Dataset Information

Analysis of a genome-wide association study-linked locus (CCR6) in Asian rheumatoid arthritis.

ABSTRACT: A genome-wide association study in Japan identified the C-C chemokine receptor type 6 gene (CCR6) as associated with rheumatoid arthritis (RA). This finding has not been validated in other Asian populations. A case-control study involving 996 subjects, comprising 440 controls and 556 RA patients, was done to determine their anticyclic citrullinated peptide (anti-CCP) antibody status and CCR6 polymorphism (rs3093024) genotype. Three hundred eighty-seven patients were anti-CCP positive and 153 anti-CCP negative. Logistic regression showed that allele A was likely to increase the risk of developing RA among females via a recessive model (odds ratio [OR]=1.55, 95% confidence interval [CI]=1.01, 2.39), whereas the risk effect appeared to be reduced among males via an additive model (OR=0.60, 95% CI=0.42, 0.85). Considering only subjects who are anti-CCP positive, allele A increased RA risk among females via a recessive model (OR=1.68, 95% CI=1.07, 2.64) but decreased the risk among males via an additive model (OR=0.59, 95% CI=0.39, 0.89). We showed that CCR6 polymorphism was a risk factor among females but a protective factor among males. Functional studies are warranted to unravel the pathophysiological relevance of the gene variant and other linked variants with RA.

SUBMITTER: Teng E

PROVIDER: S-EPMC3322399 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature

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Analysis of a genome-wide association study-linked locus (CCR6) in Asian rheumatoid arthritis.

Teng Esther E Leong Khai Pang KP Li Hui Hua HH Thong Bernard B Koh Ee Tzun ET Loi Pooi Ling PL Zhao Yi Y Tan Eng King EK

DNA and cell biology 20111117 4

A genome-wide association study in Japan identified the C-C chemokine receptor type 6 gene (CCR6) as associated with rheumatoid arthritis (RA). This finding has not been validated in other Asian populations. A case-control study involving 996 subjects, comprising 440 controls and 556 RA patients, was done to determine their anticyclic citrullinated peptide (anti-CCP) antibody status and CCR6 polymorphism (rs3093024) genotype. Three hundred eighty-seven patients were anti-CCP positive and 153 ant ...[more]

PMID: 22092173

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Project description:ObjectiveRheumatoid arthritis (RA) is a complex autoimmune disease. Using a gene-based association research strategy, the present study aims to detect unknown susceptibility to RA and to address the ethnic differences in genetic susceptibility to RA between European and Asian populations.MethodsGene-based association analyses were performed with KGG 2.5 by using publicly available large RA datasets (14,361 RA cases and 43,923 controls of European subjects, 4,873 RA cases and 17,642 controls of Asian Subjects). For the newly identified RA-associated genes, gene set enrichment analyses and protein-protein interactions analyses were carried out with DAVID and STRING version 10.0, respectively. Differential expression verification was conducted using 4 GEO datasets. The expression levels of three selected 'highly verified' genes were measured by ELISA among our in-house RA cases and controls.ResultsA total of 221 RA-associated genes were newly identified by gene-based association study, including 71'overlapped', 76 'European-specific' and 74 'Asian-specific' genes. Among them, 105 genes had significant differential expressions between RA patients and health controls at least in one dataset, especially for 20 genes including 11 'overlapped' (ABCF1, FLOT1, HLA-F, IER3, TUBB, ZKSCAN4, BTN3A3, HSP90AB1, CUTA, BRD2, HLA-DMA), 5 'European-specific' (PHTF1, RPS18, BAK1, TNFRSF14, SUOX) and 4 'Asian-specific' (RNASET2, HFE, BTN2A2, MAPK13) genes whose differential expressions were significant at least in three datasets. The protein expressions of two selected genes FLOT1 (P value = 1.70E-02) and HLA-DMA (P value = 4.70E-02) in plasma were significantly different in our in-house samples.ConclusionOur study identified 221 novel RA-associated genes and especially highlighted the importance of 20 candidate genes on RA. The results addressed ethnic genetic background differences for RA susceptibility between European and Asian populations and detected a long list of overlapped or ethnic specific RA genes. The study not only greatly increases our understanding of genetic susceptibility to RA, but also provides important insights into the ethno-genetic homogeneity and heterogeneity of RA in both ethnicities.

Project description:GWAS owe their popularity to the expectation that they will make a major impact on diagnosis, prognosis and management of disease by uncovering genetics underlying clinical phenotypes. The dominant paradigm in GWAS data analysis so far consists of extensive reliance on methods that emphasize contribution of individual SNPs to statistical association with phenotypes. Multivariate methods, however, can extract more information by considering associations of multiple SNPs simultaneously. Recent advances in other genomics domains pinpoint multivariate causal graph-based inference as a promising principled analysis framework for high-throughput data. Designed to discover biomarkers in the local causal pathway of the phenotype, these methods lead to accurate and highly parsimonious multivariate predictive models. In this paper, we investigate the applicability of causal graph-based method TIE* to analysis of GWAS data. To test the utility of TIE*, we focus on anti-CCP positive rheumatoid arthritis (RA) GWAS datasets, where there is a general consensus in the community about the major genetic determinants of the disease.Application of TIE* to the North American Rheumatoid Arthritis Cohort (NARAC) GWAS data results in six SNPs, mostly from the MHC locus. Using these SNPs we develop two predictive models that can classify cases and disease-free controls with an accuracy of 0.81 area under the ROC curve, as verified in independent testing data from the same cohort. The predictive performance of these models generalizes reasonably well to Swedish subjects from the closely related but not identical Epidemiological Investigation of Rheumatoid Arthritis (EIRA) cohort with 0.71-0.78 area under the ROC curve. Moreover, the SNPs identified by the TIE* method render many other previously known SNP associations conditionally independent of the phenotype.Our experiments demonstrate that application of TIE* captures maximum amount of genetic information about RA in the data and recapitulates the major consensus findings about the genetic factors of this disease. In addition, TIE* yields reproducible markers and signatures of RA. This suggests that principled multivariate causal and predictive framework for GWAS analysis empowers the community with a new tool for high-quality and more efficient discovery.This article was reviewed by Prof. Anthony Almudevar, Dr. Eugene V. Koonin, and Prof. Marianthi Markatou.

Dataset Information

Analysis of a genome-wide association study-linked locus (CCR6) in Asian rheumatoid arthritis.

Publications

Analysis of a genome-wide association study-linked locus (CCR6) in Asian rheumatoid arthritis.

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