Abstract
Acute myocardial infarction (AMI) remains a major cause of cardiovascular-related disability and mortality globally. Previous studies have indicated that there is a close interaction between immune responses and mitochondrial metabolism, which may affect the occurrence and development of AMI. Exploring these interactions is crucial for discovering new biomarkers and therapeutic targets. We retrieved gene expression data from Gene Expression Omnibus, employing differential expression analysis, enrichment analysis, weighted gene co-expression network analysis, and machine learning to identify mitochondria-related hub genes in AMI. The nomogram model was developed for diagnosis. Cell-type Identification by Estimating Relative Subsets of RNA Transcripts and Pearson correlation analyses were conducted to explore the relationship between these hub genes and immune cells. Gene set enrichment analysis was conducted to explore mitochondrial metabolism pathway enrichment in immune cells using single-cell sequencing data. Drug predictions were made using the EnrichR platform. Real-time quantitative polymerase chain reaction validated the expression levels of the identified hub genes. Five mitochondria-related hub genes with diagnostic potential for AMI were identified. Both classification and nomogram models exhibited good diagnostic performance. Subsequent validation via real‑time quantitative polymerase chain reaction confirmed significant upregulation of ACSL1, ALDH2, C15orf48, SLC25A37, and CYP27A1 in AMI (P < .05). Significant differences in 13 types of immune cells were observed between AMI and controls, with the 5 hub genes significantly associated with various immune cells. Most of the mitochondrial metabolism-related pathways were significantly upregulated in T cells, B cells, and dendritic cells. This exploratory study provides preliminary insight into the interplay between mitochondrial metabolism and immunity in AMI and highlights a set of potential candidate biomarkers that may support AMI diagnosis. However, rigorous external validation is essential before any clinical application can be considered.