Mining Potential Therapeutic Targets for T Cell Exhaustion in Osteoarthritis by Integrating Mendelian Randomization and Single‐Cell Sequencing

Studies have shown that T cell exhaustion (TEX) indirectly influences the onset and progression of osteoarthritis (OA). This study aimed to ascertain biomarkers associated with TEX-related genes (TEXRGs) in OA, offering potential targets for therapy and prognosis. OA related datasets were obtained from public databases. Candidate genes were ascertained by intersecting differentially expressed genes (DEGs) with TEXRGs. The expression quantitative trait locus (eQTL) data were then used as instrumental variables, and genes causally associated with OA were screened through Mendelian randomization (MR) analysis. Gene expression and receiver operating characteristic (ROC) analyses were carried out to identify biomarkers. Finally, functional enrichment, immune infiltration, drug prediction, molecular docking, and single-cell analyses were conducted to explore the underlying biological mechanisms of OA. GPR65, LDLR, PLIN2, and TRIM14 were ascertained as biomarkers for OA. MR analysis revealed that PLIN2 acted as a protective factor, whereas GPR65, LDLR, and TRIM14 were risk factors of OA. LDLR and PLIN2 exhibited significantly lower expression in OA samples, whereas GPR65 and TRIM14 showed significantly higher expression. These four biomarkers were notably co-enriched in the "lysosome" pathway. Six differential immune cell types were identified. Puromycin and gossypol were predicted as potential OA treatments. Finally, single-cell analysis highlighted T cells and mast cells as key cell types in OA, with dynamic expression of GPR65 and PLIN2 observed throughout their differentiation. This study identifies GPR65, LDLR, PLIN2, and TRIM14 as biomarkers for OA, offering valuable insights that could support the development of targeted therapies.