Identification of genetic variants associated with idiopathic inflammatory myopathies via cross-trait analysis with B...

The genetic architecture of idiopathic inflammatory myopathies (IIMs) remains incompletely defined. When increasing sample size is not feasible, cross-trait analysis of genetically correlated diseases offers an effective strategy for discovering risk loci. Using summary statistics of IIM and B cell lymphoma subtypes, we applied conditional false discovery rate (condFDR) and multi-trait analysis of genome-wide association studies (GWASs) (MTAG) to detect genetic associations with IIM risk. Single-nucleotide polymorphisms (SNPs) outside the human leukocyte antigen (HLA) region meeting significance thresholds (condFDR < 0.01 or p <5 × 10^-8 for MTAG) were clumped and subjected to both functional annotation in FUMA and Gene Ontology (GO) biological process enrichment analysis using clusterProfiler. We identified six previously unreported loci, including three associated with dermatomyositis (chr12:58674304T>C, chr13:110799415C>T, and chr17:38103285G>A (hg19)) and three associated with polymyositis (PM) (chr4:971496T>C, chr6:396321C>T, and chr6:32650631C>A). All non-HLA loci act as expression quantitative trait loci (eQTL) or localize within enhancer regions. Notably, these include cis-eQTLs for known IIM risk-associated genes (GSDMB, DGKQ, SLC26A1, and IDUA) as well as genes implicated in synaptic vesicle cycle (SVC) pathways, immune regulation (IKZF3, ORMDL3, IRF4, DUSP22, and SPON2), protein homeostasis (ATP23 and PSMD3), lipid metabolism (PGAP3, ORMDL3, STARD3, and DGKQ), and myopathy (COL4A1). GO analysis revealed significance for SVC pathways in PM (FDR < 0.05). These findings advance our understanding of IIM pathogenesis from a genetic perspective and highlight candidate regulatory variants for further mechanistic investigation.