Abstract

Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease, whose development is associated with immune cells and persistent inflammation. Exploring the biomarkers of RA holds immense significance in terms of the prevention, diagnosis, and treatment of RA. The differentially expressed genes (DEGs) in RA patients and the control group were screened by limma package. Through DEGs intersection overlapping 200 inflammatory response-related genes and 2498 immune-related genes, differentially expressed immune and inflammation-related genes (DE-IIRGs) were identified. Lasso regression analysis screened RA diagnostic biomarkers and constructed PPI networks. Finally, immune infiltration analysis and drug prediction were performed. A total of 20 DE-IIRGs were identified by overlapping DEGs with 2498 immune-related genes and 200 inflammatory response-related genes. These DE-IIRGs were primarily enriched in the cytokine-cytokine receptor interaction and other biological processes, and then five biomarker genes (TNFSF10, IL1R1, CXCL9, ACVR1B, and IL15) were identified. It was found that the expression levels of CXCL9, IL15, and TNFSF10 in the disease samples were significantly higher than those in the control group. These biomarker genes have more effective diagnostic potential. The RA samples exhibited significantly higher levels of cell infiltration compared to the control samples. hsa-miR-199a-5p's connections to the ACVR1B and CCR7 genes were identified by creating ceRNA networks from 20 screened DE-IIRGs. There was a connection between CCL5 and AEMA4D and hsa-miR-214-3p. We identified immune- and inflammation-related biomarkers in RA based on bioinformatics analysis and screened TNFSF10, IL1R1, CXCL9, ACVR1B, and IL15 as diagnostic markers for RA. Key Points • TNFSF10, IL1R1, CXCL9, ACVR1B, and IL15 may be new diagnostic biomarkers for RA. • These findings may provide a theoretical basis for early RA diagnosis.

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