of intensely sweet proteins isolated from the fruit of the tropical plant Thaumatococcus danielli. The protein crystallizes in a hexagonal lattice after a temperature shift from 293 to 277 K. The structure has been solved at 1.6 Å resolution. Its fold was found to be identical to that found in three other crystal forms grown in the presence of crystallizing agents of differing chemical natures [25]. It consists of 207 amino acid residues with eight intramolecular disulfide bonds and contains no free cysteine residues. It aggregates upon heating at pH 7.0 above 70 degrees C, whereupon its sweetness disappears [26,27]. The protein is approximately 10000 times sweeter than sugar on a molar basis [28]. It is a protein that tastes intensely sweet only to Old World monkeys and to higher primates, including man [29], as it has been found that the protein binds to certain elements in taste pores of Rhesus monkey foliate papillae [30]. Thaumatin has been approved for use in many countries as both a flavor enhancer and a high-intensity sweetener [31].
Monellin
Monellin, a sweet protein, consists of two noncovalently associated polypeptide chains, an A chain of 44 amino acid residues and a B chain of 50 amino acid residues [32]. The protein can be purified from the fruit of Dioscoreophyllum cumminsii grown in West Africa and is approximately 100,000 times sweeter than sugar on a molar basis and several thousand times sweeter on a weight basis [28]. Single-chain monellin (SCM), which is an engineered 94-residue polypeptide, has proven to be as sweet as native two-chain monellin, and is more stable than the native monellin at high temperature and in acidic environments [33]. Native monellin is relatively sensitive to heat or acid treatment, which may cause separation of the sub-units and denaturation of the protein. Despite misgivings about the stability of the protein to heat and acid, downstream processes have been established. Its D-enantiomer has been crystallized and analyzed by X-ray crystallography at 1.8 Å resolution. Two crystal forms (I and II) were found under crystallization conditions similar, but not identical, to the crystallization conditions of natural L-monellin [34]. One NMR study of a non-sweet analog in which the AspB7 of protein was replaced by AbuB7 (L-2-Aminobutylicacid), showed similar 3-dimensional structures of these two proteins, indicating that the lack of the beta-carboxyl group in the AbuB7 analog is responsible for the loss of sweetness [35]. Recent research on identifying binding sites on the receptor by means of structure-taste relationships, found that four monellin analogues, [AsnA16]-, [AsnA22]-, [GlnA25]-, and [AsnA26]-monellin were 7500, 750, 2500, and 5500 times as sweet as sucrose on a weight basis, respectively. Thus, among them, [AsnA22]-monellin and [GlnA25]-monellin were less sweet than the native monellin [36].
Curculin
Curculin which is extracted from Curculigo latifolia acts as a good low calorie sweetener. Its maximum sweetness is equal to 0.35 M of sucrose. It has taste modifying abilities since water and sour substances elicit a sweet taste after consumption of curculin [37]. There is no other protein currently available with both sweet taste and taste modifying abilities [38]. The taste modifying activity of the protein (discussed below) remains unchanged when it is incubated at 50°C for 1 hr between pH 3 and 11 [39].
The molecular weight of Curculin was determined by low angle laser light scattering and was found to be 27800 [38]. Its three-dimensional model has been built from the X-ray coordinates of GNA, a mannose-binding lectin from snowdrop (Galanthus nivalis) [38]. The three mannose-binding sites present in GNA were found in curculin but were not functional. Some well exposed regions on the surface of the three-dimensional model of the said protein could act as epitopes responsible for the sweet-tasting properties of the protein [40]. The protein can be crystallized by the vapor diffusion method using polyethylene glycol 400 as a precipitant. The crystals belong to orthorhombic space group P2(1)2(1)2(1) with unit cell dimensions: a = 105 Å, b = 271 Å, c = 48.7 Å. The crystals diffract X-rays to resolution of 3.0 Å and are suitable for X-ray crystallographic studies [41].
Mabinlin
Mabinlin is a sweet protein with the highest known thermostablility [42]. It is derived from Capparis masaikai and its sweetness was estimated to be around 400 times that of sucrose on weight basis. It consists of an A chain with 33 amino acid residues and a B chain composed of 72 residues. The B chain contains two intramolecular disulfide bonds and is connected to the A chain through two intermolecular disulfide bridges [43]. Its heat stability is due to the presence of these four disulfide bridges [44]. The sweetness of Mabinlin-2 is unchanged after 48 hr incubation at boiling point [17]and of Mabinlin-3 and -4 are unchanged after 1 hr at 80°C [45].
Miraculin
Miraculin is a taste-modifying protein that belongs to the class of sweet proteins. It is extracted from Richadella dulcifica an evergreen shrub native of West Africa. The protein is a single polypeptide with 191 amino acid residues [46]. It modifies the sweet receptor in such a way that it can be stimulated by acid [47]. Thus, miraculin has the unusual property of modifying sour taste into sweet taste [46].
Taste-modifying protein modifies the sweet taste receptor on binding and this behavior of these proteins is responsible for modification in taste of sour substance [46,47]. All acids (which are normally sour) taste sweet after consumption of these proteins. The effects of these proteins exist for around half an hour after consumption and intake of any sour substance will therefore taste sweet during this period of time. The taste buds come to there normal state with time.
Pentadin
Pentadin is a sweet protein extracted from the plant Pentadiplandra brazzeana, a shrub found in tropical forests of a few African countries. Not much information is available about the protein despite its isolation several years ago, in 1989 [48]. The protein was reported to be around 500 times sweeter then sucrose on a weight basis. It also consists of subunits coupled by disulfide bonds [49].
Interaction of sweet proteins with their receptor
Humans detect taste with taste receptor cells. These are clustered in taste buds. Each taste bud has a pore that opens out to the surface of the tongue enabling molecules and ions taken into the mouth to reach the receptor cells inside. There are five primary taste sensations salty, sour, sweet, bitter and umami. Sweet and umami (the taste of monosodium glutamate) are the main pleasant tastes in humans. T1Rs are mammalian taste receptors that assemble two heteromeric G-protein-coupled receptor complexes T1R1+T1R3, an umami sensor, and T1R2+T1R3, a sweet receptor [50].
Sweet and taste-modifying proteins interact with the T1R2-T1R3 receptor with a different mechanism compared to small molecular weight compounds [51]. Recently, it has been shown that the T1R2-T1R3 receptor has many characteristics similar to the mGluR [52], apart from some minor differences in the active site region.
The major work by Kunishima et al. [52] solving the crystal structure of the N-terminal active site region of the subtype 1 of mGluR both free and complexed with glutamate has helped a lot in understanding the mechanism of interaction between ligand and T1R2-T1R3 receptor. Their structural work on mGluR and its N-terminal domain [52,53] showing considerable conformational change induced by the glutamate complexation. The 'Active' and 'resting' conformations of m1-LBR, an extracellular ligand binding region of mGluR, is modulated by the dimer interface. The protomer can form 'open' or 'closed' confirmations and is made up of two domains namely LB1 and LB2. The population of active conformers depends on ligand binding, i.e. the so called 'closed-open_A'. The ligand-free receptor exists as two different structures, free form I (open-open_R), the 'resting' conformation with two open protomers and free form II (closed-open_A), nearly identical to the complexed form (Figure 1, references 52, 54). The mechanism suggested by these structures is that the receptor is in dynamic equilibrium, and that ligand binding stabilizes the 'active' dimer. There are thus two ways, in principle, to activate the receptor: first, to complexate form I with the proper ligand (glutamate for the mGluR, aspartame or any other small molecular weight sweetener for the T1R2-T1R3 receptor) and second, by shift the equilibrium between free form I and free form II in favor of free form II.
The exact mechanism of interaction of sweet proteins with the T1R2-T1R3 sweet taste receptor has not yet been elucidated [51]. Low molecular mass sweeteners and sweet proteins interact with the same receptor, the human T1R2-T1R3 receptor[52]. Studies have shown that the T1R3 receptor protein is encoded by the Tas1r3 gene involved in transduction of sweet taste [55].
Recently it has been found that T1R3-independent sweet- and umami-responsive receptors and/or pathways also exist in taste cells [56].
Conclusion and scope of further work
As it has been found that sweet proteins are thousands of times sweeter than sucrose and are of low calorie value, these proteins can be used as natural low calorie sweeteners by people suffering from diseases linked to consumption of sugar e.g. obesity, diabetes and hyperlipemia.
Candidate proteins can be checked for biological activity with the human taste receptor. Also mutations can be induced in candidate sweet proteins to analyze changes in their physical, chemical and biological properties. The work can be taken forward by solving the structures of the proteins and taste receptors with a view to increasing the efficiency of these sweeteners.
Acknowledgments
I would like to thank Prof. S. Ramakumar, Chairman, Bioinformatics Center, Indian Institute of Science, Bangalore for useful discussions and valuable suggestions. Access to the Bioinformatics Centre and other facilities funded by the Department of Biotechnology (DBT) is gratefully acknowledged. Also, Dr. Gayatri Saberwal, Institute of Bioinformatics and Applied Biotechnology, Bangalore for her support in writing the paper. Sincere thanks to Prof. Manju Bansal, Director, IBAB, Prof. N. Srinivasan, Molecular Biophysics Unit, Indian Institute of Science, Mr. Shashi Kant, Hannover Medical Institute, Germany and Mr. Mohan Babu, Department of Botany, Bharathiar University for their feedback and support.
Figures and Tables
Figure 1 Diagrammatic representation of the T1R2-T1R3 receptor showing possible stabilization by binding of a sweet protein to a secondary binding site on the surface of free form II. The sweet protein is represented in red on the left part of free form II, preventing it reverting to free form I. (adapted from references 52 and 54)
Table 1 Comparison of thaumatin, monellin, mabinlin, pentadin, brazzein, curculin and miraculin.
Thaumatin Monellin Mabinlin Pentadin Brazzein Curculin Miraculin
Source Thaumatococcus danielli Benth Dioscoreophyllum cumminsii Diels Capparis masakai Levl Pentadiplandra brazzeana Baillon Pentadiplandra brazzeana Baillon Curculingo latifolia Richadella dulcifica
Geographic distribution West Africa West Africa China West Africa West Africa Malaysia West Africa
Variants I, II, a, b, ca - I, II- a, III, IVa - - - -
Sweetness factor (weight basis) 3000 3000 100 500 2000 550 -
Molecular mass (active form, kDa) 22.2 10.7 12.4 12.0b 6.5 24.9 98.4
Amino acids 207 45 (A chain)
50 (B chain) 33 (A chain)
72 (B chain) ? 54 114 191
Active form Monomer Dimer (A + B) Dimer (A + B) ? Monomer Dimer (A + A) Tetramer (A+A+A+A)
Source: Adapted from Kurihara (1994). aAt least five different forms of thaumatin (Lee et al., 1988) and four different forms of mabinlin (Nirasawa et al., 1994) have been identified. bA chromatographic fraction containing a 12-kDa protein was sweet. This same fraction, when subjected to electrophoresis under non-reducing conditions showed bands in the region between 22 and 41 kDa, suggesting the presence of subunits.
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| 15703077 | PMC549512 | CC BY | 2021-01-04 16:05:47 | no | Nutr J. 2005 Feb 9; 4:5 | utf-8 | Nutr J | 2,005 | 10.1186/1475-2891-4-5 | oa_comm |
==== Front
Nutr JNutrition Journal1475-2891BioMed Central London 1475-2891-4-51570307710.1186/1475-2891-4-5ReviewSweet proteins – Potential replacement for artificial low calorie sweeteners Kant Ravi [email protected] Institute of Bioinformatics and Applied Biotechnology, ITPL, Bangalore-560066, India2005 9 2 2005 4 5 5 1 12 2004 9 2 2005 Copyright © 2005 Kant; 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.
Exponential growth in the number of patients suffering from diseases caused by the consumption of sugar has become a threat to mankind's health. Artificial low calorie sweeteners available in the market may have severe side effects. It takes time to figure out the long term side effects and by the time these are established, they are replaced by a new low calorie sweetener. Saccharine has been used for centuries to sweeten foods and beverages without calories or carbohydrate. It was also used on a large scale during the sugar shortage of the two world wars but was abandoned as soon as it was linked with development of bladder cancer. Naturally occurring sweet and taste modifying proteins are being seen as potential replacements for the currently available artificial low calorie sweeteners. Interaction aspects of sweet proteins and the human sweet taste receptor are being investigated.
Sweet proteinSweet taste receptorSweetenerT1R2-T1R3Diabetes
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Sweet and taste modifying proteins
The prevalence of obesity and diabetes has increased dramatically in recent years in the United States, with similar patterns seen in several other countries including India [1] as well. Diabetes mellitus is a chronic disease caused by inherited or acquired deficiency in production of insulin by the pancreas or by the ineffectiveness of the insulin produced [2]. Artificial sweeteners like Saccharin, Aspartame, Cyclamate and AcesulfameK are used world-wide as low calorie sweeteners by patients affected by diseases linked to the consumption of sugar, e.g. diabetes, hyperlipemia, caries, obesity etc. but they have side effects such as psychological problems, mental disorders, bladder cancer, heart failure and brain tumors [3-7]. Sweet proteins have the potential to replace these artificial sweeteners, by acting as natural, good, low calorie sweeteners, as we know that proteins do not trigger a demand for insulin in these patients whereas sucrose does.
In humans, the sweet taste is mainly due to the recently discovered T1R2-T1R3 receptor [8-10], two of the three members of the T1R class [8-10] of taste-specific proteins hypothesized to function in combination as a heterodimer. The human T1R2-T1R3 receptor recognizes natural and synthetic sweetness and T1R1-T1R3 recognizes umami taste [11,12]. So far there are seven known sweet and taste-modifying proteins, namely Brazzein [13], Thaumatin [14], Monelin [15], Curculin [16], Mabinlin [17], Miraculin [18] and Pentadin [19]. Properties and characteristics of these proteins are illustrated in Table 1. The key residues on the protein surface responsible for biological activity have not yet been identified with certainty for any of these proteins [20]. Monellin was found to be 100000 times sweeter than sucrose on a molar basis [21], followed by Brazzein and Thaumatin which are 500 times [13] and 3000 times sweeter then sucrose [14] respectively (the latter two on a weight basis). All of these proteins have been isolated from plants that grow in tropical rainforests. Although most of them share no sequence homology or structural similarity, Thaumatin shares extensive homology with certain non-sweet proteins found in other plants [15].
The potential industrial applications of these proteins are the low calorie sweetener industry and the cola, snacks, food and chocolate industries.
Brazzein
Brazzein is the smallest, most heat-stable [13] and pH-stable member of the set of proteins known to have intrinsic sweetness. The protein, consisting of 54 amino acid residues, is reported to be between 500 and 2000 times sweeter than sucrose [22] and represents an excellent alternative to available low calorie sweeteners. It was originally isolated from the fruit of an African plant Pentadiplandra brazzeana Baillon [23]. Heat and pH stability of the protein make it an ideal system for investigating the chemical and structural requirements of a sweet-tasting protein. Based on the wild-type brazzein, 25 mutants were produced to identify critical regions important for sweetness. To assess their sweetness, psychophysical experiments were carried out with 14 human subjects. First, the results suggest that residues 29–33 and 39–43, plus residue 36 between these stretches, as well as the C-terminus are involved in the sweetness [24]. Second, charge plays an important role in its interaction with the sweet taste receptor [24].
Thaumatin
The thaumatins are a class of intensely sweet proteins isolated from the fruit of the tropical plant Thaumatococcus danielli. The protein crystallizes in a hexagonal lattice after a temperature shift from 293 to 277 K. The structure has been solved at 1.6 Å resolution. Its fold was found to be identical to that found in three other crystal forms grown in the presence of crystallizing agents of differing chemical natures [25]. It consists of 207 amino acid residues with eight intramolecular disulfide bonds and contains no free cysteine residues. It aggregates upon heating at pH 7.0 above 70 degrees C, whereupon its sweetness disappears [26,27]. The protein is approximately 10000 times sweeter than sugar on a molar basis [28]. It is a protein that tastes intensely sweet only to Old World monkeys and to higher primates, including man [29], as it has been found that the protein binds to certain elements in taste pores of Rhesus monkey foliate papillae [30]. Thaumatin has been approved for use in many countries as both a flavor enhancer and a high-intensity sweetener [31].
Monellin
Monellin, a sweet protein, consists of two noncovalently associated polypeptide chains, an A chain of 44 amino acid residues and a B chain of 50 amino acid residues [32]. The protein can be purified from the fruit of Dioscoreophyllum cumminsii grown in West Africa and is approximately 100,000 times sweeter than sugar on a molar basis and several thousand times sweeter on a weight basis [28]. Single-chain monellin (SCM), which is an engineered 94-residue polypeptide, has proven to be as sweet as native two-chain monellin, and is more stable than the native monellin at high temperature and in acidic environments [33]. Native monellin is relatively sensitive to heat or acid treatment, which may cause separation of the sub-units and denaturation of the protein. Despite misgivings about the stability of the protein to heat and acid, downstream processes have been established. Its D-enantiomer has been crystallized and analyzed by X-ray crystallography at 1.8 Å resolution. Two crystal forms (I and II) were found under crystallization conditions similar, but not identical, to the crystallization conditions of natural L-monellin [34]. One NMR study of a non-sweet analog in which the AspB7 of protein was replaced by AbuB7 (L-2-Aminobutylicacid), showed similar 3-dimensional structures of these two proteins, indicating that the lack of the beta-carboxyl group in the AbuB7 analog is responsible for the loss of sweetness [35]. Recent research on identifying binding sites on the receptor by means of structure-taste relationships, found that four monellin analogues, [AsnA16]-, [AsnA22]-, [GlnA25]-, and [AsnA26]-monellin were 7500, 750, 2500, and 5500 times as sweet as sucrose on a weight basis, respectively. Thus, among them, [AsnA22]-monellin and [GlnA25]-monellin were less sweet than the native monellin [36].
Curculin
Curculin which is extracted from Curculigo latifolia acts as a good low calorie sweetener. Its maximum sweetness is equal to 0.35 M of sucrose. It has taste modifying abilities since water and sour substances elicit a sweet taste after consumption of curculin [37]. There is no other protein currently available with both sweet taste and taste modifying abilities [38]. The taste modifying activity of the protein (discussed below) remains unchanged when it is incubated at 50°C for 1 hr between pH 3 and 11 [39].
The molecular weight of Curculin was determined by low angle laser light scattering and was found to be 27800 [38]. Its three-dimensional model has been built from the X-ray coordinates of GNA, a mannose-binding lectin from snowdrop (Galanthus nivalis) [38]. The three mannose-binding sites present in GNA were found in curculin but were not functional. Some well exposed regions on the surface of the three-dimensional model of the said protein could act as epitopes responsible for the sweet-tasting properties of the protein [40]. The protein can be crystallized by the vapor diffusion method using polyethylene glycol 400 as a precipitant. The crystals belong to orthorhombic space group P2(1)2(1)2(1) with unit cell dimensions: a = 105 Å, b = 271 Å, c = 48.7 Å. The crystals diffract X-rays to resolution of 3.0 Å and are suitable for X-ray crystallographic studies [41].
Mabinlin
Mabinlin is a sweet protein with the highest known thermostablility [42]. It is derived from Capparis masaikai and its sweetness was estimated to be around 400 times that of sucrose on weight basis. It consists of an A chain with 33 amino acid residues and a B chain composed of 72 residues. The B chain contains two intramolecular disulfide bonds and is connected to the A chain through two intermolecular disulfide bridges [43]. Its heat stability is due to the presence of these four disulfide bridges [44]. The sweetness of Mabinlin-2 is unchanged after 48 hr incubation at boiling point [17]and of Mabinlin-3 and -4 are unchanged after 1 hr at 80°C [45].
Miraculin
Miraculin is a taste-modifying protein that belongs to the class of sweet proteins. It is extracted from Richadella dulcifica an evergreen shrub native of West Africa. The protein is a single polypeptide with 191 amino acid residues [46]. It modifies the sweet receptor in such a way that it can be stimulated by acid [47]. Thus, miraculin has the unusual property of modifying sour taste into sweet taste [46].
Taste-modifying protein modifies the sweet taste receptor on binding and this behavior of these proteins is responsible for modification in taste of sour substance [46,47]. All acids (which are normally sour) taste sweet after consumption of these proteins. The effects of these proteins exist for around half an hour after consumption and intake of any sour substance will therefore taste sweet during this period of time. The taste buds come to there normal state with time.
Pentadin
Pentadin is a sweet protein extracted from the plant Pentadiplandra brazzeana, a shrub found in tropical forests of a few African countries. Not much information is available about the protein despite its isolation several years ago, in 1989 [48]. The protein was reported to be around 500 times sweeter then sucrose on a weight basis. It also consists of subunits coupled by disulfide bonds [49].
Interaction of sweet proteins with their receptor
Humans detect taste with taste receptor cells. These are clustered in taste buds. Each taste bud has a pore that opens out to the surface of the tongue enabling molecules and ions taken into the mouth to reach the receptor cells inside. There are five primary taste sensations salty, sour, sweet, bitter and umami. Sweet and umami (the taste of monosodium glutamate) are the main pleasant tastes in humans. T1Rs are mammalian taste receptors that assemble two heteromeric G-protein-coupled receptor complexes T1R1+T1R3, an umami sensor, and T1R2+T1R3, a sweet receptor [50].
Sweet and taste-modifying proteins interact with the T1R2-T1R3 receptor with a different mechanism compared to small molecular weight compounds [51]. Recently, it has been shown that the T1R2-T1R3 receptor has many characteristics similar to the mGluR [52], apart from some minor differences in the active site region.
The major work by Kunishima et al. [52] solving the crystal structure of the N-terminal active site region of the subtype 1 of mGluR both free and complexed with glutamate has helped a lot in understanding the mechanism of interaction between ligand and T1R2-T1R3 receptor. Their structural work on mGluR and its N-terminal domain [52,53] showing considerable conformational change induced by the glutamate complexation. The 'Active' and 'resting' conformations of m1-LBR, an extracellular ligand binding region of mGluR, is modulated by the dimer interface. The protomer can form 'open' or 'closed' confirmations and is made up of two domains namely LB1 and LB2. The population of active conformers depends on ligand binding, i.e. the so called 'closed-open_A'. The ligand-free receptor exists as two different structures, free form I (open-open_R), the 'resting' conformation with two open protomers and free form II (closed-open_A), nearly identical to the complexed form (Figure 1, references 52, 54). The mechanism suggested by these structures is that the receptor is in dynamic equilibrium, and that ligand binding stabilizes the 'active' dimer. There are thus two ways, in principle, to activate the receptor: first, to complexate form I with the proper ligand (glutamate for the mGluR, aspartame or any other small molecular weight sweetener for the T1R2-T1R3 receptor) and second, by shift the equilibrium between free form I and free form II in favor of free form II.
The exact mechanism of interaction of sweet proteins with the T1R2-T1R3 sweet taste receptor has not yet been elucidated [51]. Low molecular mass sweeteners and sweet proteins interact with the same receptor, the human T1R2-T1R3 receptor[52]. Studies have shown that the T1R3 receptor protein is encoded by the Tas1r3 gene involved in transduction of sweet taste [55].
Recently it has been found that T1R3-independent sweet- and umami-responsive receptors and/or pathways also exist in taste cells [56].
Conclusion and scope of further work
As it has been found that sweet proteins are thousands of times sweeter than sucrose and are of low calorie value, these proteins can be used as natural low calorie sweeteners by people suffering from diseases linked to consumption of sugar e.g. obesity, diabetes and hyperlipemia.
Candidate proteins can be checked for biological activity with the human taste receptor. Also mutations can be induced in candidate sweet proteins to analyze changes in their physical, chemical and biological properties. The work can be taken forward by solving the structures of the proteins and taste receptors with a view to increasing the efficiency of these sweeteners.
Acknowledgments
I would like to thank Prof. S. Ramakumar, Chairman, Bioinformatics Center, Indian Institute of Science, Bangalore for useful discussions and valuable suggestions. Access to the Bioinformatics Centre and other facilities funded by the Department of Biotechnology (DBT) is gratefully acknowledged. Also, Dr. Gayatri Saberwal, Institute of Bioinformatics and Applied Biotechnology, Bangalore for her support in writing the paper. Sincere thanks to Prof. Manju Bansal, Director, IBAB, Prof. N. Srinivasan, Molecular Biophysics Unit, Indian Institute of Science, Mr. Shashi Kant, Hannover Medical Institute, Germany and Mr. Mohan Babu, Department of Botany, Bharathiar University for their feedback and support.
Figures and Tables
Figure 1 Diagrammatic representation of the T1R2-T1R3 receptor showing possible stabilization by binding of a sweet protein to a secondary binding site on the surface of free form II. The sweet protein is represented in red on the left part of free form II, preventing it reverting to free form I. (adapted from references 52 and 54)
Table 1 Comparison of thaumatin, monellin, mabinlin, pentadin, brazzein, curculin and miraculin.
Thaumatin Monellin Mabinlin Pentadin Brazzein Curculin Miraculin
Source Thaumatococcus danielli Benth Dioscoreophyllum cumminsii Diels Capparis masakai Levl Pentadiplandra brazzeana Baillon Pentadiplandra brazzeana Baillon Curculingo latifolia Richadella dulcifica
Geographic distribution West Africa West Africa China West Africa West Africa Malaysia West Africa
Variants I, II, a, b, ca - I, II- a, III, IVa - - - -
Sweetness factor (weight basis) 3000 3000 100 500 2000 550 -
Molecular mass (active form, kDa) 22.2 10.7 12.4 12.0b 6.5 24.9 98.4
Amino acids 207 45 (A chain)
50 (B chain) 33 (A chain)
72 (B chain) ? 54 114 191
Active form Monomer Dimer (A + B) Dimer (A + B) ? Monomer Dimer (A + A) Tetramer (A+A+A+A)
Source: Adapted from Kurihara (1994). aAt least five different forms of thaumatin (Lee et al., 1988) and four different forms of mabinlin (Nirasawa et al., 1994) have been identified. bA chromatographic fraction containing a 12-kDa protein was sweet. This same fraction, when subjected to electrophoresis under non-reducing conditions showed bands in the region between 22 and 41 kDa, suggesting the presence of subunits.
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| 15705204 | PMC549513 | CC BY | 2021-01-04 16:36:26 | no | Respir Res. 2005 Feb 10; 6(1):16 | latin-1 | Respir Res | 2,005 | 10.1186/1465-9921-6-16 | oa_comm |
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Malar JMalaria Journal1475-2875BioMed Central London 1475-2875-4-91570307210.1186/1475-2875-4-9Case ReportNosocomial Plasmodium falciparum infections confirmed by molecular typing in Medellín, Colombia González Lina [email protected] Jesus [email protected] Liliana [email protected] Marta [email protected] Eliana [email protected] Silvia [email protected] Amanda [email protected] Grupo Malaria, Facultad de Medicina, Universidad de Antioquia, Calle 62 #52-59, Lab 610, Medellin, Colombia2 Hospital A, Medellin, Colombia2005 9 2 2005 4 9 9 30 11 2004 9 2 2005 Copyright © 2005 González et al; licensee BioMed Central Ltd.2005González 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 cases of nosocomial malaria are reported from patients of the Internal Medicine Ward of a tertiary University teaching hospital in Medellin, Colombia. Epidemiological research, based on entomological captures, medical records review and interviews of nursery staff about patient care practices potentially involving contact with blood, were carried out. Molecular characterization of Plasmodium falciparum was based on the amplification of MSP1, MSP2 and GLURP genes. This method enabled confirmation of the same P. falciparum genotype in all three patients as well as in a fourth one (index case). The presence of nosocomial malaria was confirmed and it was concluded that the most likely source of transmission was through multi-dose preparations of heparin applied to heparin locks.
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Background
The city of Medellin is located in the north-western region of Colombia and, although malaria is endemic in the country, absence of anophelines within the city makes vector transmission of the infection impossible. However, this city, located within the Andes Mountains (6°13'N, 75°36'W) at 1,588 m above sea level (a.s.l.), is surrounded by highly endemic regions and imported cases are often referred to the University hospital for treatment. Here, three cases of nosocomial malaria, which occurred in hospitalized patients in the Internal Medicine Ward of Hospital A, are described. These patients were being treated for diverse conditions and they shared the hospital facilities during different periods. One of these patients was in the Emergency Ward at the same time as a Plasmodium falciparum-infected patient.
In order to confirm an association between all the cases, P. falciparum genomic DNA was amplified using specific primers for polymorphic streches of Merozoite Surface Antigen-1 (MSP-1), Merozoite Surface Antigen-2 (MSP-2) and Glutamate Rich Protein (GLURP), and the profile observed among the different isolates was compared.
Case presentations
Patient 1. Index case
A 23-year-old male woodcutter, resident in Vigia del Fuerte (6.35N, 76.53W), was referred to the hospital on 11 April 2001, diagnosed with yellow fever. Vigia del Fuerte is a highly endemic malaria region located in the Atrato River basin with a mean Annual Parasite Index (API) of 72.6 during the past five years. The patient presented 15 days with fever, headache, chills, jaundice, arthralgia, melena, dark urine and bilious vomiting. He was given a heparin lock for administration of I.V. treatment. The patient deteriorated throughout the night and died before thick smear results were available. Peripheral blood thin and thick smears confirmed the presence of P. falciparum asexual forms (>100,000 per μl). A post-mortem confirmed as cause of death complicated malaria. Dengue and yellow fever IgM antibodies were absent. The patient remained in the emergency ward for 18 hours prior to his death.
Patient 2
A 19 year-old male, unemployed, resident in Angelopolis (Antioquia, 6.06°N 75.42°W), a non-malarious area, located 1,900 m a.s.l., attended the emergency service of the hospital on 10th April 2001, and remained there for 24 hours before being transferred to the Internal Medicine Ward with diagnosis of systemic lupus erythematosus (SLE). In addition to symptoms and signs of SLE, he presented fever on 23 April, and received treatment with fenitoin, dipirone, ampicillin, ranitidine, ceftriazone, methilprednisolone, oxacillin, amikacin and enoxaparine (via an heparin lock). As part of the treatment for his condition, he was administered chloroquine 150 mg daily from 24th April 2001. He was discharged on 19th May 2001. Then, on 6th June 2001, he was hospitalized with a diagnosis of a febrile syndrome. P. falciparum malaria was confirmed on 20th June 2001 after observation of the parasite in a blood cell count. A thick smear revealed the presence of 14,440 asexual forms per μl in peripheral blood. The patient was administered quinine and sulphadoxine-pyrimethamine with good treatment response.
Patient 3
A 46 year-old male, unemployed, resident of Santa Barbara (Antioquia, 5.57°N 75.91°W), a non-malarious area located 1,800 m a.s.l., was hospitalized in the Internal Medicine Ward on 8th May with diagnosis of status asthmaticus. He was administered aminophyllin, hydrocortisone, ranitidine, enoxaparine (via a heparin lock) and was discharged on 15th May 2001. He returned to the hospital on 5th June 2001 complaining of fever, chills and adynamia and was admitted with diagnosis of toxic hepatitis due to the presence of dark urine, jaundice and hepatomegaly. On 6th June 2001, diagnosis of complicated malaria was confirmed by observation of the parasite in a blood cell count. Later, the presence of 87,500 trophozoites of P. falciparum per μl was confirmed by a thick smear. He received treatment with quinine, sulphadoxine-pyrimethamine and was discharged on June 23rd 2001
Patient 4
A 41 year-old male, flower-grower, resident of El Carmen del Viboral (Antioquia, 6.09°N 75.34°W), a non-malarious area located 2,150 m a.s.l.., was admitted directly to the Internal Medicine Ward of the hospital on 7th May 2001 with superior vena cava syndrome (100% obstruction) and was applied a heparin lock for administration of I.V treatment. The patient was diagnosed with a mediastinal mass, compatible with lymphoma, and received treatment with dexametasone (I.V.) and radiotherapy. On June 9th 2001, he evidenced fever and on 9th June 2001, he was diagnosed as complicated malaria by a cell blood count. A thick smear confirmed the presence of 166,440 asexual forms of P. falciparum per μl. He received treatment with quinine, sulphadoxine-pyrimethamine with good treatment response. However, on 1st July 2001, he died as a consequence of multiple non-malaria related complications.
Entomological captures
Search for Anopheles was carried out by expert personnel from the Secretariat of Health, both within the ward and in the surrounding gardens, around the time of malaria diagnosis of patients 2 and 4. These confirmed the absence of the vector in the hospital area.
Molecular analysis
P. falciparum genomic DNA was extracted from whole blood collected onto filter paper or from paraffin embebbed brain tissue (for the index case). Paraffin was removed from post-morten material using xylene, followed by 2 washes with 100% ethanol. DNA was isolated by proteinase K digestion, followed by four rounds of phenol-chloroform extraction. Purified DNA was stored at -20°C until amplification.
The Region 2 of MSP-1 and the central region of MSP-2 were amplified by a nested Polymerase Chain Reaction (PCR); the region RII of GLURP was amplified by a semi-nested PCR [1]. Products obtained after the first PCR were amplified using specific primers for region 2 of MSP-1 corresponding to MAD20, K1 and RO33 allelic families, and FC27 and IC-1 for the central region of MSP-2. Briefly, PCR was carried out in a total volume of 20 μL, containing 10 mm Tris-HCl (pH 9,0 at 25°C), 50 mm KCl and 0,1% Triton X-100, 125 mM dNTPs, 0,4 units Taq DNA polymerase (Promega, Madison, WI), 1,6 mM MgCl2 and 125 nM of each primer. Initial denaturation was 5 min at 95°C, 1 min at 94°C, 2 min at 58°C annealing (all first PCR reactions and second reaction for GLURP) or at 61°C (for all the second reactions of MSP-1 and 2). This was followed by extension for 2 minutes at 72°C. This first reaction underwent 25 amplification cycles and the second 30 cycles. Positive (strains HB3, K1 and RO33) and negative controls (healthy individuals), were included.
Products were electrophoresed on an agarose (MetaPhor) gel (2,5% for MSP-1 and 2% for MSP-2 and GLURP), stained with ethidium bromide and visualized under ultraviolet light. Size analysis of the amplified fragments revealed identical pattern distribution for all the examined markers assayed, confirming the presence of P. falciparum infection by matching strains in all 4 patients (Fig 1).
Figure 1 Dates, chronology of exposure, place of contact and time of malaria diagnosis of the index case and the 3 patients with nosocomial malaria. Each bar represents the location of each patient during the stay at the hospital.
Conclusions
The presence of P. falciparum malaria infection in three patients without history of malaria or travel to malaria-endemic regions is described. The first of these patients (Patient 2) shared the Emergency Ward with a fatal case of falciparum malaria. The incubation period for this nosocomial infection was 12 days, however, since he was administered high doses of chloroquine, fever receded for about two weeks. Resistance of P. falciparum to chloroquine is highly prevalent in the Antioquia region [2], this explains the lack of efficacy of the antimalarial in eradicating parasites in this patient.
Patient 2 shared the Internal Medicine facilities with patients 3 and 4 at least for one week during May. Patient 3 evidenced an incubation period of 22 days, while in Patient 4 this was 26 days.
Since patients 3 and 4 had no contact with the index case, further analysis of the incubation periods allowed us to conclude that transmission occurred from index case to patient 2 and the latter was the source of infection for patients 3 and 4. This means that at least 2 separate episodes of contamination were involved in transmission to the different patients (see figure 2). Since entomological captures were negative for vectors and Medellin is not an area of vector transmission for malaria, parenteral contamination might be the most likely mechanism of transmission. None of the patients was administered blood before diagnosis of malaria, but all of them had at least one heparinized lock during their stay either in the Emergency or in the Internal Medicine Ward.
Figure 2 Agarose gel electrophoresis showing the size of the amplified products of the genes MSP-1 (panel A), MSP-2 (panel B) and GLURP (panel C). MW represents the molecular weight marker,(-) a negative control and (+) a positive control. The numbers are equivalent to the case number. Panel A corresponds to allelic family MAD-20 of MSP-1 showing amplification products of ~150 bp in the cases, panel B corresponds to allelic family IC50 showing amplification products of ~450 bp in the cases, panel C corresponds to GLURP showing amplification products of ~700 bp in the cases.
Transmission of malaria via heparin locks has been reported previously by other authors, the source of contamination was a multidose heparin container [3]. Although the practice of multiple dose preparations of heparin into large volume syringes to be distributed among the several patients of the ward is forbidden at this tertiary institution, it has been difficult to eradicate due to the high volume of patients and the limited economical resources of the hospital.
Other researchers have reported on the use of molecular typing of P. falciparum to confirm nosocomial transmission of malaria [4]. Genotyping of all 4 cases confirmed the epidemiological suspicion of nosocomial transmission. Considering the previous report on the limited genetic polymorphism of P. falciparum observed in the Antioquia region [5], the presence of an identical genotype of P. falciparum among unrelated parasites may be possible, but unlikely, since examination of these 3 different genes has been routinely used to discriminate unrelated parasites [6]. Moreover, the molecular findings together with the epidemiological characteristics contribute to confirm nosocomial transmission of the infection.
These observations are of major relevance to sanitary and health authorities, since they confirm the importance of biosafety during minor procedures, such as application of heparin to peripheral locks. In addition, it highlights the need to rule-out malaria infections in all febrile patients sharing hospital facilities with malaria patients as well as in those not responding as expected to antimicrobial therapy.
Authors' Contributions
GL was involved in the review of clinical records, staff interviews and preparation of the manuscript. OJ coordinated the epidemiological and entomological researches. FL coordinated the microscopy diagnosis and following of the patients. AM participated on the epidemiological research. RE carried out the molecular analysis of the samples. BS, the Grupo Malaria leader, participated in the treatment and following of the patients. MA attended the patients, coordinated the clinical and molecular aspects of the research and prepared the manuscript.
Acknowledgements
The authors are grateful do Dr Mary Ruth Brome for helping to recover pathology material.
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Kirchgatter K Wunderlich G Branquinho MS Salles TM Lian YC Carneiro-Junior RA Di Santi SM Molecular typing of Plasmodium falciparum from Giemsa-stained blood smears confirms nosocomial malaria transmission Acta Trop 2002 84 199 203 12443798 10.1016/S0001-706X(02)00181-X
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Viriyakosol S Siripoon N Petcharapirat C Petcharapirat P Jarra W Thaithong S Brown KN Snounou G Genotyping of Plasmodium falciparum isolates by the polymerase chain reaction and potential uses in epidemiological studies Bull World Health Organ 1995 73 85 95 7704931
| 15703072 | PMC549514 | CC BY | 2021-01-04 16:37:31 | no | Malar J. 2005 Feb 9; 4:9 | utf-8 | Malar J | 2,005 | 10.1186/1475-2875-4-9 | oa_comm |
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Harm Reduct JHarm Reduction Journal1477-7517BioMed Central London 1477-7517-2-11570308210.1186/1477-7517-2-1ResearchThe epidemiology of college alcohol and gambling policies Shaffer Howard J [email protected] Anthony N [email protected] Richard A [email protected] Rachel C [email protected] Debi A [email protected] Harvard Medical School, Division on Addictions, The Landmark Center, 401 Park Drive, 2nd Floor East, Boston, MA 02215, USA2005 9 2 2005 2 1 1 13 10 2004 9 2 2005 Copyright © 2005 Shaffer et al; licensee BioMed Central Ltd.2005Shaffer 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 article reports the first national assessment of patterns of drinking and gambling-related rulemaking on college campuses (e.g., punitive versus recovery oriented). Analyses relating school policies to known school rates of drinking or gambling identified potentially influential policies. These results can inform and encourage the development of guidelines, or "best practices," upon which schools can base future policy.
Methods
The college policy information was collected from handbooks, Web sites and supplemental materials of 119 scientifically selected colleges included in the fourth (2001) Harvard School of Public Health College Alcohol Study (CAS). A coding instrument of 40 items measured the scope and focus of school alcohol and gambling policies. This instrument included items to measure the presence of specific policies and establish whether the policies were punitive or rehabilitative. A total of 11 coders followed a process of information extraction, coding and arbitration used successfully in other published studies to codify policy information.
Results
Although all schools had a student alcohol use policy, only 26 schools (22%) had a gambling policy. Punitive and restrictive alcohol policies were most prevalent; recovery-oriented policies were present at fewer than 30% of schools. Certain alcohol and gambling policies had significant relationships with student binge drinking rates.
Conclusions
The relative lack of college recovery-oriented policies suggests that schools might be overlooking the value of rehabilitative measures in reducing addictive behaviors among students. Since there are few college gambling-related policies, schools might be missing an opportunity to inform students about the dangers of excessive gambling.
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Background
Young people are at increased risk for alcohol- and gambling-related problems compared to their older counterparts [1-3]. College and university students are at special risk because going to college often represents the first move away from their family and, as a result, fewer restrictions on their activities. (Because universities are by definition comprised of colleges, all institutions of higher learning henceforth will be referred to as "colleges.") In the United States, each year approximately 1.2 million freshmen enter four-year colleges [4]. Some of these freshmen enter college actively involved in recovery programs for alcohol abuse or other addictive behaviors (e.g., illicit drug abuse or gambling). Others will begin a program of recovery for addiction problems that started after they enrolled at school. The college years are a time of developmental transition for most students; like other life transitions, the college experience can be associated with increased risk for a variety of psychosocial problems.
The problems associated with addictive behaviors on college campuses have been well documented (e.g., academic difficulties, psychosocial problems, traumatic injuries, overdoses, high-risk sexual behavior, and impaired driving) (e.g., Wechsler et al. 2000 [5], Wechsler et al. 2002 [6]). Despite a recent increase in college-based preventative measures (e.g., alcohol education programs, advertising restrictions, alcohol-free dormitories, policy controls), research reveals that addiction-related problems continue to plague college campuses. For example, during the past decade, past-year alcohol use and binge drinking rates have remained steady at approximately 81% and 44%, respectively [6], and alcohol-related problems have been on the rise. Wechsler et al. (2002 [6]) found that a greater percentage of students who had used alcohol in the past 30 days were involved in police-related incidents in 2001 than in 1993 (6.5% vs. 4.6%); the same was true of alcohol-related injuries (12.8% vs. 9.3%). Wechsler et al. (2002) also identified a significant increase in the rate of students riding in motor vehicles with alcohol-impaired drivers in 2001 compared to 1993 (23.2% vs. 18.4%). These findings highlight the need for college administrators to reconsider current preventative measures and develop and implement more effective methods for preventing and reducing alcohol use. For example, college health programs might be able to limit or reduce alcohol-related harms on college campuses by implementing and enforcing policies that support recovery-oriented and other programs that discourage substance misuse.
The creation and implementation of college alcohol and gambling policies is far from an exact science. Currently, there are no standardized scientific guidelines for the creation of school policy directed toward alcohol and other potentially addictive behaviors (e.g., gambling). However, science can contribute to the creation of successful policy. Recognizing the important role that science can play in the development and evaluation of public policy, the federal government recently released draft "regulatory science" guidelines [7]. The Office of Management and Budget (OMB) intends these guidelines to direct and inform public agencies in the creation and implementation of effective and targeted regulations. Science-based guidelines also could prove useful to policymaking on college campuses; however, as the results of this study will reveal, college administrators do not use empirical evidence to guide the development and implementation of student substance use and gambling regulations. This situation has led to disjunctive policy strategies among U.S. colleges.
The purpose of this study is to encourage the development of science guided school policy. To accomplish this goal, we will examine the prevalence and characteristics of alcohol- and gambling-related policies, including policy provisions for student recovery, in a scientifically selected sample of U.S. colleges. We will not include illicit drug policies in this analysis because illicit drug use is illegal for both adults and young people; these illegal behaviors fall under the purview of state and federal law that supersedes college policy. Our intent is to examine college policies that focus on legal activities. Therefore, using college alcohol and gambling policies, binge drinking rates and gambling frequency as evidence, this report describes the epidemiology (e.g., prevalence) and influence of these assorted policies.
Filling the Policy Void: A Federal Drug and Alcohol Initiative
During 1989, the federal government initiated basic alcohol and substance abuse education requirements. Previously, there was not a regulatory mandate obligating institutions of higher learning to set alcohol or drug use policy or bring students' attention to these rules if they existed. Schools also were not required to disseminate substance use policy information to parents or other interested parties. This situation changed with the passage of the federal Drug-Free Schools and Communities Act (DFSCA) of 1989.
The DFSCA applies to all U.S. colleges. The act specifies that "as a condition of receiving funds or any other form of financial assistance under any Federal program, an institution of higher education (IHE) must certify that it has adopted and implemented a drug [and alcohol] prevention program..."[8]. Thus, any U.S. college that does not maintain a drug and alcohol education program risks losing all of its federal funding. In addition, to fulfil DFSCA requirements and retain funding, schools must provide students with institutional standards of conduct that explicitly prohibit illicit drugs and illegal alcohol use, a description of potential legal and institutional sanctions for substance use violations, a description of health risks posed by drugs and alcohol, and a listing of available treatment options.
The Impact of Government Policy on College Campus Substance Use and Abuse is Unknown
The overall impact of mandated drug and alcohol programs is still unknown; as we noted before, there is some evidence that risky and addictive behaviors on college campuses are still prevalent despite targeted efforts by administrators to reduce student substance abuse [9,6]. Several studies have suggested that, despite prevention efforts, established norms of excessive drinking behavior and positive student attitudes regarding the effects of alcohol consumption continue to encourage alcohol consumption on college campuses [10,11]. The absence of universal standards governing the content of school policies on addiction might contribute to this problem. Although the DFSCA mandates that schools must make written drug and alcohol policy available to students on an annual basis, administrators at each institution still determine the content of such policy. Thus, the DFSCA mandates policy without establishing standards for content; as a result, administrative tolerance toward alcohol, drugs, and gambling can vary significantly from institution to institution.
The Potential Effect of Inconsistent College Policies
Inconsistent policy content among institutions can create a problematic state of affairs. Although DFSCA directives aim to increase awareness of the potential dangers of alcohol and drug use among students, numerous studies continue to identify high levels of alcohol abuse on U.S. college campuses in recent years [9,12-14,6]. Heavy episodic drinking adversely affects not only those students who actively participate, but also those who do not: one study identified non-heavy drinkers on heavy drinking campuses as 3.6 times as likely to experience at least one problem from another student's drinking as non-heavy drinkers on non-heavy drinking campuses [15].
Even though individual colleges have adopted different strategies for reducing the problems associated with excessive alcohol consumption, the extent and effect of these efforts are largely unknown. One approach, perhaps in response to DFSCA, has been to develop and enforce policies on student substance abuse and recovery. Although recent psychosocial programs attempting to reduce student drinking behaviors have failed to reduce binge drinking [6], official school policies on substance abuse and recovery hold the potential to reduce students' alcohol use and the multitude of consequential problems associated with drinking excessively. This potential, however, is likely contingent upon policy content: because there are few federal regulations governing the content of alcohol policies at institutions of higher learning, every college develops unique strategies of combating potentially addictive behaviors. To date, no studies have examined the policy content of a representative sample of colleges in the attempt to identify the effects of these policies on levels of alcohol and gambling involvement among students.
Policy and Recovery
Students who seek help for alcohol or other substance use problems are faced with a multitude of school-provided and external treatment options. Addiction recovery programs are diverse, ranging from formal treatment programs (e.g., inpatient medical treatment and outpatient psychotherapy) to less formal self-help options, (e.g., 12-step fellowships) [16]. Regardless of the selected type of treatment, attention to recovery from addiction requires significant time and determination, which can disrupt a schedule of college studies. Twelve-step programs, for example, usually involve attending regular, perhaps even daily meetings. Formal treatment programs frequently demand an even greater level of time commitment: in-patient detoxification or other residential care can remove students from the academic environment altogether. Mandatory abstinence, required by most treatment programs, poses an additional hurdle to treatment-seekers. Students, with their busy and often stressful schedules, undoubtedly face additional challenges in participating in recovery activities; academic and administrative policies that accommodate flexible scheduling will likely assist students seeking recovery, and policies that do not might complicate or inhibit students' recovery efforts.
College Binge Drinking and School Policy
Binge drinking, the consumption of five or more alcoholic drinks (four or more for women) on at least one occasion at one to two week intervals [12], has been unaffected by prohibitive and punitive college policies. To illustrate, on one college campus that prohibited all alcohol use in its residence halls, there was virtually no difference in the binge drinking rate among students living within areas regulated by the alcohol policy (35%) compared to those living outside the jurisdiction of the alcohol policy (34%) [17]. Although school policy (or the lack thereof) is not the only factor that affects binge drinking rates – promotions aimed at students, cheap alcohol prices at surrounding establishments and high numbers of on- and off-campus drinking venues have been found to significantly increase student binge drinking [18] – placing special emphasis on the enforcement of substance abuse policies can garner positive results. For example, Knight (2003)[19] found that, although the effect of policy was diluted by considerable variation in policy content among public colleges in a state-wide system, increased enforcement (i.e., application of policy consequences) of alcohol policies aimed at combating underage drinking did result in decreased alcohol consumption among students. Beneficial effects resulting from the enforcement of existing rules, however, can be difficult to interpret. For example, in that study, it is unclear whether the enforcement of rules encouraged lower levels of drinking or entry to treatment for intemperate drinking or, alternatively, simply forced problematic drinkers to withdraw from school.
College Gambling and School Policy
Some research suggests that gambling on college campuses is commonplace. A study of student gambling at six colleges in five different states (i.e., New York, New Jersey, Nevada, Oklahoma, and Texas) showed that of 1,771 surveyed students, 23% reported that they gambled at least weekly (ranging from 11% in Texas to 39% in Nevada) [20]. In that study, students reported whether they had ever experienced gambling-related problems as identified by the South Oaks Gambling Screen (SOGS) [21]. Of the total student sample, 5.5% were classified as lifetime probable pathological gamblers. The prevalence of lifetime pathological gamblers among these students ranged from 4% in Nevada to 8% in New York. A recent report [22] of a four-campus Connecticut college system reported a similar SOGS-based prevalence estimate of probable pathological gamblers (i.e., 5.2%).
For comparison, the National Gambling Impact Study Commission (NGISC) considered the adult rates of lifetime pathological gambling from four sources [3]. The lowest rates were 0.8% for both the University of Michigan [23] and National Opinion Research Center [24] studies; the largest (i.e., 1.5% – 1.6%) were from aggregated statistics of previously published research conducted by the National Research Council [25] and the original analysis of the same studies by the Harvard Medical School [26]. This meta-analysis included 14 SOGS-based studies of disordered gambling among college students and indicated that the lifetime prevalence of pathological gambling among college students was 5.1% [26]. An update of this meta-analysis expanded the number of student studies to 19 and increased the prevalence estimate to 5.6% with a 95% confidence interval of 3.5% to 7.6% [1]. Based on 66 studies of the general household population in various areas (i.e., states), this estimate of the proportion of college students with gambling disorders was three times the adult rate (1.9%).
Other research contradicts the findings that college students are at elevated risk for problem gambling compared to the general adult population. For example, a recently published longitudinal study of students at the University of Missouri-Columbia showed markedly lower prevalence rates than the studies summarized above [27]. In this longitudinal study, no student met the traditional criteria for problem or pathological gambling. Further, the authors note that, "there were too few participants endorsing multiple gambling problems at a single time point to obtain an adequate sample size of affected individuals for most analyses" (Slutske et al. 2003[27] p. 265). Overall, 3% of these students endorsed a single problem at any point during their lifetime due to gambling; one student endorsed two problems and all of the others reported never having had a problem due to gambling. At the next interview three years later, when most subjects were seniors, the subjects reported more symptoms; but only one subject (i.e., 0.2% of the sample) endorsed enough symptoms to meet the diagnostic criteria of the American Psychiatric Association [28] for lifetime pathological gambling. This evidence indicates that gambling behavior among students and its adverse consequences fluctuates with time and other factors and that the development of symptoms is not always progressive. Further, the Slutske results show that most adverse effects of student gambling remain sub-clinical, making this pattern more responsive to interventions than longer standing, more entrenched clinical disorders. Taken together, this evidence suggests that comprehensive college gambling policies might have the capacity to reduce the adverse consequences that can be associated with student gambling.
Despite the frequency with which college students engage in gambling activities, some evidence suggests that administrators are unaware of the dangers associated with excessive gambling among students; in addition, colleges do not have adequate policies addressing gambling [29]. This situation prompted Shaffer to suggest that the government convene "a consortium of college presidents to review their existing gambling related policies and problems so that we can take a systematic approach to the education, prevention and treatment of America's young people, who are at higher risk for gambling related disorders than their adult counterparts"[30]. Although this consortium has not yet been assembled, research confirms that college students continue to view gambling as a legitimate form of entertainment; for example, 42% of a scientifically selected sample having gambled at least once in the last year [31]. Unlike drug and alcohol education (i.e., DFSCA), there is no federal mandate requiring schools to educate students or parents about the dangers of excessive gambling; combined with the lack of a policy response by administrators, this situation leaves an open door for student-related gambling disorders to emerge unchecked.
Assessing the Relationships between College Policies and Student Drinking and Gambling
This study is the first to identify patterns of drinking and gambling-related rulemaking on college campuses (e.g., punitive versus recovery oriented). By relating school policies to known school rates of drinking or gambling [31,6] we can identify potentially influential policies. These analyses can encourage and inform the development of guidelines, or "best practices," upon which schools can base future policy.
Hypotheses
Given the paucity of empirical college-based policy research, this study will fill an important gap in knowledge. To fill this void, this research will test a variety of addiction-related hypotheses that have not yet been examined empirically. Based upon the extant literature, this study will test the following four primary hypotheses:
• Because there are few requirements guiding the creation of school substance use and gambling policies, the content and clarity of these policies will be heterogeneous across schools and modes of policy distribution (e.g., handbooks vs. school Web sites);
• College alcohol policies currently devote relatively little attention to student recovery;
• Due to differences in enforcement, awareness of the dangers of excessive alcohol consumption, educational programs and types of students, schools with either no or only restrictive alcohol use policies will experience higher levels of binge drinking among students than schools with prohibitive and recovery-oriented alcohol policies;
• Absent a federal mandate that requires gambling-related regulations or education on college campuses, gambling policies will be less prevalent than alcohol use policies.
Methods
Procedure: Sample, Policy Eligibility and Policy Selection
The purpose of this study is to identify and assess alcohol and gambling policies among U.S. colleges. To ensure a representative national sample of colleges, we examined the scientifically selected sample of public and private American colleges that was used in a recent series of Harvard studies (e.g., Wechsler 2002 [6]). The detailed methods by which the previous study identified the sample are available elsewhere [6,12-14,31]. The potential sample consisted of 120 scientifically selected schools located throughout the nation; one school ceased operation before the start of the study, so 119 schools were eligible to be included in the final sample. We received human subjects approval for this study through the Harvard Medical School Office for Research Subject Protection. On February 14, 2003, the Human Subjects Committee at Harvard Medical School granted an exemption for the study entitled: United States College and University Addiction and Recovery Policies. The study qualified for exemption under 46 CFR §102(f) and the assurance identification number is M1240-01.
At the beginning of the project, we submitted an e-mail request for a hard copy of their student handbook to each school's admissions office. Each e-mail specified that we were interested in collecting school alcohol and gambling policies and requested that our inquiry be forwarded to the most appropriate school official. We gathered e-mail addresses for admissions offices from each school's official Web site. Using each school's main telephone number to initiate contact, investigators contacted schools that did not respond within thirty days to our e-mail request and verbally requested a handbook and any other existing alcohol and gambling policy materials. Typically, the person answering the call referred us to admissions offices, deans' offices, or student services offices for further assistance; we identified ourselves as calling from Harvard Medical School only when asked.
Policy Eligibility and Identification
Eligibility Criteria
To be eligible for inclusion in this study, each college policy had to meet the following five eligibility criteria:
1. the policy had to prohibit, govern, or otherwise attempt to regulate alcohol use or gambling among students at a U.S. college or university;
2. the policy had to be in effect (i.e., in the current handbook, Web site or supplementary materials);
3. the policy had to be readily available to the public, either in electronic or hard copy;
4. the policy had to be written in English;
5. the policy had to be available for review by project investigators no later than July 31, 2003.
Identifying Policy
Our primary source of alcohol and gambling policies was each school's student handbook. (For the purpose of this study, "student handbook" refers to the institution's primary informational document made available to current and prospective students.) The student handbook is a centralized forum for regulatory information and is a primary source of official school policies for students and parents, as well as the public. In addition, the concept of a student handbook is widespread, making handbooks a common information source across many schools. Many institutions distribute student handbooks to all incoming freshmen; therefore, most students are familiar and comfortable with accessing the handbook. Student handbooks also are widely available to the public.
When available, we used electronic versions (i.e., pdf or html) of each school's handbook; otherwise, we used a hard copy. Some schools, particularly large universities with many departments and/or divisions, did not have a single handbook that they distributed to all students. In these cases, we retrieved the school's policies from other official documents (e.g., code of conduct, policy manual, judicial procedures manual). Many schools also posted policy information (i.e., separate from the handbook) on their Web sites; we analyzed this information as a secondary source. We conducted an exhaustive search of each school's Web site using each site's integrated search engine and used keywords such as "alcohol," "drinking," "alcohol policy," "gambling," "wagering," "betting," "gambling policy," "substance use policy," "college (university) regulations," and "college (university) policies" to identify relevant sections of each Web site. Several sites did not include a search function; in such cases, we conducted a comprehensive visual search of the site. We also examined supplemental materials provided by schools (e.g., policy manuals, brochures, pamphlets, etc.) for comparison against handbooks and Web-based materials. We conducted a visual search of all hard-copy handbooks and supplemental policy materials and extracted all relevant information from these sources.
We systematically archived all of the Web-based and other electronic regulatory sources (e.g., pdf- and text-based student handbooks and policy manuals, html pages, etc.) from each school on a computer. We filed hard copy materials, such as student handbooks and policy manuals, by school and kept these documents on site.
Policy Coding Procedure and Instrument
Investigators developed a coding instrument by studying alcohol and gambling policies from a variety of U.S. schools outside the current sample and identifying the underlying characteristics of the policies. These characteristics were reduced to 40 items that reflected the scope and focus of school alcohol and gambling policies. The items were converted into a coding instrument that included 25 variables for alcohol policy and 15 variables for gambling policy. This instrument included items to measure the presence of specific policies and establish whether the policies were punitive or rehabilitative. All variables used a nominal scale that included common characteristics of each school policy; response choices varied slightly with the focus of each variable. All of the variables were arranged on a six-page coding form.
To simplify coding and allow for within-school comparisons between different formats of policy dissemination (e.g. school handbook vs. school Web site), we separated each school's policy materials into three categories: (1) student handbooks (electronic or paper); (2) Web-based materials; and (3) supplementary materials (paper); a potential 357 documents required coding (three coding categories for each of 119 schools in sample = 357 potential documents). However, because not every school had documents available in all three coding categories, the final document count was 164. Specifically, at the end of our data collection process, we had collected 73 student handbooks, 70 Web-based policies, and 21 supplementary documents.
We assigned 11 coders the job of evaluating each school's alcohol and gambling policies. Each coder read a selection of policies and extracted relevant information in accordance with the coding form. The coding process proceeded as follows:
1. Each policy document was assigned to two of eleven eligible DOA coders randomly. Each assigned coder independently abstracted information from each assigned policy document and recorded this information on separate coding forms.
2. For each document, one member of the research team, designated as the "arbiter," compared the two coding forms and marked discrepant items.
3. The arbiter returned the marked coding forms to their respective coders and requested that coders reconsider their answers to the items in question. Upon reconsideration, coders were free to change their answers or keep their original answers.
4. Coders resubmitted their recoded documents to the arbiter who compared the discrepant items again. Discrepancies that remained were noted and resolved by the arbiter.
5. Once all discrepancies had been resolved, the policy assessments on the coding forms were entered into an SPSS database using a procedure that screened entries for out-of-range values and discrepancies in branching among items.
6. We assessed data entry reliability by selecting 10% of the cases in our database and rechecking each data entry point. Of the 680 items entered in these 17 randomly selected cases, there were no observed data entry errors.
Shaffer and his associates have used a similar process of information extraction, coding and arbitration successfully in other published studies [1,32].
Results
Our analysis of college alcohol and gambling policies generated several types of results. First, we describe the results of our coding procedure, the final sample of schools and available policy information. Next, we examine the policy evidence across information sources by analyzing the consistency between the information provided by handbooks and Web materials. We then present the prevalence of individual policy items and the results of a factor analysis that explored the underlying dimensions of the policy variables. Finally, we analyze the relationships between policies and student drinking and gambling rates using information collected in the most recent Harvard School of Public Health College Alcohol Study (CAS) [6].
Inter-Coder Concordance
We assessed inter-coder reliability by comparing the total number of discrepant coded items to the total number of coded items. As described previously, each policy was assigned to two of eleven eligible DOA coders randomly. The participation of eleven coders yielded 55 possible coding-pair combinations; each of these pairings coded at least one policy. Specifically, the number of policies coded by each coder-pair ranged from a minimum of one (n = 6) to a maximum of six (n = 3). Coders had up to two opportunities to code each document: (a) an initial round of coding; and (b) a second round of coding to reconsider any discrepant items identified by the arbiter after the initial round of coding. The arbiter made the final coding decision on 345 out of a total of 4,100 possible items. The coding process yielded a study-wide inter-coder reliability rate of 91.6%.
College Sample
After thirty days had passed from our initial e-mail request, 46 of 119 schools had responded by sending hard copy materials. Eighteen of these 46 colleges sent materials completely unrelated to our request for school alcohol policies (e.g., applications for admission, school newsletters). Fourteen schools sent student handbooks, and another 14 schools sent other alcohol and/or gambling related (i.e., non-handbook) materials. Seventy-three schools did not respond to our request within thirty days. Subsequent to our follow-up telephone requests, we received student handbooks and supplemental materials from an additional 22 schools. This recruitment procedure resulted in 50 schools actively providing policy information for this study; for the remainder, policy information was obtained through other investigative procedures as described earlier (e.g., Web sites).
Policy Sample
This study sought information on alcohol and gambling policy from a representative sample of 119 colleges across the U.S. We utilized three distinct common sources of information on school alcohol policy: student handbooks, school Web sites (non-handbook related) and supplementary materials (e.g., policy manuals, pamphlets). We collected a total of 164 policy-related documents from three sources: 73 policy documents from handbooks, 70 documents from school Web sites, and 21 from supplementary materials. Table 1 presents the sources of alcohol policy information for the schools in our sample. Forty schools presented their full alcohol policy in their handbook, 31 on their Web site, 2 in supplementary materials, and 44 through a combination of handbook, Web site and supplements. We were unable to locate any policy information for two schools in our sample; these schools did not respond to our requests for information.
Table 1 Sources of school alcohol policy information
Number of Schools Handbook Policies Web site Policies Supplemental Materials No materials
40
31
2
25
5
11
3
2
Total = 119 Total = 73 70 21 2
Policy across Information Sources
We aggregated and analyzed policy information across sources because a preliminary examination revealed content differences among handbooks, Web sites [33] and supplementary materials. Aggregating information across sources provides the most extensive view of each college's policy strategy because it considers all modes of policy distribution. This strategy yields the most comprehensive policy search and identifies more policy mentions than is possible by examining only one policy source. To implement this strategy, we first constructed a new database that included data for schools with a handbook, a Web site or both (n = 115). Next we created a single record of policy mentions for the 28 schools with both handbooks and Web materials by aggregating policies across sources. This database assimilated the unique handbook and Web variables into a single set of "recompiled" variables, reflecting the total number of policies attributable to either the handbook or the Web. To compare the "added value" of school Web sites (i.e., policy information presented on the Web that was not presented in the handbook), we summed the policies reflected by the recompiled variables and then subtracted the policies contained in the handbook-only variables. Of 263 total policy items present, we collected 198 (75%) policy items from student handbooks and 65 (25%) additional policy items from school Web sites that were not available in handbooks.
To determine the added contribution of supplemental materials (i.e., policy information presented in the supplements that was unavailable elsewhere), we created another set of recompiled variables following the previously outlined procedure. These variables reflected the total number of policies identified for the three schools with all three types of sources (i.e., handbooks, Web materials and supplements). We summed the policies reflected by the recompiled variables and then subtracted the policies contributed by handbooks and Web sources; this procedure revealed that supplemental materials contributed 4 of 30 (13.3%) policy items.
Although school Web sites provide a substantial amount of alcohol policy information that is not contained in the primary document customarily provided to students (i.e., handbook), the overall added contribution of the school Web site in presenting policy information varied among schools. For example, one school's Web site contained an additional eight alcohol regulations that were not included in the handbook; however, several schools' sites contained no additional information. In addition, the type of information that was presented only on Web sites also varied: while most information pertained mainly to secondary alcohol policies (e.g., school-sponsored events and drinking regulations for drinking-aged students), some schools chose to present vital alcohol policy information (e.g., stating that all drinking is prohibited for students <21) on their Web site only (n = 2). Thus, although handbooks and Web sites are both important sources of alcohol policy information and supplements contribute little additional information, consistency across sources varies. The following analyses assess the agreement of information found in multiple sources.
Handbook-Web Concordance
As mentioned earlier, of the 117 colleges for which we had information, all 117 (100%) had a written policy on student alcohol consumption and 26 schools (22%) had a student gambling policy. Because all schools had a written alcohol policy (and relatively few schools had a gambling policy), the following analyses focus on alcohol policies.
Determining concordance between handbook and Web sources is important because administrators might be unaware of inconsistencies between official school documents. In addition, contradictory information can mislead students and potential applicants. We assessed the concordance between sources of college alcohol policy materials by determining the level of agreement (i.e., presence or absence of policy information) between handbooks and Web materials; that is, we compared the content of each type of document to identify differences in the presentation of each school's policy information between sources. We did not extend this particular analysis to include supplemental materials because, as we noted before, only a small number of schools (n = 3) had all three types of sources.
Twenty-eight schools had both a handbook and Web materials; for each of these 28 schools we determined the absence or presence of the 25 alcohol policy variables in each source. We predetermined that a concordance rate of 85% would indicate a high level of agreement between documents. To be considered in agreement, complementary information had to be found in (or absent from) both sources; in cases where this requirement was not satisfied, the policies were considered in disagreement. Using these criteria, we determined that three policy variables (i.e., 12% of the policy variables) were mentioned often and were present in both handbooks and on Web sites, and consequently, showed high agreement. Either type of information resource seldom mentioned ten policy variables (i.e., 40% of the policy variables), therefore, also exhibiting high agreement. The remaining 12 policy variables (i.e., 48% of the policy variables) were often mentioned, but not consistently by both sources, indicating low agreement.
Table 2 presents the three "high agreement" alcohol policies that were mentioned consistently in both handbooks and Web materials. Variables that fell into this category generally measured broad school policies (i.e., the existence of an alcohol policy). As Table 2 illustrates, schools consistently made these types of alcohol policies available to the public in both print and electronic form, making this information highly accessible.
Table 2 "High Agreement" Alcohol Policies, Often Mentioned in Both School Handbooks and Web Materials (N = 28)
Policy % of schools, HB only % of schools, Web site only % of schools, HB and Web site % of schools, no mention in HB or Web site
Is there an alcohol policy? 0 0 100.0 0
Alcohol is prohibited on campus for students <21 7.1 7.1 85.7 0
Alcohol is allowed at sanctioned events for students ≥ 21 0 0 87.5 12.5
Policy variables that were rarely mentioned in handbooks and Web materials appear in Table 3. These variables primarily measured on- and off- campus alcohol consumption restrictions and school recovery polices regarding student alcohol use. These policies are in "high agreement," because they were seldom mentioned: as Table 3 demonstrates, this information was missing from handbooks and Web sites in nearly all cases.
Table 3 "High Agreement" Policy Variables, Rarely Mentioned in School Handbooks and Web Materials (N = 28)
Policy % of schools, HB only % of schools, Web site only % of schools, HB and Web site % of schools, no mention in HB or Web site
Alcohol is prohibited off-campus for students ≥ 21 0 0 0 100.0
Alcohol quantity limits at off-campus events 0 0 3.6 96.4
Policy on container restrictions at off-campus events 3.6 0 0 96.4
Policy on leave of absence for recovery 3.6 0 0 96.4
Policy allowing students to participate in recovery while living in dorm 3.6 3.6 0 92.9
Attendance restrictions for hosted events 0 10.7 3.6 85.7
Policy on students with an alcohol problem upon entering school 7.1 3.6 0 89.3
Policy on students who develop an alcohol problem while in school 10.7 3.6 0 85.7
Policy on students already in recovery upon entry to school 10.7 3.6 0 85.7
Policy on students who enter recovery while in school 10.7 3.6 0 85.7
Table 4 presents variables that were mentioned occasionally (i.e., concordance <85%) in handbooks or Web materials. The policies in this category primarily address consumption and event restrictions and student recovery. Table 4 illustrates that we observed considerable inconsistencies in schools' methods of distribution of these types of policies.
Table 4 "Low Agreement" Policy Variables, Mentioned Inconsistently in School Handbooks and Web Materials (N = 28)
Policy % of schools, HB only % of schools, Web site only % of schools, HB and Web site % of schools, no mention in HB or Web site
Alcohol is prohibited on-campus for students ≥ 21 0 7.1 10.7 82.1
Off-campus alcohol restrictions in place for students ≥ 21 10.7 7.1 3.6 78.6
School policy is to defer to local laws on alcohol consumption 14.3 10.7 3.6 71.4
Policy on alcohol quantity limits at events 17.9 10.7 3.6 67.9
Attendance restrictions for school sanctioned events 21.4 10.7 3.6 64.3
Campus operates an alcohol recovery program 32.1 7.1 3.6 57.1
Policy on alcohol-free campus housing 25.0 25.0 3.6 46.4
Document makes clear other ways by which the school makes students aware of the official alcohol policy 25.0 17.9 21.4 35.7
Policy on container restrictions on campus 21.4 21.4 21.4 35.7
Campus makes referrals to off-campus recovery programs 25.0 21.4 28.6 25.0
On-campus alcohol restrictions in place for students ≥ 21 13.0 26.1 56.5 4.3
Policy on alcohol at on-campus sanctioned events for students ≥ 21 17.9 21.4 57.1 3.6
Identifying the Underlying Dimensions of College Policy
As noted earlier, the coding process revealed that all 117 colleges (i.e., 100% of the schools for which information was available) in this sample had a written policy on student alcohol consumption, but only 26 (22%) had a published policy that addressed gambling. The small number of schools with gambling policies precludes confident analysis of the dimensional composition of our gambling variables; therefore, we applied the factor analysis that follows only to alcohol policy variables.
Three policy variables represented a multi-dimensional measurement strategy to yield detailed policy information. Consequently, we collapsed these three redundant policy items into the primary or gate items from which they originated (e.g., "alcohol is prohibited on-campus for students ≥ 21" and "on-campus alcohol restrictions in place for students ≥ 21" became "policy on alcohol use on-campus for students ≥ 21). This resulted in 22 alcohol policy variables in all remaining analyses. These dependent variables all measured different aspects of school alcohol policies (e.g., policy presence, content, and target). To empirically examine the underlying dimensions reflected by our variables, we conducted an exploratory factor analysis. This procedure employed an initial factor extraction (i.e., component matrix) and then an orthogonal rotation to simple structure. We selected the Varimax rotation to maximize the variance of loadings within factors and minimize the covariance across factors. The orthogonal solution identified eight policy clusters with Eigenvalues greater than 1.0 that explained 72.36% of the total variation. This explained variance lies within the 50–75% useful range suggested by Overall and Klett (1972)[34]. Consequently, we concluded that our factor analysis provided a valid identification of the policy clusters that underlie college alcohol and gambling regulations.
Table 5 presents the structure of the interrelationships among policies. To facilitate interpretation, the table reports only factor loadings ≥ 0.50 (i.e., policies with loadings in this range correlate .50 or greater with a composite measure of the overall dimension).
Table 5 Orthogonal Factor Structure and Items Loading ≥ 0.50 on Each Factor
Variable Factor Loading % Variance Explained
Factor 1 – School policy and the law 4.83
Does the school alcohol policy defer in full to local law? .88
Factor 2 – Prohibition policies 5.43
Does the policy state that alcohol is prohibited for students <21? .85
Does the policy state that alcohol is restricted on-campus for students ≥ 21? .76
Factor 3 – Policies for legal-aged drinkers 6.65
Is alcohol is allowed at sanctioned on-campus events for students ≥ 21? .75
Is alcohol prohibited off-campus for students ≥ 21? .74
Factor 4 – Limits and restrictions – on-campus 9.13
Does the policy state whether the school offers alcohol-free campus housing? .77
Does the policy address alcohol container restrictions on campus? .74
Does the policy address alcohol quantity limits (i.e., total alcohol available) at on-campus sanctioned events? .57
Factor 5 – Events policies 7.20
Are there attendance restrictions for off-campus sanctioned events? .81
Are there attendance restrictions for on-campus sanctioned events? .78
Are there restrictions on off-campus alcohol use for students ≥ 21? .56
Factor 6 – Limits and restrictions – off-campus 13.50
Is there policy on alcohol quantity limits (i.e., total alcohol available) at off-campus sanctioned events? .81
Is there policy on alcohol container restrictions off-campus? .79
Is there policy that permits students a leave of absence to participate in a recovery program? .50
Factor 7 – Recovery recognition policies 20.59
Is there policy on students who enter alcohol recovery while attending? .90
Is there policy on students who are in alcohol recovery upon entry? .88
Is there policy on students who have an alcohol problem upon entry? .87
Is there policy on students who develop an alcohol problem after entry? .79
Is there policy that permits students in an alcohol recovery program to live in a dormitory on campus? .73
Factor 8 – Recovery facilitation 5.03
Does the campus makes referrals to an off-campus recovery program for students with alcohol use disorders? .74
Does the campus operate a recovery program for students with alcohol use disorders? .73
The eight factors are ordered according to the number of policies measuring the overall domain; that is, factors containing general, or "blanket," policy items are listed first, followed by factors containing more specific policy items. Factor 1 (i.e., School policy and the law) contained only one item that loaded ≥ 0.50 and explained 4.83% of the total variance. Many schools deferred to local law entirely and did not publish other policies that were unique to the school. Factor 1 identifies this deference policy as a unique dimension. Factor 2 (i.e., Prohibition policies) expands on deference to local law and presents additional school policies that prohibit alcohol for underage and legal age students. These items accounted for 5.43% of the total variance. Factor 3 includes policies that extend restrictions to include drinking by students of legal age (i.e., Policies for legal-aged drinkers). Items in Factor 3 explained 6.65% of the total variance. Factors 1, 2 and 3 include alcohol policies that focus on the legal status (i.e., legal age) of students; in addition, for those of legal age, these policies range from no school specific policies to prohibitions for students who are old enough to drink legally.
Factors 4 through 6 include policy variables directed to alcohol use on-campus and off-campus. Factor 4 (i.e., Limits and restrictions – on campus) provides specific guidance about where on-campus students can drink and how much alcohol is available (i.e., housing and container and quantity restrictions); these items accounted for 9.13% of the total variance. Factor 5 policies (i.e., Events policies) accounted for 7.20% of the total variance and focus primarily on restrictions for on- and off-campus events. Factor 6 (i.e., Limits and restrictions – off campus) accounted for 13.50% of the total variance and includes policies that regulate off-campus activities (i.e., alcohol quantities, containers and leaves of absence).
Different from the first 6 factors, factors 7 and 8 focus on student recovery. Factor 7 policies (i.e., Recovery recognition policies) recognize that students can have alcohol related problems that require recovery, and that these problems can exist before entering college or develop during college; these items accounted for 20.59% of the total variance in the data. Finally, Factor 8 (i.e., Recovery facilitation) accounted for 5.03% of the total variance and includes policies that reflect how the school participates in the recovery process (i.e., triage or treatment). One item (i.e., "how does the campus inform students of the official school policy") failed to load ≥ 0.50 on any factor and was excluded from the final analysis.
Alcohol Policy Prevalence
College alcohol policies varied widely. Table 6 summarizes the prevalence of alcohol-related policy and the mean prevalence of alcohol policies within each factor. The prevalence of alcohol policies ranged from 100% (i.e., the presence of an alcohol use policy) to 1.7% (i.e., policy that permits a leave of absence to participate in a recovery program). The mean prevalence for the eight policy factors ranged from 92.3% (i.e., Prohibition policies) to 5.4% (i.e., Limits and restrictions-off-campus).
Table 6 Prevalence of College Alcohol Policies and Policy Attributes
Policy & Policy Attributes Prevalence % (N)
School has a written policy on alcohol use 100 (117)
Policy states that alcohol is prohibited for students <21 97.4 (114)
Policy on alcohol use on-campus for students ≥ 21 87.2 (102)
Policy addresses alcohol at sanctioned on-campus events for students ≥ 21 68.4 (80)
Campus makes referrals to an off-campus recovery program for students with alcohol use disorders♠ 57.3 (67)
Policy addresses alcohol container restrictions on-campus 50.4 (59)
Policy makes clear how the campus informs students of the official school alcohol policy 43.6 (51)
Campus operates a recovery program for students with alcohol use disorders♠ 28.2 (33)
School alcohol policy defers in full to local law 26.5 (31)
Policy addresses alcohol quantity limits (i.e., total alcohol available) at on-campus sanctioned events 26.5 (31)
School offers alcohol-free campus housing 22.2 (26)
Restrictions on off-campus alcohol use for students ≥ 21 21.4 (25)
Attendance restrictions for on-campus sanctioned events 20.5 (24)
Policy on students who develop an alcohol problem after entry♠ 10.3 (12)
Policy on alcohol quantity limits (i.e., total alcohol available) at off-campus sanctioned events 8.5 (10)
Policy on students who enter alcohol recovery while attending♠ 7.7 (9)
Attendance restrictions for off-campus sanctioned events 7.7 (9)
Policy on students who are in alcohol recovery upon entry♠ 6.0 (7)
Policy on alcohol container restrictions off-campus 6.0 (7)
Policy permits students in an alcohol recovery program to live in a dormitory on campus♠ 5.1 (6)
Policy on students who have an alcohol problem upon entry♠ 3.4 (4)
Alcohol is prohibited off-campus for students ≥ 21 3.4 (4)
Policy permits students a leave of absence to participate in a recovery program♠ 1.7 (2)
Policy Factor Mean Prevalence (%)
Factor 2 – Prohibition policies 92.3
Factor 8 – Recovery facilitation♦ 42.8
Factor 3 – Policies for legal-aged drinkers 35.9
Factor 4 – Limits and restrictions – on-campus 33.0
Factor 1 – School policy and the law 26.5
Factor 5 – Events policies 16.5
Factor 7 – Recovery recognition policies♦ 6.5
Factor 6 – Limits and restrictions – off-campus 5.4
♠Recovery-oriented policy; ♦ Recovery-oriented factor
Policy, Binge Drinking and Gambling
We conducted several analyses to determine the nature of relationships between student alcohol consumption, gambling behavior and policy content. As the factor analysis above illustrates and the relative prevalence of policies confirms, college alcohol-related policies are primarily intended to prevent, reduce or restrict alcohol use among students on college campuses. To test the relationships between alcohol policies and student drinking behaviour, we compared the mean binge drinking rates of students at schools with and without each policy variable. We obtained the mean binge drinking rates of the schools in our sample from the dataset used in Wechsler et al.'s Harvard School of Public Health College Alcohol Study (CAS)[6]. Because this is one of the first studies of college policies, we sought to identify as many potential relationships between policy, drinking and gambling as possible; therefore we set a liberal alpha level (α = .1) for this analysis. A one-way analysis of variance (ANOVA) revealed that four of the 22 policy variables had significant relationships with binge drinking rates at the colleges in our sample (see Table 7).
Table 7 Mean Binge Drinking Rates (%) and Alcohol Policy Variables
Policy variable Schools with no policy mention (N) Schools with no policy restrictions (N) Schools with restrictions policy (N) Schools with prohibition policy (N) F df
Policy on alcohol use on-campus for students ≥ 21 n/a (0) 39% (15) 47% (77) 36% (24) 7.07*** 2,113
Policy on alcohol at on-campus sanctioned events for students ≥ 21 44% (37) 46% (64) n/a (0) 33% (15) 5.25*** 2,113
Policy on students already in recovery upon entry to school 43% (109) 56% (6) 57% (1) n/a (0) 2.89* 2,113
No mention (N) Alcohol free housing available (N)
Policy on alcohol-free campus housing 42% (90) 49% (26) 4.01** 1,114
* = p < .1; ** = p < .01; *** = p < .001
Schools that had either no policy restrictions or a prohibition policy for on-campus alcohol use by students ≥ 21 had lower mean past-month student binge drinking rates (39% and 36%, respectively) compared to schools that employed an intermediate level of restrictive policies (47%) (F = 7.07, df = 2,113, p < .001). Schools that allowed or did not mention alcohol use at on-campus sanctioned events for students ≥ 21 had a higher mean binge drinking rate (46% and 44%, respectively) than schools that prohibited legal drinking at events (33%) (F = 5.25, df = 2,113, p < .001). Schools that offered alcohol-free housing had a higher mean student binge drinking rate of 49% compared to schools that did not mention alcohol-free housing which had a binge rate of 42% (F = 4.01, df = 1,114, p < .01). Two other alcohol policy variables evidenced significant relationships with student binge drinking behaviors, but these policies lacked widespread implementation at a large number of schools. Schools that specifically allowed a leave of absence for a student to participate in recovery activities (n = 2) evidenced a higher mean binge drinking rate (69%) than schools that did not mention such a policy (43%, n = 114). Keeping the small number of schools in mind, it is worth noting that schools that prohibited off-campus alcohol consumption for students ≥ 21 (n = 4) had a lower mean binge rate (10%) than schools without this provision (45%, n = 112).
There were not enough schools with gambling policies to permit a detailed analysis of the relationship between policies and student gambling behavior; therefore instead of conducting an analysis of the relationship between gambling behavior and individual policy variables, we only were able to assess gambling behavior based on whether schools had a gambling policy. Using prevalence data from LaBrie et al.'s (2003) [31] recent study of student gambling behavior, we determined that no significant difference in mean past-year student gambling behavior existed between schools with a written policy on gambling (i.e., prohibitive or restrictive) and schools with no mention of gambling policy (i.e., approximately 40% regardless of policy presence).
Unanticipated Policy Effects: Alcohol Policy can Influence Gambling Participation
Long ago, Pigou [35] noted that public policies can have unanticipated effects; policy intended to regulate one set of behaviors can influence other patterns of behavior. To test the relationships between alcohol policies and student gambling behavior, we compared the mean past-year gambling rate at schools with each alcohol policy to schools without the policy. As before, we used a liberal alpha (α = .1) to identify all potential relationships. A one-way analysis of variance (ANOVA) revealed that four of the 22 alcohol policy variables had significant relationships with the proportion of students who gambled in the past-year school year (see Table 8).
Table 8 Mean Past-Year Student Gambling Participation Rate (%) and Alcohol Policy Variables
Policy variable Schools with no policy mention (N) Schools with no policy restrictions (N) Schools with restrictions policy (N) Schools with prohibition policy (N) F df
Policy on alcohol use on-campus for students ≥ 21 n/a 46% (15) 40% (77) 41% (24) 2.64* 2,113
Policy on alcohol at on-campus sanctioned events for students ≥ 21 44% (37) 40% (64) n/a (0) 35% (15) 5.17*** 2,113
No mention (N) Limits (N)
Policy on alcohol quantity limits at on-campus events 42% (85) 37% (31) 5.39*** 1,114
Policy on off-campus alcohol restrictions for students ≥ 21 42% (91) 38% (25) 2.94* 1,114
* = p < .08; ** = p < .01; *** = p < .001
Schools that restricted or prohibited on-campus alcohol use for students over 21 evidenced similar mean past-year student gambling participation rates (i.e., 40% and 41%, respectively), and schools with no restrictive policy evidenced a higher student gambling participation rate (46%) (F = 2.64, df = 2,113, p < .08). Schools that did not mention or allowed alcohol at on-campus events for legal drinkers exhibited a higher mean gambling participation rate (i.e., 44% and 40%, respectively) than schools that prohibited alcohol at on-campus events (35%) (F = 5.17, df = 2,113, p < .001). Similarly, schools that did not limit the quantity of alcohol available at events showed higher past-year gambling participation among students (42%) compared to schools with no such provision (37%) (F = 5.39, df = 1,114, p < .001). Schools that had off-campus alcohol restrictions for legal-aged drinkers had a gambling rate of 38% while schools that did not had a mean gambling rate of 42% (F = 2.94, df = 1,114, p < .1).
Two other alcohol policy variables evidenced significant relationships with student gambling behaviors, but these policies were not widely implemented throughout the sample. Schools that did not expressly prohibit alcohol consumption for underage drinkers (n = 3) evidenced a mean past-year student gambling rate of 51%, while schools that prohibited underage drinking (n = 116) had a gambling rate of 41% (F = 3.19, df = 1,114, p < .1). Schools that banned all alcohol consumption, whether on- or off-campus (n = 4) evidenced a lower gambling rate (30%) than schools that allowed at least some drinking (41%, n = 112) (F = 5.80, df = 1,114, p < .05).
In addition to the direct relationships between policy variables and binge drinking and gambling, three alcohol policy variables evidenced unexpected interaction or intensification effects when gambling policies also were present. Schools that had both a policy prohibiting or restricting gambling activity among students and a policy prohibiting on-campus legal-aged drinking (n = 9) had a mean binge drinking rate of 29% – much lower than schools with just an alcohol policy (40%, n = 15), a gambling policy (47%, n = 17) or neither (45%, n = 75) (F = 3.15, df = 1,112, p < .1). Schools with both a gambling policy and a policy prohibiting alcohol at on-campus events (n = 6) had a significantly lower mean binge rate (22%) than schools with just an alcohol policy (40%, n = 9), a gambling policy (46%, n = 20) or neither (45%, n = 81) (F = 5.88, df = 1,112, p < .05). Schools that prohibited alcohol at on-campus events also evidenced significantly lower past-year student gambling rates than schools without such prohibitions: 30% versus 38% or higher (F = 8.63, df = 1,112, p < .05).
Discussion
Using written (i.e., hard copy) and Web based sources, this study examined the nature and extent of alcohol and gambling-related policies among a representative sample of U.S. colleges. Every school in this representative sample had at least one alcohol use policy; however, few schools (i.e., 26 of 117; 22%) had at least one gambling policy available. The relative rarity of gambling-related policies on college campuses represents a lost opportunity by school administrators to (a) prevent or limit disordered gambling among students and (b) facilitate recovery for students in need of gambling treatment. A recent study showed that, while not as prevalent as previously thought, gambling on college campuses is still quite common, with 42% of students having gambled in the past year and 2.6% gambling weekly or more [31]. The frequency with which gambling occurs on college campuses could be indicative of lingering misconceptions about gambling outcomes among student populations. For example, research has shown that gamblers are largely unaware of the probabilities associated with various forms of gambling (e.g., Ladouceur et. al. 1996[36]; Rogers 1998[37]); this circumstance leaves gamblers susceptible to cognitive errors [38]; [39]; [40] and suggests that gambling behavior is largely driven by social factors and injunctive norms (i.e., the tendency to engage in gambling as a function of personal perceptions of society's acceptance of gambling) [41,42,11]. By failing to implement comprehensive restrictive and recovery-based gambling policies and neglecting to educate students about the probabilities associated with gambling as well as the dangers of excessive gambling, school administrators are overlooking an important and potentially destructive problem that faces many of today's students. Future policy-based education and recovery initiatives might be able to effectively reduce student gambling behaviors; however, given the current dearth of gambling policies, we cannot determine whether school policies can effectively reduce at-risk gambling behaviors on college campuses.
All the schools in our sample recognized the need for some type of alcohol policy; however, the presence of more targeted policies varied considerably. Although this variation might reflect different policymaking strategies across institutions, it also could result from a variety of other influences, including the lack of federal standards guiding the creation of alcohol policy on college campuses. The absence of policy guidelines leaves administrators with a wide range of options about how to best address student substance use and abuse. Some administrators might prefer to match policy to their perception of local needs, while others might welcome policy guidelines. Both of these circumstances encourage additional research designed to help guide administrators to identify effective policies (e.g., "best practices").
Alcohol policies ranged from comprehensive restrictions and prohibition to liberal acceptance of student alcohol use. Policies encouraging recovery among students with alcohol use disorders were decidedly absent from our sample. For example, only 57.3% of schools expressed in writing that they made referrals to alcohol recovery services; all other recovery-oriented policy provisions were in place at fewer than 30% of schools, with two-thirds of these policies in effect at fewer than 10% of schools. Examination of the mean prevalence of the eight policy factors provides additional support for this finding. The mean prevalence of recovery recognition policies was 6.5% (i.e., factor 7). Although recovery facilitation policies were more common, with a mean prevalence of 42.8% (i.e., factor 8), this rate simply reflects that many schools report making referrals to outside treatment facilities. In contrast, the prevalence of prohibition policies was 92.3% (i.e., factor 1). This limited of consideration for student recovery and emphasis on punitive and prohibitive measures might reflect an underlying institutional bias against accommodating students with special needs and an unsupportive atmosphere for those who are at most risk for developing alcohol problems. The higher prevalence of policies that direct referrals to outside treatment resources might indicate an eagerness among administrators to export students with addiction problems to non-school affiliated assistance. Alternatively, placing little emphasis on recovery might simply represent a lack of understanding about addictive behaviors and addiction recovery among school administrators.
Even though the results of this study indicate that schools with recovery policies can evidence higher rates of binge drinking, this rate might reflect a pre-existing campus problem (i.e., policy as a consequence of behavior) rather than be a result of recovery policy implementation. Future policy research needs to examine whether a better balance between punishment and treatment policies will yield improved student health services, less substance misuse and, consequently, a better campus life for all students.
As hypothesized, there were considerable and important differences between the information that was available in handbooks and on the Web. This observation is not surprising because there are few requirements guiding the creation of school substance use and gambling policies and no standards requiring consistency among sources. Also, the factor analysis illustrated that alcohol policies currently concentrate primarily upon prevention and punishment, and devote relatively limited attention to student recovery. Finally, as we expected, schools with no policy restrictions on alcohol consumption or restrictive alcohol policies often experienced higher levels of binge drinking among students than schools with prohibitive alcohol policies. Nevertheless, alcohol policies were associated inconsistently with student binge drinking rates; few policy variables exerted influence on patterns of student drinking. In some cases, policies designed to reduce student alcohol consumption showed an opposite effect.
Absence of Shared Standards and Model Policies
The results of this policy analysis suggest diverse and perhaps ambivalent tolerance toward alcohol use among U.S. colleges that has led to a deep underlying problem: there is a lack of model policy guidelines to assist colleges in (a) preventing addictive behaviors among students and (b) providing assistance to students already struggling with addiction. Optimally, if available, such guidelines would provide school administrators with "best practice" model policies that address the many aspects of addiction among students (e.g., permitted and prohibited substance use on campus, legal matters, parental notification, treatment options, financial issues, academic issues, etc.) and would outline strategies for implementing and enforcing such policies. In the absence of an explicit regulatory framework (i.e., the current policy environment), schools are left to regulate addictive behaviors based upon the local attitudes and expectations of communities and implicit moral values held by school administrators. This circumstance can lead colleges to install policies intended to have immediate and drastic results (i.e., prevention and punishment policies) while neglecting policies that would promote recovery and provide lasting benefit to students. The absence of evidence-based policy leaves school administrators in a position of promulgating policy that might have effects that are contrary to their intentions. For example, the Boston Globe reported on October 30, 2002 that, "Forty-seven Massachusetts colleges will sign onto a statewide campaign today designed to punish students who abuse alcohol and to cut down on the rate of binge drinking on campuses by providing alcohol-awareness training for students, athletes, and Greek system members"[43]. This type of policy imposes blind restrictions and punitive measures on students without considering the underlying factors motivating student drinking (e.g., campus environment) or the need for specialized programs (e.g., recovery programs) to assist in reducing student drinking. Thus, even when colleges have existing policies that address alcohol, drug use or gambling, it is likely that the number of policies related to students involved with or seeking recovery programs is much more limited. It is interesting to consider that colleges routinely provide remedial courses in expository writing to help students cope with the demands of academics but resort to exclusion or punishment for students who fail to adequately cope with an academic environment where 44% of students binge drink [6].
Inconsistent Policy Presentation
The prevalence of alcohol-related problems at U.S. colleges highlights the need for comprehensive student policies addressing all aspects of alcohol use. Further, for policy to be effective students need to be aware of and understand school requirements; this requires that students know how to access policy information. Because schools currently are not required to disseminate alcohol policies in any particular form or through any specific medium, the availability of existing policy information can vary substantially among schools. Though most commonly printed in student handbooks, substance use policies also appear in policy manuals, pamphlets and, increasingly, on school Web sites. One recent study of college Web-based alcohol policy information [33] found that 50 of 52 schools included alcohol policy information on their Web site; unfortunately, schools rarely consolidated this information onto a single Web page for easy viewing. The result was that alcohol policy information was often incomplete and/or difficult to access [33]. Although the Internet provides an excellent opportunity for schools to reach technology-savvy students and parents, individuals seeking policy information on the Web are likely to face disorganization and user-unfriendly designs. Thus, while students and parents might expect to access alcohol or gambling policies by turning to a college's student handbook or Web site, the results of this study suggest that their success in locating the desired information will vary considerably. Adoption of generally accepted standards for policy dissemination could increase student awareness, and consequently, compliance with college rules.
Tables 2 through 4 illustrate that schools present different types of alcohol policy information in their handbooks and Web sites; sometimes this information agrees across sources, and often it does not. For some policy variables, this discrepancy is problematic. For example, most schools (82.1%) did not report on the presence or absence of alcohol-free campus housing at all. It is difficult to assess whether an absence of policy indicates a tacit acceptance of an activity (i.e., legal-aged alcohol consumption). More likely, however, it indicates that at these schools some drinking is permissible among students over age 21. For other policies, schools' lack of consistency in reporting uniform policy creates different problems. For example, as Table 4 illustrates, handbooks and Web sites mislead people inquiring about on-campus alcohol-free housing 25–50% of the time, at schools that have such a policy, depending upon the information source (i.e., handbook or Web site). Many schools (46.4%) did not mention alcohol-free housing at all; it is unclear whether these schools have alcohol-free on-campus housing, or simply lack an explicit policy addressing the matter.
This study reveals that to gain a complete understanding of the components of a school's alcohol policy, it is necessary to consult both the handbook and the school Web site whenever possible. However, schools do not alert students and parents to this fact, and it is unreasonable for school administrators to expect inquiring persons to conduct complex searches for information that is considered to be freely available in the public domain.
Policy Content: Prohibition, Punishment and Recovery
The results of the factor analysis provide a stark portrait of the current composition of college policies on potentially addictive behaviors. This analysis reveals that six of eight factors contained prohibitive and/or punitive policy variables. Although the factor analysis merely revealed the underlying psychometric properties of our instrument, the prevalence of specific policy variables across schools provides additional support for this finding. Whereas the results suggest that prohibition-oriented policies have been effective in reducing binge drinking and gambling under certain conditions, the relative scarcity of recovery-oriented policies prevents us from properly comparing the efficacy of these two strategies.
Policy, Binge Drinking and Gambling
The analysis of policy variables and binge drinking rates revealed a variety of relationships among policy variables and student drinking behaviors. Specifically, four policy variables related to student binge drinking (see Table 7), and four alcohol policy variables related to student gambling behaviors (see Table 8). Interpretation of some of these relationships is relatively straightforward. For example, schools that prohibited alcohol at on-campus events experienced less binge drinking than other schools. This finding suggests that most students will abide by school policy. However, other relationships are more difficult to interpret: schools that restricted legal-age drinking had higher binge drinking rates than schools that did not make restrictions for students ≥ 21. Perhaps, when forbidden, students find alcohol to be more desirable. Alternatively, students of legal age might feel constrained by prohibitions and, as a result, drink more often to excess than they would if the opportunity to drink was commonplace. This pattern of drinking was commonly observed during the Volstead Act (i.e., national prohibition from 1920–1933). Many people did not drink because it was illegal, but those who did tended to drink to excess [44]. Just as with the Volstead Act, determining the real effect of school alcohol policies is difficult because many other factors (e.g., how long the policy has been in effect, state or local culture, etc.) influence drinking. The relationship between policy and drinking can be counterintuitive. For example, schools that offered alcohol-free campus housing evidenced significantly higher mean student binge drinking than schools that did not mention alcohol-free housing (49% vs. 42%, respectively). Observers might expect schools promoting alcohol-free dormitories to evidence lower binge drinking; alternatively, schools with "dry" housing might better recognize alcohol related problems on their campus and set policy intended to counter these problems among their students. Accordingly, the 49% binge rate observed in this study could reflect a significant improvement in the rate of binge drinking for these schools. Without longitudinal data, however, this analysis is beyond the scope of this study. Four schools in the sample indicated that they prohibited all alcohol use by students both on- and off-campus. These schools had a significantly lower mean binge drinking rate than other schools (10% vs. 45% respectively), suggesting that prohibition discouraged drinking among the majority of the student body; alternatively, these schools might attract students less interested in drinking. Three of the schools were religiously affiliated, and the fourth admitted primarily African-American students; both minority status and religiosity are cultural factors that have been shown to be associated with decreased substance abuse [45,46].
Unanticipated Policy Effects
The interaction effects observed among alcohol policy variables and the presence of gambling policy on binge drinking behavior and past-year student gambling behavior presents an interesting and unanticipated finding. Because schools that have prohibitive alcohol policies and prohibitive gambling policies evidence lower mean rates of binge drinking among students than other schools, restrictive policies seem to have the intended effect of countering potentially destructive behaviors among students. However, other conditions such as cultural factors also play an important role in determining student behaviors. For example, students that choose to attend schools with rigorous policy provisions might be intrinsically more likely to refrain from excessive alcohol consumption for ethical or religious reasons. Further, five of the six schools in our sample that had both (a) a policy prohibiting alcohol at on-campus events and (b) a prohibitive gambling policy also had small enrollment (i.e., below the 50th percentile among schools in our sample); four of these six schools were state-operated. Underlying characteristics of students who seek out small state schools might be associated with the reduced binge rates reported among these institutions. These results suggest that, despite the role for shared policy guidelines, schools will benefit from analyzing the composition of their student body and tailoring new and modified alcohol policies to students' specific characteristics. Although competing explanations prevent the establishment of concrete cause-and-effect relationships in this study, the observed interaction effects between alcohol and gambling policies provide significant impetus for future research into effective policy strategy on college campuses.
Implications
From an observer's perspective, it appears that the many policy inconsistencies – and policy presentation inconsistencies – observed in this study reflect reactive policymaking strategies that are not guided by empirical evidence. The evidence suggests that effective school alcohol and drug policies, and student awareness of these policies, are important for many reasons. For example, college-aged individuals in recovery are extremely vulnerable to relapse; in addition to the generally high rate of relapse during the first year of recovery [47,48], this circumstance exists in part because of their age and the prevalence of drug and alcohol abuse among their peers. Students need to be aware of the potential health and treatment options that are available to them on-campus if relapse occurs. Young people have not had alcohol use disorders as long as their adult counterparts because of their age; similarly, college students recovering from an alcohol use disorder have not been healing for very long. Relapse can generate harmful financial, academic and other consequences that can impart severe restrictions upon students' actions, both on and off campus. Consequently, it is valuable for students struggling with addiction to be able to access specific school policies before they enter a college or university; students who develop an alcohol problem after they are enrolled in college also need access to this information, as well as policies governing recovery-seeking. Although it is possible that policies can reduce alcohol abuse and dependence, comprehensive policies governing alcohol consumption among students hold the greatest potential to reduce pre-morbid and sub-clinical alcohol use on college campuses. Addiction models generally propose that while sub-clinical alcohol use and gambling can ultimately lead to a pathological state, pre-morbid subjects also can move away from pathology and maintain controlled behavior or abstinence [49-51]. This can occur through the influence of social setting attributes, including policy directives. Nevertheless, the high rate of drinking and binge drinking among college students has continued despite evidence that schools have devoted increased attention to promoting alcohol awareness and prevention recently (e.g., Wechsler et al. 2002 [6]). Various factors, such as a lack of agreement among school policies, unbalanced policies (e.g., policies that focus on punishment but not recovery), or a failure on the part of school administrators to enforce stated rules could undermine a cohesive alcohol policy and contribute to continued student drinking in the wake of school reform.
It is especially important for school administrators to address risky drinking behaviors among students who do not currently have a drinking problem. Research has shown that addictive disorders originate with risk factors that always include exposure to potential objects of addiction [27,50,52]. More specifically, repeated object exposure (i.e., alcohol consumption) can combine with an individual's underlying psychosocial and neurobiological vulnerabilities, resulting in desirable subjective shifts and the potential for developing an addictive disorder [53]. While each person has unique underlying vulnerabilities that make them more or less likely to develop an alcohol use disorder, reduction of opportunities to develop such a disorder (e.g., in the form of focused regulations) will benefit all students. With ever-increasing numbers of students entering four-year colleges in the U.S., clear explanations of institutional expectations and requirements regarding substance and behavioral addictions is an essential component of reducing such behaviors among students. For example, McDonnell (1994)[54] suggests that "alcohol education should be seen as part of the education of character" (p. 45). DFSCA provisions have been effective in stimulating alcohol education and policy development on college campuses; however, currently, some schools might not be providing reliable and accurate information about addictive behaviors, as evidenced by the inconsistent nature of the alcohol and gambling policies observed in this study. In the absence of a similar federal mandate requiring gambling education on college campuses, other drastic federal measures (e.g., the proposed ban on all collegiate sports betting in Nevada[55]) have been proposed to reduce student gambling. Such proposals are problematic because these efforts restrict the freedom of responsible gamblers and place policy pressure on states instead of schools, thereby diverting focus from those in need of effective regulation (i.e., college campuses). Scientific guidelines toward school regulation, similar to those proposed for federal regulation by OMB, will provide school administrators a solid foundation for creating comprehensive alcohol and gambling policies. It is the responsibility of administrators to make the first steps toward scientific selection of school policies and take substantive and definitive measures to increase addiction awareness and recovery among students.
Caveats
Several methodological limitations to this study should be noted. First, this study relied solely upon written policy materials. Although we conducted an exhaustive search of the Internet and requested hard materials from schools, it is possible that we failed to identify some publicly available policy materials that could have provided additional information about schools in our sample. In addition, we identified our policy variables by examining existing policies and identifying relevant regulatory components; however, others attempting to replicate this study might identify and measure different aspects of policy and, consequently, obtain different results. Further, this study considered official alcohol policy content across a sample of U.S. colleges; however, assessing official policy provides no data on whether or how schools enforce their stated policies. It is possible, and in many cases even likely, that schools rely on informal rules and established precedents to govern alcohol use or gambling violations. Due to the complex nature of the relationships between school administrators, students, parents and legal authorities, many schools likely assess alcohol or gambling violations on a case-by-case basis; consequently, practice policy might be very different from the formal rules described by official school documentation.
Opportunities for Future Research
This study has shown that there are many opportunities and perhaps an obligation to scientifically investigate the complex relationships between college alcohol and gambling policies and addictive behaviors. Future research, for example, should focus on policy enforcement and informal policies adopted by school administrators to provide a better understanding of current college practices regarding alcohol use and abuse. In addition, as schools begin to reevaluate and amend their substance abuse policies, longitudinal research could provide insight into the effects of policy revision on student behaviors. In addition, to advance our understanding of policy effects on intemperate patterns of behavior, future college-based research will need to examine the influence of policies on more specific behaviors. New research should deconstruct the macro indices (e.g., average rates) of binge drinking to determine whether policies can impact college violence, crime, driving under the influence, etc.
College alcohol and gambling policy data holds important potential for future research. For example, for students with alcohol or gambling related disorders attending colleges with policies that interfere with treatment or fail to support recovery, the rate of relapse is likely to be higher than under a more treatment favorable public policy context. Similarly, research can demonstrate that policies can influence the likelihood of early identification and intervention: under some unsympathetic regimes, students with addiction problems will not come forward for assistance or adhere to a prescribed treatment program. Finally, new research needs to show that without supportive policies to guide college staff responses to treatment seeking students, this population will miss both the college experience and the opportunity to build a healthy foundation for their future.
Conclusions
In this study, we analyzed a representative sample of U.S. colleges to determine the attentiveness of school policies toward students with addictive disorders and their recovery. The results encourage the development and implementation of reporting tools (e.g., a rating system) that could prove valuable as both a resource for parents of at-risk students and a vehicle to raise public awareness. Identifying trends in collegiate policymaking as well as distinguishing strong and weak policies will allow us to begin to develop evidence based guidelines, or "best practices," upon which schools can base the development of future policy.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
HS conceived the study, was its principal architect, and was responsible for its overall conduct and exposition. AD was responsible for the data acquisition, adjudicated the reviewer ratings, and contributed to the drafting of the manuscript. RL was responsible for the statistical design, execution, and exposition. RK provided direct assistance to AD and participated in the preparation of the manuscript. DL contributed to the study structure, data analyses, and manuscript preparation. All the authors were members of the team that critically reviewed and coded the college policies. All authors read and approved the final manuscript.
Acknowledgements
The authors extend special thanks to Gabriel Caro, Peter Emerson, Lymari Graciano, Sarah Nelson, Christine Reilly, Michael Stanton, Chrissy Thurmond, Henry Wechsler and Clare Bruff-Graves for their important contributions to this project. This work was supported in part by funding from the National Center for Responsible Gaming and the Iowa Department of Public Health.
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| 15703082 | PMC549515 | CC BY | 2021-01-04 16:36:50 | no | Harm Reduct J. 2005 Feb 9; 2:1 | utf-8 | Harm Reduct J | 2,005 | 10.1186/1477-7517-2-1 | oa_comm |
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Int Semin Surg OncolInternational seminars in surgical oncology : ISSO1477-7800BioMed Central London 1477-7800-2-31570117510.1186/1477-7800-2-3ReviewPrognostic indicators in peritoneal carcinomatosis from gastrointestinal cancer Harmon Rhonda L [email protected] Paul H [email protected] Washington Cancer Institute, Washington Hospital Center, 110 Irving St., NW, Washington, DC, 20010 USA2005 8 2 2005 2 3 3 18 11 2004 8 2 2005 Copyright © 2005 Harmon and Sugarbaker; licensee BioMed Central Ltd.2005Harmon and Sugarbaker; 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.
Peritoneal carcinomatosis from gastrointestinal cancer has new treatment options for surgical management. The approach uses cytoreductive surgery which combines peritonectomy and visceral resection in an effort to remove all visible cancer within the abdomen and pelvis. Then the peritoneal cavity is flooded with chemotherapy solution in an attempt to eradicate residual disease. In order to select patients for this approach the quantitative prognostic indicators for carcinomatosis were reviewed, compared and contrasted. Prognostic indicators to be used to select patients for this aggressive approach at the initiation of surgery and after completion of cytoreduction were studied. Four quantitative assessments to be used at the time of abdominal exploration were the Gilly staging, Japanese gastric cancer P score, peritoneal cancer index (PCI), and the simplified peritoneal cancer index (SPCI). All have value with the PCI being the most validated and most precise. Preoperative assessments include the tumor histopathology and the prior surgical score. The completeness of cytoreduction score is an assessment of residual disease after a maximal surgical effort. An opportunity for long-term survival following treatment for carcinomatosis requires a complete cytoreduction in all reports for gastrointestinal cancer. Quantitative prognostic indicators need to be knowledgeably employed when patients with carcinomatosis are being treated. Improved patient selection with greater benefit and reduced morbidity and mortality should result.
Carcinomatosisprognostic indicatorsperitonectomycytoreductive surgerycolorectal cancergastric cancerintraperitoneal chemotherapy.
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I. Introduction
Peritoneal carcinomatosis has always been regarded as a terminal condition. It is present in 10 to 30% of patients with gastrointestinal cancer at the time of their initial surgery and is a frequent finding in patients who develop recurrent cancer. Important natural history studies establish a 6-month median survival in this group of patients [1-3]. Recent multicenter phase II and a single phase III study evaluating the usefulness of cytoreductive surgery and perioperative intraperitoneal chemotherapy are promising [4,5]. Patient selection is of utmost importance in optimizing the results of treatment and excluding patients who will not benefit from a high morbidity and potentially life threatening therapy.
Quantitative prognostic indicators are to serve as guidelines in the selection of treatments to maximize benefits of therapy and to exclude patients who have little or no chance to improve. They are of greatest utility in high risk and costly management protocols. Requirements of a useful quantitative prognostic indicator include reproducibility, prediction of survivorship, and assessment of morbidity and mortality. The goal is to establish management protocols that standardize the decision making process for multiple caregivers.
General surgery has used quantitative prognostic indicators in the past with established benefit to patient care. Examples of quantitative prognostic indicators currently in use include Ranson's criteria, which estimates the risk of life threatening complication or death in patients with acute pancreatitis; and, the Child-Pugh score for liver cirrhosis, which evaluates the severity of liver disease correlating grades with one- and two-year survival. Currently, there are several clinical assessments at many different institutions in use for the evaluation of carcinomatosis (see Table 1). Our goal in this manuscript is to critically discuss these quantitative prognostic indicators. Collaborative studies between institutions would be greatly facilitated with standardized clinical tools for management of carcinomatosis from gastrointestinal cancer.
Table 1 Quantitative prognostic indicators currently in use in patients with carcinomatosis.
Tumor histopathology
Intraoperative assessment of the extent of carcinomatosis at time of surgical exploration
• Gilly peritoneal carcinomatosis staging
• Carcinomatosis staging by the Japanese Research Society for Gastric Cancer
• Peritoneal Cancer Index (PCI)
• Dutch Simplified Peritoneal Carcinomatosis Index (SPCI)
CT PCI
Prior Surgical Score
Completeness of Cytoreduction Score
II. Histopathology
In patients with carcinomatosis from gastrointestinal cancer, invasive implants are disseminated within the peritoneal cavity. However, in two conditions the biological aggressiveness of the disease will have a broad spectrum. These two diseases are mucinous appendiceal malignancies (oftentimes clinically designated pseudomyxoma peritonei syndrome) and peritoneal mesothelioma. In these diseases a non-invasive process may be widely disseminated on the peritoneal surfaces. The biological aggressiveness of the malignancy can be estimated by the pathologist in a knowledgeable histologic review of multiple specimens. For pseudomyxoma peritonei syndrome, the histologic classification described by Ronnett and colleagues has been most widely utilized [6].
Histopathologic examination categorizes the disease process into disseminated peritoneal adenomucinosis (DPAM), peritoneal mucinous carcinoma (PMCA) or a hybrid type.
Disseminated Peritoneal Adenomucinosis
This is a minimally invasive disease, and therefore more likely to be completely removed by cytoreduction using peritonectomy. The histology of DPAM shows a bland single layer of epithelium that surrounds lobules of mucin. There are no signet rings and there is minimal atypia. Invasion of the structures upon which tumor accumulates does not occur. The primary site for DPAM is an appendiceal adenoma which has minimally invaded the wall of the appendix. Usually, the widespread intraperitoneal dissemination of mucinous tumor is caused by a rupture of the lumen of the appendix from pressure built up by the malignant mucocele. Figure 1 shows the typical disruption of the wall of the appendix by tumor. Figure 2 presents the histologic character of DPAM.
Figure 1 Right colon, terminal ileum and mucocele of the appendix. This appendix is greatly dilated; the end has ruptured releasing mucus and adenomatous epithelial cells into the free peritoneal cavity.
Figure 2 Histopathology of disseminated peritoneal adenomucinosis (DPAM). (H+E × 200)
Peritoneal Mucinous Adenocarcinoma
This is an invasive disease in which the mucinous cancer cells show invasion into surrounding tissues. Sometimes, the signet ring morphology or lymph node metastases are present. The cancer cells will be found in multiple layers surrounding the mucinous tumor globules. There is loss of nuclear polarity and atypia is common. The quantity of mucus may be variable from one patient to the other. However, the PMCA histology may be associated with very large amounts of mucoid ascites fluid. Therefore, it is categorized as pseudomyxoma peritonei syndrome but with an aggressive tumor histology. Figure 3 provides an example of PMCA.
Figure 3 Histopathology of peritoneal mucinous adenomucinosis (PMCA). (H+E × 700)
Hybrid Type Disease
In the hybrid type of mucinous carcinomatosis the field of view for the pathologist shows 95% or more DPAM. PMCA is present but in 5% or less of the total field of view (figure 4). If there is more than 5% PMCA the histology is no longer hybrid type but designated as PMCA.
Figure 4 Histopathology of hybrid type mucinous appendiceal malignancy. (H+E × 100)
Not surprisingly, the observation has been made by numerous groups that the non-invasive mucinous tumors (DPAM and hybrid type) are amenable to complete cytoreduction. Therefore more definitive treatment and improved survival using the combined approach is expected with DPAM and hybrid type [7]. The histologic and clinical differences between the different types of mucinous appendiceal and other gastrointestinal mucinous tumors are shown in Table 2.
Table 2 Histopathologic features of epithelial mucinous tumors of appendiceal, colonic, and small bowel origin are designated as disseminated peritoneal adenomucinosis (DPAM) and peritoneal mucinous carcinomatosis (PMCA).
Features DPAM PMCA
Primary site Appendix Appendix, colon, small intestine
Primary diagnosis Mucinous adenoma usually in a mucocoele Mucinous adenocarcinoma
Surgical appearance Mucinous tumors and mucinous ascites with redistribution Carcinomatosis with variable amounts of mucinous ascites, redistribution is prominent with large volume of ascites
Peritoneal tumor
• Cellularity Scant Moderate to abundant
• Morphology Abundant extracellular mucin containing simple to focally proliferative mucinous epithelium. There is a single layer of cells Moderate to abundant extracellular mucin containing extensively proliferative mucinous epithelium or mucinous glands, clusters of cells, or individual cells consistent with carcinoma
• Cytologic atypia Minimal Moderate to marked
• Mitotic activity Rare Infrequent to frequent
Lymph node involvement Almost never Moderate
Liver metastases Almost never Very infrequent
Parenchymal organ invasion Rare (except ovary) Frequent
Hybrid type tumors show less than 5% of PMCA within DPAM. Mucinous carcinomas are divided into three grades by maintenance or loss of glandular architecture.
III. Intraperitoneal Assessment of the extent of Carcinomatosis
The quantitation of tumor found at the time of surgical exploration of the abdomen has proven to be of value in assessment of prognosis and treatment planning. Four different assessments have been published. They are listed in Table 1.
Gilly Peritoneal Carcinomatosis Staging
The Gilly peritoneal carcinomatosis staging format was first described in Lyon in 1994 [8]. This prognostic tool takes into account the size of lesions found at operation (table 3). Two advantages of this system are simplicity and reproducibility. The utility of the Gilly staging device in survivorship prediction has been demonstrated in the multicentric prospective EVOCAPE study which gathered data from 370 patients with peritoneal carcinomatosis from non-gynecologic malignancies [2]. A significant difference was observed between stages 1 and 2 with a median survival of 6 months and stages 3 and 4 whose median survival was 3 months. The Gilly carcinomatosis staging has also been validated in patients having combined treatment for carcinomatosis [9].
Table 3 Gilly peritoneal carcinomatosis staging.
Stage Peritoneal carcinomatosis description
Stage 0 No macroscopic disease
Stage 1 Malignant implants less than 5 mm in diameter Localized in one part of the abdomen
Stage 2 Diffuse to the whole abdomen
Stage 3 Malignant implants 5 mm to 2 cm
Stage 4 Large malignant nodules (more than 2 cm)
Although the Gilly system has been used for almost a decade with acceptable prognostic value, there are some criticisms regarding this system. First, it should not be designated a "staging system" because patients can only be staged once in the course of their disease at the time of diagnosis of the primary malignancy. Usually, a TNM staging system is appropriate. The system might better be called the Gilly prognostic index for carcinomatosis.
A second weakness of the Gilly prognostic index concerns a failure to quantitate distribution of peritoneal surface implants in the stage 3 and 4 categories. Carcinomatosis confined to one portion of the abdomen may carry an excellent prognosis even if the localized tumor implants are of large size. If group III and group IV nodules by size are diffuse throughout the whole abdomen, certainly a much different prognosis would occur. A definitive assessment of not only the size of the nodules but also the distribution of carcinomatosis is necessary for the most accurate assessment of prognosis.
The Japanese have proposed a quantitation of carcinomatosis that is very simple, has been frequently applied, and has been validated for gastric malignancy. For the original staging a "P factor" is indicated for gastric cancer patients. P-0 means that no carcinomatosis was seen by the surgeon or could be established at the time of surgery. It would currently include patients who are cytology positive for gastric cancer cells. P-1 indicates implants immediately adjacent to the stomach and above the transverse colon. P-2 indicates scattered implants within the abdomen but not of great number. P-3 indicates numerous implants throughout the abdomen and pelvis.
This staging system can also be applied to patients who have carcinomatosis with recurrent gastric cancer. A major deficit of this staging system is its inability to accurately locate the carcinomatosis. Also, it has no size assessment of the cancerous implants. Although the P factor has been of great value historically in the management of primary gastric cancer as peritonectomy and intraperitoneal chemotherapy are used for treatment of carcinomatosis, a more precise prognostic assessment is needed to manage gastric cancer peritoneal seeding.
Peritoneal Cancer Index
The Peritoneal Cancer Index (PCI), like the other carcinomatosis assessments, is determined at the time of surgical exploration of the abdomen and pelvis. With invasive cancer it serves as an estimate of probability of complete cytoreduction and has been found to be an accurate assessment of survival when cytoreductive surgery and perioperative intraperitoneal chemotherapy are used as treatment [10].
The PCI quantitatively combines the distribution of tumor throughout 13 abdominopelvic regions with a lesion size score. Two transverse and two sagittal planes divide the abdomen into 9 regions. The upper transverse plane is located at the lowest aspect of the costal margin, and the lower transverse plane is placed at the anterior superior iliac spine. The sagittal planes divide the abdomen into three equal sectors. The lines define 9 regions, which are numbered in a clockwise direction with 0 at the umbilicus and 1 defining the space beneath the right hemidiaphragm. Regions 9 through 12 divide the small bowel into upper and lower jejunum and upper and lower ileum (Figure 5). To make the PCI tool more quantitative and reproducible, each region is not only defined by the surface landmarks as previously described, but can also be defined by the anatomic structures found in each region (Table 4).
Figure 5 Peritoneal cancer index (PCI). Two transverse planes and two sagittal planes divide the abdomen into 9 regions. The upper transverse plane is located at the lowest aspect of the costal margin and the lower transverse plane is placed at the anterior superior iliac spine. The sagittal planes divide the abdomen into three equal sectors. The lines define the nine regions which are numbered in a clockwise direction with 0 at the umbilicus and 1 defining the space beneath the right hemidiaphragm. Regions 9–12 divide the small bowel. Lesion size score is determined after complete lysis of all adhesions and the complete inspection of all parietal and visceral peritoneal surfaces. It refers to the greatest diameter of tumor implants that are distributed on the peritoneal surfaces. Primary tumors or localized recurrences at the primary site that can be removed definitively are excluded from the lesion size assessment. If there is confluence of disease matting abdominal or pelvic structures together, this is automatically scored as L-3 even if it is a thin confluence of cancerous implants.
Table 4 Anatomic structures involved in the 13 abdominopelvic regions of the peritoneal cancer index (PCI).
Regions Anatomic structures
0 Central Midline abdominal incision – entire greater omentum – transverse colon
1 Right upper Superior surface of the right lobe of the liver – undersurface of the right hemidiaphragm – right retro hepatic space
2 Epigastrium Epigastric fat pad – left lobe of the liver – lesser omentum – falciform ligament
3 Left upper Undersurface of the left hemidiaphragm – spleen – tail of pancreas – anterior and posterior surfaces of the stomach
4 Left flank Descending colon – left abdominal gutter
5 Left lower Pelvic sidewall lateral to the sigmoid colon – sigmoid colon
6 Pelvis Female internal genitalia with ovaries, tubes and uterus – bladder, Douglas pouch – rectosigmoid colon
7 Right lower Right pelvic sidewall – cecum – appendix
8 Right flank Right abdominal gutter – ascending colon
9 Upper jejunum
10 Lower jejunum
11 Upper ileum
12 Lower ileum
The lesion size (LS) score is determined after complete lysis of all adhesions and complete inspection of all parietal and visceral peritonea surfaces within the abdominopelvic regions. LS-0 indicates no implants seen. LS-1 indicates implants less than 0.25 cm. LS-2 indicates implants between 0.25 and 2.5 cm. LS-3 indicates implants greater than 2.5 cm. It refers to the greatest diameter of tumor implants that are distributed on the peritoneal surfaces. Primary tumors or localized recurrences at the primary site that can be removed definitively are excluded from the assessment. If there is a confluence of disease matting abdominal or pelvic structures together, this is automatically scored as LS-3 even if it is a thin layer of cancerous implants.
The lesion sizes are then summated for all abdominopelvic regions. The extent of the disease within all regions of the abdomen and pelvis is indicated by a numerical score from 0 to 39.
In 1995, Sugarbaker and Jablonski published that the PCI was a meaningful assessment for colon cancer but not for mucinous appendiceal tumors [11]. Elias et al., found survival to be more favorable in those patients with carcinomatosis from colon cancer with a PCI score of less than 16 [12]. In a larger number of patients Sugarbaker and Chang established survivorship using the PCI [13]. Five-year survival was 50% in colon cancer patients with carcinomatosis with a PCI less than 10, 20% for 11–20 and 0% in those with a PCI score greater than 20 (Figure 6). Tentes and colleagues validated the PCI for ovarian cancer [14]. The PCI is not only useful as a prognostic indicator but also as a guide for sequential determinations of volume of carcinomatosis over time estimating the likelihood of a complete cytoreduction at re-operative surgery [15].
Figure 6 Peritoneal carcinomatosis from colon malignancy survival by peritoneal cancer index. (Modified from Reference 13)
This quantitative prognostic indicator for colon carcinomatosis established that for patients scoring greater than 20, palliation is the goal of treatment. Currently, a PCI of greater than 20 is regarded as a relative contraindication to an elective intervention for carcinomatosis from colon cancer. It is associated with a low median survival, approximately the same as median survival without surgical intervention. In patients who have a PCI greater than 20, palliative surgery is indicated in order to alleviate symptoms or to prevent symptoms that may occur in the near future. In an asymptomatic patient with colon carcinomatosis cytoreductive surgery with intraperitoneal chemotherapy with cure as a goal of treatment is probably not indicated.
An exception to the utility of the PCI is found in treating patients with pseudomyxoma peritonei and minimally aggressive mesothelioma. Because the disease is non-invasive, a PCI of 39 can be converted to 0 by cytoreductive surgery. There is a low probability of recurrence after complete cytoreduction with perioperative intraperitoneal chemotherapy and therefore the PCI has no prognostic implication [7].
Another caveat that must be observed when using the PCI occurs in cases in which a low PCI score is recorded in the presence of invasive cancer at a crucial anatomic site. For example, at exploration one may find invasive tumor in and around the common bile duct with little disease elsewhere. Even thought the PCI is low, a complete cytoreduction may not be possible. In these cases, invasive cancer at a crucial anatomic site places the patient into the same category as would systemic metastasis in the lungs or bone. Only palliative surgery is indicated if residual disease post-cytoreduction will be present.
Simplified Peritoneal Cancer Index
The Simplified Peritoneal Cancer Index (SPCI) was established at the Netherlands Cancer Institute and has been used for colorectal and appendieal cancer staging (Table 5). This tool has prognostic implication for survival following cytoreductive surgery and hyperthermic intraperitoneal chemotherapy [16].
Table 5 Simplified Peritoneal Cancer Index
◆ Tumor is recorded as:
indent="1" • Large (> 5 cm)
indent="1" • Moderate (1–5 cm)
indent="1" • Small (< 1 cm)
indent="1" • None
◆ Seven abdominal regions:
indent="1" • I: pelvis
indent="1" • II: right lower abdomen
indent="1" • III: greater omentum, transverse colon and spleen
indent="1" • IV: right subdiaphragmatic area
indent="1" • V: left subdiaphragmatic area
indent="1" • VI: subhepatic and lesser omental area
indent="1" • VII: small bowel and small bowel mesentery
Verwaal and colleagues have provided important information regarding the relationship of the Simplified Peritoneal Cancer Index and the incidence of complications in patients who receive combined treatment [17]. In their review of the toxicity of combined treatment, complications increased when the cancer index recorded involvement of more than five regions (p = 0.044). Also, if the patient had recurrent colon cancer (as opposed to carcinomatosis with primary cancer) or if there was an incomplete cytoreduction, the incidence of complications was significantly higher. Verwaal et al., established that the peritoneal cancer index quantitated not only the survival outcome of these patients but also the expected morbidity and mortality of the combined treatment [16].
There are marked similarities between the SPCI and the PCI. Both the anatomic distribution of the tumor masses and the size of the tumor masses within each abdominal region are indicated. In the PCI, there are 13 anatomic sites designated by a diagram; in the Dutch SPCI, there are 7 anatomic regions designated by anatomic site. In both systems the volume of tumor in each region is to be scored quantitatively. Some shortcomings of the SPCI could be formulated. First, the epigastric region, very important in determining the completeness of cytoreduction in some diseases is not designated separately. Disease above the stomach in the lesser omental region may cause the cytoreduction to be incomplete [15].
A second major criticism of the Dutch SPCI concerns their misuse of their own tool. In their recent publications they perform a survival analysis by SPCI and a toxicity assessment by the SPCI. However, only the involvement of regions 0–7 was indicated. No tumor size in the regions was indicated [16,17].
Prior Surgical Score
An accepted fact regarding cancer treatment is that the optimal treatment with the highest cure rate, the greatest preservation of function, and the lowest morbidity and mortality is the initial treatment. In the management of carcinomatosis the extent of prior resection before definitive cytoreduction with intraperitoneal chemotherapy has a negative impact on the survival. This occurs because of the cancer cell entrapment phenomenon. Surgery opens tissue planes whose raw surface is a favored site for cancer cell adherence, vascularization and progression. In the use of combined treatment for carcinomatosis, the non-traumatized peritoneal surface is the body's first line of defense against carcinomatosis. Cancer progression deep to peritoneal surfaces, especially disease imbedded in scar, is difficult or impossible to remove by peritonectomy or to eradicate by intraperitoneal chemotherapy.
The prior surgical score (PSS) quantitates the extent of surgery prior to definitive combined treatment. It shows that the greater the surgery the poorer the results of carcinomatosis treatment. The assessment uses a diagram similar to that for PCI but excludes abdominopelvic regions 9–12. For a PSS of 0 no prior surgery or only a biopsy was performed; PSS of 1 indicates one region with prior surgery; PSS-2 indicates 2 to 5 regions previously dissected; PSS-3 indicates more than 5 regions previously dissected. This is equivalent to a prior attempt at complete cytoreduction but in the absence of perioperative intraperitoneal chemotherapy. In appendiceal cancer patients with a prior surgical score of 0–2, the survival using combined treatment was 70% at 5 years; with a prior surgical score of 3, the 5-year survival was 51% (p = 0.001) [18].
Completeness of Cytoreduction Score
The Completeness of Cytoreduction Score functions as a major prognostic indicator for the survival in peritoneal mesothelima, colon cancer with carcinomatosis, gastric cancer with carcinomatosis and sarcomatosis [7]. It is to be assessed after cytoreductive surgery is completed. Complete cytoreduction (CC-0 or CC-1) or incomplete (CC-2 or CC-3) are determined. A CC-0 is apparent when there is no peritoneal seeding visualized within the operative field. CC-1 indicates nodules persisting after cytoreduction less than 2.5 cm. CC-2 has nodules between 2.5 and 5 cm, whereas a CC-3 indicates nodules greater than 5 cm or a confluence of unresectable tumor nodule at any site within the abdomen or pelvis. The CC-1 tumor nodule size is thought to be penetrable by intracavitary chemotherapy and is, therefore, designated as complete cytoreduction if perioperative intraperitoneal chemotherapy is used.
Sugarbaker and colleagues found that prognosis can be estimated by completeness of cytoreduction. For colon cancer as shown in Figure 7, there is a 40% chance of survival at 5 years in those who undergo complete cytoreduction versus 0% survival in the incomplete category [7,13]. Numerous other groups have confirmed the complete cytoreduction as a requirement for survival after treatment of carcinomatosis from appendiceal, colorectal and gastric cancer [4,9,11,12,16-19].
Figure 7 Peritoneal carcinomatosis from colon malignancy survival by cytoreduction. (Modified from Reference 13)
Although no formal statement in the literature is available, it is thought that the definition of complete vs. incomplete cytoreduction varies with the histologic type of the malignancy. For example, mucinous tumors by diffusion are well penetrated with intraperitoneal chemotherapy solutions. With minimally invasive mucinous tumors such as pseudomyxoma peritonei, complete cytoreduction may occur in the combined treatment plan with tumor nodules up to a full centimeter in size. In contrast, hard fibrotic non-mucinous colon cancer is poorly penetrated by chemotherapy solution. Only cytoreduction down to no visible evidence of disease would be expected to result in long-term survival with a sclerotic malignant process. Also, some cancers may be remarkably more responsive to chemotherapy than others. This is likely the case with a majority of ovarian cancers. Their complete response to systemic chemotherapy is also frequently seen with intraperitoneal chemotherapy solutions or a bidirectional (intraperitoneal combined with intravenous chemotherapy) approach. In both these situations the definition of a complete cytoreduction scored by a CC-1 designation would vary with the clinical situation.
Computerized Tomographic PCI
The preoperative CT is an excellent tool in locating and quantifying mucinous adenocarcinoma within the peritoneal cavity [20]. Unfortunately, with intestinal histologic type of colon cancer the accuracy of the CT is considerably reduced [21]. However, for mucinous carcinomatosis CT scanning is an accurate prognostic indicator of the possibility of resectability. It may show segmental obstruction of the small bowel or tumor nodules greater than 5 cm on small bowel. Patients who have both of these findings have a likelihood of less than 5% of complete cytoreduction. Obstructed segments of bowel signal an invasive character of malignancy on small bowl surfaces that would be unlikely to be completely cytoreduced. Large tumor nodules on small bowel or its mesentery are unlikely to be adequately cytoreduced without visceral resection.
There are some special demands on CT scanning if the radiologic examination is to be optimized. Bowel loops cut in cross section are often indistinguishable from cancer nodules. Only if maximal oral contrast using a barium sulfate compound is utilized to prepare the patient for this examination can the greatest accuracy and the greatest prognostic implications of the examination be realized.
Another technical requirement is the imaging of solid tumor layered out on the peritoneal surfaces. Unless there is maximal intravenous contrast with a 60 to 120 second delay after contrast infusion will the confluence of malignancy as a thin layer on the peritoneum be imaged. In some patients, the solid tumor, or semisolid tumor may be distributed to appear as ascites on abdominal and pelvic CT. Much to the surgeon's dismay, upon opening the abdomen, a solid tumor mass filling the abdomen and pelvis and causing adherence of small bowel and small bowel mesentery will be revealed. In this situation, not even palliative surgery can be safely performed. In patients who clinically have a firm abdomen and in whom the surgeon suspects large volume of solid tumor, an ultrasound examination may be required in order to confirm an ascitic versus a solid component of the abdominal and pelvic malignancy. If ultrasound shows that there is only minimal or no ascites and that the large volume of tumor is solid or semisolid, surgical interventions are not beneficial. It is better to determine the nature of the carcinomatosis radiologically than at the time of a major surgical exploration.
Conclusion
Quantitative prognostic indicators are of value in management of peritoneal surface malignancy from gastrointestinal cancer. Preoperative CT PCI, intraoperative PCI and postresection CC score have all been reported valuable. As one knowledgeable applies these tests, proper selection of patients for combined treatment may increase benefit and decrease morbidity and mortality.
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| 15701175 | PMC549516 | CC BY | 2021-01-04 16:38:37 | no | Int Semin Surg Oncol. 2005 Feb 8; 2:3 | utf-8 | Int Semin Surg Oncol | 2,005 | 10.1186/1477-7800-2-3 | oa_comm |
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Immun AgeingImmunity & ageing : I & A1742-4933BioMed Central London 1742-4933-2-31570519810.1186/1742-4933-2-3Short ReportLDL receptor expression on T lymphocytes in old patients with Down syndrome Corsi Massimiliano M [email protected] Alexis E [email protected] Daniele [email protected] Federico [email protected] Institute of General Pathology, Laboratory of Clinical Pathology, Faculty of Medicine, University of Milan, Italy2 Department of Experimental Pathology, Section of Immunology, Faculty of Medicine, University of Bologna, Italy2005 10 2 2005 2 3 3 7 2 2005 10 2 2005 Copyright © 2005 Corsi et al; licensee BioMed Central Ltd.2005Corsi 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 Down syndrome patients several metabolic abnormalities have been reported, some involving the lipid metabolism. The level of LDL in plasma is the major determinant of the risk of vascular disease. There appear to be no studies on the LDL receptor in Down syndrome patients.
Methods
Flow cytometric methods for measuring the LDL receptor in peripheral blood mononuclear cells (PBMC) can identify patients with hypercholesterolemia. We applied this method in 19 old patients with Down syndrome and 23 healthy controls.
Results
Down syndrome patients had high levels of triglycerides and low levels of HDL, and high levels of CRP. We also found a down-regulation of LDL receptor expression.
Conclusions
Down syndrome patients show no increase in the frequency of cardiovascular disease. The low incidence in cardiovascular disease despite the low level of HDL, high levels of CRP and reduction of LDL receptor expression lead to the conclusion that either these are not risk factors in these patients or that other risks factors – not yet identified – are considerably lower.
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Introduction
Several studies have discussed the psychological and intellectual problems, immunological deficiencies, and early aging of Down syndrome (DS) patients. Several metabolic abnormalities have been reported, some involving the lipid metabolism [1]. Apart from some contradictory studies in the past, there are only few investigations of the cholesterol fractions in DS patients. Therefore, it must be concluded that the low prevalence of coronary artery disease in individuals with DS cannot be explained by their cholesterol fractions. Mortality statistics of these patients showed practically no deaths due to advanced atherosclerosis [2], and similarly, pathological studies have detected no increase in atherosclerosis – or even a complete absence of atherosclerotic changes [3].
In children [4] and also adolescents [5] with DS low levels of high-density lipoprotein (HDL) have been reported and recently, we have learned much about the vasoprotective HDL cholesterol [6]. Anyway DS remains a disease in which atherosclerosis is rare [7].
Measurements of LDL receptor expression are also necessary to fully characterize the functional status of the low-density lipoprotein (LDL) pathway which substantially influences LDL levels in plasma, and its discovery constituted a major biological advance by providing molecular explanations of hypercholesterolemia. The plasma LDL level is the major determinant of the risk of vascular disease. We analyzed, also, C reactive protein (CRP), a cardiovascular risk factors coded by genes lying on Chromosome 21. Flow cytometric methods for measurement of LDL receptor on peripheral blood mononuclear cells (PBMC) may be used to identify patients with familial hypercholesterolemia [8]. Data in uremic patients suggest that a defect in LDL receptor function in PBMC may be due to a decrease in LDL receptor expression, which could contribute to the aberrant lipoprotein metabolism [9].
We therefore investigated LDL receptor expression on uninduced PBMC, particularly T lymphocytes because they express more LDL receptors than monocytes [10]. Since the progression of atherosclerosis is age-dependent, LDL receptor interactions are important in lipid plaque formation and T cells are present in early atherosclerotic lesions, interacting with LDL through the LDL receptor [11], we studied LDL expression on T lymphocytes in a group of old patients with DS.
Methods
Blood samples were drawn from 19 old DS patients (male, average age 55 years) and 23 healthy individuals (male, average age 55 years) without dyslipidemia or any family history of coronary heart disease, no smokers or drunkers, with a Body Mass Index (BMI) < 25. Lipid measurements are given in Table 1. Plasma C reactive protein (CRP) concentration form DS and control was evaluated by LANIA (Latex Agglutination Nephelometric Immunoassay) technique (Biolatex, Spain). Samples were diluted 1:36 and results were calculated automatically by IMMAGE system. The minimum detectable concentration was 0.4 mg/dl.
Table 1 Cholesterol fractions in old patients with Down syndrome and healthy subjects. Means ± SD.
Healthy subjects Down syndrome
Total cholesterol 150 ± 19.64 152 ± 28.79
Triglycerides 55.9 ± 21.46 104.5 ± 50.2
HDL-cholesterol 48.4 ± 10.5 40.6 ± 4.24
LDL-cholesterol 88.3 ± 17.2 89 ± 24.4
None had been treated with lipid-lowering drugs before blood sampling. This study was conducted in accordance with the Declaration of Helsinki, 1975, amended in 1983.
Blood, collected in tubes containing EDTA, was cooled to 20°C and diluted 1:1 with Hank's buffered saline solution (HBSS, Biochrome, Biospa, Milan, Italy). PBMCs were prepared under sterile conditions, using Ficoll-Hypaque (Pharmacia Biotech, Milan, Italy) and diluted blood was layered in a centrifuge tube and centrifuged for 40 min at 400 g, 20°C. The interface containing the PBMCs was isolated, and the cells were washed three times in HBSS and resuspended in RPMI-1640 (Biochrome, Biospa, Milan, Italy) with L-glutamine (290 mg/L), penicillin (100,000 U/L), streptomycin (100 mg/L) and 100 mL/L human lipoprotein-deficient serum (HLPDS) to a final concentration of 106 cells/mL.
Tissue culture flasks were placed in ice-water for 60 min in the dark to reduce cell adhesion. PBMCs were removed by flushing with ice-cold HBSS (4°C) and washed twice in ice-cold HBSS with 20 mL/L HLPDS. The cell number was adjusted to 0.3 × 106 cells/mL, and 100-μL aliquots of cell suspension were pipetted into polypropylene tubes and placed in ice-water. Cells were incubated with 1.5 μg of monoclonal mouse anti-human LDL receptor-specific antibody, clone C7 (Amersham Life Science, Milan, Italy), for 30 min in the dark at 4°C. After this the cells were washed twice in ice-cold HBSS with 20 mL/L HLPDS, and incubated with 3 μL of fluorescein isothiocyanate (FITC, Dako Cytomation, Milan, Italy) for 30 min in the dark at 4°C. Cells were then incubated with 1 μL of R-phycoerythrin (RPE)-conjugated monoclonal antibody CD3-RPE or IgG1isotype-RPE for T lymphocytes.
The flow cytometry measurements were done in a FACScan flow cytometer (Becton Dickinson, Milan, Italy) equipped with a 15 mW, 488 nm, air-cooled argon laser and linked to a computer with CellQuest software. Forward scatter (FSC) and side scatter (SSC) were adjusted to exclude debris and dead cells. FITC emission was measured at 530 nm (FL1) and RPE emission at 585 nm (FL2); compensation was set using FITC-conjugated C7 (C7 FITC)-labeled cells (FL2-FL1) and CD3-RPE-labeled cells (FL1-FL2).
Means were compared by the unpaired t-test or one-way analysis of variance (ANOVA). Data are presented as means ± SD. Differences were considered statistically significant at p < 0.05.
Results
Table 1 shows cholesterol fractions of DS patients and healthy controls. DS total cholesterol and LDL did not differ from controls (p = 0.8 and p = 0.9 respectively). Blood levels of CRP were higher in DS than in controls, as illustrated in Figure 1(Controls 1.3 ± 0.3; DS = 5.7 ± 4.6 mg/L, p < 0.01). A regression analysis of data shows non relationship among CRP and cholesterol-related molecule levels.
Figure 1 Levels of C reactive protein (CRP) in plasma from children with DS and age matched controls. Data are presented as mean ± S.D.
Triglycerides were higher, and HDL lower in DS patients (p < 0.01 and p < 0.05). Our data also show that the expression of LDL receptor on T lymphocytes was down-regulated in DS patients (Table 2 and Figure 2).
Table 2 Mean fluorescence intensity (MFI, %) of LDL receptor expression in healthy subjects and old patients with Down syndrome. Means ± SD.
Healthy subjects Down syndrome
MFI (%) 196.76 ± 20.54 139.87 ± 13.32
Figure 2 Mean fluorescence intensity (MFI) of LDL receptor expression in healthy subiects (bold line) and Down syndrome old subjects (fine line).
Mean intensity fluorescence (MIF) of LDL receptor expression was significantly different in DS patients and healthy controls (p < 0.0001) (Table 2).
Discussion
Patients with DS who reach adolescence nowadays have a nearly normal life expectancy thanks to better medical care. When they die at a later age, cardiovascular diseases are less common than in the general population and they have even been proposed as "an atheroma-free model" [3]. Our results concerning cholesterol fractions suggest that DS patients should have a cardiovascular disease risk, if conclusions valid for the general population can be transferred to this category of patients. Although serum lipoprotein profiles cannot explain the lower prevalence of cardiovascular disease in individuals with DS, our triglyceride and HDL findings are in line with published figures. Similar findings were reported by other authors but in young patients [4,5].
Multiple factors are responsible for atherosclerosis, such as dietary habits but still the unexplained decline of LDL receptor expression with aging contributes importantly to borderline-high levels and cannot be ignored. For example the loss of estrogen-stimulated LDL receptor synthesis after menopause is an important contributor to elevated cholesterol in postmenopausal women. In addition, several genetic defects inherited singly appear to be causes of moderate hypercholesterolemia [10,12]. Generally defects of LDL receptor expression are associated with a high risk of premature atherosclerosis. In the elderly LDL receptor uptake is unexpectedly increased, and LDL receptor regulation and expression and serum LDL composition seem abnormal. There may also be alterations to the lipid metabolism of immune system cells during aging [13].
In our series, a reduction in LDL receptor expression was not correlated with high LDL serum levels or total cholesterol. Moreover, lipophospholipid (LPC) is generated by hydrolysis of phosphatidylcholine which is present in LDL; LPC may promote the start of an immune response and atherosclerosis may be the most extreme demonstration of this immune regulation pathway [14]. LPC may be a potent super-regulator of T-cell activation by inflammation at sites of tissue damage and in the early stages of atherosclerosis.
Interestingly, DS patients show no increase in their frequency of cardiovascular disease.
These conditions may be explained by mild immune defects in the syndrome, mainly involving macrophages and/or TH1 lymphocytes responses [15]. Alternatively, a over expression of atherosclerotic protective factors -yet unknown- maight be present in Down syndrome. As we reported earlier, the low incidence of cardiovascular disease in these patients and the high-risk factor of oxidatively modified LDL (oxLDL) [16] with – in this study – the low level of HDL, high levels of CRP and reduction of LDL receptor expression, lead to the conclusion that in this group of "healthy old" DS subjects, classical biochemical risk factors for atherosclerosis have been detected but risks, probably, are considerably lower.
List of abbreviations
Down syndrome (DS); high-density lipoprotein (HDL); C reactive protein (CRP); Body Mass Index (BMI); low-density lipoprotein (LDL); peripheral blood mononuclear cells (PBMC); lipophospholipid (LPC).
Competing interest
The author(s) declare that they have no competing interests.
Acknowledgements
This investigation was supported by research grants from BPM Foundation, and from MIUR. We are grateful to J.D. Baggott for English editing, and to Prof. Marco Trabucchi for old DS patients' samples.
==== Refs
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Pueschel SM Craig WY Haddow JE Lipids and lipoproteins in persons with Down's syndrome J Intellect Disabil Res 1992 36 365 369 1388078
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Schireman RB Muth J Toth JP [14C]Acetate incorporation by cultured normal, familial hypercholesterolemia and Down's syndrome fibroblast Biochim Biophys Acta 1988 958 352 360 2963664
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Portman RJ Scott RC Rogers DD Loose-Mitchell DS Lemire JM Weinberg RB Decreased low-density lipoprotein receptor function and mRNA levels in lymphocytes from uremic patients Kidney Int 1992 42 1238 1246 1453609
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Robert L Jacob MP Labat-Robert J Cell-matrix interactions in the genesis of arteriosclerosis and atheroma. Effect of aging Ann N Y Acad Sci 1992 673 331 341 1336648
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Fulgenzi A Wasserman K Corsi MM The significance of lipoperoxidation (MDA) and autoantibodies to oxidatively modified low density lipoproteins (oxLDL) in plasma of Down's syndrome children Clin Chem 2001 47 1135 1137 11375314
| 15705198 | PMC549517 | CC BY | 2021-01-04 16:36:31 | no | Immun Ageing. 2005 Feb 10; 2:3 | utf-8 | Immun Ageing | 2,005 | 10.1186/1742-4933-2-3 | oa_comm |
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J CarcinogJournal of Carcinogenesis1477-3163BioMed Central London 1477-3163-4-51570749810.1186/1477-3163-4-5ResearchColonic Paneth cell metaplasia is pre-neoplastic condition of colonic cancer or not? Wada Ryo [email protected] Toshikazu [email protected] Kenichi [email protected] The Department of Pathology, Juntendo Izunagaoka Hospital of Juntendo University School of Medicine, Shizuoka, Japan2 The Department of Pathology(I), Juntendo University School of Medicine, Tokyo, Japan3 R & D Center, Biomedical Laboratories, Inc, Kawagoe, Japan2005 12 2 2005 4 5 5 6 10 2004 12 2 2005 Copyright © 2005 Wada et al; licensee BioMed Central Ltd.2005Wada 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 carcinogenesis of colorectal cancer has been accepted by a model for a cascade of genetic alterations, named the adenoma-carcinoma sequence. In order to elucidate the carcinogenesis of the colorectal cancer more clearly, the genetic abnormalies of the non-neoplastic mucosal epithelium of the colon and rectum should be investigated. It has been speculated that colonic Paneth cell metaplasia (PaM) is one of the pre-neoplastic mucosa of colonic cancer. Therefore, we studied the propria mucosa of the right colon with PaM from the standpoints of the frequency of the K-ras codon 12 mutations (K-ras), which is initial genetic abnormality in colorectal cancer, and the loss of heterozygosity of microsatellite markers (LOH-MS), which has a relationship to development of colorectal cancer.
Methods
Fifty-two regions with PaM histopathologically from 12 surgically resected right colon specimens were studied. DNA extraction of the colonic mucosa with PaM was obtained using a microdissection method, and the frequency of the K-ras of PaM was investigated by enriched polymerase chain reaction-enzyme linked mini-sequence assay, and the frequency of the LOH-MS (D2S123, D17S250 and D5S346) of PaM was examined by high resolution fluorescenced labeled PCR primers.
Results
K-ras mutation was detected in fifteen regions among 52 PaM (28.9%). All mutations were a single mutation and GGT changed to AGT in eleven and GAT in four. LOH-MS were detected in twenty-one regions among 52 PaM (40.4%) (D2S123: 35.4%, 17/48 regions, D17S250: 13.7%, 7/51 regions, and D5S346: 0%, 0/52 regions). No K-ras mutations and LOH-MS were detected in the controls (Colorectal mucosa with no PaM).
Conclusions
Colonic mucosa with Paneth cell metaplasia may be one of the pre-neoplastic mucosa in the development of the colonic epithelial neoplasia.
Paneth cell metaplasiaK-ras mutationloss of heterozygosity of microsatellite markercolorectal cancermicrodissection
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Background
Vogelstein et al. [1] have reported the involvement of multistage genetic abnormalities in the development of colorectal cancers, and pointed out that K-ras mutation is the initial genetic abnormality in the adenoma-carcinoma sequence [2] of the development of the colorectal cancer. Recently, some reports have pointed out that the replication errors and loss of heterozygosity of the microsatellite markers have the development of the colorectal cancer [3,4].
However, the genetic abnormalities of the non-neoplastic mucosal epithelium of the colon and rectum has not been investigated, except the aberrant crypt foci [5] and hyperplastic polyp [6], although the colorectal epithelial neoplasia is derived from the colorectal mucosal epithelium. For the preventive medicine, the genetic abnormalities of the pre-neoplastic mucosa of the colorectal cancer should be known.
We have speculated previously that the colorectal Paneth cell metaplasia (PaM) is one of pre-neoplastic mucosa on the development of the colorectal epithelial neoplasias [7], because PaM were seen very frequently in the adjacent mucosa to the minute-sized colorectal epithelial neoplasias as well as within these neoplasias.
The main purpose of the present study was to investigate the frequencies of the K-ras codon 12 mutations (K-ras) and the loss of heterozygosity of dinucleotide microsatellite markers (LOH-MS) in the propria mucosa with PaM of the right colon.
Methods
The materials were 12 surgically resected specimens of right colon, which had the colonic carcinomas were present, and histological diagnosis was assessed at the Department of Pathology, Juntendo Izunagaoka Hospital. Although we have intended to investigate the PaM in the normal colon of the individuals without cancer, using the biopsies specimens, it was difficult to detect the PaM in these specimens. No inflammatory bowel diseases were included in the materials. Informed consent was obtained from all the patients to investigate the genetic alterations in the current study.
The specimens were fixed in 10 % buffered formalin solution and prepared by cutting the non-neoplasitic area into 3 – 5 mm sections. Each section was embedded in paraffin and stained with hematoxylin and eosin (HE), followed by immunohistochemical staining for anti-lysozyme (DAKO, Japan). Immunohistochemical stainings were performed by the avidin-biotin-peroxidase-complex method, at dilution of 1 : 100.
Fifty-two colonic mucosal regions with PaM, distant from neoplastic lesion, aberrant crypt foci and hyperplastic polyp, were detected by HE staining and anti-lysozyme antibody staining, and these mucosa were used as the target regions in the current study.
All paraffin blocks of the target regions and 12 paraffin blocks with no PaM as controls of each materials were used for the DNA extraction.
DNA extraction
Paraffin blocks with the target foci mentioned above were prepared for DNA extraction. The target foci were microdissected using a 20-gauge needle, comparing the slide with HE staining in the same position. The extracted DNA was diluted with 5 ml of TaKaRa DEXPAT (for DNA Extraction from Paraffin-embedded Tissue, TaKaRa Biomedical Inc.).
Analysis of the K-ras
Mutation of K-ras was analyzed and compared by enriched polymerase chain reaction-enzyme linked mini-sequence assay (PCR-ELMA). In PCR-ELMA [8,9], upstream primer for the first and second PCR was 5'-TAAACTTGTGGTAGTTGG-AACT-3', downstream primer for the first PCR was 5'-GTTGGATCA-TATTCGTC-CAC-3', and downstream for primer the second PCR was 5'-CAAATGAT-CTGA-ATTAGCTG-3'. The first PCR reaction was performed containing 1 μL of DNA lysate, 100 μM dNTP, 1.5 mM MgCl2, 1 μM each primer, 0.625 U Taq DNA polymerase and 1 × PCR buffer [containing 10 mM Tris-HCl(pH 8.3 at 25 degrees of temperature), 50 mM KCl and 0.001%(w/v) gelatin] in a thermal cycler. Then, 10 μL of the denatured second PCR product was hybridized with probes to detect the K-ras codon 12 wild-type (GGT) and six mutant (GAT, GCT, GTT, AGT, CGT and TGT) DNAs were immobilized, at 55 degrees of temperature for 30 minutes, and 100 μL of biotinylated A and 0.01 U of TdqDNA polypmerase were added and incubation was continued at 55 degrees of temperature for 30 minutes.
For development, 100 μL of avidin-horseradish peroxidase conjugate was added and the reaction was performed at room temperature for 30 minutes. Then, 100 μL of tetramethyl-benzidine (TMB) substrate was added and the plates were left to develop in the dark at room temperature for 20 minutes. Finally, 100 μL of stop solution was contained and the light absorbance of each sample was measured by spectrophotometry (Multiskan Multisoft, Labsystems, Tokyo) with a 450 nm filter wavelength (Figure 1).
Figure 1 Enriched polymerase chain reaction-enzyme linked mini-sequence assay (PCR-ELMA), showing K-ras codon 12 mutation in the colonic Paneth cell metaplasia. AGT-type mutation was seen in line 3.
Analysis of the LOH-MS
Although we have intended to investigate the frequency of microsatellite instabilities using five microsatellite markers, which has been recommended by National Cancer Institute[10], the replication error or microsatellite instabilities could not be detected. Although the true reasons for these failures was not know, we may think that the target foci were too small and post-formalin solution condition with long time.
Therefore, only LOH was investigated described below. Three dinucleotide microsatellite markers (D2S123, D17S250 and D5S346) were selected for LOH among the microsatellite markers, recommended by National Cancer Institute, because commonly it has been thought to be difficult to study the LOH using mononucleotide microsatellite markers.
These LOH-MS were investigated using high resolution fluorescenced labeled PCR primers in proportion to the method of Tsuchida et al. [11]. The outline of it : 1. PCR was performed containing 1 μL of DNA lysate, 100 μM dNTP, 1.5 mM MgCl2, 1 μM each primer marked with fluorescent dye of three colors as blue, green and yellow, 0.625 U Taq DNA polymerase and 1 × PCR buffer [containing 10 mM Tris-HCl(pH 8.3 at 25°C), 50 mM KCl and 0.001%(w/v) gelatin] in a thermal cycler. 2. The electrophoresis was conducted 2 hours by means of an ABI-377 DNA auto-sequencer (PE Biosystems, Inc., Foster City, CA, USA). 3. A comparison was made of peaks of same marker arising from normal tissue and the propria mucosa with PaM, using the Gene Scan TM waveform analyzed softwave, and LOH were assessed. That is to say, LOH (+) was assessed when the ratio of the peak area of (the propria mucosa with PaM/normal tissue) was less than 70 % or was more than 143 %.
The data were analyzed statistically with Student's t-test (t-test) and chi-square test ; a p-value of less than 0.05 was considered to be significant.
Results (Table 1)
Table 1 K-ras mutation and the loss of heterozygosity of microsatellitemarkers of colonic Paneth cell metaplasia
K-ras* D2S123 D17S250 D5S346 Total LOH*
PaM 28.9% 35.4% 13.7% 0% 40.4%
(15/52) (17/48) (7/51) (0/52) (21/52)
Normal 0% 0% 0% 0% 0%
(0/8) (0/8) (0/8) (0/8) (0/8)
PaM : Colonic Paneth cell metaplasia,
Normal : Normal colonic mucosa, K-ras : K-ras codon 12 mutation,
* : between PaM and Normal, p < 0.01, chi-square test
K-ras mutation was detected in fifteen regions among 52 PaM (28.9 %). All mutations were a single mutation. For K-ras mutation patterns, 11 showed GGT to AGT, and four showed to GAT.
LOH-MS was detected in twenty-one regions among 52 PaM (40.4 %) (D2S123: 35.4 %, 17/48 regions, D17S250: 13.7 %, 7/51 regions, and D5S346: 0 %, 0/52 regions). No K-ras mutations and LOH-MS were detected in the controls (Colorectal mucosa with no PaM, no neoplastic lesion, no aberrant crypt foci and no hyperplastic polyp).
Thus, the frequency of both K-ras mutation and LOH-MS in the colonic mucosa with PaM were significantly higher than those of the controls (p < 0.01, chi-square test).
Discussion
K-ras mutations have been detected in several human neoplasias [12-14], and it has been pointed out that K-ras mutation is the initial genetic abnormality in the development of the colorectal cancers [1]. Recently, the replication errors of the gene is thought to be important in the development of the colorectal cancer. And the loss of heterozygosity of the microsatellite markers, which are often used as the targets in the investigation for the replication errors of the gene, is also considered to be important in the development of the colorectal cancer [3,4]. Namely, the carcinogenesis of colorectal cancer is almost clarified.
In order to conclude the carcinogenesis of the colorectal cancer more clearly, the genetic abnormality of the non-neoplastic mucosal epithelium of the colon and rectum should be investigated, however, because the colorectal cancers are derived from the colorectal mucosa. It is also important for the preventive medicine of the colorectal cancer to know the carcinogenesis of it.
However, until now, the genetic abnormalities of the colorectal non-neoplastic mucosa is unclear, except the aberrant crypt foci [5] and hyperplastic polyp [6].
We have already reported that the colorectal Paneth cell metaplasia (PaM) is one of pre-neoplastic mucosa on the development of the colorectal epithelial neoplasias [7], because PaM were seen very frequently in the adjacent mucosa to the minute-sized colorectal epithelial neoplasias and within these neoplasias.
Therefore, K-ras mutation and the loss of heterozygosity of microsatellite markers of PaM were investigated in this study, and the current study is thought to be the first report focusing on this.
Our results showed that K-ras mutation was detected in fifteen regions among 52 PaM (28.9%), and LOH-MS was detected in twenty-one regions among 52 PaM (40.4%).
Namely, K-ras mutation and LOH-MS of PaM were not rare and the frequency of those of PaM were higher than those of the normal colonic mucosa, and it came to light that some PaM had the genetic abnormalities which had a relationship to the development of colorectal cancer.
Paneth cells, which are usually situated at the base of the glands of the small intestine, were first identified by Scwalbe [15] in 1872, were studied in detail morphologically by Paneth [16] in 1888.
Now, these cells have been one of the most famous cells in the gastro-intestinal tract, however, the detail function of these is not clear. Paneth cells are sometimes seen in the colorectal tubules, for example in the proximal colonic mucosa of elderly subjects [7,17], in patients with ulcerative colitis [18] and colonic epithelial neoplasia [1,19,20], although the reasons why Paneth cells appear in the large bowel is still unknown.
Described above, many riddles about Paneth cell are still remained. And the gene abnormalities of colonic mucosa with PaM in the current study may be not equal to those of single Paneth cell in the colonic mucosa, because it is difficult to obtain only single Paneth cell in the colonic mucosa, even if microdissection method is used.
However, we have been able to investigate the colonic mucosa with PaM, and we think it very interesting that some PaM have K-ras mutation and the loss of heterozygosity of microsatellite markers, and these PaM may be thought to be the pre-neoplastic mucosa in development of the colonic epithelial neoplasia. Further molecular studies concerning Paneth cell metaplasia in the large bowel should be warranted.
Conclusions
Colonic mucosa with Paneth cell metaplasia may be one of the pre-neoplastic mucosa in the development of the colonic epithelial neoplasia.
Abbreviations
PaM, colonic Paneth cell metaplasia; K-ras, K-ras codon 12 mutations; LOH-MS, loss of heterozygosity of microsatellite markers; HE, hematoxylin and eosin; PCR, polymerase chain reaction; ELMA, enzyme linked mini-sequence assay
Acknowledgements
The authors thank Mr D Mrozek for assistance with the manuscript.
==== Refs
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Smith AJ Stern HS Penner M Somatic APC and K-ras codon 12 mutations in aberrant crypt foci from human colons Cancer Res 1994 54 5527 5530 7923190
Otori K Oda Y Sugiyama K High frequency of K-ras mutations in human colorectal hyperplastic polyps Gut 1997 40 660 663 9203947
Wada R Miwa H Abe H Incidence of Paneth cells in minute tubular adenomas and adenocarcinomas of the large bowel Acta Pathol Jpn 1992 42 579 584 1449053
Matsubayashi H Watanabe H Yamaguchi T Difference in mucus and K-ras mutation in relation to phenotypes of tumors of the papilla of Vater Cancer 1999 86 596 607 10440687
Wada R Yamaguchi T K-ras codon 12 mutations of the super-minute dysplasia in the Barrett's esophagus by DNA extraction using a microdissection method Dis Esophagus 2003 16 214 217 14641312 10.1046/j.1442-2050.2003.00331.x
Boland CR Thibodeau SN Hamiloton SR 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
Tsuchida A Aoki T Kasuya K Micro-satellite instability in multiple and single gastric cancers using fluorescent and auto-sequencer Ann Cancer Res Ther 2000 8 112 124
Lord RV O'Grady R Sheehan C K-ras codon 12 mutations in Barrett's oesophagus and adenocarcinomas of the oesophagus and oesophagastric junction J Gastroenterol Hepatol 2000 15 730 736 10937677 10.1046/j.1440-1746.2000.02163.x
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| 15707498 | PMC549518 | CC BY | 2021-01-04 16:39:20 | no | J Carcinog. 2005 Feb 12; 4:5 | utf-8 | J Carcinog | 2,005 | 10.1186/1477-3163-4-5 | oa_comm |
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World J Surg OncolWorld Journal of Surgical Oncology1477-7819BioMed Central London 1477-7819-3-81570306810.1186/1477-7819-3-8ResearchAge dependent association of endometrial polyps with increased risk of cancer involvement Hileeto Denise [email protected] Oluwole [email protected] Maritza [email protected] Wenxin [email protected] Department of Pathology, Yale University School of Medicine, New Haven, CT, 06520-8070 USA2 Department of Obstetrics and Gynecology, Yale University School of Medicine, New Haven, CT, 06520-8070, USA2005 9 2 2005 3 8 8 19 8 2004 9 2 2005 Copyright © 2005 Hileeto et al; licensee BioMed Central Ltd.2005Hileeto 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
Endometrial polyps (EMPs) are commonly encountered in routine surgical pathology practice, but opinions differ on whether they are intrinsically a marker for concurrent or subsequent malignancy. The objectives of the present study are 1) to investigate the age-group in which EMP are most commonly encountered 2) to document the age-group in which EMP are most commonly associated with malignancies 3) To investigate whether the age of diagnosis of the various carcinoma subtypes in EMPs is congruent with published data on similar malignancies arising in non-polypoid endometrium and 4) To investigate whether the histologic subtype distribution of malignancies associated with EMPs are similar or different from the distribution of malignancies arising from non-polypoid endometrium based on published data.
Patients and methods
All cases of EMPs were retrieved from the files of Yale-New Haven Hospital for the period 1986–1995. The patients were divided into 5 age groups: Each group was further subclassified based on an association (or lack thereof) of EMPs with endometrial carcinoma. Chi-square test was used to compare the proportion of malignancy associated EMPs between the age groups.
Results
We identified 513 EMPs, of which 209 (41%) were from biopsy specimens and 304 (59%) from hysterectomy specimens. Sixty six (13%) of all EMPs were malignant. The 66 malignant EMPs included 58 endometrioid, 6 serous, 1 carcinosarcoma, and 1 clear cell carcinoma. In age group >35, only 1(2.5%) of 40 EMPs was associated with endometrial malignancy. In contrast, 37(32%) of 115 EMPs were associated with malignancy in the age group > 65. The frequency of malignant EMPs increased with age and reached statistical significance in the age group >65 (p < 0.001). The most common histologic type of malignancy was endometrioid adenocarcinoma.
Conclusions
EMPs show statistically significant age dependent association with malignant tumor involvement. Careful search for malignancy, particularly in women with multiple risk factors is advised in daily practice. Additional studies are needed to address the histological features and immunohistochemical profiles in the context of association between endometrioid and high-grade endometrial carcinoma and endometrial polyps.
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Background
Endometrial polyps (EMPs) are generally considered benign proliferative lesions and are commonly encountered in routine surgical pathology practice. The usual histological pattern of endometrial polyps is characterized by irregular proliferative glands, with a fibrotic stroma containing thick-walled blood vessels [1]. The morphologic diversity of endometrial polyps is reflective of the morphologic spectrum of the background endometrium from which EMPs arise. As such, EMPs may range from atrophic to hyperplastic to carcinomatous. However, opinions differ on whether EMPs are intrinsically a marker for concurrent or subsequent malignancy. Endometrial polyps were identified in 12–34% of uteri containing endometrial carcinoma in two earlier studies [2,3]. In another case-control study examining previous pathology in women diagnosed with endometrial carcinoma, endometrial polyps were twice as likely to be detected than in the control group [4]. Rarely, serous endometrial intraepithelial carcinoma (EIC), the presumptive early form of uterine papillary serous carcinomas, may be identified as very minute foci in EMPs [5,6]. This finding may be interpreted as the EMP homologue of similar changes that are occasionally identified in non-polypoid atrophic endometrium. However, given that nonrandom chromosomal aberrations and monoclonality that have been demonstrated in EMPs [7,8], an alternate interpretation is that molecular and/or cytogenetic alterations inherent to EMPs facilitate a neoplastic transformation. The latter interpretation would imply that endometrial polyps are a risk factor for the development of endometrial tumors. And indeed a possible association between endometrial polyps and endometrial malignancy in postmenopausal women has been suggested couple of decades ago [4]. However, there is no direct evidence for a greater propensity of polypoid endometrium to undergo malignant change as compared to the adjacent normal endometrium, and EMP may simply represent am embodiment of the greater propensity of the host endometrium to develop proliferative/neoplastic changes in general [9]. A recent study designed and conducted to investigate the pathological significance of EMPs and their association with pre-malignant and malignant conditions failed to supply evidence of such association. That study involved a large cohort of patients seen in outpatient hysteroscopy clinic for abnormal uterine bleeding. To determine the magnitude of malignant potential among polyps, the authors compared the pathological findings in polyps with non-polypoid specimens. The comparative analysis established that endometrial hyperplasia was more frequent in endometrial specimens with polyps, but the incidence of frank carcinoma in polypoid and non-polypoid endometrium remained the same. Although not age stratified, the study showed that in abnormal uterine bleeding, hyperplasia presented more frequently in women with EMPs compared to those without polyps, but cancer involvement regardless of the histological pattern was not significantly different [9]. Similar results and failure to establish any association of endometrial polyps and carcinoma were demonstrated in another recent study dealing with endometrial polyp characteristics in menopausal women on hormonal replacement therapy [10].
Most standard pathology texts list endometrial polyps as being most prevalent in perimenopausal women and suggest possible association between polyps and malignant involvement [9,11]. However, there has been no detailed age-based analysis of the incidence and malignant involvement of EMPs. In this report, age-related differences in the incidence of EMP at the time of diagnosis in the practice of a busy academic center is examined, with a detailed analysis of the incidence and histologic subtypes of malignancies associated with EMPs. The objectives of the study are 1) to investigate the age-group in which EMP are most commonly encountered in routine surgical pathology practice 2) to document the age-group in which EMPs are most commonly associated with malignancies 3) To investigate whether the age of incidence of the various carcinoma subtypes in EMPs at the time of diagnosis is congruent with published data on similar malignancies arising in non-polypoid endometrim and 4) To investigate whether the histologic subtype distribution of malignancies associated with EMPs is similar or significantly different from the distribution of malignancies arising from non-polypoid endometrium.
Patients and methods
Case retrieval and pathologic classifications
All cases with a diagnosis of EMP were retrieved from the computerized database of the Pathology Department at Yale-New Haven Hospital for the 10-year-period from 1986 to1995. All cases were further investigated for involvement of endometrial cancers including malignancies without myometrial invasion; histologic subtypes of all malignant tumors were catalogued. Histologic types of endometrial malignancies were characterized according to the WHO classification [12]. All cases were reviewed microscopically and confirmed by a second pathologist. For endometrial cancer with mixed histologic type, the presence of a second component was considered if it involved more than 10% of all available sections containing tumor. The cases of endometrial malignancy involving both EMPs and non-polyp endometrium, were classified into the category of EMPs with cancer involvement.
Patients groups
For comparative purposes, the patients were divided into 5 age groups: 25–35; 36–45; 46–55; 56–65; and >65 years; and each group was further classified based on an association (or lack thereof) with endometrial carcinoma. A starting point of 25 years of age was selected due to the very low incidence of endometrial polyps in patients below this age. Two patients (ages 18 and 19) were excluded from the study as they did not represent a sufficiently large for statistical analysis group. The proportion of both groups (polyps associated with malignancies (malignant polyps) and polyps not associated with malignancies (benign polyps) were statistically compared for each of the aforementioned age-groups. Subsequently, we merged the younger age groups and preserved the >65 year group, which we referred to as "postmenopausal", since significant differences were observed in this specific subset of patients. Larger age groups were arbitrarily designated as reproductive years (25–45), perimenopause (shortly before or after menopause, 46–65) and postmenopause (>65) and statistically analyzed. The postmenopausal status of all women above the age of 65 was verified and the term "postmenopausal" was occasionally used when referring to this particular age group. Our use of this term, although arbitrary, was important in order to put the emphasis on the fact that any pathomorphological findings in this age group are unlikely to be attributed to changes characteristic of the cycling endometrium.
Statistical analysis
Chi-square test was used to compare the proportion of malignancy associated EMPs between the age groups and in regards to particular histological type of malignancies.
Results
Out of all diagnostic and therapeutic procedures performed over this period, a total of 513 EMP were identified. The latter included 304 (59%) endometrial biopsies/curetting samples, and 209 (41%) hysterectomy specimens. In cases in which endometrial biopsies and hysterectomies both showed presence of EMP, only the hysterectomy specimen was considered. The age of patients ranged from 18–91 years with a median of 54 years. Sixty-six (13%) of 513 EMPs were malignant. The histological subtype distribution of those 66 malignancies included 58 endometrioid (87%), 6 serous (9%), 1 carcinosarcoma, and 1 clear cell carcinoma. No mixed histological type of endometrial cancer was found in our series. The incidence of EMP peaked at age group 46–55 years, which was similar to previous reports. In age group 25–35, only 1 (2.5%) of 40 EMPs was associated with endometrial malignancy. In contrast, 37 (32%) of 115 EMPs were associated with malignancy in the age group >65 years (Figure 1; Figure 2). The frequency of EMPs with malignancy involvement increased with age and reached statistical significance (p < 0.001) in the age group >65 years (Figure 3). The most common histological type of malignancy was endometrioid carcinoma, followed by serous carcinoma. The same statistically significant difference for age group >65 years (p < 0.05) remained when larger age groups, including reproductive (25–45), perimenopausal (46–65) and postmenopausal (>65) patients were compared (Figure 4).
Figure 1 Frequency of occurrence of benign endometrial polyps by age group. The frequency of occurrence of EMPs at the time of diagnosis peaked in the age group 46–55 years (29%), followed by 36–45 (27%), 56–65 (18%) and >65 years (17%). The incidence of EMPs in the age group 25–35 years was significantly lower (9%).
Figure 2 Frequency of occurrence of malignant endometrial polyps by age group. In age group 25–35 years, only 2.5% of the EMPs were associated with endometrial malignancy. In contrast, in the age group >65 years, 32% of the EMPs were associated with malignancy.
Figure 3 Distribution of benign and malignant endometrial polyps by age group Although the incidence of EMPs at the time of diagnosis in the age group > 65 years was among the lowest, the incidence of malignancy associated EMPs was the highest.
Figure 4 Benign and malignant endometrial polyps by age group
Discussion
Our results indicated a strong age dependent association of endometrial polyps and endometrial carcinoma. A linear relationship in the association rate of EMPs with malignancies and increasing age was observed, with the highest association rate identified in the >65 years age group, where 32% of the EMPs were associated with malignancy. Histological evaluation and characterization of the morphological types of carcinoma demonstrated that the vast majority (87%) of endometrial carcinomas associated with EMPs were of endometrioid, followed by the serous type (9%). These relative proportions of both major histological subtypes are in accordance with the well-known distribution of similar subtypes of endometrial carcinoma in non-polypoid endometrium [12] and thus demonstrates that neither histologic subtype is more likely than the other to develop in a polyp as compared to the adjacent endometrium. The majority of the serous carcinomas developed in the oldest age group (>65 years), whereas the majority of the endometrioid carcinomas occurred in the 46–55 age group, followed by the 36–45 age group. These age distributions are in accordance with the general concept of Type I and Type II endometrial carcinogenesis [13] and provide some evidence suggesting that carcinomas developing in EMPs do not necessarily have clinicopathologic differences from carcinoma arising in the background endometrium. It is well established that serous carcinoma may exist as a minute foci in the endometrium devoid of myometrial invasion and still show extrauterine involvement [14-16]. In a study of EMPs with serous carcinoma involvement with no or minimal invasion, Silva et al., [17] reached similar findings: in 6 (37.5%) of 16 cases in that study, there was evidence of extra uterine involvement at presentation. The similarities between the patients who presented with advanced disease and the patients who presented with initial stage disease, suggested that serous carcinoma involving endometrial polyps may represent one aspect of a multicentric disease in which, the entire female genital tract and the abdominal peritoneal surfaces would be at high risk for concurrent or subsequent involvement by serous carcinoma even in the absence of myometrial invasion [17] or the extrauterine disease may represent transtubal metastasis [18,19].
This study also confirms previous findings that EMPs are most prevalent in the perimenopausal age group. The reason(s) for this age-segregation, which has remained remarkably consistent across various studies since the mid-fifties, is unclear. Chavez et al., [20] speculated that with the introduction of new minimally invasive technologies (such as office hysteroscopy and sonohysterograms), the demographics of patients with EMPs will change over time as younger women undergoing evaluation for infertility will have "latent" EMPs discovered. However, when the authors compared the mean ages of women with EMPs in 1990 and 1996, there was no statistically significant difference. In addition, multiple EMPs are more prevalent in the postmenopausal women (26%) as compared with their premenopausal (15%) counterparts with EMPs. These findings suggest that the factor, or the constellation of factors responsible for the above mentioned observation is intrinsic to the endometrial polyps and surrounding endometrium condition depending on the age group. Lower incidence of endometrial polyps in the younger age group may be attributed to a possible spontaneous regression mechanism, which is characteristic of the cycling endometrium in young reproductive age women.
Despite the supportive evidence of no difference in the clinico-pathological features and overall distribution of carcinomas arising from EMPs with those arising from non-polypoid endometrium, our data suggest a strong age dependent association between the presence of EMPs and involvement by endometrial carcinoma. The pathogenesis and mechanisms underlying such association are complex and not well established. Recently published data, however, provided some clue of significant differences in receptor expression, response to stimuli, and apoptosis regulation in EMPs compared to benign non-polypoid endometrium which could potentially elucidate some aspects of the possible malignant potential of EMPs. Estrogen and progesterone act as modulators of endometrial proliferation and differentiation through their receptors. Glandular epithelial expression of estrogen and progesterone receptors in polyps is not significantly different from that of the normal cycling endometrium. However, fewer stromal cells express estrogen and progesterone receptors in polyps which suggests that EMPs may result from a decrease in estrogen and progesterone receptors in the stromal cells [21]. In addition, although EMPs depend partially on estrogen receptors and grow in response to estrogen stimulation, their growth is not entirely dependent on them, this is especially so in postmenopausal women. The presence of c-erbB2 over-expression in endometrial polyps, in association with higher proliferation rates were established in a recent study [22]. This finding could explain the presence of polyps showing signs of proliferation even when the adjacent endometrium is atrophic. Thus, C-erbB2 over-expression in endometrial polyps and not in the adjacent atrophic mucosa may render polyps more sensitive to the combination of high gonadotropins and low estrogen levels, which is characteristic in the postmenopausal women.
Another significant histological finding is the glandular epithelia hyperplasia in C-erbB2 -positive polyps as opposed to rather atrophic architecture in C-erbB2 -negative polyps [22]. These findings indicate that the relationship between the expression of estrogen receptors and cell proliferation in normal endometrium and EMPs differ significantly. The balance between mitotic activity and apoptosis, which regulates normal endometrial development in EMPs also shows significant alterations. Bcl-2 is a proto-oncogene, which prolongs the cell survival by inhibiting apoptosis. Bcl-2 expression has been characterized in normal cycling endometrium. Recent studies have also observed that Bcl-2 is strongly expressed in hyperplastic and malignant endometrium [23]. A localized increase in Bcl-2 expression and consequential decline or cessation of apoptosis may be another mechanism underlying the pathogenesis of endometrial polyps [24]. Elevated Bcl-2 expression results in failure of the polyp tissue to undergo normal cycle dependent sequence of proliferation, differentiation and shedding. These data imply that the relationship between receptor expression, cell proliferation and apoptosis in normal and polypoid endometrium differ significantly. Such differences combined with the nonrandom chromosomal aberrations and monoclonality, suggest that EMPs may provide a suitable microenvironment for the development of malignancy, particularly epithelial cancers. In this aspect, the molecular and/or cytogenetic alterations inherent to EMPs in a postmenopausal background could be viewed as factors facilitating and contributing to the process of malignant transformation. Our results showed a strong association of EMPs in postmenopausal patients with endometrial cancer. It raised the possibility that EMPs in postmenopausal women could represent some intermediate stage in the development of carcinoma. A similar suggestion was proposed in a study evaluating the spectrum of pathological findings in Tamoxifen treated breast cancer patients whom develop polyps and carcinoma significantly more frequently than the general population [25]. Also in favor of this hypothesis were the results provided by Silva et al., who found that 10 (76%) of 13 Tamoxifen-related endometrial carcinomas were associated with EMPs [26].
One potential limitation of our study is our lack of consideration of the impact of variables such as hypertension, obesity and family history. However, since data regarding such possible confounders were not available to us, we set the goals of our investigation to be primarily focused on age related distribution of coinciding morphologic findings. Although we are aware of the limitations of our study and the introduced analytical bias, drawbacks that certainly pertain to any similar retrospective pathomorphologic study, we feel that we have adequately addressed the proposed investigative tasks according to the initially set scope of the study. By using the database of Yale-New Haven Hospital, we collected and analyzed a significant number of cases over an extensive period of time and thereby our study population constituted an adequate representation of the general population in respect to the morphological parameters we investigated.
In summary, the age distribution, histological subtype distribution, and peak incidence of EMPs was similar to previous reports. In contrast, EMPs in postmenopausal women showed a significantly higher association with malignant tumor involvement. Careful microscopic search for malignancy in patients with multiple risk factors, particularly in postmenopausal women is advised in daily surgical pathology practice.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
DH wrote the original version of the manuscript.
OF made substantial contributions to the content of the manuscript and participated in manuscript preparation.
MM collected clinical and pathological data and revised the final version.
WZ analyzed and interpreted the data and supervised the entire project.
All authors have read and approved the final manuscript.
Acknowledgements
This study was performed in accordance to all requirements for using patient information from the hospital archived database. It was presented, in part, at the 93rd annual meeting of the United States and Canadian Academy of Pathology, Vancouver, BC, Canada, March 6–12, 2004.
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| 15703068 | PMC549519 | CC BY | 2021-01-04 16:39:05 | no | World J Surg Oncol. 2005 Feb 9; 3:8 | utf-8 | World J Surg Oncol | 2,005 | 10.1186/1477-7819-3-8 | oa_comm |
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Virol JVirology Journal1743-422XBioMed Central London 1743-422X-2-51570308510.1186/1743-422X-2-5HypothesisThe Severe Acute Respiratory Syndrome (SARS)-coronavirus 3a protein may function as a modulator of the trafficking properties of the spike protein Tan Yee-Joo [email protected] Institute of Molecular and Cell Biology, 61 Biopolis Drive, Proteos, 138673 Singapore2005 10 2 2005 2 5 5 17 1 2005 10 2 2005 Copyright © 2005 Tan; licensee BioMed Central Ltd.2005Tan; 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 recent publication reported that a tyrosine-dependent sorting signal, present in cytoplasmic tail of the spike protein of most coronaviruses, mediates the intracellular retention of the spike protein. This motif is missing from the spike protein of the severe acute respiratory syndrome-coronavirus (SARS-CoV), resulting in high level of surface expression of the spike protein when it is expressed on its own in vitro.
Presentation of the hypothesis
It has been shown that the severe acute respiratory syndrome-coronavirus genome contains open reading frames that encode for proteins with no homologue in other coronaviruses. One of them is the 3a protein, which is expressed during infection in vitro and in vivo. The 3a protein, which contains a tyrosine-dependent sorting signal in its cytoplasmic domain, is expressed on the cell surface and can undergo internalization. In addition, 3a can bind to the spike protein and through this interaction, it may be able to cause the spike protein to become internalized, resulting in a decrease in its surface expression.
Testing the hypothesis
The effects of 3a on the internalization of cell surface spike protein can be examined biochemically and the significance of the interplay between these two viral proteins during viral infection can be studied using reverse genetics methodology.
Implication of the hypothesis
If this hypothesis is proven, it will indicate that the severe acute respiratory syndrome-coronavirus modulates the surface expression of the spike protein via a different mechanism from other coronaviruses. The interaction between 3a and S, which are expressed from separate subgenomic RNA, would be important for controlling the trafficking properties of S. The cell surface expression of S in infected cells significantly impacts viral assembly, viral spread and viral pathogenesis. Modulation by this unique pathway could confer certain advantages during the replication of the severe acute respiratory syndrome-coronavirus.
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Background
The recent severe acute respiratory syndrome (SARS) epidemic, which affected over 30 countries, resulted in more than 8000 cases of infection and more than 800 fatalities (World Health Organization, ). A novel coronavirus was identified as the aetiological agent of SARS [1]. Analysis of the nucleotide sequence of this novel SARS coronavirus (SARS-CoV) showed that the viral genome is nearly 30 kb in length and contains 14 potential open reading frames (ORFs) [2-4]. These viral proteins can be broadly classified into 3 groups; (i) the replicase 1a/1b gene products which are important for viral replication, (ii) the structural proteins, spike (S), nucleocapsid (N), membrane (M) and envelope (E), which have homologues in all known coronaviruses, and are important for viral assembly, and (iii) the "accessory" proteins that are specifically encoded by SARS-CoV. Much progress have been made in characterizing these SARS-CoV proteins [5,6], but the molecular determinant for the severe clinical manifestations of SARS-CoV infection in contrast to the mild diseases caused by most coronaviruses, remains to be determined. In addition, the exact roles of "accessory" proteins of SARS-CoV are still poorly understood.
The subject of this hypothesis relate to the S protein and one of the "accessory" proteins, the SARS-CoV 3a protein. The S protein, which forms morphologically characteristic projections on the virion surface, mediates binding to cellular receptor and the fusion of viral and host membranes, both of these processes being critical for virus entry into host cells [7,8]. As such, S is known to be responsible for inducing host immune responses and virus neutralization by antibodies [9,10]. 3a (also termed ORF3 in [2] and [11], as X1 in [3], and as U274 in [12,13]) is the largest "accessory" protein of SARS-CoV, consisting of 274 amino acids and 3 putative transmembrane domains. Three groups independently reported the expression of 3a in SARS-CoV infected cells [13-15] and it was also detected in a SARS-CoV infected patient's lung specimen [14]. Antibodies against 3a were also found in convalescent patients [11,12,14].
This article hypotheses that the endocytotic properties of 3a allow it to modulate the surface expression of S and explores a functional significance for the interaction between S and 3a, which has been observed experimentally [13,15].
Presentation of the hypothesis
The cellular fate of the S protein has been well mapped [16,17]: S is cotranslationally glycosylated and oligomerized at the endoplasmic reticulum. Its N-linked high mannose side chains are trimmed, modified and become endoglycosidase H-resistant during the transportation to the Golgi apparatus. Only this fully-matured form of S can be assembled into virions and/or transported to the cell surface. The latter could cause cell-cell fusion and the formation of syncytia. Recently, Schwegmann-Wessels and co-worker reported that a novel sorting signal for intracellular localization is present in the S protein of most coronaviruses, but absent from SARS-CoV S [18]. Site-directed mutagenesis studies confirmed that a YxxΦ motif (where x is any amino acid and Φ is an amino acid with a bulky hydrophobic side chain) retains the S protein of TGEV intracellularly when it is expressed alone. On the other hand, SARS-CoV S is transported efficiently to the cell surface unless such a motif is introduced into its cytoplasmic tail by mutagenesis.
The YxxΦ motif has been implicated in directing protein localization to various intracellular compartments [19-21]. Furthermore, most YxxΦ motifs are capable of mediating rapid internalization from the plasma membrane into the endosomes. Interaction between the adaptor protein complex 2 (AP-2) with the YxxΦ motif present in the cytoplasmic domain of the internalizing protein concentrated the protein in clathrin-coated vesicle, which then budded from the plasma membrane resulting in internalization. However, it appears that the YxxΦ motif can also bind other adaptor protein complexes, like AP-1, 3 and 4, and the differential binding to the different adaptors will determine the pathway of a cargo protein containing a particular YxxΦ motif [21]. Coincidently, a YxxΦ motif in the cytoplasmic domain of 3a has previously been identified [13]. Furthermore, the juxtaposition of the YxxΦ motif and a ExD (diacidic) motif was found to be essential for the transport of 3a to the cell surface, consistent with the role of these motifs in the transportation of other proteins to the plasma membrane [22]. 3a on the cell surface can also undergo internalization [13].
Analyzing the experimental results present in these publications collectively, it is possible to postulate a functional role for the evolution of the SARS-CoV 3a protein. The SARS-CoV S protein lacks the YxxΦ motif but it can bind to the 3a protein which has internalization properties. In SARS-CoV infected cells, S is rapidly transported to the cell surface. But if 3a is expressed in the same cell, it is also transported to the cell surface where it can bind S. The interaction between 3a and S enables both proteins to become internalized, resulting in a decrease in the expression of S on the cell surface. Thus, this viral-viral interaction confers the functional role for the YxxΦ motif found in other coronaviruses to the SARS-CoV S. This hypothesis also implies that the precise mechanisms used by TGEV and SARS-CoV to reduce the expression of S are different although in both cases, the YxxΦ motifs will be crucial. In TGEV, the YxxΦ motif in S caused it to be retained intracellularly, while in SARS-CoV, S that is transported to the cell surface becomes internalized again after it interacts with the 3a protein.
Testing the hypothesis
Using mammalian cell culture system and biochemical methods, it will be possible to determine the exact effects of 3a on the trafficking properties of S. Mutagenesis studies can be used to map the protein domains that are important for the interaction between 3a and S and for the defining the manner by which 3a contributes to the reduction of cell surface expression of S. Given that a full-length infectious clone of SARS-CoV has been assembled [23], the use of reverse genetics would certainly reveal more about the interplay between 3a and S during SARS-CoV infection.
Implication of the hypothesis
This hypothesis, if proven, will indicate that the interaction between SARS-CoV-unique 3a protein and S results in a reduction of S on the cell surface through the endocytotic properties of 3a [13]. During SARS-CoV infection, expression of S on the cell surface of an infected cell mediates fusion with un-infected neighboring cells, leading to syncytium formation. It follows that reducing the cell surface expression of S will delay this cell-damaging effect and prevent the premature release of unassembled viral RNA. It may also enhance virus packaging as it appears that the assembly of coronavirus occurs intracellularly, probably in the intermediate compartments between the endoplasmic reticulum and Golgi apparatus [24]. Clearly, this has certain advantages for the virus at certain stages of its life cycle. In addition, a reduction in the cell surface expression of S may also help the infected cell evade the host defense system and reduce the production of anti-S neutralizing antibodies. Conversely, host or viral factors that disrupt the interaction between S and 3a would favor the expression of S on the cell surface and enhance cell-cell fusion, a process that is important for viral spreading.
Table 1 shows a comparison of the amino acid sequences of the cytoplasmic tails of the S protein of different coronaviruses, including SARS-CoV, which is distantly related to the established group 2 coronaviruses [25], as well as two recently identified novel human coronaviruses, HCoV-NL63 [26] and HCoV-HKU1 [27]. The YxxΦ motifs are clearly present in all group 1 coronaviruses and also in IBV, which belongs to group 3. However, no YxxΦ motif is present in SARS-CoV and MHV, both group 2 coronaviruses. In addition, there is a YGGR motif in the S protein of RtCoV and YxxH motifs in the S proteins of the other group 2 coronaviruses, BCoV, HEV and HCoV-HKU1. However, these motifs may not be able to function as signaling motifs because both R and H are not hydrophobic amino-acids. Therefore, HCoV-OC43 is the only one of these group 2 coronaviruses that encodes a S protein with a YxxΦ motif. It is still unclear how the localization of S is modulated in those viruses that lack YxxΦ motifs in the S proteins and further studies will be needed to understand the different signaling pathways that are important for regulating the trafficking properties of S. Indeed, the dilysine endoplasmic reticulum retrieval signal, which is a different type of sorting signal from the YxxΦ motif, in the cytoplasmic tail of IBV was reported to be important for intracellular retention of S [28].
Table 1 Amino acid sequences of the cytoplasmic tail of spike (S) proteins of coronaviruses are compared with the YxxΦ (where x is any amino acid and Φ is an amino acid with a bulky hydrophobic side chain) motifs found in SARS-CoV 3a protein and other cellular proteins that are known to undergo endocytosis.
Protein Amino acid sequences in the cytoplasmic taila
TGEV Sb TM-CLGSCCHSICSRRQFENYEPIEKVHVH
PRCoV Sb TM-CLGSCCHSIFSRRQFENYEPIEKVHVH
CCoV Sb TM-CLGSCCHSICSRGQFESYEPIEKVHVH
FCoV Sb TM-CLGSCCHSICSRRQFENYEPIEKVHVH
PEDV Sb TM-CCGACFSGCCRGPRLQPYEAFEKVHVQ
HCoV-229E Sb TM-CFASSIRGCCESTKLPYYDVEKIHIQ
HCoV-NL63 Sb TM-CLTSSMRGCCDCGSTKLPYYEFEKVHVQ
BCoV Sc TM-ICGGCCDDYTGHQELVIKTSHDD
HCoV-OC43 Sc TM-KCGGCCDDYTGYQELVIKTSHDD
HEV Sc TM-KCGGCCDDYTGHQEFVIKTSHDD
MHV Sc TM-KKCGNCCDECGGHQDSIVIHNISSHED
RtCoV Sc TM-KCGNCCDEYGGRQAGIVIHNISSHED
HCoV-HKU1 Sc TM-KCHNCCDEYGGHHDFVIKTSHDD
SARS-CoV Sc TM-GACSCGSCCKFDEDDSEPVLKGVKLHYT
IBV Sd TM-KKSSYYTTFDNDVVTEQYRPKKSV
SARS-CoV 3ae TM-38aa-YNSVTDTIVVTEGD-101aa
TfRe 19aa-YTRFSLARQVDGDNSHV-26aa-TM
LDLR (proximal)e TM-17aa-YQKTTEDEVHICH-20aa
LDLR (distal)e TM-34aa-YSYPSRQMVSLEDDVA
CD-M6PRe TM-34aa-YRGVGDDGLGEESEERDDHLLPM
ASGPRe MTKEYQDLQHLDNEES-24aa
aSequences were obtained from National Center for Biotechnology Information (NCBI). Yxxx tetrapeptides are underlined and abbreviations used are: TM, transmembrane domain, aa, amino acids.
bS proteins of group 1 coronaviruses: TGEV, transmissible gastroenteritis virus (AJ271965); PRCoV, porcine respiratory coronavirus (Z24675); CCoV, canine coronavirus (D13096); FCoV, feline coronavirus (AY204704); PEDV, porcine epidemic diarrhea virus (AF353511); HCoV-229E, human coronavirus 229E (AF304460); HCoV-NL63, human coronavirus NL63(AY518894).
cS proteins of group 2 coronaviruses: BCoV, bovine coronavirus (AF220295), HCoV-OC43, human coronavirus OC43 (AY585228), HEV, porcine hemagglutinating encephalomyelitis virus (AY078417), MHV, murine hepatitis virus (AF201929), RtCoV, rat coronavirus (AF207551), HCoV-HKU1, human coronavirus HKU1 (AY597011), SARS-CoV, SARS coronavirus (AY283798).
dS protein of group 3 coronavirus: IBV, infectious bronchitis virus (M95169).
eSARS-CoV 3a protein (AY283798) and other cellular proteins that are known to undergo endocytosis. Abbreviations: TfR, transferrin receptor (P02786), LDLR, low-density lipoprotein receptor (P01130); CD-M6PR, cation-dependent mannose 6-phosphate receptor (P24668); ASGPR, asialoglycoprotein receptor (P07306).
It therefore appears that the cell surface expression of S protein of SARS-CoV can be reduced like that for other coronaviruses, but the mechanism may be different. The trafficking of SARS-CoV S may be mediated through 2 separate viral proteins, expressed from separate subgenomic RNA, and regulated by numerous complex cellular processes including the efficiency of transcription and translation, post-translation modification and stability of the viral proteins, as well as their interactions with host factors. Indeed, it is crucial to determine how this unique pathway benefits replication of the SARS-CoV. It is also interesting to note that sequence comparison of isolates from different clusters of infection showed that both S and 3a showed a positive selection during virus evolution [29,30], implying that these proteins play important roles in the virus life cycle and/or disease development and is consistent with the proposal that 3a has evolved to modulate the trafficking properties of the spike protein.
Competing interests
The author(s) declare that they have no competing interests.
Author's contributions
Yee-Joo Tan is responsible for the entire manuscript.
Acknowledgements
This work was supported by grants from the Agency for Science, Technology and Research (A*STAR), Singapore.
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| 15703085 | PMC549520 | CC BY | 2021-01-04 16:39:01 | no | Virol J. 2005 Feb 10; 2:5 | utf-8 | Virol J | 2,005 | 10.1186/1743-422X-2-5 | oa_comm |
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Respir ResRespiratory Research1465-99211465-993XBioMed Central London 1465-9921-6-141570519010.1186/1465-9921-6-14ResearchMarked alveolar apoptosis/proliferation imbalance in end-stage emphysema Calabrese Fiorella [email protected] Cinzia [email protected] Bianca [email protected] Federico [email protected] Monica [email protected] Renzo [email protected] Giuseppe [email protected] Simonetta [email protected] Marina [email protected] Marialuisa [email protected] Institute of Pathology, University of Padua, Italy2 Department of Clinical and Experimental Medicine, Section of Respiratory Diseases, University of Padua, Italy3 Department of Gastroenterological Sciences, Section of Thoracic Surgery, University of Padua, Italy2005 10 2 2005 6 1 14 14 29 7 2004 10 2 2005 Copyright © 2005 Calabrese et al; licensee BioMed Central Ltd.2005Calabrese 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
Apoptosis has recently been proposed to contribute to the pathogenesis of emphysema.
