Integrated gene expression profiling reveals potential immune-related biomarkers for rheumatoid arthritis

Abstract Background As one of the most common causes of joint deformities, rheumatoid arthritis (RA) has seriously affected human health. In this study, RA biomarkers related to immunity were identified by bioinformatics methods. Methods RA synovial microarray data were obtained from GEO database and preprocessed, and then differentially expressed genes(DEGs) were screened. Subsequently, the hub nodes were screened from the PPI network of DEGs by STRING database and cytoscape software. The hub nodes were verified in independent dataset. The immune infiltration in synovial tissue of RA was analyzed by CIBERSORT algorithm. In addition, the correlation between differentially infiltrated immune cells and key genes was analyzed. Results Intersected DEGs were significantly enriched in biological processes, including immune response − activating signal transduction, B cell activation, T cell activation. Through PPI network and immune infiltration analysis, we finally identified 5 immune-related biomarkers including CCL5, CCR5, CD27, CXCL9 and TLR8. Conclusion CCL5, CCR5, CD27, CXCL9 and TLR8 may be potential diagnostic biomarkers for RA treatment strategies.