The aim is to pinpoint crucial genes linked to CD8+ T cells in rheumatoid arthritis (RA) for aiding in diagnosis, predicting disease progression, and ultimately discovering potential drug targets. This study utilized datasets from the Gene Expression Omnibus (GEO) database to analyze gene expression profiles in RA patients. Weighted Gene Coexpression Network Analysis (WGCNA) was conducted to identify gene modules associated with the diseases, followed by differential gene expression analysis. Functional enrichment and protein-protein interaction (PPI) network analysis were employed. Gene Set Enrichment Analysis (GSEA) and Disease Ontology (DO) analysis were applied to understand their potential pathways. Transcription factors (TFs) correlated with target gene expression were screened, and TF binding sites were predicted. The proportion of immune cell infiltration was calculated using CIBERSORT. The study identified 58 candidate genes associated with CD8+ T cells in RA. The top five genes, RSAD2, IFIT3, OAS1, IFIT2, and SAMD9L, were found to be upregulated in RA and other autoimmune diseases. IFIT3 showed potential diagnostic value in RA, with significant expression differences in RA vs. OA samples. TF BCL11B bound to the IFIT3 promoter. GSEA analysis indicated IFIT3's influence on pathways like the cell cycle and TNF signaling. Immune landscape analysis showed IFIT3's correlation with immune cell infiltration such as B cells and plasma cells. Drug prediction analysis suggested naringin's treatment potential for RA via targeting IFIT3. This study identifies key CD8+ T-cell genes in RA, with IFIT3 as a potential diagnostic and therapeutic target, revealing BCL11B's regulatory role.
Tian et al. (Fri,) studied this question.