Methods
In order to establish if cell fate plays a role even in end-stage disease we studied 16 lungs (9 smoking-associated and 7 α1antitrypsin (AAT)-deficiency emphysema) from patients who had undergone lung transplantations. Six unused donor lungs served as controls. Apoptosis was evaluated by TUNEL analysis, single-stranded DNA laddering, electron microscopy and cell proliferation by an immunohistochemical method (MIB1). The role of the transforming growth factor (TGF)-β1 pathway was also investigated and correlated with epithelial cell turnover and with the severity of inflammatory cell infiltrate.
Results
The apoptotic index (AI) was significantly higher in emphysematous lungs compared to the control group (p ≤ 0.01), particularly if only lungs with AAT-deficiency emphysema were considered (p ≤ 0.01 vs p = 0.09). The proliferation index was similar in patients and controls (1.9 ± 2.2 vs 1.7 ± 1.1). An increased number of T lymphocytes was observed in AAT-deficiency lungs than smoking-related cases (p ≤ 0.05). TGF-β1 expression in the alveolar wall was higher in patients with smoking-associated emphysema than in cases with AAT-deficiency emphysema (p ≤ 0.05). A positive correlation between TGF-βRII and AI was observed only in the control group (p ≤ 0.005, r2 = 0.8). A negative correlation was found between the TGF-β pathway (particularly TGF-βRII) and T lymphocytes infiltrate in smoking-related cases (p ≤ 0.05, r2 = 0.99)
Conclusion
Our findings suggest that apoptosis of alveolar epithelial cells plays an important role even in end-stage emphysema particularly in AAT-deficiency disease. The TGFβ-1 pathway does not seem to directly influence epithelial turnover in end-stage disease. Inflammatory cytokine different from TGF-β1 may differently orchestrate cell fate in AAT and smoking-related emphysema types.
apoptosisproliferationend-stage emphysema
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Background
Pulmonary emphysema, a significant global health problem, is a pathological condition characterized by enlargement of the airspaces distal to the terminal bronchiole, destruction of the alveolar walls, without and/or with mild fibrosis [1]. To date the pathogenesis remains enigmatic. The most prevailing hypothesis since the 1960s has been the elastase/antielastase imbalance theory of inflammation [2]. Briefly, the concept is that activated inflammatory cells release large quantities of elastases, overwhelming local antiprotease activity with consequent damage to the alveolar wall matrix [3]. However the emphasis on alveolar matrix destruction by a combination of inflammation and excessive proteolysis has failed to fully explain the loss of lung tissue, particularly when compared to alterations seen in other inflammatory lung diseases.
Recently more attention has been paid to alveolar epithelial injury in addition to alveolar matrix destruction. The presence of apoptosis has recently been described in animal models of emphysema [4,5] and in a few studies of human disease [6-9].
The majority of investigations have focused the attention on smoking-related emphysema keeping in mind that cigarette smoking was the main cause of apoptotic cell death. Cigarette smoke may induce alveolar cell apoptosis either directly by a cytotoxic effect on pneumocytes or indirectly by decreasing the production of vascular endothelial growth factor (VEGF) via altered epithelial cells [7]. To date smoking-associated centrilobular emphysema is the only studied form of emphysema in which apoptosis, and more recently also proliferation, have been investigated [9]. Alterations of lung epithelial cell turnover in end-stage emphysema, either smoking-associated emphysema or α1-antitrypsin (AAT)-deficiency emphysema, are up to now not well distinguished.
Moreover apoptotic phenomenon has been previously investigated in moderate/severe smoking-related forms of emphysematous lungs obtained almost exclusively from lung volume reduction surgery [6,7,9]. If cell fate is a stable, progressive and/or a decreasing process in end-stage disease is to date unknown.
Among the growth factors, transforming growth factor (TGF)-β1 could play a crucial role in the remodeling process occurring in emphysematous parenchyma. TGF-β1, other than its known profibrogenetic [10] and anti-inflammatory effects [11,12], has an important influence on epithelial cell growth [14]. It has been demonstrated that it has an inhibitory effect on the growth of lung epithelial cells, particularly for airway epithelium [14,15].
The cytokine has been shown to be over-expressed in patients with a history of smoking and chronic obstructive pulmonary disease (COPD) [16,17]. Paracrine (mainly produced by macrophages) and autocrine (released by epithelial cells) activity of this growth factor could play an important role in the loss of the alveolar walls by inducing apoptotic cell death.
In the present work the degree of apoptotic cell death and epithelial proliferation in the lungs of patients with different types of end-stage emphysema was studied. The severity of inflammatory cell infiltrate (ICI) was also quantified and correlated with epithelial cell turnover. Further, the TGF-β1 pathway was detected and correlated with the apoptotic index (AI), the proliferative index (PI) and the ICI.
Methods
Lung tissue preparation
Lung tissue used in the present study comprised material from 16 patients undergoing lung transplantation for end-stage emphysema at the Thoracic Surgery Unit of the University of Padua Medical School. Cold ischemia preservation was 60 minutes and 120 minutes, respectively, for single and double lung transplantations. Small-sized pieces from all lobes were cut and immediately fixed in Karnovsky's solution for electron microscopy. The lungs were then gently fixed in 10% phosphate-buffered formalin by airway perfusion and processed for sectioning (3 μm). Samples were selected from specimens that showed features of excellent tissue preservation and adequate lung inflation. In particular, large thin blocks approximately 30 × 25 mm were cut from the subpleural areas of the apical anterior and lingular segments of the upper lobes, as well as the apical and basal segments of the lower lobes. A more centrally placed block was taken to sample the segmented airways and blood vessels. The right lung was sampled in the same way with the middle lobe being treated in the same way as the lingula [18]. Adult control lungs were obtained from unused donor lungs for transplantation (6 cases). The Local Research Ethics Committee approved the study.
TUNEL analysis
The terminal deoxynucleotidyl transferase-mediated dUTP-biotin nick end-labeling method (TUNEL) was used to investigate the presence of apoptosis. Sections were processed in accordance with Gavrieli et al's method [19]. Briefly, after deparaffinization and rehydration, sections were digested with proteinase K (Boehringer Mannheim, Mannheim, Germany) at a concentration of 20 μg/ml for 15 minutes. The slides were then incubated with TdT/biotinylated dUTP diluted in buffer (Boehringer Mannheim, Mannheim, Germany). The slides were developed by using diaminobenzidine and 30 ml hydrogen peroxide. For negative controls, some slides were incubated in buffer without TdT or biotinylated UTP. For positive controls, some slides were incubated with 1 μg/ml DNAse (Sigma-Aldrich, Milan, Italy).
Electron microscopy
Lung specimens fixed in Karnovsky's solution (2% paraformaldehyde, 2.5% glutaraldehyde in Millonig, pH 7.3) for 24 hours were post-fixed with 1% osmium tetroxide (Millonig, pH 6.8) for 1 hour, and then progressively dehydrated in alcohol and embedded in epon. Semi-thin sections were stained with 0.1% toluidine blue for light microscopic examination. Ultra-thin sections were stained with uranyl acetate and lead citrate for transmission electron microscopy performed using a Hitachi H-7000 (Hitachi Ltd., Tokyo, Japan).
Oligonucleosomal-length DNA laddering
The presence of oligonucleosomal-length DNA cleavage was investigated with APO-DNA1 (Maxim Biotech Inc, San Francisco, CA, USA) in 12 cases (4 AAT-emphysema patients, 4 smoking-related emphysema patients and 4 controls) in which frozen tissue was available. Briefly, DNA was obtained from lung tissue samples using proteinase K-phenol extraction. Dephosphorylated adaptors were ligated to 5' phosphorylated blunt ends with T4 DNA ligase to 500 ng of lung sample DNA (for 16 h at 16°C). These then served as primers in LM-PCR under the following conditions: hot start (72°C for 8 min), 30 cycles (94°C for 1 min, and 72°C for 3 min) and extension (72°C for 15 min). Every reaction set included thymus DNA as a positive control and normalization of the amount of reaction products. Amplified DNA was subjected to electrophoresis on 1.2% agarose gel containing ethidium bromide. Images were scanned and the DNA fragmentation levels were based on the density of the bands ranging between 1000 base pairs (bp) and 300 bp. The percentage of DNA fragmentation was quantified by scanning densitometry.
Immunohistochemistry for TGF-β1, TGF-βRII and MIB1
All lung sections were subjected to antigen retrieval by heating in a microwave oven on high power for 8 minutes in 0.01 mol/l citrate buffer (ph 6.0) and then incubated with a mouse monoclonal anti-TGF-β1-β2 and-β3 primary antibody to active TGF-β1 (150 μg/ml; dilution 1:20, Genzyme Diagnostics, Cambridge, MA), with polyclonal antibody against TGF-β receptor type II (200 μg/ml, dilution 1:200, Santa Cruz Biotechnology Inc., Santa Cruz) and monoclonal MIB-1 antibody (1:50 Dako, Santa Barbara, CA, U.S.A.), which recognizes the Ki-67 antigen in paraffin-embedded tissue sections. Immunohistochemical investigations were done on the sections from the same paraffinembedded specimens processed for TUNEL analysis.
The detection system was the Vectastain ABC kit (Vector Peterborough, UK) with 3-amino-9-ethylcarbazole (for TGF-β1, TGF-βRII) and with a mixture of 3,3'-diamino-benzidine tetra7 hydrochloride (Dako) and hydrogen peroxide as the chromogenic substrates. Sections were counterstained with Mayer's hematoxylin.
Immunohistochemistry for inflammatory cell infiltrate (ICI)
In all samples, immunohistochemistry for the characterization of ICI was carried out by using the following antibody panel: CD20 (1.100), CD45RO (1.100), CD4 (1:20), CD8 (1:50), CD3 (1:100), CD68 (1:50) (Dako, Santa Barbara, CA, U.S.A.). The detection system was the Vectastain ABC kit, as described above.
For all immunohistochemistry experiments, negative controls were performed by incubation of the sections with the omission of primary antibody and using the antibody diluents alone or the appropriate non-immune IgG in each case.
Double immune-labeling
For simultaneous detection of DNA fragmentation and cell proliferation a double labeling was also performed. The TUNEL technique was first performed and the staining achieved was diaminobenzidine as chromogen. For MIB1 immunolocalization in the second staining sequence the sections were stained with 5-bromo-4-chloro-3-indoxyl phosphate/nitro blue tetrazolium (BCIP/NBT alkaline phosphatase Kit II, Vector Laboratories (Vector Peterborough, UK).
Image analysis
Immunoassay for TGF-β1 and TGF-βRII was detected by using digital quantitative analysis (Image Pro Plus software version 4.1, Media Cybernetics, Silver Spring MD) as previously described [13]. Quantification of TUNEL, MIB1 positive cells and ICI was restricted to the alveolar wall. Images for each lung section from the upper and lower lobes were acquired with a 40X lens.
In each case at least 50 microscopic randomly chosen fields were analyzed. A total of 5,000 epithelial cells were counted for AI and PI and the values were expressed as percentages.
Statistical analysis
To avoid observer bias the cases were coded and measurements were made without knowledge of clinical data. Differences between groups were detected using the analysis of variance for clinical data and the Kruskall-Wallis test for histological data. The Mann-Whitney U test was performed after the Kruskall-Wallis test when appropriate. The statistical tests used were two-sided.
Correlation coefficients were calculated using Spearman's rank method. Probability values of 0.05 or less were accepted as significant. Group data were expressed as means and SD or as medians and range when appropriate.
Results
Clinical data and histological findings
Major clinical data for patients with emphysema are shown in Table 1.
Table 1 Subject Characteristics
Case Sex Age Emphysema type Packs/year FEV1* FEV1/FVC* Transplantation
1 M§ 49 AAT deficiency 27 27 27 BSLT *
2 M 59 Smoking 36,5 31 38 RtSLT †
3 F|| 62 Smoking 7 17 55 BSLT
4 F 62 Smoking 36,5 13 30 LtSLT ‡
5 M 62 Smoking 108 15 45 BSLT
6 F 49 Smoking 73 12 33 BSLT
7 M 47 Smoking 54 22 60 BSLT
8 M 59 AAT deficiency 36,5 20 56 BSLT
9 M 64 Smoking 54 6 42 LtSLT
10 M 63 Smoking 54 24 37 BSLT
11 M 51 AAT deficiency 54 11 25 BSLT
12 M 53 AAT deficiency 108 8 14 BSLT
13 M 45 AAT deficiency 73 17 24 BSLT
14 M 56 Smoking 36,5 15 32 RtSLT
15 F 41 AAT deficiency 54 35 38 BSLT
16 M 51 AAT deficiency 36,5 34 36 BSLT
*BSLT: bilateral single lung transplantation, † RtSLT: right transplant single lung transplantation, ‡ LtSLT: left transplant single lung transplantation, §M: male, || F: female. FEV1 and FVC are given as percentages of predicted values.
Average patient age was 54.4 ± 7.5 years. FEV1 mean was 19 ± 8.9 (predicted for sex, age, and body weight). Bilateral single lung transplantation was performed in 12 out of 16 patients. All patients had been heavy smokers: 7 were only smoking-associated emphysema cases (51 ± 28 packs-year) and 9 were both AAT-deficiency emphysema and smoking cases (55 ± 27 packs-year). For the sake of brevity, the abbreviation AAT-deficiency emphysema for smoking patients with AAT-deficiency will be used throughout the manuscript.
All patients had quit smoking at least 1 year before undergoing surgery.
The average control patient age was 34 ± 16.8 years and cerebral trauma was the cause of death. All the donors stayed less than two days in intensive care without evidence of lung infection or other complications. During artificial ventilation, airway pressure (Paw) was 20,9 ± 1.5 mmHg and inspiratory oxygen fraction (FI, O2) was 0.4 ± 0.1.
All the samples showed various degrees of emphysematous changes. In particular, all the patients with AAT-deficiency showed diffuse destruction of alveolar tissue, consistent with panlobular emphysema. In contrast, relatively preserved lower portions of the lungs were observed in patients with smoking-associated emphysema, consistent with centrolobular emphysema.
Immunophenotype analysis
Emphysema patients had an increased number of ICI (CD20, CD3, CD8, CD68, CD45RO, CD4 and PMN) as compared with controls (p ≤ 0.01). An increased number of CD3 (p ≤ 0.05), CD8 (p ≤ 0.05) and CD45RO (p ≤ 0.001) was seen in AAT-deficiency emphysema compared to smoking-related emphysema (Table 2).
Table 2 Inflammatory Cells (Total Cells/MM Alveolar Wall)
AAT Smokers Controls * P†
CD20 4.77 2.1 0.0 ns
CD3 25.39 17.84 2.5 <0,05
CD8 12.32 5.07 0.99 <0,05
CD68 4.35 6.88 0.75 ns
CD45RO 25.42 8.34 2.31 0,001
CD4 12.1 12.67 1.89 ns
PMN 18.07 20.78 0.0 ns
Definition of abbreviation. PMN: Polymorphonuclear cells
* The values of control group were all statistically significant compared to both emphysema groups.
† Significant differences between AAT-deficiency and smoking patients.
Analysis of epithelial apoptosis and proliferation
Labeling of the DNA breaks by TUNEL demonstrated positive cells that were localized to peribronchiolar, intra-alveolar and septal sites in both normal and emphysematous lungs. Quantification was limited to the alveolar wall. Apoptotic bodies that were very close to each other were counted as one dying cell. Intra-alveolar apoptotic cells were not included in the cell count.
In emphysematous lungs AI ranged from 0.68 to 11.92 (mean 6.3 ± 3.5). The TUNEL-positive cells were more frequently detected within more enlarged alveolar walls. Apoptotic cells and/or bodies were frequently seen in intra-alveolar lumen that presumably represented apoptotic cells detached from the alveolar wall (Fig. 1). AI was significantly higher in patients than in controls (6.5 ± 3.5 vs 2.7 ± 2.6, p ≤ 0.01) (Fig 2). If separately compared with the control group only the AAT-deficiency emphysema showed a statistically significant difference (p ≤ 0.01 vs p = 0.09). Increased levels of oligonucleosomal-length DNA fragments were also detected in emphysema patients, particularly in AAT-deficiency emphysema, than control lungs (Fig. 3a,b). The PI of patients ranged from 0.19% to 4.81% (mean 1.9 ± 2.2). Similar numbers of MIB1-positive alveolar septal cells were observed in both types of emphysema and control lungs (1.7 ± 1.1).
Figure 1 AAT-deficiency emphysema case 1: Micrograph showing strong specific staining for DNA strand breaks in the alveolar epithelial cells and in two cells detaching from the wall. TUNEL (original magnification 160×).
Figure 2 AI in controls vs emphysema patients: Significantly higher AI was found in emphysema patients (6.5 ± 3.5 vs 2.7 ± 2.6, p ≤ 0.01) ◊ = AAT-deficiency emphysema; ○ = smoking-related emphysema.
Figure 3 Gel-electrophoresis: a) Oligonucleosomal-length DNA laddering in emphysematous and control lungs. Lane 1: DNA marker; Lanes 2–5: control donor lungs (4 cases); Lanes 6–9: AAT-deficiency emphysema patients (4 cases); Lanes 10–13: smoking-related emphysema patients (4 cases); Lane 14: positive control. b) Quantification of DNA laddering based on scanning densitometry of bands approximately between 1000 bp and 300 bp (arrowhead) followed by normalization with the density obtained with the equivalent band of the thymus DNA positive control (lung sample/control = densitometric ratio) which was included in every oligonucleosomal DNA laddering assay.
TUNEL-positive/MIB1-negative nuclei detected by double staining were seen in all cases, whereas MIB1 was never expressed in any of the TUNEL-positive nuclei (Fig. 4a,b).
Figure 4 Smoking-related emphysema case 3: a) double labeling TUNEL/MIB1 (marker of cell proliferation) showing two apoptotic cells (dark) and one MIB1-positive cell (blue), on the surface of the same alveolar wall (original magnification 160×). b) Note alveolar cell in proliferation close (blue) to apoptotic pneumocyte (dark) (Original magnification 160×).
In each group, no statistically significant correlations were found between AI and PI as well as between AI/PI and ICI.
At electron microscopy typical features of early apoptosis with margination of chromatin at the nuclear membrane and late apoptosis with completely dense nuclear chromatin, including apoptotic bodies in various stages of degradation, were seen in pneumocytes, endothelial cells and fibroblasts. Typical features of reduplication of vessel basal membranes were frequently seen in cases with more evident apoptosis (5 a-f). Ultrastructural analysis showed more frequent mitotic features in type II pneumocytes.
Figure 5 AAT-deficiency emphysema (case 1): Electron micrograph showing (a) early apoptosis with perinuclear chromatin condensation (arrow) and (b) late apoptosis with nuclear dense chromatin of pneumocytes (arrow). (c) An endothelial cell with condensed chromatin is well visible (arrow). (d) Note reduplication of the vessel basal membrane (arrow). In (e) and (f) apoptotic bodies in various degrees of degradation close to a macrophage and an intraluminal apoptotic body are well visible (arrows).
TGF-β1 and TGF-βRII receptor analysis
In emphysema patients and controls TGF-β1 and TGF-βRII were localized in bronchiolar and alveolar epithelial cells and macrophages. Quantitative analysis of TGF-β1 measured in the alveolar wall showed no statistically significant difference between emphysema patients and controls. A higher cytokine expression was noted in patients with smoking-associated emphysema compared with AAT-deficiency disease (mean 8.8 ± 1.7 vs 5.2 ± 3.9, p ≤ 0.05) (Fig. 6). A positive significant correlation between TGF-βRII and AI (p = 0.005; r2 = 0.8) was seen in control lungs (Fig. 7). A significant negative correlation was found between TGF-β pathway (particularly TGF-βRII) and T lymphocytes infiltrate (CD3+) (p ≤ 0.05, r2 = 0.99) in smoking-related cases. No correlation was noted between the TGF-β1 pathway (TGF-β1 and its RII) and the AI/ PI of emphysematous lungs.
Figure 6 TGF-β1 expression in smoking-related vs AAT-deficiency emphysema: the graphic shows the different cytokine expression in both types of emphysema. A significantly higher TGF-β1 expression was found in smoking-related emphysema versus AAT-deficiency emphysema (mean value 8.8 ± 1.7 vs 5.2 ± 3.9, p ≤ 0.05).
Figure 7 Correlation between TGF-βRII and AI: the graphic shows the correlation between TGF-βRII expression and AI in controls and emphysema patients. The degree of TGF-βRII is linearly related to the extension of apoptosis in the control group (p ≤ 0.005, r2 = 0.8).
Discussion
In the present study we have analyzed for the first time apoptosis and proliferation in different types of end-stage emphysema. The detection of a high AI in emphysematous lungs even in end-stage disease emphasizes the importance of the phenomenon in the development, and overall, in the progression of emphysema.
In general there are two main forms of cell death: oncosis and apoptosis. The latter process results in characteristic biochemical features and cellular morphology such as cell shrinkage condensation and fragmentation of the nucleus into well contained fragments called apoptotic bodies.
Perturbation of normal rates of apoptosis has been implicated in many pathologic conditions such as neuro-vegetative, cardiovascular and liver disorders and cancer [20-22]. As stated in Tuder's recent review on apoptosis and its role in emphysema, cell damage, apoptosis, apoptotic cell removal, and cellular replacement are ongoing and presumably highly regulated in order to maintain homeostasis of the entire alveolar unit. The concept of the irreversible destruction of alveolar walls due to the loss of homeostasis of the alveolar unit is a critical point. Lung inflammation, protease/antiprotease imbalance, oxidative stress and apoptosis could work together in the irreversible changes seen in emphysema [23]. Over-induction of apoptosis and inefficient cellular replenishment, modifying alveolar homeostasis, would both be expected to disrupt the alveolar wall thus inducing the development of emphysema.
Recently the causal role of apoptosis has been increasingly recognized in the destruction of alveolar walls and airspace enlargement [6-9]. Among constitutive cell populations of the alveolar wall, epithelial cells are more frequently susceptible to programmed cell death [6,9]. In our study the AI of epithelial cells was significantly higher in end-stage emphysema cases compared to the control group (p ≤ 0.01) and this was particularly more evident for those with AAT-deficiency.
To avoid a bias of under or over-estimated alveolar cell apoptosis and proliferation due to regional disease activity we analyzed large specimens taken from different lung regions (upper and lower lobes). The lower AI detected in our control lungs underlines an important concept: in non-emphysematous lungs apoptosis is an irrelevant process adequately balanced by proliferation. The increased number of apoptotic cells in patients with emphysema (not adequately replaced by new epithelial cells) suggests a new mechanism, namely "epithelial apoptosis/proliferation imbalance" in the pathogenesis of disease. In our study, different from a recent clinical study by Yokohori et al [9], a PI similar to that of the control group was detected in the alveolar epithelial cells of emphysema patients. The discrepancies between the two studies can be attributed to several factors: 1) a different monoclonal antibody used for detection of cell proliferation (MIB1 vs PCNA); 2) different case series including patients affected by emphysema in end-stage status and overall of different types (smoking-associated and AAT-deficiency emphysema), and 3) more analysis of extensive areas (upper and lower lobes) of emphysematous lung parenchyma. Regarding the monoclonal antibody used for proliferation detection, Ki-67 is now well recognized as the most reliable immunohistochemical marker for the analysis of cell proliferation in formalin-fixed, paraffin-embedded tissue [24]. Immunoassaying for proliferating nuclear cell antigen (PCNA) can also be used in paraffin-embedded tissue, but it may overestimate the proliferation rate given the long half-life of this antigen [25]. Moreover, the simultaneous positive staining of TUNEL and PCNA in the same cells has been reported [26]. In fact, it has also been demonstrated that PCNA expression can increase without a corresponding increase in S-phase DNA synthesis [27].
DNA nicks may be seen in cells with DNA synthesis/repair thus sometimes producing false TUNEL positive cells. False positive TUNEL staining can also be generated through non-apoptotic mechanisms: RNA synthesis and splicing, necrosis as well as artifacts due to preservation methods. Consequently, some authors have stressed the importance of associating other techniques, such as Taq polymerase-based DNA in situ ligation, DNA gel electrophoresis or electron microscopy, in order to avoid false positive labeling and to assess the reliability of apoptosis [28].
Our TUNEL findings have been corroborated by employing an additional quantitative apoptosis assay. Moreover, the presence of different stages of apoptosis was confirmed and the cells involved in programed cell death were well characterized by using electron microscopy investigation, which is considered the gold-standard technique for apoptotic cell detection. In our work double-immune labeling showed that all TUNEL positive cells were consistently negative for MIB1 thus suggesting the true epithelial DNA fragmentation. Although the high AI detected in our patients could be mainly explained by the high rate of apoptotic cell death, an impaired clearance mechanism of apoptotic cells/bodies should also be considered. A frequent finding of apoptotic bodies in alveolar walls and within lumen may support the latter theory as an important contributing factor for a high percentage of AI.
The principal trigger of epithelial injury leading to apoptotic cell death is up to now still unclear. The cytotoxic effects of cigarette smoke, one of the most clearly proven etiologic factors in the development of emphysema and in general of COPD, have been suggested to suppress epithelial proliferation and to induce cell death. In particular oxidants and aldehydes, major constituents in the volatile phase of cigarette smoke, have been reported to induce apoptosis of lung cells [29].
Different DNA and RNA viruses have been identified as viral pathogens associated with the disease. Double-strand DNA viruses such as adenovirus have the ability to persist in airway epithelial cells long after the acute infection has cleared. The expression of adenoviral trans-activating proteins has been demonstrated in the airway epithelium of both human and animal lungs and is associated with an amplification of cigarette smoke-induced inflammatory response [30].
Different adenovirus early proteins, in particular E4orf4, have been reported in the shutoff of host protein synthesis and in the promotion of a p53-independent cell death program [31]. It is likely that many and various noxious agents all come together to play an important role in the progression of cell death in end-stage disease, justifying the high AI in the alveolar wall, as detected in our study. The specific molecular pathogenetic pathways that regulate both cell fate and proliferation are also under investigation. Previous studies demonstrated an inhibitory effect of the TGF-β1 pathway on the growth of lung epithelial cells [14,15].
As the TGF-β1 pathway is well-known for its anti-inflammatory activity, a higher epithelial expression of TGF-β1 in patients with smoking-related emphysema compared with AAT-deficiency may partially justify the different patterns of inflammation in the two types of emphysema, as found in our study. A significantly higher increase of inflammation, particularly due to T lymphocytes, was found in AAT-deficiency emphysema (panlobular type) than in smoking-related disease (centrilobular type), with the latter displaying an increased expression of the TGF-β pathway (as demonstrated by the negative correlation with T lymphocyte infiltrate). Similar findings have been previously reported in both in vitro and in vivo studies [32,33]. An increased pro-apoptotic milieu of inflammatory related cytokines may contribute to the higher cell death rate detected in AATdeficiency emphysema. Moreover, additional cigarette smoke-mediated damage should also be considered in AAT-deficiency emphysema patients, in that in our study they were all heavy smokers.
In our work a direct correlation between TGF-βRII and AI was found in the control group thus showing that this cytokine could play a role in alveolar homeostasis in physiologic conditions. Instead no correlation was found between the AI and TGF-β1 pathway in either type of emphysema, suggesting that the TGF-β1 regulated mechanism is lost in the disease. Other cytokines besides TGF-β1 could be involved in uncontrolled programed cell death inducing the progressive disappearance of the alveolar unit.
Decreased expression of VEGF and VEGF R2 has been demonstrated to be significantly correlated with apoptosis of both epithelial and endothelial cells in cigarette smoking-induced emphysema [7]. It has been shown that VEGF receptor signaling is extremely important for the maintenance of alveolar structures. Hence an impairment of its trophic endothelial activity may be one of several factors facilitating alveolar septal cell apoptosis [4,7]. Significantly reduced levels of VEGF have also been detected in induced sputum of emphysema patients compared to that of normal individuals and patients with asthma [34].
More recently in an experimental model some authors have shown that over-expression of placenta growth factor (PIGF) causes a phenotype and pulmonary dysfunction similar to human lung emphysema by inducing apoptotic events in the alveolar septa [35]. Although epithelial cells have been demonstrated to be more susceptible to apoptosis [7], endothelial cells are also an important target for programed cell death. Our ultrastructural analysis showed evidence of endothelial cell apoptosis mainly in those cases with more increased alveolar programed cell death. The presence of a multi-layered vessel basement membrane, as found in many of our emphysematous lungs, may also reflect additional data supporting the increased apoptotic rate of endothelial cells.
In summary, our work has demonstrated for the first time that apoptotic phenomenon is extensive also in end-stage emphysema patients. This unique case series, and overall the large variety of lung tissue samples examined, (not only subpleural emphysematous regions as those from lung volume reduction surgery in which apoptosis could already be switched off) may account for the differences in our AI findings compared to other studies [9]. The higher rate of apoptotic cell death in patients with AAT-deficiency emphysema, partially influenced by the higher degree of inflammation, may allow us to consider this peculiar emphysema subtype as an additional modifier of apoptosis.
Whether the "apoptosis/proliferation imbalance" occurs before, after or at the same time as the "elastase/antielastase imbalance" is still unknown and should be the subject of future studies.
Limitations of the study
Our study had a few limitations. Firstly, the patients with AAT-deficiency can not be considered pure AAT-deficiency emphysema cases because these patients were also smokers. Panlobular emphysema occurs at a younger age in alpha-1-antitrypsin patients, especially if the patients smoke cigarettes, as in our case series (49.8 ± 5.7 yrs AAT-deficiency vs 58.2 ± 6.3 yrs smokers, p ≤ 0.01). Patients with AAT-deficiency who are smokers develop lung impairment function earlier and in a more severe form than their non-smoking counterparts. Thus, it is extremely rare to have patients who are non-smokers with AAT-deficiency as candidates for lung transplantation. Secondly, the clinical characterization of the donor was poor and according to the guidelines for the selection of donor lungs, smokers were not excluded [36]. Smokers could have been included in the control group, and it is well known that smoking itself may induce apoptosis.
However, if this was the case, the AI difference between emphysema and control patients would have been even higher because of the lower AI in healthy patients. A third potential bias is that all the donors were mechanically ventilated before lung transplantation and it is known that mechanical ventilation may induce lung apoptosis [37]. Again, the difference observed in our study would be even higher than non-ventilated controls, thus confirming the findings that enhanced apoptosis may act as a leading mechanism in the pathogenesis of emphysema.
Conclusions
Our study analyzed apoptosis and proliferation in end-stage emphysema. In particular the work described for the first time a high AI in patients with AAT-deficiency emphysema. Ultrastructural investigation, TUNEL analysis and oligonucleosomal-length DNA laddering, performed in different lung regions were all used for detection of apoptotic phenomenon. The increase of apoptotic cells in patients with emphysema not adequately replaced by new epithelial cells suggests a new mechanism, namely "epithelial apoptosis/proliferation imbalance" in the pathogenesis of disease. More inflammation, particularly due to T lymphocytes, was observed in AAT-deficiency emphysematous lungs. An increased pro-apoptotic milieu of inflammatory related cytokines may contribute to the higher cell death rate detected in AAT-deficiency emphysema. While a direct correlation between TGF-βRII and AI was found in the control group, no relation was found between the AI and TGF-β1 pathway in end-stage emphysema, suggesting that the influence of the TGF-β pathway on epithelial turnover is lost in the disease. Knowledge of the mechanism responsible for activation and progression of the apoptotic cascade could offer new information in the near future, on more appropriate stratification and treatment of the disease.
Authors' contributions
FC: conceived of the study and participated in its design and coordination
CG: substantial contribution in study design and data interpretation
BB: acquisition of clinical data and critical revision for important intellectual content
FR: thoracic surgeon providing lung specimen and critical revision for important technical aspects
ML: thoracic surgeon providing lung specimen and critical revision for important technical aspects
RZ: critical revision for important intellectual content
GP: acquisition of clinical data
SB: acquisition of clinical data and performed the statistical analysis
MS: participated in the design of the study and gave critical revision for important intellectual content
MV: substantial contribution in study design and data interpretation
All the authors read and approved the final manuscript.
Acknowledgements
We would like to thank Alessandra Dubrovich and Giovanna Mattiazzo for their excellent technical assistance and Dr. Judith Wilson for revision of the English manuscript. Sources of support: Grant Project "Chronic obstructive pulmonary disease (COPD) and lung transplantation: morphologic and molecular study of pathogenetic substrates of disease progression" and "Structure-function relationships in chronic obstructive pulmonary disease", Ministery of Education, University and Research, Rome, Italy
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| 15705190 | PMC549521 | CC BY | 2021-01-04 16:36:27 | no | Respir Res. 2005 Feb 10; 6(1):14 | utf-8 | Respir Res | 2,005 | 10.1186/1465-9921-6-14 | oa_comm |
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Biomed Eng OnlineBioMedical Engineering OnLine1475-925XBioMed Central London 1475-925X-4-101570749410.1186/1475-925X-4-10ResearchPassive and active ventricular elastances of the left ventricle Zhong Liang [email protected] Dhanjoo N [email protected] Eddie YK [email protected] Soo T [email protected] College of Engineering, School of Mechanical and Production Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 6397982 Bioengineering Division, College of Engineering, Nanyang Technological University, Singapore, 6397983 Department of Cardiology, National Heart Centre, SingHealth, Mistri Wing, 3rd Hospical Ave., Singapore, 1685722005 11 2 2005 4 10 10 6 12 2004 11 2 2005 Copyright © 2005 Zhong et al; licensee BioMed Central Ltd.2005Zhong 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
Description of the heart as a pump has been dominated by models based on elastance and compliance. Here, we are presenting a somewhat new concept of time-varying passive and active elastance. The mathematical basis of time-varying elastance of the ventricle is presented. We have defined elastance in terms of the relationship between ventricular pressure and volume, as: dP = EdV + VdE, where E includes passive (Ep) and active (Ea) elastance. By incorporating this concept in left ventricular (LV) models to simulate filling and systolic phases, we have obtained the time-varying expression for Ea and the LV-volume dependent expression for Ep.
Methods and Results
Using the patient's catheterization-ventriculogram data, the values of passive and active elastance are computed. Ea is expressed as: ; Epis represented as: . Ea is deemed to represent a measure of LV contractility. Hence, Peak dP/dt and ejection fraction (EF) are computed from the monitored data and used as the traditional measures of LV contractility. When our computed peak active elastance (Ea,max) is compared against these traditional indices by linear regression, a high degree of correlation is obtained. As regards Ep, it constitutes a volume-dependent stiffness property of the LV, and is deemed to represent resistance-to-filling.
Conclusions
Passive and active ventricular elastance formulae can be evaluated from a single-beat P-V data by means of a simple-to-apply LV model. The active elastance (Ea) can be used to characterize the ventricle's contractile state, while passive elastance (Ep) can represent a measure of resistance-to-filling.
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Background
The heart may be conceived as a pump that receives blood from a low-pressure system and raises it to a high-pressure system. Although the mechanism responsible for generation of wall stress (and hence left ventricular (LV) pressure) is contraction of the myocardial fibers, an analytical formulation linking the myocardial and LV dynamics is still lacking. In the absence of this formulation, a popular way of linking LV pressure and volume dynamics is by means of LV compliance (or elastance) [1,2]. Although this yields the cyclic values of elastance and compliance, this concept does not provide an intrinsic measure of elastance and compliance for the contractile state of the LV.
The concept of compliance or elastance was first employed for blood vessels [3], by relating incremental cross-section area (or volume) and transmural pressure. Warner appears to be have been the first to adopt a compliance description for a dynamic heart [4]. In Warner's description, a mean value of compliance is adopted for diastolic phase and another mean value for systole, with abrupt transitions between the two states.
Defares [5] avoided the stepwise transition between diastolic and systolic compliance, by making elastance a continuously varying function of time. Later, the concept of a continuously varying compliance or elastance was adopted by a number of investigators with diverse variations [2,6,7]. Nevertheless, they all share the concept of a simple and extrinsic compliance term as an adequate description of ventricular mechanics during the cardiac cycle, based on monitored values of LV pressure and volume.
Classically, ventricular compliance is defined, at any point in time, as the change in ventricular volume concomitant with the change in ventricular pressure, such that
C = dV / dP, E = dP / dV (1)
If C is assumed constant, this equation becomes a linear relation, whose integration gives
V = CP + Vc (2)
where Vc is an integration constant. If the compliance varies with time, then all terms in equation (2) may vary with time, as:
V (t) - Vc (t) = C(t)P(t) (3)
In this context, Suga [8] opted for the definition of ventricular elastance as
to represent the elastance of the contracting LV, where Vd represents the unstressed LV volume corresponding to zero LV-pressure, obtained by drawing a tangent to P-V curves at end-ejection, as illustrated in Figure 1. This model gave rise to the development of the end-systolic pressure-volume relation (ESPVR) as a measure of contractility [9-14].
Figure 1 Schematic drawing of P-V loops and end-systolic P-V relation (ESPVR). Schematic drawing of P-V loops and end-systolic P-V relationship (ESPVR) with a positive volume intercept Vd. The slope of ESPVR line is deemed to be Emax.
However, the determination of the maximal slope Emax and of the volume-axis intercept (Vd) of the tangent to the P-V curve at end-ejection (as a measure contractility of the cardiac muscle) is not only unreliable [11,15], but also requires generation of multiple P-V loops under variations loading conditions [11,15]. It is hence impractical to use clinically for a specific LV catheterization-ventriculography data. Above all, all of these variations in the concept of E obtained from LV pressure-volume data fail to explain the phenomena of LV suction and LV pressure drop during early filling as well as the generation of LV pressure increase during isovolumic contraction.
We have hence come up with a new concept of dual passive and active elastances operating throughout the cardiac cycle. The passive elastance (Ep) represents the LV pressure response to LV volume change (to LV volume increase during LV filling phase and to LV volume decrease during LV ejection phase). However, simultaneously, we also have active elastance (Ea) representing the contraction of the left ventricle due to its sarcomeric activation (and the development of force between the actin-myosin units) and relaxation (due to disengagement of the actin-myosin units).
LV Ea develops after the start of isovolumic contraction, becomes maximum some time during late ejection and thereafter decreases and becomes zero during diastolic filling. On the other hand LV Ep starts increasing after the initiation of LV filling as the LV volume increases. It reaches its maximum value at the end-of-filling phase, remains constant during isovolumic contraction, and thereafter decreases during ejection (as the LV volume decreases). While the generation of Ea helps us to explain the development of the LV pressure increase during isovolumic contraction, the decrease of Ea during diastole helps us to explain the decrease in LV pressure during early filling. The incorporation of both Ep and Ea helps us to explain the LV pressure changes during the filling and ejection phases.
Methods
Data acquisition
The subjects in this study were studied in a resting recumbent (baseline) state, after premedication with 100–500 mg of sodium pentobarbital by retrograde aortic catheterization. Left ventricular chamber pressure was measured by a pigtail catheter and Statham P23Eb pressure transducer; the pressure was recorded during ventriculography. Angiography was performed by injecting 30–36 ml of 75% sodium diatrizoate into the LV at 10 to 12 ml/s. It has been found by using biplane angiocardiograms that calculated orthogonal chamber diameters are nearly identical [16]. These findings are used to justify the use of single-plane cine techniques, which allow for beat-to-beat analysis of the chamber dimensions.
For our study, monoplane cineangiocardiograms were recorded in a RAO 30° projection from a 9 in image intensifier using 35 mm film at 50 frames/s using INTEGRIS Allura 9 system at the Nation Heart Centre (NHC), Singapore. Automated LV analysis was carried out to calculate LV volume and myocardial wall thickness. The LV data, derived from the cineangiographic films and depicted in Figure 2 consists of measured volume and myocardial thickness of the chamber as well as the corresponding pressure. All measurements are corrected for geometric distortion due to the respective recordings systems.
Figure 2 A case study of measured LV pressure, volume and wall thickness during a cardiac cycle. An example of a patient's measured LV pressure, volume and wall thickness during a cardiac cycle; t = 0-0.08s is the isovolumic contraction phase, t = 0.08s-0.32s is the ejection phase, t = 0.32s-0.40s is the isovolumic relaxation phase, and t = 0.40s-0.72s is the filling phase. Note that even after 0.4 s, the LV pressure still continues to decrease from 17 mmHg (at 0.4s, at start of filling) to 8 mmHg at 0.44s.
In Figure 2, it is noted that during the early filling phase, LV pressure decreases even though LV volume increases. This phenomenon is defined as the 'LV suction effect', which will be explained later by using our concepts of active and passive elastances. This phenomenon is also depicted in Figure 3 and Table 1.
Figure 3 Relationship between LV volume and pressure for the data of figure 2. Relationship between LV volume and pressure for the data of Figure 1. Points (21–36) constitute the filling phase, (1–5) constitute the isovolumic contraction phase, (5–17) constitute the ejection phase, and (17–21) constitute the isovolumic relaxation phase. Note that after point 21, the LV pressure decreases; this characterizes LV suction effect.
Table 1 Computed values of Ea and Ep during the cardiac cycle, for subject HEL
Point Phase Time Pressure Volume Ea Ep
1 Isovolumic contraction 0 18 136.7 0 0.968314
2 0.02 22 135.7 0.051287 0.930811
3 0.04 32 134.6 0.153167 0.891234
4 0.06 52 133.5 0.282331 0.853339
5 0.08 80 132.5 0.424912 0.820289
6 Ejection 0.1 94 129 0.570602 0.714374
7 0.12 103 124.5 0.711775 0.598039
8 0.14 110 119.3 0.843116 0.486996
9 0.16 113 114 0.961299 0.395008
10 0.18 116 107.3 1.06464 0.303159
11 0.2 118 101.8 1.15275 0.243961
12 0.22 120 97.5 1.22616 0.205852
13 0.24 121 94 1.28607 0.179272
14 0.26 122 91 1.334 0.159239
15 0.28 120 88 1.37114 0.141444
16 0.3 116 85.5 1.34002 0.128144
17 0.32 100 84.3 1.15107 0.122212
18 Isovolumic relaxation 0.34 74 85 0.846411 0.125638
19 0.36 50 85.5 0.523931 0.128144
20 0.38 30 86.4 0.269515 0.132782
21 0.4 17 90.6 0.113989 0.156743
22 Filling 0.42 10 105 0.0392726 0.276831
23 0.44 8 112 0.0109316 0.365003
24 0.46 8.4 117 0.00244008 0.444703
25 0.48 9 119 0.00043378 0.481259
26 0.5 9.6 120.2 6.10272e-005 0.50462
27 0.52 10.2 121 6.75442e-006 0.520821
28 0.54 10.5 121.4 5.84848e-007 0.529115
29 0.56 10.7 121.6 3.94098e-008 0.533312
30 0.58 10.8 121.8 2.0564e-009 0.537542
31 0.6 11 122 8.2698e-011 0.541805
32 0.62 11.8 124 2.55156e-012 0.586344
33 0.64 12.8 127 6.01397e-014 0.66011
34 0.66 14.5 130.7 1.07837e-015 0.763991
35 0.68 17 134 1.46518e-017 0.87036
36 0.7 20 136.6 1.50271e-019 0.964497
37 0.72 18 136.7 1.15909e-021 0.968314
Definition of passive elastance and active elastance of the LV
At the start of diastolic-filling phase, the LV incremental pressure dPLV is the response to (i) LV Ea continuing to decrease due to the sarcomere continuing to relax well into the filling phase, and (ii) to the rapid inflow of blood and the corresponding increase in LV volume, along with increase in LV Ep. The associated governing differential equation, relating LV pressure and volume, can be put down (by referring to the Appendix for its derivation) as [17]:
where t represents the time variable (s) from the start of filling phase;
V represents the volume of LV (ml) during the filling phase;
PLV represents pressure of the LV, in mmHg (hereafter symbolized by P) (mmHg);
M represents the inertia term = [LV wall-density (ρ)/(LV surface-area/wall-thickness)] = ρh / 4πR2, for a spherical LV model (in mmHg/(ml/s2));
E represents LV elastance (mmHg/ml).
Likewise during ejection, the LV pressure variation (dPLV) is caused by both Ea variation as well as Ep decrease. The instantaneous time-varying ventricular elastance (E) is the sum of (i) volume-dependent passive elastance (Ep) and (ii) active elastance (Ea) due to the activation of the LV sarcomere. Hence,
E = Ea + Ep (6)
We will now provide the expressions for Ep and Ea, and then their formulations. The passive (unactivated) myocardium exhibits properties of an elastic material, developing an increasing stress as strain increases, as occurs during ventricular filling. The passive stress-strain relation of myocardial muscle strip is nonlinear, and therefore cannot be described by Hooke's law. As an approximation, it follows an exponential relationship [18-20]. Therefore, the relation between LV passive pressure and volume has also been assumed to be exponential. Since Ep (= dP/dV) is volume-dependent, we can express it as:
where Ep0 is the passive elastance coefficient, zp is the passive elastance exponent, and V is the LV volume; its derivation is provided in a subsequent section.
On the other hand, we will represent Ea as an intrinsic property of the LV (derived later), as:
where (i) t is measured from the start of isovolumic contraction, (ii) the parameter Ea0 is the active elastance coefficient, (iii) the time-coefficient (τC) describes the rate of elastance rise during the contraction phase, while (τR) describes the rate of elastance fall during the relaxation phase; (iv) the exponents "ZC" and "ZR" are introduced to smoothen the curvatures of the Ea curve during isovolumic contraction and relaxation phases; (v) the parameter d is a time constant whose (to be determined) value is during the ejection phase, and (vi) u(t-d) is the unit step function, u(t-d) = 0 for t<d. The rationale for equation (8), as provided in the next section, is based on Ea incorporating parameters reflecting the (i) generation of LV pressure during isovolumic contraction, (ii) decrease of LV pressure during isovolumic relaxation and early filling, and (iii) the LV pressure-volume relationship during filling and ejection phase.
Our hypothesis
Based on equations (5–8), our hypothesis is that both Ea and Ep contribute to the relationship of LV pressure and volume. While Ep incorporates LV pressure change due to LV volume change, Ea incorporates the effect of LV myocardial activation in the generation of LV pressure during the isovolumic phases (when the LV volume remains constant). Since Ea is deemed to be the basis of LV pressure generation, its variation (as given by equation 8) corresponds to the LV pressure variation.
Determination of Ea and Ep expressions
a) Active elastance (during isovolumic contraction and relaxation)
During isovolumic contraction (because dV = 0, and Ep is constant), the governing equation (5) becomes VdE = dPLV, which can be detailed as:
Vi(Ei - Ei-1) = Vi[(Ea,i + Ep,i) - (Ea,i-1 + Ep,i-1)] = Vi(Ea,i + Eped - Ea,i-1 - Eped) = dPLV,i (9)
where i is a time instant during the isovolumic contraction and relaxation, Vi and PLV,i are the monitored LV volume and pressure at this instant, and Eped is the passive elastance at the end-diastolic phase.
Also, during isovolumic relaxation (because dV = 0, and Ep is constant), the governing equation (5) becomes VdE = dPLV, which can be represented as:
Vi (Ea,i + Ep,i - Ea,i-1 - Ep,i-1) = Vi (Ea,i + Epes - Ea,i-1 - Epes) = dPLV,i (10)
where Epes is the passive elastance at the end-systolic phase
Now, applying equations (9 & 10) to the case shown in the Figure 2, we have (using the monitored LV pressure-volume data):
1. For isovolumic contraction
Ea,1 = 0 (11-a)
Ea,2 = (P2 - P1)/V2 + Ea,1 = 0.029477 mmHg/ml (11-b)
Ea,3 = (P3 - P2)/V3 + Ea,2 = 0.103771 mmHg/ml (11-c)
Ea,4 = (P4 - P3)/V4 + Ea,3 = 0.253584 mmHg/ml (11-d)
Ea,5 = (P5 - P4)/V5 + Ea,4 = 0.463599 mmHg/ml (11-e)
2. For isovolumic relaxation
Ea,18 = (P18 - P17)/V18 + Ea,17 = Ea,17 - 0.058954 mmHg/ml (11-f)
Ea,19 = (P19 - P18)/V19 + Ea,18 = Ea,17 - 0.177824 mmHg/ml (11-g)
Ea,20 = (P20 - P19)/V20 + Ea,19 = Ea,17 - 0.312656 mmHg/ml (11-h)
Ea,21 = (P21 - P20)/V21 + Ea,20 = Ea,17 - 0.463599 mmHg/ml (11-i)
Now in the above expressions 11(f-i), Ea,17 at end-ejection is unknown. For different representative values of Ea,17, we can get different Ea curves. We need to determine the optimal value of Ea,17, such that Ea can be described by a smooth curve to fit both isovolumic contraction and ejection phases. In Figure 4, we have determined Ea,17 = 1.1 mmHg/ml, and the polynomial expression for Ea(t) to fit its above calculated values during isovolumic contraction and relaxation. However, in order to (i) more suitably represent Ea to correspond with its role during the cardiac phases (isovolumic, ejection and filling), and (ii) because of the sigmoidal shape of Ea curve and its variation resembling the LV pressure variation during systole (as seen in Figure 4), we express Ea (according to equation 8) as:
Figure 4 Ea vs. time for the data of figure 2. Points (1–5) are the computed values of Ea during isovolumic contraction phase, based on equations 11(a-e). In the isovolumic relaxation phase, the computed values are represented by the symbol Δ, for Ea,17 = 1.1 mmHg/ml. The best fit for Ea during isovolumic contraction and relaxation phase is given by the curve: Ea = -12000t6 + 17000t5 - 7700t4 + 1100t3 + 19t2 + 0.59t + 0.00056
So that its constituent parameters have physiological significance as indicated following equation (8).
Hence, to compute Ea(s) during isovolumic contraction, when u(t-d) = 0, we employ the expression
and determine its parameters Ea0, τC and ZC to fit the monitored pressure-volume data. Then, to compute Ea(s) during isovolumic relaxation, we employ the total expression
and determine its remaining parameters d, τR and ZR to fit the measured pressure-volume data.
For the sample data of Figure 2, the variation of Ea is depicted in Figure 5, along with the values of its parameters. We now propose that Ea can be employed as an index of contractility.
Figure 5 The data of figure 2 is fitted with equation (8). When the patient data of Figure 2 is fitted with equation (8), the resulting parameters values are obtained as: Ea0 = 1.48 mmHg/ml, τC = 0.1555 s, ZC = 1.631, d = 0.28 s, τR = 0.07935 s, ZR = 2.267 s, Ea,17 = 1.1 mmHg/ml, RMS = 0.026 mmHg/ml.
b) Passive elastance determination during diastolic filling
During the diastolic filling phase, equation (5) becomes
Now because Ep is constant at a particular volume Vi, equation (13) becomes
where i is a time-instant during diastolic filling, Vi and PLV,i are the monitored LV volume and pressure at this time, and M = ρh / 4πR2. For the patient data (shown in Figure 2), we can get the mean value for M during diastolic filling, M = 8.03 × 10-6 mmHg/(ml/s2). Therefore, from equation (15), we can calculate the values of Ep at various instants during filling phase. We then plot Ep vs V, in Figure 6. By fitting equation (7) to these calculated values of Ep, we obtain the values of the parameters Ep0 and zp, as:
Figure 6 Passive elastance Ep vs LV volume for the data of figure 2. Passive elastance Ep vs LV volume V, for the sample case shown in Figure 2.
zp = 0.0395 ml-1, Ep0 = 4.375 × 10-3 mmHg / ml (16)
and the Ep function (corresponding to its expression given by equation 7) as follows:
Ep = 4.375 × 10-3 e0.0395V (17)
We now propose to adopt Ep as a measure of LV resistance-to-filling.
Hence during ejection, both Ea and Ep are varying. During ejection and filling phases, Ep can be calculated at any time using equation (17). Likewise, Ea can be calculated during ejection and filling phases using equation (8), once its parameters have been determined by employing equation (12-b & 12-b) during isovolumic contraction and relaxation phases. Their values during the cardiac cycle are listed in Table 1.
Clinical application results
The analyses, presented herewith, are now applied to clinically obtained data consisting of the subject's left ventricular (instant-to-instant) dimensions (obtained by cineangiocardiograph) and chamber pressure (obtained by cardiac catheterization). For each subject, passive and active elastances are determined from the left ventricular data. Table 2 provides the measured data and the model-derived parameters for three subjects (subject HEL, DDM, and ML). Subject HEL serves as a sample patient with myocardial infarct, subject DDM with double vessel disease (DVD) and hypertension, treated with PTCA; subject ML with idiopathic myocardial hypertrophy (IMH).
Table 2 Clinical history, measured hemodynamic data and calculated passive and active elastance parameters (Ep and Ea) for subjects (HEL, DDM and ML). Where LVP: left ventricle chamber pressure, AOP: aortic pressure, EDV: end-diastolic volume, ESV: end-systolic volume, EF: ejection fraction, MI: myocardial infarct, DVD: double vessel disease, HTN: hypertension, IMH: idiopathic myocardial hypertrophy, Ea,max : maximum active elastance
Subject H.E.L D.D.M M.L
Disease MI, DVD DVD, HTN IMH
LVP (mmHg) 122/18 170/24 109/12
AOP (mmHg) 125/75 169/99 115/70
EDV/ESV (ml) 132.5/84.3 121.7/41.3 368/284
EF 0.36 0.66 0.23
Ep0 (mmHg/ml) 4.375 × 10-3 6.74 × 10-5 1.442 × 10-8
zp (ml-1) 0.0395 0.07499 0.05024
Ea0 (mmHg/ml) 1.48 4.4 0.595
τC (s) 0.1555 0.207 0.1082
ZC 1.631 1.536 1.977
d (s) 0.28 0.26 0.18
τR (s) 0.07935 0.1536 0.1377
ZR 2.267 2.943 1.873
Ea,max (mmHg/ml) 1.37 3.58 0.57
dP / dtmax (mmHg/s) 1200 1475 1125
The variations of model-derived nonlinear passive and active elastances for the subject HEL are shown in Figure 7. For this particular subject (HEL), the maximum active elastance is 1.37 mmHg/ml. In Figure 8, we have plotted Ea vs incremental pressure (P-Ped) for this patient HEL. Note that the elastance is much higher at late-ejection than early ejection. This is because of a continuing sarcomere stress development and shortening. The active elastance reaches its maximum value at late-ejection (point 15), and thereafter decreases. However as shown in Figure 7, even after the end of relaxation phase (point 21) the active elastance continue to decrease into the filling phase. This decrease can explain the suction effect during the rapid filling sub-phase, even after LV filling has commenced.
Figure 7 Pressure, active elastance Ea, and passive elastance Ep and total E = Ea + Ep for the data of figure 2. Pressure, active elastance Ea, passive elastance Ep, and total E = (Ea + Ep) for the sample subject shown in Figure 2. In this figure, 1–5 represents the isovolumic contraction phase, 5–17 represents the ejection phase, and 17–21 represents the isovolumic relaxation phase, 21–37 represents the diastolic filling phase.
Figure 8 Active elastance vs. incremental pressure. Active elastance vs. incremental pressure (P-Ped) for the same subject as shown in Figure 2. The arrow direction indicates progression of time; 1–5: isovolumic contraction phase; 5–17: ejection phase. Note the rapid decrease in Ea during the isovolumic relaxation that also extends into the filling phase, and causes suction of blood into the LV even before initiation of left-atrial contraction.
Figures 9 and 10 provide representations of the nonlinear passive and active elastance for subject HEL (with hypertension), DDM (myocardial infarct), and ML (idiopathic myocardial hypertrophy). The Ep vs LV volume plots, in Figure 9, clearly reveal that Ep increases exponentially with increase LV volume; the parameters (EP0 and zp) characterize this relationship. The passive elastance curve is steeper for a stiffer myocardium, with a corresponding bigger value of the exponential coefficient Zp (subject ML). The Ea vs incremental pressure (P-Ped) plots, in Figure 10, reveal the development and decrease of Ea during systole, which in turn governs the generation of LV pressure.
Figure 9 LV volume and corresponding volume-dependent passive elastance. Volume-dependent passive elastance (Ep) for subjects HEL, DDM, and ML.
Figure 10 Active elastance vs. incremental pressure. Active elastance vs. incremental pressure for subjects HEL, DDM, and ML.
Discussion
Ea as a contractility index
Yet another way to study Ea variation is by means of the Ea vs normalized time (t/ts) plot, shown in Figure 11. These two figures 10 and 11 make us realize that Ea,max could be regarded as an index of LV contractility. Hence, we decided to plot Ea,max vs the traditional contractility indices of EF and (dP/dt)max. These plots are displayed in Figures 12 and 13. It is noted that Ea,max has a high degree of correlation with both EF and (dP/dt)max. It is interesting to compare our correlation-coefficient value (0.8972) with the value of 0.89 obtained by Mehmel et al [12], although this paper computes elastance as an extrinsic property = [P/(V-Vd)]es.
Figure 11 Active elastance vs. normalized time. Active elastance vs normalized time (t/ts) for subjects HEL, DDM, and ML. Herein, ts is the duration from start-of-isovolumic contraction phase to end-of-isovolumic relaxation.
Figure 12 Ea,max vs EF. Relating our contractility index Ea,max to EF factor, with r being the correlation coefficient.
Figure 13 Ea,max vs dP/dtmax .Relating our contractility index Ea,max to the traditional contractility index dP/dtmax, with r being the correlation coefficient.
Demonstrating LV suction phenomenon
The active elastance curve can explain some critical LV physiological phenomena, namely LV pressure generation during isovolumic contraction and LV suction during early filling. The rapid decrease in elastance during isovolumic relaxation extends into the filling phase, and can explain the decrease in LV pressure (in Figure 7) even after LV filling has commenced. Let us show how this happens, by rewriting equation (15) as follows:
Pi - Pi-1 = (Ep,i + Ea,i)(Vi - Vi-1) + Vi (Ea,i - Ea,i-1) (18)
by neglecting the term, based on the calculation of its value being of the order of 10-2 compared to (i) (Ep,i + Ea,i)(Vi - Vi-1), which is of the order of 100 and (ii) Vi(Ea,i - Ea,i-1) which is the order of 101.
In equation (18), it is seen that Pi can be less than Pi-1 (or that Pi - Pi-1 < 0) only if (Ea,i - Ea,i-1) is negative, i.e., active elastance is decreasing. Now for subject H.E.L (Figure 1), the computed values of Ea and Ep at these 2 instants (based on equations 8 & 17) are:
Ep,22 = 0.2768 mmHg/ml, Ea,22 = 0.0393 mmHg/ml, Ea,21 = 0.1140 mmHg/ml, V22 = 105 ml, V21 = 90.6 ml (19)
Substituting these values into equation (18) gives (P22 - P21) = -3.22 mmHg, confirming decrease of pressure during early filling.
Hence, our novel concept of "decreasing Ea during the early phase of filling" enables us to explain the phenomenon of decreasing LV pressure during the early stage of filling. In other words, it is suggested that the sarcomere actin-myosin activity continues into the filling phase. The decreasing Ea during the filling phase seems to reflect decreasing sarcomeric activity during filling. Likewise, the increase in Ea during isovolumic contraction is responsible for increase in LV pressure at constant volume, as demonstrated by means of equation (11).
Demonstrating variation of LV pressure during ejection in terms of Ea and Ep
Similarly, both the active and passive elastances can explain LV pressure variation during ejection, using equation (18). Let us show how this happens by just taking two instants (t10 & t9), as follows:
P10 - P9 = (Ep,10 + Ea,10)(V10 - V9) + V10(Ea,10 - Ea,9) (20)
Substituting these computed values (listed in Table 1) into equation (20) gives P10 - P9 = 1.92 mmHg, which is approximately equal to the actual value of 2 mmHg.
Concluding comments
Previous works have described elastance as a derived parameter from LV pressure-volume data, based on the definition of P / (V - Vd) [9,10,12-14]. Also, Emax (given by ESPVR) as illustrated on Figure 1 varies with different arterial loading states and is therefore load dependent [21], and not an intrinsic index independent of LV loading states.
Our definitions of Ep and Ea enable us to explain the phenomena of (i) LV suction during early filing, (ii) LV pressure rise during isovolumic contraction (iii) LV pressure variation during the ejection phase, and (iv) LV pressure drop during the relaxation phase. Both the concepts of Ea and Ep are made possible by our redefining elastance and compliance as
dP = d(EV) = d(V/C) = VdE + EdV (21)
Our concept of Ea enables us to explain (i) the generation of pressure during isovolumic contraction and decrease of pressure during isovolumic relaxation, when the volume is constant, and (ii) the decrease of pressure during the rapid filling phase.
Our concept of decreasing Ea along with increasing Ep during filling, which enables us to explain the LV suction effect during early filling, is indirectly supported by the work of Shoucri [22]. He has indicated that the LV wall stress during the filling phase is made up of two components: (i) a passive increasing component due to LV pressure and (ii) an active decreasing component due to decreasing active fiber stress.
However, the determination of this active fiber stress in his paper is empirical and not based on a well-defined concept and expression for Ea, as provided by us.
Finally, both Ea and Ep are invoked to explain the variations of pressure during the ejection and filling phases. From the viewpoint of intrinsic indices of LV assessment, Ep can represent LV myocardial stiffness property and resistance to LV filling. On the other hand, Ea has been shown to correspond to LV contractility, by means of Figures 12 & 13. Therein, we have shown a high degree of correlation between Ea,max and (dP/dt)max as well as EF.
In future, we can also couple our LV model (of Ep and Ea) with an arterial lumped-parameter model (consisting of total peripheral resistance R, total arterial compliance C, aortic characteristic impedance Z0 and inertial L) in order to simulate and explain the mechanisms of chronic hypertensive states [23], in terms of alteration in Ea itself as a measure of LV adaptation to chronic hypertension induced in the circulation system.
Appendix: Derivation of Equation (5)
Dynamic equilibrium of the LV myocardial element gives (based on figure 14):
Figure 14 Dynamic equilibrium of a myocardial element. Dynamic equilibrium of a myocardial element. Element mass me = ρ(2r1dθ1)(2r2dθ2)h = (ρh)(4r1r2dθ1θ2) = ρhAe = msAe; dσi = (dPel)(ri) / (2h), (i = 1, 2); dPel is the incremental elastic-recoil pressure. For dynamic equilibrium of the myocardial element, me + 2(dσ1)(2r2dθ2h) + 2(dσ2)(2r1dθ1h) - AedPLV = 0, or me + AedPel - AedPLV = 0. For our LV spherical geometry model, r1 = r2 and dσ1 = dσ2.
where the myocardial element mass, me = ms Ae, ms (the myocardial surface-density or mass per unit surface area) = ρh, ρ is the myocardial density, and u is the radial displacement, dPel and dPLV are the incremental elastic-recoil and left ventricular pressures (as depicted in Figure A-1).
Now since,
By assuming r1 = r2 = R
we can write:
where ρs is the surface density, M = ρsh, and V is the LV volume. Now, referring to Figure A-1,
and
where Re is the resistance to LV filling (through the open mitral-valve), ρf is the blood density and v is the blood velocity at site 2.
Let us now define incremental elastic recoil pressure (in response to incremental LV pressure dPLV) as:
Hence, from equations (A-1, A-4, A-7 & A-8), we have
Introducing the term elastance (= 1/C), we can put down
Authors' contributions
Liang Zhong carried out the elastance studies, participated in data acquisition, performed statistical analysis and drafted the manuscript. Dhanjoo N. Ghista conceived of the study, and participated in its design and coordination and helped to draft the manuscript. Eddie Y-K Ng participated in coordination and helped to draft the manuscript. Soo T Lim participated in its design and coordination. All authors read and approved the final manuscript.
Acknowledgements
We are grateful to Dr. Terrance S.J. Chua and Technician Mr. Ng Eng Hian from National Heart Centre, Singapore, for his technical assistance in cineangiographic recordings. This study was supported by grants from Strategic Development Scheme, Nanyang Technological University, Singapore.
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| 15707494 | PMC549522 | CC BY | 2021-01-04 16:37:34 | no | Biomed Eng Online. 2005 Feb 11; 4:10 | utf-8 | Biomed Eng Online | 2,005 | 10.1186/1475-925X-4-10 | oa_comm |
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Virol JVirology Journal1743-422XBioMed Central London 1743-422X-2-61570520310.1186/1743-422X-2-6ResearchChromatography paper strip sampling of enteric adenoviruses type 40 and 41 positive stool specimens Zlateva Kalina T [email protected] Piet [email protected] Mustafizur [email protected] Ranst Marc [email protected] Laboratory of Clinical & Epidemiological Virology, Department of Microbiology and Immunology, Rega Institute for Medical Research, University of Leuven, Leuven, Belgium2 Laboratory of Virology, ICDDR, B: Center for Health and Population Research, Dhaka, Bangladesh2005 10 2 2005 2 6 6 15 12 2004 10 2 2005 Copyright © 2005 Zlateva et al; licensee BioMed Central Ltd.2005Zlateva 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 enteric subgroup F adenoviruses type 40 (Ad40) and 41 (Ad41) are the second most important cause of acute infantile gastroenteritis after rotaviruses. Repeated community outbreaks have been associated with antigenic changes among the Ad40 and Ad41 strains due to host immune pressure. Therefore large field epidemiological surveys and studies on the genetic variations in different isolates of Ad40 and Ad41 are important for disease control programs, the design of efficient diagnostic kits and vaccines against subgroup F adenoviruses. A novel method using sodium dodecyl sulphate SDS/EDTA-pretreated chromatography paper strips was evaluated for the collection, storage and shipping of Ad40/41 contaminated stool samples.
Results
This study shows that adenoviral DNA can be successfully detected in the filter strips by PCR after four months storage at -20°C, 4°C, room temperature (20–25°C) and 37°C. Furthermore no adenoviral infectivity was observed upon contact with the SDS/EDTA-pretreated strips.
Conclusions
Collecting, storing and transporting adenovirus type 40 and 41 positive stool samples on SDS/EDTA-pretreated chromatography filter strips is a convenient, biosafe and cost effective method for studying new genome variants and monitoring spread of enteric adenovirus strains during outbreaks.
enteric adenoviruses
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Background
Enteric adenoviruses (EAds) are considered to be the second most important causative agent of acute infantile gastroenteritis after rotaviruses. The fastidious subgroup F adenoviruses type 40 (Ad40) and 41 (Ad41) account for the majority of cases of severe acute diarrhea in children less than 2 years of age [1,2]. These viruses usually cause sporadic infantile gastroenteritis, but they have also been implicated in outbreaks and nosocomially acquired diarrhea [3-5]. The course of the disease is mild and self-limiting in most cases, but in immunocompromised patients these infections are associated with an increased morbidity and prolonged hospitalization [6,7]. Repeated community outbreaks and shift in the prevailing subgroup F adenovirus type have been associated with antigenic changes among the Ad40 and Ad41 strains due to host immune pressure [8-12]. Therefore, large field epidemiological surveys and studies on the genetic variations in different isolates of Ad40 and Ad41 are important for disease control programs, the design of efficient diagnostic kits and vaccines against subgroup F adenoviruses. For these purposes stool samples need to be collected, stored and transported to reference laboratories for genetic analysis. In many developing countries and remote areas, collection and storage of samples for laboratory diagnosis is difficult due to a restricted infrastructure. Moreover field conditions may limit the handling, transportation and refrigeration of the specimens.
Previous studies have demonstrated the application of different filter papers for the collection and storage of blood [13], saliva [14] and stool [15] samples for further analysis. Filter paper sampling has been successfully used for screening studies of rotaviruses [16], noroviruses [17], human herpesviruses 6 and 7 [14], human immunodeficiency virus [13,18], hepatitis C virus [19], measles virus [20] and others viruses.
This study describes the use of SDS/EDTA-pretreated filter paper strips in collection, transportation and storage of adenovirus type 40/41 positive stool samples for subsequent genetic analysis.
Results and Discussion
In the current study we describe the use of chromatography paper strips for the collection, transportation, and storage of EAds type 40/41 positive stool samples. In order to inactivate the adenoviruses and other microorganisms upon contact with the strips, the latter were pretreated with SDS, a surfactant with protein denaturising ability. This can allow safe transportation of the strips without extensive biohazard precautions. To protect the viral DNA from degradation by deoxyribonucleases (DNases) the chromatography strips were also preincubated with EDTA, and Tris-HCl. EDTA chelates magnesium ions, a necessary co-factor for most nucleases and the weak organic base Tris-HCl ensures the proper action of the chelating agent in binding the divalent cations.
A diarrheal stool sample containing 2.6 × 106 adenoviral particles per ml was serially diluted 1:8 (dilution a), 1:80 (dilution b), 1:800 (dilution c), 1:8000 (dilution d) and 1:80,000 (dilution e). The SDS/EDTA-pretreated filter paper strips were infected with each stool dilution and stored at -20°C, 4°C, room temperature (20 to 25°C), and 37°C. The presence of adenoviral DNA on the chromatography filter strips was detected by PCR amplification of a 301 bp fragment of the adenoviral hexone gene after storage for 7 days, 14 days, 56 days and 120 days (Figure 1).
Figure 1 Polyacrylamide gel electrophoresis of the PCR products amplified from the DNA of the subgroup F adenovirus positive stool sample, extracted from the SDS/EDTA pretreated chromatography paper strips that have been stored at four different temperature conditions. Five tenfold dilutions of the original stool sample were tested (a = 1:8, b = 1:80, c = 1:800, d = 1:8000, e = 1:80,000).
Our results show that adenoviral DNA can remain stable even at higher than room temperature conditions for at least 4 months, indicating that the collection and storage of the infected filter strips is possible where freezers are not available.
To be sure that the EAd40/41 contaminated filter strips are not infectious, we carried out a biosafety test to find out if any adenovirus could survive onto the SDS/EDTA-pretreated strips. Previously we showed that pathogenic bacteria such as Vibrio cholerae, enterotoxigenic E. coli, enteropathogenic E. coli, Salmonelle typhimurium and Shigella dysenteriae, were not able to survive on the SDS/EDTA strips [16]. The biosafety test performed in this study demonstrated that adenoviruses also lost infectivity upon contact with the SDS/EDTA strips (Figure 2). In HeLa cell line, no cytopathic effect was observed after incubation with the dialyzed eluate of the SDS/EDTA strips loaded with adenovirus type 1 (106 TCID 50/ml) after three passages of the infected cell line. The eluate of the untreated chromatography strips loaded with adenovirus type 1 caused cytopathic effect in the HeLa cell line. It can be concluded that the SDS/EDTA-pretreated strips can be used for the collection and shipping of adenovirus positive stool samples from remote areas to reference laboratories in a biosafe way.
Figure 2 (A) Normal HeLa confluent monolayer. (B) CPE in the HeLa cells at 3 days after infection with adenovirus type 1. (C) CPE in the HeLa cells at 3 days after infection with 500 μl eluate of the infected adenovirus type 1 untreated filter paper strips. (D) CPE in the HeLa cells after 3 days infected with the dialysed adenovirus type 1 positive cell cultured sample. (E) No CPE was observed when the HeLa cells were infected with 500 μl of the dialysed eluate from the adenovirus type 1 infected SDS/EDTA-pretreated paper strip.
Conclusions
We conclude that the use SDS/EDTA-pretreated filter strips for retrieval and subsequent analysis of adenoviral DNA from EAds type 40/41 positive stool specimens is a feasible method for sample collection. The described filter paper strips facilitate collection, transport and storage of adenoviral positive stools because they are biosafe, cost effective and require minimal storage space. This study shows that adenoviral DNA can remain stable for at least 4 months at 37°C temperature conditions making this method especially attractive for field research or population screening in tropical countries where freezers are not available.
Materials and Methods
Chromatography paper strips
Highly absorbent (870 g of water/m2) Whatman grade 17 chr pure cellulose chromatography paper with thickness of 0.92 mm and a flow rate of 190 mm/30 min (Whatman, Kent, United Kingdom) was used. Strips of 80 mm × 4 mm were cut from the chromatography paper and soaked for two minutes in a solution of 2% (w/v) sodium dodecyl sulphate (SDS), 10 mM EDTA and 60 mM TrisHCl. The chromatography paper strips were left to dry overnight at room temperature. Disposable gloves were used during the preparation of the filter paper strips.
Adenovirus sample loading on the chromatography paper strips
A diarrhea stool sample that was positive for adenovirus type 40/41 hexon antigen by the Premier Adenoclone®-Type 40/41 solid-phase sandwich enzyme immunoassay (Meridian Bioscience, Cincinnati, Ohio) was used for this study. The undiluted feces sample contained approximately 2.6 × 106 particles per ml of stool, as calculated from a standard curve supplied with the antigen enzyme immunoassay kit. The stool sample was diluted in 1 ml (dilution 1:8) DNase/RNase free water (Sigma) and the following dilutions were used: 1:8 (dilution a), 1:80 (dilution b), 1:800 (dilution c), and 1:8000 (dilution d), and 1:80000 (dilution e). The pretreated chromatography strips were infected with 100 μl of the different dilutions of stool sample and were left to air dry overnight at room temperature. After complete drying, the infected strips were stored under four different temperature conditions: -20°C, 4°C, room temperature (20 to 25°C) and 37°C.
PCR detection
Half of the strip (160 mm2) was used for the DNA extraction performed at the following storage time intervals: 7, 14, 56 and 120 days. The filter paper was inserted into an Eppendorf tube with 500 μl of Dnase/Rnase free water (Sigma) and thoroughly squeezed out. An aliquot of 200 μl of the squeezed eluate was used for DNA extraction using the QIAamp DNA Blood Mini Kit (Qiagen/Westburg, Leusden, The Netherlands) according to the manufacturer's instructions. A set of degenerate consensus primers (forward primer 5'-GCCSCARTGGKCWTACATGCACATC-3' and (reverse primer 5'-CAGCACSCCICGRATGTCAAA-3') were used to amplify a 301 bp fragment of the adenoviral hexone gene [21]. The PCR assay was performed with 10 μl of the extracted DNA in a 50 μl total volume, containing 0.5 μM of forward and reverse primer, 200 μM nucleotides, 2.5 mM MgCl2, and 1 unit Taq polymerase (Applied Biosystems, Foster City, CA). The PCR was conducted in a Geneamp PCR System 9600 thermal cycler (Applied Biosystems). The thermocycling conditions consisted of denaturation at 94°C for 3 min, followed by 35 cycles of 30 s at 94°C, 30 s at 55°C and 1 min at 72°C and 5 min of final elongation at 72°C. PCR products were visualized using polyacrylamide gel electrophoresis and ethidium bromide staining.
Biosafety test for adenovirus
A biosafety experiment was performed to check if adenoviral particles are still infectious after contact with the SDS/EDTS-pretreated chromatography paper strips. Since Ad40 and Ad41 grow poorly in cell culture it is difficult to detect these viruses in vivo. Therefore adenovirus type 1 was used for the biosafety experiments. The SDS/EDTA-pretreated filter stips were first infected with 100 μl of the HeLa cell cultured adenovirus type 1 (106 TCID 50/ml) and allowed to dry at room temperature for 60 min. The strips were then placed into an eppendorf tube containing 500 μl Dulbecco's Modified Eadle Medium (DMEM) (Invitrogen, Merelbeke, Belgium) supplemented with 200 mM L-glutamine (Sigma-Aldricht, Bornem, Belgium). The strips were thoroughly squeezed in the medium and the eluate was dialyzed using 3,500-Da Slide-A-Lyzer dialysis cassettes (Pierce Biotechnology, Rockford, IL, USA) to remove the cytotoxic SDS. The dialyzed eluate was inoculated on a confluent monolayer of HeLa cells and was incubated at 37°C in a humified incubator with a 5% CO2 environment. Untreated strips infected with adenovirus type 1 and noninfected SDS/EDTA-pretreated strips were used as positive and negative controls respectively. The presence of cytopathic effect indicated the presence of live replicating virus on the strip. Cytopathic effects were monitored up to the third passage of the tissue culture supernatant.
List of abbreviations
Eads – enteric adenoviruses
EDTA – ethylenediamine tetra-acetic acid
SDS – sodium dodecyl sulphate
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
KZ conducted the study, carried out the experiments and wrote the manuscript. PM carried out the biosafety experiments. MR developed the filter paper strip sampling method. MVR supervised the study and revised the manuscript. All authors read and approved the manuscript.
Acknowledgements
The work was funded by the Flemish Fund for Scientific Research (FWO-grand G.0288.01). Kalina Zlateva was supported in part by a grant from the Union Shipping and Trade Company Ltd., Sofia, Bulgaria and by a doctoral scholarship from the University of Leuven, Belgium.
The authors thank Annemie Debacker and Katleen Maris, from the Routine Diagnostic Virology Laboratory of the Gasthuisberg University Hospital in Leuven, Belgium for the adenovirus cell culturing experiments.
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Yolken RH Franklin CC Gastrointestinal adenovirus: an important cause of morbidity in patients with necrotizing enterocolitis and gastrointestinal surgery Pediatr Infect Dis 1985 4 42 47 2982133
Kidd AH Berkowitz FE Blaskovic PJ Schoub BD Genome variants of human adenovirus 40 (subgroup F) J Med Virol 1984 14 235 246 6094722
Kidd AH Genome variants of adenovirus 41 (subgroup G) from children with diarrhoea in South Africa J Med Virol 1984 14 49 59 6086831
Moore P Steele AD Lecatsas G Alexander JJ Characterisation of gastro-enteritis-associated adenoviruses in South Africa S Afr Med J 1998 88 1587 1592 9930257
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Shinozaki T Araki K Fujita Y Kobayashi M Tajima T Abe T Epidemiology of enteric adenoviruses 40 and 41 in acute gastroenteritis in infants and young children in the Tokyo area Scand J Infect Dis 1991 23 543 547 1662830
Beck IA Drennan KD Melvin AJ Mohan KM Herz AM Alarcon J Piscoya J Velazquez C Frenkel LM Simple, sensitive, and specific detection of human immunodeficiency virus type 1 subtype B DNA in dried blood samples for diagnosis in infants in the field J Clin Microbiol 2001 39 29 33 11136743 10.1128/JCM.39.1.29-33.2001
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Rahman M Goegebuer T De Leener K Maes P Matthijnssens J Podder G Azim T Van Ranst M Chromatography paper strip method for collection, transportation, and storage of rotavirus RNA in stool samples J Clin Microbiol 2004 42 1605 1608 15071012 10.1128/JCM.42.4.1605-1608.2004
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| 15705203 | PMC549523 | CC BY | 2021-01-04 16:38:59 | no | Virol J. 2005 Feb 10; 2:6 | utf-8 | Virol J | 2,005 | 10.1186/1743-422X-2-6 | oa_comm |
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Nutr Metab (Lond)Nutrition & Metabolism1743-7075BioMed Central London 1743-7075-2-41571004910.1186/1743-7075-2-4CommentaryAncel Keys: a tribute VanItallie Theodore B [email protected] Department of Medicine, St Luke's/Roosevelt Hospital Center, Columbia University College of Physicians and Surgeons, New York, NY, USA2005 14 2 2005 2 4 4 10 2 2005 14 2 2005 Copyright © 2005 VanItallie; licensee BioMed Central Ltd.2005VanItallie; 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.
Ancel Keys, Ph.D., who died in November, 2004, at the age of 100, was among the first scientists to recognize that human atherosclerosis is not an inevitable consequence of aging, and that a high-fat diet can be a major risk factor for coronary heart disease. During World War II, he and a group of talented co-workers at the University of Minnesota conducted a large-scale study of experimentally-induced human starvation. The data generated by this study – which was immediately recognized to be a classic – continue to be of inestimable value to nutrition scientists. In his later years, Keys spent more time at his home in Naples, Italy, where he had the opportunity to continue his personal study of the beneficial effects on health and longevity of a Mediterranean diet.
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Ancel Keys, who died in November, 2004, was an excellent testimonial to the health-promoting effects of his beloved Mediterranean diet. He lived to be 100 and, as the New York Times obituary put it, "remained intellectually active through his 97th year." His latter years were spent mostly at his home in Naples, ItaIy. I never had the privilege of knowing him well, but encountered him occasionally at scientific meetings where we were both speakers. He was friendly but, I thought, reserved. What struck me about Ancel was his remarkable absence from the counsels of the nutrition establishment. Despite his acknowledged expertise and importance in the field, he was not a member of AMA's Council on Foods & Nutrition (at least not during the many years I served on that organization). I never saw him at any of the NIH advisory committees on which I served. He did not play a role in the deliberations of the Food and Nutrition Board of the National Research Council. He was not involved in the American Society for Clinical Nutrition during its heyday. Why was this? Perhaps the fact that he was a physiologist (later an epidemiologist) and not a physician played some role. Also, I think he preferred to go his own way, and – to some extent – he remained aloof from "academic nutrition." Yet he was willing to lecture to many audiences and was not considered to be a scientific eccentric; to the contrary, his epidemiological work was frequently cited and praised, and his monumental study of experimentally-induced semistarvation in human subjects [1] was immediately recognized to be a classic.
Keys and his capable associates conducted careful physiological and psychological studies of 32 initially healthy conscientious objectors (to World War II) through 6 months of experimentally induced semistarvation, followed by a year or more of rehabilitation. These studies generated a cornucopia of data – data that are all the more valuable now because such an experiment would not have a chance of being approved by today's Institutional Review Boards. Protein-calorie malnutrition (PCM) – in effect, famine – remains endemic in many parts of the world; moreover, PCM is the most common nutritional problem encountered in U.S. hospitals and nursing homes. The studies carried out by Keys and his co-workers make it possible for us to distinguish the effects of semistarvation on the body's strength, composition, physiological status, and mood from the confounding effects of such underlying diseases as cancer, intestinal malabsorption, renal insufficiency, emphysema, etc. – illnesses that often give rise to conditioned PCM. The Minnesota group showed clearly that semistarvation can be independently responsible for an array of psychological problems such as anxiety, depression, and hypochondria. From their studies, it is possible to demonstrate a clear relationship between a decline in fat-free mass and PCM-associated morbidity.
Keys's major scientific achievements are enumerated in some detail by Jane E. Brody in her New York Times obituary, dated November 23, 2004. For those of us who worked for so many years to call attention to the relationship of serum total cholesterol to risk of coronary heart disease (CHD), and to the cholesterol-raising effects of certain saturated fats, Keys will always be one of the major prophets who provided the early evidence that atherosclerosis is not an inevitable concomitant of aging, and that a diet high in saturated fat content can be a major risk factor for CHD. The practical outcome of the work in this field – to which Ancel contributed so much – is the extraordinary decrease in mortality from coronary heart disease that has occurred during the past half-century. Cancer has finally replaced heart disease as America's number one killer. Ancel had his well-deserved reward – a long, productive life unencumbered by an excess of committee meetings, and the opportunity to contemplate the Tyrrhenian sea while enjoying the benefits of a Mediterranean diet.
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Keys A Brozek J Henschel A Mickelsen O Taylor HL The biology of human starvation 1950 Minneapolis: University of Minnesota Press
| 15710049 | PMC549524 | CC BY | 2021-01-04 16:37:46 | no | Nutr Metab (Lond). 2005 Feb 14; 2:4 | utf-8 | Nutr Metab (Lond) | 2,005 | 10.1186/1743-7075-2-4 | oa_comm |
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J Transl MedJournal of Translational Medicine1479-5876BioMed Central London 1479-5876-3-71569138910.1186/1479-5876-3-7ResearchIn vitro and in vivo evaluation of NCX 4040 cytotoxic activity in human colon cancer cell lines Tesei Anna [email protected] Paola [email protected] Francesco [email protected] Marco [email protected] Carlo [email protected] Marco [email protected] Gabriella [email protected] Dino [email protected] Manlio [email protected] Wainer [email protected] Division of Oncology and Diagnostics, Morgagni-Pierantoni Hospital, Forlì, Italy2 Istituto Oncologico Romagnolo, Forlì, Italy3 Preclinical Experimental Laboratory, Regina Elena Institute for Cancer Research, Rome, Italy4 NicOx SA, Sophia-Antipolis, France2005 3 2 2005 3 7 7 7 12 2004 3 2 2005 Copyright © 2005 Tesei et al; licensee BioMed Central Ltd.2005Tesei 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
Nitric oxide-releasing nonsteroidal antiinflammatory drugs (NO-NSAIDs) are reported to be safer than NSAIDs because of their lower gastric toxicity. We compared the effect of a novel NO-releasing derivate, NCX 4040, with that of aspirin and its denitrated analog, NCX 4042, in in vitro and in vivo human colon cancer models and investigated the mechanisms of action underlying its antitumor activity.
Methods
In vitro cytotoxicity was evaluated on a panel of colon cancer lines (LoVo, LoVo Dx, WiDr and LRWZ) by sulforhodamine B assay. Cell cycle perturbations and apoptosis were evaluated by flow cytometry. Protein expression was detected by Western blot. In the in vivo experiments, tumor-bearing mice were treated with NCX 4040, five times a week, for six consecutive weeks.
Results
In the in vitro studies, aspirin and NCX 4042 did not induce an effect on any of the cell lines, whereas NCX 4040 produced a marked cytostatic dose-related effect, indicating a pivotal role of the -NO2 group. Furthermore, in LoVo and LRWZ cell lines, we observed caspase-9 and -3-mediated apoptosis, whereas no apoptotic effect was observed after drug exposure in WiDr or LoVo Dx cell lines. In in vivo studies, both NCX 4040 and its parental compound were administered per os. NCX 4040 induced a 40% reduction in tumor weight. Conversely, aspirin did not influence tumor growth at all.
Conclusions
NCX 4040, but not its parental compound, aspirin, showed an in vitro and in vivo antiproliferative activity, indicating its potential usefulness to treat colon cancer.
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Background
One of the most important approaches for reducing cancer incidence is chemoprevention. This is especially relevant for colon cancer, which represents the third leading cause of cancer mortality in developing countries and for which diagnostic tests and clinical treatments are not satisfactory [1].
Recently published reviews [2-4] underline the growing role of nonsteroidal antiinflammatory drugs (NSAIDs) in preventing colon cancer. Epidemiologic studies [5] have found that long-term users of aspirin or other NSAIDs have a lower risk of colorectal adenomatous polyps and colorectal cancer compared to nonusers. Randomized clinical trials have confirmed that two NSAIDs, sulindac [6-9] and the selective cyclooxygenase (COX)-2 inhibitor, celecoxib [10], effectively inhibit the growth of adenomatous polyps and cause regression of existing polyps in patients with familial adenomatous polyposis (FAP), although a recent study showed very clear benefits only for the first six months of treatment with sulindac [11].
Despite a multiplicity of studies conducted on this compound family of drugs, little is known about the molecular targets that are responsible for their tumor-preventing properties and which are important, not only from a mechanistic point of view, but also because of their clinical implications in identifying individuals or subsets of patients who are sensitive to these drugs. Originally, it was believed that the regular use of these compounds acted exclusively through the inhibition of COX-1 and COX-2 activity involved in the production of prostaglandins [12]. There is now mounting evidence that the chemopreventive action of NSAIDs may involve COX-independent mechanisms [13,14]. Furthermore, despite initial enthusiasm about the potential relevance of NSAIDs, especially the selective COX-2 inhibitors, their use as chemopreventive or anticancer agents has been greatly limited by side-effects on gastrointestinal and renal systems.
In an attempt to reduce gastrointestinal toxicity, conventional NSAIDs have been coupled with a nitric oxide (NO)-releasing moiety [15,16]. The rationale for this approach is that NO compensates for the functions of prostaglandins, which are inhibited by conventional NSAIDs, in the gastrointestinal tract. Both prostaglandins and NO are capable of enhancing mucosal blood flow, mucus release and repair of mucosal injury in humans [17-19] and of reducing the severity of gastric injury in experimental models [16].
Interestingly, the activity of some NO-NSAIDs is considerably higher than that of the parental drugs. For example, NCX 4016 has been found to be much more effective than the parent aspirin in reducing aberrant crypt foci, a precancerous lesion, in a rat model of colorectal cancer [20] and in inducing cell perturbations and growth inhibition in a panel of colorectal cancer cell lines in vitro [21]. Similarly, Williams et al. [22,23], in another panel of human colon cancer lines, reported a higher antiproliferative activity of NO-NSAID compounds compared to the parent aspirin.
In the present work, we compared the effect of a novel NO-releasing derivate, NCX 4040, with that of aspirin and its denitrated analog in in vitro and in vivo human colon cancer models and investigated the mechanisms of action underlying its antitumor activity.
Materials and methods
In vitro studies
Cell lines
The studies were performed on colon adenocarcinoma cell lines: 2 (LoVo and WiDr) were obtained from the American Type Culture Collection (Rockville, MD), 1 (LRWZ) was isolated in our laboratory and derived from a patient with a confirmed diagnosis of colon adenocarcinoma, and 1 was doxorubicin-resistant (LoVo Dx) derived from the above-mentioned LoVo cells. Cell lines were maintained as a monolayer at 37°C and subcultured weekly. Culture medium was composed of DMEM/HAM F12 (1:1) supplemented with fetal calf serum (10%), glutamine (2 mM), non-essential aminoacids (1%) (Mascia Brunelli s.p.a., Milan, Italy), and insulin (10 μg/ml) (Sigma Aldrich, Milan, Italy). Cells were used in the exponential growth phase in all the experiments.
Drugs
Aspirin, NCX 4040 (NO-releasing aspirin), NCX 4042 (denitrated analog of NCX 4040) (Fig. 1), (all supplied by NicOx S.A., Sophia Antipolis, France), Z-LEHD-FMK (caspase-9 inhibitor) (BD Biosciences Pharmingen, Milan, Italy), sodium nitroprusside dihydrate and S-nitroso-N-acetylpenicillamine (NO donors) (Sigma Aldrich) were solubilized in dimethylsulfoxide (DMSO) (Sigma Aldrich) and freshly diluted in culture medium before each experiment. The final DMSO concentration never exceeded 1% and this condition was used as control in each experiment.
Figure 1 Chemical structure and molecular weight (m.w.) of traditional aspirin, its NO-derivative, NCX 4040, and the NCX 4040 denitrated analog, NCX 4042.
Chemosensitivity assay
Sulforhodamine B (SRB) assay was used according to the method by Skehan et al [24]. Briefly, cells were collected by trypsinization, counted and plated at a density of 10,000 cells/well in 96-well flat-bottomed microtiter plates (100 μl of cell suspension/well). In the chemosensitivity assay, NCX 4040, NCX 4042 and aspirin were tested at scalar concentrations ranging from 1 to 100 μM for 24 h and 48 h or for 24 h and 48 h followed by a 24-h culture in drug-free medium. Experiments were run in octuplet, and each experiment was repeated three times. The optical density of treated cells was determined at a wavelength of 540 nm by means of a fluorescence plate reader. Growth inhibition and cytocidal effect of drugs were calculated according to the formula reported by Monks et al. [25]: [(ODtreated - ODzero)/(ODcontrol - ODzero)] × 100%, when ODtreated is > to ODzero. If ODtreated is below ODzero, cell killing has occurred. The ODzero depicts the cell number at the moment of drug addition, the ODcontrol reflects the cell number in untreated wells and the ODtreated reflects the cell number in treated wells on the day of the assay.
Western blot
The cells were treated according to the previously described Western blot procedure. [26] COX-1 antibody (polyclonal C-20, dilution 1:100) was purchased from Santa Cruz-Biotechnology (Santa Cruz, CA), COX-2 (monoclonal C22420, dilution 1:250) from Transduction Laboratories (Lexington, KY), and caspases-3 and -9 (polyclonal antibodies, dilution 1:500) from Cell Signaling Technology, Inc. (Beverly, MA).
RT-PCR
Total RNA was isolated from cells by direct lysis and quantified spectrophotometrically. After quantification, RT reaction was performed with 1 μg of each sample using Gene Amp Gold RNA PCR Core Kit (Perkin Elmer Biosystems, Milan, Italy). The same cDNA was used for RT-PCR amplification of COX-1 and COX-2. PCR reactions were carried out in a final volume of 25 μl containing 2 μl of cDNA template, 1 unit of Klen Taq, 0.2 mM dNTP and 0.4-μM amounts of each forward and reverse primer, using a thermal cycler (PTC 200, Genenco, Florence, Italy). 5-μl aliquots of the amplified DNA fragments were separated on an ethidium bromide-stained 2% agarose gel.
Cell cycle distribution
After a 24-h exposure to 10 μM of NCX 4040, cells were harvested and stained in a solution containing RNase (10 Kunits/ml; Sigma Aldrich) and NP40 (0.01%; Sigma Aldrich). After 30–60 min, samples were analyzed by flow cytometry using a FACS Vantage flow cytometer. Data acquisition (10,000 events were collected for each sample) was performed using CELLQuest software. Data were elaborated using Modfit (DNA Modelling System) software and expressed as fractions of cells in the different cycle phases. Samples were run in triplicate, and each experiment was repeated three times.
Apoptosis
Apoptosis was evaluated by flow cytometric analysis according to the previously described TUNEL assay procedure [26]. Briefly, after a 24- and 48-h exposure to 5, 10 and 50 μM of NCX 4040, cells were trypsinized, fixed, exposed to TUNEL reaction mixture and counterstained with propidium iodide before FACS analysis.
In LoVo cells, positivity to TUNEL assay was also evaluated by fluorescence photomicroscope (Zeiss, Axioscope 40) according to the manufacturer's instructions (In situ cell death detection kit, fluorescein; Roche Diagnostic GmbH, Mannheim, Germany).
Finally, the cell-permeable DNA dye 4',6-DAPI and a fluorescence photomicroscope (Zeiss, Axioscope 40) were used to visualize chromatin condensation and/or fragmentation typical of apoptotic cells.
In vivo studies
Animals
Antitumor efficacy was evaluated on 6–8-week old CD-1 male nude (nu/nu) mice weighing 22–24 g (Charles River Laboratories, Calco, Italy). All procedures involving animals and their care were conducted in conformity with institutional guidelines, which are in compliance with national (D.L. No. 116, G.U., Suppl. 40, Feb. 18, 1992; Circolare No. 8, G.U., July 1994) and international laws (EEC Council Directive 86/609, OJ L 358. 1, Dec 12, 1987; Guide for the Care and Use of Laboratory Animals, United States National Research Council, 1996).
Drugs
NCX 4040 and aspirin were homogeneously suspended in 0.5% carboxymethyl cellulose (CMC) containing 10% of DMSO for antitumor efficacy studies. All the drugs were administered orally.
Antitumor efficacy
Since LRWZ line showed a low tumorigenicity when cells were injected into nude mice, in vivo experiments were performed on WiDr, LoVo and LoVo Dx lines. Tumor cells were resuspended (5 × 106 viable cells) in 0.2 ml of serum-free medium and injected into the hind leg muscles of mice.
Each experimental group included at least 6 mice. 10 mg/kg of aspirin and NCX 4040 were administered orally five days a week for 6 consecutive weeks starting on the 6th day after the tumor cell implant, when a tumor mass of about 300 mg was evident in all the animals. The dose of aspirin and NCX 4040 was chosen on the basis of previous observations obtained using the parental NCX 4016 compound [27]. Toxicity of treatments was evaluated in terms of body weight loss and drug deaths. The tumor weight was calculated from caliper measurements according to the method of Geran et al. as previously reported [28]. The antitumor efficacy of treatments was assessed by the following endpoints: a) percent tumor weight inhibition (TWI%), calculated as [1-(mean tumor weight of treated mice/mean tumor weight of controls)] × 100; b) tumor growth delay, evaluated as T – C, where T and C are the median times for treated and control tumors, respectively, to achieve equivalent size.
The significance of results was analyzed by the Mann-Whitney non parametric test. Differences were considered significant at P values < 0.05 (two-sided).
Results
In vitro studies
The effect of aspirin, NCX 4040, and its structural analog, NCX 4042, on cell growth was determined after different exposure schemes and using various concentrations. Aspirin and NCX 4042 did not exhibit an effect on any of the cell lines (Fig. 2). In contrast, NCX 4040 showed both cytostatic and cytocidal effects, as evaluated by Monk's model (Fig. 3). In particular, the highest cytostatic effect was observed after a 24-h drug exposure followed by a 24-h washout, with a 50% growth inhibition (GI50) ranging from 5.4 μM in LoVo cells to 24 μM in LoVo Dx. The same treatment scheme also induced the highest cytocidal effect, with a modulation for the different cell lines and a 50% lethal concentration (LC50) in LoVo cells (9.6 μM) about four- and threefold lower than that observed in WiDr and LRWZ, respectively. In LoVo Dx, no cytocidal effect was observed at any of the concentrations tested.
Figure 2 Antiproliferative and cytocidal activity of aspirin and NCX 4042 at concentrations of 1, 5, 10, 50 and 100 μM. Exposure time to drugs:□, 24 h; Ж, 24 h + 24-h washout; ○, 48 h; ▲, 48 h + 24-h washout. Each point indicates the mean of at least three experiments and SD never exceeded 5%.
Figure 3 Cytotoxic activity of NCX 4040 after 24-h exposure followed by 24-h washout. Ж, 24 h + 24 h-washout. The two drugs were used at concentrations of 1, 5, 10 and 50 μM. Each point indicates the mean of at least three experiments; SD never exceeded 5%.
Flow cytometric analysis of apoptosis performed after exposure to various concentrations of NCX 4040 showed 90% of apoptotic cells at 24 h starting from a 10-μM concentration in LoVo line, whereas apoptosis was not detected at the same time in any other cell line at any of the concentrations tested (Table 1). After a 48-h exposure, apoptosis was also induced in LRWZ cells, albeit to a lesser degree, at 10-μM (20%) and 50-μM (60%) concentrations.
Table 1 Apoptotic cells after a 24- or 48-h exposure to various concentrations of NCX 4040
Cell Line 24 h 48 h
5 μM 10 μM 50 μM 5 μM 10 μM 50 μM
LoVo Dx 0.7 ± 0.01 0.5 ± 0.01 0.5 ± 0.02 0.5 ± 0.0 0.02 ± 0.01 0.2 ± 0.0
WiDr 1.0 ± 0.01 4.0 ± 0.1 1.0 ± 0.05 2.0 ± 0.03 5.0 ± 0.02 5.0 ± 0.03
LRWZ 3.0 ± 0.03 5.0 ± 0.02 4.0 ± 0.1 4.0 ± 0.01 21.0 ± 0.3 60.0 ± 1.3
LoVo 2.0 ± 0.05 90.0 ± 2.3 n.e.* 3.0 ± 0.02 n.e. n.e.
* n.e.: not evaluated
In LoVo cells, which proved to be the biological system most sensitive to NO-aspirin, the induction of apoptosis produced by a 10-μM concentration was analyzed as a function of time. The results showed that the production of apoptotic cells is time-dependent, reaching as much as 80% after a 16-h drug exposure (Fig. 4A). Apoptotic elements were clearly visible using the in situ TUNEL analysis (Fig. 4B) and at fluorescent microscopic examination of cells stained with DAPI nuclear dye (Fig. 4C). Furthermore, cell death was strongly inhibited by simultaneous exposure of LoVo cells to a 10-μM concentration of NCX 4040 and a 100-μM concentration of caspase-9 inhibitor (Fig. 4D). Similar findings were obtained after exposure to caspase-3 inhibitor (data not shown).
Figure 4 (A) Percentage of apoptosis in LoVo cells after exposure times of 4, 8 12, 16, 20 and 24 h to 10 μM of NCX 4040. (B) Apoptosis in LoVo cells after a 24-h exposure as evidenced by in situ TUNEL assay. (C) Apoptosis in LoVo cells after a 24-h exposure as evidenced by DAPI staining. (D) Inhibition of NCX 4040-induced apoptosis in LoVo cells after a 24-h simultaneous exposure to the NO-NSAID and the caspase-9 inhibitor, as evidenced by TUNEL assay.
To understand the mechanisms responsible for the induction or lack of apoptosis in the different cell lines, we explored the modulation of COX-2 expression and the activation of caspases-3 and -9, which are involved in the mitochondrial pathway of apoptosis.
All the cell lines used were positive for the presence of the isoenzymatic form COX-1, as evaluated by mRNA and protein expression (Fig. 5A). Furthermore, after a 24-h exposure to NCX 4040, the COX-1 expression level remained unchanged in all the cell lines (Fig. 5B). COX-2 mRNA and protein expression were both observed in WiDr and LoVo Dx cell lines, whereas neither was detected in LRWZ, and only mRNA was observed in LoVo cells. Furthermore, in WiDr and LoVo Dx cells, no change was observed in the COX-2 protein expression level after a 24-h exposure to NCX 4040 or a 24-h exposure followed by a 24-h washout (Fig. 5C).
Figure 5 (A) COX-1 and COX-2 basal mRNA and protein expression in the different cell lines. Lane a, LoVo cells; lane b, WiDr cells; lane c, LRWZ cells; lane d, LoVo Dx. (B) COX-1 protein expression in the different cell lines. LoVo: lane 1, untreated cells; lane 2, cells exposed to 10 μM of NCX 4040 (24 h); LoVo Dx: lane 3, untreated cells; lane 4, cells exposed to 50 μM of NCX 4040 (24 h); WiDr: lane 5, untreated cells; lane 6, cells exposed to 50 μM of NCX 4040 (24 h); LRWZ: lane 7, untreated cells; lane 8, cells exposed to 50 μM of NCX 4040 (24 h). (C) COX-2 protein expression in WiDr and LoVo Dx cell lines after different exposure schemes to 10 μM of NCX 4040. Lane 1, untreated cells (24 h); lane 2, NCX 4040 (24 h); lane 3, untreated cells (24 h) + washout (24 h); lane 4, NCX 4040 (24 h) + washout (24 h).
Although all 4 lines basally expressed the 2 caspases (data not shown), these proteases were activated only in LoVo and in LRWZ cells, where apoptosis was found. In particular, in LoVo cells caspase-3 and -9 activation was already evident after 3 h, whereas in LWRZ, activation took a longer time to occur (at least 10 h for caspase-9 and 12 h for caspase-3). The temporal activation in these 2 cell lines corresponds to the early or late induction of apoptosis (Fig. 6A,6B).
Figure 6 (A) Activation of caspases-9 and -3 after exposure times of 1, 2, 3, 4, 5 and 6 h to 10 μM of NCX 4040 in LoVo cells. (B) Activation of caspases-9 and -3 after exposure times of 8, 10, 12 and 14 h to 50 μM of NCX 4040 in LRWZ cells. An antibody for actin was used as loading control.
In vivo studies
The administration of aspirin in mice bearing all 3 cell lines did not influence the growth of tumors (Fig. 7A,7B,7C). In contrast, treatment with NCX 4040 was effective in the different cell lines employed, with a reduction of about 40% in the tumor mass (P < 0.001), evaluated at the nadir of the effect, compared to untreated and aspirin-treated groups. A difference in NCX 4040 sensitivity was also evident between the lines. Tumor regrowth was observed after 8 and 11 days for LoVo Dx and WiDr lines, respectively. Conversely, inhibition of the tumor mass for LoVo tumors was maintained from day 15 to day 30 following the injection of tumor cells and a tumor growth delay of 19 days was observed (P < 0.001). These results are in agreement with the in vitro data, which demonstrated that LoVo line is the most sensitive to NCX 4040 exposure.
Figure 7 Antitumor efficacy in mice implanted with LoVo Dx (A), WiDr (B) and LoVo (C) cell lines. Each experimental group included 8 mice, each experiment was repeated at least three times, and representative independent experiments are reported. Experimental points represent means of 24 experiments (bars, SD). Arrows indicate the start of treatment.
Discussion
Our study evaluated the antitumor activity of the novel NO-aspirin NCX 4040 in vitro on a panel of human colon cancer lines with different genetic profiles representing clinical tumor heterogeneity, and in vivo on xenografted immunosuppressed mice.
Neither aspirin nor the denitrated analog, NCX 4042, influenced the growth of any of the cell lines studied, whereas NCX 4040 produced an important cytocidal effect. These findings suggest a pivotal role of the -NO2 group in the mechanism of action underlying its in vitro activity. Extensive evidence indicates that nitric oxide is capable of initiating apoptotic cell death in some cell types as a consequence of DNA-induced damage [29,30], but the pathways involved are still not fully understood. In the present study, it was seen that NCX 4040 induced apoptosis in two (LoVo and LRWZ) of the four cell lines investigated, albeit with a modulated activity. In particular, we observed early apoptosis in LoVo cells starting from a 6-h drug exposure, with a peak after 20 h, as shown by the TUNEL assay. We found that apoptotic death was induced by the concomitant activation of caspases-9 and -3 a few hours after NCX 4040 exposure.
In LRWZ cells, a relevant apoptosis was also observed but after a longer exposure time and at higher NCX 4040 concentrations, after which the irreversibly damaged cells underwent apoptotic death through the activation of caspases-9 and -3.
Moreover, two NO donors were used to better clarify the role of the aspirin component. These compounds, at concentrations similar to those utilized for NCX 4040, showed a very modest cytotoxic activity (data not shown), confirming the importance of the aspirin component for the antineoplastic effectiveness of the NCX 4040 molelcule.
In addition, WiDr and LoVo Dx cell lines, which proved to be resistant to NCX 4040-induced apoptosis, were characterized by baseline expression of COX-2 protein. This finding, which is consistent with data recently published for breast and colorectal cancer cells, would seem to support the hypothesis that a high level of COX-2 protein protects cells from apoptosis, especially that induced by NO-compounds [31,32].
With the exception of LRWZ, all the lines evaluated in in vitro studies showed a high tumorigenic capacity, making it possible to evaluate in vivo the antitumor efficacy of NCX 4040. The long-term administration of this drug was well tolerated by the mice and reduced the tumor mass of LoVo, LoVo Dx and WiDr lines compared to untreated mice. Analysis of growth curves highlighted differences in the degree of drug sensitivity between cell lines. NCX 4040 was very effective in delaying tumor growth in LoVo tumors, whereas WiDr, and especially LoVo Dx lines, regrew after the end of treatment. These results confirm the in vitro data and seem to indicate that, as observed in vitro, the ability of NCX 4040 to induce apoptosis has a key role in the antitumor efficacy of this drug.
Conclusions
In conclusion, NCX 4040 was effective in reducing the growth of several human colon cancer cell lines both in vitro and in vivo, whereas the parental compound aspirin showed no activity, which suggests that the NO-releasing derivate could prove useful in the clinical management of colon cancer, possibly in combination with conventional antineoplastic drugs.
Abbreviations
COX, cyclooxygenase; NO, nitric oxide; NO-NSAID, nitric oxide-releasing nonsteroidal antiinflammatory drug releasing; NSAID, nonsteroidal antiinflammatory drug; SRB, sulforhodamine B; TUNEL, terminal uridine nick end labeling.
Competing interests
Manlio Bolla is an employee of NicOx SA.
Authors' contributions
AT was responsible for study design, data analysis, and drafting the manuscript. WZ, DA and MB participated in the study design and acted as scientific advisors. AT, PU, FF and MR performed the in vitro experiments. CL, MS and GZ also participated in the study design and carried out the in vivo experiments. All authors read and approved the final manuscript.
Acknowledgements
The authors wish to thank Prof. Rosella Silvestrini for her invaluable scientific contribution and Gráinne Tierney for editing the manuscript. Supported by Istituto Oncologico Romagnolo, Forlì and by the Italian Ministry of Health 2003.
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| 15691389 | PMC549525 | CC BY | 2021-01-04 16:39:28 | no | J Transl Med. 2005 Feb 3; 3:7 | utf-8 | J Transl Med | 2,005 | 10.1186/1479-5876-3-7 | oa_comm |
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Malar JMalaria Journal1475-2875BioMed Central London 1475-2875-4-101570307610.1186/1475-2875-4-10ResearchEpidemiological, clinical and biological features of malaria among children in Niamey, Niger Gay-Andrieu Françoise [email protected] Eric [email protected] Véronique [email protected] Moussa [email protected] Maman Laminou [email protected] Hama [email protected] Hamadou 7boureï[email protected] Laboratory of Medical Biology, National Hospital of Niamey, Niamey, Niger2 Department of Internal Medicine, B3, National Hospital of Niamey, Niamey, Niger3 Clinique Gamkalley, Niamey, Niger4 Université Victor Segalen, Bordeaux 2, Bordeaux, France5 CERMES (Centre de Recherches Médicales et Sanitaires), Niamey, Niger6 Department of Paediatrics B, National Hospital of Niamey, Niamey, Niger7 Department of Paediatrics A, National Hospital of Niamey, Niamey, Niger2005 9 2 2005 4 10 10 8 12 2004 9 2 2005 Copyright © 2005 Gay-Andrieu et al; licensee BioMed Central Ltd.2005Gay-Andrieu 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
Malaria takes a heavy toll in Niger, one of the world's poorest countries. Previous evaluations conducted in the context of the strategy for the Integrated Management of Childhood Illness, showed that 84% of severe malaria cases and 64 % of ordinary cases are not correctly managed. The aim of this survey was to describe epidemiological, clinical and biological features of malaria among <5 year-old children in the paediatric department of the National Hospital of Niamey, Niger's main referral hospital.
Methods
The study was performed in 2003 during the rainy season from July 25th to October 25th. Microscopic diagnosis of malaria, complete blood cell counts and measurement of glycaemia were performed in compliance with the routine procedure of the laboratory. Epidemiological data was collected through interviews with mothers.
Results
256 children aged 3–60 months were included in the study. Anthropometrics and epidemiological data were typical of a very underprivileged population: 58% of the children were suffering from malnutrition and all were from poor families. Diagnosis of malaria was confirmed by microscopy in 52% of the cases. Clinical symptoms upon admission were non-specific, but there was a significant combination between a positive thick blood smear and neurological symptoms, and between a positive thick blood smear and splenomegaly. Thrombopaenia was also statistically more frequent among confirmed cases of malaria. The prevalence of severe malaria was 86%, including cases of severe anaemia among < 2 year-old children and neurological forms after 2 years of age. Overall mortality was 20% among confirmed cases and 21% among severe cases.
Conclusions
The study confirmed that malaria was a major burden for the National Hospital of Niamey. Children hospitalized for malaria had an underprivileged background. Two distinctive features were the prevalence of severe malaria and a high mortality rate. Medical and non-medical underlying factors which may explain such a situation are discussed.
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Background
Malaria accounts for 1 in 5 of all children deaths in Africa. Late presentation, misdiagnosis, inadequate management, unavailability or stock-outs of effective drugs are factors that influence high case-fatality rates even among hospital in-patients [1]. One of the targets of the Roll Back Malaria (RBM) initiative [2] is to establish systems to guarantee that adequate stocks of drugs and clinical consumables are available to health facilities, and that health facility staff are trained and supervised for the rapid identification, resuscitation and subsequent clinical care of children with severe malaria. But many African countries are still a long way from meeting this objective, and it is admitted now that malaria disproportionally affects the poorest populations [3].
Geographical and socio-economic situation
Niger is situated in the eastern part of West Africa in the Sahelo-Saharan zone. It is a landlocked country surrounded by Algeria, Libya, Chad, Nigeria, Benin, Burkina-Faso and Mali. The country's climate is a rainy season from June to October and a dry season during the rest of the year. The hottest months are April and May.
According to the Human Development Index (UNDP 2003), Niger ranks 174th of 175 countries with an annual GDP of about $160 per capita (2001). The demographic situation is characterized by a population of 11,544,000 inhabitants (2002) which is expected to double by 2025 with an annual growth rate of 3.5% (1999–2002). The infant and child mortality rate is 255‰ and 63% of the population live below the poverty line ($1 per day per person) [4-6].
The Bamako Initiative of 1987 was adopted by Niger but in a context of extreme poverty, the generalization of the cost recovery may have an impact on the access to health facilities, which should be assessed.
Malaria in Niger
Malaria is endemic in Niger with 97% of the population exposed to the risk of malaria [1], but some areas of the country are much more affected with the disease than others. Varying environmental conditions mean that the level of transmission will vary from one area to another: the northern part has an unstable situation while the South of the country (including Niamey, the capital), which is exposed to the annual monsoon rainfall following a long dry season [7,8] has an intermediate, stable situation. In the Sudan-Sahelian savanna, close to the River Niger, immunity and partial protection are acquired in children over 5 years of age [9]. Plasmodium falciparum is the predominant species partially associated with Plasmodium malariae and less frequently with Plasmodium ovale, according to geographical variations [7,8].
Among the anopheles of epidemiological importance, only Anopheles gambiae and Anopheles arabiensis may play a substantial role in malaria transmission but Anopheles funestus which was no longer found after 1970 seems to have reappeared in several sudano-sahelian zones of Niger [10,11].
Resistance to chloroquine was first described in 1991 [12] but few surveys have been conducted in the country so far [13,14]. Chloroquine remains as the first line treatment but such antimalarial treatment policy is now being challenged (2004).
Malaria remains a main cause of morbidity in Niger with an average of 850,000 cases per annum, corresponding to an annual incidence of 80‰ inhabitants, and 33.97% of reported deaths are due to malaria [4]. These estimates, however, lack accuracy as most of the reported cases are only "presumed cases" and many deaths do not occur at the hospital. It has also been estimated that only 50% of children under 5 with reported fever in the two previous weeks received chloroquine or any anti-malarial treatments, and less than 5% of households have insecticide-treated nets [1].
Rationale
In Niger, as in many sub-Saharan countries, malaria takes a heavy toll, especially among young children in poor households. An evaluation – conducted in 2003 by the University Research Corporation [15] in the context of the strategy for the Integrated Management of Childhood Illness (IMCI) adopted by Niger in 1996 – showed that 84% of severe cases and 64% of ordinary cases are not correctly managed in national, regional and district hospitals.
A high proportion of deaths in the National Hospital of Niamey (NHN) is related to malaria. The poor quality of medical care makes it difficult to assess the real burden of malaria in terms of mortality and morbidity. Misdiagnosis is likely to be quite common, either in excess or default. The objective of the present prospective study was to describe the epidemiological, biological and clinical features of cases of malaria in children in the paediatric department of the NHN in order to recommend more relevant decision-making and interventions.
Methods
Study area
The study was carried out in the NHN during the rainy season of 2003 from July 25th to October 25th, which is the peak transmission period. The NHN is the country's main referral hospital and has 852 beds. The paediatric department has two sections: section A (60 beds) for children from 0 to 24 months, and section B (60 beds) for children from 25 months to 15 years of age. A majority of patients come from the urban community of Niamey but some may be referred from all parts of the country.
Patients and methods
Children from 3 months to 5 years of age (60 months) admitted to Paediatric department A or B for presumed malaria were included in the study and treated following procedures normally used in the department: children went through the emergency department where a clinical examination was performed by doctors or by medical students in their final year, venous blood was drawn for biological tests (for the study, laboratory tests were free of charge), confirmed cases of malaria were treated intravenously with quinine twice a day for 2–3 days, followed by oral treatment (WHO protocol adapted for Niger by the National Malaria Control Program).
Upon admission, or within 24 hours, a physician conducted interviews with mothers in order to collect epidemiological data. Information such as age of the parents, number of siblings, the child's rank in relation to siblings, care-seeking previously to hospitalization, delay between the onset of disease and admission to the NHN, and treatment before hospitalization, was collected. The socio-economic background of households was evaluated through the Niamey neighbourhood where children originated from, the educational level of the mother (whether illiterate or not), the occupation of the mother and father, and the existence or non existence of a regular salary.
Biological tests were performed along the routine procedures of the NHN's laboratory. Thick and thin blood smears were prepared and stained following standard procedures: Giemsa 10% for 20 minutes (Giemsa R, RAL, CML, Nemours, France) for thick smear, and rapid staining (RAL 555, CML) for thin smear. A thick smear was declared negative only after examination of 200 fields (obj × 100). All smears were checked the following day by a different technician. Parasitaemia was measured on thin smear and expressed as a percentage of parasitised red blood cells. Haematological tests – haemoglobin concentration, hematocrit and complete blood cell count – were performed automatically using a KX21 (Sysmex). The blood glucose rate was performed with a COBAS Mira (Roche) using the glucose oxidase technique (Biomérieux, Marcy l'Etoile, France).
According to the 2000 WHO criteria [16], severe malaria is defined as the presence of P. falciparum on thick smear and at least one of the following clinical or biological criteria : coma (Blantyre coma scale ≤ 2), impaired consciousness (Blantyre >2 and < 5), repeated convulsions (≥ 2/24 hours), prostration, respiratory distress, jaundice, metabolic acidosis (bicarbonates < 15 mmol/L), severe anaemia (Hb < 5 g/dL or Ht < 15%), hyperparasitaemia (parasitaemia > 4% in non-immune patients), macroscopic haemoglobinuria, renal failure, collapse (TAS < 60 mmHg before 5 years of age), abnormal bleeding or pulmonary oedema (X-ray criterion). The conditions in the NHN in 2003 made it impossible to asses acidosis, renal failure (based on creatinine) and pulmonary oedema. Only the following criteria could be considered: coma, impaired consciousness, convulsions, respiratory distress, jaundice, abnormal bleeding, severe anaemia, hyperparasitaemia, hypoglycaemia.
Children were weighed. The index weight-for-age (weight/age ratio) was calculated and analysed with the Epi-Info software, based on the reference population defined by the US National Center for Health Statistics.(NCHS). Malnutrition was defined as a weight/age ratio more than 2 SD below the NCHS's reference population [17]. Malnutrition was considered moderate between -2 and -3 SD and severe below 3 SD.
Statistical methods
Version 6 of the program Epi-Info was used for statistical analysis. ANOVA and Kruskal Wallis tests were used for mean comparisons whenever appropriate. Proportions were compared using chi-square tests. Bivariate odds ratio and their 95% confidence intervals were calculated to measure the combination between fatal outcome and different variables. For all tests, a p-value below 0.05 was considered significant.
Ethical issues
The routine management of the children was not changed. Verbal consent was obtained from the parents after informing them in their native language. The parents were allowed to remove their child from the study at any time during follow-up. All data was entered anonymously into a database and identification numbers were coded. No ethnic data was registered. The protocol was submitted to and approved by the Ministry of Public Health and Endemic Diseases Control's National Malaria Control Program.
Results
Population
256 children were recorded over the 3 month survey: 138 males, 118 females (sex ratio = 1.17). The average age was 20.2 months: 3–12 months, n = 103 (40%), 13–24 months, n = 103 (40%) and 25–60 months, n = 50 (20%). The average age of parents was 27 years for the mothers, 39 years for the fathers. The number of living siblings averaged 2.8, and 35% of the children were first born. All children came from the urban community of Niamey, and 241/256 (94 %) from poor neighbourhoods: unsanitary neighbourhoods, near the river or near permanent ponds, some of them without electricity or tap water. The educational level of the mothers was low: 246/256 (96%) were illiterate, and 248/256 (97%) were home workers. Only 58/256 fathers (23%) had a monthly fixed income (24 civil servants and 34 salaried workers). The others had unsteady jobs with no stable income.
77 children out of 217 documented files for this item (35%) were considered malnourished and 42% dehydrated as a result of clinical examination. The percentage of malnutrition, however, was 58% based on the weight/age ratio, of which 30% were moderate and 28% severe cases of malnutrition. The youngest children (under 2 years old), particularly the 13–24 months age group, which corresponds to the weaning period, were most affected (Table 1).
Table 1 Nutritional condition of children upon admission.
3–12 13–24 24–60
number n = 103 % number n = 103 % number n = 50 %
Dehydration severe 8 (7.8) 3 (2.9) 0 (0.0)
mild 42 (40.8) 32 (31.1) 16 (32.0)
absence 46 (44.7) 60 (58.3) 32 (64.0)
ND 7 (6.8) 8 (7.8) 2 (4.0)
Clinical malnutritiona severe 4 (3.9) 8 (7.8) 0 (0.0)
mild 29 (28.1) 27 (26.2) 9 (18.0)
absence 53 (51.5) 50 (48.5) 37 (74.0)
ND 17 (16.5) 18 (17.5) 4 (8.0)
Weight / age ratiob severe 26 (25.2) 33 (32.0) 4 (8.0)
mild 30 (29.1) 32 (31.1) 6 (12.0)
absence 39 (37.9) 30 (29.1) 16 (32.0)
ND 8 (7.8) 8 (7.8) 24 (48.0)
a: clinically assessed malnutrition
b: malnutrition assessed through weight/age ratio
ND: not done
Clinical and biological diagnosis of malaria
Upon admission, mothers reported fever (91% of cases), digestive disorder (51%) and convulsions (19%). These symptoms were often combined (Figure 1). The most common combination was fever + digestive disorders (43% of the admissions). Convulsions are always reported in a context of fever. The average time (as reported by parents) between the onset of disease and admission at the NHN was 5.6 days (in the 176 documented files) ranging from 1 (arrival at the hospital the same day) to 35 days. 54% of the children were brought to hospital within 3 days after the early symptoms, and 16% after 7 days.175 children (86%) of the 203 documented cases had already received a treatment before they were admitted to the NHN (home treatment or previous care in another health structure). We could not get accurate information on the kind of treatment they received, whether antimalaria, antibiotic, antipyretic or any other treatment. Parents did not know and most of the time had no written prescription, although 53% had a health book. Only the route of administration was precisely established: oral (49%), intramuscular (41%), intravenous (7%) or intrarectal (3%).
Figure 1 Schematic representation of reasons for admission. Number of cases showing each symptom against the total number of children admitted.
132/256 children admitted for presumed malaria (52%) had a positive thick blood smear. The percentage of treated children was the same among children with a negative thick blood smear as among those with a positive one (87% versus 86%). Both groups had quite a similar corrected axillary temperature (38.6° with positive thick smear versus 38.4°).
The clinical presentation of children admitted to hospital with a respective prevalence of the various observed symptoms is summarised in Table 2. Neurological symptoms – coma (Blantyre ≤ 2), impaired consciousness (Blantyre 3–4) or convulsions – were significantly more frequent when the thick smear was positive. Other unspecific symptoms (digestive disorders, dyspnea, hepatomegaly) were also more frequent with a positive blood smear although the difference was not significant. Only 3 cases of respiratory distress were observed, all three among children with a positive blood smear. The presence of splenomegaly was more frequent in children with a positive blood smear (26% versus 13%, p = 0.017).
Table 2 Prevalence of clinical symptoms and biological markers upon admission
Positive blood smear Negative blood smear p value
number/total (%) number/total (%)
CLINICAL SYMPTOMS
comaa 22/77 (28,6) 7/64 (10,9) p = 0,022
impaired consciousnessb 15/77 (19,5) 11/64 (17,2)
convulsionsc 71/119 (59,7) 36/103 (35,0) < 0,001
digestive disorders 58/93 (62,4) 63/104 (60,6) NS
dyspnea 19/98 (19,4) 16/91 (17,6) NS
respiratory distress 3/96 (3,1) 0/96 (0,0) NS
hepatomegaly 36/107 (33,6) 28/95 (29,5) NS
splenomegaly 28/106 (26,4) 12/93 (12,9) 0,017
BIOLOGY
anaemiad 125/132 (94,7) 114/124 (91,9) NS
severe anaemiae 55/132 (41,7) 39/124 (31,5) NS
hypoglycaemiaf 30/132 (22,7) 21/124 (16,9) NS
thrombopaeniag 93/132 (70,5) 43/124 (34,7) <0,001
a: Blantyre score ≤ 2
b: Blantyre score = 3–4
c: ≥ 2 / 24 hours
d: haemoglobin < 11 g/dL
e: haemoglobin < 5 g/dL
f: glyceamia < 2.2 mmol/L
g: platelets < 150 000 / mm3
The haemoglobin rate in the overall population was 6.5 g/dL (6.17 with positive blood smear, 6.94 with negative blood smear, p = 0.038). 94 % of children had anaemia (haemoglobin < 11 g/dL). This massive proportion of anaemia was observed in both groups: 95% versus 92% (NS) for "simple anaemia" (haemoglobin < 11 g/dL), and 42% versus 31% (NS) for severe anaemia (haemoglobin < 5 g/dL) (Table 2). Similarly, hypoglycaemia was more frequent with a positive blood smear but the difference was not significant (23% versus 17%, NS) (Table 2). The average of platelets was 141,000 in children with a positive blood smear, and 292,000 for those with a negative blood smear (p < 0.001). Based on a definition of thrombopaenia as a number of platelets below 150000/mm3, we found that thrombopaenia was statistically combined with a positive blood smear (70% versus 35%, p < 0.001) (Table 2). A similar result (p < 0.001) was obtained with the cut off = 100 000/mm3.
Severe malaria attacks
114/132 children with a positive blood smear (86%) met the criteria of severe malaria according to the clinical and biological criteria explored in this study. The most frequent criteria were convulsions (71/114 = 62%) and severe anaemia (55/114 = 48%) (Table 3). Some children were affected with combined criteria: 24/114 (21%) showed impaired consciousness and convulsions, 28/114 (25%) showed a neurological form (coma, and /or impaired consciousness and/or convulsions) and severe anaemia. No collapse, jaundice or spontaneous bleeding were recorded. Total mortality in the studied population was 17%, with a higher -although not significant (20% versus 13%) – rate among individuals with a positive blood smear. Mortality among children with severe malaria was 21%. Table 3 shows specific case fatality rate according to observed criteria of severe malaria. Only hypoglycaemia and coma were related to a higher mortality. Clinical presentation of severe malaria was analysed in terms of age. Figure 2 shows that severe anaemia is more frequent among children of less than 24 months (56% versus 31 %) and, conversely, the neurological forms are more frequent after 24 months of age. The prevalence of hypoglycaemia and high parasitaemia were similar in the two age groups.
Table 3 Prevalence of severity criteria among severe malaria cases with respective case fatality rate and relative risk of dying
prevalence case fatality rate Odd Ratio p value
number n = 114 % number/total % 95 % IC
comaa 22 (19.3) 12/21 (57.1) 9.33 (2.85 – 31.58) < 0.001
impaired consciousnessb 15 (13.2) 1/14 (7.1) 0.26 (0.01 – 2.07) NS
convulsionsc 71 (62.3) 18/71 (25.3) 4.42 (0.88 – 29.83) 0.04
respiratory distress 3 (2.6) 3/3 0.002
severe anaemiad 55 (48.2) 11/50 (22.0) 1.10 (0.40 – 3.05) NS
hypoglycaemiae 30 (26.3) 11/28 (39.3) 3.72 (1.26 – 11.05) 0.006
high parasitaemiaf 39 (34.2) 7/37 (18.9) 0.82 (0.27 – 2.42) NS
a: Blantyre score ≤ 2
b: Blantyre score = 3–4
c: ≥ 2 / 24 hours
d: haemoglobin < 5 g/dL
e: glycaemia < 2.2 mmol/L
f: parasitaemia > 4%
Figure 2 Prevalence of severe malaria criteria by age group. Prevalence (%) of different WHO criteria among severe cases of malaria in children by age: 3–24 months (black) and 25–60 months (white)
Discussion
Description of the population
Hospitalized children in NHN were from underprivileged families: destitute neighbourhoods and disadvantaged socio-economic groups. This was confirmed by their poor nutritional conditions. 58% of the children had a weight/age ratio below 2 SD. This percentage is higher than national results previously published: the percentage of children with a weight/age ratio below 2 SD was 36% in 1992, and 50% in 1998 [18]. The delay before admission (5.6 days – ranging 1 to 35) is high but quite similar to other studies conducted in Africa: 6 days (ranging 1 – 30) in Dakar [19], 3.1 days (ranging 0–61) in Ouagadougou among urban patients [20]. One of the consequences of such a delay is that patients arrive at an advanced stage of disease. But in most cases, the NHN was not the first form of care sought. Interviews with the mothers highlighted the fact that traditional beliefs are still deeply rooted in families, and they interfere with the care-seeking pattern. For example malaria, "hemar ize" (= "the product of harvest season" in Zarma language) is still considered to be caused by "the smell of new plants during the rain season", despite the fact that there is some understanding of the part played by the mosquito as a result of health education. Convulsions are often linked to popular nosological entities, either "humburukumey" ("fear" in Zarma) whose origin is attributed to djins or witches, or "kyura" ("bird" in Zarma), i.e. "a bird having flown over the pregnant woman and dropped some graveyard soil onto her" (JP Olivier de Sardan, personal communication). This idea of a bird being responsible for children's convulsions is common to most of African societies and is beyond the medical context of malaria [21]. The occurrence of these convulsions, despite the parent's worry, does not necessarily encourage them to apply for a "modern" medical structure, but to refer more frequently to a "traditional" type of medicine or even to religious or superstitious practices. Thus, the neurological signs of malaria are identified and cured without mentioning malaria. The consequences can be serious, leading to delays in diagnosis and use of inefficient or even harmful traditional treatments. When finally reaching the hospital, because of the requirement for cost recovery, parents cannot afford all the medical examinations or treatments which should be undertaken.
Malaria at NHN
Diagnosis was confirmed by thick blood film in 52% of cases which shows that clinical diagnosis is not accurate and needs to be confirmed by microscopic examination. This range of 50% of confirmed malaria attacks has already been observed 20 years ago in quite a similar health situation [22]. The clinical presentation was unspecific, but a significant combination of positive blood smear with neurological symptoms, and with splenomegaly, was observed. From a biological point of view, only thrombopaenia was significantly found to be combined with a positive blood smear. This importance of splenomegaly [23,24] and thrombopaenia [25,26] in the diagnosis of malaria has already been described and discussed in previous studies.
With 94% of anaemic children, the "anaemia" symptom is not typical of malaria in this population. Most children must have had one or several previous attacks of malaria during the transmission season even if their test is negative on arrival at the hospital. It would be interesting to assess the impact of treatments carried out before hospitalization (frequent, but accurate reporting is problematic as mentioned above) on the biological diagnosis. Non-specific clinical diagnosis followed by a presumptive treatment carried out without any biological confirmation, with an almost total absence of written follow-up in the management of children, are elements showing how difficult it is to diagnose malaria attacks in endemic areas. Both theoretical and practical parameters interfering in the diagnosis of malaria have been reviewed by Rogier [27].
Severity of malaria at NHN
A particularly high percentage of severe malaria cases (86 %) was noted in the study population. Five children aged 6 months or under (one of them aged 3 months) were suffering from severe malaria, confirming the existence of severe malaria among very young children as already pointed out in other studies [28,29]. The new WHO criteria increase the percentage of severe cases [30]. This percentage may have been underestimated in this survey as some criteria could not be included for practical reasons. One of the problems was the difficulty of taking prostration into account: even if the WHO definition is clear (inability to sit upright for a child normally able to do so, or to drink in the case of children too young to sit) [16] this criterion could not be retained because of subjective interpretation. The absence of systematic chest X-ray and systematic creatinine measurements is unlikely to modify the results significantly as other surveys showed that pulmonary oedema and renal failure are infrequent criteria of severity among children [19,20]. The impossibility of performing blood gas analysis was more problematic since the importance of acidosis has been pointed out in several studies [16,31,32]. Consequently two major clinical presentations were observed: neurological form (coma, impaired consciousness or convulsions) and severe anaemia. Different breakdowns by age of these clinical presentations with a strong predominance of severe anaemia among 0–2 year-old children were reported. Several studies have already described links between clinical presentation, age of patients, and transmission level [19,20,33]. In Niamey, the severity of anaemia is probably enhanced by the very precarious nutritional condition of the infant population. Other severity criteria in the study population were hypoglycaemia and hyperparasitaemia. The small number of cases of respiratory distress (3/114 severe cases) is surprising compared to other studies [19,34], but the 3 children showing a respiratory distress in Niamey died. One may surmise that some health workers are not always sufficiently trained in assessing the severity of patients. The dramatic lack of therapeutic facilities in this hospital, and more specifically the insufficiencies of the intensive care service (5 intensive care beds for a 800-bed hospital, none of which is designated for paediatric resuscitation), does not encourage adequate concern in medical workers to make an accurate assessment based on severity criteria.
Mortality
The overall case fatality rate of malaria was 20% among confirmed cases and 21% among severe cases. These values are higher than those observed in other African countries also based on 2000 WHO criteria: 11.9% in Ethiopia [35], 12% in Senegal [30], and 14.58% in Madagascar [28]. The first line treatment in Niger remains chloroquine but in the hospital, according to WHO recommendations, children were treated intravenously with quinine twice a day for 2–3 days, followed by oral treatment (WHO protocol adapted for Niger by the National Malaria Control Program).
However, such a level of hospital mortality among children who have already received treatment before admission could indicate an increase in the level of chloroquine resistance. Data on resistance is still insufficient in Niger but studies are presently being carried out. Detection of the pfcrt (T76) mutation which confers chloroquine resistance [36] was performed on 30 isolates among the 114 severe cases. The pfcrt mutation was present in 10/30 samples (ML Ibrahim, personal communication). These preliminary results need to be completed but such a level of genotypic drug resistance clearly seems insufficient to explain the high mortality rate observed at the NHN. Other implied factors have to be identified.
One of them is anaemia. As the prevalence of severe anaemia is very high, the capacity of the blood bank to provide blood in a short time is an important factor in reducing mortality. Transfusion facilities are woefully inadequate in the NHN.
Conclusions
This survey conducted at the National Hospital of Niamey during the 2003 rainy season was an opportunity to examine the features of childhood malaria in a referral hospital of one of the world's lowest income countries. One of the dominant features in the NHN is that malaria affects an underprivileged population already affected by malnutrition. Only 52% of presumed cases are parasitologically confirmed. The rate of severe cases is high (86%) with two main clinical presentations: severe anaemia in less than 2-year old children and neurological form between 2 and 5-year old children. The mortality rate (21% among severe cases) is higher than established by most previously published data.
The study highlights several underlying factors that contribute to such an alarming situation:
(1) Patient factors: poor socio-economic background leading to multiple difficulties in getting access to healthcare (e.g. transport fees, hospital admission fees, biological tests, drug treatments...), and also the persistence of traditional beliefs interfering with care seeking behaviour.
(2) Provider factors: the recovery of medical care costs, although essential for the financial survival of the hospital, leads to multiple difficulties for the patient as seen above. Healthcare quality standards are also too low at all levels of the health organization, not just because of technical deficiencies (e.g. deficiency in intensive care units or in transfusion supplies) but also because of the inadequate training and attitudes of health-care workers.
All these factors need to be taken into account in order to find ways of improving the management of malaria in children. A recent awareness initiative is under way at the NHN, and several initiatives are being taken towards a gradual involvement of the hospital in a quality-oriented policy. But such local interventions will not reach their goal if extra efforts are not made at all levels to fight against disadvantages in the access to health facilities.
Authors' contributions
FGA was an initiator of the study and took part in its development, supervised laboratory staff, took part in the analysis of the data, and wrote this article. EA was an initiator of the study, took part in its development, coordinated the clinical study, took part in the analysis of the data and in the writing of the paper. VL and MG took part in the development of the study, collected clinical and epidemiological data, and analysed the data. MLI conducted molecular tests in the Institut Pasteur de Madagascar. HK and HB supervised medical and nursing staff in the paediatric department. All authors have read and approved the final manuscript.
Acknowledgements
We wish to thank Dr Ibrahim Sabou, the Director of the National Hospital of Niamey for his support. We are grateful to the medical and nursing staff of the two departments of paediatrics (Pédiatrie A and Pédiatrie B) and we also would like to thank the laboratory staff of the National Hospital of Niamey and particularly Me Ben Aminata Garba, Dr Alhousseini Daouda, Hassane Djibo and Djimrao Oumarou for their technical assistance. We finally wish to thank Dr Jean-Bernard Duchemin of the CERMES for helpful discussions and for his critical reading of the manuscript.
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| 15703076 | PMC549526 | CC BY | 2021-01-04 16:37:30 | no | Malar J. 2005 Feb 9; 4:10 | utf-8 | Malar J | 2,005 | 10.1186/1475-2875-4-10 | oa_comm |
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J Exp Clin Assist ReprodJournal of Experimental & Clinical Assisted Reproduction1743-1050BioMed Central London 1743-1050-2-31570307410.1186/1743-1050-2-3Short ReportCorrelation of sperm penetration assay score with polyspermy rate in in-vitro fertilization Aoki Vincent W [email protected] C Matthew [email protected] Kirtly [email protected] Harry H [email protected] Mark [email protected] Ivan [email protected] Douglas T [email protected] Andrology and IVF Laboratories, University of Utah School of Medicine, Salt Lake City, UT, 84108, USA2 Department of Surgery, University of Utah School of Medicine, Salt Lake City, UT, 84132, USA3 Department of Physiology, University of Utah School of Medicine, Salt Lake City, UT, 84132, USA4 Department of Obstetrics and Gynecology, University of Utah School of Medicine, Salt Lake City, UT, 84132, USA2005 9 2 2005 2 3 3 15 12 2004 9 2 2005 Copyright © 2005 Aoki et al; licensee BioMed Central Ltd.2005Aoki 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 sperm penetration assay (SPA) is used to predict the fertilizing capacity of sperm. Thus, some programs rely on SPA scores to formulate insemination plans in conjunction with in-vitro fertilization (IVF) cycles. The purpose of this study was to evaluate if a relationship exists between SPA scores and polyspermy rates during conventional IVF cycles.
Methods
A total of 1350 consecutive IVF patients using conventional IVF insemination were evaluated in the study. Oocytes were inseminated three hours post-retrieval by the addition of 150,000 to 300,000 progressively motile sperm. Approximately 18 hours after insemination, the oocytes were evaluated for fertilization by the visualization of pronuclei. The presence of three or more pronuclei was indicative of polyspermy. Polyspermy rates, fertilization success, embryo quality, and pregnancy rates were analyzed retrospectively to evaluate their relationship with SPA score, count, motility, number of progressively motile sperm inseminated, oocyte pre-insemination incubation time, patient age, and diagnosis.
Results
A significant positive relationship was observed between SPA score and polyspermy rate (rs = 0.10, p < 0.05). Patients with a normal SPA score had significantly higher polyspermy rates than those with abnormal SPA scores (6.3% ± 1.5% vs. 2.0% ± 0.7%, p < 0.05). Fertilization percentage was significantly lower in the group with severely abnormal SPA scores versus all other SPA groups (57.5% ± 2.1% vs. 70.2% ± 1.3%, p < 0.005). Although embryo quality was not affected, both clinical pregnancy and implantation rates improved slightly as SPA score increased. In addition, there was a decrease in the rate of spontaneous abortion as SPA score increased.
Conclusions
These data indicate SPA score is positively correlated with polyspermy rates and IVF fertilization percentage. Additionally, there is a slight increase in clinical pregnancy rates, and embryo implantation rates with increased SPA. Furthermore, there is a slight decrease in spontaneous abortions rates related to increased SPA.
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Findings
The sperm penetration assay (SPA) is used to evaluate the fertilizing capacity of human spermatozoa [1]. Some in-vitro fertilization (IVF) programs rely on the SPA to formulate their insemination plans in conjunction with IVF cycles [1,2]. Couples with normal SPA scores normally undergo conventional IVF insemination in contrast with intracytoplasmic sperm injection (ICSI), which is used for those with a diminished SPA.
Over the past decades success rates have steadily improved for human IVF embryo transfer programs. Recent advances in ovulation induction, micromanipulation, culturing conditions, and media formulations have fostered a technological revolution for IVF leading into the 21'st century (Pool, 2002). However, many common problems still remain.
One common problem associated with conventional IVF insemination is polyspermic fertilization when more than one sperm successfully penetrates and fertilizes the oocyte. These pre-embryos are considered abnormal and typically discarded. Thus, increased rates of polyspermy ultimately result in a reduced number of embryos.
Studies have been conducted that evaluate the factors associated with human IVF polyspermy [3-5]. However, most of the reports are based on data over a decade old. Recent improvements in IVF techniques may alter these relationships. Furthermore, no study has evaluated the relationship between sperm SPA score and incidence of polyspermy in human IVF.
The purpose of this study was to evaluate if a relationship exists between SPA scores and polyspermy rates during IVF cycles utilizing conventional insemination. We also evaluated the relationship between SPA score and fertilization rate, embryo quality, and pregnancy rate.
After Institutional Review Board approval, we conducted a retrospective study of 1350 consecutive IVF patients using conventional IVF insemination. Intracytoplasmic sperm injection (ICSI) patients were excluded from the study. The fertilizing capacity of each patient was assessed with the SPA. The SPA was performed on patients undergoing IVF using techniques previously described [6]. The SPA was performed on patients less than sixty days prior to the IVF cycle. The SPA score reflects the percentage of eggs successfully penetrated by the patient's sperm. SPA patients were stratified into 4 groups according to SPA score (Group 1: severely abnormal SPA (< 10% penetration), n = 182; Group 2: abnormal SPA (10–19% penetration), n = 368; Group 3: normal SPA (20 – 29% penetration), n = 404; Group 4: high-normal SPA (> 30% penetration), n = 396).
During the IVF cycle ovarian stimulation was performed using standard techniques of gonadotrophin-releasing hormone (GnRH) agonist down-regulation combined with controlled ovarian stimulation using a combination of recombinant follicle stimulating hormone (rFSH) and urinary-derived gonadotropin stimulation. Ovarian follicles were aspirated using a trans-vaginal ultrasound-guided needle.
Oocytes were inseminated three-hours post-retrieval by the addition of 150,000 to 300,000 progressively motile sperm. Approximately 18-hours post-insemination, the oocytes were evaluated for fertilization by visualization of pronuclei. The presence of three or more pronuclei was indicative of polyspermy in which case the fertilized oocyte was discarded. Embryos were cultured in HTF medium and transferred 72-hours post-retrieval. Embryo quality was assessed using a previously reported embryo scoring system that took into account the number of cells present and the level of cellular fragmentation [7].
Polyspermy rates, fertilization success, embryo quality, and pregnancy rates were analyzed retrospectively with respect to their relationship with SPA score. The correlation between SPA score and polyspermy was conducted using Spearman's correlation coefficient. Additionally, polyspermy rates, fertilization percentage, and embryo quality for the different SPA groups were analyzed for statistical difference using Kruskal-Wallis analysis. Lastly, pregnancy rates in the different groups were evaluated with a Chi-square analysis.
A significant positive relationship was observed between SPA score and polyspermy rates in 1350 IVF patients undergoing conventional IVF insemination (rs = 0.10, p < 0.05). Patients with normal SPA scores (Group 3) had significantly elevated polyspermy rates over those with severely abnormal SPA scores (6.3 ± 1.5 – 113/1,791 vs. 2.0 ± 0.7 – 20/1,020, p < 0.05, Table 1, please see file "Table1-Aoki et al.doc", Additional file 1). Conventional IVF fertilization rate was significantly lower in patients with severely abnormal SPA (57.5 ± 2.1 – 1,135/1,974) vs. all other patients (70.2 ± 1.3 – 8,519/12,135; p < 0.005, Table 1, please see file "Table1-Aoki et al.doc", Additional file 1).
Embryo quality showed no relationship to the SPA (Table 1, please see file "Table1-Aoki et al.doc" Additional file 1). Clinical pregnancy and implantation rates were increased in Group 4 (50.8% – 202/396 and 27.4% – 343/1255, respectively) versus Group 1 (31.6% – 58/182 and 15.7% – 96/612, respectively, p < 0.05) but no significant relationship between SPA and IVF outcome was observed throughout the entire study population (Table 1, please see file "Table1-Aoki et al.doc" Additional file 1). Similarly, there was a decrease in the rate of spontaneous abortion in Group 4 (14.7% – 30/202) versus Group 1 (31.3% – 18/58), although no significant relationship was observed within the entire population (Table 1, please see file "Table1-Aoki et al.doc" Additional file 1).
No relationships were observed between IVF polyspermy rates and maternal age, maternal diagnosis, amount of progressively motile sperm added, sperm morphology, ovarian stimulation protocol, or post-oocyte retrieval pre-insemination incubation time. Additionally, confounder analysis indicated the SPA groups were similar with respect to paternal age, maternal age and IVF diagnosis. Therefore, no standardization of the data with respect to these variables was required.
This is the first report to correlate SPA score with IVF polyspermy rates. Significantly elevated IVF polyspermy rates were observed in patients with normal SPA scores. Previous reports have established a relationship between IVF polyspermy and oocyte age/maturation, state of the zona pellucida, number of progressively motile sperm used for insemination, oviductal cytokine expression, and in-vitro culture conditions such as pH, temperature, and media supplementation [5].
Unlike other reports, we did not find a relationship between the number of progressively motile sperm used for insemination and IVF polyspermy rates. This discrepancy is most likely due to the narrow range of sperm number we used for insemination (150,000 to 300,000) compared with the studies of van der Ven et al. who used 500,000 to 1.5 *106 sperm [4]. Our results are consistent with Ho et al. who found no relationship between these variables [3]. However, the data still suggest minimizing the number of sperm added for IVF insemination in patients with increased SPA scores.
Poly-pronuclear formation in in-vitro fertilized eggs usually arises from polyspermic fertilization but may also be a product of second polar body retention [8]. Thus, one potential pitfall of associating poly-pronuclear fertilized oocytes with polyspermy is the uncertainty related to second polar body retention. However, a recent report showed only a small percentage of fertilized oocytes with three-pronuclei (2.5%) arise from second polar body retention. The findings of this study validate our study design of categorizing poly-pronuclear fertilized oocytes as polyspermic. Moreover, we would expect the contribution of second polar body retention to be consistent throughout the SPA groups negating any confounding effects.
Consistent with other reports, the SPA was correlated with fertilization percentage [1,6]. Furthermore, clinical pregnancy and implantation rates did show improvement in patients with a high-normal SPA versus those with a severely abnormal SPA. In addition, spontaneous abortion rates were significantly different between these two groups. This data strongly suggests ICSI may be an attractive alternative for patients with severely affected penetration ability.
Done correctly, the SPA provides a reliable assessment of the fertilizing ability of human spermatozoa with very low false negative rates (< 0.03%) and serves a valuable tool for clinicians to treat infertility patients with the appropriate modality [9]. The SPA is particularly useful in light of recent concerns about ICSI and imprinting diseases [10-12]. These concerns have led to the recommendation that IVF clinicians should be careful to employ the technique only when necessary and the SPA provides a prognostic tool to appropriately make that decision. Based on these findings, it may be valuable for individual IVF programs to re-evaluate the clinical utility of SPA testing. The SPA may prove valuable for clinicians to avoid increased amounts of polyspermy and unnecessary wasting of oocytes. Meanwhile, the SPA does not appear to be a reliable indicator of IVF embryo quality or pregnancy rates.
Authors' Contributions
VWA designed the study, carried out statistical evaluation, and was the primary author of the manuscript. CMP, KPJ, HHH, MG, and IH were involved in management of the IVF cases and collection of the clinical data. DTC was responsible for the implementation of the study, administrative requirements including IRB approval, statistical evaluation of the data, and preparation of the manuscript.
Supplementary Material
Additional File 1
Table 1. Relationship between SPA and IVF outcome measures
Click here for file
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| 15703074 | PMC549527 | CC BY | 2021-01-04 16:40:17 | no | J Exp Clin Assist Reprod. 2005 Feb 9; 2:3 | utf-8 | J Exp Clin Assist Reprod | 2,005 | 10.1186/1743-1050-2-3 | oa_comm |
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BMC Musculoskelet DisordBMC Musculoskeletal Disorders1471-2474BioMed Central London 1471-2474-6-41569137010.1186/1471-2474-6-4Research ArticlePatient characteristics and clinical management of patients with shoulder pain in U.S. primary care settings: Secondary data analysis of the National Ambulatory Medical Care Survey Wofford James L [email protected] Richard J [email protected] Raquel S [email protected] Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA2 Department of Internal Medicine, Dartmouth University, White River Junction, VT, USA2005 3 2 2005 6 4 4 11 7 2004 3 2 2005 Copyright © 2005 Wofford et al; licensee BioMed Central Ltd.2005Wofford 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 shoulder pain is a commonly encountered problem in primary care, there are few studies examining its presenting characteristics and clinical management in this setting.
Methods
We performed secondary data analysis of 692 office visits for shoulder pain collected through the National Ambulatory Medical Care Survey (Survey years 1993–2000). Information on demographic characteristics, history and place of injury, and clinical management (physician order of imaging, physiotherapy, and steroid intraarticular injection) were examined.
Results
Shoulder pain was associated with an injury in one third (33.2% (230/692)) of office visits in this population of US primary care physicians. Males, and younger adults (age ≤ 52) more often associated their shoulder pain with previous injury, but there were no racial differences in injury status. Injury-related shoulder pain was related to work in over one-fifth (21.3% (43/202)) of visits.
An x-ray was performed in 29.0% (164/566) of office visits, a finding that did not differ by gender, race, or by age status. Other imaging (CT scan, MRI, or ultrasound) was infrequently performed (6.5%, 37/566).
Physiotherapy was ordered in 23.9% (135/566) of visits for shoulder pain. Younger adults and patients with a history of injury more often had physiotherapy ordered, but there was no significant difference in the ordering of physiotherapy by gender or race. Examination of the use of intraarticular injection was not possible with this data set.
Conclusion
These data from the largest sample of patients with shoulder pain presenting to primary care settings offer insights into the presenting characteristics and clinical management of shoulder pain at the primary care level. The National Ambulatory Medical Care Survey is a useful resource for examining the clinical management of specific symptoms in U.S. primary care offices.
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Background
Shoulder pain is a common clinical problem in the ambulatory setting. The one year prevalence of shoulder pain is as high as 50% in the general population, and 50% of those afflicted consult a physician [1,2]. As many patients with shoulder pain miss work because of the condition, it should be no surprise that the costs associated with shoulder pain are high.
Examining the clinical management of shoulder pain in primary care settings, where the vast majority of patients present, is essential to improving the quality of care and to understanding the associated costs [3]. However, studies of the clinical management of shoulder pain usually come from small select populations in orthopedic clinics. To our knowledge, there have been only three published studies of shoulder pain conducted in primary care settings, and none of them were carried out in the United States.
The National Ambulatory Medical Care Survey offers a means of studying how common clinical conditions are managed by United States primary care physicians in a large, nationally representative sample. We sought to examine the presenting characteristics and clinical management of patients presenting to primary care physicians for evaluation of shoulder pain. In addition to offering insights on the clinical management of shoulder pain, this investigative strategy serves as a model for using this national data set to examine the quality of musculoskeletal care.
Methods
Data for this study comes from the National Ambulatory Medical Care Survey (NAMCS), 1993 to 2000. Conducted by the National Center for Health Statistics (Hyattsville, Maryland), the NAMCS survey uses a multistage probability sample design [4]. Using the master lists of all US physicians from the American Medical Association and American Osteopathic Association, a sample of patient care physicians is selected each year by random, stratified by geographic area and specialty. Among identified physicians, annual participation ranges from 74% in 1989 to 68% in 1998 (63% in 1999) [5,6]. For participating physicians, patient visits during a randomly selected week are sampled systematically.
For each selected patient visit, the physician completes a visit form that details patient, physician, and clinical information. Patient information includes demographics, insurance status, and up to three reasons for the visit. Physician information includes self-selected specialty, geographic location, and if the practice is in a metropolitan area. Information on clinical management includes which diagnostic and therapeutic maneuvers took place at the time of the visit or were ordered as a result of the visit.
Up to three reasons for the office visit were solicited by the survey. Using the NAMCS categorization scheme for reason for visit, we extracted all visits for which shoulder pain (number 14900–14950) was a reason for the visit [7]. We limited data to patients aged 18 or older, and to physicians who were self-reported practitioners of internal medicine, and family practice. We combined the data from the most recent years of the survey (1993–2000) to define a set of 3023 visits for shoulder pain for further analysis.
Each visit is assigned a weight derived from the probability of being sampled, to account for regional and specialty sampling bias as well as nonresponse. Sampling weights are often used to produce national estimates based on the available sample. Because the weighting scheme of NAMCS was not based on symptom, and the decision to analyze data based on a single specific condition such as shoulder pain precludes the use of weights to produce national estimates, we present our other results as unweighted analyses (Korn). All analyses were conducted using JMP-SAS (version 5.10a, SAS Institute Inc, Cary, NC) and Stata (version Intercooled Stata 8.0, College Station, TX).
This sample of patients with shoulder pain was characterized by age, race, and gender. We reported whether the shoulder pain was the result of an injury, whether the injury was work related, and how the injury states differed by demographic characteristics. Younger versus older adults were designated by using the median age of 52 years of age to separate age groups. ICD-9 diagnosis codes were reported for each patient (International Classification of Diseases, Ninth Revision, Clinical Modification (ICD9-CM)).
Clinical management of the shoulder pain was examined by analyzing the proportion of patients for which plain x-rays and more advanced imaging (CT scan, MRI, or ultrasound) and the proportion of patients for whom physiotherapy was ordered. Demographic differences for imaging and physiotherapy orders were examined.
We attempted to characterize the treatment of shoulder pain by examining (1) whether physiotherapy was ordered by the physician and (2) whether the physician administered an intraarticular steroid injection. For the physiotherapy issue, specific question was part of the survey during survey years 1995–2000. However, determining whether a corticosteroid was administered was not possible. The survey solicits whether an office surgical procedure was performed during the office visit, but the performance of a minor procedure such as arthrocentesis is not usually considered a surgical procedure. The coding of up to six medications administered or prescribed during the office visit in the NAMCAS survey should allow identification of corticosteroid medications used in a intraarticular injection. However, the route of administration (intramuscular, intraarticular, topical, etc.) is not specified by the survey, and the availability of a given corticosteroid in various preparations makes for uncertainty in assigning as truly including determining whether an intraarticular injection took place during an office visit.
Results
Figure 1 shows how the cohort of office visits for shoulder pain was assembled. For adult patients (aged 18 or older), shoulder pain was given as a reason for the visit in 3023 office visits during the years 1993 through 2000 of the survey. Of these office visits for shoulder pain, 692 (22.8%, 692/3023) were to general internists (n = 327) or family practitioners (n = 365). The mean number of patient visits contributed by any one physician was 1.55 (maximum, 8; minimum, 1; median, 1) and 1.39 (maximum, 4; minimum, 1; median, 1), respectively. The ICD codes most commonly listed for shoulder pain included 72610 rotator cuff syndrome of the shoulder (9.6%, n = 24), 71941 shoulder pain (8.5%, n = 21), 176210 (6.0%, n = 15), 71590 osteoarthritis (5.6%, n = 14), 72690 tendinitis of an unspecified site (4.8%, n = 12), but 99 different codes 176210 (6.0%, n = 15), were used by this group of physicians.
Figure 1 Cohort Assembly of Primary Care Office Visits for Shoulder Pain in the U.S. from National Ambulatory Medical Care Surveys (1993–2000). A cohort of patients ≥ 18 years of age with shoulder pain were assembled from office visits to self-reporting internal medicine and family practice physicians.
Presenting characteristics of patients with shoulder pain
The mean age of the patients seen at these visits was 53.3 ± 17.8 years, and 54.3% (376/692) of the visits were for female patients. White patients outnumbered blacks (84.6% (586/692) versus 12.1% (84/692) in this data set. The proportion of patients whose shoulder pain was a result of an injury was 33.2% (230/692). Males, and younger adults were more likely to have had an injury associated with the shoulder pain (males 36.7% versus females 30.3%, p = 0.01; age >52 19.3% versus age <52 46.9%, p < .0001), but there were no race differences in injury association (whites 33.8% versus blacks 28.6%, p = .50). For the survey years 1995–2000 when the specific question was asked, the proportion of office visits for shoulder pain from injury that were related to work was 7.6% (43/566) of all visits to these primary care physicians and 21.3% (43/202) of those associated with injury.
Diagnostic imaging
During the survey years 1995–2000 when the specific question was posed regarding the performance or ordering of an x-ray, 164/566 (29.0%) of the visits results in an x-ray order, a finding that did not differ by gender (29.0% for males versus 29.0% for females, p = 0.46), by race (29.8% for whites versus 24.3% for blacks, p = 0.65), or by age status (older adults 27.8% versus younger adults 30.0%, p = 0.43). Whether an x-ray was performed was not associated with a history of injury 27.2% versus 30.0%). Advanced imaging (CT scan, MRI, or ultrasound) was performed in 6.5% (37/566) of visits.
Therapeutic interventions for shoulder pain
Physiotherapy was ordered in the case of 23.9% (135/566) of visits. There was no significant difference in the ordering of physiotherapy by patient gender (female 27.0% versus male 20.1%, p = .052) or by patient race (white 25.1% versus African-American 17.1%, p = .070), but younger adults were more likely to have physiotherapy ordered (younger adults 18.7% versus older adults 28.7%, p = .005). Patients with a history of associated injury were more likely to receive an order for physiotherapy (injury 36.1% versus no injury 17.0%, p = <.001). As discussed above, it was not possible to determine whether intraarticular steroids were administered.
Discussion
The labeling of the years 2000–2010 as the "Bone and Joint Decade" is, in part, a worldwide plea for better understanding and management of common musculoskeletal conditions [8]. Although musculoskeletal complaints are among the most common reasons for physician consultation, clinical management of these conditions is not well understood. There are few published studies of the management of shoulder pain in the primary care setting where it most commonly presents.
To our knowledge, the only published studies of shoulder pain in the primary care setting come from the Netherlands and the United Kingdom. Van Der Windt et al examined the characteristics and management of intrinsic shoulder disorders for 349 patients from eleven Dutch general practices during a one year period (1995) [9]. Croft et al reported a prospective cohort study of 166 patients consulting twelve British general practitioners for shoulder pain during the year [10]. More recently, Hay et al conducted a randomized controlled trial of corticosteroid injection versus physiotherapy in 207 patients from nine general practices Britain [11]. Clinical management of musculoskeletal disorders in the Untied States should be different, given the differences in health care delivery and reimbursement. However, we are unaware of any studies of shoulder pain in the United States primary care practices. Our findings represent the largest study to date to examine the characteristics and clinical management of shoulder pain at the primary care level in the United States. Although our data come from a cross sectional survey and the findings are primarily descriptive, these findings provide insights into how U.S. primary care practitioners experience and manage patients with shoulder pain.
The demographic characteristics of patients of these primary care settings were similar to those of other studies of shoulder pain in primary care settings [9,11] with a female predominance (54.3% of all patients presenting with shoulder pain), and a wide age range of patients (53.3 years ± 17.8). However, studies of primary clinic populations differ from studies of shoulder pain in the general population where shoulder pain increases in prevalence with age, even to geriatric populations [12]. Our findings support the idea that older patients with shoulder pain do not seek or are not brought to medical attention as frequently as younger adults [9]. Racial characteristics of patients with shoulder pain have not been previously reported, but overall the demographic characteristics, reflect those of all patients presenting to U.S clinic settings with no salient differences.
The proportion of patients whose shoulder pain was a result of an injury was 33.2% (230/692) in this study, higher than in the van der Windt study where 12% of patients gave a history of injury and 13% of strain/overuse with unusual activities [9]. For survey years 1995–2000 when the specific question was posed, the percent of shoulder pain related to work was 7.6% (43/566) of all visits for shoulder pain and 21.3% (43/202) of those associated with injury. While there are no comparable data from primary care settings regarding the circumstances of injury, studies from occupational settings show that many factors influence the occurrence of shoulder pain in work settings [13].
Imaging was performed in 29.0% of patients in this study of U.S office visits, a marked contrast to the British study of primary care management where only 2% of the patients presenting with shoulder pain underwent x-ray studies [9]. The value of radiographic plain films may be of limited value, but plain x-rays are still recommended as an early diagnostic step in primary care settings [14]. Because nearly half of all patients who present with shoulder pain have a prior history of that condition [9], and our study did not distinguish between incident and chronic shoulder pain, the high proportion of patients receiving x-rays in our study suggests overuse of this procedure. However, other imaging procedures such as Magnetic resonance imaging, computerized tomography, or ultrasound were infrequently ordered. Comparable studies from other primary care settings are not available, to our knowledge [15].
A specific question about the clinician's actions allowed us to determine that physiotherapy was ordered a rate of 24%, comparable to the rate of 30% reported for British general practitioners [9]. Interest in the comparative value of physiotherapy versus steroid injection led us to attempt the same comparison in this data set [11]. However, there was no reliable mechanism for determining whether the ordering or performance of corticosteroid injection took place during the office encounter.
Several limitations of using this data set for investigation of shoulder pain deserve mention. A precise diagnosis for the shoulder pain would be desirable. The large number of ICD-9 diagnosis codes assigned by the clinician illustrates well the problems in defining and managing this syndrome. However, this problem of imprecise diagnosis of shoulder pain is well known and is not unique to this data set [9]. Second, as this is a cross sectional study with secondary data analysis, the amount of data available in the data set does not allow for absolute certainty in following the clinical reasoning process. As an example, while we can be certain that an imaging procedure or physiotherapy was ordered for a given office visit, albeit self-report by the clinician, we cannot be certain that the imaging procedure or physiotherapy was specific to the shoulder. Third, hypothesis testing and statistical inference is difficult with data derived from a multilevel sampling strategy [16].
In addition to seeking insights into the clinical management of shoulder pain, we were interested in exploring whether this data set based on a symptom complex was possible and meaningful. The NAMCS, a series of annual surveys conducted since 1990 in the United States, has been utilized to study health service utilization, patients with known diagnoses, and prescribing behaviour of office-based physicians. To our knowledge, there are no published studies focusing on specific symptoms. The advantages of using this data set for analyzing clinical management of symptoms includes a well organized and standardized classification system of symptoms, a large number of office visits, and the systematic sampling strategy. While our attempt to explore meaningful clinical issues was hampered by the nature of the data set, we nevertheless succeeded in offering insights into the presenting characteristics and clinical management of shoulder pain for this population of patients.
Conclusions
Shoulder pain was associated with an injury in one third of office visits in this population of US primary care physicians. Males, and younger adults were more likely to relate their shoulder pain to injury, but there were no racial differences in injury status. Shoulder pain from injury was related to work in over one-fifth of office visits. An x-ray was performed in nearly one third of office visits, a finding that did not differ by gender, race, or by age status. Other imaging (CT scan, MRI, or ultrasound) was infrequently performed. Physical therapy was ordered in one quarter of visits for shoulder pain. Younger adults and patients with a history of injury were more likely to have physiotherapy ordered but there was no significant difference in the ordering of physiotherapy by gender or race. Examination of the use of intrarticular injection was not possible with this data set. The National Ambulatory Medical Care Survey is a useful resource for examining the clinical management of specific symptoms in U.S. primary care offices.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
JW conceived of the study, and participated in its design and
coordination, and drafted the manuscript.
RM and RW participated in formulating the analysis strategy.
All authors read and approved the final manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
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Environ HealthEnvironmental Health1476-069XBioMed Central London 1476-069X-4-21570117010.1186/1476-069X-4-2CommentaryPerils of paradigm: Complexity, policy design, and the Endocrine Disruptor Screening Program Vogel Jason M [email protected] Environmental Studies Program, University of Colorado, Campus Box 397, Boulder, CO 80309-0397, USA2005 8 2 2005 4 2 2 15 11 2004 8 2 2005 Copyright © 2005 Vogel; licensee BioMed Central Ltd.2005Vogel; 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 Endocrine Disruptor Screening Program (EDSP), mandated by the United States Congress in the Food Quality Protection Act of 1996, attempts to protect public health from adverse endocrine effects of synthetic chemical compounds by establishing a new testing regime. But the complexities and uncertainties of endocrine disruption and its broader regulatory and social context all but ensure the failure of this policy. This article addresses the issues facing EDSP comprehensively and in detail, in order to move beyond the current regulatory paradigm and foster discourse on a positive role for scientists in support of EDSP's end goal: to protect public health.
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Introduction
The United States Environmental Protection Agency (EPA) created the Endocrine Disruptor Screening Program (EDSP) to regulate endocrine-disrupting chemicals (EDCs) as mandated in the Food Quality Protection Act of 1996 (FQPA) and the Safe Drinking Water Amendments Act of 1996 (SDWAA). Unlike the more easily appreciated effects of toxic chemicals, EDCs interact with the human body indirectly by mimicking, blocking, or otherwise disrupting the normal function of hormones. The prolific study of endocrine disruption has since uncovered many unconventional and worrisome mechanisms, exposures, and effects [1]. The goal of EDSP is to:
[D]evelop a screening program, using appropriate validated test systems and other scientifically relevant information, to determine whether certain substances may have an effect in humans that is similar to an effect produced by a naturally occurring estrogen, or such other endocrine effects as the [EPA] Administrator may designate [2].
If such an effect is discovered, "the [EPA] Administrator shall, as appropriate, take action under such statutory authority as is available...as is necessary to ensure the protection of public health" [2].
Unfortunately, due to four complicating factors, EDSP cannot protect public health. The first complication is practical considerations. EPA estimates the universe of potential EDCs numbers more than 87,000 items. Testing this many chemicals would take an unreasonable investment of time and resources, but even scientifically prioritizing among them is highly problematic. The second complication is hazard complexity. Establishing relationships between EDCs and health hazards proves very difficult if not impossible. Endocrine-disrupting action breaks all the rules and assumptions that have guided toxicology through the era of modern chemical regulation. Without these simplifying assumptions, science cannot establish causation efficiently or with sufficient certainty for regulation. The third complication is exposure complexity. Determining exposure levels becomes more important and more difficult because the low-dose effects of many EDCs means that low-dose and transient exposure can be just as or more dangerous than high-dose and prolonged exposure. Assessments typically discount these ill-defined exposures, but we can no longer assume them insignificant. The final complication is regulatory deficiencies. Although FQPA and SDWAA provided new authority to test for endocrine disruption, they provided no new authority for the regulation of EDCs. As a result, multiple government agencies must manage future test-positive EDCs under their jurisdiction using fragmentary and incomplete statutory authorities and different regulatory standards. This introduces significant confusion to the institutional and decision-making aspects of the EDSP regulatory framework.
The EDSP policy design represents revision at the margins of U.S. chemical regulatory policy, not a radical revision. EDSP employs the same basic strategy used to regulate carcinogenic pesticides or toxic industrial chemicals – scientifically proving harm prior to regulating a chemical. Two important aspects of this strategy include an epistemological assumption that science has the capacity to 'prove' harm under the relevant scientific and legal standards, and an ethical position that prioritizes profit over human health by placing the burden of proof on public and environmental health advocates. These assumptions remain all but unchallenged in the U.S. context, and thus comprise a paradigm. While this paradigm has faced some critique in the context of carcinogenic pesticides and toxic industrial chemicals, questions of its efficacy remain unresolved. Because EDCs present new and fundamental difficulties for the science underlying the regulatory paradigm, a critical analysis of EDSP provides a more compelling case that the current chemical regulatory paradigm is in need of radical revision.
This study investigates the policy design of EDSP and its broader context. The above four complications play varying roles in each stage of the EDSP policy design as discussed below. See figure 1 for a diagram roughly depicting the relationship between the four complications and the policy stages of EDSP. After considering the complications of each policy stage, this study briefly discusses the role of politics in regulation before considering the implications for the conventional chemical regulatory paradigm and a positive role for scientists in support of EDSP's end goal to protect public health.
Figure 1 EDSP complications and policy stages relationship
The following discussion provides a comprehensive empirical basis for considering alternatives to the status quo. This study aims to integrate the many factors conditioning the failure of EDSP for the purpose of fostering constructive discussion on U.S. regulatory policy concerning EDCs and chemicals more generally. The author does not possess a unique answer to the many and complicated issues surrounding endocrine disruption and the U.S. chemical regulatory paradigm. Given that no simple, well-developed alternatives exist that merit immediate consideration by decision-makers, it stands to reason that more creative and open discussions of EDCs, the chemical regulatory paradigm, and possible roles for the scientific community may provide long-term payoffs in public and environmental health protection well worth our attentions today.
Discussion
The design of EDSP consists of three main stages: priority setting, screening and testing, and a risk analysis leading to potential regulation. The complications shown in figure 1 and detailed throughout this study undermine each of these stages. Before dealing explicitly with these policy stages, however, some practical considerations deserve note. EPA estimates 87,000 chemicals require testing as potential EDCs, including pesticide chemicals, non-pesticide commercial chemicals, cosmetic ingredients, food additives, nutritional supplements, mixtures, and environmental contaminants [3,4]. This sets a daunting task; no U.S. chemical regulatory program has ever successfully tested so many chemicals. A quote from U.S. Congressman Mike Synar (D-OK), during a committee hearing on the safety of pesticides in foods states the problem dramatically: "Almost 20,000 pesticide products have been under review since 1972 and only 31 have been re-registered. At this rate it will take us to the year 15,520 A.D. to complete. I believe in good science. What I don't believe in is geologic time" [5]. Other researchers and watchdogs note the failure of other U.S. chemical regulatory programs to effectively gather information or protect public health (e.g. TSCA [6,7], and FQPA [8]; for a broader critique [9,10]). By applying Congressman Synar's analysis to endocrine-disrupting chemicals, we can expect characterization of all potential EDCs to take 59,000 years. EPA stated: "Testing of all of these chemicals cannot be supported at the same time because, even if EPA and industry had the resources to do so, there are not enough laboratories or other facilities capable of conducting the testing" [11].
In other words, there is reason and precedent to doubt our ability to accomplish this feat. More importantly, despite our best efforts to mobilize science in support of this difficult task, policy mechanisms allow chemical use and abuse to go forward regardless of scientific results or lack thereof. "Pesticides are registered for use while important health and safety data are still being generated; they may continue to be used after evidence of their hazards is given to EPA; they may be registered through alternative processes that bypass important tests; and they may never be required to be tested for certain kinds of hazards" ([9], also see [12]). Additionally, politics often plays a greater role in the decision to regulate than science (see Politics section below). Politics and policy design play significant roles in the modern chemical regulatory regime. Hence, a comprehensive analysis of EDC regulation must take politics and policy design as well as science into account. The appropriate standard by which to judge these disparate policy elements is Congress's mandated end goal: to protect public health. We will return to this issue.
Priority setting
After EPA sorts chemicals according to statutory considerations, data availability, and qualitative judgment, EPA decides which of the estimated 87,000 chemicals merit consideration first through 'priority setting' [13]. The sorting of chemicals into the four categories in figure 2 and the setting of priorities within 'Category 2' require functionally equivalent information (Note figure 2 disaggregates the policy stages from the right hand column of figure 1). So priority setting, as used in this article, applies to both EDSP activities described as sorting and priority setting (i.e. everything above the dashed line in figure 2). The Endocrine Disruptor Screening and Testing Advisory Committee (EDSTAC) defined 'priority' as 'of greatest concern' in their final report, presumably as determined by science [14]. EPA, however, added statutory criteria to the scientific considerations by necessity: "EPA plans to use three main categories of information to set priorities: exposure-related information, effects-related information, and statutory criteria" [15]. Setting aside the chemicals Congress mandated EPA test (the statutory criteria), how well can EPA scientifically set priorities among potential EDCs?
Figure 2 EDSP policy design
EPA simply cannot set priorities based on science alone. Almost no data on potential endocrine disruption exists for the 87,000 prospective EDCs, creating a catch-22 of needing unavailable information to decide how to gather information. EPA wants to prioritize which chemicals to develop data on by examining hazard and exposure data on those chemicals. In the information poor environment of endocrine disruption, EPA has no basis to commence setting priorities. Two methodologies, high-throughput pre-screening (HTPS) and quantitative structure activity relationships (QSAR) both discussed below, have attracted attention and resources due to a general recognition of this problem. But more important than our current lack of data, EDCs operate with a high degree of complexity. Because of system complexity, some uncertainty about endocrine disruption probably cannot be resolved – resulting in some abiding doubt about the significance of a chemical as a potential endocrine disruptor. The scientific community and EPA seem quite cognizant of this complexity, but its relevance for policy and for the end goal of protecting public health deserves careful attention.
EPA has not realized their ideal of priority setting based on hazard and exposure information because of the catch-22 mentioned above. As a result, "EPA's proposed approach focuses on human exposure-related factors rather than on a combination of exposure- and [hazard]-related factors" [16]. While this statement acknowledges some of the difficulty using scientific information for priority setting, it is misleading. EPA's current stated policy prioritizes only pesticide active ingredients and high production volume (HPV) pesticidal inerts not because of scientific criteria (hazard- or exposure-related), but for statutory reasons; Congress specifically mandated testing of these compounds [2,17]. In fact, the concept of setting priorities for potential EDCs based only on exposure-related factors is fundamentally flawed.
To set priorities based on exposure factors alone, one must assume greater exposure to a chemical implies greater potential hazard (or some other arbitrary assumption). For EDCs, this assumption is scientifically insupportable. The complexity of low-dose effects (discussed in more detail in the Screening and testing section below) implies that exposure to some EDCs at extremely dilute doses may have a greater effect than massive exposure to that same chemical. Transient or low-concentration EDCs may also pose a greater risk than other high-exposure chemicals. Low-dose effects and other exposure complexities make exposure alone a poor proxy for setting priorities. Since different vulnerabilities and sometimes different health effects manifest at different developmental stages, any exposure-only judgment will run into significant difficulties defining spatial and temporal boundaries for exposure determinations. Some short-lived chemicals may have important endocrine- disrupting effects, but may not show up in EPA's most robust exposure data sources: biological sampling and environmental monitoring [15].
Further complexities undermine scientific determinations of exposure. Maternal metabolism of fat stores containing bioaccumulated EDCs may lead to practically unidentifiable fetal exposure. Some poorly understood exposure sources, such as flame retardants in clothing and furniture or phthalates leaching from plastics, would be extremely difficult to determine because of the complex social, cultural, and ecological conditions that affect chemical release and exposure. Even conventional exposure determinations, such as ingested pesticides, are fundamentally dependent upon patterns of food consumption. Averaging exposure may obscure vulnerabilities brought on by complicated cultural, social, and economic patterns of food consumption and other subpopulation attributes or behaviors. For example, research has shown significant differences in the exposure of adults and children to certain pesticides via residual contamination of fresh and processed foods [18,19]. FQPA may further obscure exposure determinations through mandates requiring EPA to assess cumulative exposure, including all exposure routes and sources, all chemicals with similar modes of action, and other mixtures of multiple chemicals. The complexity of endocrine disruption undermines old assumptions about the relevance of exposure and prevents scientifically meaningful prioritization on the basis of exposure data alone.
Understanding this limitation to some degree, EPA continues to develop and evaluate two methodologies to include health-effects criteria in the prioritization process. The first method is high-throughput pre-screening, or HTPS. This method allows for fast, large-scale testing of chemicals for interactions with estrogen, androgen, and now thyroid receptors. HTPS, unfortunately, has flaws as a means of detecting potential hazard for priority setting. Most basically, HTPS only tests for hormone receptor interactions. The possibility of this leading to a systematic bias against consideration of non-receptor mediated endocrine disruption is significant. Receptor interaction is only one means by which a chemical can disrupt the endocrine system. Interaction with the hormone molecules themselves, stimulation or suppression of hormone production, and disruption of old hormone metabolism can all lead to endocrine-disrupting effects as well. HTPS cannot test for these effects. Other hazard-related shortcomings relevant to HTPS are discussed more thoroughly in the Screening and testing section of this study. An EPA feasibility study cited some of the same issues raised here in declaring HTPS insufficient for regulatory purposes [20].
A second methodology under development is a computer modeling technique called quantitative structure activity relationships, or QSAR. QSAR simulates the behavior of a chemical based on its structure. EPA would use QSAR to predict chemical binding with estrogen, androgen, and thyroid receptors. The dominant criticism of HTPS applies to QSAR as well – it tests for receptor binding only. However, the use of computer models will incorporate new uncertainties via the selection of system boundaries and functional relationships that may preclude mechanisms and variables relevant to some endocrine-disrupting action. While a modeling effort may yield useful knowledge, as a decision-making tool QSAR is wanting. The inevitable and likely widespread false positive and false negative results will demand a parallel testing procedure to establish QSAR's utility for priority setting. But the drive to develop QSAR derives from an inability to devise an efficient and reliable testing procedure (like HTPS) in the first place. While these limitations may or may not be overcome in time, at present the methodology is not useful for setting priorities. It is instructive, however, to consider the justifications for the development of QSAR. "Systematic toxicity testing, using conventional toxicology methodologies, of single chemicals and chemical mixtures is highly impractical because of the immense numbers of chemicals and chemical mixtures involved and the limited scientific resources" [21]. QSAR was developed as an attempt to solve the very problems cited in the Policy Design section above. Although models can provide much useful information, they are unlikely to help prioritize EDCs anytime soon.
Screening and testing
To amass the evidence necessary for regulation, EPA designed two tiers of scientific assays. Tier 1 screening involves short-term assays to detect potential chemical interaction with the endocrine system. Tier 2 testing involves long-term assays to establish such interactions, explore more complicated endpoints, and establish dose-response relationships. If enough data exists, a chemical can go straight to Tier 2 testing. Otherwise chemicals are assigned to Tier 1, where chemicals are prioritized and screened, with all positive results forwarded for Tier 2 testing (see figure 2 for the policy design). "The Tier 2 tests are longer in duration than Tier 1 tests and are designed to encompass critical life stages and processes as well as a broad range of doses, and are intended to be administrated by a relevant route of exposure" [16]. Although screening and testing are separate EDSP regulatory stages, their vulnerabilities to complexity are similar enough to group them together for purposes of this discussion.
Both screening and testing focus on identifying hazard, leaving exposure considerations for the final risk assessment. As such, this discussion addresses only hazard-related complexities and uncertainties. The toxicology of endocrine disruption is inherently complex in the sense that scientists must abandon the simplifying assumptions of standard toxicology. Most notably, we must abandon the assumption of monotonic dose-response relationships, which assume an increased exposure to a substance always leads to an increase in effect. Increasing exposure to some EDCs swamps the endocrine system and prevents or reduces dysfunction (i.e. an inverted U dose-response, e.g. [22,23]), while other EDCs exhibit effects at both high- and low-doses, but not in between (i.e. a U- or J-shaped dose-response, e.g. [24]); still others may exhibit hormesis, whereby a small dose has a beneficial effect [25,26].
The monotonic assumption allows for statistically significant results using smaller sample sizes exposed to higher doses for shorter periods of time. Linearly scaling these results down to typical exposure levels presumably yields approximate quantitative rates of, for example, disease or cancer. Abandoning this assumption decreases testing efficiency and multiplies the time and other resources necessary to understand the potential hazard posed by a chemical. A quote from University of Washington, Seattle toxicologist David Eaton, states the issue simply: "It's just too expensive ... you'll never be able to characterize [a low-dose effect] to the point where people think it's real" [25]. Non-monotonic dose-responses may also indicate some unresolvable system complexity. Other standard toxicological assumptions suffer the same fate as monotonic dose-response, for example: the threshold assumption and the assumption that a chemical has a uniform effect.
Other factors complicate a scientific determination of hazard. Two chemicals can interact in ways that alter their effects. Some chemicals together inhibit their individual effects, reducing or preventing an adverse effect where one is expected. Others simply add their effects together, and yet others interact synergistically, magnifying the effect either or both would normally have. "Synergistic interactions are the most problematic, because they indicate that the effects of multiple chemicals together can be significantly more powerful than might be predicted simply by adding up their effects one at a time. Regulatory science rarely incorporates any interactions; it is incapable, at present, of coping with synergies" [27]. Regardless of this incapacity, EPA seems determined to try and deal with this complexity: "EPA recognizes that the science of evaluating mixtures remains complex and unclear, but believes that it should begin to confront the issues raised by them" [28]. Additionally, scientists have evidenced possible synergism between EDCs and infectious disease agents [29]. Synergies with nutrients or poor nutrient levels might also prove significant (e.g. lead, [30]). These interaction effects further aggravate the difficulty of determining hazard. Several studies of the body burden of chemicals in humans evidence high and diverse concentrations of synthetic chemicals, indicating the importance and likelihood of chemical interactions [31-33].
Another serious complication involves the selection of testing endpoints, or dysfunctions possibly caused by EDCs. Some of the dysfunctions already identified through animal studies include cancer susceptibility and birth defects, but also more subtle endpoints like immunological dysfunction, suppression of secondary sex characteristics, decreased fertility, increased aggression, decreased mental capacity and focus, disrupted brain development, etc [34,35]. While scientists can examine some of these endpoints relatively easily in human populations (e.g. cancer incidence), others would be incredibly difficult to observe, measure, or prove with sufficient statistical certainty (e.g. feminization of boys or masculinization of girls). The difficulty of isolating and measuring these more subtle effects makes them impractical as regulatory endpoints. The inability of scientific testing to measure such endpoints, however, does not justify their exclusion from regulatory consideration. Such a policy would (and in fact does) bias the regulation of chemicals by exempting the most complicated chemicals and the most complex health effects from regulatory consideration.
Risk analysis and regulation
A risk analysis concludes the EDSP policy design. EPA claims it will use its standard human health risk assessment process for EDCs [36]. Simply put, EPA considers hazard and exposure data and uncertainties to make regulatory decisions (see bottom figure 2 to right of dashed line). For example, an extremely hazardous chemical associated with insignificant exposure probably would not require regulation while a mildly hazardous chemical with widespread and pervasive exposure probably would. Safety factors are built into this process to protect public health. The standard safety factor for pesticides is 100× to compensate for uncertainties such as response differences between humans and the animals studied. FQPA added an additional 10× safety factor to protect children, but EPA's uses this additional safety factor inconsistently [8].
Because EPA's risk analysis demands an explicit integration of hazard and exposure data, the risk assessment itself is vulnerable to the exposure complexities treated in the Priority setting section and the hazard complexities treated in the Screening and testing section. These complexities include: HAZARD – low-dose effects, mixtures and synergies, and uncertain endpoints; and EXPOSURE – transient and low-concentration exposure to EDCs, maternal metabolism of bioaccumulated EDCs, varying vulnerability and response by developmental stage, poorly understood exposure sources, vulnerable subpopulations, and cultural, social, and economic patterns and spatial and temporal bounds of chemical release and exposure. More science cannot resolve all of these complexities and uncertainties.
But these complexities translate into an even more pernicious difficulty, as decisions assumed answerable by science must be made under conditions of scientific ambiguity. Ambiguity is related to complexity as follows: Complexity refers to properties of the system under study, not the study itself. Such properties include interactive effects (like synergies), feedback loops, temporal delays between cause and effect, chaotic or stochastic system behavior, large numbers of intervening variables, and inter-individual variations. Uncertainty refers to limitations of the human analysis of a complex system. While science is often employed 'to reduce uncertainty,' the complexity of a system sets bounds on the prospective certainty of informed scientific judgment. For example, further science can never remove the chaos from a chaotic system or the randomness from a stochastic one. And to illustrate the point, exposure of a fetus to environmental EDC contamination in utero might easily be a chaotic or stochastic system. Ambiguity refers to a situation in which existing scientific data support equally valid but competing interpretations of risk (see [37] for a discussion of concepts).
Ambiguity is the single greatest limitation to the use of endocrine disruption science in policy. While an oft-cited truism holds that decision-makers can make better decisions with reliable information at hand, this hardly tells the whole story. Other considerations play into decision-making, including value tradeoffs, time and resource limitations, and informational constraints, including scientific ambiguity. A National Academy of Sciences report on endocrine disruption substantiates the ambiguity in this field:
[I]t became clear as the work of the committee progressed that the same data could be approached from different viewpoints. Those different views led to different judgments among the committee members about the significance of the threat posed by [EDCs]. In [some] cases, the differences do not reflect the need for research but reflect differing judgments about the significance of information. The differences are not confined to the members of this committee but are also reflected in the scientific community at large and in the comments received during review [35].
The recommendations of this committee amounted to suggestions for more research. While more research might be a good thing, such a suggestion provides no guidance on how to address the more policy-relevant question of how to make decisions with ambiguous scientific information. In a nutshell, more science is not a panacea for all the problems of risk analysis or decision-making.
This brings us to making decisions about regulation. If a reasonably certain determination of harm about an EDC could somehow be made, how would one regulate that chemical? This discussion of regulation is only tentative since EPA's Regulatory Activities Workgroup continues to study the issue. Since EPA has not yet validated any screening or testing procedures [38], regulation under EDSP has so far received little attention. Under section 408p of FQPA, EPA must use "such statutory authority as is available" to protect public health [2] (emphasis added). In other words, the statutes requiring testing for endocrine disruption provide no new process by which to regulate those chemicals – the standards for regulation remain those of previous regulatory laws. Unfortunately, this complicates enforcement authority for EDCs.
Regulation must be authorized under one of four laws: the Toxic Substances Control Act (TSCA), the Federal Food, Drug, and Cosmetic Act (FFDCA), the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA), or the Safe Drinking Water Act (SDWA). The agencies with regulatory jurisdiction for EPA's list of 87,000 chemicals are: the Environmental Protection Agency (EPA), the Food and Drug Administration (FDA) in the U.S. Department of Health and Human Services, and the Food Safety and Inspection Service (FSIS) in the U.S. Department of Agriculture. EDSTAC recommended and EPA adopted the following list of chemicals for endocrine disruptor testing: 75,500 commercial chemicals listed under TSCA, 900 pesticide active ingredients, 2,500 pesticide inert ingredients, 5,000 cosmetic ingredients, 3,000 food additives, an unspecified number of nutritional substances, and an unspecified number of natural hormonally active plant residues [14].
Testing and enforcement authority for this universe of chemicals is fragmentary. For example, EPA has authority under FIFRA and FFDCA to set tolerances for pesticides on food, but enforcement authority falls to FSIS for meat and poultry products, and FDA for other food items. The authority is also incomplete. For example, FDA has authority over the estimated 5,000 cosmetic chemicals, but FDA has no authority to require any information from the manufacturer or to mandate product safety testing. FDA's regulatory authority over cosmetics begins only after a product (possibly without any safety information) enters the market. Additionally, the standards by which to regulate differ. Under TSCA and SDWA the economic costs of regulation must be balanced against the public health threat, but under FIFRA and FFDCA, economics can be considered in only narrowly crafted situations – the standard is largely health-only based. FFDCA and FIFRA as amended by FQPA use the "reasonable certainty of no harm" standard. This standard translates into a 95% certainty that fewer than one in a million additional cancer deaths will occur due to the expected exposure over a lifetime. No translation specific to EDCs of this standard is yet available. TSCA, on the other hand, must prevent "unreasonable risk" of injury to health or the environment. A risk is "unreasonable" if the risks exceed the benefits associated with that activity, including economic benefits. SDWA explicitly requires a consideration of the cost of compliance to state, local, and other water systems when setting safety standards.
The estimated 2,500 pesticide inert ingredients may defy regulation due to trade secret norms, poor EPA data quality, and historic government neglect [39,40]. Additionally, no federal statute delegates any authority at all for the testing or regulation of nutritional supplements. Presumably, endocrine-disrupting nutritional supplements could be regulated only voluntarily, but the onus of testing would fall completely upon the executive agency that volunteers to expand its responsibilities. Significant difficulties involving confidential business information, including proprietary chemicals and chemical mixtures may further compromise enforcement capability.
The complexity of the institutional and legal landscape (multiple interacting agencies with multiple overlapping mandates and authority) creates substantial regulatory confusion. In this situation, the powers and responsibilities of different government agencies might be interpreted differently by other agencies or by affected parties. Such confusion leaves room for interpretation that may require long delays and intensive court battles to resolve. The history of TSCA indicates that such confusion (for TSCA, 'balancing economic cost' with regulations to protect public health) as well as the menace of legal action can lead to crippling regulatory inaction [41]. By requiring enforcement under existing statutory authority, FQPA leaves the regulation of the already complicated universe of EDCs to a complicated web of regulatory regimes of questionable efficacy.
Politics
Finally, the role of politics in regulatory decision-making deserves note. The conventional ideal of regulation under the current paradigm is that good science leads to an informed decision-maker who can then remove or limit a proven hazardous chemical from commerce (or, rarely, prevent its introduction). The complexities of endocrine disruption science, practical considerations, and the regulatory deficiencies discussed above impose limitations on this conventional ideal. Neglecting the role of politics in regulatory decision-making, however, is perhaps this ideal's most significant omission. A variety of academic and government research as well as environmental and public interest group analysis points to the failure of testing regimes to produce significant regulation or protect public health (e.g. [7,8,10,12,41,42]). In fact, past regulation often addressed specific chemicals by legislative mandate (e.g. the mandated ban of PCBs in TSCA) or due to media-promoted public awareness and its resultant outcry (e.g. the January 1971 court order essentially forcing EPA Administrator Ruckelshaus to ban DDT). In other words, politics often leads to regulation regardless of scientific considerations.
The Alar 'scare' of 1989, when the public and EPA reacted to evidence that contamination of apples might endanger child health, provides a visible recent example of this dynamic. A 60 Minutes show aired on February 26, 1989 [43] dedicated to the findings of a Natural Resources Defense Council study titled 'Intolerable Risk: Pesticides in our Children's Food' [18]. The public outcry about Alar (a.k.a. daminozide) led to a drop in apple sales and pushed EPA and Alar's manufacturer, Uniroyal Chemical Company, Inc., to take action [44]. After announcing the safety of Alar in March 1989, and an intention to take no action before July 1990 [45], EPA announced a preliminary determination to eventually cancel all registrations of daminozide used on foods in May 1989 [46]. A little over a week later, Uniroyal announced a voluntary recall of all remaining stocks of Alar, and EPA approved a voluntary cancellation of all Uniroyal's daminozide registrations that November [47].
In an attempt to avoid the still bitter battle between Alar critics and advocates, the relevant point is not whether Alar is or is not a health hazard, but that politics played a major if not a dominant role in its regulation. The very fact that a bitter argument about the actual risk posed by Alar persists indicates that science does not always play a definitive role in regulatory decision-making [44,48,49]. But if politics significantly affects decision-making, what is the role of science? To understand the interplay between science and regulation, we must critically consider the conventional assumptions of the modern U.S. chemical regulatory paradigm.
Conclusions
The conventional paradigm underlying EDSP and most other U.S. chemical regulation amounts to 'science leads to regulation;' it assumes a scientific determination of harm must and, in fact, does precede regulatory action. In this context, Congress mandated EPA protect public health from EDCs, but only after "develop[ing] a screening program, using appropriate validated test systems and other scientifically relevant information, to determine [harm]" [2]. Real progress on protecting public health waits on the development of a scientific testing regime, on faith that scientific testing is both necessary and sufficient to protect public health. Practical considerations, hazard complexity, exposure complexity, and regulatory deficiencies all challenge the naivety of this assumption. Rational analysis of these factors leads to the inescapable conclusion that science has limitations within the existing regulatory regime and that other important factors are disregarded by the current paradigm.
This criticism does not discount the contributions of science, although it seriously questions the assumption that simply doing more science will protect public health. Additionally, this argument does not promote unconsidered action, although it does stress the need to make decisions in the face of ambiguous information. The paradigm itself, though invisible to most adherents, is quite real. The words and actions of industry and environmental groups, government agency personnel, members of Congress, and other concerned interests, regardless of their side of the debate, indicate near universal buy-in to the 'science leads to regulation' paradigm (see [10] for discussion). But the complexity, uncertainty, and ambiguity of endocrine disruption and its broader context undermine this paradigm's simple logic.
The internal validity of 'science leads to regulation' presumes the capacity of science to prove harm with sufficient certainty to regulate. Exposure complexities, including transient and low-concentration exposure to EDCs, maternal metabolism of bioaccumulated EDCs, varying vulnerability and response by developmental stage, poorly understood exposure sources, vulnerable subpopulations, and cultural, social, and economic patterns and spatial and temporal bounds of chemical release and exposure, place the ability of science to make solid exposure determinations in significant doubt (see Priority setting section). Hazard complexities, including low-dose effects, mixtures and synergies, and uncertain endpoints, contribute further obstacles to an unambiguous scientific determination of harm (see Screening and testing section). Under current policy mechanisms, these complications of endocrine-disruption science will prevent any meaningful regulatory action. Essentially, endocrine disruption is too complex and our science too uncertain; most scientific information regarding EDCs will remain ambiguous, with the available information supporting quite different judgments of risk.
Recall this observation by the National Research Council: "In [some] cases, the differences [in scientific judgments of EDC significance] do not reflect the need for research but reflect differing judgments about the significance of information" [35]. The National Research Council has also recognized the more general prejudice that hinders regulation: "The assumption of the null hypothesis as used in risk analysis [as in the case of regulating chemicals] contains an implicit bias because it places a greater burden of proof on those who would restrict than those who would pursue a hazardous activity, presuming these activities are safe until proven otherwise" [50]. In other words, the paradigm is biased against regulation, and the complexity and uncertainty of endocrine disruption will further undermine attempts to regulate.
The external validity of 'science leads to regulation' must take into account the broader context of potential endocrine disruptor regulation. The regulatory deficiencies addressed in the Risk analysis and regulation section, the practical considerations addressed in the Policy Design section, and the significant role of politics in regulation discussed in the Politics section challenge the arbitrary constraints the paradigm places on non-scientific factors. The roles of actors besides the scientific community and agency scientists can make or break regulation. Furthermore, the legal ambiguity of regulating different chemicals under four statutes with different regulatory standards and fragmentary, incomplete statutory authority guarantees further difficulty with regulation, even if the science could meet the near-impossible burden of proof. The most basic practical considerations, including other U.S. regulatory precedents, policy mechanisms to avoid regulation, and most importantly, the sheer number of potential EDCs, each bring the conventional paradigm into doubt. 'Science leads to regulation' simply leaves too much of the decision-making context out of the picture.
