Transcriptomic and single-cell insights into mitochondrial genes NDUFA8, ECI2, and ACADM in acute myocardial infarction

Mitochondrial function plays a crucial role in understanding the pathogenesis of acute myocardial infarction.This study investigates mitochondrial function-related genes (MFRGs) in acute myocardial infarction (AMI) through bioinformatics and rigorous experimental validation. Using three integrated GEO datasets (149 samples: 80 AMI, 69 control), we applied machine learning methods (Random Forest, Support Vector Machine, Least Absolute Shrinkage and Selection Operator), phenotype scoring, consensus clustering, and weighted gene co-expression network analysis in three subgrouping stages to refine the selection of MFRGs. The intersection of three subgroup analyses results identified 11 key Mitochondrial function-Related Differentially Expressed Genes (MRDEGs). Gene Ontology / Kyoto Encyclopedia of Genes and Genomes analysis (GOKEGG), Gene Set Enrichment Analysis (GSEA), Gene Set Variation Analysis (GSVA), and immune infiltration analyses revealed significant pathways and suggested alterations in the composition of immune cell subpopulations. Single-cell analysis revealed increased expression of MRDEGs (NDUFA8, ECI2, and ACADM) in cardiomyocytes, fibroblasts, and macrophages, along with dynamic expression trends along the pseudotime trajectory. Subgroup analysis of cardiomyocytes based on mitochondrial gene scoring was performed to explore functional enrichment characteristics. Furthermore, we robustly validated these genes' expression in the cardiomyocyte hypoxia/reoxygenation model and the mouse model of myocardial infarction using flow cytometry, immunohistochemistry, and Western blot. Finally, this study constructed the mRNA regulatory network of key MRDEGs and preliminarily explored the potential therapeutic value of valproic acid and acetaminophen through molecular docking.These findings reveal the role of mitochondrial dysfunction in the mechanisms of AMI and its associated cell subpopulations, along with the involved biological pathways, offering new insights for AMI research.

Acute Myocardial Infarction; Machine learning; Mitochondrial function Genes; Molecular docking; Single-cell analysis; Transcriptomic analysis; Vivo and Vitro Verification.