High-density genetic mapping identifies new susceptibility loci for rheumatoid arthritis

Steve Eyre, John Bowes, Dorothée Diogo, Annette Lee, Anne Barton, Paul Martin, Alexandra Zhernakova, Eli Stahl, Sebastien Viatte, Kate McAllister, Christopher I Amos, Leonid Padyukov, Rene E M Toes, Tom W J Huizinga, Cisca Wijmenga, Gosia Trynka, Lude Franke, Harm-Jan Westra, Lars Alfredsson, Xinli Hu, Cynthia Sandor, Paul I W de Bakker, Sonia Davila, Chiea Chuen Khor, Khai Koon Heng, Robert Andrews, Sarah Edkins, Sarah E Hunt, Cordelia Langford, Deborah Symmons, Biologics in Rheumatoid Arthritis Genetics and Genomics Study Syndicate, Wellcome Trust Case Control Consortium, Pat Concannon, Suna Onengut-Gumuscu, Stephen S Rich, Panos Deloukas, Miguel A Gonzalez-Gay, Luis Rodriguez-Rodriguez, Lisbeth Ärlsetig, Javier Martin, Solbritt Rantapää-Dahlqvist, Robert M Plenge, Soumya Raychaudhuri, Lars Klareskog, Peter K Gregersen, Jane Worthington

Abstract

Using the Immunochip custom SNP array, which was designed for dense genotyping of 186 loci identified through genome-wide association studies (GWAS), we analyzed 11,475 individuals with rheumatoid arthritis (cases) of European ancestry and 15,870 controls for 129,464 markers. We combined these data in a meta-analysis with GWAS data from additional independent cases (n = 2,363) and controls (n = 17,872). We identified 14 new susceptibility loci, 9 of which were associated with rheumatoid arthritis overall and five of which were specifically associated with disease that was positive for anticitrullinated peptide antibodies, bringing the number of confirmed rheumatoid arthritis risk loci in individuals of European ancestry to 46. We refined the peak of association to a single gene for 19 loci, identified secondary independent effects at 6 loci and identified association to low-frequency variants at 4 loci. Bioinformatic analyses generated strong hypotheses for the causal SNP at seven loci. This study illustrates the advantages of dense SNP mapping analysis to inform subsequent functional investigations.

Figures

Figure 1. Manhattan plot of association statistics…
Figure 1. Manhattan plot of association statistics highlighting all autosomal loci associated to rheumatoid arthritis in the study
P values of association to ACPA positive rheumatoid arthritis from the meta-analysis of the Immunochip and GWAS data are shown. Known and new rheumatoid arthritis associated loci are shown in red and black respectively. Three associated loci (identified by a *) only reach P−8 when ACPA positive and ACPA negative cases are included in the analysis. The dashed grey line indicates genome-wide significance (P=5×10−8).

References

    1. Stahl EA, et al. Genome-wide association study meta-analysis identifies seven new rheumatoid arthritis risk loci. Nat. Genet. 2010;42:508–514.
    1. Zhernakova A, et al. Meta-analysis of genome-wide association studies in celiac disease and rheumatoid arthritis identifies fourteen non-HLA shared loci. PLoS. Genet. 2011;7:e1002004.
    1. Trynka G, et al. Dense genotyping identifies and localizes multiple common and rare variant association signals in celiac disease. Nat. Genet. 2011;43:1193–1201.
    1. Stahl EA, et al. Bayesian inference analyses of the polygenic architecture of rheumatoid arthritis. Nat. Genet. 2012
    1. Raychaudhuri S, et al. Five amino acids in three HLA proteins explain most of the association between MHC and seropositive rheumatoid arthritis. Nat. Genet. 2012;44:291–296.
    1. Padyukov L, et al. A genome-wide association study suggests contrasting associations in ACPA-positive versus ACPA-negative rheumatoid arthritis. Ann. Rheum. Dis. 2011;70:259–265.
    1. Jacob CO, et al. Identification of IRAK1 as a risk gene with critical role in the pathogenesis of systemic lupus erythematosus. Proc. Natl. Acad. Sci. U. S. A. 2009;106:6256–6261.
    1. Carrel L, Willard HF. X-inactivation profile reveals extensive variability in X-linked gene expression in females. Nature. 2005;434:400–404.
    1. Suzuki A, et al. Functional haplotypes of PADI4, encoding citrullinating enzyme peptidylarginine deiminase 4, are associated with rheumatoid arthritis. Nat. Genet. 2003;34:395–402.
    1. Kurreeman FA, et al. Use of a Multiethnic Approach to Identify Rheumatoid-Arthritis-Susceptibility Loci, 1p36 and 17q12. Am. J. Hum. Genet. 2012;90:524–532.
    1. Okada Y, et al. Meta-analysis identifies nine new loci associated with rheumatoid arthritis in the Japanese population. Nat. Genet. 2012
    1. Hingorani AD, Casas JP. The interleukin-6 receptor as a target for prevention of coronary heart disease: a mendelian randomisation analysis. Lancet. 2012;379:1214–1224.
    1. Sarwar N, et al. Interleukin-6 receptor pathways in coronary heart disease: a collaborative meta-analysis of 82 studies. Lancet. 2012;379:1205–1213.
    1. Ferreira MA, et al. Identification of IL6R and chromosome 11q13.5 as risk loci for asthma. Lancet. 2011;378:1006–1014.
    1. Stevens L, et al. Involvement of GATA3 in protein kinase C theta-induced Th2 cytokine expression. Eur. J. Immunol. 2006;36:3305–3314.
    1. Hu X, et al. Integrating autoimmune risk loci with gene-expression data identifies specific pathogenic immune cell subsets. Am. J. Hum. Genet. 2011;89:496–506.
    1. Heng TS, Painter MW. The Immunological Genome Project: networks of gene expression in immune cells. Nat. Immunol. 2008;9:1091–1094.
    1. Delaneau O, Marchini J, Zagury JF. A linear complexity phasing method for thousands of genomes. Nat. Methods. 2012;9:179–181.
    1. Marchini J, Howie B, Myers S, McVean G, Donnelly P. A new multipoint method for genome-wide association studies by imputation of genotypes. Nat. Genet. 2007;39:906–913.
    1. Purcell S, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 2007;81:559–575.
    1. de Bakker PI, et al. Practical aspects of imputation-driven meta-analysis of genome-wide association studies. Hum. Mol. Genet. 2008;17:R122–R128.
    1. Fehrmann RS, et al. Trans-eQTLs reveal that independent genetic variants associated with a complex phenotype converge on intermediate genes, with a major role for the HLA. PLoS. Genet. 2011;7:e1002197.

Source: PubMed

3
订阅