Bioinformatics Identification of Ferroptosis-related Genes and Therapeutic Drugs in Rheumatoid Arthritis

Abstract

Abstract Objectives Rheumatoid arthritis (RA) is a chronic immune disease characterized by synovial inflammation and bone destruction, with a largely unclear etiology. Evidences have indicated that ferroptosis may play an increasingly important role in the onset and development RA. However, ferroptosis-related genes are still largely unexplored in RA. Therefore, this work focused on identifying and validating the potential ferroptosis-related genes involved in RA through bioinformatics analysis. Methods We screened differentially expressed ferroptosis-related genes (DEFGs) between RA patients and healthy individuals based on GSE55235 dataset. Subsequently, correlation analysis, protein-protein interaction (PPI) network analysis, GO, and KEGG enrichment analyses were performed using these DEFGs. Finally, our results were validated by GSE12021 dataset. Results We discovered 34 potential DEFGs in RA based on bioinformatics analysis. According to functional enrichment analysis, these genes were mainly enriched in HIF-1 signaling pathway, FoxO signaling pathway, and Ferroptosis pathway. Four genes (GABARPL1, DUSP1, JUN, and MAPK8) were validated to be downregulated by GSE12021 dataset and may be possible diagnostic biomarkers and therapeutic targets for RA via the regulation of ferroptosis. Conclusions Our results may help shed more light on the pathogenesis of RA. Ferroptosis-related genes in RA could be valuable diagnostic biomarkers and they will be exploited clinically as therapeutic targets in the future.