Leveraging Genomic and Bioinformatic Analysis to Enhance Drug Repositioning for Dermatomyositis

Dermatomyositis (DM) is an autoimmune disease that classified as a type of idiopathic inflammatory myopathy, which affects human skin and muscles. The most common clinical symptoms DM are muscle weakness, rash, scaly skin. There currently no cure for DM. Genetic factors known to play pivotal role in progression, but few have utilized this information geared toward drug discovery the disease. Here, we exploited genomic variation associated with integrated bioinformatic analyses discover new candidates. We first genome-wide association study (GWAS) phenome-wide (PheWAS) catalogs identify disease-associated variants. Biological risk genes were prioritized using strict functional annotations, further identifying candidate targets based on druggable from databases. Overall, analyzed 1239 variants obtained 43 drugs overlapped 13 target (JAK2, FCGR3B, CD4, CD3D, LCK, CD2, CD3E, FCGR3A, CD3G, IFNAR1, CD247, JAK1, IFNAR2). Six clinically investigated DM, well eight under pre-clinical investigation, could be repositioned Further studies necessary validate potential biomarkers novel therapeutics our findings.