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Genetic Architecture of Idiopathic Inflammatory Myopathies From Meta‐Analyses
Author(s) -
Zhu Catherine,
Han Younghun,
Byun Jinyoung,
Xiao Xiangjun,
Rothwell Simon,
Miller Frederick W.,
Lundberg Ingrid E.,
Gregersen Peter K.,
Vencovsky Jiri,
Shaw Vikram R.,
McHugh Neil,
Limaye Vidya,
SelvaO'Callaghan Albert,
Hanna Michael G.,
Machado Pedro M.,
Pachman Lauren M.,
Reed Ann M.,
Rider Lisa G.,
Molberg Øyvind,
Benveniste Olivier,
Radstake Timothy,
Doria Andrea,
De Bleecker Jan L.,
De Paepe Boel,
Maurer Britta,
Ollier William E.,
Padyukov Leonid,
Wedderburn Lucy R.,
Chinoy Hector,
Lamb Janine A.,
Amos Christopher I.
Publication year - 2025
Publication title -
arthritis and rheumatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.106
H-Index - 314
eISSN - 2326-5205
pISSN - 2326-5191
DOI - 10.1002/art.43088
Objective Idiopathic inflammatory myopathies (IIMs, myositis) are rare systemic autoimmune disorders that lead to muscle inflammation, weakness, and extramuscular 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 data set 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 patients and 11,697 controls) with genotypes and imputed data from the Trans‐Omics for Precision Medicine reference panel. Fine‐mapping and expression quantitative trait locus colocalization 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–transfer RNA synthetase autoantibodies (anti–Jo‐1). 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 Epstein‐Barr virus (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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