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Sequencing of the MHC region defines HLA-DQA1 as the major genetic risk for seropositive rheumatoid arthritis in Han Chinese population
  1. Jianping Guo1,2,
  2. Tao Zhang3,4,
  3. Hongzhi Cao3,5,6,
  4. Xiaowei Li3,4,
  5. Hao Liang7,
  6. Mengru Liu1,
  7. Yundong Zou1,
  8. Yuanwei Zhang3,4,
  9. Yuxuan Wang1,
  10. Xiaolin Sun1,2,
  11. Fanlei Hu1,2,
  12. Yan Du1,
  13. Xiaodong Mo3,4,
  14. Xu Liu1,
  15. Yue Yang1,
  16. Huanjie Yang3,4,
  17. Xinyu Wu1,
  18. Xuewu Zhang1,
  19. Huijue Jia3,4,
  20. Hui Jiang3,4,
  21. Yong Hou3,4,
  22. Xin Liu3,4,
  23. Yin Su1,2,
  24. Mingrong Zhang3,4,
  25. Huanming Yang3,8,
  26. Jian Wang3,8,
  27. Liangdan Sun9,
  28. Liang Liu10,
  29. Leonid Padyukov11,
  30. Luhua Lai7,
  31. Kazuhiko Yamamoto12,
  32. Xuejun Zhang9,13,
  33. Lars Klareskog11,
  34. Xun Xu3,4,
  35. Zhanguo Li1,2,14,15
  1. 1 Department of Rheumatology and Immunology, Peking University People's Hospital, Beijing, China
  2. 2 Beijing Key Laboratory for Rheumatism Mechanism and Immune Diagnosis (BZ0135), Beijing, China
  3. 3 Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, China
  4. 4 China National GeneBank-Shenzhen, BGI-Shenzhen, Shenzhen, China
  5. 5 Shenzhen Digital Life Institute, Shenzhen, China
  6. 6 iCarbonX, Shenzhen, China
  7. 7 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
  8. 8 James D Watson Institute of Genome Sciences, Hangzhou, China
  9. 9 Institute of Dermatology and Department of Dermatology, No 1 Hospital of Anhui Medical University, Hefei, China
  10. 10 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
  11. 11 Rheumatology Unit, Department of Medicine, Karolinska Institutet, Stockholm, Sweden
  12. 12 Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
  13. 13 Institute of Dermatology and Department of Dermatology, Huashan Hospital, Fudan University, Shanghai, China
  14. 14 Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
  15. 15 State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, Beijing, China
  1. Correspondence to Professor Jianping Guo, Department of Rheumatology and Immunology, Peking University People's Hospital, Beijing 100044, China; jianping.guo{at}bjmu.edu.cn; Dr Xuejun Zhang, Institute of Dermatology and Department of Dermatology, No 1 Hospital of Anhui Medical University, Hefei 230032, China; ayzxj{at}vip.sina.com; Professor Lars Klareskog, Rheumatology Unit, Department of Medicine, Karolinska Institutet, Stockholm 171 76, Sweden; lars.klareskog{at}ki.se; Dr Xun Xu, Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen 518000, China; xuxun{at}genomics.cn; Professor Zhanguo Li, Department of Rheumatology and Immunology, Peking University People's Hospital, Beijing 100044, China; zli99{at}bjmu.edu.cn

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.

  • rheumatoid arthritis
  • gene polymorphism
  • ant-ccp

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Footnotes

  • JG, TZ, HC, XL and HL contributed equally.

  • Handling editor Josef S Smolen

  • Contributors JG, XX and ZL conceptualised and designed the study. XJZ and LK participated in the study design and supervised manuscript writing. JG, TZ and HC coordinated and supervised the study teams. JG, XWL, TZ, HL and HC conducted data management and manuscript preparation. TZ, XWL, YWZ, XM and HJY conducted the statistical analyses. HMY, HJJ, JW, LS, LP, LHL, LL and KY participated in data interpretation and manuscript writing. ML, YDZ, YW, XS, FH, YD, MZ, HJ, XuL, YH, XiL, YY, XW, XZ and YS conducted sample selection and participated in data management. All coauthors edited and reviewed the final version of the manuscript.

  • Funding This work was supported in part by the National Key Basic Research Program of China (973 Program) (No 2014CB541901), the National Natural Science Foundation of China (No 81120108020, No 31711530023, No 31670915, No 31870913, No 31470875, No 31270914, No 31530020, No 31700794, No 81401329, No 81771678, No 81471601, No 81671604), the National Key Research and Development Program of China (No 2016YFA05022300), Beijing Natural Science Foundation (No 7162192), and Shenzhen Municipal of Government of China (No CXB201108250094A).

  • Competing interests None declared.

  • Patient consent for publication Obtained.

  • Ethics approval The study was approved by the Medical Ethics Committee of Peking University People’s Hospital.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement Data are available upon reasonable request. All data relevant to the study are included in the article or uploaded as online supplementary information.

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