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ORIGINAL RESEARCH article

Front. Mol. Biosci.
Sec. Molecular Diagnostics and Therapeutics
Volume 11 - 2024 | doi: 10.3389/fmolb.2024.1448705

Comprehensive analysis of hypoxia-related genes in diagnosis and immune infiltration in acute myocardial infarction: based on bulk and single-cell RNA sequencing data

Provisionally accepted
Guoqing Liu Guoqing Liu 1Wang Liao Wang Liao 2Xiangwen Lv Xiangwen Lv 3Miaomiao Zhu Miaomiao Zhu 1Jian Xie Jian Xie 1*Xingqing Long Xingqing Long 1
  • 1 First Affiliated Hospital, Guangxi Medical University, Nanning, China
  • 2 The First People’s Hospital of Yulin, Yulin, Shaanxi Province, China
  • 3 Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Region, China

The final, formatted version of the article will be published soon.

    Background: Hypoxia has been found to cause cellular dysfunction and cell death, which are essential mechanisms in the development of acute myocardial infarction (AMI). However, the impact of hypoxia-related genes (HRGs) on AMI remains uncertain.The training dataset GSE66360, validation dataset GSE48060, and scRNA dataset GSE163956 were downloaded from the GEO database. We identified hub HRGs in AMI using machine learning methods. A prediction model for AMI occurrence was constructed and validated based on the identified hub HRGs. Correlations between hub HRGs and immune cells were explored using ssGSEA analysis. Unsupervised consensus clustering analysis was used to identify robust molecular clusters associated with hypoxia. Single-cell analysis was used to determine the distribution of hub HRGs in cell populations. RT-qPCR verified the expression levels of hub HRGs in the human cardiomyocyte model of AMI by oxygen-glucose deprivation (OGD) treatment in AC16 cells.Results: Fourteen candidate HRGs were identified by differential analysis, and the RF model and the nomogram based on 8 hub HRGs (IRS2, ZFP36, NFIL3, TNFAIP3, SLC2A3, IER3, MAFF, and PLAUR) were constructed, and the ROC curves verified its good prediction effect in training and validation datasets (AUC = 0.9339 and 0.8141, respectively). In addition, the interaction between hub HRGs and smooth muscle cells, immune cells was elucidated by scRNA analysis. Subsequently, the HRG pattern was constructed by consensus clustering, and the HRG gene pattern verified the accuracy of its grouping. Patients with AMI could be categorized into three HRG subclusters, and cluster A was significantly associated with immune infiltration. The RT-qPCR results showed that the hub HRGs in the OGD group were significantly overexpressed.A predictive model of AMI based on HRGs was developed and strongly associated with immune cell infiltration. Characterizing patients for hypoxia could help identify populations with specific molecular profiles and provide precise treatment.

    Keywords: acute myocardial infarction, hypoxia, Diagnostic model, Single-Cell Analysis, Immune infiltration

    Received: 14 Jun 2024; Accepted: 07 Aug 2024.

    Copyright: © 2024 Liu, Liao, Lv, Zhu, Xie and Long. 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: Jian Xie, First Affiliated Hospital, Guangxi Medical University, Nanning, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.