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Guo J, Zhang T, Cao H, Li X, Liang H, Liu M, Zou Y, Zhang Y, Wang Y, Sun X, Hu F, Du Y, Mo X, Liu X, Yang Y, Yang H, Wu X, Zhang X, Jia H, Jiang H, Hou Y, Liu X, Su Y, Zhang M, Yang H, Wang J, Sun L, Liu L, Padyukov L, Lai L, Yamamoto K, Zhang X, Klareskog L, Xu X, Li Z. Sequencing of the MHC region defines HLA-DQA1 as the major genetic risk for seropositive rheumatoid arthritis in Han Chinese population. Ann Rheum Dis 2019; 78:773-780. [PMID: 30936065 DOI: 10.1136/annrheumdis-2018-214725] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Revised: 03/06/2019] [Accepted: 03/09/2019] [Indexed: 12/17/2022]
Abstract
OBJECTIVE The strong genetic contribution of the major histocompatibility complex (MHC) region to rheumatoid arthritis (RA) has been generally attributed to human leukocyte antigen (HLA)-DRB1. However, due to the high polymorphisms and linkage disequilibrium within MHC, it is difficult to define novel and/or independent genetic risks using conventional HLA genotyping or chip-based microarray technology. This study aimed to identify novel RA risk variants by performing deep sequencing for MHC. METHODS We first conducted target sequencing for the entire MHC region in 357 anticitrullinated protein antibodies (ACPA)-positive patients with RA and 1001 healthy controls, and then performed HLA typing in an independent case-control cohort consisting of 1415 samples for validation. All study subjects were Han Chinese. Genetic associations for RA susceptibility and severity were analysed. Comparative modelling was constructed to predict potential functions for the newly discovered RA association variants. RESULTS HLA-DQα1:160D conferred the strongest and independent susceptibility to ACPA-positive RA (p=6.16×10-36, OR=2.29). DRβ1:37N had an independent protective effect (p=5.81×10-16, OR=0.49). As predicted by comparative modelling, the negatively charged DQα1:160D stabilises the dimer of dimers, thus may lead to an increased T cell activation. The negatively charged DRβ1:37N encoding alleles preferentially bind with epitope P9 arginine, thus may result in a decreased RA susceptibility. CONCLUSIONS We provide the first evidence that HLA-DQα1:160D, instead of HLA-DRB1*0405, is the strongest and independent genetic risk for ACPA-positive RA in Han Chinese. Our study also illustrates the value of deep sequencing for fine-mapping disease risk variants in the MHC region.
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Affiliation(s)
- Jianping Guo
- Department of Rheumatology and Immunology, Peking University People's Hospital, Beijing, China .,Beijing Key Laboratory for Rheumatism Mechanism and Immune Diagnosis (BZ0135), Beijing, China
| | - Tao Zhang
- Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, China.,China National GeneBank-Shenzhen, BGI-Shenzhen, Shenzhen, China
| | - Hongzhi Cao
- Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, China.,Shenzhen Digital Life Institute, Shenzhen, China.,iCarbonX, Shenzhen, China
| | - Xiaowei Li
- Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, China.,China National GeneBank-Shenzhen, BGI-Shenzhen, Shenzhen, China
| | - Hao Liang
- BNLMS, State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Peking-Tsinghua Center for Life Sciences at College of Chemistry and Molecular Engineering, and Center for Quantitative Biology, Peking University, Beijing, China
| | - Mengru Liu
- Department of Rheumatology and Immunology, Peking University People's Hospital, Beijing, China
| | - Yundong Zou
- Department of Rheumatology and Immunology, Peking University People's Hospital, Beijing, China
| | - Yuanwei Zhang
- Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, China.,China National GeneBank-Shenzhen, BGI-Shenzhen, Shenzhen, China
| | - Yuxuan Wang
- Department of Rheumatology and Immunology, Peking University People's Hospital, Beijing, China
| | - Xiaolin Sun
- Department of Rheumatology and Immunology, Peking University People's Hospital, Beijing, China.,Beijing Key Laboratory for Rheumatism Mechanism and Immune Diagnosis (BZ0135), Beijing, China
| | - Fanlei Hu
- Department of Rheumatology and Immunology, Peking University People's Hospital, Beijing, China.,Beijing Key Laboratory for Rheumatism Mechanism and Immune Diagnosis (BZ0135), Beijing, China
| | - Yan Du
- Department of Rheumatology and Immunology, Peking University People's Hospital, Beijing, China
| | - Xiaodong Mo
- Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, China.,China National GeneBank-Shenzhen, BGI-Shenzhen, Shenzhen, China
| | - Xu Liu
- Department of Rheumatology and Immunology, Peking University People's Hospital, Beijing, China
| | - Yue Yang
- Department of Rheumatology and Immunology, Peking University People's Hospital, Beijing, China
| | - Huanjie Yang
- Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, China.,China National GeneBank-Shenzhen, BGI-Shenzhen, Shenzhen, China
| | - Xinyu Wu
- Department of Rheumatology and Immunology, Peking University People's Hospital, Beijing, China
| | - Xuewu Zhang
- Department of Rheumatology and Immunology, Peking University People's Hospital, Beijing, China
| | - Huijue Jia
- Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, China.,China National GeneBank-Shenzhen, BGI-Shenzhen, Shenzhen, China
| | - Hui Jiang
- Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, China.,China National GeneBank-Shenzhen, BGI-Shenzhen, Shenzhen, China
| | - Yong Hou
- Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, China.,China National GeneBank-Shenzhen, BGI-Shenzhen, Shenzhen, China
| | - Xin Liu
- Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, China.,China National GeneBank-Shenzhen, BGI-Shenzhen, Shenzhen, China
| | - Yin Su
- Department of Rheumatology and Immunology, Peking University People's Hospital, Beijing, China.,Beijing Key Laboratory for Rheumatism Mechanism and Immune Diagnosis (BZ0135), Beijing, China
| | - Mingrong Zhang
- Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, China.,China National GeneBank-Shenzhen, BGI-Shenzhen, Shenzhen, China
| | - Huanming Yang
- Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, China.,James D Watson Institute of Genome Sciences, Hangzhou, China
| | - Jian Wang
- Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, China.,James D Watson Institute of Genome Sciences, Hangzhou, China
| | - Liangdan Sun
- Institute of Dermatology and Department of Dermatology, No 1 Hospital of Anhui Medical University, Hefei, China
| | - Liang Liu
- State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Macau, China
| | - Leonid Padyukov
- Rheumatology Unit, Department of Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Luhua Lai
- BNLMS, State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Peking-Tsinghua Center for Life Sciences at College of Chemistry and Molecular Engineering, and Center for Quantitative Biology, Peking University, Beijing, China
| | - Kazuhiko Yamamoto
- Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Xuejun Zhang
- Institute of Dermatology and Department of Dermatology, No 1 Hospital of Anhui Medical University, Hefei, China .,Institute of Dermatology and Department of Dermatology, Huashan Hospital, Fudan University, Shanghai, China
| | - Lars Klareskog
- Rheumatology Unit, Department of Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Xun Xu
- Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, China .,China National GeneBank-Shenzhen, BGI-Shenzhen, Shenzhen, China
| | - Zhanguo Li
- Department of Rheumatology and Immunology, Peking University People's Hospital, Beijing, China .,Beijing Key Laboratory for Rheumatism Mechanism and Immune Diagnosis (BZ0135), Beijing, China.,Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China.,State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, Beijing, China
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