Yet discussions of improving chemical regulation primarily deal with the minutiae of scientific testing regimes. For example, an Environmental Defense Fund analysis exposing the utter futility of chemical regulation under TSCA (based on the U.S. Government's own damning analysis) came to the conclusion that the failure of testing in the past means we need to test better in the future [7,41]. Though better testing might improve things, such a suggestion still ignores the hard reality of decision-making. Scientific information often remains ambiguous and consistent with quite different action alternatives. Furthermore, scientific information forever remains only one consideration of the decision maker – economic impact, resource tradeoffs, political considerations, constituent needs, and agency funding are other obvious and equally relevant considerations.
The relevance of science for regulatory decision-making lies predominantly outside the current trend of increasingly detailed mechanistic investigation of endocrine disruption. While endocrine disruption science can contribute much to a decision-maker, it cannot provide unambiguous information that 'objectively' determines the correct decision. But science could help guide decision-making under conditions of ambiguity; uncertainty does not entail 'anything goes.' On the contrary, the uncertainty itself might guide decision-making better than any other factual information. The 2001 Intergovernmental Panel on Climate Change reports provide a precedent in the explicit treatment of uncertainty – the reports indicate the relevance of scientific information for decision makers by ranking scientific conclusions by Bayesian confidence estimates (e.g. virtually certain means greater than 99% confidence, very likely 90–99%, etc) [51]. This empowers decision makers and the public by contextualizing expert knowledge and frees scientists to provide relevant information that has not yet met the rigorous standards of scientific proof and peer review. Some excellent work extrapolating from this precedent and considering its ramifications already exists [52,53].
A franker treatment of uncertainty can improve the relevance of science to decision-making and promote realistic expectations of science and the scientific community. Such progress might turn the spotlight on more significant impediments to regulatory decision-making under conditions of ambiguity, such as the difficulty of testing 87,000 chemicals and the role of politics and values in making regulatory decisions. Scientists can take action within their own communities to support the policy goal of protecting public health by exploiting and improving the role scientific information plays in chemical regulation. The possibility that scientists can empower decision makers and the public by developing community standards and norms explicitly addressing uncertainty is one creative idea, but more are needed. The key to progress is taking an active and creative role in support of the protection of public health. Waiting for a solution in the form of national legislation has failed to inspire significant change over the last several decades. But explicit action within the scientific community that discourages unrealistic expectations of science will support long-term progress on chemical regulatory policy and the protection of public health.
List of abbreviations
DDT – dichlorodiphenyltrichloroethane
EDC(s) – endocrine disrupting chemical(s)
EDSP – (U.S.) Endocrine Disruptor Screening Program
EDSTAC – Endocrine Disruptor Screening and Testing Advisory Committee
EPA – (U.S.) Environmental Protection Agency
FDA – (U.S.) Food and Drug Administration
FFDCA – (U.S.) Federal Food, Drug, and Cosmetic Act
FIFRA – (U.S.) Federal Insecticide, Fungicide, and Rodenticide Act
FSIS – (U.S.) Food Safety and Inspection Service
FQPA – (U.S.) Food Quality Protection Act
HPV – high production volume
HTPS – high-throughput pre-screening
PCBs – polychlorinated biphenyls
QSAR – quantitative structure activity relationships
SDWA – (U.S.) Safe Drinking Water Act
SDWAA – (U.S.) Safe Drinking Water Amendments Act
TSCA – (U.S.) Toxic Substances Control Act
Competing interests
The author(s) declare that they have no competing interests.
Acknowledgements
This material is based on work supported by a National Science Foundation Graduate Research Fellowship. Thanks to Richard and Idell Vogel for their intellectual generosity and insight. A special thanks to Ted Schettler, John Stegeman, Tim Verslyke, Anne Tarrant, and Alfred Spira for their exceptionally thoughtful reviews.
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| 15701170 | PMC549529 | CC BY | 2021-01-04 16:36:33 | no | Environ Health. 2005 Feb 8; 4:2 | utf-8 | Environ Health | 2,005 | 10.1186/1476-069X-4-2 | oa_comm |
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Immun AgeingImmunity & ageing : I & A1742-4933BioMed Central London 1742-4933-2-21568659710.1186/1742-4933-2-2ResearchCirculating γδ T cells in young/adult and old patients with cutaneous primary melanoma Re Francesca [email protected] Alessia [email protected] Beatrice [email protected] Giovanni [email protected] Mauro [email protected] Laboratory of Tumor Immunology, Immunology Center, I.N.R.C.A. Res. Dept., Ancona, Italy2005 1 2 2005 2 2 2 12 1 2005 1 2 2005 Copyright © 2005 Re et al; licensee BioMed Central Ltd.2005Re 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 a previous study we demonstrated the existence of numerical and functional alterations of γδ T cells in healthy elderly. Recently, we analysed the involvement of γδ T lymphocytes in malignant melanoma, describing a lower frequency of circulating γδ T cells, an altered pattern of cytokine production, and an impaired in vitro expansion of these cells in primary cutaneous melanoma patients.
Methods
In this study we investigated the existence of numerical and functional alterations of circulating γδ T cells in young/adult and old melanoma patients, comparing the data obtained with age-matched healthy subjects.
Results
We demonstrated that the number of circulating γδ+ T cells was significantly and similarly reduced in young/adult and old melanoma patients and in old healthy subjects in comparison with young healthy donors. The decrease was due to a reduction of Vδ2 T cells whereas the number of Vδ1 T cells was not affected. A higher percentage of γδ+ T cells producing TNF-α was found in old healthy donors, whereas a reduced number of TNF-α-producing γδ+ T cells was present in melanoma patients independently by age. No significant difference was observed in IFN-γ production. After a 10-day in vitro culture, both the percentage and the expansion index of γδ T cells, and in particular of Vδ2 subset, were significantly and similarly reduced both in young/adult and old melanoma patients, and in healthy aged people, in comparison with young/adult healthy subjects.
Conclusions
Our study demonstrates that the numerical and functional impairment of γδ T cells found in melanoma patients is not correlated with age and that it has characteristics very similar to the alterations of γδ T cells found in old healthy subjects. We suggest that a similar impairment of γδ T cell population may be related to the increased susceptibility to tumors present in the elderly as well as in the pathogenesis of malignant melanoma.
γδT cellsagingmelanomahumantumor immunity
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Introduction
T lymphocytes bearing the γδ T cell receptor (TCR) represent a minor population of human peripheral lymphocytes (1–10%), the majority of them expressing the CD3+CD4-CD8- phenotype [1-4]. The ability of γδ T cells to respond to nonprocessed and nonpeptidic phosphoantigens in a major histocompatibility complex (MHC)-unrestricted manner is an important feature distinguishing them from αβ T cells [5-9]. In human peripheral blood two main populations of γδ T cells have been identified based on the TCR composition. The predominant subset expresses the Vδ2 chain associated with Vγ9 and represent 70% of the circulating γδ T cells in adults, while a minor subset (approximately 30%) expresses a Vδ1-Jδ1 chain linked to a chain different from Vγ9. At birth the Vδ1 population predominates, while in adults there is a shift towards Vδ2 T lymphocytes, probably due to a selective response to environmental stimuli such as commonly encountered bacteria. [10].
Although little is known about the physiologic significance of γδ T cells, their marked reactivity toward mycobacterial and parasitic antigens as well as tumor cells suggests that γδ T cells play a role in the anti-infectious and anti-tumoral immune surveillance [11,4]. Few data are available about the number and the function of γδ T cells and of Vδ1 and Vδ2 subsets in aging. The complexity of the gamma delta T cell repertoire has been found to decrease with age as a consequence of the expansion of a few T cell clones [12]. In our previous paper [11], we have evaluated the role of γδ T cells from young, old, and centenarian subjects, demonstrating an age-dependent alteration of γδ T lymphocytes, with a lower frequency of circulating γδ T cells, an altered pattern of cytokine production, and an impaired in vitro expansion of these cells. We suggested a role of the γδ T cell impairment in the age-related increase of infections and tumor diseases. Other studies have showed the involvement of γδ T cells in the immune defence against cancer either through a direct reactivity against tumor cells, or because of their regulatory interactions with αβ T cells [13]. Recently, we described an impairment of γδ T cell population in patients with cutaneous primary melanomas, with a decrease of their absolute number and percentage, an altered cytokine production, and a reduced expansion of γδ T cells, and particularly of the Vδ2 subset [14].
On the basis of the pivotal role that γδ T cells may have in the elderly and in the immune response against melanoma we tried to find out a possible correlation in the alteration of γδ T cells between aged people and melanoma patients. In this study we evaluated the peripheral representation, the in vitro expansion, and cytokine production γδ T cells from young/adult and old melanoma patients, comparing the results with those obtained in age-matched healthy controls.
Materials and Methods
Cell preparation and stimulation
Human peripheral blood was obtained from 9 young (mean age ± SD, 42.3 ± 9.4 years; median: 41.0 years, range 30–59), 12 old (71.8 ± 5.4 years; median 72.5 years, range 60–80) melanoma patients, and 10 young (39.0 ± 5.7 years; median: 38.5, range 30–55), and 13 old (74.0 ± 2.0 years; median: 74.0 years, range 60–80) healthy donors. Healthy subjects were volunteers in good and stable clinical conditions, and had laboratory parameters in the physiological range. We excluded subjects in poor health with degenerative diseases or in therapy with drugs interfering with the immune system. Melanoma patients have been admitted to the Dermatology Unit of the I.N.R.C.A. Hospital of Ancona. Melanoma patients were in good health other than for the existence of melanoma as checked on the basis of clinical and laboratory parameters. The investigations were performed after approval by a local institutional review board. A written informed consent was obtained from each subject. Diagnosis of melanoma was histologically confirmed. All patients brought cutaneous primary non-metastatic melanoma and were staged according to the new American Joint Committee on Cancer staging system for cutaneous melanoma [15]. A blood drawing was taken before the surgical excision. Each donor was tested once and all the tests were carried out with a single blood sample.
Fresh peripheral blood mononuclear cells (PBMC) were fractionated on Ficoll-Paque (Pharmacia, Uppsala, Sweden) and separated by density gradient centrifugation (400 g, 30 min). Cells from the interface of the gradients were washed twice with Ca2+ and Mg2+- free phosphate buffered saline (PBS, Gibco/Life Technologies, Gaithersburg, MD, USA) and resuspended in RPMI 1640 supplemented with 10% heat-inactivated fetal bovine serum, penicillin (100 U/ml) and streptomycin (100 μg/ml) (all from Life Technologies, complete medium) at a concentration of 1.5 × 106/ml. Mononuclear cells were cultured in the complete medium supplemented with 100 U/ml of IL-2 (Chiron Italia, Milan, Italy). Phosphoantigen-specific stimulation of γδ T cells was performed using the nonpeptidic antigen isopentenylpyrophosphate (30 μg/ml, IPP, Sigma Chemical Co., St. Louis, MO, USA). The cells were incubated at 37°C in an atmosphere of 95% air, 5% carbon dioxide, at 90% relative humidity in 24 well plates.
Monoclonal antibodies and FACS analysis
PBMCs were analysed for cell phenotype through double staining with the following monoclonal antibodies (mAbs): anti-CD3 (PE) and anti-pan γδ T cells (FITC), or anti-TCR Vδ1 or anti-TCR Vδ2. The phycoerythrin (PE) -conjugated monoclonal antibody anti-CD3 was purchased from EuroClone (Devon, UK). The fluorescein isothiocyanate (FITC) -conjugated anti-pan TCR γδ, anti-TCR Vδ1, and anti-TCR Vδ2 were purchased from Endogen (Boston, MA, USA). IgG1 (Becton Dickinson) was used as isotype control.
0.5 × 106 PBMCs were washed in PBS containing 0,1% NaN3 plus 5% FBS and labelled with 5 μl of anti-CD3 or anti-TCR Vδ1 MoAbs or 2.5 μl of anti-pan TCR γδ or anti-TCR Vδ2 for 30 min in ice. At the end of the incubation, cells were washed in PBS containing 0,1% NaN3, resuspended in PBS (Gibco) and immediately analysed with a Coulter XL flow cytometer.
Intracellular detection of IFN-γ and TNF-α
Mononuclear cells were stimulated with IPP and IL-2 for 18 h, and GolgiPlug (a protein transport inhibitor containing brefeldin A, PharMingen, Milton Keynos, England) was added during the last 12 h of culture to block intracellular transport processes and allow cytokine accumulation. 0.5 × 106 stimulated cells were stained with the anti-pan TCR γδ mAb for 30 min at 4°C. Fixation-permeabilization of cells was performed in PBS/2% paraformaldehyde for 15 min at 4°C, followed by incubation for 30 min at room temperature in the dark with PE-conjugated anti-human IFNγ mAb or anti-human TNF-α mAb diluted in PBS, 1% BSA, and 0.05% saponin. Cells were finally washed twice in PBS, 1% BSA, and 0.01 % saponin and analysed on a XL flow cytometer (Coulter).
Expansion assay
PBMC were cultured for up to 10 days in the complete medium supplemented with 100 U/ml of IL-2 and 30 μg/ml of IPP to determine a phosphoantigen-specific stimulation of γδ T cells. After 1 wk of culture, the volume corresponding to half the culture medium was replaced by fresh medium. On day 10 of culture viable cells were determined by trypan blue exclusion and used for FACS analysis. The viability was always greater than 98% as determined by trypan blue exclusion. The expansion of γδ T cells was followed by cytometric analysis through double staining of stimulated cells with anti-CD3 (PE) and anti-pan γδ, or anti Vδ1, or anti Vδ2 T (FITC) mAbs. The absolute number of γδ T cells in each culture was calculated as follow: (percentage of γδ T cells among total cells) × (total cell count)/100. The γδ T cell expansion index was then calculated by dividing the absolute number of γδ T cells in stimulated cultures by the absolute number of γδ T cells before culture [16].
Statistical analysis
Data were analysed for statistical significance by using parametric or nonparametric tests according to the distribution of the data. Comparisons of variables among groups were made by one-way analysis of variance (ANOVA) or Kruskal-Wallis one-way ANOVA on ranks. When significant differences were found, the differences among groups were made by the Student-Newman-Keuls method or Dunn's method. Difference between means was considered significant at the 5% level (P < 0.05). The statistical analysis was performed with SigmaStat software version 1.03 (Jandel Scientific, Germany).
Results
Ex vivo analysis of γδ T lymphocytes
Peripheral blood lymphocytes from 9 young/adult and 12 old melanoma patients and 10 young and 13 old healthy subjects were analysed for the percentage and the absolute number of γδ T cells through double staining with anti-CD3 and anti-γδ mAbs. As shown in Table 1 the absolute number of γδ T cells was significantly reduced in both groups of melanoma patients and in healthy aged people in comparison with young/adult healthy subjects (p < .01). As shown in Fig. 1A, the ex vivo percentage of CD3+γδ+ T cells in the peripheral blood was significantly lower in melanoma patients than in healthy donors (p < .01). As shown in Table 1, the absolute number of Vδ1 T cells did not show significant difference in the four groups of donors. Differently, the absolute number of Vδ2 T cells was significantly reduced in both groups of melanoma patients and in old healthy people in comparison with young/adult healthy subjects (p < .0001). The Vδ2 and Vδ1 subsets were differently represented in the four groups: in young/adult healthy controls the Vδ2 subset was predominant (Vδ2/Vδ1 ratio = 2.2) whereas in old healthy donors and in young/adult and old melanoma patients the Vδ2/Vδ1 ratio was progressively decreased.
Table 1 Absolute number of γδ T cells, Vδ1 T cells, and Vδ2 T cells, in young/adult and old healthy subjects and melanoma patients.
Absolute number
Donors γδ T cells Vδ1 T cells Vδ2 T cells Vδ2/Vδ1 ratio
Healthy
Young/adult 115.2 ± 39.3a 38.0 ± 11.9 82.6 ± 34.0 2.2
Old 62.1 ± 28.7* 35.9 ± 11.7 37.7 ± 24.6* 1.0
Melanoma
Young/adult 74.5 ± 25.3* 31.9 ± 18.1 42.8 ± 9.8* 1.3
Old 52.9 ± 38.0* 20.6 ± 3.7 33.5 ± 31.2* 1.6
a Data are expressed as mean ± S.D. of the number of cells per mm3 in the peripheral blood.
*p at least <0.01 versus young/adult healthy subjects
Figure 1 Percentage of γδ T cells in young/adult and old melanoma patients and age-matched healthy subjects. Freshly isolated (A) or 10-day cultured (B) PBMC from young/adult and old melanoma patients and young/adult and old healthy subjects were double stained with MoAb anti pan- γδ (FITC) and anti-CD3 (PE) and analyzed by flow cytometry. Statistical analyses was performed as reported in Mat. and Methods.
Cytokine production by γδ T lymphocytes
Since it has been demonstrated that activated γδ T cells produce TNF-α and IFN-γ, we studied the intracellular production of these cytokines in one-day stimulated γδ T cells from healthy subjects and melanoma patients. As shown in Fig. 2 the percentage of γδ T cells producing TNF-α was significantly higher in old healthy controls in comparison with young/adult healthy, and young/adult and old melanoma patients (p < .05). The percentage of γδ T cells producing IFN-γ was similar in young/adult and old healthy subjects (mean ± SD, 17.9 ± 10.0 and 14.7 ± 8.9). In a similar way the percentage of γδ T cells producing IFN-γ did not show differences between young/adult and old melanoma subjects (8.5 ± 4.9 and 8.1 ± 1.3) (data not shown).
Figure 2 Analysis of TNF-α production by γδ T cells in melanoma patients and age-matched healthy subjects. PBMC young/adult and old melanoma patients and young/adult and old healthy subjects were stimulated for 18 h in the presence of IPP (30 μg per ml) and IL-2 (100 U per ml). The last 12 h of culture were performed in the presence of GolgiPlug, a protein transport inhibitor containing brefeldin. Single-cell analysis of TNF-α synthesis in γδ T cells from a representative subject for each group was performed following dual staining with cell surface anti- γδ T (FITC) MoAb and intracellular anti- TNF-α (PE) MoAb. Number in brackets indicate the percentages of γδ T cells synthesizing TNF-α among total γδ T lymphocytes.
Expansion of γδ T lymphocytes
The expansion of γδ T cells was evaluated after 10 days of culture in the presence of IPP and low dose interleukin-2 (IL-2). Both the proportion of γδ T cells, evidenced by double staining FACS analysis, and their relative increase in comparison with the γδ T cell number found on day 0 (expansion index), were evaluated. As shown in Fig. 1B, the proportion of γδ T cells reached on day 10 was significantly lower in both groups of melanoma patients and in old healthy subjects than in young/adult healthy donors (p < .01). In a similar way, the expansion index of γδ T cells after 10 days of in vitro culture was significantly reduced in the same three groups mentioned above (p < .05, Table 2). As shown in the same Table 2, the expansion index of the Vδ2 subset was significantly lower in all melanoma patients and in old healthy donors than in young healthy donors (p < .03).
Table 2 Expansion index of γδ T cells and Vδ2 T cells in healthy subjects and melanoma patients
Expansion Indexa
Donors γδ T cells Vδ2 T cells
Healthy
Young/adult 13.1 ± 8.8b 7.1 ± 4.5
Old 4.6 ± 3.5* 3.1 ± 2.0*
Melanoma
Young/adult 3.8 ± 2.6* 4.6 ± 0.2*
Old 2.0 ± 1.8* 0.9 ± 0.4*
a The expansion index was calculated by dividing the absolute number of γδ T cells in stimulated cultures by the absolute number of γδ T cells before culture.
bData are expressed as mean ± S.D.
*p at least <0.05 versus young/adult healthy subjects
Discussion
We and others have demonstrated an impaired potential of γδ T cells in aged people, as evidenced by the reduction of the absolute number of circulating γδ T cells, in particular of the Vδ2 T subset, an altered pattern of cytokine production, an impaired in vitro expansion of these cells, and an increased expression of the early activation marker CD69, in aged people in comparison with young subjects [11,17,18]. Recently, studying a group of melanoma patients ranging from young to old age (32–80 yr), we described numerical and functional alterations of γδ T cells from these subjects, once compared to healthy age-matched donors [14]. In this study we have investigated on whether the age-related impairment of circulating γδ T cells is similar to the alteration found in melanoma patients and if melanoma patients of advanced age have a greater impairment of γδ T cells in comparison with melanoma patients of younger age or with old healthy donors. With these premises, we studied the peripheral representation, in vitro expansion, and cytokine production of γδ T lymphocytes from young/adult and old patients with cutaneous primary melanoma comparing the data obtained with age-matched healthy subjects.
We demonstrated that both the number of circulating γδ T cells and their in vitro expansion were decreased in melanoma patients and that the impairment did not correlate with the age of patients. Young/adult and old melanoma patients had a similar derangement of γδ T cells, and this impairment had numerical and functional characteristics like to those found in old healthy subjects. This evidence stresses the relevant role that this lymphocyte population may exert, either directly or through the regulation of T cell-mediated specific responses [11], both in the elderly and in melanoma patients.
The reduction of γδ T cell number well correlated with the decrease of the Vδ2 T cell subset, i.e., the most frequent subset of circulating γδ T cells [2,4]. The Vδ2 population is involved in the reactivity toward microbial antigens and tumor cell antigens [4,19]. The role of Vδ2 T cells in the immune defence against cancer has been demonstrated on the basis of their reactivity against certain lymphoma cells, such as Daudi cells [20], and for their presence among tumor infiltrating lymphocytes in various cancer types [21]. Not only the number but also the function of γδ T cells was altered in melanoma patients as well as in old healthy subjects. The in vitro expansion of γδ T cells, that represent one of the most relevant functional parameters for γδ T cells, was significantly reduced in young/adult and old melanoma patients, and in old healthy donors.
Under normal conditions, γδ T cells respond to antigen challenge by secreting large quantities of TNF-α and IFN-γ [16,21] which contribute to the activation of both specific and aspecific immune responses. In aged subjects we found an increased production of TNF-α by γδ T cells [11]. In this study, we show that the percentage of γδ T cells producing TNF-α was significantly reduced in young/adult and old melanoma patients in comparison with age-matched healthy subjects. Probably, the pro-inflammatory state which has been described in old ages [22], may represent a stimulus for the production of TNF-α in γδ T cells from aged subjects, differently with what occurs in old melanoma patients.
In conclusion, we demonstrate that the numerical and functional derangement of γδ T cells which we have found in melanoma patients, is not correlated with age of donors, and that old patients with cutaneous primary melanoma have an impairment of γδ T cells similar to that found in old healthy subjects. This evidence suggests a link between γδ T cell deterioration and the low protection against infections and tumor diseases present in the elderly, as well as the inefficacious immune defense against melanoma, both in young/adult and old ages.
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| 15686597 | PMC549530 | CC BY | 2021-01-04 16:36:32 | no | Immun Ageing. 2005 Feb 1; 2:2 | utf-8 | Immun Ageing | 2,005 | 10.1186/1742-4933-2-2 | oa_comm |
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Respir ResRespiratory Research1465-99211465-993XBioMed Central London 1465-9921-6-181571004510.1186/1465-9921-6-18ResearchPlasma antibodies against heat shock protein 70 correlate with the incidence and severity of asthma in a Chinese population Yang Miao [email protected] Tangchun [email protected] Longxian [email protected] Feng [email protected] Qingyi [email protected] Robert M [email protected] Institute of Occupational Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China2 Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China3 Laboratory of Cell and Developmental Genetics, Dept Medicine, Faculty of Medicine, Pav. C.E. Marchand, Université Laval, Québec, G1K 7P4, Canada2005 14 2 2005 6 1 18 18 24 11 2004 14 2 2005 Copyright © 2005 Yang et al; licensee BioMed Central Ltd.2005Yang 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 heat shock proteins (Hsps) are induced by stresses such as allergic factors and inflammatory responses in bronchi epithelial cells and therefore may be detectable in patients with asthma. However, the etiologic link between anti-Hsps and asthma (its severity and related inflammatory responses such as interleukin-4 and immunoglobulin E) has not been established. We determined whether antibodies against Hsp60 and Hsp70 were present in patients with asthma and evaluated their associations with risk and severity of asthma.
Methods
We determined the levels of anti-Hsp60 and anti-Hsp70 by immunoblot and their associations with risk and symptom severity of asthma in 95 patients with asthma and 99 matched non-symptomatic controls using multivariate logistic regression analysis.
Results
Compared to the controls, asthma patients were more likely to have detectable anti-Hsp60 (17.2% vs 5.1%) and anti-Hsp70 (33.7% vs 8.1%) (p ≤ 0.001). In particular, the presence of anti-Hsp70 was associated with a greater than 2 fold risk for asthma (adjusted OR = 2.21; 95% CI = 1.35~3.59). Furthermore, both anti-Hsp60 and anti-Hsp70 levels were positively correlated with symptom severity (p < 0.05) as well as interleukin-4 and immunoglobulin E (p < 0.05). Individuals with antibodies against anti-Hsp60 and anti-Hsp70 were more likely to have a family history of asthma (p < 0.001) and higher plasma concentrations of total immunoglobulin E (p = 0.001) and interleukin-4 (p < 0.05) than those without antibodies.
Conclusions
These data suggest that anti-Hsp60 and especially anti-Hsp70 correlate with the attacks and severity of asthma. The underlying molecular mechanisms linking antibodies to heat shock proteins and asthma remain to be investigated.
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Background
Heat shock proteins (Hsps) are highly conserved proteins inducible in response to a wide variety of stresses (such as exposure to heat) and pathological (viral, bacterial or parasitic infections, and inflammation) or physiological (growth factors, cell differentiation, and hormonal stimulation) stimuli [1,2]. There are six main Hsp families (i.e., Hsp110, Hsp90, Hsp/Hsc70, Hsp60, Hsp40, and Hsp10-30) categorized on the basis of their apparent molecular masses detected by sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE). Hsps are involved in various biological functions including 1) intracellular chaperones of naive, aberrantly folded or mutated proteins, 2) cytokines of signal transduction cascades involved in inflammatory response, and 3) cytoprotective agents in response to the aforementioned stress stimuli [1,3,4]. In addition, Hsps are also involved in transport of proteins and peptides through cellular compartments, and can bind to endogenous antigenic peptides and transport them to the major histocompatibility complexes [5,6]. This suggests that Hsps may modulate immune and inflammatory responses and may be involved in the pathogenesis and/or be markers for risk and prognosis of certain diseases including asthma [7-13], given that many of the stress stimuli mentioned above are factors that can induce attacks of asthma.
Asthma is a multifactorial and likely multigenic immune inflammatory disease of the upper airways, arising from complex interactions among environmental and genetic factors [14,15]. These factors may induce Hsp60 and Hsp70 in bronchi epithelial cells during the development of asthma [16]. Some Hsps present as self-antigens to the immune system, resulting in the production of autoantibodies in patients with inflammatory diseases and immune disorders after infections by bacteria, mycobacteria and Chlamydia [17-19]. Studies have demonstrated that these autoantibodies against Hsps were involved in the pathogenesis and/or prognosis of some diseases [8,20-23].
Up to now, few studies investigated possible associations of autoantibodies to human Hsps with the severity of asthma. In the present study, we determined the presence of autoantibodies to human Hsp60 and Hsp70 in 193 subjects with (n = 95) and without (n = 99) asthma by immunoblot analysis, and evaluated the associations of these autoantibodies with asthma severity and their correlation with interleukin-4 (IL-4) and immunoglobulin E (IgE) both involved in the development of asthma, by using multivariate logistic regression analyses.
Methods
Subjects and groups
This 95 patients with asthma (54 males and 41 females) and 99 healthy, age-matched non-asthmatic controls (64 males and 35 females) were residents living in the same geographic area. Patients and controls were from Wuchang, one of the three cities of Wuhan and were all of Han nationality. Their age ranged from 10 to 45 years old (Table 1). All 95 patients were diagnosed according to diagnostic criteria and principles of management of asthma proposed by the American Thoracic Society [24] and did not have other pulmonary, cardiovascular and gastro-duodenal diseases. A standardized questionnaire was completed for each individual by physicians with extensive experience in allergic and immune diseases to obtain demographic information and known risk factors for asthma including personal and family history of asthma and frequency of attacks. Selection criteria for the controls included the absence of any personal history of asthma. Health examination and physical sign findings such as wheezing and forced expiratory volume (FEV%Pre) were also recorded. Neither patients nor controls had any history of chronic diseases such as cancer, diabetes, cardiovascular diseases and gastro-duodenal diseases. Patients with asthma were grouped by symptom severity and medication use according to the 2002 Global Initiative for Asthma Guidance [25] as intermittent, mild persistent, moderate persistent and severe persistent. Venous blood was collected into heparinized tubes to separate plasma for the detection of anti-Hsp60 and anti-Hsp70 as well as IgE and IL-4. Plasma samples from patients and controls were stored in aliquots at -80°C and thawed only once immediately before the tests were performed. Written informed consent was obtained from patients and controls, and the study was approved by the Tongji Medical College Ethics Committee.
Table 1 Comparison of selected variables between patients with asthma and healthy controls
Patients with asthma (n = 95) Control subjects (n = 99) P value
Sex (M/F) 54/41 64/35 0.266
Age (years, mean ± SD) 28.2 ± 15.8 29.1 ± 13.9 0.680
Attack once a week or a day (yes/no) 95/95 0/99 <0.000
Sign (wheezing) (yes/no) 95/95 0/99 <0.000
FEV1%Pre 58.4 ± 18.9 96.5 ± 9.8 <0.001
IgE (IU/ml, mean ± SD) 486.9 ± 595.5 75.8 ± 124.9 <0.001
IL-4 (ng/L, mean ± SD) 31.7 ± 17.1 5.1 ± 3.8 <0.001
Determination of anti-Hsp60 and anti-Hsp70
Recombinant human Hsp60 and inducible Hsp70 were obtained through the expression of corresponding cDNA in NaCl-induced E. coli GJ1168 cells using pET30 (Novegen) as the expression vector [26]. Approximately 10–15 μg of recombinant human Hsp60 or Hsp70 was loaded on each SDS-PAGE gel without combs, separated, and transferred by electrophoresis to nitrocellulose membranes. The band containing Hsp60 or Hsp70 was cut into 2 mm × 3 mm pieces and marked with a small red dot on the protein side of the membrane. These membrane pieces were placed in individual wells of an ELISA plate, rinsed with PBS, saturated with 100 μl of blocking buffer (PBS containing 5% skim milk powder) for 1 h at 37°C with gentle agitation and washed with PBS-0.05% Tween 80 for 5 min. The plasma diluted 1:10, 1:20, 1:40 and 1:80 in 100 μl PBS containing 5% skim milk powder was incubated with the membrane pieces at 37°C for 2 h with gentle agitation. After washing the membrane pieces six times (10 min each) with 200 μl PBS-0.05% Tween 80, 100 μl of HRP labelled goat anti-human IgG (Sigma) in blocking buffer (1:2500) was added and the incubation continued at 37°C for 1 h. The membrane pieces were washed again six times (10 min) with 200 μl PBS-0.05% Tween 80. The presence of anti-Hsp60 or anti-Hsp70 was then revealed with DAB (3,3-diaminobenzidine tetra hydrochloride) for 3–5 min. A visible brown band on the membrane piece was regarded as a positive test and a colourless membrane as a negative test [21,22]. An example of the microblot technique is shown in Figure 1. Samples were scored in a double blind manner by three different investigators.
Figure 1 Purified recombinant Hsp70 was electrophoresed in SDS-PAGE, transferred to nitrocellulose membranes and cut into 2 – 3 mm wide strips. These were incubated with the plasma and the presence of antibodies to Hsp70 detected as described in Methods. Lane 1 – 3: positive; Lane 4: negative.
Detection of plasma IgE and IL-4
Total IgE was measured in plasma by using a fluorescence enzyme immunoassay kit from Bayer Company (Leverkusen, Germany). IL-4 was determined using a commercial enzyme-linked immunosorbent assay kit from OptEIA (Pharmingen, California, U.S.A). Each sample was tested in duplicate by a series of dilutions using a standard provided with the kit.
Statistical analyses
All the continuous data (e.g., age, FEV1, IGE, IL4) were presented as the mean ± standard deviation (SD) and analysed by the Student's t test. Frequency data (e.g., sex) were analysed by the Chi-square test. The associations were estimated by fitting univariate and multivariate logistic regression models. Statistical inferences were based on a significance level of 0.05. All analyses were two-sided and performed by using the Statistical Package for Social Sciences (SPSS) software (Version, Chicago).
Results
The patient and control groups comprised 56.8% and 64.6% of males, respectively, and had mean ages of 28.2 and 29.1 years, respectively (Table 1). All patients had regular asthma attacks and sign of wheezing, while none of the controls showed any of these signs. Asthma patients had a significantly lower FEV1%Pre than the controls (58.4 vs 96.5, p < 0.001). In addition, the asthma patients had significantly higher concentrations of total IgE and IL-4 than the controls (p < 0.001 for all comparisons).
Presence of anti-Hsp60 and anti-Hsp70 in plasma
We first looked for the presence of anti-Hsp60 and anti-Hsp70 in plasma at dilutions of 1:10 to 1:80 in the patients with asthma and in the matched controls. At a dilution of 1:10, asthma patients had a significantly higher positive rate of anti-Hsp60 than the controls (17.9% vs 5.1%, p = 0.001). In the case of Hsp70, antibodies were observed in 33.7% of patients as compared to 8.1% in the controls at a dilution of 1:10 (p < 0.001). At plasma dilutions between 1:20 to 1:80, the difference in the detection rates of both anti-Hsp60 and anti-Hsp70 between the patients and controls remained highly significant (Table 2). The combined detection rate of both anti-Hsp60 and anti-Hsp70) at the lower plasma dilution (1:10) was also globally much higher in the asthma patients (38.9%) than in the controls (9.1%).
Table 2 Comparison of positive rates of different titers for ant-Hsp60 and anti-Hsp70 in plasma of patients with asthma and healthy controls
Titers Patients with asthma (n = 95) Control subjects (n = 99) P value
n (%) n (%)
Anti-Hsp60 1:10 17 (17.9) 5 (5.1) 0.001
1:20 8 (8.4) 1 (1.0) 0.014
1:40 5 (5.3) 0 (0.0) 0.027
1:80 5 (5.3) 0 (0.0) 0.027
Anti-Hsp70 1:10 32 (33.7) 8 (8.1) <0.001
1:20 19 (20.0) 4 (4.0) <0.001
1:40 13 (13.7) 1 (1.0) <0.001
1:80 9 (9.5) 0 (0.0) 0.001
Anti-Hsps* 1:10 37 (38.9) 9 (9.1) <0.001
* Combined positive rate of anti-Hsp60 and /or anti-Hsp70 for titers 1:10–1:80.
Association between anti-Hsp60 and anti-Hsp70 with risk for asthma
Further analysis for asthma risk factors (sex, age, family history) and anti-Hsp60 and anti-Hsp70 was carried out by using a multivariate logistic regression model built with a forward stepwise selection procedure (p values for entry and removal, 0.10) and also based on clinical experience. The results in Table 3 show a statistically significant positive association between the presence of anti-Hsp70 and risk for asthma (p = 0.001), representing a greater than 2-fold increased risk for asthma (adjusted OR = 2.21; 95% CI = 1.35~3.59) (Table 3). However, no significant association of anti-Hsp60 with risk for asthma was found (p = 0.161).
Table 3 Multivariate logistic regression analysis of the association between anti-Hsp60 and anti-Hsp70 with risk for asthma
Variables* Adjusted Regression coefficient Standard error χ2 Value P value OR (95% CI)**
Constant -0.977 0.509 3.676 0.055
Sex 0.392 0.318 1.519 0.218 1.48 (0.79~2.76)
Age 0.017 0.109 0.026 0.872 1.02 (0.82~1.26)
Family history 0.602 0.219 8.215 0.085 2.01 (1.25~3.25)
Anti-Hsp60 0.459 0.328 1.965 0.161 1.58 (0.83~3.01)
Anti-Hsp70 0.794 0.248 10.224 0.001 2.21 (1.35~3.59)
*The dependent variable is the status of asthmas patient or control; the independent variables included Sex: 0 = male and 1 = female; Age: continuous variable in years; Family history: 0 = no and 1 = yes; Anti-Hsp60: 0 = negative and 1 = positive; Anti-Hsp70: 0 = negative and 1 = positive.
**OR, odds ratio, and CI, confidence interval.
Correlation of anti-Hsp60 and anti-Hsp70 with the severity of asthma
To understand the possible significance of the anti-Hsp60 and anti-Hsp70 in asthma, we analyzed the correlation of anti-Hsp60 and anti-Hsp70 with the severity of asthma. Table 4 shows that there was a significant increase of positive rates and dilutions of anti-Hsp60 and anti-Hsp70 as the severity of asthma increased. This table also shows that there were significantly positive correlations of anti-Hsp60 and anti-Hsp70 with the numerical categories of symptom severity (p < 0.05)
Table 4 Correlation of anti-Hsp70 and anti-Hsp60 with symptom severities
Symptom Severity No. Anti-Hsp70 No. (%) Anti-Hsp60 No. (%)
1:10 1:20 1:40 1:80 1:10 1:20 1:40 1:80
Step1: intermittent 30 2 (6.7) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0)
Step2: mild persistent 36 10 (27.8) 5 (13.9) 2 (5.6) 1 (2.8) 3 (8.3) 1 (2.8) 1 (2.8) 1 (2.8)
Step3&4 moderate & severe persistent** 29 20 (69.0) 14 (48.3) 11 (37.9) 8 27.6) 14 (48.3) 5 (17.2) 4 (14.0) 4 (14.0)
R value* 0.809 0.958 0.968 0.959 0.954 0.864 0.947 0.947
P value* 0.000 0.000 0.000 0.001 0.000 0.000 0.016 0.016
* The analyses of correlation of symptom severities with different dilutions of anti-Hsp70 and anti-Hsp60
**: there are two severe persistent patients with asthma
Differences in the levels of IgE and IL-4 between asthma patients with positive and negative anti-Hsps
We finally compared the levels of IgE and IL-4, two important known risk factors for asthma, in the 95 asthma patients who were either positive (37 patients) or negative (58 patients) for the presence of anti-Hsp60 and anti-Hsp70. The patients positive for anti-Hsps were more likely than the antibody-negative group of patients to report a family history of asthma (48.6% Vs 13.8%, p < 0.001) and had higher concentrations of total IgE (758.2 Vs 313.9, P = 0.001) and IL-4 (36.9 Vs 28.5, p = 0.019) (Table 5). Further analysis showed that the presence of either anti-Hsp60 or anti-Hsp70 or both was significantly correlated with the levels of IgE and IL-4 in asthma patients (Table 6) (p < 0.05). These preliminary data also indicated a positive correlation between the presence of these autoantibodies and the severity of the disease (r = 0.461, p < 0.001 for anti-hsp60 and r = 0.538, p < 0.001 for anti-Hsp70) (Table 6) as well as a statistically significant correlation between anti-Hsp70 and anti-Hsp60 (r = 0.485, p < 0.001) by using the rank correlation analysis.
Table 5 Differences in selected risk factors, IgE, and IL-4 between asthma patients with positive and negative anti-Hsps
Anti-Hsps(+) (n = 37) Anti-Hsps(-) (n = 58) P value
Sex (M/F) 23/14 31/27 0.403
Age (years, mean ± SD) 25.6 ± 15.6 29.3 ± 15.7 0.249
Family history (yes/no) 18/19 8/50 <0.001
IgE (IU/ml, mean ± SD) 758.2 ± 685.3 313.9 ± 458.2 0.001
IL-4 (ng/L, mean ± SD) 36.9 ± 17.2 28.5 ± 16.3 0.019
Table 6 Correlation between anti-Hsps, IgE, and IL-4 in 95 asthma patients
IgE IL-4 Anti-Hsp70 Anti-Hsp60 Anti-Hsps
r P r P r P r P r P
IL-4 0.701 <0.001
Anti-Hsp70 0.369 <0.001 0.222 0.010
Anti-Hsp60 0.262 0.010 0.259 0.011 0.485 <0.001
Anti-Hsps 0.366 <0.001 0.241 0.019 0.534 <0.001 0.814 <0.001
Asthma severity 0.330 0.001 0.236 0.022 0.461 <0.001 0.538 <0.001 0.417 <0.001
Discussion
The patients included in the present study had frequent asthmatic attacks, with signs of wheezing and higher levels of IgE and IL4 and low levels of FEV1 %Pre that are characteristics of asthma. We found that these asthma patients also had a significantly higher incidence of autoantibodies against combined Hsp60 and Hsp70 than the matched non-asthmatic controls and that, in particular, the presence of anti-Hsp70 was associated with asthma. Furthermore, there was a significant positive correlation between anti-Hsp60 and anti-Hsp70 and symptom severity of asthma. Thus among asthma patients, those who had positive anti-Hsp60 and anti-Hsp70 were more likely to report a family history of asthma and had higher levels of IgE and IL-4 than those without such antibodies. These findings provide evidence to support the hypothesis that the presence of anti-Hsp60 and especially anti-Hsp70 in asthma patients is strongly associated with asthma and the presence of these antibodies may predict symptom severity of asthma and provide new strategies for diagnosis and perhaps treatment of this disease.
Asthma is an immune and inflammatory disease, arising from complex interactions among genetic and environmental factors including bacterial or viral infection [14,15]. The production of autoantibodies against Hsps may result from genetic factors, infection, denaturation and release of Hsps as a result of cell damage, and the presence of antigen-specific lymphocytes [22,23].
Hsps are often the target of humoral and T cell-mediated immune responses to infection and may provide a link between the immune response to infection and autoimmunity caused by T lymphocyte cross-reactivity among Hsps of different origins [8,27,28]. It remains to be determined whether there is a relationship between the induction of Hsp70 and production of plasma autoantibodies against this Hsp and whether there is a cross-response of induced Hsps and autoantibodies against Hsps before and during the development of asthma. However, there are several lines of evidence that support an association between anti-Hsp60 and anti-Hsp70 and symptom severity in asthma patients. Firstly, as molecular chaperones, Hsps facilitate the synthesis, folding, assembly and intracellular trafficking of many functional proteins [3,29] and protect cells and organs against different types of damages [30,31] as observed in transient protection from ischemic injury in whole organs such as heart, brain and kidney [31-34]. Hsp70 has also been suggested to play an autoprotective role in asthma and lung injury [35-37]. Secondly, autoantibodies against Hsps may have significant roles in the pathogenesis and prognosis of diseases. For example, Shinghai et al reported the presence of antibodies against Hsps in patients with autoimmune liver diseases and suggested that the presence of anti-Hsp70 was an indicator for the disease activity of primary biliary cirrhosis [8]. Earlier results from our lab also suggested that the presence of such antibodies might help assess if workers are experiencing abnormal stress within their living and working environment [21-23]. Xu et al and Schett et al have shown that mycobacterial Hsp65 may serve as an antigen to instigate chronic immune responses characteristic of human atherosclerosis. These antibodies were sustained among patients with the most severe degree of underlying atherosclerosis and were demonstrated to predict 5-year mortality [11,12,20]. Thirdly, enhanced expression of Hsp70 has been detected in bronchi and alveolar macrophages of patients with asthma and correlated with intrapulmonary eosinophilia, airway inflammation, hyperresponsiveness of bronchi [38], and severity of the disease [14,35,39]. A cross-response of induced plasma and cellular Hsps and autoantibodies against Hsps in human, has been suggested to play a role in the development and prognosis of atherosclerosis [40,41]. However, it is still unknown whether there is a cross-response between the induction of Hsps in bronchi of patients with asthma and the presence of anti-Hsps and its biological effects.
The development of most immune diseases depends on the cytokines interleukin-2 and interferon-γ produced by type 1 helper T cells (Th1), whereas the development of allergic diseases requires IL-4 and IL-5, both of which are produced by type 2 helper T cells (Th2). The reciprocal down-regulation of Th1 cells by Th2 cytokines raises the possibility that these cytokines are involved in allergy or immunity [42]. IL-4 is one of the first signals for a switch to the synthesis of IgE and IL-4 binds to receptors on B cells to induce and amplify the synthesis of IgE [43]. There is a cross-linking of IgE with allergens to activate a series of response seen in asthma [44]. Epidemiological and clinical observations have linked IgE antibodies to the severity of asthma and the initial and sustained responses of the airways to allergens [45,46]. At this time, the molecular events that link antibody to Hsp70 to the production of IL-4 and IgE and the interaction among these factors in patients with asthma remain to be investigated.
Conclusions
The present study showed that there was a significant increase in positive rates of antibodies against Hsp60 and Hsp70 in patients with asthma and that the presence of autoantibodies against Hsp70 was associated with the severity of asthma. The presence of anti-Hsp70 associated with a high risk of asthma was also correlated with the family history of asthma and higher levels of total IgE and IL-4 in the patients. These results suggest that anti-Hsp70 correlate with the pathogenesis of asthma, but the precise underlying molecular mechanisms for these interactions remain to be established.
Authors' contributions
MY and LC performed the immunoblot assays, the acquisition of data and wrote the first draft of the manuscript. FW carried out the collection and statistical analysis of data. QW was responsible for the analysis and interpretation of data, and critical revision of the manuscript. TW and RMT initiated the project, designed the experiments, and wrote the manuscript.
Acknowledgements
We are particularly grateful to all individuals who voluntarily participated in the study and to the many members of the medical personnel of Hubei College of Traditional Medicine for their generous help in the examination and sampling of subjects. This study was supported by grants from the National Key Basic Research and Development Program (2002CB512905), the National Natural Science Foundation of China (NNSFC 30200227), an exchange Program between the Canadian Institutes of Health Research (CIHR) and the NNSFC (to TW, RMT) and an operating grant from the CIHR (to RMT).
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| 15710045 | PMC549531 | CC BY | 2021-01-04 16:36:27 | no | Respir Res. 2005 Feb 14; 6(1):18 | utf-8 | Respir Res | 2,005 | 10.1186/1465-9921-6-18 | oa_comm |
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BMC PharmacolBMC Pharmacology1471-2210BioMed Central London 1471-2210-5-21568354710.1186/1471-2210-5-2Research ArticleHesperidin, a citrus bioflavonoid, decreases the oxidative stress produced by carbon tetrachloride in rat liver and kidney Tirkey Naveen [email protected] Sangeeta [email protected] Anurag [email protected] Kanwaljit [email protected] Pharmacology division, University Institute of Pharmaceutical Sciences, Panjab University, Chandigarh-160014, India2005 31 1 2005 5 2 2 22 7 2004 31 1 2005 Copyright © 2005 Tirkey et al; licensee BioMed Central Ltd.2005Tirkey 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
CCl4 is a well-established hepatotoxin inducing liver injury by producing free radicals. Exposure to CCl4 also induces acute and chronic renal injuries. The present study was designed to establish the protective effect of hesperidin (HDN), a citrus bioflavonoid, on CCl4-induced oxidative stress and resultant dysfunction of rat liver and kidney.
Methods
Animals were pretreated with HDN (100 and 200 mg/kg orally) for one week and then challenged with CCl4 (2 ml/kg/s.c.) in olive oil. Rats were sacrificed by carotid bleeding under ether anesthesia. Liver enzymes, urea and creatinine were estimated in serum. Oxidative stress in liver and kidney tissue was estimated using Thiobarbituric acid reactive substances (TBARS), glutathione (GSH) content, superoxide dismutase(SOD), and Catalase (CAT)
Results
CCl4 caused a marked rise in serum levels of ALT and AST (P < 0.05). TBARS levels were significantly increased whereas GSH, SOD and CAT levels decreased in the liver and kidney homogenates of CCl4 treated rats. HDN (200 mg/kg) successfully attenuated these effects of CCl4
Conclusion
In conclusion, our study demonstrated a protective effect of HDN in CCl4 induced oxidative stress in rat liver and kidney. This protective effect of HDN can be correlated to its direct antioxidant effect.
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Background
Drug exposure, ionizing radiations and environmental pro-oxidant pollutants induce free radical formation. Lipid peroxidation initiated by free radicals is considered to be deleterious for cell membranes and has been implicated in a number of pathological situations. Carbontetrachloride (CCl4), an industrial solvent, is a well-established hepatotoxin [1-3]. Various Studies demonstrated that liver is not the only target organ of CCl4 and it causes free radical generation in other tissues also such as kidneys, heart, lung, testis, brain and blood [4-6]. It has also been reported that exposure to CCl4 induces acute and chronic renal injuries [7,8]. Case control studies and various documented case reports increasingly establish that hydrocarbon solvents produce renal diseases in humans [9].
Extensive evidence demonstrates that as a result of the metabolic activation of CCl4, •CCl4 and •Cl, are formed which initiate lipid peroxidation process. Vitamin E protected CCl4-induced liver injury indicating the role of oxidative stress in this model [10]. Studies also show that certain natural extracts containing antioxidants protect against the CCl4-induced increased lipid peroxide levels and impairment in hepatic GSH status [11].
Hesperidin is a flavanone glycoside abundantly found in sweet orange and lemon and is an inexpensive by-product of citrus cultivation [12]. Hesperidin is effectively used as a supplemental agent in the treatment protocols of complementary settings. Its deficiency has been linked to abnormal capillary leakiness as well as pain in the extremities causing aches, weakness and night leg cramps. Supplemental hesperidin also helps in reducing oedema or excess swelling in the legs due to fluid accumulation. A number of researchers have examined the antioxidant activity and radical scavenging properties of hesperidin using a variety of assay systems [13-16].
Thus the present study was designed to investigate the effect of HDN on CCl4-induced oxidative stress and resultant dysfunction of rat liver and kidney.
Results
Effect on liver enzymes
CCl4 caused a marked rise in serum levels of ALT (control = 45 IU/L) and AST (control = 135 IU/L) demonstrating a marked liver damage. Treatment with HDN decreases the elevated levels of ALT and AST in serum (P < 0.05)(Table 1). Both the doses of HDN also attenuated the CCl4-induced elevated levels of total bilirubin (control = 0.184 mg/dl).
Table 1 Effect of different doses of Hesperidin on CCl4 induced rise in AST, ALT and total bilirubin.
ALT (IU/L) AST(IU/L) Bilirubin total (mg/dl)
Control 100 100 100
CCl4 255.55 ± 23.66a 444.44 ± 22.56a 205.21 ± 11.66a
HDN (200) 112.81 ± 13.66 126.66 ± 28.66 108.15 ± 9.66
CCl4+HDN (100) 185.18 ± 17.56a,b 333.33 ± 29.66a,b 176.63 ± 15.29a,b
CCl4+HDN (200) 144.44 ± 15.22a,b,c 244.44 ± 22.66a,b,c 149.45 ± 12.45a,b,c
Values are expressed as percent response compared to control rats. a = Statistical significant at P < 0.05 as compare to control, b = Statistical significant at P < 0.05 as compare to CCl4, c = Statistical significant at P < 0.05 as compare to CCl4+ HDN(100)
Effect on hepatic and renal TBARS levels
CCl4 challenge caused a marked lipid peroxidation in both liver (control = 1.5 micromoles/mg protein) and kidney (control = 33.86 nmoles/mg protein). Both the doses of HDN decreased the level of lipid peroxidation in liver, but in the kidney, no effect on lipid peroxidation was seen with 100-mg/kg dose, and only the higher dose of HDN (200 mg/kg) could attenuate the increased level of lipid peroxidation (P < 0.05) (Fig 1). 7-day oral feeding of HDN per se (200 mg/kg) did not result in a significant alteration of either hepatic or renal TBARS levels.
Figure 1 Effect of different doses of Hesperidin on CCl4 induced lipid peroxidation in rat liver and kidney. Values are expressed as percent response compared to control rats. a = Statistical significant at P < 0.05 as compare to control, b = Statistical significant at P < 0.05 as compare to CCl4, c = Statistical significant at P < 0.05 as compare to CCl4+ HDN(100)
Effect on the glutathione levels in CCl4 treated rats
CCl4 administration markedly decreased the levels of reduced glutathione in both the liver (control = 35.99 micromoles/mg protein) and kidneys (control = 27.99 micromoles/mg protein) demonstrating oxidative stress. HDN (200 mg/kg) per se did not produce any change in the levels of reduced glutathione either in liver or kidney. HDN (100 mg/kg) showed no effect on the levels of reduced glutathione either in liver or kidney in CCl4 treated rats whereas HDN (200 mg/kg) significantly ameliorated CCl4-induced depletion of GSH in both liver and kidney (P < 0.05)(Fig-2). HDN per se (200 mg/kg) did not result in a significant alteration of either hepatic or renal GSH levels.
Figure 2 Effect of different doses of Hesperidin on CCl4 induced depletion in GSH levels in rat liver and kidney. Values are expressed as percent response compared to control rats. a = Statistical significant at P < 0.05 as compare to control, b = Statistical significant at P < 0.05 as compare to CCl4, c = Statistical significant at P < 0.05 as compare to CCl4+ HDN(100)
Effect on the antioxidant enzymes in liver and kidneys in CCl4 treated Rats
CCl4 challenge significantly decreased the levels of SOD and catalase in both liver (SOD: control = 25.66 U/mg protein; Catalase: control = 0.32 K/min) and kidneys (SOD: control = 99.22 U/mg protein; Catalase: control = 0.32 K/min). HDN per se (200 mg/kg) had no effect on these enzymes either in liver or in kidneys. HDN (100 mg/kg) failed to improve the levels of SOD or catalase either in liver or kidneys of CCl4 administered rats but HDN (200 mg/kg) significantly increased the levels of both enzymes in liver and kidneys of CCl4 treated rats (P < 0.05)(Fig-3 and 4). 7-day oral feeding of HDN per se (200 mg/kg) did not result in a significant alteration of any of these antioxidant enzymes either in liver or kidney.
Figure 3 Effect of different doses of Hesperidin on CCl4 induced depletion in SOD levels in rat liver and kidney. Values are expressed as percent response compared to control rats. a = Statistical significant at P < 0.05 as compare to control, b = Statistical significant at P < 0.05 as compare to CCl4
Figure 4 Effect of different doses of Hesperidin on CCl4 induced depletion in Catalase levels in rat liver and kidney. Values are expressed as percent response compared to control rats. a = Statistical significant at P < 0.05 as compare to control, b = Statistical significant at P < 0.05 as compare to CCl4
Discussion
CCl4-induced lipid peroxidation is highly dependent on its bioactivation to the trichoromethyl radical and trichloromethyl peroxy radical [17-19]. It is well known that CCl4 is activated by the cytochrome P450 system. The initial metabolite is the trichloromethyl free radical, which is believed to initate the biochemical events that ultimately culminate in liver cell necrosis[20,21]. The trichloromethyl radical can form covalent adducts with lipids and proteins, interact with O2 to form a tricholoromethyl peroxy radical or abstract hydrogen atoms to form chloroform [22]. Other products include conjugated dienes, lipid hydroperoxides, malonaldehyde-like substances, and other short-chain hydrocarbons [23-25]. In response to hepatocellular injury initiated by the biotransformation of CCl4 to reactive radicals, "activated" Kupffer cells in liver respond by releasing increased amounts of active oxygen species and other bioactive agents [26].
Protective effects of various natural products in CCl4 hepatotoxicity have been reported [27]. Studies done with Ginseng showed that the antioxidant property of ginsenosides contributes to protection against CCl4 induced hepatotoxicity in rats [28]. In the present study, CCl4 induced a severe hepatic damage as represented by markedly elevated levels of ALT, AST and bilirubin coupled with a marked hepatic oxidative stress. CCl4-induced generation of peroxy radicals and O2-• leads to inactivation of catalase and SOD. We too observed that CCl4 challenge significantly decreased the levels of SOD and catalase in liver and kidney. Recently, Szymonik-Lesiuk et al [2] have shown that CCl4 intoxication can lead to alteration in gene expression and depletion of SOD and catalase levels in kidney and heart. Oxidative stress causes depletion of intracellular GSH, leading to serious consequences. HDN administration ameliorated the increased level of lipid peroxidation after CCl4 treatment. Interestingly, only the higher dose of HDN (200 mg/kg) was able to show improvement in the levels of endogenous antioxidant enzymes (SOD and catalase) and GSH in liver. Improvement of hepatic GSH levels in HDN-treated rats in comparison to CCl4 intoxicated rats demonstrates the antioxidant effect of HDN.
We failed to observe any effect of CCl4 on renal function. Neither BUN nor serum creatinine levels increased after CCl4 administration (data not shown). Studies by Zimmerman et al [29] also did not report any rise in BUN levels even after chronic treatment of CCl4 in nephrectomized rats. They found an increased frequency of glomerulosclerosis and tubulointerstitial alterations in rats with reduced renal mass on CCl4 administration thereby indicating nephrotoxicity on long-term CCl4 administration in rats. These findings raise the possibility that renal disease in man is related to hydrocarbon solvent exposure and may also be potentiated by concomitant renal disease or impaired renal function. Ogawa et al [30] also reported that chronic renal injuries and BUN elevations developed in Balb/c mice only after 12 weeks of CCl4 intoxication. On the contrary, we estimated the renal function just after 48 hrs of CCl4 challenge. Thus this brief period might not be sufficient to demonstrate any rise in serum BUN and creatinine levels. Though renal function did not alter after 48 hrs of CCl4 administration but even this short period of exposure led to a significant oxidative stress in kidneys. Fadhel and coworkers [31] had also reported increased levels of renal TBARS in rats after CCl4 exposure which could be improved by black tea extract. Similar observations were also reported with certain Indian ayurvedic Indian preparations [32].
HDN treatment has been previously demonstrated to improve GSH levels in liver and kidneys of diabetic rats and a decrease in levels of 8-hydroxydeoxyguanosine (8-OHdG), a marker of DNA fragmentation, in the urine of diabetic rats [33]. HDN in combination with Diosmin has also been shown to inhibit the reactive oxygen radicals production in Zymosan-stimulated human polymorphonuclear neutrophils [34]. Thus HDN has been shown to reduce oxidative stress in various in-vivo and in-vitro studies.
Conclusions
In conclusion, our study demonstrated that CCl4 induces a marked oxidative stress in rat liver and kidney, which is amenable to attenuation by HDN. This protective effect of HDN can be correlated directly to its antioxidant property.
Methods
Animals
Male wistar rats (150 g–200 g), bred in the central animal house of Panjab University (Chandigarh, India) were used. The animals were housed under standard conditions of light and dark cycle with free access to food (Hindustan Lever Products, Kolkata, India) and water. The experimental protocols were approved by the Institutional Ethical Committee of Panjab University, Chandigarh.
Drugs
Chemicals employed in these studies were reagent grade. Carbon tetrachloride (E Merck, India) was administered subcutaneously in olive oil Hesperidin (Sigma chemical USA) was suspended in 0.5% sodium carboxy methyl cellulose (CMC) and administered orally.
Experimental groups and protocol
Animals were divided into following groups, each containing 6–8 animals: Control: These animals received a vehicle for HDN (i.e. CMC) by oral route for eight days and on 8th day, they were administered the subcutaneous injection of olive oil. CCl4 group: These animals received vehicle for 10 days and were challenged with CCl4 2 ml/kg/s.c. (40% v/v in olive oil) on 8th day. In the preliminary studies done in our lab, we observed a very high mortality rate (50–60%) when CCl4 was administered interaperitoneally. Thus we adopted the subcutaneous route of CCl4 administration as reported in the literature [35]. With this route and dose of CCl4, the mortality rate reduced to about 20%(1-2/8 animal) HDN group: These rats received only HDN 200 mg/kg/p.o. daily for 10 days CCl4+ HDN (100): Rats received HDN continuously for 8 days. On eight day just after HDN treatment they received CCl4 2 ml/kg/s.c in olive oil. HDN was further continued for 2 more days. CCl4+ HDN (200): This group is similar to the above one except that the dose of HDN administered was 200 mg/kg/p.o. On the 10th day, animals were sacrificed 2 hr, after the last dose of HDN and blood was collected, by carotid bleeding, in centrifuge tubes. Serum was separated and was used freshly for the assessment of renal and liver function tests. Both the kidneys and the liver were quickly harvested and immediately stored at -20°C till further biochemical estimations.
Assessment of renal functions
Before sacrifice, rats were kept individually in metabolic cages for 24 h to collect urine for estimation of renal function. Serum samples were assayed for blood urea nitrogen (BUN), urea clearance, serum creatinine & creatinine clearance by using standard diagnostic kits (Span Diagnostics, Gujarat, India).
Assessment of liver function
Serum alanine aminotransferase (ALT) and serum aspartate aminotransferase (AST) were estimated by International Federation of Clinical Chemistry [36] (ERBA test kits). Serum bilirubin was estimated by Diazo method [37] (ERBA test kits).
Assessment of oxidative stress
Post mitochondrial supernatant preparation (PMS)
Kidneys and liver were, perfused with ice cold saline (0.9% sodium chloride) and homogenized in chilled potassium chloride (1.17%) using a homogenizer. The homogenates were centrifuged at 800 g for 5 minutes at 4°C to separate the nuclear debris. The supernatant so obtained was centrifuged at 10,500 g for 20 minutes at 4°C to get the post mitochondrial supernatant which was used to assay catalase and superoxide dismutase (SOD) activity.
Estimation of lipid peroxidation
The malondialdehyde (MDA) content, a measure of lipid peroxidation, was assayed in the form of thiobarbituric acid reacting substances (TBARS) by method of Okhawa et al. [38] Briefly, the reaction mixture consisted of 0.2 ml of 8.1% sodium lauryl sulphate, 1.5 ml of 20% acetic acid solution adjusted to pH 3.5 with sodium hydroxide and 1.5 ml of 0.8% aqueous solution of thiobarbituric acid was added to 0.2 ml of 10%(w/v) of PMS. The mixture was brought up to 4.0 ml with distilled water and heated at 95°C for 60 minutes. After cooling with tap water, 1.0 ml distilled water and 5.0 ml of the mixture of n-butanol & pyridine (15:1 v/v) was added and centrifuged. The organic layer was taken out and its absorbance was measured at 532 nm. TBARS were quantified using an extinction coefficient of 1.56 × 105 M-1/cm-1 and expressed as nmol of TBARS per mg protein. Tissue protein was estimated using Biuret method of protein assay and the TBARS content expressed as nanomoles per milligram of protein.
Estimation of reduced glutathione
Reduced glutathione (GSH) in the kidneys and liver was assayed by the method of Jollow et al [39]. Briefly, 1.0 ml of PMS (10%) was precipitated with 1.0 ml of sulphosalicylic acid (4%). The samples were kept at 4°C for at least 1 hour and then subjected to centrifugation at 1200 g for 15 minutes at 4°C. The assay mixture contained 0.1 ml filtered aliquot and 2.7 ml phosphate buffer (0.1 M, pH 7.4) in a total volume of 3.0 ml. The yellow colour developed was read immediately at 412 nm on a spectrophotometer.
Estimation of SOD
SOD activity was assayed by the method of Kono et al.[40] The assay system consisted of EDTA 0.1 mM, sodium carbonate 50 mM and 96 mM of nitro blue tetrazolium (NBT). In the cuvette, 2 ml of above mixture, 0.05 ml hydroxylamine and 0.05 ml of PMS were taken and the auto-oxidation of hydroxylamine was observed by measuring the absorbance at 560 nm.
Estimation of catalase
Catalase activity was assayed by the method of Claiborne et al [41]. Briefly, the assay mixture consisted of 1.95 ml phosphate buffer (0.05 M, pH 7.0), 1.0 ml hydrogen peroxide (0.019 M) and 0.05 ml PMS (10%) in a final volume of 3.0 ml. Changes in absorbance were recorded at 240 nm. Catalase activity was calculated in terms of k minutes-1.
Statistical analysis
Results were expressed as mean ± SEM. The intergroup variation was measured by one way analysis of variance (ANOVA) followed by Fischer's LSD test. Statistical significance was considered at p < 0.05. The statistical analysis was done using the Jandel Sigma Stat Statistical Software version 2.0.
Authors' contributions
Naveen Tirkey, Sangeeta Pilkhwal and Anurag did all the biochemical estimations in kidney and liver. Kanwaljit Chopra did the data interpretation after statistical analysis and contributed in manuscript preparation.
Acknowledgements
The grants from University Grants commission for conducting the study is gratefully acknowledged. The authors also like to express their thanks to Ms Saraswati Gupta, Senior Technical officer, University Institute of Pharmaceutical sciences Panjab University Chandigarh for her help in conducting the spectrophotometric analysis.
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| 15683547 | PMC549532 | CC BY | 2021-01-04 16:32:59 | no | BMC Pharmacol. 2005 Jan 31; 5:2 | utf-8 | BMC Pharmacol | 2,005 | 10.1186/1471-2210-5-2 | oa_comm |
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Int J Health GeogrInternational Journal of Health Geographics1476-072XBioMed Central London 1476-072X-4-51570519610.1186/1476-072X-4-5MethodologyFrom wealth to health: modelling the distribution of income per capita at the sub-national level using night-time light imagery Ebener Steeve [email protected] Christopher [email protected] Ajay [email protected] Christopher C [email protected] Evidence and Information for Policy, World Health Organization, Av. Appia 20, 1211 Geneva 27, Switzerland2 Global Health Initiative, Harvard University, 104 Mt. Auburn Street, Cambridge, MA 02138, USA3 NOAA, National Geophysical Data Center, Office of the Director, 325 Broadway Boulder, Colorado 80303, USA2005 10 2 2005 4 5 5 16 12 2004 10 2 2005 Copyright © 2005 Ebener et al; licensee BioMed Central Ltd.2005Ebener 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
Sub-national figures providing information about the wealth of the population are useful in defining the spatial distribution of both economic activity and poverty within any given country. Furthermore, since several health indicators such as life expectancy are highly correlated with household welfare, sub-national figures allow for the estimation of the distribution of these health indicators within countries when direct measurement is difficult.
We have developed methods that utilize spatially distributed information, including night-time light imagery and population to model the distribution of income per capita, as a proxy for wealth, at the country and sub-national level to support the estimation of the distribution of correlated health indicators.
Results
A first set of analysis are performed in order to propose a new global model for the prediction of income per capita at the country level. A second set of analysis is then confirming the possibility to transfer the country level approach to the sub-national level on a country by country basis before underlining the difficulties to create a global or regional models for the extrapolation of sub-national figures when no country data set exists.
Conclusions
The methods described provide promising results for the extrapolation of national and sub-national income per capita figures. These results are then discussed in order to evaluate if the proposed methods could not represent an alternative approach for the generation of consistent country specific and/or global poverty maps disaggregated to some sub-national level.
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Background
Economy, income and poverty do affect and are affected by population's health in many ways.
At broad scale, the macro relationship between life expectancy and the gross national product (GNP) is well known and has been presented in different publications [1].
At a smaller scale a very robust relationship exist between an adult individual's income and that individual's health. This has been confirmed in the review done by Benzeaval and Judge [2] of sixteen studies coming from four different countries and for which the authors conclude by saying that: "All of the studies that include measures of income level find that it is significantly related to health outcomes."
The conclusion of another study performed in Tanzania [3] shows that the poorest tercile of the households in this country are the ones presenting the poorest health status indicators confirming the relationship between poverty and health status. The same study also confirms the effect of the geographic distribution of poverty on the health status of the population.
In return, high level of poverty also becomes an important factor of vulnerability for the population which becomes more exposed to diseases, especially infectious ones.
By identifying the poorest area within a country it becomes possible to plan more effective intervention aimed at improving the health status of the population and therefore potentially reducing their level of poverty. As poverty tends to be clustered in specific places it is important to have access to disaggregated data. In addition to that, aggregated, national-level poverty data tends to mask sub-national variations [4].
The development of variables that can be used as indicators of economic status is not straightforward. Even the measurement of the most basic of economic variables – such as national income levels – is fraught with problems. This reliable measurement of income is particularly problematic for low-income countries, given the lack of well-developed national income accounting methods and the large size of the "informal" sector in these economies. These problems are compounded when information is sought on the spatial and temporal changes in economic activity [5]. Recent advances in measurement and estimation techniques, though, have helped substantially. So much so that it is now routine for national statistical offices of almost all countries to report on national economic activity numbers, as well as for international organizations such as the World Bank and the International Monetary Fund to report their own versions of "adjusted" income numbers (both in local currency units as well as in purchasing-power parity terms).
However, the use of self-reported income for measurement of economic status is widely regarded to be problematic [6]. In a cross-section, income for any given household tends to be a relatively noisy indicator of its underlying longer-term economic status. From an accounting point of view, income numbers for subsistence-farming and self-employed households are particularly troublesome. In addition, respondents often perceive income-related items as being invasive and this can lead to non response bias. For these and other reasons, survey income has tended to be significantly under-reported and inconsistent with income estimated using national accounts statistics. Survey-based estimates of income are often lower than those of consumption for the same household, even though national accounts data show aggregate positive savings rates [7]. The degree of under-reporting in income has been found to vary by income deciles: lower-income households tend to be more likely to under-report than higher-income households. In several instances, poorer household have been found to report expenditure levels that far exceed reported income levels – possibly because of greater underreporting of income than of expenditure – indicating the implausible implication that the poor are chronic dissavers [8].
For all these reasons, most of the national household surveys, such as the World Bank's Living Standards Measurement Study (LSMS) [9] and many national surveys prefer to measure consumption and not income as the indicator of household welfare.
If sub-national level consumption figures are therefore available for most low income countries, through the use of these tools, the data they are producing is not comparable over countries making it impossible, for the moment, to build a consistent global map of poverty, or food insecurity, disaggregated to some sub-national level. In this context the growing uses of Geographic Information Systems (GIS) as well as the generation of new geocoded data sets might offer new perspectives in order to produce globally consistent poverty maps and help predicting the distribution of welfare at the sub-national level when reliable sub-national data are still not available. As the consumption indicators produced are not comparable over countries this attempt is done using income per capita expecting that this indicator might be comparable.
In terms of data, satellite imagery is offering great potential for global data sets depicting weather patterns plus the physical and biological environment. If most of the data sensed concerns bio-physical parameters (e.g. clouds and vegetation...) there is one parameter, sensed by some satellites that can be used in the socio-economic context: night-time light.
In their publications on the use of this parameter, Elvidge et al. [[10-12] and [13]] compares country level surface area with detected lighting at night (area lit) with population, energy usage, and economic activity. They found a strong correlation between area lit and Gross Domestic Product (GDP) for 21 countries as illustrated in Figure 1.
Figure 1 Area lit (km2) versus 1994 Gross Domestic Product. GDP estimates for 21 countries on a log-log plot (extracted from Elvidge et al., 12)
More recently, an attempt to obtain a global map of socio-economic parameters at the sub-national level has been made by Doll et al. [14]. In their approach, the country-level relationship found between area lit and Gross Domestic Product (GDP) was applied to a 1° × 1° resolution grid. This research showed a potential solution for obtaining sub-national distribution map for this parameter.
The methodology presented in this paper follows a different approach, using other parameters in combination with light in order to directly predict GDP per capita and adjust the results to specific conditions. It also demonstrates the role played by other environmental and socio-economic factors on this prediction.
Results and discussion
The analysis performed at both the country and sub-national levels as well as the results obtained are presented in the coming sections.
The country level analysis
The objective of the country level analysis is to go beyond the observations done so far [[10-13] and [14]] and to see if an other component or combination of the light information (number of cells with light, total frequency of observation, mean frequency of observation) with other parameters could provide a model for the prediction of income per capita at the country level.
The relationship between area lit and GDP shown by Elvidge et al. in 1997 [10] has already been confirmed for a larger number of countries by Doll et al. in 2000 [14] and Elvidge et al. one year later [13].
Starting from this result, a new set of analysis is performed using the different parameters described in the methods section. For the parameters stored in grids (light and surface area) the GIS tool is used in order to extract the figures based on the country delimitation.
The first set of result are reported in Table 1 and present the correlation factors existing between the different parameters expressed in log for 171 countries with:
Table 1 Correlation factor between the parameters used for the country level analysis
Logdp Logdppc Lopopun Losurfli Lotofre Lonbrpix lomeanf
Logdppc 0.4295
Lopopun 0.8708 -0.0700
Losurfli 0.9340 0.3963 0.8159
Lotofre 0.9374 0.4679 0.7808 0.9906
Lonbrpix 0.9318 0.4249 0.7980 0.9975 0.9927
Lomeanf 0.4413 0.5134 0.2079 0.3728 0.48 0.3709
Losurfco 0.6723 -0.1513 0.8250 0.7442 0.6842 0.7265 -0.0164
- Logdp: log of the GDP figure (expressed in ppp)
- Logdppc: log of the GDP per capita figures (expressed in ppp)
- Lopopun: log of the UN population figures
- Losurfli: log of the area lit (km2)
- Lotofre: log of the total frequency of light observation
- Lonbrpix: log of the number of cells being highlighted
- Lomeanf: log of the mean frequency of light observation
- Losurfco: log of the surface area of the country (km2)
The logarithm of all the parameters has been used in this analysis for the following reason:
a) the relationship is expected to be linear in logs,
b) if there is heteroskedasticity, the log form is one way to remove the problem,
c) the parameters can be interpreted as elasticities if both the dependent and the independent variables are in logs
The following observation can then be extracted from Table 1:
1) Three of the light parameters are correlated to each other (lotofre, lonbrpix and losurfli). The forth one (lomeanf), not correlated to the previous ones, seems to contain a different information content connected to light,
2) Apart from the mean frequency of light observation all the parameters are more highly correlated with GDP rather than with GDP per capita,
3) There is no significant difference in the values obtained for expressing the correlation between the first three light parameters (lotofre, lonbrpix and losurfli) and GDP. Lomeanf shows a lower correlation with GDP,
4) Population presents a high correlation with GDP but none with GDP per capita. The same is observed for the surface area of the country,
5) The correlation between the first three light parameter mentioned under point 1) and population is good which is not the case with the log of the mean frequency of light observation,
6) A high correlation exists between the surface area of the country and the population.
The above-mentioned observations seem to indicate that the high correlation coefficient observed between the 3 light parameters (lotofre, lonbrpix and losurfli) and GDP is explained by the strong correlation between these parameters and population and the one between population and GDP. On the contrary the mean frequency of light observation shows a stronger correlation with GDP per capita. By predicting GDP per capita instead of GDP we therefore avoid any circularity in the model.
Based on all the observation made it is decided to consider the use of the following variable in order to model GDP per capita at the country level:
- the mean frequency of light observation as this variable present the highest correlation with GDP per capita,
- the total frequency of light observation as this parameter provides the highest correlation with GDP per capita among the other three light parameters found to be correlated to each other (lotofre, lonbrpix and losurfli). This parameter also contains more variability than the number of cells or the area lit which is an advantage when working with small areas that could be completely highlighted.
- the total population and surface area of the country. Even if these parameters do not provide a good correlation with GDP per capita they are a necessary adjustment factor for the light and population variable (density).
As the correlation between GDP per capita and the different variables may not be linear the correlation existing between the log of GDP per capita and the square of the log of these variables is analysed. This analysis shows that the square improves the prediction only for the two selected light parameters (total frequency and mean frequency of light observation) which are used as additional variables, the square of the log of population and the surface area of the country being not used.
From that point, 63 combination of the 6 variables kept for the analysis are tested in order to find a regression for modelling the log of GDP per capita at the country level. This is firstly done using the full data set, then trying to analyse the role of the climate and the one of the GDP composition by sector. Table 2 contains the information regarding the regression based on the best combination of significant variables (P > | t | < 50) using the full data set (171 countries).
Table 2 Information about the best regression obtained for the country level data set with F (5, 165) = 156.46, Prob > F = 0.0000, R-squared = 0.8258, Adj R-squared = 0.8205 and Root MSE = 0.20552
logdppc Coef. Std. Err. t P > |t| [95% Conf. Interval]
lopopun -0.4665182 0.038419 -12.14 0.000 -0.5423734 -0.39066
lotofre2 0.0574057 0.002592 22.15 0.000 0.0522876 0.062524
lomeanfr -2.677929 1.115337 -2.40 0.017 -4.880102 -0.47576
lomeanf2 0.9731717 0.364591 2.67 0.008 0.2533075 1.693036
losurfun -0.1320768 0.028785 -4.59 0.000 -0.1889105 -0.07524
_cons 7.465969 0.855281 8.73 0.000 5.77263 9.154675
The plot of the observed log of GDP per capita versus the predicted figures obtained with this regression as well as the plot presenting the residuals is reported in Figure 2.
Figure 2 Prediction of income per capita at the country level (in log). a) Plot of the observed log of GDP per capita versus the predicted ones obtained with the regression in Table 2 b) Plot presenting the residuals versus the log of GDP per capita for the same regression
The application of this model results in a significant over estimation of GDP per capita for 10 countries (United republic of Tanzania, Malawi, Zambia, Sao Tome and Principle, Tajikistan, Azerbaijan, Uzbekistan, Kyrgyzstan, Yugoslavia and Egypt) and an under estimation for most of the high income countries presenting a GDP per capita figure higher than 12'500 US$. This can be better visualized by transforming the log of GDP per capita into GDP per capita figures for the 171 countries, creating a new graph (Figure 3) similar to the one shown in Figure 2a.
Figure 3 Prediction of income per capita at the country level. Plot report the predicted versus the observed GDP per capita for the 171 country level data set using the model reported in Table 2
Figure 3 shows that the development of the lightning infrastructure follows the economic development within a country until reaching a certain level of development after which the model is underestimating income per capita for many countries. This is explained by the fact that from this level, an increment of income is not necessarily reflected in the spatial extension of the outdoor lightning system or the creation of infrastructure that requires specific lightning at night (highways, factories, etc.).
There are however some countries for which the model gives a good estimate of GDP per capita, such as Qatar (QAT), United Arab Emirates (ARE); Finland (FIN), Sweden (SWE), Monaco (MCO), Canada (CAN), Norway (NOR). Finally, the model gives a clear overestimation of GDP per capita for the United States of America (USA).
The following explanation can be given for these countries:
- "over lighting" due to an above-average wealth of the country (e.g. for Qatar, the United Arab Emirates and maybe Monaco),
- Two explanations are possible regarding the Nordic European countries that appears in this list (Norway, Sweden and Finland) connected to the fact that the night-time light grid that is used in the context of this work is based on data collected during winter: a) specific climatic conditions during winter requiring excessive lighting of the infrastructure which may be at the origin of their location in the graph (the same observation is likely to be done for Canada). b) snow may be at the origin of an over estimation of income in these countries as snow makes lights look bigger and brighter than they appear in the no-snow condition.
- The position of the United States in the graph is related to the fact that the square of the log of the total frequency of light observation is the highest observed in the entire sample. Several hypothesis are proposed in order to explain this situation. This includes the fact that light is more easily spread due to the big habitable surface, electricity is cheap and the road network very wide.
The Root Mean Square Error (Root MSE) observed when applying this model is of 4000 US$. 27 countries are presenting an error higher than this value. The 5 countries with the highest error are: Luxembourg, Switzerland, Austria, Australia and Germany. The 5 lowest error are observed for: The Federal State of Micronesia, Burkina Faso, Haiti, Mali and Rwanda.
Trying to improve the prediction of GDP per capita at the country level by including other variables we can observe that grouping the countries according to their agricultural level is giving better results than grouping them by climatic type.
The figures given by the World Bank [15] or by the CIA world factbook 2001 [16] allows a decomposition of the economy into 3 sectors: agriculture, industry and services, the last two being the sectors that are the source of most of the light production. Thus the type of economy within a country has an important effect on the development of the infrastructure and then indirectly on their level of lighting. When the percentage of GPD due to the agricultural sector (Figure 4) is used to group the countries there is an improvement in the specific regression for each group.
Figure 4 Repartition of the GDP per capita in function of the percentage of GDP due to agriculture
In Figure 4, we can observe a continuous distribution of the points with breaks indicated by the vertical and horizontal lines. These breaks (5, 10 and 25 %) are therefore used for grouping the countries (170 countries used for this analysis as 1 variable is missing for 1 country part of the initial sample) and the same approach than the one described earlier is applied in order to find the regression giving the best prediction for each group as follow:
- below 5 % (38 countries): lopopun, lotofre, losurfun (Adj R-squared: 0.5785)
- between 5 and 10 % (28 countries): lopopun, lotofre, losurfun (Adj R-squared: 0.6289)
- between 10 and 25 % (55 countries): lopopun lotofre2 losurfun (Adj R-squared: 0.5463)
- above 25 % (49 countries): lopopun lotofre losurfun (Adj R-squared: 0.5512)
We can observe the same combination of variables (lopopun lotofre losurfun) in 3 of the 4 grouping but the coefficients for each of these variables are significantly different.
Figure 5 shows the plot of the observed log of GDP per capita versus the predicted figures obtained as well as the plot presenting the residuals when applying these regressions to the respective group while Figure 6 shows the same graph than the one reported in Figure 5a without the logarithmic function.
Figure 5 Prediction of income per capita at the country level (grouping by agricultural level in log). a) Plot of the observed versus the predicted log of GDP per capita figures obtained when applying the best model by agricultural level b) Plot presenting the residuals versus the log of GDP per capita for the same regression
Figure 6 Prediction of income per capita at the country level (grouping by agricultural level). Plot of the predicted GDP per capita versus the observed one for the 170 countries of the data set when applying the best model found for each of the GDP agricultural contribution group.
From the 170 countries used in this analysis, 33 countries are presenting an error higher than the Root MSE (2877 US$). The 5 countries presenting the highest error are: Luxembourg, Australia, Switzerland, New Zealand and Singapore. The 5 lowest error are observed for: Chad, Somalia, Bangladesh, Iran and the Republic of Moldova.
The sub-national level analysis
The sub-national level analysis has two objectives: to examine the possibility of applying the country level approach to the sub-national level on a country-by-country basis and to explore the possibility of generating global or regional models to be used for countries where sub-national data are either missing or are deemed to be unreliable.
This analysis is based on the log of the same parameters successfully used at the country level. The population, total frequency and mean frequency of light observation as well as the surface area figures are extracted from the grids described in the methods section using the boundaries of corresponding sub-national administrative or statistical units.
In order to keep the consistency with the values used for country level analysis, the sub-national figures for the population and the total frequency of light observation are adjusted by applying an homogeneous factor and rounding the resulting figures to the closest integer number.
Transferring the country level approach to the sub-national level
The analysis of the correlation factor existing at the sub-national level between each variables and GDP per capita (expressed in log) shows significant heterogeneity from one country to another. For few countries, some variables even appear as being not significant for the prediction of GDP per capita at the sub-national level. The list of variables observed in the country specific regression giving the best prediction vary therefore also from one country to another. In this case we do not look for models that were based on significant variables but take the one that is presenting the highest Adj R-squared value as the number of observation is generally low. The Adj R-squared obtained for these regressions varies from 0.2492 for The Netherlands to 1.00 for Portugal.
This analysis indicates that it may be difficult to find a universal global or regional model that could be applied at the sub-national level. It is nevertheless important to underline the fact that at least one of the light variables is present in all the regression which is not the case for the population or the surface area of the sub-national units.
For 3 countries (Italy, the Republic of Korea and the United Kingdom) the high correlation existing between GDP and population seems to indicate that these sub-national figures have been generated using a linear model based on population only. This finding demonstrates that not all reported sub-national data are reliable and emphasizes the need for independent methods for generating sub-national estimates. The sub-national level data for these 3 countries are therefore taken out from the sample for all the analysis reported in this publication.
Figure 7 summaries, in a unique graph, the result obtained when applying the country specific regression and converting the results into GDP per capita figures.
Figure 7 Prediction of income per capita at the sub-national level (country specific model). Plot of the predicted GDP per capita versus the observed one when applying the sub-national country specific model.
Table 3 list the number of units with an error bigger than the country specific Root MSE (also listed) as well as the percentage of units this correspond to. This represents a total of 97 sub-national units (mean value of 12.8 % of unit per country). All the countries presenting a national GDP per capita higher than 15,000 US$ as well as the 3 Latin American countries part of the sample (Argentina, Brazil and Mexico) are at the top of this list. The countries for which the prediction obtained is bellow the Root MSE for all the units are: Bangladesh, Greece, India, Mozambique, Portugal and South Africa.
Table 3 Root MSE, number of units outside the 1*RMSE range and percentage of the total number of unit this represents when applying the country specific model
Country Root MSE Number of unit outside 1*RMSE % of the number of units
DEU 4615 17 48
USA 3546 24 47
ARG 3240 7 29
ESP 2312 4 25
BEL 2384 2 18
BRA 1405 5 18
SVN 1427 2 16
MEX 1777 5 15
IDN 1651 4 14
RUS 2693 11 14
AUT 1405 1 11
THA 2074 9 11
FRA 1605 2 9
NLD 2669 1 8
FIN 1437 1 5
SWE 1264 1 4
CHN 981 1 3
Among these 97 units, 31 are containing at least one city with a population larger than 1,000,000 inhabitants (including some capital cities). Their presence in the list can be explained by the high concentration of buildings which represents vertical highlighted structures for which the satellite sensor is not able to capture the total intensity of the light being produced. This also confirms that in some countries the capital cities are more highly lit than their in country counterparts. Five other units contains oil and/or gas production infrastructure (2 in Indonesia, 2 in the USA and 1 in the Russian Federation). The separation of the lights produced by gas flares from the city lights could be the explanation for the under prediction of income per capita in these units. The difficulty in these cases is to know if the income produced by this activity remains within the concerned unit or goes directly to the government or even outside the country. This observation is to be extended to the offshore infrastructures that should also be considered in the model.
Even if no particular characteristics are identified for the remaining 61 units, these results illustrate the possibility to transfer the approach developed at the country level to the sub-national level on a country-by-country basis. This analysis also demonstrate the need to have income figures for some sub-national units in order to find the regression that provides the extrapolated figures for the remaining ones. This concerns units containing big cities (more than 1,000,000 inhabitants) and units containing oil and/or gas production. Additional analysis have to be performed in order to make sure that these are the only cases or if other specificity also have to be taken into account.
An out of sample analysis should also be performed in order to determine what is the smallest sample (% of all the units) necessary to obtain a regression providing prediction of acceptable quality.
Generating a global or regional model for the prediction of sub-national figures
As the availability of disaggregated income data is very poor, and despite the observation made in the previous section regarding the heterogeneity of the country specific sub-national model, tests and analysis are done in order to see if it is possible to generate a model that would allow the generation of sub-national income per capita series for countries where no sub-national figures are available. Four approaches are used:
- application of the country level model described in Table 2
- generation of a model based on all the sub-national data (with and without country dummy)
- generation of a model grouping the countries by climatic types
- generation of a model grouping the countries by agricultural level using the GDP composition by sector
The best results being obtained with the last approach, only this one is described in details in this section. For the other approaches only the major findings are reported.
Applying the country level regression to the sub-national data set and presenting the results on a summary graph (all the countries on the same graph) gives an acceptable prediction for sub-national units presenting a GDP per capita figure bellow 5,000 US$. Above this limit the application of this approach under estimate GDP per capita. When we generate country specific graphs we can observe that the important variety of income per capita figures at disposal in the sample is in fact at the origin of the observation done earlier on the summary graph and not the result of a good prediction for each country considered in the sample. This emphasizes the need to make country specific graph for analysing the results.
This analysis also demonstrates that applying the country level regression to the sub-national level may introduce an important quantitative error. In this regards, the attempt done by Doll et al. in their publication [14] should only be considered as a qualitative result.
When using the entire sub-national sample for generating one unique regression, the combination of variables giving the best results (Adj R-squared = 0.7692) is the same set found for the country level model (Table 2). The coefficients observed for each of the variables are also very close to the ones observed for the country level regression (-0.4955732*Lopopun + 0.059074*lotofre2 - 2.959219*lomeanfr + 1.176556*lomeanf2 - 0.1686316*losurfun + 7.774052). These small differences have an impact on the prediction of the income per capita figures for the units presenting a value higher than 10,000 US$ (ppp). The sub-national model gives better result than the country level model in only a few countries: Austria, Brazil, Greece, Portugal, Spain, South Africa, Thailand and the Netherlands.
If we integrate a dummy variable in the same regression we can observe one more time the same combination of variables than the one obtained for the country level model (Table 2) but the coefficients are slightly different. This alternate approach improves the prediction of the sub-national GDP per capita figures (Adj R-squared = 0.8971) reducing the dispersion of the estimates obtained for the middle and high income countries.
Another advantage of this approach is the fact that a good correlation exist between the country specific residual observed when applying the regression in Table 2 at the country level and the country specific constant obtained when applying the sub-national level model including the dummy variable (Figure 8).
Figure 8 Correlation between the country and the sub-national level prediction. Illustration of the correlation existing between the residual observed at the country level and the country specific constant observed at the sub-national level
In theory we could then apply the regression mentioned in Figure 8 on the residual found for a particular country during the country level analysis in order to find the constant to be used for predicting the sub-national GDP per capita figure for the same country. Even if the Adj R-squared for this regression is quite high (0.50) we can observed that Mozambique already represents an outliner indicating that using this correlation may unfortunately also generate important errors in the estimation of the country specific constant.
In conclusion, even if this approach is giving better results than the previous ones (application of the country level regression and generation of a unique regression without country dummy) and is presenting an important advantage due to the existing correlation with the country level model we can not consider that the results obtained are of sufficient quality for applying it to other countries where we would not have any sub-national figures.
Grouping the countries part of the sub-national data set by climatic types improves the prediction of GDP per capita for Bangladesh, France, India, The Netherlands, The Russian Federation, Sweden and Spain. This improvement mainly concerns sub-national units presenting an observed GDP per capita higher than 10,000 US$ and is not related to a particular climatic type.
When the sub-national sample is grouped according to the percentage of GDP associated with agriculture in each country, using the same cut off point than for the country level analysis (Figure 4), the following set of countries are obtained:
- Below 5 % of GDP due to agriculture: Austria, Belgium, Finland, France, Germany, Portugal, Slovenia, Spain, Sweden, the Netherlands and USA,
- Between 5 and 10 %: Argentina, Brazil, Greece, Mexico, Russian Federation and South Africa,
- Between 10 and 25 %: China, Indonesia, and Thailand,
- More than 25 %: Bangladesh, India and Mozambique.
The regression found for each group (based on significant variables except for the country specific constant and the country dummy) are presenting an Adj R-squared varying from 0.5731, for the countries presenting a percentage of GDP due to agriculture between 5 and 10 %, to 0.8013 for the countries with a percentage higher than 25 %. Like for the grouping by climatic type, the list of variables found is different for each group. Figure 9 shows the plot of the observed versus the predicted log of GDP per capita as well as the plot presenting the residuals obtained when applying these regressions. Figure 10 contains the same graph than the Figure 9a when taking out the logarithmic function.
Figure 9 Prediction of income per capita at the sub-national level (grouping by agricultural level in log). a) Plot of the observed versus the predicted log of GDP per capita obtained when applying the regression giving the best prediction with the sub-national data set separated into groups based on the percentage of GDP due to agriculture and with a country specific dummy variable b) Plot presenting the residuals versus the log of GDP per capita for the same regression
Figure 10 Prediction of income per capita at the sub-national level (grouping by agricultural level). Plot of the predicted versus the observed GDP per capita for the sub-national data set when applying the models grouping the countries using the percentage of GDP due to agriculture including a country dummy.
Using this approach, 108 sub-national units are presenting a prediction error bigger than the Root MSE, which represent a mean percentage of units by country of 21 %. The countries for which this grouping induces a significant improvement of the prediction, compare to the models used previously, are: Bangladesh, India, Belgium, Spain, France, the Netherlands, Portugal, Slovenia, Sweden, USA, Finland and the Russian Federation which represents 5 more countries than when using the grouping by climatic types. We can also observe that this improvement does mainly concerns countries were agriculture represent less than 5 % of the country GDP. Only exceptions: Bangladesh, India and the Russian Federation.
Even so, 3 of the countries for which the unique regression with dummy variable was not capturing the variability of GDP per capita before (Mexico, Argentina and Greece) are still presenting the same type of results.
Due to the small number of observation for each grouping it is not possible to identify if a correlation exists between the residuals observed at the country level and the country specific sub-national constant making it difficult to generate a regional model for these groupings using the same approach than the one described previously (Figure 8).
Conclusions
This study demonstrates that night-time lights data are useful in generating estimates of both national and sub-national GDP per capita figures. Because night-time lights are produced with zero reliance on national reporting data, they provide an independent measure of economic activity.
The country level results reported here confirm the conclusion given by Doll et al. [14] regarding the possibility of expanding the relationship between area lit and GDP to a larger number of countries. But these results raise the question whether the high correlation observed between these two parameters is in fact not coming from the good correlation existing between population and area lit and the one between population and GDP.
By introducing parameters other than area lit in the regression we have demonstrated the possibility of independent estimation of GDP per capita at the country level with a high level of confidence. This offers an interesting possibility for completing country level data sets for which data are missing or are in error. Special attention should nevertheless be paid to small densely populated territories with high level of lighting (e.g. Singapore and Monaco). In these areas, the models tend to underestimate GDP per capita as light produced by vertical infrastructures like high rise buildings fails to expand the area of lighting. This effect may be reduced if brightness information on the lights is available.
The graph reported in Figure 3 demonstrate that satellite observed area lit and percent frequency of lighting can be successfully used for the prediction of GDP per capita at the country level until a certain limit of economic development above which the relationship breaks down. GDP per capita estimates can be improved by developing models for groups of countries having similar climate or having similar proportions of the country GDP associated with agriculture. Even if the Root MSE observed when using these two models are close to each other our preference goes to the model grouping the countries by agricultural level as it produces fewer outliers. The disadvantage of adding more sub-groupings than the one proposed is that the number of countries in each group becomes small, reducing the strength of the model.
The result demonstrate that the approach developed for the country level can also be apply at the sub-national level but only through the generation of country specific models. Figure 11 illustrate the result obtained by the application of the country specific model found for South Africa as well as the distribution of the prediction error expressed in percentages.
Figure 11 South Africa, application of the country specific model. a) Distribution of the predicted GPD per capita figure when applying the country specific model b) Distribution of the prediction error when applying the same model
In this regard the possibility to generate country specific model for the extrapolation of sub-national income per capita figure is offering an interesting solution for countries where sub-national data on welfare are not available or where the application of other methods (e.g. small area estimation) would be difficult.
Nevertheless, the fact that income per capita figures are necessary for some sub-national units in order to generate the country specific model represent a limitation to the application of this approach. If the analysis done in the context of this work already gives an indication of the type of units for which it would be necessary to have a good estimation of the income per capita figures additional work would be necessary in order to confirm this list, maybe add other type of units and also have a better indication regarding the minimum number of units for which input data are needed to insure a good prediction. In addition to that, further analysis are also needed in order to define the level of desegregation to which it would be possible to go based on the developed approach. It will finally be necessary to consider including the amount of light due to gas or oil production infrastructure in the model if the income they are producing stays within the sub-national units where they are located.
Despite the caveats, the results obtained clearly demonstrate an interesting potential for making independent estimates of GDP per capita at the sub-national level especially for low income countries where the prediction obtained are of good quality and the need for them definitively the most important. Improving the data sets required to operationalize this approach may be far easier than improving the national reporting of sub-national economic data.
It would nevertheless be important to compare the results obtained by this approach with other methods also producing sub national estimated using consumption indicators in the context of poverty mapping exercises [[4] and [17]]. In addition to that, the possibility to maybe apply this approach to consumption indicators instead of income per capita figure should be explored as this would then represent an additional method, presenting the advantage of being less sophisticated, for the generation of desegregated country specific poverty maps. An other advantage would be that this approach would then not only be applicable to data collected in the context of the World Bank Living Standards Measurement Study (LSMS) [9] but also to the ones collected for example in the context of the WHO World Health Survey [18]. Even if this new instrument is presenting an additional advantage, by also collecting health indicators at the household level, work has to be done in order to confirm that the data collected are sub-nationally representative.
Trying to generate a consistent global or regional poverty map desegregated to some sub-national level, the grouping of the sample at disposal by climate or percentage of GPD due to agricultural level is definitively improving the prediction but does not provide us with a model generating consistent estimates for all the countries. Between these two grouping the preference again goes to the second one which improves the estimation for the middle and high income countries. The result obtained when applying this model to South Africa as well as the distribution of the prediction error expressed in percentages are reported in Figure 12 as an example. Despite being the best regional model analysed in the context of this research the grouping by agricultural level is still producing significant error when applying it on a country by country basis (Figure 12b) compare to the country specific model itself (Figure 11b).
Figure 12 South Africa, application of the model grouping the countries by agricultural level. a) Distribution of the predicted GPD per capita figure when applying the model grouping the countries by agricultural level. b) Distribution of the prediction error when applying the same model (see Figure 11 for the legend).
In this regards, the analysis performed is not offering us the possibility to generate consistent global map showing the sub-national distribution of income per capita figures.
These type of exercises are sorely needed to improve our knowledge regarding the health and well being of people in the poorest areas of the world. In this context night-time lights remain a useful data set for the evaluation of the impact of international efforts to improve the economic and therefore health conditions of these populations. It would therefore be important to pursue the type of work described in this paper and to see if the results obtained could not be improved.
For both the country and the sub-national level model, the combination of the two groupings used in the context of this present work could for example improve the proposed models but this would have to be confirmed through additional analysis.
The more recent global night-time light mosaic that NOAA has compiled is another element which might improve the results presented in the context of this work. This new global mosaic has the advantage of covering a longer period of observation (full years instead of the six month composite used in this study) which would improve the homogeneity of the distribution of the number of observation per pixel and also reduce the effect of the snow observed on images collected during winter. These new products were processed with major improvements in the exclusion of all but the highest quality segments of the individual orbits. They also include one information that was missing in the data set used for the context of this work: the digital number brightness of the lights. It has been found that adding in brightness of the lighting greatly improves the relationship to variables such as electric power consumption and GDP. Even if some difficulties to make products with brightness values remains, due to saturation in urban centers and the lack of on-board calibration, this new generation of grids could allow a significant improvement of the models described in the present paper. Another advantage of this data set is that the NGDC is producing a full global composite for each year from 1992 through 2004 allowing therefore for trend analysis.
Before being able to test such new source of spatially distributed information it would be important to correctly address the question of the lack of documentation regarding the methods used for generating sub-national income estimates reported by individual countries in case this indicator would provide better results than consumption when trying to generate a consistent global poverty map. Inclusion of erroneous data may lead to misleading interpretations (see the case of the data for the United Kingdom, Italy and the Republic of Korea in the sub-national level analysis section).
Such discrepancies also underline the value of high quality geospatial data for use in making independent estimates of economic activity. This for example includes standardization of the basic vector GIS layers (national and sub national borders for example) in order to insure a proper use of the information collected at the sub national level or stored in different raster layers (night-time light and population for the present work). Among the different initiatives that are trying to answer the need for standardization in this area we can mention the Second Administrative Level Boundaries data set project (SALB). The first objective of this project is to create a redistributable Second Administrative Level Boundaries global data set (SALB) representative of January 2000 to be used with the GIS technology. The information finally collected has extended the period of representativity of the database for finally covering the period 1990-present. A process has also been put in place in order to insure the updates of the database in the future. You can find all the relevant information about this project as well as the data already available on the project web site [19]. The growing use of this database and more specifically of its specific coding scheme should improve the availability and comparability of sub national income figures in the future.
Finally, the shifts observed between all these layers of geographical distributed information is emphasizing the need for defining a "master" that could be used as a ground reference when generating or working with them. If the precision of its georeferencing is confirmed, the global mosaic of satellite images that are now publicly available (e.g the Landsat mosaic) could for example constitute this master.
Methods
In order to perform the analysis at the country and at the sub-national level it was necessary to compile existing data sets on income as well as geographically distributed parameters that would be used to model these figures using a GIS. These concerns:
- night-time light imagery
- population
- international and sub-national boundaries
- surface area
- climate
The data sets used for the context of this paper are presented now. In order to insure the consistency of the analysis, all the data sets compiled or created were adjusted to 1995, which is the year of representativity of the only night-time light grid available at the beginning of this research.
We utilized GDP per capita data that have been collected at both the country and sub-national level. For the country level, GDP in International Dollars (GDP I$) for 171 countries have been calculated for the year 1996 from GDP figures expressed in local currency unit using price level data [20] and were adjusted to be representative of 1995.
For the sub-national level, GDP figures representative of the first or second administrative or statistical level have been collected for 26 countries (653 units) from the 5 continents (Table 4). These figures were homogenised in order to obtain a final data set expressed in Power Purchasing Parity (PPP) representative of 1995. A country specific adjustment factor has been applied to these figures in order to keep the consistency with the country figures before dividing them by their corresponding population.
Table 4 Source of the income figures for the sub-national analysis
Country ISO 3 Code Admin-Stat./Level/Nb unit Representativity Source of the data Income level
Argentina ARG Adm/1/24 1995 National statistics agency, Argentina Middle
Austria AUT Adm/1/9 1994 Sozialstatistic Austria High
Bangladesh BGD Admin/2/19 1993 Statistical Yearbook of Bangladesh, 1994 Low
Belgium BEL Admin/2/11 1994 MaconUSA High
Brazil BRA Admin/1/27 1997 IBGE; Brazil Middle
China CHN Admin/1/30 1998 Statistical Yearbook of China, 1998 Low
Finland FIN Stat/3/19 1997 Statistics Finland High
France FRA Stat/2/22 1994 MaconUSA High
Germany DEU Stat/2/35 1994 MaconUSA High
Greece GRC Admin/1/13 1994 Statistical Office of Greece High
India IND Admin/1/25 1991 Statistical Outline of India 1999–2000 Low
Indonesia IDN Admin/1/27 1994 Statistical Information Services, Indonesia Middle
Italy ITA Stat/2/20 1994 MaconUSA High
Mexico MEX Admin/1/32 1995 INEGI, Mexico Middle
Mozambique MOZ Admin/1/10 1997 Instituto Nacional de estatistica, Mozambique Low
Netherlands NLD Stat/2/12 1994 MaconUSA High
Portugal PRT Stat/2/7 1994 MaconUSA High
Russian Federation RUS Admin/1/77 1996 State Com. Of the Russian Federation on Statistics Middle
Slovenia SVN Stat/2/12 1996 Statistics Slovenia Middle
South Africa ZAF Admin/1/9 1994 Statistics South Africa Middle
Republic of Korea KOR Admin/1/14 1995 National Statistical Office of Korea High
Spain ESP Stat/2/16 1994 MaconUSA High
Sweden SWE Stat/3/21 1996 Statistics Sweden High
Thailand THA Admin/1/76 1995 Chulalongkorn University, Bangkok Middle
United Kingdom GBR Stat/2/35 1994 MaconUSA High
United States of America USA Admin/1/51 1997 Harvard University, USA High
The night-time light grid used has been provided by NOAA's National Geophysical Data Center (NGDC). This grid data set is the result of a 6-month 1 km resolution composite based on images collected between October 1994 and March 1995 by the U.S. Air Force Defence Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) [10]. Only the grid with the distribution of lights associated with human settlements has been used in the context of the present research. Due to improvements in the algorithms used during the processing, this grid is different than the one used by Doll et al. for their publication [14]. By comparing these two grids it has been possible to identify some of these differences and to take advantage of their respective specificity for generating the grid used here. From this grid it possible to extract 4 parameters connected to light observation at night which are capturing a different information making it possible to extract the figures at the country or sub-national level for the analysis:
- the number of cells highlighted at night
- the area lit (surface area being highlighted at night) which is giving an indication of the extension of the highlighted surfaces,
- the total frequency of light observation (obtained by adding the percents frequency of light detection observed in each cell on a given surface) which is giving an indication of the total intensity of the highlighting
- finally, the mean frequency of light observation, in the highlighted areas, which gives us an indication of the dispersion of this intensity. For example: one pixel with a 100 % of light observation or 100 pixels with 1 % of light observation are giving the same value for the total frequency of light observation but a totally different figure for the mean frequency of light observation and area lit.
These information being stored in a grid it is possible to extract them at the country or sub-national level for the analysis.
Regarding population, the country level data that have been used are the UN population figures for the year 1995 [21]. For the sub-national level the Gridded Population of the World (GPW) version 2 has been selected [22] as being consistent with the UN country level data set. In addition to that, this data set is offering the possibility to use GIS in order to make spatial analysis at the sub-national level.
Climate is known to have an important influence on many elements on the earth surface, including human behaviour and well being [23], and also on the need for specific lighting of infrastructure. The Köppen climate classification distribution grid derived by the Food and Agriculture Organization (FAO) from the International Institute for Applied Systems Analysis (IIASA) data sets has therefore been used for the context of this project [24]. Using this grid it is possible to determine the general climate of any geographical entity (national or sub-national). Köppen categories are based on the annual and monthly averages of temperatures and precipitation.
Five major climatic types are recognized in this system, each type being designated by a capital letter (each of them being divided into sub types):
A – Tropical moist climates: all months have an average temperature above 18 degrees celsius.
B – Dry climates: with deficient precipitation during most of the year
C – Moist mid-latitude climates with mild winters
D – Moist mid-latitude climates with cold winters
E – Polar climates: with extremely cold winters and summers
The delimitation of the units of analysis (countries and sub-national units), corresponding to the GDP figures collected for the context of this study, have also been prepared in a format that could be used in the GIS tool. In order to insure the consistency from one country to another the delimitation of the international borders has been adjusted to 1995.
Finally, the surface area of the units of analysis has also been included in the data set.
Two types of software have been used in analysing national and sub-national income: a Geographic Information System (GIS) and a statistical package. In order to take advantage of the specificity of the two modes of representation observed in the compiled data set (vector and raster) we have worked with the ArcView GIS software (version 3.2) for the vector part complemented by the Spatial Analyst extension (version 1.1) for the raster part. As no statistical analysis could be done directly in the GIS software the statistical support was provided by the STATA software (Version 5).
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| 15705196 | PMC549533 | CC BY | 2021-01-04 16:39:06 | no | Int J Health Geogr. 2005 Feb 10; 4:5 | utf-8 | Int J Health Geogr | 2,005 | 10.1186/1476-072X-4-5 | oa_comm |
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Reprod Biol EndocrinolReproductive biology and endocrinology : RB&E1477-7827BioMed Central London 1477-7827-3-71570308410.1186/1477-7827-3-7ResearchExpression of plasminogen activators in preimplantation rat embryos developed in vivo and in vitro Aflalo Eliahu D [email protected] Uriel A [email protected] Gad [email protected] Iris [email protected] Department of Life Sciences, Ben-Gurion University of the Negev, P.O.Box 653, Beer-Sheva 84105, Israel2 Fertility and In vitro Fertilization (IVF) Unit, Department of Obstetrics and Gynecology, Soroka University Medical Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, Israel2005 10 2 2005 3 7 7 8 12 2004 10 2 2005 Copyright © 2005 Aflalo et al; licensee BioMed Central Ltd.2005Aflalo 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
Embryo implantation plays a major role in embryogenesis and the outcome of pregnancy. Plasminogen activators (PAs) have been implicated in mammalian fertilization, early stages of development and embryo implantation. The invasion of trophoblast cells into the endometrium during the implantation process can be blocked by inhibitors of serine proteases, illustrating the role of these enzymes in the invasion process. As in vitro developing embryos resulted in lower implantation rate than those developed in vivo we assume that a reduced PAs activity may lead to it. There is hardly any information regarding qualitative or quantitative differences in expression of PAs in preimplantation embryos, or comparisons between in vivo and in vitro developed embryos. The purpose of this study was to assess the expression of urokinase type (uPA) and tissue type (tPA) plasminogen activators in in vivo and in vitro preimplantation development in rat embryos using immunofluorescence confocal microscopy and computerized image analysis.
Methods
Zygotes, 2-cell, 4-cell, 8-cell, morula and blastocyst stages of development were flushed from the reproductive tract (control groups) of Wistar rats. Zygotes were flushed and grown in vitro to the above mentioned developmental stages and comprised the experimental groups. Immunofluorescence microscopy and computerized image analysis were used to evaluate both qualitative (localization) and quantitative expression of plasminogen activators.
Results
uPA and tPA were found to be expressed in rat embryos throughout their preimplantation development, both in vivo and in vitro. While uPA was localized mainly in the cell cytoplasm, the tPA was detected mainly on cell surface and in the perivitelline space. In blastocysts, both in vivo and in vitro, uPA and tPA were localized in the trophectoderm cells. Total uPA content per embryo was higher in the in vivo as compared with the in vitro developed embryos at all stages measured. Blastocyst uPA content was significantly low as compared with the four-cell, eight-cell, and morula stages. Total tPA content was higher in embryos developed in vivo than those developed in vitro except for the 4-cell and 8-cell stages.
Conclusion
In vitro embryo development leads to lower PAs expression in a stage dependent manner as compared with in vivo developing controls. The enzymes studied vary probably in the ratio of their active and inactive forms as there is no correlation between their content and the activity observed in our previous study. The localization of both PAs in the blastocysts' trophectoderm supports the assumption that PAs plays a role in the implantation process in rats.
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Background
Plasminogen activators (PAs) and matrix metalloproteinases (MMPs) have been implicated in mammalian gametogenesis [1], ovulation [2,3], fertilization [4,5], early stages of development and embryo implantation [6,7]. The PAs are serine proteases, which convert the inactive plasminogen to the potent protease plasmin. Plasmin can degrade directly or indirectly, through the activation of metalloproteinase zymogens, all components of the extracellular matrix [8,9]. There are two types of PAs, tissue-type plasminogen activator (tPA) and urokinase-type plasminogen activator (uPA). Plasminogen, its activators and inhibitors, participate in the implantation process. Trophoblast cells of human blastocysts cultured in vitro produced PAs during the period corresponding to the in vivo invasion into the endometrium [10]. In embryos of the homozygous tw73 mouse mutant, PAs were reduced and was concomitantly associated with implantation failure [11]. The invasion of trophoblast cells during the implantation process could be blocked by inhibitors of serine proteases, illustrating the role of these enzymes in the invasion process [12,13]. In the human, embryo implantation following in vitro fertilization and embryo transfer (IVF-ET) is considered to play a major role in the success of the treatment. Only 12% of the transferred embryos are able to successfully implant [14].
In the implantation process, two major factors participate: the uterus undergoes changes that prepare it for the arrival and implantation of embryos, and the embryos undergo cellular reorganization that enables them to penetrate the endometrium and to form the placenta. We assume that one of the reasons for low implantation rate of embryos developed in vitro involves reduced PAs activity.
In a previous study we demonstrated differences in PAs activities between in vivo and in vitro preimplantation developed embryos. In both, uPA activity increased from the zygote towards the blastocyst stage while tPA activity remained relatively unchanged. However, tPA and uPA activities were lower in in vitro developed embryos as compared with in vivo developing ones, at all developmental stages, which may lead to a reduced implantation rate of in vitro developed embryos [15].
There is hardly any information regarding qualitative or quantitative differences in expression of PAs in preimplantation embryos, or comparisons between in vivo and in vitro developed embryos. Therefore, the purpose of this study was to investigate the PAs expression and localization during embryo development in vivo and in vitro by immunofluorescence confocal microscopy.
Methods
The following study was approved by the Institutional committee for animal care and ethics at Ben-Gurion University of the Negev, Beer-Sheva, Israel.
Animals
Mature female Wistar rats 2–3 months old, weighing 180–230 g were used. The animals were kept in a temperature-controlled room maintained at 22–24°C with lighting regimen of 14 hours light 10 hours dark (light on 5:00 AM – 7:00 PM). The rats were allowed free access to rat chow and tap water.
Daily vaginal smears were taken at 10:00 AM, and the stage of estrous cycle was determined. Overnight caging of a proestrous female with a male of proven fertility induced pregnancy. The next day, the presence of a vaginal plug or spermatozoa in the vaginal smear was designated as day 1 of pregnancy.
Collection of embryos
Zygotes, two-cell, four-cell, eight-cell embryos and morulae were flushed with rat 1-cell embryo culture medium (R1ECM) [16] from oviducts at days 1, 2, 3 and 4 of pregnancy, respectively, and blastocysts at day 5 from the uterine horns. All equipment and media used were sterile. Ovary-oviduct complexes were removed from anesthetized animals. The complexes were placed in R1ECM, and the oviducts were separated under a dissecting microscope. 30-gauge blunt-end needle attached to a syringe containing R1ECM was inserted through the oviductal end held by forceps surrounding the needle and tube. Embryos were gently flushed into 35-mm-diameter culture dish. Embryos were washed 3 times by transfer into fresh R1ECM to remove cell debris and any maternal factors present in the oviduct.
Zygotes in their cumulus mass were flushed and the cumulus cells were removed by gentle aspiration through a micropipette (diameter, 150–200 μm) several times in R1ECM containing 80 U/mL of hyaluronidase. Clean zygotes were washed 3 times by transfer into fresh R1ECM to remove traces of hyaluronidase. Flushed embryos were collected with a mouth-controlled micropipette (diameter, 150–200 μm).
Blastocysts were flushed from the uterine horns by insertion of a 23-gauge needle attached to a syringe containing R1ECM. Flushed, free-floating blastocysts were collected into a polypropylene tube inserted through the vagina and pushed gently to surround the cervical openings. Tubes were removed, and their contents were poured into Petri dishes. Blastocysts were washed and collected as described for zygotes and embryos. These embryos developed in vivo were the control groups.
Embryo culture
As described for the in vivo embryos, clean zygotes were grown in vitro to the same developmental stages as controls; these were the experimental groups. Each group of embryos consisted of 25–35 embryos collected from six pregnant females. This was repeated three times for each developmental stage (total of about 90 embryos per stage). Groups of 25–35 zygotes were placed into 35-mm-diameter culture dishes (Nunc, Roskilde, Denmark) containing 50μL of R1ECM medium under a layer of mineral oil (previously equilibrated to the experimental conditions) and cultured at 37°C under 5% CO2 in air. This medium was shown by Miyoshi et al. [16] to enable rat embryo culture to the blastocyst stage. In a comparison of various media at our laboratory, R1ECM was found to be the best medium to enable a synchronous development of embryos (95% of total) to the blastocyst stage. The developing embryos seemed to be normal in their morphology, with almost no fragmentation. At the end of incubation, embryos were washed 3 times with fresh R1ECM.
Embryo immunocytochemistry
The method used was basically that of Dubey et al. [17] with various modifications. Groups of 20–25 embryos at different developmental stages from the experimental and control groups were fixed in 4% paraformaldehyde in phosphate buffered saline (PBS) at room temperature and washed twice in PBS, PH 7.4 for 5 minutes. Five percent bovine serum albumin (BSA) in PBS was used for dilution of antibodies and washings (PBS-BSA). The embryos were washed four times in PBS-BSA before immunoreaction. Embryos, randomly chosen were either exposed to polyclonal rabbit anti rodent uPA or rabbit anti rat tPA (American Diagnostics, Pendelton, IN) at a concentration of 4μg/mL. Embryos were then incubated overnight in 50μL of each antibody solution under paraffin oil in a 35 mm culture plate in a moist chamber at 4°C. The embryos were then washed four times in PBS-BSA and incubated with Cy3-conjugated goat anti-rabbit IgG (Jackson ImmunoResearch Laboratories, Inc., West Grove, PA) at 37°C for 60 minutes. The conjugated antibody was used at a dilution of 1:300 in PBS-BSA. After incubation with the secondary antibody, the embryos were washed again in PBS-BSA and stained with DNA stain 4', 6-diamidino-2-phenylindole (DAPI) (Vector Laboratories, Burlingame, CA) and mounted in Flouromount – G (Southern Biotechnology Associates, Inc. Birmingham, AL) to minimize quenching. To confirm that the fluorescence observed was neither attributable to nonspecific binding of the secondary antibody nor to formaldehyde-induced autofluorescence, negative controls (without primary antibody) were established during each immunoreaction procedure. The immunocytochemistry staining procedure was repeated three times for each stage of embryo development on different batches of embryos.
Image Analysis
The distribution and concentration of PAs in the embryos were visualized by fluorescent microscopy on a Zeiss laser scanning confocal microscope equipped with an X100 objective. Z-sections and XZ-sections were obtained from 3D scanning by using LSM510 software (Zeiss, Feldbach, Switzerland) The PAs density for each embryo was computed by image analysis based on the same principles as manual counting described elsewhere [17]. The embryos' fluorescent images were downloaded using an image analysis software, ImagJ (NIH, Bethesda, MD). These images were stored in the computer by use of pixels. All the slices obtained from 3D scanning were of 0.7μ and were analyzed by counting the number of pixels of the Cy3 (red color) in the whole slice. Total pixels in a whole embryo were calculated by summing the number of pixels in all the slices of an embryo. This method showed the total amount of PAs expression in each embryo. The number of pixels in an embryo represents the intensity of PAs staining (fluorescence), which is in turn proportional to the amount of PAs in that embryo. Each experimental group consisted of 8–10 embryos and the measurements repeated three times with different batches of embryos from each developmental stage stained at different times (total number of 24–30 embryos per stage).
Statistical analysis
Data are expressed as means ± SEM. Statistical analysis was performed with two-way analysis of variance, followed by the least significant differences test for multiple comparisons using computer software (Statistica 6.0, Statsoft, Inc. Tulsa, OK). P < 0.05 was defined as statistically significant difference.
Results
PAs localization
Immunohistochemical staining for the location of tPA and uPA in preimplantation embryos developed in vivo and in vitro are shown in figure 1. The PAs were detected in all stages of embryo development, both in in vivo and in vitro (Fig. 1A–V). The uPA was expressed in the cell cytoplasm and plasma membrane (Fig. 1A–K) while tPA was detected on the cell membrane and in the perivitelline space (Fig. 1L–V). In blastocysts developed in vivo and in vitro PAs were localized mainly in the trophectoderm (Fig. 1F, K, Q, V). There was no difference in PAs localization comparing in vivo and in vitro developed embryos at the same stage.
Figure 1 PAs localization. Expression of uPA (A-K) and tPA (L-V) in preimplantation developing rat embryo stages grown in vivo and in vitro. (A, L)-Zygote. (B, G, M, R)-2-cells. (C, H, N, S)-4-cells. (D, I, O, T)-8-cells. (E, J, P, U)-Morula. (F, K, Q, V)-Blastocyst. (A-F)-uPA in vivo. (G-K)-uPA in vitro. (L-Q)-tPA in vivo. (R-V)-tPA in vitro. (X)-2-cell uPA negative control. (XX)- 2-cell tPA negative control.
Quantitative measurement of uPA
Quantitative measurement of total uPA in an embryo at each stage showed significantly lower expression (p < 0.01) in in vitro developed embryos from the 4-cell stage up to the blastocyst stage compared with the in vivo developed corresponding timepoint. The highest expression of uPA was found in in vivo developed embryos from 4-cell to the morula stage (90.58, 78.78 and 79.35 Pixels per embryo × 103, respectively, Fig. 2). In the in vitro developed embryos, a significant increase (p < 0.01) in uPA expression was found from the 2-cell stage to the 4-cell stage (43.91 and 61.86 Pixels per embryo × 103, respectively).
Figure 2 Quantitative measurement of uPA. Quantitative (Pixels/Embryo) uPA expression in preimplantation rat embryos developed in vivo and in vitro. Different letters represent statistically significant differences (P < 0.05).
Quantitative measurement of tPA
Total tPA expression in a whole embryo showed highest expression in in vivo developed embryos at the 2-cell, 8-cell, morula and blastocyst stages (61.59, 52.71, 48.03 and 52.34 Pixels per embryo × 103, respectively, Fig. 3). At the 2-cell stage, morula and blastocyst, a significantly lower expression (p < 0.01) was found in in vitro developed embryos as compared with the in vivo ones.
Figure 3 Quantitative measurement of tPA. Quantitative (Pixels/Embryo) tPA expression in preimplantation rat embryos developed in vivo and in vitro. Different letters represent statistically significant differences (P < 0.05).
Discussion
Our study demonstrates that uPA and tPA are expressed throughout all stages of preimplantation development of rat embryos. Zhang et al. [18] reported expression of uPA gene and uPA activity in preimplantation rat embryos developed in vitro and Khamsi et al. [19] reported the presence of mRNA for uPA in human blastocysts. However, information about the expression and immunolocalization of uPA and tPA has not been reported in in vivo nor in in vitro preimplantation developing rat embryos. We present here a quantitative measurement of PAs expression in a whole embryo allowing comparison of embryos at different developmental stages, grown in vivo or in vitro.
The results show localization of immunoreactive uPA in the embryonic cell cytoplasm and plasma membrane in all developmental stages both in vivo and in vitro, while tPA is detected on the cell membrane and in the perivitelline space. In the blastocyst stage, PAs are localized mainly in the trophectoderm. In our previous study [15] we showed that the activity of uPA was higher than that of tPA in the blastocyst. Its presence in the trophectoderm combined with its high activity in this stage, support the assumption that uPA is important for proper implantation. This assumption is supported by the study of Kubo et al. [20] who showed that inhibition of PAs activity prevents the adhesion of mouse embryos to decidual cells grown in vitro. In addition, trophoblast cells grown in vitro showed PAs activity at the time of their penetration into the endometrium in vivo and uPA was the major enzyme secreted from trophectoderm cells with the highest activity on days five to seven of pregnancy [7]. The exact source(s) of the immunoreactive PAs in in vivo developing embryos cannot be identified. The serum, oviduct and endometrium could be contributing sources as suggested in previous studies [10,21-23]. Lack of the these source(s) in in vitro situation may lead to lower implantation ability of embryos as shown earlier [15].
Pro-uPA is synthesized as an inactive single chain that can be stored or secreted. The secreted pro-uPA can be cleaved to produce the two-chain active molecule, uPA, by the aid of limited proteolytic activity of plasmin [24]. The secreted pro-uPA or the active uPA can be found free in cytoplasm and extracellular matrix or bound to a membrane uPA receptor [25]. Whether the uPA identified in this study is the inactive pro-uPA or the active uPA associated with the embryonic cell membrane uPA receptor, is unknown. In our previous work we have shown an increase in uPA activity towards the blastocyst stage in in vivo and in in vitro developing embryos [15]. The results of the present study, showing lower expression of uPA in the blastocyst stage, may suggest a shift of uPA from the inactive form to the active form resulting in an increase of activity despite the reduction in its expression.
High tPA expression was detected at the zygote stage which is in accordance with high tPA activity found in this stage [15]. This is supported by the report of Zhang et al. [18] who showed presence of tPA mRNA in rat oocytes and two-cell embryos. The embryonic genome of rats and mice start to be expressed at the 2-cell stage [26] and the high tPA levels in the zygote are probably due to maternal mRNA expressed and accumulated in the oocyte [27].
The embryonic extracellular matrix is in a continuous turnover during the embryonic development. The 8-cell stage is characterized by structural changes taking place in the embryo during the compaction process. It is therefore very likely that such changes at the 8-cell stage could be associated with increased tPA expression and activity which is known to participate in tissue remodeling [8]. The high increase in tPA expression from the 4-cell stage to the 8-cell stage in in vitro developed embryos suggests de novo synthesis of tPA since there is no extraembryonic tPA source but the embryos in the culture.
Lower expression of uPA was observed in in vitro developed embryos as compared with in vivo ones from the 4-cell up to the blastocyst stage while tPA expression was lower only in the morula and blastocyst stages. This could be explained by reduced metabolic activity in the in vitro developed embryos as suggested by Krisher et al. [28]. In addition, in vitro conditions may lead to a slower cell division rate which may result in a blastocyst comprised of fewer cells and decreased ability to hatch from the zona pellucida [28,29]. Carroll et al. [30] showed that the oviduct is also a source of PAs, which could attach to receptors on embryonic cell membrane, and this source is lacking in in vitro developing embryos. It should be noted that any culture media would lack maternal factors, known or yet unknown, which affect embryo development and thus, implantation rate, through their effect on the PA/plasmin system.
Additional studies addressing the regulation of PA/Plasmin system by adding exogenous factors may provide insights into its role in early embryo development and implantation.
Conclusions
The purpose of the study was to determine the relative importance of tPA and uPA in preimplantation embryo development. In vitro embryo development leads to lower PAs expression in a stage dependent manner as compared with in vivo developing ones. The localization of both PAs in the blastocysts' trophectoderm supports the assumption that PAs may play a role in the implantation process in rats.
Authors' contributions
EDA participated in the planning of the project, carried out the animal experimentation, immunohistochemistry and the image analysis studies. USM participated in the planning of the project, animal experimentation and participated in preparation of the manuscript. GP participated in preparation of the manuscript. IHV participated in the planning of the project, statistical analysis and in preparation of the manuscript.
Acknowledgements
We would like to thank Ms. Vera Lapidot for her technical assistance and Ms. Inez Mureinik for styling the manuscript.
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BMC GenomicsBMC Genomics1471-2164BioMed Central London 1471-2164-6-131569400310.1186/1471-2164-6-13Methodology ArticleDevelopment of a cDNA array for chicken gene expression analysis Burnside Joan [email protected] Paul [email protected] Jianshan [email protected] Ryan [email protected] Richard [email protected] Mark [email protected] David [email protected] Jeff [email protected] Delaware Biotechnology Institute, University of Delaware, 15 Innovation Way, Room 229, Newark, DE 19711 USA2 Division of Basic Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N. C2-023, P.O. Box 19024, Seattle, WA 98109-1024 USA3 Bioinformatics Systems and Databases Glaxo Smith Kline King of Prussia, PA4 Genomics Resource, DNA Array Laboratory, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N. C2-023, P.O. Box 19024, Seattle, WA 98109-1024 USA5 Dept. of Genomics & Bioinformatics Roslin Institute (Edinburgh) Roslin, Midlothian EH25 9PS, UK6 Biocomputing Resource, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N. B1-080, P.O. Box 19024, Seattle, WA 98109-1024 USA2005 4 2 2005 6 13 13 29 9 2004 4 2 2005 Copyright © 2005 Burnside et al; licensee BioMed Central Ltd.2005Burnside 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 application of microarray technology to functional genomic analysis in the chicken has been limited by the lack of arrays containing large numbers of genes.
Results
We have produced cDNA arrays using chicken EST collections generated by BBSRC, University of Delaware and the Fred Hutchinson Cancer Research Center. From a total of 363,838 chicken ESTs representing 24 different adult or embryonic tissues, a set of 11,447 non-redundant ESTs were selected and added to an existing collection of clones (4,162) from immune tissues and a chicken bursal cell line (DT40). Quality control analysis indicates there are 13,007 useable features on the array, including 160 control spots. The array provides broad coverage of mRNAs expressed in many tissues; in addition, clones with expression unique to various tissues can be detected.
Conclusions
A chicken multi-tissue cDNA microarray with 13,007 features is now available to academic researchers from [email protected]. Sequence information for all features on the array is in GenBank, and clones can be readily obtained. Targeted users include researchers in comparative and developmental biology, immunology, vaccine and agricultural technology. These arrays will be an important resource for the entire research community using the chicken as a model.
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Background
The chicken is an important experimental model for evolutionary and developmental biologists, immunologists, cell biologists, geneticists, as well as being an important agricultural commodity. The recent release of a draft of the chicken genome sequence, as well as the development of a large (531,351) collection of expressed sequence tags (ESTs) has dramatically changed the landscape for biologists wishing to use genomic tools to study the chicken. DNA microarrays are well accepted as an essential part of functional genomics. Several small chicken cDNA arrays have been fabricated and used in studies focused on the chicken immune system [1-4]. To enhance the utilization of existing resources and further develop the chicken as a model organism, a consortium was formed to produce microarrays using clones from the Biotechnology and Biological Sciences Research Council (BBSRC), University of Delaware (UD) and Fred Hutchinson Cancer Research Center (FHCRC). The BBSRC chicken cDNA project generated a large (>300,000) collection of ESTs that represents a wide range of adult and embryonic tissues [5]. The UD Chick EST project has focused on tissues important in agricultural production, with a heavy emphasis on the immune system [6]. The FHCRC EST collection was generated from DT40 cells (a transformed bursal cell line) [1,2], along with clones from the bursal EST project [7,8] and the UD activated T cell library [9]. By combining resources and clones from these projects, we have established a collection that encompasses a variety of tissues, and generated microarrays with 13,007 usable features. This paper describes the array with respect to clone selection and quality control parameters.
Results and discussion
Selection of clones for the array
A compilation of 363,838 chicken ESTs from the BBSRC, UD, and FHCRC collections were sorted into contigs (33,323) singlets (27,235), and singletons (8,794), using the default parameters of the phrap assembly program [10]. The phrap singletons contain sequences represented in the contig group, but could not be assembled, and were eliminated from further consideration. Both contigs and singlets groups were analyzed by using BlastX to compare to GenBank (nr) and BlastN to compare to human dbEST. Because of the evolutionary divergence between chicken and the majority of the sequences that populate GenBank, a Blast score >50 was considered a significant hit, and clones with scores<50 were excluded. Clones belonging to the existing chicken immunology collection (4,162 cDNAs from DT40 cells, bursa and lymphoid tissues) were sorted from the entire contig/singlet set, and after screening for E.coli, mitochondrial and ribosomal RNA contaminants, and identical Blast hits, a total of 2,248 and 13,584 singlets and contigs, respectively, remained as candidates from which to choose cDNAs for the final array. About half of the clones in the contig group were expressed in 4 or more libraries, indicating wide tissue expression (Figure 1). The remaining half was found in less than 3 libraries, indicating a more restrictive expression. For clones belonging to contigs, the most 5' clone was selected for inclusion on the array. This potentially introduces a 5' bias in the sequence available for hybridization; however, since the average insert size for all clones is approximately 1.2 kb and most cDNAs were made by oligo dT priming, clones should contain the entire downstream sequence.
Figure 1 Library coverage in clones assembled into contigs. Clones from the BBSRC, UD, and FHCRC collections were assembled into 13,584 high scoring (BlastX>50) contigs using phrap software [10], and the number of different tissue libraries represented in each contig were scored. There were 6,832 contigs that had clones from 4 or more libraries, while the remaining contigs consisted of clones from 3 or fewer libraries.
The library representation of the clones in the singlets group is shown in Figure 2. The numbers tended to reflect the depth of sequencing of the individual libraries [5,11]. The chondrocyte, ovary and stage 20–21 whole embryo libraries have more singlets; more than 25,000 ESTs were sequenced from each of these libraries, as opposed to 7–15,000 from the other libraries. The correlation is not perfect, however, and the lack of correspondence likely reflects similarities of some libraries to others in the collection, or relative specialization of the tissue, or a combination of these factors.
Figure 2 Library coverage of the singlets. Clones that are only represented once in the ESTs assembled with the phrap software [10], and with Blast scores>50, were analyze for distribution in the different libraries.
The final selection of clones for the array was made by randomly choosing about 4,800 ESTs expressed in a wide range (>3) of tissues, and about 4,800 with a more narrow (1–3 tissues) expression profile, in addition to 1,735 singlets. The library distribution of the final clone selection is shown in Figure 3. However, it is important to note that because >50% of the clones were represented in multi-library contigs, the potential tissue representation on the array is greater than that depicted by library representation. Figure 4 shows the minimal expected tissue coverage of the 11,447 clones chosen from the BBSRC collection. Note, for example, that while only 724 clones from the stage 36 trunk library were selected for the array, at least 2,000 mRNAs from that tissue are represented by clones from various libraries.
Figure 3 Library distribution in final clone set. The clones in the original immunology collection and clones randomly selected from the contigs and singlets were scored for library of origin.
Figure 4 Minimal expected tissue coverage. The libraries represented in each of the contigs or singlets from which a clone was chosen for the array were scored to give an estimation of the expected coverage for a given tissue. Only clones in the BBSRC collection were included in this analysis.
Annotation
A list of the clones can be accessed on-line [12]. The clones represented in the list total 15,769. PCR product quality was assessed using gel electrophoresis and the results were meticulously scored and recorded. After identifying poor quality PCR products (e.g., no detectable product, detection of multiple products), the number of useable features totals approximately 13,000, including control features. The annotation file contains accession numbers, source clone name, and source assigned annotation or Blast derived annotation. In addition the EST identification assigned by The Institute for Genome Research (TIGR) and found in TIGR's Gallus gallus Gene Index (GgGI) [13] is provided, as is the identifier for TIGR's consensus (TC) sequence and TIGR annotation. An analysis of the TC identifiers for clones on the array revealed that 1,184 mRNAs are represented by more than one clone. This is due to clones in non-overlapping contigs and some redundancy in the original immune collection. A more detailed annotation file, as well as a database for array data is under development and will be accessible on line [6].
Clone selection and array fabrication predated the sequencing of the chicken genome. An analysis of the sequence of the clones on the array indicates that 10,168 of the 21,447 predicted or annotated chicken genes in the GenBank chicken Unigene collection are present on the array. The remaining clones match cDNAs not yet included in Unigene, or other portions of the chicken genome, or are redundant.
Clones are available from their original source: the BBSRC collection, distributed by the MRC gene service [14]; the DKFZ collection at Heinrich-Pette-Institute maintained by Dr. Jean-Marie Buerstedde [15]; the DT40 collection at Fred Hutchinson Cancer Research Center, maintained by Dr. Paul Neiman [16]; the T-cell and lymphoid libraries, maintained by Dr. Joan Burnside of the Delaware Biotechnology Institute [6].
Chicken 13K array performance
An image of the 13K array hybridized to RNA extracted from chicken brain and myc-transformed embryo fibroblast samples and independently labeled with Cy3™ or Cy5™ fluorescent dyes is shown in Figure 5. There is good discrimination between the two samples, as well as many commonly expressed genes. Of noted prominence is the striking difference in signal intensities associated with the spots located near the bottom of each block. These spots correspond to clones represented in the DT40/UD/DKFZ immune collection, which were originally selected with a bias towards highly expressed genes. Since the BBSRC clones are predominantly from highly normalized libraries and were chosen as non-overlapping with the original immune system set, this resulted in a survey of lower abundance and more tissue-specific transcripts.
Figure 5 Image of 13K array hybridized to brain (Cy5™) and myc-transformed fibroblasts (Cy3™). The array layout is 32 blocks in a 4 × 8 configuration and each PCR product is represented once, with the exception of negative controls, which are replicated in each block.
Reproducibility
Labeled samples were co-hybridized to the array for 16 hrs using standard protocols [12]. The same brain and fibroblast RNA extracts were also labeled by reversing the dye orientation and then co-hybridized to a second array. After image analysis, modest signal-to-noise (S/N) filtering, log base-2 ratio transformation, loess normalization, and corrections for the inverted dye orientations, the results from the two hybridizations were compared and were shown to be highly correlated (Figure 6; Pearson correlation coefficient, r = 0.972). The high correlation is indicative of a very high-level of technical reproducibility in array performance. Rare outlying data points and the slight deviation from a slope = 1, may reflect the influence of the different dyes used in the amino-allyl labeling.
Figure 6 Correlation of signals from chicken 13k array hybridized to brain and fibroblast RNA. Samples were each labeled with Cy3™ and Cy5™ to perform a dye swap comparison.
Signal-to-noise, specificity and sensitivity
We randomly chose one of the "myc-transformed embryo fibroblast vs. brain" array comparisons and determined the signal-to-noise (S/N) values for each channel using the background-corrected feature signals and the variation in the local background signal. Table 1 contains the results for the individual channels/samples. Of note is the high number of features with a S/N > 3.0, a value commonly used for defining the lower-bound threshold of detection. The mean S/N is also provided in Table 1 for each channel. These results reflect the significant detection capabilities obtainable in using the array. For example, the data from this representative comparison spanned the maximum fluorescent dynamic range of detection, from over 65,000 counts down to background count levels. In addition, the average local background signal for both channels was consistently low across the entire array, with no appreciable spatial block-level differences (see Table I). Furthermore, the variation in the local background signal was less than 38%. Taken collectively, the array provides a significant level of sensitivity for expression profiling.
Table I Chicken 13K cDNA Microarray Performance Metrics
Label / Sample Mean BG Signal Spot-Level S/N >3 Mean Spot-Level S/N
Cy3 / Fibroblast 118 ± 6 88.0% 35.1
Cy5 / Brain 48 ± 3 86.3% 38.3
± standard deviation of the mean
Figure 7 is a box plot of a "brain vs. brain" and a "myc-transformed embryo fibroblast vs. brain" comparison using the array. The y-axis is the Iog2-transformed (Cy3™/Cy5™) values for each comparison. The bar inside the box is the median value, the upper and lower dimensions of the box define the inter-quartile range, and the crossbars demark the 10th to 90th percentile range. The difference in the Iog2 ratio distributions between comparisons highlights the capabilities of the array to detect transcript-level differences between the fibroblast and brain samples.
Figure 7 Box plot of Iog2 ratios from arrays hybridized to brain labeled independently with Cy5™ and Cy3™ and brain versus fibroblasts. The y-axis is the Iog2-transformed values for each comparison. The bar inside the box is the median value, the box upper and lower dimensions define the inter-quartile range, and the crossbars demark the 10th to 90th percentile range.
The Venn diagram in Figure 8 (A,B) indicates the sample-specific "detectable signals" (spot-level S/N >3.0) from bursa, liver, brain, and myc-transformed embryo fibroblast. Note that signals were obtained for 7,422 spots with RNA from bursa, suggesting that this array provides wide coverage for experiments with lymphoid tissues. Excellent coverage of liver, brain and fibroblast transcripts was obtained as well. The identification of tissue-specific transcripts is noteworthy and reflects the clone selection process, which was designed to provide detection of mRNAs in a wide range of tissues, as well as low abundance, unique transcripts. It is of interest that the myc-transformed fibroblasts are a quail derived cell line; these results indicate that these arrays will be useful for studies in other gallinaceous birds.
Figure 8 Performance of amplified RNA (aRNA) and mRNA from different tissues. Common and tissue specific expression is illustrated in panels A and B. Panel C shows fair concordance of hybridizing spots between aRNA and mRNA;
In a separate experiment, T7 amplified, random-primer labeled RNA was compared with random-primer labeled poly A RNA (from the same preparation). Figure 8C shows a fair concordance with about 80% of the same spots showing hybridization with each sample. However, this comparison reveals that amplification loses some signals detected with mRNA but picks up others, presumably from low abundance messages which amplify better (with respect to the cDNA sequences on the chip) than average. In another experiment (not shown) repeat amplifications of the same RNA prep give satisfactorily consistent results (correlation coefficient >0.9). These results emphasize that it is important to use the same method of RNA preparation and labeling to obtain reliable comparisons.
Conclusions
An international consortium of researchers interested in using the chicken as both a model biological system and as an important agricultural commodity have consolidated resources to produce a microarray containing 13,000 features representing approximately 12,000 different mRNAs. These are now available to academic researchers through [email protected]. This array overlaps previous chicken immunology arrays and extends the coverage to 24 different tissues or cell types. In conjunction with the recent release of the chicken genome sequence, this tool will have wide application to studies in developmental biology, immunology, vaccine application, as well as identification of well-characterized complex traits. The availability of genomics tools will enhance the further development of the chicken as a powerful biological model.
Materials and methods
Libraries and array construction
BBSRC and UD clones were shipped to the FHCRC core genomics lab. Information on the libraries joined to produce this collection is available at individual web sites and previous publications [1,6,11,15]. Microarrays were constructed using modified protocols of those discussed by De Risi et al. [17]. Individual PCR products were verified as unique via gel electrophoresis and purified using the Millipore Multiscreen-PCR filtration system. Purified PCR products were mechanically "spotted" in 3X SSC (1X = 150 mM sodium chloride, 15 mM sodium citrate, pH 7.0) onto poly-lysine coated microscope slides using a GeneMachines OmniGrid high-precision robotic gridder (Genomics Solutions, Ann Arbor, MI). The array layout consists of 32 blocks in a 4 × 8 configuration and each PCR product is represented once on the array. In addition, each array sub-grid (i.e., "block") contains spots representing 4 different Arabidopsis genes (negative controls) and 1 spot consisting of sheared chicken (white leghorn) genomic DNA.
A GenePix scanner-compatible file (chicken 13k_v1.0.gal) is available on line [12]. For other scanners, this file can be opened in a text editor and used to construct a similar file that meets other image analysis software's format specifications.
RNA preparation, labeling and hybridization
Total RNA was prepared using Qiagen (Chatsworth, CA) RNeasy kits and amplified using a linear T7 promoter-based mRNA amplification method incorporating amino -allyl dUTP followed by random primer labeling with Cy™3 or Cy™ 5 (Amplification and labeling kits are available from Ambion, Inc., Austin, TX).
For hybridization, 10%, sodium dodecyl sulfate (SDS), 0.6 μl was added to the labeled RNA and heated at 99 C for 2 min. RNA was then centrifuged at 14,000 rpm for 3 min, and the sample cooled to room temperature. After placing an array slide in a hybridization chamber, 10 μl 3X SSC was added to the slide, away from the spotted area. RNA sample was then added to the array area and the cover slip promptly positioned over the array. The sealed hybridization chamber was incubated in a water bath at 63 C for 16 h. The slide was then washed for 2 min in a standard slide washing container, first in 1X SSC/0.03% SDS, then in 1X SSC, followed by a 20 min wash with agitation (60 rpm) in 0.2X SSC and a 10 min wash with agitation in 0.05X SSC. The slide was protected from light during the prolonged washes. The slide was then centrifuged (500 rpm × 5 min) to dry. Fluorescent array images were collected for both Cy3™ and Cy5™ using a GenePix 4000A fluorescent scanner (Axon Instruments, Inc., Foster City, CA) and image intensity data was extracted and analyzed using GenePix Pro 3.0 microarray analysis software.
Authors contributions
JB and PN generated UD and FHCRC clones, respectively. DB provided the BBSRC clones. JB and JT performed the analysis for clone selection. JD and RB fabricated the microarrays. PN, JD, RB performed the analysis and validation of the microarray. MA generated the annotation file.
Acknowledgements
This work was supported in part by FHCRC Pilot Project Funds and NIH grant R01 CA20068 to PN, the UD Chick EST project, the US Poultry Genome project (Hans Cheng and Jerry Dodgson), USDA-NRI grant 00-35205-9407 to JB and Robin Morgan.
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| 15694003 | PMC549535 | CC BY | 2021-01-04 16:39:33 | no | BMC Genomics. 2005 Feb 4; 6:13 | utf-8 | BMC Genomics | 2,005 | 10.1186/1471-2164-6-13 | oa_comm |
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Cancer Cell IntCancer Cell International1475-2867BioMed Central London 1475-2867-5-21570306510.1186/1475-2867-5-2Primary ResearchProton NMR visible mobile lipid signals in sensitive and multidrug-resistant K562 cells are modulated by rafts Mannechez Aurélie [email protected] Paiboon [email protected] Certaines Jacques D [email protected] Geneviève [email protected] Moyec Laurence [email protected] Laboratoire de Résonance Magnétique en Biologie et Médecine, Université Rennes 1, avenue du Professeur Léon Bernard, 35043 RENNES Cedex. France2 Laboratoire LPBC-CSSB, UMR CNRS 7033, Université Paris 13, 74 avenue, Marcel Cachin, 93017 Bobigny Cedex. France2005 9 2 2005 5 2 2 8 1 2004 9 2 2005 Copyright © 2005 Mannechez et al; licensee BioMed Central Ltd.2005Mannechez 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
Most cancer cells are characterized by mobile lipids visible on proton NMR (1H-NMR), these being comprised mainly of methyl and methylene signals from lipid acyl chains. Erythroleukemia K562 cells show narrow signals at 1.3 and 0.9 ppm, corresponding to mobile lipids (methylene and methyl, respectively), which are reduced when K562 cells are multidrug resistant (MDR). While the significance of the mobile lipids is unknown, their subcellular localization is still a matter of debate and may lie in the membrane or the cytoplasm. In this study, we investigate the role of cholesterol in the generation of mobile lipid signals.
Results
The proportion of esterified cholesterol was found to be higher in K562-sensitive cells than in resistant cells, while the total cholesterol content was identical in both cell lines. Cholesterol extraction in the K562 wild type (K562wt) cell line and its MDR counterpart (K562adr), using methyl-β-cyclodextrin, was accompanied by a rise of mobile lipids in K562wt cells only. The absence of caveolae was checked by searching for the caveolin-1 protein in K562wt and K562adr cells. However, cholesterol was enriched in another membrane microdomain designated as "detergent-insoluble glycosphingomyelin complexes" or rafts. These microdomains were studied after extraction with triton X-100, a mild non-ionic detergent, revealing mobile lipid signals preserved only in the K562wt spectra. Moreover, following perturbation/disruption of these microdomains using sphingomyelinase, mobile lipids increased only in K562wt cells.
Conclusion
These results suggest that cholesterol and sphingomyelin are involved in mobile lipid generation via microdomains of detergent-insoluble glycosphingomyelin complexes such as rafts. Increasing our knowledge of membrane microdomains in sensitive and resistant cell lines may open up new possibilities in resistance reversion.
Proton Magnetic Resonance SpectroscopyMultidrug resistanceMobile lipidsRafts
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Background
When studied by NMR proton spectroscopy, most cancer cells are characterized by increased narrow signals at 0.9 and 1.3 ppm corresponding, respectively, to methyl and methylene resonances that belong to lipid acyl chains moving isotropically. This so-called "mobile lipid signal" (or ML signal) has been studied for several decades (for review see[1]). However, research has failed to elucidate the molecular origin of mobile lipids, their subcellular localization or their physiological significance.
Regarding their molecular origin, acyl chains can form part of triglycerides or esterified cholesterol. Phospholipidic acyl chains may also be involved if they are not embedded in membrane lipid bilayers. As far as localization is concerned, two types of subcellular origin are still debated. As early as 1988 [2], Mountford et al proposed an origin in lipoprotein-like microdomains within the plasma membrane. More recently, some authors [3] have suggested the occurrence of cytosolic droplets, which appear concomitantly with the ML in stressed cells [4] or which are associated with necrosis [5] and apoptosis. However, it has been shown that ML intensity is not always correlated with the number of cytoplasmic droplets [6]. These studies (op cit.) tend to show that cytosolic lipid droplets generate mobile lipid signals in NMR spectra, without excluding the possibility that such signals could arise independently of the presence of cytosolic lipid bodies.
1H-NMR spectroscopy shows that ML are decreased in erythroleukemia K562 cells when these become resistant (K562adr)[7], whereas the compositions of lipids extracted from K562wt (drug sensitive) and K562adr cells are the same, except for sphingomyelin content which is increased in resistant cells [8]. Thus, although we may explain this by a structural difference in lipid "organization", the significance of such a behaviour is not yet elucidated. In a previous study [9], we showed that the ML signal is not linked to the externalization of phosphatidylserine (a membrane phospholipid), this being a phenomena that precedes apoptosis.
In model membranes, free cholesterol interacts with phospholipids and sphingolipids to influence membrane fluidity [10]. In vivo, cellular-free cholesterol is located in the plasma membrane [11], which exhibits increasing structural order as demonstrated in erythrocytes [12], LM and CHO cells [13,14]. Moreover, cholesterol in model membranes is able to promote microdomains towards an intermediate state called the liquid-ordered phase (Lo), with less fluidity than the gel phase state and more fluidity than the surrounding membrane in the liquid crystalline state [15].
The aim of this study was to investigate a possible contribution from the cholesterol-containing membrane domain to the ML detected in the NMR proton spectra of wild-type K562 and K562 adriamycin-resistant cells.
In a first set of experiments, cell membrane cholesterol was extracted by methyl-β-cyclodextrin (MCD). MCD is an oligosaccharid able to pump cholesterol out of the cell [16]. Moreover, cholesterol extracted by MCD originates primarily from the plasma membrane [17]. Cell incubation with MCD was expected to change the membrane microdomains via cholesterol extraction, and consequently produce variations in ML. In a second set of experiments, we used triton-X100 to separate membrane microdomains and then investigated their role in ML generation. In this study, we use the term "Detergent Insoluble Glycosphingolipid Complexes" (DIGCs) or "rafts" to refer to the membrane microdomains isolated by treatment with this mild non-ionic detergent (for review see [18]). Finally, as these raft microdomains are also enriched in sphingolipids, we used sphingomyelinase to modify their "organization", with the aim of inducing changes in ML signal intensity.
Results
Cholesterol quantification
K562wt and K562adr cells do not differ in their total cholesterol contents. The proportion of cholesterol-ester were found to be lower in the resistant cells than in the wild type cells (Table 1). This implies that K562wt cells contain more free cholesterol than K562adr cells. Total cholesterol content after MCD treatment (Table 1) shows a 45 % decrease in both K562wt and K562adr cells with respect to the control.
Table 1 Quantification of cholesterol in K562 cells. Results are expressed as means ± SD.
K562 wt K562adr
Total cholesterol (μg/106 cells) 3.6 ± 0.5 (n = 5) 3.5 ± 0.3 (n = 4)
Cholesterol ester (percentage of total cholesterol) 26.5 ± 1.3 (n = 6) 19.4 ± 2.4 (n = 5)
Cholesterol variation with MCD treatment (% of control) 57 ± 13 (n = 5) 54 ± 15 (n = 4)
Cell proliferation after incubation with methyl-β-cyclodextrin
The cell proliferation results for K562wt and K562adr are presented in Figs. 1 and 2. The two-hour incubation without FCS had no effect on proliferation in K562wt or K562adr when compared to cells incubated in RPMI+FCS. Treatment with MCD inhibited proliferation in K562wt. This was not the case with K562adr, which grew normally.
Figure 1 K562wt cells (up) and K562adr cells (down) were incubated for 2 hours in medium alone (WT RPMI; full line and square, n = 6) supplemented in FCS 10% (dot line and lozenge, WT R10; n = 6), in methyl-β-cyclodextrin 5 mM (dot line and triangle, WT MCD; n = 6) and successively incubated in R10 for 72 hours. Data points are the percentages of the cellular concentration normalized to cellular concentration at T = 0 hours expressed as means, with vertical bars representing standard deviation (SD).
Figure 2 K562adr resistance modulation after MCD treatment. K562adr cells were incubated for 2 hours in medium supplemented in SVF 10% (R10-DN; n = 4) or in methyl-β-cyclodextrin 5 mM (CD-DN; n = 4) and seeded in R10 containing daunorubicin for 72 hours. Data points are the percentages of the cellular concentration normalized to cellular concentration at T = 0 hours expressed as means, with vertical bars representing standard deviation (SD).
When K562adr cells were resuspended in R10 containing daunorubicin (0.25 nM), they were able to proliferate at this daunorubicin concentration. However, after treatment with MCD, the K562adr proliferation rate was decreased as shown in figure 2. This shows that MCD treatment reversed the resistance phenotype in K562adr; despite having no effect on cell growth, MCD affected the K562adr cell membrane.
Caveolin-1 expression: Western-Blot
Caveolin-1 expression was studied in K562 cells by SDS-page and western-blotting. Caveolin-1 is a protein of 21 kD [19]. As a positive control, we chose a protein extract of NIH-3T3 cells that are known to express caveolin-1. In this control, a band appeared between the 19 and 32 kD size markers. In the present study, however, neither K562wt nor K562adr expressed caveolin-1.
1H-NMR spectra
Incubation with methyl-β-cyclodextrin
Figure 3 shows spectra obtained on K562wt and K562adr cells, and resonance ratios are presented in Table 2. These results show that MCD increases the lipid signals only in K562wt cells. This increase can also be seen in Table 3, which reports a significant increase of CH3/Ct and CH2/Ct ratios in MCD-treated K562wt cells compared with non-treated cells.
Figure 3 NMR proton spectra obtained at D3 on K562wt (left side) and K562adr (right side) on control cells (top spectra) or treated with 5 mM MCD during 2 hours (bottom spectra). Peak assignment – 1: CH3 from fatty acid chains; 2: CH2 from fatty acid chains; 3: Alanine; 4 : glutamine and glutamate; 5: creatine; 6 N-trimethyl from choline, 7: Inositol; 8 : CH2 in β position from ester function in fatty acid ester; 9: CH2 in a position of a double bond in fatty acids; 10 : CH2 in α position from ester function in fatty acid ester.
Table 2 NMR peak ratios measured on K562wt and K562adr spectra. Cells were incubated for 2 hours in RPMI, or in RPMI containing methyl-β-cyclodextrin 5 mM (MCD). Results are expressed as means of arbitrary units ± SD multiplied by tenStatistical analysis : *: P < 0.05 when compared with RMPI incubated cells.
K562wt K562adr
Group RPMI (n = 6) MCD (n = 5) RPMI (n = 4) MCD (n = 4)
CH3/Ct 50 ± 5 101 ± 22* 34 ± 3 34 ± 2
CH2/Ct 247 ± 35 537 ± 13* 142 ± 22 130 ± 18
N+(CH3)3/Ct 23 ± 3 22 ± 7 17 ± 3 21 ± 16
Table 3 NMR peak ratios measured on K562wt and K562adr spectra. PBS: incubation in PBS; PFA: incubation in PFA; Triton : incubation in PFA and triton X; Smase: incubation in PFA, triton X-100 and 0.5 units sphingomyelinase. Results are expressed as means of arbitrary units ± SD multiplied by ten.
K562wt K562adr
Group PBS (n = 4) PFA (n = 7) Triton (n = 7) Smase (n = 4) PBS (n = 4) PFA (n = 7) Triton (n = 8) Smase (n = 5)
CH3/Ct 198 ± 21 231 ± 12 312 ± 42* 392 ± 105° 161 ± 19 192 ± 22 265 ± 62* 267 ± 42*
CH2/Ct 541 ± 52 611 ± 78 1060 ± 164* 1696 ± 441° 308 ± 93 386 ± 56 695 ± 141* 565 ± 167*
N(CH3)3/Ct 132 ± 6 141 ± 18 53 ± 10* 79 ± 17° 114 ± 12 132 ± 36 60 ± 15* 94 ± 39*
Statistical analysis : * : P < 0.05 when compared with PBS-incubated cells,
°: P < 0.05 when compared with Triton-treated cells,
Triton X-100 and sphingomyelinase treatments
spectra obtained after treatments with PFA, triton and sphingomyelinase are presented in Figures 4 and 5 for K562wt and K562adr cells, respectively. The ratios of the peak intensities with respect to the creatine peak are reported in Table 3. When compared to the control, PFA treatment did not modify the cell spectra. After microdomain separation by triton treatment, the CH2/Ct ratio was increased for K562wt cells and, to a lesser extent, for K562adr cells. N-trimethyl to creatine peak ratios were decreased in both cell lines. After treatment of these microdomains with sphingomyelinase, the spectra showed an increased CH2/Ct ratio compared with the previous spectrum obtained on "DIGCs" in K562wt cells. However, the spectra of K562adr cells treated with Smase remained unchanged compared with spectra obtained on DIGCs from K562adr cells.
Figure 4 K562wt 1H-NMR spectra: effects of Triton X-100 and sphingomyelinase treatments. A: non-treated cells; B: cells fixed with PFA; C: cells fixed with PFA 4% in triton-X100 1%; D: cells fixed with PFA 4% incubated in triton-X100 1% and with 0.5 units sphingomyelinase. For peak assignment, see figure 4. Peaks at 3.6 ppm after SMase treatment arise from enzyme working buffer.
Figure 5 K562adr 1H-NMR spectra: effects of Triton X-100 and sphingomyelinase treatments. A: non-treated cells; B: cells fixed with PFA; C: cells fixed with PFA 4% in triton-X100 1%; D: cells fixed with PFA 4% incubated in triton-X100 1% and with 0.5 units sphingomyelinase. H-NMR spectra: Triton X-100 and sphingomyelinase treatment. For peak assignment, see Fig. 4. Peaks at 3.6 ppm after SMase treatment arise from enzyme working buffer.
Discussion
We studied the modification of cell spectra using cholesterol and sphingomyelin because: i) cholesterol levels affect membrane fluidity; ii) membrane microdomains, rafts and caveolae are all enriched in these lipids. Western-blot did not detect the presence of caveolin-1 in either K562wt or K562adr. This confirms previous results showing the absence of caveolin-1 in K562wt [20]. Even if membrane microdomains exist in this cellular type, this implies they represent rafts and not caveolae.
Rafts have been described as corresponding to membrane microdomains enriched in cholesterol and sphingomyelin lipids [18]. In our first set of experiments, we disrupted the rafts using MCD to extract cholesterol from the cells. Before MCD treatment, K562wt and K562adr cells displayed the same cholesterol concentrations, which were found to be in agreement with previous results obtained for other cancer cells [21,22]. In K562wt cells, this cholesterol was preferentially in the form of cholesterol-ester, implying that the absolute concentration of free cholesterol is lower in K562wt cells compared with K562adr cells. 90% of the free cholesterol is contained in plasma membrane [11]. On the other hand, cholesterol-ester synthesized in the endoplasmic reticulum is generally localized in the cytosol and is able to form cytoplasmic lipid bodies. This cholesterol is less available to MCD extraction. Thus, MCD treatment may affect the free-cholesterol plasma membrane pool [17] and not the intracellular pool that mainly contains cholesterol-ester in K562wt cells. Consequently, in our study, a higher proportion of membrane cholesterol (corresponding to free cholesterol) was extracted in K562wt cells compared against K562adr cells. This may account for the fact that the proliferation rate for K562wt was more affected than for K562adr. Moreover, the removal of a greater proportion of membrane cholesterol modified the NMR proton spectra of the cells, since the mobile lipid signals only increased in the K562wt cells.
Nevertheless, we observe that MCD treatment affected the K562adr cell line. This is demonstrated by the reversion of daunorubicin resistance. In the plasma membrane, K562adr cells express the P-gp glycoprotein responsible for the extrusion of drugs. When K562adr cells were treated with MCD, the resistance to daunorubicin was decreased, showing that the P-gp is unable to extrude daunorubicin from the cells. P-gp has been widely reported to be sensitive to the lipid content of plasma membrane [23]. The present study shows that MDR is sensitive to the cellular cholesterol content. Indeed, it has been shown that drugs can accumulate in MDR cells grown in the presence of MCD [24].
This first set of experiments suggests that ML signals are generated during the disruption of membrane microdomains in K562wt cells, because MCD has been shown to extract cholesterol preferentially from membrane microdomains [17]. Overall, these results tend to show a link might exist between microdomains and the ML signal in K562 cells.
In a second set of experiments, we isolated rafts using triton X-100 at 4°C, a mild detergent in which they are insoluble [25]. We applied this method to K562wt and K562adr cells. NMR spectra obtained on these isolated raft fractions show an increase of the ML signals for K562wt and K562adr cells. In this particular case, this implies that ML could be produced by raft domains. Although it has been shown that raft structures are tightly packed at 4°C, there is no report of their ?organization/structure at 25°C, which is the temperature chosen for the NMR experiments [26]. At this temperature, microdomain lipids could be in another physical state allowing them to move more isotropically and produce an NMR-visible signal: their solubility in triton at 25°C supports this hypothesis [27].
In the final set of experiments, we incubated detergent insoluble fractions with sphingomyelinase, which was supposed to metabolise the sphingomyelin included in the rafts. Only the K562wt spectra exhibited an increase in ML signal compared with the raft spectra. Again, this suggests that microdomains are differently organized between K562wt and K562adr. Several hypotheses may be proposed to explain the difference between K562wt and K562adr: i) sphingomyelin concentrations are higher in K562adr; ii) lipid microdomains in K562adr may be organized in such a way that sphingomyelin is inaccessible to sphingomyelinase and iii) there are more microdomains in K562adr, as suggested previously by some authors [28].
Conclusions
These results suggest that, while isolated rafts generate ML signals within the membrane, the presence of rafts seems to maintain a relatively tight organization. When this organized structure is disrupted by MCD or sphingomyelinase, the ML signal may be detected in K562wt cells and the P-gp function can then be modulated in K562adr cells. Taken together, the results suggest that ML signals may be sensitive to modifications in the lipidic organization of the cells and membrane, in which microdomains behave as rafts enriched in cholesterol and sphingomyelin. A better knowledge of these microdomains, as well as the differences in behaviour between sensitive and resistant cells, could open up new therapeutic perspectives for reversing the drug-resistance phenotype.
Materials and Methods
Chemicals
Methyl-β-cyclodextrin, sphingomyelinase, cholesterol, chloroform, isopropanol and paraformaldehyde, as well as deuterium oxide (D2O) and all chemicals for western-blot analysis were provided by Sigma-Aldrich (Saint-Quentin Fallavier, France). Triton X-100 was supplied by Merck (Schuchardt, Darmstadt, Germany), and methanol by Acros Organics (Geel, Belgium).
Cell culture
Human erythroleukemia K562 cells were grown in the culture medium RPMI 1640 (Bio-Whittaker Europe, Verviers, Belgium) supplemented with fœtal calf serum (FCS) (10%) and glutamine (2 mM) (R10 medium) at 37°C and 5 % CO2. The K562 resistant variant cells (K562adr) were a gift from F. Calvo, Université Paris 7, and were grown in the same medium with 0.5 μg/ml adriamycin.
Cholesterol quantification
Lipids were extracted as previously described [29], and then desiccated and resuspended in isopropanol. Total cholesterol and free cholesterol were assayed using a kit (Cholesterol RTU, Biomérieux Craponne, and Boeringher, France) based on cholesterol esterase. This was followed by cholesterol oxidase reaction and colour development measured on an absorption spectrometer at 500 nm. Concentration was determined using a standard solution of 0.5 mg/ml cholesterol. We first checked that the solvent (isopropanol or chloroform) did not have any effect on colour development.
Cholesterol extraction using methyl-β-cyclodextrin
Cells were incubated in RPMI, glutamin 2 mM, containing methyl-β-cyclodextrin 5 mM for 2 hours at 37°C, 5% CO2. Controls were incubated in RPMI, glutamin 2 mM, with or without FCS 10% for 2 hours.
Proliferation
After incubation with methyl-β-cyclodextrin, with RPMI+ FCS or with RPMI (the last being used as a control for RPMI+FCS, considering that methyl-β-cyclodextrin is not used in the medium with FCS), cells were collected, washed and resuspended at 150,000 cells/ml in RPMI, glutamin 2 mM, FCS 10%. Cells were seeded in triplicate on 96-well microplates and incubated at 37°C and 5% CO2. Proliferation was assessed by counting cells with a cell coulter (Beckman Coulter, ZI model) at 24, 48 and 72 hours after seeding.
Caveolin-1 detection: western-blot
Cells were collected in late log-phase and washed twice in PBS 150 mM and were resuspended in loading buffer (urea 4 M, lauryl sulphate 3.8%, glycerol 20%, tris base 75 mM pH 6; β-mercaptoethanol 5%; bromophenol blue 5%) for 5 mn at 95°C. They were centrifuged at 12500 g, 4°C for 10 minutes, and 50 μg of extracted protein were deposited per well on an 8% acrylamide gel. Migration was performed in an electrophoresis buffer (TRIS base 125 mM; glycine 250 mM; lauryl-sulphate 0.1%, pH 8.1) for 1 hour at 125 V with a size marker (Kaleidoscope prestained standards Bio-rad). Protein was transferred on a nitrocellulose membrane for 2 hours at 80 V and 4°C in a transfer buffer (tris-base 48 mM; glycine 39 mM, SDS 0.037%, methanol 20%). Non-specific sites were blocked with 1% milk (Regilait, skimmed milk, Saint-Martin-Belle-Roche, France) in TBS 1X (tris-base 20 mM, NaCl 500 mM, and pH 7.5). The nitrocellulose membrane was incubated for 1 hour at room temperature with 1 μg/ml anti-caveolin 1 rabbit antibody (Tebu, France) and washed three times for 10 minutes with TBS before incubation for 1 hour at room temperature with goat anti-rabbit and conjugate secondary antibody (1:3000). After three washes in TBS for 10 minutes, staining was developed in a phosphatase alkaline buffer (NaHCO3 0.1 M; MgCl2, 6H2O 1 mM) with tetrazolium nitro-blue 3% in N,N-dimethylformamide 70% and bromo-4-chloro-3-indolylphosphate p-toluidine 1% in N,N-dimethylformamide 70% for 30 minutes at room temperature in the dark.
Triton treatment
Cells were collected at the end of the log-phase, 4 days after seeding, when ML were at a maximum, and washed twice with 1 ml PBS 150 mM at 4°C. They were resuspended in paraformaldehyde (PFA) 3% in PBS 150 mM for 30 minutes at 4°C and washed twice with 1 ml PBS 150 mM at 4°C to be resuspended in triton X-100 1% in PBS 150 mM at 4°C for 30 minutes. Cells or triton-insoluble fractions were collected and washed for NMR experiments at 25°C.
Sphingomyelinase treatment
After triton treatment, cells were collected, washed with PBS 150 mM and treated for 35 mn at 37°C with 0.5 units of sphingomyelinase. Cells were washed as described for NMR experiments at 25°C.
NMR analysis
Cells were washed twice in 1 ml PBS 150 mM, twice in PBS/D2O, centrifuged at 250 g and counted. Then, 107 cells were resuspended in 400 μl PBS/D2O before transfer to a 5-mm Shigemi NMR tube. Experiments were performed without rotation, and the ?analysed cell pellet was maintained in the coil volume in the Shigemi NMR tube.
The NMR proton spectra of whole cells were obtained at 25°C on a Unity Inova spectrometer (Varian, France) working at 500 MHz. One-dimensional runs were performed by accumulating 128 transients of 90° pulse with 2 s relaxation time. The signal from the residual water was suppressed by the presaturation technique, by using 0.03 mW irradiation for 2 s. Acquisition time was 1.34 s on 16K data points, corresponding to a spectral width of 6 kHz. The Fourier transform was applied without zero-filling using an exponential window multiplication function corresponding to 1 Hz line broadening. The resonances were integrated after automatic baseline correction. Two-dimensional COSY runs were performed with 2K data points in the F2 direction and 256 data points in the F1 direction. The two-dimensional Fourier transformation was applied after zero filling to 512 data points in the F1 direction with a sine-bell function in both directions. Each run consisted of a one-dimensional acquisition and a two-dimensional COSY spectrum. Peak assignments were based on data from the literature. The peak areas were measured by manual integration with the Bruker WINNMR software using a manual tangential baseline correction for each peak, and the assigned peak areas were normalized to the creatine peak area. The following resonances were integrated: methyl group (CH3 at 0.9 ppm), methylene group (CH2 at 1.3 ppm), choline N-trimethyl group (N+(CH3)3 at 3.2 ppm) and creatine (CH3 at 3.05 ppm). The values obtained for the different treatments of the two cells lines were compared by ANOVA analysis followed by a Student-Neumann-Keuls test for group-to-group comparison. P < 0.05 was considered as a significant value.
NMR proton spectra of PFA or triton- or SMase-treated cells were acquired at 500 MHz and 25°C on a Bruker Advance DMX500 spectrometer (Bruker, Wissembourg, France). The runs consisted of a 1D acquisition with similar parameters as the previous 1D spectra, and the spectrum analysis was performed as previously with Bruker WINNMR software.
The possible contribution of lactate to the 1.3 ppm signal was eliminated by analysing 2D Cosy spectra in whole cells, which resolved the resonances of lactate from fatty acid chains. In fixed cells, we calculated the ratio of the double-bond signal (CH = CH at 5.4 ppm) to CH2 peak area. As both groups belong to fatty acyl chains, this ratio remained constant since lactate did not significantly contribute to the increase of the CH2 signal [1].
List of abbreviations
NMR: Nuclear Magnetic Resonance; MDR: multi-drug resistance; ML: mobile lipid; K562wt: K562 wild type; K562adr: K562 adriamycin-resistant; MCD: methyl-β-cyclodextrin; DIGC: detergent-insoluble glycosphingolipid complex; FCS: fœtal calf serum; R10: RPMI culture medium with 10% FC; PBS: Phosphate buffer saline; TRIS: Tris(hydroxymethyl)-1,3-propanediol; TBS: TRIS buffer Saline; PFA: paraformaldehyde; COSY: correlated-spectroscopy; CH3: methyl; CH2: methylene; N(CH3)3: N-trimethyl; Ct: creatine
Authors' contributions
all authors contributed equally to this work
Acknowledgements
This work was supported by a grant from the Ligue Nationale Contre le Cancer.
Reungpatthanaphong P. was supported by the Royal Golden Jubilee PhD programme and the French Embassy in Bangkok, Thaïland. M.S.N. Carpenter post-edited the English style.
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| 15703065 | PMC549536 | CC BY | 2021-01-04 16:40:10 | no | Cancer Cell Int. 2005 Feb 9; 5:2 | utf-8 | Cancer Cell Int | 2,005 | 10.1186/1475-2867-5-2 | oa_comm |
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BMC Plant BiolBMC Plant Biology1471-2229BioMed Central London 1471-2229-5-11570118010.1186/1471-2229-5-1Research ArticleExpression of human dopamine receptor in potato (Solanum tuberosum) results in altered tuber carbon metabolism Skirycz Aleksandra [email protected]Świędrych Anna [email protected] Jan [email protected] Institute of Biochemistry and Molecular Biology, University of Wrocław, Przybyszewskiego Street 63/77, 51 – 148 Wrocław, Poland2 Max-Planck-Institute of Molecular Plant Physiology, Am Mühlenberg 1, D-14476 Golm, Germany3 Department of Plant Physiology University of Szczecin, Wąska Street 13, 71–415 Szczecin, Poland2005 9 2 2005 5 1 1 16 8 2004 9 2 2005 Copyright © 2005 Skirycz 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
Even though the catecholamines (dopamine, norepinephrine and epinephrine) have been detected in plants their role is poorly documented. Correlations between norepinephrine, soluble sugars and starch concentration have been recently reported for potato plants over-expressing tyrosine decarboxylase, the enzyme mediating the first step of catecholamine synthesis. More recently norepinephrine level was shown to significantly increase after osmotic stress, abscisic acid treatment and wounding. Therefore, it is possible that catecholamines might play a role in plant stress responses by modulating primary carbon metabolism, possibly by a mechanism similar to that in animal cells. Since to date no catecholamine receptor has been identified in plants we transformed potato plants with a cDNA encoding human dopamine receptor (HD1).
Results
Tuber analysis of transgenic plants revealed changes in the activities of key enzymes mediating sucrose to starch conversion (ADP-glucose phosphorylase and sucrose synthase) and sucrose synthesis (sucrose phosphate synthase) leading to altered content of both soluble sugars and starch. Surprisingly the catecholamine level measured in transgenic plants was significantly increased; the reason for this is as yet unknown. However the presence of the receptor affected a broader range of enzyme activities than those affected by the massive accumulation of norepinephrine reported for plants over-expressing tyrosine decarboxylase. Therefore, it is suggested that the presence of the exogenous receptor activates catecholamine cAMP signalling in plants.
Conclusions
Our data support the possible involvement of catecholamines in regulating plant carbon metabolism via cAMP signalling pathway.
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Background
The catecholamines (dopamine, norepinephrine and epinephrine) are a group of biogenic amines possessing a substituted 3, 4-dihydroxy phenyl ring that are widespread in the animal kingdom; but they have also been detected in plants [1,2]. The role of catecholamines in plants is poorly documented, but it is clear that they are involved in many aspects of growth and development. They were proposed as precursors for various alkaloids [3,4] and to be associated with processes such as ethylene production, nitrogen fixation, defence against herbivores, flowering, prevention of 3-indole acetic acid (IAA) oxidation and gibberellin signalling [5,6]. Analogous with animal cells in which catecholamines stimulate glycogen mobilization a similar role for catecholamines in the regulation of plant carbohydrate metabolism was suggested. Transgenic plants over-expressing tyrosine decarboxylase, which controls an important step of catecholamine synthesis, were characterized by highly increased concentrations of norepinephrine and soluble sugars, whereas starch level was dramatically decreased. Observed changes indicated a positive correlation of norepinephrine with soluble sugars and a negative correlation with starch [7]. The physiological action of catecholamines in animal cells is mediated by their interaction with G-protein coupled receptors that stimulate or inhibit the enzyme adenylyl cyclase (AC). In most animal cells cyclic AMP (cAMP) exerts its effect by activating cAMP dependent, serine-threonine protein kinase (PKA). Recently strong evidence for the occurrence and function of cAMP in higher plants has emerged [8]. It was demonstrated that cAMP levels in tobacco bright yellow 2 (TBY-2) cells are tightly connected to cell cycle progression [9]. The involvement of cAMP in gibberellin and ABA action has also been suggested [10,11]. Molecular evidence has shown the existence of plant protein kinases containing a high degree of sequence homology with PKA [12]. Moreover, molecular techniques led to the identification of cAMP response element-binding proteins (CREBs) [13], cyclic nucleotide-gated cation channels [14] and cAMP binding enzymes [15]. These data strongly indicate the involvement of catecholamines in regulating plant carbohydrate metabolism, possibly by a mechanism similar to that in animal cells. However, this suggestion is limited by the fact that to date no catecholamine receptor has been identified in plants. In the present study we characterize potato plants transformed with a cDNA encoding human dopamine receptor (HD1). The receptor is a rhodopsin-like integral membrane protein of 446 amino acids, seven transmembrane domains and molecular mass of 49 kDa. Our analysis revealed a regulatory effect of HD1 on carbohydrate metabolism including changes in key enzyme activities.
Results
Transgenic plant selection
Solanum tuberosum plants transformed with pHD1-BinAR, a plasmid carrying a cDNA for the human dopamine receptor under the control of the CaMV 35S promoter (Figure 1A), were pre-selected by means of PCR with the primers for neomycin phosphotransferase (kanamycin) gene and then selected by northern blot analysis with a HD1 specific cDNA as a probe (Figure 1B). Four transgenic lines showing the highest mRNA expression of the expected length (1300 bp) were chosen for further analysis by western blot (HD1.10, HD1.27, HD1.35 and HD1.36). Using commercially available monoclonal rabbit IgG anti-HD1 antibody a ~37 kDa protein band was detected in transgenic plants. It was absent from control plants (Figure 1C). Surprisingly the protein was ~10 kDa smaller than expected which may suggest posttranslational modification. Careful inspection of the cDNA sequence revealed the presence of two translational signals (232 bp and 313 bp) that would result in 40 kDa and 37 kDa proteins, respectively. However, as the translational machinery is very similar in plants and animals we suggest that the short form of receptor resulted from proteolytic action rather than de novo synthesis. It should be pointed out that a stronger signal for HD1 expression was accompanied by a stronger protein signal (lines HD1.10; HD1.35; HD1.36). Conversely in plants with weak HD1 expression, the protein signal was comparatively weak (line HD1.27). HD1 extraction with 1% Triton was much more efficient than extraction with 0.1%Triton in agreement with the expected membrane localization of the HD1 protein.
Phenotype analysis
Tubers of HD1 plants grown in a field were harvested after four months and analyzed. All examined transgenic lines produced more tubers per plant. The yield was not significantly changed since increase in tuber number was accompanied by decrease in tuber weight (Table 1). There were no obvious morphological differences between aerial parts of wild type Desiree and HD1 plants.
Catecholamine level
In order to develop an easy and reliable assay for the quantitative and qualitative determination of catecholamines in plants, the suitability of gas chromatography coupled to a quadruple mass spectrometer (GCMS) was recently investigated. A sensitive GCMS method based on the analysis of the trimethylsilylated catecholamine derivatives was developed to monitor the presence and concentration of these compounds and related metabolites. Based on the retention times and the mass spectra of standards the presence of dopamine, norepinephrine and a new compound normetanephrine in potato leaves and tubers was clearly detected [2].
In contrast to the previous studies performed on plants over-expressing tyrosine decarboxylase [7], which controls an important step of catecholamine synthesis, the goal of our work was to stimulate an alternative signalling pathway by introducing human dopamine receptor. Surprisingly the expression of dopamine receptor resulted in a more than two-fold increase of dopamine, norepinephrine and normetanephrine in all transgenic lines examined (Figure 2B). This increase of catecholamines content was accompanied by significant increase of tyramine and L-DOPA, which are direct precursors of dopamine (Figure 2A). Despite changes in concentration of catecholamines and their precursors, the level of tyrosine, which serves as a precursor for tyramine and L-DOPA, was not altered (data not shown).
Determination of carbohydrate content in tubers of transgenic plants
Following our recent finding that the action of dopamine and norepinephrine in potato is on starch mobilization, we decided to analyze transgenic tubers expressing dopamine receptor for soluble sugars and starch content. All transgenic plants showed decreased starch content, with levels that ranged from 20 to 60% percent of the wild type. This was accompanied by a significant increase in soluble sugar concentration ranging from 2.7 to 1.15 fold in comparison to Desiree (Figure 3). Concentrations of starch and soluble sugars were highly correlated. The calculated correlation coefficients between catecholamines content and the levels of glucose, sucrose, fructose and starch were 0.38, 0.69, 0.38 and -0.95, respectively.
Changes in carbohydrate are most likely responsible for the altered phenotype of transgenic HD1 tubers. Reduced tuber mass can be explained by decreased starch content whereas increased tuber number by the increase of soluble sugar concentration.
Sucrose – starch metabolism
Under normal growth conditions the major flux in potato tuber carbon metabolism is the conversion of sucrose through hexose phosphates to starch [16].
Since HD1 plants were characterized by changed concentrations of both soluble sugars and starch we measured the activities of enzymes involved in this pathway. Sucrose transported from leaves is symplastically unloaded from the phloem and degraded by sucrose synthase (SuSy). ADP-glucose phosphorylase (AGPase) converts glucose-1-phosphate (Glu-1-P) into ADP-glucose, an immediate precursor of starch. Both SuSy and AGPase are considered as key enzymes for starch synthesis [17].
Activities of AGPase and SuSy were significantly decreased in HD1 plants to 56% and 68% of the wild type level, respectively (Figure 4). In agreement with their roles in starch synthesis, and their proposed coordinated regulation, activities of both enzymes and starch content were all significantly correlated (cor >0.9).
Phosphoglucomutase (PGM) catalyzes the conversion of glucose-1-phosphate to glucose-6-phosphate. Tubers are characterized by the presence of cytosolic and plastidial isoforms of phosphoglucomutase. Repression of either of them results in plants with decreased starch levels pointing out the importance of the enzyme for starch accumulation [18,19]. The activity of PGM was significantly decreased in all transgenic lines, most likely contributing to the reduction in starch synthesis (Figure 4). Activities of other enzymes involved in sucrose-starch conversions (hexokinase, UGPase and starch synthase) were not changed significantly (Figure 4). In most of the transgenic lines inhibition of starch synthesis was accompanied by increased hexose-6-phosphates (Table 2).
To establish whether enhanced starch mobilization also contributed to the observed decreases in starch content we measured the activity of starch phosphorylase. In two out of the four examined transgenic lines the activity of starch phosphorylase was significantly increased, further contributing to decreased starch content of HD1 plants (Figure 4)
Moreover HD1 expression led to activation of sucrose phosphate synthase (SPS), responsible for sucrose production. Maximum SPS activity (measured wih saturating substrates, Vmax) only changed in two lines, whilst activity of the enzyme measured in the assay that contained limiting substrate concentration (Vmax/Km) and as a consequence 1/Km increased in all the lines.
1/Km, correlated well with the sucrose content of transgenic tubers (cor -0.81) (Figure 4).
Glycolysis/TCA cycle
The high concentrations of glucose and glc-6-P measured in the HD1 plants indicated changes in the glycolytic pathway. However, activities of glycolytic enzymes (hexokinase, phosphofructokinase and enolase) were not changed. The only exception was pyruvate kinase, which showed a significant decrease of activity in all transgenic lines (Figure 5). To investigate if this reduction of activity led to changes in carbon metabolism via the TCA cycle we measured the content of TCA intermediates. In all transgenic lines citric acid, isocitric acid and malate were significantly reduced, while fumarate showed a significant increase (Table 2).
Discussion
In contrast to the vast knowledge concerning the role and action of catecholamines in mammals, very little is known about the physiological significance of catecholamines in plants. Since most of the components of animal catecholamine signaling pathway have been also identified in plants (G-proteins, cAMP, PKA homologs) the involvement of catecholamines in plant signalling pathways is possible. Recently, the analysis of transgenic plants over-expressing tyrosine decarboxylase, which accumulate a high quantity of catecholamines, suggested a possible signalling effect on plant primary metabolism. The increase of catecholamines resulted in decreased starch concentration but increased soluble sugars [7].
The only component of mammalian catecholamine signaling pathway that to date has not been identified in plants is the catecholamine receptor. We transformed potato plants with a cDNA encoding human dopamine receptor (HD1) in order to analyze whether the presence of a receptor affects the endogenous catecholamine action. Western blot analysis showed that the protein was produced in transgenic plants and biochemical analysis of transgenic tubers revealed vast changes in carbohydrate metabolism and carbohydrate content. Surprisingly the catecholamine level was changed as well. It has to be pointed out that in contrast to plants over-expressing tyrosine decarboxylase, those expressing human dopamine receptor are characterized by increases of all known tuber catecholamines (dopamine, norepinephrine and normetanephrine). Whereas norepinephrine content was positively correlated with soluble sugars and negatively with starch, normetanephrine was considered as the product of norepinephrine turnover. Increased catecholamine content was accompanied by an increase of their precursors, tyramine and L-DOPA, suggesting upregulation of the biosynthetic pathway, mediated by tyrosine decarboxylase and tyrosine hydroxylase, respectively. It is hard to explain how expression of a human receptor triggers a positive loop leading to enhanced catecholamine synthesis and turnover. It is interesting to compare data on tuber carbohydrate levels from plants over-expressing tyrosine decarboxylase (TD) with those expressing human dopamine receptor. In both cases starch content is strongly decreased, this decrease was larger for HD1 plants (from 40% to 80%) than for TD tubers (from 12% to 60%) although the norepinephrine content was higher in TD plants (Figure 6). The norepinephrine content in TD plants was about four folds higher than in HD1 plants.
Therefore we suggest that the exogenous receptor activates catecholamine action in potato plants. A difference in enzyme activities involved in starch biosynthesis was noted. The sucrose level was comparable in HD1 and TD plants and consistent with enhanced activity of SPS. Activity of starch phosphorylase was significantly increased in both TD and HD1 plants but the decreases in activity for AGPase, SuSy and PGM was seen only for HD1 plants.
Expression of HD1 in potato (Solanum tuberosum) results in altered carbon metabolism
The previously reported positive correlation between catecholamine level and soluble sugars content and negative correlation with starch level for tubers of potatoes over -expressing tyrosine decarboxylase and in tubers stored at 4°C [2,7], was also found in our study. Expression of a dopamine receptor resulted in increased catecholamine content and was accompanied by decreased starch level and increases of glucose, fructose and sucrose content. It seems likely that the introduced dopamine receptor activates catecholamine action in carbohydrate metabolism. The question now arises whether catecholamine activates starch breakdown or inhibits its synthesis or whether both processes are affected.
In mammalian systems epinephrine and norepinephrine regulate glycogen turnover by stimulating glycogen mobilization and inhibiting glycogen synthesis. This appears similar in potato, with decreased starch content in HD1 tubers being a consequence of both inhibition of starch synthesis and enhanced starch mobilization. AGPase and SuSy, two key enzymes involved in starch biosynthesis, showed 44% and 32% decreases in their activities respectively. Also the activity of PGM was significantly decreased; we have not determined the contribution of the different isoforms (cytosolic and plastidial) to the observed changes. Increased content of hexose-6-phosphates demonstrates that a direct inhibition of AGPase, rather than a substrate shortage may cause inhibition of starch synthesis. Alternatively the increased hexose phosphate levels may be due to increased starch degradation in response to elevated catecholamine levels. This is supported by the increased activity of starch phosphorylase in two of four transgenic lines. The inhibition of starch synthesis and accumulation of hexose phosphates was accompanied by an increase of sucrose synthesis. Two factors should be taken into consideration. First, that SPS is subject to allosteric activation by Glc-6-P and inhibition by Pi. Second, elevated catecholamine content led to a decrease of SPS Km suggesting increase of the enzyme catalytic activty. Sucrose phosphate synthase has many potential sites of phosphorylation and three of them were shown to influence its catalytic activity. In spinach leaf, phosphorylation of Ser 158 is responsible for enzyme downregulation in darkness, phosphorylation of Ser 229 enables binding of 14-3-3 proteins and down- regulates the enzyme whereas phosphorylation of Ser 424 under stress conditions stimulates SPS activity. There is a growing body of correlative evidence that the potato tuber SPS is regulated in an analogous manner to the leaf enzyme [20].
Since the level of 14-3-3 proteins was not changed in any of the transgenic lines (data not shown) it is thus suggested that enzyme phosphorylation targeted to the stress site is responsible for its activity enhancement in HD1 plants.
In mammals the action of epinephrine and norepinephrine is mediated by phosphorylation of enzymes involved in glycogen mobilization and synthesis. Very recent studies reported direct evidence that enzymes of starch metabolism (amylopectin synthesis) are regulated by protein phosphorylation and indicate a wider role for protein phosphorylation in the control of starch anabolism and catabolism [21]. Therefore, it is possible that catecholamine action in plants could also involve phosphorylation of enzymes involved in starch metabolism.
Catecholamines – the new stress hormones in plants?
In mammalian systems, catecholamines serve as stress hormones increasing as a result of stress. In order to see whether or not a similar response occurs in plants, leaves of potato plants were wounded and catecholamines levels prior to and 5, 10 and 13 min after wounding were determined. Although the data varied, there was a consistent increasing trend in concentration of dopamine, norepinephrine and normetanephrine [2]. Very recently a similar increase in norepinephrine was measured in potato leaves subjected to ABA and water stress treatment. Activities of both tyrosine hydroxylase (1.5 and 1.7 fold) and tyrosine decarboxylase (2.33 and 1.2fold) were increased [22]. Under normal growth conditions the major flux in potato tuber carbon metabolism is the conversion of sucrose through hexose phosphates to starch [16]. During environmental perturbations like wounding [23,24] water stress [25], high temperature [26] and hypoxia [27,28] this balance is disturbed and, consequently, large changes in tuber metabolite levels occur. Elevated temperature or water stress leads to increased respiration, a decline in 3-phosphoglycerate (3PGA), inhibition of AGPase and consequently an inhibition of starch synthesis. Decreased starch was accompanied by a stimulation of sucrose synthesis caused by increased hexose posphate levels and activation of SPS via protein phosphorylation. The activity of SuSy was decreased whereas starch mobilization was suggested to increase. These changes in carbohydrate metabolism and carbohydrate content are very similar to those observed in HD1 plants, making it conceivable that catecholamines might play a role in plant stress responses by modulating tuber primary carbon metabolism.
Conclusions
Introducing humane dopamine receptor into plant cells can be considered as controversial but the obtained data would argue for the value of our approach.
Vast changes in the activities of key enzymes mediating carbon metabolism of potato tuber (in HD plants) led to a dramatic reduction of starch but increased sucrose content. The relation between catecholamine, primary carbon metabolism and stress seems possible. We speculate that similarly to situation in animal cells expression of HD1 in potato resulted in activation of the cAMP mediated signalling pathway. This can be supported by the result obtained for potato plants expressing another isoform of human dopamine receptor, HD2. In contrast to HD1, HD2 receptor does not affect activity of adenylate cyclase in animal cells.
Similarly plants expressing HD2 showed no changes in carbohydrate metabolism (data not shown). The obvious next step would be further investigation of our plants with respect to their kinase activity as well as cAMP levels. In parallel we have made efforts to identify a plant dopamine receptor.
Methods
Plant material
Potato plants (Solanum tuberosum L. cv. Desiree) obtained from "Saatzucht Fritz Lange KG" (Bad Schwartau, Germany) were cultivated in a greenhouse in soil under 16 h light (22°C) and 8 h dark (15°C) regime. Plants were grown in individual pots and watered daily. For analysis, the leaves were harvested at noon from 30-day-old greenhouse grown plants and the tubers were harvested in September, 3 months after the transfer of the tissue culture plants to the greenhouse.
Construction of a transgenic plant
The 1.3 kb SmaI, XbaI cDNA encoding HD1 from Homo sapiens ((kindly provided by Marc G.Caron (Duke University, Medical Center); [EMB: XX55760])), was ligated in the sense orientation into the same restriction site of the plant binary vector under the control of the 35S CaMV promoter and Nos terminator. The vector was introduced into the Agrobacterium tumefaciens strain C58C1:pGV2260 and the integrity of the plasmid was verified by restriction enzyme analysis. Young leaves of wild-type potato S. tuberosum L.(cv. Desiree) were transformed with A. tumefaciens by immersing leaf explants in bacterial suspension. A. tumefaciens inoculated leaf explants were subsequently transferred to callus induction medium and shoot regeneration medium. Transgenic plants were pre-selected by using PCR with the primers for the respective phosphotransferase (kanamycin resistance) gene and then selected by northern blot analysis with a HD1 specific cDNA fragment as probe.
Northern blot analysis
Total RNA was prepared from frozen plant material using the guanidinium hydrochloride method. Following electrophoresis (1.5% (w/v) agarose, 15% formaldehyde (w/v)), RNA was transferred to nylon membranes (Hybond N, Amersham, UK). Membranes were hybridised overnight at 42°C in 250 mmol sodium phosphate buffer (pH 7.2) containing 7% (w/v) SDS, 1% (w/v) bovine serum albumin (BSA) and 1 mM EDTA. Radioactively labelled full-length cDNA was used as a hybridisation probe. Filters were washed three times in 1 × SSC containing 0.5% (w/v) SDS at 65°C (highly stringent condition) or in the same buffer but at 42°C (medium stringent condition) for 30 min.
Western blot analysis
Proteins were extracted from frozen plant material using extraction buffer E (100 mM Hepes-NaOH, pH 7.4, 10 mM MgCl2, 1 mM EDTA, 1 mM EGTA, 20%glycerol (v/v), 0.5 mM PMSF, 70 mM beta-mercaptoethanol) supplemented either with 0.1% or 1% TritonX- 100 (v/v). The assessment of the expression of HD1 gene by means of western blot analysis using rabbit IgG anti HD1 protein was conducted as described previously. Briefly, solubilised protein was run on 12% SDS polyacrylamide gels (w/v) and blotted electrophoretically onto nitrocellulose membranes (Schleicher and Schuell). Following transfer, the membrane was sequentially incubated with blocking buffer (5% (w/v) dry milk), and then with antibody directed against the HD1 protein (1:2000 dilution). Formation and detection of immune complexes were performed as previously described [28]. Alkaline phosphatase-conjugated goat ant rabbit IgG at a dilution of 1:1500 was used as a secondary antibody.
Determination of starch and soluble sugar contents
Potato tuber slices and leaf discs were extracted with 80% ethanol-50 mM HEPES KOH, pH 7.4, at 80°C. The supernatant was used for enzymatic analysis of glucose, fructose and sucrose [29]. For starch measurement, extracted plant material was homogenized in 0.2N KOH, and following incubation at 95°C was adjusted to pH 5.5 with 1N acetic acid. Starch was hydrolyzed with amyloglucosidase, and the released glucose was determined enzymatically.
Tissue extraction for catecholamine content measurement
Frozen plant tissue (400 mg) was powdered in liquid nitrogen and extracted with methanol (4 ml per g-1 fresh weight), heated for 15 min at 70°C, and centrifuged (5 min., 12000 g). Samples were diluted with water to 50% methanol concentration and extracted with chloroform (1:1 v/v). A portion of the water phase was dried under vacuum and used for derivatisation [2]. Ribitol was used as an internal standard added directly to the sample homogenate (30 μg g-1 fresh weight).
GC – MS analysis
The dried extracts were incubated in pyridine/methoxyamine (20 mg mL-1) at 37°C for 90 min and then acidic protons were derivatised with N-Methyl- N-trimethylsilyltrifluoroacetamide (MSTFA) at 37°C for 90 min. 2 μl of sample was used for analysis [2]. A HP quadrupole mass spectrophotometer (HP 5972A), combined with a gas chromatograph HP 6890 and autosampler (all Hewlett Packard, Germany) and equipped with 30 m HP – 5MS, fused silica capillary column, was used. Injection temperature was 230°C, with the interface set to 250°C and the ion source adjusted to 180°C. The carrier gas used was helium set at a constant flow rate of 1 ml min-1. The temperature program was 5 min isothermal heating at 70°C, followed by a 5°C min-1 oven temperature ramp to 310°C and final 1 min heating at 310°C. The system was then temperature equilibrated for 6 min at 70°C prior to injection of the next sample. Mass spectra were recorded at 2 scan s-1 with an m/z 50 – 600 scanning range. The chromatograms and mass spectra were evaluated using the MSD ChemStation program (Hewlett Packard, Germany). As standards, dopamine, norepinephrine, normetanephrine, L-Dopa, tyramine and tyrosine (Sigma) were used. The recovery samples were spiked with dopamine, norepinephrine, normetanephrine, L-Dopa, tyramine and tyrosine; the estimated recoveries were 80, 93, 85, 95, 82, 90%, respectively. The following ions were used for quantification: ribitol 307; 319, L-Dopa 218; 267; 368, dopamine 174; 338; 426, norepinephrine 174; 355, 514, normetanephrine 174; 297; 456, tyramine 174; 264; 338, tyrosine 218; 280, 354. The amounts of catecholamines were determined from the ratio of peak areas of catecholamines to peak area of the internal standard (ribitol).
