Dataset Information

Visualizing human leukocyte antigen class II risk haplotypes in human systemic lupus erythematosus.

ABSTRACT: Human leukocyte antigen (HLA) class I and class II alleles are implicated as genetic risk factors for many autoimmune diseases. However, the role of the HLA loci in human systemic lupus erythematosus (SLE) remains unclear. Using a dense map of polymorphic microsatellites across the HLA region in a large collection of families with SLE, we identified three distinct haplotypes that encompassed the class II region and exhibited transmission distortion. DRB1 and DQB1 typing of founders showed that the three haplotypes contained DRB1*1501/ DQB1*0602, DRB1*0801/ DQB1*0402, and DRB1*0301/DQB1*0201 alleles, respectively. By visualizing ancestral recombinants, we narrowed the disease-associated haplotypes containing DRB1*1501 and DRB1*0801 to an approximately 500-kb region. We conclude that HLA class II haplotypes containing DRB1 and DQB1 alleles are strong risk factors for human SLE.

SUBMITTER: Graham RR

PROVIDER: S-EPMC379191 | biostudies-literature | 2002 Sep

REPOSITORIES: biostudies-literature

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Visualizing human leukocyte antigen class II risk haplotypes in human systemic lupus erythematosus.

Graham Robert R RR Ortmann Ward A WA Langefeld Carl D CD Jawaheer Damini D Selby Scott A SA Rodine Peter R PR Baechler Emily C EC Rohlf Kristine E KE Shark Katherine B KB Espe Karl J KJ Green Linda E LE Nair Rajan P RP Stuart Philip E PE Elder James T JT King Richard A RA Moser Kathy L KL Gaffney Patrick M PM Bugawan Teodorica L TL Erlich Henry A HA Rich Stephen S SS Gregersen Peter K PK Behrens Timothy W TW

American journal of human genetics 20020726 3

Human leukocyte antigen (HLA) class I and class II alleles are implicated as genetic risk factors for many autoimmune diseases. However, the role of the HLA loci in human systemic lupus erythematosus (SLE) remains unclear. Using a dense map of polymorphic microsatellites across the HLA region in a large collection of families with SLE, we identified three distinct haplotypes that encompassed the class II region and exhibited transmission distortion. DRB1 and DQB1 typing of founders showed that t ...[more]

PMID: 12145745

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Project description:Class II human leukocyte antigens (HLA II) are proteins involved in the human immunological adaptive response by binding and exposing some pre-processed, non-self peptides in the extracellular domain in order to make them recognizable by the CD4+ T lymphocytes. However, the understanding of HLA-peptide binding interaction is a crucial step for designing a peptide-based vaccine because the high rate of polymorphisms in HLA class II molecules creates a big challenge, even though the HLA II proteins can be grouped into supertypes, where members of different class bind a similar pool of peptides. Hence, first we performed the supertype classification of 27 HLA II proteins using their binding affinities and structural-based linear motifs to create a stable group of supertypes. For this purpose, a well-known clustering method was used, and then, a consensus was built to find the stable groups and to show the functional and structural correlation of HLA II proteins. Thus, the overlap of the binding events was measured, confirming a large promiscuity within the HLA II-peptide interactions. Moreover, a very low rate of locus-specific binding events was observed for the HLA-DP genetic locus, suggesting a different binding selectivity of these proteins with respect to HLA-DR and HLA-DQ proteins. Secondly, a predictor based on a support vector machine (SVM) classifier was designed to recognize HLA II-binding peptides. The efficiency of prediction was estimated using precision, recall (sensitivity), specificity, accuracy, F-measure, and area under the ROC curve values of random subsampled dataset in comparison with other supervised classifiers. Also the leave-one-out cross-validation was performed to establish the efficiency of the predictor. The availability of HLA II-peptide interaction dataset, HLA II-binding motifs, high-quality amino acid indices, peptide dataset for SVM training, and MATLAB code of the predictor is available at http://sysbio.icm.edu.pl/HLA .

