Identification of diagnostic genes for myocardial ischemia reperfusion injury associated with metabolic syndrome through the integration of bioinformatics analysis, molecular docking and experimental validation

Background Metabolic dysregulation in metabolic syndrome (MetS) exacerbates myocardial ischemia-reperfusion injury (MIRI). This study aimed to identify diagnostic biomarkers and therapeutic candidates for MetS-associated MIRI. Methods Three MIRI and two MetS datasets from GEO were analyzed using differential expression analysis, WGCNA, and machine learning (LASSO/SVM-RFE). Hub genes were validated via qRT-PCR in hypoxia-induced H9C2 cells. Drug candidates were predicted via PPI networks, CTD, and molecular docking, followed by experimental evaluation of dexamethasone. Results Five hub genes—DAK, GTF3C5, KCNMB1, TRAF1, and ZNF692—were identified, with distinct expression patterns (DAK/GTF3C5 downregulated; KCNMB1/TRAF1/ZNF692 upregulated). These genes were enriched in immune-related pathways, and their diagnostic performance was robust (AUCs: 0.875–0.969). Dexamethasone downregulated KCNMB1/TRAF1/ZNF692 and reduced apoptosis in H9C2 cells. Conclusion This study reveals immune-metabolic dysregulation as a key driver of MetS-MIRI, proposes five biomarkers for diagnosis, and highlights dexamethasone as a promising therapeutic candidate.