Preparation and analysis of samples for enzyme activities
Tissue was harvested, weighed and immediately frozen in liquid N2. 0.5 g ± 0.1 g tissue was homogenised in a chilled mortar in 2 ml of an extraction buffer containing 30 mM HEPES-NaOH, pH 6.9, 10 mM DTT, 1 mM MgSO4, 0.5 mM EDTA, 0.5% (w/v) BSA and 0.5% (w/v) PVP at 4°C. The homogenate was centrifuged at 16000 g for 10 min and the supernatant desalted using Sephadex G-25 columns. Enzyme activities were determined using the following published methods; SPS [30]; AGPase [31]; SuSy, PK [32]; PGM [33]; starch synthase [34]; PGI, enolase [35]; UGPase [36]; hexokinase [37] and starch phosphorylase as described by [38].
3.9. Statistical analysis
The t-tests were performed using the algorithm embedded into Microsoft Excel. The term significant is used when P < 0.05.
Authors' contributions
AS carried out the metabolic analysis of transgenic plants and drafted the manuscript. AŚ carried out the construction and selection of transgenic plants and performed the statistical analysis. JS conceived of the study, and participated in its design and coordination. All authors read and approved the final manuscript.
Acknowledgements
This work was supported by grant No. 3P06A 01523 from State Research Committee (KBN).
Figures and Tables
Figure 1 Selection of transgenic HD1 plants. Potato plant transformed with pHD1-BinAR construct carrying a cDNA for human dopamine receptor under the control of the CaMV 35S promoter (A) were selected by northern blot analysis (B). Lines showing the highest expression were further submitted to western blot analysis. For this purpose proteins were extracted with 0.1% or 1% Triton (C) and 50 μg of protein extract was run on 12% SDS polyacrylamide gel. D refers to control plants, numbers to different transgenic lines and S to Full Range Rainbow Molecular Weight Marker RPN 800 (Amersham Bioscience).
Figure 2 Catechoalmines analysis. GC-MS analysis of HD1 plants revealed changes in catecholamine levels. Concentration of catecholamine's precursors, tyramine and L-DOPA, is elevated as well. Results are mean ± SE of four independent measurements on three individual plants per line. Asterisks (*) indicate values that are significantly different from the wild type plants.
Figure 3 Sugars analysis. Tubers were harvested in September after 3 months of growth and the glucose, sucrose, fructose and starch contents were determined. Data represents the mean ± SE of determination on three individual plants per line. Asterisks (*) indicate values that are significantly different from the wild type plants.
Figure 4 Enzyme activities. The activity of enzymes involved in sucrose and starch metabolism in tubers of control (D) and HD1 plants. Enzyme activities were measured in the same tuber's samples as the one used for carbohydrate, catecholamine and metabolite analysis. Data represent the mean ± SE of determination on three individual plants per line. Asterisks (*) indicate values that are significantly different from the wild type plants. SPS – sucrose phosphate synthase; UGPase – UDPglucose pyrophosphorylase; AGPase – ADPglucose pyrophosphorylase; SuSy – sucrose synthase, PGM – phosphoglucomutase; PGI – phosphoglucoisomerase; SS – starch synthase
Figure 5 Glycolytic enzyme activities. Activities of the enzymes involved glycolysis in tubers of HD1 plants. Enzyme activities were measured in the same tuber's samples as the one used for carbohydrate, catecholamine and metabolite analysis. Data represent the mean ± SE of determination on three individual plants per line. Asterisks (*) indicate values that are significantly different from the wild type plants. PFK – phosphophructokinase; PK – pyruvate kinase.
Figure 6 Comparison of starch and catecholamine content measured in tubers from HD1 and TD plants.
Table 1 Phenotype analysis of HD1 plants revealed significant changes in single tuber mass and tuber number, whereas tubers yield was only slightly changed. Data represent the mean of determination on six individual plants per line. Asterisks (*) indicate values that are significantly different from the wild type plants.
Mean FW per tuber Tuber number per plant Tuber weight per plant
DESI 69.49 ± 5.5 7.33 ± 1.4 509.3 ± 70.3
HD1.10 50.38 ± 3.0* 10.00 ± 1.2* 503.8 ± 42.7
HD1.27 53.39 ± 18.4 12.66 ± 5.2 675.9 ± 254.6
HD1.35 31.43 ± 10.6* 13.66 ± 3.4* 429.3 ± 125.8
HD1.36 49.73 ± 4.0* 10.50 ± 0.9* 522.1 ± 43.2
Table 2 Metabolite analysis of HD1 plants revealed changes in glucose-6-phosphate, fructose-6-phophate and intermediates of TCA cycle. Data represent the mean ± SE of determination on three individual plants per line. Asterisks (*) indicate values that are significantly different from the wild type plants.
DESI HD1.27 HD1.35 HD1.36
Phosphate hexose
Glu-6-phosphate 4.823 ± 0,52 4.025 ± 0.36 5.605* ± 0.24 10.268* ± 0.79
Fru-6-phosphate 1,615 ± 0,14 1.301 ± 0.29 2.182* ± 0.27 4.264* ± 0.62
TCA cycle metabolites
isocitric acid 21.048 ± 3.09 16.463* ± 1.42 16.295* ± 1.27 20.606 ± 2.05
citric acid 375.434 ± 27.29 118.433* ± 16.63 153.121* ± 19.25 189.106* ± 16.73
fumaric acid 0.744 ± 0.067 2.611* ± 0.124 1.400* ± 0.137 2.653* ± 0.128
malate 76.478 ± 6.29 27.878* ± 3.45 65.754* ± 4.21 63.814* ± 3.56
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| 15701180 | PMC549537 | CC BY | 2021-01-04 16:03:52 | no | BMC Plant Biol. 2005 Feb 9; 5:1 | utf-8 | BMC Plant Biol | 2,005 | 10.1186/1471-2229-5-1 | oa_comm |
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Lipids Health DisLipids in Health and Disease1476-511XBioMed Central London 1476-511X-4-41570519110.1186/1476-511X-4-4ResearchChanges in lipids over twelve months after initiating protease inhibitor therapy among persons treated for HIV/AIDS Levy Adrian R [email protected] Lawrence [email protected] P Richard [email protected] Robert S [email protected] Greg [email protected] Uchenna H [email protected] Jayanti [email protected] Julio S [email protected] Department of Health Care and Epidemiology, University of British Columbia (UBC), Vancouver, Canada2 Centre for Health Evaluation & Outcome Sciences, St. Paul's Hospital, Vancouver, Canada3 BC Centre for Excellence in HIV/AIDS, St. Paul's Hospital, Vancouver, Canada4 St. Paul's Hospital HIV Metabolic and Lipid Clinic, Vancouver, Canada5 Bristol-Myers Squibb, Wallingford, Connecticut, USA6 Department of Medicine, UBC, Vancouver, Canada2005 10 2 2005 4 4 4 1 10 2004 10 2 2005 Copyright © 2005 Levy et al; licensee BioMed Central Ltd.2005Levy 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 inhibitors are known to alter the lipid profiles in subjects treated for HIV/AIDS. However, the magnitude of this effect on plasma lipoproteins and lipids has not been adequately quantified.
Objective
To estimate the changes in plasma lipoproteins and triglycerides occurring within 12 months of initiating PI-based antiretroviral therapy among HIV/AIDS afflicted subjects.
Methods
We included all antiretroviral naïve HIV-infected persons treated at St-Paul's Hospital, British Columbia, Canada, who initiated therapy with protease inhibitor antiretroviral (ARV) drugs between August 1996 and January 2002 and who had at least one plasma lipid measurement. Longitudinal associations between medication use and plasma lipids were estimated using mixed effects models that accounted for repeated measures on the same subjects and were adjusted for age, sex, time dependent CD4+ T-cell count, and time dependent cumulative use of non-nucleoside reverse transcriptase inhibitors and adherence. The cumulative number of prescriptions filled for PIs was considered time dependent. We estimated the changes in the 12 months following any initiation of a PI based regimen.
Results
A total of 679 eligible subjects were dispensed nucleoside analogues and PI at the initiation of therapy. Over a median 47 months of follow-up (interquartile range (IQR): 29–62), subjects had a median of 3 (IQR: 1–6) blood lipid measurements. Twelve months after treatment initiation of PI use, there was an estimated 20% (95% confidence interval: 17% – 24%) increase in total cholesterol and 22% (12% – 33%) increase in triglycerides.
Conclusions
Twelve months after treatment initiation with PIs, statistically significant increases in total cholesterol and triglycerides levels were observed in HIV-infected patients under conditions of standard treatment. Our results contribute to the growing body of evidence implicating PIs in the development of blood lipid abnormalities. In conjunction with the predominance or men, high rates of smoking, and aging of the treated HIV-positive population, elevated lipoproteins and triglycerides may mean that patients such as these are at elevated risk for cardiovascular events in the future.
HIV/AIDSprotease inhibitorscholesteroltriglyceridescardiovascular disease
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Introduction
Abnormalities in the lipid metabolism of persons infected with human immunodeficiency virus (HIV), potentially induced by the disease itself and the medications used for treatment, were first reported in the early 1990s[1]. Reductions in high- (HDL) and low-density lipoprotein (LDL) cholesterol were observed amongst persons infected with HIV and increases in triglycerides were observed among persons with AIDS[1]. Following the introduction of protease inhibitors (PI), morphological changes in fat distribution were reported. This was followed by numerous reports of metabolic disturbances, including glucose and lipid abnormalities presenting as insulin resistance, impaired glucose tolerance, hyperglycemia, type 2 diabetes mellitus [2-5], elevated serum triglycerides, LDL and very low density lipoprotein cholesterol, apolipoprotein B, E, and lipoprotein(a) [2-4,6]. The combination of metabolic disturbances and morphological changes are now described as the HIV-related "lipodystrophy syndrome"[2,3].
Up to one-half of subjects treated with PIs have shown elevated levels of triglycerides, total cholesterol (TChol), LDL, insulin, and fasting glucose [7-10]. The onset of metabolic changes appears to occur soon after initiation of treatment, often as quickly as within several weeks[11]. The high prevalence of disturbances of lipoproteins and triglycerides, the rapidity of their onset, and large changes that have been observed in randomized trials have led to concern regarding the potential impact of PIs on the cardiovascular health of persons with HIV/AIDS. However, the direction and magnitude of changes in plasma lipoproteins and triglycerides induced by PIs has yet to be quantified in an observational setting. The aim of this study was to quantify the magnitude of change in lipoprotein and triglyceride levels over twelve months following any initiation of PI-based treatment in a cohort of subjects treated for HIV/AIDS in a large tertiary care institution.
Methods
We included all antiretroviral naïve HIV-infected persons treated at St-Paul's Hospital, British Columbia (BC), Canada, who initiated use of PIs between August 1996 and January 2002. Plasma lipoprotein and triglyceride levels were obtained from measurements taken over the course of regular monitoring. Longitudinal effects of the impact of PIs on lipoproteins and triglycerides were estimated using statistical models that accounted for correlation due to repeated measurements on the same individuals.
Study Setting and Population
In BC, antiretroviral drugs have been centrally distributed at no cost to eligible HIV-infected individuals since 1986[12,13]. In October 1992, the HIV/AIDS Drug Treatment Program became the responsibility of the BC Centre for Excellence in HIV/AIDS. Since December 1996, the mainstay of treatment for HIV/AIDS has been highly active antiretroviral therapy (HAART) including two nucleosides and either a PI or a non-nucleoside reverse transcriptase inhibitor (NNRTI). Typically, HIV-infected subjects receiving antiretroviral therapy are monitored by physicians at intervals no longer than three months at which time prescriptions are renewed or modified based on clinical and laboratory parameters, and necessary laboratory tests are conducted. This research received ethical approval from the Institutional Review Board of Providence Health Care in BC.
Exposure to antiretroviral therapy for HIV/AIDS
At the BC Centre for Excellence in HIV/AIDS, records of CD4+ T-cell counts and a profile of dispensed antiretroviral therapy are routinely maintained, including the: prescription fill dates, medications prescribed, and amount dispensed. Records of dispensed antiretroviral medications, (including nucleoside analogs, PI and NNRTI) were used to determine the drugs dispensed and available to each subject during each month of follow-up. Subjects were considered unexposed until the first month that a PI was dispensed. The exposure at the time of the lipid measurement was calculated as the cumulative number of consecutive months of drug exposure up until and including the month in which a measurement was taken. As we were interested in estimating changes that occur in plasma lipoproteins and triglycerides within the first year after treatment initiation, we included measurements with a cumulative PI exposure up to a maximum of twelve months. Subjects were considered unexposed thirty days after the last PI was dispensed and, at that time, the cumulative exposure was set to zero.
Plasma lipoproteins and triglycerides
Approximately one-half of HIV-infected patients in BC are followed at one treatment centre located at St. Paul's Hospital, a large teaching hospital in Vancouver. For these subjects, in addition to virological testing, the hospital laboratory records the results of plasma lipoproteins and triglycerides. Subjects were routinely instructed to fast for 12 hours prior to the sample being drawn. Blood samples were collected in 10-1 EDTA-coated vacutainer tubes. Plasma was separated by centrifugation for 10 minutes at 2,000 revolutions per minute. TChol in the plasma was determined using an enzymatic method[14] and plasma triglyceride was determined as previously described[15]. HDL cholesterol was determined using a heparin manganese precipitation of apo B-containing lipoproteins[16] and LDL cholesterol was calculated using the Friedewald formula[17,18].
For some subjects, the first lipid measurement was taken prior to the dispensation of any antiretroviral drug ("treatment naïve" baseline lipid measurements). Other subjects had their first recorded plasma lipoproteins and triglycerides after HAART was initiated (initiation lipid levels).
Statistical analysis
We used linear mixed effects models[19] to estimate the effect of PI-based HAART on changes in plasma lipoproteins and triglycerides over twelve months. As blood lipid levels were always greater than 0, the responses were log transformed prior to model fitting. Effect estimates were obtained via restricted maximum likelihood estimation using the R© function lme(.). An analysis of variance indicated that simple parallel-line models, where the exposure effect was assumed to be constant over subjects, could adequately explain variation in the data compared to more complex models with random slopes. To account for correlated responses due to repeated measurements on the same individual, the correlation structure of the model was specified to include only a random intercept for each subject.
The following explanatory variables were included in the models: age, sex, and CD4+ T- cell count at PI initiation, concomitant use of NNRTI, and a measure of adherence to antiretroviral therapy. Exposure to NNRTI was considered time-dependent and quantified using the same algorithm that was used to calculate time dependent PI exposure. Adherence was calculated by dividing the number of months of antiretroviral medications dispensed by the number of months of follow-up in the first twelve months after treatment initiation. Incomplete adherence represents the gap between the time that the previous medication supply ran out until the next refill date, and/or until the last contact date with the program. This method is reliably associated with both clinical outcomes and un-timed drug level monitoring[20,21].
For each outcome and associated regression coefficient β, the quantity exp(β)-1 represented the adjusted monthly percent change in that plasma lipid fraction. These values were annualized using the formula exp(12 × β)-1. Ninety five percent confidence intervals (95% CI) for the effect estimates were obtained using the standard error for each regression coefficient.
Two sensitivity analyses were conducted. The first analysis involved restricting the analysis to lipid measurements which were taken on subjects prior to any change from baseline antiretroviral therapy. The second sensitivity analysis included only subjects who had lipid measurements taken prior to initiation of therapy.
Results
There were 679 subjects who were eligible for analysis, 91% of whom were male (Table 1). The median age was 38 years at initiation of therapy and the median baseline CD4+ T-CELL COUNT was 210 cells/mm3. All subjects initiated therapy that included a nucleoside analog and a PI.
Table 1 Demographic and clinical characteristics at treatment program enrollement among 679 subjects treated with PI-based HAART initiation for HIV/AIDS at St Paul's Hospital, Vancouver, BC, August 1996 – January 2002
Characteristic*
Age (y)
Mean (SD) Median 39 (8.9) 38
Sex (% male) 91
Status (% alive) at end of follow-up 93
CD4 (cells/mm3)
Mean (SD) Median 255 (222) 210
Abbreviations: SD = Standard deviation; PI protease inhibitor.
Subjects were followed for a median of 47 months (Table 2). During that follow-up time, subjects had a mean of 73% of months in which a PI had been dispensed, with a mean of 31 prescription refills. The mean adherence in the first year was 89%, and the median adherence was 100% indicating that more than one-half of subjects were dispensed all their medications.
A total of 3,010 lipid measurements were used in the analysis, with 400 subjects having had two or more lipid measurements during the course of follow-up. There were a median of 3 (IQR 1–6) measurements per subject. The median time between lipid measurements was 3 (IQR 2–5) months for all subjects.
Table 2 Use of PIs among 679 subjects initiating PI-based HAART for HIV/AIDS at St Paul's Hospital, Vancouver, BC, August 1996 – January 2002
Characteristic*
Number of months between initiation of PI and end of observation, median (IQR)** 47 (29–62)
% of follow-up time with dispensed therapy mean (SD), median for PI 73 (30) 84
Mean (SD) number prescriptions for***
PI 31 (19)
% adherence in first year
mean (SD) 89 (21)
median (IQR) 100 (92 – 100)
Abbreviations: SD = Standard deviation; IQR = Interquartile range; NRTI = nucleoside reverse transcriptase inhibitors; PI protease inhibitor; NNRTI = non-nucleoside reverse transcriptase inhibitor
* PIs available during follow-up included: indinavir, nelfinavir, saquinavir, and ritonavir. All data taken from time of first therapy initiation (treatment program enrollement).
** Time between first dispensation of HAART (enrollment) and last date of follow-up.
*** All prescriptions are of 30 day duration
Table 3 shows the percentage change in plasma lipoprotein and triglyceride levels after 12 months of PI use, after adjustment for age, sex, and CD4+ T- cell count at initiation, concomitant use of NNRTI, and adherence. Statistically significant increases of about 20% were observed in TChol, the lipoprotein fractions, and triglycerides.
Table 3 Baseline plasma cholesterol and triglycerides and estimated percent changes after 12 months when using PI among 679 subjects treated for HIV/AIDS at St Paul's Hospital, Vancouver, BC, August 1996 – January 2002
Number of measurements (subjects) Mean lipid baseline measurements (SD) % change* (95% CI)
TChol 1620 (529) 4.2 (1.0) 20 (17, 24)
HDL 1250 (419) 1.0 (0.3) 22 (15, 29)
LDL 677 (295) 2.5 (0.8) 12 (5, 20)
N-HDL 1247 (419) 3.1 (1.2) 20 (15, 26)
TRG 1743 (556) 1.9 (1.2) 22 (12, 33)
Abbreviations: PI protease inhibitor; TChol = total cholesterol; HDL = high-density lipoprotein cholesterol; LDL = low- density lipoprotein cholesterol; N-HDL = Non-HDL Cholesterol; TRG = triglycerides
* Adjusted for age, sex, and CD4+ cell count at first prescription for HAART, concomitant use of non-nucleoside reverse transcriptase inhibitor and adherence to antiretroviral therapy in the first year of treatment
The sensitivity analyses indicated that the models were robust to changes in the sub-population studied and the exposures that were included. In the analysis that included subjects who had a baseline measurement prior to start of HAART, a plasma profile prior to antiretroviral therapy initiation showed a similar pattern but with wider confidence intervals. In the analysis which was restricted to lipid measurements taken on subjects prior to switching from baseline therapy, the effect estimates were similar to those in Table 3.
Discussion
In patients treated for HIV infection with HAART in a naturalistic setting, we observed that treatment with PIs was estimated to result in 20% increases in the levels of total cholesterol, HDL- and LDL-cholesterol and triglycerides twelve months after treatment initiation. Our results contribute to the growing body of evidence implicating PIs in the development of blood lipid abnormalities[22] and are in keeping with findings of randomized trials where a change from PI-based HAART to NRTI- or NNRTI-based HAART was associated with improvements in the lipid profile[23]. The observed increases in LDL-cholesterol and triglycerides were expected based on results reported from randomized trials. The finding of an increase in HDL-cholesterol has been reported only in some[24] but not all randomized trials.
Low HDL levels and other forms of dyslipidemia, and disturbances in glucose metabolism, as well as central obesity, have been shown to be strong independent risk factors for cardiovascular morbidity and mortality in the general population[25,26]. Furthermore, the clustering of risk factors leads to greater cardiovascular morbidity and mortality than would be expected to occur in relation to each component alone[25]. These factors, when considered together, provide grounds to suspect that persons being treated for HIV infection with PI are at an increased risk of cardiovascular disease[8]. The increases in triglycerides caused by use of PI is of concern because there is growing evidence that these lipids are an independent risk factor for cardiovascular disease[27,28].
Two large observational cohort studies, published in 2003, showed discrepant results regarding the risks of cardiovascular disease among persons treated with HAART[29,30]. A retrospective administrative claims database study from the US Veteran's Affairs indicated that there was no relation between the use of antiretroviral therapy and the risk of cardiovascular or cerebrovascular hospitalizations [29]. A prospective multi-country collaborative study, with clinical events validation from eleven cohorts of HIV-infected persons showed that the incidence of myocardial infarction increased with longer exposure to combination antiretroviral therapy[30].
This study has a number of features that add credence to the results. First, while only based at one hospital, the study population comprised about one-half of the treated population in BC. The study sample had similar demographic composition (age and sex) and CD4+ T-cell count at initiation of therapy as other treated subjects in the province. We believe that these results are therefore generalizable to PI-regimen treated HIV-infected patients in BC, as well as to other target populations with similar demographic characteristics. Second, as all dispensed PIs and other antiretroviral medications are paid for and recorded centrally, there was complete information on all HAART medications available to all study subjects. We adjusted for adherence using each subjects' refill compliance in the first year of treatment. Third, data on the plasma lipid profile, including both lipoproteins and triglycerides, were of high quality. The measurements, while lacking the feature of being taken at uniformly spaced intervals as in closely monitored system such as randomized trial, represent the actual experience in an observational setting. Fourth, the enrollment period lasted over five years, allowing a large sample size. We employed repeated measures analyses to account for the correlated structure of the data.
This study was also subject to several limitations. First, lipid measurements were not collected in a predetermined manner as is typical in a prospective research study. Consequently, the timing of measurements was irregular and not all lipid fractions were measured when blood was drawn. Second, despite instructions some subjects may not have fasted for the full 12 hour period prior to blood draws. Non-fasting triglyceride measurements are still useful for predicting cardiovascular disease and death[31]. Third, other potent risk factors for changes in lipid profiles such as family history and diet were not considered. It is possible but unlikely that the type of triple therapy prescribed by physicians could have been influenced by the belief that PIs may negatively impact lipid levels, likely leading to an attenuation of the estimates. Fourth, a number of factors contributed to a bias towards underestimating the true changes: for some subjects baseline values were not obtained prior to treatment initiation; it was not possible to adjust for concomitant use of lipid modifying agents such as statins because these data were not available; subjects with large changes in their lipid profiles may have been switched to another class; and treatment interruptions would also have affected exposure estimates. As a result of these limitations, the actual changes in plasma lipoprotein and triglycerides may be greater than reported in this study. Fifth, we assumed that patients who stop therapy or skip a month of therapy can be modelled as treatment naïve with respect to any subsequent therapy. More sophisticated statistical techniques are available[32] for handling this limitation, but appropriate software and resolution of technical issues are still in the developmental stages. Lastly, it is possible that the PI effect on lipids and triglyceride levels is not a class effect. The recently introduced PI, atazanavir sulfate, has been shown in several randomized clinical trials not to adversely affect lipid levels [33-38].
Due to changes in the HAART regimen that occurred because of resistance, non-compliance, or other reasons, it was not possible to isolate the effect of individual PIs. Over the period under study, most subjects initiating PI-based HAART were prescribed either indinavir or nelfinavir.
Treating PI-induced dyslipidemia
As PI-based HAART is very effective in increasing survival in HIV-infected patients[39], discontinuing PI is undesirable, even in patients with dyslipidemia. However, as PI-induced dyslipidemia is often asymptomatic and typically occurs in younger patients whose baseline risk of cardiovascular disease is low, the need for primary prevention is often under-appreciated in clinical practice[40]. When it is recognized, rather than discontinuing or switching PI therapy, one response is to initiate pharmacologic therapy with statins and/or fibrates[41].
Statins have been shown to be effective drugs to prevent cardiovascular disease in non-HIV patients[26]. While the role of statins in preventing cardiovascular disease in HIV patients remains to be demonstrated definitively, several smaller randomized controlled trials that have shown that these medications have beneficial effects on PI-induced dyslipidemia [42]. Until recently, pravastatin was the preferred statin for treating PI-induced dyslipidemia because it does not require metabolism by the cyp 3A4 system. However, recent studies have shown that moderate lipid lowering with pravastatin was less effective than intensive lipid lowering with atorvastatin in reducing: progression of atherosclerotic lesions [43] in patients requiring coronary angiography; and death or major cardiovascular events in patients with an acute coronary syndrome[44]. Atorvastatin is a powerful and effective statin, though there are still only limited published studies with this agent in HIV patients[45]. Because of metabolism by cyp 3A4, the dose of atorvastatin should be reduced one-half in patients receiving PIs. Lovastatin and simvastatin require metabolic activation by cyp 3A4 and should be avoided in patients receiving PIs. Rosusvastatin, a recently introduced statin has features that make it attractive for treating patients with PI-induced dyslipidemias: it does not require metabolism by the cyp 3A4 system and it effectively reduces LDL cholesterol. The safety and effectiveness of rosuvastatin in reducing clinical outcomes in HIV patients remain to be demonstrated.
Fibrates are effective in lowering triglycerides and increasing HDL and have been shown to be effective in HIV patients[42]. Despite the impact on plasma lipids and triglycerides, only one trial has shown fibrates to reduce clinical outcomes[46,47]. Therefore, the role of fibrates in reducing cardiovascular disease outcomes remains to be fully elucidated. The main role of fibrates is to reduce the risk of pancreatitis associated with hypertriglyceridemia. In HIV patients, gemfibrozil should be limited to monotherapy because of the risk for myopathy. Fenofibrate is the preferred drug if combination therapy with a statin is contemplated. The efficacy of other lipid lowering drugs such as niacin and cholesterol transport blockers (ezetimibe) remains to be demonstrated. Bile acid sequestrants are contraindicated in patients receiving HAART.
We conclude that there was an estimated 20% increase in lipoproteins and triglycerides in the first year after initiating PI-based antiretroviral therapy in HIV-infected patients under conditions of standard treatment. Whether these increases continue beyond one year is of considerable interest because lipoproteins and triglycerides are known risk factors for cardiovascular disease. In conjunction with the predominance or men, high rates of smoking, and aging of the treated HIV-positive population, elevated lipoproteins and triglycerides may mean that patients such as these are at elevated risk for cardiovascular events in the future.
Acknowledgements
The authors gratefully acknowledge the following persons: Dr. Frances Rosenberg, Ms. Linda Row and Ms. Angie Lim from Department of Pathology at St Paul's Hospital for providing access to blood lipid measurements; to Ms. Benita Yip and Mr. Keith Chan for preliminary data analysis, and to Anne Drummond PhD for editorial support.
Financial support: Partial funding for this study was provided by an unrestricted grant from the Bristol-Myers Squibb Company.
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| 15705191 | PMC549538 | CC BY | 2021-01-04 16:39:19 | no | Lipids Health Dis. 2005 Feb 10; 4:4 | utf-8 | Lipids Health Dis | 2,005 | 10.1186/1476-511X-4-4 | oa_comm |
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BMC Med EducBMC Medical Education1472-6920BioMed Central London 1472-6920-5-71570519310.1186/1472-6920-5-7Research ArticleComparison of knowledge scores of medical students in problem-based learning and traditional curriculum on public health topics Gurpinar Erol [email protected] Berna [email protected] Gazanfer [email protected] Reyhan [email protected] Akdeniz University School of Medicine Department of Medical Education, Antalya Turkey2 Dokuz Eylul University School of Medicine Department of Medical Education, Izmir Turkey3 Dokuz Eylul University School of Medicine Department of Public Health, Izmir Turkey2005 10 2 2005 5 7 7 10 11 2004 10 2 2005 Copyright © 2005 Gurpinar et al; licensee BioMed Central Ltd.2005Gurpinar 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 purpose of the study was to compare the knowledge scores of medical students in Problem-based Learning and traditional curriculum on public health topics.
Methods
We planned a cross-sectional study including the fifth and sixth year medical students of Dokuz Eylul University in Turkey. The fifth year students (PBL group, n = 56) were the pioneers educated with PBL curriculum since the 1997–1998 academic year. The sixth year students (traditional education group, n = 78) were the last students educated with traditional education methods. We prepared 25 multiple-choice questions in order to assess knowledge scores of students on selected subjects of Public Health. Our data were collected in year 2002.
Results
Mean test scores achieved in PBL and traditional groups were 65.0 and 60.5 respectively. PBL students were significantly more successful in the knowledge test (p = 0.01). The knowledge scores of two topics were statistically higher among PBL students. These topics were health management and chronic diseases.
Conclusion
We found that mean total evaluation score in the PBL group was 4.5 points higher than in the traditional group in our study. Focusing only on the knowledge scores of students is the main limitation of our study. Upon the graduation of the first PBL students in the 2002–2003 academic year, we are planning additional studies regarding the other functions of a physician such as skill, behaviour and attitude.
==== Body
Background
During the last 25 years, ideas concerning the aim, structure and system of medical education have been discussed. Debates generally have arisen from the perception that medical education couldn't serve the purpose of improving health standards of the communities [1].
"Health for All" was adopted in 1977 and launched at the Alma Ata Conference in 1978 to underline the fact that large numbers of people and even whole countries were not enjoying an acceptable standard of health [2]. In order to achieve the goal of "Health for All" and to improve the health standards, medical schools must provide physicians who are familiar with the community and its health problems, their prevention and solutions. Then their curriculum must be expedient to this goal [3,4]. World Health Organization (WHO) also emphasizes the fact that medical students must be educated considering the health needs of the population in which they live [5].
In the Edinburgh Declaration of the World Medical Association in 1988, similar problems were mentioned and the purpose of the medical education was declared as training physicians capable of improving communities' health standards. This declaration suggested that medical education should be focused on common health problems of the large communities, and the medical school curriculum should be restructured according to the health requirements of the community. According to the declaration, medical students must gain professional skills and social values in addition to theoretical knowledge and the principle of lifelong medical education should be adopted [6].
The ideas and suggestions mentioned above have aroused strong winds of change in the medical education arena. Mc Donald et al. from Mc Master University determined an approach based on the community's main health problems and stressed the importance of focusing on these problems while designing their medical school's curriculum [7].
Since then, this approach has been adopted by many medical schools all over the world. The schools which designed their curriculum according to the priority health problems of the community, managed to raise the physicians' awareness of their community and the preventive measures and solutions of their main health problems.
In Turkey, problems of medical education have been discussed since early 1970s. Several studies showed that the goals of medical education did not overlap with the health requirements of the Turkish community. The education of health professionals was abstracted from the realities of the country. In 1990s Turkish Parliament and Turkish Medical Association determined and reported the difficulties of medical education. In a 1991 report of the Turkish Parliament, the facts that the number of qualified physicians who were trained according to the health needs of the country was limited and that this number was not sufficient to improve its health standards were underlined. Several deans from different medical schools of the country contributed to Turkish Parliament's study and reported that a greater importance should be given to the health problems of the population while planning the educational programs and the medical education should not be restricted to the university hospitals [8].
In The Turkish Medical Association's report the fact that medical education was not relevant to health needs of the country was emphasized. New medical graduates were not fully aware of common national health problems. The recommendations of the Turkish Medical Association to improve the health standards of the Turkish population were; training the general practitioners capable of working effectively in the primary health care and restructuring the medical education on a community basis and implementing Problem-based Learning methods [9].
International developments and the reports of Turkish Parliament and Turkish Medical Association led the faculty of Dokuz Eylül University School of Medicine (DEUSM) to seek solutions to the problems mentioned in the reports. As a result, Problem-based Learning (PBL) a more active and student-centred learning- was adopted and launched in the 1997–98 academic year. One of the main features of the education program was its relevancy to the philosophy of community-based medical education [10].
The curriculum of DEUSM was structured considering social, biological, behavioural and ethics objectives of medical education. The curriculum was structured in a modular system and adopted to a spiral configuration providing horizontal and vertical integration. During the first three years of undergraduate education, PBL sessions are the main focus of a modular structure. The weekly schedule of a module allowed for all the educational activities such as PBL sessions, lectures, field studies, communication skills and clinical skills courses lectures existing one hour a day in the weekly program support the PBL sessions and independent learning [11].
PBL sessions were based on written problems, which are likely to happen in real life. Special emphasis was also given to the integration of knowledge, acquisition of professional and moral values and to the development of communication skills.
Medical knowledge and practical skills that a physician is supposed to have were on the basis of the advice of Turkish Medical Association and the faculty departments. The Department of Public Health also contributed to the education program by setting social standards and determining the most important health problems of the community.
PBL Curriculum of DEUSM aimed to teach the students the main health problems of the community, their prevention and ways of treatment.
Public Health topics of Dokuz Eylül University School of Medicine consists of;
• Holistic approach in health,
• Basic principles of Public Health,
• Personal and social points of view on health events,
• Bio-psychosocial (holistic) approach to any individual,
• Principles of preventive medicine,
• Structure and mechanisms of national health organization,
• Demographic structure and trends, factors affecting them,
• Basic principles of planning and conducting a scientific research on health,
• Sound knowledge on leading health problems of the country, personal and social approaches for their solutions,
• Environmental and occupational factors threatening community health and their prevention.
Cases in the scenarios of the PBL modules were selected among common and important health problems, for which early diagnosis or prevention is possible. Lectures and small group studies with students were also organized to contribute to the educational effectiveness of the modules. Public Health topics of the medical education may be achieved more easily when theoretical knowledge and practical skills are complemented by field studies [12]. It is recommended to start such activities as early as possible and to continue them during medical education. In DEUSM Public Health perspective, objectives of each academic year were determined and relevant field study programs were developed to contribute these objectives. These programs were put into practice beginning from the beginning of the medical education.
Prior to the implementation of PBL curriculum in the 1997–1998 academic year, lectures on Public Health were presented to the first, the third and the last year students by the faculty members of the Department of Public Health. Lectures on bio-statistics and research methods were given weekly throughout the first year. The other topics of Public Health were held in 72-hour Public Health Courses at the end of the third year [13]. In the new curriculum public health subjects were held in PBL sessions. Each PBL scenario had at least one chapter associated with public health issues. Another difference between traditional and problem based education methods was changing roles of the students and teaching. Traditional education was teacher based and the students were passive receivers while the lecturer was giving information. But in PBL method, roles were exchanged and the sessions were carried out by noninformative teachers and more active students.
Comparison of old and new curriculum using some measurement tools is mandatory to observe the effects of innovations. In the literature, the determination of students' performances in scientific or licensing examinations was used to compare the efficiency of traditional education and PBL. Nandi P. et al. reviewed the studies and meta-analyses comparing PBL and traditional lecture-based education methods. In meta-analysis of the data published between 1980–1999, they concluded that PBL helped students show slightly but not significantly better performance than the others on clinical examinations [14]. Similar results were reported by Albanese M. et al., in a meta-analytic study evaluating published data between 1972–1992 [15].
Blake et al. compared formerly lecture-based educated and recently Problem-based educated graduates of Missouri-Columbia School of Medicine concerning their performances on medical licensing examinations. They reported that mean scores achieved on these examinations were better among graduates of PBL, but the difference between old and new graduates' scores was not statistically significant [16].
Some other studies have attempted to compare students' performances on special areas of medicine instead of general evaluation. Antepohl and Herzig conducted a randomized controlled study among the students who enrolled for the course of basic pharmacology at the University of Cologne. They randomly divided the students into two groups of PBL and traditional lecture based learning in order to compare their final examination scores. They could not find any significant difference between the two groups. However, in short essay questions there was a tendency towards higher scores among the students in the PBL group. The authors also found that the PBL students reached almost identical scores in their multiple choice questions and their short essay questions whereas the students who had been in the lecture based group scored significantly lower scores in their short essays than in their multiple choice questions [17].
In a multi-centric study conducted by Schmidt et al., comparison of PBL and lecture based learning students showed that PBL students had higher knowledge scores on the areas of primary care services, psychological health, collaboration of different sectors on health and occupational ethics [18].
The purpose of our study was to compare the knowledge scores of medical students in PBL and traditional curriculum on public health topics.
Methods
We planned a cross-sectional study including the fifth and sixth year medical students of DEUSM. The fifth year students (PBL students) were the pioneers educated with PBL curriculum since the 1997–1998 academic year. The sixth year students (traditional education group) were the last students educated with traditional education methods. The knowledge scores of students on Public Health topics were evaluated. In both of the PBL and Traditional curriculum, all the knowledge acquired in the first five years of the school was reviewed during the two-month Public Health internship period in the sixth year. Since this period may remind the students of some issues which may have been previously forgotten, we decided to exclude the sixth year students who have completed their internship period. 56 fifth year students and 78 sixth year students who have not so far completed their internship period in the Department of Public Health were included in our study. Participation rates were 96.4% (54 out of 56 students) in the fifth year and 100% (all of the students) in the sixth.
Before the application of the inquiry form, the purpose of the study was explained to the students and their oral consents were obtained.
We analyzed the knowledge scores of the two groups of students' on Public Health issues. PBL and traditional programs were the independent variables. Descriptive variables were age and gender.
By reviewing a five yearlong section of educational programs, we determined that nine Public Health main topics were common to both PBL and traditional programs. The main topics were communicable diseases, epidemiology, mother and child health, health management, chronic diseases, occupational health, nutritional principles in community, demography and environmental health.
We prepared 25 multiple-choice questions in order to assess knowledge scores of students on selected subjects. The number of questions related to each topic was proportional to the time allocated for each of the topic in the curriculum. The content validity of the questions was tested by consulting experts in relevant fields. All the data were collected between February and March 2002. Scoring procedure was implemented over "100 points" where each correct answer was scored "four points" and each wrong answer was scored "zero point".
Data were subjected to statistical analysis by the chi-square test and the t-test in SPSS 10.0.
Results
Overall mean age was 23.6 ± 2.1 (21–45) years. The rates of male and female students were 55.4 % and 44.6 % respectively. There were no statistically significant differences between the two groups regarding mean ages, gender distribution or other personal variables.
Mean scores achieved at the 25 question-test were 65.0 in PBL group and 60.5 in the traditional group. Students in the PBL group were significantly more successful in the knowledge test (Table-1).
Table 1 Comparison of mean scores of the students in PBL and traditional programs
Topics Max. point for each topic PBL Traditional t p
Mean Score (±) SD Mean score (±) SD
Communicable diseases 20 12.5 4.32 12.3 3.74 0.290 0.77
Epidemiology 20 6.2 4.23 5.4 4.13 0.990 0.32
Mother and child health 20 14.9 3.89 15.5 3.70 -0.851 0.39
Health management 12 9.6 2.74 7.7 3.34 3.447 0.00
Chronic diseases 8 6.7 2.17 5.3 2.78 3.255 0.00
Occupational health 8 6.1 2.54 5.7 2.46 0.743 0.45
Nutritional principles in community 4 1.9 2.01 2.0 2.01 -0.416 0.67
Demography 4 3.3 1.50 2.9 1.75 1.257 0.21
Environmental health 4 3.6 1.17 3.3 1.45 1.070 0.28
Total 100 65.0 10.99 60.5 9.22 2.395 0.01
The knowledge scores of seven topics were higher among students in PBL curriculum. These topics were communicable diseases, epidemiology, health management, chronic diseases, occupational health, demography and environmental health. Traditional curriculum students were found to be more knowledgeable on two topics; mother and child health and nutritional principles in the community. However, the differences between PBL and traditional students' knowledge scores in only two topics, chronic diseases and health management, were statistically significant (Table-1).
Conclusions
In our study, we found a statistically significant difference between knowledge scores of PBL and Traditional education groups in favour of the PBL group (Table 1).
The students of the PBL group had higher knowledge scores on 7 of the 9 identified topics. But the difference between mean scores of the groups was statistically significant in only two topics, "health management" and "chronic diseases". The reason of significantly higher knowledge scores among the students in PBL group may be that these students have more opportunities such as observations during field studies, work-shops or presentations to study on these two topics than those in the other group. They experienced a two week training period in a "community health center" at the end of the first year and observed the health center services and prepared a structured form concerning the procedures of health centers. They also studied in "community health centers" as small groups including two students in each fortnightly during their third year in the school and completed comprehensive forms about the topics on which they studied. The reason of better knowledge scores of PBL group on "chronic diseases" may result from the special educational efforts improving the effects of relevant modules on this topic. Actually special learning opportunities were provided for all topics and we were expecting to find a difference on remaining 7 topics too. On the other hand, the students in the traditional education group had slightly higher mean scores about the topics of "mother and child health" and "nutritional principles in community" although the differences between the groups' mean scores were not statistically significant. These knowledge deficiencies among PBL students were already revealed and an additional module was implemented in the curriculum to compensate them. Curriculum of DEUSM is being looked over by curriculum committee continuously and the departments try to make interventions for problematic parts.
We found that the mean total evaluation score in the PBL group was 4.5 points higher than in the traditional group in our study. Actually, we expected a much larger difference between the two groups in favour of PBL students for their education was supported by lectures, small group studies and field studies in addition to the PBL sessions. They also had the advantage of studying on Public Health issues in each year of the school by means of homogenous allocation of the modules and blocks in the first five years instead of accumulation in a short period of time as it was in the traditional curriculum. Therefore, the difference between the evaluation scores of the groups did not meet our expectations although it was statistically significant. The reason for this underachievement of Public Health objectives among our PBL students may be related to both students and PBL tutors. The common perception among the students that they have enough knowledge to say something about social and behavioural aspects of PBL modules lead them to focus on biological objectives more and they do not need to study on social issues in depth. Furthermore, a common misunderstanding among faculty members that achieving the Public Health objectives in PBL is just the responsibility of the Department of Public Health may have led the PBL tutors to withdraw from the responsibility of focusing on these subjects sufficiently. Additionally, when they are less informed or less equipped with supporting material about Public Health objectives, they may not have felt very competent while facilitating their groups by asking appropriate questions.
One assumption of curricular comparison studies, included this one, is that students will do better either in one or the other type of curriculum. However, each curriculum demands different skills and deployment of learning strategies from the students. This is important because, it is well known in the educational literature that not all students do well in one particular learning program and that they do better when the program adapts to their preferred way of learning. The studies of learning styles may shed light in why the differences between performance scores are always so close when medical curricula are compared.
As we mentioned before, in DEUSM, the written problem used in PBL sessions are oriented to biological as well as social and behavioural objectives. In order to achieve all these three objectives the tutors must attach the same importance to each subject and ensure that their groups give enough time and effort for each objective. But when the tutors get inadequate information and support from the experts of the related subjects, they generally focus only on biological objectives and their groups can't manage to integrate all objectives. If the tutors are less sensitive to objectives other than biological ones, then their students will be less motivated to learn and, like their educators, will be equally insensitive to Public Health topics. In order to prevent this, faculty members of the department of Public Health who take place in the scenario committees review the PBL problems regarding Public Health objectives. They make every effort to insure that the Public Health objectives are included while writing the problems and that the tutors are sufficiently informed on these objectives before their sessions. Field Work Committee has been trying to increase students' motivation and raise their awareness on Public Health issues to increase the effectiveness of field studies.
Focusing only on the knowledge scores of students is the main limitation of our study. Upon the graduation of the first PBL students in the 2002–2003 academic year, we are planning additional studies regarding the other functions of a physician such as skill, behavior and attitude.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
EG conceived of the study, participated in the design of the study and drafted the manuscript, BM conceived of the study, participated in the design of the study and coordination, performed the statistical analysis, GA participated in the design of the study and performed the statistical analysis, RU conceived of the study, participated in the design of the study. All authors read and approved the final manuscript.
Appendix
Sample questions
Chronic diseases
While working in a health center as a general practitioner, you have noticed that hypertension prevalence is high among the people living in the region under your responsibility. Which of the following would be your choice as primary prevention method?
a) I would educate the hypertensive patients on their disease.
b) I would treat the hypertensive patients with antihypertensive drugs.
c) I would send the hypertensive patients to a secondary care hospital for further investigation and treatment.
d) I would educate healthy individuals on risk factors associated with hypertension and prevention methods.
Nutritional rules in community
Which of the followings is the most common childhood nutritional disorder in Turkey?
a) Protein calorie deficiency
b) Marasmus
c) Iron deficiency anaemia
d) Rickets
Demography
Which of the following is wrong?
a) Demography is a science that analyse the body, structure and differentiations of human populations.
b) The goal of family planning is to decrease current number of population.
c) Dependent population ratio is found by dividing the total number of population younger than fifteen years and older than 65 years of age by the total number of population between 15–65 years of age.
d) Principal of pronatalist population policy is to increase the total number of population.
Health Management
Which of the followings is not one of the basic records kept in a health center?
a) Household determination card.
b) Follow-up card for the females between 15–49 years old.
c) Follow-up card for aged individuals.
d) Antenatal and postnatal follow up card.
e) Infant and child follow-up card.
Occupational health
Which of the followings is not among the responsibilities of an occupational health unit?
a) Health prevention services in work settings
b) Work safety preventions
c) Following up the health and safety conditions in work settings
d) Preventing any interruption in production
e) Giving outpatient clinic services in work setting.
Communicable diseases
An 11 year old girl was bitten by a neighbour-dog while she was playing in her house-garden. Which of the followings is not required as an immediate intervention?
a) To investigate if the dog is vaccinated.
b) To vaccinate the girl for rabies prevention.
c) To clean the wound by soap and water.
d) To apply one dose of tetanus vaccine.
e) To try to understand how the dog bit the girl.
Mother and child health
Which of the followings is the most common used effective family planning (contraception) methods?
a) Intrauterine device
b) Withdrawal (coitus interruptus)
c) Combined oral contraceptives
d) Condom
e) Subcutaneous implants
Environmental health
Which of the followings best represents the environmental health related responsibilities of a general practitioner who works in a health centre?
a) Waste control and giving education to correct misapplications
b) Analyzing and chlorinating drinking water, control of potable water
c) Controlling and improving the condition of toilets,
d) Coordination of conduction of above mentioned services by auxiliary personnel of health centre, although these services are among the tasks of municipality.
e) All of the statements above are true.
Epidemiology
After looking over one-year medical records of an internal medicine outpatient clinic, it was found that 25 % of the diagnoses were Diabetes mellitus. Regarding this result a screening procedure was conducted in the field and Diabetes mellitus prevalance was found 5 %.
Which of the followings can not be the conclusion of above mentioned situation?
I) Outpatient clinic may admit people coming from other regions.
II) Outpatient clinic records represent the health status of the community.
III) One-fourth of the patients have Diabetes mellitus diagnosis.
IV) Field studies are needed to determine the real prevalance of a disease.
a) I, II
b) I, III
c) II, III
d) I, II, IV
e) II, III, IV
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgement
This study was carried out in 2002 while the first author, Erol Gurpinar was a research assistant in Dokuz Eylül University School of Medcine, Department of Public Health.
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| 15705193 | PMC549539 | CC BY | 2021-01-04 16:30:55 | no | BMC Med Educ. 2005 Feb 10; 5:7 | utf-8 | BMC Med Educ | 2,005 | 10.1186/1472-6920-5-7 | oa_comm |
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Proteome SciProteome Science1477-5956BioMed Central London 1477-5956-3-11570749510.1186/1477-5956-3-1ResearchMass spectrometrical analysis of recombinant human growth hormone (Genotropin®) reveals amino acid substitutions in 2% of the expressed protein Hepner Felix [email protected] Edina [email protected] Elisabeth [email protected] Gert [email protected] Department of Pediatrics, Medical University of Vienna, Vienna, Austria2 Mass Spectrometry Unit, University of Vienna, Austria2005 11 2 2005 3 1 1 22 9 2004 11 2 2005 Copyright © 2005 Hepner et al; licensee BioMed Central Ltd.2005Hepner 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 structural integrity of recombinant proteins is of critical importance to their application as clinical treatments. Recombinant growth hormone preparations have been examined by several methodologies. In this study recombinant human growth hormone (rhGH; Genotropin®), expressed in E. coli K12, was structurally analyzed by two-dimensional gel electrophoresis and MALDI-TOF-TOF, LC-MS and LC-MS/ MS sequencing of the resolved peptides.
Results
Electrospray LC-MS analysis revealed one major protein with an average molecular mass of 22126.8 Da and some additional minor components. Electrospray LC-MS/MS evaluation of the enzymatically digested Genotropin® sample resulted in the identification of amino acid substitutions at the residues M14, M125, and M170; di-methylation of K70 (or exchange to arginine); deamidation of N149, and N152, and oxidation of M140, M125 and M170. Peak area comparison of the modified and parental peptides indicates that these changes were present in ~2% of the recombinant preparation.
Conclusion
Modifications of the recombinant human growth hormone may lead to structural or conformational changes, modification of antigenicity and development of antibody formation in treated subjects. Amino acid exchanges may be caused by differences between human and E. coli codon usage and/or unknown copy editing mechanisms. While deamidation and oxidation can be assigned to processing events, the mechanism for possible di-methylation of K70 remains unclear.
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Background
The structural integrity of recombinant products generated by prokaryotic and eukaryotic organisms is a major concern. Modifications such as amino acid sequence substitution/mutations of recombinant proteins may lead to pharmacological inactivation, autoimmune phenomena [1-3] and adverse effects [4,5]. Human growth hormone (hGH) replacement is a frequent therapeutic intervention [6,7]. Genetic changes in human growth hormone have been linked to biological inactivity and disease: Lewis et al (2004) reported that a growth hormone variant I179_M179 showed decreased ability to activate the extracellular signal-regulated kinase pathway and Binder et al. (2002) described hGH deficiency due to mutations of the coding regions of the growth hormone-1 gene [8,9]. Zhu et al. (2002) reported a case of hGH R183_H183. This single mutation causes autosomal dominant growth hormone deficiency type II by prolonged retention time of R183_H183 aggregates into secretory granules [10].
However, although such changes can be detrimental, non functional sequence alteration induced by poor editing of recombinant proteins may act as a marker of growth hormone abuse in situations such as athlete doping. We therefore were highly interested in the homogeneity and structure of rhGH preparations.
Genotropin® is expressed by E. coli, strain K12. It consists of a single polypeptide chain containing 191 amino acids and two disulfide bonds (C53-C165; C182-C189) [11] with a molecular mass of 22 124 Da – representing the most abundant growth hormone form in humans [12].
In humans two major hGH splicing variants have been described, a 22 kDa protein and a 20 kDa protein, that bind different sites at the growth hormone receptor and serve different biological activities [13,14].
The genetic origin of hGH is the hGH-N gene, located on the long arm of chromosome 17, in a 66-kbp cluster region closely related to four other genes: hGH-V, hCS-A, hCS-B and hCS-L. The hGH-N gene is expressed in both, pituitary and several nonpituitary sites [12], all other gene products are produced by placental syncytio-trophoblasts.
A series of posttranslational modifications of hGH have been described and range from N-glycosylation, acetylation, deamidation, oxidation at M14 and M125 to polymerisation [12,15-18].
As mentioned above, Genotropin® is expressed by E. coli. Since the fidelity of hGH translation in E. coli cannot rely on copy editing [19,20], nor on correct codon usage [21-23], there is a large potential for sequence errors. That's why investigations of structural/sequential integrity, including amino acid exchanges/mutations, and post translational modifications of rhGH Genotropin® is of particular interest to for modern medicine and pharmacotherapy.
The aim of the present study was to investigate the homogeneity of a commercial available rhGH, Genotropin®. This was achieved using two dimensional gel electrophoresis (2-DE), matrix-assisted laser desorption/ionisation mass spectrometry (MALDI-MS) followed by tandem mass spectrometry (MALDI-MS/MS) and liquid chromatography mass spectrometry (LC-MS) followed by tandem mass spectrometry (LC-MS/MS). These modern analytical tools provide definitive structural analysis independent of antibody availability and specificity.
Results
Two dimensional gel electrophoresis
Two dimensional gel electrophoresis (2-DE) of 1 mg Genotropin® showed a multiple spot pattern with masses between 20 000 and 35 000 Da and pIs from 4.5 to 7.0. Several two dimensional (2D) gels with sample amounts of 0.5, 1, 2, 5, 10, 20, 50, 100, 200 and 500 g of Genotropin® were performed. Decreasing protein load showed reduction of spot size and number and finally, limitation to two spots of 22000 Da with pI of 5.3 and 5.4.
Neither MALDI-TOF-TOF nor LC-MS analysis of picked gel spots indicated any modifications or isoforms in an amount, that would explain differences between the two spots.
Electrospray LC-MS measurements of the Genotropin® sample
Electrospray liquid chromatography – mass spectrometry (LC-MS) measurements of the intact Genotropin® have shown that the main product was a molecule with an average molecular weight (MW) of 22126.8 Da. The manufacturers had determined the average MW of Genotropin® to be 22124 Da.
The mass difference of approximately 3 Da may originate from the deconvulation of some broader, lower intensity peaks. Several minor components could be also detected. (Figure 1) The mass differences between the main product (Nr. 1) and components Nr. 2–5 respectively indicate the oxidation of several amino acid residues. Components Nr.6 and Nr.7 show a mass discrepancy of approximately +268 Da and -19 Da respectively. According to the ratios of peak areas (Table 1), the sample consists to 84.4% of the unmodified main component; the oxidation products are present to 13.7% of the whole sample and the ratio of other minor components, which may represent additional modifications or amino acid substitutions, is approximately 2%.
Figure 1 Reconstructed electrospray LC/MS spectrum of the Genotropin® sample. The spectrum was recorded in positive ionization modus; 1 pM of the protein was injected. Detected average molecular masses: Nr.1.:22126.8 Da; Nr.2: 22143.5 Da; Nr.3: 22158.7 Da; Nr.4: 22174.4 Da; Nr.5: 22240.7 Da; Nr.6: 22395.9 Da; Nr7.: 22107.6 Da
Table 1 Relative peak areas of the components detected by electrospray LC/MS measurement
Molecular mass (Da) Area (cps) Area (%)
22126.9 4909.8 84.4
22143.5 479.7 8.2
22158.7 121.5 2.1
22174.4 120.8 2.1
22107.6 76.9 1.3
22240.7 69.9 1.2
22395.9 40.4 0.7
Average molecular masses of the components detected in the LC/MS spectrum of 1 pM Genotropin® sample. The peak areas were calculated from the reconstructed spectrum (Figure 1) recorded in positive ionization.
Electrospray LC-MS/MS measurements following the tryptic digestion of the Genotropin® sample
Electrospray tandem liquid chromatography – mass spectrometry (LC-MS/MS) measurements of the samples prepared from one dimensional SDS-PAGE indicated mass differences at several peptides. Doubly or triply charged ions were chosen for all MS/MS experiments due to their better fragmentation pattern. Table 2 shows the sequences of the modified peptides and possible explanations for the mass discrepancies.
Table 2 Results of electrospray LC-MS/MS and MALDI-TOF MS/MS measurements
Sequence M calculated (Da) M observed (Da) delta M (Da) Modification
EETQQKSNLELLR 1586.83 1614.74 27.91 K70: di-methylation or → R *
FDTNSHNDDALLK 1488.68 1489.60 0.92 N149 / N152 deamidation
RLEDGSPR 928.47 900.46 -28.01 R127→ Q or K *
LFDNAMLR 978.50 994.40 15.90 M14 : oxidation
DMDKVETFLR 1252.61 1268.40 15.79 M170: oxidation
DLEEGIQTLMGR 1360.61 1376.66 16.05 M125: oxidation
LFDNAMLR 978.50 960.40 -18.10 M14 → I
DLEEGIQTLMGR 1360.61 1342.60 -18.01 M125 → I
DMDKVETFLR 1252.61 1234.60 -18.01 M170 → I
LFDNAMLR 978.50 1035.40 56.90 Carbamidomethyl – N terminus
• Nearly isobaric mass differences
Sequences and mass differences of modified peptides detected in the Genotropin sample. Column 1: sequence of modified peptides following tryptic digestion of Genotropin®; column 2: calculated monoisotopic masses of the unmodified tryptic peptides; column 3: observed monoisotopic masses; column 4: differences of calculated and observed masses; column 5: possible explanations of the mass differences.
A mass difference of +28 Da was detected at the position K70 (Figure 2), could be explained by the di-methylation of this residue, or by the exchange of this lysine to an arginine. These modifications result in a mass difference of 28.03 Da and 28.01 Da respectively. The accuracy of the mass spectrometric detection was not high enough to differentiate between these possibilities. Figure 2 shows the fragment spectrum of the peptide EETQQKSNLELLR. Intensive y ions verify that all residues have unchanged masses except of K70, which makes the localization of the mass discrepancy on that lysine residue unambiguous.
Figure 2 Electrospray LC-MS/MS spectrum of the modified peptide EETQQK*SNLELLR. Positive ionization product ion spectrum of the tryptic peptide m/z 808.4 generated by a linear ion trap mass spectrometer. Intensive y fragment ions verify that the K170 residue shows a mass increment of 28 Da compared to its theoretical mass.
Deamidation of the amino acids N149 and N152 was also detected. The molecular mass of the peptide RLEDGSPR was decreased with 28 Da. The mass difference could be localized to the N terminus of the peptide and might indicate the substitution of R127 with a lysine or glutamine. The mass difference of these residues is only 0.04 Da and the accuracy of the mass spectrometric detection was not high enough to differentiate between these amino acids. Residues M14, M125 and M170 were observed partly oxidized and in some cases the non oxidized residue showed a mass discrepancy of -18 Da (Table 2). This phenomenon is illustrated by Figure 3, which shows a product ion spectrum of the modified peptide LFDNAMLR. Fragment ions from the y series verify the mass reduction at the M14 residue. This mass difference can be explained by the replacement of these methionines with isoleucines, which can be originate from the substitution of the last base in the genetic codon of methionine (M:ATG; I:ATT/C/A). According to the ratios of the peak areas of the peptides containing the unmodified and possibly substituted methionines, these changes were present at < 2% of the whole protein amount. A mass increase of 57 Da was detected at the peptide LFDNAMLR. It could be localized at the N terminus of the peptide and it is supposed to be an artefact of the alkylation step during sample preparation. All modifications were partial; in each case peptides with both modified and unmodified residues were present. LC-MS/MS spectra for all modified peptides are available as supplementary material.
Figure 3 Electrospray LC-MS/MS spectrum of the peptide LFDNAM*LR. Positive ionization product ion spectrum of the tryptic peptide m/z 482.3 generated by a linear ion trap mass spectrometer. Ions of the y series verify the mass discrepancy of -18 Da at the M14 residue compared to its theoretical value.
MALDI analysis of Genotropin®
Approximately 96 spots were excised from a 2D gel with a sample load of 1 mg Gentotropin® and identified by MALDI-TOF on the basis of peptide mass matching [24] following in gel digestion with trypsin. Those samples which were analysed by peptide mass fingerprinting from MALDI-TOF were additionally analysed using LIFT-TOF/TOF MS/MS from the same target. A maximum of three precursor ions per sample were chosen for MS/MS analysis.
Genotropin® was unambiguously identified by MS and MS/MS Data (Figure 4 and 5), with a maximum of 24 matching peptides, representing a sequence- coverage of 86% to human growth hormone sequence present in database (Figure 4, Table 3). All picked and analysed spots showed similar peptide mass fingerprints. Only the oxidation status of M varied, represented by a mass difference (ΔM) of 16 Da. Oxidation at M14 was demonstrated in 59,52% of analysed spots, 80,91% of M125 and 54,87% of M170 showed oxidation too (Table 3). Neither changes in amino acid sequence, nor post translational modifications like phosphorylation or deamidation could be detected by this method.
Figure 4 MS spectrum of Genotropin showing oxidation of M14, M125 and M170.(a) MS spectrum of Genotropin® generated by an Ultraflex™ TOF/TOF (Bruker Daltonics) operated in the reflector mode for MALDI-TOF peptide mass fingerprint (PMF). Enlarged sections (b-d) from PMF of Genotropin® showing oxidised/non-oxidised status (ÄM+16Da) of Methionine. (b) first peak: LFDNAMLR (979.529 Da)/ second peak: LFDNAMLR + oxidation of Methionine (995.519 Da); (c) first peak: DMDKVETFLR (1253.587 Da) / second peak: DMDKVETFLR + oxidation of Methionine (1269.572); (d) first peak: SVFANSLVYGASDSNVYDLLKDLEE-GIQTLMGR (3605.040) / second peak: SVFANSLVYGASDSNVYDLLKDLEE-GIQTLMGR + oxidation of Methionine (3621.064)
Figure 5 MS/MS spectra of Genotropin® .LIFT-TOF/TOF (MS/MS) (a, b) spectra of Genotropin® generated by an Ultraflex™ TOF/TOF (Bruker Daltonics) operated in LIFT mode for MALDI-TOF/TOF fully automated using the FlexControl™ software. The parent ions (m/z 1205.56 and m/z 2342.12) were selected for further analysis by MS/MS and the amino acid sequences NYGLLYCFR (5a) and LHQLAFDTYQEFEEAYIPK (5b) were unambiguously assigned to human growth hormone.
Table 3 Sequence coverage and peptide masses of Genotropin®
Sequence Coverage: 86%
Matched peptides shown in Bold
1 FPTIPLSRLF DNAMLRAHRL HQLAFDTYQE FEEAYIPKEQ KYSFLQNPQT
51 SLCFSESIPT PSNREETQQK SNLELLRISL LLIQSWLEPV QFLRSVFANS
101 LVYGASDSNV YDLLKDLEEG IQTLMGRLED GSPRTGQIFKQTYSKFDTNS
151 HNDDALLKNY GLLYCFRKDM DKVETFLRIV QCRSVEGSCG F
Start – End Observed Mr(expt) Mr(calc) Delta Miss Sequence
1–8 930.61 929.60 929.53 0.07 0 FPTIPLSR
1–16 1906.97 1905.96 1906.01 - 0.05 1 FPTIPLSRLFDNAMLR Oxidation (M)
9–16 979.51 978.50 978.50 0.01 0 LFDNAMLR
17–38 2706.34 2705.33 2705.32 0.00 1 AHRLHQLAFDTYQEFEEAYIPK
20–38 2342.12 2341.11 2341.13 - 0.02 0 LHQLAFDTYQEFEEAYIPK
20–41 2727.35 2726.34 2726.32 0.02 1 LHQLAFDTYQEFEEAYIPKEQK
39–64 3058.51 3057.50 3057.45 0.05 1 EQKYSFLQNPQTSLCFSESIPTPSNR
42–64 2673.26 2672.26 2672.25 0.00 0 YSFLQNPQTSLCFSESIPTPSNR
42–70 3416.79 3415.78 3415.60 0.18 1 YSFLQNPQTSLCFSESIPTPSNREETQQK
65–77 1587.80 1586.79 1586.83 - 0.03 1 EETQQKSNLELLR
78–94 2055.19 2054.18 2054.19 - 0.01 0 ISLLLIQSWLEPVQFLR
95–115 2262.09 2261.08 2261.12 - 0.04 0 SVFANSLVYGASDSNVYDLLK
95–127 3621.02 3620.02 3619.77 0.25 1 SVFANSLVYGASDSNVYDLLKDLEEGIQTLMGR Oxidation (M)
116–127 1377.62 1376.62 1376.66 - 0.05 0 DLEEGIQTLMGR Oxidation (M)
141–158 2097.01 2096.00 2095.98 0.02 1 QTYSKFDTNSHNDDALLK
146–158 1489.66 1488.65 1488.68 - 0.03 0 FDTNSHNDDALLK
146–167 2676.26 2675.25 2675.24 0.01 1 FDTNSHNDDALLKNYGLLYCFR
159–167 1205.56 1204.55 1204.57 - 0.02 0 NYGLLYCFR
159–168 1333.64 1332.63 1332.66 - 0.03 1 NYGLLYCFRK
169–178 1253.58 1252.57 1252.61 - 0.04 1 DMDKVETFLR
169–178 1269.57 1268.56 1268.61 - 0.04 1 DMDKVETFLR Oxidation (M)
Sequence coverage of 86% and 21 matching peptides of Genotropin® to human growth hormone could be detected using MALDI MS/ MS-MS data.
Discussion
The dominant protein in the Genotropin® preparation has an average molecular mass of 22127 Da. Electrospray LC-MS/MS evaluation of the trypsinized recombinant human growth hormone (rhGH) resulted in the identification of amino acid substitutions at residues M14, M125 and M170. Di-methylation of K70 or exchange to arginine, deamidation of N149 and N152, and oxidation of M14, M125 and M170 were also observed. These sequence alteration account for 2% of the recombinant protein.
Amino acid exchanges of a rhGH has been described before: Gellerfors et al. (1990) describe exchanges rhGH Q65_V65 and rhGH Q66_K66[25]. Since the product was not identified we cannot compare our results. Binding of recombinant human growth hormone to the GH receptor may be modified by the five amino acid exchanges observed in the present study. Pal et al. (2003) calculated binding energy differences between modified human growth hormone (hGHv; M14_W14) and wild type human growth hormone (hGHwt; M14) with the result that the hGHv had more binding affinity to its receptor than hGHwt [26,27]. Cunningham et al. showed that M14 influenced binding, even if it is not a "hot spot" for linkage to its receptor. Furthermore, the amino acid exchanges detected may very well lead to antigenic differences and thus form the molecular basis for eliciting immune responses.
The underlying cause of amino acid exchanges may be codon usage and/or absence of copy editing in E. coli: The M_I exchanges may be due to miscast of the third nucleoside of the cognate anticodon at the so-called Wobble-position, i.e. switch cytosine to guanine/adenosine, a phenomenon described by Crick as "Wobble- hypothesis [28]. Crick (1966) postulated a certain amount of wobble at the third base position of the codon allowing more than one possible codon-anticodon- base pairing. Methionine (M)_I exchange of rhGH Genotropin® may have been generated as the base pair G-G / G-A was replacing G-C. Arginine (R)_K/Q and R_G exchanges of rhGH Genotropin® may be due to difficulties in translation of the rare codon AGG. Kane et al. (1995) predicted translational problems with an abundant mRNA species containing an excess of rare tRNA codons that may arise after the initiation of transcription of a cloned heterologous gene in the E. coli host [21]. Recent studies suggest clusters of AGG/AGA codons can reduce both quantity and quality of the synthesized protein [22,29]. Translational modification normally does not include amino acid exchanges but rather frameshift mutations/deletions [21,29-31].
In summary, we found two different pathways for amino acid exchanges in Genotropin®: translation errors due to usage of (1) the rare codon AGG in E. coli and (2) incorrect codon usage consisted with Crick's "Wobble-hypothesis".
Oxidative modification of a recombinant human growth hormone has been described by Karlsson et al. (1999) who demonstrated M14 and M125 oxidation as detected by LC-MS [32]. No other group have reported oxidation of M170 as in our study. Indeed Teh et al. (1987) oxidised natural hGH extracted from pituitary glands and detected M14 and M125 oxidation by reversed phase chromatography [33]. Gellerfors et al. (1990) oxidised rhGH with hydrogen peroxide but again failed to show oxidation of M170, as detected by reversed phase chromatography [25]. It is not known whether oxidation of methionines in recombinant human growth hormone leads to functional impairment but conformational changes are unlikely as proposed by circular dichroism and 1H-NMR studies [33]. It is worth mentioning that oxidised methionines are not localised at the receptor binding site.
Post translational modification such as N-acetylation, N-glycosylation, deamidation and oxidation have been reported for rhGH, hGH and bovine growth hormone (bGH) [15-17,34]. Dimethylation of K70 in rhGH and hGH have not previously been reported.
Whether transmethylation occurred during processing or is a post translational event during rhGH production in E. coli is unknown. Nevertheless, Martal et al. (1985) demonstrated reduction of biological activity of hGH and bGH by methylation and ethylation of its residues K41, K70, and K115[35]. Therefore, dimethylation of K70 in Genotropin® could have biological relevance, probably reducing its pharmacotherapeutic activity.
Deamidation of N149 and N152 may be due to technical processing, probably by heat treatment or lyophilisation and has already been reported by Gellerfors et al (1990) and Karlsson et al. (1999) [25,32]. Though these appear to have no function significance [26,27,36].
Modifications of the recombinant human growth hormone, as shown in this study, may effect functionality and safety depending on the prevalence of such forms in the preparation. As already mentioned above, impaired binding to the receptor, conformational changes leading to impaired function, amino acid exchanges as mutations may well lead to immune phenomena or even disease [1-3,37]. In addition, such modifications may act as markers of these proteins in situations like rhGH doping.
Conclusions
Using one- and two-dimensional gel electrophoresis, electrospray LC-MS, LC- MS/MS and MALDI-TOF-TOF mass spectrometry we detected a series of modifications of the recombinant human growth hormone (Genotropin®) including amino acid exchanges, oxidation, di-methylation and deamidation. This analytical battery is a reliable, specific and sensitive analytical tool for this purpose.
Methods
Sample preparation
Genotropin © MiniQuick 1,0 mg (Pharmacia & Upjohn; Stockholm, Sweden) was suspended in 0,5 ml of sample buffer consisting of 8 M urea (Merck, Darmstadt, Germany), 4% CHAPS (3- [(3-cholamidopropyl) dimethylammonio]-1-propane-sulfonate) (Sigma, St. Louis, MO, USA), 10 mM 1,4-dithioerythritol (Merck, Germany) and 0,5% carrier ampholytes "Resolyte" 3,5–10 (BDH Laboratory Supplies, Electran ®, England). The suspension was transferred into Ultrafree-4 centrifugal filter units (Millipore, Bedford, MA), for desalting and concentrating proteins. Protein content of the supernatant was quantified by the Bradford protein assay system [38]. The standard curve was generated using bovine serum albumin and absorbance was measured at 595 nm.
One-dimensional SDS-polyacrylamide gel electrophoresis
One dimensional SDS-polyacrylamide gel was performed as described by Laemmli [39]. Samples of 0.5, 1, 2, 5, 10, 30, 50 and 100 μg were loaded on the gel. For determination of molecular weight 10 μl of precision plus protein standards, all blue (Bio Rad, California, USA), were applied on the gels.
Two-dimensional gel electrophoresis (2-DE)
2 DE was performed essentially as reported [40]. Samples of 1 mg protein were applied on immobilized pH 3–10 nonlinear gradient strips in sample cups at their basic and acidic ends. Focusing was started at 200 V and the voltage was gradually increased to 8000 V at 4 V/min and then kept constant for a further 3 h (approximately 150,000 Vh totally). After the first dimension, strips (18 cm) were equilibrated for 15 min in the buffer containing 6 M urea, 20% glycerol, 2% SDS, 2% DTT and then for 15 min in the same buffer containing 2.5% iodoacetamide instead of DDT. After equilibration, strips were loaded on 9–16% gradient sodium dodecylsulfate polyacrylamide gels for second-dimensional separation. The gels (180 × 200 × 1.5 mm) were run at 40 mA per gel. Immediately after the second dimension run, gels were fixed for 12 h in 50% methanol, containing 10% acetic acid, the gels were stained with Colloidal Coomassie Blue (Novex, San Diego, CA) for 12 h on a rocking shaker. Molecular masses were determined by running standard protein markers (Biorad Laboratories, Hercules, CA) covering the range 10–250 kDa. pI values were used as given by the supplier of the immobilized pH gradient strips (Amersham Bioscience, Uppsala, Sweden). Excess of dye was washed out from the gels with distilled water and the gels were scanned with ImageScanner (Amersham Bioscience).
Electronic images of the gels were recorded using Adobe Photoshop and Microsoft Power Point Softwares.
Matrix-assisted laser desorption ionisation mass spectrometry
Spots were excised with a spot picker (PROTEINEER sp™, Bruker Daltonics, Germany), placed into 96-well microtiter plates and in-gel digestion and sample preparation for MALDI analysis were performed by an automated procedure (PROTEINEER dp™, Bruker Daltonics) [41,42]. Briefly, spots were excised and washed with 10 mM ammonium bicarbonate and 50% acetonitrile in 10 mM ammonium bicarbonate. After washing, gel plugs were shrunk by addition of acetonitrile and dried by blowing out the liquid through the pierced well bottom. The dried gel pieces were reswollen with 40 ng/μl trypsin (Promega, U.S.A.) in enzyme buffer (consisting of 5 mM Octyl β-D-glucopyranoside (OGP) and 10 mM ammonium bicarbonate) and incubated for 4 hrs at 30°C. Peptide extraction was performed with 10 μl of 1% TFA in 5 mM OGP. Extracted peptides were directly applied onto a target (AnchorChip™, Bruker Daltonics) that was load with α-cyano-4-hydroxy-cinnamic acid (Bruker Daltonics) matrix thinlayer. The mass spectrometer used in this work was an Ultraflex™ TOF/TOF (Bruker Daltonics) operated in the reflector mode for MALDI-TOF peptide mass fingerprint (PMF) or LIFT mode for MALDI-TOF/TOF fully automated using the FlexControl™ software. An accelerating voltage of 25 kV was used for PMF. Calibration of the instrument was performed externally with [M+H]+ ions of angiotensin I, angiotensin II, substance P, bombesin, and adrenocorticotropic hormones (clip 1–17 and clip 18–39). Each spectrum was produced by accumulating data from 200 consecutive laser shots. Those samples which were analysed by PMF from MALDI-TOF were additionally analysed using LIFT-TOF/TOF MS/MS from the same target. A maximum of three precursor ions per sample were chosen for MS/MS analysis. In the TOF1 stage, all ions were accelerated to 8 kV under conditions promoting metastable fragmentation. After selection of jointly migrating parent and fragment ions in a timed ion gate, ions were lifted by 19 kV to high potential energy in the LIFT cell. After further acceleration of the fragment ions in the second ion source, their masses could be simultaneously analysed in the reflector with high sensitivity. PMF and LIFT spectra were interpreted with the Mascot software (Matrix Science Ltd, London, UK). Database searches, through Mascot, using combined PMF and MS/MS datasets were performed via BioTools 2.2 software (Bruker). A mass tolerance of 100 ppm and 2 missing cleavage sites for PMF and MS/MS tolerance of 0.5 Da and 1 missing cleavage sites for MS/MS search were allowed and oxidation of methionine residues was considered. The probability score calculated by the software was used as criterion for correct identification.
The algorithm used for determining the probability of a false positive match with a given mass spectrum is described elsewhere [43].
Nano-electrospray LC-MS and LC-MS/MS analysis
Genotropin® MiniQuick 0.6 mg (Pharmacia & Upjohn; Stockholm, Sweden) was suspended in the solution provided in the two-chamber cartridge and diluted with 1% formic acid (Merck; Darmstadt, Germany) in water (Maxima, Elga; High Wycombe, UK) to 1 pM/μl. 1 μl of this solution was used for the nano-electrospray LC-MS investigation. The HPLC used was an UltiMate™ system (Dionex Corporation; Sunnyvale, CA, USA) equipped with a PepMap C18 purification column (300 μm × 5 mm) and a 75 μm × 150 mm analytical column of the same material. 0.1% TFA (Pierce Biotechnology Inc.; Rockford, IL, USA) was used on the Switchos module for the binding of the peptides and a linear gradient of acetonitrile (Chromasolv®, Sigma-Aldrich; Seelze, Germany) and 0.1% formic acid in water was used for the elution. The gradient was (A = 5% acetonitrile / 0.1% formic acid in water; B = 80% acetonitrile / 0.1% formic acid in water) 0% B for 12 min, 80% B in 30 min, 100 % B in 3 min, 100% B for 10 min, 0% B in 2 min, 0% B for 23 min. The flow rate was 240 nl/min. The LC-system was coupled on-line to a QSTAR Pulsar hybrid mass spectrometer (Applied Biosystems; Foster City, CA, USA). The nanospray source of Proxeon (Odense, Denmark) was used with the distal coated silica nanospray capillaries of New Objective (Woburn, MA, USA). The electrospray voltage was set to 1800 V. Spectra were acquired over the mass range of m/z 600–1600. The accumulation time was 1 sec. Protein spectra were deconvoluted by Analyst® (Applied Biosystems; Foster City, CA, USA). LC-MS/MS analyses were carried out also with the UltiMate™ system interfaced to the QSTAR Pulsar or to an LTQ (Thermo; San Jose, CA, USA) linear ion trap mass spectrometer. The gradient was (A = 5% acetonitrile / 0.1% formic acid in water B = 80% acetonitrile / 0.1% formic acid in water) 0% B for 12 min, 60% B in 88 min, 100 % B in 5 min, 100% B for 10 min, 0% B in 5 min, 0% B for 20 min. Peptide spectra were recorded over the mass range of m/z 450–1300, MS/MS spectra were recorded in information dependent data acquisition over the mass range of m/z 50–1600. One peptide spectrum was recorded followed by two MS/MS spectra on the QSTAR Pulsar instrument; the accumulation time was 1 sec for peptide spectra and 2 sec for MS/MS spectra. The collision energy was set automatically according to the mass and charge state of the peptides chosen for fragmentation. One full spectrum was recorded followed by 3 MS/MS spectra on the LTQ instrument, automatic gain control was applied and the collision energy was set to the arbitrary value of 35. Doubly or triply charged ions were selected for product ion spectra. MS/MS spectra were interpreted by Mascot (Matrix Science Ltd, London, UK).
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
Felizardo, Maureen carried out MALDI-TOF-TOF analysis. Raja, Karlin participated in sequence alignments and in the design of the study. All authors read and approved the final manuscript.
Acknowledgements
We are highly indebted to the Red Bull Company, Salzburg, Austria, for generous financial support and acknowledge the contribution of the Verein zur Durchführung der wissenschaftlichen Forschung auf dem Gebiet der Neonatologie und Kinderintensivmedizin "Unser Kind". We appreciate excellent technical assistance by M. Felizardo and K. Raja.
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| 15707495 | PMC549540 | CC BY | 2021-01-04 16:37:15 | no | Proteome Sci. 2005 Feb 11; 3:1 | utf-8 | Proteome Sci | 2,005 | 10.1186/1477-5956-3-1 | oa_comm |
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World J Surg OncolWorld Journal of Surgical Oncology1477-7819BioMed Central London 1477-7819-3-111571323610.1186/1477-7819-3-11Case ReportSpontaneous rupture of giant gastric stromal tumor into gastric lumen Mehta Rajiv M [email protected] Vayoth O [email protected] Anil K [email protected] Raghavan R [email protected] Puneet S [email protected] Surendran [email protected] Vallath [email protected] Department of Gastroenterology, Amrita Institute of Medical Sciences, Cochin, Kerala, 642026 India2 Department of Surgical Gastroenterology, Amrita Institute of Medical Sciences, Cochin, Kerala, 642026 India2005 15 2 2005 3 11 11 13 10 2004 15 2 2005 Copyright © 2005 Mehta et al; licensee BioMed Central Ltd.2005Mehta 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
Gastrointestinal stromal tumors (GIST) constitute a large majority of mesenchymal tumors of the gastrointestinal (GI) tract, which express the c-kit proto-oncogene protein, a cell membrane receptor with tyrosine kinase activity. GI stromal tumors of the stomach are usually associated with bleeding, abdominal pain or a palpable mass.
Case presentation
A 75-year-old male presented with upper abdominal pain and palpable mass. Computed tomographic (CT) scan of the abdomen showed a large mass arising in the posterior aspect of fundus, body, and greater curvature of the stomach. Second day after the admission, there was significant reduction in the size of the tumor, clinically as well as radiologically. Endoscopic biopsy showed large bulge in fundus and corpus of the stomach posteriorly with an opening in the posterior part of the corpus, and biopsy from the edge of the opening reveled GIST. Patient underwent curative resection.
Conclusion
Spontaneous ruptured of giant gastric stromal tumor is very rare presentation of stomach GIST. Thorough clinical examination and timely investigation can diagnose rare complication.
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Background
Gastrointestinal stromal tumors (GIST) are the most common form of mesenchymal tumors arising from the gastrointestinal (GI) wall, mesentery, omentum or retroperitoneum that express the c-kit proto-oncogene protein [1]. This expression of c-kit distinguishes GIST from true leiomyomas, leiomyosarcomas, and other mesenchymal tumors of the GI tract [1,2]. Stomach (60–70%) and small intestine (20–30%) is the most common site for GIST [2]. Approximately 10–30% of patients with GIST may be asymptomatic. Stomach and small intestinal stromal tumors are usually associated with abdominal pain, GI bleeding or palpable mass. Around 30% of all GISTs are malignant and liver is the most common site for metastasis. Surgical resection is the primary treatment of GIST [3]. The 5-year survival following curative resection ranges from 20–80% [3-7]. Imatinib mesylate, tyrosine kinase inhibitor, is the first effective drug with response rate of 54% in the treatment of metastatic GIST. We report here a case of GIST which presented with rupture in to the gastric lumen.
Case presentation
A 75-year-old diabetic male presented with dull upper abdominal pain of one-week duration. He noticed swelling in left upper abdomen. There was no history of vomiting, fever or gastrointestinal bleeding. He had no significant medical or family history and was non-smoker and non-alcoholic. Physical examination showed a 14 × 10 cm mass palpable in epigastrium and left hypochondrium with minimal intrinsic mobility.
Routine biochemical investigations were normal. Ultrasonogram and CT-scan of the abdomen showed large heterogeneous mass of 13 × 10 cm extending from the tail of pancreas to anterior pararenal space, lesser sac to gastrosplenic ligament enveloping the posterior aspect of fundus, body and greater curvature (Figure 1). One day after the admission, examination showed reduction in the size of palpable mass to 8 × 6 cm size which was not associated with aggravation of the symptoms. Ultrasonography of the abdomen was repeated which showed reduction in the diameter of mass to 8 × 8 cm. Upper endoscopy showed large bulge in fundus and corpus of the stomach posteriorly with an opening in the posterior part of the corpus with edematous margin with dissemination of serous fluid and necrotic material in to the stomach (Figure 2). Fluid analysis was normal for CEA and CA 19-9. Biopsy taken from the edge of the opening showed bundles of spindle cells with elongated nuclei and tumor cells (Figure 3) and was strongly positive for CD117 immunohistochemical examination, diagnostic of gastrointestinal stromal tumor (Figure 4). At laparotomy a large tumor was seen arising from the posterior wall of stomach measuring 8 × 8 cm, which has ruptured into the gastric lumen, and was infiltrating the upper pole of spleen, anterior capsule of pancreas and mesocolon. He underwent total gastrectomy and splenectomy with esophagojejunostomy, and segmental transverse colectomy. Histopathology of resected specimen showed large spindle cell GIST with >5/50 HPF (high-power field) mitotic activity. Postoperative period was uneventful. Postoperatively he was put on imatinib mesylate 400 mg once daily. Patient is asymptomatic on follow up for 11 months.
Figure 1 CT-Scan showed large heterogeneous mass of 13 × 10 cm size extending from the tail of pancreas to anterior prararenal space, lesser sac to gastrosplenic ligament enveloping the posterior aspect of fundus, body and greater curvature.
Figure 2 Upper endoscopy picture shows opening in the posterior part of the corpus with edematous margin with dissemination of serous fluid and necrotic material in to the stomach.
Figure 3 Photomicrograph showing upper endoscopy biopsy specimen of gastric GIST showing multiple spindle cells with eosinophilic cytoplasm and ovoid to elongated nuclei
Figure 4 Photomicrograph of biopsy specimen with immunohistochemical staining for CD117
Discussion
GI stromal tumors express c-kit protein also known as CD 117, and is considered as highly specific marker that differentiates GIST from other mesenchymal tumors such as leiomyomas [8-10]. The majority of GISTs occur in the stomach (60–70%) and small intestine (20–30%) [9]. GIST arises from the stomach, presented with abdominal pain, GI bleeding or palpable mass. Around 20–30% of GISTs detected during surgery for intestinal obstruction or bleeding [9]. Among the diverse clinical presentation of stomach GISTs, spontaneous ruptured in to peritoneal cavity lead to peritonitis [11], extragastric growth [12], complicated with hiatus hernia [13], ruptured of gastric stromal tumor with cystic degeneration presenting as hemoperitoneum [14], gastric stromal tumor with myxoid degeneration [15] have been reported in the literature. Our patient had giant gastric GIST, which ruptured into the stomach with dissemination of its necrotic tissue in the stomach. There was no aggravation of the symptoms. Abdominal examination revealed reduction of the size of tumor from 13 × 10 cm to 8 × 6 cm size. Ultrasound abdomen also confirmed 40% reduction in the size of the tumor. Upper endoscopy biopsy from the edge of the opening, posterior wall of the stomach was suggestive of GIST. Since most of the GISTs are submucosal and grow endophytically, preoperative tissue diagnosis is difficult. In our patient biopsy from the edge of the rent and deep inside the opening confirmed diagnosis of GIST preoperatively. Patient underwent complete tumor resection, with uneventful postoperative period.
Assessment of malignant potential of a primary GIST lesion is difficult in many cases; even as small as less than 2 cm size GIST has certain malignant potentials [9]. Currently, there is no single prognostic factor that can be used alone to predict tumor behavior. Biological behavior of tumor also depends on the location; for example, GISTs arising from the small bowel or colon are generally associated with a less favorable outcome than those arising in the stomach [16]. Radiological and surgical factors that have been used to determine malignancy include invasion to adjacent organs; omental or peritoneal seeding; tumor recurrence after surgical resection; or distant metastasis [8,17]. Pathological factors that determine malignancy are tumor size, mitotic activity, nuclear pleomorphism, degree of cellularity, nuclear to cytoplasmic ratio, and mucosal invasion [18]. Both mitotic activity and tumor size have been identified as the most important factors predicting malignant behavior [3,9,19]. In our patient, most of the factors like size of the tumor, local invasion and high mitotic activity indicated high malignant potential.
Imatinib mesylate, competitive inhibitors of certain tyrosine kinases including the intracellular kinases ABL and BCR-ABL fusion proteins present in some leukemia's, and platelet-derived growth factor receptors [20], is the first effective drug in the treatment of metastatic GIST. Demetri et al [21] had reported a response rate of 54%, with median time to response is about 13 weeks, in patients with either inoperable or metastatic GISTs treated with a daily dose of 400 mg or 600 me with follow-up of at least 6 months. Even in patients with large tumor, response to imatinib mesylate can occur rapidly [22]. The optimum dose of imatinib mesylate in the treatment of GIST is not yet known. Toxicity increases with increasing dose, with maximum tolerated dose was 800 mg taken for 8 weeks [22]. Role of imatinib mesylate in the treatment of malignant GIST after curative response is still under investigation. Rational of giving imatinib mesylate in our patient following curative resection, was presence of a very large tumor (>10 cm) with local invasion and high mitotic activity (>5/50 HPF).
Conclusions
Spontaneous ruptured of giant gastric stromal tumor is very rare presentation of stomach GIST. Clinical examination and timely investigations can diagnose this rare complication.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
RM, AJ: Preparation of manuscript
NR: performed upper endoscopy and biopsy and helped in preparation of draft manuscript.
SOV, SS, PD: surgical management, manuscript revision for scientific content
PD, BV: Revision of manuscript and preparation of final manuscript.
All authors read and approved the final version of the manuscript.
Acknowledgement
Written consent was taken from the patient for publishing his clinical details, CT scan endoscopy and histology photographs
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Miettinen M Sarlomo-Rikala M Lasota J Gastrointestinal stromal tumors: recent advances in understanding of their biology Hum Pathol 1999 30 1213 1220 10534170 10.1016/S0046-8177(99)90040-0
Fletcher CD Berman JJ Corless C Gorstein F Lasota J Longley BJ Miettinen M O'Leary TJ Remotti H Rubin BP Shmookler B Sobin LH Weiss SW Diagnosis of gastrointestinal stromal tumors; a consensus approach Hum Pathol 2002 33 459 465 12094370 10.1053/hupa.2002.123545
Miettinen M Sobin LH Sarlomo-Rikala M Immunohistochemical spectrum of GISTs at different sites and their differential diagnosis with a reference to CD 117 (KIT) Mod Pathol 2000 13 1134 1142 11048809 10.1038/modpathol.3880210
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Cheon YK Jung IS Cho YD Kim JO Lee JS Lee MS Kim JH Hur KY Jin SY Shim CS A spontaneously ruptured gastric stromal tumor with cystic degeneration presenting as hemoperitoneum: a case report J Korean Med Sci 2003 18 751 755 14555833
Alvarado-Cabrero I Ramirez-Balderrama L Sierra-Santiesteban FI Gastric stromal tumor with myxoid degeneration. Report of a case and review of the literature Rev Gastroenterol Mex 2000 65 22 25 11464587
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| 15713236 | PMC549541 | CC BY | 2021-01-04 16:39:05 | no | World J Surg Oncol. 2005 Feb 15; 3:11 | utf-8 | World J Surg Oncol | 2,005 | 10.1186/1477-7819-3-11 | oa_comm |
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BMC NursBMC Nursing1472-6955BioMed Central London 1472-6955-4-21568659110.1186/1472-6955-4-2Research ArticleThe effects of long-term total parenteral nutrition on gut mucosal immunity in children with short bowel syndrome: a systematic review Duran Beyhan [email protected] School of Nursing, University of Connecticut, Storrs, Connecticut, USA2 Children's Clinical Research Center, Yale-New Haven Children's Hospital, New Haven, Connecticut, USA3 (Time of Writing) Infant-Toddler/Pediatric Respiratory Care Unit, Yale-New Haven Children's Hospital, New Haven, Connecticut, USA2005 1 2 2005 4 2 2 28 1 2004 1 2 2005 Copyright © 2005 Duran; licensee BioMed Central Ltd.2005Duran; 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
Short bowel syndrome (SBS) is defined as the malabsorptive state that often follows massive resection of the small intestine. Most cases originate in the newborn period and result from congenital anomalies. It is associated with a high morbidity, is potentially lethal and often requires months, sometimes years, in the hospital and home on total parenteral nutrition (TPN). Long-term survival without parenteral nutrition depends upon establishing enteral nutrition and the process of intestinal adaptation through which the remaining small bowel gradually increases its absorptive capacity. The purpose of this article is to perform a descriptive systematic review of the published articles on the effects of TPN on the intestinal immune system investigating whether long-term TPN induces bacterial translocation, decreases secretory immunoglobulin A (S-IgA), impairs intestinal immunity, and changes mucosal architecture in children with SBS.
Methods
The databases of OVID, such as MEDLINE and CINAHL, Cochran Library, and Evidence-Based Medicine were searched for articles published from 1990 to 2001. Search terms were total parenteral nutrition, children, bacterial translocation, small bowel syndrome, short gut syndrome, intestinal immunity, gut permeability, sepsis, hyperglycemia, immunonutrition, glutamine, enteral tube feeding, and systematic reviews. The goal was to include all clinical studies conducted in children directly addressing the effects of TPN on gut immunity.
Results
A total of 13 studies were identified. These 13 studies included a total of 414 infants and children between the ages approximately 4 months to 17 years old, and 16 healthy adults as controls; and they varied in design and were conducted in several disciplines. The results were integrated into common themes. Five themes were identified: 1) sepsis, 2) impaired immune functions: In vitro studies, 3) mortality, 4) villous atrophy, 5) duration of dependency on TPN after bowel resection.
Conclusion
Based on this exhaustive literature review, there is no direct evidence suggesting that TPN promotes bacterial overgrowth, impairs neutrophil functions, inhibits blood's bactericidal effect, causes villous atrophy, or causes to death in human model.
The hypothesis relating negative effects of TPN on gut immunity remains attractive, but unproven. Enteral nutrition is cheaper, but no safer than TPN. Based on the current evidence, TPN seems to be safe and a life saving solution.
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Background
In the late 1960's, the introduction of total parenteral nutrition (TPN) as an alternative nutrition provided a life saving solution to children with chronic bowel obstructions, fistulas, loss of mucosal body surfaces, short bowel syndrome, and other clinical problems that precluded enteral diet by mouth or tube feeding for long periods of time. Intravenous administration of TPN became an essential fluid to meet nutritional needs and to avoid progressive starvation-induced malnutrition, which changed the outcome of patients from dying [1]. Since then, TPN has been a gold standard practice in treatment and a panacea for infants and children who are unable to eat or to absorb enterally provided nutrients [1-4]. As a result, the prognosis for patients with SBS has changed dramatically and the management with the expected survival for infants with congenital gastrointestinal anomalies and gut failure have improved significantly [5,6].
However, its use has been shown to associate with an increased incidence of infection [7]. A number of independent experimental studies have been carried out shown that intravenous TPN negatively influences gut barrier functions and mucosal immunity while withholding nutrients by mouth or enteral tube feeding, after the resection of small intestine. These studies demonstrated that TPN is associated with: 1) increases in intestinal permeability, bacterial overgrowth, and bacterial translocation, 2) rapid changes in gut-associated lymphoid tissue (GALT) T cells, B cell, and secretory immunoglobulin A (S-IgA) levels, 3) impairment in IgA-mediated mucosal immunity defenses in the respiratory tract, 4) impairment in neutrophil function, 5) alteration in gastrointestinal (GI) architecture or mucosal atrophy [8-14].
This paper presents a descriptive systematic review of published research articles on the effects of the long-term TPN on gut mucosal immunity in children with SBS; specifically, it addresses whether TPN: 1) promotes bacterial translocation, 2) impairs intestinal mucosal immunity by decreasing S-IgA levels, 3) inhibits neutrophil and cytokine functions in blood, 4) promotes atrophy of the mucosal villi, 5) hyperglycemia, and 6) causes death. It is hoped that these findings will expand the knowledge of pediatric nurses, and have an impact on clinical practice by being included in the pediatric parenteral nutritional guidelines. Since the review of literature did not reveal any systematic reviews of TPN and mucosal immunity on children with SBS, the aim of this descriptive systematic review of individually published scientific studies is to impart a better understanding of the effects of TPN on gut mucosal defense and barrier function.
Short bowel syndrome, one of the major indications for diagnostic categories using long-term TPN [15], is a clinically complex disorder resulting from multiple alterations of normal intestinal anatomy and physiology and producing a variety of nutritional, infectious, and metabolic complications because of impairment caused by vascular disease, intestinal volvulus, ischemic bowel, inflammatory bowel, and necrotizing enterocolitis (NEC) [16,17]. SBS is also described as, " the malabsorptive state" that mostly follows massive resection of the small intestine [18,19].
After resection, the residual or remaining small bowel undergoes intestinal adaptation, a process characterized by mucosal hyperplasia, villus lengthening, increased crypt depth (intestinal gland), and bowel dilation. The process of adaptation is complex and includes both structural and functional changes. The earliest sign can be detected within 24-48 hours, and process may continue for months, possibly years. In the early phase, mucosal hyperplasia and villus hypertrophy occur. Oral nutrients and hormones stimulate this intestinal adaptation. The main clinical challenge in SBS lies in managing the many nutritional problems that occur as a result of malabsorption secondary to the reduced absorptive surface area [20,21].
Anatomy and physiology of the gastrointestinal immune system
The normal length of intestine in full-term newborn is estimated at 200 cm-250 cm [22], and the normal adult small intestine is about 400 cm [23]. The small intestine extends from the pylorus to the ileocecal valve. It is functionally divided into three segments: the duodenum, the jejunum, and the ileum. The duodenum begins at the pylorus and ends where it joins the jejunum. The end of jejunum and beginning of the ileum are not distinguished by an anatomic marker[24]. The ileocecal valve functions as a barrier to prevent both reflux of colonic contents into small intestine and rapid passage of contents through the ileum [25].
The primary function of the small intestine is to absorb nutrients into the circulation [26]. During the course of this activity the intestine is exposed to a wide variety of antigens derived from foods, resident bacteria, and invading microorganisms. All products of carbohydrate, protein, and fat digestion, as well as most of the ingested electrolytes, vitamins, and water are normally absorbed by small intestine indiscriminately. Normally, nutrient digestion and absorption occur predominantly in the upper intestine. The jejunum has a larger absorptive surface due to longer villi, and a higher concentration of mucosal digestive enzymes and transport proteins, whereas the ileum has shorter villi. Very little absorption occurs in the ileum, not because the ileum does not have absorptive capacity but because most absorption has been already accomplished before the intestinal contents reach the ileum[21,25,27].
The tight junctions of the jejunum are highly porous, so that exposure of the mucosa to hyperosmolar nutrient solutions leads to efflux or flow of water and electrolytes into the lumen (interior space of intestine). This fluid is then reabsorbed in both the ileum and colon. The distal ileum has specialized transport carriers for the absorption of bile salts and vitamin B12. The ileocecal valve forms an important barrier, slowing transit from the small intestine to the colon and limiting bacterial colonization of the small intestine [21]. Ileocecal valve prevents retrograde colonization of distal small bowel to a significant extent. In the absence of the valve, however, free reflux of right-sided liquid colonic content occurs, and the total load of colonic bacteria exposed to the distal intestine increases greatly [28].
Histological organization of the intestinal wall is divided into four major layers. These major layers include: (1) the mucosa, the innermost layer, which comprises epithelium, lamina propria, and muscularis layers; (2) The submucosa consists largely of loose connective tissue with collagen and elastin fibrils. Glands, nerve trunks and blood vessels are also present in the submucosa; (3) The next layer, the muscularis, typically consists of two substantial layers of smooth muscle cells; an inner circular layer and an outer longitudinal layer; and (4) The serosa is the outermost layer of intestinal tract [25,29-31].
The mucosa is considered an "architectural marvel." The epithelial layer of mucosa regulates absorptive, secretory, and protective barrier functions. This thin epithelial layer composed of columnar absorptive cells, goblet cells, undifferentiated crypt epithelial cells, panet cells, enteroendocrine cells, tuft cells, cup cells, and intraepithelial lymphocytes [32]. This mucosal layer covers the villus, a finger like projection that is made up of epithelial cells called enterocytes and its crypt or submucosal gland, and is responsible for absorption of electrolytes, water, and nutrition. The enterocyte surface contains special luminal projections called microvilli, which provide an increased surface area that is referred to as brush border membrane. Although not part of the epithelium, mucus on the surface of the mucosa shields the mucosal epithelial cells from direct contact with the intestinal luminal environment [29,32,33].
Beneath the mucosal epithelium is the connective and supportive tissue called the lamina propria. The lamina propria contains various immunocompetent cells, including plasma cells, mast cells, macrophages, and lymphocytes that produce not only immunoglobulins but also cytokine mediators [32].
Mucosal defense system
Nonimmune antibacterial factors
A complex intestinal mucosal defense system plays an important role to prevent invasion of gut bacteria or absorption of endotoxin. Peristaltic waves and contractions sweep the intestinal contents in a steady distal flow toward the colon, which is a major importance in reducing the growth of bacteria in the proximal intestine [28]. During fasting, motilin, a putative regulatory peptide, is believed to be one mechanism that initiates the cyclic motility pattern termed the migrating motor complex (MMC), which functions as a gastrointestinal "housekeeper" by sweeping lumenal content and bacteria from stomach and small bowel into colon[34].
Mucus, an epithelial secretion, also helps reducing bacterial overgrowth. Mucus has special properties that enable to trap bacteria in an intraluminal location while moving organisms distally in bolus fashion. Carbohydrate serves as a nutrient for some bacteria, thus attracting them to a mobile colonization site that is continuously replaced. Enzymatic digestion also significantly reduces bacterial overgrowth. Pancreatic juice has antibacterial activity. Intestinal secretions from the stomach, intestine, and pancreas are a significant deterrent to growth due to their ability to dilute the bacterial mass [28,32].
Gastric acidity acts as an initial line of defense against ingested bacteria. Gastric juice with pH less than 4.0 is bactericidal for most organisms, although not immediately [28]. In one in vitro study, bacteria instilled into an intact lumen of a normal human stomach were promptly killed in less than 15 minutes at a pH of less than 3.0, but remained viable in the achlorhydric stomach for at least 1 hour [35]. Chronic inhibition of gastric acid secretion by histamine2 (H2) receptor blockade in healthy adults, however, has been shown to increase the number of gastric bacteria [36].
The intestinal tight junctions between epithelial cells and permeability have been reviewed [37]. Permeability refers to the ability of small molecules to penetrate the gastrointestinal mucosa. The tight junctions are an important part of the intestinal barrier. Tight junctions are dynamic structures, and their barrier function may be modulated by nutrients such as glucose and amino acids as well as bacterial toxins and chemotaxins. Loss of intestinal barrier is associated with translocation of enteric bacteria in animal modal, but in humans bacterial translocation is not associated with increased intestinal permeability or villous atrophy. Glutamine, a nonessential amino acid, is considered to be the principal respiratory fuel for enterocytes. A lack of glutamine promotes mucosal atrophy and increases intestinal permeability [37-39].
Thomson and colleagues [40-42], citing various sources, suggest that enterocytes function as "nonclassical" immune cells, which play a major role as a source of proinflammatory cytokines and cytotoxins. A key proinflammatory mediator produced in intestinal mucosa is the free radical nitric oxide. Nitric oxide (NO), a pluripotent signaling and effector molecule, is increased with mild acidosis and enhances intestinal permeability. Nitric oxide is produced as a result of conversion of arginine to citrulline by the enzyme NO synthase (NOS). Nitric oxide has potent bactericidal effects against a wide variety of micro-organisms, including the majority of the intestinal microflora. Furthermore, arginine supplementation has been shown to improve survival in a guinea-pig model of peritonitis. Inhibition of NO synthesis has been shown to increase intestinal permeability via mast cells, which suggests that NO may regulate intestinal barrier function [43,44].
The permeability of the intestine can be increased by variety of factors, such as psychological stress, fasting, and certain drugs. During fasting or malnutrition, intestinal secretion of ions and fluid increased, permeability to ions and macromolecules is increased and associated mucosal atrophy reduces intestinal absorption of nutrients. Some drugs also alter intestinal permeability. Nonsteroidal anti-inflammatory drugs (NSAIDs) increase intestinal permeability in both animals and humans. Glutamine, the major source of the small intestinal mucosa, may be partially normalize this NSAID-induced permeability [37,45].
Immunological factors
The gastrointestinal track or gut associated lymphoid tissue (GALT) has an important role in gut immunity. The gut is considered the largest lymphoid organ in the body housing more than 1012 lymhocytes and more antibody (secretory IgA) than any other site in the body including spleen [46]. The lamina propria plasma cells produce secretory immunoglobulin A (S-IgA) in response to food antigens and microorganisms. Secretory IgA coats the lumen or interior surface of small intestine and prevents any microbial pathogens or viruses penetrating the epithelial layer and passing into the other organs [29,47].
S-IgA contains antibodies directed to biologically active antigens such as viruses, bacteria, enterotoxins, and enzymes normally restricted to the intestinal tract. A reduction in S-IgA level results in a greater frequency of GI infections and impaired reticuloendothelial or macrophage function, which predispose the child to systemic bacteremia [12,46,48].
The effects of surgery or trauma on mucosal immunity
After surgical intervention, sympathetic response is activated creating a positive relationship between the severity of injury and the plasma concentration of adrenalin, noradrenalin and dopamine [49]. Following injury, the inflammatory cytokines, such as tumor necrosis factor (TNF), interleukin-1 (IL-1) and interleukin-6 (IL-6) are also released, which act only locally [39]. Cytokines are hormonelike peptides or intracellular signaling proteins released from white blood cells and all nucleated cells. They function by serving as chemical messengers within the immune system, and also communicate with certain cells in the nervous system. They have immune modulating effects, in which they work in parallel with other signal arising from direct cell-to-cell contact, providing a communication network involved in everyday function of the immune response [50-52].
In the systemic level, counter-regulatory hormones, such as adrenocorticotropic hormone (ACTH), antidiuretic hormone (ADH), catecholamines and stress hormone, cortisol are released. These cytokines and systemic hormones working together cause the multiorgan system failure. They also induce hypercatabolism, which is characterized by protein breakdown within skeletal muscle, accelerated breakdown of branched-chain amino acids and increased release of glutamine and alanine into systemic amino-acid pool. Glutamine, conditionally essential amino acid, is critical as an energy source for enterocytes, immune cells, and rapidly growing tissues. Overall, physiological stress response results with increased intestinal permeability and bacterial translocation, which promotes sepsis or multiorgan failure and potantiate hypercatabolism and protein-calorie malnutrition [39].
During illness, stress increases the concentration of counterregulatory hormones (glucagons, epinephrine, cortisol, and growth hormone) and cytokines. Counterregulatory hormones increase serum blood sugars by increasing hepatic glucose production and by decreasing peripheral glucose uptake [53]. Glucose turnover is increased in sepsis and trauma, but glucose is oxidized with reduced efficiency. Fat becomes a preferred energy substrates in septic patients. In critical surgical illness the rates of both protein synthesis and catabolism are increased. However, the increase in catabolism is of greater magnitude resulting in a net breakdown of protein and, if prolonged, immune compromise [49]. Overall, this leads to prominent metabolic derangements composed of high release and low use of glucose, amino acids, and free fatty acids (FFA), resulting in increased blood levels of these substrates. Increased levels of glucose and FFA have stimulating effects on inflammatory signaling leading to additional release of proinflammatory mediators and endothelial and neutrophil dysfunction. Insulin has the inherent capability to counteract the metabolic changes in septic patients [54].
Complications of SBS
The most important ongoing complications in children with SBS reported in the literature are: recurrent sepsis, catheter related sepsis, TPN-associated cholestasis, metabolic disturbances, hyperglycemia, electrolyte imbalances, hypertriglyceridemia, gastric hypersecretion, diarrhea, and organ dysfunction [15,55-57].
Bacterial overgrowth
Bacterial overgrowth is defined as the presence of potentially pathogenic microorganism (PPM) in high concentration (≥ 105 colony forming units/mL) [58]; that is, increased numbers and species of bacteria in the small intestine. Bacterial growth in the normal bowel is controlled by gastric acid, pancreatic enzyme activity, enterocyte turnover, normal peristaltic activity in the small intestine, and ileocecal valve [59]. Bacterial overgrowth is found in children who have no ileacecal valve, the primary means for preventing reflux of bacteria from the colon into the small intestine. Progressive dilation of the small intestine as part of the adaptation response limits the efficacy of peristalsis in ridding the small intestine of bacteria. The diagnosis of bacterial overgrowth is made by culture of jejunal aspirate or by breath hydrogen testing.
Bacterial translocation is a phenomenon where intestinal pathogenic microorganisms, which are normally resident within the lumen of the intestinal tract, travel from the gut lumen into local mesenteric lymph nodes, and from there to distant sites, such as upper gastrointestinal tract, thereby causing sepsis and septicemia [8,60-62]. Sepsis in infants and children is defined as the systemic response to a possible infection. Evidence of bacteremia or an infectious focus is not required. The term septicemia is used when organisms or their toxic products are identified in the bloodstream, in other words, a pathogen is recovered from blood cultures or identified [63].
Most studies of the pathogenesis of sepsis in animals have been carried out shown that gut mucosa is particularly susceptible to injury through a variety of mechanisms, such as decreased mucosal blood flow, increased oxygen demand, decreased oxygen delivery, and reperfusion injury [64]. Sepsis is also associated with metabolic and inflammatory response to trauma or surgical illness. It has been suggested that the neuroendocrine response to sepsis and trauma results in metabolic changes; and inflammatory mediators released from wound itself or from a septic focus may play a part in these changes.
It is also widely believed that these infectious complications are related to the central venous access devices because the most recurring infection was reported as line infection [8,58,60,65,66]. However, it has been suggested that lipid emulsions of TPN may impair host defense, and in particular the bactericidal and migratory functions of the neutrophil polymorhonuclear (PMN) granulocyte in infants receiving TPN [7,51,60,67-69]. A large case-control study [70] involving 882 infants in two neonatal intensive care units, and one experimental animal study [71] conducted suggest that administration of lipids in parenteral nutrition regimens may cause phagocyte dysfunction, resulting in infectious complications such as bacteremia, pneumonia, and wound abscesses. In addition, these studies also suggest that the lipid component of TPN, which constitutes only long-chain triglycerides, possesses immunosuppressive properties that interfere with binding of interleukin 2 (IL-2), a product of activated T (helper) cell or cytokine, to its cellular receptor and impairs host defense, in particular the bactericidal and migratory functions of the neutrophil polymorphonuclear (PMN) granulocyte [50,69-72]. However, three randomized control clinical trials [73-75], and a case study with 4 patients [76] did not show that intralipid in TPN is associated with any immunosuppression. Interestingly, in contrast to others, one of the randomized control trials [73] showed that, rather than being immunosuppressive, lipid emulsions of TPN had immunostimulatory properties.
D-lactate acidosis
Bacterial overgrowth frequently complicates, especially when the ileocecal valve is absent and the dysmotility is present in the remaining bowel loops. In the colon, unabsorbed carbohydrates undergo bacterial fermentation to D-lactate, short-chain fatty acids (acetate, propionate and butyrate), which can not be metabolized by D-lactate dehydrogenase; and these small molecules are absorbed from colon, "carbohydrate salvage" [21,77]. Absorption of this metabolite (D-lactate) may cause neurological symptoms, metabolic acidosis with increased anion gap in these patients [55]. It is called, "D-lactic acidosis Syndrome." The episode of this syndrome causes patients develop slurred speech, ataxia, and altered affect. These patients appear "drunk." This condition is resolved after placing patient on a diet with restricted carbohydrate intake and metronidazole [23].
Methods
In this review, a descriptive systematic, non-quantitative literature review was conducted using methodological guidelines [78-80]. A systematic review is a technique that uses systematically guided strategies to locate, select and critically appraise relevant original studies for its subjects, and summarizes the results that address a specific clinical question from studies that are included in the review. It is either descriptive (non-quantitative) when results of primary studies are summarized, but not statistically combined, or quantitative, in which statistical methods are used to combine results, also known as meta-analysis [80-83].
A descriptive systematic review is also called a synthesis of literature. This form of literature synthesis involves tabulation of study characteristics and results to summarize their findings in an area, and it also leads to new conclusions and knowledge as a result of systematically pulling together the fragmented results from single studies[80,84].
Selecting and appraising studies for systematic review
To select and assess the methodological quality of the research studies to be included in this review, the author used a list of standardized criteria or the guidelines (Table 1) proposed by a group of researchers [78,82,85-89]. Studies were excluded if their published method section was not clear or absent; TPN was not used; study outcomes were not mucosal immunity related; or participants were not children.
Table 1 Study selection criteria
Review Question:
To what extent does long-term TPN affect the intestinal immune system of infants who undergo bowel resection with no enteral nutritional support?
Population Were study patients pediatric age groups between newborn to 17 years old?
Did study patients have intestinal resection prior to TPN given?
Did study patients have documented bacterial infection after TPN started?
Did study patients have documented impaired mucosal immunity after TPN started?
Study Intervention Did at least one study group received Intravenous (IV-TPN?
Did study group received IV-TPN more than10 days?
Control Intervention Did one study group receive enteral feeding, but no IV-TPN?
Outcomes Was one of the measured outcomes documented as bacterial translocation, villi atrophy, impaired immuno-function, and death?
Note. Modified Table from "Selecting and appraising studies for systematic review," by M. O. Meade and
W. S. Richardson, 1997, Annals of internal medicine, 127 (7), p. 531-537 [86]. Copyright 2002 by the American College of Physicians-American Society of Internal Medicine. Adapted with permission.
Research question
To what extent does long-term TPN affect the intestinal immune system of infants who undergo bowel resection with no enteral nutritional support?
Search strategies
For the purpose of this paper, searches of the following resources were used to do a comprehensive and exhaustive literature search: 1) Electronic bibliographic databases, 2) Reference lists from relevant primary and review articles, 3) The Internet, 4) Hand-searched journals, and 5) Unpublished studies, such as Thesis and Dissertation Abstracts [80].
A literature search was conducted using the following online databases: OVID Databases (MEDLINE, BIOSIS, CINAHL, Current Contents, HealthStar, OVID Full text journal articles), Cochran Library, Dissertation Abstracts, Thesis, PubMed, Web of Science, Evidence-Based Medicine, Evidence-Based Nursing, Journal Citation Reports, MD Consult, Academic Search, CancerLit, and Journal Collection Databases (Academic/IDEAL, Blackwell Science, Elsevier, and SpringerLink).
The newer articles provided a reference list of citations of previous articles. The research covered the years from 1990 through 2001 for original articles published in English. The following subject heading terms were included: Total parenteral nutrition, bacterial translocation, immunity, infant, children, short bowel-syndrome, short gut syndrome, intestinal immunity, epithelial permeability, immunonutrition, hyperglycemia, and sepsis. To prevent this systematic review from publication bias, unpublished studies were searched via Dissertation Abstract Online (FirstSearch) database, and one unpublished thesis relevant to this review was included [90].
Sample
In this systematic review, 12 published studies using quantitative methods met the clinical trials criteria. In addition, one unpublished study was included in this review. These 13 studies included a total of 414 infants and children between the ages approximately 4 months to 17 years old, and 16 healthy adults as controls. One of the 13 clinical trial samples was not counted because the same sample was used for secondary analysis [58,60].
Although high quality, well-designed study, or the preferred research design for a review would be the one that randomly allocates (concealing the assignment code) the participants with the condition of interest to alternative therapeutic interventions, but when prospective randomized clinical trials (PRCT) are not possible to find or not available, NHS Center for Review and Dissemination Guidelines suggest that the next best available evidence should be considered based on the hierarchy of study designs, which are from highest to lowest level: 1) prospective experimental studies (e.g. randomized control trial with concealed allocation), 2) experimental study without randomization (quasi-experimental), 3) observational study with control group, a) cohort, b) case-control studies, 4) observational studies without control group, a) cross-sectional, b) before-and-after study, c) case series, and 5) expert opinion [80,91,92]. In this review, the following available research designs are included: two prospective experimental-control clinical trials [90,93], one case-control [94], two cohort studies [58,60], three in-vitro studies [7,51,67], one case study [95], and four retrospective medical chart reviews [5,96-98]. The studies were published between 1993 and 2001 in pediatric journals, annals of surgery, nutritional science journals, and immunology.
The descriptive methodological and characteristics of the samples are given in Table 2.
Table 2 Methodological Characteristics of the Clinical Trials Included in This Systematic Review
Studies Discipline Year Publication Country Funding Trial Type (Setting) Participants
Andorsky et al. [96] Surgery 2001 J. Pediatrics USA Yes Retrospective (Hospital) Neonates
Okada, Klein, Pierro, et al. [20] Pediatric Surgery 1999 J Pediatric Surgery UK Yes In Vitro, (Hospital) Infants and adults
Okada, Klein, van Saene, et al. [7] Pediatrics 2000 Annals of Surgery UK Yes In Vitro, (Hospital) Infants
Okada, Papp, et al. [19] Pediatric Surgery, Immunobiology 1999 J Pediatric Surgery UK Yes In Vitro (Hospital) Infants and adults
Bines et al. [95] Gastroenterology & Clinical Nutrition 1998 J. Pediatric Gastroenterology and Nutrition Australia Yes Case study (Hospital) Infants and children
Sondheimer et al [97] Pediatrics 1998 J. Pediatrics USA No Retrospective (Hospital) Neonates
Kaufman et al. [98] Pediatric Gastroenterology & Ped. Surgery 1997 J. Pediatrics USA Yes Retrospective (Hospital) Infants and children
Pierro, van Saene, Donnel, et al. [17] Pediatric Surgery 1996 Archives of Surgery UK No Cohort study (Hospital) Infants
Pierro, van Saene, Jones, et al [18] Pediatric Surgery 1998 Annals of Surgery UK No Cohort study (Hospital) Infants
Weber [94] Pediatric Surgery 1995 J Pediatric Surgery USA No Case-control (Hospital) Infants
Chaet et al. [5] Pediatric Surgery 1994 J Pediatric Gastroenterology & Nutrition USA No Retrospective (Hospital) Children
Rossi et al. [93] Pediatric Gastroenterology 1993 Digestive Disease and Sciences USA No Experimental-Control (Hospital) Infants and children
Dahlstrom [90] Pediatrics 1988 Unpublished Thesis Sweden Yes Experimental-control (Hospital) Infants and children
Data analysis
To collate and present the extracted data, a coding sheet was used to collect information or study characteristics that included both demographic and methodological from the retrieved primary studies [79,99]. The results of the retrieved primary studies were reviewed and summarized in a coherent manner by using the NHS Center for Reviews and Dissemination [80] non-quantitative data synthesis guidelines, and classifying and structuring processes [100]. The data synthesis processes involve categorizing and classifying extracted data results, tabulation of each characteristic of the study and the major findings related to TPN, and then drawing a conclusion or making a coherent integrated report from the individual studies. Once the results were extracted, they were organized, and then categorized into similar themes. For example, the results related to sepsis, septicemia, bacterial overgrowth and bacterial translocation are grouped under sepsis. Five major themes were found and organized based on the most frequent reports.
Results
Five themes were identified: 1) sepsis, 2) impaired immune functions: In vitro studies, 3) mortality, 4) villous atrophy, 5) duration of dependency on TPN after bowel resection. Table 3 provides the demographic characteristics of the studies included in this systematic review.
Table 3 Demographic characteristics of individual clinical trials included in this review
Studies Participants (Age) Interventions Results
Pierro, van Saene, Jones et al. (1998) [18] 94 infants on PN (median age 37 weeks) 94 infants were on TPN. Throat and rectal swabs (surveillance cultures) were obtained before and twice a week after TPN started. Cefotaxime and metronidazole were given for prophylaxis, then blind therapy with a combination of Gentamicin and teicoplanic was given at the onset of sepsis. Blood cultures (central/peripheral) were sent. 41 patients (44%) on PN for 30 days, developed abnormal carriage. Among these carriers, 2 infants developed oropharyngeal E. Coli followed by Klebsiella spp, enterobacter spp, and Pseudomonas aeruginosa. 9 infants had blood cultures positive with enterococci, E. Coli, Klebsiella, Candida, and coagulase (-) staphylococci.
Pierro, van Saene, Donnell et al. (1996) [17] 94 infants, median gestation was 37 weeks Surveillance cultures of oropharynx and gut were obtained at the start of TPN and thereafter twice a week. Blood cultures (central/peripheral) were sent. 15 infants developed sepsis. 10 patients experienced septicemia. 6 patients had bacterial translocation, and overgrowth of bacteria observed in 9 patients.
Andorsky et al. (2001) [96] Total of 30 infants with SBS (age <30 days) NEC = 13, Intestinal atresia = 9, Gastroschisis = 5, Malrotation/volvulus = 3 Median residual small bowel length was 61 cm. All infants were on TPN. The shortest duration of PN use was 101 days, and the longest was 3287 days, and median was 245 days. Of the 30 patients in the study, 20 (67%) were weaned from PN; 9 of the 10 TPN-dependent infants died from infection, cardiac arrest while receiving TPN.
Okada, Klein, van saene et al. (2000) [7] 41 babies enrolled (<4 mos. old). Gastroschisis = 11, (NEC) = 7, intestinal atresia = 3, diaphragmatic hernia = 2, esophageal atresia = 2, infant with no GI problems = 11, control infants = 5, and healthy adult volunteers (control) = 5. 5 infants receiving TPN for more than 10 days. 5 infants on normal enteral diet. Coagulase-negative staphylococci were added to whole blood from control patients receiving TPN. Body weight was significantly lower in patients receiving TPN. The blood from control group killed 65% of the coag-neg. Staph, while the blood from long term TPN group failed to kill this organism.
Okada, Klein, Pierro et al. (1999) [20] Surgical infants (NEC, gastroschisis)= 5, infants (control)= 5, healthy adults (control)= 5. 5 surgical infants on long term TPN (>10 days), 5 infants on normal enteral diet, 5 healthy adults. The percentage of bacteria killed by the neutrophils increased with time. However, the ability of killing was significantly lower in infants on TPN.
Okada, Papp, et al. (1999) [19] 5 enterally fed infants (age<6 mos), and 6 healthy adults Fasting blood samples:
A) 10 ml normal saline (N/S)
B) 0.1 ml TPN in 9.9 ml N/S
C) 1 ml TPN in 9 ml N/S
D) 10 ml TPN In infants, 1 ml of TPN in 1 ml blood produced a significant decrease in TNF-α production.
Weber (1995) [94] 21 infants and children with short bowel length (<80 cm) on TPN through central line. 20 infants without SBS (13 NEC, 4 atresia, 1 gastroschisis, 2 volvulus) had surgery No enteral feeding for 7 to 14 days during the post-op period. Blood cultures from central line and peripheral line were sent to identify the organism 6 patients had 8 separate episodes of sepsis before enteral feeding was began. After enteral feeding started, 16 patients had 67 episodes of bacteremia.
Chaet et al. (1994) [5] 32 children with SBS Gastroschisis = 3 Volvulus = 5, NEC = 8, Atresia = 8, Hirschprung's = 5 32 children with residual small bowel length <100 cm (range 14-94, median 40). All patients required TPN support for minimum 2 months. 10 patients were on TPN for>3 years. 4 patients died. Two of these deaths were from complications of TPN, and other 2 had pneumonia and respiratory failure secondary to broncho-pulmonary dysplasia. All four patients were TPN dependent up to the time of their deaths. One of these death patients bowel length was 30 cm and ICV was intact while the other did not (bowel length, 15 cm).
Kaufman et al. (1997). [98] 49 neonates with SBS, NEC = 20, Atresia = 12, Gastroschisis = 9, Volvulus = 8. Infants with SBS required TPN for more than 3 months after initial surgery. Oral feeding was permitted in small volumes. Patients went home with TPN. 42 patients were able to wean completely from TPN. Bacterial overgrowth was diagnosed in all 7 children who were receiving TPN. Occurrence of bacterial growth was related to small bowel length. 6 of them died.
Sondheimer et al. (1998) [97] 44 infants NEC = 14, Atresia = 6, Gastroschisis = 4 Volvulus = 2, unknown = 10 Almost half of 32 infants had 50% or more of the estimated intestinal length resection. The remaining 12 infants had 10-50% of bowel resection. Of the 44 patients, four patients have died from liver failure while on TPN. Seven patients depended on TPN from 40 to 129 months. The rest, 27 patients were off TPN after 36 months of age. Outcome of 10 patients unknown.
Bines et al. (1998). [95] 4 patients with SBS (6 months to 5 yrs), NEC = 2, Volvulus = 1 Hirschprung = 1 All patients had central line. Patients received pregestemil formula via continues GT, while on TPN, then study formula (Neocate) was given All patients were able to discontinued TPN within 15 months of initiating the study formula. After tolerating enteral study formula, morbidity and hospitalization reduced dramatically.
Rossi et al. (1993) [93] 7 children, ages 9 months to 17 years. 3 children with inflammatory bowel disease (IBD) were on TPN for one month. 4 children with SBS on TPN for 7 to 54 months. 22 infants (control) on normal diet. All patients while on TPN for one month, underwent to intestinal endoscopy and biopsy. Of these patients: 7 on TPN, and had upper intestinal biopsy. 4 patients required TPN for >9 months Biopsies from patients in the IBD group didn't show atrophy. 3 patients on long-term TPN for SBS had very mild (grade I) villus atrophy.
Dahlstrome (unpublished, 1988) [90] 29 children (4–111 month) SBS = 11/9 on TPN/ PPN (small bowel<25 cm) pseudoobstruction = 7 on PPN immunodeficiency = 1 radiation enteritis = 1 28 (control) healthy children (10 USA and 18 Swedish the same age group) Group I children absorb <5% of their daily caloric intake; Group II children was 30-70%. Home-TPN was given each night, and children were encouraged to eat daytime as much as possible for an average of two years. After two years of long-term TPN, children had abnormal lymphocyte count, low levels of serum albumin and protein in-group I. Four children developed selenium deficiency, and 15 children on PN for 3 yrs had significantly low Hb and Hct compared to controls. Eleven of 29 children died from low lymphocyte count. Seven died (5 from SBS, 1 from pseudoobstruction, 1 from immune deficiency), 4 from TPN induced cholesistatic liver disease and from bacterial septicemia.
PPP:Partial parenteral nutrition, PN: Parenteral nutrition, Hb: Hemoglobin, Hct: Hematocrit
Sepsis
Six of the 13 trials reported bacterial overgrowth, sepsis, or septicemia [58,60,90,94,96,98]. In the first study, [96] investigators reported that two children died from gram-positive central venous catheter infections. In the second study [98], researchers compared a total of 49 neonates with 7 SBS who were on TPN and 42 weaned children. It was ascertained that the occurrence of bacterial overgrowth was related to small bowel length. Eleven TPN-weaned subjects who had bacterial overgrowth had a mean bowel length of 54 cm as compared to 105 cm in those without bacterial growth. In Pierro and colleagues' study [58], 41 children whose surveillance cultures developed abnormal carriage. These investigators stated that infants receiving TPN are at a very low risk of developing sepsis and septicemia as long as their surveillance cultures reveal normal flora only. Conversely, the presence of abnormal PPM in the throat and/or the gut increases the risk of sepsis and septicemia to about 25% of the population art risk. They have also stated that the sicker and more physiologically stressed infants would not regain normal gut function as fast as neonates who were doing clinically better.
In the third study [60], the purpose of the investigation was to demonstrate an association between microorganisms that were carried in the digestive tract and present in the blood of infants with sepsis who were receiving TPN. Sepsis occurred in 15 patients (43 episodes) and 10 patients experienced septicemia (24 episodes). Six infants had 15 episodes of bacterial translocation due to E. coli, Klebsiella, Candida species and enterococci. Eight patients had nine episodes of septicemia caused by coagulase-negative staphylococci. The researchers concluded that there was an association between septicemia and elevated serum bilirubin level, indicating TPN related cholestasis.
Dahlstrome [90] investigated a total of 29 children, most of whom had SBS and had been on TPN for 2 years. Children receiving TPN for an average of 2 years developed low biochemistry levels. The children were divided into two groups. The children in group I were estimated to have absorbed less than 5% of their daily caloric intake from the intestinal tract, while intake in the children in group II was 30-70%. Based on previous animal studies, the investigator predicted that the low lymphocyte count was related to extensive bowel resection, (the average bowel length of group I was<25 cm). Eleven of these children eventually died from TPN related sepsis, septicemia, central line infections, or cholestatic liver diseases.
Impaired immune functions: in vitro studies
In three in-vitro control studies, investigators elucidated that long-term TPN in infants suppresses specific mechanisms of immune functions [7,51,67]. In the first study, Okada and colleagues (1999) investigated the effects of TPN solution on neutrophil phagocytosis and whole-blood cytokine production in response to coagulase-negative staphylococci in an in vitro challenge in five enterally fed infants (age<6 months) and 6 healthy adults. They found that in infants, after 2 hours of incubation with a physiological dose of TPN (1 μ of TPN in 1 ml of blood) there was a significant decrease (P < 0.05) in tumor necrosis factor alpha (TNF-α) production.
The other two in vitro controlled-clinical trials focused on the cellular mechanism of neutrophil dysfunction, and the whole blood bactericidal activity against coagulase negative staphylococci in the infants receiving TPN [7,67]. These investigators used an in vitro-controlled whole blood model to measure the host bactericidal activity against coagulase-negative staphylococci. When researchers added coagulase-negative staphylococci to whole blood drawn from control patients receiving enteral feeding, the median killing of coagulase-negative staphylococci was 65%. In contrast, blood from infants receiving long-term TPN failed to kill this organism as effectively. Infants on long-term TPN had the lowest levels of both whole blood and intracellular killing of coagulase-negative staphylococci due to a defect in neutrophil function. These investigators reported that there was a negative linear correlation between the duration of TPN in days and killing of coagulase-negative staphylococci (P = 0.002). For every additional week of TPN, there was a 7% reduction in killing of coagulase-negative staphylococci. These investigators also noted that there was a significant positive correlation between neutrophil count and killing of coagulase-negative staphylococci (r = 0.80, P = 0.001).
Mortality
A total of 34 TPN complicated deaths were reported in five of the 13 clinical trials. Of these 34 deaths, 7 children died from SBS, 12 from sepsis, respiratory infections, and low immune deficiency, and other 15 from liver failure [5,90,96-98].
Duration of dependency on TPN after bowel resection
There were only three studies, retrospective and case study that showed the dependency on TPN in infants who had undergone resection of the small intestine [95-97]. As reported in these studies, there were only 17 children who were totally dependent on TPN, and nine of them died while on TPN. In one of these studies, investigators also noticed that no child successfully discontinued TPN after 36 months of age [97]. They concluded that children dependent on TPN at or more than 36 months of age are permanently dependent on TPN. Andorsky and his co-workers [96] also emphasized that residual bowel length was highly correlated with duration of TPN. Their conclusion was that remaining functional small bowel length was an independent predictor of successful weaning.
Although most children had difficulty being weaned from TPN in other studies, Bines and her co-workers [95] were able to wean all four children from TPN within 15 months of initiation of a study formula. They used an amino acid-based complete infant formula (Neocate, SHS Inc, Rockville, MD, USA) as enteral feeding. Small bowel length of these children was documented between 40 cm to 80 cm with no ileocecal, and in only one child had 13 cm with ileocecal present. All patients had repeated esophagogastroduodenoscopy and colonoscopy or jejunoscopy with findings of mild, nonspecific neutrophilic inflammation involving areas from biopsy specimens from upper and lower intestinal tract.
In addition, two other studies used enteral formulas while children were on TPN. Andorsky and colleagues [96] fed the patients with continuous breast milk or protein hydrolysate formula. Of the 30 patients in the study, 20 were weaned from TPN. Based on their report, median residual bowel length was 61 cm, and ileocecal valve was preserved in 57% of the patients. There was a significant high correlation between use of breast milk and shorter the duration of TPN. Infants who received breast milk were weaned from TPN in 290 days versus 720 days in non-breast-fed infants.
Villous atrophy
In two separate clinical trials, researchers [93,95] examined whether the effects of TPN on the intestines of children are similar to those reported in animals. In the Rosi and colleagues' study, a total of 32 children (ages 9 months to 19 years) were involved. Based on the biopsy results, the investigators reported that 3 of the 4 patients receiving long-term parenteral nutrition for short-bowel syndrome (TPN >7 months) had mild villous atrophy. Biopsies from 3 patients in the inflammatory bowel disease (IBD) group (TPN = 1 month) did not exhibit atrophy. Bines and colleagues [95] also reported similar results; in their study only one of four children (bowel length, 40 cm) had partial villous atrophy of the small intestinal mucosa.
Discussion
Systematic reviews focus on empirical studies and seek to summarize past research by drawing overall conclusions from many separate investigations that address related or identical hypotheses [101]. The purpose of this descriptive systematic review was to assess the literature documenting whether TPN negatively influences gut barrier function and is associated with increases in intestinal bacterial overgrowth, bacterial translocation, increases in mucosal permeability, decreases in S-IgA levels, and changes in mucosal architecture in infants and children after small bowel resection. Thirteen clinical trials in children from 1990 to 2001 examined the effects of TPN on infection, mortality, impaired intracellular immune functions, villous atrophy, and long-term TPN dependency. These studies were conducted in four countries from various disciplines; they ranged in size from 4 to 94 children, and age from approximately 4 months to 17 years old, with the majority of children spending time in hospital.
Numerous experimental studies suggest that long-term TPN has harmful effect. Evidence in experimental studies about TPN's effects on mucosal immunity and villous atrophy is very convincing [9,14]; however, findings in human subjects were inconsistent. Although animal models provide us wealth of evidence and continue to offer valuable information to apply to clinical conditions, Rossi and coworkers [93] argue that extrapolating these results to apply to the human model is inappropriate. Their study results showed that infants with SBS on TPN for more than 9 months had only minimal grade villi atrophy. They concluded that humans are more resistant to hypoplastic intestinal changes induced by TPN; and effects in humans seem to require longer periods of TPN. In adults, 203 surgical patients who had at least 10 days of preoperative TPN without enteral nutrients, no significant decrease in villous height or increase in bacterial translocation were noted compared with those on enterally fed controls [102]. Guedon and colleagues [103] performed biopsies in the duodenum of seven adults (all with inflammatory bowel disease) before TPN, after about 3 weeks of TPN, and after discontinuing TPN and restarting oral feedings. They noted no change in gross villous morphology with only moderate decrease in microvillus height after 21 days of TPN. Buchman and colleagues [3], however, found a significant decrease in villous height after 2 weeks of TPN study involving eight healthy volunteers. Although mucosal thickness decreased significantly, in contrary to animal studies, villous architecture was preserved after TPN; and five days of enteral refeeding was sufficient to reverse the intestinal morphologic changes. Pironi and colleagues [104] performed endoscopic biopsies in 2 adult patients who underwent long-term TPN for the treatment of a postoperative enterocuteneous fistula, and their results showed changes in villous height and crypth depth after 2 and 3 months of TPN; two months after oral refeeding, the values of morphometric parameters were significantly greater than those observed after TPN and were similar to those controls. Groos and colleagues [105] also conducted a study involving 20 adults to investigate whether TPN causes morphological changes in intestinal mucosa of human adults similar to those observed in animals experiments. They found jejunal mucosal atrophy, and a remodeling of luminal surface architecture with disappearance of cell shedding.
Bacterial translocation
In this review, bacterial translocation was reported only in one study [60]; it stated that 10 children experienced 24 episodes of septicemia, but only 6 out of 94 infants had bacterial translocation. Andorsky [96] reported that 9 of 10 children died from infection while on TPN, but no statement has been found whether those children died from infection or from other causes. In a large review, Lipman [106] critically assessed the effects of TPN and enteral nutrition, and did not find any convincing evidence that TPN promotes bacterial translocation or enteral nutrition prevents bacterial translocation in humans.
In a large critical review, Lipman [107] examined the existence of bacterial translocation and the effects of enteral nutrition on bacterial location using both animal and clinical trials. He did not find any evidence supporting that enteral nutrition preserves gut barrier functions and prevents bacterial translocation. He concluded that bacterial translocation is an independent of intestinal structure; and also the villous atrophy seen may be species specific.
Pierro and colleagues [58] used throat and rectal swabs as surveillance culture samples twice a week to investigate whether carriage of abnormal flora was associated with increased risk of sepsis and septicemia in children receiving TPN; and they concluded that infants receiving TPN are at very low risk of developing sepsis or septicemia as long as their surveillance cultures reveal normal flora only. However, the presence of abnormal PPM in the throat or the gut increases the risk of sepsis and septicemia by 25 % [58]. Surveillance samples are defined as specimens obtained from body sites were PPM are normally carried by the digestive tract.
IgA
The importance of enteral stimulation on the mucosa-associated lymphoid tissue (MALT) system was studied in neonates who died soon after birth. Histological examination of the biopsies showed that infants who received enteral stimulation showed clear evidence of B cells and T cells within the mucosa; whereas, parenterally fed infants who died had a villous atrophy. Gut and bronchus samples were obtained and related to time of death of infants who died of sudden infant death syndrome between two weeks and 90 moths after birth. IgA plasma cells first appeared in the gut and later in the bronchi as the system matured. Plasma cells increased rapidly over time as IgA plasma cells predominated by three weeks in the gut and six weeks within the bronchi [108].
In this review, none of these studies have tested whether TPN decreases S-IgA levels in intestinal mucosa causing increased bacterial translocation. Although there was only one study focused on the changes in IgA production during TPN in 8 healthy human volunteers [109], the results of this study did not show significant differences in the number of immunoglobulin-containing cells. Intestinal immune function was not affected by 2 weeks of TPN. Woodcock and colleagues [61] also investigated whether bacterial translocation is associated with changes in gut immune function in 22 adult patients (11 of whom were positive bacterial translocation and 11 negative). However, these patients were not on TPN. The study results showed a significant increase in immune functions, especially higher numbers of plasma cells and IgA and IgM values in small bowel mucosa of patients in whom bacterial translocation has been positive.
Hyperglycemia
In this review in vitro studies on infants and children demonstrate that TPN inhibits functions of neutrophils, cytokines, and bactericidal activity of phagocytosis [7,51,67]. Investigators found that cytokine production after bacterial challenge was directly impaired by addition of TPN solution. In these patients calorie intake varied from 100 to 130 kcal/kg/day; and TPN emulsion consisted of carbohydrate 15 to 18 g/kg/day, amino acids 2-3 g/kg/day, and fat 3 to 4 g/kg/day. Although these studies do not state whether these children's serum glucose levels were high, perhaps TPN-induced hyperglycemia may have also contributed to dysfunction of neutrophils. It has been hypothesized that the elevation of blood glucose in patients receiving TPN may be associated with complications, such as immunosuppression [110]. Glucose concentrations above 220 mg/dL have been shown to glycosylated immunoglobulins, causing a significant reduction in opsonic activity, which adversely affects wound healing and immunity [111].
There is a large body of evidence demonstrates that there is a positive correlation between high serum glucose levels and increased infection rates in acutely ill patients in critical care medicine. Insulin therapy seems to be beneficial in sepsis patients [54]. Rassias and colleagues recently performed two comparative randomized control clinical trials one involving 30 non-diabetic adult cardiac patients (15 in each group) [112], and the second clinical trial involving 26 diabetic adult cardiac patients (13 in each group) [113] who were scheduled for elective cardiac surgery with cardiopulmonary bypass surgery. The experimental group received intensive insulin treatment while the control group received standard insulin therapy. They found a significant increased in neutrophil count and neutrophil functions in intensive insulin therapy group. They suggest that hyperglycemia leads to increased endothelial adherence of neutrophils and may lead to lower white blood cells in hyperglycemic patients.
Since its introduction, TPN has been a life saving nutrient to severely malnourished patients. It was believed that "if some nutrition is good, more is better" [114]. Even in treating diabetic patients in the hospital, for decades, an oral tradition was passed down from clinician to clinician, "keep the patient a little sweet" [115]. It has been recently recognized that in the presence of sepsis an increased intake of energy, or overfeeding the patients with carbohydrates or fats, increases the risk of complications, which contributes to hyperglycemia and sepsis. This TPN-induced and/or physiological stress-induced hyperglycemia may have also contributed to increased rates of sepsis [39,114]. In a careful analysis of stress-induced hyperglycemia in 102 non-diabetic patients receiving TPN, subjects who received dextrose at >5 mg/kg/min, had 50% chance of developing hyperglycemia [116]. In contrast, dextrose infusion at < or = 4 mg/kg/min, risk was substantially reduced. Therefore, to prevent hyperglycemia and infection complications in hospitalized patients, TPN dextrose infusion rates should be at < or = 4 mg/kg/min [117].
Two randomized prospective clinical trials [118,119] of aggressive insulin therapy now have revolutionized our current philosophy about treating critically ill hospitalized patients [53]. In the first study, a total of 620 patients (306 patients randomized to treatment with insulin-glucose infusion followed by multidose subcutaneous insulin for ≥ 3 months and 314 to conventional therapy) [119]. In the second study, Van den Berghe and coworkers [118] conducted a large prospective, nonblinded, randomized clinical trial (a total of 1548 surgical patients in ICU) of intensive glycemic control (glycemic goal of 80-110 mg/mL [4.4-6.1 mmol/L] compared with conventional treatment (maintenance of blood glucose at a level between 180 and 200 mg/dL). At the end of the study, results showed that intensive insulin treatment reduced episode of septicemia by 46%, and overall mortality rate by 32% during their stay in ICU.
Hyperglycemia is commonly seen in stressed patients during administration of TPN or other glucose-containing solutions. Stress may also induce insulin resistance in adipose tissue, liver and heart [120]. However, the treatment of hyperglycemia starts only after glucose levels have exceed 200 to 250 mg/dL (11–14 mmol/L) because it was believed that avoidance of hypoglycemia and its potential consequences is more important than glycemic control while patients are hospitalized. The most recent target range for plasma glucose in the hospital are: preprandial = <110 mg/dl; peak postprandial = <180 mg/dl; and for critically ill patients = 80-110 mg/dl [53].
Some studies reported that the complications during TPN were associated with the residual or the remaining bowel length in patients with SBS. The longer the residual small bowel, the shorter the duration of TPN, and the fewer infections [5,96]. The results of Dahlstrome's [90] study revealed that children whose bowel length was <25 cm developed very low levels of circulating lymphocytes causing immuno-competence due to very short bowel length, and not ingesting the food antigens which are the main stimulants of lymphocytic proliferation and immunoglobulin (IgG, IgA) synthesis. Dahlstrome predicted that lack of ingested antigens might have caused the low circulating lymphoctes, which resulted in infection. He found that enteral support in combination with TPN did improve, but not normalize the plasma amino acid concentrations in the children investigated.
Enteral versus parenteral nutrition
It has been suggested that enteral stimulation is a required component to protect gastrointestinal and respiratory immunity via increased levels of mucosal IgA [15,121]. Enteral nutrition refers to nutrition either ingested orally or delivered to the stomach or intestine by tube via nasogastric (NG) tube, gastrostomy tube (GT), nasojejunal (NJ) tube, or jejunostomy tube (JT). Evidence showed that enteral nutrition is less expensive, but not safer, or more physiologic than TPN [106]. In a prospective observational nursing study [122], 64 elderly patients who were fed by an NG tube in an internal medicine. The type of formula was not stated in the study, but based on this report; most patients had electrolyte imbalances, tube dislodgements, hyperglycemia, diarrhea, pulmonary aspirations, and nasal ulcers. In another prospective observational study [123], a total of 153 critically ill patients also were fed with NG tube. Before each feeding, gastric residual volume was checked by using 50-ml syringe by aspirating the tube. The study results showed that there was a negative relationship between high gastric residual volume and days in the hospital stay. High gastric aspirate volume was associated with a higher incidence of nasocomial pneumonia, a longer length of hospital stay, and higher mortality.
Effects of early enteral feeding on bacterial translocation
In Weber's study [94], 21 infants and children with SBS were begun with enteral feedings via continuous drip technique with an elemental formula (Pregestemil:Mead-Johnson, Evansville, IN), after 3 weeks of postoperative period. Results showed that after enteral feeding began, 76 % of children had 67 episodes of bacteremia. The investigator suggests that early enteral feeding increases infection. However, Marik and Zaloga [124] performed a systematic review of 15 PRCT included 603 patients to evaluate the effect of early enteral nutrition on outcome of critically ill and injured patients. The results of this study showed that there was a significantly lower risk of infection in 19 % of the patients who received early enteral diet compared with 41 % in the delayed group. This study concluded that early feeding decreases infectious complications and length of hospital stay. In a large review, by pooling data from four PRCT involving 142 patients who had gastrointestinal cancer, Klein et al. [125] compared early postoperative JT feeding with the usual advancement of oral diet as tolerated. Based on the aggregated data, there were no significant differences in postoperative morbidity or mortality.
However, Daly et al. [126] performed a PRCT involving 85 adult the patients (41 on supplemented diet, 44 on standard diet) with cancer of upper gastrointestinal tracts. The patients who were fed early postoperatively [on the first postoperative day] via JT with a formula supplemented with arginine, ribonucleic acids, and ω-3 fatty acids had fever infections, minimal wound complications, and a shorter duration of hospitalization compared to those who received standard formula. Braga at al. [127] also performed a PRCT involving 166 patients undergoing gastrointestinal surgery to evaluate the impact of the route of administration of artificial diet, IMPACT® (Novartis Nutrition, Bern, Switzerland) supplemented with arginine, ribonucleic acid, and omega-3 fatty acids versus standard diet on outcome. Their results showed that early postoperative enteral infusion of nutrients is safe and well tolerated and stimulates an early return of bowel function.
Immunonutrition
There has been a considerable amount of interest in recent years in the use of alternative specific gut substrates. The term immunonutrition has been coined to describe molecular compound that, while being dietary components, such as glutamine, arginine, ω-3 fatty acids, ribonucleic acid, also influence immunologic response mechanisms when added to standard TPN solutions or enteral nutrition [128-130]. Glutamine, a nonessential amino acid, is considered to be the principal respiratory fuel for enterocytes, colonocytes, lymphocytes, and macrophages, and is a precursor for nucleotides synthesis and for glutathione, an important antioxidant that may be protective in a variety of circumstances. It has been hypothesized that during the stress, glutamine becomes conditionally essential amino acid.
In the late 1980s, glutamine has been the most extensively studied substrate in animal research, especially in rat TPN model. It has been suggested that parenteral or enteral glutamine supplements could dramatically effect on the maintenance of GALT; and glutamine-enriched TPN significantly attenuates the mucosal hypoplasia associated with prolonged TPN following massive bowel resection [131-134]. Therefore, it was hypothesized that glutamine supplementation in human modal would have similar effects [77]. Encouraged by findings in animal investigations, in 1991 Darmaun and colleagues [135] first time reported a reduced rate of glutamine turnover in short bowel syndrome [adult] patients, and in 1994 in pediatric patients [136]. They suggested that the small intestine was a target organ for glutamine utilization in both adults and children. C.K. Ogle (unpublished, cited in Alexander, 1993) [137] also has shown that excess glutamine added to culture media can improve antimicrobial killing by neutrophils isolated from blood of burn patients and normal controls. Alexander also argues that infection can be reduced 75% and hospital stay by 20% by immune enhancement via enteral nutrition.
In the following years, many controlled trials and case series were conducted to demonstrate the benefits of immune enhancing substrates to the intestinal adaptation process in patients with SBS during long-term TPN [138-147]. The results of these published studies have been conflicting. Although glutamine supplementation has been shown to be value in pediatric patients [38,148], Duggan and colleagues [149] conducted a randomized double-blinded, controlled clinical trial of enteral glutamine supplementation in 20 infants with SBS. At the end of study, there was no significant difference in weight and length gain between two groups. Two of nine infants in the glutamine group developed urinary and bloodstream infections. Overall, this study results showed that glutamine supplementation was safe, but had no effect on duration of TPN, tolerance of enteral feeds, or intestinal absorption or barrier function. However, in a PRCT pilot study Barbosa and colleagues [150] examined the tolerance and efficiency of glutamine in a pediatric intensive care unit setting with nine mechanically ventilated infants (treatment group = 5, and control group = 4). Their results showed that tolerance to glutamine-supplemented diet was good. Bacterial infections reported in 75% of the placebo population and 20% of the treated infants. There were two deaths from microbial infection in control group, suggesting a beneficial effect of glutamine.
However, Scolapio and colleagues [142,151] conducted a series of double-blind, 6-week, placebo-controlled, crossover trial in 8 adult patients with SBS to assess: 1) the effects of growth hormone, glutamine, and high-carbohydrate-low-fat (HCLF) diet on body composition, and 2) to evaluate the potential mechanisms that might explain the beneficial effects of immunonutrition treatment. Active treatment consisted of subcutaneous recombinant human growth hormone and oral L-glutamine. In this study, two patients developed carpal tunnel syndrome that resolved 5 days after discontinuation of active treatment. Two patients noted sleep disturbances while on active treatment. Patients developed peripheral leg edema and weight gain; this combination therapy resulted in a significant increase in sodium and potassium absorption. Two studies [145,152] also reported similar findings in addition to severe hand pain, and gynaecomastia in a male patient. Two systematic reviews [138,153], and two large critical reviews [77,125] conclude that glutamine and growth hormone at present time can not be recommended in short bowel syndrome; more large-scale studies, or multicentered clinical trials are required.
Currently, two commercially prepared immune-enhancing enteral formulas are available in the market, IMPACT® (Novartis Nutrition, Bern, Switzerland) containing glutamine, arginine, dietary nucleotides and fish oil; and Immune-Aid (McGaw, Irvine, CA) containing glutamine, arginine, nucleic acids, and omega-3 fatty acids. Some studies indicate that these immune-enhancing diets demonstrated successful results or benefits in studies of sepsis, immunity, altered intestinal permeability, inflammation, including reduced mortality and the length of hospital stay [154-156].
Some studies also show that the use of breast milk in SBS contains high levels of immunoglobulin A (IgA), nucleotides, leukocytes, and other components that bolster the neonate's immune system[20]. In a study, a continuous infusion of small amounts of breast milk in infants with SBS is also resulted in a shorter duration of TPN compared to control group [96].
Overall, findings are inconclusive. Immunonutrition may be species or patient specific.
Implications for evidence-based nursing practice
Multidisciplinary nutritional team
The successful management of infants and children with SBS is demanding and requires a multidisciplinary approach. The care of patients with SBS can become so complex that many patients with SBS almost lose their primary physician and become patients of multiple specialists. Long-term care is, therefore, best delivered by a variety of healthcare professionals, including the gastroenterologists, surgeon, nurses, nutritional support team, care coordinators, microbiologist or infection control team, clinical chemist, pharmacists, social workers, and psychologist with expertise in infant feeding difficulties. Patients cared for in this way have better outcomes [25,148,157].
Infants go through a critical developmental phase in feeding at about 6–12 months, and those who do not receive oral feeds at that time will loose the window of opportunities for sucking and swallowing coordination, and will have long-term eating difficulties [21,158]. In addition, children fed enterally or parenterally may have forgotten or never learned the association of with hunger, oral feeding, and satiety; they develop "defensive oral behaviors," such as gagging, choking, and vomiting. For a sick child, if this important developmental phase is ignored during the first year of life, flavor, texture, odor, and extreme temperature can be overwhelming. It is important that the pediatric nurses should consult pediatric occupational therapist and speech therapist, and behavioral psychologist to work with these children [159].
Clinical management
The management of neonates and children with SBS continues to provide a major challenge for practitioners [160]. A group of pediatric surgeons critiqued the current clinical management of SBS in children, which is mostly based on "trial and error" regimen. They strongly recommended that prospective, randomized controlled trials should be established, and an evidence-based rather than a "gut-feeling" -based approach to be used in SBS children, such as intestinal permeability and sugar absorption tests, evaluation of adaptation by gut hormone production, immunohistochemistry, and other new techniques which are still in experimental stage [154]. Pediatric nurses should, therefore, provide an evidenced-based nursing care to these children with the support of APRN.
Hypersecretion is seen in infants and children during the initial first 6 months after surgery and a start of enteral feeding. The H2 blockers and proton pump inhibitors are effective for reducing gastric fluid secretion, and therefore, will also reduce fluid losses during this period [77,161].
The diagnosis of bacterial overgrowth is determined by aspiration of the jejunum and demonstration of increased bacterial contents by culture. Since this procedure is invasive and infeasible in some sick infants, breath hydrogen test can be used easily as noninvasive diagnostic test [162]. The breath hydrogen test is an oral test that uses the measurement of hydrogen in the breath to evaluate carbohydrate malabsorption and bacterial overgrowth in small intestine. Hydrogen gas is produced by bacterial fermentation of undigested carbohydrate that reaches the colon, enters the portal and systemic venous return, and is then released in the breath. After fasting 4-6 hours, the child ingests a load of carbohydrate (12 g/kg, maximum 50 g), and the end-expired air is collected in sealed plastic bags by aspirating 5 mL of air after each breath to total of 20-30 mL via nasal prong attached to a face mask at timed intervals up to 2 hr after ingestion. Malabsorption of any carbohydrate can be evaluated. The child should not be taking antibiotics at the time of the study because these drugs alter the colon flora and suppress hydrogen gas production [163-165]. In one of the clinical studies, investigators used 50 mg 13C-xylose in children ages 3 to 12 years for breath hydrogen test [166]. 13C-xylose is a safe, nonradiactive isotope that has recently been developed (Martek, Columbia, MD). This study results showed that all patients with bacterial overgrowth had positive breath test results (100% sensitivity).
For infants prone to overgrowth, routine scheduled antibiotic treatment may be useful. D-Lactic acidosis has been reported in children with bacterial overgrowth, causing metabolic acidosis, drowsiness, and confusion. This diagnosis should be considered in a child with SBS who presents with metabolic acidosis, high serum anion gap, normal lactate level, and without urinary ketones [161]. Treatment for this syndrome is to start oral metronidazole, neomycin, vancomycin, and avoidance of "refined" carbohydrates [77].
Dietary management
Optimal timing of the initiation of enteral nutrition has not been established [161]. Patients who undergone massive bowel resection require TPN for the first 7-10 days. American Gastroenterological Association (AGA), based on the current literature review, suggests that nutritional therapy should not be introduced until the patient is hemodynamically stable and fluid management issues are relatively stable.
Although the optimal formula for feeding infants and children with SBS is not well established, elemental amino acid based hydrolyzed formulas are suggested by some clinicians and have been shown to be well tolerated [95]. Dietary protein is first digested, and then absorbed as dipeptides and tripeptides. Therefore, it was reasoned that dietary protein provided in a predigested form would be more readily absorbed [77].
A prospective, randomized, cross-over trial compared two protein hydrolysate formulas given by continuous nasogastric infusion to six malnourished infants with SBS aged 1-13 months [167]. Although there was good tolerance for both formulas and satisfactory weight gain, and also energy absorption was the same, but differences in the amount of malabsorbed carbohydrate existed. These researchers suggested that protein hydrolysate formulas should be reformulated with a lower concentration of carbohydrates and a higher one of fat.
A controlled trial compared two feeding regimens, continuous intragastric feedings and intermittent oral feeding, in nine infants with protracted diarrhea and malnutrition and two infants with surgically created short bowel [168]. Continuous nasogastric feeding caused significant increases in enteral balance of the major nutrients, whereas intermittent feedings resulted in negative or only slightly positive enteral balance. There was also a significant increase in body weight during the continuous feeding as compared to the intermittent feeding. The authors suggest that improved enteral balance can be achieved with continuous feeding in infants with short bowel disease [168].
In infants under 1 year of age with SBS who might have dilated gut, poor motility, or bacterial overgrowth, increased epithelial permeability to food antigens occurs frequently and may result in the development of allergic reaction to any protein in the formula. In order to reduce the risk of allergic injury to the gut, a hypoallergenic formula, such as Nutramigen, Pregestemil(Mead Johnson Laboratories, Evansville, IN), and Alimentum (Ross laboratories, Columbus, OH), should be used during the first year of life. To further decrease the risk of allergic reaction in highly susceptible infants, an amino acid based formula should be used. Neocate (SHS Inc, Rockville, MD, USA) is the only one listed in this category for infants. Elecare (Ross Laboratories), which is quite similar to Neocate, was formulated for use in children over 1 year of age [169].
Initially slow introduction of continuous enteral feeding via a nasogastric or gastrostomy tube feeding is beneficial to reduce emesis, diarrhea, and maximally saturate carrier proteins. Rationales for this that constant saturation of mucosal digestive enzymes and transport carriers should be optimize absorption. Regardless of the length of small intestine, some oral, even if only 1 or 2 ml per day, and a few ml in continuous fashion should be offered from an early stage [158].
A diluted infusion is initiated continuously at low volumes and increased to 0.67 cal/mL for infants less than 1 year of age or to 1.0 cal/mL in older children. Once the final concentration is achieved in low volumes, enteral feeding rates are advanced, and TPN rates are decreased isocalorically every 1 to 3 days as tolerated [170]. A marked increase in stool loss by 50 % is usually contraindication to advancing enteral feedings. There is no agreement on the amount of stool output that should be accepted. Limits should be imposed on feeding once the stool output exceeds 45 ml/kg per day [161]. However, a higher volume of stool output may be acceptable by some clinicians [171]. If stool losses greater than 45 ml/kg/day or ostomy output strongly positive for reducing substances suggest that enteral feeding advancement should be slowed. Careful fluid and electrolyte management is essential as dehydration can occur rapidly [20,158,161,170].
Monitoring enteral feedings and verifying tube location
Monitoring patients on enteral feeding is required routine assessment of gastrointestinal, metabolic, mechanical, and growth parameters [172]. Tolerance of enteral feeding is assessed by noting the presence or absence of vomiting, retching, abdominal distention, and diarrhea. For patients receiving gastric feedings, checking for residual formula for every 4 hrs is required to evaluate feeding tolerance or delayed gastric emptying [173]. During continuous feeding, if a single high gastric residual volume is greater than 1.5 times the hourly feeding of formula infusion, this indicates a sign of intolerance. Feeding should be stopped, and clinician should be notified. Gastric residual should be rechecked every 1-2 hours until the residual drops below the greater than or equal to 50% of the hourly rate mark [174]. Decreasing the rate by half for a few hours, rechecking residuals, and slowly advancing is recommended to achieve feeding tolerance. Changing the tube feeding might be beneficial. If this is unsuccessful, child can be placed in the right lateral decubitus position and i.v. metaclopromide (Reglan) can be started to enhance gastric emptying [172,175].
A literature review conducted by Metheny and colleagues [176] found that there was a confusion as how gastric residuals should be handled. Fifty percent of the respondents (registered nurses) from a survey (Mateo, 1996, cited in Metheny et al., 2004) [176] reported discarding the gastric contents and 49% reported re-administering them. Only one study was located that dealt with outcomes of discarding or returning gastric residuals to the patients (Brooker et al., 2000, cited in Metheny et al., 2004) [176]. In this study 35 subjects receiving enteral feedings were randomized to either a discard group or a return group. Repeated measures analysis of variance found no significant differences between the two groups in the body weight, serum electrolyte levels, tube clogging, nausea, and the feeding delays. In the absence of more convincing evidence, Metheny and colleagues [176] suggest for returning gastric residuals less than 500 mL to the patients.
Ensuring correct placement of the feeding tube is also necessary. Although auscultation is the most common method of confirming placement, it has been found unreliable. The best evidence for confirming correct tube placement is X-ray [177]. Metheny and colleagues [177,178] provide evidence-based nonradiographic methods to check the tube location. There are two methods currently available at bedside to nurses to test tube placement during continuous feedings include (1) observing the appearance of fluid aspirated from the tube, and (2) measuring the fluid's pH. Gastric pH usually falls in the range of 1 to 5, whereas intestinal or respiratory pH is usually 7 or higher. If a pH ≤ 6 is a significant indicator of the gastric placement, whereas a pH >6 is an indicator of intestinal placement. Metheny and Stewart [178] also provide additional methods for checking the position of the tube, such as capnography, spring-gauge pressure manometer, enzyme tests (pepsin and trypsin), and bilirubin analysis; however, the most reliable method of tube placement assessment is the radiograph [172].
Monitoring TPN complications
According to American Gastroenterological Association (AGA) [77], and American society for parenteral and enteral nutrition (ASPEN) guidelines [161], TPN should be infused via single lumen catheter with its tip positioned in either the superior vena cava or inferior vena cava to decrease the risk of infection and trombosis. Tunnelled catheters, implantable port, or percutaneously inserted central catheters (PICCs) should be used at home. Peripheral infusion of parenteral formulations is limited to dextrose concentrations of less than 12.5% [161]. ASPEN suggests that initially, TPN should be started with low dextrose infusion rate [161]. Starting rate is usually half of the hourly rate for the first hour, and then rate is increased to full rate after checking the blood sugar. Blood glucose should be monitored at least 4 times a day, and should be <180-200 mg/dl [77]. Glucose intolerance is the major adverse effect seen during the initial infusion period [179]. Urine sugar and acetone or ketone levels should be less than 2+. ASPEN suggests that dextrose infusion rates in infants and neonates should be 10 to 14 mg/kg per minutes[161]. Continuous insulin infusion (0.01-0.1 unit/kg per hour) has been shown to be safe and effective in managing hyperglycaemia in the neonate. Glucose concentration should be monitored at least every 2 hours, aiming for blood glucose concentration between 100 and 150 mg/dL. In children less than 2 years of age, hypoglycaemia develops rapidly if feedings are delayed or interrupted. ASPEN recommends that TPN be tapered over 1 to 2 hours in infants before discontinuation to avoid hypoglycaemia [161]. Some iv medications need to be administered over 30 to 60 minutes. If the patient has only one line which TPN is running, the nurse should communicate with the paediatric pharmacist to reconstitute the drug with 5% or 10% dextrose if that drug is incompatible with TPN. This will also prevent hypoglycaemia if TPN is temporarily interrupted for iv medication.
Four major categories of complications exist: (1) mechanical or technical; (2) infectious; (3) metabolic; and (4) nutritional [161]. Mechanical or technical complications are usually related to catheter placement, such as pneumothorax, hemothorax, cardiac tamponade, or equipment malfunction. Catheter thrombosis is a significant problem of all central lines. A potential early sign of catheter thrombosis is progressively sluggish or absent blood return on catheter aspiration. Thrombolytic agents are effectively used to dissolve thrombi.
Catheter related infections are the most common complications associated with central line TPN [161]. Localized infections are, such as erythema, tenderness, induration, or purulence that occurs at the exit-site or along the tunnel. Pocket infections occur only with implantable ports. Systemic infections, formerly called catheter sepsis or bacteraemia, are defined as positive culture of the catheter tip or a positive pathogen isolated from both blood drawn through the catheter and peripherally. Staphylococcus epidermidis, Staphylococcus aureus, and other skin flora are the most common pathogens isolated in patients with systemic infections. Enterococcus and enteric flora are the next most frequently isolated organisms. Catheter-related infections are treated based on the type of infection and pathogen [161].
Conclusion
TPN is a life saving alternative nutritional support to severely malnourished surgical patients. Its use is indicated to prevent the adverse effects of malnutrition in patients who are unable to tolerate nutrients by oral or enteral routes. Evidence from a large systematic reviews involving 82 randomized control clinical trials on both adult and paediatric population showed that: 1) TPN did not have a significant impact on survival, 2) TPN did not affect either the total or infectious complication rates, 3) TPN had no effect on the duration of hospitalization of surgical patients [180]. Based on the current evidence, TPN seems to be safe and a life saving solution.
List of abbreviations used
Short bowel syndrome (SBS)
Total parenteral nutrition (TPN).
Immunoglobulin A (IgA)
Secretory immunoglobulin A (S-IgA),
Gut-associated lymphoid tissue (GALT)
Gastrointestinal (GI)
Mucosa-associated lymphoid tissue (MALT)
Necrotizing enterocolitis (NEC)
Migrating motor complex (MMC),
Histamine2 (H2)
Nitric oxide (NO),
Nitric oxide synthase (NOS
Nonsteroidal anti-inflammatory drugs (NSAIDs)
Tumor necrosis factor (TNF)
Interleukin-1 (IL-1)
Interleukin-6 (IL-6)
Adrenocorticotropic hormone (ACTH)
Antidiuretic hormone (ADH),
Free fatty acids (FFA),
Pathogenic microorganism (PPM)
Neutrophil polymorhonuclear (PMN)
Prospective randomized clinical trials (PRCT)
Intensive Care Unit (ICU)
Nasogastric (NG)
Gastrostomy tube (GT)
Nasojejunal (NJ)
Jejunostomy tube (JT)
American Gastroenterological Association (AGA)
American society for parenteral and enteral nutrition (ASPEN)
Percutaneously inserted central catheters (PICCs)
Competing interests
The author(s) declare that they have no competing interests.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
I would like to thank my BMC Nursing reviewers, Dr. Jeejeebhoy and Dr. Sigalet for constructively critiquing my paper and giving me the best valuable suggestions to improve my research writing. I would like to express my deepest respect, appreciation, and thank my admired professors Patricia J. Neafsey, RD, PhD, Cheryl Tatano Beck DNSc, CNM, FAAN, and Carol Polifroni, RN, EdD, CNAA at the University of Connecticut for editing and reading many times my previous draft papers and giving me the most valued suggestions. I would also like to thank Wendy Mackey, APRN, MSN, CNS at Yale University, Pediatric Surgery for reviewing my previous manuscripts; Jan Glover, MLS, AHIP, a Senior Reference Librarian at Yale University Medical Library for giving me an initial crash course in library science and electronic biomedical databases. I also would like to thank the library staff at the University of Connecticut interlibrary loan department, UConn Health Center Medical Library staff, Sasha Singer and Wilhelmina Buckley; and Yale University Medical Library staff for their great patience with my over due books and their support.
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World J Surg OncolWorld Journal of Surgical Oncology1477-7819BioMed Central London 1477-7819-3-91570519410.1186/1477-7819-3-9Case ReportLong-term survival from gastrocolic fistula secondary to adenocarcinoma of the transverse colon Forshaw Matthew J [email protected] Jamasp K [email protected] Kothandaraman [email protected] Michael C [email protected] Department of Surgery, Darent Valley Hospital, Dartford, Kent, DA2 8DA, UK2005 10 2 2005 3 9 9 29 11 2004 10 2 2005 Copyright © 2005 Forshaw et al; licensee BioMed Central Ltd.2005Forshaw 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
Gastrocolic fistula is a rare presentation of both benign and malignant diseases of the gastrointestinal tract. Malignant gastrocolic fistula is most commonly associated with adenocarcinoma of the transverse colon in the Western World. Despite radical approaches to treatment, long-term survival is rarely documented.
Case presentation
We report a case of a 24-year-old woman who presented with the classic triad of symptoms associated with gastrocolic fistula. Radical en-bloc surgery and adjuvant chemotherapy were performed. She is still alive ten years after treatment.
Conclusions
Gastrocolic fistula is an uncommon presentation of adenocarcinoma of the transverse colon. Radical en-bloc surgery with adjuvant chemotherapy may occasionally produce long-term survival.
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Background
Gastrocolic fistula is a rare complication of both benign and malignant diseases of the gastrointestinal tract [1-6]. In the Western World, adenocarcinoma of the transverse colon is the commonest cause of a fistulous connection between the stomach and the colon with a reported incidence of 0.3–0.4% in operated cases [3,4]. Despite radical en-bloc surgery, these patients usually have a poor prognosis [5,6]. Long-term survival for these patients is rarely reported [5].
The authors report a 24-year-old woman who presented with a gastrocolic fistula secondary to an adenocarcinoma of the transverse colon and describe her treatment and long-term follow up.
Case presentation
A 24-year-old woman presented to the surgical clinic with epigastric pain, feculent vomiting and post-prandial diarrhoea of three months duration; she had lost over one stone in weight. She was previously healthy and was not taking any regular medications. There was no history of peptic ulcer disease, inflammatory bowel disease, trauma or previous abdominal surgery. She had been investigated two years previously by a gastroenterologist for intermittent left-sided abdominal pain at which time the clinical examination and blood tests were normal. Irritable bowel syndrome had been diagnosed, although no colonic imaging was performed. Both her maternal grandfather and great-grandfather had suffered from colonic cancer.
An initial ultrasound scan of the abdomen revealed thickened bowel in the right upper quadrant with a dilated duodenum. A barium meal and follow through was then performed: this demonstrated a mucosal abnormality on the greater curvature of the stomach with a fistulous tract into the transverse colon (Figure 1). Barium enema and colonoscopy were not performed. The presence of a mucosal abnormality on the greater curvature of the stomach was confirmed on upper gastrointestinal endoscopy although initial biopsies revealed no evidence of a malignant neoplasm. Her blood tests revealed: haemoglobin 9.5 g/dl, mean cell volume 71.6 fl and a white cell count 20.2 × 109/l; urea, electrolytes and liver function tests were all normal.
Figure 1 Barium meal demonstrating fistulous connection between greater curvature of the stomach and the distal half of the transverse colon (arrowed).
In view of her symptoms, an exploratory laparotomy was undertaken. At surgery, a large mobile tumour of the distal transverse colon was identified; this was adherent to the greater curvature of the stomach, the mesentery and to several loops of jejunum. A radical en-bloc resection was performed involving a subtotal gastrectomy, transverse colectomy and small bowel resection (Figure 2). The patient made an uneventful recovery from surgery. Histology revealed a poorly differentiated mucinous adenocarcinoma of colon without lymphatic involvement (Dukes' Stage B): this was adherent to and had penetrated the stomach wall. She received adjuvant 5-fluorouracil (420 mg/m2) and folinic acid (20 mg/m2) chemotherapy every four weeks for the following six months.
Figure 2 Macroscopic en-bloc surgical specimen showing fistula between stomach and transverse colon (arrowed).
She has been followed-up with two-yearly colonoscopy and five-yearly upper gastrointestinal endoscopy. She remains well with no signs of either local or distant recurrence more than ten years after initial diagnosis.
Discussion
Advanced neoplasms of the stomach and transverse colon are the commonest causes of a gastrocolic fistula: adenocarcinoma of the transverse colon is commoner in the Western World [1,3,4], whereas adenocarcinoma of the stomach is a more frequent cause in Japan [5]. Gastrocolic fistula has also been reported with other tumour types such as gastric lymphoma [7], carcinoid tumours of the colon [8] and rarely, metastatic tumours [9] and infiltrating tumours of the pancreas, duodenum and biliary tract [3]. With advances in medical treatment, gastrocolic fistula secondary to peptic ulcer disease is now less common [6]. A variety of other causes of gastrocolic fistula have been reported: these include syphilis, tuberculosis, abdominal trauma, Crohn's disease, Cytomegalovirus gastric infection in AIDS patients and percutaneous endoscopic gastrostomy (PEG) tubes [10-13].
The fistulous connection in a gastrocolic fistula usually arises between the greater curvature of the stomach and the distal half of the transverse colon because of their close anatomical proximity separated only by the gastrocolic omentum [13]. Two theories have been advanced for the development of a fistula [1,3,4]: the tumour may invade directly across the gastrocolic omentum from the orginating organ; alternatively, a tumour ulcer may provoke a surrounding inflammatory peritoneal reaction leading to the adherence and fistulation between the two organs. Cases of malignant gastrocolic fistula have usually been characterised by the presence of large infiltrative tumours with a surrounding inflammatory reaction, as seen in our patient; lymph node involvement is unusual [13].
Our patient presented with the characteristic triad of symptoms associated with a gastrocolic fistula [5,14]: diarrhoea, weight loss and faeculent vomiting. Other symptoms include: abdominal pain, fatigue, faeculent eructations and nutritional deficiencies. The gastrocolic fistula was identified in our patient by means of an upper gastrointestinal contrast series. Because the flow in the fistula is predominantly from transverse colon to stomach [15], several authors have suggested that barium enema is the more sensitive investigation in detecting and delineating such a fistula, although the detection rate may be lower in neoplastic cases [2,16-18]. Computerised tomography may also be useful in both delineating the fistula and identifying the underlying aetiology [5,19]. Endoscopy is an excellent tool for visualising the fistulous opening (especially in the stomach) and also allows preoperative histological confirmation [20,21].
Although two stage approaches have been advocated historically for malignant gastrocolic fistula, in order to first correct nutritional deficiencies [22], most authors now prefer radical en-bloc resections [14]. Despite such approaches, most patients have a poor prognosis and no patient has survived for more than nine years after resection [5]. This case report describes the longest disease free survival of a patient with a malignant gastrocolic fistula. To the authors' knowledge, she is also the youngest patient to be reported. It is worth noting that colorectal cancer in patients aged less than 35 years is normally associated with a poorer prognosis compared with older age groups [23-25]. This is related to the biological characteristics of such tumours with a higher proportion of mucinous poorly differentiated tumours. As a result, younger patients present with more advanced disease. Such patients require early diagnosis and a radical approach to treatment.
Conclusions
Gastrocolic fistula is an uncommon presentation of adenocarcinoma of the transverse colon. Radical en-bloc surgery with adjuvant chemotherapy may occasionally produce long-term survival.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
MJF collated the information, searched literature and wrote the manuscript.
JKD assisted in literature search and writing of the manuscript.
KM was responsible for long-term follow up of the patient and assisted in literature search.
MCP managed the patient, helped in preparing the manuscript and edited the final version.
All authors have read and approved the final version of the manuscript.
Acknowledgements
Written consent was obtained from the patient for publication of the case report.
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| 15705194 | PMC549543 | CC BY | 2021-01-04 16:39:05 | no | World J Surg Oncol. 2005 Feb 10; 3:9 | utf-8 | World J Surg Oncol | 2,005 | 10.1186/1477-7819-3-9 | oa_comm |
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BMC PsychiatryBMC Psychiatry1471-244XBioMed Central London 1471-244X-5-81569138810.1186/1471-244X-5-8Research ArticlePsychometric properties and clinical utility of the Scale for Suicidal Ideation (SSI) in adolescents Holi Matti M [email protected] Mirjami [email protected] Linnea [email protected] Olli [email protected] Titta [email protected]ä Hannele [email protected] Virpi [email protected] Mauri [email protected] Department of Mental Health and Alcohol Research, National Public Health Institute, Helsinki, Finland2 Department of Psychiatry, Lapinlahti Hospital, Helsinki University Central Hospital, Helsinki, Finland3 Department of Adolescent Psychiatry, Peijas Hospital, Helsinki University Central Hospital, Helsinki, Finland4 Department of Psychiatry, Kuopio University and Kuopio University Hospital, Kuopio, Finland5 Department of Psychiatry, Turku University Central Hospital, Turku, Finland2005 3 2 2005 5 8 8 26 11 2004 3 2 2005 Copyright © 2005 Holi et al; licensee BioMed Central Ltd.2005Holi 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
Accurate assessment of suicidality is of major importance in both clinical and research settings. The Scale for Suicidal Ideation (SSI) is a well-established clinician-rating scale but its suitability to adolescents has not been studied. The aim of this study was to evaluate the reliability and validity, and to test an appropriate cutoff threshold for the SSI in a depressed adolescent outpatient population and controls.
Methods
218 adolescent psychiatric outpatient clinic patients suffering from depressive disorders and 200 age- and sex-matched school-attending controls were evaluated by the SSI for presence and severity of suicidal ideation. Internal consistency, discriminative-, concurrent-, and construct validity as well as the screening properties of the SSI were evaluated.
Results
Cronbach's α for the whole SSI was 0.95. The SSI total score differentiated patients and controls, and increased statistically significantly in classes with increasing severity of suicidality derived from the suicidality items of the K-SADS-PL diagnostic interview. Varimax-rotated principal component analysis of the SSI items yielded three theoretically coherent factors suggesting construct validity. Area under the receiver operating characteristic (ROC) curve was 0.84 for the whole sample and 0.80 for the patient sample. The optimal cutoff threshold for the SSI total score was 3/4 yielding sensitivity of 75% and specificity of 88.9% in this population.
Conclusions
SSI appears to be a reliable and a valid measure of suicidal ideation for depressed adolescents.
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Background
Accurate assessment of suicidality is of major importance in both clinical and research settings. Adolescent suicide occurs usually in the context of an active, often treatable, but unrecognized or untreated mental illness [1-3]. The increase in the antidepressant treatment of adolescents in the USA [4] may partly explain the decline in the incidence of youthful suicide [5], though recently some reports have connected SSRI-treatment in adolescents to an increase in suicidality [6].
Suicide attempts are complex acts for which no single set of clinical features can be expected to be a good predictor [7]. Suicidal ideation, self-harming, suicide attempts and completed suicides are different forms of suicidality. Although the domain of suicidal behavior probably is multidimensional [8], a continuum from suicide ideation to suicide attempts has been reported in youthful clinical populations [9,10]. Thus, although most patients with suicidal ideation do not attempt suicide, identification and assessment of severity of suicidal ideation is of major importance.
The Scale for Suicidal Ideation (SSI) [11] was designed to measure the intensity, pervasiveness, and characteristics of suicidal ideation in adults. It also aims to assess the risk of later suicide attempt in individuals who have thoughts, plans, and wishes to commit suicide [12]. It is a well-established clinician-rating scale and is presented in a semi-structured interview format.
The psychometric properties of the SSI have been evaluated in adult population and in inpatient children. Both in a sample of adult psychiatric inpatients and in a sample of inpatient children the internal consistency of the scale was good [11,13]. SSI reportedly has three dimensions [11], which have been only partly replicated in some factor analytical studies [e.g. [13,14]]. SSI has been found to converge with scales measuring related constructs e.g. hopelessness and depression in adults, and hopelessness, depression and self-harm in children [11,13].
The predictive validity of the SSI has been studied in a sample of hospitalised patients, where the SSI scores of those who committed suicide were not significantly higher than the scores of inpatients that did not [15]. In a sample of 3701 adult outpatients those who scored over a SSI threshold value had 5.42 times higher odds of committing suicide than those who scored under [16]. The threshold value was derived from a receiver operating characteristic (ROC) analysis that yielded optimal threshold of 1/2 for predicting future suicide. In the same study, SSI-scores inquiring the worst point in life (SSI-W) yielded an odds ratio of 13.84 for predicting suicide. A recent study that inquired retrospectively records of suicide victims to find communications that fit the SSI-items found no suicide-predicting power for the instrument [17].
Some instruments have evolved from the SSI, for example the Modified scale for suicidal ideation (MSSI) [18] that was designed to suit paraprofessionals and the Beck scale for suicidal ideation (BSS) [19] that is a self-report scale.
The SSI has been used widely in adult psychiatric populations [e.g. [20,21]], but its psychometric properties have not been evaluated in adolescents. According to a recent comprehensive review "despite its potential utility, the SSI's suitability to adolescents... remains to be elucidated" [22]. Rating scales should be validated in each patient population in which they are used. The aim of this study was to evaluate the reliability and validity of the SSI and test an appropriate cutoff threshold for clinically significant suicidal ideation in an adolescent population.
Methods
Sample
The study population consisted of two samples; a psychiatric outpatient sample of 218, and an age- and sex-matched control sample of 200 school-attending adolescents. The outpatients suffered from depressive mood disorder, were of ages 13 through 19, and took part in the Adolescent Depression Study (ADS). They were recruited between 1.2.1998 and 31.12.2001 from a consecutive sample of patients attending the outpatient clinics of the Department of Adolescent Psychiatry of Peijas Medical Health Care District covering approximately 210,000 inhabitants and comprising the cities of Vantaa and Kerava in the Helsinki metropolitan area, southern Finland.
Of the eligible (appropriate age, knowledge of Finnish language and adequate cognitive capacity) 660 outpatients, 624 (94.5%) were screened during their first consultation visit by the Beck Depression Inventory (BDI) [23] and the General Health Questionnaire-36 (GHQ-36) [24,25]. Those 373 (59.8%) with scores of 10 or more and 5 or more, respectively, were considered screen positives, and were asked to participate in the study. 118 (31.6%) outpatients refused and 34 (9.1%) dropped out at this stage. 221 (33.5%) remaining outpatients were evaluated by a diagnostic interview (K-SADS-PL) [26] and those 218 (33.0%) with a current depressive mood disorder were included in the study.
The control sample was drawn from the enrollment lists in four schools in the corresponding geographical area. It was a random sample of age- and sex-matched students equating the distribution of the educational level of the outpatients.
Instruments
1) The Scale for Suicide Ideation (SSI) is a clinician-rating scale and is presented in a semi-structured interview format [11]. It consists of 19 items that evaluate three dimensions of suicide ideation: active suicidal desire, specific plans for suicide, and passive suicidal desire. Each item is rated on a 3-point scale from 0 to 2. The higher the total score, the greater the severity of suicide ideation. In some previous studies on adult suicidality a score of 6 or more has been used as a cutoff threshold for clinically significant suicidal ideation [e.g. [20]]. The psychometric properties of the SSI have been evaluated for adult psychiatric patient population; the internal consistency of the scale was found to be good (α = 0.89), and factor analysis yielded the three above-mentioned dimensions [11]. Among inpatient children rated by trained raters the factors could not be replicated; only two factors ("active suicidal desire" and a mixture of "active and passive desire") existed with miscellaneous items left over [13]. Nine trained raters did the SSI rating in our study.
2) The Schedule for Affective Disorders and Schizophrenia for School-Aged Children-Present and Lifetime (K-SADS-PL) [26] is a widely used semi-structured diagnostic interview. Suicidal behavior was determined using four questions from the screening-section of the K-SADS-PL diagnostic interview: item-1 suicidal thoughts ("1" = none, "2" = occasional, "3" = frequent), item-2 suicide attempts and their seriousness ("1" = none, "2" = ambivalent, "3" = serious) and item-3 suicide attempts and their lethality ("1" = none, "2" = not life-threatening, "3" = life-threatening). Self-harming behavior was asked using item-4, the question on deliberate self-harm without intent to die ("1" = none, "2" = occasional, "3" = frequent) in the screening section of the K-SADS-PL.
The K-SADS-PL is considered internationally reliable and valid diagnostic instrument for adolescent population [27]. It has been translated (and back translated) into Finnish and used widely in studies concerning suicidality [e.g. [9,28]]. Nine trained raters did the rating. Inter-rater reliability, assessed using 15 randomly selected videotaped interviews, was good for mood disorder diagnoses [weighted kappa [29] for MDD, other mood disorder, no mood disorder 0.87 (95 % CI 0.81, 0.93)].
3) Clinical suicidality assessment (CSA): A three-point mutually exclusive grouping of suicidality (1-non-suicidal, 2-suicide ideation, 3-suicide attempts) is a simplified version of the 5-item "Spectrum of Suicidal Behavior Scale" [30]. It has been used in both research and clinical purposes [e.g. [10]]. The grouping is done by a clinician, and is based on two simple questions "Have you thought of killing yourself?" and "Have you attempted suicide?" and on patient records when appropriate. There is some evidence supporting the predictive validity of this grouping [10] but it has not been validated by comparing it with more structured measures like the K-SADS-PL. In this study, after a brief training the treating clinicians of the outpatient clinic did the CSA. They were instructed to include in class-3 also self-mutilation and other self-harming behavior with no explicit suicide intent.
Procedure
After a description of the study, a written informed consent was obtained from the subjects. For subjects less than 18 years consent was also asked from the parents or other legal guardians. For the community sample the K-SADS-PL and the SSI were performed at the same day by an expert clinician. For the outpatient sample the K-SADS-PL was performed within variable time from the SSI rating. The CSA was performed for the patient sample by clinicians during the beginning of the treatment.
Statistical analysis
Central tendencies of some data were reported using medians and quartiles because of non-normal distribution. Mann-Whitney U test was used to assess the significance of differences between the two samples.
Internal consistency of the SSI was evaluated by calculation of Cronbach's α for the whole scale.
Concurrent validity of the instrument was examined by comparing it with the K-SADS-PL with the CSA classifications. SSI total scores were first assessed in 5 classes of increasing suicidality derived from the K-SADS-PL responses in the following way: 1-no suicidal ideation or acts, 2-mild suicidal ideation (score 2 on item-1), 3-severe suicidal ideation (score 3 on item-1), 4-mild suicidal acts (score 2 on any of items 2–4 regardless of ideation), 5-severe suicidal acts (score of 3 on any of items 2–4 regardless of ideation).
Then the SSI total scores were measured in 3 classes of increasing suicidal ideation severity, regardless of possible suicidal acts, derived from the K-SADS-PL responses on item 1: 1-no ideation, 2-mild ideation, and 3-severe ideation. Severe ideation (score 3) in this item was considered as "clinically significant suicidal ideation".
Finally the SSI total score was assessed in the three classes of the CSA: 1-no suicidality, 2-suicidal ideation, 3-suicidal or self-harming acts.
The statistical significance of the between-class differences was evaluated by Kruskal-Wallis test. For the analyses of concurrent validity only SSI-measurements in a range of 30 days from the K-SADS-PL and the CSA were included.
Construct validity was measured by performing a principal component analysis (PCA) with varimax rotation in the outpatient sample. The internal consistencies (Cronbach's α) of the extracted components as well as the originally reported factors [11] were calculated.
ROC-analysis was performed to evaluate the screening properties of the SSI, and the cutoff threshold for the instrument was defined by optimal trade-off between sensitivity and specificity (Youden's index [31]). The K-SADS-PL (score 3 in item-1) was used as the standard to define cases with clinically significant suicidal ideation.
SPSS 11.0 (Chicago, Illinois 60606, SPSS Inc) was used for the statistical analysis.
Results
Eighteen percent (n = 40) of the outpatient sample were boys and 82% (n = 178) girls, in the community sample the percentages were 18.6% (n = 37) and 81.4% (n = 162), respectively. The subjects' mean age was 16.4 (SD 1.6) in the outpatient sample and 16.5 (SD 1.6) in the community sample. The median SSI total score for the patient sample was 0 (Q1–3 = 0–6) and for the community sample 0 (Q1–3 = 0-0) (z = -9.6, p = 0.000). The median SSI total score for subjects aged 13–15 was 0 (Q1–3 = 0–1) and those aged 16–19 0 (Q1–3 = 0–1) (z = -0.685, p = 0.493). The median time distance between SSI and K-SADS-PL was 21.5 days (Q1–3 = 9–36) for the patient sample and 0 days (Q1–3 = 0-0) for the control sample (z = -18.0, p = 0.000). The median time distance between SSI and the CSA was 6 days (range 0–35).
Forty-seven (21.6%) outpatients and one (0,5%) control subject had current clinically significant suicidal ideation (p = 0.000) according to the K-SADS-PL.
Reliability
Cronbach's α was 0.95 for the whole sample, 0.81 for the community sample and 0.95 for the outpatient sample.
Concurrent validity
146 (67%) of the outpatients and 199 (99.5%) of the controls were included in the analyses for concurrent validity, as their measurements were within the required range of 30 days.
The median SSI sum scores in the five suicidality classes derived from the K-SADS-PL were class-1 = 0 (Q1–3 = 0-0); class-2 = 5.5 (Q1–3 = 0–8); class-3 = 13 (Q1–3 = 0–18.5); class-4 = 4 (Q1–3 = 0–17.3); class-5 = 8 (Q1–3 = 0–13). The differences were significant (χ2 = 111.6, df 4, p = 0.000).
The median SSI sum scores in the three classes of suicidal ideation derived from the K-SADS-PL were class-1 = 0 (Q1–3 = 0-0); class-2 = 4 (Q1–3 = 0–8); class-3 = 13 (Q1–3 = 4–18). The differences were significant (χ2 = 132.6, df 2, p = 0.000).
The median SSI sum scores in the three clinical suicidality evaluation classes (only the outpatient sample) were class-1 = 0 (Q1–3 = 0–1); class-2 = 10 (Q1–3 = 5–18); and class.3 = 15 (Q1–3 = 13.3–16.6). The differences were significant (χ2 = 57.9, df 2, p = 0.000).
Construct validity
Principal Component analysis could be performed only for the outpatient sample due to a small variance of responses in the community sample. The analysis yielded a strong first unrotated factor, which explained 53% of the variance, and two more factors with eigen value > 1. The three factors and their internal consistencies after varimax rotation are presented in Table 1. The internal consistencies (Cronbach's α) of the originally reported [11] three dimensions were "active suicidal desire" α = 0.92, "preparation" α = 0.69, "passive suicidal desire" α = 0.79.
Table 1 Factor loadings and internal consistencies of the varimax rotated Principal Component Analysis (PCA) of the SSI in an outpatient sample of 218 adolescent outpatients with mood disorder. (* = Items that loaded identically to Beck's [11] original study) In the original study items 8, 10, 11 loaded on "active suicidal desire"-factor; items 13 and 15 on "preparation"-factor; and items 14 and 18 on "passive suicidal desire"-factor; item 17 did not load adequately on any of the factors.
Item Loadings
Factor 1: Factor 2: Factor 3:
(active suicidal desire) (passive suicidal desire) (preparation)
7. time dimension: frequency 0.824 * 0.208 0.180
6. time dimension: duration 0.764 * 0.321 0.225
4. desire to make active suicide attempt 0.753 * 0.389 0.142
9. control over suicidal action 0.746 * 0.140 0.140
1. wish to live 0.716 * 0.170 0.063
12. method: specificity/planning 0.714 * 0.383 0.303
2. wish to die 0.702 * 0.360 0.137
3. reasons for living/dying 0.689 * 0.364 0.219
14. sence of "capability" 0.657 0.405 0.322
13. method: availability/opportunity 0.649 0.409 0.285
α = 0.94
5. passive suicidal desire 0.256 0.720 * 0.016
19. deception/concealment of suicide 0.196 0.711 * 0.201
8. attitude toward ideation/wish 0.508 0.650 0.177
10. deterrents to active attempt 0.242 0.633 0.389
11. reason for contemplated attempt 0.527 0.619 0.058
15. expectancy/anticipation of event 0.445 0.603 0.226
α = 0.85
18. final acts 0.098 0.151 0.802
17. suicide note 0.358 0.001 0.787
16. actual preparation 0.133 0.319 0.646 *
α = 0.65
Validity as a screening instrument
ROC analysis (Fig. 1) of the SSI total score against the K-SADS-PL-confirmed suicidal ideation yielded an area-under-curve (AUC) of 0.84 for the whole sample (n = 418) and an AUC of 0.80 for the patient sample (n = 218). The optimal trade-off between sensitivity and specificity (Youden's index) was achieved at a cutoff threshold score of four or more in the whole sample as well as the patient sample. In the whole sample the sensitivity and the specificity at this threshold were 75% and 88.9%, respectively (Table 2) with 53 subjects classified incorrectly. In the patient sample the sensitivity and the specificity at this optimal threshold were 76.6% and 77.2%, respectively (Table 3) with 50 subjects classified incorrectly.
Figure 1 Detection of suicidal ideation by the Scale for suicidal ideation (SSI) against the K-SADS-PL as a standard, at a sample of 146 depressed adolescent outpatients and 199 age- and sex-matched controls. ROC-curve with a reference line.
Table 2 Validity coefficients of different SSI cutoffs against K-SADS-PL diagnosed significant suicidal ideation at a mixed adolescent sample of 146 outpatients and 199 community controls
SSI cutoff 0–1 1–2 2–3 3–4 4–5 5–6 6–7 7–8 8–9 9–10 10–11
Sensitivity 77.1% 75% 75% 75% 66.7% 64.6% 58.3% 58.3% 58.3% 56.3% 50.0%
Specificity 83.0% 86.5% 87.6% 88.9% 90.0% 91.6% 93.0% 94.6% 95.9% 96.2% 96.8%
Youden 0.60 0.62 0.63 0.64 0.57 0.57 0.51 0.53 0.54 0.53 0.47
Table 3 Validity coefficients of different SSI cutoffs against K-SADS-PL diagnosed significant suicidal ideation at an adolescent sample of 146 outpatients
SSI cutoff 0–1 1–2 2–3 3–4 4–5 5–6 6–7 7–8 8–9 9–10 10–11
Sensitivity 78.7% 76.6% 76.6% 76.6% 68.1% 66.0% 59.6% 59.6% 59.6% 57.4% 51.1%
Specificity 66.7% 73.1% 74.3% 77.2% 78.9% 82.5% 85.4% 88.9% 91.2% 91.8% 93.0%
Youden 0.46 0.50 0.51 0.54 0.47 0.49 0.45 0.49 0.51 0.49 0.44
Discussion
This study was the first to evaluate the psychometric properties of the SSI in an adolescent population. It was a part of the ongoing Adolescent Depression Study (ADS) and the sample of patients was large compared to earlier similar studies in adult populations, and probably representative of adolescent psychiatric outpatients with depressive disorders. The main finding was that the SSI appeared to be a reliable and valid instrument for evaluation of suicidal ideation in a depressed adolescent population. Its internal consistency and different aspects of validity were good and similar to what has been reported among adults.
The construct validity of the SSI was checked by Principal Component Analysis, which yielded 3 theoretically meaningful and coherent factors, only slightly different from the original ones, with good internal consistencies. This suggests good construct validity. The first factor ("active suicidal desire") was nearly identical to Beck's original one [11]. The second factor ("passive suicidal desire") included theoretically coherent items, two of which were identical to Beck's original factor of similar content. The third factor was also theoretically meaningful, included three items concerning final preparations, and had one item in common with Beck's original "preparations" factor.
The SSI converged theoretically meaningfully with both the three-class K-SADS-PL suicidal ideation-item and the clinical suicidality assessment (CSA); growing SSI scores were found within categories with increasing severity of suicidality. As to the convergence with the 5-class K-SADS-PL suicidality instrument, the results were more complex. The Kruskal-Wallis test yielded significant differences between the SSI scores in the different categories as expected, but the SSI-scores in the K-SADS-PL classes 4 and 5, with the supposedly most severe suicidality were not higher than in class 3. Classes 4 and 5 inquire about suicidal acts, and may represent a partly separate domain from suicidal ideation, which may be related to the presence of comorbid personality traits or conduct disorders. The SSI was designed to tap suicidal ideation and it may not satisfactorily tap features related with suicidal acts. In accordance with the theory of multidimensional nature of suicidality [8], severe suicidal ideation may not always be a prerequisite for suicidal acts in adolescents.
The authors are not aware of previous empirical estimations of clinically relevant cutoff for the SSI in adolescents. In this study ROC analysis of the whole sample yielded a reasonable result, but the validity coefficients for the different cutoffs of the SSI were somewhat difficult to interpret. In the community sample, there was only one subject with K-SADS-PL-diagnosed clinically significant suicidal ideation, which may have biased the analyses made with the whole sample. The results for both the whole sample and the patient sample suggest that a cutoff threshold score of four or more might be optimal for adolescents. Depending on the purpose the SSI is used, however, the emphasis between sensitivity and specificity may change, and a different threshold may be useful. For example, if the purpose is to detect the maximum number of potential suicides the cutoff threshold should be lowered to minimize the number of false negatives.
Limitations
Several methodological limitations should be noted, some suggesting caution in interpreting the findings. Inter-rater and test-retest reliabilities, which would have given a complete picture of the reliability of the SSI, could not be evaluated in our setting; they would have required repeated SSI measurements for each subject. However, the alpha-coefficients are a marker of internal consistency, which is one indicator of reliability.
Although large and representative, the sample was a pure outpatient sample with age- and sex-matched controls, and females were over-represented. The absence of inpatients may have caused us to see the spectrum of suicidal ideation narrower than in real clinical situations. The sample was limited to an urban area in southern Finland, the generalizability of our findings to rural areas, or to other countries, is not known.
The use of K-SADS-PL as a standard for clinically significant suicidal ideation and behavior may be criticized, as the authors are not aware of a data on its validity. It is used, however, as one of the best available standards in adolescent mood disorder diagnostics, and taps suicidality with 4 relevant items.
