Epigenetic Biomarkers for Myocardial Infarction Risk in Diabetic Patients

Myocardial infarction (MI) is a leading cause of mortality, with diabetic patients at significantly elevated risk. Identifying reliable biomarkers for early MI detection in this population remains a challenge. This study investigates epigenetic modifications, specifically histone acetylation marks, as potential diagnostic biomarkers. Using integrated RNA-sequencing (RNA-seq) data from eight Gene Expression Omnibus (GEO) datasets (n = 327), we identified differentially expressed genes (DEGs) between MI cases (n = 110) and diabetic controls (n = 217). Histone acetylation marks, including H4K5, H4K12, H4K20, H3K9, H3K27, and H2AK5, were associated with MI risk. Machine learning models, including Random Forest and Graph Neural Networks, achieved high predictive accuracy (AUC > 0.85). Enrichment analyses revealed pathways linked to inflammation and cardiovascular disease. These findings suggest that histone acetylation profiles may serve as novel biomarkers for early MI detection in diabetic patients, offering opportunities for improved risk stratification and intervention.