Genome-wide association study in a Korean population identifies six novel susceptibility loci for rheumatoid arthritis.

Genome-wide association study in a Korean population identifies six novel susceptibility loci for rheumatoid arthritis.
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DOI:
10.1136/annrheumdis-2020-217663
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发表时间:
2020-11
影响因子:
27.4
通讯作者:
Bae SC
Bae SC
中科院分区:
医学1区
文献类型:
--
作者:
Kwon YC;Lim J;Bang SY;Ha E;Hwang MY;Yoon K;Choe JY;Yoo DH;Lee SS;Lee J;Chung WT;Kim TH;Sung YK;Shim SC;Choi CB;Jun JB;Kang YM;Shin JM;Lee YK;Cho SK;Kim BJ;Lee HS;Kim K;Bae SC

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类风湿性关节炎(RA)的全基因组关联研究(GWAS)发现了100多个RA基因座,解释了患者相关的RA发病机制,但显示了很大一部分缺失的遗传性。作为一项持续的努力,我们在一个大型韩国RA病例对照人群中进行了GWAS。我们在两个独立的韩国队列中新生成了全基因组变异数据,包括4068例RA病例和36487例对照,随后进行了全基因组插补和两个队列中疾病关联结果的荟萃分析。通过将公开的组学数据与GWAS结果相结合,进行了一系列生物信息学分析,以优先考虑RA基因座中的RA风险基因,并剖析疾病相关的生物学机制。我们确定了6个新的RA风险位点(SLAMF 6,CXCL 13,SWAP 70,NFKBIA,ZFP 36 L1和LINC 00158),pmeta<5×10−8,两个队列中的疾病效应大小一致。根据物理距离、调节变体和染色质相互作用,从6个新的和13个复制的RA位点中总共优先考虑122个基因。生物信息学分析突出了RA相关基因的组织特异性表达的潜在RA相关组织(包括免疫组织、肺和小肠),并提示免疫相关基因集(如CD 40途径、IL-21介导的途径和瓜氨酸)和与其他疾病共享的风险等位基因。这项研究确定了六个新的RA相关基因座,有助于更好地了解RA的遗传病因学和生物学。
Genome-wide association studies (GWAS) in rheumatoid arthritis (RA) have discovered over 100 RA loci, explaining patient-relevant RA pathogenesis but showing a large fraction of missing heritability. As a continuous effort, we conducted GWAS in a large Korean RA case–control population. We newly generated genome-wide variant data in two independent Korean cohorts comprising 4068 RA cases and 36 487 controls, followed by a whole-genome imputation and a meta-analysis of the disease association results in the two cohorts. By integrating publicly available omics data with the GWAS results, a series of bioinformatic analyses were conducted to prioritise the RA-risk genes in RA loci and to dissect biological mechanisms underlying disease associations. We identified six new RA-risk loci (SLAMF6, CXCL13, SWAP70, NFKBIA, ZFP36L1 and LINC00158) with pmeta<5×10−8 and consistent disease effect sizes in the two cohorts. A total of 122 genes were prioritised from the 6 novel and 13 replicated RA loci based on physical distance, regulatory variants and chromatin interaction. Bioinformatics analyses highlighted potentially RA-relevant tissues (including immune tissues, lung and small intestine) with tissue-specific expression of RA-associated genes and suggested the immune-related gene sets (such as CD40 pathway, IL-21-mediated pathway and citrullination) and the risk-allele sharing with other diseases. This study identified six new RA-associated loci that contributed to better understanding of the genetic aetiology and biology in RA.
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