The same rater rated the K-SADS-PL and the SSI, which is a weaker test of concurrent validity than correlating measures rated by separate raters.
Clinical implications
The SSI can safely be used to evaluate suicidal ideation in adolescents where it seems to perform as well as in adults, where it is considered to be well established. When screening clinically significant suicidality in adolescents, a total score threshold of 3/4 may be useful.
Suicidal acts may occur among adolescents with only "mild" suicidal ideation. Thus, prevention of suicidal acts cannot rely solely on the SSI, which does not seem to tap them accurately. Furthermore, questionnaires should be only an adjunct to the clinical evaluation of suicidality.
Conclusions
SSI appears to be a reliable and a valid measure of suicidal ideation at depressed adolescents, with a cutoff threshold value of four or more of total SSI score being an appropriate for detecting significant suicidal ideation.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
MMH analyzed the data and wrote the paper. MP interviewed patients, participated in planning the study and analyses, and writing the paper. LK, TR, HH and VT participated in planning the study, interviewed patients, and commented on the manuscript. OK participated in planning the study and the analyses, and commented on the manuscript. MM supervised the study, interviewed patients and participated in planning of the study and analyses, and writing the paper. All authors read and approved the final manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
Acknowledgement of financial support: The study was financially supported by the Yrjö Jahnsson Foundation, Helsinki University Hospital and the Peijas Hospital.
We thank research assistant Mrs. Eevaliisa Orelma for her contribution in patient recruitment and data management.
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| 15691388 | PMC549544 | CC BY | 2021-01-04 16:33:03 | no | BMC Psychiatry. 2005 Feb 3; 5:8 | utf-8 | BMC Psychiatry | 2,005 | 10.1186/1471-244X-5-8 | oa_comm |
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BMC BiotechnolBMC Biotechnology1472-6750BioMed Central London 1472-6750-5-61570307810.1186/1472-6750-5-6Methodology ArticleFunctional complementation of RNA interference mutants in trypanosomes Rusconi Filippo [email protected] Mickaël [email protected] Philippe [email protected] UMR5153 CNRS, USM0503 MNHN, U565 INSERM – 57, rue Cuvier – B.P. 26 – F-75231 – Paris Cedex 05 – France2005 9 2 2005 5 6 6 10 11 2004 9 2 2005 Copyright © 2005 Rusconi 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 many eukaryotic cells, double-stranded RNA (dsRNA) triggers RNA interference (RNAi), the specific degradation of RNA of homologous sequence. RNAi is now a major tool for reverse-genetics projects, including large-scale high-throughput screens. Recent reports have questioned the specificity of RNAi, raising problems in interpretation of RNAi-based experiments.
Results
Using the protozoan Trypanosoma brucei as a model, we designed a functional complementation assay to ascertain that phenotypic effect(s) observed upon RNAi were due to specific silencing of the targeted gene. This was applied to a cytoskeletal gene encoding the paraflagellar rod protein 2 (TbPFR2), whose product is essential for flagellar motility. We demonstrate the complementation of TbPFR2, silenced via dsRNA targeting its UTRs, through the expression of a tagged RNAi-resistant TbPFR2 encoding a protein that could be immunolocalized in the flagellum. Next, we performed a functional complementation of TbPFR2, silenced via dsRNA targeting its coding sequence, through heterologous expression of the TbPFR2 orthologue gene from Trypanosoma cruzi: the flagellum regained its motility.
Conclusions
This work shows that functional complementation experiments can be readily performed in order to ascertain that phenotypic effects observed upon RNAi experiments are indeed due to the specific silencing of the targetted gene. Further, the results described here are of particular interest when reverse genetics studies cannot be easily achieved in organisms not amenable to RNAi. In addition, our strategy should constitute a firm basis to elaborate functional-dissection studies of genes from other organisms.
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Background
RNA interference (RNAi) can be triggered by introduction of long double-stranded RNA molecules (dsRNAs) in cells [1], and proceeds in a number of sequential steps, starting with the cleavage of long dsRNAs into shorter ≈ 21–23 nucleotide-long dsRNAs called short interfering RNAs (siRNAs; these were initially discovered in plants [2]). The enzyme responsible for this chopping (DICER; [3,4]) displays RNase III activity, producing characteristic siRNAs with a phosphorylated 5' end and a two nucleotide-overhanging 3'OH end. These siRNAs enter an RNA-induced silencing complex, or RISC [5,6]. A helicase activity unwinds the two strands of the siRNA, and RISC scans the mRNAs in the cytoplasm and cleaves the molecules that are found complementary to the RISC-contained siRNA [5].
RNA-silencing processes have been described in a variety of organisms: post-transcriptional gene silencing in plants [7,8], quelling in fungi [9], homology-dependent gene silencing in ciliates [10], or RNA interference in worms [1], flies [11,12], trypanosomes [13,14] and mammals [15,16]. It is thought that this machinery has evolved to protect cells against undesirable RNAs, like RNA viruses in plants [17,18], or to limit the mobility of transposable elements in animals [19-21].
While RNAi and associated phenomena constitute exceptional recent basic science findings, they also provided a basis for the elaboration of powerful research tools. RNAi methodologies have been set up to perform reverse-genetics studies in a number of organisms. RNAi potency and flexibility have allowed to perform high-throughput genetic screens in several organisms [22-26]. In mammalian cells, the presence of long dsRNA (>50 base pairs) triggers the activation of sequence-unspecific interferon-related pathways [27-29]. To circumvent this difficulty, researchers resorted to the transfection of small interfering RNAs [16] or in vivo synthesis of small hairpin RNAs, which were demonstrated to produce gene-specific silencing [27,30,31]; reviewed in [32,33].
However, an siRNA might trigger a number of potential unspecific events such as the degradation of partially complementary mRNA due to cross-hybridization, leading to unspecific RNAi, or the translational arrest due to a micro RNA-like effect where an siRNA hybridizes to a mRNA with one or few mismatches. It is thus of paramount importance to ensure that the phenotypic effects observed as a result of siRNA presence in cells are due to silencing of the target gene only. Two large-scale studies show that siRNA-induced gene silencing of transiently- or stably-expressed mRNA is highly gene-specific and does not produce secondary effects detectable by genome-wide expression profiling [34,35]. In contrast, other works provided evidence that siRNAs can be target-unspecific, with the observation of silencing of genes that had limited sequence homology with the siRNA [36,37]. These reports should prompt scientists to assess the specificity of RNAi-silencing in any experiment. A solution to that problem, that we devised in trypanosomes and which is described in this report, is based on the rescueing of the RNAi-mediated loss-of-function phenotype by expressing an RNAi-resistant version of the target gene.
Trypanosomes are protozoan parasites belonging to the Kinetoplastida order. These unicellular flagellated organisms diverged very early in eukaryotic evolution, and exhibit a number of original features [38-40]. Trypanosomes were amongst the first organisms where RNAi was discovered [13,14], and a number of strategies have been devised to either transiently or permanently induce gene-specific RNAi-silencing in these cells [14,41-43]. Examples of successful RNAi in trypanosomes used flagellar genes as targets which yielded easily monitored phenotypes [44]. From a structural point of view, the most conserved morphological feature of eukaryotic flagella is the axoneme, which is made of nine doublets of outer microtubules plus 2 central microtubules (so-called 9+2 axonemal structure). In trypanosomes, the flagellum not only has that axone-mal structure, but it also has a lattice-like structure called the paraflagellar rod (PFR) that is positioned along the axoneme. The two main components of the PFR are TbPFR2 and TbPFR1, that share 60% primary sequence identity [45,46]. TbPFR2 silencing leads to flagellar paralysis and trypanosomes do not swim anymore [13,47]. During the cell cycle, the cell first replicates its mitochondrial DNA (kinetoplast) and starts to grow a new flagellum whilst maintaining the old flagellum in place. Hence, a trypanosome which has two kinetoplasts and two nuclei will be close to completion of its cell cycle and will possess an old and a new flagellum [48]. This aspect is an interesting feature for RNAi-based studies of flagellar morphogenesis, because bi-flagellated cells have an "internal control" flagellum (the old one), while the new one has a phenotype corresponding to the RNAi-based gene knock-down. The presence of both the old and the new flagella in the same cell gives an indication of the time course of events when RNAi is induced in trypanosomes, leading to the appearance of a visible phenotype in the new flagellum while the older one is unchanged because it is not affected by gene silencing.
We previously established the degree of identity between the gene sequences capable of leading to cross-RNAi [47,49]. However, as mentioned earlier, each time a phenotype is observed in RNAi experiments, it is necessary to ensure that it is indeed due to the specific silencing of the targeted gene(s). Inspired by the procedure with which gene knock-out is usually performed (the control experiment is done by re-introducing the knocked-out gene to ensure that the lost function gets complemented), we devised a functional complementation strategy aimed at assessing that RNAi indeed targets the intended gene. This strategy, elaborated using the TbPFR2 gene as a model system, involved the silencing of the TbPFR2 target via its UTRs and the expression of a RNAi-resistant copy of the targetted gene. The RNAi-resistant gene was either a copy of TbPFR2 with different UTRs or its Trypanosoma cruzi orthologue: TcPFR2. We found that inter-species complementation experiments were straight forward. This strategy opens a venue for functional gene dissection experiments where modified gene sequences can be tested for their ability to encode functional protein that can complement the RNAi-based loss-of-function phenotype.
Results and discussion
Multiple RNAi on trypanosomes
We wanted to establish if the co-transfection of two distinct dsRNAs, targeting two different genes, could trigger their simultaneous silencing. The genes selected were TbPFR2 and FLA1; TbPFR2 encodes one of the two major components of the paraflagellar rod and is necessary for flagellum motility [13]; FLA1 encodes a protein required for flagellum attachment to the cell body [50]. These dsRNAs were transfected simultaneously in wild-type trypanosomes. As a control experiment, we used GFP dsRNA.
Cells were monitored for their acquired phenotype 15 h and 22 h after transfection (Table 1). The extinction of TbPFR2 was followed by immunofluorescence microscopy using the L8C4 anti-TbPFR2 monoclonal antibody. FLA1 gene silencing was analyzed by differential interference contrast microscopy, as it results in the visible detachement of the flagellum from the cell body (Figure 2).
The transfection of TbPFR2 dsRNA yielded potent silencing, as more than 60 % of the cells showed no staining for L8C4 15 h later. Since old flagella pre-exist in cells which were affected by RNAi at the beginning of cell replication, the real percentage of silenced cells is probably higher than 60 %, which is confirmed by the fact that it built up to more than 74 % at time point 22 h. The transfection of FLA1 dsRNA produced a phenotype in which the flagellum was detached from the cell body in more than 50 % of the cells. When both dsRNAs were co-transfected, both phenotypes were indeed observed, with similar frequencies to experiments where only one dsRNA was transfected. All the transfected cell populations did show a comparable growth rate (data not shown). The trypanosomes shown in Figure 2 had been transfected with both dsRNAs and the cell on the right is starting cytokinesis. The old flagellum of that cell is detached, while the new flagellum is attached along the cell body. The new flagellum exhibits a dilation of its distal tip, probably corresponding to the accumulation of TbPFR1, that is not assembled but still transported to the distal tip of the flagellum in the absence of TbPFR2 [13]. This observation demonstrates the usefulness of double-transfection experiments also for kinetics analysis. In our case, 22 h after dsRNAs transient transfection, the phenotype due to the FLA1 silencing is no longer visible in the new flagellum while that same flagellum still exhibits the phenotype due to the TbPFR2 silencing, clearly indicating different turn-over for TbPFR2 and FLA1 proteins.
The RNAi machinery could cope with two different dsRNA populations, without – in our conditions – any visible saturation effect. These results show the feasibility of experiments involving the use of multiple dsRNAs, thus allowing studies on complex processes in the cell physiology. However, such complex experiments can only be envisaged after ensuring that the phenotypes resulting from RNAi are specifically due to silencing of the target gene. In order to address that specific problem, we elaborated a method that involves RNAi experiments on trypanosomes that were engineered to possess an extra RNAi-resistant copy of the targeted gene, leading to functional complementation.
Gene silencing by dsRNA targeting UTRs
As a model for this study, we chose the TbPFR2 gene, which is present in four copies in the WT trypanosome genome (Figure 1A), all transcribed as a single long polycistronic mRNA. All these gene copies are separated by three identical intergenic UTRs (igUTR), while the first copy has a unique 5' UTR and the last copy has a unique 3'UTR. Three types of dsRNA populations were used in our experiments, and termed as follows. dsRNA homologous to the GFP sequence was labelled "GFP dsRNA"; dsRNA homologous to coding sequence of the TbPFR2 gene was labelled "CDS dsRNA"; finally, the mixture of three dsRNAs homologous to the 5' UTR, igUTR and 3'UTR of the TbPFR2 gene was termed "UTRs MIX dsRNAs" (Figure 1A). These dsRNAs were transfected into three cell lines: WT, TbPFR2tag and TbPFR2tag-ΔHLA (see Methods). For each experiment, the presence or absence of TbPFR2 in the new flagellum of bi-nucleated/bi-flagellated cells was monitored by immunofluorescence 14 h after the transfection (Table 2).
Reports in [14,24] showed that RNAi silencing of a gene can be accomplished by targeting transcribed non-coding sequences. Here, we wanted to make sure that this kind of experiment was still feasible with a more complex system such as the TbPFR2 multigene locus, where multiple and distinct UTRs regulate the expression of four TbPFR2 isogenes. We first transfected WT trypanosomes with GFP dsRNA as a negative control and did not detect any TbPFR2 silencing (Figure 3A). Second, WT trypanosomes were transfected with the CDS dsRNA: 88 % of cells showed typical TbPFR2 silencing with an anti-TbPFR2 immunofluorescence showing that the protein was missing from the new flagellum (Figure 3B). Finally, the WT trypanosomes were transfected with the UTRs MIX dsRNAs, yielding the same phenotype as for the CDS dsRNA, although the silencing appeared less pronounced (Figure 3C and Table 2). Overall, these results demonstrate that RNAi could efficiently silence all of the TbPFR2 gene copies by targeting non-coding sequences present at the mRNA level.
When WT trypanosomes were transfected with TbPFR2 dsRNA complementary to only one UTR, the cells did not display any specific phenotype (data not shown). This observation is probably explained by the organization of the TbPFR2 locus: the polycistronic transcript is rapidly spliced into three different types of mRNA, each encoding one of the four copies of TbPFR2 [51-53]. Thus, even if one type of TbPFR2 RNA is destroyed, the three remaining ones would likely provide enough RNA to synthesize TbPFR2 levels compatible with normal PFR formation.
To demonstrate that the silencing observed upon transfection of WT trypanosomes with the UTRs MIX dsRNAs was due to the actual targeting of TbPFR2, we used two cell lines expressing a supplementary tagged TbPFR2 gene copy. The TbPFR2tag cell line expresses the TbPFR2-TAG protein which correctly localizes to the flagellum.
The TbPFR2tag-ΔHLA cell line expresses TbPFR2-TAG-ΔHLA, lacking the HLA tripeptide, which prevents its localization to the flagellum. To determine both the cellular localization of the tagged TbPFR2 proteins (TbPFR2-TAG and TbPFR2-TAG-ΔHLA) and the completeness of the PFR assembly, immunofluorescence experiments were carried out with the BB2 and ROD-1 antibodies; the former recognizes the Ty-1 epitope tag present on the two tagged TbPFR2 proteins [54], while the latter is a marker for full PFR assembly [55,56].
GFP dsRNA was transfected as a negative control in each cell line. As expected, this did not yield any TbPFR2 silencing: TbPFR2 was decorated in both the old and new flagella by the anti-TbPFR2 antibody, and the PFR could be assembled fully, as evidenced by its staining with the ROD-1 antibody (data not shown, Table 2). In TbPFR2tag cells, TbPFR2-TAG was able to localize to the PFR, as evidenced by the PFR decoration with BB2 (red color, Figure 4A). In contrast, TbPFR2-TAG-ΔHLA failed to do so in TbPFR2tag-ΔHLA cells, and the BB2 signal was detected in the cytoplasm, as expected (red color, Figure 4D).
We next compared TbPFR2tag trypanosomes after transfection with either CDS dsRNA or UTRs MIX dsRNAs. TbPFR2tag cells transfected with CDS dsRNA had a flagellum not (or faintly) decorated with the anti-TbPFR2 antibody, demonstrating that both the WT and the recombinant TbPFR2 gene copies were effciently silenced (Table 2). That result was confirmed with anti-TAG immunofluorescence that showed no staining of the flagellum, demonstrating that TbPFR2-TAG was absent (no red color, Figure 4B). This lack of both TbPFR2 and TbPFR2-TAG led to an incomplete assembly of the PFR, which was therefore not decorated with the ROD-1 antibody (no yellow color, Figure 4B). In contrast, cells transfected with the UTRs MIX dsRNAs exhibited a WT phenotype, with only 2 % of the cells displaying TbPFR2 silencing in the flagellum (Table 2). In this case, the tagged protein was expressed, leading to complete assembly of the PFR (yellow color, Figure 4C) because the protein is functional and localized to the flagellum (red color, Figure 4C; [56]). This remarkable result indicates a complementation phenomenon that is explained by the fact that the tagged TbPFR2 gene was not silenced, as it was expressed from a coding sequence flanked by UTRs from the expression vector: from the 5' UTR of the procyclin gene and from the 3'UTR of the aldolase gene (Figure 1B; [57]).
To definitely demonstrate that the complementation described above is indeed due to the expression of functional TbPFR2-TAG, we transfected the same dsRNA into TbPFR2tag-ΔHLA trypanosomes expressing a modified TbPFR2 protein missing three amino acids (that is nine nucleotides out of 1800). TbPFR2tag-ΔHLA does not access the flagellar compartment and thus cannot be functional [58]. Transfecting either CDS dsRNA or UTRs MIX dsRNAs produced cells in which the new flagellum was not (or faintly) decorated by the anti-TbPFR2 antibody (Table 2). TbPFR2-TAG-ΔHLA was not decorated by the anti-TAG antibody when cells were transfected with CDS dsRNA (red color, Figure 4E), indicating that both the WT and the tagged TbPFR2 copies were silenced, thus leading to an incomplete PFR edification (yellow color, Figure 4E). In contrast, transfection of UTRs MIX dsRNAs did not prevent the expression of the recombinant TbPFR2-TAG-ΔHLA protein, as it appeared stained by the anti-TAG antibody (red color, Figure 4F). However, that non-functional protein could not participate in the construction of the PFR, as shown by the absence of ROD-1 signal in the new flagellum, since it cannot access the flagellum (yellow color, Figure 4F).
RNA-directed RNA polymerase activity (RdRP) has been implicated as one possible step in the formation of siRNA in fungi [59], plants [17,18], and worms [60]. The fact that we could specifically silence WT TbPFR2 by targeting its UTRs, without interfering with the tagged TbPFR2 genes, suggests that spreading of silencing beyond the initial targeted sequence does not occur in trypanosomes [61-64].
Functional complementation with orthologue genes
We next asked if an RNAi-mediated loss of function could be complemented by the expression of a gene orthologue to the silenced one. The system used to answer that question involved the TbPFR2i cell line – that expresses TbPFR2 dsRNA under the control of a tetracycline-inducible promoter [47] – into which constitutive expression of Trypanosoma cruzi TbPFR2 orthologue (TcPFR2) was established using stable transfection procedures. TbPFR2 and TcPFR2 proteins share 90 % identity (both of them are recognized by the anti-TbPFR2 L8C4 antibody), but their gene sequences have diverged enough for us to envisage that the RNAi-silencing of TbPFR2 would not affect significantly the introduced TcPFR2 gene (83 % overall nucleotide identity). We thus created two new cell lines based on the previously described TbPFR2i cells [47] (see Methods). TbPFR2 expression and cell motility were analyzed.
Our first experiment showed that the PCGFP cells constitutively expressed GFP, as detected by microscope observation of living cells (data not shown). Both the PCGFP and PCTcPFR2 cell lines were induced to express TbPFR2 dsRNA for 48 hours. Immunofluorescence revealed that non-induced PCGFP cells exhibit a WT-like phenotype (Figure 5A, -TET). When these cells were induced with tetracycline, expected TbPFR2 silencing occurred (Figure 5A, +TET). Non-induced PCTcPFR2 cells displayed an intense anti-TbPFR2 antibody decoration with bright dots in the cytoplasm, indicative of TcPFR2 overexpression (such overexpression by the EP procyclin promoter is frequent; Figure 5B, -TET). When these same cells were tetracycline-induced, the flagellar staining was still perfectly visible, at a level comparable to the one previously observed in the non-induced PCGFP control cells (Figure 5B, +TET). Bright dots previously observed had disappeared, probably as a result of TbPFR2 silencing. The fact that the paraflagellar rod was still neatly decorated by the anti-TbPFR2 antibody demonstrated that the structural inter-species complementation had indeed taken place in these cells, with TcPFR2 being effectively located at the flagellum.
Did these structurally-complemented cells show a functional complementation, i.e. a normal flagellum motility (hence a normal cellular mobility)? To address this question, we performed a sedimentation assay [56] on non-induced and tetracycline-induced PCGFP and PCTcPFR2 trypanosomes (Figure 6). Non-induced PCGFP cells showed a little tendency to sediment due to the fact that expression of TbPFR2 dsRNA in TbPFR2i cells is partially leaky, producing low amounts of TbPFR2 dsRNA even in the absence of tetracycline ([43]; Durand-Dubief and Bastin, unpublished data). When expression of TbPFR2 dsRNA was fully induced, motility stopped leading to increased sedimentation (Figure 6, left panel). In contrast, expression of TbPFR2 dsRNA in PCTcPFR2 cells did not reduce motility (Figure 6, right panel). That result definitely demonstrates that the ortholog protein TcPFR2 fully complemented the loss of function resulting from TbPFR2 silencing.
The complementation described above shows the robustness of our strategy, because TbPFR2 and TcPFR2 are highly similar (they share 82 % identity at the nucleotide level [65]) and are nonetheless correctly differenciated by the RNAi machinery. However, our complementation strategy might be more diffcult to implement when the gene studied is too similar to the T. brucei counterpart. While this unfavorable case might happen with extremely evolutionarily-related organisms, studies have shown that the overall genetic sequence identity between Trypanosoma brucei and Trypanosoma cruzi, for example (the closest evolutionarily-related organisms envisaged for these studies), is roughly 80 % ([65] and [66]). [47] showed that this identity percentage is still compatible with an RNAi-based complementation strategy. It goes without saying that when the organisms are evolutionarily-distant, gene sequences diverge more rapidly than the protein sequences, thus laying off a field where our strategy can be implemented with good confidence that complementation will occur.
Conclusions
In this report, we demonstrated that RNAi-mediated silencing of a gene by targeting its UTRs is useful in studies where the loss of function resulting from this silencing must be complemented with the expression of an RNAi-resistant copy of the silenced gene, in order to demonstrate that the phenotype is indeed due to silencing of that gene, and not to inactivation of another one. The results obtained in this work are of particular interest when reverse-genetics studies cannot be easily achieved in organisms not amenable to RNAi, like Leishmania [67] or Trypanosoma cruzi [68], or where genetics experiments are hardly set up, like mammals. When genes from these organisms are to be studied, a complementation experiment can be set up as a three-step procedure whereby: 1) the ortholog gene in Trypanosoma brucei is RNAi-silenced and the loss-of-function phenotype is established; 2) T. brucei cells are engineered to ensure constitutive heterologous expression of the gene of interest, still allowing RNAi-mediated silencing of the T. brucei gene; 3) function of the investigated gene is assessed by checking if the loss-of-function phenotype observed in the first place gets complemented. Additionally, one application of the strategy described herein is genetic functional dissection, which is of interest when protein domains are to be characterized with respect to their function (e.g. the HLA tripeptide sequence in TbPFR2 that localizes the protein to the flagellum).
Complementation had previously been demonstrated following transformation of mammalian cells with EGFP siRNA and expression of a codon-modified, but functional, EGFP version [69]. Our strategies are increasing flexibility for complementation studies after RNAi as unmodified genes can be used for rescue.
Methods
Trypanosomes
The procyclic T. brucei brucei strain 427 (or its derivatives) was used throughout this work. Cells were cultured at 27°C in semi-defined medium 79 (SDM 79) containing 10% foetal calf serum. PFRAi cells were described in [47]. The TbPFR2i trypanosomes can be tetracycline-induced to express TbPFR2 dsRNA, thus eliciting an RNAi response against that gene. Note that this cell line is referred to as TbPFR2i in this article because of a change in the gene nomenclature [70].
RNAi assays by transient transfection
RNA was synthesized in vitro with T3 and Sp6 polymerases using PCR products as templates [71]. The following primers (incorporating T3 or Sp6 promoters) were used:
for GFP (from the nucleotide coding sequence 476–691 of the EGFPN2 gene; Clontech), AATTAACCCTCACTAAAGGGAGAAG AACGGCATCAAGGTGAAC (T3 promoter italicized) and ATTTAGGTGACACTATAGAAG AGTGATCCCGGCGGCGGTCACG (Sp6 promoter italicized);
for FLA1, AATTAACCCTCACTAAAGGGAGA CCAAACCGTGGGCACCAAGG (T3 promoter italicized) and ATTTAGGTGAACTATAGAAGAG GTGGGATGATTAAAACGAGC (Sp6 promoter italicized);
for the TbPFR2 5' untranslated region (5' UTR; nucleotide sequence [-545→-1] upstream of TbPFR2 ATG start codon), AATTAACCCTCACTAAAGGGAGA (T3 promoter) and ATTTAGGTGACACT-ATAGAAGAG (Sp6 promoter);
for the TbPFR2 intergenic untranslated region (igUTR), AATTAACCCTCACTAAAGGGAGA CGCTGCGCTTAAATGTCTT (T3 promoter italicized) and ATTTAGGTGACACTATAGAAGA GTGATGCTTTATTGCTTTCT (Sp6 promoter italicized);
for the TbPFR2 3'untranslated region (3'UTR; nucleotide sequence [1→533] downstream of the TbPFR2 TAG stop codon), AATTAACCCTCACTAAAGGGAGA (universal T3 promoter) and ATTTAGGTGACACTATAGAAGAG (universal Sp6 promoter);
for the TbPFR2 coding sequence (CDS; nucleotide coding sequence [1084→1358]), ATTTAGGTGACACTATAGA GAGGTGAAGCGCCGTATTGAGGA (Sp6 promoter italicized) and AATTAACCCTCACTAAAGGGAGA GTTTTGTACAGGCGACGGAA (T3 promoter italicized);
Figure 1A shows the TbPFR2 locus and the position of the two dsRNA populations that were used, and their homology to either the coding sequence (labelled "CDS dsRNA") or the different 5'UTR, igUTR and 3'UTR all together (labelled "UTRs MIX dsRNAs"). A third dsRNA, homologous to the GFP gene is labelled "GFP dsRNA" throughout this work and was used as a control dsRNA. dsRNA was introduced into trypanosomes by electroporation, as described [14].
Plasmids
Plasmid pPC was generated from plasmid pSk1-GFP [50] as follows: pSk1-GFP was digested with Hind III and Eco RI to remove the GFP gene. Oligonucleotides AGCT GTCTAGCGATATCGGATCCG (forward) and AATT CGGATCCGATATCGCTAGCA (reverse) were annealed (protruding ends italicized) and the resulting double-strand oligonucleotide was ligated into the pSk1-GFP plasmid, resulting in the insertion of a poly-linker containing restriction sites Cla I, Hind III, Nhe I, Eco RV, Bam HI and Eco RI (Branche and Bastin; unpublished data). Plas-mid pPCTcPFR2 was generated as follows: amplification of the TcPFR2 gene was performed using Trypanosoma cruzi genomic DNA (kind gift of Cécile Gallet and Philippe Grellier, MNHN) and the two primers TcPFR2H (GAGTCTAAGCTTATGAGCTACAAGGAGGCATC) and TcPFR2ER (GCGTGGAATTCTTACTGTGTGATCTGCTGCAC). Both the amplified DNA fragment and the pPC plasmid were digested with Eco RI and Hind III. The fragment was ligated into pPC so as to yield the plasmid pPCTcPFR2 (Figure 1B).
Cell lines
The different constructs used to transform trypanosomes are shown on Figure 1B. The cell lines were established as follows.
WT-derived trypanosomes constitutively expressing TbPFR2-TAG proteins
The TbPFR2tag cell line was derived from the WT cell line into which the pTbPFR2TAG430 plasmid [72] was transfected. The recombinant cells constitutively expressed the TbPFR2-TAG protein, that is localized in the flagellum (Fig 4D). Tagged TbPFR2 is known to be functional [56,72]. In contrast, transformation of WT cells with the pTbPFR2TAGΔHLA430 plasmid lead to the expression of slightly modified TbPFR2 protein, missing only three amino acids, that failed to enter the flagellum compartment and hence was found in the cell body cytoplasm [58] (Fig 4G). This cell line was called TbPFR2tag-ΔHLA. After electroporation [73], cells were grown overnight and then distributed in 24-well plates in the presence of phleomycin (2 μg/mL) for selection.
TbPFR2i-derived trypanosomes constitutively expressing GFP and TcPFR2
TbPFR2i cells [47] constituted the genetic background into which we established the PCGFP and PCTcPFR2 new cell lines. The PCGFP cell line was established by transfecting TbPFR2i cells with plasmid pPCGFP after linearization with BstX I. For establishing the PCTcPFR2 cell line, the pPCTcPFR2 plasmid was linearized with BstX I and transfected into TbPFR2i cells. Recombinant cells were selected by addition of puromycin (1 μg/mL), phleomycin (2 μg/mL), G418 (15 μg/mL) and hygromycin (20 μg/mL) to the culture medium.
Immunofluorescence and microscopy
Three different monoclonal antibodies were used as hybridoma supernatants: L8C4, IgG recognizing T. brucei TbPFR2 and cross-reacting with T. cruzi orthologue TcPFR2 [74]; BB2, IgG recognizing the Ty-1 tag of the TbPFR2-TAG and TbPFR2-TAG-ΔHLA recombinant proteins [54]; and ROD-1, IgM recognizing a doublet of minor PFR proteins [55]. For immunofluorescence, trypanosomes were spread onto poly-L-lysine-coated slides, fixed in cold methanol and processed as described [75]. Experiments involving the use of L8C4 only were performed with an FITC-conjugated anti-mouse IgG secondary antibody. Double-staining experiments using BB2 and ROD-1 were performed with a TRITC-conjugated specific anti-mouse IgG secondary antibody and an FITC-conjugated specific anti-mouse IgM secondary antibody. DNA was systematically stained with 4',6-diamidino-2-phenylindole (DAPI). Slides were examined with a Leica DMR microscope, images were captured using a cooled CCD camera (Cool Snap HQ, Roper Scientific) and processed with the GNU image manipulation program version 2 [76].
Cell sedimentation assay
The trypanosome sedimentation assay was performed as described in [56]. Briefly: trypanosomes were grown at ≈ 5.106 cells/mL in normal culture medium, with or without 48 hour tetracycline induction. 1 mL of these cultures was dispensed to 5 plastic spectrophotometry cuvettes, for time points 0, 2, 4, 6, 8 hours, and left still. At each time point, the optical density at 600 nm was measured twice: first without mixing (O.D.no mix) and second after mixing the cuvette (O.D.mix). Data were plotted as a function of time.
Authors' contributions
F.R. carried out most of the experiments reported and wrote the manuscript, M.D.-D. performed the double transfection reported at Table 1 & Figure 2 and P.B. conceived the study and participated in its design and coordination.
Acknowledgements
We wish to thank Linda Kohl for live image acquisition, Carole Branche for providing pPC, Cécile Gal-let and Philippe Grellier for providing T. cruzi genomic DNA and Sabrina Benghanem for helpful discussions. M.D.-D. is supported by a "Bourse de formation recherche du Gouvernement luxembourgeois". This work was financed with the following grants: "ACI dynamique et réactivité des assemblages biologiques", (CNRS and Ministère de la recherche), "ACI biologie du développement et physiologie intégrative" (Ministère de la recherche), "GIS recherche sur les maladies rares" (INSERM and Institut des Maladies rares).
Figures and Tables
Figure 1 dsRNAs and plasmids used for transfections. (A) Not-to-scale schematic representation of the endogenous TbPFR2 locus, with four copies of TbPFR2 coding sequence and specific UTRs. Regions targeted by RNAi are highlighted. The TbPFR2 coding sequence was targeted using CDS dsRNA and the UTRs were targeted all together with a set of dsRNA homologous to the 3' UTR, the intergenic UTR (igUTR) and the 5' UTR (UTRs MIX dsRNAs). (B) Not-to-scale representation of the constructs used for the transfection of WT cells (pTbPFR2TAG430 and pTbPFR2TAG430-ΔHLA; integration in the rDNA spacer) or TbPFR2i cells (pPCGFP and pPCTcPFR2; integration in the tubulin intergenic region). Large boxes represent protein coding sequences (black boxes: proteins of interest; grey boxes: antibiotic-resistance activities). Each plasmid was linearized with the indicated restriction enzyme prior to transfection into the cells. 3' ALD UTR: 3' UTR of the aldolase gene; ACT UTR: 5' or 3' UTR of the actin gene; EP ig reg: EP procyclin intergenic region; TUB ig reg: tubulin intergenic region.
Figure 2 Silencing of FLA1 and TbPFR2 in Trypanosoma brucei. Wild type cells were simultaneously transfected with FLA1 and TbPFR2 dsRNA. At 22 h post-transfection, live cells were observed by differential interference contrast microscopy. Note the detached old flagellum and the dilation at the tip of the new flagellum (shorter one) of the rightmost cell.
Figure 3 TbPFR2 silencing by targeting its UTRs all together. WT cells were transfected with GFP dsRNA (A), CDS dsRNA (B) or UTRs MIX dsRNAs (C). At 14 h post-transfection, cells were treated for immunofluorescence using the L8C4 anti-TbPFR2 antibody (green) and counterstained with DAPI (blue). Cells of interest are bi-nucleated/bi-flagellated. Transfection of GFP dsRNA did not produce any specific phenotype. Both the CDS dsRNA and the UTRs MIX dsRNAs successfully silenced TbPFR2. Scale bar: 10 μm. See text for details.
Figure 4 Structural complementation of RNAi mutants. TbPFR2tag (panels A–C) or TbPFR2tag-ΔHLA (panels D–F) cells were transfected with GFP dsRNA (first column), CDS dsRNA (second column) or UTRs MIX dsRNAs (last column). At 14 h post-transfection, cells were treated for immunofluorescence with both the ROD-1 antibody (marker for full PFR assembly, yellow) and the BB2 anti-TAG antibody (red). All cells were counterstained with DAPI (blue). Cells of interest are bi-nucleated/bi-flagellated. Transfection of GFP dsRNA (A, D) did not produce any specific phenotype, whatever the recipient cells: the paraflagellar rod could assemble normally (yellow). As expected, TbPFR2-TAG localized to the flagellum (A, red), while TbPFR2-TAG-ΔHLA accumulated in the cytosol (D, red). The CDS dsRNA (B, E) successfully silenced the WT and the tagged TbPFR2 genes on both cell lines: no tagged TbPFR2 was stained with BB2; the paraflagellar rod could not assemble (no yellow signal is visible in the new flagellum). When using the UTRs MIX dsRNAs in TbPFR2tag and TbPFR2tag-ΔHLA cells, the wild-type TbPFR2 gene is silenced (see Figure 3). However, only in the TbPFR2tag cells does TbPFR2-TAG complement the missing TbPFR2 protein: TbPFR2-TAG was stained in the flagellum in (C, red). TbPFR2-TAG-ΔHLA failed to complement in the TbPFR2tag-ΔHLA cells: TbPFR2-TAG-ΔHLA was stained in the cytoplasm in (F, red). Thus, the paraflagellar rod could assemble fully in (C, yellow) but failed to do so in (F, yellow). Scale bar: 10 μm.
Figure 5 Interspecies structural complementation of RNAi mutants. TbPFR2i-derived trypanosomes, constitutively expressing GFP (panel A; PCGFP cells) or TcPFR2 (panel B; PCTcPFR2 cells) were cultured for 48 h in the absence (-TET) or in the presence (+TET) of tetracycline. In these TbPFR2i-derived cells, tetracyline-induction triggers RNAi-silencing of the endogenous TbPFR2 gene. The cells were then treated for immunofluorescence using L8C4 as an anti-TbPFR2 (right panel, black background) and counterstained with DAPI (left panel, merged with phase contrast image). Non-induced PCGFP cells show normal flagellar staining (A, -TET) while induced cells show an almost total loss of flagellar signal (A, +TET) due to silencing of TbPFR2. Non-induced PCTcPFR2 cells show an intense L8C4 signal in the flagellum and sometimes in the cytoplasm, due to overexpression (B, -TET). Upon tetracycline-induction of these cells, the flagellar L8C4 decoration did not disappear, indicating that TcPFR2 was not subject to RNAi and that TcPFR2 could successfully localize to the flagellum (B, +TET).
Figure 6 Phenotype analysis by sedimentation assay. PCGFP and PCTcPFR2 trypanosomes were induced (+Tet) with tetracycline for 48 h or non-induced (-Tet) and grown in cuvettes. Non-motile cells do not swim and sediment to the bottom of the cuvette, leading to a reduction in optical density that can be monitored over time. The PCTcPFR2 cells show an almost perfect functional complementation phenotype, as induced and non-induced cells had virtually identical sedimentation curves.
Table 1 Silencing effciencies after transfection of various dsRNAs. WT trypanosomes were transfected with TbPFR2, FLA1 or GFP dsRNA.
Time (hours)
dsRNA Phenotype (%) 0 h 15 h 22 h
TbPFR2 TbPFR2 silencing 0 61.2 (n = 1069) 74.2 (n = 1069)
FLA1 FLA1 silencing 0 56 (n = 586) 54 (n = 472)
TbPFR2 + GFP TbPFR2 silencing 0 56.2 (n = 301) 70.9 (n = 243)
TbPFR2 + FLA1 TbPFR2 silencing 0 53.6 (n = 349) 69.7 (n = 210)
FLA1 silencing 0 59 (n = 349) 53 (n = 210)
Table 2 Silencing effciencies after transfection of various dsRNAs.
Cell line TbPFR2 silencing in the new flagellum (% bi-flagellated cells)
dsRNA transfected
TbPFR2 CDS TbPFR2 UTRs MIX
WT 88 % (n = 53) 62 % (n = 147)
TbPFR2tag 68 % (n = 113) 2 % (n = 51)
TbPFR2tag-ΔHLA 78 % (n = 100) 72 % (n = 100)
WT, TbPFR2tag and TbPFR2tag-ΔHLA trypanosomes were transfected with GFP, TbPFR2 CDS or TbPFR2 UTRs MIX dsRNAs and bi-nucleated/bi-flagellated cells were counted for the status of their new flagellum. The data presented in this table correspond to the immunofluorescence experiment described in Figure 3 (see text for details).
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| 15703078 | PMC549545 | CC BY | 2021-01-04 16:02:58 | no | BMC Biotechnol. 2005 Feb 9; 5:6 | utf-8 | BMC Biotechnol | 2,005 | 10.1186/1472-6750-5-6 | oa_comm |
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BMC Med EducBMC Medical Education1472-6920BioMed Central London 1472-6920-5-61570116310.1186/1472-6920-5-6Research ArticleA quantitative survey of intern's knowledge of communication skills: an Iranian exploration Tavakol Mohsen [email protected] Sima [email protected] Owen D [email protected] Ali A [email protected] School of Education, Nottingham University, Wollaton Road, Nottingham, UK2 Ministry of Science, Research and Technology, Institute for research and planning in higher education, Iran3 Institute of Mathematics, Statistics and Actuarial Science, University of Kent, UK4 Educational Development Centre, Tehran University of Medical Science, Iran2005 8 2 2005 5 6 6 18 11 2004 8 2 2005 Copyright © 2005 Tavakol et al; licensee BioMed Central Ltd.2005Tavakol 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
It is a high priority that health care providers have effective communication skills. It has been well documented that the doctor-patient relationship is central to the delivery of high quality medical care, and it has been shown to affect patient satisfaction, to decrease the use of pain killers, to shorten hospital stays, to improve recovery from surgery and a variety of other biological, psychological and social outcomes. This study sought to quantify the current knowledge of interns in Iran about communication skills.
Methods
A cross-sectional study using a self-report questionnaire was conducted among interns. Data analysis was based on 223 questionnaires. The internal consistency of the items was 0.8979.
Results
Overall, knowledge levels were unsatisfactory. Results indicated that interns had a limited knowledge of communication skills, including identification of communication skills. In addition, there was a significant difference between the mean scores of interns on breaking bad news and sex education. The confidence of males about their communication skills was significantly higher than for females. Analysis of the total scores by age and sex showed that there was a statistically significant main effect for sex and the interaction with age was statistically significant. Free response comments of the interns are also discussed.
Conclusions
It is argued that there is a real need for integrating a communication skills course, which is linked to the various different ethnic and religious backgrounds of interns, into Iranian medical curricula. Some recommendations are made and the limitations of the study are discussed.
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Background
The expectations of the public have been dramatically increased and the majority of them are familiar with their rights in the health care system. As a consequence, it is a high priority that health care providers have effective communication skills. It has been well documented that the doctor-patient relationship is central to the delivery of high quality medical care. It has been shown to affect patient satisfaction, to decrease the use of pain killers, to shorten hospital stays, to improve recovery from surgery and a variety of other biological, psychological and social outcomes [1-4]. Lack of knowledge of communication skills, or an inability to use them effectively, can be distressing and is potentially hazardous for patients. It may also be a cause of stress for medical students arriving on the ward for the first time [5]. There is a large body of evidence indicating the importance of students' knowledge of communication skills and [6,7] how behaviours learned from communication skills training transfer into the clinical setting and such training is known to have long term effects on students behaviour [8-11].
However, little is known about the importance of communication skills in the practice and training of doctors in Iran, where the culture differs greatly from that of the West. Sensitivity to religious matters is particularly important in Iranian doctor-patient relationships where Islam is more than a religion; it is a way of life. It controls politics, local laws, behaviour and many other aspects of daily life. It gives guidance in all spheres of human activity from birth to death. Therefore doctors coming into contact with religious patients need to be aware that there are numerous potential barriers to good communication [12].
A major criticism of current medical training in Iran is that communication skills have not been embedded in the curriculum of Iranian medical students, despite the richness and variety of evidence from elsewhere concerning the importance of communication skills. Concerns over poor doctor-patient communication amongst Iranian doctors led to an exploration of the current situation [13]. In this paper we investigate the knowledge level of interns about communication skills to gain a clearer picture of some challenges relating to health care promotion, especially patient satisfaction and adherence to treatment. Two questions guided the study: (a) How do interns assess their knowledge about communication skills? (b) Is there a significant difference between the level of knowledge among male and female interns?
Methods
A quantitative survey was performed at Tehran University of Medical Science (TUMS). A cross-sectional study was conducted using a questionnaire administered to 235 interns. Anonymity was maintained throughout. The subjects received the self-administered questionnaire with a covering letter explaining the project and the subject's rights. 12 subjects did not return the questionnaire and an additional 7 subjects did not give their age and one person did not give his/her sex. Therefore data analysis was based on 223 questionnaires, but covariate-based analysis on fewer. The subjects were asked to complete the questionnaire without referring to source books.
The questionnaire consisted of three sections. The first section asked students to give personal details including the demographic items age and gender (summarised in Table 1). The second section is related to the educational items: subjects studied or attended in a specific course about communication skills (Table 2). The third section asked students to rate their knowledge of communication skills and, if they rated themselves higher than 5, discuss the item briefly in the space provided in order to assess their real knowledge with regard to that communication skill. In addition, they were encouraged to provide additional written comments on the questionnaire. The communication skills knowledge scale (CSKS) developed here consists of 10 items about communication skills. Each item is measured on a 10-point scale, ranging from 1 (low) to 10 (high).
Table 1 Distribution of background characteristics
Variables Number Percentages
Sex
Male 132 59.5
Female 90 40.5
Total 222 100
Age
Less than 25 114 52.8
25–30 96 44.4
More than 30 6 2.8
Total 216 100
Table 2 Percentage response to educational items by interns
Educational item Yes No
% %
1. Have you studied a paper in relation to communication skills? (n = 219) 21.9 78.1
2. Have you formally attended communication skills courses? (n = 221) 8.6 91.4
The choice of items was based on the communication skills an intern will need. All items were verified and subjected to content validation by three major experts in communication skills. These experts were given copies of the CSKS and the purpose and objectives of the study. They then evaluated the CSKS on an individual basis. Comparisons were made between these evaluations and the authors then made some minor changes within the CSKS. The CSKS had a high internal consistency (Cronbach alpha = 0.8979).
The validity of the CSKS can only be examined through logical rather than empirical means. Since the CSKS was not compared to a standardised test, it was impossible to obtain a numerical estimate of the validity of the test. However, based on logical means, i.e., a respectable Cronbach alpha and high inter-rater agreements on each item, the authors believe that the test is valid. The questions and responses have been translated from Persian into English for this paper.
Results
The potential score range from the 10-item CSKS (by summing all 10 item scores) is 10 to 100, with 10 indicating low knowledge. Analysis of the total scores produced a mean score of 51.30 [95 per cent confidence interval (CI) 49.05–53.55]. The subjects' performance on the CSKS suggests a knowledge deficit in communication skills. The mean scores for males and females were respectively 53.6 and 48.2 (P = 0.02). The vast majority of interns (78.1%) had not studied a paper on communication skills. When asked whether they had formally attended communication skills courses, 91.4% of interns reported "no". Of the few interns who reported "yes", these interns specified courses such as CPR, injections and semiology (Table 3), which are not formal communication skills courses.
Table 3 Courses of communication skills training reported by interns
Courses Number
CPR 2
EBM 1
Ethics 4
Health 2
Injection 1
Skills lab 3
Semiology 3
Workshop 1
Total 17
The analysis of the scores by topic is shown in table 4. The possible range of scores for each item was 1 to 10. Mean scores for topics ranged from 2.8 to 6.1. Interns were most confident on "giving and receiving information", and the least confident on "sex education".
Table 4 Analysis of results by communication skill
Topics Mean P Value
Male (SD) Female (SD)
Breaking bad news 4.6 (2.0) 3.7 (2.0) 0.02
Dealing with anger/difficult patient 5.0 (2.4) 4.4 (2.2) 0.81
Demonstration of empathy 5.3 (2.3) 5.5 (2.4) 0.56
Giving and receiving information 6.1 (2.3) 5.9 (2.2) 0.46
Non-verbal communication skills 5.3 (2.5) 5.0 (2.0) 0.37
Dealing with patient perception 5.8 (2.4) 5.4 (2.1) 0.22
Shared decision making 5.7 (2.2) 5.4 (2.3) 0.28
Patient-oriented interviewing 5.4 (2.3) 5.3 (2.3) 0.17
Sex education 4.6 (2.7) 2.8 (1.9) 0.00
Closing skills 5.4 (2.4) 4.8 (2.4) 0.08
Total 53.6 (17.4) 48.2 (15.8) 0.02
A two-way between-groups analysis was conducted to explore the impact of sex and age on levels of knowledge, as measured by the CSKS. Subjects were divided into two groups according to their age (less than 25 years, or 25 years and above). There was a statistically significant main effect for sex [F (1, 212) = 4.90, p = 0.02] and the interaction effect [F (1, 212) = 4.06, p = 0.04) did reach statistical significance. However the effect size was small (eta squared = 0.02). The young male interns were more confident than average, while the young female interns were less confident.
Free responses included the following comments:
'Nobody has trained us about communication skills. Our knowledge in respect of communication skills is very poor. Your items show that we are very far behind other countries. Our universities are not as advanced as other universities'.
'I feel we are not familiar with the ABC of communication skills'.
'A good guide to communication skills needed'.
'I feel communication skills would be an excellent course since it gives us an idea of how we can handle bad news'.
'Attending doctors are not totally familiar with the aims and use of communication skills in the clinical setting'.
'All our courses only focus on biological issues rather than psychosocial issues'
Limitations
There were a number of limitations to this study.
1. The CSKS has not been normed for a population of interns.
2. Criterion-related validity of the CSKS was not determined, although content validity was established on the instrument.
3. Since it is a self-assessed questionnaire, these may be problems with bias, such as prestige bias.
Discussion
The very high response rate (95%) of this questionnaire may have reflected general interest, or may have resulted from the advantages of self-assessment which itself may improve performance. The results on the CSKS show that basic knowledge of interns in Iran about communication skills is limited. Researchers have reported similar findings in other countries which reveal a deficit in the knowledge of doctors about communication skills [14]. The importance of communication skills has long been acknowledged in general practice training [15] and the need to teach communication skills formally, as part of British undergraduate medical education, has also been recognised [16]. In Iran, interns' knowledge deficiency may be attributed to the fact that interns have never been trained to consult in the general practice setting, and their skills are limited to making value judgements, often using the only available criterion, comparison with their own style [13]. This approach to a patient is not cost effective and may lead to negative health outcomes such as patient dissatisfaction, poor adherence to treatment and medical errors [17]. A few students reported their attendance at courses such as EBM, semiology, skills lab or CPR, which have no relation with communication skills training. This indicates that students are not familiar with the tasks of communication skills [18].
The vast majority of research studies have been conducted on the outcome of communication skills in the practice and training of doctors in western countries. Even here, despite doctors trained in communication skills and the advocacy of the use of a patient-oriented approach, some evidence suggests that there are difficulties in practice [19,20]. However, research has demonstrated that communication skills training intervention using behavioural, cognitive and affective domains can increase not only potentially beneficial and effective interviewing styles, but also alter attitudes and confer other benefits [9,21].
The results of the study show that there were significant differences between males and females with regard to their reported knowledge of the main communication skills. Women were less confident of their skills. The deficit may partly be an artefact of an inadvertent prestige bias of the male students. The deficit is particularly notable in sex education. There are three possible explanations for this. Firstly, in general, Iranian female interns are very shy to ask patients about sexual issues. Therefore they may feel that sex education skills have no implications for their practice and hence pay less attention to sex education training. Secondly, it may be a systematic error in female respondents, i.e. they may be shy to discuss their knowledge about sex education skills rather than lack knowledge. Thirdly, in the past, sex education was regarded as a taboo in Iran and was not available in schools, especially for girls [22]. This perhaps acts as an inhibitory factor on the basic knowledge of sex education. Within this context, there is no evidence that shows similar results for gender difference on the knowledge of sex education in the practice and training of doctors.
The results on the CSKS suggest that there are areas of weakness in the communication skills confidence of interns, particularly in breaking bad news. While it is well recognised that delivering bad news is a difficult task that requires skills and sensitivity [23], both female interns and male interns reported that their confidence in breaking bad news is low, especially the female interns. While the interns commented on the need to improve medical students' communication skills, it seems that guidelines on delivering bad news to patients and patients' family members have not been seriously taken into consideration in the practice and training of doctors in Iran. This could be due to interns possessing deep fears regarding delivering bad news to patients' family members, or because they are unaware of the general guidelines about delivering bad news [24]. Three studies which have attempted to address residents' perception of delivering bad news indicate that residents had experienced discomfort with psychosocial issues related to the conveyance of bad news, such as personal fears and different perceptions of bad news [25-27].
There is a significant difference between the mean score of the interns on breaking bad news. The female interns have reported lower confidence than the male interns. The deficit could be an inadvertent prestige bias of the male students. However, to our knowledge, there is no evidence that underpin such finding. Although Orlander et al's work [28] demonstrated there were no significant differences between males and females with regard to the type of bad news, residents' knowledge with regard to breaking bad news was not reported by the authors. Therefore, some empirical research is essential.
Given the poor levels of confidence about communication skills, particularly sex education skills, revealed in this study, it is concluded that educational programmes are necessary. In sex education skills training, given the complex interplay of cultural and religious beliefs in Iran, particular attention must be paid to multicultural and religious issues. Therefore, further work is needed on gender education and stereotypes in sex education; learning styles; the 'hidden curriculum'; and how far medical schools make organisational and administrative arrangements on the basis of gender and the implication for female and male interns.
The enthusiastic response to the questionnaires may suggest that medicine is accepting the need for developing communication skills within the medical curriculum. Medical education in Iran must respond to this challenge.
Finally, our findings may be somewhat limited in generalisability because they are derived from only one medical school in Iran. Self-assessment data may suffer from biases such as prestige bias. Despite these caveats, the authors believe the data to be an accurate reflection of current practice in Iran, based on the Iranian authors training experiences, and consistency with previous accounts.
Conclusions
Whilst the approach to this research has been shaped by a government-recognised health need, the authors recognise the need for, and welcome, further examination of these findings from multiple perspectives, especially with regards to ethnicity and social issues. Since not enough attention has been focused on individuals as makers of health as a service rather than customers of health care services, it is strongly recommended, therefore, that medical students be trained in the context of psychosocial issues that may influence health behaviour, as has been indicated by one of the participants. It is particularly important that this type of approach be incorporated into the curricula of medical training. This may assist in transferring from the disease-oriented to the patient-oriented approach and ultimately lead to patients understanding more and taking greater responsibility for their own health.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
MT and ST carried out the conception, design, initial analysis and interpretation of the data. MT drafted the paper. ODL was involved in revising the draft critically, revising the statistical analysis and gave final approval of the version to be published. AAZ contributed to the collection of data and the reviewing of the manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
The authors wish to acknowledge Tehran University of Medical science, Centre for Medical Education for their support of this study. Thanks also to the two reviewers whose comments allowed us to improve on our previous draft.
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| 15701163 | PMC549546 | CC BY | 2021-01-04 16:30:55 | no | BMC Med Educ. 2005 Feb 8; 5:6 | utf-8 | BMC Med Educ | 2,005 | 10.1186/1472-6920-5-6 | oa_comm |
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BMC Med EducBMC Medical Education1472-6920BioMed Central London 1472-6920-5-61570116310.1186/1472-6920-5-6Research ArticleA quantitative survey of intern's knowledge of communication skills: an Iranian exploration Tavakol Mohsen [email protected] Sima [email protected] Owen D [email protected] Ali A [email protected] School of Education, Nottingham University, Wollaton Road, Nottingham, UK2 Ministry of Science, Research and Technology, Institute for research and planning in higher education, Iran3 Institute of Mathematics, Statistics and Actuarial Science, University of Kent, UK4 Educational Development Centre, Tehran University of Medical Science, Iran2005 8 2 2005 5 6 6 18 11 2004 8 2 2005 Copyright © 2005 Tavakol et al; licensee BioMed Central Ltd.2005Tavakol 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
It is a high priority that health care providers have effective communication skills. It has been well documented that the doctor-patient relationship is central to the delivery of high quality medical care, and it has been shown to affect patient satisfaction, to decrease the use of pain killers, to shorten hospital stays, to improve recovery from surgery and a variety of other biological, psychological and social outcomes. This study sought to quantify the current knowledge of interns in Iran about communication skills.
Methods
A cross-sectional study using a self-report questionnaire was conducted among interns. Data analysis was based on 223 questionnaires. The internal consistency of the items was 0.8979.
Results
Overall, knowledge levels were unsatisfactory. Results indicated that interns had a limited knowledge of communication skills, including identification of communication skills. In addition, there was a significant difference between the mean scores of interns on breaking bad news and sex education. The confidence of males about their communication skills was significantly higher than for females. Analysis of the total scores by age and sex showed that there was a statistically significant main effect for sex and the interaction with age was statistically significant. Free response comments of the interns are also discussed.
Conclusions
It is argued that there is a real need for integrating a communication skills course, which is linked to the various different ethnic and religious backgrounds of interns, into Iranian medical curricula. Some recommendations are made and the limitations of the study are discussed.
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Background
The expectations of the public have been dramatically increased and the majority of them are familiar with their rights in the health care system. As a consequence, it is a high priority that health care providers have effective communication skills. It has been well documented that the doctor-patient relationship is central to the delivery of high quality medical care. It has been shown to affect patient satisfaction, to decrease the use of pain killers, to shorten hospital stays, to improve recovery from surgery and a variety of other biological, psychological and social outcomes [1-4]. Lack of knowledge of communication skills, or an inability to use them effectively, can be distressing and is potentially hazardous for patients. It may also be a cause of stress for medical students arriving on the ward for the first time [5]. There is a large body of evidence indicating the importance of students' knowledge of communication skills and [6,7] how behaviours learned from communication skills training transfer into the clinical setting and such training is known to have long term effects on students behaviour [8-11].
However, little is known about the importance of communication skills in the practice and training of doctors in Iran, where the culture differs greatly from that of the West. Sensitivity to religious matters is particularly important in Iranian doctor-patient relationships where Islam is more than a religion; it is a way of life. It controls politics, local laws, behaviour and many other aspects of daily life. It gives guidance in all spheres of human activity from birth to death. Therefore doctors coming into contact with religious patients need to be aware that there are numerous potential barriers to good communication [12].
A major criticism of current medical training in Iran is that communication skills have not been embedded in the curriculum of Iranian medical students, despite the richness and variety of evidence from elsewhere concerning the importance of communication skills. Concerns over poor doctor-patient communication amongst Iranian doctors led to an exploration of the current situation [13]. In this paper we investigate the knowledge level of interns about communication skills to gain a clearer picture of some challenges relating to health care promotion, especially patient satisfaction and adherence to treatment. Two questions guided the study: (a) How do interns assess their knowledge about communication skills? (b) Is there a significant difference between the level of knowledge among male and female interns?
Methods
A quantitative survey was performed at Tehran University of Medical Science (TUMS). A cross-sectional study was conducted using a questionnaire administered to 235 interns. Anonymity was maintained throughout. The subjects received the self-administered questionnaire with a covering letter explaining the project and the subject's rights. 12 subjects did not return the questionnaire and an additional 7 subjects did not give their age and one person did not give his/her sex. Therefore data analysis was based on 223 questionnaires, but covariate-based analysis on fewer. The subjects were asked to complete the questionnaire without referring to source books.
The questionnaire consisted of three sections. The first section asked students to give personal details including the demographic items age and gender (summarised in Table 1). The second section is related to the educational items: subjects studied or attended in a specific course about communication skills (Table 2). The third section asked students to rate their knowledge of communication skills and, if they rated themselves higher than 5, discuss the item briefly in the space provided in order to assess their real knowledge with regard to that communication skill. In addition, they were encouraged to provide additional written comments on the questionnaire. The communication skills knowledge scale (CSKS) developed here consists of 10 items about communication skills. Each item is measured on a 10-point scale, ranging from 1 (low) to 10 (high).
Table 1 Distribution of background characteristics
Variables Number Percentages
Sex
Male 132 59.5
Female 90 40.5
Total 222 100
Age
Less than 25 114 52.8
25–30 96 44.4
More than 30 6 2.8
Total 216 100
Table 2 Percentage response to educational items by interns
Educational item Yes No
% %
1. Have you studied a paper in relation to communication skills? (n = 219) 21.9 78.1
2. Have you formally attended communication skills courses? (n = 221) 8.6 91.4
The choice of items was based on the communication skills an intern will need. All items were verified and subjected to content validation by three major experts in communication skills. These experts were given copies of the CSKS and the purpose and objectives of the study. They then evaluated the CSKS on an individual basis. Comparisons were made between these evaluations and the authors then made some minor changes within the CSKS. The CSKS had a high internal consistency (Cronbach alpha = 0.8979).
The validity of the CSKS can only be examined through logical rather than empirical means. Since the CSKS was not compared to a standardised test, it was impossible to obtain a numerical estimate of the validity of the test. However, based on logical means, i.e., a respectable Cronbach alpha and high inter-rater agreements on each item, the authors believe that the test is valid. The questions and responses have been translated from Persian into English for this paper.
Results
The potential score range from the 10-item CSKS (by summing all 10 item scores) is 10 to 100, with 10 indicating low knowledge. Analysis of the total scores produced a mean score of 51.30 [95 per cent confidence interval (CI) 49.05–53.55]. The subjects' performance on the CSKS suggests a knowledge deficit in communication skills. The mean scores for males and females were respectively 53.6 and 48.2 (P = 0.02). The vast majority of interns (78.1%) had not studied a paper on communication skills. When asked whether they had formally attended communication skills courses, 91.4% of interns reported "no". Of the few interns who reported "yes", these interns specified courses such as CPR, injections and semiology (Table 3), which are not formal communication skills courses.
Table 3 Courses of communication skills training reported by interns
Courses Number
CPR 2
EBM 1
Ethics 4
Health 2
Injection 1
Skills lab 3
Semiology 3
Workshop 1
Total 17
The analysis of the scores by topic is shown in table 4. The possible range of scores for each item was 1 to 10. Mean scores for topics ranged from 2.8 to 6.1. Interns were most confident on "giving and receiving information", and the least confident on "sex education".
Table 4 Analysis of results by communication skill
Topics Mean P Value
Male (SD) Female (SD)
Breaking bad news 4.6 (2.0) 3.7 (2.0) 0.02
Dealing with anger/difficult patient 5.0 (2.4) 4.4 (2.2) 0.81
Demonstration of empathy 5.3 (2.3) 5.5 (2.4) 0.56
Giving and receiving information 6.1 (2.3) 5.9 (2.2) 0.46
Non-verbal communication skills 5.3 (2.5) 5.0 (2.0) 0.37
Dealing with patient perception 5.8 (2.4) 5.4 (2.1) 0.22
Shared decision making 5.7 (2.2) 5.4 (2.3) 0.28
Patient-oriented interviewing 5.4 (2.3) 5.3 (2.3) 0.17
Sex education 4.6 (2.7) 2.8 (1.9) 0.00
Closing skills 5.4 (2.4) 4.8 (2.4) 0.08
Total 53.6 (17.4) 48.2 (15.8) 0.02
A two-way between-groups analysis was conducted to explore the impact of sex and age on levels of knowledge, as measured by the CSKS. Subjects were divided into two groups according to their age (less than 25 years, or 25 years and above). There was a statistically significant main effect for sex [F (1, 212) = 4.90, p = 0.02] and the interaction effect [F (1, 212) = 4.06, p = 0.04) did reach statistical significance. However the effect size was small (eta squared = 0.02). The young male interns were more confident than average, while the young female interns were less confident.
Free responses included the following comments:
'Nobody has trained us about communication skills. Our knowledge in respect of communication skills is very poor. Your items show that we are very far behind other countries. Our universities are not as advanced as other universities'.
'I feel we are not familiar with the ABC of communication skills'.
'A good guide to communication skills needed'.
'I feel communication skills would be an excellent course since it gives us an idea of how we can handle bad news'.
'Attending doctors are not totally familiar with the aims and use of communication skills in the clinical setting'.
'All our courses only focus on biological issues rather than psychosocial issues'
Limitations
There were a number of limitations to this study.
1. The CSKS has not been normed for a population of interns.
2. Criterion-related validity of the CSKS was not determined, although content validity was established on the instrument.
3. Since it is a self-assessed questionnaire, these may be problems with bias, such as prestige bias.
Discussion
The very high response rate (95%) of this questionnaire may have reflected general interest, or may have resulted from the advantages of self-assessment which itself may improve performance. The results on the CSKS show that basic knowledge of interns in Iran about communication skills is limited. Researchers have reported similar findings in other countries which reveal a deficit in the knowledge of doctors about communication skills [14]. The importance of communication skills has long been acknowledged in general practice training [15] and the need to teach communication skills formally, as part of British undergraduate medical education, has also been recognised [16]. In Iran, interns' knowledge deficiency may be attributed to the fact that interns have never been trained to consult in the general practice setting, and their skills are limited to making value judgements, often using the only available criterion, comparison with their own style [13]. This approach to a patient is not cost effective and may lead to negative health outcomes such as patient dissatisfaction, poor adherence to treatment and medical errors [17]. A few students reported their attendance at courses such as EBM, semiology, skills lab or CPR, which have no relation with communication skills training. This indicates that students are not familiar with the tasks of communication skills [18].
The vast majority of research studies have been conducted on the outcome of communication skills in the practice and training of doctors in western countries. Even here, despite doctors trained in communication skills and the advocacy of the use of a patient-oriented approach, some evidence suggests that there are difficulties in practice [19,20]. However, research has demonstrated that communication skills training intervention using behavioural, cognitive and affective domains can increase not only potentially beneficial and effective interviewing styles, but also alter attitudes and confer other benefits [9,21].
The results of the study show that there were significant differences between males and females with regard to their reported knowledge of the main communication skills. Women were less confident of their skills. The deficit may partly be an artefact of an inadvertent prestige bias of the male students. The deficit is particularly notable in sex education. There are three possible explanations for this. Firstly, in general, Iranian female interns are very shy to ask patients about sexual issues. Therefore they may feel that sex education skills have no implications for their practice and hence pay less attention to sex education training. Secondly, it may be a systematic error in female respondents, i.e. they may be shy to discuss their knowledge about sex education skills rather than lack knowledge. Thirdly, in the past, sex education was regarded as a taboo in Iran and was not available in schools, especially for girls [22]. This perhaps acts as an inhibitory factor on the basic knowledge of sex education. Within this context, there is no evidence that shows similar results for gender difference on the knowledge of sex education in the practice and training of doctors.
The results on the CSKS suggest that there are areas of weakness in the communication skills confidence of interns, particularly in breaking bad news. While it is well recognised that delivering bad news is a difficult task that requires skills and sensitivity [23], both female interns and male interns reported that their confidence in breaking bad news is low, especially the female interns. While the interns commented on the need to improve medical students' communication skills, it seems that guidelines on delivering bad news to patients and patients' family members have not been seriously taken into consideration in the practice and training of doctors in Iran. This could be due to interns possessing deep fears regarding delivering bad news to patients' family members, or because they are unaware of the general guidelines about delivering bad news [24]. Three studies which have attempted to address residents' perception of delivering bad news indicate that residents had experienced discomfort with psychosocial issues related to the conveyance of bad news, such as personal fears and different perceptions of bad news [25-27].
There is a significant difference between the mean score of the interns on breaking bad news. The female interns have reported lower confidence than the male interns. The deficit could be an inadvertent prestige bias of the male students. However, to our knowledge, there is no evidence that underpin such finding. Although Orlander et al's work [28] demonstrated there were no significant differences between males and females with regard to the type of bad news, residents' knowledge with regard to breaking bad news was not reported by the authors. Therefore, some empirical research is essential.
Given the poor levels of confidence about communication skills, particularly sex education skills, revealed in this study, it is concluded that educational programmes are necessary. In sex education skills training, given the complex interplay of cultural and religious beliefs in Iran, particular attention must be paid to multicultural and religious issues. Therefore, further work is needed on gender education and stereotypes in sex education; learning styles; the 'hidden curriculum'; and how far medical schools make organisational and administrative arrangements on the basis of gender and the implication for female and male interns.
The enthusiastic response to the questionnaires may suggest that medicine is accepting the need for developing communication skills within the medical curriculum. Medical education in Iran must respond to this challenge.
Finally, our findings may be somewhat limited in generalisability because they are derived from only one medical school in Iran. Self-assessment data may suffer from biases such as prestige bias. Despite these caveats, the authors believe the data to be an accurate reflection of current practice in Iran, based on the Iranian authors training experiences, and consistency with previous accounts.
Conclusions
Whilst the approach to this research has been shaped by a government-recognised health need, the authors recognise the need for, and welcome, further examination of these findings from multiple perspectives, especially with regards to ethnicity and social issues. Since not enough attention has been focused on individuals as makers of health as a service rather than customers of health care services, it is strongly recommended, therefore, that medical students be trained in the context of psychosocial issues that may influence health behaviour, as has been indicated by one of the participants. It is particularly important that this type of approach be incorporated into the curricula of medical training. This may assist in transferring from the disease-oriented to the patient-oriented approach and ultimately lead to patients understanding more and taking greater responsibility for their own health.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
MT and ST carried out the conception, design, initial analysis and interpretation of the data. MT drafted the paper. ODL was involved in revising the draft critically, revising the statistical analysis and gave final approval of the version to be published. AAZ contributed to the collection of data and the reviewing of the manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
The authors wish to acknowledge Tehran University of Medical science, Centre for Medical Education for their support of this study. Thanks also to the two reviewers whose comments allowed us to improve on our previous draft.
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| 15701178 | PMC549547 | CC BY | 2021-01-04 16:02:51 | no | BMC Bioinformatics. 2005 Feb 8; 6:23 | latin-1 | BMC Bioinformatics | 2,005 | 10.1186/1471-2105-6-23 | oa_comm |
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BMC Evol BiolBMC Evolutionary Biology1471-2148BioMed Central London 1471-2148-5-131569847310.1186/1471-2148-5-13Research ArticleThe evolution of the Sin1 gene product, a little known protein implicated in stress responses and type I interferon signaling in vertebrates Wang Shu-Zong [email protected] R Michael [email protected] Veterinary Pathobiology, University of Missouri, Columbia, USA2 Biochemistry, University of Missouri, Columbia, USA3 Animal Sciences, University of Missouri, Columbia, USA4 Center for Developmental Biology, University of Texas Southwestern, Medical Center, Dallas USA2005 7 2 2005 5 13 13 14 9 2004 7 2 2005 Copyright © 2005 Wang and Roberts; licensee BioMed Central Ltd.2005Wang and Roberts; 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 yeast, birds and mammals, the SAPK-interacting protein 1 (Sin1) gene product has been implicated as a component of the stress-activated protein kinase (SAPK) signal transduction pathway. Recently, Sin1 has also been shown to interact with the carboxyl terminal end of the cytoplasmic domain of the ovine type I interferon receptor subunit 2 (IFNAR2). However, the function of Sin1 remains unknown. Since SAPK pathways are ancient and the IFN system is confined to vertebrates, the organization of the Sin1 gene and the sequences of the Sin1 protein have been compared across a wide taxonomic range of species.
Results
Sin1 is represented, apparently as a single gene, in all metazoan species and fungi but is not detectable in protozoa, prokaryotes, or plants. Sin1 is highly conserved in vertebrates (79–99% identity at amino acid level), which possess an interferon system, suggesting that it has been subjected to powerful evolutionary constraint that has limited its diversification.
Sin1 possesses at least two unique sequences in its IFNAR2-interacting region that are not represented in insects and other invertebrates. Sequence alignment between vertebrates and insects revealed five Sin1 strongly conserved domains (SCDs I-V), but an analysis of any of these domains failed to identify known functional protein motifs. SCD III, which is approximately 129 amino acids in length, is particularly highly conserved and is present in all the species examined, suggesting a conserved function from fungi to mammals. The coding region of the vertebrate Sin1 gene encompasses 11 exon and 10 introns, while in C. elegans the gene consists of 10 exons and 9 introns organized distinctly from those of vertebrates. In yeast and insects, Sin1 is intronless.
Conclusions
The study reveals the phylogeny of a little studied gene which has recently been implicated in two important signal transduction pathways, one ancient (stress response), one relatively new (interferon signaling).
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Background
Sin1 was originally described as a human protein that modulated Ras function in Saccharomyces cerevisiae [1]. Strains of yeast that expressed the constitutively activated RAS2Val 19 mutation had elevated levels of cyclic AMP, impaired growth control and were acutely sensitive to heat shock. This phenotype was reversed when the yeast strain was transfected with a cDNA (clone JC310) that encoded a then unknown protein. Although the authors suggested that the inferred interaction between the JC310 product and RAS might be fortuitous, they favored the possibility that that the unknown protein either was a true inhibitor of RAS or that it was a RAS target protein, which when over-expressed, had a protective action. A S. cerevisiae protein encoded by the AVO1 gene showed distant similarity the human JC310 product [2,3].
Approximately eight years after the identification of JC310 it was again identified, on this occasion in a yeast two-hybrid screen of a Schizosaccharomyces pombe cDNA library as a 665 amino acid protein that bound via polypeptide sequences in its C-terminal 244 amino acids to the Sty1/Spc1, stress activated MAP kinase (SAPK) [2]. A fission yeast strain lacking the Sin1 gene was sterile, sensitive to multiple types of stress, including heat shock, and had delayed cell cycles compared to a parental strain. Sin1 acted downstream of activated Sty1/Spc1 and appeared to be necessary for normal function of the transcription factor Atf1, a homolog of human ATF2. Wilkinson et al. [2] found that an apparent full length homolog of Sin1 from chicken allowed the heat sensitive strain of S. pombe to grow at 37°C, albeit very poorly. Moreover, fusion of the first 486 amino acids of yeast Sin1 (which does not restore growth) with the C-terminal 182 amino acids of the chicken Sin1 sequence protected against heat shock. Together, these data showed that Sin1 functions as a component of the stress-activated Sty1/Spc1 MAP kinase pathway in S. pombe and that a functional homolog of Sin1 exists in vertebrates.
No further information concerning Sin1 appeared since the paper of Wilkinson et al. [2] until our discovery that the ovine (ov) Sin1 associated via its C-terminus to the cytoplasmic domain of IFNAR2, a subunit of the type I IFN receptor [4], and Schroder et al. [5] described transcripts for Sin1 in human tissue and provided an analysis of the human gene. The latter study confirmed that Sin1 was relatively well conserved across Metazoa and fungi (Ascomyctes and Basidiomycetes) and was also represented in amoebae, but not in other protozoan species.
Ovine Sin1, which is 88% identical in sequence to chicken Sin1, can be co-immunoprecipated with the IFN receptor subunit IFNAR2 and shows a similar subcellular distribution to the receptor protein when co-expressed in mammalian cells [4]. Although ovSin1 was identified from a cDNA present in ovine endometrium and was initially considered to have a role in reproduction associated with the action of IFN-τ on the uterus during early pregnancy in the sheep, it became clear that the Sin1 gene was expressed in tissues other than endometrium and might have a general role in the action of type 1 IFN. In particular, it seemed possible that Sin1 might link the action of IFN to the stress activated SAPK signal transduction pathways. Such a linkage has been inferred from earlier studies in which early activation of p38 MAPK had been noted following exposure of a variety of cell lines to IFN-α, -β, or -τ [6-12].
Although the SAPK pathway is itself ancient and is found in all the species in which the Sin1 gene exists, the IFN system of receptors and ligands is restricted to vertebrates. We reasoned, therefore, that an analysis of Sin1 gene sequences might not only provide insight into the function of Sin1, but indicate how the protein evolved to interact with IFNAR2. The fact that the Sin1 gene appears to be expressed ubiquitously, that it is highly conserved across a wide range of taxa, and that it is a likely participant in several important signaling pathways, makes it an intriguing candidate for a functional/evolutionary analysis.
Results
Conservation of the Sin1 gene from yeast to mammals
A combination of searching methods was employed to locate Sin1 genes in available cDNA and genome data bases (Table 1). Sin1 sequences were found in two yeast species (Schizosaccharomyces pombe and Saccharomyces cerevisiae), the red bread mold (Neurospora crassa) and a number of other fungal species (not shown here), Caenorhabditis elegans, a mosquito species (Anopheles gambiae), fruit fly (D. melanogaster), frog (Xenopus laevis), two fish species (Fugu rubripes and Danio rerio), chicken (Gallus gallus), mouse (Mus musculus), rat (Rattus norvegicus), human (Homo sapiens), sheep (Ovis aries), cattle (Bos taurus), and pig (Sus scrofa) (Table 1). No apparent ortholog could be detected in the plant Arabidopsis thaliana. Nor could sequences corresponding to Sin1 be found in protozoa other than amoebae and prokaryotic species.
Table 1 Sin1 genes and their GenBank accession numbers
Organism GenBank Accession No. Comments
Yeast (Saccharomyces cerevisiae NP_014563 Blastp the yeast protein database with fission yeast Sin1 protein.
Yeast (Schizosaccharomyces pombe NP_594703 Wilkinson et al. 1999.
Red bread mold (Neurospora crassa XP_322410 Blastp protein databases with budding yeast Sin1 protein.
Worm (Caenorhabditis elegans) NM_064195 Blastp the worm protein database with ovSin1 protein.
Fly (Drosophila melanogaster) AE003814 Blastp the fly protein database with ovSin1 protein.
Mosquito (Anopheles gambiae) XM_319576 Blastp the mosquito protein database with ovSin1 protein.
Fish (Fugu rubripes) N.A. Blastp the fugu protein database with ovSin1 protein.
Frog (Xenopus lavis) BC043789 Search EST databases with chicken Sin1 cDNA.
Chicken (Gallus gallus) AF153127 Wilkinson et al. 1999.
Mouse (Mus musculus) BQ713136, BF781677, BU152256 Search mouse EST and genome databases with sheep Sin1 cDNA
Rat (Rattus norvegicus) CK476507, BE127132, BF553331, BU759329, AW141364 Search EST and genome databases with sheep Sin1 cDNA.
Pig (Sus scrofa) CF791532, CF178115, BP459453, CF177341 Search EST databases with sheep Sin1 cDNA.
Cattle (Bos taurus) BF230134, AV603930, CB433957, BM480500 Search EST databases with sheep Sin1 cDNA.
Sheep (Ovis aries) AY547378 Wang oberts, 2004
Human (Homo sapiens) NM_024117, BC002326 Search human EST and genome database with sheep Sin1 cDNA
"Comments" briefly describe the methods used to obtain the sequences.
The marked dissimilarity in inferred amino acid sequence between Sin1 from vertebrates and C. elegans (25% identity, Table 2), between the two yeast species (29% identity, Table 2; see Additional file: 1) and between S. pombe and N. crassa (28% identity, Table 2, see Additional file: 2) in the approximately 500 aa of overlap suggests that even if homologs existed in plants and prokaryotes they would likely be overlooked by the search methods employed.
Table 2 Pairwise comparisons of Sin1 cDNA and amino acid sequences from various species
S. pomb e (665 aa) N. crassa (798 aa) C. elegans (684 aa) D. melanogaster (569 aa) A. gambiae (548 aa) F. Rubripes (530 aa) X. lavis (520 aa) G. gallus (522 aa) M. musculus (522 aa) R. norvegicus (522 aa) O. aries (522 aa) B. Taurus (522 aa) S. scrofa (522 aa) H. sapiens (522 aa)
S. pombe (665 aa) - 28.2 34.1* 28.8* 35.6* 21.7 28.2 21.1 24.6 26.1 25.5 25.4 24.8 25.3
N. crassa (798 aa) NA - 32.6* 28.3* 30.7* 22.6 31.9* 20.3 36.2* 20.5 20.9 20.9 20.9 20.5
C. elegans (684 aa) NA NA - 27.5* 29.4* 22.3 22.6 21.8 23.0 23.0 23.5 23.2 22.8 23.2
D. melanogaster (569 aa) NA NA NA - 46.0 31.8 34.5 32.9 35.2 35.3 31.1 31.7 32.0 31.9
A. gambiae (548 aa) NA NA NA NA - 34.9 33.4 35.3 33.8 34.0 33.2 33.0 33.2 33.4
F. rubripes (530 aa) NA NA NA NA NA - 80.0 82.9 78.7 79.2 79.8 80.2 79.8 80.4
X. lavis (520 aa) NA NA NA NA NA 71.8 - 88.5 84.4 85.0 84.6 85.2 85.2 85.6
G. gallus (522 aa) NA NA NA NA NA 74.7 78.0 - 88.0 88.3 88.3 89.3 89.3 90.0
M. musculus (522 aa) NA NA NA NA NA 73.6 76.1 80.9 - 99.2 91.7 96.9 97.3 96.9
R. norvegicus (522 aa) NA NA NA NA NA 73.6 76.3 80.5 96.2 - 91.3 96.9 96.9 96.9
O. aries (522 aa) NA NA NA NA NA 73.3 75.3 81.7 96.0 96.0 - 98.7 97.9 98.1
B. taurus (522 aa) NA NA NA NA NA 73.4 75.6 81.7 91.9 91.8 98.2 - 98.9 99.0
S. scrofa (522 aa) NA NA NA NA NA 73.1 75.8 82.3 92.5 92.2 94.7 95.7 - 98.7
H. sapiens (522 aa) NA NA NA NA NA 73.9 75.9 82.8 92.4 92.5 94.1 94.9 95.7 -
Notes: 1. Numbers in the upper-right half above the diagonal are identity percentages for amino acid sequences.
2. Numbers in the lower-left half below the diagonal are identity percentage for DNA sequences.
3. Numbers below the species names are the lengths of the Sin1 protein.
4. NA, Not applicable, i.e. no significant similarity was found.
5. Astericks, significant similarity occurs only in one region of the protein. For details, see the notes below:
S. pombe-C. elegans: significant similarity occurs in one region (170 aa: 252–391).
S. pombe- D. melanogaster : significant similarity occurs in one region (120 aa: 278–407).
S. pombe- A. gambiae: significant similarity occurs in one region (94 aa: 282–375).
N.crassa-C. elegans: significant similarity occurs in one region (90 aa: 376–465).
N.crassa-D. melanogaster: significant similarity occurs in one region (58 aa: 407–464).
N.crassa-A. gambiae: significant similarity occurs in one region (207 aa: 250–456).
N.crassa-Xenopus: significant similarity occurs in one region (127 aa: 338–464).
N.crassa-M. musculus: significant similarity occurs in one region (127 aa: 338–464).
C. elegans-D. melanogaster: significant similarity occurs in one region (169 aa: 198–366).
C. elegans-A. gambiae: significant similarity occurs in one region (178aa: 198–375).
6. Sequences and their GenBank accession numbers are: O. aries (AY547378), B. taurus (BF230134, AV603930, CB433957, BM480500), H. sapiens (NM_024117, BC002326), S. scrofa (CF791532, CF178115, BP459453, CF177341), M. muscus (BQ713136, BF781677, BU152256), R. norvegicus (CK476507, BE127132, BF553331, BU759329, AW141364), G. gallus (AF153127), X. laevis (BC043789), F. rubripes (Sequence accessible at ), D. melanogaster (AE003814), A. gambiae (XM_319576); S. pombe (AL136521, NP_594703, CAB66311); N. crassa (XP_322410).
Figure 1 Alignment of Sin1 proteins from the fission yeast and sheep. The GAP program was used to align the two sequences. Black shading shows identical residues. Abbreviations: S. pombe, Schizosaccharomyces pombe (fission yeast. GenBank accession No. AL136521). O. aries, Ovis aries (sheep. GenBank accession No. AY547378).
Figure 2 A phylogenetic tree for Sin1 primary sequences from various species. Sin1 polypeptide sequences were aligned by the program ClustalW, and the alignment output used by the program MEGA to generate a neighbor joining phylogenetic tree for the regions of alignment. GeneBank accession numbers for Sin1 sequences are listed in Table 1. Numbers beside branch points indicate the confidence levels for the relationship of the paired sequences as determined by bootstrap statistical analysis (1000 replicates). The lengths of the arms represent the extent of amino acid differences between the paired sequences, with the scale bar equivalent to 50 residues.
Sin1 from the yeast species, S. cerevisiae and S. pombe which consist of 1172 aa and 665 aa, respectively, and also from the red bread mold, N. crassa (798 aa) are much longer than Sin1 from vertebrate and insect species, which are ~520 aa long. The regions of similarity among these three fungal proteins are confined entirely to the carboxyl termini of these molecules, although several gaps have to be introduced to align them. No similarities are detectable in the amino terminal extensions, which, in the case of S. cerevisiae, is 370 aa long. It is the carboxyl regions of the fungal proteins that can also be aligned with the Sin1 sequences from C. elegans, insects, and vertebrate species, including Ovis aries, the sheep (Fig. 1).
A phylogenetic tree reconstructed from an alignment of amino acid sequences of Sin1 is shown in Fig. 2. As anticipated, the sequences from the three fungi, C. elegans, the two insect species, and vertebrate species fell into distinct branches of the tree. The sequences for the mammalian species were tightly clustered, with identities ranging from 99% (humans and cattle) to 91.3% (sheep and rat) (Table 2). All the vertebrate cDNA encoded polypeptides of 522 aa (Table 2).
There is considerable conservation of Sin1 from mammals to birds (~90%), amphibians (~85%), and fish (~80%) (Table 2). The insect sequences are rather longer than the ones from vertebrates, and several gaps have to be introduced to provide alignments (Fig. 3, 4, 5). Nevertheless, the insect amino acid sequences are approximately 33% identical to those of the mammals (Table 2). Five blocks of sequence (SCD I-V) are significantly more conserved than others when two insects, a fish, an amphibian, a bird and several mammals are compared (Figs. 3, 4, 5 &6). Three of these regions are located towards the N-terminus and two additional regions towards the C-terminus. The most diverse region is located centrally.
Figure 3 The alignment of Sin1 polypeptide sequences from insects and vertebrates. The ClustalW program was used to align all the protein sequences. Symbols (*, :, and .) show residues that are either identical(*), strongly similar (:), or weakly similar (.), respectively. Five Sin1 conserved domains (SCD) are highlighted as SCD I-V. The GenBank accession numbers for the sequences are: O. aries (AY547378), B. taurus (BF230134, AV603930, CB433957, BM480500), H. sapiens (NM_024117, BC002326), S. scrofa (CF791532, CF178115, BP459453, CF177341), M. musculus (BQ713136, BF781677, BU152256), R. norvegicus (CK476507, BE127132, BF553331, BU759329, AW141364), G. gallus (AF153127), X. laevis (BC043789), F. rubripes , D. melanogaster (AE003814), A. gambiae (XM_319576).
Figure 4 The alignment of Sin1 polypeptide sequences from insects and vertebrates. The ClustalW program was used to align all the protein sequences. Symbols (*, :, and .) show residues that are either identical(*), strongly similar (:), or weakly similar (.), respectively. Five Sin1 conserved domains (SCD) are highlighted as SCD I-V. The GenBank accession numbers for the sequences are: O. aries (AY547378), B. taurus (BF230134, AV603930, CB433957, BM480500), H. sapiens (NM_024117, BC002326), S. scrofa (CF791532, CF178115, BP459453, CF177341), M. musculus (BQ713136, BF781677, BU152256), R. norvegicus (CK476507, BE127132, BF553331, BU759329, AW141364), G. gallus (AF153127), X. laevis (BC043789), F. rubripes , D. melanogaster (AE003814), A. gambiae (XM_319576).
Figure 5 The alignment of Sin1 polypeptide sequences from insects and vertebrates. The ClustalW program was used to align all the protein sequences. Symbols (*, :, and .) show residues that are either identical(*), strongly similar (:), or weakly similar (.), respectively. Five Sin1 conserved domains (SCD) are highlighted as SCD I-V. The GenBank accession numbers for the sequences are: O. aries (AY547378), B. taurus (BF230134, AV603930, CB433957, BM480500), H. sapiens (NM_024117, BC002326), S. scrofa (CF791532, CF178115, BP459453, CF177341), M. musculus (BQ713136, BF781677, BU152256), R. norvegicus (CK476507, BE127132, BF553331, BU759329, AW141364), G. gallus (AF153127), X. laevis (BC043789), F. rubripes , D. melanogaster (AE003814), A. gambiae (XM_319576).
Figure 6 The five highly conserved domains of Sin1 proteins. Sin1 primary sequences from various species were aligned by using the ClustalW program, and the five most conserved domains identified from the alignment in Fig. 3 and the sequences listed in Table 1. Conserved domains are shown as boxes with remaining regions as solid lines. SCD, Sin1 conserved domain. Numbers beneath the species names are the lengths of the Sin1 proteins. Values in the boxes are the number of amino acid residues within a conserved domain. Numbers on the lines reflect the lengths of that region.
The region of the greatest identity between these divergent insect and vertebrate sequences is an acidic region placed in conserved SCD III (Fig. 3, 4, 5). In mammals, this region is completely conserved and corresponds to residues L232-K267 (LHIAEDDGEVDTDFPPLDSNEPIHKFGFSTLALVEK; Figs. 3, 4, 5; Fig. 7). However, an analysis of this sequence reveals no known functional motifs and no strong similarity to sequences represented in other known proteins. Schroder et al. [5] have also noted this conserved sequence in their analyses of Sin1 sequences and have named it CRIM for conserved region in the middle.
Figure 7 Alignment of Sin1 conserved domain III from various species. Sequences have been aligned by using the GCG PILEUP and GeneDoc programs. Degree of conservation is illustrated by intensity of shading (black, complete identity; light gray with black letters, complete identity across some but not all species; dark gray with white letters, high conservation but with conservative differences). The GenBank accession numbers for the sequences are: mm, M. musculus (BQ713136, BF781677, BU152256); rn, R. norvegicus (CK476507, BE127132, BF553331, BU759329, AW141364); bt, B. taurus (BF230134, AV603930, CB433957, BM480500); oa, O. aries (AY547378); ss, S. scrofa (CF791532, CF178115, BP459453, CF177341); hs, H. sapiens (NM_024117, BC002326); gg, G. gallus (AF153127); xl, X. laevis (BC043789); fr, F. rubripes); dm, D. melanogaster (AE003814); ag, A. gambiae (XM_319576); ce, Caenorhabditis elegans (NM_064195); sp, Schizosaccharomyces pombe (AL136521, NP_594703, CAB66311); nc, Neurospora crassa (XP_322410).
Sin1 from C. elegans retains the highly conserved 36 amino acid SCD I and the 127 amino acid Domain III (Fig. 6 &7). SCD III is also retained in the fission yeast and the red bread mold.
Vertebrates possess several unique sequences not present in insects and yeast, and, therefore, potentially implicated in the IFN signal transduction pathway including a carboxyl terminal region (KLSRRTSFSFQKDKK) immediately following the end of SCD V.
Functional motifs in the Sin1 primary sequence
When the ovine Sin1 sequence is scanned for functional motifs [13], the structure appears unusually barren. Two weak bipartite nuclear localization signals (NLS) [14] can be detected. One (residues 82–98, RRSNTAQRLERLRKERQ) is present in the SCDII domain, and the other (residues 503–519, RKLNRRTSFSFQKEKKS) is almost at the C-terminus within conserved domain V (Fig. 3). Nevertheless, data from the subcellular localization experiment showed that Sin1 is excluded from the nucleus when transfected in COS1 or L929 cells [4], suggesting these NLS are probably not functional.
There are numerous motifs that are recognized as potential but weak sites for phosphorylation by either casein kinase II (CK2), protein kinase C, or protein kinase A (data not shown). None of the 17 CK2 sites, the 12 protein kinase C, or the 5 protein kinase A sites present in the ovine Sin1 primary sequence are conserved from mammals to fission yeast, although many are retained across all vertebrates. A weak site for myristylation (ovine residues 170–175, GTTATK; Figs. 1 &3, 4, 5), and hence for membrane association, is retained in all the vertebrate species examined, but is absent in insects and yeast. In absence of any data on the functional significance of these sites, they will not be discussed further.
Gene structure of Sin1 from various species
The genomic sequence encompassing the transcribed region of the gene could be retrieved from the genome data bases for S. pombe, S. cerevisiae, C. elegans, D. melanogaster, A. gambiae, F. rubripes, R. norvegicus, M. Musculus, H. sapiens [15,16]. Sin1 exists as a single copy gene in all these species. For example, the human Sin1 gene is located on chromosome 9 (9q34.11-9q34.12) (data not shown) with the transcribed region composed of 11 exons and 10 introns and spanning a region of about 240 kb (Fig. 8). Exon 7 is spliced out of the shorter form of Sin1 [4,5]. The lack of exon 7 does not cause a frame shift because the intron phases of the two introns on both sides of exon 7 are identical (data not shown). Schroder et al. [5] have also demonstrated or predicted other minor splice variants for Sin1 in the human. The 11 exons account for only 0.9% of the gene sequence. It is, of course, unclear how many additional exons and introns are associated with the 5' UTR beyond the transcription start site(s), whose location has not been determined.
Figure 8 A comparison of the Sin1 gene structure across species. The gene structure for all species was retrieved from the genome database of the species by using the BLASTn program to analyze the open reading frame of each Sin1 cDNA sequence. Only the regions of the gene containing the open reading frame are shown in the diagram. All sequences begin with start codons and end with stop codons. The numbers under species names are the protein length.
Currently, the sheep and bovine genome sequences are not available, but it is likely that the Sin1 gene organization will be similar to that in the human. The current comparative synteny maps between human, sheep and cattle [17-19] predict that the Sin1 gene is located on sheep chromosome 3 (3p1.7-3p2.6) and bovine chromosome 11 (11q2.3-11q2.8), respectively.
A comparative map for all the genes is shown in Fig. 8. In fission yeast and insects, the Sin1 gene consists of a single exon. In worm, fish, rat, mice, and human, Sin1 has multiple exons. The exon/intron pattern, consisting of 11 exons, is observed in all vertebrates, including the two fish species (Fig. 8). It is noteworthy that although the genomic sequences of sheep and cattle are not available, the exon/intron pattern of their Sin1 genes is similar to that of other vertebrates based on the comparison between sheep or cattle Sin1 cDNA and human genomic sequence of Sin1 (data not shown). The lengths of these 11 exons are also remarkably conserved and fall within the normal range (50–200bp for most internal exons) (International Human Genome Sequencing Consortium, 2001). As expected, the sizes of the introns differ across species, and some are extremely long. Intron sizes generally decrease in the order human > mouse > rat > fish (Fig. 8). As expected, intron sizes were quite similar between rodents and human.
The Sin1 gene from C. elegans is organized quite differently from that in mammals. It consists of 10 exons interrupted by nine relatively short introns. The region of the C. elegans gene that contains regions of similarity with the mammalian protein sequences consists of exon 1 (SCD I) and exon 5 (SCD III). As noted above and in Figure 8, the Sin1 gene from insects and S. pombe is comprised of only a single exon.
Discussion
Sin1 is a little studied gene product of unclear function found in species ranging from mammals to fungi. Although the S. pombe gene product is longer than that of mammals, with an extension at its N-terminus, human Sin1 can rescue the stress sensitivity noted in the phenotype of a S. pombe strain that expressed a constitutively active form of RAS, indicating that function, as well as structure, has been conserved over hundreds of millions of years.
Two facts should be considered when attempting to infer a role for Sin1 in vertebrates. The first, as discussed in the Background, is the known ability of type 1 IFN to activate MAPK/SAPK in mammalian cells. The second is the proven involvement of Sin1 in the yeast SAPK (Sty1/Spc1) pathway and its involvement in controlling transcription of stress-activated genes [2]. The present analysis was conducted in an attempt to gain more detailed information about Sin1 function from a phylogenetic analysis and comparison of Sin1 genes and gene products in different taxonomic groups.
The Sin1 gene is remarkably divergent in both length and sequence identity within the fungi S. pombe, S. cerevisiae, and N. crassa, emphasizing the evolutionary distance between these three species. The regions of similarity are confined to the ~600 amino acid C-terminal regions of the three sequences (data not shown), and it is this region that is also conserved in insects and vertebrates (see Additional file: 1 &2). This diversity in structure within the fungi is probably reflected in divergence of function. AVO1, the apparent Sin1 ortholog of S. cerevisiae, forms a membrane-associated complex with TOR2 and other protein components (AVO2, AVO3 and LST8), which control cell growth in response to nutrients [3,32]. Cells with deletion of AVO1 are unable to organize their actin cytoskeleton [3]. In contrast, the Sin1 ortholog of S. pombe is involved in a stress response signaling pathway by interacting with Sty1 [2]. A cross-species comparison of all the Sin1 sequences available, indicates five regions of greatest conservation, only one of which, a ~127 amino acid central region (SCD III), was easily defined in all taxa (Figs. 3, 4, 5 &6). Even this region is poorly conserved in the budding yeast, S. cerevisiae, although certain landmark amino acids are retained (data not shown). Interestingly, Sin1 from insects and vertebrates, despite having only about 35% identity, are of similar length and possess the five regions of high identity. Conceivably, the SCD III domain is functionally essential in all the species, while SCDs I, II, IV, and V have evolved conserved function within the Metazoa. A not unreasonable assumption is that that Sin1 plays an evolutionarily conserved role in SAPK signaling across a broad range of taxa, including all metazoan and fungal species [5] but has assumed an additional function in vertebrates in mediating crosstalk with the IFN-signal transduction pathway.
In vertebrates Sin1 falls into a class of highly conserved gene products. Its conservation is lower than that of two structural proteins, histone H3 and β-actin, but is comparable to that of CDK1 (Table 3). However, while CDK1 in yeast and insects retains considerable sequence identity with the vertebrate orthologs, much of the conservation of Sin1 is lost. It is tempting to speculate that Sin1 has been subjected to powerful evolutionary constraint that has limited its amino acid sequence divergence within vertebrates. It should be noted that our analyses cannot exclude the possibility that conservation of Sin1 among vertebrates reflects recent divergence of the sampled vertebrates relative to the other taxa examined. Once data become available, it will be instructive to compare Sin1 gene sequences from the invertebrate chordates (Tunicata and Cephalochordata) with those of the other metazoan taxa.
Table 3 Comparison across species of the amino acid sequence conservation of Sin1 with some other conserved genes
Yeast Drosophila Frog Chicken Mouse Cattle Human
Histone H3 91.2% 98.5% 94.9% 95.6% 97.8% 98.5% 100%
β-actin 90.4% 97.9% 99.5% 100% 100% 98.1% 100%
CDK1 64.9% 71.7% 88.5% 93.3% 97.0% 98.7% 100%
Sin1 25.3% 31.9% 85.6% 90.0% 96.9% 99.0% 100%
Values for percentage identities were obtained by aligning amino acid sequences from various species with their human counterparts. CDK, cyclin-dependent kinase. The GenBank accession numbers for sequences are as follows. Human (Homo sapiens): histone H3 (AAH66884), β-actin (NP_001092), CDK1 (P06493), Sin1 (NM_024117, BC002326). Cattle (Bos taurus): histone H3 (P16105), β-actin (AAM98378), CDK1 (P48734), Sin1 (BF230134, AV603930, CB433957, BM480500). Mouse (Mus musculus): histone H3 (NP_062342), β-actin (NP_031419), CDK1 (NP_031685), Sin1 (BQ713136, BF781677, BU152256). Chicken (Gallus gallus): histone H3 (I50245), β-actin (NP_990849), CDK1 (P13863); Sin1 (AF153127). Frog (Xenopus laevis): histone H3 (P02302), β-actin (AAC27796), CDK1 (P35567, Sin1 (BC043789). Fly (Drosophila melanogaster): histone H3 (NP_724345), β-actin (NP_511052), CDK1 (NP_476797), Sin1 (AE003814). Yeast (Schizosaccharomyces pombe): histone H3 (NP_595567), β-actin (NP_595618), CDK1 (NP_595629), Sin1 (NP_014563).
Sin1 was shown to be associated with the cytoplasmic domain of IFNAR2, a subunit of the type I IFN receptor [4]. Since insects appear to lack genes for type I IFN and their receptors (R. M. Roberts, unpublished observations), whereas vertebrates utilize this system primarily as an anti-viral response [20-22], it should be theoretically possible to define a sequence in silico unique to vertebrates but clearly absent in both D. melanogaster and A. gambiae that might account for the association of Sin1 with IFNAR2. Sin1 binds to the carboxyl end of the cytoplasmic domain of IFNAR2 via its own carboxyl 114 amino acids [4]. At least two candidate sequences exist in that part of Sin1. One is the rather basic carboxyl terminus (aa 510–522), another a HDYKHLYFESDA (aa 458–469) sequence, both of which are absent in the insect proteins (Figs. 3, 4, 5). Whether these sequences are participants in the interaction of Sin1 with IFNAR2 in vertebrates has not been examined experimentally. Of course, it is quite possible that insect Sin1 can bind vertebrate IFNAR2 or that amino acid substitutions elsewhere in the carboxyl end of the vertebrate sequence have evolved to promote the interaction. These possibilities have also not been tested. In this regard, IFNAR2, with which Sin1 interacts, has evolved much more rapidly than Sin1 itself. The sequence of human IFNAR2, for example, shows only about 58% and 29% identity to those of ovine and chicken IFNAR2, respectively [21,23], while orthologs have yet to be defined for IFNAR2 in frogs and fish, even though these animals are believed to have a functional IFN system, which includes the production of Type I IFN and downstream components in response to double stranded RNA [20,22]. Interestingly, the only highly conserved continuous sequence of chick and mammalian IFNAR2 within the Sin1 binding region is an acidic region (aa 493–515; human IFNAR2 numbering) at the very carboxyl terminus of the molecule ([23]; R.M. Roberts, unpublished observations). It seems possible that this conserved sequence provides the scaffold for Sin1 binding.
As also observed by Schroder et al. [5], Sin1 is represented by a single gene in all species where it exists. In both insects and the two yeast species, the gene is intronless, while in C. elegans and in vertebrate species introns are present (Fig. 8). In budding yeast, only a small number (3.8%) of genes have introns [24], whereas in most other eukaryotes, including Drosophila, intronic sequences are a feature of the majority of genes and must be excised to produce a functional mRNA [25]. For D. melanogaster, for example, there is an average of 3 introns per gene [26]. These introns are short, averaging 240 bp in Drosophila [27]. Why the Sin1 genes are intronless in these species is unclear, but there is considerable evidence that retrotransposition occurs in yeast, Drosophila [28] and mammals [29]. In this process, reverse transcription of mRNA from a parental gene creates an intronless copy of the parental gene at a new position in the genome. If this mechanism created the Sin1 gene, a remnant or evolved version of the parental gene might be anticipated to exist, particularly if the transposition event occurred in recent evolutionary time [28]. It is unclear whether the intronless Sin1 gene in Drosophila resulted from such a retrotransposition event since there is not a detectable intronic copy elsewhere in the genome. The Sin1 gene from C. elegans has introns, but is organized very differently from that of vertebrates, where the intron/exon organization is highly conserved (Fig. 8).
Unfortunately, the function of Sin1 is unknown. Its structural conservation from vertebrates to yeast [30] and its expression in most, if not all tissues of mammals [4] suggest a central, if elusive, role in life processes.
Conclusions
SAPK-interacting protein 1 (Sin1), a little-studied but widely expressed gene product, is encoded by a single gene in fungi, nematodes, insects, and all vertebrates analyzed and shows modest conservation of amino acid sequence that is consistent with some degree of conserved function in stress-activated signal transduction pathways. Sin1 is highly conserved in vertebrates where it has been implicated in linking interferon responses to the SAPK pathway.
Methods
Databases
Sin1 genomic sequences from human, mouse, rat, fruit fly, mosquito, C. elegans, S. pombe, and S. cerevisiae, were retrieved from at NCBI Genome databases [18]. Sin1 cDNA sequences from human, mouse, rat, cattle and pig, and other Sin1 ESTs were retrieved from GenBank EST database after BLASTn analysis at NCBI [18]. For fish Sin1 genomic sequences, the incomplete puffer fish (Fugu rubripes) and zebrafish (Danio rerio) genome databases at the Ensembl site [16] were used. The budding yeast (Saccharomyces cerevisiae) ORF (open reading frame) database [33] was used to retrieve budding yeast Sin1.
Software programs used to analyze sequences
Pairwise global sequence alignment was performed by using either the BESTFIT or the GAP program from GCG (Madison, WI). Multiple global sequence alignment was performed by using either the PILEUP program (GCG, Madison, WI) and GeneDoc [34] or ClustalW program [35]. The phylogenetic tree for Sin1 was generated by using the ClustalW program and the MEGA program [36]. Motif search was performed by using the ScanProsite program [13].
Methods for obtaining Sin1 sequences from various species
Fission yeast (Schizosaccharomyces pombe) and chicken (Gallus gallus): The two Sin1 sequences were published by Wilkinson et al. [2].
Budding yeast (Saccharomyces cerevisiae): The BLASTp program was used to search the budding yeast ORF database for any protein sequence that had significant similarity to the fission yeast Sin1 protein. The obtained budding yeast Sin1 protein sequence had a GenBank link where its cDNA was available. The cDNA sequence was used to analyze its genomic structure at the NCBI yeast genome site.
Red bread mold (Neurospora crassa): Sin1 protein was retrieved from the Neurospora crossa protein data base by searching (BLASTp) with the budding yeast Sin1 protein.
Worm (Caenorhabditis elegans): The Sin1 protein sequence was obtained from the C. elegans protein database by searching with ovine Sin1 protein. The cDNA sequence was then obtained from the GenBank link and used to determine the structure of the Sin1 gene.
Fly (Drosophila melanogaster): The fruit fly Sin1 protein sequence was retrieved from the D. melanogaster protein database as above. The cDNA sequence was obtained from the GenBank link. Unexpectedly, querying the Drosophila genomic sequence with the C. elegans Sin1 sequence and vice-versa failed to yield a match in either case.
Mosquito (Anopheles gambiae): The mosquito Sin1 protein sequence was retrieved from the Anopheles gambiae str. PEST protein database as above. The cDNA sequence was then obtained from the GenBank link.
Puffer fish (Fugu rubripes) and Zebrafish (Danio rerio): Both Fugu rubripes and Danio rerio genome databases, which are accessible at two websites, NCBI and ENSEMBL, were queried with Sin1 cDNA sequences from sheep, chicken, and frog. For both species, only the Ensembl site provided the complete genomic sequence. Although the Fugu rubripes genome sequence is incomplete, the exons of Sin1 cDNA can be retrieved and successfully assembled into the full length structure by alignment with other Sin1 cDNA and gene sequences. No GenBank entry was available for the Fugu rubripes Sin1 gene. When a similar method was used to retrieve the Zebrafish Sin1 cDNA sequence, the full length sequence could not be obtained because the region (~20 kb) covering one exon (exon 4) was incomplete. Therefore, the fish Sin1 protein sequence used here is from Fugu rubripes.
Frog (Xenopus lavis): The full-length cDNA sequence of Sin1 reported here was from African clawed frog, and was obtained by blasting the Xenopus EST database [37] with the chicken Sin1 sequence. The protein sequence was deduced from this cDNA sequence.
Mouse (Mus musculus): The mouse Sin1 cDNA sequence was obtained by editing several ESTs, after performing a BLASTn search of the Mus Musculus EST database with the ovine Sin1 cDNA sequence. Searching the mouse genome database with the mouse Sin1 cDNA coding region then allowed the gene, down stream of its transcription start site to be located and its structure to be inferred.
Rat (Rattus norvegicus): The rat Sin1 cDNA sequence was retrieved from several overlapping ESTs, which were obtained by searching the Rattus norvegicus EST database with the ovine Sin1 cDNA sequence. The coding region of the rat Sin1 cDNA was then used to search the rat genome database at the NCBI website for the genomic structure of the gene.
Cattle (Bos taurus): The full length bovine Sin1 cDNA sequence was obtained from overlapping ESTs, which were obtained by searching the NCBI EST database with the ovine Sin1 cDNA sequence.
Pig (Sus scrofa): The swine Sin1 cDNA sequence was obtained as above by searching the NCBI EST database with the ovine Sin1 cDNA sequence.
Human (Homo sapiens): The sequence published by Colicelli et al. [31] was confirmed by performing a BLASTn search on human EST data bases with the ovine Sin1 cDNA sequence. Since the previously published sequence was not full-length, an additional human Sin1 EST (GenBank Acc. No. BC002326) was used to assembly the full length Sin1 cDNA sequence. The location of the gene and its structure downstream of its transcription start site were determined by searching the full human genome database with the Sin1 open reading frame.
Sheep (Ovis aries): The sheep Sin1 cDNA sequence was cloned from a sheep endometrial cDNA library in a yeast two-hybrid screen [4]. GenBank accession numbers are summarized in Table 1.
Authors' contributions
SW carried out the majority of the computational analyses under the direction of RMR, and wrote the first draft of the manuscript. RMR conceived of the study and participated in its design and coordination. All authors read and approved the final manuscript.
Supplementary Material
Additional file 1
Alignment of Sin1 proteins from the fission yeast and the budding yeast. The Bestfit program was used to align the two sequences. Black shading shows identical residues. A conserved region (SCD III; see Fig. 4) is highlighted by a line above the sequence, and appears not so well conserved in the budding yeast as in other species. Abbreviations: S. pombe, Schizosaccharomyces pombe (fission yeast. GenBank accession No. AL136521). S. cerevisae, Saccharomyces cerevisae (budding yeast. GenBank accession No. NP_014563).
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Additional file 2
Alignment of Sin1 proteins from the fission yeast and the red bread mold. The Bestfit program was used to align the two sequences. Black shading shows identical residues. Abbreviations: S. pombe, Schizosaccharomyces pombe (fission yeast. GenBank accession No. AL136521). N. crassa, Neurospora crassa (red bread mold. GenBank accession No. XP_322410).
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Acknowledgements
We thank Jim Bixby for facilitating computing and software use, and Drs. Mark Hannink and John Cannon for helpful discussion. This research was supported by NIH Grant HD 21896.
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| 15698473 | PMC549548 | CC BY | 2021-01-04 16:37:16 | no | BMC Evol Biol. 2005 Feb 7; 5:13 | utf-8 | BMC Evol Biol | 2,005 | 10.1186/1471-2148-5-13 | oa_comm |
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BMC NeurosciBMC Neuroscience1471-2202BioMed Central London 1471-2202-6-101570749910.1186/1471-2202-6-10Research ArticleThe responses of Ht22 cells to oxidative stress induced by buthionine sulfoximine (BSO) Chen Jun [email protected] Andrea [email protected] Amy [email protected] Marla J [email protected] Department of Cell & Molecular Biology, John A Burns School of Medicine, University of Hawaii, 1960 East West Rd, Honolulu, HI 96822 USA2005 12 2 2005 6 10 10 16 11 2004 12 2 2005 Copyright © 2005 Chen 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
glutathione (GSH) is the most abundant thiol antioxidant in mammalian cells. It directly reacts with reactive oxygen species (ROS), functions as a cofactor of antioxidant enzymes, and maintains thiol redox potential in cells. GSH depletion has been implicated in the pathogenesis of neurological diseases, particularly to Parkinson's disease (PD). The purpose of this study was to investigate the change of cellular antioxidant status and basic cell functions in the relatively early stages of GSH depletion.
Results
in this study, GSH was depleted by inhibition of glutamylcysteine synthetase using buthionine sulfoximine (BSO) treatment in Ht22, a neuronal cell line derived from mouse hippocampus. Treatment with BSO produced dose-dependent decreases in total GSH level, Fe3+-reducing ability (FRAP assay), Cu2+-reducing ability (Antioxidant Potential, AOP assay), and ABTS free radical scavenging ability (ABTS assay) of the cells, but the sensitivity of these indicators to dosage varied considerably. Most of the changes were completed during the first 8 hours of treatment. Cell viability was tested by MTT (3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyl tetrazolium bromid) assay, and cells at lower density in culture were found to be more sensitive to GSH depletion. The activity of antioxidant enzymes, such as glutathione peroxidase (GPx), glutathione reductase (GR), and copper/zinc superoxide dismutase (Cu/Zn-SOD) were affected by GSH depletion. A cDNA expression array assay of the effects of BSO treatment showed significantly decreased mRNA level for 3 genes, and significantly increased mRNA level for 10 genes, including the antioxidant enzymes Cu/Zn-SOD and thioredoxin peroxidase 2 (TPxII).
Conclusions
the study suggests that there are BSO-sensitive and BSO-resistant pools of GSH in Ht22 cells, and that different categories of antioxidant react differently to GSH depletion. Further, the effect of GSH status on cell viability is cell density dependent. Finally, the alterations in expression or activity of several antioxidant enzymes provide insight into the various cellular responses to GSH depletion.
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Background
Glutathione (GSH, tripeptide γ-L-glutamyl-L-cysteinyl-glycine) is the most abundant thiol antioxidant in mammalian cells. It reacts directly with reactive oxygen species (ROS), or functions as a cofactor of antioxidant enzymes such as the glutathione peroxidases (GPxs). In addition, GSH keeps sulfhydryl groups of cytosolic proteins in reduced form by maintaining thiol redox potential in cells [1], and regulates cell signaling pathway in apoptosis [2,3]. The requirement for GSH and total antioxidant capacity is particularly high in brain.
Brain consumes 20% of total oxygen in the body, and thus undergoes high levels of oxidative challenge. Cumulative oxidative damage has been strongly implicated in neurodegeneration and neurological diseases, such as Parkinson's disease (PD), Alzheimer's disease (AD), and amyotrophic lateral sclerosis (ALS). The importance of GSH in particular has been indicated in the case of PD. Among the progressive oxidative stresses that occur in the pathogenesis of PD, an characteristic is the decrease in total GSH concentrations in the substantia nigra in preclinical stages, when other biochemical changes are still undetectable [4].
Investigation of the consequences of intracellular GSH depletion in neuronal cell lines has relied predominantly on one of three methods. These are: (a) treatment with homocysteic acid (HCA) or glutamate to block the uptake of cystine, a substrate for GSH synthesis [5-7]; (b) treatment with BSO [5] to inactivate γ-glutamylcysteine synthetase, the rate limiting enzyme in GSH synthesis, and (c) treatment with ethacrynic acid [8] or diethyl maleate [9] to react with the thiol group of GSH. The oxidative stress caused by GSH depletion further affects the status of other antioxidants. The concept of total antioxidant capacity (TAC) has been developed to assess the general antioxidant activity in biological samples without distinguishing the contribution from each individual component. Measurements of TAC have been intensively developed in the past 20 years. The principle of these methods is to evaluate the total effect of all contributing compounds in the system by one criterion, such as free radical scavenging, electron donation or protection against the oxidative damage to lipids, proteins or DNA. But considering the fact that different categories of antioxidant work through different mechanisms and need specified conditions for maximal function, it is impossible to cover the activities of all antioxidants in one assay. Thus multi-dimensional measurements on TAC have been suggested [10].
In this study, GSH was depleted by BSO in Ht22, a neuronal cell line derived from mouse hippocampus. GSH level, TAC, antioxidant enzyme activity, cell viability and gene expression were assessed.
Results and discussion
Intracellular total GSH level vs. cell density in culture
Before depleting GSH from cells, total GSH levels in Ht22 were monitored from pre-log phase to the end of log phase of cell growth (Figures 1 &2). Intracellular GSH levels decreased as cell density increased, with this effect being more dramatic as the cells entered log phase growth.
Whether the decrease of GSH with cell growth is due to limited nutrient supply or to programmed regulation is not known. It has been reported that the GSH content of brain cells depends strongly on the availability of precursors for GSH [11]. It was also noticed that as Ht22 cells grow denser in culture, the intracellular ROS level decreased (Chen et al., unpublished data), as apparently balances with the decreased GSH concentration.
Dose responses
Intracellular GSH
The dose responses of Ht22 to BSO were analyzed by varying BSO concentration from 0.03 to 10 mM in a 15-hr treatment, and the changes of intracellular GSH level and TAC were measured (Figure 3). Treatment with 0.03 mM BSO resulted in a dramatic decrease of total GSH level to 35% of the control level. Increasing the BSO concentration to 10 mM further decreased the GSH level to 22% of control, representing an additional drop of only 13%. In comparison to 0.03 mM of BSO, increasing the concentration to 1 mM or higher caused significant decreases in GSH levels (P values ≤ 0.0399). This result suggests there are two pools of GSH in the cell, one easily depleted by BSO, and the other more resistant to depletion. A previous study by Seyfried et al. [12] showed that BSO treatment of PC12 cells was more efficient at depleting cytosolic GSH than mitochondrial GSH, indicating that the BSO-sensitive and BSO-resistant GSH pools in Ht22 might localize to cytosol and mitochondria, respectively.
After 10 mM BSO treatment for 15 hrs, the predominant form of glutathione was the reduced form (GSH); only about 5% of the total glutathione was found in the oxidized form (GSSG). After 15 hrs BSO treatment, malondialdehyde (MDA) assay showed the increases of Abs at 586 nm caused by MDA formation were: control = 0.011 ± 0.006; 1 mM BSO = 0.012 ± 0.006; 3 mM BSO = 0.009 ± 0.004; and 10 mM BSO = 0.011 ± 0.004 (average ± SD, 3–5 independent experiments), no increase in lipid peroxidation after the treatments was observed, indicating GSH depletion at these levels was not yet destructive to the cells.
Total antioxidant capacity
Three methods were employed in this study to investigate antioxidant status following BSO treatment of Ht22 cells. The Cu2+-reducing ability assay (Antioxidant Potential, AOP) and Fe3+-reducing ability assay (FRAP) both measure the activity of metal ion-reducing antioxidants, but the FRAP assay is characterized by its low pH (3.7), thus excluding the antioxidant function of thiols. Figure 3 shows that from 0.03 to 10 mM BSO treatment, the FRAP value had a sharp decrease from 76 to 32% of the control, indicating that some non-thiol antioxidants were expended to preserve the BSO-resistant GSH or to cope with oxidative stress caused by the depletion of BSO-sensitive GSH. In comparison to FRAP, the AOP value showed a gradual decrease from 76 to 50 % of control through the range of BSO concentrations, and this lesser decrease may be partially maintained by the BSO-resistant GSH pool in the cells.
In contrast to FRAP and AOP, the ABTS free radical scavenging ability (ABTS assay) of the cells maintained at about 80% of the control level at all BSO concentrations. Cao et al. [13] previously showed that GSH is highly reactive to ABTS radical. Unlike the FRAP and AOP assays, the ABTS assay appears to be less sensitive to the metal ion-reducing antioxidants that were consumed by GSH depletion.
Cell viabilities and bioreduction activity
Cell viabilities
Effects of GSH depletion on cell viability were assayed using the MTT (3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyl tetrazolium bromid)-based cell viability assay, an indicator of mitochondrial activity (Figure 4). Ht22 cells at higher density (1e5 cells per well, equal to 1.3e5 cells per square cm) were more resistant to GSH depletion, and in spite of the change in BSO concentration, the decrease in cell viability remained at about 10% of control. Lower cell density (5e4 cells per well, equal to 6.5e4 cells per square cm) rendered higher sensitivity; as BSO concentration increased from 0.03 to 10 mM, the viability dropped from 100 to 50% of control. At 3 and 10 mM BSO concentrations, the differences caused by cell density are significant (P values ≤ 0.0027). These results show that the mitochondrial activity of cells is influenced by GSH depletion, and that this effect is sensitive to the density of cells in culture. The reason(s) behind the cell density factor is not clear. Either proliferation status or communication between cells may contribute. In neurodegenerative diseases, the effect of cell death, thus the decrease of cell density, on the susceptibility of neurons to GSH depletion will be worth investigating. Wither sever cell death can accelerate GSH loss is not known.
No changes in cell viability in response to BSO treatment were detected by trypan blue staining, which distinguishes dead cells from live ones. Cell viabilities were 98.9% (N = 25) for untreated cells, and 99.6% (N = 5), 99.1% (N = 5), and 98.1% (N = 12), after 15 hrs treatment with 1, 5, and 10 mM BSO, respectively. The oxidative stress produced in these treatments is not sufficient to be lethal to the cells, in accordance with the MDA assay, which shows no increase in lipid peroxidation.
Bioreduction activity
Figure 5 shows a slight tendency of increase in the bioreduction activity in cells after BSO treatment, as is more evident when cells were at lower density. The effective resazurin-reducing compound(s) in Ht22 is not clear, but the possible background from BSO was excluded. The mechanism behind the change is yet to be understood.
Time course
The responses of Ht22 cells to 0.1 mM BSO treatment were tested at 4, 8, 12 and 15 hrs, and results are expressed as percentage of 0 hr (Figure 6). For total GSH, FRAP and ABTS, 4-hr treatment induced significant decreases (P values ≤ 0.0001), while AOP value did not change significantly. From 4 hrs to 8 hrs, all of the assays showed significant decreases (P values ≤ 0.0326). Whereas from 8 through 15 hrs, no significant change was seen. The data suggests that for 0.1 mM BSO treatment, the majority of the GSH depletion occurred in the first 8 hrs, and that the depletion of other antioxidants were dynamically parallel to GSH depletion. Cell death was visible under microscopy after 20 hrs of 0.1 or 10 mM BSO treatments.
Seyfried et al. [12] found that PC12 cells treated with 0.5 mM BSO maintained 100 % of mitochondrial GSH in the first 4 hrs, while cytosolic GSH was completely depleted. Extending the treatment from 4 hrs to 6 hrs resulted in 50 % depletion of mitochondrial GSH. These data are in agreement with the significant decreases of total GSH level from 0 to 4 hrs, and from 4 hrs to 8 hrs in this study, although the differences in cell line and dosage of BSO in the two studies should be kept in mind while comparing the results.
Antioxidant enzyme activities
Glutathione peroxidase
Glutathione peroxidases (GPxs) are selenium-containing antioxidant enzymes that reduce hydrogen peroxide to water, or lipid peroxides to ethanols, with GSH as reducing cofactor. Five isoforms of the GPx family are commonly known. In this study, the major activity detected by the assay is cellular GPx (GPx1). Figure 7 shows the change of GPx activity in response to 1, 3 and 10 mM BSO treatments for 15 hrs. Treatment with 1 mM BSO significantly increased the GPx activity to 127% of control (P = 0.0401). Treatment with 3 or 10 mM BSO decreased the activity by about 20% of control. This treatment was not significant compared to control, but is significant when compared to 1 mM BSO treatment (P values ≤ 0.0421). The results show that the regulation of GPx activity is dependent on the level of GSH depletion, and that the reserve pool of GSH may have critical function, since slight depletion caused significant changes.
Glutathione reductase
Glutathione reductase (GR) reduces GSSG to GSH using NADPH as cofactor. When Ht22 cells were subjected to 1, 3 and 10 mM BSO treatment for 15 hrs, the GR activity in the cells dropped to 97%, 95% and 94% of control, respectively (Figure 8). At 10 mM BSO concentration, the decrease is significant (P = 0.045) in comparison to the control level. However, the toxicology cDNA expression array study in Section 5 did not show significant changes in the mRNA level of GR. The activity decrease of this enzyme may be due to enzyme inactivation caused by oxidative stress.
Superoxide dismutase
Superoxide dismutase (SOD) converts superoxide anion to hydrogen peroxide, which can be further detoxified by GPx1 or catalase. Two isoforms of SOD are found in mammalian cells, known as Cu/Zn-SOD and Mn-SOD, and localized in cytosol and mitochondria, respectively. Incubating Ht22 cells with 1, 3, and 10 mM BSO for 15 hrs increased the Cu/Zn-SOD activity to 104%, 112%, and 152% (P= 0.0619) of the control level (Figure 9). The toxicology cDNA expression array study found a 2-fold increase of Cu/Zn-SOD mRNA level in response to treatment with 10 mM BSO treatment. In contrast to GPx, SOD responds more to severe GSH depletion or higher level of oxidative stress.
Toxicology cDNA expression array
cDNA expression arrays are powerful tools for studying gene expression under various circumstances. In this study, we employed the Atlas rat toxicology array II (BD) to monitor the changes in gene expression after 15 hrs treatment with 10 mM BSO. Out of a total of 465 genes in the array, mRNA level of 3 genes were significantly decreased, and 10 significantly increased (Table 1). The increased mRNA level of heat shock protein (HSP, the induction of which correlates with the abundance of unfolded polypeptide chains) and eukaryotic peptide chain release factor 1 (ERF1, which functions in termination of translation) indicate the stress caused by BSO treatment affected proteins at translational and structural levels. The increased mRNA level of antioxidant enzymes Cu/Zn-SOD and thioredoxin peroxidase 2 (TPx II, a peroxidase that requires thioredoxin or thiol-containing intermediates to carry out its peroxidase function) suggests these enzymes have important functions in coping with the oxidative stress caused by GSH depletion. Furthermore, both of these enzymes have been shown to protect cells from different inducers of apoptosis [14,15], indicating that they may have contributed to maintaining high cell viability after BSO treatment in this study.
Conclusions
Inhibition of glutamylcysteine synthetase in Ht22 cells by BSO revealed two pools of GSH in the cells, one susceptible to depletion by low concentration of BSO, and the other more resistant to depletion. TAC values measured by FRAP, AOP and ABTS methods showed parallel time courses to GSH depletion, but different dose-responses. The GSH depletion studied did not result in increases in GSH/GSSG ratio, lipid peroxidation, or cell death, but affected MTT-based cell viability. The antioxidant enzyme activities of GPx, GR and Cu/Zn-SOD were affected by the GSH depletion. The mRNA levels of HSP90-beta, ERF1, Cu/Zn-SOD and TPx II were significantly increased after 10 mM BSO-15 hr treatment.
Methods
Cell maintenance and treatment
Ht22 cells were fed with Dulbecco's Modified Eagle Medium (DMEM) with 10% fetal bovine serum (FBS) supplement, and cultured at 50–55% relative humidity (RH), in 5% CO2 at 37°C. For MTT-based cell viability assay and Resazurin-based bioreduction activity assay, cells were seeded at a density of 1 or 0.5 million cells per well (corresponding to 1.3e5 and 6.5e4 cells per square cm, respectively) in 48-well cell culture plates (Costar) 12 hrs before BSO treatment. For other assays, the cells were allowed to reach 80–90% of optical confluency (about 2e5 cells per square cm) in 100 mm cell culture dishes (Costar) before the BSO treatment.
TAC, GSH/GSSG, MDA assays
In this study, three methods were employed for total antioxidant capacity assay. The AOP assay (Antioxidant Potential assay kit, Oxis) tests the ability of samples to reduce Cu2+ to Cu+ at physiological pH, (assayed according to manufacturer's instructions with minor adjustments). The FRAP assay [16] tests the ability of samples to reduce Fe3+ to Fe2+ at pH 3.6, a low pH that inactivates thiol antioxidants. The ABTS assay [17] tests the ability of samples to scavenge ABTS radical at physiological pH. Modified versions [18] of FRAP and ABTS assays were used in this study. GSH was assayed for total level as well as GSH/GSSG ratio using GSH/GSSG ratio assay kit (Oxis). Manufacturer's instructions were followed with minor adjustments. Lipid peroxidation in cells was assayed using malondialdehyde (MDA), a product of lipid peroxide decomposition, as an indicator. The assay was carried out using a Malondialdehyde assay kit (Oxis).
Cell viabilities and bioreduction activity assays
A common method of testing cell viability is trypan blue staining. As a vital dye, trypan blue enters dead cells, distinguishing them from live ones. In this study, 0.4% (w/v) trypan blue-PBS solution was mixed with properly diluted cells at 5:1 ratio, and cell numbers were counted using a hemocytometer. Cell viability can also be reflected by dehydrogenase activity, which indicates the activity of mitochondria (Cell growth determination kit/MTT based, Sigma). Dehydrogenase converts MTT into purple MTT formazan, causing a colorimetric change that can be monitored photometrically. The bioreduction activity of cells was monitored by an in vitro toxicology assay kit (Sigma), based on a blue to red color change when the oxidoreduction dye, resazurin, is reduced by the bioreduction activity of the cells. Both MTT and Resazurin assays were carried out following the kit instructions.
GPx, GR, and SOD activity assays
GPx activity assay was based on the classical principle [19] with optimization to the Ht22 cell lysis. The peroxide used in this study was t-butyl hydroperoxide (0.323 mM), the concentration of GSH was reduced to 1.875 mM, and the pH of the assay was increased to 7.6. The GR and SOD activities were assayed by corresponding kits from Oxis.
Toxicology cDNA array assay
Atlas rat toxicology array II was purchased from BD, and the assay was carried out following the instruction manual.
Statistical work
F-test in SAS procedure "Proc GLM" was used for statistical work.
Authors' contributions
JC designed experiments, treated and harvested samples, optimized and participated in the antioxidant assays, participated in the toxicology cDNA array assay. ASH participated in the toxicology cDNA array assay. AY participated in harvesting samples, and the antioxidant assays. MJB contributed to conception and design, critical revision and final approval of the article.
Acknowledgements
We thank Dr. Helen Turner in the Laboratory of Cell Biology and Immunology in Queen's Center for Biomedical Research (Honolulu, Hawaii) for providing technical support on the toxicology cDNA array study. We Thank Feng Chen in the Department of Statistics and Operations Research in the University of North Carolina at Chapel Hill for assistance on statistical work. We thank Denise Merz in our lab for participating in GSH assay.
Figures and Tables
Figure 1 Growth curve of Ht22 cells. Cell number counted by hemocytometer, three counts for each point.
Figure 2 Total intracellular GSH concentration in Ht22 cells. The GSH levels decrease with increasing cell density in culture.
Figure 3 Dose response of Ht22 cells to BSO treatment. The effects of 15-hour BSO treatment on GSH level and total antioxidant capacity in Ht22 cells were measured. Average value and SD are shown, N = 3. In comparison to 0.03 mM of BSO, increasing the concentration to 1 mM or higher caused significant decreases in GSH levels (P values ≤ 0.0399).
Figure 4 MTT assay for the viability of Ht22 cells treated with BSO for 15 hours. Average value and SD are shown (1e5 cells/ well, N = 9; 5e4 cells/ well, N = 5). At 3 and 10 mM BSO concentrations, the differences caused by cell density are significant (P values ≤ 0.0027).
Figure 5 Resazurin based bioreduction assay of Ht22 cells treated with BSO for 15 hours. Average value and SD are shown (1e5 cells/ well, N = 6; 5e4 cells/ well, N = 5). For 1e5 cells/well, treatment of 0.03 mM BSO caused significant increase in the bioreduction activity vs control (P = 0.0053); for 5e4 cells/well, the increases caused by treatments of 0.1 and 3 mM BSO were significant vs control (P ≤ 0.0175).
Figure 6 Time course of the responses of Ht22 cells to BSO treatment. The effects of total GSH level and total antioxidant capacities of Ht22 cells treated with 0.1 mM BSO for 4, 8, 12, and 15 hours were measured. Average value and SD are shown, N = 3. For total GSH, FRAP and ABTS, 4-hr treatment induced significant decreases vs control (P values ≤ 0.0001); from 4 hrs to 8 hrs, all of the assays showed significant decreases (P values ≤ 0.0326).
Figure 7 GPx activity of Ht22 cells treated with BSO for 15 hours. Average value and SD are shown, N = 3. Treatment with 1 mM BSO significantly increased the GPx activity vs control (P = 0.0401); and the decreases caused by 3 or 10 mM BSO are significant vs 1 mM BSO treatment (P values ≤ 0.0421).
Figure 8 GR activity of Ht22 cells treated with BSO for 15 hours. Average value and SD are shown, N = 3. At 10 mM BSO concentration, the decrease is significant (P = 0.045) vs control.
Figure 9 Cu/Zn-SOD activity of Ht22 cells treated with BSO for 15 hours. Average value and SD are shown, N = 3. Treatment of 10 mM BSO caused a trend of increase in SOD activity vs control (P = 0.0619).
Table 1 Genes with significantly changed mRNA levels after BSO treatment. The results were detected by Atlas rat toxicology array II in Ht22 cells treated with 10 mM BSO for 15 hours.
Protein/gene Normalized Intensity of control Normalized Intensity of BSO sample Ratio
mRNA increased
heat shock cognate 71-kDa protein (HSC73; HSC70) Y00054 1773 4780 2.70
eukaryotic peptide chain release factor subunit 1 (ERF1); TB3-1; C11 protein [rat homolog of human] M75715 (human) 208 519 2.50
thioredoxin peroxidase 2 (TDPX2); thioredoxin-dependent peroxide reductase 2; heme-binding 23-kDa protein (HBP23) D30035 1710 3989 2.33
78-kDa glucose-regulated protein precursor (GRP78); immunoglobulin heavy chain binding protein (BIP); steroidogenesis-activator polypeptide; HSPA5 M14050 66 154 2.33
60S ribosomal protein L6 (RPL6) X87107 1932 4353 2.25
copper-zinc-containing superoxide dismutase 1 (Cu-Zn SOD1) Y00404 1285 2813 2.19
proliferating cell nuclear antigen (PCNA); cyclin Y00047 1463 3210 2.19
thymosin beta-10 (TMSB10; THYB10); PTMB10 M17698 3545 7637 2.15
high mobility group protein 2 (HMG2) D84418 957 1976 2.06
heat shock 90-kDa protein beta (HSP90-beta); HSP84; HSPCB S45392 7737 15881 2.05
mRNA decreased
DNA topoisomerase IIB (TOP2B) D14046 4146 1502 0.36
osteopontin M14656 3630 1535 0.42
contrapsin-like protease inhibitor related protein; SPI-3 serine protease inhibitor D00753 13996 5961 0.43
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| 15707499 | PMC549549 | CC BY | 2021-01-04 16:03:48 | no | BMC Neurosci. 2005 Feb 12; 6:10 | utf-8 | BMC Neurosci | 2,005 | 10.1186/1471-2202-6-10 | oa_comm |
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BMC Evol BiolBMC Evolutionary Biology1471-2148BioMed Central London 1471-2148-5-101569137810.1186/1471-2148-5-10Research ArticleStructural similarity of loops in protein families: toward the understanding of protein evolution Panchenko Anna R [email protected] Thomas [email protected] Computational Biology Branch, National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD 20894, USA2005 3 2 2005 5 10 10 6 10 2004 3 2 2005 Copyright © 2005 Panchenko and Madej; licensee BioMed Central Ltd.2005Panchenko and Madej; 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
Protein evolution and protein classification are usually inferred by comparing protein cores in their conserved aligned parts. Structurally aligned protein regions are separated by less conserved loop regions, where sequence and structure locally deviate from each other and do not superimpose well.
Results
Our results indicate that even longer protein loops can not be viewed as "random coils" and for the majority of protein families in our test set there exists a linear correlation between the measures of sequence similarity and loop structural similarity. Results suggest that distance matrices derived from the loop (dis)similarity measure may produce in some cases more reliable cluster trees compared to the distance matrices based on the conventional measures of sequence and structural (dis)similarity.
Conclusions
We show that by considering "dissimilar" loop regions rather than only conserved core regions it is possible to improve our understanding of protein evolution.
==== Body
Background
Globular proteins are considered to be structurally similar if their regular secondary structure elements can be superimposed well and are connected in the same order. The loop regions connecting secondary structures demonstrate less regularity in their conformations even though short loops linking specific secondary structures can be classified into distinct classes [1-6]. The structures and sequences in loop regions may deviate from each other so that they do not superimpose well and as a result loops are very often not aligned by structure-structure or sequence alignment methods. Loops apparently do not contribute much to protein stability but may be quite important for protein specific function and for the interaction with other components of the cell. In our previous work we showed that a measure derived from the loop regions can distinguish homologous from analogous proteins with the same or higher accuracy compared to the conventional measures which are based on comparing proteins in structurally aligned regions only [7].
Recently it has been observed that structural variation in the core of homologous proteins is linearly correlated with sequence changes [8,9]. As was also shown several years ago, the probability of insertion and deletion events, which occur predominantly in the loop regions, strongly depends on the evolutionary distance between two homologous proteins [10,11]. Based on these observations one might argue that more closely related proteins may exhibit more similarity in the structure of their loop regions compared to distantly related proteins and the structural loop (dis)similarity should correlate with evolutionary distance.
To check this hypothesis we performed an analysis of structural variation in the loop regions within different homologous protein families using a recently introduced new measure of loop similarity [7]. This new measure is based on the concept of the Hausdorff metric, which is used in mathematical topology to define a distance between two point sets of a metric space. It does not require an alignment or one to one correspondence between two point sets. We show that there exists a linear correlation between the average structural change in the loop regions and the evolutionary distance, which allows us to use the loop (dis)similarity measure for inferring the phylogenetic history of homologous protein families.
Methods
Test set
To select sets of homologous proteins the Conserved Domain Database (CDD) version 1.62 was taken, which can be accessed at [12]. The CDD collection of protein domain alignments included curated CDDs [13] and preprocessed domain families imported from SMART and PFAM, altogether 6222 protein domain families[14]. Upon import, the sequences from SMART/PFAM alignments with more than 75% identity with known structures were substituted by the most similar structures from the Protein Data Bank [15].
Each CDD family was decomposed into a set of pairwise structure-structure alignments. Structural alignments were computed by the VAST algorithm [16] and only those structures which had more than 80% mutual overlap between the VAST alignment footprint and CDD footprint were considered in the analysis. The footprint for a given sequence was defined as a region between the first and the last residues aligned by VAST or CDD. Those families containing short sequence repeats and having average alignment length less than 50 residues were excluded from the test set. The structural pairs within the remaining CDD families were disregarded if at least one of the following conditions held true:
- at least one structure in a pair had X-ray resolution of greater than 3.0 Å
- the Blast E-value calculated for the VAST alignment exceeded 0.01
- at least one structure in a pair contained a chain discontinuous domain inconsistently aligned between VAST and CDD
- at least one structure in a pair contained more than 25% of its nonaligned loops with missing residues.
To ensure that protein families span a wide range of sequence similarity, all families were examined and those having less than 30% sequence identity span were not considered in further analysis. The redundancy between protein families was checked by using the procedure implemented in the CDART algorithm [17] and not more than 2 protein families from the same CDD cluster were retained in the final test set. At the end, the test set comprised 59 CDD families with more than 10 structurally aligned pairs of homologs. This test set covered a wide range of functional and structural classes and the list of test families together with their length, number of protein pairs and correlation coefficients is shown in Table 1.
Table 1 List of the names of 59 test protein families together with their CDD accession names, lengths, number of protein pairs, Pearson correlation coefficients between LHM (AHM) and normalized Blast bitscore. The families are ordered with respect to decreasing quality of LHM correlation. The supplementary table is available at [27].
Family name CDD acc Length #Obs AHM LHM
Xylose_isom pfam00259 381 28 -0.99 -0.98
MHC_I pfam00129 175 28 -0.95 -0.96
PTPc smart00194 248 25 -0.92 -0.96
IPT smart00429 97 21 -0.90 -0.94
ZnMc_1 smart00235 137 34 -0.83 -0.94
RNAse_Pc cd00163 99 25 -0.82 -0.94
gpdh_C pfam02800 153 39 -0.72 -0.93
Aamy_C smart00632 81 31 -0.94 -0.90
peroxidase pfam00141 240 48 -0.90 -0.90
copper-bind pfam00127 81 87 -0.84 -0.89
CBM_20 pfam00686 94 15 -0.91 -0.89
RnaseA pfam00074 98 44 -0.48 -0.87
IGv cd00099 105 133 -0.78 -0.86
ADH_zinc_N pfam00107 337 64 -0.93 -0.86
ldh_C pfam02866 143 29 -0.93 -0.86
RIP pfam00161 232 28 -0.87 -0.85
Peptidase_C1 pfam00112 200 55 -0.82 -0.85
ZnMc_2 cd00203 134 23 -0.87 -0.85
PROF cd00148 120 15 -0.90 -0.85
plant_peroxidase cd00314 236 76 -0.90 -0.83
alpha-amylase_C pfam02806 78 39 -0.93 -0.82
sodcu pfam00080 139 15 -0.98 -0.81
fer2_1 cd00207 78 38 -0.86 -0.80
Pept_C1 smart00645 202 90 -0.86 -0.79
ferritin pfam00210 152 19 -0.94 -0.79
ldh pfam00056 135 44 -0.82 -0.78
SH2 pfam00017 86 21 -0.48 -0.78
flavodoxin pfam00258 143 26 -0.88 -0.78
EFh cd00051 57 59 -0.75 -0.77
rhv_1 cd00205 195 71 -0.86 -0.76
LYZ1_1 smart00263 116 67 -0.66 -0.75
aldo_ket_red pfam00248 277 28 -0.93 -0.73
COesterase pfam00135 485 28 -0.80 -0.72
TIG pfam01833 89 39 -0.90 -0.72
fer2_2 pfam00111 69 73 -0.77 -0.70
beta-lactamase pfam00144 264 45 -0.90 -0.70
rhv_2 pfam00073 216 95 -0.86 -0.70
GLECT cd00070 124 28 -0.80 -0.67
globin pfam00042 133 96 -0.74 -0.66
GST_C pfam00043 107 77 -0.77 -0.63
LYZ1_2 cd00119 109 24 -0.43 -0.61
PA2c smart00085 102 210 -0.29 -0.57
lipocalin pfam00061 131 55 -0.62 -0.56
phoslip pfam00068 102 102 -0.21 -0.54
proteasome pfam00227 189 56 -0.80 -0.51
UBCc smart00212 141 45 -0.79 -0.50
Sm smart00651 63 30 -0.54 -0.49
Tryp_SPc smart00020 208 561 -0.55 -0.46
CLECT_1 smart00034 90 35 -0.59 -0.44
crystall pfam00030 81 10 -0.76 -0.41
CLECT_2 cd00037 93 263 -0.45 -0.36
RHO smart00174 173 10 -0.52 -0.36
IGc1 cd00098 88 85 -0.65 -0.32
Tryp_SPc cd00190 211 378 -0.55 -0.31
MHC_II_beta pfam00969 86 32 -0.52 -0.26
ADK pfam00406 174 28 -0.37 -0.19
Rho cd00157 172 66 -0.20 -0.16
Phycobilisome pfam00502 148 15 -0.85 -0.10
ADF smart00102 116 10 -0.85 0.34
Measures of structural and sequence similarity
To measure the sequence similarity between homologous proteins from the same family we used a Blast bitscore normalized by the alignment length. Among structure similarity measures used in this paper, two of them, RMSD and alignment-based Hausdorff measure (AHM) were computed by comparing the proteins in structurally aligned regions, while the loop-based Hausdorff measure (LHM) quantified the difference in the loop regions.
The root mean squared deviation (RMSD) was calculated using the superposition algorithm due to McLachlan [18]. The AHM and LHM measures were based on the mathematical concept of Hausdorff distance[19]. Let A = {a1,..., am} and B = {b1,..., bn} be finite point sets in a Euclidean space. The Hausdorff distance between the sets A and B is then defined by:
dH (A, B) = max {min j d(a1, bj),..., min j d(am, bj), min i d(ai, b1),..., min i d(ai, bn)} (1)
Here the terms d(ai, bj) denote the usual Euclidean distance between the points. In other words, the Hausdorff distance between the sets A and B is the smallest distance such that every point ai ∈ A is within this distance of some point bj ∈ B and vice versa. Hausdorff distance can be calculated under the assumption that the Cα atoms for both structures are in a common coordinate frame which is defined by the structural alignment between two domains. The Hausdorff measure for loops (LHM) was calculated as an average of Hausdorff distances over all loops in the protein pair, where ns is the number of aligned secondary structure elements:
The "loop" was defined as a region between two consecutive aligned secondary structure elements and:
hi = 0, if the i-th loop regions do not have any unaligned residues;
hi = dH (Ai, Bi), where Ai contains the set of Cα coordinates of non-aligned residues in the i-th loop of the first structure in a pair, the last aligned residue from the preceding aligned region and the first aligned residue from the following aligned region. Similarly, Bi is defined for the second structure in a pair. The sets (Ai, Bi) are defined to include two aligned residues so that the measure can be defined even if one of the sets of non-aligned residues is empty. The Hausdorff measure for the structurally aligned regions (AHM) was defined similarly. In this case, instead of the sets that contain the coordinates for the Cα atoms in the loops, we use the coordinates for the Cα atoms in the aligned segments and average over the number of aligned segments.
The correlation analysis between the measures of sequence and structural similarity, linear/nonlinear regression analyses and cluster analysis were performed using Splus version 6. Pearson (ρ) and Spearman correlation coefficients were calculated to quantify the accuracy of linear correlation. The P-value under the null hypothesis that the correlation coefficient between two variables is equal to zero has been estimated and those families with the P-values less than 0.01 were considered as having statistically significant correlation. The cluster analysis was done using the complete linkage clustering [20] where the distance between two clusters was measured as a maximum distance between a point in one cluster and a point in another cluster. The cluster trees based on p-distance and LHM were compared using the Phylip program [21] by generating 1000 bootstrap alignments from the structural alignments of a protein family and by calculating p-distance based cluster trees from the bootstrap alignments. The bootstrap support for the LHM based tree or different partitions of this tree was calculated by counting how many times the LHM topology occurs among the bootstrap cluster trees.
Results and discussion
Tables 1 and 2 show the accuracy of correlation obtained between the various measures of structural similarity (RMSD, AHM and LHM). As can be seen from these tables, the correlation quantified by the Pearson correlation coefficient is quite high for most of the families and half of the families have coefficients between -0.76 and -0.81 depending on the structural similarity measure used (Spearman rank correlation coefficients were shown to be very close to those reported in Tables 1 and 2). This result is consistent with the studies of Wood and Pearson who showed on a smaller test set of 35 protein families that half of them have correlation coefficients greater than 0.878 [8]. In their case the sequence-structure correlation was quantified, however, by using only the measures based on the structurally aligned regions of the proteins.
The dependence of structural similarity on sequence similarity in some cases can be more accurately described by the nonlinear regression model taking into account higher order quadratic terms. To quantify how much the nonlinear terms improve the data fitting, we use the ratio of squared correlation coefficient for linear () and nonlinear () models (). In the overall test set only 12 families have r2 – ratio smaller than 0.9 (with LHM used as a structural similarity measure) indicating that for these cases adding the non-linear term improves the performance of modeling by about 10%.
As was shown previously, the evolutionary relatedness between proteins can be successfully gauged from the comparison of their loop regions [7]. Indeed, Table 2 and Figure 1 show that within the families of homologous proteins, the structural changes in loops are strongly coupled with evolutionary distance, which in the first approximation can be estimated using normalized Blast score. The structural-sequence dependence in loop regions for 71% of our protein families can be well described by a linear model and for 88% of protein families the linear correlation coefficients are found to be statistically significant. Comparing different measures of structural similarity one can see that AHM performs somewhat better than other quantities yielding 90% of families with statistically significant linear correlation coefficients (with P-value < 0.01) and 80% of families with r2 > 0.9.
Table 2 Table shows the median of Pearson correlation coefficients, fraction of families with statistically significant correlation (P-value less than 0.01) and the fraction of families with the ratio r2 higher than 0.9 for each measure of structural similarity used in the study.
Median correlation coefficient % families with significant correlation % families with r2 > 0.9
RMSD -0.81 90 71
AHM -0.82 90 80
LHM -0.76 88 71
Figure 1 Hausdorff measure (in Angstroms) for loop (LHM) and aligned (AHM) regions is plotted versus the normalized Blast bitscore for three families: Pancreatic ribonucleases (RnaseA), Ig-like plexins/transcription factors (IPT) and Trypsin-like serine proteases (Tryp_SPc). Solid line shows the linear regression fit of the data.
However, not all families exhibit such good correlation. One example of a protein family showing particularly low LHM correlation is the family of Actin depolymerisation factor/cofilin-like domains (ADF). The sequence-structure correlation for loop regions of this family is not statistically significant (the Pearson correlation coefficient is close to zero) whereas the sequence-structure correlation for the protein core is very high (ρ = -0.85 with AHM). Indeed, different proteins of this family show distinctly different loop conformations and evolutionary analysis of ADF family argued that the insertions present in the vertebrate ADF/cofilins (and not present in non-vertebrate cofilins) might be important for nuclear function of mammalian cofilins [22]. Therefore, in this case the structural heterogeneity of loop regions can be explained by the acquisition of a new distinct function by some members of this family. For some families, for example, Trypsin-like serine protease (Tryp_SPc), neither LHM (ρ = -0.31) nor AHM (ρ = -0.55) similarity measures exhibit a good sequence-structure correlation (Figure 1(c)).
Among families with particularly high LHM correlation are the families of Xylose isomerase (Xylose_isom), Class I Histocompatibility antigen (domains alpha 1 and 2, MHC_I), Protein tyrosine phosphatase (PTPc) and others. Figure 1 shows two families with high sequence-structure correlation using the LHM measure: Ig-like plexins (IPT) and Ribonucleases A (RnaseA). The IPT family is characterized by high sequence-structure correlation for both core (ρAHM = -0.90) and loop regions (ρLHM = -0.94). On the other hand, the protein core structure of the RnaseA family changes very little with sequence whereas the loop structure gradually diverges as sequence becomes more and more dissimilar (ρAHM = -0.48, ρLHM = -0.87).
To understand whether significant sequence-structure correlation for loop regions has an underlying biological meaning, we performed a cluster analysis of proteins from two diverse families, Ribonuclease A (RnaseA), and SH2 domain (SH2, ρAHM = -0.48, ρLHM = -0.78), using different measures of sequence and structural similarity. Figure 2 depicts the cluster trees constructed using distance/similarity matrices which were based on the fraction of non-identical residues (p-distance), RMSD and LHM for these two families.
Figure 2 Complete linkage cluster tree produced using fraction of non-identical residues (p-distance), RMSD (Å), and LHM (Å) is plotted between proteins from Pancreatic ribonuclease family (RnaseA). Five major groups of RnaseA family according to Rosenberg et al [23] are: eosinophil ribonucleases (ER), pancreatic ribonucleases (PR), angiogenins (ANG), Rana ribonucleases (RR) and ribonuclease 4 (R4). The maximum parsimony tree described by Rosenberg et al [23] is given in the Phylip format: (RR, ((ANG, R4), (PR, ER))).
The RnaseA family represents a very interesting example to study as it is characterized by considerably different catalytic efficiency and substrate preferences among family members and the different aspects of its activity is not well understood. Although cysteines that form disulfide bonds, catalytic histidines and lysine residues are mostly structurally and sequence conserved, there is a great variability in sequence between other regions of RnaseA proteins [23,24]. We compared the obtained cluster trees (Figure 2) with the maximum-parsimony phylogenetic tree derived by Rosenberg et al [23], the Phylip format of this tree is given in the captions of Figure 2. As shown in this figure, the RMSD-based tree divides pancreatic ribonucleases (PR) into two groups and puts together two very different proteins: angiogenin (ANG) and Rana ribonuclease (RR) although angiogenin has a very weak enzymatic activity and is a tumor-growth promoter while Rana ribonuclease P-30 has ribonuclease activity and antitumor effects. In contrast to the RMSD cluster tree, distance matrices based on the loop (dis)similarity measure correctly cluster the representatives of the five major groups of the Ribonuclease family as per Rosenberg et al [23]. Although the topology of the p-distance based cluster tree is somewhat different from the topology of the LHM based tree (with bootstrap support less than 0.001), it also produces a biologically meaningful clustering as judged from Rosenberg et al [23].
SH2 domains represent phosphor-tyrosyl peptide binding modules which are found in many signaling proteins. The specificity of phosphate interaction with a protein has been attributed to the hydrophobic pocket which is mostly formed by two loop regions [25]. Our analysis shows that indeed the loop regions have a much higher accuracy in clustering of functional subfamilies of SH2 domains. Comparing our cluster trees with the classification of Songyang et al [26] and cluster trees of SH2 phosphotyrosyl binding sites [25] we can see from Figure 3 that p-distance based and RMSD based distance matrices cluster correctly two representatives of the "1A" subfamily (vsrc, hck), but separate proteins from subfamily "1B" (csk, csk, syk) and "4" (shptp2 and shc). In contrast, these subfamilies ("1B" and "4" [26]) are very well supported by the cluster tree which is based on the LHM measure. The bootstrap calculations (see Methods) show that the LHM based topology is supported by the p-distance based clustering algorithm at less than the 0.001 level. Different partitions of this tree are supported at higher but still non-significant levels, namely 0.11 for the "1B" subfamily (csk, csk, syk) and 0.01 for the subfamily "4" (shptp2 and shc). This in turn indicates that the two cluster trees can be considered statistically different.
Figure 3 Complete linkage cluster tree produced using fraction of non-identical residues (p-distance), RMSD (Å), and LHM (Å) is plotted between proteins from SH2 family (SH2). The classifications of SH2 domains according to [25, 26] are given in the parentheses: syk (1B, B), shptp2 (4, C), vsrc (1A, A), hck (1A, A), csk (1B, B), P85a (3, D) and shc (4,).
Conclusions
Here we have presented an analysis of how the structure of protein loops changes in evolution as homologous proteins diverge from each other. We showed that for the majority of protein families there exists a statistically significant linear correlation between measures of sequence similarity and average loop structural similarity. This in turn suggests that loops change in evolution via a stepwise insertion or deletion process and clearly one can not portray even longer loop regions as "irregular conformations" or "random coils". Indeed, our results imply that, in general, loops are under constant evolutionary constraints which, apparently, are weaker than those for a protein core but still strong enough to preserve the loop overall structure. Since loops do not contribute much to the protein core stability, these constraints predominantly arise from the importance of loops in interacting with ligands, other proteins and cells, as well as a possible role of loops in protein folding.
Modeling of insertion and deletion events in evolution poses a lot of difficulties and protein evolution is usually reconstructed based only on the aligned regions of proteins. We demonstrated that loop regions which usually correspond to the non-aligned protein regions can be very important in inferring the phylogenetic history of a protein family. Moreover, it was shown, that sometimes sequence and structure similarity measures comparing proteins in their core are not sensitive enough to detect subtle (dis)similarities between the subfamilies. Loop-based measures which emphasize the dissimilarities between different protein members can shed light on the evolutionary relationships between homologous proteins.
Authors' contributions
AP and TM contributed equally to this paper.
Acknowledgements
We especially thank Stephen Bryant and Yuri Wolf for insightful discussions. This work has been supported by the NIH Intramural Research Program.
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| 15691378 | PMC549550 | CC BY | 2021-01-04 16:37:16 | no | BMC Evol Biol. 2005 Feb 3; 5:10 | utf-8 | BMC Evol Biol | 2,005 | 10.1186/1471-2148-5-10 | oa_comm |
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BMC GenetBMC Genetics1471-2156BioMed Central London 1471-2156-6-51569847910.1186/1471-2156-6-5Methodology ArticleAn automated system for measuring parameters of nematode sinusoidal movement Cronin Christopher J [email protected] Jane E [email protected] Saleem [email protected] Young-Mee [email protected] Robert C [email protected] Jehoshua [email protected] Paul W [email protected] HHMI and Division of Biology, California Institute of Technology, Pasadena, CA, USA2 Computation and Neural Systems, California Institute of Technology, Pasadena, CA, USA3 Jet Propulsion Laboratory, Pasadena, CA, USA4 21018 Wendy Drive, Torrance, CA 90503, USA2005 7 2 2005 6 5 5 19 8 2004 7 2 2005 Copyright © 2005 Cronin et al; licensee BioMed Central Ltd.2005Cronin 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
Nematode sinusoidal movement has been used as a phenotype in many studies of C. elegans development, behavior and physiology. A thorough understanding of the ways in which genes control these aspects of biology depends, in part, on the accuracy of phenotypic analysis. While worms that move poorly are relatively easy to describe, description of hyperactive movement and movement modulation presents more of a challenge. An enhanced capability to analyze all the complexities of nematode movement will thus help our understanding of how genes control behavior.
Results
We have developed a user-friendly system to analyze nematode movement in an automated and quantitative manner. In this system nematodes are automatically recognized and a computer-controlled microscope stage ensures that the nematode is kept within the camera field of view while video images from the camera are stored on videotape. In a second step, the images from the videotapes are processed to recognize the worm and to extract its changing position and posture over time. From this information, a variety of movement parameters are calculated. These parameters include the velocity of the worm's centroid, the velocity of the worm along its track, the extent and frequency of body bending, the amplitude and wavelength of the sinusoidal movement, and the propagation of the contraction wave along the body. The length of the worm is also determined and used to normalize the amplitude and wavelength measurements.
To demonstrate the utility of this system, we report here a comparison of movement parameters for a small set of mutants affecting the Go/Gq mediated signaling network that controls acetylcholine release at the neuromuscular junction. The system allows comparison of distinct genotypes that affect movement similarly (activation of Gq-alpha versus loss of Go-alpha function), as well as of different mutant alleles at a single locus (null and dominant negative alleles of the goa-1 gene, which encodes Go-alpha). We also demonstrate the use of this system for analyzing the effects of toxic agents. Concentration-response curves for the toxicants arsenite and aldicarb, both of which affect motility, were determined for wild-type and several mutant strains, identifying P-glycoprotein mutants as not significantly more sensitive to either compound, while cat-4 mutants are more sensitive to arsenite but not aldicarb.
Conclusions
Automated analysis of nematode movement facilitates a broad spectrum of experiments. Detailed genetic analysis of multiple alleles and of distinct genes in a regulatory network is now possible. These studies will facilitate quantitative modeling of C. elegans movement, as well as a comparison of gene function. Concentration-response curves will allow rigorous analysis of toxic agents as well as of pharmacological agents. This type of system thus represents a powerful analytical tool that can be readily coupled with the molecular genetics of nematodes.
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Background
A major motivation for establishing C. elegans as an experimental molecular genetic system was to understand how genes control behavior, especially locomotion, since the uncoordinated (Unc) mutants were discovered early in the history of C. elegans genetics [1,2]. While studies of hundreds of genes involved in this behavior have led to many insights into processes such as axonal guidance (unc-5, unc-6 and unc-40; [3,4]), synaptic transmission (unc-13, unc-18; [5-7]), myosin assembly (unc-54 [8]), regulation of G protein signaling [9-16]), neuropeptide function [17] among many others, there has been no general understanding of how C. elegans moves. Starting with Brenner [1]C. elegans researchers have identified several hundred genes with effects on movement. Recently, RNAi screens have identified 1371 of 27,574 experiments (approximately 800 genes) that confer abnormal movement [18]. Normal nematode movement is indicative of a toxicant-free environment, and of youthful vigorous worms. Drugs and toxins affect worm movement [19-21], and locomotory defects are a hallmark of aging worms [22]. Models for C. elegans movement (e.g. [23-25]) would be enhanced by additional quantitative data.
Descriptions of movement phenotypes, particularly hyperactive locomotion, have been partial and to some extent anecdotal. For example, mutations in a number of genes result in activation of the EGL-30 (Gαq) signaling pathway and cause an increase in the frequency of body bends [7,9,10,12,15,17,26-30]. Overexpression of or gain-of-function mutations in egl-30 also cause animals to move with exaggerated body bends [28,29], but the presence or absence of this phenotype has only been reported for a few of the Gαq pathway activators [15,17,26]. The rate of locomotion has often been determined by manually counting body bends per minute (e.g., [30-32]). Amplitude of body waves has also been determined manually [17,26]. Keating et al. [33] used visual inspection or manual quantification to screen for movement defects caused by RNAi depletion of neuropeptide receptors. These approaches, while useful, are labor intensive and provide only a partial description of the movement of a particular genotype.
We therefore developed a system to analyze the body posture of C. elegans hermaphrodites over time and extract quantitative information concerning their movement. Here we describe a functional system, metrics, analysis tools, and example applications for distinguishing closely related C. elegans mutants and establishing concentration-response relationships for toxic agents.
There have been other developments of automated systems. For example, Williams and Dusenbery [34] tracked the centroids of multiple worms simultaneously. Several other studies have also used automatic tracking of centroids to analyze velocity, dispersal and turning rate [35-41]. Hirose et al., [42] have recently described a system to automatically measure body length, using image processing similar to that described here. At the time we developed the prototype of the system described here (1999–2000), there were no systems available. Here we describe a set of metrics that allow intuitive use of an automated system, and show the utility of these metrics for genetic studies and studies of toxic agents. During preparation of this paper, we have implemented a combined system that uses the metrics and some algorithms described here with components of a related system developed by Schafer and colleagues [43,44]. The hardware and software for the hybrid system is described by [45]; the metrics and applications are described here in relation to our system.
Results
The movement analysis system
Our system analyzes motion in two phases. First, video and worm posture data are acquired using the system hardware. Second, measures of behavior are extracted by software. Data acquisition is a two-step process: videotaping and data extraction.
Videotaping
We assembled a videotaping apparatus comprising a personal computer with the Tracker software package that we developed, a Matrox Meteor-II/Standard video frame grabber, a Wild M5A stereo dissecting microscope with camera mount, a Dage-MTI CCD72 video camera and controller, a Sony video monitor, a Ludl Electronic Products BioPoint motorized inverted-microscope stage and controller with a joystick for manually moving the stage, a stage-mounted custom Petri dish carrier, and a Panasonic model AG-5710P VHS video cassette recorder (which has an RS-232 connection for computer control and feedback of VCR operation) (Figure 1A).
Figure 1 Tracker and Recognizer Schematic. A. Tracker. A Petri plate with worm is placed on a computer-controlled motorized stage. A joystick is used to center the worm in the field of view. The worm is recorded on VCR. B. Recognizer. The video tape is played into a computer by a computer-controlled VCR to recognize the worm and record its body posture and position as a function of time.
The behavior of individual worms is examined on Petri plates with fresh, uniform bacterial lawns (see Methods), conditions that favor continued forward movement of the worms.
With the videotaping apparatus powered and the Tracker program started on the desktop computer, a single young hermaphrodite is placed at the center of a prepared Petri dish without transferring excess food, and the dish is placed onto the carrier on the motorized microscope stage. The operator uses the joystick and/or Tracker on-screen controls to position the moving worm within a bounding box on the Tracker program's graphical user interface (GUI) and starts the tracking function of the program (Figure 2A).
Figure 2 User Interfaces. A. Tracker User Interface. A simple GUI controls the tracking and recording. B. Recognizer2.1 User Interface. A simple user interface illustrates the progress of the recognition process. The image of the worm is shown with the spine and points superimposed. C. Wormproc User Interface. The interface for processing body posture shows a reference image of worm on plate to assist with worm orientation (left) and the main data processing control window (right) depicting an abstraction of worm during processing. If Recognizer2.1 inappropriately flips head and tail, it can be overridden with the Flip function. The program automatically rejects frames in which the worm length is outside of a calculated normal range, but these can be overridden with the Accpt/Rejct button, or all frames can be scored manually by hitting the Un-Reject All button.
Our Tracker program grabs images (frames) from the video stream from the camera looking for differences between successive frames that indicate a moving worm. Tracker identifies the changed regions as either newly occupied or newly vacated. If a changed region falls outside of a 240 × 160 pixel bounding box (within the 320 × 240 pixel image) Tracker sends a command to the motorized microscope stage controller to shift the stage half of a screen width and/or height to relocate the itinerant worm back to the middle of the camera's view field. With the computer re-positioning the worm as necessary, the video stream from the camera is recorded onto VHS tape for use in the data extraction step.
Tracker was designed to move the microscope stage in rapid, discrete shifts, allowing the worm to crawl to the edge of the view field before being reined back to the center of our camera's view field. We chose this protocol to eliminate the need for position feedback sensors and stage position data storage.
Data extraction
Our Data Extraction apparatus consists of a personal computer with our Recognizer2.1 software package, a Matrox Meteor-II/Standard video frame grabber, a Panasonic model AG-5710P VHS video cassette recorder (which has an RS-232 connection for computer control and feedback of VCR operation), and an optional Sony video monitor (Figure 1B).
We use our Recognizer2.1 program to extract worm position and posture data from the video recording made in the previous step. Recognizer2.1 commands the VCR to play back segments of the worm videotape made previously and, using a double-buffering paradigm, grabs and processes images (frames) from the video stream at the rate of ~6 Hz. (Processing rate is a function of available computing bandwidth.) During extraction, Recognizer2.1 displays the grabbed/annotated images in its GUI window (Figure 2B).
Recognizer2.1 locates the worm in each 640 × 480 pixel image using contrast thresholding, identifies the worm's boundary curve, and uses the boundary curve to calculate the worm's "spine." The program mathematically distributes points along the length of the "spine" and records the X-Y position of the points in an output file. (n points define n-1 body segments, between which there are n-2 articulation points, or "bends", whose angles we calculate.) We typically set Recognizer2.1 to distribute 13 points (13 points: 12 body segments: 11 articulation points) along the worm's spine, but the program can be easily user-customized to apply as many or as few points as desired if, for example, a longer worm is analyzed.
The result of running Recognizer2.1 is a set of folders saved to hard disk, each containing a file called "points" containing the table of X-Y coordinates for the 13 points on the worm spine in each grabbed image, and a set of bitmap worm images. The X-Y coordinate table's rows are the data for each image, with the first pair of rows containing the coordinate data from the first image grabbed, and the last pair of rows containing the data from the last image. The table's columns are the data for each of the points distributed along the worm's spine, but since Recognizer2.1 does not identify head versus tail, the saved coordinate data simply represents the posture and screen position of the worm in each processed image without regard to head-tail orientation. Data "orientation" is performed as part of the data processing phase.
We assume the time between successive grabbed and processed images is consistent within a data set, and calculate the effective grab rate as the number of grabbed frames in the data set divided by the length of the data set (in seconds). Measurements of the distribution of inter-grab intervals were made by saving computer-generated timestamps corresponding to the X-Y coordinate data normally saved. The distribution of intervals indicates that there is less than 10% variability and thus this only accounts for a small fraction of the observed variability within observations of each animal (see Figure 4 below). Videotape stretch before or during playback could also be a source of variability but we assumed this to be negligible.
Figure 3 Sample Attributes. The key attributes that are extracted by Wormproc program are shown schematically. Centroid velocity is the translation of the mean position of the rear two-thirds of the animal. Point velocity is the velocity of each point along the animal's track; velocity is the mean of the point velocities for points 5–13. Track amplitude is the maximum width of a box around the worm. Track wavelength is the length of the sine wave that fits the worm's posture. Bending frequency is the frequency of oscillations between adjacent segments. Flex is the maximum difference in angle between the ventral- and dorsal-most flexion at each articulation point. Time delay is the time required to propagate flexion between adjacent articulation points.
Figure 4 Variability of wild-type movement. For each metric, the aggregate statistics are shown along with individual days' experiments. Each daily group is designated by date. The 'other' group comprises 25 individuals that were tested on 16 different days in groups of 1–3. For each metric, a bar graph of the means is displayed (A, C, E, G, I, K) as well as histograms (B, D, F, H, J, L). For bar charts: Blue, mean; green, forward; red, backwards. For histograms: Blue, all 48 N2 animals (n = 48); Green, 2-18-03 dataset (n = 5); Red, 7-18-03 dataset (n = 8); light blue, 9-05-03 dataset (n = 4); magenta, 10-17-03 dataset (n = 6); yellow, other dataset (n = 25). n = number of individuals tested; n is the same for all panels. A. Mean velocity. B. Velocity histogram. C. Mean centroid velocity. D. Centroid velocity histogram. E. Mean frequency at bend 5. F. Frequency at bend 5 histogram. G. Mean flex at bend 5. H. Flex at bend 5 histogram. I. Mean length-normalized track amplitude. J. Length- normalized track amplitude histogram. K. Mean length-normalized wavelength. L. Length-normalized wavelength histogram. Each histogram curve represents the distribution of 632 to 1485 individual measurements per worm.
Data processing and analysis
Data processing and analysis is performed using a suite of programs we developed in Matlab (from The MathWorks) comprised of three applications: "Wormproc" (worm processing), "Metrics", and "Histograms." Data processing proceeds in several steps.
Wormproc
The researcher runs the "Wormproc" program for each worm to convert the X-Y data into a usable format. First, Wormproc loads into RAM the X-Y coordinate data and images captured and saved to disk by Recognizer2.1. Since Recognizer2.1 does not distinguish between head and tail, Wormproc orients spines by selecting the spine orientations (either oriented "as recorded" or "reversed") that are minimally different from each preceding spine. Further, Wormproc flags spines with lengths that are outside of a calculated "normal" range (asserting that they are invalid or missing data), and identifies the end of the worm that moves the most as the head-end (based on typical C. elegans foraging behavior). Disjointed data segments, for example before and after an omega bend, are treated as separate data segments; Wormproc identifies head position before and after such breaks.
Next, Wormproc mathematically removes the microscope stage shifts from the X-Y data; the program recognizes stage shifts by a velocity spike (a very large displacement between two consecutive frames) uncharacteristic of a nematode. The program offsets the X-Y coordinate data after each stage shift to continue the worm's path of locomotion, interpolating over any single missing frames. Occasionally Recognizer2.1 will have grabbed a worm image while the microscope stage is moving. In these instances Recognizer2.1 either will not be able to identify any worm in the image or, because of the interlaced video and contrast, will only be able to recognize a tiny area of the smeared image as worm. In either case the X-Y data for these frames will have been automatically rejected for being outside of the normal length range for the worm.
Finally, Wormproc provides a GUI (Figure 2C) that allows the user to verify (and modify, if necessary) the computer's assertions on valid/invalid data, and worm head/tail orientations via an animation of the subject worm's movements with still images presented in a second window for reference. When the user is satisfied, the program saves the oriented and verified data to hard disk.
Metrics
We developed a software application called Metrics which extracts useful measures of nematode locomotion and morphology from the processed X-Y coordinates for each worm. For each worm we extract eleven attributes (Figure 3).
One set of attributes concerns the speed of worm movement. We calculate the instantaneous speed of the animal's centroid (its 'centroid velocity' or VELC). We define the centroid as the mean position of points 5–13 (approximately the posterior two-thirds of the body), and the instantaneous centroid velocity as the change in centroid position over time. Likewise, we calculate the instantaneous velocities of all 13 points along the spine as they move over time (the point velocity, or PTVEL). We define the means of the point velocities for points 5–13 as the worm's 'velocity' (VEL). Instantaneous velocity, point velocity and centroid velocity are identified as 'forward' (positive) or 'backward' (negative) reflecting the direction the animal is moving. The MODE lists the instantaneous movement direction with 1's (forward) or -1's (backward). MODE is determined automatically in Metrics by evaluating whether the majority of points 5–12 are moving closer to their anterior or to their posterior neighbors through successive frames. Due to signal noise, MODE cannot at present be set to "no movement". THETA is the instantaneous velocity (VEL) vector direction.
A second set of attributes concerns propagation of the contractile wave. The flex (FLEX) is the difference between maximum positive and negative bend angles in a sliding time window for each of the articulation points. The bending frequencies (FRE) are the time-windowed bending frequencies at each of the worm's articulation points. Time delay (PHS) is a matrix containing the time delay required for an articulation point to reach the same angle as its next anterior neighbor; this metric describes the rate of wave propagation along the worm.
A third set of attributes describes the worm's waveform. The track amplitude (AMPT) is the instantaneous worm track waveform amplitude, specifically the width of a best-fit bounding box aligned with the worm's instantaneous velocity vector. Wavelength (WAVELNTH) is a measure of the instantaneous physical wavelength of the worm's sinusoidal body posture.
Another attribute describes morphology. The worm's length (LEN) is the sum of the distances between the points along the worm's "spine."
Histograms and other data visualization routines
We developed several data visualization routines to display and compare the movement attributes of worms.
The most common program we use is "Histograms" which displays a set of histograms for comparing locomotory parameters for populations of nematodes. The standard attributes displayed are: Centroid Velocity, (Mean Point) Velocity (velocity of the worm along its sinusoidal track), Flex (for several articulation points), Bending Frequency (for several articulation points), Time Delay (for several articulation points), Track Wavelength, and Track Amplitude (both in millimeters and normalized as a percent of mean worm body length).
In addition to comparing populations of worms, it is often useful to compare individual worms within a population, for which we developed "iHistograms." This application produces the same charts as "Histograms," but displays the data for individual worms instead of populations.
Using the flexibility of the Matlab programming environment we have developed a multitude of specialty analysis tools, ranging from toxicant concentration-response curves, to speed decay as a function of time, to animation routines to visualize wave propagation, to reversal frequency. With a bit of creativity, output can be customized to a broad range of experiments. To demonstrate the general applicability of this type of system to nematode biology, we provide a few salient examples: genetics and toxicology.
Reproducibility of data
One common problem in behavioral studies on C. elegans is day-to-day variability. To test whether data obtained on different days could be pooled, we analyzed the movement of small numbers of wild-type individuals on different days. We then compared the means for each movement parameter of each daily group to those for the pooled total. Specifically, we compared seven groups comprising four-twelve individuals to the total data set of 58 individuals. Two groups, with five animals each, had means for more than one parameter that were significantly different from the pooled total and were eliminated from our analysis. For the remaining groups, the p values for all parameters except FLEX ranged from 0.07 to 0.99. For two of the included groups, mean values for FLEX for the more posterior articulation points were significantly different from the pooled total. We therefore report FLEX measurements for a more anterior articulation point (bend 5) only. Comparison of the daily groups to the pooled total is displayed in Figure 4, which shows types of graphical representation available in our system.
Genetic analysis
We tested whether the system was useful for comparing alleles of the same gene, and alleles of different genes that result in qualitatively similar movement phenotypes. goa-1 encodes the only Go-alpha subunit in C. elegans and is involved in locomotion [18,26,27,46]. goa-1(n1134) is a reduction-of-function allele, defective in the consensus sequence for myristoylation at the amino-terminus [27], and is protein-negative on a Western blot [47]. goa-1(sy192) is an antimorphic allele [48]. Although n1134 and sy192 homozygous mutant animals look very similar by visual examination, quantification of their movement revealed that sy192 affects certain movement parameters more severely than n1134 (Figure 5). The mean forward point velocity of sy192 is 0.37 (+/- .04) mm/sec versus 0.29 (+/- .06) mm/sec for n1134 and 0.20 (+/- .04) mm/sec for wild type (Figure 5). These values are significantly different (p < 0.001 for each pair). The centroid velocities show the same relationship sy192 >n1134 > wild type. The flex is also significantly different: sy192 has a flex at articulation point (bend) 5 of 1.4 (+/- .05) radians, n1134 1.3 (+/- .09) radians and N2 1.0 (+/- .09) radians (p < 0.0005 for all pairs). The frequencies of n1134 and sy192 hermaphrodites, however, are similar: 0.58 (+/- .06) Hz at bend 5 for sy192 versus 0.53 (+/- .10) Hz for n1134 (p = 1.08) versus 0.36 (+/- .08) Hz for wild type (p < 0.0005). The track amplitudes of all three genotypes are significantly different. When normalized for body length, sy192 has a track amplitude of 25.53 (+/- 1.14) % body length, n1134 22.00 (+/- 1.64) % body length, and N2 19.27 (+/- 2.34) % body length (p < 0.0005 for all pairs). The wavelengths, however, are not different for all genotypes. sy192 has a wavelength significantly different from wild type (64.19 +/- 1.40 % body length versus 62.03 +/- 2.28 % body length, p = 0.004). However, the wavelength of n1134 (63.39 +/- 2.3 % body length) is not different from N2 (p = 0.07) or from sy192 (p = 0.34). In summary, mutations in goa-1 that cause hyperactive movement increase both the point and centroid velocities, increase the flex of articulation points, increase the frequency of body bends, and increase the track amplitude compared to wild type. With the exception of frequency, the antimorph sy192 has a more profound effect on these parameters than the null mutation n1134. sy192 also decreases the wavelength compared to wild type, but n1134 has only a mild effect on wavelength.
Figure 5 Comparison of two alleles of goa-1. Blue, wild-type (n = 48); green, goa-1 (n1134), a null allele (n = 12); red, goa-1 (sy192), an antimorphic allele (n = 11). n = number of individuals tested; n is the same for all panels. A. Distribution of velocity. B. Distribution of centroid velocity. C. Flex at bend 5. D. Frequency at bend 5. E. Length-normalized track amplitude. F. Length-normalized track wavelength. Each curve represents the distribution of 632 to 1485 individual measurements per worm. The population mean values reported in the text reflect only forward moving worms and are based on 550 to 1454 individual measurements per worm.
For movement, goa-1 acts antagonistically to egl-30, thus increased egl-30 activity is similar to loss of goa-1 activity [28,29]. We therefore compared the movement of worms bearing a strong egl-30 gain-of-function allele, tg26 [49,50], to those lacking goa-1 activity (goa-1(n1134)). Visually, tg26 mutants move with more exaggerated body bends than both wild type and n1134. This difference was detected by our movement analysis system (Figure 6). The mean forward point velocity of both n1134 and tg26 are similar (0.28 +/- .03 mm/sec for tg26 and 0.29 +/- .06 mm/sec for n1134, p = 0.76), and faster than wild type (0.20 +/- .04 mm/sec, p < 0.0005). Although not statistically significant, the forward centroid velocity for tg26 (0.21 +/- .02 mm/sec) is more similar to that of N2 (0.18 +/- .03 mm/sec, p = 0.02) and less similar to that of n1134 (0.24 +/- .05 mm/sec, p = 0.05) than the mean forward point velocities. This difference reflects the increased path length any point on the spine of the tg26 mutant must travel to displace the centroid. Both mutations cause increased flex and frequency compared to wild type. The flex of tg26 at bend 5 was 1.77 (+/- .04) radians versus 1.27 (+/- .09) radians for n1134 (p < 0.0005), and 1.00 (+/- .09) radians for wild type (p < 0.0005). The frequency of tg26 at bend 5 was 0.56 (+/- .05) Hz versus 0.53 (+/- .10) Hz for n1134 (p = 0.37), and 0.36 (+/- .08) Hz for wild type (p < 0.0005). While both alleles affect frequency similarly, tg26 has a more profound effect on flex than does n1134. tg26 also has a more profound effect on amplitude than does n1134. When normalized for body length, tg26 has an amplitude of 26.08 (+/- .67) % body length compared to 22.00 (+/- 1.63) % body length for n1134 (p < 0.0005) and 19.27 (+/- 2.36) % body length for wild type (p < 0.0005). The track wavelength for tg26 is shorter than that of n1134 and N2: 54.04 (+/- 1.13) % body length for tg26, 63.4 (+/- 2.33) % body length for n1134 (p < 0.0005), and 62.3 (+/- 2.28) % body length for wild type N2 (p < 0.0005).
Figure 6 Comparison of goa-1 loss-of-function and egl-30 gain-of-function mutations. Blue, wild-type (n = 48); green, goa-1 (n1134), a null allele (n = 12); red, egl-30 (tg26), a gain-of-function allele of egl-30 Gq (n = 8). n = number of individuals tested; n is the same for all panels. A. Distribution of point velocity. B. Distribution of centroid velocity. C. Flex at bend 5. D. Frequency at bend 5. E. Length-normalized track amplitude. F. Length-normalized track wavelength. Each curve represents the distribution of 632 to 1485 individual measurements per worm. The population mean values reported in the text reflect only forward moving worms and are based on 550 to 1454 individual measurements per worm.
Our movement analysis system is thus able to discriminate between the effects of different mutations that affect the same parameters of movement.
Toxicology
To test the utility of our system for analyzing the effects of toxicants, we focused on the neurotoxin aldicarb and the metabolic inhibitor arsenite. We first established baseline conditions for these toxins. We then tested whether existing mutations would increase the sensitivity to these compounds. We focused on mutations that affect cuticle and P-glycoprotein transporters.
We analyzed C. elegans movement in the presence of increasing concentrations of aldicarb (2-methyl-2-(methylthio)propionaldehyde O-methylcarbamoyloxime) and sodium-arsenite (NaAsO2). We first determined that a 30-minute exposure to 6.4 mM aldicarb induced near paralysis in wild-type C. elegans. We then recorded movement of individual hermaphrodites following a 30-minute exposure to aldicarb concentrations from 0 to 6.4 mM. We tested 16–17 individual wild-type worms for each concentration of aldicarb and found that the concentration reducing wild-type mean forward point velocity by 50% (EC50) is 0.39 mM aldicarb (Figure 7A). We similarly determined that a 3-hour exposure to 80 mM sodium-arsenite induced paralysis in wild-type worms. We have determined an EC50 of 9.7 mM NaAsO2 for wild-type C. elegans (Figure 7B). Of the movement parameters tested, mean point velocity, centroid velocity, track amplitude and track wavelength were equally sensitive to aldicarb, with differences apparent at the lowest concentration tested (0.1 mM). A reduction of frequency was seen at 0.2 mM, but flex was resistant to the effects of aldicarb and alterations were only apparent at the highest concentrations (data not shown). For sodium arsenite, most parameters were affected after exposure to 2.5 mM, except for flex which was only affected at concentrations above 20 mM (data not shown).
Figure 7 Toxicant sensitivity of wild-type and cat-4. A. Sensitivity to aldicarb. For N2, n = 16 animals for 0 mM aldicarb and 17 for all other concentrations. For cat-4, n = 6 for all concentrations. B. Sensitivity to arsenite. For N2, n = 17 animals for 2.5 mM sodium arsenite and 18 for all other concentrations. For cat-4, n = 4 for all concentrations.
We tested three candidate hypersensitive mutant C. elegans strains for movement in response to increasing doses of aldicarb and sodium-arsenite.
The cat-4 gene encodes GTP cyclohydrolase I (C. Loer, personal communication; see also [51]) necessary for biosynthesis of biogenic amines; it is hypersensitive to several disparate agents such as the neurotransmitter serotonin and the detergent SDS, suggesting a weaker or more porous cuticle (C. Loer, pers. comm.). cat-4 mutants are 2.2-fold more sensitive to aldicarb (EC50 = 0.18 mM vs. 0.39 mM; Figure 7A) and 8.1 fold -fold more sensitive to arsenite (EC50 = 1.2 mM vs. 9.7 mM; Figure 7B) than wild-type C. elegans. Only the EC50s of wild type and cat-4 on arsenite are significantly different.
P-glycoproteins are membrane transporters in certain cells that protect the cell against environmental toxins by moving such agents out of the cell. The strain NL130 carries deletions for two P-glycoproteins encoded by pgp-1 and pgp-2 [52]. Mutants lacking these two P-glycoproteins are hypersensitive to colchicine and chloroquinone. We have shown that NL130 is 3.5-fold more sensitive to aldicarb (EC50 = 0.11 mM vs. 0.39 mM; Figure 8A) and 1.2-fold more sensitive to arsenite (EC50 = 8.2 mM vs. 9.7 mM; Figure 8B) than wild-type C. elegans. The strain NL152 carries deletions for mrp-1 as well as those for pgp-1 and pgp-3 [53]. The mrp-1 gene encodes a C. elegans homolog of the mammalian multidrug resistance-associated protein (MRP), another transporter that protects cells from toxins. NL152 also showed increased sensitivity (9.7-fold) to aldicarb (EC50 = 0.04 mM vs. 0.39 mM; Figure 8A), and only slightly increased sensitivity to arsenite (EC50 = 5.8 mM vs. 9.7 mM; Figure 8B). However, NL152 is also somewhat movement impaired in the absence of toxic agents.
Figure 8 Toxicant sensitivity of NL130 and NL152. A. Sensitivity to aldicarb. For N2, n = 16 animals for 0 mM aldicarb and 17 for all other concentrations. For NL130 and NL152, n = 6 for all concentrations. B. Sensitivity to arsenite. For N2, n = 17 animals for 2.5 mM sodium arsenite and 18 for all other concentrations. For NL130 and NL152, n = 4 for all concentrations.
Our system is thus useful for analyzing the effects of toxicants on nematode movement and for examining the effects of genetic background on toxicant sensitivity.
Discussion
We describe a usable automated system to record and analyze C. elegans locomotion and to display quantitative data. We describe several useful parameters of locomotory behavior. These include automatic determination of the velocity of the worm's centroid, the velocity along its track, the degree of flex of body at various positions along the body axis, the bending frequency between adjacent segments, and the body-length normalized track amplitude and wavelength (Figure 3). Many of these measurements match what C. elegans geneticists have typically observed in describing movement variations such as velocity and body bends per minute. Our system thus provides facile quantification of standard phenotypes. Additionally, our system provides measurements that describe many aspects of movement that relate to underlying neural and mechanical mechanisms of locomotion such as propagation of the contraction wave. We envision that the ability to describe in a quantitative and automatic manner nematode movement will facilitate modeling of C. elegans movement.
We have demonstrated that our system can be used to distinguish between different alleles of the same gene, different genes, and different environmental conditions. It thus provides a rich dataset for analysis of gene function and toxicology. In addition, this system can be adapted to score other phenotypes. For example, the frequency of spontaneous reversals can be easily extracted from the data set. This system gives worm length as well, and thus we can normalize the track wavelength. Measurement of body length has been used to screen for suppressor mutations and to analyze mutations that affect gene expression [47,54], and thus this system can be used for genetic studies besides behavior.
The basic platform described here might be readily extensible to analysis of other nematode behaviors such as male mating, as well as the behavior of other organisms such as the crawling of insect larvae. Although the system is not high throughput, recording of each individual hermaphrodite takes only seven minutes of largely hands-off time on the part of the researcher. Including processing of the data, a single data set comprising 10–12 individuals can be generated in less than three hours.
There are a number of limitations to our system. We use all relative coordinates, and thus tracking worms with respect to specific locations on the Petri plate, for example a gradient of chemoattractant, is not possible. In addition, the noise inherent in our tracking system, most likely arising from its use of analog video, precludes our detecting a worm that is definitively not moving. Moreover, the throughput of our system is limited by its inability to follow multiple worms simultaneously.
While preparing this manuscript, we compared our system to that of W. Schafer and colleagues [43,44], and identified useful features of each system. We have begun to develop a joint system taking advantage of the best features of each system to allow further software development to proceed in an efficient manner. A prototype has been described [45], but the system described here has been used in a number of ongoing studies in our laboratory and is still in continual use.
Methods
Strains and media
C. elegans N2 [1]. NL131 pgp-3(pk18)X [52]; goa-1(sy192)I [26]; goa-1(n1134)I [27]. CB1141 cat-4(e1141)V[55]. NL130 pgp-1(pk17)IV; pgp-3(pk18)X [52]. NL152 pgp-1(pk17) IV; pgp-3(pk18) X; mrp-1(pk89)X [53]. Nematode Growth Medium (NGM) is from Brenner [1].
Preparation of plates for observation
10 cm NGM recording plates are equilibrated to 20°C for 18–20 hours prior to being spread with bacteria. Approximately one hour before beginning our recordings, 600 μl of fresh OP50 overnight culture is spread onto each plate, rapidly swirling and shaking to achieve a thin, featureless lawn of food across the entire surface. Excess solution is drawn from the edge with a Pipetman. Each food-spread plate is covered with a tissue (Kimwipe), to ensure that the plate remains dust-free as it dries. The food is allowed to dry onto the NGM surface just until the surface exhibits a matte finish (about 45 minutes), at which time the tissues are replaced by the Petri dish lids and the plates are ready for use. The time required for drying is monitored as a crude measure of the relative moisture content of the plates. Plates requiring more than 60 minutes to dry are discarded. Each plate is used within three hours of drying.
Assay conditions
L4 hermaphrodites are selected 18–20 hours prior to recording to control for age. Individuals are placed on assay plates and the plate is placed in the holder on the microscope stage. After two minutes the worm is located and recording begins. Each worm is recorded for five minutes and the central four minutes of data are analyzed. Incubations and recordings are done in a constant temperature room at 20°C.
Toxicant treatment
Aldicarb and sodium-arsenite stocks were prepared in H2O (at 55°C for aldicarb), and the appropriate volume added to cooled NGM media prior to pouring plates. The volume of added solution was kept constant. The pH of media containing sodium arsenite was adjusted to 5.8–6.0 (to match NGM without toxicant) with concentrated HCl. This was not necessary for plates containing aldicarb. 10 cm assay plates and 5 cm pre-incubation plates were prepared similarly and stored at 4°C until needed. To insure an ample source of food during pre-incubation, 5 cm plates were seeded with fresh OP50 18–20 hours before use and stored at 37°C until 2 hours prior to the assay when they were placed at 20°C. 10 cm assay plates were equilibrated to 20°C and spread with a thin lawn of OP50 as described above. Hermaphrodites were placed on pre-incubation plates and incubated for 30 minutes for aldicarb and 3 hours for sodium-arsenite prior to recording. Following pre-incubation, individuals were transferred to assay plates and recorded after a 2-minute rest on the microscope stage as described above. All preincubations and assays were performed at 20°C.
Microscope
Our recordings were made using a Wild M5A stereo dissecting microscope with a 25× objective lens and a 1.25× camera mount.
Hardware and software
Tracker and Recognizer2.1 are written in Microsoft Visual C++ (6.0), using Matrox ActiveMIL-Lite libraries for image manipulation from the Matrox Meteor-II frame grabbers.
Tracker is programmed to work with the optics present on our Wild microscope but can be customized to work with other microscopes with minor software changes reflecting the appropriate magnification levels. For our microscope, each stage shift commanded by Tracker to re-center a worm is between 0.362 mm and 0.904 mm depending on the orientation and speed of the worm. Our BioPoint controller is programmed to move the stage with a starting speed of 6.3 mm/sec (= 10,000 pulses/sec with a 0.628 μm/pulse step size), an acceleration rate of 44.8 mm/sec2 (71,400 pulses/sec2), and a maximum run speed of 31.4 mm/sec (50,000 pulses/sec). However, because of the small distances traveled, we expect the stage to reach a maximum velocity of 8.5 mm/sec (13,500 pulses/sec) during a stage shift.
Recognizer2.1 calculates the location of the user-defined number of points (typically 13) along each worm's spine as follows: Recognizer2.1 identifies the center of the darkest portion of the image as its focus of attention and extracts a portion of the image surrounding the center point for further processing. Next, the extracted gray-scale image is turned into a binary image using a segmentation algorithm. The segmentation routine compares the ratio of pixel values resulting after applying two smoothing filters (sum of squared pixel values and square of summed pixel values, both in a typically 15 × 15 pixel neighborhood) against a user defined threshold. Pixels with pixel value ratios less than the threshold are "worm" while the others are "background." Connected regions in the binary image are labeled and Recognizer2.1 then selects the largest-area connected region as the worm in the image. Recognizer2.1 calculates the worm's boundary polygon with a user-defined number of vertices – typically 50 – by interpolating equidistant vertices along the chain of pixels on the perimeter of the worm region. Boundary polygon vertices are passed to Triangle [56], which generates constrained Delaunay triangulations across the worm boundary polygon. Finally, Recognizer2.1 connects the circumcenters of the resulting triangles to form segments of the worm's spine curve, along which Recognizer2.1 interpolates the 13 equally spaced "spine" points.
Feature extraction tools are written in Matlab and C++. Attributes are calculated as follows, described based on a typical analysis distributing 13 points along a worm's spine:
Speed attributes
Centroid Velocity (VELC)
Centroid velocity is a series of speed values, one for each pair of successive frames, and is calculated as the distance the worm's centroid moves between successive frames divided by the time between successive frames. We define the worm's centroid as the mean position of points 5–13 (approximately the rear two-thirds of the worm).
VELC = (Δ Centroid Position) / (Δ Time)
Sign of VELC describes forward (positive) or backward (negative) movement. Movement of the anterior one-third of the worm is ignored from this calculation (and the VEL calculation below) to minimize the effect of foraging behavior on speed.
Point Velocity (PTVEL)
Point velocity is a matrix of speed values, one for each of the 13 points for each pair of successive frames, calculated as the distance each point along a worm's spine moves between successive frames divided by the time between successive frames.
PTVEL = (Δ Point Positions [all 13 points]) / (Δ Time)
Signs of PTVEL describe each point's forward (positive) or backward (negative) movement. PTVEL describes the speed with which each point travels along the worm's serpentine path.
Velocity (VEL)
Velocity is a series of speed values, one for each pair of successive frames, calculated as the distance each point along a worm's spine moves between successive frames divided by the time between successive frames.
VEL = Mean of PTVEL's 5–13 for each pair of successive frames
Sign of VEL describes forward (positive) or backward (negative) movement. VEL describes mean speed of the worm's body along its sinusoidal path.
Forward or Backward Direction (MODE)
MODE is a series of flags indicating the signs of a worm's instantaneous speed attributes (VEL and VELC), that is, whether the worm is moving forward or backward. Mode is calculated automatically at the same time as speed attributes by comparing:
D1: mean of the distances between points 4–11 at time τ and their posterior neighbors, points 5–12 at time τ + 1
with
D2: mean of the distances between points 6–13 at time τ and their anterior neighbors, points 5–12 at time τ + 1
Forward movement is indicated by D1<D2; backward by D2<D1. The MODE flags can be either 1 (forward) or -1 (backward). (Note that the points distributed along a worm's spine are equidistant, so a non-moving worm would have no difference in the distance between neighboring points over time.)
Instantaneous Velocity Vector Direction (THETA)
The instantaneous velocity vector direction is calculated as the direction the worm's centroid moves between successive grabbed frames. (Calculated as:
THETA = arc tangent of the worm's X-Y displacement.)
Wave propagation attributes
Flex (FLEX)
We calculate the matrix of angles between each segment (that is, at each articulation point) for each frame by:
angle = acos [(V1x*V2x + V1y*V2y) / (|V1|*|V2|)]
where
V1 = first segment vector and
V2 = second segment vector
We define the FLEX at each articulation point as the maximum angle difference during each possible 32 frame (~6 second) time window; that is, the most positive angle minus the most negative angle.
Bending Frequency (FRE)
We apply the spectrogram function ("specgram") from Matlab's Signal Processing Toolbox to the matrix of bend angles calculated for FLEX. Specgram calculates a windowed discrete-time Fourier transform (short-time Fourier transform) for the changing angles for each articulation point using a sliding window 32 frames (~6 seconds) wide. We quote from Matlab's documentation for specgram: "specgram calculates the spectrogram for a given signal as follows: 1. It splits the signal into overlapping sections and applies the window specified by the window parameter to each section. 2. It computes the discrete-time Fourier transform of each section with a length nfft FFT to produce an estimate of the short-term frequency content of the signal; these transforms make up the columns of B. The quantity (length(window) – numoverlap) specifies by how many samples specgram shifts the window. 3. For real input, specgram truncates the spectrogram to the first nfft/2 + 1 points for nfft even and (nfft + 1)/2 for nfft odd." The magnitude of the function indicates the relative energies of the signal's component frequencies. We take the highest magnitude (non-constant) component frequency as the characteristic frequency of that time-window of angles. (If two or more frequencies share the highest magnitude, the lower frequency is identified as the characteristic frequency.)
Time Delay (PHS)
For the time delay calculation, the program correlates anterior bend angles with posterior bend angles occurring at later time using a Dynamic Time Warping function. The program then uses these correlations to calculate the time required for the posterior bend to reach the same angle as its anterior neighbor.
