Shared gene signatures between rheumatoid arthritis and Sjögren's syndrome.

Abstract

Rheumatoid arthritis (RA) is a chronic autoimmune disease that can lead to multiple complications. Sjögren's syndrome (SS) is another autoimmune condition that may occur as a primary disorder or in conjunction with other autoimmune diseases, including RA. This study aimed to investigate the shared gene signatures between RA and SS. Gene expression datasets for RA (GSE15573, GSE93776) and SS (GSE48378, GSE94510, GSE93683) were obtained and analyzed to identify differentially expressed genes (DEGs) in peripheral blood mononuclear cells (PBMCs) and T cells. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed on the DEGs identified. Quantitative real-time PCR (qRT-PCR) was used to validate the expression levels of DEGs in PBMCs from patients with RA and SS. A total of 244 DEGs were identified from the RA PBMC dataset, comprising 142 upregulated genes and 102 downregulated genes. These DEGs were significantly enriched in biological processes related to immune responses, including cellular response to lipopolysaccharide, defense response against fungi, inflammatory responses, and antibacterial humoral responses. In contrast, 335 DEGs were identified from the SS PBMC dataset; among these, 320 genes were upregulated, while 15 were downregulated. The DEGs associated with SS showed strong involvement in defense responses against viruses, innate immune responses, viral responses, as well as cellular reactions to lipopolysaccharide. Moreover, we identified 12 shared DEGs between RA and SS PBMCs: RNASE2, NDUFB3, LY96, ANKRD22, EIF2AK2, RNASE3, CLEC4D, TNFAIP6, DYNLT1, RPS27L, LILRA5, and F5. Validation through qRT-PCR confirmed increased expression levels of RNASE2, RNASE3, NDUFB3, and EIF2AK2 in PBMCs. This study successfully delineated key DEGs along with their associated biological processes within the context of RA and SS PBMCs. Through bioinformatics analyses combined with qRT-PCR validation, we have identified four critical genes that may serve as potential biomarkers or therapeutic targets for further investigation.