ArticleFrontiers in cardiovascular medicine2026
Clinically validated immune-related gene markers and molecular subtypes in acute myocardial infarction revealed by peripheral blood transcriptomics.
Article in Frontiers in cardiovascular medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Acute myocardial infarction (AMI) is a leading cause of morbidity and mortality worldwide. Beyond ischemic injury, sterile inflammation and immune activation critically shape infarct expansion, healing, and adverse remodeling. However, immune-related genes (IRGs) that distinguish AMI from stable coronary artery disease (sCAD) and reflect patient heterogeneity remain incompletely characterized. Methods: Two microarray datasets (GSE59867 and GSE62646) were retrieved from database and integrated after batch correction. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were combined with CIBERSORT to identify differentially expressed immune-related genes (DEIRGs) and hub genes associated with immune infiltration. Consensus clustering was then applied to explore molecular subtypes of AMI. Finally, hub genes were preliminarily validated by RT-qPCR in a clinical cohort and in an independent public dataset (GSE60993). Results: A total of 155 differentially expressed genes (DEGs) and 27 DEIRGs were identified. WGCNA highlighted the MEblue module as most strongly associated with AMI, and intersection analysis yielded 13 overlapping DEIRGs. Protein-protein interaction analysis prioritized six hub genes (CSF3R, CD14, AQP9, S100A9, SLC11A1, and IL1RN), which were mainly correlated with neutrophil and monocyte fractions. Consensus clustering indicated three molecular subtypes with distinct hub-gene expression patterns. RT-qPCR confirmed significantly increased expression of AQP9, S100A9, and SLC11A1 in AMI compared with sCAD. External validation in GSE60993 supported the diagnostic potential of the identified genes. Conclusions: AQP9, S100A9, and SLC11A1 are promising immune-related biomarkers and may reflect heterogeneity in inflammatory responses among AMI patients. These findings provide mechanistic clues and candidate targets for future experimental and translational studies.
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