Screening and Validation of Key Genes of Autophagy in Acute Myocardial Infarction Based on Bioinformatics

Author:

Geng Yingjie1,Han Yu’e2,Wang Shujuan1,Qi Jia1,Bi Xiaoli3

Affiliation:

1. Department of Cardiology, Zibo Central Hospital, Zibo, Shandong Province, China

2. Department of Pulmonary and Critical Care Medicine, Zibo Central Hospital, Zibo, Shandong Province, China

3. Department of Cardiology, Zibo First Hospital, Zibo, Shandong Province, China

Abstract

Aims: Autophagy plays a significant role in the development of acute myocardial infarction (AMI), and cardiomyocyte autophagy is of major importance in maintaining cardiac function. We aimed to identify key genes associated with autophagy in AMI through bioinformatics analysis and verify them through clinical validation. Materials and Methods: We downloaded an AMI expression profile dataset GSE166780 from Gene Expression Omnibus (GEO). Autophagy-associated genes potentially differentially expressed in AMI were screened using R software. Then, to identify key autophagy-related genes, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, protein-protein interaction (PPI) analysis, Receiver Operating Characteristic (ROC) curve analysis, and correlation analysis were performed on the differentially expressed autophagy-related genes in AMI. Finally, we used quantificational real-time polymerase chain reaction (qRT-PCR) to verify the RNA expression of the screened key genes. Results: TSC2, HSPA8, and HIF1A were screened out as key autophagy-related genes. qRT-PCR results showed that the expression levels of HSPA8 and TSC2 in AMI blood samples were lower, while the expression level of HIF1A was higher than that in the healthy controls. Conclusions: TSC2, HSPA8, and HIF1A were identified as key autophagy-related genes in this study. They may influence the development of AMI through autophagy. These findings may help deepen our understanding of AMI and may be useful for the treatment of AMI.

Publisher

SAGE Publications

Subject

Computer Science Applications,Genetics,Ecology, Evolution, Behavior and Systematics

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