Track waveform attributes
Track Amplitude (AMPT)
The program aligns the major axis of a best-fit bounding box with the worm's instantaneous velocity vector. The width of the bounding box (its minor axis) is taken as the instantaneous wormtrack waveform amplitude.
Track Wavelength (WAVELNTH)
We apply a rotation and translation transform to the spine of the worm from every frame to mathematically align each worm with y = 0 using the instantaneous velocity vector as the worm's centerline:
We create a matrix w containing the XY coordinates of the 13 points for a worm's spine and create a translation transform that we will use to center the worm's midpoint at the XY origin:
We also create a rotation transform to align the instantaneous velocity vector (with angle theta), to y = 0:
We multiply the two matrices to create a convenient combined transform
C = B*A;
and finally multiply our matrix by the combined transform matrix
ww = C*w;
which yields a matrix ww with the rotated and aligned coordinates for the 13 points. We perform a spatial Fast Fourier Transform (FFT, using Matlab's built-in fft function) on the rotated "spine" of each worm, using the varying y-values as the "signal" with their corresponding x-position values defining the signal to be in a spatial (rather than temporal) domain. By working in the spatial domain, the result from our FFT is in cycles per mm. The inverse of this result is the track wavelength, in mm per cycle.
Morphology attribute
LEN (spine length)
Sum of the distances between the points distributed along the worm's spine with each point-to-point distance calculated by (Δ x2 + Δ y2)0.5
Data Analysis and Comparison tools are written in Matlab. Our most common tool is called Histograms, which produces a set of charts displaying distributions of measures of behavior: Velocity, Centroid Velocity, Bending Frequency, Flex, Time Delay, Track Amplitude, Track Wavelength, Length-Normalized Track Amplitude, and Length-Normalized Track Wavelength.
To create a histogram curve for a given metric, for example a velocity histogram curve, we sort (or 'bin') each worm's velocity data into discrete ranges (or 'bins'). For velocity we use 'bins' that are 0.03333 mm/sec wide, i.e. bins would represent 0 to 0.03333 mm/sec, another 0.03333 to 0.06666 mm/sec, and so on. Bin sizes for each parameter are as follows: Point and Centroid Velocity, 0.03333 mm/sec; Flex, 0.1 radian; Frequency, 0.16665 Hz; Time Delay, 0.075 sec; Track Amplitude, 0.01 mm; Track Wavelength, 0.05 mm; Length-Normalized Track Amplitude, 1% mean body length; Length-Normalized Track Wavelength, 5% mean body length.
Again using our velocity example, the frequency of occurrence for the number of velocity values in each bin is normalized to a percent of velocities observed for that worm, and the normalized velocity distribution is added to a list of the other normalized velocity distributions for that population. (Normalizing each worm's data affords each worm equal mathematical significance.) The final histogram curve for the population is generated by plotting the mean value of each data bin's normalized frequency of occurrence (on the y-axis) versus the bin value (on the x-axis) which shows us the proportion of worms that exhibited each velocity. The same method is used for creating the histogram curves for each metric, naturally selecting bin sizes appropriate for the data in question:
Statistical analysis
Standard statistical tests were performed using Matlab functions. Each p-value reported was from a one-way analysis of variance (ANOVA) comparing the distribution of mean values (one per individual) from each population of worms against that of each other population; each ANOVA tested the null hypothesis that the mean of the mean values from each populations were the same. Unless otherwise noted, statistical tests were performed on data from worms only when moving forward. For the toxicant concentration-response data, curves were fit by non-linear regression using Prism (GraphPad Software) sigmoidal dose-response equation with variable slope.
Availability of source code
Source code is available through a GPL at
Documentation of this software is available as a pdf from
Contributions of authors
SM, JB, JM and PS conceived and designed the original automated system for tracking and movement measurement. SM developed a working prototype system and brought in the key algorithms used. CC wrote most of the code in the current release. JM developed the protocol for the plate assay, and devised the dose-response and genetic experiments. RS conceived of applying automated analysis of C. elegans movement for toxicology studies, YK performed most of the toxicology experiments. JM, CC, RS and PS analyzed the data. CC, JM, and PS wrote the paper. All authors read and approved the final manuscript.
Acknowledgements
We thank X. Xu for suggesting length normalization, Jonathan Shewchuk for Triangle, and anonymous reviewers for many helpful suggestions. Supported by grants from the ONR (S.B.), DARPA (R. S.) and Howard Hughes Medical Institute, with which PWS is an Investigator.
==== Refs
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| 15698479 | PMC549551 | CC BY | 2021-01-04 16:38:18 | no | BMC Genet. 2005 Feb 7; 6:5 | utf-8 | BMC Genet | 2,005 | 10.1186/1471-2156-6-5 | oa_comm |
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BMC PhysiolBMC Physiology1472-6793BioMed Central London 1472-6793-5-31569400710.1186/1472-6793-5-3Research ArticleTroglitazone, a PPAR-γ activator prevents endothelial cell adhesion molecule expression and lymphocyte adhesion mediated by TNF-α Sasaki Makoto [email protected] Paul [email protected] Tomas [email protected] Alireza [email protected] Takashi [email protected] Makoto [email protected] John W [email protected] J Steven [email protected] Department of Molecular and Cellular Physiology, LSU Health Sciences Center, Shreveport, LA, 71130, USA2 Department of Gastroenterology, LSU Health Sciences Center, Shreveport, LA, 71130, USA3 Department of Neurology, LSU Health Sciences Center, Shreveport, LA, USA, 71130, USA4 Nagoya City University Graduate School of Medical Sciences, Departments of Internal Medicine and Bioregulation, Nagoya City University Graduate School of Medical Sciences, 1-Kawasumi-Mizuho, Nagoya 467-8601, Japan2005 6 2 2005 5 3 3 23 8 2004 6 2 2005 Copyright © 2005 Sasaki 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
Cytokine mediated induction of the mucosal addressin cell adhesion molecule-1(MAdCAM-1) expression is associated with the onset and progression of inflammatory bowel disease (IBD).
Results
Using western blotting and cell-based ELISA, we show in this study that troglitazone, an activator of the peroxisome proliferator-activated receptor-γ (PPAR-γ), widely used in the treatment of diabetes, has as well recently been highlighted as protective in models of inflammation and cancer. We found that troglitazone (10–40 μM), significantly reduced the TNF-α (1 ng/ml) mediated induction of endothelial MAdCAM-1 in a dose-dependent manner, achieving a 34.7% to 98.4% reduction in induced MAdCAM-1. Trogliazone (20μM) reduced TNF-α induced VCAM-1, ICAM-1 and E-selectin expression. Moreover, troglitazone significantly reduced α4β7-integrin dependent lymphocyte adhesion to TNF-α cultured endothelial cells.
Conclusions
These results suggest that PPAR-γ agonists like troglitazone may be useful in the clinical treatment of IBD.
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Background
Endothelial cell adhesion molecules or 'ECAMs' play essential roles in the development of chronic inflammation by recruiting leukocytes, especially lymphocytes through their ability to promote leukocyte rolling, firm adhesion and extravasation [15]. Tissue infiltration by leukocytes is a common hallmark in several chronic inflammatory states which include the inflammatory bowel diseases, ulcerative colitis (UC), and Crohn's disease (CD), but also several other chronic inflammatory states such as arthritis, lupus, diabetes [17,47,58]. In the setting of IBD, the expression of ECAMs like ICAM-1, VCAM-1, and MAdCAM-1 is observed in experimental models of colitis, [11,33,34,48] and also within the inflamed human colon in Crohn's disease and ulcerative colitis [3,49]. Among the adhesion molecules that are up-regulated in IBD, MAdCAM-1, the mucosal cell adhesion molecule is thought to be preeminent in the development of chronic gut inflammation. MAdCAM-1 is normally expressed in the gut, and its expression is dramatically increased during inflammation [11,48]. The functional significance of increased expression of MAdCAM-1 in IBD is supported by several reports which demonstrate that immunoneutralization of either MAdCAM-1 or its lymphocyte ligand, the α4β7 integrin, attenuate inflammation and mucosal damage in a variety of animal models of colitis [14,24,55]. However, since monoclonal antibodies directed against other ECAMs, particularly VCAM-1, can as well reduce disease activity in animal models of colitis [2,16,46,53], the literature suggests that MAdCAM-1 is probably necessary, but insufficient for the maximal penetrance of experimental and clinical IBD. Based on these results, it is apparent that an improved understanding of the mechanisms regulating ECAM expression, especially MAdCAM-1, might help to design improved therapies for colitis.
Peroxisome proliferator-activated receptors (PPARs) are members of the nuclear hormone receptor superfamily of transcription factors, whose activities are regulated through the high affinity binding of small lipophilic ligands that include steroid hormones [29]. A new class of antidiabetic drugs, known as 'glitazones' which includes troglitazone, rosiglitazone, and pioglitazone, have been developed as agonists that bind to the gamma (γ)-subtype of the PPARs. While glitazones have been extensively used in the treatment of diabetes, several investigators have now demonstrated that PPAR-γ ligands will markedly reduce colonic inflammation of in two different mouse models of colitis [12,51]. In addition, glitazones provide some benefit in the treatment of ulcerative colitis in humans as well [27].
Although PPAR-γ is expressed at high levels in adipose tissues, PPAR-γ has also been described in many other kinds of cells, including those in the vasculature like endothelial cells, vascular smooth muscle cells and monocytes and macrophages [19]. Although it not yet completely clear, the literature suggests that glitazones may be therapeutic in these models through the ability of these PPAR-γ activators to inhibit several events in inflammation particularly leukocyte infiltration into tissues mediated by NF-kB-dependent ECAM expression [6,21,32,38,51].
However, the literature does not uniformly support protective roles for all PPARs. For example, it has been suggested that activation of PPAR-α, rather than PPAR-γ activation is responsible for blocking cytokine induced ECAM expression [30,41] and these differences may reflect tissue- and/or species specific responses to glitazones. Regardless, glitazones might be therapeutic in the setting of IBD through their ability to restrict expression of MAdCAM-1, one of the more important regulators of gut inflammation in IBD. However, this has not yet been investigated.
In the present study we have examined the ability of a candidate glitazone PPAR-γ ligand, troglitazone, to limit cytokine induction of MAdCAM-1 and also VCAM-1, ICAM-1 and E-selectin, and decrease MAdCAM-1 dependent lymphocyte endothelial adhesion in vitro.
Results
PPAR-γ expression by endothelial cells
To confirm the presence of PPAR-γ on SVEC endothelial cells, western blotting for PPAR-γ was performed using an antibody generated to a synthetic peptide corresponding to amino acid residues 284–298 of murine PPAR-γ; importantly, this antibody exhibits no significant homology to PPAR-α. This antibody recognized a PPAR-γ specific band at 55 kD by western blotting in SVEC cells (Fig. 1).
TNF-α induced MAdCAM-1 protein expression is reduced by troglitazone, a PPAR-γ ligand
To examine the effect of PPAR-γ activation on endothelial cell inflammatory responses, SVEC endothelial cells were treated with TNF-α either with or without a pre- and co-treatment with troglitazone. TNF-α (1 ng/ml, 24 h) increased MAdCAM-1 expression to 13.4 times that of the untreated control level. This TNF-α induced MAdCAM-1 was dose dependently attenuated by pre- and co-treatment with troglitazone (i.e. from 69% to 7% of TNF-α stimulated levels) at concentrations of 10 to 40 μM (Fig. 2). At 40 μM troglitazone, the MAdCAM-1 expression (7% of TNF-α stimulated) was not significantly different from untreated controls. Troglitazone alone did not alter the expression of MAdCAM-1 (data not shown). Troglitazone was not overtly toxic, and did not affect cell protein content (i.e. protein content per well), or change the expression of either actin or vimentin, two cell structural proteins (measured by total protein staining of transferred western blots) (data not shown).
To examine the effect of troglitazone on other ECAMs expression stimulated by TNF-α surface expression assay was performed.
TNF-α induced VCAM-1 protein expression is reduced by troglitazone, a PPAR-γ ligand
TNF-α (1 ng/ml, 24 h) enhanced VCAM-1 expression to 8.5 times that of untreated controls. This elevated expression was significantly reduced (to only 80% of the TNF-α stimulated level) by troglitazone at 20 μM (Fig. 3). Alone, this compound had no effect on the expression of VCAM-1 (Fig. 3).
TNF-αinduced ICAM-1 protein expression is reduced by troglitazone, a PPAR-γ ligand
TNF-α (1 ng/ml, 24 h) increased ICAM-1 expression to a level 4.7 times greater than untreated control levels. This TNF-α enhanced ICAM-1 expression was strongly attenuated (to 32% of the TNF-α stimulated level) by troglitazone at 20 μM (Fig. 4). Again, troglitazone alone had no effect on the expression of ICAM-1 (Fig. 4).
TNF-α induced E-selectin protein expression is reduced by troglitazone, a PPAR-γ ligand
TNF-α (1 ng/ml, 24 h) increased the expression of E-selectin 4 times over untreated control levels; this increase in E-selectin was also blocked by troglitazone (to 22% of the TNF-α stimulated level) at 20 μM (Fig. 5). Alone, troglitazone had no effect on E-selectin expression (Fig. 5).
Adhesion of α4β7 expressing lymphocytes to TNF-α stimulated endothelium
Having established that troglitazone exerts a significantly protective effect against TNF-α stimulated endothelial MAdCAM-1 induction, we examined the effects of troglitazone on the adhesion of α4β7 expressing mouse lymphocytes (using the cell line TK-1) to endothelial monolayers following TNF-α treatment. TNF-stimulation (24 h) significantly increased the adhesion of TK-1 lymphocytes to SVEC monolayers. Troglitazone (20 μM) significantly reduced TK-1 adhesion in response to TNF-α stimulation at 24 h (Fig. 6). Troglitazone did not modify the basal level of lymphocyte adhesion to the endothelium without TNF-α treatment.
TNF-α induced phosphorylation of NF-kB p65 is prevented by troglitazone, a PPAR-γ ligand
Mechanistically, the expression of all of these adhesion molecules is known to depend on the activation of NF-kB following TNF-α stimulation. Therefore, we examined whether troglitazone-mediated protection against TNF-α induced MAdCAM-1 expression and lymphocyte adhesion were related to the activation and/or inhibition of NF-kB. In this study, phosphorylation of the p65 subunit of NF-kB was used as an index of NF-kB activation. TNF-α (1 ng/ml, 1 h) induced the phosphorylation of NF-kB p65; this activation was significantly reduced by the PPAR-γ ligand, troglitazone at 20 μM (Fig. 7). Alone, troglitazone significantly attenuated the phosphorylation of NF-kB p65 compared to untreated controls (Fig. 7).
Discussion
MAdCAM-1 is a 60 KD endothelial cell surface molecule that is strongly expressed by mucosal endothelial cells, particularly following exposure of these cells to pro-inflammatory cytokines such as TNF-α. Expression of MAdCAM-1 has as well been reported in the brain, and in the heart, [23,47], and based on these findings, it has now been suggested that MAdCAM-1 might play roles in chronic inflammation of these organs as well.
With respect to inflammatory bowel disease, MAdCAM-1 appears to be necessary for lymphocyte homing to mucosa associated lymphoid tissue [3-5,50]. Since MAdCAM-1 is normally expressed within the gut microvasculature, and is dramatically increased during IBD, it has been suggested that increased MAdCAM-1 expression participates in the etiology of IBD through its ability to control homing of lymphocytes to the gut. This notion is supported by several observations that show that antibodies directed against either MAdCAM-1, or its lymphocyte ligand, the α4β7 integrin will significantly attenuate several indices of injury in experimental models of colitis [24,39].
TNF-α is thought to be perhaps the most important cytokine responsible for driving the onset and progression of IBD. Because of this primary role of TNF-α in IBD, anti-TNF-α antibody therapy has been successfully used in IBD to reduce both colonic injury and expression of ECAMs in IBD [1]. While TNF-α significantly increased the expression of MAdCAM-1, it also increases the expression of intercellular cell adhesion molecule-1 (ICAM-1), vascular cell adhesion molecule-1 (VCAM-1), E-selectin, P-selectin [15,37]. It should be noted that in colitis, all of these adhesion molecules are elevated in the colon [25], and likely contribute to the development of chronic gut injury.
This is the first study to demonstrate that a PPAR-γ ligand, troglitazone, can significantly reduce the expression of MAdCAM-1, an endothelial cell adhesion molecule which is closely linked to chronic gut inflammation. Troglitazone significantly reduced TNF-α induced expression of several other ECAMs as well [6,21,30,32,38,41,57], and decreased the adhesion of α4β7-expressing lymphocytes (TK-1) to TNF-α stimulated endothelium. Since at least 50% of the adhesion of these lymphocytes to TNF-stimulated endothelium is MAdCAM-1-dependent [35], our results suggest that MAdCAM-1 mediates most of the stimulated adhesion, with more minor contributions from other ECAMs. The results strongly support a novel therapeutic action of PPAR-γ activators like troglitazone which might explain their beneficial effects PPAR-γ agonists in murine models of colitis [12,51] and in human ulcerative colitis [27].
NF-kB is a member of the Rel family of dimeric transcription factor complexes key transcription factor that modulates expression of MAdCAM-1 in inflammation, and is governs the expression of several other endothelial adhesion molecules in response to cytokines [9,22,33,35,40,52]. Prior to cytokine stimulation, NF-kB is restricted to the cytosol as an inactive complex with its inhibitor, Ik-B. Upon activation by cytokines, Ik-B is phosphorylated, dissociates from the NF-kB, and is subsequently ubiquitinated and degraded. This allows active NF-kB to enter the nucleus and bind kB consensus regulatory elements in the promoters of the genes for several ECAM (ICAM-1, VCAM-1, E-selectin, and MAdCAM-1) [9,33-36,54]. NF-kB can be activated through several kinases including IkB kinases (IKKs). IKKs phosphorylate IkB, but also phosphorylate the p65 NF-kB subunit on Serine-536 as part of the activation of the NF-kB complex. Phosphorylation of the p65 subunit is an important step in the activation of the NF-kB complex which permits this complex to enter the nucleus and activate NF-kB dependent genes [45]. Consequently, phosphorylation of p65 has been proposed as a simple index of NF-kB activation [45], although it may not be as sensitive as the electrophoretic mobility shift assay (EMSA).
PPAR-γ ligands like troglitazone apparently suppress activation of NF-kB, and in our hands reduce both basal and TNF-stimulated NF-kB p65 phosphorylation (figure 7). Consequently, glitazones like troglitazone should reduce the expression of both cytokines and ECAMs driven by NF-kB [6,41,57]. Interestingly, under control culture conditions, we observe basal phosphorylation of p65, suggesting that normally, p65 is at least partially activated. This may be related to the role of basal NF-kB activity in maintaining cell survival and blocking apoptosis [8,42]. Since excessive inhibition of NF-kB can propel cells into apoptosis, agents like troglitazone, (which may inhibit NF-kB) could have a limited therapeutic window, and should be administered cautiously. However, under the conditions used in our study, (10–40 μM) we did not see evidence for the loss of cell viability assessed by trypan blue staining; all cells remained >99% viable by this method. In addition, the concentration of troglitazone in our study (10–40 μM) is near the therapeutic level since the physiological levels of glitazones, like troglitazone are 5–20 μM, with an average dose of 15 μM [28].
PPAR-γ ligands like glitazones should not only attenuate MAdCAM-1, but also diminish the expression of other ECAMs like ICAM-1, VCAM-1 and E-selectin. This reflects a decrease in the synthesis of some, but not all proteins, since densitometry of troglitazone treated monolayers shows no difference in total protein content between wells following troglitazone, but western blotting or surface expression assay find a significant decrease in the expression of ECAMs.
While studies with glitazones in endothelial models for the most part demonstrate an inhibition of ECAMs such as ICAM-1 in response to TNF-α [10,38], Chen et al. [6,7] have reported that the ECV304 cell line showed an increase in the expression of ICAM-1 in response to troglitazone. This stands in sharp contrast to our current study. However, since The ECV304 cell line has been mistakenly designated as 'endothelial' in many cases, (and is actually a bladder carcinoma in many instances) [56], those results may be called into question.
It is also possible that PPAR-γ activators might well affect inflammation through NF-kB independent pathways. Some described PPAR-γ ligands, like the cyclopentanone prostanoids, exert anti-inflammatory effects through a PPAR-γ-independent pathways [43] specifically the inhibition of the IKK beta subunit which would suppress NF-kB activation. Further, troglitazone also activates ERK1/2 [20] and blocks c-fos synthesis [6] which could also modulate these effects. Therefore, we cannot completely exclude the possibility that troglitazone similarly protects in these models through direct inhibition of IKK, as well as indirect blockade through PPAR-γ.
Since high levels of PPAR-γ protein are expressed within the colon, [13] it is possible that agonists for this pathway could have an important role in the regulation of normal colon functioning and disease progress.
Conclusions
Our results indicate that troglitazone and other glitazones may provide an effective means of treating forms of chronic inflammation including inflammatory bowel disease through their ability to interfere with steps in the activation of NF-kB, effectively blocking the expression of adhesion molecules like MAdCAM-1 which increase infiltration of tissues by leukocytes.
Methods
Reagents
Recombinant mouse TNF-α was purchased from ENDOGEN (Stoughton, MA), and troglitazone was provided as a generous donation from Sankyo corp., Japan.
Cell culture
The SVEC4-10 line is an endothelial cell line derived by SV40 (strain 4A) transformation of murine small vessel endothelial cells, originally isolated from the axillary lymph node vessels of an adult male C3H/Hej mouse [4,5]. These cell types were all maintained in Dulbecco's modified Eagle's medium (DMEM) with 10% fetal calf serum with 1% antibiotic/ antimycotic. Cells were seeded into 24-well tissue culture plates at approximately 20,000 cells/cm2, and cultures were used immediately upon reaching confluence (usually 3–4 days after seeding).
Lymphocytes
The mouse CD8+ T cell lymphoma TK-1 cells (that constitutively expresses the α4β7 integrin [44] were obtained as a generous gift from Dr. Eugene Butcher (Stanford University, CA). These cells were cultured in RPMI-1640 medium supplemented with 10% FCS and 0.05 mM 2-mercaptoethanol (minus antibiotic/ antimycotic).
PPAR-γ expression on SVEC endothelial cell – Western analysis of cell lysates
Cell lysates were electrophoretically separated on 7.5% SDS- PAGE gels, transferred to nitrocellulose, blocked and incubated in primary anti-PPAR-γ synthetic peptide (Affinity Bioreagents Inc., Golden, CO) at a 1: 500 dilution overnight (4°C). Membranes were washed 2× with wash buffer. Secondary goat anti-rabbit horseradish peroxidase conjugated secondary antibody (Sigma) was added at a 1:2,000 dilution for 1 h. Membranes were washed 3 times and developed using the ECL detection system (Amersham, La Jolla, CA).
Western analysis of cell lysates
Monolayers were either pretreated (1 h) with blockers, and then incubated with cytokines (24 h), or treated without test agents and then treated with cytokines (24 h). All cell samples were harvested at 24 hours. Equal quantities of protein (75 μg) from each sample were electrophoretically separated on 7.5% SDS- PAGE gels. Gels were transferred to nitrocellulose membranes (Sigma) and blocked with 5% milk powder in PBS at 4°C (overnight). These membranes were washed twice for 10 min with wash buffer (0.1% milk powder in PBS). Primary rat anti-mouse MAdCAM-1 mAb (MECA 367; generous gift from Dr. Sharon Evans, RPMI, NY) was added at a concentration of 10 μg/ml and incubated at room temperature for 2 h. In p65 NF-kB phosphorylation studies, membranes were incubated with anti-phospho p65 antibody (Cell Signaling Technology, Beverly, MA) diluted 1:1000 overnight (4°C). These membranes were washed twice with wash buffer. Secondary goat anti-rat horseradish peroxidase conjugated secondary antibody (Sigma) was added at a 1:2000 dilution for 2 h for MAdCAM-1, while goat anti-rabbit antibody was used for detecting phospho-p65 NF-kB. Lastly, membranes were washed 3 times and developed using the enhanced chemiluminescence (ECL) detection system. The density of MAdCAM-1 staining was measured by scanning the 60 KD band, using a HP ScanJet™ flatbed scanner. Images were analyzed for density using Image Pro Plus™ image analysis software (Media Cybernetics, Silver Springs, MD). The data are expressed as a percentage of TNF-α-induced level of density.
Endothelial cell surface adhesion molecule expression assay
Surface expressions of ECAMs were measured using the method of Khan et al. [26]. SVEC monolayers were grown in 48-well plates as described and were pretreated (1 h) with troglitazone and of 1 μg/ml in HBSS/PBS + 5% FCS at 37°C for 30 min. Monolayers were then washed twice with 0.5 ml HBSS/PBS, and incubated with horseradish peroxidase conjugated rabbit anti-rat IgG (1:2,000 diluted, Sigma) in HBSS/PBS + 5% FCS at 37°C for 30 min. Monolayers we then co-treated with TNF-α (1 ng/ml) at 37°C in medium for 24 h. The cells were washed three times with 0.5 ml HBSS/PBS [1:1] at 24 hours, and monolayers incubated with anti-mouse VCAM-1, anti-ICAM-1 or anti-E-selectin. All antibodies were added to cultures after treatment at a concentration re washed four times with 0.5 ml HBSS/PBS followed by incubation with 0.25 ml of 0.003% hydrogen peroxide + 0.1 mg/ml 3, 3', 5, 5'-tetramethlbenzidine (Sigma) at 37°C for 60 min in the dark. The color reaction was stopped by adding 75 μl of 8 N H2SO4, and the samples were transferred to 96-well plates. Plates were read on a Titertek MCC340 plate reader (Titertek Instruments, Inc., Huntsville, AL) at 450 nm. Blanking (i.e. background) was performed on monolayers stained only with second antibody and reacted as above.
TK-1 lymphocyte adhesion assay
Briefly, TK-1 cells were suspended in culture medium and fluorescence labeled by incubating TK-1 cells at 2 × 106 cells/ml with 0.02 mg fluorescein diacetate (FDA) (Sigma) at 37°C for 30 min. The cells were then washed twice with ice-cold HBSS, spun at 250 g for 5 min to remove unincorporated fluorescence and suspended in HBSS. The TK-1 lymphocyte cell line used in this assay expresses high levels of the α4β7 integrin, [35,44] which can interact with multiple ligands including mucosal addressin-1 (MAdCAM-1), as well as VCAM-1, L-selectin and fibronectin [18]. In this system, TNF stimulated TK-1 adhesion to SVEC4-10 endothelial cells is at least 50% MAdCAM-1 dependent [35]. SVEC monolayers were grown in 48-well plates as described, and to activate endothelium, the monolayers were incubated with TNF-α (1 ng/ml) for 24 h. Cytokine treated endothelial cells were washed three times with media. Labeled TK-1 cells were then added to the endothelium at a 5:1 lymphocyte to endothelial cell ratio [31] and allowed to bind for 30 min under static conditions. At the end of the incubation period, the supernatant was removed and the Monolayers were washed twice with HBSS. Plates were read on a Fluorescent Ascent (Lab systems, Helsinki, Finland) set for excitation at 485 nm, and emission at 515 nm. Blank wells (0% TK-1 adhesion) were run as controls that did not contain labeled TK-1 cells; 100% adhesion was measured on monolayers where TK-1 cells were not removed from the supernatant.
Abbreviations
PPAR-γ – peroxisome proliferative activated receptor gamma
MAdCAM-1 – Mucosal Addressin Cell Adhesion Molecule-1
VCAM-1 – Vascular Cell Adhesion Molecule-1
E-selectin – Endothelial Selectin
ICAM-1 – Intercellular Adhesion Molecule-1
IBD – Inflammatory Bowel Disease
TNF-α – Tumor Necrosis Factor-α
Authors' contributions
Dr. Sasaki accomplished the studies described in this manuscript, all authors contributed equally in the design, interpretation and execution of this article.
Acknowledgments
The authors would like to acknowledge Mr. Michael Harper for outstanding literary assistance with this manuscript.
Grant Support. This work supported by NIH DK43785 and a grant in aid from the American Heart Association.
Figures and Tables
Figure 1 PPAR-γ expression in SVEC endothelial cell. Western blotting for PPAR-γ in SVEC cells reveals a 55 kD band after reacting with anti-PPAR-γ peptide antibody, indicating that PPAR-γ is in fact present within the cells used in this study.
Figure 2 TNF-α induced MAdCAM-1 protein expression is reduced by troglitazone, a PPAR-γ ligand. TNF-α (1 ng/ml, 24 h) induced MAdCAM-1 expression was dose dependently blocked by the PPAR-γ ligand, troglitazone at concentrations between 10 to 40 μM (Fig. 2).
Figure 3 TNF-α induced VCAM-1 protein expression is reduced by troglitazone, a PPAR-γ ligand. TNF-α (1 ng/ml, 24 h) induced VCAM-1 expression was also blocked by the PPAR-γ ligand, troglitazone at 20 μM (Fig. 3). Alone, this compound had no effect on the expression of VCAM-1 (Fig. 3).
Figure 4 TNF-α induced ICAM-1 protein expression is reduced by troglitazone, a PPAR-γ ligand. TNF-α (1 ng/ml, 24 h) induced ICAM-1 expression was dose dependently blocked by the PPAR-γ ligand, troglitazone at 20 μM (Fig. 4). Alone, this compound had no effect on the expression of ICAM-1 (Fig. 4).
Figure 5 TNF-α induced E-selectin protein expression is reduced by troglitazone, a PPAR-γ ligand. TNF-α (1 ng/ml, 24 h) induced E-selectin expression was blocked by the PPAR-γ ligand, troglitazone at 20 μM (Fig. 5). Alone, this compound had no effect on the expression of E-selectin (Fig. 5).
Figure 6 Adhesion of α4β7 expressing lymphocytes (TK-1) to TNF-α stimulated endothelium. TNF-α stimulation (24 h) significantly increased adhesion of TK-1 lymphocytes to monolayers of SVEC cells. Troglitazone (20 μM) significantly reduced TK-1 adhesion in response to TNF-α stimulation at 24 h (Fig. 6).
Figure 7 TNF-α induced phosphorylation of NF-kB p65 is prevented by troglitazone, a PPAR-γ ligand. TNF-α (1 ng/ml, 1 h) induced phosphorylation of NF-kB p65 was significantly attenuated by the PPAR-γ ligand, troglitazone (20 μM). Alone, troglitazone also attenuated phosphorylation of NF-kB p65.
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| 15694007 | PMC549552 | CC BY | 2021-01-04 16:03:51 | no | BMC Physiol. 2005 Feb 6; 5:3 | utf-8 | BMC Physiol | 2,005 | 10.1186/1472-6793-5-3 | oa_comm |
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BMC Struct BiolBMC Structural Biology1472-6807BioMed Central London 1472-6807-5-31570117710.1186/1472-6807-5-3Research ArticleDeciphering structure and topology of conserved COG2042 orphan proteins Armengaud Jean [email protected] Alain [email protected] Olivier [email protected] Jean-Luc [email protected] Eric [email protected] CEA-VALRHO, DSV-DIEP-SBTN, Service de Biochimie post-génomique & Toxicologie Nucléaire, Bagnols-sur-Cèze, France2005 8 2 2005 5 3 3 13 10 2004 8 2 2005 Copyright © 2005 Armengaud 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 cluster of orthologous group COG2042 has members in all sequenced Eukaryota as well as in many Archaea. The cellular function of these proteins of ancient origin remains unknown. PSI-BLAST analysis does not indicate a possible link with even remotely-related proteins that have been functionally or structurally characterized. As a prototype among COG2042 orthologs, SSO0551 protein from the hyperthermophilic archaeon Sulfolobus solfataricus was purified to homogeneity for biophysical characterization.
Results
The untagged protein is thermostable and behaves as a monomeric protein in gel filtration experiment. Several mass spectrometry-based strategies were combined to obtain a set of low resolution structural information. Kinetic data from limited proteolysis with various endoproteases are concordant in pointing out that region Glu73-Arg78 is hyper-sensitive, and thus accessible and flexible. Lysine labeling with NHS-biotin and cross-linking with DTSSP revealed that the 35 amino acid RLI motif at the N terminus is solvent exposed. Cross-links between Lys10-Lys14 and Lys23-Lys25 indicate that these residues are spatially close and in adequate conformation to be cross-linked. These experimental data have been used to rank multiple three-dimensional models generated by a de novo procedure.
Conclusion
Our data indicate that COG2042 proteins may share a novel fold. Combining biophysical, mass-spectrometry data and molecular model is a useful strategy to obtain structural information and to help in prioritizing targets in structural genomics programs.
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Background
Genomic comparative studies on entirely sequenced genomes from the three domains of life, i.e. Bacteria, Archaea and Eukaryota [1], evidenced that proteins involved in the organization or processing of genetic information (structures of ribosome and chromatin, translation, transcription, replication and DNA repair) display a closer relationship between Archaea and Eukaryota than between Bacteria and Eukaryota [2-4]. To identify new proteins involved in such important cellular mechanisms, an exhaustive inventory of proteins of unknown function common to only Eukaryota and Archaea but not in Bacteria has been devised [5-7]. Among such proteins, the Cluster of Orthologous Group COG2042 comprises proteins ubiquitously present in Eukaryota and present in many, but not all, Archaea; a hallmark of their ancient origin. The corresponding ancestral protein should have been present in the common ancestor of these two domains of life. Some partial experimental data are known from the Saccharomyces cerevisiae COG2042 homolog. Deletion of the Yor006c gene was shown to result in a viable phenotype but some apparent moderate growth defects were noticed on a fermentable carbon source [8,9]. Two putative protein partners for Yor006c were identified through a high-throughput two-hybrid study [10]: Ydl017w, a serine/threonine kinase also known as the cell division control protein 7 (Cdc7), and Yil025c, a hypothetical ORF. However, the cellular function of COG2042 proteins remains unknown.
A polar region, named RLI, is conserved at the N terminus of COG2042 proteins as well as at the N terminus of another cluster of orthologous proteins, namely COG1245. The latter, exemplified by SSO0287 in Sulfolobus solfataricus [11], are large proteins (about 600 residues) that encompass four different domains: a RLI domain, a [4Fe-4S] ferredoxin domain, and two ATPase domains, usually found in ABC transporter. Their putative function is currently subjected to discussion [12,13] but could be related to rRNA metabolism. Indeed, four of the eleven proteins shown to interact with the yeast COG1245 homolog (Ydr091c) were identified as involved in rRNA metabolism (Ymr047c, Ydl213c, Ylr340w, Ylr192c). Experimental data on the human homolog of Ydr091c indicated that this protein reversibly associates with RnaseL, and thus COG1245 proteins were named RNase L inhibitor [14].
Because knowledge of protein structure is of high importance to understand protein function, huge efforts have been recently invested in high-throughput protein structure determination programs [15]. Recent reports indicate that only a relatively small percentage of expressed and purified proteins are amenable to full 3D structure by NMR or crystallography and X-ray diffraction [16,17]. In silico modeling (homology modeling, fold recognition, ab initio and de novo modeling) is the alternative to quickly gain the fold of a protein. However, such approach sometimes remains ambiguous in reliably identifying correct structures for protein sequences remotely-related to those found in PDB database. A promising strategy is the use of experimental data (if possible easily obtained) for model discrimination or refinement [18-20]. For example, the tertiary structure of the bovine basic fibroblast growth factor (FGF)-2 was probed with a lysine-specific cross-linking agent and subjected to tryptic peptide mapping by mass spectrometry to identify the sites of cross-linking [21]. The low resolution interatomic distance information obtained experimentally allowed the authors to distinguish among threading models in spite of a relatively low sequence similarity (13 % of identical residues). Interestingly, the constant development of novel cross-linking reagents suitable for mass spectrometry [22] enables enrichment of cross-linked peptides facilitating such strategy. A chemical modification approach [23-26], in combination with limited proteolysis procedures [27,28], can also provide useful structural constraints [29] for model refinement.
A step further is to attempt such approaches with proteins having no detectable homologs. In order to get insight into the topology of COG2042 members and if possible to use these experimental data to discriminate among structural protein templates, we combined limited proteolysis, lysine labeling and cross-linking strategies. The protein SSO0551 from the hyperthermophilic archaea Sulfolobus solfataricus was chosen as a prototype because of its thermostability and the probable absence of post-translational modifications when produced as a recombinant form in Escherichia coli. The SSO0551 protein is monomeric with a low molecular mass (19 kDa). This size is easily amenable to characterization by mass spectrometry. Our results reveal that the polar RLI motif at the N terminus is probably structured and solvent exposed, pointing at a common trait between COG2042 and COG1245 proteins, this latter group being also conserved in Eukaryota and Archaea but absent in Bacteria. The accessible and flexible regions defined by limited proteolysis combined with lysine accessibility assessed by NHS-biotin labeling and DTSSP cross-linking allowed us to discriminate among ten top ranking de novo three-dimensional (3D) models.
Results
COG2042 comprises members exclusively from Eukaryota and Archaea
The sequence of SSO0551 from S. solfataricus was used as query in a PSI-BLAST database search to identify homologous proteins. A constant cutoff expectation value of 10-15 resulted after three iterations in selection of 40 sequences (15 from Archaea and 25 from Eukaryota) that were all aligned over their full length. No close homologs (E-value below 10-10 in the third iteration) with full-length sequence matching to SSO0551 were found among Bacteria. Remarkably, all completely sequenced Eukaryal organisms were found to have one SSO0551 homolog. Fig. 1 shows an unrooted phylogram of the updated COG2042 family (Fig. 1A) and an alignment of a selection of six representative sequences (Fig. 1B), selected on the basis of their phylogenetic distribution. When experimental evidences concerning the protein are unfortunately lacking for ORF description genome annotators usually take into consideration the most upstream initiation codon. For this reason, the most probable start codons of several open reading frames should be reconsidered after exhaustive alignment (Fig. 1). For example, atg codon starting at nucleotide 484790 on the Crick strand for SSO0551 from S. solfataricus (NC_002754) should be a more appropriate start codon than atg starting at nucleotide 484916 and mentioned erroneously in current database. From the unrooted phylogram (Fig. 1A), two main lineages (archaeal and eukaryal) can be defined based on organism origin. This suggests that occurrence of these proteins is at least as ancient as divergence of these two phyla. No paralogs, sign of a possible evolution of a new derived function, have been evidenced in entirely sequenced organisms currently available. Although these proteins are of ancient origin, the core sequence appears well conserved as observed in Fig. 1B. Thirty-three residues (38%) are found identical in the core central segment (out of 88 amino acids) between the most distant COG2042 orthologs, namely gi48852409 from Ferroplasma acidarmanus and gi6324579 from Saccharomyces cerevisiae (Fig. 1B). From the alignment, several conserved motifs that may be functionally crucial (cofactor or substrate binding, catalysis, or partner interactions) were detected. A conserved hexapeptide sequence, Val-Val/Ile/Leu-Asp/Glu-Cys-Ser-Trp (motif I in Fig. 1B), is found distant of 14–17 amino acids from another conserved motif of 25 amino acids containing 4 polar, 18 hydrophobic and 3 aromatic residues (motif II). Database searches with these motifs as queries did not allow identification of remotely-related proteins. All sequences from COG2042 encompass a stretch of 35 conserved amino acids upstream of the core common sequence. This motif, called RLI, is extremely polar (11 basic and 4 acidic residues) and is also found at the N terminus of another group of orthologous sequences, namely COG1245.
Expression in E. coli of two engineered SSO0551 constructs
From multiple sequence alignments, SSO0551 should encode a 166 amino acid polypeptide. An N-terminal 6His tagged recombinant construct (pSBTN-AB31) was engineered. As we could not exclude that the 42 amino acids extension at the N terminus was not an annotation artifact, we intended to check experimentally whether this putative extension could have some influence on SSO0551. A second construct (pSBTN-AB30) was simultaneously engineered supposedly allowing production of a 26 kDa N-terminal 6His variant. Unexpectedly, no major difference in expression was detected between the two cellular extracts when they were resolved on SDS-PAGE. Two overexpressed products with both an apparent molecular weight of approximately 20 kDa were obtained upon addition of IPTG (data not shown). Fingerprint identification of these two products was carried out by trypsin proteolysis and mass spectrometry. Table 1 shows the MALDI-TOF mass measurements recorded for the two samples. The tryptic peptides that were detected revealed that both products correspond to native SSO0551 sequence. From the 6His-SSO0551 product (pSBTN-AB31 construct), thirteen peptides map with the theoretical sequence (57 % sequence coverage). Noteworthy, a peptide (1590.64 amu) was attributed to part of the 6His-modified N terminus (Table 1). The twelve peptides recorded from the 6His-SSO0551 extended version (pSBTN-AB30 construct) fit only to the C terminus of the theoretical construct (43 % sequence coverage). These results along with low molecular weight observation on SDS-PAGE indicate that probably a truncated protein was obtained during expression of the ORF comprising the 126 nt 5'-extension (42 additional amino acids at the N-terminus). This product, corresponding in fact to untagged SSO0551 as confirmed hereafter with purified product, showed no binding on Ni-NTA chromatography. This observation is in agreement with absence of 6His tag at the N terminus.
Recombinant SSO0551 is structured, thermostable and monomeric
Crude extract containing native untagged SSO0551 polypeptide from E. coli Rosetta(DE3)(pLysS)(pSBTN-AB30) cells was heated at different temperatures. Proteins that remained soluble were analyzed on SDS-PAGE. Most of E. coli contaminants were removed by such treatment. SSO0551 polypeptide remained soluble even when cell extract was heated to 80°C and therefore this protein was considered as thermostable. This protein was purified to homogeneity by a three-step purification protocol. A 20 min heat treatment at 70°C (Fig. 2A, lane 3), followed by a Resource-S ion exchange chromatography (Fig. 2A, lane 4) and a Superdex75 gel filtration (Fig. 2A, lane 5), yielded approximately 1.6 mg of pure protein per L of culture. Purified protein was subjected to MALDI-TOF mass analysis. Fig. 2B shows the spectrum recorded. The experimental m/z of 19,198 measured for the monocharged polypeptide matches perfectly with theoretical average mass of native untagged SSO0551 protein (average mass of 19,197 Da). This measurement unequivocally confirmed that a truncated protein is produced using E. coli Rosetta(DE3)pLysS transformed with pSBTN-AB30. Both SDS-PAGE (Fig. 2A, lane 5) and MALDI-TOF spectrum (Fig. 2B) testify for homogeneity of the sample.
Content of secondary structure elements in SSO0551 was estimated by far-UV circular dichroïsm. Fig. 3 shows the spectrum recorded at 20°C. Purified protein presents negative ellipticity in the near-UV with minima at 208 (-14.7 103 deg cm2 dmol-1) and 222 nm (-12.7 103 deg cm2 dmol-1). Deconvolution of the CD spectrum leads to an estimation of secondary structural element content of about 28–29 % of α-helices and 14–16 % of β-sheets using K2D neural-software. Predictions of SSO0551 secondary structures by PSIPRED and Jpred web servers gave values of 10–11 % of β-sheets in relative agreement with the circular dichroïsm data, but overestimated the α-helix average content (54 %). PSIPRED and Jpred predictions are based on neural networks trained on known folds. The overestimation of the α-helix content may be due to the novel fold of these COG2042 proteins as discussed here below.
Native molecular mass of SSO0551 was determined by size-exclusion chromatography on a Superdex 200 HR10/30 calibrated column. Pure protein eluted as a peak centered at 39.1 mL in the assay conditions corresponding to an apparent molecular mass lower than 20 kDa. This elution profile indicates that this structured protein behaves as a compact monomer.
Limited proteolysis defines Glu73-Arg78 as a hyper-sensitive region
Purified SSO0551 protein was subjected to limited proteolysis with various endopeptidases (trypsin, chymotrypsin, ArgC and GluC). MALDI-TOF mass spectrometry was used to determine cleavage sites by following the time course generation of peptides. Several protease/substrate ratios were assessed to confirm which preferential sites on entire protein were first attacked (earliest cleavage), thus corresponding to a native state of the protein. The two fragments generated by such cleavage may be more vulnerable to subsequent attacks than native protein and therefore late proteolytic sites are considered less informative. Both small and large peptides generated during proteolysis were evaluated. Partial proteolyzed products obtained with trypsin were first resolved by reverse-phase chromatography and analyzed by MALDI-TOF mass spectrometry. Results recorded from direct analysis of the digestions without prior separation were almost similar to those obtained with separation. Therefore, the latter cost-effective strategy was used for analyzing the numerous conditions tested. Figure 4 shows the MALDI mass spectrum of the main large products obtained from a tryptic digest of SSO0551 (enzyme/protein ratio of 1:20) after 60 sec of reaction. In these conditions, the signal of intact protein was still visible at m/z 19198.4, but mixed with signals corresponding to 8 different large fragments. Among these, 7 peptides arose from an N-terminal proteolysis: [32–166], [35–166], [56–166], [57–166], [76–166], [79–166], [101–166] (Fig. 4). Such peptidic profile indicates that SSO0551 N terminus is rather solvent exposed in comparison to C terminus.
During the earliest events of the trypsin proteolysis analyzed in various conditions for detection of large products but also smaller peptides, monocharged cations with following m/z: 8614.6 amu, 10603.4 amu, 6489.8 amu, and 12724.1 amu, were attributed to fragments [1–75] (Δmass: -178 ppm), [76–166] (+89 ppm), [1–56] (+145 ppm), [57–166] (+200 ppm), respectively (data not shown). These data clearly indicate that Lys75 and Arg56 are two sites of early cleavage by trypsin. Identification of peptides Val32-Lys166 (15478.7 amu, -53 ppm) and Gly35-Lys166 (15191.2 amu, +153 ppm) also indicates that Arg31 and Lys34 could be two other initial nick-sites.
Similar experiments with endoproteinase Arg-C resulted in observation of two pairs of complementary peptides with m/z of 1920.9 amu ([1-15] +70 ppm) and 17296.8 amu ([16–166], -95 ppm) on one hand, 8998.1 amu ([1–78], -176 ppm) and 10217.5 amu ([79–166], +332 ppm) on the other hand. These data indicated that Arg78 and Arg15 are the main proteolyzed sites when ArgC enzyme was used. Chymotrypsin attacks SSO0551 native protein mainly at Phe74 because two complementary peptides with m/z of 8487.0 amu ([1–74], -249 ppm) and 10734.2 amu ([75–166], -157 ppm) were clearly evidenced. Glu73 is the main proteolyzed site when GluC protease was used, as peptides with m/z of 8338.7 amu ([1–73], -118 ppm) and 10880.0 amu ([74–166], +28 ppm) were detected. For all these analysis, smaller peptidic fragments that accumulated over time could be attributed from further proteolysis of the products arising from initial attacks (data not shown). All these results are concordant in pointing out that Glu73-Arg78 and Glu28-Arg31 are two accessible solvent-exposed regions of the protein as they can be proteolyzed by several endopeptidases, the first cited being definitively hyper-sensitive. Local unfolding not just surface exposure is necessary for efficient in vitro proteolysis because the polypeptide segment being cleaved must form a specific structure with the associated protease [30]. For this reason, Glu73-Arg78 region should also correspond to a flexible region, i.e. a protruding loop.
Lysine labeling with NHS-biotin and DTSSP cross-linking confirm that the N terminus is rather solvent-exposed
The SSO0551 protein contains 21 lysine residues (12 %) distributed along the whole polypeptide sequence. Under mild conditions that should keep the native conformation of the protein, specific labeling of these residues with NHS-biotin may give further details about their respective surface accessibility and/or their interactions with other residues [31]. After reaction with various amount of chemical reagent (molar ratio NHS-Biotin/total lysines of 1:40, 1:20, 1:10, 1:2, 1:1, 2:1), protein labeling was monitored by determining the mass of undigested samples. Figure 5 shows the signals measured by MALDI-TOF mass spectrometry for four of these ratios. The fact that some unmodified protein is still present at ratio below 1:20 testifies for mild conditions that should allow modification of protein still in a native state. As expected with NHS-biotin, each peak exhibits the predictable mass increment (average mass of 226.3 amu per label). Figure 5 shows that at molar ratio of 1:40 a simple modification is obtained, while a more heterogeneous population was detected for higher ratio. For examples, 1 to 3 modifications are detected at ratio 1:20, 2 to 5 modifications at ratio 1:2. However, a limited number of modifications (8–10) are recorded for higher ratio, indicating that among the 21 lysine residues only a fraction is accessible to the chemical.
To localize all labeled residues, NHS-biotin treated samples were subsequently subjected to proteolysis with various endoproteases (trypsin, Arg-C, or Glu-C) and compared to untreated samples. SSO0551 sequence coverage was estimated to be 92 % with all 21 lysine residues included in this coverage. Peptides (Δmass below 120 ppm) detected with NHS-biotin treated samples but not detected with untreated samples are listed in Table 2. Using limiting amount of NHS-biotin (molar ratios of 1:10, 1:20 or 1:40), nine reactive residues are unequivocally identified: Lys10, Lys14, Lys20, Lys23, Lys25, Lys51, Lys75, Lys128, and Lys154, assuming that proteases do not cleave after a modified residue. Other residues, such as Lys34 and Lys49 might be also labeled (Table 2). The number of labeled lysines is in agreement with the limited number of modifications recorded at higher ratio. Remarkably, spectra of whole peptide mixture were informative enough to give assignment of all modified peptides without the need of a purification step. Therefore, other amine reactive reagent that creates a mass shift could have been used.
Using a lysine cross-linking reagent, DTSSP, it is possible to assess intra- or inter-molecular protein contacts [21,32]. DTSSP enables cross-linking of amino groups up to 12 Å apart. As SSO0551 was shown to be monomeric and its concentration used in the assays was low (2.5 pM), intramolecular cross-links should be favored over intermolecular cross-links. In addition, the low reagent concentration used should avoid unwanted conformational changes that may be induced by multiple intramolecular cross-linking. After reaction with DTSSP, products were subjected to trypsin proteolysis and peptides were identified by MALDI-TOF. As the protein is relatively small, mass signals could be attributed with a good confidence (tolerance < 120 ppm). In addition, peak attribution was always confirmed upon reduction of products and sometimes through redundancy due to miss-cleavage. SSO0551 sequence coverage was 89%. The monoisotopic cations at m/z 1169.55, 2077.04, 2715.11 and 2871.14, detected for SSO0551 treated by DTSSP (ratio DTSSP/total polypeptide of 20:1) correspond in mass to addition of a DTSSP moiety on peptides [24-31] (Δmass tolerance: +16 ppm), [123–138] (-7 ppm), [57–78] (+61 ppm) and [56–78] (+82 ppm). Since trypsin does not cleave after a modified lysine, we conclude that Lys25, Lys75 and Lys128 were modified. After DTT treatment, peaks corresponding to the expected products (-103.993 amu theoretically) were detected at m/z 1065.46 (-109 ppm), 1973.03 (0 ppm), 2611.21 (-28 ppm) and 2767.26 (-45 ppm), respectively. Fig. 6 shows two monoisotopic [MH]+ ions at m/z 1491.76 and 1835.84 corresponding to intrapeptide cross-linked peptides: [21-31] (+31 ppm) and [3-15] (+3 ppm), respectively. These peptides contain two proximal lysine residues (Lys23-Lys25 and Lys10-Lys14). As shown in Fig. 6, these two peaks were absent in mass spectrum following DTT reduction but new peaks at m/z 1493.69 and 1837.81 appears at the expected increment (+2.016 amu theoretically). An additional peak at m/z 2502.22 could be attributed to peptide [35–55] (+37 ppm) with an intrapeptide cross-link between Lys49 and Lys51. However, the corresponding reduced peak was not detected. Strikingly, every lysines that were reactive with DTSSP were also detected by NHS-biotin labeling. Most modifications are located at the N terminus of the protein where five modified residues belong to the RLI motif.
Discussion
Although COG2042 proteins are distributed among a large number of organisms, no experimental evidences have yet been reported concerning their biochemical characterization and function. As they are not related, even remotely, to any other family of proteins, COG2042 members can be phylogenetically considered as orphans. Figure 7 (Panel A) summarizes the structural information obtained with chemical modification approach, in combination with limited proteolysis procedures. Using MALDI-TOF mass spectrometry to identify protease-accessible sites, we have shown that the most exposed regions are located at the first half of the protein, the Glu73-Arg78 region being revealed hyper-sensitive to various proteases (Fig. 7A). It probably indicates a protruding loop out of the globular protein. This charged region is relatively conserved among COG2042 orthologs and lies between two highly conserved segments of COG2042 (motif I and II as shown on Fig. 7). Chemical modification agrees with limited proteolysis in that the RLI motif is solvent exposed while the C terminus appeared rather inaccessible (Fig. 7A). The length of the RLI motif, first defined by conserved domain search [33], matches perfectly with two sensitive proteolytic sites (Arg31 and Lys34). The RLI domain is also present at the N terminus of another group of orthologous proteins, namely COG1245. Remarkably, COG1245 proteins only occur in two domains of life (Archaea and Eukarya) similarly to COG2042 proteins. Although co-occurrence of protein members is not strictly identical (for example, pyrococci encompass the information for COG1245 but not for COG2042 polypeptides), such occurrence pattern may reflect a functional link between the two protein families.
Our initial objective was to obtain about SSO0551 as much low-resolution structural information as possible in order to discriminate among putative three-dimensional models representing COG2042 protein structure. However, currently available threading tools applied on SSO0551 failed to detect any structurally related-proteins. Alternatively, we obtained ten different ab initio models of SSO0551 using the fully-automated ROBETTA server based on ROSETTA procedures [34]. On these ten models, we applied all the low-resolution structural information gathered in this work. We predicted for every model location of preferential proteolytic sites using the NickPred software [35]. Models M1, M2 and M6 on one hand, and M9 and M10 on the other, show hypersensitive regions in the RLI motif or C terminus, respectively. These features do not correspond to our experimental data. Only models M4, M7 and M8 predict that the loop Glu73-Arg78 is solvent exposed (data not shown). Among these three models, M4 and M8 respect the ranking of preferential nick-sites for trypsin, chymotrypsin, ArgC and GluC proteases. Solvent accessibility for lysine side chain was evaluated for models M4, M7 and M8 and compared with experimental data (data not shown). All the lysine residues labeled with NHS-biotin are found solvent-exposed in model M8. Manual inspection of cross-linked lysines (Lys10-Lys14 and Lys23-Lys25) revealed that model M4 is not valid because of the opposite orientation of Lys10 and Lys14. Figure 7 (Panels B & C) shows cartoon views of the M8 model that fulfills all our experimental constraints. For this model, the distance between the two reactive amine groups of Lys10-Lys14 and Lys23-Lys25 pairs are 12.7 Å and 13.3 Å, respectively. Search with DALI for structural homologs using model M8 did not result in significant scores with any known PDB structures. This is consistent with the PSI-BLAST results and may indicate that COG2042 proteins share a novel fold. COG2042 proteins are thus a target of choice for genomic structural studies.
In conclusion, we have presented a strategy consisting in obtaining low-resolution structural information (determination of nick-sites, solvent exposed residues, and residue-residue distances) that can be used to distinguish among a large set of theoretical molecular models. Lack of remotely-related structural templates or lack of adequacy between experimental data and most theoretical models indicates that such family of proteins should become a priority in structural genomic projects.
Methods
Chemical and biological reagents
Most chemicals used in this study were obtained from Sigma and were of analytical grade. Oligonucleotide primers were purchased from Genset. N-hydroxysuccinimide-biotin (NHS-biotin) and 3,3'-dithio-bis [sulfosuccinimidyl-propionate] (DTSSP) were obtained from Pierce. Matrices for Matrix-assisted Laser Desorption Ionization-Time of Flight (MALDI-TOF) mass spectrometry and calibration standards were purchased from Bruker Daltonics. Sequencing grade proteolytic enzymes were from Roche Applied Science.
Cloning and overexpression of SSO0551
Two constructs were designed in order to get overexpression of the SSO0551 ORF (starting with an ATG codon at nucleotide 484790 on the Crick strand of S. solfataricus P2 genome (NC_002754)) and an N-terminal extended version of SSO0551 (starting with an ATG codon at nucleotide 484916). For both proteins, an N-terminal 6His tag was added to render the purification of the recombinant products easier. For this purpose, synthetic oligonucleotide primers were oAB22 (5'-gctagcATGAAGCCCAAACCC-3') and oAB49 (5'-gctagcATGAAGGTATATATTATAGAC-3') that both contain an engineered NheI site, oAC34 (5'-cggatcctacTCATTTTTCAAGTATTTTC-3') and oAE62 (5'-ggatcctcaTCATTTTTCA AGTATTTTCTC-3') that both contain an engineered BamHI site (restriction sites underlined in the primer sequences and nucleotides not present in the original sequence shown by lower case). Oligonucleotide pairs oAB22/oAC34 and oAB49/oAC34 were used for two distinct PCR amplifications of SSO0551 with S. sulfolobus total DNA as template. A 643-bp fragment (N-ter 6His-tag extended version of SSO0551) and a 517-bp fragment (N-ter 6His-tag SSO0551) were obtained, respectively. They were cloned into pCRScript-cam (Stratagene), resulting in plasmids pSBTN-AB36 and pSBTN-AB37, respectively. The two inserts were removed by digestion with NheI and BamHI and ligated with T4 DNA ligase into plasmid pSBTN-AB23 (Armengaud J. & Chaumont V., unpublished data), a derivative of pCR T7/NT-topo (Invitrogen) containing a T7 promoter and 6 His-tag, previously digested with the same endonucleases. The resulting plasmids pSBTN-AB30 and pSBTN-AB31, respectively, were verified by DNA sequencing in order to ascertain the integrity of the nucleotide sequence. Hyperexpression of the recombinant SSO0551 constructs was achieved with E. coli Rosetta(DE3)pLysS strain (Novagen), freshly transformed with the plasmids described above. Cultures were carried out at 30°C as described earlier [6].
Purification of recombinant SSO0551 protein
The purification of recombinant SSO0551 was performed from 44 g (wet material) packed cells. Buffer A consisted of 50 mM K2HPO4/KH2PO4 buffer (pH 7.2) containing 400 mM K-glutamate. The pellet was thawed on ice and resuspended in 120 mL of buffer A. The cells were disrupted by sonication with a total energy delivered of 71 kJ. The cell-extract was then centrifuged at 30,000 g for 20 min at 4°C to remove cellular debris and aggregated proteins. The supernatant was subjected to a 20 min heat treatment using a water bath maintained at 70°C, and immediately centrifuged a second time at 30,000 g for 20 min at 4°C. Chromatographic steps were performed at room temperature using an Äkta Purifier FPLC system (Amersham Biosciences). The 135 mL supernatant was applied at a flow rate of 2.8 mL/min onto a XK 26 × 20 column (Amersham Biosciences) containing 50 mL of Chelating Sepharose Fast Flow (Amersham Biosciences) and previously loaded with 200 mM NiSO4, washed with milliQ water and equilibrated with Buffer A containing 50 mM imidazole. The fraction collected during the IMAC loading was shown to contain the SSO0551 protein. This 222 mL fraction was concentrated to a volume of 56 mL by means of Centricon Plus-20 filtration units (Millipore) and then dialyzed overnight at 4°C against 20 mM K2HPO4/KH2PO4 buffer (pH 7.2) containing 20 mM NaCl (buffer B). The 78 mL supernatant obtained after centrifugation at 30,000 g for 10 min at 4°C was divided and applied in two separate runs onto a 6 mLResource-S ion-exchange column (30 mm × 16 mm, 15 μm) from Amersham Biosciences, previously equilibrated with buffer B and operated at a flow rate of 3 mL/min. After a 10 column volume wash with buffer B, proteins were resolved with a 25 column volume linear gradient from 20 to 500 mM NaCl in buffer B. Recombinant SSO0551 was eluted at approximately 250 mM NaCl and desalted by overnight dialysis against Buffer B. The resulting 20 mL protein solution was concentrated to a volume of 8 mL by means of Centricon Plus-20 filtration units (Millipore). The sample was again divided and applied in two separate runs onto a superdex75 gel filtration packed into a HR 16/50 column at a flow rate of 1.5 mL/min in 20 mM K2HPO4/KH2PO4 buffer (pH 7.2) containing 100 mM NaCl. The fractions obtained with the two runs were pooled and dialyzed overnight at 4°C against 10 mM HEPES buffer (pH 7.2). After dialysis, the fraction was centrifuged at 26,000 g for 20 min at 4°C and the protein concentration was measured by spectrophotometry using a molar absorption coefficient of 19060 M-1 cm-1 at 280 nm. The purified protein was flash frozen in liquid nitrogen and stored at -80°C at a concentration of 0.48 mg/mL.
Circular dichroïsm
Far- and near-UV circular dichroism spectra were recorded at 20°C between 200 and 300 nm on a J-810 Jasco spectropolarimeter equipped with a PTC-424S Jasco Peltier, using a quartz cuvette of 1 mm path length, with a 20 nm/min scanning speed and a band-width of 1 nm. Three spectra of purified SSO0551 at 1.92 μM in 10 mM HEPES buffer (pH 7.2) were averaged and corrected from the baseline for buffer solvent contribution. Experimental data were analyzed using the program K2D [36] described by Andrade et al. [37].
Determination of native molecular mass by gel filtration
The native molecular mass of SSO0551 was estimated by gel filtration chromatography on a Superdex 200 gel packed into a HR10/30 column (Amersham Biosciences) with a final bed volume of 24 mL. The column was equilibrated at room temperature at a flow rate of 0.5 mL/min with 50 mM Tris/HCl buffer, pH 8.3, containing 50 mM NaCl and eluted with the same buffer. Protein standards used to calibrate the column were ribonuclease A (15.8 kDa), chymotrypsinogen A (21.2 kDa), ovalbumin (49.4 kDa), albumin (69.8 kDa), aldolase (191 kDa) and catalase (215 kDa), all from Amersham Biosciences. Exclusion limit was evaluated with dextran blue 2000 (Amersham Biosciences). A sample consisting of 90 μL of SSO0551 at 25.2 μM was injected and specific absorptions at 280 and 266 nm were followed.
Mass spectrometry
Matrix-Assisted Laser Desorption/Ionization Time-Of-Flight (MALDI-TOF) mass measurements were performed using a Biflex IV instrument (Bruker Daltonics) in positive ionization mode. Protein samples and large peptidic fragments (>3500 Da) were applied to the target using sinapinic acid prepared as saturated solution in 30 % acetonitrile, 70 % milli-Q water and 0.1 % TFA as matrix. Samples were prepared using the dried droplet method and measured in linear mode. Small peptide samples were measured in reflectron mode using α-cyano-4-hydroxycinnamic acid in 30% acetonitrile containing 0.1% trifluoroacetic acid as matrix. Mass spectra were obtained by summation of 100–210 laser shots. The instrument was calibrated for determination of entire protein masses using either a mixture of chymotrypsin and bovine serum albumine, or apomyoglobin and aldolase. For peptides, the instrument was calibrated using a pepmix calibration kit (Bruker Daltonics). When necessary, the mass spectrometer was also internally calibrated using some of the theoretical peptide masses.
Limited protease digestion
For in-solution partial digestion, 0.2 nmol of pure SSO0551 were diluted into buffer D1 (20 mM TRIS/HCl, pH 7.8), buffer D2 (20 mM NH4HCO3, pH 7.8) or buffer D3 (20 mM TRIS/HCl, pH 7.8, containing 10 mM CaCl2 and 5 mM DTT). Trypsin or chymotrypsin was added to SSO0551 diluted into buffer D1, whereas Glu-C or Arg-C was added to the protein diluted into buffer D2 or D3, respectively. Several enzyme/protein ratios (1:50 (w/w), 1:20 (w/w) and 1:2 (w/w)) were tested for each endoprotease. The digestions were performed at room temperature and aliquots were analyzed from 30 sec to 10–240 min. Digested samples were desalted using ZipTipC18 or ZipTipC4 pipette tips (Millipore) according to the protocol specified by the manufacturer and their mass directly evaluated by MALDI-TOF. Eventually, partially proteolyzed mixtures of larger quantities (10 nmol of SSO0551) were fractionated by reverse-phase HPLC using an Aquapore RP-300 column (PerkinElmer; 100 × 1.0 mm, 7 μm, 300 Å pore size) developed at 200 μL/min with a linear gradient from 5 to 90 % of acetonitrile in TFA 0.1 % over 45 min. The elution was monitored at 220 nm with an Agilent 1100 Series HPLC system equipped with a G1315 diode array detector. Individual fractions were concentrated by evaporation in a SpeedVac (Savant) and directly analyzed by MALDI-TOF.
Lysine labeling by NHS-biotin
N-hydroxysuccinimide-biotin (NHS-biotin) was used to label ε-amino groups of SSO0551 lysines. After reaction the biotin labels resulted coupled to the lysines through a stable amide bond. The increase in mass for each label (C10H14N2O2S1) should be 226.293 amu if average mass is considered or 226.078 amu in monoisotopic mode. Modification of lysine residues was carried out by incubating 1.25 nmol of SSO0551 in 20 mM HEPES, pH 7.2, with various amount of freshly prepared NHS-biotin reagent dissolved in anhydrous dimethylsulfoxide. After 30 min of incubation at room temperature, the reagent in excess was removed by a 30 min micro-dialysis against 20 mM HEPES, pH 7.2. Samples were directly desalted by using ZipTipC4 (Millipore) prior MALDI-TOF analysis. They were eventually digested overnight with an endoprotease (trypsin, GluC or ArgC) and desalted by using ZipTipC18 pipette tips (Millipore) prior mass analysis.
Lysine cross-linking with DTSSP
3,3'-Dithio-bis [sulfosuccinimidyl-propionate] (DTSSP) was used to cross-link two ε-amino groups of SSO0551 lysines, essentially as described in [32]. The mass increase (in monoisotopic mode) for each label should be 191.991 amu (C6H8O3S2) or 87.998 amu (C3H4O1S1) when DTT treated. The increase in mass for an intramolecular cross-link between two lysines should be 173.981 amu (C6H6O2S2) or 175.997 amu (2 × C3H4O1S1) when DTT treated. Therefore after reduction of the disulfide bridge by DTT, an additional increase of 2.016 amu should be measured. Reaction was carried out by incubating 0.25 nmol of SSO0551 in 20 mM NaH2PO4/Na2HPO4, pH 7.5 containing 150 mM NaCl, with various amount of DTSSP reagent (molar ratio of 20, 35, and 50 mol of DTSSP per mol of polypeptide). After 30 min of incubation at room temperature, the reagent in excess was removed by a 30 min micro-dialysis against 20 mM NaH2PO4/Na2HPO4, pH 7.5 containing 150 mM NaCl. Prior overnight trypsin proteolysis, urea (330 mM final concentration) was added to each sample. Before being desalted by using ZipTipC18 pipette tips (Millipore), the digested peptide mixture was eventually reduced with 50 mM DTT for 30 minutes at 37°C to reduce the thiol linker.
In silico analysis
Sequence searching was performed using PSI-BLAST with default parameters. Multiple sequence alignments were performed using VectorNTI software package (Informax Inc). Secondary structure predictions were obtained through the PSIPRED v2.4 web-interfaced facilities [38] described by McGuffin et al. [39]. The molar absorption coefficient at 280 nm for SSO0551 was obtained from calculation of the amino acid composition of the recombinant protein [40,41]. Isotopic and average mass of both DTSSP cross-linker and NHS-biotin were calculated using a web-interfaced molecular weight calculator [42]. The peptide assignment and the first attempt for identifying the labeled products and cross-linking products were performed using the FindMod package at ExPaSy [43]. If no match was found, a more detailed search for multiple labels or combinatorial cross-linkable peptide pairs was carried out. Partially proteolyzed products were assigned using the FindPept tool [44]. Tertiary structure predictions were carried out using publicly available online services, including 3D-PSSM [45], FUGUE [46] and PSIPRED [39]. Ab initio modeling was performed using the ROBETTA server [34,47]. Each model was analyzed in terms of proteolytic sensitivity using the NICKPRED software [35,48,49]. Residues accessibility have been calculated using a modified version of Connolly's MS program ([50]; Pellequer JL, unpublished results). Structural homologs were searched using DALI web server from the European Bioinformatics Institute [51]. Model views were obtained with the MOLSCRIPT program [52] and rendered using RASTER3D [53].
List of abbreviations
amu, atomic mass unit; COG, Cluster of Orthologous Group; DTSSP, 3,3'-dithio-bis [sulfosuccinimidyl-propionate]; IPTG, isopropyl-γ-D-thiogalactopyranoside; HPLC, high performance liquid chromatography; EDTA, Ethylenediaminetetraacetic acid; HEPES, 4-(2-hydroxyethyl)piperazine-1-ethanesulfonic acid; HEPPS, N-(2-hydroxyethyl)piperazine-N'-(3-propanesulfonic acid);IMAC, immobilized metal ion adsorption chromatography; MALDI-TOF, Matrix-assisted Laser Desorption/Ionization Time-of-Flight; NHS-biotin, N-hydroxysuccinimide-biotin; PSI-BLAST, Position-Specific Iterated Blast; Tris, 2-[bis(2-hydroxyethyl)amino]-2-(hydroxymethyl)-propane-1,3-diol.
Authors' contributions
JA conceived, coordinated the study and participated in all its experimental aspects. He analyzed the genomic distribution of this family of proteins, designed and engineered the recombinant SSO0551 molecule, conceived the mass spectrometry strategies and interpreted the data. He proposed ab initio modeling of SSO0551 and drafted the original manuscript. AD actively participated in conception of the mass spectrometry strategies, advised OS on execution and interpretation of mass spectrometry experiments and assisted in figure design. OS performed and interpreted all mass spectrometry experiments. JLP contributed its experience for the modeling aspects of the project. EQ contributed its experience in mass spectrometry-based topology. All authors participated in manuscript preparation, read and approved the final manuscript.
Acknowledgements
We gratefully acknowledge Yvan Zivanovic (CNRS-IGM, Orsay, France) for kind gift of S. sulfolobus total genomic DNA and Patrick Forterre (Université d'Orsay, Orsay, France) for initial discussions of the interest of characterizing SSO0551 protein. We thank our enthusiast technical assistants (CEA-VALRHO): Valérie Chaumont for performing the cloning and overexpression experiments, Charles Marchetti for operating the fermenter facilities, Bernard Fernandez for assistance with chromatography and recording circular dichroïsm signal, Isabelle Dany for initial fingerprint mass characterization of overproduced SSO0551, and Pascale Richard for technical support.
Figures and Tables
Figure 1 COG2042 sequences comparison. A – Phylogenetic analysis of archaeal and eukaryal COG2042 sequences. Archaeal and eukaryal homologs were obtained from public databases [54] by PSI-BLAST searches. To get the most conserved alignment between COG2042 polypeptide sequences, most probable start codons should be considered as atg at nucleotide 500978 on Crick strand for MTH554 from Methanothermobacter thermoautotrophicus str. DeltaH (NC_000916), gtg at nucleotide 1526308 on Watson strand for Vng2075c from Halobacterium sp. NRC-1 (NC_002607), atg at nucleotide 8398 on Watson strand for Mbur141901 from Methanococcoides burtonii DSM6242 (NZ_AADH01000008) and atg at nucleotide 484790 on Crick strand for SSO0551 from S. solfataricus (NC_002754). Asterisks indicate modified protein sequences according to this new proposed annotation. Multiple alignments were performed by ClustalW. Following removal of a few ambiguously aligned regions, a data set was assembled comprising 40 sequences over 162 amino acid positions. An unrooted evolutionary distance tree was constructed based on Kimura distances and neighbor joining tree reconstruction algorithm. Bootstrap confidence levels at nodes were computed by the Phylips package with 400 replicates. Scale bar represents unit of amino acid substitutions per position. Accession numbers (gi) are indicated beside the organism. B – Conserved sequence blocks in the alignment of COG2042 members. Based on the phylogenetic analysis (Panel A), eight representative sequences were selected out of 40 COG2042 sequences. Four first sequences are from Archaea while last four sequences are from Eukaryota. SSO0551 sequence (gi38605619) from S. solfataricus, labeled with an asterisk, has been numbered according to the new annotation proposed in RESULTS section. Invariant residues in the eight sequences are shown in red and conserved residues in blue. Two conserved motifs commented in the results section are indicated with grey boxes.
Figure 2 Analysis of untagged SSO0551 purification. A – Various purification steps followed by SDS-PAGE. SDS-PAGE was performed on a 4–12% gradient Novex bis-tris acrylamide gel (Invitrogen) and stained with BlueSafe Coomassie solution (Biorad). Lane M, molecular weight markers; Lane 1, cell-free extract of E. coli Rosetta(DE3)(pLysS)(pSBTN-AB30) ; Lane 2, soluble proteins from cell-free extract; Lane 3, soluble proteins after the 60°C heat treatment; Lane 4, Resource-S eluate ; Lane 5, Superdex75 eluate. Bands corresponding to recombinant SSO0551 polypeptide are indicated with the arrow. B – SSO0551 mass measurement by MALDI-TOF mass spectrometry. Measurements from 250 laser shots of purified protein cristallized with sinapinic acid were averaged.
Figure 3 Evaluation of SSO0551 secondary structure elements by circular dichroïsm. The molar ellipticity was calculated on the basis of exact amino acid composition of SSO0551 recombinant product.
Figure 4 MALDI-TOF mass spectrum of large peptide fragments produced by SSO0551 partial trypsin proteolysis. A partial enzymatic proteolysis was carried out during 60 sec at 20°C with a trypsin/SSO0551 protein ratio of 1/20 (w/w). The products were then resolved onto a C8 reverse phase chromatographic column and the different UV absorbing fractions were analyzed by MALDI-TOF. The m/z spectrum obtained with the fraction eluting at 40–50 % acetonitrile is shown. The asterisk labels a peak arising from trypsin autolysis. Peaks that could be assigned are identified with numbers (experimental m/z, residues, Δmass in ppm compared to theoretical [M+H]+ average mass): M1 (19198.4, [1–166], -1), M2 (15478.7, [32–166], -53), M3 (15191.2, [35–166], +153), M4 (12883.4, [52–162] or [56–166], -46 or -43), M5 (12724.2, [57–166], +193), M6 (10603.8, [76–166], +51), M7 (10220.1, [79–166], +77), M8 (9257.2, [83–162], +63) and M9 (7717.0, [101–166], -134). Peptides C1 and C2, complementary of M5 and M6, were not observed in this spectrum but in another fraction from the C8 reverse-phase chromatography corresponding to smaller peptides.
Figure 5 MALDI-TOF mass spectra of proteins labeled with NHS-biotin. Protein samples were mixed with various amount of NHS-biotin for 15 min at room temperature. Unlabeled protein mass spectrum is shown in grey solid line. Reagent/total lysine ratios were in Fig. 5A: 1:40 (black dotted line) and 1:20 (black dashed line), and in Fig. 5B: 1:2 (black solid line) and 2:1 (grey dotted line). The number of labeled lysines is indicated above each peak.
Figure 6 DTSSP cross-linked peptides identified by MALDI-TOF mass spectrometry. Protein samples were mixed with DTSSP for 30 min at room temperature at a molar ratio 1:20 (protein:DTSSP). They were then subjected to trypsin proteolysis. Masses of peptides treated with DTT (grey spectrum) or untreated (black spectrum) were measured by MALDI-TOF mass spectrometry. Peptide sequences are indicated and DTSSP cross-links or DTSSP moieties arising from DTT treatment are depicted schematically. Monoisotopic masses of protonated peptides [MH+] are theoretically: 1491.807 amu and 1493.822 amu for LVKLKIAEFTR [21-31] cross-linked with one DTSSP molecule (untreated (C68H115N16O17S2) and DTT-reduced (C68H117N16O17S2), respectively), 1835.846 amu and 1837.862 amu for VYIIDYHKDDPKR [3-15] cross-linked with one DTSSP molecule (untreated (C82H123N20O24S2) and DTT-reduced (C82H125N20O24S2), respectively).
Figure 7 Experimental topology information obtained on SSO0551 and theoretical 3D model M8 shown to be compatible. A – Schematic representation of experimental low-resolution structural information. SSO0551 sequence is displayed with its predicted secondary structural elements (α-helices and β-strands are represented by helices and arrows, respectively). The two conserved COG2042 motifs described in this study (I and II) and the 35 amino acids RLI motif are specified. Vertical arrows indicate sites of limited proteolysis that have been experimentally determined. Lysines labeled with NHS-biotin are indicated with asterisks and lysines involved in DTSSP cross-links are schematically bridged. Sequence numbering refers to the native version (untagged) of SSO0551 experimentally characterized. B – Schematic drawing of ab initio model M8. Secondary structure elements are shown as coil for α-helices, arrows for β-strands, and lines for loops. The color code follows a rainbow style where N terminus is in blue and C terminus in red. C – Molecular surface of ab initio model M8. The localization of solvent-exposed lysines, as determined by NHS-biotin labeling experiments, is colored in red whereas other lysines are colored in blue. This view shows the protein in the same orientation as in B.
Table 1 Fingerprint identification of recombinant products from pSBTN-AB31 and pSBTN-AB30 constructs.
pSBTN-AB31 constructa pSBTN-AB30 constructa Theoretical peptides
[MH]+ observed (in amu) Δmass (in ppm) [MH]+ observed (in amu) Δmass (in ppm) [MH]+ expected (in amu) Positionb (Start-End) Peptide assignment
1590.64 -31 nd c - 1590.69 3–16 GSHHHHHHGMASMK
nd c - 1050.54 -19 1050.56 17–24 VYIIDYHK
1505.71 -33 nd c - 1505.76 17–28 VYIIDYHKDDPK
1661.83 -18 1661.85 -6 1661.86 17–29 VYIIDYHKDDPKR
1601.84 -31 1601.83 -37 1601.89 49–63 GVVLDPFAQITLSNK
1844.98 -16 1845.00 -5 1845.01 49–65 GVVLDPFAQITLSNKD
2328.28 -4 2328.28 -4 2328.29 49–69 GVVLDPFA...KDKDIVR
2484.35 -16 2484.34 -20 2484.39 49–70 GVVLDPFA...KDKDIVRR
2140.06 0 2140.06 0 2140.06 71–89 IGITIVDTSWNNTSQSEFK
2296.16 0 2296.16 0 2296.16 70–89 RIGITIVDTSWNNTSQSEFK
2043.17 10 2043.18 15 2043.15 97–114 RIPILFAGNPIHYGIAYK
1887.05 0 1887.06 5 1887.05 98–114 IPILFAGNPIHYGIAYK
1244.62 -16 1244.59 -40 1244.64 143–152 WGHTFIELNK
2091.09 0 nd c - 2091.09 143–159 WGHTFIELNKELLEAYK
nd c - 865.53 69 865.47 153–159 ELLEAYK
aThe two products were isolated from SDS-PAGE and treated with trypsin. The resulting peptides were analyzed by MALDI-TOF spectrometry in reflectron mode. The expected length for the two products are: 180 amino acids for SSO0551 with the 6His-tag at the N terminus (pSBTN-AB31 construct) and 222 amino acids for SSO0551 extended version (42 additional amino acids at the N terminus and a 6His-tag; pSBTN-AB30 construct).
bPeptide positions refers to SSO0551.
c«nd» denote the peptides not detected in one of the samples.
Table 2 Monoisotopic [M+H]+ peptides generated by various proteases after NHS-biotin labeling of SSO0551.
Protease [M+H]+ (observed) [M+H]+ (expected) Δmass (ppm) Position (Start-End) Peptide assignmenta NHS-biotin labelb Modified residuesa
Trypsin 1731.94 1731.84 -57 3–14 VYIIDYHKDDPK 1 K10
Trypsin 2114.27 2114.02 118 3–15 VYIIDYHKDDPKR 2 K10andK14
Trypsin 1888.15 1887.94 111 3–15 VYIIDYHKDDPKR 1 K10orK14
Trypsin 1991.21 1990.98 -119 1–14 MKVYIIDYHKDDPK 1 K2orK10
Trypsin 2147.33 2147.08 -120 1–15 MKVYIIDYHKDDPKR 1 K2orK10orK14
Trypsin 2163.33 2163.07 -120 1–15 MoxyKVYIIDYHKDDPKR 1 K2orK10orK14
Trypsin 2373.41 2373.16 -107 1–15 MKVYIIDYHKDDPKR 2 K2or/andK10or/andK14
Trypsin 1180.77 1180.69 -64 20–25 KLVKLK 2 K20andK23
Trypsin 1203.76 1203.66 -87 24–31 LKIAEFTR 1 K25
Trypsin 1770.16 1769.98 102 21–31 LVKLKIAEFTR 2 K23andK25
Trypsin 1898.15 1898.08 -39 20–31 KLVKLKIAEFTR 2 K20orK23orK25
Trypsin 1127.68 1127.60 -71 50–56 DKDIVRR 1 K51
Trypsin 3064.63 3064.63 1 32–55 VGKGVVL...NKDKDIVR 2 K34or/andK49or/andK51
Trypsin 2554.57 2554.37 -78 35–55 GVVL...NKDKDIVR 1 K49orK51
Trypsin 2710.61 2710.47 -51 35–56 GVVL...NKDKDIVRR 1 K49orK51
Trypsin 2838.65 2838.55 -34 32–55 VGKGVVL...NKDKDIVR 1 K34orK49orK51
Arg-C 2838.75 2838.55 -69 32–55 VGKGVVL...NKDKDIVR 1 K34orK49orK51
Trypsin 2749.36 2749.36 0 57–78 IGIT...SEFKNIR 1 K75
Arg-C 2749.60 2749.36 -87 57–78 IGIT...SEFKNIR 1 K75
Glu-C 1089.56 1089.55 -8 74–80 FKNIRGE 1 K75
Trypsin 2111.22 2111.11 -52 123–138 LSNVVKWGHTFIELNK 1 K128
Glu-C 2068.19 2068.10 -41 120–135 AIKLSNVVKWGHTFIE 1 K122orK128
Trypsin 1330.74 1330.67 -55 146–154 NKTEEDIKK 1 K147orK153
Glu-C 1256.65 1256.67 13 151–158 DIKKIERE 1 K153orK154
Trypsin 1486.85 1486.76 -60 148–157 TEEDIKKIEREIIEK 1 K153orK154
Trypsin 1383.76 1383.77 5 154–162 KIEREIIEK 1 K154
Trypsin 1867.14 1867.07 -36 154–166 KIEREIIEKILEK 1 K162orK154
Trypsin 1340.71 1340.75 29 158–166 EIIEKILEK 1 K162orK166
Trypsin 1739.01 1738.98 -19 155–166 IEREIIEKILEK 1 K162orK166
aUnequivocal modified residues are indicated in bold characters.
bNHS-biotin label (+226.08 amu).
==== Refs
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| 15701177 | PMC549553 | CC BY | 2021-01-04 16:03:53 | no | BMC Struct Biol. 2005 Feb 8; 5:3 | utf-8 | BMC Struct Biol | 2,005 | 10.1186/1472-6807-5-3 | oa_comm |
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BMC Cardiovasc DisordBMC Cardiovascular Disorders1471-2261BioMed Central London 1471-2261-5-51570749710.1186/1471-2261-5-5Research ArticleNine-year comparison of presentation and management of acute coronary syndromes in Ireland: a national cross-sectional survey Doyle Frank [email protected] La Harpe Davida [email protected] Hannah [email protected] Emer [email protected] Ronán [email protected] Department of Epidemiology and Public Health Medicine, Royal College of Surgeons in Ireland, 123 St. Stephen's Green, Dublin 2, Ireland2 Department of Psychology, Royal College of Surgeons in Ireland, 123 St. Stephen's Green, Dublin 2, Ireland2005 11 2 2005 5 5 5 11 10 2004 11 2 2005 Copyright © 2005 Doyle et al; licensee BioMed Central Ltd.2005Doyle 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
Shorter time to treatment is associated with lower mortality in acute coronary syndromes (ACS). A previous (1994) survey showed substantial delays for acute myocardial infarction (AMI) in Ireland. The present study compared current practice with 1994 and surveyed acute coronary syndromes as a more complete contemporary evaluation of critical cardiac care than assessing AMI alone.
Methods
Following ethics committee approval, all centres (N = 39) admitting acute cardiac patients to intensive/coronary care unit provided information on 1365 episodes. A cross-sectional survey design was employed.
Results
Since 1994, median hospital arrival to thrombolysis time was reduced by 41% (76 to 45 minutes). Thrombolysis was delivered more often in the emergency department in 2003 (48% vs 2%). Thrombolysis when delivered in the emergency department was achieved faster than thrombolysis delivered in intensive/coronary care (35 mins v 60 mins; z = 5.62, p < .0001). Suspected AMI patients who did not subsequently receive thrombolysis took longer to present to hospital (5 h vs 2 h 34 mins; z = 7.33, p < .0001) and had longer transfer times to the intensive/coronary care unit following arrival (2 h 17 mins vs 1 h 10 mins; z = 8.92, p < .0001). Fewer confirmed AMI cases received thrombolysis in 2003 (43% vs 58%). There was an increase in confirmed cases of AMI from 1994 (70% to 87%).
Conclusions
Substantial improvements in time to thrombolysis have occurred since 1994, probably relating to treatment provision in emergency departments. Patient delay pre-hospital is still the principal impediment to effective treatment of ACS. A recent change of definition of AMI may have precluded an exact comparison between 1994 and 2003 data.
==== Body
Background
Ireland has one of the highest mortality rates from cardiovascular disease in the European Union [1]. Acute coronary syndrome (ACS) is a major portion of cardiovascular diseases. ACS includes unstable angina and both persistent-ST-segment elevation and non-ST segment elevation acute myocardial infarction (AMI) [2-4]. Thrombus formation is the primary reason for myocardial infarction [5]. This usually occurs after a complex interaction between coronary atherosclerosis, plaque rupture and platelet activation. Thrombolysis is an appropriate treatment for thrombus formation in ST-elevation AMI and when delivered in a 'timely' manner, preferably within 6 hours but including up to 12 hours after symptom onset [6,7], can significantly reduce morbidity and mortality from AMI. Each hour of time saved can lead to a decrease of about 1.6 deaths per 1000 patients treated [7]. Therefore, shortening of time to treatment for AMI patients is an important life-saving goal for health services [6].
International guidelines, for example those from the European Society of Cardiology [8,9] and the British Heart Foundation [10], have proposed a 'call-to-needle' time of 90 minutes for thrombolysis administration. The National Service Framework (NSF) in the United Kingdom (UK) further reduced the recommended time in 2000 with a proposed 'call-to-needle' time of 60 minutes [11]. Furthermore, eligible patients should be thrombolysed within 30 minutes of arrival at hospital [9]. In Ireland, the 1994 national census found a median time to treatment of 4 hours 30 minutes [12]. This compares unfavourably to more recently recorded median treatment times in other countries, e.g. 2 hours 45 minutes in the UK [13] or 2 hours 54 minutes in Switzerland [14]. Approximately 50% of AMI deaths in the community occur within two hours from the onset of symptoms [15]. Early management of AMI patients with thrombolysis significantly reduces morbidity and mortality [16]. Time to treatment can be shortened by thrombolysing patients in the emergency department prior to transfer to intensive/coronary care. This strategy has lead to significant reductions in delay [17].
Since 1994, there has been no examination of time to treatment and the extent to which international guidelines for treatment of AMI are being achieved in Ireland. This study assessed the presentation and management of a national cohort of suspected ACS patients admitted to intensive/coronary care units (I/CCUs) in all 39 Republic of Ireland hospitals providing such care. We decided to extend the range of patients assessed from those with suspected AMI (as was the case in previous surveys [12,18]) to all suspected ACS patients, to profile the pool of possible patients presenting from which testing determines eligibility for reperfusion therapy. Differing proportions of reperfusion-eligible patients over time or centre, alongside the absolute number of patients presenting, may influence the speed of management of eligible patients. Also, some treatments for other ACS (e.g. unstable angina) can be similar to treatment for AMI, depending on the severity of the event [19] (e.g. angioplasty treatment for unstable angina). Changes in the definition of AMI in recent years have lead to an increase in the proportion of diagnosed AMI patients and a decrease in the proportion of patients diagnosed as having unstable angina [20-22]. which may preclude exact comparison to previous findings. Where possible we compare data to results from 1994.
Methods
Sample
All Irish centres admitting suspected ACS patients to I/CCU (N = 39) agreed to participate following relevant ethics approval [23]. Data collection was conducted from January to October 2003. Four hospitals had not recruited 25 suspected AMI patients by the study cut-off date. Suspected acute coronary syndrome (ACS) patients admitted to I/CCU were recruited. Staff were provided with the consensus definition of ACS as agreed in 2000 by the Joint European Society of Cardiology/American College of Cardiology Committee [4]. This definition uses enzyme (troponin) change as a marker of myocardial necrosis. The survey was of suspected ACS and the main focus was on how patients with suspected ACS are treated in the early phase of their hospital admission. Therefore the admission diagnosis was used to categorise patients (e.g. if a patient was admitted to I/CCU with a diagnosis of 'chest pain – query AMI', they were listed as suspected AMI for the purposes of this study; if patients were admitted with suspected ACS or suspected unstable angina, they were categorised as 'other ACS'). Data on successive admissions were audited anonymously from hospital charts. Participating hospitals recruited all consecutive suspected ACS patients, until 25 suspected cases of AMI had been admitted to I/CCU. Data on a total of 1365 episodes were collected (935 suspected AMI and 430 suspected other ACS admitted contemporaneously). Data collected assessed demographic details, clinical history, risk factors, presentation and management profile. Eligible patients were also approached to participate in a follow-up survey (results to be reported elsewhere).
Analysis
Analysis was conducted on the data using STATA/SE 8.0. Mann-Whitney U tests were used to test for significance between treatment times, χ2 was used for categorical variables, and t-tests were used for continuous variables. Results from 1994 are reported, but significance tests were not conducted between 1994 and 2003 data (as raw data from 1994 was unavailable). Total time to treatment was defined as follows: symptom onset to reperfusion (thrombolysis or direct infarct angioplasty). Inpatient and other hospital transfer times were not included in the analysis for 1994 or 2003 samples.
Results
Baseline characteristics
The sample consisted of 1365 episodes, 935 suspected AMI and 430 suspected other ACS patients. The gender breakdown has been described elsewhere (manuscript submitted for publication). The overall mean age was 64 years (std dev = 13; median = 65; range = 20–100 yrs). Admission characteristics are shown in table 1.
Table 1 Comparative demographic and admission profile in 1994 and 2003
Demographic 1994 (N = 950 suspected AMI) 2003
Suspected AMI (N = 935) Suspected Other ACS (N = 430) Combined (N = 1365)
Mean age (years) (mean) (std dev) - 66 (13) 61*** (14) 64 (13)
Men 64 (12) 64 (13) 60*** (13) 63 (13)
Women 69 (11) 71 (13) 64*** (14) 69 (13)
Referral source (%)
Primary care physician 69 53 55 53
Self 24 39 33 38
Other 7 8 12 9
Admission mode to hospital (%)
Ambulance 46 48 38** 45
Car (passenger) 42 42 43 42
Car (driver) 8 6 12*** 8
Other 4 4 7 5
Distance from hospital at symptom onset
Median (range) miles 9 (0–165) 9 (0–80) 8 (0–150) 8 (0–150)
Previous CHD history (%)
AMI 24 16 31*** 21
Unstable angina 14 14 28*** 19
Coronary artery bypass graft 4 5 13*** 7
Percutaneous coronary intervention 2 6 18*** 10
(*p < .05, **p < .01, ***p < .001)
The demographic profile of patients admitted for suspected AMI in 2003 appears similar to those admitted in 1994. Other ACS patients differed from suspected AMI patients in 2003 in the following aspects: they were younger, less likely to be admitted by ambulance, more likely to drive themselves to hospital, and had a higher prevalence of previous ACS and coronary interventions.
Thrombolysis
Both location of, and speed of administration of thrombolysis have changed considerably in a positive direction since 1994 (Figure 1). In 1994, 38% of suspected AMI and 58% of confirmed AMI patients received thrombolysis, which occurred in I/CCU (96%), emergency department (2%) or other location (2%). In 2003, 41% of suspected AMIs and 44% of confirmed AMIs were thrombolysed in I/CCU (48%), emergency department (48%) or other location (4%). A further 4% of suspected AMIs received direct infarct angioplasty.
Figure 1 Thrombolysis administration locations and treatment times in 1994 and 2003
Emergency department delivered thrombolysis occurred in a significantly shorter time (median 35 minutes) than I/CCU administered thrombolysis (median 60 minutes) in 2003 (z = 5.62, p < .0001).
In 2003, 29% of those thrombolysed were treated within 90 minutes of calling for professional help. This rose to 42% and 62% within 2 and 3 hours respectively. On hospital arrival, 35% of patients were thrombolysed within 30 minutes, rising to 60% and 74% within 60 and 90 minutes respectively. Thirty-six per cent of hospitals thrombolysed 80% or more of patients in the emergency department while 56% of hospitals thrombolysed over 50% of patients in the emergency department.
Time to treatment
Suspected AMI patients waited a similar length of time to get to hospital from onset of symptoms in 2003 as 1994 (Table 2). Symptom onset to hospital arrival time was significantly higher for patients admitted with suspected other ACS in 2003 (3 h 35 mins vs 4 h 39 mins, z = 2.99, p < .01).
Table 2 Median overall time to treatment for all patients in 1994 and 2003
Treatment times 1994 Suspected AMI (n = 950) 2003
Thrombolysed AMIs (n = 382) Suspected AMI – non-thrombolysed (n = 553) All suspected AMI (n = 935) Suspected other ACS (n = 430) Total (n = 1365)
Symptom onset to hospital 3 h 30 mins 2 h 34 mins 5 h 00 mins*** 3 h 35 mins 4 h 39 mins** 3 h 56 mins
Call-to-thrombolysis Unavailable 2 h 20 mins - 2 h 20 mins - -
Hospital arrival to I/CCU 55 mins 1 h 10 mins 2 h 17 mins*** 1 h 40 mins 2 h 43 mins*** 1 h 55 mins
Hospital arrival to thrombolysis 76 mins 45 mins - 45 mins - -
I/CCU admission to thrombolysis 25 mins 20 mins - 20 mins - -
(*p < .05, **p < .01, ***p < .001)
Patients waited longer to be admitted to I/CCU in 2003, but received thrombolysis more quickly (45 mins v 76 mins) after hospital arrival. This represents a 41% decrease in time-to-thrombolysis since 1994. In 2003, total time to treatment for suspected AMI patients who received reperfusion was 4 hours 00 mins.
Patients with suspected AMI who were subsequently thrombolysed (thrombolysed AMIs) presented to hospital (2 h 34 mins vs 5 h, z = 7.33, p < 0.0001) and had a faster I/CCU transfer time (1 h 10 mins vs 2 h 17 mins, z = 8.92, p < 0.0001) than suspected AMI patients who were not thrombolysed (non-thrombolysed AMIs). Suspected other ACS patients also waited significantly longer than non-thrombolysed AMIs for hospital transfer to I/CCU (2 h 43 mins vs 2 h 17 mins; z = 2.128, p < 0.05).
In 1994, treatment times for patients referred by primary care physicians were significantly longer than those who self-referred (symptom onset to hospital arrival: primary care physician-referred 4 h 15 mins, self-referred 2 h 05 mins, p < 0.001). In 2003, primary care physician-referred suspected AMI patients also had a significantly longer pre-hospital delay (5 h vs 2 h 28 mins, z = 7.9, p < 0.001).
For suspected AMI patients, a previous experience of AMI made no difference to hospital presentation time (3 h vs 3 h 45 mins, z = 1.2, p > 0.05). There were no gender differences in pre-hospital delay time (3 h 53 mins for men vs 3 h 14 mins for women, z = 0.63, p > 0.05), or hospital arrival to thrombolysis time (45 mins for men vs 50 mins for women, z = 1.43, p > 0.05) for suspected AMI patients in 2003.
Discharge
For suspected AMI patients, there was an increase in those patients diagnosed with myocardial infarction of 21% from 1994 to 2003, and a 10% reduction in the diagnosis of unstable angina (Table 3).
Table 3 I/CCU discharge diagnoses and hospital mortality (%)
Discharge diagnosis 1994 Census (suspected AMI) % CCU 2003 Survey
Thrombolysed AMIs (n = 382) Suspected AMI – non-thrombolysed (n = 553) Suspected AMI Suspected Other ACS Total
Myocardial infarction 70 97 86*** 91 19*** 68
Unstable angina 14 <1 6*** 4 47*** 17
Other cardiac 9 5 11** 9 32*** 16
Non cardiac 7 1 5** 3 17*** 8
Mortality 11 9 10 10 1*** 7
Patients may have more than one diagnosis
(*p < .05, **p < .01, ***p < .001)
In 2003, thrombolysed AMIs were more likely to be discharged as having myocardial infarction than non-thrombolysed AMIs, but were less likely to receive a discharge diagnosis of unstable angina, other cardiac or non-cardiac diagnoses. All suspected AMI patients in 2003 were more likely to be discharged as having had myocardial infarction and were more likely to die in hospital than suspected other ACS patients, but were less likely to have discharge diagnoses of unstable angina, other cardiac or non cardiac.
Discussion
The present survey outlines the current presentation and management of ACS in Ireland. This study built on the previous research conducted in 1994, but also expanded its findings beyond suspected AMI patients to all suspected ACS patients. Pre-hospital patient delay remains stable and substantial, while a considerable reduction (41%) in time to thrombolysis from hospital admission has occurred since 1994. This can probably be attributed in large part to the relocation of thrombolytic administration to the emergency department, thereby reducing the 'door-to-needle' times in 2003. Similarly, treatment of AMI patients in emergency departments prior to transfer to I/CCU may account for longer I/CCU transfer times in 2003.
Significant progress has been made in the treatment of AMI patients who receive thrombolysis, which has yielded faster 'door-to-needle' times. Suspected AMI patients who received thrombolysis in the 2003 sample were treated more quickly than 1994 (median 45 mins v 76 mins).
The transfer of thrombolytic administration from the I/CCU (96% in 1994) to the emergency department (48% in 2003, with 48% administered in I/CCU) is probably the main reason for the decreased time to treatment for thrombolysed patients. The present survey found, for instance, that 56% of hospitals thrombolysed over half of their patients in the emergency department. It is not clear, however, that an additional shift of thrombolysis to the emergency department in the remaining hospitals would also result in a further reduction of 'door-to-needle' time. This is because some hospitals already adopt a 'fast-track' policy, where chest pain patients are admitted directly to CCU, bypassing emergency department assessment. Adopting a strategy of emergency department thrombolysis may have little or no effect in these cases.
Nonetheless, only 35% of patients received thrombolysis within 30 mins of hospital arrival, which compares unfavourably to other surveys (e.g. in England and Wales in 2003, the MINAP study found that over 80% of patients were thrombolysed within 30 mins of hospital arrival [24]). These comparisons must be interpreted with some caution however, since MINAP does not count cases which have a component of extra delay due to clinical reasons (i.e. patients presenting with contraindications to thrombolysis), and reports on all eligible STEMI cases treated within 30 mins of hospital arrival. Our analysis included all patients who eventually received thrombolysis, even those patients who developed ST-elevation some time after hospital arrival. While our results may not be completely comparable to other similar surveys, the overall message that thrombolysis is unsatisfactory both in absolute and comparative terms is clear.
Substantial pre-hospital and in-hospital delays were seen for non-thrombolysed AMIs. Suspected AMI patients who did not receive thrombolysis waited significantly longer for transfer to I/CCU than those who received thrombolysis. Indeed, this group of AMIs had comparable times to patients with suspected other ACS. These patients presented to hospital more slowly than thrombolysed AMIs. This may indicate the less severe symptoms of unstable angina and non-ST-elevation myocardial infarction. Also, recent changes in AMI definition have lead to increases in proportions of diagnosed AMI patients and decreases in proportions of patients diagnosed with unstable angina [20-22]. These changes probably preclude exact comparison with 1994 findings. Adding credence to this hypothesis was the large change in discharge diagnoses. Considering suspected AMIs, the proportion of patients diagnosed with myocardial infarction increased by 21% from 1994 to 2003, with a corresponding 10% reduction in unstable angina diagnoses. The reduction in 'non cardiac' discharges for suspected AMI patients (7% in 1994 to 3% in 2003), may be partially attributed to definition change [21]. Finally, the 14% decrease in thrombolysed confirmed AMIs may also be attributed to the definition change, with a larger portion of AMI patients being ineligible for thrombolysis in 2003.
Suspected AMI patients who did not receive thrombolysis took significantly longer from hospital arrival to arrive in I/CCU than did patients who received thrombolysis. Suspected other ACS patients presented to hospital in time frames similar to suspected AMI patients who did not receive thrombolysis, but were not admitted to I/CCU as quickly. The development of chest pain assessment units and other similar units (e.g. medical admission units), which involve the initial screening of chest pain patients to determine whether the pain is cardiac in origin prior to transfer to I/CCU, may have skewed the data in the current survey. A typical scenario may be that a patient currently arrives at hospital, without ST-elevation when assessed by ECG, and is assessed for some time in the chest pain assessment unit to either 'rule-in' or 'rule-out' ACS. In the past, such patients may have been admitted directly to I/CCU. In addition, these findings may reflect the triaging of patients in the emergency department, where patients labelled as suspected AMI were treated more quickly than those labelled as suspected other ACS. Patients can be triaged into groups reflecting the necessity for immediate treatment. Non-ST-elevation myocardial infarction and unstable angina patients may be detained for observation in the emergency department. It might also be that pressure for I/CCU bed places is more quickly resolved for the more acute ST-elevation AMI patients. However, further prospective observational research on this aspect of care is required.
Patient delay prior to hospital arrival is still the biggest impediment to improving treatment times for AMI and other ACS. Patients who were referred by primary care physicians had a significantly longer time to treatment than those who self-referred in both 2003 and 1994. Clearly, in the present system, although substantial improvements have been made since the mid-1990s, a 'call-to-treatment' standard of 90 minutes is not currently being met. The present survey found that 29% of patients were thrombolysed within 90 minutes of calling for professional help. Future research and resources need to focus on a reduction in pre-hospital delay factors by the services and professional groups concerned. A number of psychological studies have provided detailed examination of patient contributions to delayed help-seeking for AMI [25-27]. These highlight possibilities for intervention to reduce symptom onset to help-seeking times but caution against a simplistic public education campaign approach. Since general public advertising/education campaigns have little efficacy [25,26,28] and even a previous experience of AMI has no effect on pre-hospital call for assistance times, sophisticated strategies are needed to address this problem.
As regards reducing health services delay, one method is to authorise health professionals in the pre-hospital setting to administer thrombolysis. Ambulance personnel and primary care physicians are the two most obvious choices. The administration of thrombolysis by ambulance personnel has been shown to reduce time to treatment [29]. A recently completed study on thrombolysis administered by primary care physicians showed the practicalities of this approach in an Irish setting [30]. In the hospital setting, involving nurses in decision-making processes for thrombolysis has been shown to be effective in reducing treatment times [31,32]. The provision of more mobile coronary care units may also reduce delay times in rural areas [33].
The present study has highlighted the need for a national prospective registry of ACS. The value of such registries has been shown in other countries. For example, registries increase the use of appropriate reperfusion therapy, but to ensure this practice continues they need to be ongoing [34]. In the UK, MINAP [35] has contributed to an increase in the numbers of patients thrombolysed within recommended timescales. For example, following the publication of the NSF guidelines on CHD in 2000 [11], the proportion of patients receiving thrombolysis within 30 minutes of hospital arrival more than doubled (79% in 2002, compared with 38% pre-2000) [36]. Registries can also underscore the extent of adherence to international guidelines. The current Irish data highlight progress in some areas over a nine-year period but indicate that improvements need to occur in other aspects. A national registry can provide the continuous feedback needed to keep a focus on areas for improvement. The monitoring of guideline adherence should even be considered a part of optimal practice procedures [37].
Conclusions
Significant progress in some aspects (e.g. time to thrombolysis) of care for suspected ACS has occurred, but there is still scope for improvement. A necessary goal is to increase the proportions of patients seen within the recommended time. Other aspects of ACS care also now require attention. Patient delay pre-hospital should remain the main focus of future research. The implementation of a national registry would allow resources to be focused on these aspects and facilitate routine health care monitoring.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
FD carried out the survey, analysed the data and drafted the manuscript. HM, DD & ES conceived of the study and participated in its design and coordination. RC participated in the study design and coordination, and provided statistical input on data analysis and interpretation. All authors provided critical input on manuscript drafts, and approved the final version.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
This project was funded by a grant from the Cardiovascular Strategy, Department of Health and Children.
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| 15707497 | PMC549554 | CC BY | 2021-01-04 16:30:06 | no | BMC Cardiovasc Disord. 2005 Feb 11; 5:5 | utf-8 | BMC Cardiovasc Disord | 2,005 | 10.1186/1471-2261-5-5 | oa_comm |
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BMC Cardiovasc DisordBMC Cardiovascular Disorders1471-2261BioMed Central London 1471-2261-5-51570749710.1186/1471-2261-5-5Research ArticleNine-year comparison of presentation and management of acute coronary syndromes in Ireland: a national cross-sectional survey Doyle Frank [email protected] La Harpe Davida [email protected] Hannah [email protected] Emer [email protected] Ronán [email protected] Department of Epidemiology and Public Health Medicine, Royal College of Surgeons in Ireland, 123 St. Stephen's Green, Dublin 2, Ireland2 Department of Psychology, Royal College of Surgeons in Ireland, 123 St. Stephen's Green, Dublin 2, Ireland2005 11 2 2005 5 5 5 11 10 2004 11 2 2005 Copyright © 2005 Doyle et al; licensee BioMed Central Ltd.2005Doyle 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
Shorter time to treatment is associated with lower mortality in acute coronary syndromes (ACS). A previous (1994) survey showed substantial delays for acute myocardial infarction (AMI) in Ireland. The present study compared current practice with 1994 and surveyed acute coronary syndromes as a more complete contemporary evaluation of critical cardiac care than assessing AMI alone.
Methods
Following ethics committee approval, all centres (N = 39) admitting acute cardiac patients to intensive/coronary care unit provided information on 1365 episodes. A cross-sectional survey design was employed.
Results
Since 1994, median hospital arrival to thrombolysis time was reduced by 41% (76 to 45 minutes). Thrombolysis was delivered more often in the emergency department in 2003 (48% vs 2%). Thrombolysis when delivered in the emergency department was achieved faster than thrombolysis delivered in intensive/coronary care (35 mins v 60 mins; z = 5.62, p < .0001). Suspected AMI patients who did not subsequently receive thrombolysis took longer to present to hospital (5 h vs 2 h 34 mins; z = 7.33, p < .0001) and had longer transfer times to the intensive/coronary care unit following arrival (2 h 17 mins vs 1 h 10 mins; z = 8.92, p < .0001). Fewer confirmed AMI cases received thrombolysis in 2003 (43% vs 58%). There was an increase in confirmed cases of AMI from 1994 (70% to 87%).
Conclusions
Substantial improvements in time to thrombolysis have occurred since 1994, probably relating to treatment provision in emergency departments. Patient delay pre-hospital is still the principal impediment to effective treatment of ACS. A recent change of definition of AMI may have precluded an exact comparison between 1994 and 2003 data.
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Background
Ireland has one of the highest mortality rates from cardiovascular disease in the European Union [1]. Acute coronary syndrome (ACS) is a major portion of cardiovascular diseases. ACS includes unstable angina and both persistent-ST-segment elevation and non-ST segment elevation acute myocardial infarction (AMI) [2-4]. Thrombus formation is the primary reason for myocardial infarction [5]. This usually occurs after a complex interaction between coronary atherosclerosis, plaque rupture and platelet activation. Thrombolysis is an appropriate treatment for thrombus formation in ST-elevation AMI and when delivered in a 'timely' manner, preferably within 6 hours but including up to 12 hours after symptom onset [6,7], can significantly reduce morbidity and mortality from AMI. Each hour of time saved can lead to a decrease of about 1.6 deaths per 1000 patients treated [7]. Therefore, shortening of time to treatment for AMI patients is an important life-saving goal for health services [6].
International guidelines, for example those from the European Society of Cardiology [8,9] and the British Heart Foundation [10], have proposed a 'call-to-needle' time of 90 minutes for thrombolysis administration. The National Service Framework (NSF) in the United Kingdom (UK) further reduced the recommended time in 2000 with a proposed 'call-to-needle' time of 60 minutes [11]. Furthermore, eligible patients should be thrombolysed within 30 minutes of arrival at hospital [9]. In Ireland, the 1994 national census found a median time to treatment of 4 hours 30 minutes [12]. This compares unfavourably to more recently recorded median treatment times in other countries, e.g. 2 hours 45 minutes in the UK [13] or 2 hours 54 minutes in Switzerland [14]. Approximately 50% of AMI deaths in the community occur within two hours from the onset of symptoms [15]. Early management of AMI patients with thrombolysis significantly reduces morbidity and mortality [16]. Time to treatment can be shortened by thrombolysing patients in the emergency department prior to transfer to intensive/coronary care. This strategy has lead to significant reductions in delay [17].
Since 1994, there has been no examination of time to treatment and the extent to which international guidelines for treatment of AMI are being achieved in Ireland. This study assessed the presentation and management of a national cohort of suspected ACS patients admitted to intensive/coronary care units (I/CCUs) in all 39 Republic of Ireland hospitals providing such care. We decided to extend the range of patients assessed from those with suspected AMI (as was the case in previous surveys [12,18]) to all suspected ACS patients, to profile the pool of possible patients presenting from which testing determines eligibility for reperfusion therapy. Differing proportions of reperfusion-eligible patients over time or centre, alongside the absolute number of patients presenting, may influence the speed of management of eligible patients. Also, some treatments for other ACS (e.g. unstable angina) can be similar to treatment for AMI, depending on the severity of the event [19] (e.g. angioplasty treatment for unstable angina). Changes in the definition of AMI in recent years have lead to an increase in the proportion of diagnosed AMI patients and a decrease in the proportion of patients diagnosed as having unstable angina [20-22]. which may preclude exact comparison to previous findings. Where possible we compare data to results from 1994.
Methods
Sample
All Irish centres admitting suspected ACS patients to I/CCU (N = 39) agreed to participate following relevant ethics approval [23]. Data collection was conducted from January to October 2003. Four hospitals had not recruited 25 suspected AMI patients by the study cut-off date. Suspected acute coronary syndrome (ACS) patients admitted to I/CCU were recruited. Staff were provided with the consensus definition of ACS as agreed in 2000 by the Joint European Society of Cardiology/American College of Cardiology Committee [4]. This definition uses enzyme (troponin) change as a marker of myocardial necrosis. The survey was of suspected ACS and the main focus was on how patients with suspected ACS are treated in the early phase of their hospital admission. Therefore the admission diagnosis was used to categorise patients (e.g. if a patient was admitted to I/CCU with a diagnosis of 'chest pain – query AMI', they were listed as suspected AMI for the purposes of this study; if patients were admitted with suspected ACS or suspected unstable angina, they were categorised as 'other ACS'). Data on successive admissions were audited anonymously from hospital charts. Participating hospitals recruited all consecutive suspected ACS patients, until 25 suspected cases of AMI had been admitted to I/CCU. Data on a total of 1365 episodes were collected (935 suspected AMI and 430 suspected other ACS admitted contemporaneously). Data collected assessed demographic details, clinical history, risk factors, presentation and management profile. Eligible patients were also approached to participate in a follow-up survey (results to be reported elsewhere).
Analysis
Analysis was conducted on the data using STATA/SE 8.0. Mann-Whitney U tests were used to test for significance between treatment times, χ2 was used for categorical variables, and t-tests were used for continuous variables. Results from 1994 are reported, but significance tests were not conducted between 1994 and 2003 data (as raw data from 1994 was unavailable). Total time to treatment was defined as follows: symptom onset to reperfusion (thrombolysis or direct infarct angioplasty). Inpatient and other hospital transfer times were not included in the analysis for 1994 or 2003 samples.
Results
Baseline characteristics
The sample consisted of 1365 episodes, 935 suspected AMI and 430 suspected other ACS patients. The gender breakdown has been described elsewhere (manuscript submitted for publication). The overall mean age was 64 years (std dev = 13; median = 65; range = 20–100 yrs). Admission characteristics are shown in table 1.
Table 1 Comparative demographic and admission profile in 1994 and 2003
Demographic 1994 (N = 950 suspected AMI) 2003
Suspected AMI (N = 935) Suspected Other ACS (N = 430) Combined (N = 1365)
Mean age (years) (mean) (std dev) - 66 (13) 61*** (14) 64 (13)
Men 64 (12) 64 (13) 60*** (13) 63 (13)
Women 69 (11) 71 (13) 64*** (14) 69 (13)
Referral source (%)
Primary care physician 69 53 55 53
Self 24 39 33 38
Other 7 8 12 9
Admission mode to hospital (%)
Ambulance 46 48 38** 45
Car (passenger) 42 42 43 42
Car (driver) 8 6 12*** 8
Other 4 4 7 5
Distance from hospital at symptom onset
Median (range) miles 9 (0–165) 9 (0–80) 8 (0–150) 8 (0–150)
Previous CHD history (%)
AMI 24 16 31*** 21
Unstable angina 14 14 28*** 19
Coronary artery bypass graft 4 5 13*** 7
Percutaneous coronary intervention 2 6 18*** 10
(*p < .05, **p < .01, ***p < .001)
The demographic profile of patients admitted for suspected AMI in 2003 appears similar to those admitted in 1994. Other ACS patients differed from suspected AMI patients in 2003 in the following aspects: they were younger, less likely to be admitted by ambulance, more likely to drive themselves to hospital, and had a higher prevalence of previous ACS and coronary interventions.
Thrombolysis
Both location of, and speed of administration of thrombolysis have changed considerably in a positive direction since 1994 (Figure 1). In 1994, 38% of suspected AMI and 58% of confirmed AMI patients received thrombolysis, which occurred in I/CCU (96%), emergency department (2%) or other location (2%). In 2003, 41% of suspected AMIs and 44% of confirmed AMIs were thrombolysed in I/CCU (48%), emergency department (48%) or other location (4%). A further 4% of suspected AMIs received direct infarct angioplasty.
Figure 1 Thrombolysis administration locations and treatment times in 1994 and 2003
Emergency department delivered thrombolysis occurred in a significantly shorter time (median 35 minutes) than I/CCU administered thrombolysis (median 60 minutes) in 2003 (z = 5.62, p < .0001).
In 2003, 29% of those thrombolysed were treated within 90 minutes of calling for professional help. This rose to 42% and 62% within 2 and 3 hours respectively. On hospital arrival, 35% of patients were thrombolysed within 30 minutes, rising to 60% and 74% within 60 and 90 minutes respectively. Thirty-six per cent of hospitals thrombolysed 80% or more of patients in the emergency department while 56% of hospitals thrombolysed over 50% of patients in the emergency department.
Time to treatment
Suspected AMI patients waited a similar length of time to get to hospital from onset of symptoms in 2003 as 1994 (Table 2). Symptom onset to hospital arrival time was significantly higher for patients admitted with suspected other ACS in 2003 (3 h 35 mins vs 4 h 39 mins, z = 2.99, p < .01).
Table 2 Median overall time to treatment for all patients in 1994 and 2003
Treatment times 1994 Suspected AMI (n = 950) 2003
Thrombolysed AMIs (n = 382) Suspected AMI – non-thrombolysed (n = 553) All suspected AMI (n = 935) Suspected other ACS (n = 430) Total (n = 1365)
Symptom onset to hospital 3 h 30 mins 2 h 34 mins 5 h 00 mins*** 3 h 35 mins 4 h 39 mins** 3 h 56 mins
Call-to-thrombolysis Unavailable 2 h 20 mins - 2 h 20 mins - -
Hospital arrival to I/CCU 55 mins 1 h 10 mins 2 h 17 mins*** 1 h 40 mins 2 h 43 mins*** 1 h 55 mins
Hospital arrival to thrombolysis 76 mins 45 mins - 45 mins - -
I/CCU admission to thrombolysis 25 mins 20 mins - 20 mins - -
(*p < .05, **p < .01, ***p < .001)
Patients waited longer to be admitted to I/CCU in 2003, but received thrombolysis more quickly (45 mins v 76 mins) after hospital arrival. This represents a 41% decrease in time-to-thrombolysis since 1994. In 2003, total time to treatment for suspected AMI patients who received reperfusion was 4 hours 00 mins.
Patients with suspected AMI who were subsequently thrombolysed (thrombolysed AMIs) presented to hospital (2 h 34 mins vs 5 h, z = 7.33, p < 0.0001) and had a faster I/CCU transfer time (1 h 10 mins vs 2 h 17 mins, z = 8.92, p < 0.0001) than suspected AMI patients who were not thrombolysed (non-thrombolysed AMIs). Suspected other ACS patients also waited significantly longer than non-thrombolysed AMIs for hospital transfer to I/CCU (2 h 43 mins vs 2 h 17 mins; z = 2.128, p < 0.05).
In 1994, treatment times for patients referred by primary care physicians were significantly longer than those who self-referred (symptom onset to hospital arrival: primary care physician-referred 4 h 15 mins, self-referred 2 h 05 mins, p < 0.001). In 2003, primary care physician-referred suspected AMI patients also had a significantly longer pre-hospital delay (5 h vs 2 h 28 mins, z = 7.9, p < 0.001).
For suspected AMI patients, a previous experience of AMI made no difference to hospital presentation time (3 h vs 3 h 45 mins, z = 1.2, p > 0.05). There were no gender differences in pre-hospital delay time (3 h 53 mins for men vs 3 h 14 mins for women, z = 0.63, p > 0.05), or hospital arrival to thrombolysis time (45 mins for men vs 50 mins for women, z = 1.43, p > 0.05) for suspected AMI patients in 2003.
Discharge
For suspected AMI patients, there was an increase in those patients diagnosed with myocardial infarction of 21% from 1994 to 2003, and a 10% reduction in the diagnosis of unstable angina (Table 3).
Table 3 I/CCU discharge diagnoses and hospital mortality (%)
Discharge diagnosis 1994 Census (suspected AMI) % CCU 2003 Survey
Thrombolysed AMIs (n = 382) Suspected AMI – non-thrombolysed (n = 553) Suspected AMI Suspected Other ACS Total
Myocardial infarction 70 97 86*** 91 19*** 68
Unstable angina 14 <1 6*** 4 47*** 17
Other cardiac 9 5 11** 9 32*** 16
Non cardiac 7 1 5** 3 17*** 8
Mortality 11 9 10 10 1*** 7
Patients may have more than one diagnosis
(*p < .05, **p < .01, ***p < .001)
In 2003, thrombolysed AMIs were more likely to be discharged as having myocardial infarction than non-thrombolysed AMIs, but were less likely to receive a discharge diagnosis of unstable angina, other cardiac or non-cardiac diagnoses. All suspected AMI patients in 2003 were more likely to be discharged as having had myocardial infarction and were more likely to die in hospital than suspected other ACS patients, but were less likely to have discharge diagnoses of unstable angina, other cardiac or non cardiac.
Discussion
The present survey outlines the current presentation and management of ACS in Ireland. This study built on the previous research conducted in 1994, but also expanded its findings beyond suspected AMI patients to all suspected ACS patients. Pre-hospital patient delay remains stable and substantial, while a considerable reduction (41%) in time to thrombolysis from hospital admission has occurred since 1994. This can probably be attributed in large part to the relocation of thrombolytic administration to the emergency department, thereby reducing the 'door-to-needle' times in 2003. Similarly, treatment of AMI patients in emergency departments prior to transfer to I/CCU may account for longer I/CCU transfer times in 2003.
Significant progress has been made in the treatment of AMI patients who receive thrombolysis, which has yielded faster 'door-to-needle' times. Suspected AMI patients who received thrombolysis in the 2003 sample were treated more quickly than 1994 (median 45 mins v 76 mins).
The transfer of thrombolytic administration from the I/CCU (96% in 1994) to the emergency department (48% in 2003, with 48% administered in I/CCU) is probably the main reason for the decreased time to treatment for thrombolysed patients. The present survey found, for instance, that 56% of hospitals thrombolysed over half of their patients in the emergency department. It is not clear, however, that an additional shift of thrombolysis to the emergency department in the remaining hospitals would also result in a further reduction of 'door-to-needle' time. This is because some hospitals already adopt a 'fast-track' policy, where chest pain patients are admitted directly to CCU, bypassing emergency department assessment. Adopting a strategy of emergency department thrombolysis may have little or no effect in these cases.
Nonetheless, only 35% of patients received thrombolysis within 30 mins of hospital arrival, which compares unfavourably to other surveys (e.g. in England and Wales in 2003, the MINAP study found that over 80% of patients were thrombolysed within 30 mins of hospital arrival [24]). These comparisons must be interpreted with some caution however, since MINAP does not count cases which have a component of extra delay due to clinical reasons (i.e. patients presenting with contraindications to thrombolysis), and reports on all eligible STEMI cases treated within 30 mins of hospital arrival. Our analysis included all patients who eventually received thrombolysis, even those patients who developed ST-elevation some time after hospital arrival. While our results may not be completely comparable to other similar surveys, the overall message that thrombolysis is unsatisfactory both in absolute and comparative terms is clear.
Substantial pre-hospital and in-hospital delays were seen for non-thrombolysed AMIs. Suspected AMI patients who did not receive thrombolysis waited significantly longer for transfer to I/CCU than those who received thrombolysis. Indeed, this group of AMIs had comparable times to patients with suspected other ACS. These patients presented to hospital more slowly than thrombolysed AMIs. This may indicate the less severe symptoms of unstable angina and non-ST-elevation myocardial infarction. Also, recent changes in AMI definition have lead to increases in proportions of diagnosed AMI patients and decreases in proportions of patients diagnosed with unstable angina [20-22]. These changes probably preclude exact comparison with 1994 findings. Adding credence to this hypothesis was the large change in discharge diagnoses. Considering suspected AMIs, the proportion of patients diagnosed with myocardial infarction increased by 21% from 1994 to 2003, with a corresponding 10% reduction in unstable angina diagnoses. The reduction in 'non cardiac' discharges for suspected AMI patients (7% in 1994 to 3% in 2003), may be partially attributed to definition change [21]. Finally, the 14% decrease in thrombolysed confirmed AMIs may also be attributed to the definition change, with a larger portion of AMI patients being ineligible for thrombolysis in 2003.
Suspected AMI patients who did not receive thrombolysis took significantly longer from hospital arrival to arrive in I/CCU than did patients who received thrombolysis. Suspected other ACS patients presented to hospital in time frames similar to suspected AMI patients who did not receive thrombolysis, but were not admitted to I/CCU as quickly. The development of chest pain assessment units and other similar units (e.g. medical admission units), which involve the initial screening of chest pain patients to determine whether the pain is cardiac in origin prior to transfer to I/CCU, may have skewed the data in the current survey. A typical scenario may be that a patient currently arrives at hospital, without ST-elevation when assessed by ECG, and is assessed for some time in the chest pain assessment unit to either 'rule-in' or 'rule-out' ACS. In the past, such patients may have been admitted directly to I/CCU. In addition, these findings may reflect the triaging of patients in the emergency department, where patients labelled as suspected AMI were treated more quickly than those labelled as suspected other ACS. Patients can be triaged into groups reflecting the necessity for immediate treatment. Non-ST-elevation myocardial infarction and unstable angina patients may be detained for observation in the emergency department. It might also be that pressure for I/CCU bed places is more quickly resolved for the more acute ST-elevation AMI patients. However, further prospective observational research on this aspect of care is required.
Patient delay prior to hospital arrival is still the biggest impediment to improving treatment times for AMI and other ACS. Patients who were referred by primary care physicians had a significantly longer time to treatment than those who self-referred in both 2003 and 1994. Clearly, in the present system, although substantial improvements have been made since the mid-1990s, a 'call-to-treatment' standard of 90 minutes is not currently being met. The present survey found that 29% of patients were thrombolysed within 90 minutes of calling for professional help. Future research and resources need to focus on a reduction in pre-hospital delay factors by the services and professional groups concerned. A number of psychological studies have provided detailed examination of patient contributions to delayed help-seeking for AMI [25-27]. These highlight possibilities for intervention to reduce symptom onset to help-seeking times but caution against a simplistic public education campaign approach. Since general public advertising/education campaigns have little efficacy [25,26,28] and even a previous experience of AMI has no effect on pre-hospital call for assistance times, sophisticated strategies are needed to address this problem.
As regards reducing health services delay, one method is to authorise health professionals in the pre-hospital setting to administer thrombolysis. Ambulance personnel and primary care physicians are the two most obvious choices. The administration of thrombolysis by ambulance personnel has been shown to reduce time to treatment [29]. A recently completed study on thrombolysis administered by primary care physicians showed the practicalities of this approach in an Irish setting [30]. In the hospital setting, involving nurses in decision-making processes for thrombolysis has been shown to be effective in reducing treatment times [31,32]. The provision of more mobile coronary care units may also reduce delay times in rural areas [33].
The present study has highlighted the need for a national prospective registry of ACS. The value of such registries has been shown in other countries. For example, registries increase the use of appropriate reperfusion therapy, but to ensure this practice continues they need to be ongoing [34]. In the UK, MINAP [35] has contributed to an increase in the numbers of patients thrombolysed within recommended timescales. For example, following the publication of the NSF guidelines on CHD in 2000 [11], the proportion of patients receiving thrombolysis within 30 minutes of hospital arrival more than doubled (79% in 2002, compared with 38% pre-2000) [36]. Registries can also underscore the extent of adherence to international guidelines. The current Irish data highlight progress in some areas over a nine-year period but indicate that improvements need to occur in other aspects. A national registry can provide the continuous feedback needed to keep a focus on areas for improvement. The monitoring of guideline adherence should even be considered a part of optimal practice procedures [37].
Conclusions
Significant progress in some aspects (e.g. time to thrombolysis) of care for suspected ACS has occurred, but there is still scope for improvement. A necessary goal is to increase the proportions of patients seen within the recommended time. Other aspects of ACS care also now require attention. Patient delay pre-hospital should remain the main focus of future research. The implementation of a national registry would allow resources to be focused on these aspects and facilitate routine health care monitoring.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
FD carried out the survey, analysed the data and drafted the manuscript. HM, DD & ES conceived of the study and participated in its design and coordination. RC participated in the study design and coordination, and provided statistical input on data analysis and interpretation. All authors provided critical input on manuscript drafts, and approved the final version.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
This project was funded by a grant from the Cardiovascular Strategy, Department of Health and Children.
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| 15703081 | PMC549555 | CC BY | 2021-01-04 16:03:07 | no | BMC Cancer. 2005 Feb 9; 5:16 | latin-1 | BMC Cancer | 2,005 | 10.1186/1471-2407-5-16 | oa_comm |
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BMC Public HealthBMC Public Health1471-2458BioMed Central London 1471-2458-5-141569847210.1186/1471-2458-5-14Research ArticleTreatment outcome of new culture positive pulmonary tuberculosis in Norway Farah Mohamed Guled [email protected] Aage [email protected] Tore W [email protected] Einar [email protected] Arne B [email protected] Gunnar [email protected] Norwegian Institute of Public Health, Oslo, Norway2 Department of General Practice and Community Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway3 Health and Welfare Agency, City of Oslo, Norway2005 7 2 2005 5 14 14 3 9 2004 7 2 2005 Copyright © 2005 Farah et al; licensee BioMed Central Ltd.2005Farah 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 key elements in tuberculosis (TB) control are to cure the individual patient, interrupt transmission of TB to others and prevent the tubercle bacilli from becoming drug resistant. Incomplete treatment may result in excretion of bacteria that may also acquire drug resistance and cause increased morbidity and mortality. Treatment outcome results serves as a tool to control the quality of TB treatment provided by the health care system. The aims of this study were to evaluate the treatment outcome for new cases of culture positive pulmonary TB registered in Norway during the period 1996–2002 and to identify factors associated with non-successful treatment.
Methods
This was a register-based cohort study. Treatment outcome was assessed according to sex, birthplace, age group, isoniazid (INH) susceptibility, mode of detection and treatment periods (1996–1997, 1998–1999 and 2000–2002). Logistic regression was also used to estimate the odds ratio for treatment success vs. non-success with 95% confidence interval (CI), taking the above variables into account.
Results
Among the 655 patients included, the total treatment success rate was 83% (95% CI 80%–86%). The success rates for those born in Norway and abroad were 79% (95% CI 74%–84%) and 86% (95% CI 83%–89%) respectively. There was no difference in success rates by sex and treatment periods. Twenty-two patients (3%) defaulted treatment, 58 (9%) died and 26 (4%) transferred out. The default rate was higher among foreign-born and male patients, whereas almost all who died were born in Norway. The majority of the transferred out group left the country, but seven were expelled from the country. In the multivariate analysis, only high age and initial INH resistance remained as significant risk factors for non-successful treatment.
Conclusion
Although the TB treatment success rate in Norway has increased compared to previous studies and although it has reached a reasonable target for treatment outcome in low-incidence countries, the total success rate for 1996–2002 was still slightly below the WHO target of success rate of 85%. Early diagnosis of TB in elderly patients to reduce the death rate, abstaining from expulsion of patients on treatment and further measures to prevent default could improve the success rate further.
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Background
The key elements in tuberculosis (TB) control are to detect the disease as early as possible and to ensure that those diagnosed complete their treatment and get cured. The World Health Organization (WHO) target for treatment success is 85 percent of all detected smear-positive cases [1]. Even where free medication is available, many patients are not successfully treated [2,3]. Main reasons for non-success are death (while on treatment or before start of treatment) and loss to follow-up. Incomplete treatment may result in prolonged excretion of bacteria that may also acquire drug resistance, cause transmission of disease and lead to increased morbidity and mortality [4].
Norway has about 4.5 million inhabitants, with foreign-born residents comprising 6.9% of the total population in 2002. The proportion of TB cases from foreign-born residents has increased from 19 % in 1986 to 76 % in 2002 [5]. However, the total number of cases has remained relatively stable. The reporting of treatment outcome for all TB cases has been obligatory since 1996. A study on treatment outcome for culture positive pulmonary TB in Norway in 1995 showed a high death rate and a high rate of loss to follow-up. Only 76% of patients who were included in that study completed treatment [6]. While the incidence rate of TB is low in Norway compared to most countries in the world, challenges still remain in achieving the WHO target for treatment success. However, there are some problems with the WHO definition of success rate and other measures have been proposed. A working group from the WHO, the International Union Against Tuberculosis and Lung Disease (IUATLD) and the Royal Netherlands Tuberculosis Association (KNCV) have defined a reasonable target for treatment outcome in low-incidence countries as to reduce the proportion of patients with a potentially bacteriologically unsuccessful outcome (failure, default, transfer) to less than 10% [7].
The aims of this study were to evaluate the treatment outcome for new culture positive pulmonary TB cases registered in Norway during the period 1996–2002, and to identify factors associated with non-successful treatment.
Methods
Setting and study population
This was a register-based cohort study. In Norway, there is compulsory nominative notification of all TB cases directly to the National TB Registry. Both suspected and confirmed cases have to be reported by clinicians. Laboratories of clinical microbiology are also required to report all isolates of Mycobacteria. A total of 25 microbiological laboratories isolate M. tuberculosis from patient samples. The laboratory at the Norwegian Institute of Public Health functions as a national reference laboratory for TB. The Pharmacy at the National Hospital is the only pharmacy distributing drugs for TB treatment, and TB prescriptions are compared with the National TB Registry in order to identify cases that may not have been notified. The notification is therefore considered to be quite complete [8]. There is also compulsory notification of all treatment outcomes to the Registry. Nine months after treatment start, the Register sends a special form to the clinician in charge to be filled out with details of the treatment outcome.
In this study, we included all new cases with culture positive pulmonary TB notified during 1996–2002. The sputum smear results were not recorded or reported for all cases, especially in the first years of the study period. We therefore based our analysis of treatment outcome on new cases with culture positive pulmonary TB.
The mode of detection was determined by information on the notification form. Data on susceptibility to TB drugs was obtained from the notification forms and laboratory reports. In addition to the information in the TB Registry, we used data from the Cause of Death Registry at Statistics Norway to determine the cause of death for those who died under treatment or before start of treatment.
Recommended regime for TB treatment in the study period consisted of isoniazid (INH), rifampicin and pyrazinamide in the intensive phase (two months). Ethambutol was added when resistance was suspected such as in foreign-born patients and in previously treated patients. The continuation phase consisted of four months with INH and rifampicin [9].
Directly Observed Therapy (DOT) was used before 2003 on an individual basis. However, we have no data to show how many patients in this study received DOT.
Definition
The treatment outcome was divided into six categories according to WHO guidelines, with some modifications [10]. These categories were: cured (finished treatment with negative bacteriology result at the end of treatment), completed treatment (finished treatment, but without bacteriology result at the end of treatment), failure (remaining smear/ culture positive at five months despite correct intake of medication), defaulted treatment (patients who interrupted their treatment for two consecutive months or more after registration), died (patients who died due to TB or other cause before or during treatment), transferred out (patients whose treatment results are unknown due to emigration before or during treatment). Patients who changed treatment due to multi-drug resistant TB (MDR-TB), i.e. resistance to both INH and rifampicin, were also defined as failures [11].
Treatment success was defined as the sum of the cases that were cured and that completed treatment.
The proportion of patients with a potentially bacteriologically unsuccessful outcome (failure, default, transfer) was also calculated [7].
Statistical analysis
We used the statistical package SPSS, version 11.0 for data analysis. To estimate the odds ratio for treatment outcome (success vs. non-success), logistic regression analysis was used. Confidence interval (CI) for the odds ratio has also been given. Variables such as sex, birthplace, age group, INH susceptibility, mode of detection and treatment periods (1996–1997, 1998–1999 and 2000–2002) were entered into both univariate and multivariate logistic regression model. P values of less than 0.05 were considered statistically significant.
Results
Six hundred and fifty-five new culture positive pulmonary TB patients were included in the study (table 1). Of these, 397 patients (61%) were foreign-born. Three hundred and twenty three patients (49%) were cured and 221 patients (34%) completed treatment. This gives a treatment success rate of 83% (95% CI 80%–86%). The treatment success rates for women and men were 86% (95% CI 82%–90%) and 81% (95% CI 77%–85%) respectively. For those born in Norway and abroad, the rates were 79% (95% CI 74%–84%) and 86% (95% CI 83%–89%) respectively. The rates for the treatment periods 1996–1997, 1998–1999 and 2000–2002 were 83% (95% CI 77%–89%), 82% (95% CI 76%–88%) and 84% (95% CI 80%–88%) respectively.
Table 1 Number of new culture positive pulmonary tuberculosis patients by patient characteristics and treatment outcome, Norway, 1996–2002
Cured Completed treatment Failure* Defaulted treatment Died Transferred Out† Total
Sex
Women 144 90 2 7 17 11 271
Men 179 131 3 15 41 15 384
Birthplace
Norway 119 84 1 5 49 0 258
Abroad 204 137 4 17 9 26 397
Age group (yrs)
0–14 6 19 0 1 0 0 26
15–39 170 105 3 13 4 14 309
40–64 59 45 2 4 11 10 131
65+ 88 52 0 4 43 2 189
INH-resistance‡
No 295 210 0 15 53 22 595
Yes 21 10 5 7 2 4 49
Mode of detection# (due to symptoms)
Yes 221 154 3 16 47 12 453
No 100 67 2 6 11 13 199
Treatment periods
1996–1997 67 48 0 3 19 2 139
1998–1999 83 58 1 7 20 3 172
2000–2002 173 115 4 12 19 21 344
*All patients are MDR-TB patients
†All patients have left the country
‡Information for INH susceptibility was available for 98.3% of the patients
#Information for mode of detection was available for 99.5% of the patients
In our study, the proportion of patients with a potentially bacteriologically unsuccessful outcome (failure, default, transfer) was 8%.
The average duration of residence in Norway for foreign-born patients at TB registration was 3.8 (range 1–31) years. There were no differences in the treatment success rates for those who had lived in Norway for less than three years and for those who had stayed longer than three years.
Among the 22 patients who defaulted treatment (3%) (table 1), four had MDR-TB and three additional patients had isolated INH resistant strains at the start of the treatment. The default rate was higher among foreign-born and male patients.
There were 26 patients (4%) who were transferred out (table 1). Of these, 21 were reported in 2000–2002. All of them have left the country. Twenty-two were on treatment when they left the country and four had not started treatment. Among the 26, seven were expelled from the country. Six of these were on treatment and one had not started treatment at the time of expulsion. For those who left the country while on treatment, the average duration of treatment was 78 days. Twelve of them had treatment only for two months or less. Of the 26 patients who were transferred out, three had isolated INH resistant strains and one had MDR-TB when they left the country.
Altogether 58 patients (9%) died, 19 (3%) before treatment start and 39 (6%) while on treatment. Of those who died before treatment start, four were diagnosed after death at autopsy. Eighty four percent of those who died were born in Norway. The median age for all who died was 80 years. For those who died before treatment start, the median age was 71 years. For those who died while on treatment, the median age was 81 years and the average duration of treatment was 67 days. Sixteen patients died within 14 days of treatment start. For 23 patients, TB was the primary cause of death. It was the only cause of death for nine of those 23 patients. For further 20 patients, TB was a contributing factor to their death. Fourteen patients died from other diseases than TB. The cause of death was unknown for one patient (table 2).
Table 2 Primary causes of death among new culture positive pulmonary tuberculosis patients, Norway, 1996–2002*
Tuberculosis mentioned on the death certificate
Yes (N = 43) No (N = 14))
Tuberculosis (N = 23)† Heart failure (N = 1)
Acute myocardial infarction (N = 3) Unspecified HIV disease (N = 1)
Heart failure (N = 2) Unspecified non-Hodgkin's lymphoma (N = 1)
Unspecified cardiac arrest (N = 1) Amyloidosis (N = 1)
Stroke, not specified as haemorrhage or infarction (N = 2) Multiple myeloma (N = 1)
Chronic ishaemic heart disease (N = 2) Mental and behavioural disorders due to use of opoids (N = 1)
Paroxysmal tachycardia (N = 1) Mental and behavioural disorders due to multiple drug use and use of other psychoactive substances (N = 1)
Other chronic obstructive pulmonary disease (N = 1) Malignant neoplasm of bronchus and lung (N = 5)
Unspecified respiratory failure (N = 1) Liver cell carcinoma (N = 1)
Unspecified HIV disease (N = 1) Other ill-defined and specified causes of mortality (N = 1)
Other acute viral hepatitis (N = 1)
Unspecified sepsis (N = 1)
Unspecified non-Hodgkin's lymphoma (N = 1)
Spinal muscular atrophy and related syndromes (N = 1)
Malignant neoplasm of breast (N = 1)
Malignant neoplasm of bronchus and lung (N = 1)
*The cause of death was unknown for one patient
†Including respiratory and miliary tuberculosis
There was no systematic registration of TB/ human immunodeficiency virus (HIV) co-infection at the TB Registry. For those who died while on treatment or before treatment started, HIV disease was registered as the cause of death for two patients (table 2).
Table 3 gives the odds ratio from logistic regression. The effect of birthplace in the treatment success changed from the univariate to the multivariate analysis. Patients who were born abroad had higher odds of success in the univariate analysis, but this changed to lower odds for success in the multivariate analysis. This is due to a strong confounding effect of age. The effect of age was distinct and graded, slightly stronger in the multivariate analysis. Both in the univariate and multivariate analysis, the odds for success were lower for those with INH resistant strains than for those with INH susceptible strains.
Table 3 Odds ratio (OR) for treatment success vs. non-success among new culture positive pulmonary tuberculosis patients notified in Norway, 1996–2002
Treatment Success Univariate Multivariate*
Yes No OR 95% CI OR 95% CI
Sex
Women 234 37 ref. ref. ref. ref.
Men 310 74 0.7 04–1.0 0.7 0.4–1.1
Birthplace
Norway 203 55 ref. ref. ref. ref.
Abroad 341 56 1.7 1.1–2.5 0.7 0.3–1.3
Age group (yrs)
0–14 25 1 8.7 1.2–65.6 11.8 1.5–92.6
15–39 275 34 2.8 1.7–4.6 4.8 2.3–10.0
40–64 104 27 1.3 0.8–2.3 2.0 1.1–3.9
65+ 140 49 ref. ref. ref. ref.
INH-resistance
No 505 90 ref. ref. ref. ref.
Yes 31 18 0.3 0.2–0.6 0.2 0.1–0.4
Mode of detection (due to symptoms)
Yes 375 78 ref. ref. ref. ref.
No 167 32 1.1 0.7–1.7 1.1 0.7–1.7
Treatment periods
1996–1997 115 24 0.9 0.6–1.6 1.2 0.7–2.2
1998–1999 141 31 0.9 0.5–1.4 0.9 0.5–1.5
2000–2002 288 56 ref. ref. ref. ref.
*In the multivariate analysis, all variables in the univariate analysis were considered
Susceptibility testing for the main TB drugs was done in most of the patients. However, susceptibility testing for streptomycin was done for fewer patients than other main TB drugs. Resistance to INH and streptomycin was most common, and resistance was frequent among foreign-born patients. Of those with MDR-TB, two were born in Norway and eight abroad.
Of the 655 patients included in this study, 453 were detected through passive case finding (due to their symptoms). Another 101 patients were discovered through the immigration TB screening program. A total of 52 patients were detected through following ups of close contacts of identified infectious cases (22 cases) and of previous abnormal mass miniature radiology (MMR) (32 cases). The remainder was discovered through other screening programs. No information on mode of detection was available for three patients.
Discussion
In our study, the total treatment success rate for new culture positive pulmonary TB for the period 1996–2002 was 83%. This is close to the WHO target of success rate of 85% of all smear positive cases. However, subgroups of patients contributing to low success rate warrant special attention such as those who defaulted treatment, those who were transferred out and those who died. The first two subgroups mainly comprise patients who were born abroad and the last subgroup mainly comprises patients who were born in Norway. Despite these problems, Norway has reached the reasonable target for treatment outcome in low-incidence countries [7].
Our study shows a default rate of 3%. Higher default rates have been described in other studies such as Vaud County, Switzerland (16%) [2], Hamburg, Germany (10%) [12], and Sweden (7%) [3]. Although the default rate in Norway is lower than in these countries, some of the patients who defaulted treatment, including patients with MDR-TB, have been the cause of small on-going outbreaks [13]. Default can constitute a major public health problem. Although incomplete treatment can prevent patients from dying from TB, the patients may remain infectious and even develop MDR-TB. It is therefore worrying that several patients in our study who defaulted treatment had isolated INH resistant strains or MDR-TB prior to treatment. Language problems, lack of understanding of the patients' cultural background, lack of communication between primary health care and hospitals, frequent change of address and stigma related to TB might be some of the reasons for defaulting. DOT was used on an individual basis during the study period, especially when an increased risk of non-adherence was suspected, but it became mandatory in Norway from 2003 according to the new TB regulations [14]. Adoption of this strategy will hopefully improve treatment adherence further.
In the transferred out group, the majority of patients left the country on their own initiative, but seven were expelled. Most of the patients who left the country were on treatment, but we do not have information about their treatment outcome. It is worrying that some of the patients who were expelled moved to countries with political unrest and poorly functioning TB programs. In this group three patients already had isolated INH resistant strains and one had MDR-TB. Expelling patients with TB before completion of treatment is unfortunate, unless it can be guaranteed that adequate treatment will be provided elsewhere. Efforts should be made to ensure the continuity of treatment for patients who move out of the country and, if possible, to allow them to start and complete their treatment, even if they have to leave the country later. The Netherlands have adopted a system where patients are not expelled from the country as long as they are on treatment. According to the new Norwegian manual for TB control and prevention [11], health personnel should encourage patients who are at risk to be expelled from the country to inform the Norwegian Directorate of Immigration through their legal representatives about their disease, and they may then be allowed to stay until treatment is completed. However, we believe there is a need for more awareness among health personnel, immigration authorities, the police and the legal representatives of the patients about this possibility.
The death rate in our study was 9%. Other studies from low TB incidence regions of the world showed death rates among TB patients of 24%, 14% and 6% in Baltimore City, USA [15], Vaud County, Switzerland [2] and Hamburg, Germany [12] respectively. Common for these studies and our study is that most patients who died were old, and many of them also had other illnesses. But if we only include only patients who started treatment, the actual death rate for our study was 6%. When considering the treatment outcome of TB, many studies including ours, include patients who never started treatment. This might seem contradictory, but it is an important issue that shows a deficiency in TB control. This is also in line with the recommendations of a working group of the WHO and the European Region of the IUATLD for uniform reporting by cohort analysis of treatment outcome in TB patients [16]. It has been suggested that acceptable treatment success rates need to be revised under such circumstances. It is difficult to know to what extent the death of the nine patients whose only cause of death was TB could have been prevented. Diagnosis of pulmonary TB can be especially difficult in older patients with co-existing illness. In one study, it was suggested that treatment of latent TB in such high risk elderly patients should be a high priority although advanced age is a relative contraindication [17]. Other studies recommend the start of anti-TB treatment on suspicion whilst awaiting results of diagnostic tests in elderly patients, provided there is no other obvious cause of their illness [18,19]. This makes sense as our study shows that 19 patients died before treatment start and four of them were diagnosed at autopsy. Two studies from Canada [20] and former Yugoslavia [21] have concluded that delay in diagnosis of TB was the main factor contributing to death from TB. Delay in diagnosis is outside the scope of this study. But autopsy rates in Norway are low [18] and therefore it is likely that there is under-diagnosis of deaths due to TB.
As indicated in the results section, TB/HIV co-infection is not a common cause of death for TB patients in Norway as most of the patients born in Norway were elderly persons with low risk of HIV and most foreign-born patients were from countries with low levels of HIV infection [22]. Therefore, we believe that it had a minor impact on the treatment outcome.
In the logistic regression model, increasing age and INH resistance were significant risk factors for non-successful treatment. We expected to find that age played a role, since old age in itself will contribute towards higher mortality, partly through co-existing illness. INH is a powerful bactericidal drug and resistance to the drug might reduce the effectiveness of standard short-course treatment [23]. Treatment was fairly standardized even in the previous TB manual from 1996: Four drugs to all foreign-born and to all previously treated TB patients and three drugs to patients born in Norway who were not likely to have been infected with drug resistant strains abroad. However, an analysis made by the National TB register in 1999 showed that only 75% of foreign-born patients received four drugs at the start of their treatment (Heldal E, personal communication, National TB Registry of Norway).
Conclusion
Although the TB treatment success rate in Norway has increased compared to previous studies and although it has reached a reasonable target for treatment outcome in low-incidence countries, the total success rate for 1996–2002 was still slightly below the WHO target of success rate of 85%. Early diagnosis of TB in elderly patients to reduce the death rate, abstaining from expulsion of patients on treatment and further measures to prevent default could improve the success rate further.
List of abbreviations
CI- Confidence interval
HIV- Human immunodeficiency virus
INH- Isoniazid
IUATLD- International Union Against Tuberculosis and Lung Disease
KCNV-Royal Netherlands Tuberculosis Association
MDR-TB- Multi-drug resistant tuberculosis, i.e. resistance to both isoniazid and rifampicin
TB- Tuberculosis
WHO- World Health Organization
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
MGF participated in all phases of preparation of the manuscript (collection of data, analysis and interpretation of results and writing of the manuscript) and is corresponding author. AT, TWS, EH, ABB and GB have participated the interpretation of results and writing 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:
Acknowledgement
We thank Nanne Brattås, Vigdis Dahl, Oddny Lillevik, Britta Winje and Ellen Nelson for technical assistance and help in data collection. We also thank John-Arne Rottingen and Preben Aavitsland for their constructive comments. This study was conducted at the Norwegian Institute of Public Health, Oslo, Norway, in co-operation with the Department of General Practice and Community Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway. It was financed with the support of the Norwegian Foundation for Health and Rehabilitation and the Norwegian Heart and Lung Association.
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| 15698472 | PMC549556 | CC BY | 2021-01-04 16:28:54 | no | BMC Public Health. 2005 Feb 7; 5:14 | utf-8 | BMC Public Health | 2,005 | 10.1186/1471-2458-5-14 | oa_comm |
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BMC GeriatrBMC Geriatrics1471-2318BioMed Central London 1471-2318-5-41570306610.1186/1471-2318-5-4Research ArticleUse of dietary supplements by female seniors in a large Northern California health plan Gordon Nancy P [email protected] Donna M [email protected] Kaiser Permanente Medical Care Program, Oakland, California, USA2005 9 2 2005 5 4 4 6 4 2004 9 2 2005 Copyright © 2005 Gordon and Schaffer; licensee BioMed Central Ltd.2005Gordon and Schaffer; 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
Women aged ≥ 65 years are high utilizers of prescription and over-the-counter medications, and many of these women are also taking dietary supplements. Dietary supplement use by older women is a concern because of possible side effects and drug-supplement interactions. The primary aim of this study was to provide a comprehensive picture of dietary supplement use among older women in a large health plan in Northern California, USA, to raise awareness among health care providers and pharmacists about the need for implementing structural and educational interventions to minimize adverse consequences of self-directed supplement use. A secondary aim was to raise awareness about how the focus on use of herbals and megavitamins that has occurred in most surveys of complementary and alternative therapy use results in a significant underestimate of the proportion of older women who are using all types of dietary supplements for the same purposes.
Methods
We used data about use of different vitamin/mineral (VM) supplements and nonvitamin, nonmineral (NVNM) supplements, including herbals, from a 1999 general health survey mailed to a random sample of adult members of a large Northern California health plan to estimate prevalence of and characteristics associated with supplement use among women aged 65–84 (n = 3,109).
Results
Based on weighted data, 84% had in the past 12 months used >1 dietary supplement, 82% a VM, 59% a supplement other than just multivitamin or calcium, 32% an NVNM, and 25% an herbal. Compared to white, nonHispanic women, African-Americans and Latinas were significantly less likely to use VM and NVNM supplements and Asian/Pacific Islanders were less likely to use NVNM supplements. Higher education was strongly associated with use of an NVNM supplement. Prevalence did not differ by number of prescription medications taken. Among white, nonHispanic women, multiple logistic regression models showed that college education, good health, belief that health practices have at least a moderate effect on health, and having arthritis or depression significantly increased likelihood of NVNM use, while having diabetes decreased likelihood.
Conclusions
An extremely high proportion of older women are using dietary supplements other than multivitamins and calcium, many in combination with multiple prescription medications. Increased resources should be devoted to helping clinicians, pharmacists, supplement vendors, and consumers become more aware of the safety, effectiveness, and potential side effects of dietary supplements.
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Background
A recent national survey of medication use patterns found the highest prevalence of medication use over a one-week period was among women aged ≥ 65 years [1]. Over 80% of women in this age group had taken at least one prescription or over-the-counter medication during the week preceding the survey, and over half had taken five or more medications. In addition to these prescription medications, nearly 60% had used some type of vitamin/mineral supplement and 14% an herbal or other type of dietary supplement. These estimated prevalences of vitamin/mineral, herbal, and other supplement use are higher than those derived from previous national surveys [2-4], and by extrapolation, so is the prevalence of concomitant use of supplements and drugs. While many herbal medications and dietary supplements are safe for most people to use [5], there is growing evidence that some herbs and other types of non-herbal supplements can cause serious adverse effects [6-9]. Given the large proportion of this group concurrently using clinician-prescribed medications and self-prescribed dietary supplements, there is a great potential for drug-supplement interactions, especially since several surveys have shown that patients generally do not report or under-report use of supplements to their clinicians and pharmacists [10-13].
In a previous study, we used data from a 1999 general health survey of adult members of the Kaiser Permanente Medical Care Program of Northern California (KPCMP) to characterize use of nonvitamin, nonmineral (NVNM) supplements, including herbals, among the adult membership of this large health plan [14]. The results presented here expand on the earlier work by including vitamin/mineral (VM) supplement use, focusing on women aged 65–84, and employing logistic regression modeling to identify predictors of different types of dietary supplement use among these women. Our intent is to provide a comprehensive picture of dietary supplement use among this growing segment of the health care seeking population as a basis for planning structural and educational interventions to minimize adverse consequences of self-directed supplement use. A second aim is to raise awareness about how the focus on use of herbals and megavitamins that has occurred in most surveys of complementary and alternative therapy use results in a significant underestimate of the proportion of older women who are using all types of dietary supplements for the same purposes. This project was approved by the Kaiser Foundation Research Institute's Institutional Review Board in Oakland, CA.
Methods
Data sources
During Spring 1999, a confidential general health survey ("Adult Member Health Survey") was mailed to a stratified random sample of 40,000 adults aged ≥ 25 who were members of the Kaiser-Permanente Medical Care Program in Northern California. Up to three attempts were made to obtain a mailed response from each person in the sample unless the individuals refused or were deemed ineligible due to curtailment of membership, death, language barrier, or incorrect address. The survey questionnaire used in the first two mailing attempts included questions about use of complementary and alternative medicine (CAM) modalities and dietary supplement use, in addition to questions covering demographic and health-related characteristics and medication use. (A shortened form of the questionnaire sent to non-respondents to the first two mailings did not contain the CAM and dietary supplement questions.) Completed non-abridged questionnaires were received from 72% (n = 3,109) of women aged 65–84 in the survey sample. We restricted our estimates to women under age 85 because both the response rate and numbers of respondents aged ≥ 85 were too low to generalize about the "oldest old" cohort.
Use of dietary supplements during the previous 12 months was ascertained through two questions. First, a question covering use of 19 different CAM modalities: "Have you used the following methods to help treat or prevent health problems?" included items for "Any herbal medicine or supplement" and "Megavitamins/high dose vitamin therapy (not including daily multiple vitamin)." A separate question asked about use of selected dietary supplements: "In the past 12 months, did you use any nutritional supplements?" This question had a response checklist that included daily multiple vitamin with or without minerals (e.g., Centrum, One-a-Day), calcium with or without vitamin D, vitamin C, vitamin E, melatonin, ginkgo biloba, Echinacea, kava kava, glucosamine, St. John's Wort, and a space to write in other supplements, which were then individually coded and categorized as herbal supplements, other nonvitamin/nonmineral (NVNM) supplements, or vitamin/mineral (VM) supplements. Respondents were classified as VM users if they reported use of one or more vitamins/minerals, although we further subdivided this group into multivitamin and/or calcium users only and those who reported using other VMs such as vitamins C and E or minerals such as zinc and magnesium, with or without a daily multivitamin and/or calcium ("Dietary Supplement other than a Multivitamin and/or Calcium"). Respondents were classified as herbal users if they had indicated herbal use on the CAM modality checklist or indicated use of one or more herbals in the dietary supplement checklist. Respondents were classified as NVNM supplement users if they had indicated use of any of the herbals, glucosamine, or melatonin on the dietary supplement checklist or wrote in a supplement subsequently categorized as an herbal/botanical, amino acid, enzyme, protein, hormone or other non-herbal NVNM dietary supplement [15].
The estimated percentages of women who regular took one or more prescription medications were based on response to the question "How many prescription medicines do you regularly take," while estimated use of prescription medication with a narrow therapeutic index was based on health plan pharmacy data for the sample. The decision to use self-report rather than pharmacy data to estimate the numbers of prescription medications regularly was made because nearly 17% of the women had reported filling prescriptions outside of the health plan during the 12 months preceding the survey, and also because it was going to be extremely labor-intensive to determine from pharmacy data the numbers of different types of prescription medications each respondent "regularly" used.
Statistical analysis
The respondent sample was assigned post-stratification weights so that analyses with weighted data would reflect the actual age (by 5-year intervals), gender and geographic distribution of the adult membership from which the sample was drawn. All percentages reported in the text and tables are based on weighted data. However, the tables include the actual (unweighted) subgroup denominators used in the analyses. All analyses were performed using PC-SAS version 8.2 [16]. Calculations of 95% confidence intervals (CI) and significance testing were done using the Proc Surveymeans procedure for data collected using a multi-stage survey design. The range of the confidence intervals is affected by the size of the subgroup denominator, which is why confidence intervals are tighter around prevalence estimates for the white, nonHispanic (whiteNH) subgroup than the estimates for the other race/ethnic subgroups.
Prevalence ratios (PR) were calculated to compare supplement use rates for subgroups of interest against rates for a reference group (e.g., herbal use among women aged 75–79 vs. aged 65–74). Confidence intervals around the PRs were used to assess the range of PR's compatible with the data at a level of 95% confidence. In the text and tables, a PR confidence interval that includes 1.0 indicates that rates are not statistically significantly different from each other at the p < .05 level. Logistic regression models run with unweighted data were used to test whether African-American/Black (AA/B), Hispanic/Latina (H/L), and Asian/Pacific Islander (A/PI) women differed significantly from white nonHispanic (whiteNH) women in use of different supplements after controlling for age and also after controlling for age, education, and health status.
Logistic regression models were used to identify statistically significant independent predictors of four types of use: (a) any dietary supplement, (b) any dietary supplement other than a multivitamin and/or calcium supplement only, (c) any NVNM supplement, and (d) any herbal supplement. The results we present are restricted to whiteNH women because we found that the predictor variables did not operate the same way in separately run models for the other race/ethnic groups in the sample. Indicator variables included in the logistic models were 3 age groups (75–79, 80–84 vs. 65–74), 4 education levels (< 12 years, some college, college graduate vs. high school graduate), overall health status (good/excellent health vs. fair/poor health), arthritis (yes vs. no), diabetes (yes vs. no), depression for at least two weeks during the past 12 months, and belief that "lifestyle/habits (what you eat, exercise, and weigh) affect health" moderately to extremely vs. not at all/a little bit. Rates of supplement use were not substantially different for ages 65–69 and 70–74, so these age groups were collapsed. All four logistic models included the same set of predictor variables and were run using data from the 96% (n=2378) whiteNH women who had complete data for all variables. In the text and tables, adjusted odds ratios (Adj. OR) with 95% confidence intervals that cross 1.0 are not statistically significant at the p < .05 level.
Results and discussion
Table 1 shows selected demographic and health-related characteristics of the sample. The sample is predominantly whiteNH (80%), educated beyond high school (55%), and in good health (80%), although a large percentage have chronic health problems such as hypertension, diabetes, arthritis, and depression. Nearly 85% reported regularly taking at least one prescription medication and 19% five or more. Approximately 16% regularly used a prescription medication with a narrow therapeutic index, such as an anticoagulant, cardiac glycocide, or tricyclic antidepressant. Approximately 70% believed that their health habits had a moderate to large effect on their health.
Table 1 Characteristics of the sample population (n = 3109)
N Unwtd.% Wtd.%*
All Ages
Ages 65–74 1468 47.2 64.1
Ages 75–79 1356 43.6 22.9
Ages 80–84 285 9.2 13.0
Race/Ethnicity
White, nonHispanic 2483 81.1 80.2
African-American/Black 169 5.5 5.7
Hispanic / Latina 147 4.8 5.0
Asian / Pacific-Islander 222 7.3 7.8
Other 41 1.3 1.2
Educational Attainment
< High School Graduate 472 15.4 15.0
High School Graduate/GED 921 30.0 30.0
Some College 1090 35.6 34.8
4-Year College Graduate 583 19.0 20.2
Health Status
Excellent/Very Good/Good 2436 78.7 79.6
Fair/Poor 658 21.3 20.4
Health Conditions
Heart Disease 561 18.0 17.3
Diabetes 350 11.3 11.4
Hypertension 1449 46.6 46.4
Arthritis 1202 38.7 38.1
Depression for ≥ 2 weeks during yr 365 11.7 12.0
# Rx Medications Used (by self-report)
1 500 16.9 16.8
2–4 1429 48.4 48.9
5 or more 567 19.2 19.1
Taking Rx Medication with a Narrow Therapeutic Index** 513 16.5 15.9
Belief About How Much Health Habits/Lifestyle Affect Health
Little or no effect 917 30.8 29.6
Moderate effect 591 19.8 19.1
Great deal of effect 1472 49.4 51.3
* Weighted percentages are based on respondent data weighted to reflect the age, gender, and geographic distribution of the membership. N's in table are actual numbers of respondents with this characteristic.
** Estimated based on health plan pharmacy records for sample.
Table 2 [See Additional file 1 ] shows estimates of the percentages of female seniors who used specific types of dietary supplements. Estimates are provided for all women and for women in the four major race/ethnic groups because the estimates for the overall population are so heavily influenced by the large proportion of whiteNH women in the sample. Overall, 84% of the women had used at least one dietary supplement during the previous 12 months, 82% a VM supplement, 59% a dietary supplement other than just a multivitamin and/or calcium, 32% an NVNM supplement, and 25% an herbal supplement. Among those who used at least one supplement (n = 2,574), a mean of 3.25 (sd = 15.29) supplements were used, with 22% using only one and 57.1% using ≥ 3 supplements. The mean number of supplements used excluding daily multivitamins and calcium was 2.14 (sd = 12.42), with 49% using only one and 27.3% using ≥ 3.
After adjusting for age, African-American/Black seniors were significantly less likely than whiteNH seniors to use daily multivitamins and calcium, as well as all the other categories of dietary supplements. This difference remained statistically significant after also adjusting for education, health status, and the three chronic health conditions. Hispanic/Latina seniors were also significantly less likely than whiteNH seniors to use VM supplements (with the exception of vitamin E) and NVNM supplements, but did not significantly differ on herbal use. Asian/Pacific Islander seniors did not significantly differ from whiteNH seniors on use of any type of dietary supplement, use of VMs, or use of dietary supplements other than just a multivitamin and/or calcium. However, they were significantly less likely than whiteNH women to use NVNM supplements. Among women using any supplement, mean use of all supplements and supplements excluding multivitamins and calcium were both significantly higher among whiteNH women than among women of color (not shown). Table 2 also shows that use of glucosamine by women with arthritis was significantly lower among African-American/Black, Hispanic/Latina, and Asian/PI women as compared to whiteNH women (ORAA/B = 0.32, CI: 0.13–0.82; ORH/L = 0.19, CI: 0.06–0.61; ORA/P = 0.56, CI: 0.28–1.11). Similarly, women of color who had experienced depression for at least two weeks during the 12-month interval were substantially less likely than whiteNHs to report using St. John's Wort to treat depression. Rates of ginkgo biloba use did not significantly differ by race/ethnicity.
Table 3 [See Additional file 2 ] shows how use of dietary supplements varied by personal characteristics other then race/ethnicity for the whole sample and Table 4 [See Additional file 3 ] provides this information for the whiteNH women who comprised most of the sample. The NVNM and herbal supplement use rates were lower for seniors aged 75–84 than for those aged 65–74, but the differences were smaller than those observed for race/ethnicity. While higher education was significantly associated with supplement use, it was more strongly associated with use of NVNM and herbal supplements than VM use. For example, NVNM use among college graduates was approximately 40% higher than that for high school graduates, while the rate for those who had not completed high school was approximately 40% lower than the rate for high school graduates. Health status and belief about the effect of health practices were more strongly associated with NVNM supplement use than use of any dietary supplement.
Table 5 [See Additional file 4 ] shows the results of multiple logistic regression models predicting use of any dietary supplement, use of any dietary supplement other than just a multivitamin or calcium, use of any NVNM supplement, and use of any herbal by whiteNH women. Women who had not completed high school were significantly less likely than high school graduates to use a dietary supplement other than daily multivitamin/calcium and an NVNM, but did not significantly differ in likelihood of using herbals. Higher education, especially a college degree, was associated with significantly higher likelihood of use of all four categories of supplements as compared to high school education. Good health remained significantly associated with use of dietary supplements other than multivitamin/calcium, NVNM use, and herbal use, although in the case with herbals, it was only significant after the three health conditions were entered into the model. Belief that health practices had a moderate-large effect on health was a significant predictor of both VM and NVNM use, even after controlling for its strong association with educational attainment. Having arthritis increased the likelihood of use of VMs and NVNMs, but not herbals. In contrast, having diabetes decreased the likelihood of using VM and NVNM supplements. Experiencing depression did not have a significant effect on use of VM supplements, but doubled the likelihood of use of NVNM supplements, especially herbals.
A logistic regression model predicting glucosamine use among women with arthritis found that being African-American/Black (OR = 0.42, CI: 0.16–1.08) or Hispanic/Latina (OR = 0.25, CI: 0.08–0.82) race/ethnicity significantly decreased the likelihood of glucosamine use as compared to whiteNH women, while having education beyond high school (OR = 1.64, CI:1.16–2.30) and the belief that health practices have a moderate-large effect on health (OR = 1.49, CI:1.03–2.15) were associated with significantly greater likelihood of glucosamine use.
The prevalence of use of NVNM supplements and dietary supplements other than a multivitamin and/or calcium did not differ by number of prescription medications taken (0, 1, 2–4, or ≥ 5) nor by whether a prescription medication with a narrow therapeutic index was being taken. Approximately 10% of women seniors who were taking an anticoagulant were also using ginkgo biloba or garlic supplements, even though there is evidence that this combination of blood thinners can lead to adverse consequences.
Figure 1 shows how use of dietary supplements as a complementary or alternative therapy to treat or prevent health problems is probably underestimated among female seniors due to study investigators' focus on herbals and megavitamins. Prevalences of use of herbal and other dietary supplements were estimated based on responses provided by the same women to both the herbal supplement item in the complementary and alternative medicine (CAM) checklist and the nutritional supplement question. The estimated prevalence of herbal supplement based on reported specific supplements was twice as high as that based on the CAM checklist item alone. Broadening supplement use to include any NVNM significantly increased the percentage of users, primarily due to use of glucosamine for arthritis and other joint conditions. Further broadening to use of any NVNM or VM other than multivitamin and/or calcium resulted in a percentage twice as high as herbal use based on the coded supplements. Lastly, the prevalence of use of any type of VM or NVNM supplement, including more mainstream daily multiple vitamins and calcium, was more than three times greater than the prevalence of herbal use based on the coded supplements.
Figure 1 Underestimation of dietary supplement use by tracking herbal use only among women aged 65–84. NVNM = Nonvitamin, nonmineral including herbals. Based on respondent data weighted to reflect the age, gender, and geographic distribution of the membership.
Finally, Figure 2 shows estimated rates of NVNM supplement use among 45–54 and 55–64 year old women in this same health plan membership compared with rates of use among current seniors based on their responses to the same survey questions. Since current supplement use is probably one of the best predictors of future supplement use, the data suggest that the prevalence of NVNM use among women aged ≥ 65 years will increase substantially over the next couple of decades as the health plan population ages.
Figure 2 Differences in dietary supplement use among women by age cohort in a health plan population. NVNM = Nonvitamin, nonmineral supplement including herbals. Supplement other than Multivitamin/Calcium = any dietary supplement other than multivitamin and/or calcium. Based on respondent data weighted to reflect the age, gender, and geographic distribution of the membership.
Conclusions
The 84% prevalence of use of any vitamin/mineral (VM) or nonvitamin/nonmineral (NVNM) supplements, 32% prevalence of NVNM supplement use, and 25% prevalence of herbal supplement use by women aged 65–84 in this Northern California health plan membership are substantially higher than prevalences previously reported for women ≥ 65 years of age. Compared to the results of the national Slone Survey of medication use among adults, this population was significantly more likely to report use of any vitamin/mineral (82% vs. 59%), daily multivitamin (57% vs. 33%), calcium (57% vs, 23%), any herbal or other NVNM supplement (32% vs. 14%), and specific NVNM supplements, including ginkgo biloba (15% vs. 5%), glucosamine (12% vs. 4%), and Echinacea (8% vs. < 1%) [1]. While the time frame for the surveys differed (use during the past 12 months vs. use during the past week), this is unlikely to affect the comparison of most of the specific VM and NVNM supplements which are generally used almost daily. The percentages of herbal users (25%) and women using both herbals and prescription medicines (21%) were also higher than rates observed by Foster et al. (9% and 6%, respectively) based on Eisenberg et al's 1997 national survey of alternative medicine use over a 12-month interval [17]. Further, our survey found that the 32% prevalence of NVNM use and 59% prevalence of use of NVNM or VM supplements other than just a multivitamin or calcium (59%) were substantially higher than prevalence of herbal use and were not affected by the number of prescription medications women were taking nor whether any of those medications had a narrow therapeutic index.
Our findings that supplement use was significantly higher among women who had higher levels of education, were white, nonHispanic (vs. African-American/Black or Hispanic/Latino), and were in good health are consistent with findings reported by other studies [18-22]. However, we also found that belief that one's health practices and lifestyle had at least a moderate effect on health was an additional significant predictor, but only for white, nonHispanic women; bivariate and logistic analyses done separately for African-American, Hispanic/Latino, and Asian/Pacific Islander subgroups found no indication that this factor influenced supplement use. For women of color, education beyond high school was the strongest predictor of use. Finally, we showed that some health conditions were significantly associated with higher likelihood of use of certain kinds of supplements (arthritis, depression), while another (diabetes) was associated with lower likelihood of use. This suggests that studies which employ one variable to represent presence of any chronic health problem may yield inaccurate results.
The higher rates we observed in our study may be a result of differences in the demographic composition of the survey populations. Our sample was predominantly (80%) white, nonHispanic and education beyond high school (35% some college and 20% college graduates), and in this and other surveys, being whiteNH and better educated was significantly associated with supplement use. However, while the usage rates among African-American/Black and Hispanic/Latina women and those without post-high school education are substantially lower, the demographics of the 1998–1999 Slone survey and 1997 Eisenberg et al. national survey samples are not substantially different from ours. Our observed usage rates may also be higher because of the social environment. Previous national surveys have shown that rates of NVNM and any alternative therapy use among people in the Western United States are higher than rates for the entire country [3,23,24]. However, the health plan membership is diverse with regard to education, socioeconomic status, and health-related attitudes.
The higher herbal and NVNM usage rates observed in this study compared to those reported by Foster et al. and Radimer et al. also may be related to the timing of the surveys. Eisenberg et al. reported highly significant increases in use of herbal medicine (2.5% to 12.1%) and megavitamin use (2.4% to 5.5%) for the adult population overall in1990 vs. 1997 [10]. In an earlier study, we reported an increase from 1.2% in 1996 to 9% in 1999 of use of herbals by women ≥ 65 years based on response to a question about use of different types of alternative therapies in this triennial health plan membership survey [25].
Finally, the wording of the questions to ascertain herbal use and NVNM use were not totally comparable across surveys. The estimates of VM and NVNM use reported in the Slone study are based on an open-ended question about use of any medication during the preceding 7 days, with a prompt for both VM and herbal supplement use, but not use of other types of NVNM supplements. Foster's estimate is based on response to a question about use of herbals as one of several different types of therapies. In contrast, our results are based on a question that provided a response checklist of some specific VM, herbal, and other NVNM supplements along with the opportunity for individuals to add additional supplements used, which were later coded and categorized. In an earlier study of alternative therapy use, we examined the difference in estimates of herbal use by the health plan membership based on indication of herbal use in a checklist of 17 different methods (not labeled as alternative therapies) used to treat or prevent health problems and indication of herbal use based on that item and response to the dietary supplement use question. We found that basing the estimate on the combined questions versus the single item nearly doubled the rate of herbal use among women ≥ 65 years (17.6% vs. 9.6%) [25].
Our finding that much larger percentages of adult women are taking NVNMs and VMs other than multivitamins and calcium suggests that for purposes of surveying populations about complementary and alternative therapy use and for medical interviews, the focus should be on use of all types of dietary supplements and medicinal teas, not just herbal supplements. There are several reasons for this. First, VMs and NVNMs other than herbals have the potential for causing adverse reactions, such as high doses of Vitamin C or zinc resulting in gastric upset, that can lead to further self-medication and/or medical visits. Second, certain VMs and NVNMs other than herbals also have the potential to interact with prescription medications, resulting in decreased effectiveness or affecting physiological indicators of how the medication is affecting the individual. Third, a focus on herbals alone excludes other NVNMs that are commonly used by patients with certain health conditions. For example, we estimate that nearly 3% of women used melatonin and 15% of whiteNH women (24% of those with arthritis) use glucosamine, neither of which is an herbal supplement. Finally, surveys of Mexican-American and Central American older women have shown a high prevalence of use herbal and other types of medicinal teas, which may not be picked up by questions asking about dietary supplement use [26]. However, since a growing proportion of the population is drinking herbal teas for nonmedicinal reasons (i.e., other than to treat health problems or symptoms), it will be important to find the best way to ask about medicinal tea use so as to avoid including in estimates those people who are drinking non-medicinal herbal teas as an alternative to caffeinated beverages.
Several surveys have found that patients do not tend to report use of herbals and other dietary supplements to their health care providers in clinical encounters [1,9,11,27]. Because of this lack of communication, there is a great potential for adverse interactions of drugs and dietary supplements in this age group. It may also be the case that some dietary supplements or particularly high dosages of supplements might actually cause symptoms or changes in physiological indicators that may be incorrectly attributed to other underlying health problems, resulting in unnecessary or inappropriate treatment either by the woman or her clinician. As the cost of prescription medications continues to rise and health insurers continue to place caps on medication coverage, it is likely that increasing numbers of older women, especially those on limited incomes, will turn to dietary supplements as a lower-cost alternative for treating health conditions. Concomitantly, the incidence of supplement-related health problems is likely to increase.
Our finding that nearly 60% of older women in this population were using dietary supplements other than multivitamins and calcium underscores the importance of clinicians querying patients about use of all types of dietary supplements when assessing health problems and prescribing medications, and as a back up, pharmacists inquiring about use of dietary supplements that may interact with prescription and over-the-counter medicines that are being purchased. Initiation of the communication by clinicians and pharmacists is likely to result in increased patient awareness that these dietary supplements may affect their health and treatment outcomes, which should then lead to higher rates of patient-initiated communication about dietary supplements they are using or considering using. Greater clinician and pharmacist awareness of all the different prescribed and self-directed regimens patients are using may lead to more proactive interventions to decrease adverse effects of supplement use. However, in order for clinicians and pharmacists to be able to respond to patient questions about dietary supplements, as well as to identify individuals at high risk for adverse effects, better information about the safety, effectiveness, and side-effects of dietary supplements need to be available and easily accessible, such as through the Natural Standard and National Medicines Databases.
In conclusion, our study indicates that use of dietary supplements to treat or prevent health problems is very prevalent among older insured women, and that based on current use in younger age groups, the prevalence can be expected to increase over the next few decades. It will be important for federal agencies, professional associations, manufacturers, and consumer groups to promote research into the safety and effectiveness of commonly used dietary supplements, to develop standards for product quality, and to develop guidelines for recommended dosages based on age, weight, and health history that can be disseminated to both health care professionals and stores or clinics which sell these products. At the same time, it is important to begin to educate patients and the broader public about the importance of more thoroughly researching the safety, effectiveness, and potential negative effects of particular dietary supplements before beginning to use them.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
NG designed the study, conducted the survey, analyzed the data, and drafted the manuscript. DS developed the scheme for coding the dietary supplement data, consulted on data analysis, and participated in manuscript development. Both authors 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
Table 2 - Estimated percentages of female health plan members aged 65–84 using specific types of dietary supplements, overall and by race/ethnicity
Click here for file
Additional File 2
Table 3 - Estimated use of dietary supplements by women aged 65–84 by selected personal characteristics other than race/ethnicity
Click here for file
Additional File 3
Table 4 - Association of selected personal characteristics with dietary supplement use by white, nonHispanic women aged 65–84
Click here for file
Additional File 4
Table 5 - Results of multiple logistic regression models predicting dietary supplement use by white, nonHispanic women aged 65–84
Click here for file
Acknowledgements
This study was supported by Kaiser Permanente's Community Benefit Program.
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BMC Clin PharmacolBMC Clinical Pharmacology1472-6904BioMed Central London 1472-6904-5-11570308310.1186/1472-6904-5-1Research ArticleHospital use of systemic antifungal drugs de With Katja [email protected] Michaela [email protected] Holger [email protected]örje Frank [email protected] Egid [email protected] Ulrich [email protected] Ludwig [email protected] Winfried V [email protected] Center for Infectious Diseases and Travel Medicine, University Hospital, D-79106 Freiburg, Germany2 Academic Medical Center Pharmacy, Technical University, Dresden, Germany3 Pharmacy Service, Hospital of the Friedrich-Alexander University, Erlangen, Germany4 Pharmacy Service, University Hospital, Freiburg, Germany5 Pharmacy, University Hospital, Regensburg, Germany6 Pharmacy, Ulm University Hospital and Medical Center, Ulm, Germany2005 10 2 2005 5 1 1 21 10 2004 10 2 2005 Copyright © 2005 de With et al; licensee BioMed Central Ltd.2005de With 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
Sales data indicate a major increase in the prescription of antifungal drugs in the last two decades. Many new agents for systemic use that only recently have become available are likely to be prescribed intensively in acute care hospitals. Sales data do not adequately describe the developments of drug use density. Given the concerns about the potential emergence of antifungal drug resistance, data on drug use density, however, may be valuable and are needed for analyses of the relationship between drug use and antifungal resistance.
Methods
Hospital pharmacy records for the years 2001 to 2003 were evaluated, and the number of prescribed daily doses (PDD, defined according to locally used doses) per 100 patient days were calculated to compare systemic antifungal drug use density in different medical and surgical service areas between five state university hospitals.
Results
The 3-year averages in recent antifungal drug use for the five hospitals ranged between 8.6 and 29.3 PDD/100 patient days in the medical services (including subspecialties and intensive care), and between 1.1 and 4.0 PDD/100 patient days in the surgical services, respectively. In all five hospitals, systemic antifungal drug use was higher in the hematology-oncology service areas (mean, 48.4, range, 24 to 101 PDD/100 patient days, data for the year 2003) than in the medical intensive care units (mean, 18.3, range, 10 to 33 PDD/100) or in the surgical intensive care units (mean, 10.7, range, 6 to 18 PDD/100). Fluconazole was the most prescribed antifungal drug in all areas. In 2003, amphotericin B consumption had declined to 3 PDD/100 in the hematology-oncology areas while voriconazole use had increased to 10 PDD/100 in 2003.
Conclusion
Hematology-oncology services are intense antifungal drug prescribing areas. Fluconazole and other azol antifungal drugs are the most prescribed drugs in all patient care areas while amphotericin B use has considerably decreased. The data may be useful as a benchmark for focused interventions to improve prescribing quality.
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Background
There has been a major increase in the prescription of antifungal drugs after the introduction of fluconazole into the market in the late 1980s, and again in the late 1990s. The systemic antifungal market has continued to experience growth since 1999, increasing in value from $2.1 billion to $3.3 billion in 2003. The azoles dominate the systemic antifungal market, accounting for 52% of total sales in 2003 [1-8]. The reasons for the increasing antifungal drug use are manifold. Among hospitalized patients, the empiric use of antifungals in both hematology-oncology as well as intensive care patients is now common. Often, treatment is initiated based on preliminary microbiology results, and definite diagnosis of invasive infection versus colonization may be difficult [4,9-11]. New antifungal drugs such as itraconazole, caspofungin, and voriconazole have become available and broadened therapeutic options [12]. In some settings an increasing incidence of invasive fungal infections and the emergence of infections due to rare and atypical organisms has been observed, and this changing epidemiology has contributed to more intense use of antifungal drugs [13]. In the ambulatory care setting there was a shift from prescribing intravaginal antifungal preparations to fluconazole over-the-counter, raising concern about the possible development of azole drug resistance [14-16].
Although multiple current and projected market and sales data on systemic antifungal drugs are available, few studies have provided estimates of antifungal drug use density especially in hospitals. Alvarez-Lerma and colleagues reported a prescription rate of 14% in intensive care unit patients [9]. In a survey we conducted in 1994 the prescription prevalence rate in hospitalized patients was 10.2% per patient-week in the medical service and 3.5% per patient-week in the surgical services [17]. Hospital expenditures were also evaluated in some studies. However, we were unable to find information on recent hospital antifungal drug utilization that uses the daily doses per 100 patient days format which is now common in pharmacoepidemiologic surveys. We therefore collected data from the pharmacies of five university hospitals and here report overall and comparative use density values for defined patient care areas.
Methods
Pharmacy data on systemic antifungal drug use in the medical and surgical services of five university hospitals located across Germany were obtained for the period 2001 to 2003. The five university hospitals included, here designated A through E, varied in size from ~1,000 to ~1,700 beds, and differed from each other in structure, special services offered, and in the availability of interdepartmental guidelines and an antiinfective therapeutics committee, drug formularies, formulary restrictions, and infectious disease consultation services.
We used a consensus definition of (usually) prescribed daily doses (PDD) in adults (Table 1) according to local guidelines. This definition differs from the daily doses defined by the WHO/ATC classification which defines lower doses for amphotericin B, fluconazole, and itraconazole (Table 2). Antifungal drug use density was calculated as yearly PDD/100 patient days (i.e. occupied bed days). Separate data were calculated for the medical ICU (MICU), the surgical ICU (SICU), and the hematology-oncology services, respectively. We also calculated yearly means of overall and specific antifungal use densities to assess time trends.
Table 1 Definitions of prescribed daily doses (PDD) and WHO/ATC defined daily doses (DDD) for systemic antifungal drugs.
PDD DDD
amphotericin B deoxycholate* 50 mg 35 mg
liposomal amphotericin B 250 mg nd#
flucytosin 10 g 10 g
ketoconazole 400 mg 400 mg
fluconazole 400 mg 200 mg
itraconazole 400 mg 200 mg
voriconazole 400 mg 400 mg
caspofungin 50 mg 50 mg
*conventional amphotericin B
#not defined
Results and discussion
The yearly antifungal drug use densities differed between the five hospitals in particular for the medical services. Hospital A showed use density values of consistently >20 PDD/100 patient days while hospital E values were consistently <10 PDD/100 patient days (Figure 1). Less variation between the hospitals were observed in the surgical services (Figure 1). Here, 3-year averages for the hospitals ranged between 1.1 (hospital A) and 4.0 PDD/100 patient days (hospital B), respectively.
Figure 1 Yearly systemic antifungal drug use density in the medical and surgical services of five university hospitals (A through E) for the years 2001–2002–2003.
Time trend
Overall, the mean antifungal drug use for the five hospitals increased between the years 2001 and 2003 from 12.4 to 15.4 PDD/100 patient days in the medical services (+24%), but only from 2.1 to 2.2 PDD/100 patient days in the surgical services (+5%). Applying the WHO/ATC definition of daily defined doses (DDD; including our daily dose definition for liposomal amphotericin B), corresponding values for the years 2001 and 2003 were calculated to be 22.8 to 26.3 DDD/100 patient days (+15%) in the medical services, and 4 to 4.1 DDD/100 patient days (+4%) in the surgical services, respectively (data not shown).
Use of specific antifungal drugs
As in other reports [5], fluconazole was the most frequently prescribed antifungal drug in the medical as well as surgical services of the five hospitals. Its use did not decrease over time. Figure 2 shows the yearly mean use density for fluconazole and other antifungal drugs (except the rarely used 5-flucytosin and ketoconazole) in the medical service. Interestingly, conventional as well as liposomal amphotericin B use decreased over time (Figure 2). In the year 2003, the mean use of fluconazole in the medical service was 7.7 PDD/100 patient days (representing 50% of all PDDs), and 1.8 PDD/100 patient days in the surgical service (representing 78% of all PDDs), respectively.
Figure 2 Use density for different antifungal drugs in the medical service of five university hospitals. Data are yearly means for 2001, 2002 and 2003. cAmB, conventional amphotericin B; L-AmB, liposomal amphotericin B; Caspo, caspofungin; Fluco, fluconazole; Itra, itraconazole; Vori, voriconazole.
Differences between patient care areas
As expected, antifungal drug use was much more intense in the hematology-oncology services and intensive care areas (Figure 3) than in general internal medicine (mean use, 2.3 PDD/100 patient days, data for the year 2003) and general surgery (mean use, 1.1 PDD/100 patient days, data for the year 2003). Figure 3 shows that there was some variation between the hospitals in the use density values, particularly in hematology-oncology and the SICU area. These differences were not explained by different incidences of invasive fungal infections as perceived by the local physicians, but in none of the hospitals specific surveillance for fungal infections was activated. Large differences were also noted in the fluconazole use, with very high use density values in hospital A hematology-oncology and comparatively low density values in hospital E hematology-oncology areas (53.8 versus 5.8 PDD/100 patient days, data for the year 2003). The high use density values in hospital A hematology-oncology could primarily be explained by the heavy use of relatively high doses of fluconazole (400 mg daily) for prophylactic purposes which was much less common in the other hospitals.
Figure 3 Use of fluconazole (grey bars) versus other systemic antifungal drugs (black bars) in the SICU, MICU, and in the hematology-oncology services of five university hospitals (A through E) during the years 2001–2002–2003.
Of note, hospital E had a moderately active infectious disease consultant service with an antimicrobial agents management program, and this was previously associated with low antibacterial drug use in the medical service [18,19]. According to the present study, this programme was also perhaps linked to the low antifungal drug use density in the hospital E medical service including hematology-oncology.
In hospital C, there was a program in the MICU attempting to decrease the use of fluconazole based solely on positive cultures for yeasts in tracheal or bronchial secretions. This program, which was primarily a focused infectious diseases consultation program was started in 2002, and appeared to be effective in decreasing fluconazole use from 13.5 to 5 PDD/100 patient days without changing the use density of other systemic antifungal drugs (Figure 3).
The decreasing use of amphotericin B consumption seen in the medical service was to a large part explained by decreasing use of the drug in the hematology-oncology wards. Mean use density values changed between 2001 and 2003 from 5.8 to 2.4 PDD/100 patient days for conventional amphotericin B, and from 1.6 to 0.6 for liposomal amphotericin B, respectively. These changes were associated with increasing values for voriconazole in hematology-oncology. This new drug after its introduction into the market in 2002 increased from zero to a use density of 10.3 PDD/100 patient days in 2003. Interestingly. 80% of all doses of voriconazole in hematology-oncology were by the oral route.
Limitations and conclusions
Our study was not designed to evaluate appropriateness of antifungal drug therapy. Few studies in the hospital setting have addressed this issue. In two previous studies, it was found that dosages of fluconazole were not always adequate [20,21]. In another study, therapy was considered "unconventional" in 27% of the courses and 41% of the regimens, mainly because either the indication or the duration of treatment did not conform to conventional practice [4]. Conventional practice, however, can differ considerably as indicated by our results. We think it is unlikely that the observed high use density values in hospital A hematology-oncology (>50 PDD/100 patient days) represents an unusual epidemiologic situation or a major difference in hematology-oncology patient-mix. Rather, the intense use can be explained by liberal antifungal drug use in high doses for prophylaxis and perhaps empiric combination therapy. The present study, thus, provided a useful benchmark suggesting that more detailed analysis of antifungal therapy indication practice is warranted in this particular hospital.
In summary, this report describes the range of antifungal drug use in certain patient care areas of large tertiary-care teaching hospitals in Germany. Consistent with other reports, we found that fluconazole has remained the most frequently prescribed drug in this setting.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
KdW and WVK analysed and interpreted the data and wrote the article. MSB is data manager, analysed the data and presented them through a searchable database. HK, FD, ES, UR and LM checked the data for consistency and correctness, provided them in electronic format, and helped with interpretation of the data and revision of the manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgement
The study was in part supported by BMBF grant 01 KI 9951.
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| 15703083 | PMC549558 | CC BY | 2021-01-04 16:27:54 | no | BMC Clin Pharmacol. 2005 Feb 10; 5:1 | utf-8 | BMC Clin Pharmacol | 2,005 | 10.1186/1472-6904-5-1 | oa_comm |
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BMC BioinformaticsBMC Bioinformatics1471-2105BioMed Central London 1471-2105-6-271570520810.1186/1471-2105-6-27Research ArticleA statistical approach for array CGH data analysis Picard Franck [email protected] Stephane [email protected] Marc [email protected] Christian [email protected] Jean-Jacques [email protected] Institut National Agronomique Paris-Grignon, UMR INAPG/ENGREF/INRA MIA 518, Paris, France2 Université Paris Sud, Equipe Probabilités, Statistique et Modélisation, Orsay, France3 University of California San Francisco, Diabetes Center, San Francisco, USA2005 11 2 2005 6 27 27 18 8 2004 11 2 2005 Copyright © 2005 Picard 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-CGH experiments are used to detect and map chromosomal imbalances, by hybridizing targets of genomic DNA from a test and a reference sample to sequences immobilized on a slide. These probes are genomic DNA sequences (BACs) that are mapped on the genome. The signal has a spatial coherence that can be handled by specific statistical tools. Segmentation methods seem to be a natural framework for this purpose. A CGH profile can be viewed as a succession of segments that represent homogeneous regions in the genome whose BACs share the same relative copy number on average. We model a CGH profile by a random Gaussian process whose distribution parameters are affected by abrupt changes at unknown coordinates. Two major problems arise : to determine which parameters are affected by the abrupt changes (the mean and the variance, or the mean only), and the selection of the number of segments in the profile.
Results
We demonstrate that existing methods for estimating the number of segments are not well adapted in the case of array CGH data, and we propose an adaptive criterion that detects previously mapped chromosomal aberrations. The performances of this method are discussed based on simulations and publicly available data sets. Then we discuss the choice of modeling for array CGH data and show that the model with a homogeneous variance is adapted to this context.
Conclusions
Array CGH data analysis is an emerging field that needs appropriate statistical tools. Process segmentation and model selection provide a theoretical framework that allows precise biological interpretations. Adaptive methods for model selection give promising results concerning the estimation of the number of altered regions on the genome.
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Background
Chromosomal aberrations often occur in solid tumors: tumor suppressor genes may be inactivated by physical deletion, and oncogenes activated via duplication in the genome. Gene dosage effect has become particularly important in the understanding of human solid tumor genesis and progression, and has also been associated with other diseases such as mental retardation [1,2]. Chromosomal aberrations can be studied using many different techniques, such as Comparative Genomic Hybridization (CGH), Fluorescence in Situ Hybridization (FISH), and Representational Difference Analysis (RDA). Although chromosome CGH has become a standard method for cytogenetic studies, technical limitations restrict its usefulness as a comprehensive screening tool [3]. Recently, the resolution of Comparative Genomic Hybridizations has been greatly improved using microarray technology [4,5].
The purpose of array-based Comparative Genomic Hybridization (array CGH) is to detect and map chromosomal aberrations, on a genomic scale, in a single experiment. Since chromosomal copy numbers can not be measured directly, two samples of genomic DNA (referred to as the reference and test DNAs) are differentially labelled with fluorescent dyes and competitively hybridized to known mapped sequences (referred to as BACs) that are immobilized on a slide. Subsequently, the ratio of the intensities of the two fluorochromes is computed and a CGH profile is constituted for each chromosome when the log2 of fluorescence ratios are ranked and plotted according to the physical position of their corresponding BACs on the genome [6]. Different methods and packages have been proposed for the visualization of array CGH data [7,8].
Each profile can be viewed as a succession of "segments" that represent homogeneous regions in the genome whose BACs share the same relative copy number on average. Array CGH data are normalized with a median set to log2(ratio) = 0 for regions of no change, segments with positive means represent duplicated regions in the test sample genome, and segments with negative means represent deleted regions. Even if the underlying biological process is discrete (counting of relative copy numbers of DNA sequences), the signal under study is viewed as being continuous, because the quantification is based on fluorescence measurements, and because the possible values for chromosomal copy numbers in the test sample may vary considerably, especially in the case of clinical tumor samples that present mixtures of tissues of different natures.
Two main statistical approches have been considered for the analysis of array CGH data. The first has focused many attentions, and is based on segmentation methods where the purpose is to locate segments of biological interest [7,9-11]. A second approach is based on Hidden Markov Models (aCGH R-package [12]), where the purpose is to cluster individual data points into a finite number of hidden groups. Our approach can be put into the first category. Segmentation methods seem to be a natural framework to handle the spatial coherence of the data on the genome that is specific to array CGH. In this context the signal provided by array CGH data is supposed to be a realization of a Gaussian process whose parameters are affected by an unknown number of abrupt changes at unknown locations on the genome. Two models can be considered, according to the characteristics of the signal that is affected by the changes: it can be either the mean of the signal [7,10,11] or the mean and the variance [9]. Since the choice of modeling is crucial in any interpretation of a segmented CGH profile, we provide guidelines for this choice in the discussion. Two major issues arise in break-points detection studies: the localization of the segments on the genome, and the estimation of the number of segments. The first point has lead to the definition of many algorithms and packages: segmentation algorithms [9,10] and smoothing algorithms [11] where the break-points are defined with a posterior empirical criterion. These methods are defined by a criterion to optimize and an algorithm of optimization. Different criteria have been proposed: the likelihood criterion [9,11], the least-squares criterion [7], partial sums [10], and algorithms of optimization are based on genetic algorithms [9], dynamic programing [7], binary segmentation (DNAcopy R-package [10]) and adaptive weigths smoothing (GLAD R-package [11]). Since many criteria and algorithms have been proposed, one important question is the resulting statistical properties of the break-point estimators they provide. Note that smoothing techniques do not provide estimators of the break-point coordinates, since the primary goal of the underlying model is to smooth the data, and break-points are not parameters of the model (in this case, they are defined after the optimization of the criterion [11]). Here we consider the likelihood criterion and we use dynamic programming that provides a global optimum solution, contrary to genetic algorithms [9], in a reasonable computational time.
