High-density genotyping of immune loci in Koreans and Europeans identifies eight new rheumatoid arthritis risk loci

Abstract

Objective: A highly polygenic aetiology and high degree of allele-sharing between ancestries have been well elucidated in genetic studies of rheumatoid arthritis. Recently, the high-density genotyping array Immunochip for immune disease loci identified 14 new rheumatoid arthritis risk loci among individuals of European ancestry. Here, we aimed to identify new rheumatoid arthritis risk loci using Korean-specific Immunochip data.

Methods: We analysed Korean rheumatoid arthritis case-control samples using the Immunochip and genome-wide association studies (GWAS) array to search for new risk alleles of rheumatoid arthritis with anticitrullinated peptide antibodies. To increase power, we performed a meta-analysis of Korean data with previously published European Immunochip and GWAS data for a total sample size of 9299 Korean and 45,790 European case-control samples.

Results: We identified eight new rheumatoid arthritis susceptibility loci (TNFSF4, LBH, EOMES, ETS1-FLI1, COG6, RAD51B, UBASH3A and SYNGR1) that passed a genome-wide significance threshold (p<5×10(-8)), with evidence for three independent risk alleles at 1q25/TNFSF4. The risk alleles from the seven new loci except for the TNFSF4 locus (monomorphic in Koreans), together with risk alleles from previously established RA risk loci, exhibited a high correlation of effect sizes between ancestries. Further, we refined the number of single nucleotide polymorphisms (SNPs) that represent potentially causal variants through a trans-ethnic comparison of densely genotyped SNPs.

Conclusions: This study demonstrates the advantage of dense-mapping and trans-ancestral analysis for identification of potentially causal SNPs. In addition, our findings support the importance of T cells in the pathogenesis and the fact of frequent overlap of risk loci among diverse autoimmune diseases.

Keywords: Ant-CCP; Gene Polymorphism; Rheumatoid Arthritis.

Figure 1

Manhattan plot from the meta-analysis of the Korean and European datasets. Newly identified and known RA risk loci passing the genome-wide significance level (p < 5×10⁻⁸) are shown with the locus names in red and black, respectively. The dashed gray line indicates the genome-wide significance threshold.

Figure 2

Forest plots of the 8 lead SNPs for the 13 independent collections. ORs of the lead SNP in each RA susceptibility locus (A-H) were shown for each individual collection as well as the meta-analysis across the sample collections. Locus and SNP name are shown in the top of each plot. The OR patterns for Korean and European collections are on the blue and pink background, respectively.

Figure 3

Overlap of proxy SNPs shared in the ancestries and regulatory SNPs in the SYNGR1 locus. (A) Regional association plot for the meta-analysis for the RPL3-SYNGR1 locus in the chromosome 22. The best hit was found at rs909685 in the intron of SYNGR1. The 13-kb region containing all proxy SNPs of rs909685 was highlighted with pink. Coordinates are based on the hg19 assembly. (B) The proxy SNPs (circle) correlated with the lead SNP rs909685 in Korean and/or European (r² ≥ 0.9). The two proxy SNPs, rs909685 (red) and rs2069235 (orange), were observed in both population in contrast to the others (grey). (C) The functional annotation of the proxy SNPs. Each proxy SNP was annotated for that it significantly alters the transcription factor binding motifs by the alleles and that it is in histone-mark region, DNase-hypersensitive site (DHS), Protein-binding site and eQTL.