免疫学
人类白细胞抗原
连锁不平衡
主要组织相容性复合体
类风湿性关节炎
医学
基因分型
等位基因
遗传学
单倍型
抗原
基因型
生物
基因
作者
Jianping Guo,Tao Zhang,Hongzhi Cao,Xiaowei Li,Hao Liang,Mengru Liu,Yundong Zou,Yuanwei Zhang,Yuxuan Wang,Xiaolin Sun,Fanlei Hu,Yan Du,Xiaodong Mo,Xu Liu,Yue Yang,Huanjie Yang,Xinyu Wu,Xuewu Zhang,Huijue Jia,Hui Jiang
标识
DOI:10.1136/annrheumdis-2018-214725
摘要
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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