Meta-analyses uncover the genetic architecture of Idiopathic Inflammatory Myopathies

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.