As for the estimation of the number of segments, the existing articles have not defined any statistical criterion adapted to the case of process segmentation. This problem is theoretically complex, and has lead to ad hoc procedures [9-11]. Since the purpose of array CGH experiments is to discover biological events, the estimation of the number of segments remains central. This problem can be handled in the more general context of model selection. In the discussion we explain why classical criteria based on penalized likelihoods are not valid for break-points detection. Criteria such as the Akaike Information Criterion (AIC) and the Bayes Information Criterion (BIC) lead to an overestimation of the number of segments. For this reason, an arbitrary penalty constant can be chosen in order to select a lower number of segments in the profile [9]. We propose a new procedure to estimate the number of segments, choosing the penalty constant adaptively to the data. We explain the construction of such penalty, and its performances are compared to other criteria in the Results Section, based on simulation studies and on publicly available data sets. Put together, we propose a methodology that considers a simple modeling, a fast and effective algorithm of optimization and that takes advantages of the statistical properties of the maximum likelihood. Our procedure has been implemented on MATLAB Software and is freely available .
Results
Comparison of model selection criteria
To show the importance of the choice of the model selection criterion on simple data, we use the results of a single experiment performed on fibroblast cell lines (see the Materials Section), with one known chromosomal aberration. Figure 1 shows the resulting segmentations when using the Bayesian Information Criterion, and our criterion. BIC leads to an oversegmented profile that is not interpretable in terms of relative copy numbers. Our procedure estimates the correct number of segments . This example shows the practical consequences of the use of theoretically unappropriated criteria. This point constitutes the main purpose of the discussion (see the Discussion Section).
Numerical simulations are performed to study the sensitivity of different criteria to varying amounts of noise. The simulation design is described in the Methods Section. We compare four different criteria: the Bayesian Information Criterion, two previously described criteria [9,13], and the criterion we propose, in their ability to estimate the correct number of segments. Two configurations were tested, for a true number of segments K* = 5. In the first situation, the segments are regularly spaced with a jump of the mean of 1 (Figure 3), whereas in the second case, the segments are not regularly spaced and the differences of means vary between d = 2 and d = 0.5 (Figure 4). The first result is that BIC overestimates the number of segments, whatever the noise and the configuration (Figure 2). On the contrary, previously described criteria [9,13] tend to underestimate the number of segments when the noise increases, whatever the configuration. These results suggest that those two criteria "prefer" to detect no break-point as the noise increases, leading to possible false negative results.
The behavior of the criterion we propose is different. It seems to be more robust to the noise, as it will give a number of segments that is close to the true number. In particular, the irregular configuration presents a segment of small size (5 points at t = 80) that could be interesting to detect in the case of array CGH profile (a putative gained region for instance). Since the previously described criteria [9,13] tend to underestimate the number of segments, this particular region would not be detected. On the contrary, the adaptive criterion will be able to detect it, even if the noise is important, since it selects a constant number of segments close to the true number whatever the noise. These simulation examples perfectly illustrate the capacity of an adaptive criterion to find a reasonable number of segments even in configurations where the profile is not very separated.
We also compare the performance of our criterion and of the arbitrary criterion [9] on breast cancer cell lines. Figure 5 shows the resulting segmentations on chromosomes 9 and 10 of the Bt474 cell line (see the Materials Section for further description). As previously mentioned, the arbitrary criterion [9] selects a lower number of segments compared to the adaptive criterion, and we note that interesting regions are not detected (a putative outlier on chromosome 9 at 1.58 Mb and a putative deleted region on chromosome 10 at 1.76 Mb). Since the aim of array CGH experiments is to discover unknown chromosomal aberrations, the use of an adaptive criterion seems more appropriate in this context since it allows the identification of regions that seem biologically relevent.
The second simulation-based result concerns the ability of dynamic programming to locate the break-points at the correct coordinate, given different amounts of noise (Figures 3 and 4). In the regular configuration (Figure 3), simulation results show that dynamic programming perfectly localizes the break-points when the variability of the noise σ2 is low regarding the jump d of the mean. If d/σ = 10 the estimated probability to localize the break-points at the correct coordinate is 1, and this probability deacreases with the noise (probability close to 0.65 for d/σ = 2 and 0.25 for d/σ = 1). The effect of additional noise is to widden the zone of estimation, but the estimated break-points remain close to the true break-points. If the true break-point is located at t*, the estimated break-point stays in the interval t* ± 3. In the irregular configuration, additional noise has similar effects on the break-point's positioning, but the probability to correctly estimate a break-point depends on the jump of the mean between two segments. In the irregular case, Figure 4, at position t = 40 the difference of mean is d = 2, and the probability to locate the break-point at the true coordinate is higher than 0.65 for any additional noise. On the contrary, at position t = 85 where the different of mean equals d = 0.5 the probability to correctly locate the break-point decreases dramatically with the noise (probability 1 for σ = 0.1 and probability 0.25 for σ = 0.5). This means that dynamic programming is sensitive to small segments that present little differences in the mean regarding the noise. Nevertheless, the example on the real data set presented in Figure 5 shows that using an adaptive criterion with dynamic programming allows for the identification of small regions of putative biological interest as mentioned above. Put together, these simulation results show that the adaptive method selects the good number of segments even in the presence of important noise, and that when this number is selected, dynamic programming is able to correctly localize the break-point. In addition to its ability to locate precisely the break-points, it is important to notice that dynamic programming provides a global optimum of the likelihood that is required for any model selection procedure to select the number of segments, compared to genetic algorithms [9].
Segmentation models in the Gaussian framework
The CGH profile is supposed to be a Gaussian signal. In a segmentation framework, two types of changes can be considered: changes in the mean and the variance of the signal, or changes in the mean only. Let us define model where each segment has a specific mean and variance [9], and model , where the variance is common between segments [7].
Since both models can be used, it is important to explore their behavior in order to know which model is the best adapted to the special case of array CGH data. We use clinical data obtained from primary dissected tumors of colorectal cancers (see the Materials Section for further details). Figure 6 presents the results of segmentations for three experiments obtained with the two models and when our criterion is used to estimate the number of segments. The main result of this comparison is that the number of segments is higher using model compared to model . This behavior of model could be interpreted as a trend to divide large segments into smaller parts, in order to maintain the variance homogeneous between segments. This leads to a more segmented profile, maybe more precise, but that may be more difficult to interpret in terms of relative copy numbers. Nevertheless, as model allows the exploration of segments with one observation, it will be more efficient for the identification of outliers, as shown in Figure 6 (experiment X411, model , point at 100 Mb).
Discussion
The definition of an appropriate penalized criterion has been an issue for previous works using segmentation methods for array CGH data analysis [8,9,11]. In this section, we explain the specificity of model selection in the case of process segmentation, in order to give further justification to the inefficiency of classical criteria to select the number of segments, as shown in the Results Section.
Estimating the number of segments via penalized likelihood
When the number of segments is known, the maximization of the log-likelihood gives the best segmentation with K segments (see the Methods Section). In real situations this number is unknown, and one has to choose among many possible segmentations. The maximum of the log-likelihood can be viewed as a quality measurement of the fit to the data of the model with K segments, and will be maximal when each data point is in its own segment. Therefore selecting the number of segments only based on the likelihood criterion would lead to overfitting. Furthermore, the number of parameters to estimate is proportional to the number of segments, and a too large number of segments would lead to a large estimation error. A penalized version of the likelihood is used as a trade-off between a good adjustement and a reasonable number of parameters to estimate. It is noted
where pen(K) is a penalty function that increases with the number of segments, and β is a constant of penalization. The estimated number of segments is such as :
It is crucial to notice that the criterion which is penalized should provide the best partition of K-dimensional, ie for a fixed K the criterion has to be globally maximized to ensure convergence of the break-point estimators to the true break-points [14]. This optimum is provided by dynamic programming, but not by other algorithms [9,10].
Choice of the penalty function and constant
Classical penalized likelihoods use the number of independent continuous parameters to be estimated as a penalty function. Even though those criteria are widely used in the context of model selection, theoretical considerations suggest that they are not appropriate in the context of an exhaustive search for abrupt changes.
Let us focus on the penalty function in a first step. Table 1 provides a summary of different penalties. For classical information criteria, such as the Akaike Information Criterion and the Bayes Information Criterion, the penalty function equals to 2K (K means and K variances) for a heteroscedastic model with K segments. Penalized criteria have already been used in the context of array CGH data analysis to estimate the number of segments [9]. In addition to the 2K parameters, they implicitly consider that the break-points are also continuous parameters, leading to a new penalty function pen(K) = 3K - 1, which considers K - 1 break-points. Nevertheless, the characteristic of break-point detection models lies in the mixture of continuous parameters and discrete parameters that can not be counted as continuous parameters, since the number of possible configurations for K segments is finite and equals (with n the total number of points) [13].
This leads to the definition of a new penalty function adapted to the special context of the exhaustive search of abrupt changes. This function (table 1) is proportional to the number of continuous parameters, but is also proportional to a new term in that takes the complexity of the visited configurations into account. It is written pen(K) = 2K(c1 + c2), where c1 and c2 are constant coefficients that have to be calibrated using numerical simulations. Since AIC and BIC and the criterion proposed in [9] do not consider the complexity of the visited models, they select a too high number of segments. The second term of the penalty is the penalty constant β. This term is constant in the case of AIC and BIC (β = 1, β = , respectively), and contributes to the oversegmentation as mentioned above. This can lead to an empirical choice for the constant, in order to obtain expected results based on a priori knowledge. For this reason, an arbitrary penalty constant can be chosen for the procedure to select a reasonable number of segments (β = 10/3 in [9]). Instead of an arbitrary choice for this constant, β can be adaptively chosen to the data [13,14]. Furthermore, when the number of segments is small with respect to the number of data points (which is the case in CGH data analysis), the log-term can be considered as a constant [14]. The author rather suggests to use the penalty function pen(K) = 2K and to define an automatic procedure to choose the constant of penalization β adaptively. We explain the estimation procedure for the penalty constant in the Methods Section.
The power of adaptive methods for model selection lies in the definition of a penalty that is not universal (such as in the case of AIC and BIC). This means that the dimension of the model is estimated adaptively to the data. The efficiency of such method has been shown on simulated data as well as on experimental results (Results Section), and adaptive model selection criteria seem to be very appropriate for array CGH data analysis.
Choice of modelling for array CGH data
Since the choice of modeling affects the resulting segmentation, it is crucial to provide guidelines for their use. This can be done with the interpretation of the statistical models in terms of their biological meaning. The difference between model and concerns the modeling of the variance: model assumes that the variability of the signal is organized along the chromosome, whereas model specifies that the variance is constant. Since it has been shown that the vast majority of clones all had the same response to copy number changes in the aneuploid cell lines [6], the use of model would be justified regarding this experimental argument.
Outliers seem to be a major concern in microarray CGH data analysis. For instance, if only one BAC is altered whereas its neighbors are not, the conclusion could be either that it is biologically relevant, or that the signal is due to technical artefacts. Replications are crucial in this situation, as well as secondary validations. An other possibility could be that the BAC is misannotated: if the ratio is plotted at the wrong coordinate on the genome, it will appear as an outlier, when it is not. The importance of outlier identification is another argument in favor of model , that can detect changes for one data point, whereas with model outliers would belong to segments with higher variance.
It has to be noted that classical models used in segmentation methods assume the independence of the data. This may be a reasonnable assumption for BAC arrays whose genome representation is approximately 1 BAC every 1.4 Mb [6]. Nevertheless, a new generation of arrays now provides a tiling resolution of the genome [15]. The overlapping of successive BACs could lead to statistical correlations that will require developments of new segmentation models for correlated processes.
Conclusions
Microarray CGH currently constitutes the most powerful method to detect gain or loss of genetic material on a genomic scale. To date, applications have been mainly restricted to cancer research, but the emerging potentialities of this technique have also been applied to the study of congenital and acquired diseases. As expression profile experiments require careful statistical analysis before any biological expertise, CGH microarray experiments will require specific statistical tools to handle experimental variability, and to consider the specificity of the the studied biological phenomena. We introduced a statistical method for the analysis of CGH microarray data that models the abrupt changes in the relative copy number ratio between a test DNA and a reference DNA. We discuss the effects of different modelings that can be used in segmentation methods, and suggest the use of a model that considers the homogeneity of the signal variability based on experimental arguments and regarding the specificity of array CGH data.
The main theoretical issue of array CGH data analysis lies in the estimation of the number of segments that requires the definition of appropriate penalty function and constant. We define a new procedure that estimates the number of segments adaptively to the data. This method selects the number of segments with high accuracy compared to previously mapped aberrations, and seems to be more efficient compared to others proposed to date. The use of dynamic programming remains central to localizing the break-points, and the simulation results show that when the good number of segments are selected, the algorithm localizes the break-points very close to the truth. Assessing the number of segments in a model is theoretically complex, and requires the definition of a precise model of inference. To that extent, microarray CGH analysis not only requires computational approaches, but also a careful statistical methodology.
Methods
Materials
We briefly present the data we used in this article. The first data we use in the Results Section consist of a single experiment on fibroblast cell lines (Coriell Cell lines) whose chromosomal aberrations have been previously mapped. Those defaults concern partial or whole chromosome aneuploidy. This data have been previously used by other authors [10]. The second group of data used in the Results section is described in [6]. A test genome of Bt474 cell lines is compared to a normal reference male genome. The last data set used is described in [16] and consists of 125 primary colorectal tumors that were surgically dissected and frozen. The arrays used for these analysis are BAC arrays described in [6].
Models and Likelihoods
In this section, we define the models and . Let us consider a CGH profile, and note yt, the log2-ratio of the intensities for the tth BAC on the genome. Precisely yt represents the average signal obtained from the replicated spots on the slide. BACs are the basic units in our model, and are ordered according to their physical position. We suppose that the yt are the realizations of independent random variables {Yt}t = 1...n, with Gaussian distributions . We assume that K - 1 changes affect the parameters of the distribution of the Ys, at unknown coordinates (t0, t1, t2,...,tK - 1, tK) with convention t0 = 1 and tK = n, and that the parameters of the Ys distributions are constant between two changes:
where μk is the mean of the kth segment. Model specifies that the variance is segment-specific (), whereas considers that the variance is common between segments (σ2). Since BACs are supposed to be independent, the log-likelihood can be decomposed into a sum of "local" likelihoods, calculated on each segments: , with
Estimation of the segment's mean and variance
Given the number of segments K and the segments' coordinates (t0, t1, t2,...,tK-1, tK), we estimate the mean and the variance for each segment using maximum likelihood :
If the variance of the segments is homogeneous, its estimator is given by:
Notice that when the segment coordinates are known, the estimation of the mean and variance for each segment is straightforward. Then, the key problem is to estimate K and (t0, t1, t2,...,tK - 1, tK). We will proceed in two steps: in the first step, we will consider that the number of segments is known, and the problem will be to estimate the tks, that is, to find the best partition of a set of n individuals into K segments. In the second step, we will estimate the number of segments, using a penalized version of the likelihood.
A segmentation algorithm when the number of segments is known
When the number of segments K is known, the problem is to find the best partition of {1,...,n} into K segments, according to the likelihood, where n is the size of the sample. An exhaustive search becomes impossible for large K since the number of partitions of a set with n elements into K segments is . To reduce the computational load, we use a dynamic programming approach (programs are coded in MATLAB language and are available upon request). Let be the maximum log-likelihood obtained by the best partition of the data {Y(i), Y(i + 1),...,Y(j)} into k + 1 segments, with k break-points, and let note . The algorithm is as follows:
Dynamic programming takes advantage of the additivity of the log-likelihood described above, considering that a partition of the data into k + 1 segments is a union of a partition into k segments and a set containing 1 segment. This approach presents two main advantages: it provides an exact solution for the global optimum of the likelihood [17], and reduces the computational load from (nK) to (n2) for a given K (the algorithm only requires the storage of an upper n × n triangular matrix). At the end of the procedure, the quantities are stored and will be used in the next step. Notice that this problem of partitioning is analogous to the search for the shortest path to travel from one point to another, where represents the total length of a (k + 1)-step-path connecting the point with coordinate 1 to the point with coordinate n.
An adaptive method to estimate the penalty constant
The purpose of this section is to explain an adaptive method to estimate the number of segments. Further theoretical developments can be found in [14]. If we consider that the likelihood measures the adjustment of a model with K segments to the data, we aim at selecting the dimension for which ceases to increase significantly. For this purpose, let us define a decreasing sequence (β) such as β0 = ∞ and
If we represent the curve (pen(K), ), the sequence of βi represents the slopes between points (pen(Ki + 1), ) and (pen(Ki), ), where the subset {(pen(Ki),),i ≥ 1}) is the convex hull of the set {(pen(K),)}.
Since we aim at selecting the dimension for which ceases to increase significantly, we look for breaks in the slope of the curve. We define li, the variation of the slope, that exactly corresponds to the length of the interval ]βi, βi - 1] : li = βi - 1 - βi. The length of these intervals is directly related to the second derivative of the likelihood. The automatic procedure to estimate the number of segments is then to calculate the second derivative (finite difference) of the likelihood:
and we select the highest number of segments K such that the second derivative is lower than a given threshold :
Other procedures have been developed to automatically locate the break in the slope of the likelihood. Nevertheless, the criterion we use can be interpreted geometrically and is easy to implement. The choice of the constant s is arbitrary. According to our experience, a threshold s = -0.5 seems appropriate for our purpose. A criticism that can be made to this procedure is its dependency on the threshold which is chosen. Nevertheless, it is important to point out that despite this thresholding the procedure remains adaptive, since the penalty constant is estimated according to the data.
Simulation studies
We performe numerical simulations to assess the sensitivity of our procedure to the addition of noise. In the first case, we simulate 100 points with K* = 5 segments. In the first case Figure 3, the segments are regularly spaced and the difference of the means between two segments is d = 1. In the second case (Figure 4) the segments are irregularly spaced and the difference of the means varies between d = 2 and d = 0.5. The standard deviation of the Gaussian errors varies from σ = 0.1 to σ = 2. Each configuration is simulated 500 times, and we calculate the average selected number of segments over 500 simulations. In order to assess the performance of the dynamic programming algorithm, we calculate the empirical probability over 500 simulations for a break-point to be located at coordinate t (for t = 1 to 100).
Authors' contributions
FP developed the statistical models and the programs dedicated to array CGH data analysis, ML developped the adaptive selection of the number of segments. SR, CV and JJD supervised the study.
Acknowledgements
The authors want to thank Prs D. Pinkel and D. G. Albertson, and Dr E. Lebarbier for helpful discussion and comments, and L. Spector for editing the manuscript. CV is supported by grant NIH RO1 DK60540.
Figures and Tables
Figure 1 Results of the segmentation procedure when using the Bayesian Information Criterion (BIC) and the proposed criterion. Data shown corresponds to Coriell cell lines GM03563, chromosome 3. Red lines represent the estimated mean of each segments, and green lines, the estimated mean plus one standard deviation.
Figure 2 Estimated number of segments for 4 different penalized criteria in the regular case (top) and the irregular case (bottom). Top : Results of the simulations for 5 regularly spaced segments with n = 100 data points. The graph represents the average estimated number of segments for each criterion according to the standard deviation of the noise (σ). Bottom: Results of the simulations for 5 unregularly spaced segments with n = 100 data points. The adaptive criterion is robust to the additional noise since it maintains an estimate close to 5 segments whatever the noise and the configuration.
Figure 3 Example of a simulation in the regular case, and result of the dynamic programming algorithm for the estimation of the break-point coordinates. Top: Example of simulation for 100 data points and 5 segments in the regular case. The true break-points are designated by vertical lines, and the red lines correspond to the mean of each segment. The difference of means d is constant and equals 1. Bottom: Estimated frequency for a break-point to be located at coordinate t for t = 1 to 100. Different levels of noise are considered with σ = 0.1, σ = 0.5, σ = 1.
Figure 4 Example of a simulation in the irregular case, and result of the dynamic programming algorithm for the estimation of the break-point coordinates. Top: Example of simulation for 100 data points and 5 segments in the irregular case. The true break-points are designated by vertical lines, and the red lines correspond to the mean of each segment. The difference of means varies between d = 2 to d = 0.5. Bottom: Estimated probability for a break-point to be located at coordinate t for t = 1 to 100. Different levels of noise are considered with σ = 0.1, σ = 0.5, σ = 1.
Figure 5 Comparison of segmentation results based on Breast Cancer Cell lines using the adaptive criterion and Jong criterion. Results of the segmentation procedure for Breast cancer cell lines Bt474, chromosomes 9 and 10. Fluoresence log2-ratios are plotted according to their location on the genome in megabases. Left profiles are segmented using the adaptive criterion and right profiles using Jong's criterion. The adaptive method detects a break-point at 1.58 MB on chromosome 9 that seems to be an outlier, and detects a putative deleted region on chromosome 10 at 1.76 MB.
Figure 6 Comparison of segmentation results based on colorectal cancer data, using model and . Results of the segmentation procedure for colorectal cancer data, chromosome 1 and chromosome 8. Fluoresence log2-ratios are plotted according to their location on the genome in megabases. Left profiles are segmented using model , and right profiles using model . Our criterion is used to estimate the number of segments.
Table 1 Constants and penalty funtions for different penalized criteria, in a heteroscedastic model with K segments.
criterion β pen(K)
AIC I 2K
BIG 2K
Jong (2003) 10/3 3K - 1
Lebarbier (2003) adaptive
Lavielle (2003) adaptive 2K
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| 15705208 | PMC549559 | CC BY | 2021-01-04 16:02:49 | no | BMC Bioinformatics. 2005 Feb 11; 6:27 | utf-8 | BMC Bioinformatics | 2,005 | 10.1186/1471-2105-6-27 | oa_comm |
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BMC GenomicsBMC Genomics1471-2164BioMed Central London 1471-2164-6-141569847410.1186/1471-2164-6-14DatabaseSpecialized microbial databases for inductive exploration of microbial genome sequences Fang Gang [email protected] Christine [email protected] Yaowu [email protected] Virginie [email protected] Zhou [email protected] Cédric [email protected] Frankie [email protected] Ivan [email protected] Antoine [email protected] HKU-Pasteur Research Centre, Dexter HC Man Building, 8, Sassoon Road, Pokfulam, Hong Kong, China2 Plate-forme Intégration et Analyse Génomiques, Genopole, Institut Pasteur, 28 rue du Docteur Roux, 75724 Paris Cedex 15, France3 Unité de Génétique des Génomes Bactériens, CNRS URA2171, Institut Pasteur, 28 rue du Docteur Roux, 75724 Paris Cedex 15, France2005 7 2 2005 6 14 14 1 12 2004 7 2 2005 Copyright © 2005 Fang et al; licensee BioMed Central Ltd.2005Fang 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 enormous amount of genome sequence data asks for user-oriented databases to manage sequences and annotations. Queries must include search tools permitting function identification through exploration of related objects.
Methods
The GenoList package for collecting and mining microbial genome databases has been rewritten using MySQL as the database management system. Functions that were not available in MySQL, such as nested subquery, have been implemented.
Results
Inductive reasoning in the study of genomes starts from "islands of knowledge", centered around genes with some known background. With this concept of "neighborhood" in mind, a modified version of the GenoList structure has been used for organizing sequence data from prokaryotic genomes of particular interest in China. GenoChore , a set of 17 specialized end-user-oriented microbial databases (including one instance of Microsporidia, Encephalitozoon cuniculi, a member of Eukarya) has been made publicly available. These databases allow the user to browse genome sequence and annotation data using standard queries. In addition they provide a weekly update of searches against the world-wide protein sequences data libraries, allowing one to monitor annotation updates on genes of interest. Finally, they allow users to search for patterns in DNA or protein sequences, taking into account a clustering of genes into formal operons, as well as providing extra facilities to query sequences using predefined sequence patterns.
Conclusion
This growing set of specialized microbial databases organize data created by the first Chinese bacterial genome programs (ThermaList, Thermoanaerobacter tencongensis, LeptoList, with two different genomes of Leptospira interrogans and SepiList, Staphylococcus epidermidis) associated to related organisms for comparison.
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Background
We are facing a deluge of genome sequences. As of January 14th, 2005, the GOLD site identified 1248 completed or ongoing genome programs , and this certainly reflects only a partial view of the existing programs. While this shows that we implicitely possess an enormous wealth of information about the functions carried out by genes and genomes, the very fact that this amount is enormous makes it extremely difficult to mine that information easily. The role of specialized databases is to make this task easier for end-users. Many types of microbial genome databases exist. Most of them have been developed in a context of bioinformatics centres or laboratories purely favoring in silico research rather than the coupling between experiments using computers and experiments at the bench, and this is reflected in the structure and aims of the databases [1-8]. In contrast, at the onset of genome programs, we decided to set up a data structure for bacterial genomes that would help experimentalists to access knowledge on genes and genomes in an end user-oriented fashion. This was first the aim of the Colibri project, with the goal to organize Escherichia coli genome data, well before the whole genome sequence was known [9]. Later on, the SubtiList database was at the core of the Bacillus subtilis genome program data access [10]. Many databases constructed on the GenoList data schema were subsequently constructed (, [11]). However, with the exponentially growing set of genome sequences, it became important to divide up the work while maintaining the main goal of the project, that of being end-user-driven and of course, user-friendly. While an ongoing effort aims at integrating all bacterial genomes within the GenoList frame into a single database, it is important to create individual databases that could be regularly updated by a selected team of scientists (preferably those that initiated the corresponding genome program). This is particularly important for countries that are beginning to develop at a high speed into the genomics era. We took the opportunity of the creation of the HKU-Pasteur Research Centre in Hong Kong (China) to set up genome databases for the microbial sequencing projects developed in China (with databases for related organisms for comparison). Within this economic context, it was also important to take into account the cost of development. The paradigm GenoList databases are based on commercial DataBase Management Systems (DBMS) [11] and we decided to shift from a commercial DBMS to a non-commercial one, providing more freedom for the future of the project. In the present set of databases (GenoChore), emphasis is placed on retrieval of information centered on the gene as the central object, with exploration methods that query simple properties of the gene products (such as molecular mass or isoelectric point) in addition to more complex features such as the class of codon usage bias used in the gene [12]. Furthermore, queries can be made on the sequence itself using large scale analyses such as BLAST, and search for word patterns present in DNA and protein sequences.
Construction and content
Data schema
Because we wished to shift from a commercial DBMS to an open-source one, there were some applications that could not be implemented readily due to the lack of certain advantages possessed by the commercial DBMSs. Hence, we had to alter the data structure in order to cope with this situation. The core data schema used in this work was that of GenoList version 3.1 [11], with slight modifications (Figure 1).
Figure 1 Data Schema of the Databases. The core object of the schema is the Genomic_object, as in GenoList. It uses pointers in the sequence that delimits several categories of objects, including protein Coding DNA Sequences (CDSs), RNAs and other objects such as transcription terminators or riboswitches.
Database management system
In the present GenoList databases, the DBMS used is Sybase™. While this is convenient because of excellent stability and maintenance, this may pose problems in terms of commercial policies, especially if the structure has to be exported. We therefore decided to rewrite the management of the GenoList structure using MySQL . Most function transfers were straightforward. However some functions such as nested subquery that were not available in MySQL had to be dealt with indirectly. The nested subquery has been entirely circumvented in the PERL code and is dealt with in the Extended Search algorithm by concatenating different SQL queries simply using the "AND" or "OR"connector.
Data input
Sequence and annotation data were parsed from the files extracted from the International Nucleotide Sequences Database (INSD: DDBJ/EMBL-EBI/GenBank [13,14]) with the following procedure. To get access to the INSD, the authors of a genome sequence must follow the specification of the Feature Table Definition (FTD) jointly issued by the INSD partners . The current version is Version 6.2 Oct 15, 2004. While this specification is rigid, there is still a significant degree of freedom in annotation, so that a large number of individual situations have to be taken care of semi-automatically. The basic idea of the parser is firstly to read through the input file at the INSD and check file formats. Subsequently, the information is collected and distributed into several temporary files using a set of predefined keywords and their qualifiers (i.e. those characterizing the data schema). Subsequently, a check process is initiated to identify all situations that do not fit the specifications, so that they can be corrected manually. Usually, most of the process of creating tables is automatic and only a few exceptions have to be corrected individually. A second type of input is also provided as an interactive interface to tell the database curator what information has to be collected: once collected this information can be loaded into the databases directly (Figure 2). Teraprot data are obtained from Infobiogen .
Figure 2 Implementation of a Database Curator Page. In order to help users who would participate in the improvement of the database annotation a Curator Page is provided permitting input of updated information. It is available to users after acceptation of their collaboration, through a password protected access. Once data consistency has been verified the new annotations are implemented in the current database.
Query methods and interface
We kept the interface of GenoList as published, except that a box providing access to protected curation of annotations is now provided, aiming initially at helping the first party (sequencing teams) annotators. The front page is made of three frames. Briefly, the vertical frame on the left contains the controls necessary to get access to the content of the database. The upper part of this frame contains text fields for querying the database according to five types of queries: gene name(s), chromosome region around a gene, chromosome region defined by positions, free text, functional classification (more detailed information about each type of query can be obtained by clicking on the question mark near the query title). The "Extended Search" button gives access to a search form allowing the user to perform multicriteria searches on all the database fields. The lower part of this frame allows one to launch sequence analysis tools: BLAST and FASTA database searches (on the sequence data), and DNA or protein pattern searches. In the former case, the user can choose to explore sequences located upstream of putative operons. In the latter case, the user can search for patterns anywhere in proteins, but also restrict the search to the beginning or end of the protein. The upper frame on the right can contain various types of information, depending on the genome and on the query. It can contain a graphical representation of a chromosome region, that can be obtained in several ways: usually from a gene in the bottom frame. This frame may contain launch forms and result lists from the sequence analysis tools available (pattern search, BLAST or FASTA scanning). The bottom frame on the right always contains detailed information about one given gene, including regularly updated BLAST searches and Teraprot reports as well as related bibliographic references. The original package managing the interface of GenoList databases was written in C/C++, following the first database schema [10], that had been adapted for use with the Sybase™ DBMS (the initial platform was using the DBMS 4th Dimension™). The modification of the database schema needed for using MySQL required additional adaptations of the application interfaces. Using the original package would have required iterative work that was systematically adding complexity into the system. Current best Web interfaces and application interfaces (i.e. friendly for sharing parties) are often based on Perl scripts. For this reason a new core management script was recreated, written in Perl, while keeping the package architecture and the Web interfaces. Among other languages that have comparable functionalities, the choice of Perl to create the system was motivated by its powerful capability to glue different programs or scripts together. In addition it is widely used by the INSD, and at the European Bioinformatics Institute in particular within the BioSapiens program . Furthermore, this choice allowed us to keep the optimized fast C code that has been constructed for searching pattern (strings of symbols) inside the DNA or amino acids sequences. The GenoList C/C++ package chose to use the GD library for generating graphic representations of genome regions. The GD graphics library is an open source library which allows programmers to easily generate PNG, JPEG, and WBMP images from many different programming languages. We used here a newer version of the same library (perl module perl-GD version 2.11) to make use of its improvements in creating dynamic pictures. In rewriting the core of the program we used the Perl module DBI . A DBI is a middle layer between the outside applications and the communicator (DBD). Different DBMSs have their own communication mechanism to talk with outside applications, and in the present version the choice of the DBI module has been implemented in such a way that we could change the DBMS if necessary with minimal work. In this way, when changing the DBMS, it will only be necessary to tell the DBI about the specifications of the new DBMS without having to modify any other code. Finally, we used the Perl module CGI to facilitate the production of the WebPage interfaces. As a consequence further developments of the GenoChore package should be performed with minimal effort.
Utility and discussion
Data schema
In the original GenoList structure, the central table corresponding to genomic objects carried all relevant features that are associated to genes and gene products. For the sake of future developments and to accommodate new feature annotation present in genome flatfiles, we separated this table into several gene product tables, specific for RNAs and proteins. The current data structure remains open to include tables for other types of data, such as regulation properties annotations when they will become available. Figure 1 displays a diagram of the current generic database schema (we did not show tables that remain empty for want of annotation data). As expected for a database meant to provide knowledge from genome programs, the central tables are focussing on genomic objects, the main one corresponding to protein Coding DNA Sequences (CDSs). To match this structure, the information present in the flat files created by the sequencing consortia, and present in the INSD, is split into three parts, namely, a) genomic objects, i.e. what we see in a chromosome, at precisely identified positions in the genome sequence (depending on the annotation tools available to the consortia), such as a CDS, a promoter, a terminator, a tRNA, an sRNA etc.; b) genome annotations, i.e. protein, RNA and other bio-molecules' products, functions, comments and so on; c) relations between genomic objects: e.g. the typical concept of gene requires its association to a promoter, a terminator and usually a CDS. In this representation, a set of genome objects' identifiers (ids) is used to represent a gene. This facilitates the association of genomic objects together with much more sophisticated relationships into more complex structures, when required.
It is important here to notice that, in contrast to a rather ubiquitous practice, we explicitely separate between Open Reading Frames (ORFs) that are simply sequences multiple of 3 between two termination codons (TAA, TAG and TGA) and CDSs, that begin with a specific codon, usually ATG (in the DNA text), preceded by a ribosome binding site (RBS), typically AAGGAGGT in many bacterial genomes. One must remember that in most genomes the beginning of CDSs has not been experimentally identified. Identification of CDS starts is however much easier in low G+C Firmicutes that do not possess a counterpart of ribosomal protein S1 found in gamma proteobacteria [15]. In the same way, G+C-rich organisms have usually long ORFs, but the CDSs they harbour are usually highly enriched in A+T at the third codon position. Some caution, therefore, should be exerted by users when using the information collected in the databases about the beginning of proteins in these organisms (for example in the Streptomyces coelicolor database, CoeliList).
Nomenclature: naming genes
Users know that the system used for naming genes in genome databases is extremely unwieldy and completely lacks standardization. This is usually because genes are simply labelled in databases by access numbers corresponding to the annotation phase of the relevant genome program (e.g. PA3004 for a gene found in the genome of Pseudomonas aeruginosa). In the absence of knowledge of a gene name it takes some time to identify it (often using BlastP), for example when aiming at the study of its neighborhood ((i.e. proximity of an object or a relationship with others sharing the same conceptual space, including presence in a common article [12]). Naturally, because most genes have never been experimentally identified in the majority of the newly sequenced genomes, this approach is certainly safer than giving a name without proper identification criteria. However it is extremely useful for scientists studying a genome to start from "islands of knowledge", with genes with a known background, reflected by a known gene (and a gene name has usually been coined by experimentalists for that gene). For this reason, we decided to use a conservative approach, using bidirectional best Blast hits of the genome of interest with model genome (Escherichia coli K12 and Bacillus subtilis 168). Orthologues were identified as reciprocal best hits [16] (using a global alignment where the gaps on the edges of the largest sequence are ignored) with at least 50% identity in amino acid sequence and less than 20% difference in protein length. When possible, in order to increase the likelihood of the putative identification we used a second well known representative of the genome under study and looked for orthologues between every pair of each of the two triplets (i.e. between each pair of the three organisms: the organism of which the database is constructed, B. subtilis for Firmicutes and another organism of the same family, such as Listeria monocytogenes, and E. coli for gamma-proteobacteria, with another one of the same family, such as Photorhabdus luminescens). Finding putative orthologues in the three organisms was considered as substantiating evidence for the use of a gene name. Then, in each triplet, we did not transfer the model organism gene name to all orthologues that were not simultaneously present in the three genomes or that gave different correspondences in different comparisons. In another comparison where the orthologues were found with at least 50% similarity, the model organism gene names to be transferred were preceded by the letter 'y'. In order to help users recognize gene names (and all the knowledge they associate with those names) we used as reference names those in the model bacteria, trying to comply as much as possible with the names used at SwissProt in the HAMAP project [17].
This allows the users to have "anchor" points to start to use the databases in a more efficient way. Naturally, the names previously used in the corresponding genome programs are kept as synonyms, so that access to the sequences with these names is still allowed. For example, in AeruList, gene rpsA can be accessed directly or using its synonym PA3162: it is then found downstream of cmk (a context similar to that found in many Gram negative bacteria) and upstream of himD. We are aware that some erroneous identification (or propagation of erroneous identifications) must have occurred in some cases, but we think that this is a trade-off (which will be continuously corrected) for a much more user-friendly usage of the databases. A 'y' letter starting a gene name indicates that it has not been experimentally identified, nor convincingly identified after in silico analysis yet. We provide curation pages (see below) to help users to correct annotation errors and improve annotation in a continuous way.
Functional categories and bioprocesses
An important feature for allowing users to explore biological functions is to investigate the genes neighborhoods [12]. Related functions are often coded by genes in close vicinity in the chromosome. We therefore used the GenoList table for functional categories, that allows the user to make links with the roles of proteins in the cell. The functional classification used in some of the present databases has been created by superimposing the functional classification (ontology) created for SubtiList, and that of Escherichia coli created by Monica Riley and her collaborators [18] (Additional file). In addition we created a field for the ontology describing underlying bioprocesses: explore, sense, shape, circulate, excrete, replicate, grow, respire, manage energy, store, scavenge, maintain, protect, control. They will be used in the future to color the arrows indicating genes in the picture of the region surrounding a gene of interest, allowing the user, at a glance, to have a rough idea of the processes encoded in the corresponding region.
Queries using mining algorithms
In addition to using keyword queries or sequence tags (such as molecular mass or isoelectric point of a protein) the database provides a versatile way to identify sequences from the biological knowledge viewpoint. In particular, as in many other databases, it allows the user to use Fasta, BlastP and BlastN to compare a sequence of interest to that of those present in the database. Furthermore, in contrast to most cases, it allows the user to extract information using motifs, that can be either continuous or discontinuous (e.g. finding all proteins with motif CXXCHX12–25C). This facility has already, in a quite unobtrusive but efficient way, permitted discovery of many unexpected functions. We have also provided means to explore the beginning and the end of protein sequences, as well as DNA regions upstream of putative operons, computed as strings of genes transcribed in the same orientation and separated by a maximum number of nucleotides (60 nt by default).
Automatic updates
Genome annotation is continuously updated by scientists all over the world, at a time when new genome sequences appear every three days or so. In order to cope with this enormous flux of information, a facility for browsing automatically new entries in major data libraries has been implemented. In the gene information panel, where each gene of interest is described after being identified as the result of a query (including resulting from a Blast or Pattern search), an "Automatic Blast" link provides a list of updated blast searches against the UniProt library (SWISSPROT+TREMBL). In addition, when the genome belongs to the 'Teraprot' Smith and Waterman Z-score family , the corresponding links (that are statistically much more significant than the results of Blast searches) are provided, allowing the user to look for remote kinships.
To discuss the use of the databases we shall restrict our exploration to two databases from the package. LeptoList, that comprises two genomes (each one having two chromosomes) for Bacteria, and CunicuList, that describes the genome sequence and annotation of a small eukaryote.
An example: LeptoList
LeptoList is the reference database dedicated to the genome of Leptospira interrogans serovar Lai, the paradigm of leptospirosis causative agents [19]. It is presented together with a second sequence, that of L. interrogans serovar Copenhageni in order to allow easy comparison [20]. The WWW interface takes into account the fact that L. interrogans has two chromosomes (this feature was not yet displayed in GenoList databases). Using the regular comparison to the CDS to the non-redundant INSD protein database allowed us to suspect that a significant proportion of the short putative CDSs in the genome are likely ORFs and not authentic CDSs. This fits with the recent sequencing of the second Leptospira genome [20,21].
A couple of examples of its use are given here. We looked for counterparts of RRF, the ribosome release factor. In order to find the gene we used a known sequence, from B. subtilis (frr gene product) and compared it using BLAST with the functionality implemented in LeptoList. This search led to a single gene, LA3295, located downstream of gene pyrH (as in most other bacterial genomes). This synteny is obviously highly significant. In the same way, the gene immediately upstream from pyrH (LA3297), as in other bacteria, is likely to be coding for elongation factor EFTs (tsf). When curating the database, we suggest to the curator that it would be of excellent policy to replace the gene numbers by the corresponding gene name. In another type of investigation, looking for patterns of the type TTGACA (1 ambiguity) – 17 nt – TATAAT# (1 ambiguity) (consensus sequence of the σ70-type promoter) in the 300 nt region upstream of genes revealed 70 sequences in chromosome I, many of which are likely to be promoters (at least they would be good guesses to start investigating promoters in L. interrogans). In the same way, the putative DNA binding site located in the 300 nt nucleotide region upstream of genes, TGTGA (1 ambiguity) – 2 nt – KK – 2 nt – TCACA (1 ambiguity) (consensus sequence of the CAP/FNR family of transcriptional regulators), yielded 130 matches in chromosome I of serovar Lai and 72 matches in serovar Copenhageni and 2 in chromosome II of serovar Lai and 0 in serovar Copenhageni, allowing one to start investigating possible regulatory elements.
This result is interesting as it suggests that chromosome I genes are submitted to a regulation recognizing that particular DNA-protein binding site. Furthermore, most genes found with the site in serovar Copenhageni are also found in serovar Lai, with sometimes several repeats in the latter, occuring upstream of some genes (such as fadH or prfC), accounting for the higher total number of putative binding sites in that organism. It seems most interesting that genes involved in the control of respiration (cytochrome c biosynthesis), control of the TCA cycle (pyruvate dehydrogenase synthesis), control of the coupling between translation and transcription (stringent control) or translation itself (release factor 3 synthesis) are present in the list. While there are several putative adenylyl cyclase genes present in the organism, as well as several homologs of crp, it is plausible to propose that cAMP plays an important role in the life cycle of L. interrogans, perhaps suggesting ways to allow multiplication on plates of this elusive organism.
LeptoList is accessible at the URL
CunicuList: a database for a small eukaryote genome
The GenoList structure has been initially constructed for organizing sequence data from prokaryotic genomes. However it may be extended to other organisms as well (the "genomic object" type must be extended accordingly). We have therefore tested the implementation of the structure for the genome of Encephalitozoon cuniculi, belonging to the Microsporidia taxon. Eleven chromosomes are present in this organism. Extraction of information is similar to that from other databases. For example we looked for counterparts of genes involved in tRNA modification (often essential genes). Using MesJ (TilS) [22] as well as TrmU [23] we found that gene Ecu03_1240 is most probably involved in driving the codon and amino acid specificity of a tRNA (possibly isoleucine or lysine tRNA). In the same way we could predict that gene Ecu07_1610 codes for synthesis of dihydrouridine in tRNA, a general feature of tRNA structure, because of its similarity with the yacF B. subtilis gene. Looking for counterparts of genes in the methionine salvage pathway [24], we failed to identify any gene that would code for the enzymes of the pathway, indicating that the parasite obtains all the metabolites derived from S-adenosylmethionine from its host. This is substantiated by the fact that the genes needed to synthesize queuosine [25] are apparently absent from the genome. Some organisms do not use this major tRNA modification, but this could be an interesting information for identification of drug targets against the parasite, since this suggests that those metabolites have to be transported into the cell by specific permeases.
Database curation
Several other similar bacterial databases are accessible at URL . Table 1 presents the list of microbial databases that are available at the Bioinfo server of the University of Hong Kong.
Table 1 List of databases present at the Bioinfo server The GenoChore suite presented here manage bacterial genome data, except for CunicuList, which presents the sequence and annotation data of the small eukaryote Encephalitozoon cuniculi.
AeruList Pseudomonas aeruginosa PA01 EMBL:AE004091
AnthraList Bacillus anthracis str. Ames EMBL:AE016879
CampyloList Campylobacter jejuni NCTC 11168 EMBL:AL111168
CereList Bacillus cereus ATCC 14579 EMBL:AE016877
CholeList Vibrio cholerae EMBL:AE003852
, EMBL:AE003853
CoeliList Streptomyces coelicolor A3(2) EMBL:AL645882
DiphteList Corynebacterium diphtheriae NCTC 13129 EMBL:BX248353
CunicuList Encephalitozoon cuniculi EMBL:AL391737
, EMBL:AL590442
, EMBL:AL590443
, EMBL:AL590444
, EMBL:AL590445
, EMBL:AL590446
, EMBL:AL590447
, EMBL:AL590448
, EMBL:AL590449
, EMBL:AL590450
, EMBL:AL590451
InfluList Haemophilus influenzae Rd KW20 EMBL:L42023
LeptoList Leptospira interrogans Lai str. 56601 EMBL:AE010300
, EMBL:AE010301
Leptospira interrogans Fiocruz L1-130 EMBL:AE016823
, EMBL:AE016824
MeningoList Neisseria meningitidis MC58 EMBL:AE002098
PutidaList Pseudomonas putida KT2440 EMBL:AE015451
SepiList Staphylococcus epidermidis ATCC 12228 EMBL:AE015929
SubtiList Bacillus subtilis str. 168 EMBL:AL009126
ThermaList Thermoanaerobacter tencongensis MB4 EMBL:AE008691
VulnifiList Vibrio vulnificus YJ016 EMBL:BA000037
, EMBL:BA000038
XylelList Xylella fastidiosa 9a5c EMBL:AE003849
Despite of – or because of – the large number of genome programs, once a sequence has been deposited at the INSD, its annotation is seldom updated. This is because the cost of curating annotations is extremely high, and usually not considered, despite its enormous importance. One of our aims was therefore to allow curation by selected teams by creating a curator page where such teams would input their annotations, that would then be propagated to the databases. The basic schema of the curator interface is shown in Figure 2. In order to preserve the quality of the input data, potential users are asked to write to the database's webmaster to ask for account and passwords. We kept the interface of GenoList as published, except that a box providing access to protected curation of annotations is now provided, aiming initially at helping the first party (sequencing teams) annotators. If this works to our satisfaction this will be extended to selected third party annotators. Subsequently, on a yearly basis (or more frequently if needed) the collected re-annotation of the curators would be submitted as a new version of the same genome to the INSD. We hope that this service will be useful for the scientific community as a whole.
Conclusions
A set of 17 specialized end-user-oriented microbial databases (including one instance of Microsporidia) has been implemented in Hong Kong. They allow one to browse genome sequence and annotation data using the most frequent queries that end-users would like to ask. In addition they provide a weekly update of searches against the world-wide protein sequences data libraries, allowing one to monitor annotation on genes of interest. Finally, they allow users to search for patterns in DNA or protein sequences present in the databases. All comments, bug reports and suggestions for improvement are more than welcome: this work is meant to be useful for the community of microbiologists interested in genomics.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
GF wrote the parsers used to create the preliminary C/C++ MySQL package, and created important sections of the Perl package; CH created the procedure for renaming orthologs with reference to accepted names for model bacteria (Bacillus subtilis and Escherichia coli), created the link to Teraprot for identification of gene functions, and implemented parts of the PERL package; YQ implemented parts of the Perl package; CC and VC implemented most of the databases into the core structure; ZY wrote part of the new parsers, implemented the two chromosomes of LeptoList by changing the data structure in the database and set up with CC the first LeptoList database; FC set up and administered the Apache web server and MySQL database; IM over the years designed most of the GenoList data schema and user interface; AD was at the origin of the project, participated in the design and evolution of the data schema, was the systematic tester and end-user and wrote the core of the article.
Supplementary Material
Additional File 1
Functional categories. The genes' roles are listed into six major categories. The three first ones are directly linked to biological roles, while the remaining categories are created ad hoc: adaptation to atypical conditions correspond to miscellaneous roles, while the two last categories correspond to roles that have not yet been ascribed to genes because of lack of in vivo or in silico data
Click here for file
Acknowledgements
These databases are implemented at the Hong Kong University Computer Centre (Dr Nam Ng, Director). This effort is sponsored by the Innovation and Technology Fund of the government of the SAR Hong Kong, China (program BIOSUPPORT), granted to A. Danchin for the creation of the HKU-Pasteur Research Centre, with the collaboration of N. Ng, Computer Centre. We thank the CNRS (URA 2171, Genetics of Genomes) for support. GF was supported by the Friends of the Institut Pasteur in Hong Kong. Initial development stages of GenoList were performed in the framework of the European B. subtilis genome project (European Commission Biotechnology program – contracts BIO2-CT93-0272, BIO2-CT94-2011, BIO4-CT96-0655), coordinated by F. Kunst and supported by the BACillus Industrial Platform (BACIP). We thank the contribution at various stages of P. Glaser, A. Hénaut, C. Médigue, M. Pupin, and A. Viari. We acknowledge the fruitful collaboration with Infobiogen and with A. Bairoch and the SWISSPROT team. In the most recent part of this work we benefited from the BioSapiens EU grant LSHG-CT-2003-503265.
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| 15698474 | PMC549560 | CC BY | 2021-01-04 16:39:33 | no | BMC Genomics. 2005 Feb 7; 6:14 | utf-8 | BMC Genomics | 2,005 | 10.1186/1471-2164-6-14 | oa_comm |
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BMC Med Res MethodolBMC Medical Research Methodology1471-2288BioMed Central London 1471-2288-5-71569847010.1186/1471-2288-5-7Research ArticleEffects of the search technique on the measurement of the change in quality of randomized controlled trials over time in the field of brain injury Borsody Mark K [email protected] Chisa [email protected] Department of Neurology Northwestern Memorial Hospital Chicago, Illinois 60611 USA2 Department of Pathology Albert Einstein University Bronx, New York 10463 USA2005 7 2 2005 5 7 7 6 8 2004 7 2 2005 Copyright © 2005 Borsody and Yamada; licensee BioMed Central Ltd.2005Borsody and Yamada; 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 determine if the search technique that is used to sample randomized controlled trial (RCT) manuscripts from a field of medical science can influence the measurement of the change in quality over time in that field.
Methods
RCT manuscripts in the field of brain injury were identified using two readily-available search techniques: (1) a PubMed MEDLINE search, and (2) the Cochrane Injuries Group (CIG) trials registry. Seven criteria of quality were assessed in each manuscript and related to the year-of-publication of the RCT manuscripts by regression analysis.
Results
No change in the frequency of reporting of any individual quality criterion was found in the sample of RCT manuscripts identified by the PubMed MEDLINE search. In the RCT manuscripts of the CIG trials registry, three of the seven criteria showed significant or near-significant increases over time.
Conclusions
We demonstrated that measuring the change in quality over time of a sample of RCT manuscripts from the field of brain injury can be greatly affected by the search technique. This poorly recognized factor may make measurements of the change in RCT quality over time within a given field of medical science unreliable.
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Background
Considerable effort has been directed toward improving randomized controlled trial (RCT) design, execution, and reporting [1-6,14]. Such efforts to define standards of quality for RCTs beg the question: are RCTs improving in quality over time? Many reviews have attempted to answer this question. In general, these reviews measure the presence or absence of several criteria chosen to define quality in a sample of RCT manuscripts that was selected from a parent population of RCT manuscripts. The parent population of RCT manuscripts may be either a field of medical science or a defined part of the medical literature (e.g., RCT manuscripts from a chosen journal). Then, by examining a score of quality as a function of the year-of-publication of the sampled RCT manuscripts, conclusions are drawn as to whether or not quality is changing over time in the parent population of RCTs. If such reviews are to be useful, then, the sample of RCT manuscripts that was chosen for analysis must represent the parent population of RCT manuscripts.
As much as the RCT manuscripts published in a single journal or group of journals would provide a well-defined parent population, the RCT manuscripts from a given field of medical science would be difficult to completely identify. Ultimately no search strategy can claim to identify all manuscripts on a given topic that have been published in every book and journal worldwide. Thus, two search techniques might provide considerably different samples of RCT manuscripts from the same field of medical science depending upon how much and / or what parts of the parent population of RCT manuscripts they can access. The current communication empirically demonstrates this point as a potential pitfall in measuring the change in quality over time of RCT manuscripts sampled from a representative field of medical science.
Methods
Criteria of quality
We chose internal validity as a measure of quality according to the definition given by Gehlbach [7], namely that a RCT is internally valid when "within the confines of the study, results appear to be accurate and interpretation of the investigators is supported". We selected criteria of internal validity according to the recommendations of Moher et al. [8]. The relevant points are addressed below.
I. Definition of the quality construct
We intended to measure the presence or absence of various criteria of RCT quality as described in the published manuscript. No attempt was made to contact the authors of a manuscript either to clarify the information provided in the manuscript or to gain additional information about a RCT. We acknowledge that relying on the published manuscript in order to assess the quality of a RCT may be biased (1) against well-designed RCTs that were reported in poorly written manuscripts and (2) in favor of poorly-designed RCTs that were reported in well-written manuscripts [9]. Thus, our scoring process ultimately measured the quality of the report of the RCT manuscript, rather than the true methodological quality of the trial as it was conducted. However, attempting to obtain an understanding of the true methodological quality of a RCT in a retrospective manner by contacting the authors of the manuscripts would undoubtedly collect more information on recent RCTs because their authors will be more accessible (i.e., less likely to have relocated, retired, or died). Attempting to contact the authors of manuscripts is rarely successful [10] and, when it is successful, accurate information about the design and conduct of the RCT is not always forthcoming [11,12].
II. Definition of the scope of internal validity and identification of quality criteria
Although random allocation and the use of a concurrent control group are the sine qua non of the RCT, additional criteria have been so frequently included in their design and execution that they are now commonly considered as part of quality RCTs. Several sources (themselves located by PubMed MEDLINE and bibliography searches) were used to identify such criteria [2,9,13-18]. After forming a composite list of internal validity criteria from these sources, we searched the literature (again by means of PubMed MEDLINE and bibliographies) for instances where the presence or absence of each criterion in a RCT affected the results obtained from the RCT. Thus, we identified criteria that were supported by empirical evidence as measures of RCT quality. We identified six criteria that had predominantly supporting evidence in their favor. Subsequently, allocation concealment was included as a separate quality criteria. The quality criteria, with brief descriptions, are listed in Table 1.
Table 1 The quality scale This table lists the criteria of quality that were used to score the RCT manuscripts. Abbreviated definitions for the presence (1 point) or absence (0 points) of each criterion are provided.
1) assessment of the distribution of patient characteristics and prognostic factors between groups
present distribution of patient characteristics and prognostic factors assessed without asymmetry between groups
absent not mentioned; distribution of patient characteristics and prognostic factors assessed with asymmetry noted between groups
2) prevention of the movement of patients between groups after allocation, and the use of intention-to-treat analysis
present use of intention-to-treat analysis; no movement of patients between groups confirmed
absent not mentioned; patients known to change groups before analysis
3) the blinding of the patients to the treatment they received
present statements of double-blind present; use of a placebo; statements of the treatments being indistinguishable present; patients not aware of study due to clinical condition
absent not mentioned; lack of placebo use in control group; readily-distinguishable treatments; blinding breakdown confirmed
4) the blinding of the health care providers to the treatments received by the patients
present third-party dispensation of treatments; statements of health care provider blinding present; health care provider identical to outcome observer, and outcome observer is blinded
absent not mentioned; health care team aware of patient allocation; lack of placebo in control condition; readily-distinguishable treatments; blinding breakdown confirmed
5) the blinding of the outcome observer to the treatment received by the patient
present statements of double blind present; objective outcome; use of standardized tests or questionnaires that do not require an outcome observer; subjective principle outcome but outcome observer blinded to treatment; blinded health care providers performing outcome assessment
absent not mentioned; subjective outcome without blinding of the outcome observer; blinding breakdown confirmed
6) completeness of follow-up
present no patients lost to follow-up; acute experimental design does not permit loss of patients; analysis of lost patients provided according to randomization groups, with reason for loss
absent not mentioned; no analysis of lost patients provided; effect of patient loss to follow-up confirmed
7) allocation concealment
present use of consecutive opaque envelopes or pre-ordered treatments; third party assignment of allocation
absent not mentioned; repeatable pattern of allocation; use of obvious identifiers for allocation (e.g., birth date, record number); assignment of treatment by treating physician
We limited our quality scale to measure criteria that have been demonstrated empirically to be associated with the quality of RCTs. This necessarily excluded many items associated with RCT design and execution that are widely thought to affect quality or that are included in commonly-used quality scales, but it provided us with a defensible "bare minimum" definition of quality. It should be noted that we did not intend our list of criteria to be encompassing of all aspects of quality; our criteria were intended to serve only as a tool for the comparative analysis of the two sets of RCT manuscripts for the purpose of this study.
III. Scoring System
Each of the seven criteria was scored as being present (1 point) or as absent (0 points) in the RCT manuscript. Definitions of each criterion are shown in Table 1. If a RCT manuscript did not mention the presence of a criterion, it was considered absent. Conversely, all written statements in the manuscripts were assumed to be accurate both factually and semantically.
IV. Criteria Scoring Verification
The intra-rater reliability for the scoring of the quality criteria was determined by comparing the individual criteria scores given to n = 16 RCT manuscripts by one of the authors of this communication (MKB) on two occasions separated by 3 weeks. The correlation coefficient (Kappa) measured in this manner was 0.94.
Inter-rater reliability was determined by comparing the quality criteria scores given to n = 10 RCT manuscripts by two different examiners. One copy of each manuscript was scored by one of the authors of this communication (MKB) while the other copy was scored by an independent examiner (Dr. Babak Jahromi, Department of Neurosurgery, the University of Toronto) who was provided with a thorough description of the criteria. The correlation coefficient (Kappa) for inter-rater reliability was determined to be 0.74.
Manuscript selection and the screening process
We chose to evaluate the field of brain injury because two search techniques for sampling the population of these RCT manuscripts were readily available. The first search technique was our own PubMed MEDLINE search. The second search technique was performed by the Cochrane Collaboration Injuries (CIG) Group, and forms the CIG trials registry. Copies of the RCT manuscripts identified by these two search techniques were retrieved through the library holdings and interlibrary loan services of five universities.
Next, the manuscripts were read by one of us (CY) to screen-out inappropriately identified manuscripts. Table 2 provides a detailed list of these exclusions. Inherent in the phrase 'randomized controlled trial' is (1) the random allocation of patients into multiple groups for prospective analysis, and (2) the concurrent comparison of at least one group that receives the experimental treatment against another group that does not; manuscripts that did not include random allocation and a concurrent control group were excluded. Furthermore, in order for a manuscript to be considered pertinent to the study of brain injury one of the following conditions had to be met: (1) brain injury had to directly define the patient population; (2) brain injury had to be the cause of a second condition (e.g., seizures) that defined the patient population; or (3) brain injury had to be the outcome measure for the patient population. If none of the above conditions were met the manuscript was discarded from further examination. Duplicate publications, protocol descriptions, abstracts, letters-to-the-editor, and incomplete or preliminary reports were also removed during the screening process.
Table 2 Exclusion of manuscripts from the PubMed MEDLINE and CIG Trials Registry groups of manuscripts Manuscripts inappropriately identified by the PubMed MEDLINE search and the CIG trials registry were removed from review during a screening process performed by one of the authors of the current communication (CY).
reason for exclusion PubMed MEDLINE search CIG Trials Registry group
INITIALLY IDENTIFIED 139 312
libraries unable to locate 0 15
unrelated to brain injury 2 3
duplicate publications 2 8
inaccurately claimed to be a controlled trial 22 47
inaccurately claimed to use randomization 11 30
abstracts / letters-to-the-editor 1 31
protocol descriptions 3 0
incomplete / preliminary reports 0 4
non-human subjects 0 1
TOTAL NUMBER DISCARDED 41 139
REMAINING 98 (70% of initially identified) 173 (55% of initially identified)
The design and yield of the two search techniques was as follows:
1) the PubMed MEDLINE search: The first search technique we used to identify RCT manuscripts pertaining to brain injury involved the PubMed search engine of the MEDLINE database. It was designed to represent a typical literature search performed by a North American researcher who is fluent only in English. The search term "brain injuries" (C10.228.140.199) was used with the limitations of (1) randomized controlled trial, (2) human subjects, and (3) publication in English. The PubMed MEDLINE search included manuscripts indexed from January, 1966, up to February, 2001 (the time at which the search was performed).
The PubMed MEDLINE search identified n = 139 manuscripts. During the screening process, n = 41 manuscripts from the original 139 (30%) were discarded leaving n = 98 manuscripts (see Table 2 for a detailed list of the exclusions).
2.) the CIG trials registry: The Injuries Group of the Cochrane Collaboration was kind enough to share their list of RCT manuscripts with us for the purpose of conducting this study. The list of manuscripts they provided was compiled by means of the following three steps:
step 1) The CIG trials master list was searched using the keywords "head" or "brain" in conjunction with "injur*" or "trauma*". The CIG trials master list is a local database maintained at the London School of Hygiene and Tropical Medicine that uses a detailed search strategy to identify RCTs from multiple computerized databases (a copy of this search strategy is available from Ms. Fiona Renton of the London School of Hygiene and Tropical Medicine [email protected]) as well as various hand searches of journals performed during the writing of systemic reviews; it is updated quarterly.
step 2) MEDLINE, EMBASE, and CENTRAL databases were searched using the exploded keyword "head injuries:ME" or "head injuries:TI". EMBASE includes references from 1974 onward and, while it uses its own database, it is based on an indexing hierarchy which incorporates that used by MEDLINE. Here, MEDLINE was searched with the SilverPlatter search engine, not with the PubMed Search engine. Manuscripts of the MEDLINE database indexed as early as 1966 were accessible to the SilverPlatter search engine. The CENTRAL database is a general list of clinical trials that is maintained by the collaborative efforts of multiple Cochrane specialty groups.
step 3) Manuscripts identified by hand searches of relevant journals and from references provided by direct contact with experts in the field of brain injury were also included.
The original CIG trials registry was completed in 1998 and was last fully updated in May, 2001; it is that version which was used in our study.
The CIG trials registry included n = 312 manuscripts. During the screening process, n = 139 manuscripts from the original 312 (45%) were discarded leaving n = 173 RCT manuscripts (see Table 2 for a detailed list of the exclusions).
3.) overlap between the PubMed MEDLINE search and the CIG trials registry: Of the total unscreened samples of manuscripts identified through each search technique, n = 80 manuscripts were present in both samples; this corresponded to 58% of the sample of manuscripts identified by PubMed MEDLINE search and 26% of the sample of manuscripts from the CIG trials registry. After the removal of inappropriate manuscripts during the screening process, and scoring process only n = 56 manuscripts were identified by both the PubMed MEDLINE search and the CIG trials registry. This corresponded to 57% and 32% of the PubMed MEDLINE search and the CIG trials registry samples, respectively.
The scoring process
Each of the RCT manuscripts was read by both authors of the current communication (CY and MKB) who, for clarity's sake, will be referred to as "examiners". One examiner ("non-judging examiner": CY) performed the screening process described previously, then recorded the year-of-publication of each manuscript that survived the screening process in a computerized spreadsheet (Microsoft Excel) and marked them with identification numbers. Then, the non-judging examiner hid the names of the authors of the manuscript, the authors' degrees and departmental affiliations, the journal in which the RCT manuscript was published, and the year-of-publication of the manuscript with black marker. This information was covered wherever it was found in the manuscript so that when the manuscript was scored by the second examiner ("judging examiner": MKB) there would be no potential for bias [8,19]. The data collected by the judging examiner was entered into a computerized spreadsheet that was different from the one linking the year-of-publication of the manuscripts with their identification numbers. The two spreadsheets were combined only when all the manuscripts had been read.
As mentioned above, allocation concealment was included in the list of quality criteria after the first evaluation of the manuscripts. Accordingly, the judging examiner re-read all the manuscripts specifically to determine the inclusion of allocation concealment. The manuscripts were still blinded as described above, and the data was entered into a third spreadsheet that was subsequently analyzed independently of the preexisting data.
Manuscripts in French and Spanish were read without written translation by the judging examiner, whereas written translations were provided to the judging examiner for manuscripts in Japanese (by CY), German and Italian (by Mrs. Margaret K. Borsody), and Chinese (by Language Line, Inc., document translation service).
Statistical analysis
After completion of the scoring process, statistical analyses were conducted by the judging examiner. The data was considered interval in nature and thus data analysis for discrete variables was used [20]. Furthermore, since this study was constructed as a longitudinal analysis of the change in quality scores over time, it was necessary to use some form of regression analysis to examine the data. Considering these requirements, binary logistic regression analyses were performed for each individual quality criteria. All statistical analyses were done by SPSS (version 11.5, SPSS Inc.). Scores for the individual quality criteria were examined as dependent variables against the independent variable of year-of-publication. Significance is defined as a P < 0.05.
Since the samples of manuscripts from the PubMed MEDLINE search and the CIG trials registry are known to be derived from the same parent population of RCTs (i.e., RCTs in the field of brain injury), it is inappropriate to directly compare them against each other with statistical tests. Rather, it was our goal to analyze the two samples of RCT manuscripts separately, and to make likely conclusions about the parent population from each sample of manuscripts as if there was no other sample of manuscripts available for comparison. Then, knowing that the two samples of RCT manuscripts represent the same parent population, it was our intention to compare the conclusions derived from the separate analyses to determine the impact of the search technique thereupon.
Results
Regression analysis of the individual quality criteria against the year-of-publication of the RCT manuscripts was performed to determine if the frequency of reporting of each quality criteria changed over time. For the sample of RCT manuscripts identified by the PubMed MEDLINE search, no significant relationship was found for any individual quality criterion (listed in Table 3 with the results from the statistical analysis). The RCT manuscripts identified by the CIG trials registry were also examined in this manner. Analyzing each quality criterion individually as a function of the year-of-publication of the manuscripts in that sample showed that two criteria ("prevention of the movement of patients between groups after allocation, and the use of intention-to-treat analysis"; "the assessment of the distribution of patient characteristics and prognostic factors between groups") and nearly another ("completeness of follow-up") were reported in the manuscripts with increasing frequency over time (Table 4).
Table 3 Regression analysis of individual quality criteria versus year-of-publication of the manuscripts identified by the PubMed MEDLINE search This table lists the results of the regression analyses comparing year-of-publication against the individual quality criteria.
quality criterion regression result
(W = Wald stat) Cox & Snell R2 regression line
the assessment of the distribution of patient characteristics and prognostic factors between groups W = 0.96, P = 0.33 0.01 y = -0.075x + 9.45
prevention of the movement of patients between groups after allocation, and the use of intention-to-treat analysis W = 1.63, P = 0.20 0.02 y = 0.088x - 10.30
the blinding of the patients to the treatment they received W = 0.30, P = 0.58 0.003 y = 0.022x - 0.80
the blinding of the health care providers to the treatments received by the patients W = 2.00, P = 0.16 0.02 y = 0.055x - 5.71
the blinding of the outcome observer to the treatment received by the patient W = 0.01, P = 0.93 0.000 y = 0.003x + 0.57
adequacy of follow-up W = 0.03, P = 0.86 0.000 y = -0.006x + 1.18
allocation concealment W = 1.06, P = 0.30 0.011 y = 0.39x - 78.4
Table 4 Regression analysis of individual quality criteria versus year-of-publication of the manuscripts identified by the CIG Trials Registry This table lists the results of the regression analyses comparing year-of-publication against the individual quality criteria.
quality criterion regression result
(W = Wald stat) Cox & Snell R2 regression line
the assessment of the distribution of patient characteristics and prognostic factors between groups W = 5.53, P = 0.02 0.03 y = 0.072x - 4.71
prevention of the movement of patients between groups after allocation, and the use of intention-to-treat analysis W = 4.74, P = 0.03 0.03 y = 0.054x - 13.25
the blinding of the patients to the treatment they received W = 0.04, P = 0.84 0.000 y = 0.006x + 0.77
the blinding of the health care providers to the treatments received by the patients W = 0.16, P = 0.69 0.001 y = -0.010x + 0.32
the blinding of the outcome observer to the treatment received by the patient W = 0.27, P = 0.60 0.002 y = 0.012x - 0.57
adequacy of follow-up W = 3.25, P = 0.07 0.02 y = 0.043x - 3.25
allocation concealment W = 0.23, P = 0.88 0.000 Y = 0.004x - 7.64
Discussion
Many of reviews have attempted to measure the change in RCT quality over time in a field of medical science. It occurred to us that such an analysis could be influenced by the search technique that was used to identify the RCT manuscripts. Based on this concern we hypothesized that two samples of RCT manuscripts taken from the same field of medical science by different search techniques could provide different measures of the change in quality over time. We empirically tested this hypothesis, and by doing so demonstrated that the conclusions made about the change in quality of RCT manuscripts from a representative field of medical science could be significantly influenced by the search technique that was used to sample the field. This demonstration may then bring into question the validity of previous reviews that have claimed to define the change in quality of RCTs over time in various fields of medical science.
In our study, the samples of RCT manuscripts provided by the PubMed MEDLINE search and the CIG trials registry had less overlap than we would have expected considering that both search techniques involved the MEDLINE database. In particular, the CIG trials registry identified only about 60% of the RCT manuscripts found by the PubMed MEDLINE search despite involving its own search of the MEDLINE database. This observation may ultimately relate to the use of different search terms to identify manuscripts from the MEDLINE database, and to the use of different search engines of the MEDLINE database (i.e., PubMed, versus SilverPlatter in the CIG trials registry) that themselves can affect the identification of manuscripts from the common database. Whatever may be the cause for the discrepancy between our two samples, it may undermine any claim that a search technique necessarily produces a more representative sample from a field of medical science simply because it identifies a greater number of RCT manuscripts.
The two search techniques otherwise differ in several ways. For example, the PubMed MEDLINE search was designed so as to exclude any manuscripts published in a non-English language. This would approximate the typical literature search performed by many researchers in North America, and accordingly all the manuscripts identified by the PubMed MEDLINE search were readily available in local university libraries. Conversely, the CIG trials registry tended to include more references from the non-English language literature (n = 27 manuscripts after the screening process). This inclusiveness of the CIG trials registry seemed to account for the 15 irretrievable manuscripts listed by the CIG trials registry. It is reasonable to state that the non-English language literature is part of medical science and that it should not be discounted solely because of its country-of-origin or the language in which it was written. As another difference, the CIG trials registry involved hand-searches of journals and lists of references provided by authorities in the field of brain injury, which are not features of the PubMed MEDLINE search and which may predispose the CIG trials registry search technique toward recovering more recently-published manuscripts. Recently published manuscripts may be of higher quality, thereby biasing the longitudinal measurement of quality in the RCT manuscript sample provided by the CIG trials registry. Alternatively, such extra efforts would be considered by most to improve on the yield of a search technique by including journals and books that are not indexed by computerized databases.
Arguments can be made that either of the search techniques provided a more representative sample of RCT manuscripts from the field of brain injury, but which search technique is superior – if either can be said to be so – is not a concern of the current study. It was solely our intention to compare the findings provided by two commonly-used search techniques to demonstrate that the search technique can in fact influence the measurement of the change in RCT quality over time. We acknowledge a priori that neither of the search techniques we used necessarily sampled RCTs from the field of brain injury in a representative manner. Furthermore, we do not claim to have accurately measured how the quality of RCT manuscripts is changing over time in the field of brain injury with either one of them. This is because we are not confident that either search technique provided a representative sampling of the field of brain injury (i.e., that either search technique had access to all the relevant manuscripts). With regards to the field of brain injury, it is clear from our observations that neither the PubMed MEDLINE search nor the CIG Trials Registry can claim to be complete, as each search technique failed to identify a large number of RCT manuscripts that were found by the other search technique. In other fields of medical science there may be specialized databases or registries that claim to identify all relevant manuscripts (e.g., the Renal Registry in the field of nephrology [F.P. Schena, personal communication]). The authors of the current communication cannot understand how such a claim can be made or proven, since demonstrating the completeness of a search strategy would require proving that there are no relevant manuscripts that it does not identify. Ultimately, proving that something does not exist is scientifically impossible. Alternatively, it might be claimed that a search strategy identifies the majority of relevant manuscripts. This, of course, depends upon (1) the definition of a majority and (2) the assumption that the finding of even a few relevant manuscripts not identified by the search strategy means there are no other such manuscripts outside of the reach of that search strategy. Again, such a claim would depend upon the assumption that the inability to find further relevant manuscripts indicates that no further relevant manuscripts exist; as described above, this is a scientific impossibility. Rather than claiming perfection or near-perfection, it would seem to us to be more appropriate and accurate to claim that a given search strategy has exhausted all options for identifying relevant manuscripts.
What, then, should be done to avoid a biasing influence related to the search technique during reviews of RCT quality over time? The simplest means of avoiding a such an influence would have apparently been to use multiple search techniques in order to better sample the parent population of RCT manuscripts in a field of medical science. In general, including multiple techniques into a single 'comprehensive' search would be preferable to a simple search involving only a single technique, but even so this does not ensure that the combination is truly comprehensive (as we have demonstrated with the CIG Trials Registry). Essentially this was the goal of the CIG trials registry, but even it did not completely encompass the sample of manuscripts identified by the PubMed MEDLINE search despite involving a MEDLINE search of its own. Similarly, previous reviews of RCT quality have often involved secondary searches following an initial computerized search, but such efforts certainly cannot match the breadth and thoroughness of that from the Cochrane Collaboration. If such reviews of RCT quality are to judge entire fields of medical science it would seem that the search techniques they employ must be shown to produce a representative sampling of the parent population of RCT manuscripts as well as a high yield from that parent population. We hope that the findings presented here bring more attention to this concern in future reviews of the change in RCT quality over time.
Conclusions
We demonstrated that measuring the change in quality over time of a sample of RCT manuscripts from the field of brain injury can be greatly affected by the search technique. This poorly recognized factor may make measurements of the change in RCT quality over time within a given field of medical science unreliable. The search strategy should be accurately reported in any study that attempts to follow trends in the quality of RCT manuscripts over time, and its limitation in sampling the RCT manuscripts from a field of medical science should be acknowledged and evaluated.
Competing Interests
The author(s) declare that they have no competing interests.
Authors' contributions
Both MKB and CY contributed equally to this study, and the exact nature of their contributions are described in the Methods section.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
The authors wish to express their gratitude to Dr. Babak Jahromi and Mrs. Margaret K. Borsody for their assistance in completing this work. We also wish to thank Dr. Michael Coco of Coco Communications, Inc. (Atlanta, Georgia), for his expert assistance in editing the manuscript.
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| 15698470 | PMC549561 | CC BY | 2021-01-04 16:32:52 | no | BMC Med Res Methodol. 2005 Feb 7; 5:7 | utf-8 | BMC Med Res Methodol | 2,005 | 10.1186/1471-2288-5-7 | oa_comm |
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BMC MicrobiolBMC Microbiology1471-2180BioMed Central London 1471-2180-5-51567347110.1186/1471-2180-5-5Research ArticleSurface expression, single-channel analysis and membrane topology of recombinant Chlamydia trachomatis Major Outer Membrane Protein Findlay Heather E [email protected] Heather [email protected] Richard H [email protected] Division of Biomedical Sciences, University of Edinburgh Medical School, George Square, Edinburgh EH8 9XD, UK2 Department of Biochemistry, School of Medical Sciences, University of Bristol, Bristol BS8 1TD, UK2005 26 1 2005 5 5 5 3 9 2004 26 1 2005 Copyright © 2005 Findlay 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
Chlamydial bacteria are obligate intracellular pathogens containing a cysteine-rich porin (Major Outer Membrane Protein, MOMP) with important structural and, in many species, immunity-related roles. MOMP forms extensive disulphide bonds with other chlamydial proteins, and is difficult to purify. Leaderless, recombinant MOMPs expressed in E. coli have yet to be refolded from inclusion bodies, and although leadered MOMP can be expressed in E. coli cells, it often misfolds and aggregates. We aimed to improve the surface expression of correctly folded MOMP to investigate the membrane topology of the protein, and provide a system to display native and modified MOMP epitopes.
Results
C. trachomatis MOMP was expressed on the surface of E. coli cells (including "porin knockout" cells) after optimizing leader sequence, temperature and medium composition, and the protein was functionally reconstituted at the single-channel level to confirm it was folded correctly. Recombinant MOMP formed oligomers even in the absence of its 9 cysteine residues, and the unmodified protein also formed inter- and intra-subunit disulphide bonds. Its topology was modeled as a (16-stranded) β-barrel, and specific structural predictions were tested by removing each of the four putative surface-exposed loops corresponding to highly immunogenic variable sequence (VS) domains, and one or two of the putative transmembrane strands. The deletion of predicted external loops did not prevent folding and incorporation of MOMP into the E. coli outer membrane, in contrast to the removal of predicted transmembrane strands.
Conclusions
C. trachomatis MOMP was functionally expressed on the surface of E. coli cells under newly optimized conditions. Tests of its predicted membrane topology were consistent with β-barrel oligomers in which major immunogenic regions are displayed on surface-exposed loops. Functional surface expression, coupled with improved understanding of MOMP's topology, could provide modified antigens for immunological studies and vaccination, including live subunit vaccines, and might be useful to co-express MOMP with other chlamydial membrane proteins.
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Background
Every Gram-negative bacterium in the order Chlamydiales is an obligate intracellular pathogen [1]. The organisms are dimorphic, and alternate between free-living, infectious "elementary bodies" (EBs) endocytosed by mucosal cells into vesicular inclusions, and metabolically active, intracellular "reticulate bodies" (RBs). RBs replicate and redifferentiate into EBs before being released to infect neighboring cells, and infections (including Chlamydia muridarum pneumonitis, an important animal model) are often complicated by a damaging immune response and chronic inflammation. Human genital C. trachomatis infections are associated with ectopic pregnancy and infertility, and serovars that target ocular membranes can lead to trachoma and blindness. Chlamydophila pneumoniae (Ch. pneumoniae) causes pneumonia in the elderly, and colonization of the placenta by Ch. abortus causes abortion in ewes (and, occasionally, in women).
Uniquely among bacteria, the chlamydial outer membrane (OM) is reinforced by a network of disulphide bonds [2]. Treatment of EBs with Sarkosyl produces "chlamydial OM complexes" (COMCs) [3] containing three relatively detergent-resistant, cysteine-rich proteins: the Major Outer Membrane Protein (MOMP), encoded by ompA, and OmcB and OmcA, encoded by omp2 and omp3, respectively. MOMP (~40 kDa) is expressed in both EBs and RBs [4]. It contains extensive β-sheet secondary structure and forms large pores [5,6], similar to β-barrel porins found in other outer bacterial membranes (e.g. E. coli OmpF). The MOMPs encoded by different C. trachomatis serovars share five well-conserved regions and four "variable sequence" (VS) domains [7,8]. C. trachomatis VS domains, and homologous regions in MOMPs from other species, could correspond to cysteine-rich surface-exposed loops in a porin β-barrel, and EB MOMP is oxidised and highly cross-linked, making the OM very stable. RBs in contrast are osmotically active with reduced, mainly monomeric, MOMP [9]. MOMP's pore-forming ability is enhanced by reduction [5], compatible with a link between reversible disulphide bond formation and the developmental stage of the bacteria. Supporting this idea, DTT-reduced EBs tend to resemble RBs [5], and native MOMP is monomeric when solubilised in SDS under reducing conditions, but forms monomers, dimers, trimers, tetramers and even larger complexes [e.g. [6,10,11]] under oxidising conditions.
C. trachomatis MOMP is highly immunogenic. Antibodies to the protein neutralised EB infectivity [12], and triggered approaches to generate MOMP-based vaccines [e.g. [13,14]]. However, as implied earlier, the immunopathology of chlamydial infections is complicated [15], with TH1 type immune responses as well as specific antibodies (TH2 responses). MOMP is not equally immunogenic in all spp., and it also stimulates T-cell division, including CD4+ and CD8+ T-cells, enhancing IFN-γ secretion [16]. C. trachomatis MOMP will probably need to be modified to form a safe and effective subunit vaccine, emphasizing the importance of understanding its structure in more detail.
OmcA and OmcB (the other main components of the COMC) are present as approximately 1 OmcB:2 OmcA:5 MOMP [17]. Ch. psittaci (formerly known as C. psittaci) OmcA is a 9 kDa lipid-anchored protein with 14 cysteine residues [18], while OmcB (60 kDa) contains 37 cysteines [19]. The Omc proteins may not be integral membrane proteins. Reduced OmcB is water-soluble, and although OmcA remains membrane-associated, it can be readily solubilised when reduced [20], and neither protein was detected on the surface of intact EBs by immunogold labeling [21]. Regardless of their membrane association, OmcB appears to be extensively cross-linked in the periplasm of EBs, forming disulphide bonds with both MOMP and OmcA. Appropriately, both Omc proteins are expressed late in the developmental cycle (from a bicistronic operon), as RBs are reorganized into EBs [22], consistent with the idea that RB MOMP is functional and exchanges nutrients and other factors (possibly including signaling molecules) with the host cell. Extensive disulphide cross-linking in EBs may inactivate the porin, and prevent expansion of the growing bacterial cell wall.
Although MOMP is of major biological and clinical interest, chlamydia only grow in eukaryotic cells, and MOMP is difficult to isolate and purify because it can aggregate when oxidized, or interact with other cysteine-rich chlamydial proteins. As a result, many groups have expressed recombinant MOMP in E. coli using full-length ompA genes that include the signal sequence to target the translated protein to the OM. Although leadered MOMP can be expressed in a heterologous system [23-25], this approach has proved to be highly problematic, because the protein tends to misfold and aggregate. Koehler et al. [26] demonstrated surface-exposure, but with a dramatic reduction in cell viability, including OM disruption and substantial cell lysis (i.e. unincorporated, periplasmic MOMP may have been exposed). Jones et al. [27] co-reconstituted recombinant MOMP with endogenous E. coli porins, and showed altered solute permeabilities in liposome-swelling assays. Although attributed to novel porin activity, this could have reflected modification of endogenous porins. Wyllie et al. [28] pursued an alternative approach with truncated versions of Ch. abortus and Ch. pneumoniae MOMP, and obtained small amounts of folded proteins without prior denaturation and refolding, sufficient for incorporation into planar bilayers and single-channel recording. Other expression systems, pioneered because of their potential for vaccine delivery, include mammalian COS cells [29] and Vibrio cholerae [30].
PorB (37 K), a second putative porin, is also surface-exposed in chlamydia [31]. Recombinant PorB specifically transported dicarboxylates in liposome-swelling assays [32], although. it was used with a C-terminal His tag. The terminal residues of porins normally meet to complete a transmembrane β-strand, and may even be linked by a salt bridge. Being integral to the protein fold, additional terminal residues might affect the conformation and, therefore, the specific function of a porin. We expressed PorB as well as MOMP to help determine the factors affecting chlamydial porin expression, but because of these theoretical concerns concerning porin folding and function, we avoided tagged proteins in the present study, and built on previous work with leadered constructs.
We developed improved conditions for the surface expression of MOMP in E. coli cells, and demonstrated unambiguously by single-channel recording that recombinant C. trachomatis MOMP folded and formed a functional protein in the absence of many endogenous porins. We showed that MOMP can insert into the outer membrane of E. coli cells and form SDS-sensitive oligomers in the absence of cysteine residues, and generated a "working model" of the topology of MOMP to provide structural hypotheses that could be tested by engineering the recombinant protein.
Results
Optimised MOMP expression in E. coli cells
Our first objective was to obtain properly folded recombinant chlamydial porins in the outer membranes of E. coli cells. Building on previous work (e.g. [26]), BL21(DE3) cells were transformed with pET-ompA or pET-porB constructs, and expression was induced by 1 mM IPTG at 37°C after growth to an OD600 of 0.6. Compared to the expression of non-leadered proteins (which accumulate in cytoplasmic inclusion bodies), cells expressing leadered porins must transport the immature full-length porin across the inner membrane, cleave the leader sequence in the periplasmic space, and fold and insert the mature protein into the OM. Expression of mature, leaderless C. trachomatis MOMP did not inhibit growth compared to non-transformed cells, in contrast to substantial inhibition with full length MOMP (Fig. 1A). To investigate whether different leader sequences could improve processing, C. trachomatis MOMP was expressed with the OmpT leader rather than its native leader. Initial growth rates were comparable to those shown by non-transformed cells, and similar to cells expressing mature MOMP (i.e. MOMP without a leader sequence), although the cultures again showed a reduced final cell density.
We next investigated the expression of MOMPs from other chlamydial spp. to determine whether the observed effects were specific to C. trachomatis MOMP, and we also expressed C. muridarum PorB to exclude a universal problem with the expression of all putative chlamydial porins in E. coli. The constructs had different effects on cell viability (Fig. 1B). Bacteria expressing C. muridarum MOMP grew more slowly than bacteria expressing C. trachomatis MOMP, although the bacteria continued to grow slowly throughout the entire period of induction. The growth of bacteria expressing Ch. abortus MOMP or C. muridarum PorB was markedly reduced, and the density decreased after 30 min. The "recovery" at later stages reflected multiplication of non-expressing cells in the presence of β-lactamase released from dead or dying cells (growth ceased on fresh Ampicillin plates, data not shown). We then changed the leader sequences. The growth of cells expressing C. trachomatis MOMP and C. muridarum PorB was improved by replacing the native chlamydial leader with the E. coli OmpT leader, and the decrease in optical density occurred later in the induction and continued more slowly. In contrast, no significant improvement was seen when Ch. abortus MOMP was expressed with the OmpT leader (data not shown).
We also expressed full-length constructs in E. coli BL21(DE3)omp8 cells lacking expression of the endogenous porins LamB, OmpA, OmpC and OmpF [34]. Toxicity was more pronounced than in unmodified BL21 cells, and after establishing conditions for detergent extraction of recombinant MOMP (Additional Data File #1), expression conditions were further optimised to improve the yield of processed, recombinant protein. Native and OmpT-leadered C. trachomatis MOMP constructs were induced rapidly at 37°C with 1 mM IPTG or slowly at 16°C with 0.1 mM IPTG (Fig. 2). At 37°C both versions of MOMP were expressed, and by 4 hours about half the protein was processed, as shown by the doublet band of OM-associated MOMP with and without its signal sequence (Fig. 2). The ~2 kDa difference between the cleaved and non-cleaved protein bands (38 kDa and 40 kDa, respectively), is similar to the difference seen when leadered versions of E. coli OmpF are expressed). There was a slight decrease in total protein when MOMP was expressed with its native leader at 16°C, but the proportion of processed protein was unchanged. Although protein decreased following slow induction of MOMP containing the OmpT leader, most of the protein was processed. Based on these observations, slow induction of native-leadered MOMP was carried out in different growth media for prolonged periods. After growing for 6 hours, cultures in LB medium plateaued at an OD600 ~0.85, after which the cells began to lyse. In contrast, cells cultured in more supportive SOC medium continued to grow steadily, and began to plateau about 12 hours after induction (Additional Data File #2).
Processing and surface expression of mutagenised and engineered MOMPs
Given the known difficulties associated with protein misfolding and aggregation (e.g. [23-26]), a particular problem for chlamydial MOMPs compared to other bacterial porins, our next objective was to determine whether MOMP was actually inserted into the E. coli outer membrane. Although recombinant MOMP was associated with the OM fraction following subcellular fractionation, the observation that its leader sequence was not always cleaved (Fig. 2) suggested that some leadered protein co-fractionated with OMs, possibly as a peripheral membrane protein. This raised the possibility that even cleaved recombinant proteins might not be fully integrated into the OM. To determine whether processed MOMP was actually inserted into (and across) the OM, we carried out whole cell immunoblots to probe for the presence of MOMP epitopes on the surface of intact E. coli BL21 cells. Because of the importance of reduced temperature (Fig. 2), we carried out inductions for whole cell immunoblotting at 37°C, 16°C and an intermediate temperature of 25°C. MOMP was incorporated into the OM at both 25°C and 16°C, when induced in the presence of either 1 mM or 0.1 mM IPTG, respectively. Expression and processing were more rapid at 25°C, and because the presence of some unprocessed protein was irrelevant in this experiment, we induced the cells at 25°C for 2 hrs. Non-transformed BL21 cells, or cells transformed with an empty plasmid, and BL21 cells transformed with constructs encoding mature, leaderless C. trachomatis MOMP, or with OmpT-leadered MOMP and native leadered-MOMP, were applied to a nitrocellulose membrane (avoiding methanol-activated PVDF, and the risk of OM permeabilisation and exposure of periplasmic MOMP), and probed with anti-MOMP pAb (Fig. 3A).
The absence of a signal from control cells and cells expressing MOMP in its non-leadered, mature form confirmed the incubation and blotting conditions did not cause cell lysis and expose unincorporated protein. Both OmpT- and native-leadered MOMP were detected on the cell surface (Fig. 3A, whole cell blots), confirming they were inserted into the OM. Unfortunately, BL21omp8 cells were too fragile to survive the same blotting procedure. SDS-PAGE analysis of OG-solubilised OM fractions (Fig. 3A, middle panel) confirmed MOMP expression and processing, although parallel immunoblots (Fig. 3A, lower panel) showed faint additional bands of ~40 kDa for the leadered proteins, indicating that processing was incomplete, as expected. Parallel immunofluorescence data (Fig. 3B) showed MOMP was confined to cytoplasmic inclusion bodies containing the mature protein when the appropriate cells were fixed and permeabilised before staining (Fig. 3B, panel b). As expected, staining was absent when the antibody was applied before permeabilisation (data not shown). However, OM staining was seen for MOMP expressed with both the OmpT leader and the native leader (panels c and e, respectively). When these cells were permeabilised before staining (panels d and f, respectively), immunoreactive protein was also noted internally, as expected (e.g. Fig. 3A, lower panel), although reduced or absent in BL21omp8 cells induced for 12 hrs at 16°C in more supportive SOC medium (Fig. 3B, inset in panel d).
We concluded that MOMP constructs encoding appropriate leaders could be expressed in E. coli, cross the inner membrane, and be processed in the periplasm. Furthermore, under modified incubation and induction conditions (especially at reduced temperatures, and in the relatively supportive medium SOC), MOMP could be folded and incorporated into the outer membrane.
Membrane topology of MOMP
Having confirmed that C. trachomatis MOMP was inserted into the OM of E. coli cells, we set out to investigate how the protein was organized in the membrane. While noting that predictive algorithms must always be deployed with care, and with reference to established findings for a given protein, we first analyzed MOMP's primary sequence for membrane crossings using a neural network trained with OM proteins of known structure [36]. The analysis (Fig. 4A) showed 16 membrane crossings. As expected, the VS domains of C. trachomatis MOMP generally corresponded to regions of the protein predicted to be extracellular.
We then reanalyzed the sequence using two β-strand prediction programs (Fig. 4B). The combined analysis revealed a total of 16 strands, corresponding numerically to the initial "membrane crossing" prediction (which does not on its own appear to be sufficient to identify the specific extramembrane domains). We discarded the strand coinciding with VS1 in B2TMPRED (see Methods) because VS domains are likely to be extracellular loops, and inserted an extra strand between G210 and S218 to bring the chain back across the membrane, so that all 4 VS domains remained external. Minor adjustments were made to accommodate known constraints on β-strand organization and porin structures [39,40]. The final working model (Fig. 5) provided testable hypotheses concerning the pattern of transmembrane folding. All the cysteine residues were predicted to be accessible for inter- or intrasubunit disulphide bond formation or cross-linking with other proteins. Most were predicted to be external, but two were periplasmic. Although one thiol group was in a predicted transmembrane domain, it faced the central water-filled pore rather than the lipid bilayer, where it could potentially interact with a cysteine thiol on a pore-confined loop.
We designed four C. trachomatis MOMP constructs (with intact cysteines and native leaders, to correspond exactly in these respects to the "wild-type" protein) in which substantial regions of VS domains 1, 2, 3 or 4 (shown in Fig. 6A) were deleted, to test the prediction that these domains are surface-exposed loops that can be shortened without compromising the main β-barrel fold and membrane insertion. The region removed from VS1 was G63 to Y87; from VS2, E141 to F156; from VS3, Y220 to G238; and from VS4, D278 to T318. Our strategy (see Methods) resulted in some mutations. Most were conservative changes (M62T in VS1, T239V in VS3 and A277V in VS4), apart from G219D in VS3. However, our topology prediction placed this residue in an external loop, where the additional charge was unlikely to be significant. We also generated another pair of constructs with deletions of either one or two of the predicted β-strands between VS domain 1 and VS domain 2 (summarized in Fig. 6B–C), in an attempt to disrupt the formation of OM-inserting β-barrels. These constructs were designated: Δβ5, with removal of E95 to F111 (with no residue changes) and Δβ5,6, with removal of F97 to A129 (with 2 changes, E95D and M96V).
Before expressing the cDNAs encoding putative loop or strand deletions, we re-examined the expression and OM insertion of full-length C. trachomatis MOMP using a construct in which all 9 cysteine residues (Fig. 4A, circles; Fig. 5, shaded residues) were replaced by alanine. The results (Fig. 7A) were similar to those for the non-mutagenised protein, showing that folding and membrane insertion could proceed without cysteine residues and without the controlled formation of disulphide bonds (as it may do in RBs). We then expressed each of the "loop-deleted" MOMP proteins in BL21 cells. All four were detected on the cell surface (Fig. 7B), demonstrating incorporation into the OM. In contrast, recombinant proteins expressed from constructs with putative β-stand deletions were not detectable on the surface of E. coli cells (Fig. 7). We considered the unusual possibility that all the epitopes in the "strand-deleted" proteins might have been unreactive in the E. coli membrane, due to masking or oligomerisation, but suspension of the cells in Tris (rather than phosphate) buffer (100 mM NaCl, 50 mM Tris-HCl, pH 7.4), or the addition of 2 mM EDTA, failed to "unmask" any immunoreactivity (Additional Data File #3).
MOMP forms oligomers in the E. coli outer membrane
Native MOMPs are difficult to purify free from other chlamydial proteins [6], precluding firm conclusions about native subunit structure, especially in the absence of protein (cysteine) oxidation. In preliminary investigations of the subunit organisation of recombinant MOMP, we noted that the recombinant protein did not form SDS-resistant oligomers (Additional Data File #4). However, unlike trimeric E. coli porins [40], oligomers of isolated MOMP, away from their normal membrane environment [6], may be unstable in the presence of SDS, so we subjected detergent-solubilised OM extracts to large-scale non-denaturing GE chromatography in milder detergents. For these and all subsequent experiments, MOMP was expressed in BL21omp8 cells with the OmpT leader (in SOC medium, at 16°C), to exclude heterooligomers containing endogenous E. coli porins, and minimize uninserted periplasmic protein, respectively.
We carried out GE chromatography in LDAO or Zwittergent 3–14 (having previously noted these to be cheaper but equally effective detergents to replace OG, Additional Data File #1), with excess (5 mM) DTT in the presence of MOMP cysteine residues (calibrating the column in the presence of detergent). Under these conditions, MOMP appeared to form oligomers containing 2–4 subunits, although some recombinant MOMP always formed higher-order oligomers (Fig. 8). Similar results were obtained after repeating each experiment at least twice. The apparent subunit stoichiometry of recombinant MOMP depended on the detergent, with putative dimers in LDAO, and trimers or tetramers in Zwittergent 3–14, depending on the presence or absence of cysteine residues, respectively. However, it should be emphasized that only the major quaternary species was identified in each case. The presence of oligomers in LDAO or Zwittergent 3–14 contrasted with the absence of SDS-resistant oligomers during SDS-PAGE, and oligomer formation even in the absence of cysteine residues argued against an essential role for disulphide bonds.
We also investigated the subunit organization of MOMP by covalent cross-linking following expression and insertion into BL21omp8 OMs, by removing DTT to allow in situ cysteine oxidation by dissolved oxygen. OM proteins were then incubated in SDS sample buffer with or without reducing agent at room temperature for 10 mins, separated by SDS-PAGE, and detected by Western blotting (Fig. 9). Reduced MOMP appeared as a single band of ~38 kDa, but non-reduced MOMP occupied several distinct bands. SDS-denatured, monomeric MOMP appeared as a band of ~38 kDa (labeled "denatured monomer"), corresponding to the reduced sample. However, monomeric MOMP also formed a band of ~35 kDa, running "ahead" of its normal apparent molecular mass, as previously seen with "folded" porin monomers [41,42]. Additional, fainter bands at higher molecular masses corresponded to dimers, tetramers and possible trimers (~80 kDa, ~160 kDa and ~120 kDa, respectively), similar to the findings following GE chromatography, with an upper band of aggregated protein that failed to enter the gel.
Surface-expressed MOMP is functional
Fully processed and correctly folded MOMP should function as a porin-like ion channel [6]. We tested this crucial prediction by expressing "wild-type" full-length recombinant C. trachomatis MOMP in BL21omp8 cells which express only a small subset of native E. coli porins, and not OmpF or OmpC [34]. We then functionally reconstituted solubilised BL21omp8 OM protein GE fractions in voltage-clamped planar lipid bilayers. Fractions containing "oligomeric" MOMP complexes gave rise to large-conductance, porin-like ion channels (Fig. 10). Similar channels were recorded irrespective of whether the detergent was LDAO or Zwittergent 3–14 (using fractions corresponding to 195 ml or 180 ml, respectively). The channels were voltage-dependent, closing at relatively high holding potentials (e.g. + or - 100 mV), but remaining open around 0 mV. The single-channel conductance in symmetric 500 mM KCl was 480 ± 19 pS (mean ± SEM, n = 6 independent experiments), and the reversal potential in 500 mM vs 50 mM KCl (cis vs trans) was -31 ± 1.5 mV (mean ± SEM, n = 9 independent experiments). This corresponded to a relative cation vs anion selectivity of 3.8 under these specific ionic conditions. Control preparations (detailed under Methods), including membrane proteins from control BL21omp8 cells subjected to the same experimental conditions, where OM proteins were solubilised and subjected to GE chromatography in exactly the same way, did not give rise to similar channel activity (6 experiments).
Discussion
Functional reconstitution of recombinant C. trachomatis MOMP at the single-channel (single molecule) level from cells lacking many endogenous porins provides very strong evidence that MOMP adopted its native fold when expressed in E. coli under suitable conditions. Although a leadered version of recombinant chlamydial MOMP was expressed and functionally analysed previously [27], membranes containing the protein were co-reconstituted with endogenous E. coli porins for liposome-swelling studies. Although MOMP may have contributed additional porin-like activity, functional modification of endogenous porins could not be ruled out.
Interestingly, the successful expression and processing of recombinant chlamydial porins in E. coli cells depends on the precise leader sequence, as well as on the specific protein. PorB is less "toxic" with its native leader, in contrast to MOMP, which is less "toxic" with the E. coli OmpT leader, and native-leadered C. muridarum MOMP is less deleterious to E. coli than Ch. abortus MOMP. Although a full investigation of the role of leader sequences could not be undertaken here, it is known that successful OM insertion, as well as prior transport across the inner membrane and processing, is also signal sequence-dependent. For example, a large proportion of E. coli LamB porins with signal sequence mutations remained "tethered" to the inner membrane (probably by their unprocessed signal sequence), even though the protein was also closely associated with the OM [43]. For C. trachomatis MOMP, use of the Omp-T leader and induction at 16°C (not induction at 37°C, as previously employed), in either "wild-type" cells or "porin knockout" cells in a supportive medium (SOC), provides improved processing and OM insertion, and there is also significant insertion at 25°C in "wild-type" E. coli.
The single-channel properties of C. trachomatis MOMP are consistent with previous data on bacterial [40] and putative chlamydial [6] porins. In particular, the channels show "bell-shaped" voltage-dependent gating and are mainly open around ~0 mV, with very high conductances (close to the saturating conductances predicted for a large water-filled pore) and poor ionic selectivity, showing only a slight preference (~4:1) for cations over anions (using a Nernst-Plank analysis because relatively wide, water-filled porin channels are probably electroneutral [35], and poorly-described by electrodiffusion theory). The channels often appeared in groups of three, as might be expected for a trimeric "triple-barrelled" porin (e.g. Fig. 10). However, unless the channels were randomly incorporated into the bilayer (which is difficult to demonstrate), these complexes may represent a selected sub-population.
Despite the lack of sequence similarity to known bacterial porins, a combination of different predictive approaches (none of which was entirely satisfactory in isolation), set in the context of elegant and pioneering work from many laboratories on the properties of VS domains, predicted that C. trachomatis MOMP, like putative porins in the intracellular pathogens Burkholderia thailandensis and B. pseudomallei [44], could be a 16-stranded β-barrel. Our working model pays due attention to the construction principles for β-barrels [39,40]. The N and C termini complete final strand 16, the periplasmic turns are short, and most external loops are long and include the immunogenic VS domains. The barrel surface in contact with the bilayer consists largely (though not exclusively) of hydrophobic side chains, and all 18 strand residues with charged side chains project into the pore to line the central water-filled central channel. 6 cysteines lie in extracellular loops, and 2 periplasmic cysteines lie on opposite sides of the barrel where they are unlikely to form an intrasubunit disulphide bond, although they could form intersubunit bonds, or bonds with other proteins. A single membrane thiol projects into the barrel pore, where it could be involved in disulphide bond formation if a loop (e.g. L1) were to fold into the barrel.
Our working model for the membrane topology of C. trachomatis MOMP differs in some significant respects from the recent prediction for C. muridarum MOMP [45] (which was based partly on hydrophobicity plots). Although both studies predict that MOMPs are 16-stranded β-barrels with an average strand length of ~8 residues, periplasmic thiols are absent from the C. muridarum prediction. This would preclude the significant interactions with OmcB and OmcA, described in the Background. We also assigned L2, 4, 6 and 7 as C. trachomatis VS domains, not L2, 3, 5 and 6, the homologous regions in C. muridarum MOMP. Experimental tests of the predicted membrane topology of C. trachomatis MOMP are consistent with our model, because individual VS domains can be substantially truncated without preventing incorporation of the protein into the bacterial OM. If MOMP is a β-barrel porin, as suggested, and VS domains are confined to specific extracellular loops, it is conceivable that MOMP can continue to fold into a β-barrel in the absence of one of these domains. On the other hand, the removal of β-strands would disrupt folding. Removal of a single strand, bringing periplasmic residues into direct contact with external residues, is predicted to be particularly destructive to the global fold. Removal of more than one strand might be better tolerated, provided the β-barrel can form with a significantly reduced diameter. In practice, it appears that C. trachomatis MOMP cannot accommodate either type of strand modification.
GE chromatography suggested that MOMP forms oligomers in the presence of Zwittergent or LDAO, and in line with these findings, in situ cysteine cross-linking of recombinant MOMP in E. coli OMs revealed oligomeric MOMP complexes, together with a species of folded or partially-folded MOMP monomers containing at least one intramolecular disulphide bond. This species contrasts with reduced, denatured MOMP monomers seen when chlamydial MOMP is solubilised directly from OMs (or native EBs [6]). However, the exact stoichiometry of MOMP oligomers in the E. coli OM remains uncertain because our size estimates for the oligomers, and thus their stoichiometries, may be too high because of uncorrected bound detergent. Also, it is clear that the stability of MOMP oligomers is detergent-dependent.
Native Ch. abortus MOMP forms SDS-resistant oligomers of ~100 K [6], unlike the SDS-unstable MOMP oligomers isolated from E. coli OMs. We speculate that this may be because native MOMP oligomers are stabilised by interactions with other chlamydial components (e.g. co-purified Omp90 [6]), and possibly also by disulphide bonds. Disulphide bond formation (whether transient or permanent) does not appear to be essential during protein folding and OM insertion, because a cysteine-free mutant can be fully processed (Fig. 7A) and can also form oligomers. Overall, our results show that the subunit stoichiometry of detergent-solubilised MOMPs expressed and processed in E. coli is detergent-dependent, that MOMP subunits can be cross-linked by disulphide bridges, and that folded monomers contain at least one intrasubunit disulphide bond (Fig. 8).
Conclusions
C. trachomatis MOMP, an immunodominant, cysteine-rich, chlamydial surface protein of crucial importance in the immune response to infection, is a major subunit vaccine target. However, unlike many other bacterial porins, it has been difficult to refold from inclusion bodies or to achieve and demonstrate functional surface expression. This study is the first to report unambiguous functional analysis, by single-channel recording, of recombinant chlamydial MOMP recovered from bacterial outer membranes. The modified expression system described in the present study provided a means to test specific hypotheses provided by a working model for the C. trachomatis protein. However, although our results are consistent with a working model of MOMP as a 16-stranded β-barrel, more mutations or other approaches are needed before a specific model can be accepted. The protein also formed oligomers, even in the complete absence of cysteine residues. The surface display of modified, functional MOMP in E. coli cells (potential vehicles for a live, subunit vaccine), together with a working topological model, could guide the removal of unwanted or harmful epitopes from engineered proteins, and it might also be possible to display external loops containing specific MOMP epitopes on other porin "scaffolds" in living cells. However, it is important to note that such approaches will be limited if essential disulphide bonds in the native chlamydial envelope, including bonds involving non-MOMP cysteines, stabilise the conformation of key immunogenic VS domains.
Methods
DNA manipulations
C. trachomatis ompA (corresponding to X62918, from the Da serovar) and Ch. abortus ompA were cloned without their leader sequences into the Nde-I/Nco-I sites of pET22b(+) (Novagen) after destroying an internal Nde-I site in C. trachomatis ompA by Quik-Change PCR mutagenesis (Stratagene). This did not alter the encoded protein. C. muridarum ompA and porB were amplified with and without their leaders from genomic DNA and cloned into the Nde-I/Bam-HI sites and Nde-I/Nco-I sites, respectively, of the same vector (C. muridarum ompA also required null mutation removal of an internal Nde-I site). The E. coli OmpT protease leader sequence or the native C. trachomatis MOMP leader sequence was added to the 5' end of the leaderless C. trachomatis and Ch. abortus inserts by sequential gene extension PCR using three overlapping primers. A 5' Nde-I site was again used to provide the starting methionine codon in the final full-length construct. Quik-Change PCR was also used to create pairs of unique internal restriction sites in native-leadered C. trachomatis ompA to permit the deletion of specific domains by plasmid restriction and religation [33]. These sites were: for VS1, Age-I; for VS2, Bcl-I; and for VS3, VS4 and the predicted β-strands, Aat-II. Successful deletions were confirmed by hemi-nested single-colony PCR (using Taq polymerase) to identify clones that could be amplified by gene-spanning primers but not by primers complementary to regions that had been removed. We also generated C. trachomatis MOMP expression constructs containing inserts in which all 9 cysteine residues (C26, C29, C33, C102, C115, C182, C184, C207 and C335) were replaced by alanine using Quik-Change PCR. Most of the modifications were carried out in a pSTBlue-I/NovaBlue system, and the fidelity of each insert was confirmed by automated DNA sequencing (MWG Biotech).
Protein expression and recovery
E. coli BL21(DE3) or BL21(DE3)omp8 [34] cells were harvested from cultures of LB (Luria-Bertani) medium (10 g/l Bacto tryptone, 5 g/l yeast extract, 10 g/l NaCl, pH 7.0) or SOC medium (20 g/l Bacto tryptone, 5 g/l yeast extract, 0.5 g/l NaCl, 20 mM glucose, pH 7.0) by centrifugation at 6,000 × g for 5 mins after inductions as described in the Results section, and washed in 50 ml phosphate buffered saline (PBS). The cell pellet was resuspended in 5 ml TEN buffer (50 mM Tris-HCl, pH 8.0, 10 mM EDTA, 100 mM NaCl) containing 1 mg lysozyme and incubated for 30 min. at room temperature. Following sonication (6 × 15 s, 6 μm amplitude, Sanyo Soniprep 150 sonicator) the cell lysate was incubated with 20 U/ml Benzonase (Novagen) for 15 min at room temperature. OM fragments were pelleted by centrifugation at 15,000 × g for 10 min, and washed twice in 20 ml TEN buffer. Membrane proteins were solubilised by resuspending the pellet in 6 ml solubilisation buffer containing 50 mM Tris-HCl, pH 8.0, 1 mM EDTA, 50 mM NaCl and 10 mM DTT with either 1% (w/v) octyl glucoside (OG, Anatrace), 1% (w/v) lauryl (dodecyl) dimethylamine oxide (L(D)DAO, Anatrace) or 1% (w/v) Zwittergent 3–14 (Anzergent 3–14, Anatrace), and incubating at 37°C for 1 hour. The solution was clarified by ultracentrifugation (Beckman TLA-100) for 20 mins at 100,000 rpm. Protein concentrations were determined after TCA precipitation.
SDS-PAGE and Western blotting
Unless otherwise indicated, SDS-PAGE was carried out under reducing conditions using 10–12% (w/v) gels. Molecular masses were estimated from plots of relative mobility vs the logarithm of the molecular mass of Precision Plus unstained protein markers (BioRad). For Western blotting, proteins were electrophoretically transferred to PVDF membranes under conditions compatible with the transfer of high-MW proteins including native MOMP oligomers [6]. The membranes were blocked in 5% (w/v) non-fat milk in PBS-T (0.005% (v/v) Tween-20 in PBS) then incubated in 1:5000 goat anti-C. trachomatis MOMP antibody (Fitzgerald International) for 1 hour at room temperature. Following 2 × 30 sec and 3 × 5 min washes in PBS-T, membranes were incubated in 1:10,000 HRP-conjugated anti-goat/sheep antibody (Sigma) for 1 hr at room temperature. After washing, immunoreactive proteins were detected by ECL.
Whole cell immunoblotting and immunofluorescence
10 ml of LB medium was seeded 1:100 with cultures grown to saturation overnight, and incubated until the OD reached 0.6. The cells were pelleted by centrifugation (6,000 g × 10 mins) and resuspended in fresh medium. Following incubation at the selected temperature for 10 mins, 0.1–1 mM IPTG was added and incubation was continued for another 2–16 hrs. Intact cells were harvested by gentle centrifugation (4,500 g × 5 mins) and washed in 1 ml PBS. The pellets were resuspended in 200 μl PBS, and 10 μl was applied to a nitrocellulose membrane and allowed to dry. The membrane was blocked and probed with anti-C. trachomatis MOMP polyclonal antibody as described above. Immunofluorescence was carried out as described previously [26], with fixation and permeabilisation either before or after immunostaining, using 1:200 dilutions of the above primary antibody and fluorescein-conjugated anti-goat secondary antibody (Sigma). The cells were then observed by bright field, phase contrast and fluorescence microscopy using a Leica TCS-NT confocal microscope.
Gel-exclusion chromatography
Solublised OM proteins were separated by GE chromatography using a high resolution 26/60 HiLoad Superdex 200 prep grade column (Amersham Pharmacia Biotech) freshly equilibrated in 50 mM Tris-HCl (pH 8.0), 1 mM EDTA, 50 mM NaCl and 5 mM DTT (omitting the latter for the cysteine-less MOMP mutant). The buffer also contained either 0.05% (w/v) LDAO or 0.05% (w/v) Zwittergent 3–14. 2 ml aliquots of solubilised OM proteins (containing up to 10 mg protein, solubilised as described earlier under protein expression) were loaded, and the column was eluted with the same buffer for 800 min. at a flow rate of 0.5 ml/min. 5 ml fractions were collected and 10 μl of each protein-containing fraction was deposited onto a pre-prepared PVDF membrane and probed for MOMP as described earlier under Western blotting. The column (Vt 320 ml) was calibrated in the presence of detergent using standard proteins. V0 (the void volume) was 115 ml, and Kav was calculated as (Ve - V0)/(Vt - V0), where Ve is the elution volume.
Bilayer reconstitution and single-channel analysis
Planar bilayers were cast from diphytanoyl phosphatidylcholine (Avanti) between two 0.5 ml chambers containing 50 mM KCl, 20 mM Tris-HCl (pH 8.0) and 1 mM DTT, designated cis and trans [6]. The cis chamber was voltage clamped with respect to the trans chamber using an Axon 200B amplifier or a Biologic RK300 amplifier. 1–5 μl aliquots of pre-diluted solubilised proteins (containing up to 10 ng protein and no more than 5 ng detergent) were added to the cis chamber, followed by aliquots of 5 M KCl to raise the salt concentration to 500 mM. Channel incorporation usually occurred within 30 min, accelerated by switching the holding potential between +/- 60 mV. Experimental protocols were programmed and the digitised data were low-pass filtered (1 kHz, 8-pole Bessel-type response) and recorded using pClamp8 software (Axon Instruments), and analysed offline. The bilayer potential was slowly and repeatedly ramped between -100 mV and +100 mV (each sweep taking 32 s) in the presence of an asymmetric (500 mM vs 50 mM, cis vs trans) gradient of KCl, or with equimolar 500 mM or 1 M KCl. At least 3 voltage ramps were recorded and analysed for each experiment, and equilibrium recordings were obtained at defined holding potentials. Holding potentials refer to the cis chamber, and upgoing deflections represent net movement of cations from cis to trans or of anions from trans to cis. Relative ionic permeabilities were determined from the equilibrium solution of the Nernst-Planck flux equations [35]. When the cation and anion fluxes are equal:
Er is the equilibrium (zero current, or reversal) potential in asymmetric KCl, and R, T and F have their usual significance. (the permeability ratio of K+ to Cl-) was calculated using appropriate activity coefficients (a) from standard tables. Control experiments were carried out using equivalent amounts of detergent and with equivalent amounts of solubilised OM proteins purified from non-transformed bacteria, selecting identical GE column fractions.
Membrane topology prediction
The number of membrane crossings was predicted using a neural network based-outer membrane protein topology prediction program trained with known porins [36]. We discounted a predicted membrane crossing very near the N-terminus that was only apparent after numerical rounding. β-strands were predicted independently by similar computational approaches using B2TMPRED [37] and TMBETA [38], respectively. The three predictions were combined and adjusted manually, taking account of the accessibility of the VS domains of C. trachomatis MOMP and the known characteristics of antiparallel, amphipathic β-barrel strands in porins.
Authors' contributions
HEF and HM carried out most of the experiments. HEF analysed and organised the data, and drafted the first version of the manuscript. RHA conceived the overall project, provided experimental guidance, carried out some of the experiments, and redrafted the manuscript. All the authors read and approved the final manuscript.
Supplementary Material
Additional File 1
Detergent extraction of recombinant MOMP. Immunoblot with ECL detection following SDS-PAGE of OM proteins (10 μg per lane) from BL21 cells expressing OmpT-leadered C. trachomatis MOMP, induced for 2 hrs at 37°C. OM proteins (see Methods) were solubilised in 1% (w/v or v/v) octylglucoside, Triton X-100, Zwittergent 3–14 or LDAO, as indicated. NB & B are non-boiled and boiled samples, respectively. NE = non-expressing (control) cells.
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Additional File 2
Optimisation of C. trachomatis MOMP expression and processing in BL21omp8 cells. Growth curves of BL21omp8 cells expressing C. trachomatis MOMP with its native leader, in LB or SOC medium (means ± SEM, n = 4).
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Additional File 3
MOMP epitopes are not unmasked by Tris buffer or EDTA in whole cell immunoblots. Control BL21 cells and cells expressing "strand-deleted" constructs were suspended in 100 mM NaCl containing 50 mM Tris-HCl (pH 7.4) with or without 2 mM EDTA, applied to nitrocellulose membranes, and probed with anti-C. trachomatis MOMP polyclonal antibody.
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Additional File 4
Recombinant MOMP does not form SDS-resistant oligomers. SDS-PAGE and immunoblot analysis of C. trachomatis MOMP expressed with its native leader in BL21omp8 cells at 16°C (induced for 12 hrs in the presence of 0.1 mM IPTG). Lanes 1 & 2 contain 10 μg non-boiled and boiled OM proteins, respectively, solubilised in 1% (w/v) OG. Note successful transfer of high-MW proteins.
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Acknowledgements
We thank Tilman Schirmer for BL21omp8 cells. This work was supported in part by the Wellcome Trust, and by a University of Edinburgh Faculty of Medicine Scholarship to HEF.
Figures and Tables
Figure 1 Effects of leader sequences on the growth of E. coli BL21 cells expressing chlamydial porins. A. Moderate inhibition of bacterial (BL21) growth during expression of C. trachomatis MOMP containing native (nL-TR) and OmpT (oT-TR) leaders, contrasting with lack of significant inhibition during expression of mature, leaderless C. trachomatis MOMP (TR). B. Slight inhibition of bacterial growth during expression of C. muridarum MOMP with its native leader (nL-MU, compare to BL21 in A), contrasting with strong inhibition when Ch. abortus MOMP is expressed with its native leader (nL-AB). Cell growth is markedly reduced with both native-leadered PorB (nL-PB) and OmpT-leadered PorB (oT-PB). Note the "recovery" as non-resistant organisms overgrow in β-lactamase-containing cultures (see text). Measurements are means ± SEM (n = 4 independent experiments).
Figure 2 Expression and processing of C. trachomatis MOMP in BL21omp8 cells. Coomassie-stained 12% (w/v) SDS-PAGE of OM proteins extracted using 1%(w/v) OG (10 μg protein per lane) from cells induced for 4 hrs in LB medium, showing dependence of C. trachomatis MOMP expression and processing on temperature and leader sequence. Cells incubated at 16°C and 37°C were induced with 0.1 mM IPTG and 1 mM IPTG, respectively. omp8: non-transformed omp8 cells; oT-TR: cells expressing C. trachomatis MOMP with the OmpT leader; nL-TR: cells expressing C. trachomatis MOMP with its native leader.
Figure 3 Insertion of MOMP into the E. coli outer membrane. A. Recombinant C. trachomatis MOMP was expressed for 2 hrs at 25°C from constructs encoding either no leader (mature), the OmpT (oT) leader, or the native (n) leader, and immunodetected on the surface of intact BL21 cells (upper panel) using a specific anti-MOMP polyclonal Ab. Non-expressing BL21 cells (BL) show no signal, and mature, leaderless MOMP does not reach the cell surface. The middle and lower panels show, respectively, SDS-PAGE and immunoblot analyses of the corresponding recombinant proteins under these conditions (prepared as in Fig. 2). Note the presence of some unprocessed protein, revealed by the immunoblots of leadered protein expression. Representative of 3 similar experiments. B. Immunofluorescence confocal microscopy (panels b–f), with examples of unstained cells (panel a); cells permeabilised and stained after expressing mature, non-leadered MOMP (panel b); cells expressing OmpT-leadered MOMP stained before (panel c) and after permeabilisation (panel d, with inset permeabilised omp8 cell after 12 hrs induction at 16°C); cells expressing native-leadered MOMP under corresponding conditions (panels e and f, respectively). The scale bar (panel c) is 3 μm, and the arrow points out membrane staining. Representative of 3 similar experiments.
Figure 4 Membrane topology and secondary structure predictions for C. trachomatis MOMP. A. "Membrane crossing" prediction. Surface-exposed VS domains and cysteine residues are indicated by boxes and circles, respectively. A "complete membrane crossing" corresponds to a (contiguous) region of the plot that crosses both dotted lines in sequence, where the dotted lines represent the internal (periplasmic) and external borders of the outer membrane (in Z units). B. Two independent β-strand predictions, TMBETA [38] (upper line) and B2TMPRED [37] (below). The strands are boxed. The residue numbers refer to the mature (processed) protein.
Figure 5 Model of C. trachomatis MOMP. The MOMP β-barrel is broken apart at the putative N-C salt bridge in β-strand 16 to display the protein in a 2-D projection. Residues in the transmembrane strands are boxed, with a bold border to indicate side chains facing the bilayer. External loops (including constituent VS domains) are labeled, and cysteine residues are shaded.
Figure 6 Loop and strand deletion maps. A. Summary of individual loop deletions (filled residues) providing four C. trachomatis MOMP proteins deficient in VS domains 1, 2, 3 or 4 (designated ΔVS1-4, respectively). B. Deletion of predicted β-strand 5 and its associated internal loop, designated in the text as Δβ5. C Deletion of predicted β-strands 5 and 6 and their associated internal and external loops, designated in the text as Δβ5,6.
Figure 7 Effects of cysteine mutagenesis and loop and strand deletions on surface exposure of MOMP. A. Replacement of all 9 cysteine residues in C. trachomatis MOMP by alanine residues fails to prevent surface exposure. BL: non-expressing BL21 cells; mature: cells expressing mature MOMP without a leader sequence; oT-leader and n-leader, cells expressing MOMPs with ompT and native leaders, respectively. B. Removal of loops containing putative external VS domains (shown in Fig. 6A) fails to prevent surface exposure. TR: cells expressing mature MOMP; nL-TR: unmodified MOMP with its native leader. C. Removal of putative β-strand regions illustrated in Fig. 6B–C prevents surface exposure. Each result is representative of at least 3 similar experiments.
Figure 8 Gel-exclusion chromatography of solubilised MOMPs. A. GE analysis of C. trachomatis MOMP expressed in BL21omp8 cells with the OmpT leader, solubilised from an OM preparation in 1% (w/v) LDAO. Immuno-dotblots from successive 5 ml fractions between 100–220 ml (shown below the absorbance trace) reveal the appearance of high-molecular mass MOMP aggregates after the void volume, with a second immunoreactive peak at 195 ml (range 185–205 ml), corresponding to a molecular mass of 80 kDa (note inset column calibration trace, also in the presence of detergent). B. GE analysis of C. trachomatis MOMP expressed as in A but solubilised in 1% (w/v) Zwittergent 3–14. Oligomeric MOMP peaks at 180 ml (range 170–190 ml), corresponding to a molecular mass of 120 kDa. C. GE analysis of C. trachomatis MOMP in which all 9 cysteines were changed to alanine, expressed and solubilised as in B. Oligomeric MOMP peaks at 170 ml (range 160–190 ml), corresponding to a molecular mass of 160 kDa. Each trace is representative of at least 3 experiments.
Figure 9 Cysteine cross-linking of recombinant C. trachomatis MOMP. MOMP expressed in BL21omp8 cells with the OmpT leader was covalently cross-linked as described in the text and OM proteins were separated by reducing (RED) and non-reducing (OX) SDS-PAGE, followed by Western blotting using a specific anti-MOMP antibody. The positions of molecular mass markers are shown to the left, and the proposed identities of bands are shown to the right.
Figure 10 Single-channel analysis of recombinant C. trachomatis MOMP from BL21omp8 cells. A. Channel currents in response to two transmembrane voltage ramps (-100 mV to +100 mV), with 1 M KCl cis and trans. Up to 3 channels are open during ramp (a), and 2 of the channels close in succession at about +80 mV. In ramp (b), 1 channel is open at 0 mV, and 2 channels are open at +100 mV. B. Channel currents in the presence of 500 mM KCl cis and trans during two voltage ramps (as in A). Note the reduction in single-current amplitudes, and current reversal at 0 mV as in A. C. Currents during two voltage ramps in asymmetric KCl, 500 mM cis vs 50 mM trans. Note the shift in equilibrium potential (Er) from 0 mV to -30 mV (arrowed). Positive (upgoing) currents at 0 mV indicate a net flux of K+ cis to trans in the absence of an electrical driving force. D. Equilibrium currents in symmetric 500 mM KCl at a constant holding potential of +100 mV, showing brief single-channel closures and voltage-dependent inactivation of all 3 channels within 5 s.
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| 15673471 | PMC549562 | CC BY | 2021-01-04 16:03:39 | no | BMC Microbiol. 2005 Jan 26; 5:5 | utf-8 | BMC Microbiol | 2,005 | 10.1186/1471-2180-5-5 | oa_comm |
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BMC Pulm MedBMC Pulmonary Medicine1471-2466BioMed Central London 1471-2466-5-21568354010.1186/1471-2466-5-2Research ArticleThe Darlington and Northallerton Long Term Asthma Study: pulmonary function Connolly C Kevin [email protected] Robin J [email protected] The Department of Medicine, The Memorial Hospital, Darlington, DL3 6HX, UK2 Medical Statistics Unit, University of Edinburgh, Edinburgh, EH8 9AG, UK2005 31 1 2005 5 2 2 9 4 2004 31 1 2005 Copyright © 2005 Connolly and Prescott; licensee BioMed Central Ltd.2005Connolly and Prescott; 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 Darlington and Northallerton Asthma Study is an observational cohort study started in 1983. At that time little was published about long term outcome in asthma and the contribution of change in reversible disease or airway remodelling to any excess deterioration in function. The study design included regular review of overall and fixed function lung. We report the trends over fifteen years.
Methods
All asthmatics attending secondary care in 1983, 1988 and 1993 were recruited. Pulmonary function was recorded at attendance and potential best function estimated according to protocol. Rate of decline was calculated over each 5-year period and by linear regression analysis in those seen every time. The influence of potential explanatory variables on this decline was explored.
Results
1724 satisfactory 5-year measurements were obtained in 912 subjects and in 200 subjects on all occasions. Overall rate of decline (ml/year (95%CI)) calculated from 5-year periods was FEV1 ♂41.0 (34.7–47.3), ♀28.9 (23.2–34.6) and best FVC ♂63.1 (55.1–71.2)ml/year, ♀45.8 (40.0–51.6).The principal association was with age. A dominant cubic factor suggested fluctuations in the rate of change in middle life with less rapid decline in youth and more rapid decline in the elderly. Rapid decline was possibly associated with short duration. Treatment step did not predict rate of deterioration.
Conclusions
Function declined non-linearly and more rapidly than predicted from normal subjects. It reports for the first time a cubic relationship between age and pulmonary function. This should be taken into account when interpreting other articles reporting change in function over time.
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Background
It is recognised that the average decline in pulmonary function is greater in asthmatic subjects than in the general population [1,2]. This might be due to deterioration in potentially reversible disease [3] or the development of persistent obstruction following airway remodelling [4]. The published longitudinal studies do not differentiate between the two possible mechanisms. The Darlington and Northallerton Long Term Asthma Study was started in 1983 when little was known about long term outlook in asthmatics. Its objective was to observe mortality and decline in pulmonary function in asthmatics sufficiently severe to be referred for a hospital opinion. Decline in best achievable function is proposed as a measure of the airway remodelling. We accept that this decline might also be associated with Chronic Obstructive Pulmonary Disease (COPD). This label implies a physiological diagnosis, but the condition, like asthma, is better defined in terms of the underlying inflammation [5]. The diagnoses are therefore not necessarily mutually exclusive. Changes in best function are reported without prejudice to the underlying type of inflammation whether asthmatic, COPD, or both.
We wished this to be a population study as far as possible, so we invited all subjects satisfying a broad definition of asthma referred to a single-handed respiratory physician in a well defined geographical area to participate. Very few refused, but patients managed entirely in general practice were necessarily excluded. Best function, assessed according to a defined protocol [6] implicitly accepted in published guidelines [7], and potential explanatory variables were recorded prospectively at each visit. Smokers were not specifically excluded, but smoking habit was taken into account when the diagnosis was in doubt. Subjects with severe established fixed obstruction were excluded. Thus there was bias against the inclusion of asthmatic smokers destined to develop fixed obstruction rapidly, so we do not present any analyses confined to smokers. Although it was not until the mid 1980's that the use of prophylactic inhaled corticosteroids became standard practice, the majority of our subjects were maintained on inhaled steroids throughout the period, but the dose intensified [8]. Therefore only the change in dose could not account for any secular trends in decline in function. In this paper we explore the influence of demographic and other factors on change in function as observed over five year intervals.
Methods
These, described in detail elsewhere [8-11] are summarised and where directly relevant expanded below.
Subjects
All asthmatics currently attending secondary care clinics in the Darlington and Northallerton Health Districts were eligible for recruitment in 1983, 1988 and 1993, and reviewed in 1988, 1993 and 1998. Asthma was diagnosed clinically and confirmed by reversibility of FEV1 or peak flow of at least 15% on more than one occasion, either spontaneously, or in response to bronchodilator at any time since referral [9]. Subjects were only eligible for the study if they had been observed for at least one year before entry, and if not stable when first reviewed, entry was deferred by three months in an attempt to achieve stability. Socio-demographic variables were recorded as previously reported [10]. The first group of this dynamic cohort study was recruited during the calendar year 1983 but subsequent review and recruitment was between the 1st April and the 31st March in subsequent 12-month periods[11]. Allowance for the extra 3 months of the first interval has been made in calculating rate of change. Subjects are included in this report provided they had two technically satisfactory measurements of actual FEV1 or two estimates of best FEV1 or best FVC according to protocol.
Social and demographic variables
The following variables recorded included: age, gender, height, duration of asthma, atopy, childhood asthma, smoking habit and lifetime amount smoked, social class. Duration of asthma was determined from the first onset or from relapse after a symptom free interval of at least five years, if this was applicable. Atopy was determined by at least one of the following skin tests resulting in a diameter at least 3 mm greater than control: D Pterynissimus, cat, grass pollen, A fumigatus. Childhood asthma was defined as a childhood history of recurrent lower respiratory tract symptoms with wheeze, in the absence of a localised structural damage such as bronchiectasis. It was sub-divided into those with (Gap Asthmatics) and without (Continuous since Childhood) a symptom free gap of at least five years. Never smokers were those smoking less than one cigarette a day for one year. Ex-smokers had been abstinent for at least three months at the time of examination. The lifetime amount smoked was determined from the average consumption (expressed in packs of 20 cigarettes) multiplied by the duration of smoking to give a figure in pack-years.
Therapeutic regimen
This was characterised by the use of long acting beta agonists and the corticosteroid step: none, low dose inhaled (<800 micrograms per day), intermediate dose inhaled (800–1000 micrograms per day), high dose inhaled (>1000 micrograms per day), oral 1–9 mgs per day, oral ≥ 10 mgs per day, unstable (treatment not mutually agreed as satisfactory over the last three months).
Pulmonary function
Actual function
Actual function was that recorded at attendance.
Best function
This was estimated according to the published protocol [6]. The notes were searched from January 1st of the previous year, and the highest value, including the after-bronchodilator reading at attendance, was accepted as best subject to the following.
(a) If >80% predicted (Cotes [12]); after-bronchodilator
(b) If 70–80% predicted; after-bronchodilator and stable on mutually agreed satisfactory preventative treatment with twice daily recording of peak flow for one week
(c) If <70% of predicted; after-bronchodilator with formal trial of corticosteroids (prednisolone 30 mgs for at least five days with stability of peak flow for at least 48 hours)
If the above was not already satisfied, best function was immediately established according to the protocol.
Measurement
Spirometry was performed using a rolling wedge spirometer (Vitalograph Limited) and peak flow with the mini peak flow meter (Clement Clark Limited). Actual function was measured opportunistically at the clinic in current attenders and at a special clinic for those who had been discharged. One of three research fellows, one of two research nurses or CKC were responsible for checking current pulmonary tests in the clinical records and performing further tests when required by protocol for best function.
Ethical approval
This was obtained from the Darlington, Northallerton and South Durham Ethics Committees at various stages of the study.
Statistical analysis
The principal independent variable was change during each 5-year period so each individual contributed up to 3 observations to the analysis. For the 200 subjects with observations on all four occasions a secondary analysis could be based on decline over 15 years, and for each of these subjects the mean rate of decline was estimated from the four observations using linear regression analysis.
Best and actual/best peak flow measured independently of the spirometric outcome variables were chosen as the functional potential predictors of outcome. This approach was taken to avoid the mathematical relationship between baseline level and change that applies if the spirometric variables are used as predictors of outcome. Many of these potential predictive variables are correlated with each other and there are arguments for and against models examining the effect of socio-economic variables with or without allowance for the respiratory function of the patients and their age. We present a relevant selection from the large range of unrestricted and hierarchical models that we constructed.
We allowed for the inevitable regression to the mean associated with outcome measures subject to appreciable variability. Initially the starting value of an outcome functional variable was regressed against a full set of potential predictors of this function in order to generate a set of residuals indicating the extent to which an individual starting measurement is higher or lower than would be expected. Then the change in function was regressed against the residual. The new set of residuals indicates the extent to which the apparent rate of change is affected by regression to the mean enabling an adjusted rate of change to be calculated. This adjusted change in function was then taken as the dependent variable in subsequent analyses. These included the univariate effect of potential risk factors on the adjusted change in function. In the multivariate analyses we omitted variables which were consistently non-significant, but all others are retained in the presentation. Models are shown with and without the inclusion of age. Univariate analysis showed that there were cubic relationships between change in function and age and duration. The cubic terms are retained in the multivariate presentation. We also examined interactions between predictor variables where there was some a priori reason for believing that such an interaction was plausible but none was demonstrated.
Results
General
Of 1138 subjects recruited, 155 died before the first review, 49 were lost to follow up and 22 did not have satisfactory spirometric tests. The remaining 912 had at least one paired result of actual or best FEV1 or best FVC and 200 had satisfactory assessments of best FVC on all four occasions. Demographic details at entry are given in Table 1. There were no relevant differences in social factors between the subjects observed on all four occasions and the rest. Current smokers represented approximately 13% of the population in 1983/88 and 10% in 1993/98 with a mean tobacco load of ♂29.2 (ex-smokers 27.6) and ♀21.4 (ex-smokers 13.2) pack years. Ever-smokers were significantly older than never-smokers (53.9 v 44.9 years p < 0.001), but allowing for age, the atopic status of ever-smokers and never-smokers was the same. The proportion of subjects stable on inhaled or oral steroids rose from 66.5% in 1983 to 82.1% in 1988 with no increase thereafter. Higher doses (> = 800 micrograms) of inhaled steroids increased from 30.8% in 1988 to 41.6% in 1998.
Table 1 Details of subjects at entry
Male Female
n 457 455
Age (years)(sd) 50.4(15.4) 49.3(16.3)
Duration of asthma (years)(sd) 17.0(16.2) 18.6(15.4)
Atopic n(%) 258(56.5) 227(49.9)
Asthma n(%) childhood 124(27.1) 131(28.8)
gap 53(11.6) 42(9.2)
adult 280(61.3) 282(63.3)
Social Class n(%) 1–2 131(28.8) 139(30.5)
3 168(36.9) 180(39.6)
4–5 156(34.3) 136(29.9)
Smoking Habit n(%) never 147(32.2) 247(54.3)
ever 239(52.3) 161(35.4)
current 71(15.5) 47(10.3)
Pulmonary Function(sd) Actual FEV1 l. 2.50(1.09) 1.97(0.79)
Best FEV1 l. 2.60(1.08) 2.08(0.82)
Best FVC l. 4.17(1.25) 3.05(0.84)
Best PEF l/min 465.7(113.7) 382.0(85.1)
Actual/Best PEF % 84.4(13.7) 83.2(15.9)
Change in function
The mean annual decline in function calculated using all five-year intervals (Table 2) was greater than expected when compared with predicted values and when expressed as %predicted [12] there were no consistent differences in the rates of decline of male and female never-smokers. As the confidence intervals suggest, standard deviations were large indicating a wide distribution of changes in different individuals. There was no secular trend in outcome in successive calendar periods. Figure 1 shows changes over 5, 10 and 15 year periods after entry against predicted [12] (improved >7.5%, no change, deteriorated >7.5%). Actual FEV1 improved in approximately one quarter and best FVC in rather less than 20% of subjects. The proportion of subjects showing deterioration in FEV1 >7.5% (35%) did not increase with time after entry, but excess decline in FVC was observed in more subjects after 15 year's observation (58%) than after five (37%) (χ2 for trend, 59.0 (p < 0.001)).
Table 2 Annual Decline in Pulmonary Function calculated from the mean of all 5-year paired observations, and by linear regression over 15 years in the 200 subjects with all four observations
Annual Decline n Actual FEV1 l. Best FEV1 l. Best FVC l.
Males Over 5 Years All Subjects 776 41.0 (34.7–47.3) 42.9 (37.5–48.3) 63.1 (55.7–71.2)
Never smokers 256 34.2 (22.2–46.2) 33.4 (22.7–44.1) 49.2 (35.6–62.8)
Over 15 Years 85 46.7 (38.7–54.7) - 64.7 (54.6–74.8)
Females Over 5 Years All Subjects 848 28.9 (23.2–34.6) 34.4 (29.8–39.0) 45.8 (40.0–51.6)
Never smokers 375 28.7 (22.4–38.8) 30.6 (22.2–35.2) 45.2 (36.4–54.0)
Over 15 Years 115 24.7 (14.8–31.2) - 44.6 (37.9–51.3)
Figure 1 The proportion of all subjects and never-smokers showing decline (>7.5%), no change, or improvement (>7.5%) in function against predicted over 5, 10 and 15 years.
For the 200 subjects with complete observations over 15 years the mean rate of decline was similar to that observed over five year periods, but the standard deviation of the rates of decline was half that of the 5-year estimates, reflecting greater accuracy from multiple measurements. Even when calculating change this way several individuals improved or showed excessive loss in function against predicted [12].
Associations with entry variables
As there was no secular trend in the change of function over the five year periods, the date of observation is not considered in the analyses below.
All subjects: 5-year intervals
Univariate analysis
The univariate relationships between the potential explanatory variables and change in function after allowance for regression to the mean are summarised in Table 3. These are derived from all available pairs of observations at five year intervals. The strong associations with age are not linear. This is demonstrated in fig 2 which shows the fitted plots of the cubic equations for the unadjusted rate of decline for all three measures. The maximum decline was in the mid 40's for all three variables (actual FEV1 44 ml/yr; best FEV1 56 ml /yr; best FVC 70 ml/yr). During the eighth decade rate of decline in function recovered towards the published predicted values [12] to 27, 29 and 49 ml/yr respectively.
Table 3 Rate of loss of Function Univariate Coefficients (ml per year) (after allowance for regression to the mean)
Actual FEV1 Best FEV1 Best FVC
Estimate 95% CI Estimate 95% CI Estimate 95% CI
Gender (male v female) 7.7 0.8+,16.1 6.2 2.5+,14.9 12.2 2.5,21.9
Age at entry (per decade) (difference from age 50) Linear 5.6+ 11.4+,0.2 10.1+ 15.9+,4.8+ 2.1+ 8.7+,4.5
quadratic 4.3+ 6.0+,2.5+ 5.0+ 6.8+,3.3+ 4.5+ 6.5+,2.6+
cubic 1.3 0.3,2.3 2.0 1.0,2.9 1.4 0.3,2.6
Duration of asthma at entry (per decade) (difference from duration 20 yrs) Linear 3.1+ 7.4+,1.1 0.5 3.8+,4.8 0.1 4.8+,5.0
quadratic 3.6 0.6,6.6 2.7 0.5+,5.8 5.6 2.2,9.0
cubic 0.9+ 1.6+,0.1+ 0.9+ 1.7+,0.1+ 1.4+ 2.3+,0.6+
Atopic 5.7+ 14.2+,2.8 0.2 8.5+,8.9 3.0+ 12.7+,6.7
Childhood asthma (versus no childhood asthma) Gap 3.4+ 16.7+,9.9 1.4 12.2+,15.0 4.0+ 19.4+,11.3
Yes 20.8+ 30.6+,10.9+ 10.6+ 20.9+,0.4+ 22.0+ 33.3+,10.6+
Social Class (versus classes 1 and 2) Three 6.3+ 16.5+,3.8 11.2+ 21.7+,0.8+ 9.2+ 20.8+,2.3
Four and Five 10.2+ 21.0+,0.7 14.5+ 25.6+,8.3+ 8.6+ 21.0+,3.9
Amount smoked (per 10 pack years) 1.5 0.6+,3.7 0.2 2.1+,2.4 2.9 0.4,5.4
Best PEF(per 10% deficit) 3.3+ 5.3+,1.2+ 2.8+ 4.8+,0.7+ 0.4+ 2.7+,2.0
Actual/Best PEF(10% deficit) 12.7+ 15.6+,9.8+ 2.8+ 6.2+,0.6 0.6+ 4.1+,2.8
(+) Indicates relative gain in function
Figure 2 The relationship between age and annual change in function, observed over 5-year periods
There were no statistically significant relationships with atopy. Longer duration of asthma was significantly associated with favourable outcome for all variables. In all cases a cubic relationship between loss of function and duration suggests high initial rates of loss (actual FEV1 55 ml/yr; best FEV1 51 ml/yr; best FVC 74 ml/yr at one year), with improvement to a plateau at around 20 years duration (30 ml/yr, 37 ml/yr and 45 ml/yr). Childhood asthma was significantly associated with a relatively favourable outcome, though this benefit was only seen in those for whom asthma had been continuous. The outcome of the 'gap asthmatics' was similar to those with adult onset. Higher social class was associated with worse outcome, significantly so for best FEV1. Low initial function and worse control as assessed by actual/best PEF both predicted less loss in actual FEV1. Although there were no significant associations with current smoking status, there was significantly greater loss in best FVC with amount smoked.
Multivariate analysis
As childhood asthma, duration of asthma and age at entry are potentially confounded and were significant in some of the univariate analyses, we performed a series of multivariate analyses progressively including each in turn. Tables 4, 5, 6 show the results after the inclusion of duration and then age. Male gender was significantly associated with greater decline in best FEV1 and, in contrast to the univariate analysis, best FVC. After the inclusion of duration, childhood asthma was still associated with favourable outcome in both actual FEV1 and best FVC, but it was displaced by age in all the models. Duration remained significantly associated with less change in best FVC even after allowance for age. In both models, actual FEV1 declined less with lower entry actual/best PEF. Best FEV1 declined more rapidly in those with a high initial best PEF. When age was not included in the model, membership of social classes 1 and 2 remained associated with unfavourable outcome for best FEV1.
Table 4 Multivariate Coefficients (sd) for Rate of loss of Actual FEV1 (after allowance for regression to the mean)
Age Excluded Age Included
Coefficient p Coefficient p
Gender (male v female) 5.5 (4.8) 0.25 5.7 (4.7) 0.23
Asthma since childhood 13.5+ (5.1) 0.008 4.9+ (5.8) 0.40
Social Classes 1 & 2 (v. classes 4 & 5) 4.8 (5.4) 0.65 1.8 (5.4) 0.88
Social Class 3 (v. classes 4 & 5) 1.1 (5.1) 0.6+ (5.0)
Amount smoked (per 10 pack years) 1.8 (1.2) 0.13 1.0 (1.2) 0.39
Best PEF(per 10% deficit) 1.2+ (1.2) 0.33 0.9+ (1.2) 0.41
Actual/Best PEF(10% deficit) 12.0+ (1.6) <0.0001 13.2+ (1.6) <0.0001
Age at entry (per decade) (difference from age 50) Linear 3.5+ (3.1)
quadratic 4.9+ (0.9)
cubic 1.2 (0.6) 0.02
Duration of asthma at entry (per decade) (difference from duration 20 yrs) Linear 1.3 (2.8) 2.0+ (2.4)
quadratic 3.2 (1.5) 0.9 (0.5)
cubic 0.85+ (0.38) 0.03 2.5+ (0.39) 0.52
(+) Indicates relative gain in function
Table 5 Multivariate Coefficients for loss of Best FEV1 (after allowance for regression to the mean)
Age Excluded Age Included
Coefficient (sd) p Coefficient (sd) p
Gender (male v female) 11.3 (5.1) 0.03 11.9 (5.4) 0.02
Asthma since childhood 5.1+ (5.3) 0.34 1.1+ (6.0) 0.86
Social Classes 1 & 2 (v. classes 4 & 5) 13. (5.7) 0.05 10.7 (5.6) 0.11
Social Class 3 (v. classes 4 & 5) 2.9 (5.3) 1.4 (5.2)
Amount smoked (per 10 pack years) 0.7 (1.3) 0.60 0.5 (1.3) 0.71
Best PEF(per 10% deficit) 3.4+ (1.3) 0.008 3.1+ (1,2) 0.01
Actual/Best PEF(10% deficit) 0.7+ (1.8) 0.71 1.4+ (1.8) 0.44
Age at entry (per decade) (difference from age 50) Linear 8.4+(3.2)
quadratic 5.1+ (0.9)
cubic 1.8 (0.5) 0.0003
Duration of asthma at entry (per decade) (difference from duration 20 yrs) Linear 3.1 (2.4) 0.2 (2.4)
quadratic 2.5 (1.6) 0.4 (1.6)
cubic 0.91+ (0.39) 0.02 0.29+ (0.40) 0.46
(+) Indicates relative gain in function
Table 6 Multivariate Coefficients for Rate of loss of best FVC (after allowance for regression to the mean)
Age Excluded Age Included
Coefficient (sd) p Coefficient (sd) p
Gender (male v female) 10.8 (5.6) 0.05 11.4 (5.6) 0.04
Asthma since childhood 16.0+ (6.0) 0.007 4.7+ (6.9) 0.49
Social Classes 1 & 2 (v. classes 4 & 5) 10.7 (6.4) 0.13 7.5 (6.4) 0.29
Social Class 3 (v. classes 4 & 5) 0.2+ (6.0) 1.4+ (5.9)
Amount smoked (per 10 pack years) 1.9 (1.4) 0.18 0.9 (1.4) 0.52
Best PEF(per 10% deficit) 0.6+ (1,.4) 0.65 0.6+ (1.9) 0.67
Actual/Best PEF(10% deficit) 1.3 (1.8) 0.47 0.1 (1.9) 0.94
Age at entry (per decade) (difference from age 50) Linear 2.1+ (3.7)
quadratic 4.0+ (1.0)
cubic 1.4 (0.6) 0.02
Duration of asthma at entry (per decade) (difference from duration 20 yrs) Linear 4.0 (2.8) 0.8 (2.8)
quadratic 5.2 (1.7) 3.2 (1.8)
cubic 1.46+ (0.44) 0.001 0.97+ (0.46) 0.03
(+) Indicates relative gain in function
Height (not tabulated) was consistently directly associated with decline at a significance level of the order of 15% in univariate and multivariate analyses. In the latter analyses, height suppressed the associations with gender and social class. There were no significant associations with instability of regimen, nor with steroid step or the regular prescription of bronchodilators. None of the models considered made any relevant difference to the shape or gradients of the curves shown in fig 2.
200 Subjects: decline estimated using all four observations
Generally similar univariate associations were demonstrated. However on multivariate analysis, amount smoked remained in the FVC model (coefficient 13.3 ml/year per 10 pack years P = 0.020), and the effect of gender was stronger in both models (actual FEV1 23.8, actual FVC 19.8 ml/year, (P < 0.001). Height was again consistently directly associated with decrease in function at a significance level of the order of 15%. When height was included to allow for its association with gender, the difference in rate of decline in FEV1 between males and females was substantially reduced to 12.5 ml per year (p = 0.010) and was no longer significant for best FVC (p = 0.14).
Discussion
The hypothesis that persistent airway obstruction may develop in asthmatics implies that persistent airway obstruction and reversible obstruction associated with asthma are not mutually exclusive diagnoses However if COPD is regarded as a syndrome; this implies a non-asthmatic inflammatory process [5]. As the two types of inflammation need not be mutually exclusive, some asthmatics might have both types raising the possibility of an interaction between the two processes in some individuals, 'The Dutch Hypothesis' [13]. We have already shown that on cross sectional analysis green sputum, which is a feature of severity in COPD [14], is associated with diminished best function independent of smoking habit [15].
We are satisfied that our subjects satisfied the clinical criteria for asthma and had the relevant inflammatory process. Of course, the study is not of the entire asthmatic population as some individuals will remain undiagnosed while others will have been managed entirely in general practice, but all those referred to hospital and willing were entered into the study. We believe that the referral threshold was relatively low, and very few patients were referred outwith the local area. The subjects were recruited by a single handed hospital physician, with no other selection. There were no differences in the demography or function of those entering at different times [11]. Most were stable on maintenance corticosteroids [8].
The rate of decline of actual FEV1 was similar to that reported by Ulrik [1] (38 ml/year) and Lange [2] (50 ml/year). This study demonstrates for the first time that decline in best after bronchodilator function, the definitive physiological measurement for COPD [16], is similar to that of actual function. Actual/best PEF tended to improve over the period [8], so measurement of actual FEV1 potentially under-estimates any decline in best FEV1, but in practice loss of actual FEV1was not relevantly different from that of best FEV1.
As in the previous studies [1,2] the rate of decline of actual FEV1 is greater than that suggested by reference equations [12,17] which are derived from cross-sectional data. Values derived from longitudinal data may differ from cross-sectional observations for a number of reasons [18,19]. These include a cohort effect and, with lung function, loss of height with ageing which will mask decline in the cross sectional tables. We allowed for loss of height by using height at the start of each 5-year period. After discounting this there was little difference between the genders, the principal association with change in function being the age of the subjects. Longitudinal studies suggest increased loss of FEV1 in elderly normal subjects [20-22], but the rate of decline in our study is greater at all ages than that reported from the general population [20]. Our results suggest that that a cubic model involving age is appropriate for all of the three measures of respiratory function that we have analysed. Although the pattern in a particular individual cannot be determined from these computed curves, they strongly suggest that decline is not linear. The interpretation of the pattern of change is critically dependent on its normal course. The critical points on the curve include the age at which maximum life-time function is achieved and the possibility of a plateau, before deterioration starts The age when personal best is achieved is variously estimated between the early twenties and the late thirties [19], and may well vary from person to person. In looking for a plateau phase Robbins et al [23] demonstrated both positive and negative slopes in different individuals. Any decline seen where improvement or no change is anticipated must be excessive and so the slow decline that we observed in the third decade may be an under-representation of the true loss of function. It is more difficult to explain the faster decline in early compared to late middle age. As the entry criteria of this study were a diagnosis of asthma with no attempt to exclude co-existent COPD, it is possible that this reflects a period of life when the effects of the inflammatory process associated with COPD are particularly apparent. In subjects where asthma and COPD co-exist, COPD might contribute to presentation in these subjects, and decline in function might be particularly rapid especially if there were interaction between the two inflammatory processes. The above is compatible with the apparently unsustainable rates of decline observed early in COPD as in the Euroscop study [24]. We confirmed that decline accelerates after in late life in these asthmatics as it does in normal subjects [[20,21], and [22]].
Outcome in successive periods is necessarily confounded by the effects of management and attrition. Attrition is particularly relevant to the analysis of change in function, as the most powerful predictor of survival in these subjects is best function [11]. Higher dose of inhaled corticosteroids at the start of an observation period was not associated with better outcome within the same period. This is unsurprising because a higher dose reflects more severe disease. More surprisingly, there was also no evidence that the higher average dose in successive periods was associated with a favourable secular trend in observed, or maximum, function. Nevertheless in contrast, actual/best peak flow improved [8] and standardised mortality declined with time [11]. The latter was reduced twofold although subjects on higher therapeutic steps remained more likely to die even after allowance for other risk factors including best function. It may be that clinicians are able to recognise subjects of poor prognosis irrespective of function, but are more successful in reducing mortality than loss of function by adjustment of therapy. None of these considerations necessarily imply that the use of inhaled corticosteroids is ineffective in terms of function. As there were, of necessity, no controls, any effect of treatment, dictated by clinical need, is impossible to confirm. Improvement in functional outcome might have been confounded by reduced mortality in those with severe disease, or the dose response curves for reduction of mortality might be very different from those for prevention of airway remodelling.
We depended primarily on patient recall in making a diagnosis of childhood asthma. Although we had a low threshold for accepting the diagnosis, presumably recall would be more consistent when childhood symptoms were severe. This might produce a bias in favour of demonstrating associations. Nevertheless the univariate associations with change in function were stronger in those who claimed that they had had persistent symptoms since childhood, than in those who recalled childhood asthma after a gap of at least five years. The outcome in gap asthmatics was similar to those with adult onset, but surprisingly subjects with symptoms persistent since childhood showed a more favourable trend. This appears to be inconsistent with the long established observation that childhood asthma compromises adolescent and early adult lung function and that this is related to persistent symptoms [25,26]. However duration is probably the critical factor. The history of asthma is likely to be long in adults with symptoms persistent from childhood and rapid decline is shown to be associated with short duration. Although these subjects did have relatively poor lung function at entry to the study [10], probably reflecting their function on reaching maturity, it does not necessarily follow that retarded development will be succeeded by an excessive rate of decline later in life. It may be that at any age whether in childhood or adulthood the first decade of the disease is critical in determining loss of function. This might not be true in those with pure COPD, and explain why our findings are contrary to the 'horseracing effect' (the horse that runs fastest continues to extend its lead) as described by Fletcher in his classical population studies [27]. There the comparison was with normal subjects rather than those with established airway disease with differing lengths of history.
The effect of smoking appeared small, but there were few current smokers and the tobacco load was light. The study was not designed to observe the effects of tobacco smoking in asthma; the separate analysis of non-smokers was intended to describe the decline in the function of asthmatics unencumbered by the effects of cigarette smoking. It is inevitable that we have underestimated the potential association between smoking and decline in function in asthma and so do not suggest that the effect of smoking in asthmatics in general is unimportant.
The association between low initial actual/best function, implying poor control, and apparently favourable outcome is highly likely to reflect response to treatment. There was a strong relationship between low social class and poor control in the 1983 entry [10]. This may account for some of the paradoxical benefit of lower social class, possibly even hiding a real disadvantage.
Conclusions
We present the decline in function in a dynamic cohort of adult asthmatics observed over fifteen years. The majority were treated with inhaled corticosteroids throughout the period. As there are no internal asthmatic or normal controls our study cannot determine definitively whether there is excess decline in the pulmonary function of adults managed conventionally with inhaled cortico-steroids. It does suggest, however, that the dose of inhaled steroids may not be critical over the recommended range. Our study confirms that the pattern of decline in actual and best ventilatory function is similar. This is important when comparing this study with epidemiological exercises where actual rather than best function has been measured. Furthermore these original findings in respect of the cubic effect of age should be taken into account when interpreting other articles reporting age effects on function, particularly where analysis of cross-sectional observations may imply that decline in the function is linear.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
CKC conceived the study and was responsible for design of data forms, recruitment and all the clinical aspects. RJP undertook the analysis of data. Both authors read and approved the final manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
We wish to thank former research fellows: NK Murthy, PM Roy, AA Gatnash, M Mamun and H Dasgupta for their clinical contributions, and Urike Paulus and Mirjam Göhler for help with the analysis.
This study was supported at various phases by Glaxo Welcome Plc (Duncan Flockhart Ltd and Allen and Hanbury's Ltd), the National Asthma Campaign and Breath North (in association with the British Lung Foundation) and local research funds.
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| 15683540 | PMC549563 | CC BY | 2021-01-04 16:30:12 | no | BMC Pulm Med. 2005 Jan 31; 5:2 | utf-8 | BMC Pulm Med | 2,005 | 10.1186/1471-2466-5-2 | oa_comm |
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PLoS MedPLoS MedpmedplosmedPLoS Medicine1549-12771549-1676Public Library of Science San Francisco, USA 1573699010.1371/journal.pmed.0020011Health in ActionInfectious DiseasesMalariaMedicine in Developing CountriesTeaching Health Workers Malaria Diagnosis Health in ActionIcke Graham *Davis Richard McConnell William Graham Icke is a principal scientist, Richard Davis is an emeritus consultant haematologist, and William McConnell is a senior scientist in the Division of Laboratory Medicine, Royal Perth Hospital, Perth, Australia.
Competing Interests: To produce and distribute the CD-ROMs discussed in this article, the authors received sponsorship from Becton Dickinson (Franklin Lakes, New Jersey, United States of America) and Abbott Diagnostics (Abbott Park, Illinois, United States of America).
*To whom correspondence should be addressed: E-mail: [email protected] 2005 22 2 2005 2 2 e11Copyright: © 2005 Icke 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.In most parts of the world, microscopy is still the gold standard for diagnosing malaria. An online tool could help to improve your diagnostic skills
An online tool allows microscopists to test their knowledge
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Malaria kills over one million people in Africa each year and contributes 10% of the continent's burden of disease [1]. One of the factors that affects the morbidity and mortality rate is incorrect diagnosis [2]. In this article, we describe a freely available online training tool for health professionals to learn malaria diagnosis. We describe why we launched it and discuss how it is being used.
The Burden of Disease
Malaria affects at least 200–300 million people every year and causes from 1–2 million deaths—mostly children under five and pregnant women in sub-Saharan Africa [1]. These deaths largely occur in remote rural areas with poor access to health services. In non-pregnant adults, although mortality rates are lower, the debilitating disease affects quality of life. The economic burden is also extremely high, accounting for a reduction of 1.3% in the annual economic growth rate of countries where malaria is endemic [3]. Malaria costs Africa more than US$12 billion every year in lost GDP, even though it could be controlled for a fraction of that sum [1].
Malaria is not limited to Africa—40% of the world's population is at risk of acquiring the disease [4,5]—and it is crucial for all physicians, medical scientists, and other healthcare professionals to be alert to the diagnosis. In addition, each year, 25–30 million people from non-tropical countries visit areas where malaria is endemic [6], and between 10,000 and 30,000 contract malaria [7]. Some 90% of infected travellers do not become ill until they return home; this “imported malaria” is easily treated, but only if it is diagnosed promptly [2,8].
The Importance of Correct Diagnosis
Despite the efforts of a global campaign to roll back the disease, the number of deaths from malaria is increasing in Africa [9]. This statistic highlights the importance of local capacity to diagnose and treat malaria in order to prevent illness and death [10]. In many parts of the world, education about malaria diagnosis and treatment is limited—and the incorrect diagnosis of malaria by clinical, laboratory staff, and other healthcare workers can contribute to morbidity and mortality [2,11].
There is another important reason why correct diagnosis matters. Because of rising drug resistance in Africa, the conventional drugs for treating malaria—chloroquine and sulfadoxine-pyrimethamine—are now failing in up to 80% of cases [12]. There is a highly effective alternative to these drugs, which is artemisinin-based combination therapy (ACT) [13], but ACT is expensive (an adult dose of chloroquine costs around 10 cents, whereas a dose of ACT costs at least ten times that amount) [14]. Scaling up the use of ACT is now a core strategy in the global campaign to control malaria. But in order to control costs, and to prevent the emergence of resistance to ACT, its use should be targeted to real (rather than presumptive) cases of malaria [14]. Currently, however, a comparison of the number of parasitologically confirmed cases of malaria with those that are presumptively diagnosed shows high rates of overdiagnosis outside of hospitals at the community level, where self treatment is routine [14].
Microscopy as the Gold Standard for Diagnosis
We still regard microscopy as the gold standard for the diagnosis and characterisation of malaria infection (Figure 1). Modern “dipstick” technology and molecular techniques have emerged as an aid to diagnosis [13,14]. Some of these are useful particularly for Plasmodium falciparum [15]—although they are less effective for other species or for mixed infections [16,17]—but these techniques are often only available in larger hospitals, which are more likely to be able to afford them.
Figure 1 Thin Film Micrograph Showing a Red Blood Cell Containing Two Ring-Form P. vivax Parasites
P. vivax rings have a large quantity of cytoplasm and a large chromatin dot, as well as occasional pseudopods. The red blood cells are normal, to 1.5× normal, sized, round, and contain fine Schüffner's dots, and they quite often contain multiple parasites.
(Photograph: CDC/Dr Mae Melvin)
Some authors have suggested that these new tests should not be considered a complete substitute for direct microscopic examination of blood smears [16]. We agree. While microscopy has limitations—morphology can be misleading if a patient has received partial treatment or incomplete prophylaxis, and in some locations a microscope (let alone a microscopist) can be rare—the new dipstick tests also have their flaws. For example, they must be stored correctly, used correctly, and interpreted correctly. There are concerns about the variability in the different tests' false positive and false negative rates and about their cost–benefit ratio. There are many supporters of the new dipstick technology, and as it improves and becomes more robust and reliable, it may well replace the microscope in practice. But for much of the world, the front-line diagnosis of malaria still remains in the hands of the reasonably trained microscopist.
Analysis of DNA by the polymerase chain reaction (PCR) may be a useful tool for diagnosis of malaria when the results of conventional techniques are negative, especially since PCR allows accurate species identification [18]. And when compared with the “gold standard” of microscopy, PCR has a sensitivity and specificity of 100%, with a detection limit of just one P. falciparum or three P. vivax parasites per microlitre of blood [19]. However, in most areas with malaria transmission, limited financial resources, persistent subclinical parasitaemia, and inadequate laboratory infrastructure preclude PCR as a routine diagnostic method [20]. Even in affluent, nonendemic countries, PCR is not a suitable method for routine use. Capital investment and ongoing running costs are prohibitive for many laboratories, and certainly for the foreseeable future this technology will remain a tool for the more specialised services in the more affluent societies. At this stage, it is not considered a “routine” assay.
Teaching Microscopy Online
In the hope of improving health professionals' understanding of malaria diagnosis, treatment, and prophylaxis, we launched an online malaria education tool that went live in July 1998 (http://www.rph.wa.gov.au/labs/haem/malaria/index.html). The materials are now available in English, French, and Spanish. One of the most important features is a “Test and Teach” section to allow microscopists to develop and sharpen their skills in malaria diagnosis (Figure 2).
Figure 2 A Clinical Case from the “Test and Teach” Section
Because of regional variability in Internet access, we also made the tool freely available as a CD-ROM. The first CD-ROMs we produced, which were in English, reached institutions and centres in 41 countries during the first few months after the launch. By October 1999, we produced a new CD-ROM that incorporated a French translation of key areas of the project; a Spanish version followed. By the end of 1999, the CD-ROM version had reached over 70 countries and the website had received nearly 30,000 visitors.
To date, the website has received more than 500,000 visitors. Around 83 million pages of text were downloaded from the website between July 2001 and September 2003. The CD-ROM version (over 8,000 copies) has been sent on request to institutions and centres in 149 countries, a number that does not include unauthorised (pirated) copies of the CD-ROM. The number of hits to the site (the number of pages or images of the site that are accessed) has risen dramatically, from 1,500 to over 100,000 per week.
Feedback from Users
Through a circulated questionnaire with a 63% response rate, we have received feedback from users in 15 countries. Respondents said they valued the content, presentation, and usefulness of the online information. Who is using the material? A wide range of people—from students through to experienced personnel, and from clinicians to scientific, research, and technical staff. Many tropical medicine institutions have requested copies of the CD-ROM to supplement their own training programs. We have discussed the project at scientific conferences around the world and in scientific journals, advertising the fact that this educational material is freely available. Institutions wishing to obtain a free copy of the CD-ROM should contact E-mail: [email protected].
We also became aware that unauthorised copies of the CD-ROM were being produced. Although there is a real need to guarantee the integrity of the information on the CD-ROMs and ensure proper credit for the authors and patrons, our main aim is to spread the “good word”, and such unauthorised copies are a powerful aid to distribution. Given that there is no need to recoup profit from this project, our only concern is its usefulness. Consequently, we have welcomed the production of these pirated copies, on condition that they were of good quality and were made freely available at no cost.
Conclusion
The Internet and associated technologies make it possible for educators with a desire to teach to contact those with a need to learn, regardless of the geographical distances involved. By enlisting assistance from international colleagues, language barriers can be overcome. In addition to the English, French, and Spanish versions, we are aware that our project has been translated into German, Thai, and Vietnamese and has been distributed through small regional health group networks.
There can be little doubt that these new technologies have the potential to revolutionise information dissemination, with particularly significant implications for healthcare professionals in developing countries. The malaria educational program could be a model on which future health education programs are based. With rapidly increasing access to these new information technologies, health care professionals from anywhere in the world can now join the global health community.
Citation: Icke G, Davis R, McConnell W (2005) Teaching health workers malaria diagnosis. PLoS Med 2(2): e11.
Abbreviations
ACTartemisinin-based combination therapy
PCRpolymerase chain reaction
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Kain KC MacPherson DW Kelton T Keystone JS Mendelson J Malaria deaths in visitors to Canada and in Canadian travellers: A case series CMAJ 2001 Available: http://www.cmaj.ca/cgi/content/full/164/5/654 . Accessed 4 December 2004
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World Health Organization The world health report 1997: Conquering suffering, enriching humanity 1997 Available: http://www.who.int/whr/1997/en/ . Accessed 4 December 2004
Murphy GS Oldfield EC Falciparum malaria Infect Dis Clin North Am 1996 10 747 755 8958167
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International Artemisinin Study Group Artesunate combinations for treatment of malaria: Meta-analysis Lancet 2004 363 9 17 14723987
Barnish G Bates I Iboro J Newer drug combinations for malaria BMJ 2004 328 1511 1512 15217846
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Humar A Ohrt C Harrington MA Pillai D Kain KC Parasight test compared with the polymerase chain reaction and microscopy for the diagnosis of Plasmodium falciparum malaria in travelers Am J Trop Med Hyg 1997 56 44 48 9063360
Gatti S Bernuzzi AM Bisoffi Z Raglio A Gulletta M Multicentre study, in patients with imported malaria, on the sensitivity and specificity of a dipstick test (ICT Malaria P.f./P.v.) compared with expert microscopy Ann Trop Med Parasitol 2002 96 15 18 11989528
Murray CK Bell D Gasser RA Wongsrichanalai C Rapid diagnostic testing for malaria Trop Med Int Health 2003 8 876 883 14516298
Morassin B Fabre R Berry A Magnaval JF One year's experience with the polymerase chain reaction as a routine method for the diagnosis of imported malaria Am J Trop Med Hyg 2003 66 503 508
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| 15736990 | PMC549582 | CC BY | 2021-01-05 10:40:26 | no | PLoS Med. 2005 Feb 22; 2(2):e11 | utf-8 | PLoS Med | 2,005 | 10.1371/journal.pmed.0020011 | oa_comm |
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PLoS MedPLoS MedpmedplosmedPLoS Medicine1549-12771549-1676Public Library of Science San Francisco, USA 1573699110.1371/journal.pmed.0020014Neglected DiseasesInfectious DiseasesOtherScience PolicyEpidemiology/Public HealthHealth PolicyMedicine in Developing CountriesDrugs and adverse drug reactionsPublic HealthThe Courage to Change the Rules: A Proposal for an Essential Health R&D Treaty Neglected DiseasesDentico Nicoletta *Ford Nathan Nicoletta Dentico (based in Italy) and Nathan Ford (based in London) are both members of the Neglected Diseases Group (http://www.accessmed-msf.org/dnd/index.asp), an interdisciplinary, independent working group established by Médecins sans Frontières (http://www.msf.org) in 1999. They are writing in their own capacity, and the views expressed cannot be taken as the views of Médecins sans Frontières.
Competing Interests: The authors declare that they have no competing interests.
*To whom correspondence should be addressed: E-mail: [email protected] 2005 22 2 2005 2 2 e14Copyright: © 2005 The Neglected Diseases Group.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 medical needs of many of the world's population go unmet. A new treaty on essential health R&D could provide a binding framework to redirect today's scientific expertise to priority needs
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Biomedical science and technology are developing at a more rapid pace than ever. Investments in health research and development (R&D) have never been higher—global spending on health research increased from US$30 billion in 1990 to US$105.9 billion in 2001. But despite advances in technology and unparalleled research spending, the medical needs of many of the world's population go unmet. For example, only 1% of new drugs approved between 1975 and 1999 were specifically developed for tropical diseases and tuberculosis—diseases that account for over 10% of the global disease burden (Figure 1) [1].
Figure 1 Clinical Officer Preparing Sodium Stibogluconate Solution Injection for a Patient with Visceral Leishmaniasis
Sodium stibogluconate solution is administered by intramuscular injection for 30 days. The injection is painful and can cause toxic reactions. Developed in 1934, resistance of up to 65% has been documented in India. Around 50,000 people die from visceral leishmaniasis each year. New, effective drugs and diagnostics are urgently needed.
(Photograph: Copyright Espen Rasmussen/MSF, Somalia, 2004)
In recent years, some important steps have been taken to improve access to existing treatments in the developing world by increasing generic competition. Yet there continues to be a tension between promoting access to lifesaving medicines as a human right and maintaining a global trade regime that seeks to finance health R&D by allowing monopolies to charge high prices [2].
There is a growing demand from many quarters for a new international policy framework [3]. A new international treaty on essential health R&D could provide a binding framework to redirect today's knowledge and scientific expertise to priority health needs. The treaty could help to cement new political commitments and coordinate complementary partnerships aimed at generating and rewarding health innovation as a global public good.
The Patent System: An Unhealthy Motive for Medical Innovation?
Until recently, providing patent protection for pharmaceuticals was a choice made by individual governments according to their level of industrial development. Today, pharmaceutical patents are globalized through the World Trade Organization's Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS Agreement) [4], and then further reinforced through bilateral and regional arrangements (the so-called TRIPS-Plus agreements [5]). But the patent system stimulates innovation only where industry sees the opportunity for increasing sales and market share; much of the resulting “innovation” is in fact imitation, producing “me-too” drugs that offer little, if anything, in the way of therapeutic benefit over existing drugs (Box 1).
Box 1. How Innovative Is the Profit Motive?
A study published in the Lancet in 2002 showed that 68% of all new chemical entities marketed worldwide in the last 25 years were me-too products, representing little or no therapeutic gain [1].
According to the United Nations Development Programme, less than 5% of drugs introduced by the top 25 pharmaceutical companies in the US represented true therapeutic advances; of these, 70% were developed with government involvement ([20], p. 69).
Studies of drug development over the last decade in the US [21] and the last two decades in France [23] show that around two-thirds of medicines are me-too products.
92% of medicines approved in 2002 by the US Federal Drug Administration were me-too drugs [23].
The poorest are hardest hit. While R&D of new therapies against tropical diseases has ground to a standstill, 14 million people die from infectious diseases each year, predominantly in developing countries [1]. Most of the world's 40 million people with HIV/AIDS, including 2.2 million children under 15, live in the developing world (www.unaids.org). The poor also dominate non-communicable disease tables, accounting for 59% of the 56.5 million annual global deaths [6].
The patent system is also promoting new inequalities in high-income countries. Americans now spend a staggering $200 billion a year on prescription drugs. This figure is growing at a rate of about 12% per year [7]. The average price of the fifty drugs most used by senior citizens in America was nearly $1,500 for a year's supply in 2002. Prescription drugs have become inaccessible even to many people in the rich world.
Patents, with their focus on maximizing profits, have at least three negative consequences. First, it has been argued that the patent system causes substantial welfare losses because consumers who would buy the product if it were priced at somewhere nearer production cost do not buy it at the monopoly price [8]. Second, the system encourages counterfeiting—counterfeit drugs may represent up to 10% of the global market for pharmaceuticals [9]. Third, patented drugs are promoted through excessive marketing—on average, twice as much is spent on marketing a drug as on its R&D [10]. Across industries, it is becoming increasingly apparent that the patent system isn't working well [11], leading some in industry to express public concern that the blockbuster business model is “irreparably broken” [12]. A new approach is needed, for all our sakes.
Prescriptions for an Innovative Approach: A New Treaty for Essential Health R&D
The only major international policy instrument that exists today to stimulate and finance health R&D is the TRIPS Agreement [4]. The TRIPS Agreement provides 20 years of patent protection on pharmaceuticals in the hope of stimulating the development of new medicines. Beyond that, governments try to stimulate R&D in neglected areas by providing industry with incentives such as tax breaks and patent extensions. However, the effectiveness of these policies is hardly known.
In 2001, the Doha Declaration on TRIPS and Public Health affirmed the sovereign right of WTO members to take measures to protect public health by overcoming patents whenever needed [4]. The last few years have seen increased attention to the fact that patents keep drug costs high and limit access to medicines. However, there has been no movement in international policy to address the crisis in pharmaceutical innovation.
Health R&D must be treated as an international problem that requires an international solution. It should be treated like other strategic sectors, as happens today for defense and space discovery—sectors that both benefit from very strong government support for innovation. When global public goods do correspond to national needs, governments should step in to mobilize and enforce the collective action required. For example, global cooperation in the sharing of infectious disease monitoring from 1890 onwards set a valuable precedent [13].
The recent epidemic of severe acute respiratory syndrome—SARS—clearly shows that biomedical knowledge and the pharmaceutical sciences can be mobilized to achieve rapid advances relevant to social needs if sufficient resources and political will can be mustered. The SARS virus was completely sequenced in just six days, and a diagnostic test was developed in only three months. The public-sector funded, collaborative “public-goods model” used for the Human Genome Project shows that public collaborative research can be more efficient than the closed, monopolistic, private sector approach.
An international treaty (Box 2) would promote a health-needs-driven approach to drug discovery. The elaboration of such a treaty would have to meet the two crucial requirements for an effective system of funding innovation in pharmaceuticals. First, the reward for innovation should be proportional to the social (that is, therapeutic) value. Second, prices should be near average production cost.
Box 2. Key Concepts of an R&D Treaty
A global, needs-driven R&D agenda: allowing policy makers, funding agencies, and the research community to set priorities for developing safe, effective, and affordable medicines according to health needs.
Prioritization for neglected diseases: to ensure that immediate efforts are made toward finding new tools for lethal diseases that are currently difficult or impossible to diagnose and treat.
Adequate international financing of health R&D: a new funding mechanism is urgently needed to support R&D on an ongoing basis, particularly for neglected diseases. All governments will need to participate according to their means.
Equitable pricing: governments should ensure that the poor also have access to innovations resulting from government-funded or university research.
Open access: governments should require access to the compounds and tools that result from public research in order to stimulate follow-on innovation elsewhere.
International exchange: strengthening openness and transfer of technologies on a global basis will greatly help developing countries by improving access to information and ideas and accelerating the development of science and technology.
The idea is to shift the discourse from trade to health. The treaty—focussed directly on R&D rather than patent rights or drug prices—would address the global management of publicly funded health R&D. Priorities for R&D would be defined through public-sector leadership and based on public health needs. R&D opportunities would be aimed at new lead compounds, new types of health tools (Figure 2) and new treatment approaches. As the only legally mandated international government agency responsible for global health, the World Health Organization should work toward establishing this essential R&D agenda. Individual states would need to periodically evaluate targets for priority research and make adequate recommendations toward needs-driven R&D.
Figure 2 Detection of African Sleeping Sickness by Lumbar Puncture
Lumbar puncture in patients with African sleeping sickness can be a painful and potentially dangerous maneuver that is the only way to determine if the disease has progressed to the second stage. New diagnostic tools are urgently needed, as are new treatments; current medicines are old, toxic, difficult to use, and their production is not guaranteed. Around 60,000 people die from Afican sleeping sickness every year.
(Photograph: copyright Serge Sibert/MSF, Uganda, 1998.)
How Will the Treaty Work?
One of the main objectives of the treaty would be to encourage the broad dissemination of information and knowledge-sharing, and to support diversity, competition, and collaboration among researchers from developed and developing countries.
There are already precedents for the free, public sharing of innovations with the aim of developing new drugs. The Tropical Diseases Initiative (www.tropicaldisease.org), for example, is a new, Internet-based, community-wide effort to develop new drugs for tropical diseases [14]. The BioBricks project (http://parts.mit.edu/) at the Massachusetts Institute of Technology is exploring standardized tools and processes for DNA work, largely by computer. The Bios Initiative (Biological Innovation for Open Society), launched by the Australian non-profit organization Cambia (the Center for the Application of Molecular Biology to International Agriculture; www.cambia.org), is an effort to develop new innovation systems for market failures and for neglected priorities [15].
Among other incentives, technology exchange frameworks could include licensing agreements with developing countries, or affirmative commitments of research funds for collaborative projects with these countries. Such collaboration is currently being implemented in Europe, for example, through the European and Developing Countries Clinical Trial Partnership (www.edctp.org) [16]. The partnership is a new funding body established to fund research in developing countries, particularly in Africa, which contributes to the development of affordable prophylactics and drugs for HIV/AIDS, tuberculosis, and malaria. The treaty on health R&D should also promote partnerships between countries in the developing world and encourage the creation of regional technology networks in developing countries.
Much of today's drug development know-how exists within the private sector. Further work is needed to define obligations and incentives in the treaty that maximize industry contributions to publicly funded R&D by providing in-kind contributions in areas where industry has the skills that public groups need. The treaty should also provide an expanded use of government rights against patent abuse on drugs developed with public support. This would include the right of a government to intervene if an invention is not made available to the public on reasonable terms, such as is included in the march-in rights clause of the United States's 1980 Bayh-Dole Act (which enabled public universities to license inventions for commercial development [17]).
Making the Treaty Happen
There are a number of obvious difficulties in moving the treaty forward, and these should not be underestimated. A delicate issue is the treaty's relation with other binding agreements, particularly the TRIPS Agreement. Governments that join the treaty should be granted patent exceptions and should not be accused of “free-riding,” since they would be contributing to R&D through a different juridical avenue.
Substantial government resources would need to be mobilized to finance the highest priority medical research. All governments should participate according to their means. Countries already contribute significantly to global R&D through the purchase of costly patented drugs. Among other measures, not-for-profit initiatives working to develop new drugs, vaccines, and diagnostic tools for neglected diseases should be funded at levels that enable them to reach their objectives. Recent examples clearly show that when political will is mobilized, resources are rapidly made available to generate R&D in a particular area. In 2001, the anthrax scare in the US led to increases in biodefense research spending at the US National Institutes of Health from US$53 million in 2001 to US$1.6 billion in 2004.
A treaty on health R&D is certainly a feasible proposal—the successful adoption of a treaty on plant genetic resources shows that it can be done. After seven years of negotiations, the Food and Agriculture Organization of the United Nations adopted the International Treaty on Plant Genetic Resources for Food and Agriculture in November 2001 [18]. This legally binding treaty covers all plant genetic resources relevant for food and agriculture. Through the treaty, countries agree to establish an efficient, effective, and transparent multilateral system to facilitate access to plant genetic resources for food and agriculture, and to share the benefits in a fair and equitable way. While there has been a growing consensus in development circles that more international public goods need to be supplied as part of the development strategy, increasing their provision will be influenced by the extent to which inspirational groups of individuals step in to play a leadership role to meet the collective need.
The Ottawa Convention to Ban Anti-Personnel Landmines and the 2003 Framework Convention on Tobacco Control show that international frameworks are essential to the regulation of the private sector for the good of global health. The World Health Organization, together with other relevant United Nations agencies, has full legitimacy to work with member states toward crafting challenging proposals, and provoking policy action. One lesson from these treaties is that support will have to be built from a strong coalition of like-minded countries that would steer the process internationally.
While the development of the treaty is still at an early stage of discussion, the concept is already being aggressively opposed. As with tobacco, landmines, and more recently, sugar, the involvement of civil society will be crucial to defend these health improvement strategies where these may conflict with powerful vested interests in the private sector [19].
It takes courage to change the rules. If governments are indeed persuaded to face up to their responsibilities in the coming years, it may very well be because of the many voluntary organisations that seek to promote the global public interest.
This paper draws on the work of many people who have dedicated their time to confronting the issue of neglected diseases over the past five years. We would like to thank all members of the Neglected Diseases Group, some of whom have given extensive time to developing a much longer version of this proposal.
Citation: Dentico N, Ford N (2005) The courage to change the rules: A proposal for an essential health R&D treaty. PLoS Med 2(2): e14.
Abbreviations
R&Dresearch and development
TRIPS Agreementthe World Trade Organization's Agreement on Trade-Related Aspects of Intellectual Property Rights
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Lee K Koivusalo M Trade and health: Is the health community ready for action? PLoS Med 2005 2 e8 15696218
Hubbard T Love J A new trade framework for global healthcare R&D PLoS Biol 2004 2 e147
World Trade Organization Declaration on the TRIPS agreement and public health 2001 Adopted on 14 November 2001. Available: http://www.wto.org/english/thewto_e/minist_e/min01_e/mindecl_trips_e.htm . Accessed 11 November 2004
Replogle J Central American trade pact may limit access to generics Lancet 2004 363 1612 1613 15146865
World Health Organization The world health report 2002: Reducing risks, promoting healthy life 2002 Geneva World Health Organization 250
Health IMS IMS reports constant dollar growth in 2002 audited global pharmaceutical sales to $400.6 billion 2003 Available: www.imshealth.com/ims/portal/front/articleC/0,2777,6599_3665_41336931,00.html . Accessed December 4, 2004
Hollis A An efficient reward system for pharmaceutical innovation 2004 Available: www.who.int/entity/intellectualproperty/news/en/Submission-Hollis6-Oct.pdf . Accessed 15 November 2004
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Mahan D Profiting from pain: Where prescription drug dollars go 2002 Available: http://www.familiesusa.org/site/DocServer/PPreport.pdf?docID=249 . Accessed 3 December 2004
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Gilbert J Henske P Singh A Rebuilding big pharma's business model In Vivo: The Business and Medicine Report 2003 21 73
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Barbour V Cohen B Yamey G A new vision for clinical trials in Africa PLoS Med 2004 1 e71 15630472
Moses H Martin JB Academic relationships with industry: A new model for biomedical research JAMA 2001 285 933 935 11180737
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| 15736991 | PMC549583 | CC BY | 2021-01-05 10:39:29 | no | PLoS Med. 2005 Feb 22; 2(2):e14 | utf-8 | PLoS Med | 2,005 | 10.1371/journal.pmed.0020014 | oa_comm |
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PLoS MedPLoS MedpmedplosmedPLoS Medicine1549-12771549-1676Public Library of Science San Francisco, USA 1573699210.1371/journal.pmed.0020033PerspectivesGenetics/Genomics/Gene TherapyNeurology/NeurosurgeryMultiple SclerosisGeneticsCan Blood Gene Expression Predict Which Patients with Multiple Sclerosis Will Respond to Interferon? PerspectivesKaminski Naftali *Achiron Anat Naftali Kaminski is Associate Professor of Medicine and Director of the Dorothy P. and Richard P. Simmons Center for Interstitial Lung Disease and the Lung Translational Genomics Center, in the Division of Pulmonary, Allergy, and Critical Care Medicine at the University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America. Anat Achiron is Senior Lecturer in Neurology and Director of the Multiple Sclerosis Center at Sheba Medical Center, Tel Hashomer and Sackler School of Medicine, Tel Aviv University, Israel.
*To whom correspondence should be addressed. E-mail: [email protected]
Competing Interests: The authors are inventors on a patent application regarding the use of peripheral blood mononuclear cell gene expression in the diagnosis of multiple sclerosis.
2 2005 22 2 2005 2 2 e33Copyright: © 2005 Kaminski and Achiron.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.
Test Your Knowledge: Ten Questions about Multiple Sclerosis
Gene expression patterns from peripheral blood cells may be useful as biomarkers for monitoring MS progression and response to therapy, argue Kaminski and Achiron
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Despite the significant progress in increasing our understanding of the immune mechanisms of multiple sclerosis (MS), in improving clinical classification and brain imaging, and in developing new treatments, the factors that determine the course of the disease are mostly unknown [1]. Currently, it is nearly impossible to predict the course of MS, its severity in terms of disability progression, or when a relapse will happen.
The most commonly used disease-modifying therapies are interferon β (IFNβ) [2] and glatiramer acetate [2,3]. Despite initial excitement, these therapies have beneficial effects in some, but not all, patients [2,3]. Because of the potential favorable effects of these therapies, it has been suggested that they should be initiated as early as possible to maximize neuroprotection [4]. Additionally, it has been recommended that patients should be monitored closely to determine whether and when it is necessary to modify treatment in order to maximize the benefit [5]. The recommended monitoring is based on annual rate of relapses, neurological deterioration, and evidence of disease activity on brain magnetic resonance imaging scans. However, given the destructive nature of the disease, if we rely solely on clinical or radiological manifestations (such as a relapse or a new lesion on a scan) to determine a patient's response to therapy, we will probably be responding too late.
Gene Expression Patterns in Affected Organs
The diagnosis and management of disease could be transformed thanks to the completion of the human genome project, the availability of sequence information for nearly every gene, and the advent of novel high throughput technologies (microarrays—see Glossary) that allow parallel profiling of thousands of genes. By definition, nearly every aspect of a disease phenotype should be represented in gene expression signatures of multiple genes in the affected organ. Indeed, studies that analyze affected tissues (mostly in cancer) clearly show that it is possible to predict prognosis, to identify new classes of diseases, and potentially to determine response to therapy [6,7,8].
Glossary
cDNA arrays: Microarrays in which the gene detectors are pieces of cDNA.
Cross-validation: A method by which an available sample is split into learning and testing sets to test classifiers.
Gene expression signature: Statistically significant changes in the expression of multiple genes that characterize (classify) a biological state.
Glatiramer acetate: A synthetic protein made of four amino acids found in myelin. It is used as an immunomodulator drug in treating MS.
IFNβ: A cytokine that is secreted from fibroblasts in response to stimulation by a live or inactivated virus or by double-stranded RNA. It is used as an immunomodulator drug in treating MS.
Microarray: A technology that allows the simultaneous profiling of the expression of thousands of genes (even whole genomes). Multiple gene detectors (oligonucleotides or cDNAs) are deposited on a slide that is hybridized with fluorescently labeled samples.
PCR (polymerase chain reaction): The exponential amplification of a DNA fragment using repeated activation of a heat-stable DNA polymerase.
Real-time PCR (also called one-step kinetic RT-PCR): A method in which the quantitation of the products of PCR is made by measuring fluorescent emission. It is used for accurate quantitation of mRNA.
RT-PCR (reverse transcription–polymerase chain reaction): PCR that is performed on cDNA generated from RNA. It is used for mRNA detection and quantitation.
Supervised classification: A process in which classifiers are learned from user-defined groups (classes).
Unsupervised classification: A process in which classifiers are learned without user-defined groups (classes), i.e., without a predefined training set.
In diseases that do not require tissue resection for diagnosis or therapy, it is rare to obtain tissues for analysis. This problem is even more pronounced in diseases like MS, in which the target organ is the very inaccessible brain and spinal cord. Despite these limitations, several groups used microarrays to analyze brain tissues obtained posthumously from patients who had MS and identified genes that characterized either acute or chronic lesions [9,10,11]. However, although these studies identified some potential genes that may be involved in the local pathogenesis of the disease, they did not produce any information that could be used for identifying biomarkers associated with disease activity.
Diagnostic Peripheral Blood Mononuclear Cell Gene Expression Signatures
In MS, looking for markers of disease activity in the much more accessible peripheral blood does not require a significant leap of faith. MS is an autoimmune disease, and it is possible that some of the cells involved in the pathogenesis of the disease will be found in the bloodstream. Abnormal T cell populations have repeatedly been observed in the peripheral blood of patients with MS [12,13,14]. While these results supported looking at the easily accessible peripheral blood mononuclear cells (PBMCs) for potential markers that reflect the disease, some doubts persisted. These revolved around two very strong arguments. The first argument was that if the signal comes from a minority of the cells within the bloodstream it will be too low to be detected. The second was that interpersonal variability, added to the inherent noisy nature of gene expression data, will make the data impossible to reproduce.
Fortunately, recent observations suggest that these doubts are unfounded. Bomprezzi et al. [15] determined that gene expression patterns can distinguish patients with MS from controls and suggested that at least some of the differences identified were derived from activated T cells. Achiron et al. [16] analyzed the expression of 12,000 genes in patients with relapsing–remitting MS. Gene expression patterns clearly distinguished patients with MS from controls as well as relapse from remission. Mandel et al. [17] compared patients with systemic lupus erythematosus and MS, and identified a common autoimmunity signature as well as disease-specific gene expression signatures. Interestingly, similar findings were recently described for pulmonary arterial hypertension [18].
Could PBMC Gene Expression Signatures Be Used for Predicting Response to Therapy?
Weinstock-Guttman et al. [19] analyzed the acute transcriptional response of 4,000 genes in peripheral blood lymphocytes to IFNβ. They identified increases in known interferon-inducible genes, and in genes involved in antiviral activity and interferon signaling. Using complementary DNA (cDNA) arrays, Sturzebecher et al. [20] identified gene expression signatures that distinguished IFNβ responders from nonresponders.
And now, in a new study published in last month's PLoS Biology, Baranzini et al. [21] provide compelling evidence that these PBMC gene expression signatures can be used to predict response to therapy (Figure 1). They studied the expression of 70 genes selected for their presumed biological function in 52 patients with MS, followed up for at least two years after initiation of IFNβ therapy. Instead of using microarrays that carry probes for thousands of genes, they chose to use real-time PCR. This method is highly sensitive, specific, and reproducible across different laboratories. It is often used to verify microarray findings. Baranzini et al. identified MX1 (interferon-inducible protein p78), a known interferon-inducible gene, as the marker of treatment with IFNβ. They did not find overall differences between responders and nonresponders, but they did, using supervised classification methods, identify triplets of genes that distinguish IFNβ responders and nonresponders.
Figure 1 Expression Levels of Three Genes in Patients Who Responded (Red) and Who Did Not Respond (Blue) to IFNβ
(Source: [21])
Interestingly, individual and pairs of genes did not perform that well, and all three genes in a triplet were required for the highest accuracy (about 80%–90%). The minimal combinatorial number of genes that contains the most predictive information is not available since combinations of more than three genes were not performed. Although the results were not tested on an independent dataset, as is frequently requested [22], the authors applied an array of cross-validation strategies that convincingly suggested that the identified predictive signal was robust.
Implications of the Study
What could Baranzini and colleagues' findings mean? Clearly, the most obvious conclusion is that the lack of response did not result from the deactivation of IFNβ. The effect of IFNβ on MX1, IFNAr1, and STAT2 was observed for two years in all patients, suggesting that the response did not depend on IFNβ bioavailability. Considering that PBMCs represent an admixture of multiple cell types, the most plausible explanation is a simple lack of shift in subcellular populations.
However, the importance of Baranzini and colleagues' study lies not in its mechanistic insights, but in its clinical relevance. The careful design of the experiment, the use of reproducible real-time PCR instead of microarrays, the meticulous analysis, and the previous observations [15,16,17,19,20] support the notion that PBMCs express clinically relevant gene expression signatures in MS and probably in other organ-confined diseases. To further prove this notion will require a significant investment in large studies that prospectively test the utility of these signatures in guiding the management of MS. Only when direct evidence shows that therapy guided by markers expressed in PBMCs improves patient outcome will PBMC gene expression patterns take their place as biomarkers at the center stage of monitoring MS progression and response to therapy.
Citation: Kaminski N, Achiron A (2005) Can blood gene expression predict which patients with multiple sclerosis will respond to interferon? PLoS Med 2(2): e33.
Abbreviations
cDNAcomplementary DNA
IFNβinterferon β
MSmultiple sclerosis
PBMCperipheral blood mononuclear cell
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References
Hafler DA Multiple sclerosis J Clin Invest 2004 113 788 794 15067307
Billiau A Kieseier BC Hartung HP Biologic role of interferon beta in multiple sclerosis J Neurol 2004 251 Suppl 2 II10 II14 15264107
Wolinsky JS Glatiramer acetate for the treatment of multiple sclerosis Expert Opin Pharmacother 2004 5 875 891 15102570
Freedman MS Blumhardt LD Brochet B Comi G Noseworthy JH International consensus statement on the use of disease-modifying agents in multiple sclerosis Mult Scler 2002 8 19 23 11936483
Freedman MS Patry DG Grand'Maison F Myles ML Paty DW Treatment optimization in multiple sclerosis Can J Neurol Sci 2004 31 157 168 15198439
Kaminski N Krupsky M Gene expression patterns, prognostic and diagnostic markers, and lung cancer biology Chest 2004 125 111S 115S
Gascoyne RD Emerging prognostic factors in diffuse large B cell lymphoma Curr Opin Oncol 2004 16 436 441 15314511
Cleator S Ashworth A Molecular profiling of breast cancer: Clinical implications Br J Cancer 2004 90 1120 1124 15026788
Whitney LW Becker KG Tresser NJ Caballero-Ramos CI Munson PJ Analysis of gene expression in mutiple sclerosis lesions using cDNA microarrays Ann Neurol 1999 46 425 428 10482277
Lock C Hermans G Pedotti R Brendolan A Schadt E Gene-microarray analysis of multiple sclerosis lesions yields new targets validated in autoimmune encephalomyelitis Nat Med 2002 8 500 508 11984595
Chabas D Baranzini SE Mitchell D Bernard CC Rittling SR The influence of the proinflammatory cytokine, osteopontin, on autoimmune demyelinating disease Science 2001 294 1731 1735 11721059
Santoli D Moretta L Lisak R Gilden D Koprowski H Imbalances in T cell subpopulations in multiple sclerosis patients J Immunol 1978 120 1369 1371 305941
Huddlestone JR Oldstone MB T suppressor (TG) lymphocytes fluctuate in parallel with changes in the clinical course of patients with multiple sclerosis J Immunol 1979 123 1615 1618 314466
Hafler DA Fox DA Manning ME Schlossman SF Reinherz EL In vivo activated T lymphocytes in the peripheral blood and cerebrospinal fluid of patients with multiple sclerosis N Engl J Med 1985 312 1405 1411 2985995
Bomprezzi R Ringner M Kim S Bittner ML Khan J Gene expression profile in multiple sclerosis patients and healthy controls: Identifying pathways relevant to disease Hum Mol Genet 2003 12 2191 2199 12915464
Achiron A Gurevich M Friedman N Kaminski N Mandel M Blood transcriptional signatures of multiple sclerosis: Unique gene expression of disease activity Ann Neurol 2004 55 410 417 14991819
Mandel M Gurevich M Pauzner R Kaminski N Achiron A Autoimmunity gene expression portrait: Specific signature that intersects or differentiates between multiple sclerosis and systemic lupus erythematosus Clin Exp Immunol 2004 138 164 170 15373920
Bull TM Coldren CD Moore M Sotto-Santiago SM Pham DV Gene microarray analysis of peripheral blood cells in pulmonary arterial hypertension Am J Respir Crit Care Med 2004 170 911 919 15215156
Weinstock-Guttman B Badgett D Patrick K Hartrich L Santos R Genomic effects of IFN-beta in multiple sclerosis patients J Immunol 2003 171 2694 2702 12928423
Sturzebecher S Wandinger KP Rosenwald A Sathyamoorthy M Tzou A Expression profiling identifies responder and non-responder phenotypes to interferon-beta in multiple sclerosis Brain 2003 126 1419 1429 12764062
Baranzini SE Mousavi P Rio J Caillier SJ Stillman A Transcription-based prediction of response to IFNâ using supervised computational methods PLoS Biol 2004 3 e2 15630474
De Jager PL Hafler DA Gene expression profiling in MS: What is the clinical relevance? Lancet Neurol 2004 3 269 15099539
| 15736992 | PMC549584 | CC BY | 2021-01-05 10:39:34 | no | PLoS Med. 2005 Feb 22; 2(2):e33 | utf-8 | PLoS Med | 2,005 | 10.1371/journal.pmed.0020033 | oa_comm |
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PLoS MedPLoS MedpmedplosmedPLoS Medicine1549-12771549-1676Public Library of Science San Francisco, USA 1573699310.1371/journal.pmed.0020034Research in TranslationAllergy/ImmunologyRespiratory MedicineToxicology/Environmental HealthAsthmaImmunology and AllergyEpidemiologyEnvironmental HealthAsthma Severity and Prevalence: An Ongoing Interaction between Exposure, Hygiene, and Lifestyle Research in TranslationPlatts-Mills Thomas A. E Thomas A.E. Platts-Mills is Professor of Medicine at the University of Virginia Asthma and Allergic Diseases Center, Charlottesville, Virginia, United States of America. E-mail: [email protected]
Competing interests: The author declares that he has no competing interests.
