Integrative Analyses of Biomarkers and Potential Therapeutic Drugs for Rheumatoid Arthritis.

Objective: This study aims to explore key candidate genes and predict potential therapeutic agents for rheumatoid arthritis (RA).

Methods: Differentially expressed genes (DEGs) of synovial tissue in patients with RA compared with normal donors are identified by analyzing four expression profiles. Coexpressed DEGs are confirmed by Venn diagrams. Gene ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, protein-protein interaction network, gene-microRNAs (miRNAs) network, and gene-drugs network are interrogated to identify hub genes and discover possible therapeutic drugs.

Results: A total of 69 DEGs in RA synovium samples are identified. GO analysis reveals that DEGs are significantly enriched in lymphocyte activation, adaptive immune response, and leukocyte migration in biological process. The most enriched KEGG pathway is cytokine-cytokine receptor interaction. Gene set enrichment analysis shows that most genes are enriched and upregulated in interferon gamma response. The top 10 hub genes are , and . Finally, a miRNA-mRNA network and a drug-mRNA network are constructed, and 105 miRNAs and 35 drugs are screened out.

Conclusions: The identified hub genes and drugs may provide valuable novel markers and treatment options for diagnosis and therapy of RA.