Identification of mitophagy-related genes with potential clinical utility in myocardial infarction at transcriptional level - Yang, Zhikai; Sun, Liang; Wang, Hua (Frontiers in Cardiovascular Medicine, 2023)
Background: Myocardial infarction ranks among the most prevalent cardiovascular diseases. When blood flow to the coronary arteries is insufficient, it leads to ischemic necrosis of the heart muscle. However, the mechanism of myocardial injury after myocardial infarction remains unclear. This article aims to explore the potential common genes between mitophagy and MI and to construct a suitable prediction model. Methods: A total of three Gene Expression Omnibus (GEO) datasets (GSE62646 and GSE59867) were used to screen the differential expression genes in peripheral blood. SVM, RF, and LASSO algorithm were employed to find MI and mitophagy-related genes. Moreover, DT, KNN, RF, SVM and LR were conducted to build the binary models, and screened the best model to further external validation (GSE61144) and internal validation (10-fold cross validation and Bootstrap) respectively. The performance of various machine learning models was compared. Then a logistic model was built, 24 external samples were performed. In addition，immune cell infiltration correlation analysis was conducted with MCP-Counter and CIBERSORT. Results: We finally identified ATG5, TOMM20, MFN2 transcriptionally differed between MI and stable coronary artery diseases. Both internal and external validation supported that these three genes could accurately predict MI with under the curve [AUC]= 0.914 and 0.930 by logistic regression respectively. Additionally, functional analysis suggested that monocytes and neutrophils might be involved in mitochondrial autophagy after myocardial infarction. Conclusion: The data showed that the mRNA levels of ATG5, TOMM20 and MFN2 in patients with MI were significantly different from the control group. These genes can accurately diagnose diseases and have potential application value in clinical practice.