Mapping rheumatoid arthritis susceptibility through integrative bioinformatics and genomics

Rheumatoid arthritis (RA) is an autoimmune disease that influences several organs and tissues, especially the synovial joints, associated with multiple genetic environmental factors. Numerous databases provide information on relationship between a specific gene pathogenesis. However, it important to further prioritize biological risk genes for downstream development validation. This study aims map RA-association variation using genome-wide association (GWAS) influential in RA pathogenesis based functional annotations. These annotations include missense/nonsense mutations, cis-expression quantitative trait locus (cis-eQTL), overlap knockout mouse phenotype (KMP), protein-protein interaction (PPI), molecular pathway analysis (MPA), primary immunodeficiency (PID). 119 variants mapped had potential high scoring. The top eight of are TYK2 IFNGR2, followed by TNFRSF1A, IL12RB1 CD40, C5, NCF2, IL6R . candidate biomarkers can aid drug discovery diagnosis.