ORIGINAL RESEARCH article
Front. Immunol.
Sec. Inflammation
Volume 16 - 2025 | doi: 10.3389/fimmu.2025.1567572
This article is part of the Research TopicMolecular Biomarkers of Cardiometabolic Disease - Volume IIView all 12 articles
Identification of Diagnostic Genes for Myocardial Ischemia Reperfusion Injury Associated with Metabolic Syndrome through the Integration of Bioinformatics Analysis, Molecular Docking and Experimental Validation
Provisionally accepted
- 1Department of Nuclear Medicine, First Hospital of Shanxi Medical University, Taiyuan, China
- 2Yangzhou University, Yangzhou, Jiangsu Province, China
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Metabolic dysregulation often exacerbates myocardial ischemia-reperfusion injury (MIRI) in patients with myocardial ischemia. The aim of this study is to investigate candidate biomarkers that promote the occurrence and progression of MIRI in metabolic syndrome (MetS), as well as small molecular drugs for prevention and treatment. Using three MIRI datasets and two MetS datasets obtained from the Gene Expression Omnibus (GEO) database, differential expression analysis, Weighted Gene Coexpression Network Analysis (WGCNA), and machine learning techniques, including LASSO regression and SVM-RFE, were employed to identify hub genes implicated in MetS-MIRI. The results indicated that the key genes were primarily involved in immune cell-related signaling pathways, suggesting significant immune dysregulation in both MetS and MIRI. Five hub genes-DAK, GTF3C5, KCNMB1, TRAF1, and ZNF692-were identified as candidate biomarkers, with the former two downregulated and the latter three upregulated in MIRI. A nomogram based on these genes demonstrated excellent diagnostic performance for MIRI, with high diagnostic values for each gene (area under the curve: DAK, 0.938; GTF3C5, 0.875; KCNMB1, 0.969; TRAF1, 0.875; ZNF692, 0.969). Validation through qRT-PCR in a hypoxia-induced MIRI H9C2 cell model confirmed that the expression profiles of these genes were consistent with those observed in bioinformatics analysis of MIRI myocardial samples. Further, through protein-protein interaction (PPI) analysis, the Comparative Toxicogenomics Database (CTD), and molecular docking, dexamethasone was predicted as potential small molecule therapeutics for MIRI. In the MIRI-induced H9C2 model, dexamethasone effectively inhibited the expression of KCNMB1, TRAF1, and ZNF692, while also reducing apoptosis in H9C2 cells. These findings not only provide valuable biomarkers for diagnosing MIRI but also suggest dexamethasone as a promising therapeutic candidate, offering new perspectives for the future treatment of MIRI-induced injury.
Keywords: Myocardial ischemia reperfusion injury, metabolic syndrome, machine learning, molecular docking, Immune infiltration
Received: 27 Jan 2025; Accepted: 12 May 2025.
Copyright: © 2025 Li, Liu, Zhang, Zhao, Wu, Tian, Pang and Wu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Sijin Li, Department of Nuclear Medicine, First Hospital of Shanxi Medical University, Taiyuan, China
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