한빛사 논문
Young-Chang Kwon1, Jiwoo Lim2, So-Young Bang1,3, Eunji Ha2, Mi Yeong Hwang4, Kyungheon Yoon4, Jung-Yoon Choe5, Dae-Hyun Yoo1,3, Shin-Seok Lee6, Jisoo Lee7, Won Tae Chung8, Tae-Hwan Kim1,3, Yoon-Kyoung Sung1,3, Seung-Cheol Shim9, Chan-Bum Choi1,3, Jae-Bum Jun1,3, Young Mo Kang10, Jung-Min Shin3, Yeon-Kyung Lee3, Soo-Kyung Cho1,3, Bong-Jo Kim4, Hye-Soon Lee1,3, Kwangwoo Kim2,*, Sang-Cheol Bae1,3,*
1Hanyang University Institute for Rheumatology Research, Seoul, Republic of Korea
2Department of Biology and Department of Life and Nanopharmaceutical Sciences, Kyung Hee University, Seoul, Republic of Korea
3Department of Rheumatology, Hanyang University Hospital for Rheumatic Diseases, Seoul, Republic of Korea
4Division of Genome Research, Center for Genome Science, National Institute of Health, Osong Health Technology Administration Complex, Cheongju, Republic of Korea
5Department of Rheumatology, Catholic University of Daegu School of Medicine, Daegu, Republic of Korea
6Division of Rheumatology, Department of Internal Medicine, Chonnam National University Medical School and Hospital, Gwangju, Republic of Korea
7Division of Rheumatology, Ewha Womans University School of Medicine, Seoul, Republic of Korea
8Department of Internal Medicine, Dong-A University Hospital, Busan, Republic of Korea
9Division of Rheumatology, Department of Internal Medicine, Chungnam National University Hospital, Daejeon, Republic of Korea
10Division of Rheumatology, Department of Internal Medicine, Kyungpook National University Hospital, Daegu, Republic of Korea
Y-CK, JL and S-YB contributed equally.
*Corresponding author
Abstract
Objective
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.
Methods
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.
Results
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.
Conclusion
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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TOP52020년 후보
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