Bioinformatic analysis to find small molecules related to rheumatoid arthritis.

Background Rheumatoid arthritis (RA) is a chronic, systemic inflammatory disorder that may affect many tissues and organs, but principally attacks flexible (synovial) joints. Aims Our aim is to explore the change of gene expression profile in patients with RA, and investigate the underlying mechanism of the pathogenesis and progression of RA. Methods We downloaded the dataset GSE2053 from Gene Expression Omnibus database and screened the differentially expressed genes by analyzing the profiles between RA and normal cells with bioinformatics methods. Furthermore, Gene Ontology (GO) function analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were used to screen GO and the significantly changed signaling pathways in RA cells with the Database for Annotation, Visualization and Integrated Discovery (DAVID). Results By bioinformatics methods, we obtained the metabolic pathway changed in the cells of patients with RA, and explored small molecule drugs that can restore these changes. Conclusions These results may provide a new approach for explore the pathogenesis of RA and a new breakthrough in the medical treatment of patients with RA.