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Meta‐analyses uncover the genetic architecture of Idiopathic Inflammatory Myopathies

肌炎 皮肌炎 多发性肌炎 全基因组关联研究 候选基因 遗传学 表达数量性状基因座 生物 遗传关联 基因座(遗传学) 人类白细胞抗原 数量性状位点 基因 免疫学 医学 单核苷酸多态性 基因型 病理 解剖 抗原
作者
Catherine Zhu,Younghun Han,Jinyoung Byun,Xiangjun Xiao,Simon Rothwell,Frederick W. Miller,Ingrid E. Lundberg,Peter K. Gregersen,Jiří Vencovský,Vikram R. Shaw,Neil McHugh,Vidya Limaye,Albert Selva-O’Callaghan,Michael G. Hanna,Pedro Machado,Lauren M. Pachman,Ann M. Reed,Lisa G. Rider,Øyvind Molberg,Olivier Benveniste,Timothy R. D. J. Radstake,Andrea Doria,Jan De Bleecker,Boél De Paepe,Britta Maurer,William Ollier,Leonid Padyukov,Lucy R. Wedderburn,Hector Chinoy,Janine A. Lamb,Christopher I. Amos
出处
期刊:Arthritis & rheumatology [Wiley]
标识
DOI:10.1002/art.43088
摘要

Objective Idiopathic inflammatory myopathies (myositis, IIMs) are rare, systemic autoimmune disorders that lead to muscle inflammation, weakness, and extra‐muscular manifestations, with a strong genetic component influencing disease development and progression. Previous genome‐wide association studies identified loci associated with IIMs. In this study, we imputed data from two prior genome‐wide myositis studies and analyzed the largest myositis dataset to date to identify novel risk loci and susceptibility genes associated with IIMs and its clinical subtypes. Methods We performed association analyses on 14,903 individuals (3,206 cases and 11,697 controls) with genotypes and imputed data from the Trans‐Omics for Precision Medicine (TOPMed) reference panel. Fine‐mapping and expression quantitative trait locus co‐localization analyses in myositis‐relevant tissues indicated potential causal variants. Functional annotation and network analyses using the random walk with restart (RWR) algorithm explored underlying genetic networks and drug repurposing opportunities. Results Our analyses identified novel risk loci and susceptibility genes, such as FCRLA, NFKB1 , IRF4 , DCAKD , and ATXN2 in overall IIMs; NEMP2 in polymyositis; ACBC11 in dermatomyositis; and PSD3 in myositis with anti‐histidyl‐tRNA synthetase autoantibodies (anti‐Jo1). We also characterized effects of HLA region variants and the role of C4 . Colocalization analyses suggested putative causal variants in DCAKD in skin and muscle, HCP5 in lung, and IRF4 in EBV‐transformed lymphocytes, lung, and whole blood. RWR further prioritized additional candidate genes, including APP, CD74 , CIITA, NR1H4, and TXNIP , for future investigation. Conclusion Our study uncovers novel genetic regions contributing to IIMs, advancing our understanding of myositis pathogenesis and offering new insights for future research.
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