Development and Validation of a Diagnostic Model Based on Hypoxia-Related Genes in Myocardial Infarction

基于缺氧相关基因的心肌梗死诊断模型的开发与验证

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Abstract

PURPOSE: Myocardial infarction (MI) is a common cardiovascular disease, and its underlying pathological mechanism remains unclear. We aimed to develop a diagnostic model to distinguish different subtypes of MI. PATIENTS AND METHODS: The gene expression profiles of MI from the GEO database and hypoxia-related genes (HRGs) from MSigDB were downloaded. Then, the different MI subtypes based on HRGs were identified with unsupervised clustering. The difference of expression patterns and hypoxic-immune status among different subtypes of MI were investigated. The diagnostic model to distinguish the different subtypes of MI was developed and validated. RESULTS: Based on HRGs, MI samples were divided into two subtypes, cluster A and cluster B. A total of 211 genes showed significant changes in expression between the two subtypes. Cluster A was characterized by high hypoxia status and low immunity status. Based on weighted gene co-expression network analysis, ROC analysis and LASSO regression algorithm, 5 genes were identified as potential diagnostic markers. Finally, a diagnostic model based on these 5 genes was established, which can distinguish the two subtypes well. CONCLUSION: The five hub genes, including ANKRD36, HLTF, KIF3A, OXCT1 and VPS13A, may be associated with the different subtypes of MI.

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