ArticleJournal of cardiothoracic surgery2026
Identification of biomarkers associated with mitochondria and macrophage polarization in acute myocardial infarction: a bioinformatics analysis and validation study.
Article in Journal of cardiothoracic surgery, 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
backgroundStudies have shown that mitochondrial dysfunction in macrophages worsens inflammation and impedes repair after acute myocardial infarction (AMI). This study aimed to identify and validate biomarkers of AMI associated with mitochondria-related genes (MRGs) and macrophage polarization-related genes (MPRGs), offering new targets and strategies for therapeutic intervention of AMI.
methodsIn this study, the GSE61144 and GSE60993 datasets were employed. Initially, candidate genes were identified by overlapping the differentially expressed genes (DEGs) from differential expression analysis, key module genes from weighted gene co-expression network analysis (WGCNA), and MRGs. Then, biomarkers were identified by machine learing, receiver operating characteristic (ROC), and gene expression analyses. Finally, functional enrichment, immune infiltration, drug prediction, and reverse transcription quantitative polymerase chain reaction (RT-qPCR) analyses were performed to explore the roles of these biomarkers.
resultsThe study identified APEX1, ECHDC2, NME3, and PUS1 as biomarkers associated with AMI, all of which exhibited reduced expression in AMI samples. RT-qPCR results further validated these findings. Notably, all 4 biomarkers were predominantly co-enriched in the “ribosome” pathway, highlighting its significance in AMI. Additionally, 11 differential immune cells were identified. Correlation analysis revealed that these biomarkers showed the strongest positive correlations with activated CD8 T cells and the most negative correlations with neutrophils. Drug prediction indicated that valproic acid, which targeted all 4 biomarkers, could be a promising therapeutic option for AMI.
conclusionsIn this study, APEX1, ECHDC2, NME3, and PUS1 were identified as biomarkers for AMI, with their expression levels validated in clinical samples. These findings offered a potential theoretical foundation for developing targeted treatments for AMI. CLINICAL TRIAL NUMBER: Not applicable.
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