Identification of important genes associated with acute myocardial infarction using multiple cell death patterns

Abstract

Acute myocardial infarction (AMI) is a global health threat, and programmed cell death (PCD) plays a crucial role in its occurrence and development. In this study, integrated bioinformatics tools were used to explore new biomarkers and therapeutic targets in AMI. Thirteen types of PCD-related genes were identified through literature review, KEGG, and GSEA pathways. Gene expression matrices and clinical data from AMI patients and healthy controls were obtained from the GEO database. Statistical analysis in R identified 377 differentially expressed genes in AMI patients. Intersection analysis between the differentially expressed genes and PCD-related genes revealed 24 genes positively correlated with immune cells such as Neutrophils and Monocytes, while negatively correlated with T cells CD4 memory resting and Plasma cells. Unsupervised clustering analysis divided patients into two groups (C1 and C2) based on the expression levels of these 24 genes. GSVA analysis showed that C2 patients were more active in pathways related to maintaining normal cell morphology and promoting phagocytosis, suggesting a lower programmed cell death rate and a higher tendency to maintain cell survival. Two hub genes, TNFAIP3 and TP53INP2, were identified through LASSO regression analysis and SVM-RFE, and were validated using an external dataset and RT-qPCR、Western blot and ELISA analysis. These hub genes showed significantly higher expression and protein secretion levels in AMI patients compared to healthy individuals. Overall, regulating and controlling PCD, particularly through the identified hub genes, TNFAIP3 and TP53INP2, may provide new therapeutic strategies for improving the prognosis of AMI patients and preventing heart failure.

Keywords: Acute myocardial infarction; Integrated bioinformatics; Programmed cell death; Real-time quantitative PCR; Western blot.