Qichang Gao, Tuo Shao, Yiming Ma, Zhange Yu, Jiaao Gu, Keying Yuan
Osteoarthritis (OA) is a chronic inflammatory and degenerative joint disease that commonly affects the aging population. This study was designed to decipher gene-metabolite regulatory networks driving OA progression via combined computational prediction and experimental validation. Differential gene expression analysis, weighted gene coexpression network analysis, and machine learning algorithms were integrated to screen for key regulatory genes. To infer causal associations between these candidates and OA susceptibility, we performed Mendelian randomization (MR) using cis-expression quantitative trait loci (cis-eQTL) as genetic instruments and identified significant associations between TNFRSF10B and OA. In parallel, single-nucleus RNA sequencing (snRNA-seq) was used to map the cell-type-specific expression profile of TNFRSF10B, and its expression was validated in human knee synovial tissues. The protective effect of TNFRSF10B on OA was statistically mediated in part by the alpha-tocopherol-to-sulfate ratio, as inferred from Mendelian randomization analysis, with the indirect effect accounting for 16.85% (95% CI: 2.96-30.74%) of the total protective effect. snRNA-seq data revealed that TNFRSF10B was widely expressed across synovial cell populations but reduced in OA samples. Collectively, this study identified TNFRSF10B as a candidate protective factor in OA, supported by genetic evidence from MR analysis and reduced expression in OA synovial tissues, offering statistical evidence for gene-metabolite interplay in OA pathogenesis.