ArticleFrontiers in genetics2026
Identification of potential biomarkers and therapeutic targets for osteoarthritis associated with arginine and proline metabolism based on transcriptome sequencing and bioinformatics.
Article in Frontiers in genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background and Objectives: Osteoarthritis (OA) is a chronic degenerative joint disease. Approximately 300 million people worldwide suffer from OA, which shows a high incidence in middle-aged and elderly populations, with a prevalence of 50% among individuals aged over 60 years. Its core clinical symptoms consist of joint pain, swelling, and dysfunction. Studies have shown that arginine and proline metabolism play an important role in the pathogenesis and progression of OA, but the specific mechanism is still unclear. This study aimed to identify biomarkers and drug therapeutic targets for OA associated with arginine and proline metabolism. Methods: Synovial tissues of healthy individuals and OA patients were collected for transcriptome sequencing, and the differentially expressed genes (DEGs) between the two groups were compared and analyzed. Arginine and proline metabolism-related genes (APRGs) were obtained from the molecular signature database. The candidate genes were identified by weighted gene co-expression network analysis (WGCNA), and then gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis and protein-protein interaction (PPI) were performed. Expression validation was performed using machine learning and ROC analysis to identify key genes. Gene set enrichment analysis (GSEA), immune cell infiltration, and drug prediction were used to explore the mechanism of key genes in OA and potential therapeutic drugs. Finally, clinical samples were experimentally validated through RT-qPCR experiments. Results: Two hub genes (MYOM2 and TCAP) involved in arginine and proline metabolism were identified. A nomogram constructed based on these genes indicated that MYOM2 and TCAP are key and reliable predictors for osteoarthritis risk. The RT-qPCR experiments on clinical samples showed that the expression levels of these hub genes were significantly downregulated in the synovial tissue of OA patients (p < 0.05), suggesting their potential as diagnostic biomarkers. Discussion: MYOM2 and TCAP are hub genes in OA metabolism with arginine and proline, which may become new diagnostic markers and potential therapeutic targets for OA.
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