Dataset Information

Two independent alleles at 6q23 associated with risk of rheumatoid arthritis.

ABSTRACT: To identify susceptibility alleles associated with rheumatoid arthritis, we genotyped 397 individuals with rheumatoid arthritis for 116,204 SNPs and carried out an association analysis in comparison to publicly available genotype data for 1,211 related individuals from the Framingham Heart Study. After evaluating and adjusting for technical and population biases, we identified a SNP at 6q23 (rs10499194, approximately 150 kb from TNFAIP3 and OLIG3) that was reproducibly associated with rheumatoid arthritis both in the genome-wide association (GWA) scan and in 5,541 additional case-control samples (P = 10(-3), GWA scan; P < 10(-6), replication; P = 10(-9), combined). In a concurrent study, the Wellcome Trust Case Control Consortium (WTCCC) has reported strong association of rheumatoid arthritis susceptibility to a different SNP located 3.8 kb from rs10499194 (rs6920220; P = 5 x 10(-6) in WTCCC). We show that these two SNP associations are statistically independent, are each reproducible in the comparison of our data and WTCCC data, and define risk and protective haplotypes for rheumatoid arthritis at 6q23.

SUBMITTER: Plenge RM

PROVIDER: S-EPMC2652744 | biostudies-literature | 2007 Dec

REPOSITORIES: biostudies-literature

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Two independent alleles at 6q23 associated with risk of rheumatoid arthritis.

Plenge Robert M RM Cotsapas Chris C Davies Leela L Price Alkes L AL de Bakker Paul I W PI Maller Julian J Pe'er Itsik I Burtt Noel P NP Blumenstiel Brendan B DeFelice Matt M Parkin Melissa M Barry Rachel R Winslow Wendy W Healy Claire C Graham Robert R RR Neale Benjamin M BM Izmailova Elena E Roubenoff Ronenn R Parker Alexander N AN Glass Roberta R Karlson Elizabeth W EW Maher Nancy N Hafler David A DA Lee David M DM Seldin Michael F MF Remmers Elaine F EF Lee Annette T AT Padyukov Leonid L Alfredsson Lars L Coblyn Jonathan J Weinblatt Michael E ME Gabriel Stacey B SB Purcell Shaun S Klareskog Lars L Gregersen Peter K PK Shadick Nancy A NA Daly Mark J MJ Altshuler David D

Nature genetics 20071104 12

To identify susceptibility alleles associated with rheumatoid arthritis, we genotyped 397 individuals with rheumatoid arthritis for 116,204 SNPs and carried out an association analysis in comparison to publicly available genotype data for 1,211 related individuals from the Framingham Heart Study. After evaluating and adjusting for technical and population biases, we identified a SNP at 6q23 (rs10499194, approximately 150 kb from TNFAIP3 and OLIG3) that was reproducibly associated with rheumatoid ...[more]

PMID: 17982456

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Project description:INTRODUCTION: The gene MICA encodes the protein major histocompatibility complex class I polypeptide-related sequence A. It is expressed in synovium of patients with rheumatoid arthritis (RA) and its implication in autoimmunity is discussed. We analyzed the association of genetic variants of MICA with susceptibility to RA. METHODS: Initially, 300 French Caucasian individuals belonging to 100 RA trio families were studied. An additional 100 independent RA trio families and a German Caucasian case-control cohort (90/182 individuals) were available for replication. As MICA is situated in proximity to known risk alleles of the HLA-DRB1 locus, our analysis accounted for linkage disequilibrium either by analyzing the subgroup consisting of parents not carrying HLA-DRB1 risk alleles with transmission disequilibrium test (TDT) or by implementing a regression model including all available data. Analysis included a microsatellite polymorphism (GCT)n and single-nucleotide polymorphisms (SNPs) rs3763288 and rs1051794. RESULTS: In contrast to the other investigated polymorphisms, the non-synonymously coding SNP MICA-250 (rs1051794, Lys196Glu) was strongly associated in the first family cohort (TDT: P = 0.014; regression model: odds ratio [OR] 0.46, 95% confidence interval [CI] 0.25 to 0.82, P = 0.007). Although the replication family sample showed only a trend, combined family data remained consistent with the hypothesis of MICA-250 association independent from shared epitope (SE) alleles (TDT: P = 0.027; regression model: OR 0.56, 95% CI 0.38 to 0.83, P = 0.003). We also replicated the protective association of MICA-250A within a German Caucasian cohort (OR 0.31, 95% CI 0.1 to 0.7, P = 0.005; regression model: OR 0.6, 95% CI 0.37 to 0.96, P = 0.032). We showed complete linkage disequilibrium of MICA-250 (D' = 1, r2= 1) with the functional MICA variant rs1051792 (D' = 1, r2= 1). As rs1051792 confers differential allelic affinity of MICA to the receptor NKG2D, this provides a possible functional explanation for the observed association. CONCLUSIONS: We present evidence for linkage and association of MICA-250 (rs1051794) with RA independent of known HLA-DRB1 risk alleles, suggesting MICA as an RA susceptibility gene. However, more studies within other populations are necessary to prove the general relevance of this polymorphism for RA.

Project description:Rheumatoid arthritis (RA) is an autoimmune disease affecting approximately 1% of the population worldwide. Previously, we showed that human T-cell leukemia virus type I-transgenic mice and interleukin-1 receptor antagonist-knockout mice develop autoimmunity and joint-specific inflammation that resembles human RA. To identify genes involved in the pathogenesis of arthritis, we analyzed the gene expression profiles of these animal models by using high-density oligonucleotide arrays. We found 1,467 genes that were differentially expressed from the normal control mice by greater than threefold in one of these animal models. The gene expression profiles of the two models correlated well. We extracted 554 genes whose expression significantly changed in both models, assuming that pathogenically important genes at the effector phase would change in both models. Then, each of these commonly changed genes was mapped into the whole genome in a scale of the 1-megabase pairs. We found that the transcriptome map of these genes did not distribute evenly on the chromosome but formed clusters. These identified gene clusters include the major histocompatibility complex class I and class II genes, complement genes, and chemokine genes, which are well known to be involved in the pathogenesis of RA at the effector phase. The activation of these gene clusters suggests that antigen presentation and lymphocyte chemotaxis are important for the development of arthritis. Moreover, by searching for such clusters, we could detect genes with marginal expression changes. These gene clusters include schlafen and membrane-spanning four-domains subfamily A genes whose function in arthritis has not yet been determined. Thus, by combining two etiologically different RA models, we succeeded in efficiently extracting genes functioning in the development of arthritis at the effector phase. Furthermore, we demonstrated that identification of gene clusters by transcriptome mapping is a useful way to find potentially pathogenic genes among genes whose expression change is only marginal.

Dataset Information

Two independent alleles at 6q23 associated with risk of rheumatoid arthritis.

Publications

Two independent alleles at 6q23 associated with risk of rheumatoid arthritis.

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