Identification of Biomarkers for m6A-Mediated Programmed Cell Death in Osteoarthritis Transcripts with Experimental Validation.

Introduction: Osteoarthritis (OA) is a common progressive joint disorder with limited treatment options. Emerging evidence suggests that N6-methyladenosine (m6A)-mediated programmed cell death (PCD) plays a crucial role in OA progression, yet the key regulatory genes remain unidentified. This study aims to identify m6A-modified PCD biomarkers to facilitate improved OA management. Materials and Methods We performed a comprehensive multi-omics analysis using transcriptomic data from two independent OA cohorts. Differentially expressed genes were integrated with 1,548 PCD-related genes and 23 m6A regulators. Feature selection was conducted using LASSO regression and Boruta algorithm. Biomarkers were validated through cross-dataset consistency verification, ROC curve analysis, and RT-qPCR. Mechanistic insights were explored through gene set enrichment analysis, immune infiltration deconvolution, and drug-gene interaction prediction. Results Integration analysis identified 26 candidate genes, from which machine learning selected six key genes. Five biomarkers (TNFAIP3, MYC, CDKN1A, ATF3, and CX3CR1) were robustly validated. These genes are involved in inflammatory and apoptotic pathways. Immune infiltration analysis revealed increased M2 macrophages, resting mast cells, plasma cells, and Tregs in OA tissues. Cadmium compounds were predicted as potential therapeutics. RT-qPCR confirmed significant downregulation of TNFAIP3, MYC, CDKN1A, and ATF3 in OA patients. Conclusions This study identified five m6A-PCD-related biomarkers associated with OA pathogenesis, providing new insights into OA mechanisms and potential therapeutic targets.