Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by dysregulation of immune homeostasis, abnormal activation of autoreactive B and T lymphocytes, and production of autoantibodies leading to the formation of immune complexes . The etiology of SLE is complex and influenced by genetic and environmental factors. The severity of disease, clinical symptoms, and response to treatment vary significantly among SLE individuals. Its pronounced heterogeneity and complex pathogenesis pose substantial challenges for clinicians in diagnosis and treatment. Current diagnostic criteria for SLE rely on a combination of clinical presentation and traditional laboratory tests, which may lack sensitivity and specificity . Therefore, a comprehensive exploration of potential candidate genes for SLE is of significant importance.

The mRNA expression profiles of GSE100163 and GSE49454 were obtained from the Gene Expression Omnibus (GEO) website. Differentially expressed genes (DEGs) analysis was identified by GEO2R platform. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to elucidate the signaling pathways associated with these DEGs. The protein-protein interaction network was constructed by the STRING database and visualized with Cytoscape. Furthermore, we validated the expression of the hub genes in the whole blood (RT-qPCR) and serum (ELISA) of SLE patients, explored the correlations between hub genes and clinicopathological characteristics, and conducted receiver operating characteristic (ROC) curve analysis to evaluate the association of hub genes with SLE.

A total of 229 DEGs were identified in the GSE79850 dataset, with 188 genes upregulated and 41 genes downregulated. GO and KEGG pathway enrichment analysis indicated that these DEGs were primarily associated with the response to virus infection and interferon signaling pathways. Among these DEGs, the top 5 key genes identified using the Degree algorithm were IFIT3, RSAD2, IFIT2, XAF1, and ISG15. Furthermore, experimental validation showed that the expression levels of RSAD2 and IFIT3 were upregulated in patients with SLE compared with healthy controls (HCs). Notably, circulating RSAD2 exhibited a significant correlation with disease activity.

In conclusion, RSAD2, IFIT3, IFIT2, XAF1 and ISG15 might play a key role in the development of SLE. Particularly, RSAD2 emerges as a potential biomarker for SLE, closely related to disease activity.