Project description:BACKGROUND:Associations between human leukocyte antigens (HLA) alleles and cervical cancer are largely representative of squamous cell carcinoma (SCC), the major histologic subtype. We evaluated the association between HLA class I (A, B, and C) and class II (DRB1 and DQB1) loci and risk of cervical adenocarcinoma (ADC), a less common but aggressive histologic subtype. METHODS:We pooled data from the Eastern and Western US Cervical Cancer studies, and evaluated the association between individual alleles and allele combinations and ADC (n = 630 ADC; n = 775 controls). Risk estimates were calculated for 11 a priori (based on known associations with cervical cancer regardless of histologic type) and 38 non a priori common alleles, as odds ratios (OR) and 95% confidence intervals (CI), adjusted for age and study. In exploratory analysis, we compared the risk associations between subgroups with HPV16 or HPV18 DNA in ADC tumor tissues in the Western US study cases and controls. RESULTS:Three of the a priori alleles were significantly associated with decreased risk of ADC [DRB1*13:01 (OR = 0.61; 95% CI: 0.41-0.93), DRB1*13:02 (OR = 0.49; 95% CI: 0.31-0.77), and DQB1*06:03 (OR = 0.64; 95% CI: 0.42-0.95)]; one was associated with increased risk [B*07:02 (OR = 1.39; 95% CI: 1.07-1.79)]. Among alleles not previously reported, DQB1*06:04 (OR = 0.46; 95% CI: 0.27-0.78) was associated with decreased risk of ADC and remained significant after correction for multiple comparisons, and C*07:02 (OR = 1.41; 95% CI: 1.09-1.81) was associated with increased risk. We did not observe a difference by histologic subtype. ADC was most strongly associated with increased risk with B*07:02/C*07:02 alleles (OR = 1.33; 95% CI: 1.01-1.76) and decreased risk with DRB1*13:02/DQB1*06:04 (OR = 0.41; 95% CI: 0.21-0.80). CONCLUSION:RESULTS suggest that HLA allele associations with cervical ADC are similar to those for cervical SCC. An intriguing finding was the difference in risk associated with several alleles restricted to HPV16 or HPV18-related tumors, consistent with the hypothesis that HLA recognition is HPV type-specific.

Project description:The diagnosis of Systemic Lupus Erythematosus (SLE) is challenging due to its heterogeneous clinical presentation and lack of robust biomarkers for laboratory testing to distinguish it from other autoimmune or infectious diseases. Current diagnostic criterion relies on a combination of clinical examination and laboratory tests, and it does not readily distinguish between those with active clinical disease from those that are clinically quiescent. Several groups have attempted to apply emerging high throughput profiling technologies to diagnose SLE. Despite showing promising diagnostic potential, many of them are expensive and technically challenging for routine clinical uses. Here we report a pilot study of applying a technically simple and highly customisable leukocyte capture antibody microarray to profile healthy (n=24) and SLE patients (n=60) of various disease activities. Our analysis reveals a set of surface antigen biomarkers that have significant association with SLE. In addition, we present a computational method to calculate a score from the entire microarray profile to obtain a score that correlate most reliably with SLE disease activity. Although the current version of our microarray alone does not match the discriminatory power of the standard laboratory tests (serum dsDNA, complements C3 and C4), the combination of the two yields a test with significantly increased discriminatory ability than what can be achieved individually. This work paves the way for a customised SLE-specific antibody microarray for accurate diagnosis and monitoring of SLE that can be readily translated to routine clinical use. Blood samples were collected from 60 patients of Systemic Lupus Erythematosus (SLE) of different disease activity (11 active, 16 semi-active, and 33 inactive), and compared it with blood samples from 24 healthy blood donors. For each subject, we extracted PBMCs and apply them to a leukocyte capture antibody microarray. The microarray was then scaned by a DotScan™ slide reader (Medsaic; Eveleigh, NSW, Australia). The number of immobilized cells was proportional to the light scattered at each antibody spot. Binding of PBMCs to each antibody dot was monitored by light scatter and averaged between the duplicate spots on each slide. We then performed statistical analysis to identify CD antigen markers that are associated with SLE, as well as determining the potential diagnostic ability of this microarray for SLE.

Dataset Information

Visualizing human leukocyte antigen class II risk haplotypes in human systemic lupus erythematosus.

Publications

Visualizing human leukocyte antigen class II risk haplotypes in human systemic lupus erythematosus.

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