Integrative Bioinformatics and Experimental Validation Identify LOX as a Glycolysis-Related Biomarker in Myocardial Ischemia-Reperfusion Injury.

Reprogramming of glycolytic metabolism plays a critical role in the pathogenesis of myocardial ischemia-reperfusion injury (MIRI). Although transient glycolysis activation may alleviate energy deficits, excessive glycolytic flux can worsen myocardial damage. This study aimed to identify specific biomarkers and therapeutic targets by investigating glycolysis-related genes in MIRI. We analyzed differentially expressed genes (DEGs) from GEO datasets GSE61592 and GSE160516 and constructed co-expression modules using weighted gene co-expression network analysis (WGCNA). By intersecting DEGs, WGCNA modules, and glycolysis-related genes, we identified glycolysis-related DEGs (GR-DEGs). Machine learning (support vector machine-recursive feature elimination and Random Forest) was applied to GR-DEGs; LOX emerged as the top intersecting feature (log2FC = 3. 67, adjusted P = 1. 44 × 10⁻⁵, validation set AUC = 0. 97). Diagnostic value was assessed using gene set enrichment analysis (GSEA), decision curve analysis (DCA), and nomogram modeling. Immune infiltration was evaluated using CIBERSORT. Experimental validation was conducted in a rat MIRI model and H9c2 hypoxia-reoxygenation (H/R) cells. GR-DEGs were enriched in pathways including ribose phosphate metabolism, collagen binding, and apoptosis. Machine learning identified LOX as a hub gene, significantly upregulated in both models. Functional analysis suggested LOX expression was significantly associated with extracellular matrix (ECM) receptor interaction pathways, with its upregulation coinciding with myocardial injury progression. LOX expression correlated positively with CD8⁺ T cells and activated memory CD4⁺ T cells, indicating its potential association with metabolic and immune microenvironment remodeling in MIRI. Our findings suggest that LOX may serve as a key candidate gene associated with MIRI pathogenesis in preclinical models, with a potential value for preclinical research exploration.