2 2005 22 2 2005 2 2 e34Copyright: © 2005 Thomas A. E. Platts-Mills.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.Why are the prevalence and severity of asthma increasing? Platts-Mills looks at the key studies that can help to anwer this important question
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Over the last hundred years, there have been major triumphs in medicine related to public health, vaccination, and the introduction of new medicines. However, over the same period, several diseases have increased in prevalence and/or severity. In some cases, the causes of the increase have become obvious—the increases in lung cancer, coronary artery disease and type 2 diabetes, for example, are not considered to be a mystery. On the other hand, a large group of diseases related broadly to “inflammation” have also increased. For these, a wide range of hypotheses about causation have been proposed. Type 1 diabetes, rheumatoid arthritis, and inflammatory bowel disease have increased since 1980 [1]. Some analyses of the increase in hay fever and asthma would suggest a similar time course, and this parallelism of the time frame has been taken to suggest that there could be a common cause. Indeed, there is a proposal that these diseases are all related to some changes in “cleanliness” or “hygiene” that have resulted in decreased activation of a common control mechanism. Specifically, this control has been ascribed to T regulator cells, which produce interleukin-10 (IL-10) or transforming growth factor-beta.
Change in Living Conditions
The major changes in rural areas, tropical villages or in Europe pre-1900 that could be related to the change in immune responses include: decreases in helminth infection; physical proximity to farm animals [2]; exposure to those mycobacteria that are commonly found in the soil; bifidobacteria colonization of the gut; as well as decreased prevalence of Hepatitis A infection [3]. The implication in each case is that asthma has increased secondary to an increase in inflammation or an increase of the allergic response that is closely associated. This assumes that hay fever, asthma, and other diseases have increased in parallel, which is probably not true.
Hay fever became a problem in Northern Germany and England as early as 1900. Clear evidence for this view comes from Noon's description of the development of immunotherapy for hay fever in 1911, the studies on hay fever prevalence by Ratner and Silverman in New York in 1935, and the recognition that hay fever was a major community problem in New York in 1946. More recently, Harold Nelson analyzed all the studies on hay fever published in the United States and found a prevalence of ~15% in 1960, with no convincing evidence of an increase since then (H. Nelson, personal communication).
If seasonal hay fever was epidemic in 1960, then the subsequent increase in asthma has to be seen in a different light. The best estimates for the start of the asthma epidemic are around 1960 for such diverse populations as army recruits in Finland [4], school children in Birmingham in the United Kingdom, and African American children in Charleston, South Carolina, United States [5]. In each of these studies, the increase in asthma symptoms or disease has been greater than tenfold. However, the absolute values of the change have been dramatically different in New Zealand and Scotland (from ~2% up to 20%) compared with Finland (from 0.2% to 4%) [6]. Furthermore, some countries have experienced much greater increases in hospitalization than others. Clear evidence for increases in mortality has only come from the United Kingdom, New Zealand, and the United States, countries with a high prevalence of symptoms and hospitalization.
Several hypotheses have been proposed to explain the increase in asthma (Box 1). At this point, our questions about the increase in asthma are: 1) Is an increase in allergy or hay fever a necessary precursor for the increase in asthma, a parallel event, or separate? 2) Why did the increase in asthma have such a consistent time course throughout the Western world in countries where changes in infectious diseases have occurred very differently? and 3) Why is asthma more common and more severe in some countries than in other countries that have had an equal scale of increase (i.e., tenfold) over the same time course?
Box 1. Hypotheses about the Cause of the Increase in Asthma: Arguments For and Against
Hypothesis 1: Increased exposure to perennial allergens, e.g., dust mites
For:
(A) Housing changes: houses are built more tightly and are more well insulated; more furnishings; fitted carpets, and (B) more time spent indoors. Increased exposure leads to increased sensitization.
Against: Increases in asthma have been seen in countries where dust mites are not present in homes, and in the Netherlands the concentration of mite allergens has actually decreased by as much as tenfold over the past 15 years
Hypothesis 2: Changed immune responsiveness is due to cleanliness
For:
(A) Bacterial and other infections have decreased due to improved hygiene, immunization, and antibiotics, and (B) changed gut flora (antibiotics, diet, etc.). Change from Th1 to Th2 leads to increased allergy.
Against: In New York City, the increase in seasonal hay fever occurred 30 years before the increase in asthma, and in Africa, children whose families move into cities, including informal settlements, have experienced increases in infections, wheezing, and diagnosed asthma
Hypothesis 3: Loss of a lung-specific protective effect, 1960–2000
For:
(A) Changing diet leads to a changed inflammatory response, and (B) decline in physical exercise. Increased wheezing among allergic children.
Against: This is unlikely to be just be a lung-specific effect
The Persistent Association between Specific IgE, Total IgE, and Asthma
Long before the first case control or prospective study, the association between allergy and asthma was obvious in case series. These earlier studies reported skin testing with an amorphous extract called “house dust,” but it was not until the identification of dust mites that the association was clarified [7]. Indeed, as late as 1978, there were significant doubts that allergens played a role in asthma. Using extracts of Dermatophagoides pteronyssinus (dust mites), the strong association between this allergen and asthma was established in many parts of the world, with odds ratios as high as 6 or even 10 [7,8]. The possibility of a causal relationship was further supported by bronchial challenge studies and avoidance experiments [9]. The cohort in Poole, Dorset was, until recently, the only study with household measurements of allergen and the results strongly suggested that exposure in the child's own house was the primary determinant of sensitization [8]. Subsequently, studies from other parts of the world provided evidence about other indoor allergens, particularly cats, dogs, and the German cockroach [10,11]. These studies showed that perennial exposure to allergens was an important cause of inflammation in the lungs and associated nonspecific bronchial hyperreactivity (Figure 1). In most of the case-control and prospective studies, sensitization to seasonal pollens has not been significantly associated with asthma [7]. This is an important issue; if allergy is associated with asthma for genetic reasons or because of some common immunological feature, it is not clear why the association should be with perennial allergens only.
Figure 1 Sensitization, Inflammation, and Wheezing
Increases in prevalence/severity of asthma (reversible airway obstruction) could occur because of changes in different parts of the hypersensitivity and inflammatory response in the lungs. The Roman numerals refer to the three hypotheses in Box 1.
Since assays for total serum IgE became available in the 1970s, it has been clear that patients with asthma have, on average, higher total IgE than patients with hay fever or no allergy. Indeed, by 1980 this was considered an established fact in textbooks of immunology. It was assumed that the increased total IgE related to allergen-specific responses. However, in some studies, the association between total IgE and asthma was stronger than the association between asthma and specific IgE. In 1989, Burrows et al. went further and suggested that specific IgE correlated with hay fever, while total IgE correlated with asthma [12]. The implication was that IgE has a complex relationship with asthma that is not dependent on specific allergens.
The strength of the association between asthma and total IgE raises questions that have not been resolved. Do specific IgE antibody responses contribute to or even push total IgE? If so, do the IgE antibody responses to some allergens have more effect than others? This question is relevant both to attempts to explain major differences in total IgE between countries and to studies on acute asthma. In emergency room and hospital studies, the geometric mean total serum IgE of patients with asthma is often greater than 200 IU/ml higher than values found in population-based studies. Recent work from Heymann et al. and Green et al. on patients hospitalized for asthma has suggested that the interaction between rhinovirus and allergy occurs predominantly among patients with total IgE > 200 IU/ml [13]. Thus, the different properties of allergens could influence both the prevalence and severity of asthma. However, the properties of the dominant allergens do not explain the overall increase in prevalence, which has occurred in countries with very different houses, climates, and traditions of domestic pet ownership.
The Paradoxical Relationship between Cat Ownership and Sensitization: Significance for Prevalence or Severity
Antigen exposure is considered to be a primary requisite for immune responses, and allergen-specific responses are no exception. There are many examples of allergens that are not significant in areas where the allergen is not encountered. For example, the pollen of olive trees is not relevant in northern countries, dust mite allergens are not significant in the northern part of Scandinavia or the mountain states of the United States, and cockroach allergens are not significant in suburban areas of the United States, the United Kingdom, or New Zealand.
For dust mites, there is a wide range of evidence that increased exposure increases sensitization. Homes in Sweden, Berlin, the United Kingdom, and New Zealand have progressively higher concentrations of mite allergen and progressively higher prevalence of sensitization to mite allergens [7]. But there is now evidence that increasing exposure to cats does not lead to a higher prevalence of allergy [14,15,16]. On a population basis, the effect may be profound; sensitization to cats among school-age children is generally ~10%, while mite sensitization is often as high as 30% (Figure 2). This effect cannot be ascribed to inadequate exposure, since all estimates of the quantity of cat allergen inhaled are higher than for dust mites. Furthermore, the quantity of cat allergen found in schools or even in houses without cats is sufficient to sensitize at-risk children [11].
Figure 2 Contrast between Exposure to Dust Mite or Cat Allergens and the Relevant Immune Responses
The dashed line indicates the approximate value of 20 mg Fel d 1/g floor dust or the presence of a cat.
In fact, children raised in a house with a cat were less likely to be sensitized to cats [15]. Initially, it seemed possible that the effect was an example of reverse causation. However, the effect has been observed in countries where a large proportion of families keep cats, and very few families report choosing not to own a cat because of asthma in the family. Furthermore, the presence of a cat in a house in New Zealand does not decrease IgE antibody response to dust mites—in other words, tolerance to cats can be cat-specific [17]. Understanding how the response to cat allergen is controlled could provide an insight into how both the prevalence and the titre of IgE antibody responses in general are (or should be) controlled. It seems inevitable that the primary control is by T cells specific for cat allergens. Indeed, there is already excellent evidence that injection of peptides derived from the cat allergen Fel d 1, which give T cell responses, can be used for immunotherapy [18]. Studying overlapping peptides of Fel d 1, we identified a striking response to two peptides at the terminal end of Chain 2. Furthermore, both allergic and tolerant individuals respond to these peptides by producing IL-10 and interferon gamma [19]. The implication is that Fel d 1 inherently induces control, and that this control influences both allergic and non-allergic responses to cat allergen (Figure 3). In keeping with this, IgE antibody responses to cat allergen are not quantitatively as high as those to dust mites [17].
Figure 3 Mechanisms of T Cell Control over the Hypersensitivity Response to Cat Allergen
The response to cat allergen, Fel d 1, includes T cells that produce high levels of IL-10 that have some of the features of the T regulator one cells (Tr1). However, these cells appear to be a feature of both allergic and non-allergic responses, implying that the whole response to cat allergen is controlled. Some of the effects of cat exposure may need to occur early, but other studies suggest strongly that the different responses can change following a prolonged change in exposure late in life.
One of the central assumptions of the cleanliness hypothesis is that regulation of immune responses is, at least in part, non-specific. It is assumed that helminth infection, mycobacteria, Hepatitis A, endotoxin, and early-life infections can create a milieu that leads to a decrease in allergic responses in general. Likewise, we might expect that exposure to high concentrations of cat allergen, which can induce IL-10 producing cells, should have a general effect. There is some evidence for this hypothesis. In Detroit, the presence of two or more animals in the house tended to reduce allergy in general. In Sweden, the presence of a cat in the house is associated with decreased sensitization to cat, and also to birch and dog. However, in the United States and New Zealand, the presence of a cat in the home has no effect on the prevalence or titre of IgE antibody to dust mites [15,17]. Thus, it is clear that under some circumstances the tolerance to cats can occur in highly atopic individuals and be cat-specific. This phenomenon is not in keeping with any version of the cleanliness hypothesis. It has been proposed that animals in the home could have a non-specific effect because they shed or encourage endotoxin. However, recent studies on airborne endotoxin found that the presence of cats had no effect, and that there were significantly lower endotoxin levels in houses with cats compared to dogs.
The Possible Role of Lifestyle Changes
Over the last half of the 20th century, there have been major changes in diet and physical activity. The most obvious result of these changes is an increase in obesity, which has reached epidemic proportions in the United States. Since 1994, there have been multiple reports of an association between elevated body mass index (BMI) and asthma [20]. In 1996, we suggested that changes in physical activity could be related to bronchospasm [21]. Thus, there are three distinct but strongly interrelated aspects of lifestyle that could be relevant to the prevalence and severity of asthma: diet, physical activity, and obesity.
It is much easier to document BMI than diet or physical activity, and although some of the obesity data are convincing, they are not consistent and certainly not comparable to the association between obesity and diseases such as type 2 diabetes in childhood. In a typical study, Camargo et al. found that the prevalence of wheezing was 13% among the heaviest quintile and 7% among the lowest quintile for BMI [22]. Comparable values for type 2 diabetes would be 5% and 0.1%.
Studies using questionnaires have attempted to ask whether there is a relationship between wheezing and physical activity. However, the track record for questionnaires on this subject is very poor. Westerterp and his colleagues have reported two observations: first, that general activity contributes more to energy consumption than “aerobic exercise” does and second, that many subjects who initiate an exercise program (such as a twice weekly visit to the gym) overcompensate so that they actually decrease overall activity [23]. Recently, we have documented a decrease in activity among children (age ~4 years) in the United States Head Start program (a child-development program that aims to increase the school-readiness of young children in low-income families) who have a history of wheezing [24]. Although there are several possible explanations for this result, it seems clear that decreased activity can be present before elevated BMI.
The next question to ask is whether physical activity would have a beneficial effect on asthma? Fredburg concluded that full expansion of the lungs had a more potent effect on bronchial smooth muscle than isoprenaline [25]. Togias and his colleagues have shown that prolonged shallow breathing (=20 minutes) can lead to increased non-specific bronchial reactivity [26]. It is obvious that expansion of the lungs is decreased during prolonged periods of sitting down. However, periodic expansion of the lungs occurs with sighs. Recent data from our group shows that “sigh rates” while seated are very variable but are significantly lower when watching a video than while reading [27]. Thus there is a real possibility that some forms of childhood behavior—TV, videos, computer games, etc.—might be associated with sigh rates low enough to increase non-specific bronchial hyperreactivity.
A different explanation for the effects of physical activity comes from evidence that physical activity can be “anti-inflammatory.” This evidence relates to several different models though not at present to the lungs. In some studies, obesity appears to be a risk factor for wheezing among non-allergic children. However, in most studies, the association between allergen sensitization and asthma has been found in obese and non-obese children equally [28]. Obviously, some obese individuals are unfit and become breathless on exercise. In addition, these individuals may have sleep-disordered breathing. Thus, there are other conditions that are easily confused with exercise-induced asthma or nocturnal asthma. Taken together, there are excellent reasons for asking whether lifestyle changes have contributed to the increased prevalence or severity of asthma. However, it seems unlikely that this effect occurs on normal lungs, so the hypothesis has to be that decreased physical activity in patients who are allergic can allow persistent or increased severity of wheezing.
Conclusions
Although the explanation for the increase in asthma is not yet clear, it is possible to put forward a model that includes elements of each of the three main hypotheses. Children raised in the tropics, on farms, or in villages such as those in Africa or Papua New Guinea have exposure to endotoxin or infections sufficient to interfere with the development of allergen-specific IgE antibody responses. Once water supplies are clean, and major infectious diseases have been controlled, allergic diseases will appear.
However, asthma appears to be associated with perennial, i.e., indoor exposure, and may be more common or more severe in countries where mites or cockroaches are the major source of allergens. Even with indoor allergen exposure, wheezing may remain transient or mild, provided prolonged outdoor play is normal. It is the combination of the control of infectious diseases, prolonged indoor exposure, and a sedentary lifestyle that is the key to the asthma epidemic and, in particular, the key to the rise in severity. Using this analysis, the severity of asthma in North American cities becomes much easier to explain. Children in New York, Atlanta, Philadelphia, and Washington, D.C. spend long hours indoors, have high exposure to mite, cockroach, and/or rodent allergens, and have very low levels of physical activity.
In conclusion, it appears that these combined factors are the key to the asthma epidemic and, in particular, the key to the rise in severity. We clearly need to develop ways to increase prolonged physical activity, both among patients with asthma and in the general population. We also need to investigate whether prolonged moderate activity is beneficial in the treatment of asthma and/or is “anti-inflammatory.” What is equally clear is that the current obsession of the medical profession with the pharmaceutical management of asthma (as well as other lifestyle-related diseases) does not address the reasons why the disease has become so common and so severe.
Citation: Platts-Mills TAE (2005) Asthma severity and prevalence: An ongoing interaction between exposure, hygiene, and lifestyle. PLoS Med 2(2): e34.
Abbreviations
BMIbody mass index
IL-10interleukin-10
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| 15736993 | PMC549585 | CC BY | 2021-01-05 11:13:37 | no | PLoS Med. 2005 Feb 22; 2(2):e34 | utf-8 | PLoS Med | 2,005 | 10.1371/journal.pmed.0020034 | oa_comm |
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PLoS MedPLoS MedpmedplosmedPLoS Medicine1549-12771549-1676Public Library of Science San Francisco, USA 1573699410.1371/journal.pmed.0020037Research ArticleHIV/AIDSHIV Infection/AIDSMedicine in Developing CountriesIndividual Level Injection History: A Lack of Association with HIV Incidence in Rural Zimbabwe Injections and HIV in ZimbabweLopman Ben A
1
*Garnett Geoff P
1
Mason Peter R
2
Gregson Simon
1
2
1Department of Infectious Disease Epidemiology, Faculty of MedicineImperial College LondonUnited Kingdom2Biomedical Research and Training InstituteHarareZimbabweBinagwaho Agnes Academic EditorCommission Nationale de Lutte contre le SIDARwanda
Competing Interests: GPG has acted as a consultant for and/or received grants from GlaxoSmithKline, Aventis Pasteur, Merck, and Abbott Pharmaceuticals. GPG also chaired a meeting of the World Health Organization in 2003 to develop a consensus on the importance of unsafe injections in HIV epidemiology. SG owns shares in GlaxoSmithKlineBeecham and Astra Zeneca.
Author Contributions: GPG and SG designed the study. PRM organised testing of samples for HIV. BAL, GPG, PRM, and SG analyzed the data and contributed to writing the paper.
*To whom correspondence should be addressed. E-mail: [email protected] 2005 22 2 2005 2 2 e3719 10 2004 16 12 2004 Copyright: © 2005 Lopman 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.
Injections and HIV in Rural Zimbabwe
Background
It has recently been argued that unsafe medical injections are a major transmission route of HIV infection in the generalised epidemics of sub-Saharan Africa.
Methods and Findings
We have analysed the pattern of injections in relation to HIV incidence in a population cohort in Manicaland in a rural area of Zimbabwe. In Poisson regression models, injections were not found to be associated with HIV in males (rate ratio = 0.33; 95% confidence interval: 0.07 to 1.46) or females (rate ratio = 1.04; 95% confidence interval: 0.59 to 1.85).
Conclusion
It is important that unsafe medical injections can be confidently excluded as a major source of HIV infection. In rural Zimbabwe the evidence is that they can.
A debate is raging over whether unsafe medical injections are an important cause of HIV infection in Africa; in rural Zimbabwe evidence suggests they are not
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Introduction
The widely held belief that heterosexual transmission is the driving force behind sub-Saharan Africa's (SSA's) HIV epidemic [1] has recently been questioned [2]. According to Gisselquist and colleagues, investigators have overlooked the importance, and indeed suppressed analysis, of unsafe medical injections as a route of transmission for HIV. Hitherto, assessments of this hypothesis have largely relied on ecological analyses—relating population-level data on unsafe injections to the distribution of HIV prevalence [3,4]. The absence of investigation into the role of unsafe injections, based on the assumed predominance of sexual transmission, has rightly been criticised. However, this criticism trivialises the difficulty of collecting and analysing relevant field data.
Presently, the only published data on the possible contribution of injections to HIV transmission in SSA come from rural Uganda, where Kiwanuka et al. demonstrated no association of injections with HIV incidence [5]. Data from other SSA countries with generalised epidemics where spread has varied in scale and pattern are required to inform this debate.
In this paper, we analyse data from a population cohort in Manicaland in rural Zimbabwe. We describe the determinants of injections in adults and then test the association between injections and incidence of HIV infection.
Methods
Data were analysed from the baseline (1999/2000) and follow-up (2002/2003) rounds of a cohort of adults in the Manicaland HIV/STD Prevention Study. Eligible men and women aged 15 to 54 were recruited based on an initial household survey [6]. In response to the awakening controversy, a question exploring exposure to injection was added two-thirds of the way through follow-up. Thus, data were available from individuals from four of the 12 study sites. In these sites, 505 males and 1,342 females were interviewed, representing a follow-up of 69.7% of individuals interviewed at baseline. The subset of individuals who were HIV-negative at baseline (n = 1,606; 83.6%) was used for all analyses except for the examination of rates of injections stratified by HIV status at baseline.
At follow-up, participants were asked whether they had received an injection or had been pricked by a needle since the baseline interview. A range of health and socio-demographic data were also collected, including self-reported history of sexually transmitted disease (STD) symptoms. Reports on STD symptoms were from the 1-y period before the follow-up interview, and thus did not correspond to the entire 3-y follow-up period. HIV serological testing was performed on dried blood spots using a highly sensitive and specific antibody dipstick assay [7].
Ethical approval for this study was granted by the Medical Research Council of Zimbabwe (MRCZ/A/681) and the Applied and Qualitative Research Ethics Committee, Oxford University, United Kingdom (N97.039). Written informed consent was sought from study participants.
The objective of this analysis was to test the plausibility that injections are an important risk factor for HIV incidence. Having received an injection was modelled as a proximate cause with demographic variables, sexual behaviour, and STDs acting as potential confounders. Determinants of injections were analysed with univariable and multivariable Poisson regression models of incidence rate ratios (RRs). Attributes were retained in age-adjusted multivariable models if the stratum-specific RR differed from one and had a Wald-test p-value ≤ 0.1. Using the same strategy, models were then fitted with HIV as the outcome variable.
Results
Overall, 744 out of 1,847 individuals (40.3%) reported having received an injection or needle prick during the 3-y follow-up period. Females reported more injections than males (RR = 1.93). Rates were not significantly higher for individuals who were HIV positive at baseline (RR = 1.07, p = 0.81 for males; RR = 1.13, p = 0.28 for females) (Table 1).
Table 1 Univariable and Multivariable Poisson Regression Models of Incidence of Injections and Needle Pricks—Presented Separately for Males and Females
Reported injections and person years may not add up across different attributes because of missing data
a Adjusted for age and attributes significant at p ≤ 0.1 (Wald test)
b Exposure between baseline and follow-up (approximately 3 y)
c Exposure in the 1 y prior to follow-up
d Not significant but shown to demonstrate the direction of effect
CI, confidence interval; PYAR, person years at risk
Being widowed, separated, or divorced was the only attribute associated with increased rates of injections for males (Table 1). For females, STD symptoms and childbearing/pregnancy were significant in adjusted models (Table 1).
There were 67 HIV seroconversions (48 females and 19 males); 13 (19%) of those seroconverting reported not having had sex in the inter-survey period, and 40 (60%) reported not having had an injection during the period (Table 2).
Table 2 Univariable and Multivariable Poisson Regression Models of HIV Incidence—Presented Separately for Males and Females
Seroconversions and person years may not add up across different attributes because of missing data
a Adjusted for age and attributes significant at p ≤ 0.1 (Wald test)
b Exposure between baseline and follow-up (approximately 3 y)
c Not significant but shown to demonstrate the direction of effect
d Exposure in the 1 y prior to follow-up
CI, confidence interval; PYAR, person years at risk
There was no significant association between injections and HIV incidence among either males or females—in either unadjusted or adjusted models. For males, HIV seroconversion rates were elevated amongst 25- to 44-y-olds, sexually active individuals, and those who had suffered STD symptoms, though none of these attributes reached levels of statistical significance (Table 2). For females, having multiple sexual partners, having STD symptoms, and being widowed/separated/divorced were associated with increased HIV incidence. Childbearing/pregnancy, which was strongly associated with injections (see Table 1), had no association with HIV incidence (Table 2).
Discussion
These data, from a population cohort in rural Zimbabwe, suggest that—at the population level—injections are not a major route of HIV transmission. There was a very slight, non-significant association between injections and HIV amongst females. Could this association achieve significance with a greater sample size or more events? Given the strong association between STD symptoms and both injections and HIV incidence, this is possible, but would likely be a result of residual confounding. In other words, both HIV and injections have a common association with STDs. It has been argued that the association between sexual activity and HIV is confounding between STDs and pregnancy and injections and that it is the injections that are causal. Our analysis does indeed find these associations—but finds STD symptoms the strongest predictor of new HIV infections.
Our measure of injection risk is unambiguous but lacks many dimensions relating to unsafe injections. Presently, we have collected data about the receipt of injections and other needle pricks. Thus, the exposures in these analyses are not restricted to injections received from the health-care sector—the source that Gisselquist et al. originally hypothesized as a major route of transmission [2]. Also, these data reflect only whether an individual had an injection or not—rather than the number of injections received. World Health Organization estimates suggest that the number of injections people receive is not evenly distributed in SSA populations [8].
Thirteen of 67 individuals seroconverting in this study reported no sexual partners in the inter-survey period. Only four of these 13 reported never having had sex. This leads us to suspect that incorrect categorisation of HIV status at baseline in addition to misreporting of sexual behaviour may explain some of these infections: it is possible that a proportion of the nine individuals who reported having had sex in their lifetime but not in the inter-survey period had been recently infected but had not yet seroconverted at the time of the baseline testing [9]. In this scenario, their exposure would have occurred prior to baseline, rather than in the follow-up period. Recall biases may also play a role, given the relatively long follow-up of 3 y [10]. Non-regular partners, especially those from the beginning of the recall period, may have been under-reported. Eliciting accurate reporting of sexual activity is notoriously difficult in Africa and elsewhere, though the use of informal confidential voting interviews has decreased social desirability biases in this cohort [11]. Nonetheless, the cases (n = 4) where individuals seroconverted who had reported never having had sex may still be a product of social desirability reporting bias. Clearly, incidence data offer the most explanatory power in elucidating the determinants of the HIV epidemic, but these anomalous cases also highlight the difficulties of collecting time-varying sexual behaviour and serostatus information.
Interestingly, in light of expected HIV-associated disease and care, individuals who were HIV positive at baseline did not have higher rates of injections than individuals who were HIV negative. Injections were found to be highly associated with childbirth/pregnancy. HIV-positive women—and especially those at advanced stages of infection—are known to experience reduced fertility [12]. Therefore, a reduction in use of maternal health services may partially explain why injections were not more common in the HIV-positive population. A more discriminating measure of exposure, including the reason for injection, could help to explain this observation.
Had injections proven to be a risk factor for HIV incidence, further investigations would have been needed to determine the source and types of risky needle pricks. However, no such association was found. Unsafe injections are unacceptable, but this evidence suggests that they do not play a major role in the transmission of HIV in rural Zimbabwe.
Patient Summary
Background
There is a lot of controversy over whether the spread of HIV in sub-Saharan Africa is predominantly caused by unsafe sexual practices, or whether unsafe medical injections given by health professionals might also have a prominent part to play. A recent paper suggested that unsafe medical injections were important.
What Did the Authors Do?
In an ongoing survey in rural Zimbabwe between 1999/2000 and 2002/3 that was trying to assess why some individuals get infected with HIV, the authors asked 505 men and 1,342 women a number of questions. They asked them about their sexual history, whether they had children, and whether they received injections. They tested the adults for HIV at the beginning and end of the study period.
What Did They Find?
744 people had had a medical injection and 67 people acquired HIV. There was no evidence overall that injections were linked with an increase in HIV infection. The strongest link with HIV infection was with symptoms of sexually transmitted diseases (in other words, people with these symptoms were more likely to acquire HIV infection).
What Do These Findings Mean?
These findings suggest that although it is still possible for an individual to get HIV through unsafe medical injections, overall in this population in Zimbabwe, unsafe injections are not an important cause of HIV infection. Hence policymakers should concentrate more on trying to prevent infection from unsafe sex.
Where Can I Get More Information?
Information on safe sex: http://www.thebody.com/safesex.html
World Health Organization Web page on reducing the risk of HIV infection in drug users who inject drugs intravenously: http://www.who.int/hiv/topics/harm/reduction/en/
Fact sheet from the Joint United Nations Programme on HIV/AIDS on HIV/AIDS in Zimbabwe: http://www.unaids.org/html/pub/publications/fact-sheets01/Zimbabwe_en_pdf.htm
We thank the Wellcome Trust, the Joint United Nations Programme on HIV/AIDS, and Center for Disease Control Zimbabwe for support of the Manicaland HIV/STD Prevention Project. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Citation: Lopman BA, Garnett GP, Mason PR, Gregson S (2005) Individual level injection history: A lack of association with HIV incidence in rural Zimbabwe. PLoS Med 2(2): e37.
Abbreviations
RRrate ratio
SSAsub-Saharan Africa
STDsexually transmitted disease
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| 15736994 | PMC549586 | CC BY | 2021-01-05 10:39:29 | no | PLoS Med. 2005 Feb 22; 2(2):e37 | utf-8 | PLoS Med | 2,005 | 10.1371/journal.pmed.0020037 | oa_comm |
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PLoS MedPLoS MedpmedplosmedPLoS Medicine1549-12771549-1676Public Library of Science San Francisco, USA 1573699510.1371/journal.pmed.0020038Research ArticleInfectious DiseasesEpidemiology/Public HealthPediatricsRespiratory MedicineInfectious DiseasesPneumoniaPediatricsGlobal healthUse of Procalcitonin and C-Reactive Protein to Evaluate Vaccine Efficacy against Pneumonia Prevention of PneumoniaMadhi Shabir A
1
2
*Heera Jayvant R
1
2
Kuwanda Locadiah
1
Klugman Keith P
1
3
1National Health Laboratory Service/University of the Witwatersrand/Medical Research Council Respiratory and Meningeal Pathogens Research Unit, University of the WitwatersrandJohannesburgSouth Africa2Paediatric Infectious Diseases Research Unit, Wits Health ConsortiumUniversity of the Witwatersrand, JohannesburgSouth Africa3Department of International Health, Rollins School of Public Healthand Division of Infectious Diseases, School of Medicine, Emory University, Atlanta, GeorgiaUnited States of AmericaDagan Ron Academic EditorSoroka University Medical Center and Ben-Gurion University of the NegevIsrael
Competing Interests: The phase 3 study was supported by a grant from Wyeth-Lederle Vaccines and Pediatrics. SAM has received previous research support and consultancy fees from Wyeth Vaccines and Pediatrics. KPK has received previous research support and consultancy fees from Aventis, Bayer, GlaxoSmithKline, ID Biomedical, Oscient, Roche, and Wyeth-Ayerst.
KPK is a member of the Editorial Board of PLoS Medicine.
Author Contributions: SAM, JRH, and KPK designed the study. SAM, JRH, LK, and KPK analyzed the data and contributed to writing the paper.
*To whom correspondence should be addressed. E-mail: [email protected] 2005 22 2 2005 2 2 e3827 9 2004 17 12 2004 Copyright: © 2005 Madhi 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.
Towards Better Evaluation of Pneumococcal Vaccines
Background
Pneumonia remains the leading cause of death in young children. The poor specificity of chest radiographs (CXRs) to diagnose pneumococcal pneumonia may underestimate the efficacy of pneumococcal conjugate vaccine in preventing pneumococcal pneumonia.
Methods and Findings
The efficacy of nine-valent pneumococcal conjugate vaccine among children not infected with HIV (21%; 95% confidence interval, 1%–37%) increased when CXR-confirmed pneumonia was associated with serum C-reactive protein of 120 mg/l (12mg/dl) or more and procalcitonin of 5.0 ng/ml or more (64%; 95% confidence interval, 23%–83%). Similar results were observed in children infected with HIV.
Conclusion
C-reactive protein and procalcitonin improve the specificity of CXR to diagnose pneumococcal pneumonia and may be useful for the future evaluation of the effectiveness of pneumococcal conjugate vaccine in preventing pneumococcal pneumonia.
Adding two blood measurements to the standard X-ray exam might lead to more specific diagnoses for pneumococcal pneumonia and allow more accurate estimate of the efficacy of pneumococcal vaccines
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Introduction
While pneumonia remains the leading cause of death in children, the absence of sensitive and specific tools to make an etiological diagnosis is a major limitation to our understanding of the efficacy of vaccines against pneumonia. Blood cultures lack sensitivity, and cultures from lung aspirates may be influenced by delayed presentation, antecedent antibiotic therapy, difficulties finding an accessible site to aspirate, lack of skills in performing the procedure, and the perception of both parents and clinicians that the procedure is too invasive [1,2].
Procalcitonin, at a low threshold (≥0.25 ng/ml), has been shown to be useful in directing the use of antibiotics in adults with pneumonia [3], and a recent meta-analysis concludes that procalcitonin may offer some advantages over C-reactive protein (CRP) for discriminating bacterial from nonbacterial infections [4]. Most studies support the observation that children with bacterial infections have higher levels of CRP and procalcitonin than those with viral infections [4,5,6]. Our recent observation that many children with viral-associated pneumonia have a bacterial super-infection [7], however, suggests that a high level of CRP and procalcitonin may be associated with unrecognised bacterial co-infection in a child with an established viral aetiology for pneumonia. This may also explain why some studies have found procalcitonin and CRP not to be useful in distinguishing between bacterial and “viral” pneumonia [4,8].
Based on the postulate that the most likely chest radiograph (CXR) manifestation of pneumococcal pneumonia is alveolar consolidation, we reported the efficacy of a nine-valent pneumococcal conjugate vaccine (PnCV) in reducing CXR-confirmed pneumonia based on definitions recommended by a World Health Organization working group [9]. The observed reduction in the incidence of CXR-confirmed pneumonia in the intent-to-treat analyses in PnCV recipients not infected with HIV (20%; 95% confidence interval [CI], 2% to 35%) and infected with HIV (13%; 95% CI, −7% to 29%) likely underestimated the reduction in the incidence of pneumococcal pneumonia [10]. The reason for this is that the outcome measure (i.e., CXR-confirmed pneumonia) is not highly specific for pneumococcal pneumonia. Consequently, it is likely that many of the CXR-confirmed pneumonia episodes were not pneumococcal in origin and therefore could not have been prevented by the vaccine under evaluation.
We thus evaluated the usefulness of procalcitonin and CRP to improve the specificity of CXR-confirmed pneumonia as an endpoint in vaccine efficacy trials. This analysis was not a primary objective of the study, and is therefore an hypothesis-generating analysis, which should be tested as an a priori hypothesis in other study settings.
Methods
The methods of the randomised, double-blind, placebo-controlled trial, the objectives of which were to measure PnCV efficacy against invasive pneumococcal disease and CXR-confirmed pneumonia, have been published [10] (Protocol S1). Briefly stated, the study included 39,836 children, including an estimated 6.47% infected with HIV [7], and was performed in Soweto, South Africa. Children were randomised to receive either a nine-valent PnCV conjugated to CRM197 (Wyeth-Lederle Vaccines and Pediatrics, Pearl River, New York, United States) or a placebo at 6, 10, and 14 wk of age. The nine-valent PnCV included serotypes 1, 4, 5, 6B, 9V, 14, 18C, 19F, and 23F (i.e., vaccine serotypes) [10]. We now further measured procalcitonin and CRP levels in serum obtained within 12 h of hospitalisation among children with CXR-confirmed alveolar consolidation in the intent-to-treat analysis. CXRs were requested for any child hospitalised with a clinical diagnosis of lower respiratory tract infection according to the diagnosis of the attending study-physician.
CRP values were determined at the time of admission by immunoturbidometry (717 Automated Analyzer, Boehringer Mannheim/Hitachi, Mannheim, Germany) and were reported in milligrams per liter with a lower threshold set at 3 mg/l or lower. In those children in whom CRP was not measured on admission to hospital, archived serum obtained within 12 h of admission and stored at −70 °C was used for analysis. The archived serum samples were also used for measuring quantitative procalcitonin levels using the LUMItest PCT assay (BRAHMS Diagnostica, Berlin, Germany). The CRP and procalcitonin tests were performed using commercially available assays according to the manufacturers' recommendations at the National Health and Laboratory Services, Johannesburg, South Africa.
Bacterial Cultures
Blood was cultured for bacterial growth on admission and processed using the BacT/Alert microbial detection system (Organon Teknika, Durham, North Carolina, United States). Isolates of Streptococcus pneumoniae were serotyped using the quellung method at the Respiratory and Meningeal Pathogens Research Unit and the results validated at the Statens Serum Institute in Copenhagen, Denmark [10].
Statistics
Data were analysed using S
TATA version 8.0 (StataCorp, College Station, Texas, United States) and Epi Info version 6.04d (Centers for Disease Control and Prevention, Atlanta, Georgia, United States). Vaccine efficacy was calculated using Epi Info based on the formula: vaccine efficacy (percent) = [(ARU − ARV)/ARU] × 100, where ARU is attack rate in unvaccinated individuals and ARV is attack rate in vaccinated indivduals. The vaccine-attributable reduction in disease (VAR) was estimated by measuring the difference in incidence rate between vaccine and placebo recipients and expressed per 100,000 child years of observation. A p-value of 0.05 or lower was considered significant.
All analyses were performed on an intent-to-treat basis, which included the first event of CXR-confirmed pneumonia in any child who had received at least a single dose of study vaccine. Vaccine efficacy calculations were also performed for bacteremic pneumococcal pneumonia that included all first episodes of pneumonia associated with growth of S. pneumoniae of any serotype from blood.
Ethical Considerations
The efficacy study and subsequent study evaluating the role of procalcitonin and CRP in children with CXR-confirmed pneumonia were approved by the Ethics Committee for Research on Human Subjects, University of the Witwatersrand, South Africa (Protocol S2). Guardians gave informed consent for the collection of serum and its use for diagnostic assays that may improve the diagnosis of pneumonia (Protocol S3).
Results
In children not infected with HIV with CXR-confirmed pneumonia, procalcitonin and CRP values were available for 132 (78.1%) of 169 vaccine recipients and 167 (78.8%) of 212 placebo recipients (p = 0.88). The point estimate of vaccine efficacy in this cohort of children for whom serum was available was 21% (p = 0.04; 95% CI 1%–37%), not significantly different from that determined in the original study (20%, p = 0.03; 95% CI 3%–35%). At CRP levels of 120 mg/l or more in conjunction with the primary CXR-confirmed outcome measure, the estimate of vaccine efficacy increased to 38% (p = 0.05); at procalcitonin levels of 5 ng/ml or more, the estimated efficacy increased to 46% (p = 0.04); and if both conditions were met, the estimated efficacy increased to 64% (p = 0.006) (Table 1).
Table 1 CRPand Procalcitonin Improve the Specificity of CXR to Measure the Efficacy of PnCV in the Prevention of Pneumococcal Pneumonia
CXR-confirmed alveolar consolidation based on World Health Organization guidelines for interpretation. Point estimates differ from those previously published because only children with CXR-confirmed pneumonia for whom serum for CRP and procalcitonin measurements were available are included
a CXR-AC, CXR-confirmed alveolar consolidation; PCT, procalcitonin
b Pneumonia associated with growth from blood of S. pneumoniae, of any serotype
c Pneumonia associated with growth from blood of S. pneumoniae of vaccine-serotype-specific bacteremic pneumonia
Among children infected with HIV with CXR-confirmed pneumonia, procalcitonin and CRP values were available for 139 (76.4%) of 182 vaccine recipients and 153 (73.2%) of 209 placebo recipients (p = 0.47). Whereas vaccine efficacy was not significant for CXR-confirmed pneumonia (9%; p = 0.38), vaccine efficacy was significant when measured against CXR-confirmed pneumonia in conjunction with a CRP level of 120 mg/l or more (35%; p = 0.03) or a procalcitonin level of 5 ng/ml or more (33%; p = 0.04). As observed in children not infected with HIV, the point efficacy estimate in children infected with HIV with CXR-confirmed pneumonia was greatest if both CRP and procalcitonin were at or above 120 mg/l and 5 ng/ml, respectively (52%; p = 0.004; Table 1).
The sensitivity of CXR-confirmed pneumonia plus CRP ≥120 mg/l plus procalcitonin ≥5 ng/ml in detecting vaccine efficacy against pneumococcal pneumonia was analysed by comparing the VAR per 100,000 child years to that observed using an outcome of bacteremic pneumococcal pneumonia. In children not infected with HIV, the combined outcome of CXR-confirmed pneumonia plus CRP ≥120 mg/l plus procalcitonin ≥5 ng/ml (VAR = 37) identified 5.3-fold more cases of pneumonia that were prevented by vaccination than was identified by bacteremic pneumococcal pneumonia (VAR = 7) and 4.1-fold more cases than was identified by vaccine-serotype-specific bacteremic pneumococcal pneumonia (VAR = 9). Similarly, CXR-confirmed pneumonia plus CRP ≥120 mg/l plus procalcitonin ≥5 ng/ml in children infected with HIV (VAR = 772) identified 1.6-fold more cases of pneumonia that were prevented by vaccination than was identified by pneumococcal bacteremic pneumonia (VAR = 483) and 2.2-fold more cases than was identified by vaccine-serotype-specific bacteremic pneumococcal pneumonia (VAR = 344).
Among the children not infected with HIV with CXR-confirmed pneumonia, the likelihood of a difference between placebo and vaccine recipients was significantly increased by the presence of a CRP level of 120 mg/l or more and a procalcitonin level of 5 ng/ml or more (odds ratio = 1.37; 95% CI, 1.09–1.73; p = 0.027). This was true also among children infected with HIV (odds ratio = 1.41; 95% CI, 1.14–1.75; p = 0.005).
Discussion
Our results show that the true efficacy of the PnCV against pneumococcal pneumonia may be underestimated if one relies solely on a radiological diagnosis of pneumococcal pneumonia. The lack of specificity of CXRs for inferring bacterial versus non-bacterial etiology of pneumonia has been previously described [11,12]. The specificity of CXR-confirmed pneumonia as an outcome measure of efficacy of PnCV to prevent pneumococcal pneumonia was improved when it was analysed together with indirect evidence suggestive of bacterial infection, namely, elevated CRP and procalcitonin levels. This outcome measure of CXR-confirmed pneumonia plus CRP ≥120 mg/l plus procalcitonin ≥5 ng/ml, while more specific than CXR-confirmed pneumonia alone, will not be 100% accurate because pneumonia associated with other bacteria, including that due to pneumococcal serotypes against which the PnCV has no effect, may well present in a similar manner.
An alternate explanation for our results, rather than that of improved specificity in diagnosing pneumococcal pneumonia, may be that the criteria of CXR-confirmed pneumonia coupled with a CRP level of 120 mg/l or more and a procalcitonin level of 5 ng/ml or more detected more severe disease against which the vaccine may have been more efficacious. Although we are unaware of data to support that CRP and procalcitonin are elevated in those with severe pneumonia, the absence of such data supporting this interpretation does not rule out this possibility.
Importantly, the levels of CRP and procalcitonin used in this report are designed for specificity rather than sensitivity; it would be inappropriate to use the same threshold values of CRP or procalcitonin during the course of routine clinical practice when managing individuals suspected of having bacterial pneumonia. In that instance, it would be more appropriate to use thresholds that have a high sensitivity, to ensure that all children with possible bacterial infection are adequately treated [3,4,8].
Procalcitonin and CRP were equally useful in children infected and not infected with HIV to improve the specificity of the pneumococcal pneumonia efficacy endpoint in the vaccine trial among children with CXR-confirmed pneumonia. This is particularly important, as our initial observation of a non-significant reduction in CXR-confirmed pneumonia was attributed to the complexity of etiology of pneumonia, and thus the even poorer specificity of CXRs for identifying pneumococcal pneumonia in children infected with HIV compared to children not infected with HIV [13,14]. The current study thus indicates that the specificity of CXR-confirmed pneumonia for diagnosing pneumococcal pneumonia may also be improved in children with HIV through the concurrent use of procalcitonin and CRP.
A distinction must be made between measures of vaccine efficacy for which the increased specificity of CXR-confirmed pneumonia plus CRP ≥120 mg/l plus procalcitonin ≥5 ng/ml over CXR-confirmed pneumonia alone is apparent, and studies of the burden of disease prevented (VAR), which are optimised when vaccine sensitivity is maximised. Our data show that the VAR is greater for CXR-confirmed pneumonia plus CRP ≥120 mg/l plus procalcitonin ≥5 ng/ml than that calculated using the very highly specific endpoints of serotype-specific or all-serotype pneumococcal bacteremic pneumonia. The best estimates of VAR will, however, be provided by endpoints that sacrifice some specificity for maximal sensitivity. Such studies include less specific clinical endpoints and are outside of the scope of the current analysis [7].
Our findings have implications for the planning of future studies aimed at evaluating the effectiveness of pneumococcal vaccines against bacterial pneumonia. Our data suggest that the outcome measure of CXR-confirmed pneumonia together with elevated CRP and procalcitonin levels may be more accurate as a surrogate of pneumococcal pneumonia than CXRs on their own. The increased specificity of this endpoint may allow smaller sample sizes for future vaccine efficacy/effectiveness studies. Based on the incidence of CXR-confirmed pneumonia in this report (167 [0.9%] of 18,626), a sample size of 80,058 children were required to detect the 20% reduction in CXR-confirmed pneumonia with 80% power and an alpha of 0.05. The actual power for this outcome in this study was thus only 46.8%. Using the more specific outcome measure of CXR-confirmed pneumonia with a CRP level of 120 mg/l or more and a procalcitonin level of 5 ng/ml or more, the sample size required to detect the observed 64% reduction in outcome was 44,734, i.e., 56% of the sample size required when measuring vaccine efficacy against CXR-confirmed pneumonia alone, and the power of the current study would have been increased from 46.8% to 71.5%.
Our findings therefore suggest that CXR-confirmed pneumonia coupled with serological markers of CRP and procalcitonin is a more specific marker of pneumococcal pneumonia and may therefore provide a closer estimate of the efficacy of the PnCV against pneumococcal pneumonia.
Supporting Information
Protocol S1 Protocol of the Original Phase 3 Study
(250 KB DOC).
Click here for additional data file.
Protocol S2 Ethics Committee Letter of Approval
(378 KB DOC).
Click here for additional data file.
Protocol S3 Informed Consent Form for Original Phase 3 Study
(24 KB DOC).
Click here for additional data file.
Patient Summary
Background
Pneumonia is the leading cause of death in children worldwide. Pneumonia can be caused by different bacteria and viruses, and there are no easy diagnostic tests to find out which bacterium or virus has caused the disease in a particular patient. This not only causes problems with prescribing the best treatment, but also makes it hard to evaluate vaccines that might protect against some causes of the disease but not others.
Why Was This Study Done?
The researchers involved in this study have evaluated vaccines against a particular bacterium (called Pneumococcus) that is the leading cause of pneumonia in children. They have begun to test these vaccines in children, but were looking for more specific ways to distinguish cases of pneumonia caused by this particular bacterium from those caused by other bacteria or viruses.
What Did the Researchers Do?
They had previously done a trial for a vaccine that relied on chest X-rays to diagnose pneumonia. They had also collected blood from children who had participated in the trial and had become sick with pneumonia. They now checked those blood samples for two markers that indicate a bacterial infection and re-analyzed the study.
What Did They Find?
The vaccine was able to protect children—to some extent—against pneumonia. The vaccine appeared to offer greater protection against pneumonia when the pneumonia was diagnosed by a combination of X-rays and high levels of the two blood markers than when the illness was diagnosed just with a chest X-ray.
What Does This Mean?
These results raise the possibility that a combined test (chest X-ray plus two blood markers) is better at assessing whether the pneumonia vaccine works than just a chest X-ray alone.
What Next?
Because of the way this study was done—adding a specific analysis to a clinical trial after it was completed, rather than planning to test a hypothesis from the outset—it cannot be considered as proof of the idea tested. The results suggest that it is worth testing whether the combined diagnosis is more specific for pneumococcal pneumonia than chest X-rays alone, but new studies are needed to resolve the issue.
More Information Online
The Global Alliance for Vaccines and Immunization (GAVI): http://www.vaccinealliance.org/
GAVI Web page “Call for Intensified Research after Pneumococcus Trial Surprises”: http://www.vaccinealliance.org/Resources_Documents/Immunization_Focus/Download/update.php
World Health Organization (WHO) Web site on vaccines: http://www.who.int/vaccines/
WHO Web page “Pneumococcal Vaccines”: http://www.who.int/vaccines/en/olddocs/pneumococcus.shtml)
The authors acknowledge the World Health Organization and the Global Alliance for Vaccines and Immunization's Pneumococcal Accelerated Development and Introduction Plan for financial support to perform the procalcitonin and CRP assays. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Citation: Madhi SA, Heera JR, Kuwanda L, Klugman KP (2005) Use of procalcitonin and C-reactive protein to evaluate vaccine efficacy against pneumonia. PLoS Med 2(2): e38.
Abbreviations
CIconfidence interval
CRPC-reactive protein
CXRchest radiograph
PnCVpneumococcal conjugate vaccine
VARvaccine-attributable reduction in disease
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References
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Christ-Crain M Jaccard-Stolz D Bingisser R Gencay MM Huber PR Effect of procalcitonin-guided treatment on antibiotic use and outcome in lower respiratory tract infections: Cluster-randomised, single-blinded intervention trial Lancet 2004 363 600 607 14987884
Simon L Gauvin F Amre DK Saint-Louise P Lacroix J Serum procalcitonin and C-reactive protein levels as markers of bacterial infection: A systematic review and meta-analysis Clin Infect Dis 2004 39 206 217 15307030
Moulin F Raymond J Lorrot M Marc E Coste J Procalcitonin in children admitted to hospital with community acquired pneumonia Arch Dis Child 2001 84 332 336 11259234
Gendrel D Raymond J Coste J Moulin F Lorrot M Comparison of procalcitonin with C-reactive protein, interleukin 6 and interferon-alpha for differentiation of bacterial vs. viral infections Pediatr Infect Dis J 1999 18 875 881 10530583
Madhi SA Klugman KP The Vaccine Trialist Group A role for Streptococcus pneumoniae in virus-associated pneumonia Nat Med 2004 10 811 813 15247911
Korppi M Remes S Serum procalcitonin in pneumococcal pneumonia in children Eur Respir J 2001 17 623 627 11401055
World Health Organization Pneumonia Vaccine Trial Investigators' Group Standardization of interpretation of chest radiographs for the diagnosis of pneumonia in children. Geneva: World Health Organization. Available: http://www.who.int/vaccine_research/documents/en/pneumonia_children.pdf
2001 Accessed 28 December 2004
Klugman KP Madhi SA Huebner RE Kohberger R Mbelle N A trial of a 9-valent pneumococcal conjugate vaccine in children with and those without HIV infection N Engl J Med 2003 349 1341 1348 14523142
Courtoy I Lande AE Turner RB Accuracy of radiographic differentiation of bacterial from nonbacterial pneumonia Clin Pediatr (Phila) 1989 28 261 264 2656052
Friis B Eiken M Hornsleth A Jensen A Chest X-ray appearances in pneumonia and bronchiolitis. Correlation to virological diagnosis and secretory bacterial findings Acta Paediatr Scand 1990 79 219 225 2321485
Madhi SA Cumin E Klugman KP Defining the potential impact of conjugate bacterial polysaccharide-protein vaccines in reducing the burden of pneumonia in human immunodeficiency virus type 1-infected and -uninfected children Pediatr Infect Dis J 2002 21 393 399 12150175
Madhi SA Cutland C Ismail K O'Reilly C Mancha A Ineffectiveness of trimethoprim-sulfamethoxazole prophylaxis and the importance of bacterial and viral coinfections in African children with Pneumocystis carinii pneumonia Clin Infect Dis 2002 35 1120 1126 12384847
| 15736995 | PMC549587 | CC BY | 2021-01-05 10:39:31 | no | PLoS Med. 2005 Feb 22; 2(2):e38 | utf-8 | PLoS Med | 2,005 | 10.1371/journal.pmed.0020038 | oa_comm |
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PLoS MedPLoS MedpmedplosmedPLoS Medicine1549-12771549-1676Public Library of Science San Francisco, USA 1573699610.1371/journal.pmed.0020040Learning ForumDiabetes/Endocrinology/MetabolismNephrologyOpthalmologySexual HealthDiabetesOphthalmologyNutrition and MetabolismDiabetic renal diseaseNeurologyCase-Based Study: From Prediabetes to Complications—Opportunities for Prevention Learning ForumRappaport Jonathan *Fonseca Vivian Lightman Susan Section EditorLynn William Section EditorJonathan Rappaport is Fellow in the Section of Endocrinology, Diabetes and Metabolism, and Vivian Fonseca is Professor of Medicine and Pharmacology, Tullis Tulane Alumni Chair in Diabetes, and Chief of the Section of Endocrinology, Tulane University Health Sciences Center, Veterans Affairs Medical Center, New Orleans, Louisiana, United States of America.
Competing Interests: JR declares that he has no competing interests. VF has pharmaceutical research grants funded by AstraZeneca, Merck, Pfizer, P&G Pharmaceuticals, Novo Nordisk, Aventis, Takeda, SmithKline Beecham, Schering-Plough, Novartis, Diobex Corporation, and MannKind Corporation.
*To whom correspondence should be addressed. E-mail: [email protected] 2005 22 2 2005 2 2 e40Copyright: © 2005 Rappaport and Fonseca.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.A 31-year-old man presents with central obesity, hypertension, and abnormal lipids. How would you manage this patient?
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DESCRIPTION of CASE
A 31-year-old white male with no significant past medical history is referred by his workplace to a primary care physician for an elevated blood pressure (BP). He presents to the clinic with no complaints. His mother and grandmother both have diabetes, and his father has hypertension. He has had a 15-pound (lb) weight gain over the last year and has become more sedentary.
His BP is 142/90 mm Hg, pulse is 88 beats per minute (bpm), weight is 209 lb, and height is 5′ 11″. On examination he displays moderate central obesity, but otherwise the examination is normal. His fasting cholesterol is 228 mg/dl (to convert milligrams per deciliter of cholesterol [total, HDL or LDL] to micromoles per liter, divide by 39), low-density lipoprotein (LDL) is 166 mg/dl, high-density lipoprotein (HDL) is 32 mg/dl, triglycerides (TG) are 223 mg/dl (to convert mg/dl of triglycerides to mmol/l, divide by 89), and fasting glucose is 114 mg/dl (to convert mg/dl of glucose to mmol/l, divide by 18).
What Is the diagnosis?
This patient meets the diagnostic criteria for the metabolic syndrome as defined by the National Cholesterol Education Program Adult Treatment Panel III guidelines [1]. Any three or more of the criteria make this diagnosis (see Table 1). Intensive lifestyle modifications such as exercise and weight loss should be made to improve cholesterol, blood pressure, and other cardiovascular disease (CVD) risk factors [2]. It may be timely to address the prevention of diabetes in patients with metabolic syndrome since these patients are at high risk for development of type 2 diabetes. Lifestyle changes delay the onset or prevent the incidence of type 2 diabetes in patients with glucose intolerance, a key feature of metabolic syndrome [3]. The patient is started on an exercise and weight loss program, sent for nutritional counseling, and scheduled for a return clinic appointment for three months later.
Table 1 National Cholesterol Education Program Clinical Identification of the Metabolic Syndrome
Adapted from [1]
Two Years Later
The patient returns to the clinic two years later. He presents with complaints of increasing frequency of urination and episodes of blurry vision. He has nocturia and has lost 5 lb in the last week. Otherwise, his review of systems is unremarkable. His blood pressure is 146/88 mm Hg, pulse 80 bpm, and weight 216 lb. His fundoscopic examination is normal. He continues to have moderate central obesity. Current medications are a thiazide diuretic, 12.5 mg once daily (QD), started one year prior. A non-fasting blood sugar is 267 mg/dl.
Can a diagnosis be made?
There are three criteria for the diagnosis of type 2 diabetes as defined by the American Diabetes Association (ADA), of which any one is sufficient to make the diagnosis (see Box 1). This patient meets the criteria for type 2 diabetes. He does not need to have a fasting blood sugar done because a random glucose greater than 200 mg/dl with symptoms of diabetes meets the first criterion. Failing to comply with lifestyle modification, his weight has increased 7 lb in two years and likely contributes to his development of diabetes. Of note, his recent weight loss is presumably due to overt hyperglycemia and glycosuria, further underestimating his true weight increase.
Box 1. ADA Diagnostic Criteria for Type 2 Diabetes
Random plasma glucose ≥200 mg/dl (11.1 mmol/l) and symptoms or
Fasting plasma glucose =126 mg/dla (6.99 mmol/l) or
Two-hour plasma glucose =200 mg/dla (11.1 mmol/l) in oral glucose tolerance test.
aIn the absence of symptoms, these criteria should be confirmed by repeat testing on a different day.
Source: [28].
His additional investigations are as follows: fasting glucose, 215 mg/dl; hemoglobin A1c (HbA1c), 8.6%; and urine albumin-to-creatinine ratio, 2.0 mg/mmol (normal is <2.5 mg/mmol in men and <3.5 mg/mmol in women). LDL is 176 mg/dl, HDL 32 mg/dl, and TG 292 mg/dl. His electrocardiogram is normal.
What are the next steps in management at this time?
Diabetes management should involve a multifaceted, goal-directed approach, which includes dietary modifications, diabetes education, assessment of blood sugar readings, and pharmacotherapy. The ADA recommends glycemic and other CVD risk factor goals (see Table 2), in addition to foot evaluation and screening for nephropathy and retinopathy, for all adults with diabetes [4]. The patient is started on metformin, 500 mg twice daily (BID) with meals. Therapy with metformin appears to decrease the risk of diabetes-related endpoints, including a reduction in cardiovascular events independent of glycemic control. There is also less weight gain and fewer hypoglycemic attacks than with insulin and sulphonylureas. Therefore, metformin may be an effective first-line pharmacotherapy of choice in these patients [5]. There are several oral hypoglycemic agents (i.e., sulfonylureas, metformin, acarbose, and thiazolidinediones) that are effective monotherapy for reducing hyperglycemia.
Table 2 ADA Summary of Goals in Adult Patients with Diabetes
Source: [4]
The patient is also started on low-dose aspirin, indicated for primary prevention of macrovascular disease in people with diabetes who have any risk factors for CVD [4], and a cholesterol-lowering agent, a statin, for his increased LDL cholesterol [6]. He is given a glucose meter, is scheduled to have diabetes education classes and diabetes nutritional counseling for a 1,800-calorie ADA diet, and is instructed to record his pre-meal blood sugars. Smoking cessation is another important aspect of diabetes management to address. He returns in three months for follow-up and has an HbA1c of 7.3%, at which time no additional therapy is started.
Three Years Later
The patient is now 37 years old and returns for a follow-up appointment. He states that he has felt “pins and needles” in his feet and fingertips. He has had difficulty with maintaining erections but has a normal libido. Blood sugars are 160–190 mg/dl in the mornings and 200–240 mg/dl in the evenings, and the patient reports no hypoglycemic events. He has diminished sensation to vibration over his right great toe and left toes and heel with intact monofilament sensation. The remainder of his examination is unchanged. His medications are metformin at 1 g BID, a thiazide diuretic at 25 mg QD, a statin QD, and an aspirin QD. He is 215 lb, BP is 142/86 mm Hg, and pulse is 76 bpm. Recent laboratory tests produced the following results: a HbA1c of 8.1%, a fasting glucose of 212 mg/dl, and normal electrolytes, creatinine, and liver enzymes. Fasting lipids are LDL 144 mg/dl, HDL 33 mg/dl, and TG 209 mg/dl.
What additional diagnostic tests would be helpful at this time, and why?
A spot urine albumin-to-creatinine ratio is 7.6 mg/mmol. This measurement technique is preferred because it has lower rates of false-positive and false-negative results than a spot urine microalbumin. Persistent microalbuminuria should be confirmed on two or three subsequent readings within a six-month period to rule out false-positive results. The elevated ratio of microalbumin in the urine signifies early nephropathy because microalbuminuria has been shown to progress to macroalbuminuria and eventual nephropathy in type 1 and type 2 diabetes. Any degree of albuminuria is a risk factor for cardiovascular events in individuals with or without diabetes; the risk increases with the level of absolute microalbuminuria [7]. Therefore, screening for microalbuminuria should be done annually in all people with type 1 and type 2 diabetes [8].
Annual screening for diabetic retinopathy should be performed in all people with diabetes after an initial evaluation and reassessed more frequently if retinopathy is diagnosed. This patient remains free of retinopathy, but a significant number of patients with type 2 diabetes have retinopathy at the onset of diagnosis owing to the insidious nature of type 2 diabetes and the failure to diagnose type 2 diabetes early. Tight glycemic control can slow the progression of diabetic retinopathy (Figures 1–3
) [9] and help prevent development of proliferative diabetic retinopathy.
Figure 1 Very Mild Diabetic Retinopathy
Figure 2 Non-Proliferative Diabetic Retinopathy Showing Several Exudates around the Macula
Figure 3 Non-Proliferative Diabetic Retinopathy Showing Macular Edema, a Cotton-Wool Spot below the Optic Disk, and a Few Hemorrhages and Exudates
What additional pharmacotherapy should be started at this time?
The patient has developed neuropathy and erectile dysfunction, both of which are complications of diabetes. He continues to have suboptimal glycemic control; therefore, additional therapy in the form of combinations is appropriate. The patient is started on a thiazolidinedione (TZD) QD. With continued elevated systolic BP >130 mm Hg and diastolic BP >80 mm Hg, an angiotensin-converting enzyme inhibitor (ACE-I) is started. An ACE-I at this time is appropriate for BP control and has the additional preventative effects of reducing progression to nephropathy and CVD events [10,11]. In addition, continued strict BP control is as effective as tight glycemic control in preventing macrovasular disease in diabetic patients and slowing the progression of diabetic nephropathy and retinopathy [12]. Erectile dysfunction is a complication associated with diabetes and can be an early sign of neuropathy and vascular disease, therefore a phosphodiesterase-5 enzyme inhibitor is an appropriate choice for patients not on vasodilators or with a history of significant CVD. The statin dose is increased to achieve a goal LDL of ≤100 mg/dl. Diabetic neuropathy is a significant cause of morbidity in diabetes, and its progression correlates directly with glycemic control. Tighter glucose control and proper foot care are effective. It is important to continue emphasis on dietary, exercise, and lifestyle modifications in addition to pharmacotherapy.
Five Years Later
The patient returns to clinic today after spending the last three years overseas and has not seen a physician in two years. He complains of fatigue, occasional blurry vision, awakening three to four times at night to urinate, and diarrhea at least once a week. He says that he has been compliant with his diabetes medications but has gained 15 lb in the last six months. His medications include metformin at 1 g BID, a TZD BID, and an ACE-I QD. His blood sugar is 289 mg/dl (fasting), BP is 130/90 mm Hg, pulse is 88 bpm, and weight is 221 lb. There are no foot sores or ulcers, but he has diminished sensation to monofilament on the plantar surfaces of both feet. The remainder of his examination is unchanged, including normal fundoscopy. His HbA1c is 9.6%, LDL is 143 mg/dl, and spot urine albumin-to-creatinine ratio is 15 mg/mmol. His creatinine and liver enzymes are normal. His pre-meal blood sugars average 210–250 mg/dl.
What is the next most appropriate step in his medical management?
He continues to have an elevated HbA1c, worsening neuropathy, and weight gain, which prompt a more effective treatment strategy. There are several options for pharmacotherapy available to choose from at this point. The patient could begin a third oral agent after maximizing the doses of metformin and TZD, or he could begin insulin injections with or without additional oral agents. Because of the significant cost associated with three oral medications and his need for further glycemic control, insulin would be an appropriate choice at this time. However, he should be advised of the side effect of additional weight gain when beginning insulin therapy.
DISCUSSION
This case presentation illustrates an otherwise healthy appearing patient who is found to have the metabolic syndrome and despite evidence-based management develops type 2 diabetes. This patient likely represents the natural history of type 2 diabetes in most patients. Mild hypertension is often the only presenting sign of metabolic syndrome and prediabetes, allowing an opportunity for prevention of type 2 diabetes.
There is an association between metabolic syndrome and the development of CVD and type 2 diabetes [13]. This syndrome is characterized not only by the criteria given in Table 1, but also by a state of compensatory hyperinsulinemia [14]. However, a diagnosis of metabolic syndrome alone does not imply diabetes, as patients with metabolic syndrome can have a fasting plasma glucose less than 110 mg/dl. It is the body's ability to maintain glucose utilization and suppress endogenous glucose production in the setting of this compensatory hyperinsulinemia that separates metabolic syndrome from diabetes. The effect of this hyperinsulinemic state in metabolic syndrome is also believed to be involved in excess pro-inflammatory and pro-thrombotic markers associated with the development of diabetes and CVD [15]. These patients develop diabetes when tissues of the body fail to utilize glucose appropriately owing to increased resistance to insulin and concomitant beta-cell dysfunction of the pancreas [16].
Metformin is in the class of biguanides and works by decreasing hepatic glucose output and increasing insulin action in tissues. Metformin has been suggested to help prevent the onset of diabetes but is less effective than diet and lifestyle changes [3]. Other medications shown to possibly delay or prevent the onset of type 2 diabetes are ACE-I and angiotensin II receptor blockers [17,18]. Patients treated with diuretics can progress to type 2 diabetes even though thiazide diuretics are proven effective in treating hypertension [19,20].
Intensive therapy in patients with type 2 diabetes results in a decreased risk of microvascular complications; therefore, it is appropriate to use combinations of medications in patients with suboptimal glycemia [21]. The class of TZDs works to lower plasma glucose levels by increasing insulin sensitivity in muscle and liver [22]. TZDs lower mean HbA1c modestly when added to metformin as compared to metformin alone [23]. Side effects include weight gain and water retention, and patients with a history of New York Heart Association class III or IV heart failure should not use TZDs [24,25].
The pathophysiology of type 2 diabetes involves, in part, a “relative” deficiency of insulin. Although a state of endogenous hyperinsulinemia occurs, the degree of tissue resistance causes a total decrease in “effective” endogenous insulin. Progression of disease is also attributed to worsening beta-cell dysfunction and decreased release of insulin [26]. Insulin is used in a variety of combinations and is individualized to patient lifestyle. A frequent starting dose consists of a long- or intermediate-acting insulin, such as NPH insulin, divided into morning and evening doses, or insulin glargine given QD, usually at bedtime. The patient whose case is described here was started on NPH at bedtime, which decreases overnight hepatic glucose production such that the patient begins the morning with near-normal glycemia for daytime oral therapy. There may be times when a post-meal surge in glucose requires extra insulin in addition to the intermediate-acting NPH. In such a case, using a short-acting (regular) insulin before meals provides insulin action that closely approximates normal insulin secretion (Figure 4). The rapid-acting lispro and aspart insulins have an even shorter half-life and quicker onset of action than regular insulin. Common empirical initiation doses range from 0.4–1.2 units of insulin per kilogram per 24 hours. Patients should be advised of hypoglycemia and weight gain as the main side effects of insulin therapy. Insulin and insulin-sensitizer combinations significantly improve hyperglycemia; however, there is an increased incidence of heart failure reported with this combination, prompting close monitoring of patients for signs and symptoms of heart failure [27].
Figure 4 Using a Short-Acting (Regular) Insulin before Meals Provides Insulin Action That Closely Approximates Normal Insulin Secretion
In summary, diabetes prevention and management is an important goal in practice. The morbidity and mortality from diabetes is a significant burden to health care, emphasizing the need for effective prevention and control of diabetes in improving outcomes.
Editorial Note
The management of the patient in this Learning Forum article is in keeping with two national guidelines—those of the United States National Cholesterol Education Program and the ADA. Both peer reviewers pointed out that clinicians in other countries would follow their own national or regional guidelines. For example, the guidelines for the management of type 2 diabetes published by the United Kingdom's National Institute for Clinical Excellence differ in key ways from the ADA guidelines. We as editors debated whether to insist that the authors include guidance from other parts of the world. We decided that as an international journal we should reflect global variations in practice and allow authors to discuss how patients would be optimally managed in their own countries. There is much we can learn from different approaches to clinical practice worldwide.—The PLoS Medicine Editors
Useful Links
National Institute for Clinical Excellence Clinical Guidelines for Type 2 Diabetes: www.nice.org.uk/pdf/NICE_full_blood_glucose.pdf
International Diabetes Federation (European Region) Desktop Guide to Type 2 Diabetes: www.staff.ncl.ac.uk/philip.home/t2dg1999.htm
Key Learning Points
The natural history of diabetes suggests that it is a progressive disease, and therapy may need to be frequently changed or augmented over time.
The diagnosis of the metabolic syndrome should alert primary care physicians to prescribe intensive lifestyle modifications for prevention of diabetes.
Strict BP, lipid, and weight control is just as essential as strict glycemic control in preventing CVD in patients with diabetes.
Metformin can reduce the risk of CVD in obese patients with diabetes independent of glycemic control.
The decision of combination oral therapy with or without insulin should be individualized to optimize glycemic control and reduce micro- and macrovascular complications.
Diabetes research and education at Tulane University Health Sciences Center is supported in part by the John C. Cudd Memorial Fund, the Tullis–Tulane Alumni Chair in Diabetes, and the Susan Harling Robinson Fellowship in Diabetes Research
Citation: Rappaport J, Fonseca V (2005) Case-based study: From prediabetes to complications—Opportunities for prevention. PLoS Med 2(2): e40.
Abbreviations
ACE-Iangiotensin-converting enzyme inhibitor
ADAAmerican Diabetes Association
BIDtwice daily
BPblood pressure
bpmbeats per minute
CVDcardiovascular disease
HbA1chemoglobin A1c
(HDLhigh-density lipoprotein
lbpound
LDLlow-density lipoprotein
QDonce daily
TGtrigycerides
TZDthiazolidinedione
==== Refs
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Grundy SM Hansen B Smith SC Cleeman JI Kahn RA Clinical management of metabolic syndrome: Report of the American Heart Association/National Heart, Lung, and Blood Institute/American Diabetes Association conference on scientific issues related to management Circulation 2004 109 551 14757684
Knowler WC Barrett-Connor E Fowler SE Hamman RF Lachin JM Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin N Engl J Med 2002 346 393 403 11832527
American Diabetes Association Standards of medical care in diabetes Diabetes Care 2004 27 Suppl 1 S15 S35 14693923
UK Prospective Diabetes Study (UKPDS) Group Effect of intensive blood-glucose control with metformin on complications in overweight patients with type 2 diabetes (UKPDS 34) Lancet 1998 352 854 865 9742977
National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) 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) final report Circulation 2002 106 3143 3421 12485966
Gerstein HC Mann JF Yi Q Zinman B Dinneen SF Albuminuria and risk of cardiovascular events, death, and heart failure in diabetic and nondiabetic individuals JAMA 2001 286 421 426 11466120
Bennett PH Haffner S Kasiske BL Keane WF Mogensen CE Screening and management of microalbuminuria in patients with diabetes mellitus: Recommendations to the Scientific Advisory Board of the National Kidney Foundation from an ad hoc committee of the Council on Diabetes Mellitus of the National Kidney Foundation Am J Kidney Dis 1995 25 107 112 7810516
The Diabetes Control and Complications Trial Research Group The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus N Engl J Med 1993 329 977 986 8366922
Heart Outcomes Prevention Evaluation Study Investigators Effects of ramipril on cardiovascular and microvascular outcomes in people with diabetes mellitus: Results of the HOPE study and MICRO-HOPE substudy Lancet 2000 355 253 259 10675071
Lebovitz HE Wiegmann TB Cnaan A Shahinfar S Sica DA Renal protective effects of enalapril in hypertensive NIDDM: Role of baseline albuminuria Kidney Int Suppl 1994 45 S150 S155 8158885
UK Prospective Diabetes Study Group Tight blood pressure control and risk of macrovascular and microvascular complications in type 2 diabetes: UKPDS 38 BMJ 1998 317 703 713 9732337
Sattar N Gaw A Scherbakova O Ford I O'Reilly DS Metabolic syndrome with and without C-reactive protein as a predictor of coronary heart disease and diabetes in the West of Scotland Coronary Prevention Study Circulation 2003 108 414 419 12860911
Alberti KG Zimmet PZ Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: Diagnosis and classification of diabetes mellitus provisional report of a WHO consultation Diabet Med 1998 15 539 553 9686693
Pradhan AD Manson JE Rifai N Buring JE Ridker PM C-reactive protein, interleukin 6, and risk of developing type 2 diabetes mellitus JAMA 2001 286 327 334 11466099
Weyer C Bogardus C Mott DM Pratley RE The natural history of insulin secretory dysfunction and insulin resistance in the pathogenesis of type 2 diabetes mellitus J Clin Invest 1999 104 787 794 10491414
Yusuf S Gerstein H Hoogwerf B Pogue J Bosch J Ramipril and the development of diabetes JAMA 2001 286 1882 1885 11597291
Dahlof B Devereux RB Kjeldsen SE Julius S Beevers G Cardiovascular morbidity and mortality in the Losartan Intervention For Endpoint reduction in hypertension study (LIFE): A randomized trial against atenolol Lancet 2002 359 995 1003 11937178
Siragy HM Major outcomes in high-risk hypertensive patients randomized to angiotensin-converting enzyme inhibitor or calcium channel blocker vs. diuretic: The Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT) JAMA 2002 288 2981 2997 12479763
Luna B Feinglos MN Drug-induced hyperglycemia JAMA 2001 286 1945 1948 11667913
UK Prospective Diabetes Study (UKPDS) Group Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33) Lancet 1998 352 837 853 9742976
Nolan JJ Ludvik B Beerdsen P Joyce M Olefsky J Improvement in glucose tolerance and insulin resistance in obese subjects treated with troglitazone N Engl J Med 1994 331 1188 1193 7935656
Fonseca V Rosenstock J Patwardhan R Salzman A Effect of metformin and rosiglitazone combination therapy in patients with type 2 diabetes mellitus: A randomized controlled trial JAMA 2000 283 1695 1702 10755495
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| 15736996 | PMC549588 | CC BY | 2021-01-05 11:13:37 | no | PLoS Med. 2005 Feb 22; 2(2):e40 | utf-8 | PLoS Med | 2,005 | 10.1371/journal.pmed.0020040 | oa_comm |
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PLoS MedPLoS MedpmedplosmedPLoS Medicine1549-12771549-1676Public Library of Science San Francisco, USA 1573699710.1371/journal.pmed.0020041EssayOtherPrimary CareGeneral MedicineCommunication in Health CarePatientsGeneral Practice/Family Practice/Primary CareA Person-Centred Approach to Communicating Risk EssayAlaszewski Andy Andy Alaszewski is a professor of health studies at Canterbury's Centre for Health Services Studies, University of Kent, Canterbury, United Kingdom, and editor of Health, Risk and Society. E-mail: [email protected]
Competing Interests: The author declares that he has no competing interests.
2 2005 22 2 2005 2 2 e41Copyright: © 2005 Andy Alaszewski.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.Standard approaches to communicating risk to patients do not appear to be very effective, argues Alaszewski. We need a new approach that takes patients' own perceptions into account
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Doctors and other health professionals play a key role in communicating risk information. They are advisers to patients, especially when patients have to make fateful decisions that can irrevocably change their lives. There is a developing body of literature on the ways in which risk information can be effectively communicated [1,2]. However, much of this literature focuses on the nature of risk information and ways in which the transfer of this information can be improved. It does not fully take into account the complexity of the real world of clinical practice, nor the importance of considering patients as active partners in communication.
The Rational Model of Risk Communication
Much of the discussion of risk communication is grounded in the rational model of risk communication [3,4]. This model emphasises the role and position of experts such as doctors who have the ability to identify relevant risk knowledge. In the context of medical decision-making this is knowledge about the probable consequences of different courses of action based on scientific research. The role of the doctor is to make such knowledge available so that the patient can then use it to make an informed decision.
With the rational model, when there is evidence that patients have not used risk knowledge effectively, then the response of the professional is to consider ways in which risk communication can be improved, such as by improving its presentation or mode of communication. When patients appear to be making irrational or harmful decisions, for example, continuing to smoke, choosing not to vaccinate a child against measles, mumps, and rubella, or not complying with medication, the professional's response is to work harder to convey the risks.
Patients actively seek information on risks from many different sources
(Illustration: Margaret Shear, Public Library of Science)
But the rational model contains two key flaws. One relates to the nature of risk knowledge and the second to the nature of communication [5]. Within the rational model, risk knowledge is treated as a relatively simple and straightforward matter—in other words, there is a single uncontested source of knowledge that is relatively easy to access. In reality, risk knowledge is often a complex matter. While such knowledge may be produced by scientific research, it can and often is contested. There may be a scientific consensus, for example, that eating beef or having your child vaccinated against measles, mumps, and rubella is relatively safe, but there are often alternative scientific views, sometimes represented by high-profile media “mavericks” who emphasise the potential hazards [6].
Risk knowledge cannot actually be used directly by patients to inform their decision-making. Scientific research such as in epidemiology generates knowledge about the probability of harmful events occurring within populations. Individual patients need information on their own personal risks. Expert assessments of risk tend to focus on the knowable and measurable components of risk, that is, the extent to which future events are the same as and predictable by the knowledge of past events. Such assessments by definition exclude uncertainty—those aspects that cannot be assessed and measured. Given the speed of social and technological change, it is not clear that the past is an effective guide to the future. As such, there is an increasing awareness of the uncertainty of risk assessment, for example, in relationship to new diseases such as HIV/AIDS or new technologies such as mobile phones or genetically modified foods.
The Need for a Person-Centred Approach
Within the rational model of risk communication, the emphasis is on the flow of knowledge from the knowledgeable doctor to the uninformed patient. However, communication is a two-way process, and increasingly there is awareness of the active role of patients and the public [7]. Patients actively seek information, especially when they are aware that they are facing a crucial decision. While they can use traditional sources such as friends and relatives, if they have the skills and resources they can, through media such as the Internet, access highly sophisticated risk knowledge. For example, via the Cochrane Collaboration Web site (www.cochrane.org) they can find the latest evidence-based assessments of medical treatments and technologies, or via the Dr. Foster Web site (www.drfoster.co.uk) they can find the risks associated with different treatment facilities in the United Kingdom. Many patients access a variety of different sources, so they can clearly compare and evaluate the information provided by each.
Patients do give particular credibility to sources that they know, which may include family and friends but also medical advisers with whom they have developed a relationship. They are particularly concerned about the trustworthiness of particular sources. While individuals can use their personal experience to evaluate the trustworthiness of personal sources, such as a particular relative or doctor, they often use contextual information to judge the trustworthiness of impersonal sources [8]. For example, information provided by a source that has an identifiable commercial interest, such as a company marketing a food product, will be considered as less trustworthy than a source without such an interest, for example, an expert committee of scientists.
Patients will actively interpret risk information. If the information is timely and relevant it will tend to be accepted. Patients tend to define relevance in terms of the way they view or frame a situation, and there may be considerable differences between the ways that experts and patients view the same situation. As Zinn notes, the ways in which individuals frame and perceive risk will be highly influenced by their social situation, especially their personal biography [9]. Individuals may identify and respond to the same risks in very different ways. For example, Ziegeler has shown how the background and social context of individuals who have been diagnosed as having multiple sclerosis influence the ways in which they identify and manage their risks and opportunities [9].
Features of a Person-Centred Approach
Standard approaches to risk communication, whether targeted at groups or individuals, do not appear to be very effective. For example Ruston and Clayton have shown the ways in which women disregard information and conceptually distance themselves from the risk of coronary heart disease—this applies even to those admitted to hospital with the disease [10]. Coleman has documented the failure of strategies that focus on providing information about the risks of teenage pregnancy to have any marked effect [11]. If doctors want to communicate effectively, then they need to develop a person-centred approach to risk communication, one that recognises that communication forms part of a relationship and builds upon it. Communication should be a dialogue that develops as the relationship develops, and those involved should have complementary and linked roles.
Thus, the initial stage of communication could involve identifying the key issues, that is, those that cause concern for the patient. In this phase the emphasis might be on the patient talking and the doctor listening. If there is a major difference in the ways in which patient and doctor are framing the risk issues, then there might need to be an exchange or negotiation in which both parties adjust their mutual expectations and seek a mutually acceptable definition of what the problem is. If such an exchange does not take place, and if the patient's definitions are disregarded and not acknowledged, there is the danger that the patient will passively acquiesce but treat much of the information provided by the doctor as irrelevant and disregard it.
If and when there is agreement, then there is the possibility of discussing the future and the likely consequences of taking different actions (risk communication in its traditional form). During this part of the exchange the emphasis might shift towards the doctor talking more and the patient listening more. There is a transfer of information, but it is a two-way process. The doctor should learn something about the patient's situation, including the risks that the patient is concerned about and the patient's beliefs about the nature of such risks. The patient should learn about the doctor's views of the nature of the risks that the patient is facing and the options for managing such risks.
Underpinning the development of an effective relationship is the development of mutual trust. While trust usually takes time to develop, it is possible even during a short but positive exchange, in which mutual respect is shown, for a form of “swift” trust to be developed [12].
While I have focussed on communication in face-to-face relationship, the same issues and processes can be identified in more impersonal communication, such as the provision of risk information in health promotion campaigns. In such campaigns special mechanisms need to be created for dialogue. For example, Jones has described a project that engages young drug users in Hong Kong by helping them make videos about drug use, and has shown how such techniques can be used to evaluate and improve current health promotion adverts [13].
Conclusion
There are no quick technical fixes for communicating risk information. If health professionals are serious about communicating risk information so that patients and others can make informed choices, they need to recognise that communication is a two-way process, and they need to take time to access patients' accounts and perceptions. Such investment should pay off both in an improved relationship and also in improved concordance with treatments.
Citation: Alaszewski A (2005) A person-centred approach to communicating risk. PLoS Med 2(2): 41.
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Gigenenzer G Reckoning with risk 2003 London Penguin Books 310
Hobson-West P Understanding vaccination resistance: Moving beyond risk Health Risk Soc 2003 5 273 283
Duff C The importance of culture and context: Rethinking risk and risk management in young drug using populations Health Risk Soc 2003 5 285 299
Alaszewski A Horlick-Jones T How can doctors communication about risk more effectively? BMJ 2003 327 721 731 14512481
Reilly J Philo G ‘Just another food scare?’ Public understanding and the BSE crisis Message received: Glasgow Media Group research, 1993–1998 1999 New York Longman 128 145
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Frewer LJ Miles S Temporal stability of the psychological determinants of trust: Implications for communication about food risks Health Risk Soc 2003 5 259 271
Zinn J The biographical approach—A better way to understand behaviour regarding health and illness? Health Risk Soc 2005 In press
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Coleman LM New opportunites for reducing the risk from teenage pregancy—What is the evidence base for tackling risk behaviours in combination? Health Risk Soc 2002 4 77 93
Dibben MR Lean MEJ Achieving compliance in chronic illness management: Illustrations of trust relationships between physicians and nutrition clinic patients Health Risk Soc 2003 5 241 258
Jones RH Mediated addiction: The drug discourses of Hong Kong youth Health Risk Soc 2005 In press
| 15736997 | PMC549589 | CC BY | 2021-01-05 11:13:37 | no | PLoS Med. 2005 Feb 22; 2(2):e41 | utf-8 | PLoS Med | 2,005 | 10.1371/journal.pmed.0020041 | oa_comm |
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PLoS MedPLoS MedpmedplosmedPLoS Medicine1549-12771549-1676Public Library of Science San Francisco, USA 1573699810.1371/journal.pmed.0020042EssayOtherPrimary CareGeneral MedicineCommunication in Health CarePatientsGeneral Practice/Family Practice/Primary CareCommunicating with Patients about Harms and Risks EssayHerxheimer Andrew Andrew Herxheimer is an emeritus fellow of the United Kingdom Cochrane Centre, Oxford, United Kingdom. E-mail: [email protected]
Competing Interests: The author declares that he has no competing interests.
2 2005 22 2 2005 2 2 e42Copyright: © 2005 Andrew Herxheimer.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.Health professionals, says Herxheimer, must share their understanding of the benefits and harms of any treatment with patients and their families
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Everything that doctors and other health workers do involves communication about the benefits and harms to be expected from interventions—whether they are therapeutic, diagnostic, or prophylactic. As health-care professionals, we need to share our understanding and perceptions of benefits and harms with patients and their families as fully as we can. We also have to share them with other professionals. When we do so we have to remember that how we personally value particular benefits and harms may well differ from how another person values them.
A clinician who recommends an intervention does so in the belief that its benefits outweigh the harms that it can cause. In most consultations there is little time in which to explain in detail what these benefits and harms are, or to find out what the patient thinks about them. Moreover, most clinicians are not trained or practised at describing and explaining benefits and harms clearly to patients, and much of the time they also lack important information about these aspects.
“Risk” Versus “Harm”
The problems begin with the word “risk”. Very often people use it when they mean “harm”, and this causes ambiguities and confusion. The widely used expression “benefit/risk ratio” is meaningless—no such ratio exists. Before a decision is made to use an intervention, its benefits and harms must be weighed, ideally by the clinician and the patient together. Other advantages and disadvantages, such as convenience and cost, may also be relevant. This analysis requires use of the same dimensions for considering both benefits and harms. These dimensions have not been generally recognised or taught, though they seem obvious enough.
Health professionals need to share their understanding of harms and benefits with patients and their families
(Illustration: Margaret Shear, Public Library of Science)
In this context any benefit or harm has four dimensions (see sidebar). The clinician is expected to know or find out about the nature and probability of each benefit and harm, and how to maximise benefits and minimise harms. A great many clinicians do not meet this expectation, and often that is not their fault. But only patients can say how they regard the hoped for benefits and the possible harms, though they may need help to think clearly about them. Clinicians should identify how much the benefits matter to their patient—for example, are the benefits of taking a medicine or having an operation “worth the trouble”?—and whether a specific harm is particularly threatening or would be intolerable to that particular patient. People's fears, wishes, and priorities differ greatly and unpredictably.
The deepening of the voice that occurs with long-term use of tamoxifen for breast cancer, and that is usually irreversible, is an example of a side effect that prescribers, manufacturers, and drug regulators have considered trivial and have largely ignored. While this side effect does not bother most women, for professional or keen amateur singers it is a disaster—it can rob them of what they enjoy most.
A patient who is offered a treatment with serious implications needs time and encouragement to think, and to talk to other people, before making a decision. Three major issues are important in helping patients with decision-making: obtaining reliable information about benefits and harms, effectively communicating probabilities to the patient, and determining what to do to reverse or mitigate harmful effects when they occur.
Explaining Uncertainties and Probabilities
Innumeracy is very widespread. Many people cannot handle percentages, and most are unclear about the meaning of “relative risk”, “absolute risk”, “odds ratio”, and “number needed to treat”, including many clinicians who want to tell their patients about the likelihood of benefits or harms [1]. Gigerenzer has shown that information on outcomes presented as natural frequencies (for example, “a one in five chance”) is much easier to understand than information expressed in probabilities (for example, “a 20% chance”) [2]. The reason, he suggests, is that “natural frequencies result from natural sampling, the process by which humans and animals have encountered information about risks during most of their evolution” ([1], p. 48–49). So, to put it in its simplest form, it is most effective to say to a patient “this treatment is effective in eight patients out of ten”, or “this drug causes nausea or vomiting in three people out of every ten who use it”.
The Four Dimensions of Any Benefit or Harm
Its nature, described by its quality, its intensity, and its time course (onset, duration, and reversibility).
The probability that it will occur.
Its importance to the person experiencing it.
How the benefit can be maximised, or the harm prevented or minimised.
Obtaining Reliable Information
The effectiveness of an intervention (the extent to which a treatment produces a beneficial effect when implemented under the usual conditions of clinical care for a particular group of patients) is most readily estimated from controlled clinical trials. With the rise of evidence-based medicine, there are now many more critical analyses, systematic reviews, and meta-analyses of the best evidence, as in the rapidly growing Cochrane Database of Systematic Reviews (www.cochrane.org). Nevertheless, there are huge gaps—we still lack reliable evidence about many important interventions.
Even in the case of common conditions for which many high-quality trials have been published, trial reports have not addressed some elementary questions, for example, on optimal drug dosage and duration of treatment. Almost all drug effects are related to dose [3], but we rarely learn what the lowest effective dosage is in different circumstances, and how far it is worth increasing the dosage if the effect is insufficient.
Details of dose–response relationships are hardly ever published. They are usually studied early in the development of a drug in a relatively small number of volunteers, and are used to decide on the dosages to be used in the major clinical trials that will support the licensing application. They are regarded as internal working data of the company, which is not interested in publishing them. Regulatory agencies do not appear to ask for them or examine them critically. Everybody now habitually uses means and group differences to judge effectiveness, although individuals commonly differ greatly in their sensitivity to both beneficial and harmful effects of drugs. This thoughtless reliance on means and group differences, which ignores an important dimension of evidence, is now embedded in “evidence-based practice”. Marketing departments prefer a “one size fits all” approach: it is hard to sell a drug whose dose may need to be titrated.
Another important unanswered question is the variation in response between individuals. Because controlled trials compare treatments they usually report only group means and test their significance. This gives clinicians no help in treating people who are more or less sensitive to the drug than average.
Reliable information on harms is for several reasons even harder to get [4]. Far less research is done to investigate them. Companies do not want to do more work than regulators require, and once they have marketed a drug they hesitate to pay for more research, especially if the results might be inconvenient. Independent public funding hardly exists. Many kinds of harm—often unforeseen and uncommon—need to be first detected and then diligently investigated and analysed. And the available research designs yield less robust evidence than can be obtained for predefined therapeutic effects. Here, too, dose–response data are almost completely lacking.
We still lack reliable evidence about many important interventions.
Thus, much of the time prescribers and patients are poorly informed, and have to rely on cautious exploration, common sense, and personal experience. Nevertheless, as Yoon Kong Loke has pointed out, there are certainly some situations at the bedside when it is particularly important to base treatment decisions on as precise an estimate as possible of the balance of benefits and harms [5]. An example is when there is a narrow margin between benefit and harm, such as giving aspirin to a patient with a stroke who has a past history of gastrointestinal haemorrhage. Another example is when there are several efficacious treatments with differing safety profiles, such as warfarin versus aspirin in a healthy, middle-aged patient with lone atrial fibrillation.
Checking Effectiveness and Detecting and Dealing with Harms
Doctor and patient need to work together to check that the treatment is as effective as intended, and to detect possible harm promptly. Monitoring can be left to patients if they (or the family) can understand what to watch for and what to do if a problem arises. If not, or if examination or lab tests are necessary, then monitoring and follow-up by a nurse or doctor will need to be arranged.
Here is a checklist of points for clinicians—and of course also drug regulators—to consider. (1) When an adverse effect occurs, should the dose be reduced, or the drug changed? (2) If reduced, by how much? (3) Is reducing the dose possible and practicable with the available preparations? (4) How and over what time should the effect of the change be observed and assessed? (5) Should the patient, as well as the clinician, keep the records of adverse effect(s) and their intensity and timing? Such notes can help both the patient and current and future doctors. Medication experiences can remain relevant for life. (6) Should an adverse effect be reported to a local or national adverse drug reaction register? (If in doubt, the answer is yes).
Conclusion
Effective communication about harms and risks is an essential component of care, and it requires learning, preparation, and rehearsal. The onus lies with professionals to persuade and to teach patients to play their part in coming to an informed decision about treatments.
I thank Jørgen Hilden for valuable comments.
Citation: Herxheimer A (2005) Communicating with patients about harms and risks. PLoS Med 2(2): e42.
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Gigerenzer G Reckoning with risk 2003 London Penguin Books 310
Hoffrage U Gigerenzer G Using natural frequencies to improve diagnostic inferences Acad Med 1998 73 538 540 9609869
Aronson J Ferner R Joining the DoTS: New approach to classifying adverse drug reactions BMJ 2003 327 1222 1225 14630763
Cuervo LG Aronson JK The road to health care BMJ 2004 329 1 2 15231586
Loke YK Assessing the benefit-harm balance at the bedside BMJ 2004 329 7 8 15231591
| 15736998 | PMC549590 | CC BY | 2021-01-05 10:39:29 | no | PLoS Med. 2005 Feb 22; 2(2):e42 | utf-8 | PLoS Med | 2,005 | 10.1371/journal.pmed.0020042 | oa_comm |
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PLoS MedPLoS MedpmedplosmedPLoS Medicine1549-12771549-1676Public Library of Science San Francisco, USA 1573699910.1371/journal.pmed.0020043Research ArticleBiotechnologyGenetics/Genomics/Gene TherapyInfectious DiseasesMicrobiologyEpidemiology/Public HealthHealth PolicyPathologyRespiratory MedicineInfectious DiseasesGeneticsGlobal healthScreeningSARS Transmission Pattern in Singapore Reassessed by Viral Sequence Variation Analysis SRAS Transmission in SingaporeLiu Jianjun
1
*Lim Siew Lan
1
Ruan Yijun
1
Ling Ai Ee
2
Ng Lisa F. P
1
Drosten Christian
3
Liu Edison T
1
Stanton Lawrence W
1
Hibberd Martin L
1
1Genome Institute of SingaporeSingaporeSingapore2Department of Pathology, Singapore General HospitalSingapore3Bernhard Nocht Institute for Tropical Medicine, National Reference Center for Tropical Infectious DiseasesHamburgGermanySibbald William Academic EditorSunnybrook and Women's College Health Sciences CentreCanada
Competing Interests: The authors have declared that no competing interests exist.
ETL is a member of the Editorial Board of PLOS Medicine.
Author Contributions: JL, ETL, LWS, and MLH designed the study. JL, SLL, and CD analyzed the data. LFPN performed the experiments. YR coordinated sample acquiring and provided the genome sequence variation data for designing MS assays. AEL provided SARS-CoV samples from patients. JL, SLL, YR, AEL, LFPN, CD, ETL, LWS, and MLH contributed to writing the paper.
*To whom correspondence should be addressed. E-mail: [email protected] 2005 22 2 2005 2 2 e434 8 2004 17 12 2004 Copyright: © 2005 Liu 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.
Mass Spectometry-Based SARS Genotyping
Background
Epidemiological investigations of infectious disease are mainly dependent on indirect contact information and only occasionally assisted by characterization of pathogen sequence variation from clinical isolates. Direct sequence analysis of the pathogen, particularly at a population level, is generally thought to be too cumbersome, technically difficult, and expensive. We present here a novel application of mass spectrometry (MS)–based technology in characterizing viral sequence variations that overcomes these problems, and we apply it retrospectively to the severe acute respiratory syndrome (SARS) outbreak in Singapore.
Methods and Findings
The success rate of the MS-based analysis for detecting SARS coronavirus (SARS-CoV) sequence variations was determined to be 95% with 75 copies of viral RNA per reaction, which is sufficient to directly analyze both clinical and cultured samples. Analysis of 13 SARS-CoV isolates from the different stages of the Singapore outbreak identified nine sequence variations that could define the molecular relationship between them and pointed to a new, previously unidentified, primary route of introduction of SARS-CoV into the Singapore population. Our direct determination of viral sequence variation from a clinical sample also clarified an unresolved epidemiological link regarding the acquisition of SARS in a German patient. We were also able to detect heterogeneous viral sequences in primary lung tissues, suggesting a possible coevolution of quasispecies of virus within a single host.
Conclusion
This study has further demonstrated the importance of improving clinical and epidemiological studies of pathogen transmission through the use of genetic analysis and has revealed the MS-based analysis to be a sensitive and accurate method for characterizing SARS-CoV genetic variations in clinical samples. We suggest that this approach should be used routinely during outbreaks of a wide variety of agents, in order to allow the most effective control.
Mass spectrometry-based sequence analysis provides a sensitive and accurate method to characterize genetic variation of the SARS coronavirus in clinical samples
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Introduction
During infectious disease outbreaks, due to either new or established agents, extensive information gathering is required to enable identification of the source, transmission routes, and the effect of containment policies. It is becoming increasingly clear that traditional approaches based on travel and contact tracing are not sufficient for tracking an outbreak. New sequence-based techniques for pathogen detection and identification have the potential to become perhaps the most important component of these investigations, as demonstrated in the recent worldwide effort in fighting the epidemic of severe acute respiratory syndrome (SARS). The discovery of the SARS coronavirus (SARS-CoV) as the etiological agent for SARS was a major breakthrough [1], which was quickly followed by the successful sequencing of the whole genome of the virus [2,3]. Genome sequence comparison between this new coronavirus and the three known classes of coronavirus revealed a similar genome structure, but minimum homology at the amino acid level, strongly suggesting that the SARS-CoV was a new class of coronavirus [2,3,4]. A comparative sequence analysis of 14 SARS isolates from different countries suggested a moderate genetic diversity among the SARS isolates and thus implied a slow evolution of the SARS-CoV genome [5]. Furthermore, sequence variation analyses of SARS-CoV isolates demonstrated that common genetic variations in the SARS-CoV genome could be used as “molecular fingerprints” to partition the viral isolates into different genetic lineages, track the transmission of a specific viral lineage, and infer the origin of infection [5,6]. Therefore, the characterization of SARS-CoV's genetic variations is not only instrumental for understanding its genetic diversity and genome evolution but also important for tracking its transmission and understanding its epidemiological pattern in human populations.
Direct sequence analysis of a pathogen in a large number of clinical samples, particularly at a population level, is generally cumbersome, technically challenging, and expensive. Therefore, a rapid, sensitive, high-throughput, and cost-effective screening method would greatly facilitate large-scale characterization of genetic variation of pathogens at a population level. A mass spectrometry (MS)–based method for detecting single nucleotide polymorphisms has been routinely used as a high-throughput method for genotyping human samples, and, thus, we sought to extend this methodology to detect pathogen sequence variations. Here, we demonstrate the high sensitivity of the MS-based analysis in detecting SARS-CoV sequence variations and apply it to analyzing both cultured viral isolates and uncultured tissue samples of SARS-CoV.
Methods
Patients and Samples
The SARS-CoV samples used in the sensitivity study were previously described [7]. Briefly, five in vitro samples were generated by spiking 200-μl human whole-blood samples with SARS-CoV virus obtained from a Vero E6 cell culture of an anonymous Singapore patient.
Vero cell cultured viral isolates were obtained from 13 Singapore patients: the presumed index case (patient Sin2500) of the Singapore SARS outbreak, whose date of illness onset was 25 February 2004; three primary contacts (patients Sin2677, Sin2774, and Sin2748), whose dates of onset were 9 March 2004 (Sin2677 and Sin2774) and 14 March 2004 (Sin2748); one secondary contact (patient Sin2679), who was believed to have contracted SARS from index patient Sin2500 through another primary contact not included in this study and whose date of illness onset was 15 March 2004; and another eight patients (Sin842, Sin845, Sin846, Sin847, Sin848, Sin849, Sin850, and Sin852), who were believed to be the fifth- or six-generation contacts of index patient Sin2500 (based on contact tracing records) and whose dates of illness onset ranged from 2 April to 14 April 2004. All the patients fitted the World Health Organization case definition for probable SARS [8]. The virus was cultured in vero cells following isolation from respiratory samples (three endotracheal tube swabs, three throat swabs, one nasal swab, two nasopharyngeal aspirates, and four lung tissues) obtained from the patients between 0 and 11 d after onset of symptoms. Uncultured lung tissue samples were also obtained from patients Sin842, Sin848, Sin849, and Sin852. Bronchoalveolar lavage material was obtained from a serologically confirmed German patient with SARS who had been traveling on the same flight as an early Singaporean patient with SARS who was later hospitalized in Germany [9]. Virus could not be isolated from the sample owing to its inappropriate storage.
RNA Extraction and cDNA Synthesis
For the spiked human blood samples, RNA was extracted from 200 μl of blood into 50 μl of water using a HighPure RNA kit (Roche, Basel, Switzerland). For the clinical samples, RNA was extracted into 30 μl of water using a QiAmp viral RNA mini kit (Qiagen, Valencia, California, United States). RNA samples were reverse transcribed into cDNA using 2 μl of RNA as template, a SuperScript kit (Invitrogen, Carlsbad, California, United States), and 13 sequence-specific primers [10]. All cDNA products were purified by ethanol precipitation and then resuspended in 20 μl of water.
Real-Time Quantitative PCR Analysis
Real-time quantitative PCR analyses of the RNA samples from spiked human blood were performed using a Lightcycler Sars-CoV quantification kit (Roche). Each analysis was done using 1 μl of RNA and in accordance with the manufacturers' instructions.
Single Nucleotide Variations of SARS-CoV
Twenty-one single nucleotide variations (SNVs) of SARS-CoV were analyzed in this study. Eight of these were identified from our previous sequence analysis of five Singapore SARS-CoV viral isolates and represent variations [5], and 13 SNVs were identified from a more recent genome sequence analysis of additional Singapore SARS-CoV viral isolates. The former eight SNVs were used in evaluating the sensitivity of MS-based genotyping analysis in detecting SARS-CoV viral genotypes, and the later 13 SNVs, as well as five of the former eight SNVs, were used to genotype the patient-derived samples.
SNV Analysis
A primer extension genotyping assay was designed for each SARS-CoV SNV using SpectroDesigner software (Sequenom, San Diego, California, United States) and analyzed using the MassARRAY system (Sequenom) and the recommended protocol for the MADLI-TOF (matrix-assisted laser desorption ionization/time-of-flight) MS-based genotyping analysis [11]. One microliter of cDNA (equivalent to 0.1 μl of RNA from 1 μl of spiked human blood) was used as template in each analysis.
Statistical Analysis of Sensitivity
The analytical detection limit of the combined RNA preparation/RT-PCR/MALDI-TOF MS system was determined by probit analysis [12] using the Statgraphics Plus 5.0 software package (Statistical Graphics, Jena, Germany).
Results
Sensitivity for Detecting SARS-CoV SNVs
Prior to determining viral sequence variants in clinical samples, we measured the sensitivity of the MS-based assay for detecting SARS-CoV sequence variations by analyzing eight SNVs in in vitro human blood samples spiked with SARS-CoV. The viral RNA copy numbers in five spiked human blood samples were quantified by real-time PCR analysis and determined to be 1.64 × 106 (SB1), 3.84 × 103 (SB2), 2.17 × 103 (SB3), 6.21 × 102 (SB4), and 1.20 × 102 (SB5) copies per microliter (Figure S1). The three samples (SB3, SB4, and SB5) with the lowest virus copy numbers were used to determine the sensitivity of the MS-based assay.
We were able to successfully type the virus in 16 of the 16 analyses of the SB3 sample (equivalent to 217 RNA copies per reaction), 12 of the 15 analyses of the SB4 sample (equivalent to 62 RNA copies per reaction), and six of the 15 analyses of the SB5 sample (equivalent to 12 RNA copies per reaction). According to probit analysis, this corresponds to a 95% probability of detection when at least 75 copies of viral RNA (95% confidence interval, 59–107 copies) are present per reaction, and still a 50% detection chance at 38 copies of virus RNA per reaction (95% confidence interval, 29–53 copies). All 64 sham spiked samples gave negative genotype calls.
Sequence Variant Determination of SARS-CoV in Viral Isolates
Having demonstrated the high sensitivity of the MS-based analysis, we typed 18 SARS-CoV SNVs in the cultured viral isolates from nine Singapore patients, including five early Singapore cases (Sin2500, Sin2774, Sin2748, Sin2677, and Sin2679) and four later Singapore cases (Sin842, Sin848, Sin849, and Sin852).
Of the 18 SNVs analyzed, nine were detected in at least two SARS isolates (Table 1). Assuming that a common sequence variation originated through a single mutation in a host and was then propagated by subsequent infection to others, the sharing of a specific sequence variant by different viral isolates suggests that either these viral isolates share a common ancestor or they have direct ancestor–descendant relationship. Sequence variants at the nine common SNV sites were used to reconstruct the molecular relationship among the nine viral isolates. The pattern of the shared variants among the nine viral isolates (Table 1) clearly indicated two major molecular lineages of isolate (Figure 1). One lineage includes the four early isolates from patients Sin2500, Sin2774, Sin2748, and Sin2677, and the other includes the early isolate from patient Sin2679 and the four later isolates. The first lineage is defined by the sequence variant T:C:T at SNV positions19,084, 23,174, and 28,268, whereas the second lineage is defined by the sequence variant C:T:C. Both the variants are distinct from the presumed ancestral sequence variant C:C:C observed in the Urbani viral isolate. The later Singapore isolates were also differentiated from the early isolates by the sequence variant pattern at SNV positions 22,549 and 23,735.
Figure 1 The Molecular Relationship among 13 Singapore SARS-CoV Isolates Based on the Genotype Sharing Pattern of the Viral Isolates
Table 1 Genotypes of Five Early and Four Later Singapore SARS-CoV Isolates in 18 SNVs
a SNV positions are numbered according to their nucleotide positions in the genome sequence of the Urbani isolate
NA, not analyzed
In addition, the sequence variant sharing pattern at SNVs 28,008, 548, 1,727, and 13,347 can further differentiate the four fifth- and six-generation isolates into three different sub-lineages (Figure 1) defined by three distinct variants: C:T:T:C in the isolate from patient Sin842, T:T:T:C in the isolate from patient Sin849, and T:C:C:T in the isolates from patients Sin852 and Sin848 (Table 1). To further confirm this three-sub-lineage pattern observed in the later Singapore isolates, we typed another four later Singapore isolates, from patients Sin845, Sin846, Sin847, and Sin850, at five critical SNVs (19,084, 28,008, 548, 1,727, and 13,347). The detected sequence variations in the four new isolates supported the three-sub-lineage pattern in the later Singapore isolates (Table 2; Figure 1). The second and third sub-lineages are more closely related to each other than to the first one, as all the members of the latter two sub-lineages show the variant T at SNV position 28,008, whereas the two members of the first sub-lineage show the variant C.
Table 2 Genotypes of Two Early and Eight Later Singapore SARS-CoV Isolates at Five SNV Positions
The molecular relationship among the viral isolates derived from MS-based viral sequence analysis is consistent with the one derived from the whole-genome sequence analysis of the same isolates [13], clearly demonstrating that a small subset of commonly shared variances can be used as “molecular signature” to differentiate and thus track viral isolates.
Direct Sequence Variation Determination of SARS-CoV in Primary Lung Tissue Samples
We also typed the 18 SNVs in four uncultured lung tissue samples from patients Sin842, Sin848, Sin849, and Sin852, and compared their sequence variations with their matched cultured isolates (Table 3).
Table 3 Comparison of Paired Direct Tissue Samples and Vero Cell Cultured Isolates of SARS-CoV
Of the 72 direct sequence variation comparisons (18 SNVs in four sample pairs), nine differences were identified. Six of these were due to heterogeneous sequences in primary tissue samples. For example, the cultured isolate from patient Sin849 showed the sequence variant T:T:C at SNV positions 548, 1,727, and 13,347, a subset of the heterogeneous T/C:T/C:T/C variant observed in the matched lung tissue sample from the same patient. Direct comparison of the MS spectrums of the three different sequence variants (T, T/C, and C) at SNV position 1,727 in Figure 2 clearly ruled out the possibility of variant miscall. More interestingly, the heterogeneous variant T/C:T/C:T/C in the primary lung tissue sample revealed both of the two existing variants of T:T:C and C:C:T seen in other cultured and lung tissue samples (Table 3).
Figure 2 MS Spectrums of the Three Distinct Genotypes at SNV Position 1,727
The T example is from the cultured viral isolate from patient Sin849, the T/C example is from the uncultured lung tissue sample from patient Sin849, and the C example is from the cultured viral isolate from patient Sin852.
In addition, another three sequence variant differences were observed between the paired cultured and tissue samples from patient Sin848 at SNV positions14,807, 26,205, and 26,509, where the tissue sample showed the sequence variant C:C:T, but the matched culture isolate showed the variant T:T:C (Table 3). In all three SNV positions, the cultured isolate showed novel sequence variants, whereas the primary lung tissue showed the Urbani isolate's variants (see Table 3).
Confirmation of the Singapore Origin of a German SARS-CoV Isolate
The application of tagging and thus tracking of SARS-CoV strains using viral lineage- and/or strain-specific sequence variants was further demonstrated in our investigation of a clinical sample from a German patient. This patient stayed in Hanoi, Vietnam, before sharing an airplane flight with an early Singapore SARS patient on his way to New York via Frankfurt [9]. German health authorities assumed that this patient was infected somewhere in Hanoi, Vietnam, although the possibility of him being infected by a Singapore SARS-CoV strain during his flight to New York could not be ruled out.
We genotyped the virus directly from a brochoalveolar lavage specimen from the German patient at four SNV positions (19,084, 23,792, 26,428, and 27,111) that were distinctive for the early Singapore SARS-CoV isolates (see Table 1). The sequence of the isolate from the German patient was determined to be T:C:G:A at these SNV positions. The detection of the variant T at SNV position 19,084 in the isolate from the German patient strongly suggested that this patient was indeed infected by an early Singapore SARS-CoV strain, as the T sequence variant at position 19,084 was detected only in the early Singapore isolates [5,6] and is clearly different from the C variant at position 19,084 observed in the Vietnam-originated isolates [6,14]. Furthermore, this German isolate's sequence variant, T:C:G:A, was detected only in the isolate from the Singapore primary case Sin2748, suggesting that this German patient was probably infected by a SARS-CoV strain originating from or closely related to the SARS-CoV strain of the Singapore primary case Sin2748 and not from the Hanoi outbreak. Indeed, the T:C:G:A variant is also present in the Frankfurt-1 isolate [15], which was contracted from the early Singaporean patient traveling on the same flight as the German patient.
Discussion
Through the application of this MS mini-sequencing approach to the SARS outbreak in Singapore we have demonstrated the precision that pathogen sequence data can add to an epidemiological investigation. We analyzed 18 SARS-CoV SNVs and determined the molecular relationship among the viral isolates from 13 Singapore SARS patients (see Figure 1) from different stages of the Singapore outbreak. The molecular relationship among the patients' viral isolates derived from our MS-based viral sequence analysis is not consistent with the current understanding of the clinical transmission relations between these patients. According to contact tracing records, patient Sin2500 was believed to have been the index case of the Singapore SARS outbreak and to have introduced the SARS-CoV virus into the Singapore population following a visit to the Hotel M (Hong Kong) [5,6]. Patients Sin2774, 2748, and Sin2677 were believed to have been infected directly by the index case Sin2500, and patient Sin2679 was believed to have been infected by the index case through another, unidentified, primary patient [5]. Given the pattern of sequence variations observed in the viral isolates, in order for this presumed clinical transmission relationship among these five patients to be correct, one has to assume that during viral transmission from index case Sin2500 to secondary case Sin2679 via an unidentified primary case (two human-to-human transmissions), two reverse mutations at SNV positions 19,084 and 28,268 and one novel mutation at SNV position 23,174 occurred. Although this is not impossible, it is unlikely considering the observed mutation rate among the post–Hotel M SARS-CoV isolates [5,16,17]. A more parsimonious explanation would be a single-mutation scenario in which, instead of contracting the virus from the presumed index case Sin2500, the secondary patient Sin2679 and all the later Singapore cases were infected by a virus strain from the Hotel M cluster through another, as yet unidentified, route, and during this transmission, a novel mutation occurred at SNV position 23,174. Thus, patient Sin2679 or another unidentified Singapore patient from whom patient Sin2679 contracted SARS should be the index case of all the late-generation Singapore SARS patients. Further viral genetic characterization of additional Singapore SARS cases, especially early-generation ones, may shed light on this hypothesis. Unidentified secondary SARS-CoV infection routes from Guangdong to Hong Kong were also suggested by the genetic characterization of SARS-CoV isolates, although none of these contributed substantially to the subsequent Hong Kong outbreak [6,18].
A further application of MS-based viral sequence variation analysis in tracking the virus strain and thus the transmission of SARS-CoV was demonstrated by our confirmation of the Singapore origin of a SARS-CoV isolate from a German patient. Travel and contact tracing records for this German patient indicated more than one potential exposure to SARS-CoV, and because virus could not be cultured from the patient, it was difficult to pinpoint the origin of his infection by classical sequencing methods that require virus enrichment by culture. By genotyping the four SNV positions that showed unique variants in the early Singapore SARS-CoV isolates, we confirmed that this German patient was indeed infected by an early Singapore virus strain, most likely in a hitherto unnoticed aircraft transmission event from an early Singaporean patient who was later hospitalized with SARS in Germany [9]. Therefore, our results clearly demonstrate the usefulness of the sequence variation information as molecular fingerprint in “tagging” SARS-CoV viral strains.
Direct viral sequence variation analysis of uncultured lung tissue samples identified cases of heterogeneous viral sequences in single patient samples. As the SARS-CoV virus is a single-strand RNA virus, the discovery of different sequences in a single tissue sample suggests the presence of multiple viral sequence variants, or quasispsecies, within the host when the sample was retrieved. Our result has further confirmed a recent observation of SARS-CoV quasispecies in individual patients [19] and is consistent with observations in other viral infections. Furthermore, direct comparison between cultured and uncultured samples from the same patient confirmed the existence of the heterogeneous viral sequences only in the uncultured tissue sample, which suggests that of the two initial variants in the human host, only one survived in the vero cell culture. This raises a concern that viral genetic characterization in cultured viral isolates may not capture the whole sequence variation spectrum of a virus in a patient population.
Our study has clearly demonstrated the advantages of MS-based genetic analysis as a method for large-scale viral genetic characterization in clinical samples. Firstly, MS-based analysis has high sensitivity, providing successful detection of virus more than 95% of the time at virus concentrations as low as 75 RNA copies per reaction (equivalent to a detection sensitivity of 103–104 RNA copies per milliliter), which is close to the detection limit of real-time RT-PCR based diagnostic tests (demonstrated to be 5–85 copies of viral RNA per reaction) [7,20,21,22] and within the concentration range reported for SARS-CoV in respiratory and plasma samples [9,20,22,23,24]. Typical RT-PCR sequencing usually requires as many as 1,000 copies of template, as large PCR fragments are typically amplified with less efficiency than the small fragments (about 100 bp) that are commonly used in MS-based analysis. Secondly, our detection of heterogeneous viral sequences in single clinical samples demonstrated the accuracy of the MS-based assay in characterizing SARS-CoV sequence variations. Thirdly, MS-based assay requires only a small amount of starting material for genetic characterization, 0.1 μl of RNA per reaction in the present study. Currently, MS-based genotyping analysis of human genetic variation is routinely done in a multiplex fashion, where multiple single nucleotide polymorphisms are genotyped simultaneously in a single assay. It is thus conceivable that the development of a multiplexing MS-based SNV assay for SARS-CoV could further reduce the required amount of starting material, which would be especially beneficial for analyzing uncultured clinical samples, in which viral materials are often limited. Multiplexing analysis of MS-based assays also greatly reduces the cost of analysis to about US$0.10–$0.20 per analysis (depending on the level of multiplexing), which is much cheaper than conventional sequence analysis, whose cost is typically a few dollars per analysis. Therefore, MS-based sequence variation analysis is a sensitive, accurate, cost-effective, and high-throughput method for confirming putative variations and characterizing known variations in clinical samples, especially for large-scale population studies.
MS-based sequence variation analysis is complementary to the identification of new sequence variation by direct sequence analysis and is particularly suitable for investigating agents for which there is already extensive sequence information. Direct sequence analysis is still the “gold standard” for identifying new sequence variations, but it is inefficient and is not necessary for characterizing known sequence variations in a large number of samples. A combination of initial characterization of genome sequence by direct sequence analysis in a subset of samples and the subsequent analysis of informative genetic variations via a MS-based approach is more efficient and suitable for large-scale population investigations. The genome sequences of a wide variety of pathogens and strains are being rapidly accumulated. In bacterial pathogens, strain sequence information is frequently limited to a relatively small number of genes (where using all of them simultaneously might be appropriate), whereas in viruses such as influenza, extensive genomic knowledge is accumulating. Such accumulation of both partial- and whole-genome sequence information for pathogens will further extend the usefulness of this approach.
In summary, our reassessment of the SARS-CoV transmission route in Singapore using MS-based viral sequence variation analysis highlighted the limitation of conventional epidemiological analysis based on travel and contact tracing, and the importance of informing clinical and epidemiological investigation of pathogen transmission by genetic analysis. With its demonstrated high throughput [25], sensitivity, accuracy, and cost effectiveness in determining viral sequence variations, MS-based genetic analysis can greatly facilitate the large-scale epidemiological investigations of SARS-CoV and other agents of infectious disease, and may allow for real-time investigation in outbreak situations.
Supporting Information
Figure S1 Detection of SARS-CoV by Real-Time Quantitative PCR in Spiked Human Blood Samples
The x-axis denotes the cycle number of the quantitative PCR assay, and the y-axis denotes fluorescence intensity (F2) over the background level. RNA standards were as follows: 1.05 × 106 copies per reaction (line a), 1.01 × 105 copies per reaction (line b), 9.4 × 103 copies per reaction (line c), 8.9 × 102 copies per reaction (line d), and 1.07 × 102 copies per reaction (line e). The virus loads determined in the five spiked human blood samples were as follows: SB1, 1.64 × 106 copies per reaction; SB2, 3.84 × 103 copies per reaction; SB3, 2.17 × 103 copies per reaction; SB4, 6.21 × 102 copies per reaction; and SB5, 1.20 × 102 copies per reaction. NTC, non-template control.
(244 KB DOC).
Click here for additional data file.
Accession Numbers
The GenBank (http://www.ncbi.nlm.nih.gov/Genbank/index.html) accession number for the Frankfurt-1 isolate is AY291315 and for the Urbani isolate is AY278741.
Patient Summary
Background
Molecular biology (studying the makeup and function of molecules) is increasingly being used to track outbreaks of infectious diseases. For example, molecular biology can help to identify the cause of a disease (such as a virus, bacterium, or parasite) and understand how it spreads.
Why Was This Study Done?
These researchers had previously used molecular biology techniques to study different strains of the SARS virus, which causes the often fatal disease called severe acute respiratory syndrome. They had found that different strains could be distinguished from each other on the basis of specific genetic “fingerprints.” They now wanted to find quick and easy ways to determine the identity of particular viral strains found in sick patients.
What Did the Researchers Do?
They used a molecular biology technique called mass spectrometry. They took samples from patients (such as blood samples and nasal swabs) and determined whether they could detect the SARS virus, identify specific strains, and distinguish between them.
What Did They Find?
They found that mass spectrometry is a useful tool for detecting the SARS virus and for distinguishing between different strains. They also found that they could use this tool to help understand how the SARS virus had been transmitted between specific patients.
What Are the Limitations?
For this technique to work, the researchers needed pre-existing information about genetic differences between strains. This means that detailed DNA sequencing is necessary to find these differences in the first place and to discover new ones as the virus evolves.
What Next?
The authors suggest that combining initial genetic sequencing of the different strains with the mass spectrometry technique to analyze subsequently large numbers of samples is the most efficient and cost-effective approach.
More Information Online
Public access Web pages on SARS from Science Magazine:
http://www.sciencemag.org/feature/data/sars/
News article on the SARS genome on the Genome Network News Web site: http://www.genomenewsnetwork.org/articles/05_03/sars_3.shtml
Genome Institute of Singapore (GIS): http://www.gis.a-star.edu.sg/homepage/default.jsp
GIS's press release on differences between SARS strains: http://www.gis.a-star.edu.sg/homepage/gismediapress.jsp?pid=19
Special thanks to Dr. Eng Eong Ooi for providing the spiked human blood samples. We also want to express our special thanks to Drs. Wei Chia Lin and Christopher Wong for providing us with the primer sets for reverse transcription of RNA. We also want to thank Ms. Carine Bonnard and Mr. Mea Wee Yang for their assistance in the genotyping analysis. This study was supported by funding from the Agency for Science and Technology and Research of Singapore. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Citation: Liu J, Lim SL, Ruan Y, Ling AE, Ng LFP, et al. (2005) SARS transmission pattern in Singapore reassessed by viral sequence variation analysis. PLoS Med 2(2): e43.
Abbreviations
SARS-CoVsevere acute respiratory syndrome coronavirus
MSmass spectrometry
SARSsevere acute respiratory syndrome
SNVsingle nucleotide variation
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| 15736999 | PMC549591 | CC BY | 2021-01-05 10:39:30 | no | PLoS Med. 2005 Feb 22; 2(2):e43 | utf-8 | PLoS Med | 2,005 | 10.1371/journal.pmed.0020043 | oa_comm |
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PLoS MedPLoS MedpmedplosmedPLoS Medicine1549-12771549-1676Public Library of Science San Francisco, USA 1573700010.1371/journal.pmed.0020044The PLoS Medicine DebateScience PolicyHematologyObstetrics/GynecologyOncologyPediatricsObstetricsPediatricsHematology (including Blood Transfusion)Health PolicyCan Routine Commercial Cord Blood Banking Be Scientifically and Ethically Justified? The PLoS Medicine DebateFisk Nicholas M Roberts Irene A. G Markwald Roger Mironov Vladimir Nicholas M. Fisk is Professor of Obstetrics and Fetal Medicine and Irene A. G. Roberts is Professor of Paediatric Haematology, Imperial College London, United Kingdom. E-mail: [email protected] (NMF)
Roger Markwald is Distinguished University Professor and Chair and Vladimir Mironov is Associate Professor in the Department of Cell Biology and Anatomy, Medical University of South Carolina, Charleston, South Carolina, United States of America. E-mail: [email protected](RM)
Competing Interests: NMF is a consultant to OmniCyte, and chaired the Royal College of Obstetricians and Gynaecologists' Scientific Advisory Committee at the time of its opinion paper on cord blood banking. He is on the editorial board of PLoS Medicine. IAGR declares that she has no competing interests. RM is an unpaid consultant on the Board of Advisors of CureSource, a commercial umbilical cord blood bank. VM declares that he has no competing interests.
2 2005 22 2 2005 2 2 e44Copyright: © 2005 Fisk 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.Background to the debate: Umbilical cord blood—the blood that remains in the placenta after birth—can be collected and stored frozen for years. A well-accepted use of cord blood is as an alternative to bone marrow as a source of hematopoietic stem cells for allogeneic transplantation to siblings or to unrelated recipients; women can donate cord blood for unrelated recipients to public banks. However, private banks are now open that offer expectant parents the option to pay a fee for the chance to store cord blood for possible future use by that same child (autologous transplantation.)
Private banks offer expectant parents the option to pay a fee for the chance to store cord blood for possible future use by the child. The practice is controversial, for scientific and ethical reasons
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Nicholas Fisk and Irene Roberts's Viewpoint: There Are Good Reasons to Be Wary of Private Banking
No one disputes the merit of public cord blood banking, in which women altruistically donate umbilical cord blood (UCB) for haemopoietic stem cell (HSC) transplantation, in a way similar to bone marrow donation. Unrelated UCB transplants have good outcomes in children and are associated with less graft-versus-host disease than adult marrow or peripheral blood stem cells [1,2]. Public cord blood banks also increase the availability of donor HSCs for ethnic groups underrepresented in bone marrow registries [3]. Similarly, there is little argument against storing UCB from siblings in families with a known genetic disease amenable to HSC transplantation [4].
The validity of directed UCB storage in “low risk” families, however, has been widely challenged. After early concerns from the American Academy of Pediatrics [5] and American College of Obstetricians and Gynecologists [6], the United Kingdom's Royal College of Obstetricians and Gynaecologists concluded in 2001 that routine, directed commercial UCB storage could not be justified scientifically, was logistically difficult, and therefore could not be recommended [7]. In 2002, the French National Consultative Ethics Committee for Health and Life Sciences reached similar conclusions [8]. In Italy the practice has been banned. A recent European Union report highlighted serious ethical concerns about commercial UCB banks and questioned their legitimacy in selling a service of no real use [9]. So what's wrong with allowing parents who can afford it the biological luxury of storing their child's stem cells?
Are commercial UCB banks exploiting the emotional vulnerabilities of parents for financial gain?
(Illustration: Giovanni Maki)
First, UCB is very unlikely ever to be used. The probability of needing an autologous transplant is less than one in 20,000 [9,10], although commercial providers quote figures at least an order of magnitude higher, often confusing prearranged usage in at risk children with unanticipated use in those at low risk. For acute leukaemia, perhaps the most likely indication for autologous UCB transplantation, improvements in conventional therapy and allogeneic transplantation mean few proceed to autologous transplantation. In any case, there are arguments against the use of autologous UCB, including the presence of pre-leukaemic mutations and the high rate of relapse [11]. Similar considerations apply to bone marrow failure [11]. Of current indications for HSC transplantation [12], only for solid tumours, lymphomas, and auto-immune disorders might autologous UCB find a role, and even here, UCB collections often contain only enough HSCs to reconstitute children (not adults). Other uses for UCB remain speculative since it is unclear whether non-haemopoietic stem cells are present in sufficient numbers for use against degenerative conditions. Even in the uncommon event of a requirement for autologous stem cells, failure to store UCB is unlikely to be disastrous; HSCs could still be harvested from bone marrow or peripheral blood, and multipotent stem cells are increasingly being isolated from other accessible sources (e.g., deciduous teeth).
Umbilical cord blood is very unlikely ever to be used.
Second, there are important moral issues. The persuasive promotional materials of commercial UCB banks target parents at a vulnerable time, urging them to take this “once in a lifetime opportunity” to “save the key components to future medical treatment” and freeze “a spare immune system” [7]. Even at a typical cost of several thousand dollars, how could any responsible parent fail to provide for their child's future by preserving “something that may conceivably save his or her life”? As well as enumerating conditions currently treated by HSC transplantation, such literature boasts lengthy lists of diseases potentially amenable to stem cell therapy in the future, including Parkinson disease, diabetes, cancer, and heart disease. Such banks have been said to raise hopes of utopia and to use the promise of “helping children” to disguise a mercantile project
CureSource, a commercial UCB bank, believes that banking is a “once in a lifetime opportunity” (Figure: CureSource)
Third, collection imposes a considerable logistic burden on the obstetrician or midwife. In addition to consent, parental blood collection, and the associated packaging and paperwork, a large volume of blood has to be collected from the umbilical vessels in utero, requiring multiple syringes under aseptic technique. This may distract professionals from their primary task of caring for the mother and baby at this risky time or, more generally, divert delivery room staff from attending others [7]. This applies particularly in multiple or operative deliveries, and thus UCB collection is not recommended at complicated births [5]. These problems do not apply to altruistic donations to public cord blood banks, which can be harvested less intrusively ex utero; inadequate or logistically difficult samples can be discarded or forgone without consequence [3].
Finally, individual UCB banks need to remain in business long term if cryopreserved stem cells are to be retrieved. The commercial attractiveness of a service paid years in advance is attested to by the burgeoning number of private providers, yet it seems unlikely that all will survive. Indeed, some US providers are already in trouble for infringing collection patents. There remain reservations about whether laboratories will meet national standards and be accredited. There is a further danger that misplaced enthusiasm for commercial auto-collection will undermine the proven utility of altruistic public cord blood banks.
Notwithstanding the above, we accept that the utility of UCB storage in low-risk families is very different from the entirely speculative post-mortem cryonics industry. We acknowledge the possibility that autologously stored UCB stem cells may eventually be used. Indeed, recent research documenting the multi-potentiality of UCB mesenchymal lineages [13] and the in vitro expandability of cord HSC numbers sufficient to transplant an adult [14,15] may even improve such prospects. Private banks, however, must provide clear, honest, and unambiguous information for their customers. EU guidance recommends they be told that the likelihood of stored UCB stem cells being used to treat their child is negligible and that future therapeutic possibilities are very hypothetical [9].
Roger Markwald and Vladimir Mironov's Viewpoint: No One Has a Second Chance to Collect Their Cord Blood
Stem cells may potentially be used in life-saving therapies for degenerative diseases or injuries. Stem cells self-replicate and are multi-potential—they can differentiate into diverse cell types [13]. While stem cells can come from many sources, our viewpoint is that UCB is an important source of progenitor (stem) cells that can be used as an immediate alternative for bone marrow transplantation and for engineering healthy new cells and tissues.
To fully realize this potential will require collection and banking of UCB cells, which are harvested without pain or trauma from placental structures that are normally discarded after birth. We realize that UCB banking (public and private) has sparked controversy. Critics of routine banking question its cost-to-benefit ratio, citing doubts about the clinical relevance of cord stem cells or the likelihood that they will ever be used [16]. Other critics argue that embryonic stem cells (ESCs) are the better option.
The “stemness” of UCB cells is not merely theoretical (as suggested by Steinbrook; [16]). UCB has two types of multi-potential progenitor cells—HSCs and mesenchymal stem cells. These express different cell surface markers, making it possible to show that HSCs can differentiate into new red and white blood cells and, as with mesenchymal stem cells, can also transdifferentiate in vivo into liver, kidney, brain, bone, skeletal, and cardiac muscle cells [13,17,18,19,20]. While ESCs have the potential to form all types of cells, they are harvested from embryos shortly after fertilisation, raising moral and legal issues not attributed to UCB cells [21].
The real question is who should pay for umbilical cord blood collection and storage.
ESCs also represent an allogeneic source of cells—they are derived from another individual whose tissue type does not match up with the recipient, resulting in immune rejection when transplanted [22]. We know of no clinical or preclinical animal study that provides hard evidence of functional integration (without immune rejection) of transplanted ESCs. Even with somatic nuclear transfer (cloning), ESCs remain allogeneic, as they still have foreign mitochondrial DNA for which there remains untested potential risk for auto-immune diseases. In contrast, 2,000 allogeneic UCB transplants have been performed, mostly in children, for the treatment of a variety of malignant and nonmalignant conditions [22]. A London Cord Blood Bank report found that two years after transplantation the survival rate varied between 54% and 69%, depending upon the number of matched units [23]. For reasons not fully understood, allogeneically transplanted UCB cells have immune tolerance (of HLA mismatch) [24], and the risk of causing graft-versus-host disease is considered to be acceptable [24,25].
With millions of healthy babies born each year, there is potentially a large UCB supply that can be stored, tissue-typed, and made available at short notice. If saved for potential use by the donor, UCB cells become a source of perfectly matched, autologous stem cells (plus there is a 25% probability of being an exact match for a sibling). Yet the American Academy of Pediatrics came out against UCB banking, saying that the odds (with some exceptions) of a donor ever using a UCB sample were low, between 1/1,000 and 1/200,000. While the chance of a donor benefiting may presently be low, this does not automatically mean that another member of society could not benefit. For people with genetic diseases or cancers, the chances of finding an immune-tolerant donor match would obviously be increased by the expansion of cord blood sampling. Also, at the pace that stem cell research is moving, perhaps there will be new uses for UCB cells in the next decade, especially in the field of tissue engineering [26]. Importantly, unlike bone marrow, an increase in UCB samples will enhance availability for every ethnic group for tissue matching. What is certain is that no one has a second chance to collect their cord blood.
Who should operate cord blood banks—the private or the public sector? There are around 20 private UCB banks in the United States. They charge a collection fee, typically $1,000–$1,500, which includes testing for pathogens and genotyping. Samples are maintained in a frozen state for around $100 a year. An additional $15,000–$25,000 is charged if a sample is used for transplantation (usually covered by health insurance). The cost of UCB cell transplantation is significantly less than bone marrow transplantation, and the risk of graft-versus-host disease is lower [24]. The private sector, not government, has been the innovator for most new technology related to harvesting, storing, and utilizing cord blood as well as stem cell research. Licensing fees and patent protection are essential to biotechnology companies—they are needed to attract venture capital, build businesses, and develop new technologies. The only alternative in most countries is public cord banks, which suffer from insufficient funding.
Any exploitation by companies of the vulnerabilities of expectant parents for financial gain is clearly unacceptable. Federal legislation to establish a national cord blood stem cell bank network—free to all donors—has been introduced in the US Senate and House of Representatives that, if approved, should diminish the risk of exploitation. But unless the network is well-designed from a sociological viewpoint, it could generate a situation where not all cultural and ethnic groups are represented or where benefits are accessible only to families with health insurance or sufficient income to afford transplants. It still remains difficult to find full matches for African, Asian, and Native Americans—mostly because of an insufficient number of UCB donors and the diversity of HLA types in different ethnic groups [16].
The real question is who should pay for UCB collection and storage—the individual donor, who currently has only a small prospect of using their cord blood, or society as a whole? We believe that it is the job of government to assure that people of all ethnic groups are informed and educated about donating UCB. Then, to facilitate UCB banking and the development of technological innovations for its storage and clinical utility, we recommend a national network that is a mixture of for profit, non-profit, and governmental organizations.
Fisk and Roberts's Response to Markwald and Mironov's Viewpoint
Markwald and Mironov argue that commercial UCB banking is ethically justified on the grounds that UCB transplantation is effective treatment for many haematological disorders, that autologous UCB is a useful future source of stem cells for the donor, and that there is no second chance to collect these cells.
We did not dispute (indeed we acknowledged) the value of UCB HSCs for the treatment of many malignant and non-malignant haematological disorders. However, evidence of their value derives from allogeneic HSCs from public UCB banks [27]. Like many in the routine UCB collection industry, Markwald and Mironov fail completely to distinguish between public and private banks in their discussion, and further neglect to mention that most transplants have been of allogeneic cells donated altruistically by non-related donor families.
Markwald and Mironov state that the real question is who should pay for routine UCB collection and storage. However, they take no account of the considerable logistic burden this imposes, the extremely low chance that autologous cells will ever be used (less than one in 20,000), and the costs of routine UCB collection [9]. They also fail to mention that autologous UCB HSCs are frequently unsuitable for use for two reasons. First, they cannot cure inherited disorders (e.g., β-thalassaemia major or congenital bone marrow failure syndromes), and second, clinically hidden pre-leukaemic and/or leukaemic cells may be present in UCB at birth in children who years later develop full-blown leukaemia [28]. In addition, the authors introduce the irrelevant argument of the likely unsuitability of ESC transplants, with which, given the propensity of these transplants to cause teratomas, we agree [29].
Thus the real questions are, first, why should society in general, or the government as a representative of at least a substantial proportion of society, pay for a service not shown to be of any real use? (After all, as we pointed out, autologous HSCs are rarely required and there is no evidence that UCB can treat degenerative disease in elderly humans.) And second, why should commercial banks be allowed to continue to target vulnerable parents anxious to do the best for their children while making no mention of the low chance of use, of alternative sources of available stem cells (e.g., autologous marrow, a better source of non-haemopoietic stem cells), or of the risks of reducing stocks of allogeneic HSC in public UCB banks?
Markwald and Mironov's Response to Fisk and Roberts's Viewpoint
We agree with Fisk and Roberts that exploiting the emotional vulnerabilities of expectant parents is unjustifiable—thus we support regulation of UCB banking, monitoring, certification, and informed consent. But we disagree that there is a lack of solid scientific evidence for UCB collection and that “future therapeutic possibilities are very hypothetical.” Research on stem cells is advancing rapidly, and stem cells derived from UCB are emerging as a reasonable first choice for the field of regenerative medicine.
Fisk and Roberts are inconsistent in their views. They claim that stem cells collected in UCB units often are not “in sufficient numbers for use against degenerative conditions” in adult life but then acknowledge that “the in vitro expandability of cord HSC numbers is sufficient for transplantation into an adult.” They argue that private and public UCB collections create dramatically different “logistic burdens,” but in our experience, the syringes, paperwork, and level of personal distraction are generally the same for public or private banking.
We strongly disagree that private UCB banking has no future. While we anticipate a consolidation phase for this industry, surviving companies should be eager to acquire UCB units collected from competitors. If all stem cell sources were under a state monopoly—without private sector contribution—there would be less incentive or opportunity for fostering innovation in long-term storage, expansion, or phenotype characterization of UCB stem cells. The growth of new biotech companies focused on regenerative medicine would be discouraged, compromised, or undermined by the absence of competition, inadequate access to venture capital, and the typical resistance of state health-care systems and their affiliated medical professionals to innovation.
Fisk and Roberts are creating obfuscations by mixing “speculative cryobionic companies” that promise “immortality and eternity” with serious biotech companies and private UCB banks that focus on a realistic commercialisation of UCB stem cells as a platform for promoting new biotech initiatives.
The collection and storage of UCB stem cells is an opportunity for society to build a representative collection of UCB units that can improve the chances of identifying suitably matched donors for transplantation. Human ESCs are mired in ethical concerns and concerns about immunological intolerance. Autologous cells from the bone marrow or elsewhere lose their attractiveness if there is a genetic mutation or a progressive loss of “stemness” due to normal aging [30]. UCB cells offer the best short- and long-term hope for treating sick children with cancers or adults with a variety of diseased organs and tissues.
Citation: Fisk NM, Roberts IAG, Markwald R, Mironov V (2005) Can routine commercial cord blood banking be scientifically and ethically justified? PLoS Med 2(2): e44.
Abbreviations
ESCembryonic stem cell
HSChaemopoietic stem cell
UCBumbilical cord blood
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| 15737000 | PMC549592 | CC BY | 2021-01-05 10:39:32 | no | PLoS Med. 2005 Feb 22; 2(2):e44 | utf-8 | PLoS Med | 2,005 | 10.1371/journal.pmed.0020044 | oa_comm |
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PLoS MedPLoS MedpmedplosmedPLoS Medicine1549-12771549-1676Public Library of Science San Francisco, USA 1573700110.1371/journal.pmed.0020045Research ArticleDiabetes/Endocrinology/MetabolismDiabetesDiabetic Renal DiseaseMultiple Metabolic Hits Converge on CD36 as Novel Mediator of Tubular Epithelial Apoptosis in Diabetic Nephropathy CD36 and Diabetic NephropathySusztak Katalin
1
2
Ciccone Emilio
3
McCue Peter
4
Sharma Kumar
3
*Böttinger Erwin P
1
*1Division of Nephrology, Department of MedicineMount Sinai School of Medicine, New York, New YorkUnited States of America2Division of Nephrology, Department of MedicineAlbert Einstein College of Medicine, Bronx, New YorkUnited States of America3Dorrance Hamilton Research Laboratories, Division of NephrologyDepartment of Medicine, Thomas Jefferson University, Philadelphia, PennsylvaniaUnited States of America4Department of Pathology, Anatomyand Cell Biology, Thomas Jefferson University, Philadelphia, PennsylvaniaUnited States of AmericaShulman Gerald Academic EditorYale Medical SchoolUnited States of America
Competing Interests: The authors have declared that no competing interests exist.
Author Contributions: K. Susztak, K. Sharma, and E. Böttinger designed the study. K. Susztak, E. Ciccone, P. McCue, K. Sharma, and E. Böttinger performed the experiments. K. Susztak, P. McCue, K. Sharma, and E. Böttinger analyzed the data and contributed to writing the paper.
*To whom correspondence should be addressed. E-mail: [email protected], E-mail: [email protected] 2005 22 2 2005 2 2 e4510 6 2004 21 12 2004 Copyright: © 2005 Susztak 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.
Why Blood Glucose Control Matters for the Kidney
Background
Diabetic nephropathy (DNP) is a common complication of type 1 and type 2 diabetes mellitus and the most common cause of kidney failure. While DNP manifests with albuminuria and diabetic glomerulopathy, its progression correlates best with tubular epithelial degeneration (TED) and interstitial fibrosis. However, mechanisms leading to TED in DNP remain poorly understood.
Methods and Findings
We found that expression of scavenger receptor CD36 coincided with proximal tubular epithelial cell (PTEC) apoptosis and TED specifically in human DNP. High glucose stimulated cell surface expression of CD36 in PTECs. CD36 expression was necessary and sufficient to mediate PTEC apoptosis induced by glycated albumins (AGE-BSA and CML-BSA) and free fatty acid palmitate through sequential activation of src kinase, and proapoptotic p38 MAPK and caspase 3. In contrast, paucity of expression of CD36 in PTECs in diabetic mice with diabetic glomerulopathy was associated with normal tubular epithelium and the absence of tubular apoptosis. Mouse PTECs lacked CD36 and were resistant to AGE-BSA-induced apoptosis. Recombinant expression of CD36 in mouse PTECs conferred susceptibility to AGE-BSA-induced apoptosis.
Conclusion
Our findings suggest a novel role for CD36 as an essential mediator of proximal tubular apoptosis in human DNP. Because CD36 expression was induced by glucose in PTECs, and because increased CD36 mediated AGE-BSA-, CML-BSA-, and palmitate-induced PTEC apoptosis, we propose a two-step metabolic hit model for TED, a hallmark of progression in DNP.
The CD36 receptor may have a key role in the degeneration of the renal tubular epithelium, the first step in diabetic nephropathy
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Introduction
Diabetic nephropathy (DNP) is a serious and common complication of type 1 and type 2 diabetes mellitus, leading to end-stage renal failure in up to 30% of individuals with diabetes. Early abnormalities of DNP affect glomeruli and include an increase in glomerular filtration rate, microalbuminuria, glomerular hypertrophy, and thickening of the glomerular basement membrane, followed by expansion of mesangial extracellular matrix and glomerulosclerosis [1,2]. As with most chronic degenerative kidney diseases, the gradual decline of renal function at later stages of DNP is invariably associated with tubular epithelial degeneration (TED), also called tubular atrophy, and interstitial fibrosis (IF), hallmarks of degeneration to end-stage renal failure [3]. Pathomechanisms that may initiate and/or mediate TED in DNP remain poorly understood. While glomerular lesions consistent with human DNP have been described in various mouse models of diabetes, TED and IF have not been described in diabetic mice [4].
Combining detailed renal phenotype analysis with gene expression profiling of hyperglycemic mouse models of type 1 (streptozotocin [STZ]) and type 2 (db/db) diabetes, we recently reported that decreased mRNA levels of CD36 in kidneys were strongly correlated with albuminuria [5]. CD36 is a transmembrane protein of the class B scavenger receptor family and is involved in multiple biological processes [6]. CD36 is widely expressed and may interact with multiple extracellular ligands, including thrombospondin-1 (TSP-1), long-chain free fatty acids (FFAs), modified (oxidized) low-density lipoprotein (ox-LDL), advanced glycation end (AGE) products, and collagens I and IV [6]. CD36 mediates phagocytosis of apoptotic cells and malaria-parasitized erythrocytes [7]. Furthermore, CD36 mediates antiangiogenic activity associated with endothelial cell apoptosis induced by TSP-1 through p38 MAP kinase (MAPK) and caspase 3 [8]. Hyperglycemia-induced synthesis of CD36 protein in macrophages has been associated with increased uptake of ox-LDL by macrophages and foam cell formation in atherosclerotic lesions in people with diabetes [6,9,10]. While diabetic cardiovascular complications are closely linked epidemiologically with albuminuria and DNP, a role for CD36 in DNP and renal pathophysiology has not to our knowledge been described to date.
Here we report a novel functional role for CD36 scavenger receptor and AGE and FFA palmitate (PA) in tubular epithelial apoptosis associated with TED and progression of DNP. Specifically, we show that glucose stimulates CD36 cell surface expression in proximal tubular epithelial cells (PTECs), and increased CD36 renders PTECs susceptible to both AGE- and PA-induced PTEC apoptosis by mediating sequential activation of src kinase, proapoptotic p38 MAPK, and caspase 3. Based on these findings, we propose a new two-step metabolic hit model for TED in the progression of DNP.
Methods
Animals
Kidneys were obtained from 28-wk-old C57BLKS/J-leprdb/db, STZ-treated C57BL/6J, or STZ-treated 129SvJ mice and from age-matched control C57BLKS/J-leprdb/m, C57BL/6J, and 129SvJ mice as described [5].
Cell Culture
Human proximal tubular cell line HK-2 and murine collecting duct cell line M1 were purchased from American Type Culture Collection (Manassas, Virginia, United States) and cultured according to the vendor's instructions. Mouse proximal tubular cell line MCT was provided by Fuad Ziyadeh (University of Pennsylvania, Philadelphia, Pennsylvania, United States). Transfections were performed with Fugene 6 (Roche Diagnostics, Indianapolis, Indiana, United States) according to manufacturer's protocol. CD36-containing plasmid was a kind gift of Nada Abumhrad (SUNY at Stony Brook, New York, United States). Cells were also co-transfected with EGFP (Clontech, Franklin Lakes, New Jersey, United States) to assess transfection efficiency. Cells were serum starved in 0.2% serum containing DMEM (1 g/l glucose) for at least 24 h prior to stimulation with AGE–bovine serum albumin (BSA), glucose, or FFA.
Quantitative Real-Time PCR
Quantitative real-time PCR analysis of mouse and human CD36, HPRT1, and beta actin was performed as described previously [5]. The following primers were used: mouse CD36 5′
TGCTGGAGCTGTTATTGGTG and 3′
CATGAGAATGCCTCCAAACA, mouse beta actin 5′
ACCGTGAAAAGATGATGACCCAG and 3′
AGCCTGGATGGCTACGTACA, mouse HPRT1 5′
TGTTGTTGGATATGCCCTTG and 3′
TTGCGCTCATCTTAGGCTTT, human CD36 5′
GCTCTGGGGCTACAAAGATG and 3′
TAGGGAGAGATATCGGGCCT, human beta actin 5′
GATGAGATTGGCATGGCTTT and 3′
CACCTTCACCGTTCCAGTTT, and human HPRT1 5′
AAAGGACCCCACGAAGTGTT and 3′
TCAAGGGCATATCCTACAACAA.
Immunostaining and Immunoblotting
Primary antibodies specific for the following proteins were used: monoclonal mouse anti-CD36 antibody, clone FA 6–152 (IgG) (Immunotech, Fullerton, California, United States), clone SMO (IgM) (Santa Cruz Biotechnology, Santa Cruz, California, United States), rabbit polyclonal anti-CD36 (Santa Cruz Biotechnology), rabbit polyclonal anti-aquaporin1, anti-aquaporin2, anti-Na/K/2Cl (Chemicon, Temecula, California, United States), rabbit polyclonal phospho38/MAPK and mouse monoclonal p38 (Cell Signaling Technology, Beverly, Massachusetts, United States), rabbit polyclonal p-src (Y418) (Biosource, Camarillo, California, United States), and mouse monoclonal anti-tubulin (Sigma, St. Louis, Missouri, United States). Immunostaining was performed on frozen sections with FITC- and Cy3-labeled secondary antibodies (Jackson Laboratories, USA), or on paraffin-embedded sections with immunoperoxidase, as described earlier [5]. Immunoblotting was performed with 30 μg of protein isolated from cultured cells. Protein samples were resolved on a 10% SDS-PAGE and immunoblotted with primary antibody and revealed with horse radish peroxidase (HRP)-conjugated anti-mouse IgM, or anti-rabbit IgG (Jackson Laboratory, Bar Harbor, Maine, United States). Immuncomplexes were detected by enhanced chemiluminescence (Pierce, Rockford, Illinois, United States). The proximal tubular immunostaining was evaluated semi-quantitatively by two independent pathologists who were unaware of the diagnosis; distribution and intensity of staining was scored on a ten-point scale.
Fluorescence Flow Cytometric Analysis
Cells were incubated in 0.5 mM EDTA in PBS at 37 °C for 20 min, scraped, and then washed with 1% fetal bovine serum. Cells were then exposed to monoclonal anti-CD36 IgG FA6 (5 μg/ml), or control mouse IgG1 (5 μg/ml) (Sigma), for 45 min on ice in the presence of 10% fetal bovine serum then washed with PBS. This was followed by an incubation with phycoerythrin-conjugated goat anti-murine secondary antibody (Southern Biotechnology, Birmingham, Alabama, United States) 1:50 for 45 min on ice. Cells (1 × 104) were analyzed by using a SCAN flow cytometer (BD, Franklin Lakes, New Jersey, United States), with appropriate gating. Flow cytometry data were analyzed using Cellquest (BD).
Preparation of Glycated Albumin and Carboxymethyl-Lysine Albumin
Briefly, to prepare AGE-BSA, essentially fatty-acid-free and endotoxin-free BSA (250 mg/ml) was incubated at 37 °C for 2, 5, and 10 wk with D-glucose (500 mM) in a 0.4-M phosphate buffer containing EDTA, ampicillin, Fungazone, polymixin B, and protease inhibitors. Control preparations were treated identically except that glucose was omitted. Carboxymethyl-lysine (CML)–BSA was prepared as described earlier [11]. Briefly, BSA with minimal CML content (CMLmin-BSA) was prepared by incubation of BSA (0.66 mM) with glyoxylic acid (2.15 mM) in the presence of sodium cyanoboronydrate (56 mM) in 200 mM sodium phosphate buffer (pH 7.8) at 37 °C under aseptic conditions. Finally, preparations were extensively dialyzed against phosphate buffer to remove free glucose. Preparations were then tested for the presence of LPS with a Quantitative Chromogenic LAL kit (Cambrex, East Rutherford, New Jersey, United States). The concentration of LPS was lower than 0.07 IU/mg protein in all preparations.
Preparation of FFA
Palmitic acid (P5585), oleic acid, and FFA-free low-endotoxin BSA (A8806) were purchased from Sigma. Palmitic acid was dissolved at 12 mM in PBS containing 11% fatty-acid-free BSA, sonicated for 5 min, shaken overnight at 37 °C, and sonicated for 5 min again [12]. For control experiments, BSA in the absence of fatty acids was prepared, as described above. The effective concentration of PA was determined using a commercially available kit (Wako Chemicals, Neuss, Germany).
Apoptosis Detection
In situ detection of DNA fragmentation was performed using the ApoTag TUNEL assay following the manufacturer's protocol (Intergen, Purchase, New York, United States) [13]. Apoptotic nuclei were detected using DAPI staining (1 μg/ml; 10 min) in cell cultures fixed with 4% paraformaldehyde, and analyzed via fluorescence microscopy to assess chromatin condensation and segregation. Caspase3 activity was detected by using the ApoAlert Caspase3 Fluorescent Detection system (BD) according to the manufacturer's protocol. Activity was normalized to total protein content. Z-DEVD-fmk, z-VAD-fmk, z-FA-fmk, and z-LEHD-fmk were purchased from BD.
Human Kidney Biopsy Sample and Patient Characteristics
Human kidney tissues (ten controls, ten with diabetic nephropathy, and ten with focal segmental glomerulosclerosis [FSGS]) were obtained from archived kidney biopsy samples or from discarded nephrectomy specimens. All diabetic samples were from patients with biopsy-proven advanced DNP with serum creatinine ranging from 1.7 to 5.6 mg/dl (151 to 444 μM/l), heavy proteinuria (3+ by dipstick or 3–6 gr/d), and hypertension. All patients with FSGS were from patients with creatinine levels of 1.7 to 4.9 mg/dl (151 to 435 μM/l), heavy proteinuria (3+ by dipstick), and hypertension. The diagnosis of FSGS was made on Periodic acid–Schiff staining in the absence of immunodeposits on electron microscopy. The diagnosis of diabetic nephropathy was based on the presence of diabetes, proteinuria, and the characteristic light microscopy findings. Institutional Review Board approval was obtained for procurement of kidney specimens at the Thomas Jefferson University Hospital.
Statistical Methods
Data are reported as mean and standard error of the mean (SEM) for continuous variables. All cell culture experiments were performed at least three times and summarized. Standard software packages (SPSS and Excel for Windows) were used to provide descriptive statistical plots (unpaired t-tests). The Bonferroni correction was used for multiple comparisons. Significance for the quantification of the CD36 staining in human biopsy samples was calculated via the Wilcoxon Rank Sum Test.
Results
Increased Expression of CD36 Specifically in Proximal Tubules of Human Diabetic Kidneys Is Associated with TED
Using microarray-based gene expression profiling on whole kidney RNA together with supervised clustering methods, we previously identified and validated gene expression patterns for molecular classification of diabetic mice with albuminuria and mesangial expansion [5]. Reduced renal mRNA levels of the class B scavenger receptor CD36 were characteristic for diabetic mice with albuminuria [5]. Here we examined patterns of CD36 protein expression in kidneys of non-diabetic and diabetic mice and humans. CD36 protein was detectable in the thick ascending limb of loop of Henle and in the collecting duct, and absent in proximal tubules in both control and diabetic mouse kidneys (Figure 1A–1D). In contrast, CD36 was detectable only rarely in individual proximal tubular cells in sections from non-diabetic human kidneys (controls) (Figure 1E and 1H), but was markedly increased specifically in PTECs in human diabetic kidneys (Figure 1F and 1I). In addition, we did not observe increased proximal tubular CD36 expression in kidney biopsy samples from patients with FSGS (Figure 1J), that were matched with DNP samples for the severity of proteinuria (all in the nephrotic range) and renal insufficiency (all with elevated serum creatinine; 1.7–5.0 mg/dl). Semi-quantitative analysis of the distribution and intensity of CD36-positive PTECs (CD36 PTEC score), which was performed by two independent pathologists in a blinded manner, demonstrated that mean CD36 PTEC scores were not different between FSGS kidneys and normal human kidneys, but were significantly increased in DNP kidneys (Figure 1K).
Figure 1 Differential Localization and Expression of CD36 Protein in Kidneys of Diabetic Mice with Glomerulopathy and of Humans with DNP
(A and B) Indirect double-immunofluorescence labeling of kidney sections from non-diabetic control (A) and diabetic (B) mice with anti-CD36 (green) and proximal tubular marker anti-aquaporin1 (red).
(C and D) Double labeling of non-diabetic control mice with anti-CD36 (green) and loop-of-Henle marker sodium potassium chloride cotransporter anti-NKCC (red) (C) and collecting duct marker aquaporin2 (red) (D) (arrow depicts colocalization of anti-CD36 and anti-aquaporin2 staining).
(E and F) Double labeling of human kidney sections from control individuals (E) and individuals with diabetes with DNP (F) using anti-CD36 (green) and anti-aquaporin1 (red).
(G) Higher-magnification image of (F) with arrows depicting colocalization of anti-CD36 and anti-aquaporin1. (Note that anti-CD36 labeling is heterogeneous: staining is isolated proximal tubular cells.)
(H–J) Representative images of anti-CD36 immunoperoxidase staining of sections of normal human kidney (H), human kidney with DNP (I), and human kidney with FSGS (J). Arrow in (I) depicts proximal tubular epithelial staining.
(K) CD36 PTEC expression score derived from blinded, semi-quantitative analysis of distribution and intensity of proximal tubular CD36 staining of human biopsy samples from ten normal control, ten DNP, and ten FSGS kidneys and the result shown on a dot plot. Significance was calculated by Wilcoxon Rank Sum Test, and PTEC scores for DNP kidneys were significantly different from those of FSGS kidneys and normal human kidneys.
Periodic acid–Schiff–stained sections of kidneys from mice exposed to type 2 diabetes (db/db mice) for 20 wk (Figure 2A), or type 1 diabetes (STZ-treated C57BL/6J mice) for 20 wk (data not shown) demonstrated moderate to advanced mesangial expansion and glomerulosclerosis (Figure 2A). Tubular abnormalities were not detectable in either model (Figure 2A). In contrast, TED and IF were associated with moderate to advanced mesangial expansion and glomerulosclerosis on kidney sections of human DNP (Figure 2B). These findings indicate that in humans with DNP, diabetes-induced upregulation of CD36 expression in proximal tubules was associated with moderate to advanced stages of TED and IF. In contrast, in diabetic mice with albuminuria, mesangial expansion, and glomerulosclerosis, absence of CD36 expression was associated with normal appearance of the tubular epithelium and interstitial space. These findings suggest an association between diabetes-induced proximal tubular CD36 expression and TED.
Figure 2 TED and IF Coincide with Proximal Tubular Apoptosis and CD36 Expression in Human DNP
(A and B) Periodic Acid–Schiff staining of diabetic mouse kidney (28-wk-old C57BLKS/J-leprdb/db) (A) and human DNP kidney (B). Arrowheads denote glomeruli with advanced mesangial expansion and glomerulosclerosis; arrows depict normal proximal tubule in diabetic mouse (A) and TED in human with DNP (B).
(C) TUNEL assay (green) and anti-CD36 (red) double labeling of human DNP. Arrows indicate apoptotic, CD36-positive tubular epithelial cells.
(D) TUNEL assay (green) and anti-aquaporin1 (red) double labeling of human DNP. Arrows depict TUNEL-positive and aquaporin1-positive PTECs.
(E) Dot plot indicates the number of TUNEL-positive tubular cells per 100 total tubular cells in kidneys of control (CTL) and diabetic (DM) mice and humans, as indicated.
Coincidence of Increased CD36 Expression and Increased Tubular Epithelial Cell Apoptosis in Human DNP
CD36 has been shown to mediate apoptosis signaling induced by TSP-1 in endothelial cells [8] and by ox-LDL in macrophages [14]. We examined whether the strong upregulation of CD36 protein in PTECs, observed specifically in human DNP, was associated with tubular epithelial cell apoptosis in vivo. TUNEL-positive tubular epithelial cells also stained positive for CD36 protein (Figure 2D) and aquaporin1 (Figure 2C), indicating that apoptosis and CD36 expression coincided in PTECs in human DNP. In contrast, CD36 was not detectable in TUNEL-positive PTECs in non-diabetic FSGS kidneys and in normal human kidney (data not shown). Statistical analysis showed that the rate of TUNEL-positive tubular cells was significantly increased in kidneys of human DNP compared with normal control human kidney (Figure 2E). In addition, tubular epithelial apoptosis was increased, but highly variable, in FSGS kidneys (data not shown). In contrast, tubular epithelial apoptosis rates were comparable between non-diabetic control and all diabetic mouse kidneys (Figure 2E). The diabetic mouse group included 24-wk-old STZ-treated diabetic C57BL/6J or 129SvJ mice (0.23 ± 0.1 TUNEL-positive cells per 100 tubular cells) and 24-wk-old leprdb/db mice (0.2 ± 0.1 TUNEL-positive cells per 100 tubular cells). Together, these findings indicate that CD36 expression in PTECs is associated with apoptotic events of proximal tubular cells and TED specifically in human DNP, but not in FSGS with matched functional and clinical abnormalities. These in vivo findings demonstrate a strong association of diabetes-induced CD36 expression and apoptosis in PTECs in human DNP, suggesting that CD36 may play a critical role in TED by mediating PTEC apoptosis in progressive human DNP.
High Ambient Glucose Induces CD36 Expression in Human PTECs
High ambient glucose has been shown to induce CD36 protein synthesis in macrophages [9]. Because CD36 protein was markedly increased in proximal tubules in human DNP, we examined the effects of high ambient glucose on CD36 mRNA and protein expression in the human PTEC line HK-2 (Figure 3). Exposure of cells to 30 mM D-glucose for 24 h, but not to control L-glucose, significantly increased levels of CD36 mRNA (Figure 3A), CD36 cell surface protein (Figure 3C), and CD36 protein expression in cell lysates (Figure 3D). In contrast, CD36 mRNA and protein were not detectable in the murine PTEC line MCT at either normal or high ambient glucose concentrations (data not shown). Interestingly, glucose stimulation decreased CD36 mRNA levels (Figure 3B) and CD36 cell surface protein (Figure 3C) in the murine collecting duct cell line M1, consistent with our previously reported findings in diabetic mouse kidney [5]. Exposure of human HK-2 and murine M1 cell lines to defined preparations of FFA PA or AGE-BSA had no effect on CD36 mRNA and protein expression levels (data not shown). These findings demonstrate that high ambient glucose causes upregulation of CD36 mRNA and protein specifically in human, but not in mouse, PTECs. Together with our in vivo observations, these results suggest that hyperglycemia may induce upregulation of CD36 mRNA and protein selectively in proximal tubules in kidneys of human DNP, but not diabetic mice with albuminuria.
Figure 3 CD36 mRNA and Protein Synthesis Is Stimulated in Human, but Not in Murine, PTECs, and Is Suppressed in Murine Collecting Duct Cells by High Ambient Glucose
(A) Relative CD36 mRNA abundance determined by quantitative real-time PCR in human PTEC line HK-2 treated with 30 mM D-glucose (open bars) or control L-glucose (black bars) for 4 and 24 h following maintenance of cells in 5 mM D-glucose medium. Bars represent mean ± SEM of three to five repeat experiments. Numbers on top of bars indicate significant p-values of experimental groups relative to 0 h.
(B) Bar graphs show experiment as described under (A), using mouse collecting duct cell line M1 instead of human HK-2 PTECs. The relative expression of CD36 was normalized to internal control housekeeping genes HPRT and beta actin, and to baseline controls (untreated cells).
(C) Relative cell surface expression of CD36 protein determined by FACS in M1 cells (open bars) and HK-2 cells (black bars) maintained in 5 mM D-glucose medium (CTL), or in medium containing 30 mM D-glucose (D-gluc) or L-glucose (L-gluc) for 72 h. (Original FACS histograms are provided in Figure S1.) Bars represent mean ± SEM of three to five repeat experiments. Numbers indicate significant p-values of experimental groups relative to control.
(D) Immunoblot showing CD36 protein levels in human HK-2 PTECs maintained in control 5 mM D-glucose (CTL), or after stimulation for 72 h with 30 mM L-glucose (L-gluc) or D-glucose (D-gluc), as indicated. Tubulin is shown for loading control. All data represent at least four independent repeat experiments.
AGE-BSA, CML-BSA, and FFA PA Induce Apoptosis in Human PTECs via CD36
AGE albumin [15] and FFAs [16] have been implicated in the pathogenesis of diabetic complications, including tubular degeneration [17] and tubular epithelial-to-mesenchymal transition [18]. In addition, AGE albumin and FFA are known to interact with CD36 [19,20]. However, it is not known whether AGE and/or FFA can activate CD36 signaling and apoptosis in tubular epithelial cells. Treatment with AGE-BSA for 2, 5, or 10 wk or with CML-BSA induced a significant increase in the number of apoptotic nuclei in CD36-positive HK-2 cells compared with control BSA-treated or untreated HK-2 cells (Figure 4A). In contrast, AGE-BSA and CML-BSA had no effect on the rate of apoptotic nuclei in CD36-negative murine MCT PTECs (data not shown). Because AGE-BSA glycated for 5 wk (AGE-BSA5) induced robust apoptosis at concentrations between 20 and 40 μM (Figure 4A), we chose this preparation and concentration for further analysis in all subsequent experiments. AGE-BSA5-induced apoptosis was blocked when cells were preincubated with neutralizing anti-CD36 antibody, while preincubation with control IgG antibody had no effect (Figure 4A). These results were confirmed by DNA laddering assay (data not shown).
Figure 4 AGE-BSA, CML-BSA, and FFA PA Induce Apoptosis in Human PTECs through CD36 Signaling
Bar graphs show mean ± SEM of apoptotic nuclei, visualized by DAPI staining and normalized to 100 total cells, in human HK-2 PTECs. Data are derived from three independent repeat experiments. Numbers on top of bars indicate significant p-values of experimental groups relative to control, or as indicated by bracket.
(A) Cells were treated for 48 h with control BSA (40 μM), TSP-1 (1 μg/ml), and AGE-BSA modified for 2, 5, or 10 weeks (AGE-BSA2, AGE-BSA5, and AGE-BSA10, respectively) in the absence or presence of control IgG (10 μg/ml) or anti-CD36 neutralizing antibody (10 μg/ml), as indicated.
(B) Cells were treated with control BSA (40 μM), or CMLmin-BSA at 0.5, 1, 2, 5, and 10 μM, in the absence or presence of anti-CD36 neutralizing antibody, as indicated.
(C) Cells were treated with monounsaturated FFA oleic acid (OA) or PA at increasing concentrations, in the absence or presence of control IgG (10 μg/ml) or anti-CD36 neutralizing antibody (10 μg/ml), as indicated.
Among the most abundant glucose-modified proteins detectable in the plasma of diabetic individuals are CML proteins [21], which are typically present at 1.6 to 2.3 μM concentrations in the plasma and urine of diabetic individuals [22,23]. To use physiologically relevant CML proteins in our in vitro experiments, we prepared CMLmin-BSA, characterized by glycation of approximately 30% of lysine residues [21]. When applied to HK-2 PTECs at concentrations ranging from 0.5 to 10 μM, CMLmin-BSA increased apoptosis rates significantly (Figure 4B). The proapoptotic effect of CMLmin-BSA was blocked by CD36 neutralizing antibody, but not by control IgG (Figure 4B).
CD36 has been shown to transport fatty acids in adipocytes [24] and in muscle cells [25]. Concentrations of FFAs may be substantially elevated, to levels of up to 700 μM, in individuals with type 2 diabetes or obesity [26]. Thus, we examined the effects of saturated FFA PA and monounsaturated FFA oleate on apoptosis of HK-2 PTECs in the absence or presence of anti-CD36 neutralizing antibody. PA significantly increased rates of apoptotic nuclei in a concentration-dependent manner in HK-2 PTECs (Figure 4C). Anti-CD36 neutralizing antibody, but not control IgG, blocked PA-induced apoptosis (Figure 4C). In contrast, oleate did not induce apoptosis, even at concentrations as high as 300 μM (Figure 4C), neither did it prevent PA-induced apoptosis (data not shown). Of note, these experiments were performed using a total fatty acid:BSA ratio of 6.6:1, in order to closely model pathophysiologic states in which unbound FFA concentration is high [27]. Taken together, our findings demonstrate that pathophysiologically relevant species of AGE-BSA and CML-BSA, as well as saturated FFA PA, induce apoptosis in human PTECs at concentrations previously observed in plasma and/or urine in humans with diabetes.
AGE-BSA and PA Sequentially Activate src kinase, Proapoptotic p38 MAPK, and Caspase 3 through CD36 Receptor
CD36 has previously been shown to trigger the activation of p59fyn, p38 MAPK, and caspase 3 (GeneID: 836) in response to thrombospondin in endothelial cells [8]. Therefore we examined phospho-src, phospho-p38 levels and caspase 3 activation in HK-2 PTECs treated with AGE-BSA and PA in the absence or presence of anti-CD36 neutralizing antibody. Both AGE-BSA5 and PA increased phospho-src levels rapidly (after as little as 5 min), and over a prolonged time interval (up to 3 h) (Figure 5A and 5B). Phosphorylation of src kinase was blocked by anti-CD36 neutralizing antibody (Figure 5A and 5B). This observation is consistent with previous findings demonstrating direct interaction between CD36 and p59fyn [8]; however, the involvement of other src kinases cannot be excluded. We also observed increased levels of phosphorylation of p38 MAPK beginning 1 to 2 h after treatment, and p38 activation was also completely blocked by anti-CD36 neutralizing antibody (Figure 5C and 5D). These findings indicate that CD36 activates proapoptotic p38 MAPK possibly via src kinase activation in human PTECs when stimulated with AGE-BSA5 and PA. Chemical inhibition of p38 MAPK prevented the increase in the rate of apoptotic nuclei induced by both AGE-BSA5 and PA in HK-2 PTECs (Figure 5G), indicating that p38 MAPK function is required for apoptosis induced by AGE-BSA and PA through CD36 receptor. AGE-BSA and PA significantly increased activity of effector caspase 3 in human PTECs (Figure 5E and 5F). Caspase 3 activation was blocked by anti-CD36 neutralizing antibody, but not by control IgG (Figure 5E and 5F). Pan-caspase inhibitor z-VAD-fmk and the specific caspase 3 inhibitor z-DEVD-fmk prevented apoptosis induced by PA and AGE-BSA, while the specific caspase 9 inhibitor z-LEHD-fmk had no significant inhibitor effect (Figure 5G). Together these findings indicate that CD36 receptor mediates sequential phosphorylation of src kinases and p38 MAPK, leading to activation of caspase 3 and apoptosis in human PTECs exposed to AGE-BSA and PA ligands. Interestingly, we did not observe phosphorylation of Smad2 and p42/44 ERK MAPK under these conditions, as previously reported for AGE binding to the RAGE receptor [28].
Figure 5 Activation of Intracellular Pathways following AGE-BSA and PA Treatment of Human HK-2 PTECs
(A and C) Immunoblots show levels of (A) phosphorylated (Y418) src kinase and tubulin or (C) phosphorylated p38 MAPK (pp38) and total p38 MAPK (p38) in HK-2 cells treated with AGE-BSA5 (40 μM) in the absence or presence of control IgG or anti-CD36 neutralizing antibody (10 μg/ml) for different time periods, as indicated.
(B and D) As shown in (A) and (C), except HK-2 cells were treated with PA (150 μM) instead of AGE-BSA5.
(E and F) Bar graphs demonstrate mean ± SEM of caspase 3 activity in three independent repeat experiments. Caspase 3 activity was measured by quantitative ELISA in HK-2 cells after 18 h of stimulation with AGE-BSA5 and PA, as per manufacturer's protocol. Numbers on top of bars indicate significant p-values of experimental groups relative to control, or as indicated by brackets.
(G) Bar graphs demonstrate number of apoptotic nuclei of HK-2 cells, normalized to 100 total cells, treated with AGE-BSA5 (40 μM) or PA (150 μM) in the absence (black bars) or presence of pan-caspase inhibitor (z-VAD-fmk [100 μM]; open bars), caspase 3 inhibitor (z-DEVD-fmk [20 μM]; first striped bars), caspase 9 inhibitor (z-LEHD-fmk (20 μM); gray bars), or chemical inhibitors of p38 MAPK (SB203580 [10 μM]; second striped bars). Mean ± SEM of three independent repeat experiments is presented. Numbers on top of bars indicate the significant p-values for comparison relative to control (no inhibitor).
CD36 Is Sufficient to Mediate Apoptosis Induced by AGE-BSA and FFA
In contrast with CD36-positive human HK-2 PTECs, we found that treatment of CD36-negative mouse MCT PTECs with AGE-BSA had no effect on rates of apoptotic nuclei (data not shown). To test whether CD36 was sufficient to mediate AGE-BSA-induced apoptosis, we transfected CD36-negative mouse MCT PTECs with a plasmid expressing human CD36 or empty control vector, followed by treatment with control BSA or AGE-BSA5. AGE-BSA5 treatment had no significant effect on rates of apoptotic nuclei in MCT PTECs transfected with control vector (Figure 6). In contrast, AGE-BSA significantly increased apoptotic nuclei compared with unglycated BSA in MCT PTECs transiently transfected with CD36 expression vector (Figure 6). Nonglycated control albumin did not cause apoptosis. Thus, transgenic de novo expression of human CD36 in CD36-negative mouse PTECs was sufficient to mediate apoptosis induced by AGE-BSA.
Figure 6 Expression of CD36 Transgene Confers Susceptibility to AGE-BSA-Induced Apoptosis
(A–D) Representative images show DAPI (A and C) and FITC (B and D) labeling of CD36-negative MCT cells treated with 40 μM AGE-BSA5 for 24 h after co-transfection with green fluorescent protein plasmid pEGFP and pcDNA3.1 empty control vector (A and B), or pEGFP and CD36 expression plasmid pcDNA3.1/CD36 (C and D).
(E) The dot plot shows results of four independent experiments where apoptotic nuclei per 100 total cells were quantitated in transfected cell cultures with or without treatments as indicated.
Discussion
Advanced diabetic nephropathies in humans with type 1 or type 2 diabetes are uniformly characterized by TED, or tubular atrophy, and IF leading to renal failure [29,30]. Although TED and IF are the strongest predictors for progression of DNP [31], mechanisms that underlie TED in DNP remain poorly understood. Based on our in vitro and in vivo findings we propose a two-step metabolic hit model for TED in DNP. High ambient glucose, but not AGE or FFA, cause stimulation of CD36 expression in PTECs specifically in diabetic kidneys. Increased CD36 expression mediates sequential activation of src kinase, proapoptotic p38 MAPK, and caspase 3 in PTECs in the presence of AGE and FFA PA, resulting in PTEC apoptosis. Proximal tubular epithelial apoptosis may be an initial mechanism for TED in DNP.
Our conclusions are supported by several key observations. First, we identify a new functional role for CD36 as an essential mediator of proximal tubular epithelial apoptosis, inducible by AGE-BSA, CMLmin-BSA, and FFA PA. Previous reports demonstrated a role for CD36 in mediating apoptosis induced by TSP-1 in endothelial cells and ox-LDL in macrophages [8,14]. In the present study, we show for the first time, to our knowledge, that CD36 mediates apoptosis in differentiated epithelial cells that are exposed to AGE-BSA-, CMLmin-BSA-, and FFA-induced metabolic injury characteristic of the diabetic milieu. Interestingly, AGE albumins and CML are present in the urine of individuals with diabetes with albuminuria due to DNP and have been shown to bind proximal tubular epithelium [22,32]. While the presence or absence of FFAs in the urine of diabetics with DNP has not been determined to date, FFAs may cause tubular apoptosis [33]. It remains to be determined whether FFA interacts with CD36 to activate CD36 receptor signaling, or whether CD36 mediates FFA uptake to activate src kinase and p38 MAPK signaling. Irrespective of the upstream mechanism of FFA and CD36 interaction, our results demonstrate very rapid activation of a well-characterized intracellular kinase cascade of proapoptotic signaling. Our finding that AGE-BSA and PA induce apoptosis through a CD36-mediated and p38- and caspase-dependent mechanism in tubular epithelial cells, similar to TSP-1 and ox-LDL in endothelial cells and macrophages, respectively, suggests that multiple, context-dependent extracellular stimuli of apoptosis may converge on CD36 scavenger receptor to activate src kinase and proapoptotic p38 MAPK pathway. In the context of the diabetic milieu and diabetic complications, our findings provide new molecular insights into diabetes-induced AGE- and FFA-dependent injury of renal epithelial cells.
Almost all TUNEL-positive apoptotic tubular epithelial cells showed increased expression of CD36, suggesting a strong correlation between upregulation of CD36 expression and increased apoptosis in PTECs specifically in human diabetic kidney in vivo. Importantly, biopsy samples from cases of FSGS that were matched for degree of proteinuria, renal function, and hypertension were characterized by TED, IF, and increased tubular epithelial apoptosis; however, proximal tubular CD36 expression was similar to that in normal human control kidney. Therefore, CD36 expression in PTECs is specifically associated with the diabetic condition and appears to be independent of degree of proteinuria and renal failure. Indeed, increased CD36 expression in PTECs in human DNP in vivo may be caused by hyperglycemia, as we show that high glucose concentration stimulates CD36 expression in vitro. It is intriguing that CD36 expression was not detected in PTECs in diabetic mice with longstanding hyperglycemia in vivo, although underlying mechanisms for the species-dependent differential regulation of CD36 in PTECs in vivo and in vitro between mouse and human remain unclear at this time. Comparisons of human CD36 and mouse Cd36 genes indicate a high degree of sequence and structural similarity in both coding and regulatory regions, suggesting that the mechanism or mechanisms that underlie our findings are likely determined by sequence-independent, epigenetically distinct response patterns to the diabetic milieu that differ between these species. It is also possible that dietary or metabolic factors account for the differences in CD36 expression, as mice were maintained on standard mouse chow characterized by significantly lower fat and cholesterol contents than typical western diets consumed by humans. However, dietary or other unknown environmental factors cannot explain the differential CD36 regulation by glucose in human and mouse PTECs. Thus, we are exploring whether biochemical or functional differences between mouse and human PTECs in glucose metabolism or glucose-induced signaling can be identified. However, current lack of understanding of the observed differential regulation between human and mouse does not diminish the translational research significance of our findings, with their clear therapeutic implications. Thus, the present study identifies a new CD36-dependent molecular signaling pathway that mediates tubular epithelial apoptosis, and may underlie TED and IF, hallmarks of disease progression, specifically in human diabetic nephropathy.
Third, to our knowledge, our report provides the first controlled study demonstrating increased apoptosis specifically in PTECs in DNP with TED and IF. These findings are consistent with a recent uncontrolled case series of five patients with DNP [34], and with previous reports demonstrating tubular apoptosis in kidneys of STZ-treated diabetic rats [35,36]. Interestingly, our study shows that tubular epithelial apoptosis was associated with TED and IF in human DNP, while normal appearance of tubular epithelium and interstitium was associated with baseline apoptosis rates in diabetic mouse models. Together, published observations from experimental diabetes models in mouse and rat, and human DNP, and our own findings in diabetic mouse models and human DNP, suggest a striking association of TED and tubular epithelial apoptosis. However, whether tubular epithelial apoptosis causes TED in DNP will require further investigation. Interestingly, acute and chronic chemical inhibition of caspase activity in a nephrotoxic serum nephritis model of chronic progressive glomerulonephritis with TED and IF reduced tubular apoptosis and TED [37]. Decreased tubular apoptosis and TED were associated with significantly reduced IF and decreased collagen synthesis in this model. This finding suggests that tubular epithelial apoptosis may trigger TED and IF in this model of chronic glomerulonephritis in rat, and supports our conclusions that diabetes-induced tubular epithelial apoptosis may underlie TED associated with IF in human DNP.
In conclusion, we report a new functional role for CD36 scavenger receptor in tubular epithelial apoptosis associated with tubular degeneration and progression of DNP. Specifically, we show for the first time that both AGE and FFA PA induce PTEC apoptosis through CD36-mediated activation of src kinase, p38 MAPK, and caspase 3. Because high glucose stimulates CD36 expression in human PTECs and because CD36 expression is increased in apoptotic tubular epithelial cells in human DNP, we propose a two-step metabolic hit model relevant for TED, a hallmark of progression of human DNP.
Supporting Information
Figure S1 Glucose Regulates CD36 Expression in Tubular Cells
Flow cytometric analysis of (A) human (HK-2) and (B) murine (M1) tubular epithelial cells incubated with control IgG (green curve) or with anti-CD36 antibody (FA6) (black curve) in medium containing 5 mM glucose (empty curve) or in medium containing 30 mM glucose (red curve) for 3 d.
(45 KB PPT).
Click here for additional data file.
Accession Numbers
The LocusLink (http://www.ncbi.nlm.nih.gov/LocusLink/) accession numbers for the gene products discussed in this paper are caspase 3 (GeneID: 836), CD36 (GeneID: 948), MAPK (GeneID: 1432), p42/44 ERK MAPK (GeneID: 50689), p59fyn (GeneID: 2534), and Smad2 (GeneID: 4087).
Patient Summary
Background
The kidneys are often affected in people with diabetes. Around one in three people with type 1 (juvenile, or insulin-dependent) and one in ten people with type 2 (late onset, or non-insulin-dependent) diabetes will develop kidney disease (called diabetic nephropathy). Diabetic nephropathy is one of the leading complications of diabetes and is the leading cause of kidney failure worldwide. Some risk factors make it more likely that certain people with diabetes will develop kidney disease—for example, kidney disease occurs more often in patients from South Asian or African backgrounds, in men, in patients with poor control of their blood sugar levels, and in those with high blood pressure or who smoke. However, the details of how, exactly, diabetes damages the kidneys are not clear.
What Did the Investigators Do?
They studied samples taken from the kidneys of humans and mice with and without diabetes and looked at the effects of high glucose concentrations on the cells in the kidneys. They found that in one part of the human kidneys high glucose caused a change in the cell surface causing an increase in a protein called CD36. This change occurred in the samples from people with diabetes, but did not occur in the samples from mice with diabetes. The investigators also found that some substances that are often found in the blood of people with diabetes could join to CD36; in doing so, these substances triggered the death of these cells, which is one of the first steps that occurs in diabetic nephropathy.
What Do These Findings Mean?
This particular protein (CD36) could have a central role in triggering diabetic nephropathy. Although there are no immediate clinical implications of this research for the treatment of people with kidney problems, this research helps in understanding how high glucose damages the kidney. In particular, it highlights how important it is to keep blood glucose levels as normal as possible.
Where Can I Get More Information?
Medline Plus's article on diabetic nephropathy: http://www.nlm.nih.gov/medlineplus/ency/article/000494.htm
Diabetes UK's online information centre: http://www.diabetes.org.uk/infocentre/index.html
National Diabetes Information Clearinghouse: http://diabetes.niddk.nih.gov/
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Animal Models of Diabetic Complications Consortium (AMDCC): http://www.amdcc.org/
We thank Dr. Michael Brownlee for helpful discussions and advice in preparing AGE-BSAs, Dr. Paul J. Thornalley for his advice on glycated proteins, and Dr. Nada Abumrad for providing CD36 expression plasmid. We are grateful to Mr. Chih-Kang Huang and Mrs. Yutong Zhang for expert technical support. K. Susztak was supported by the National Kidney Foundation and by an Albert Einstein College of Medicine Clinical Investigator Fellowship. This work was supported by National Institutes of Health grants R01 DK056077 and DK060043 (E. P. Böttinger), R01 DK053867 (K. Sharma) and U01 DK060995 (E. P. Böttinger and K. Sharma).
Citation: Susztak K, Ciccone E, McCue P, Sharma K, Böttinger EP (2005) Multiple metabolic hits converge on CD36 as novel mediator of tubular epithelial apoptosis in diabetic nephropathy. PLoS Med 2(2): e45.
Abbreviations
AGEadvanced glycation end
AGE-BSA5advanced glycation end–bovine serum albumin glycated for 5 wk
BSAbovine serum albumin
CMLcarboxymethyl-lysine
CLMminbovine serum albumin with minimal carboxymethyl-lysine content
DNPdiabetic nephropathy
FFAlong-chain free fatty acid
FSGSfocal segmental glomerulosclerosis
IFinterstitial fibrosis
MAPKMAP kinase
ox-LDLmodified (oxidized) low-density lipoprotein
PApalmitate
PTECproximal tubular epithelial cell
SEMstandard error of the mean
STZstreptozotocin
TEDtubular epithelial degeneration
TSP-1thrombospondin-1
==== Refs
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Gilbert RE Cooper ME The tubulointerstitium in progressive diabetic kidney disease: More than an aftermath of glomerular injury? Kidney Int 1999 56 1627 1637 10571771
Beyenbach KW Kidneys sans glomeruli Am J Physiol Renal Physiol 2004 286 F811 F827 15075177
Sharma K McCue P Dunn SR Diabetic kidney disease in the db/db mouse Am J Physiol Renal Physiol 2003 284 F1138 F1144 12736165
Susztak K Bottinger E Novetsky A Liang D Zhu Y Molecular profiling of diabetic mouse kidney reveals novel genes linked to glomerular disease Diabetes 2004 53 784 794 14988265
Febbraio M Hajjar DP Silverstein RL CD36: A class B scavenger receptor involved in angiogenesis, atherosclerosis, inflammation, and lipid metabolism J Clin Invest 2001 108 785 791 11560944
Savill J Hogg N Haslett C Macrophage vitronectin receptor, CD36, and thrombospondin cooperate in recognition of neutrophils undergoing programmed cell death Chest 1991 99 6S–7S
Jimenez B Volpert OV Crawford SE Febbraio M Silverstein RL Signals leading to apoptosis-dependent inhibition of neovascularization by thrombospondin-1 Nat Med 2000 6 41 48 10613822
Griffin E Re A Hamel N Fu C Bush H A link between diabetes and atherosclerosis: Glucose regulates expression of CD36 at the level of translation Nat Med 2001 7 840 846 11433350
Febbraio M Podrez EA Smith JD Hajjar DP Hazen SL Targeted disruption of the class B scavenger receptor CD36 protects against atherosclerotic lesion development in mice J Clin Invest 2000 105 1049 1056 10772649
Thornalley PJ Langborg A Minhas HS Formation of glyoxal, methylglyoxal and 3-deoxyglucosone in the glycation of proteins by glucose Biochem J 1999 344 109 116 10548540
Maedler K Oberholzer J Bucher P Spinas GA Donath MY Monounsaturated fatty acids prevent the deleterious effects of palmitate and high glucose on human pancreatic beta-cell turnover and function Diabetes 2003 52 726 733 12606514
Schiffer M Bitzer M Roberts IS Kopp JB ten Dijke P Apoptosis in podocytes induced by TGF-beta and Smad7 J Clin Invest 2001 108 807 816 11560950
Wintergerst ES Jelk J Rahner C Asmis R Apoptosis induced by oxidized low density lipoprotein in human monocyte-derived macrophages involves CD36 and activation of caspase-3 Eur J Biochem 2000 267 6050 6059 10998066
Brownlee M The pathological implications of protein glycation Clin Invest Med 1995 18 275 281 8549013
Listenberger LL Ory DS Schaffer JE Palmitate-induced apoptosis can occur through a ceramide-independent pathway J Biol Chem 2001 276 14890 14895 11278654
Kamijo A Kimura K Sugaya T Yamanouchi M Hase H Urinary free fatty acids bound to albumin aggravate tubulointerstitial damage Kidney Int 2002 62 1628 1637 12371963
Oldfield MD Bach LA Forbes JM Nikolic-Paterson D McRobert A Advanced glycation end products cause epithelial-myofibroblast transdifferentiation via the receptor for advanced glycation end products (RAGE) J Clin Invest 2001 108 1853 1863 11748269
Kuniyasu A Ohgami N Hayashi S Miyazaki A Horiuchi S CD36-mediated endocytic uptake of advanced glycation end products (AGE) in mouse 3T3-L1 and human subcutaneous adipocytes FEBS Lett 2003 537 85 90 12606036
Coort SL Willems J Coumans WA van der Vusse GJ Bonen A Sulfo-N-succinimidyl esters of long chain fatty acids specifically inhibit fatty acid translocase (FAT/CD36)-mediated cellular fatty acid uptake Mol Cell Biochem 2002 239 213 219 12479588
Thornalley PJ Battah S Ahmed N Karachalias N Agalou S Quantitative screening of advanced glycation endproducts in cellular and extracellular proteins by tandem mass spectrometry Biochem J 2003 375 581 592 12885296
Morcos M Sayed AA Bierhaus A Yard B Waldherr R Activation of tubular epithelial cells in diabetic nephropathy Diabetes 2002 51 3532 3544 12453911
Ahmed N Argirov OK Minhas HS Cordeiro CA Thornalley PJ Assay of advanced glycation endproducts (AGEs): Surveying AGEs by chromatographic assay with derivatization by 6-aminoquinolyl-N-hydroxy-succinimidyl-carbamate and application to Nepsilon-carboxymethyl-lysine- and Nepsilon-(1-carboxyethyl)lysine-modified albumin Biochem J 2002 364 1 14 11988070
Febbraio M Abumrad NA Hajjar DP Sharma K Cheng W A null mutation in murine CD36 reveals an important role in fatty acid and lipoprotein metabolism J Biol Chem 1999 274 19055 19062 10383407
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| 15737001 | PMC549593 | CC BY | 2021-01-05 10:39:29 | no | PLoS Med. 2005 Feb 22; 2(2):e45 | utf-8 | PLoS Med | 2,005 | 10.1371/journal.pmed.0020045 | oa_comm |
==== Front
PLoS MedPLoS MedpmedplosmedPLoS Medicine1549-12771549-1676Public Library of Science San Francisco, USA 1573700210.1371/journal.pmed.0020047Correspondence and Other CommunicationsNeurology/NeurosurgeryPathologyPathologyNeurologyFree Community Science and the Free Development of Science CorrespondenceStallman Richard
1
Free Software FoundationBoston, MassachusettsUnited States of AmericaE-mail: [email protected]
Competing Interests: I own stocks through mutual funds that are rather general, and I don't know what companies they invest in. My only professional relationships are with the Free Software Foundation (FSF) and the Union for the Public Domain. A list of the FSF's corporate donors can be found at http://www.fsf.org. I have received probably 60 different travel grants and honoraria this year. Most were from universities, conferences, and government bodies, but included also Google and OSDL.
2 2005 22 2 2005 2 2 e47Copyright: © 2005 Richard Stallman.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.
A Free Community Approach to Classifying Disease
==== Body
In free community science, where large numbers of scientists participate as volunteers in a single project, the ideal of scientific cooperation finds a new expression. Free community science was inspired by the free software movement, which itself was inspired by the application of the ideal of scientific cooperation, as it was applied to software development by the operating system developers of the Massachusetts Institute of Technology Artificial Intelligence Lab in the 1970s. This ideal has suffered for two decades from corporate pressure to privatize science, so it is very gratifying to see that the free software movement can today help reinvigorate the principle that inspired it.
The ideal of scientific cooperation goes beyond the conduct of individual projects. Scientific cooperation is also being reinvigorated today through the open-access movement, which promotes the public's freedom to redistribute scientific and scholarly articles. In the age of the computer networks, the best way to disseminate scientific writing is by making it freely accessible to all and letting everyone redistribute it. I give a vote of thanks to the Public Library of Science for leading the campaign that is now gaining momentum. When research funding agencies pressure journals to allow free redistribution of new articles they fund, they should apply this demand to the old articles “owned” by the same publishers—not just to papers published starting today.
Journal editors can promote scientific cooperation by adopting standards requiring internet publication of the supporting data and software for the articles they publish. The software and the data will be useful for other research. Moreover, research carried out using software cannot be checked or evaluated properly by other scientists unless they can read the source code that was used.
A significant impediment to publication and cooperation comes from university patent policies. Many universities hope to strike it rich with patents, but this is as foolish as playing the lottery, since most “technology licensing offices” don't even cover their operating costs. Like the Red Queen, these universities are running hard to stay in the same place. Society should recognize that funding university research through patents is folly, and should fund it directly, as in the past. Meanwhile, laws that encourage universities to seek patents at the expense of cooperation in research should be changed.
Another impediment comes from strings attached to corporate research funding. Universities or their public funding agencies should ensure private sponsors cannot block research they do not like. These sponsors must never have the power to veto or delay publication of results—or to intimidate the researchers. Thus, sponsors whose interests could be hurt by publication of certain possible results must never be in a position to cut the funding for a specific research group.
The free software movement, the free redistribution policy of this journal, and the practice of free community science for developing diagnostic disease classifications [1] are all based on the same fundamental principle: knowledge contributes to society when it can be shared and developed by communities. All three face opposition from those who would like to privatize knowledge and charge tolls for its use. In the free software movement we have 20 years' experience in resisting this opposition, and we have built up considerable strength and momentum. We can give the other two movements a boost, so they can advance more quickly.
Citation: Stallman R (2005) Free community science and the free development of science. PLoS Med 2(2): e47.
==== Refs
References
Graeber MB Lowe J Radotra B A free community approach to classifying disease PLoS Med 2004 1 e16 15578101
| 15737002 | PMC549594 | CC BY | 2021-01-05 10:39:29 | no | PLoS Med. 2005 Feb 22; 2(2):e47 | utf-8 | PLoS Med | 2,005 | 10.1371/journal.pmed.0020047 | oa_comm |
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PLoS MedPLoS MedpmedplosmedPLoS Medicine1549-12771549-1676Public Library of Science San Francisco, USA 1573700310.1371/journal.pmed.0020048Correspondence and Other CommunicationsOtherGeneral MedicineClinical TrialsMedical JournalsEditorial Policies (Including Conflicts of Interest)Unregistered Trials Are Unethical CorrespondenceKrishnan Eswar
1
Arthritis and Osteoporosis CenterReading, PennsylvaniaUnited States of AmericaE-mail: [email protected]
Competing Interests: I continue to work with the pharmaceutical industry in developing clinical protocols and enrolling patients for clinical trials. I have received monetary compensation for consulting for this activity.
2 2005 22 2 2005 2 2 e48Copyright: © 2005 Eswar Krishnan.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.
From Registration to Publication
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Current journal requirements forcing clinical trials to be registered [1] are insufficient and are unlikely to solve the problem of negative trials never even making it to a journal. Most of the patients consenting to clinical trials do so out of altruism. It is a great betrayal of their trust to suppress clinical trial data. I suggest that institutional review boards refuse to allow human experimentation unless the protocol is filed in a central (online) repository. The primary data should also be required to be in the public domain (say, within 1–2 years after completion). Data obtained by appealing to altrusitic instincts, similar to money in public charities, are not proprietary information, nor can physicians cash out the trust of their patients. In reality, it is the pharmaceutical industry that stands to gain the most if data are made public as such data inform future research and help smaller, innovative companies avoid redundancy. Voluntarily sticking to higher standards of ethics will raise societal respect for the industry (currently being battered for greed) and attract a more talented workforce, and may even help the current efforts to reform the tort law.
Citation: Krishnan E (2005) Unregistered trials are unethical. PLoS Med 2(2): e48.
==== Refs
References
From registration to publication PLoS Med 2004 1 e46 [No authors listed] 15578113
| 15737003 | PMC549595 | CC BY | 2021-01-05 10:40:28 | no | PLoS Med. 2005 Feb 22; 2(2):e48 | utf-8 | PLoS Med | 2,005 | 10.1371/journal.pmed.0020048 | oa_comm |
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