基于缺氧相关基因的心肌梗死诊断模型的建立与验证

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

作者信息

Jiang Ke, Kang Ling, Jiang Andong, Zhao Qiang

机构信息

Department of Cardiovascular Medicine, The Second Affiliated Hospital of Shandong First Medical University, Tai'an, Shandong, People's Republic of China.

Medical Imaging Department, The Second Affiliated Hospital of Shandong First Medical University, Tai'an, Shandong, People's Republic of China.

出版信息

Int J Gen Med. 2023 May 29;16:2111-2123. doi: 10.2147/IJGM.S407759. eCollection 2023.

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.

摘要

目的

心肌梗死(MI)是一种常见的心血管疾病,其潜在的病理机制仍不清楚。我们旨在开发一种诊断模型以区分MI的不同亚型。

患者与方法

从基因表达综合数据库(GEO数据库)下载MI的基因表达谱,并从分子特征数据库(MSigDB)下载缺氧相关基因(HRGs)。然后,通过无监督聚类识别基于HRGs的不同MI亚型。研究不同MI亚型之间表达模式和缺氧免疫状态的差异。开发并验证区分MI不同亚型的诊断模型。

结果

基于HRGs,MI样本被分为两个亚型,A簇和B簇。共有211个基因在两个亚型之间表现出显著的表达变化。A簇的特征是高缺氧状态和低免疫状态。基于加权基因共表达网络分析、受试者工作特征(ROC)分析和套索回归算法,确定了5个基因作为潜在的诊断标志物。最后,建立了基于这5个基因的诊断模型,该模型能够很好地区分这两个亚型。

结论

包括锚蛋白重复结构域36(ANKRD36)、解旋酶样转录因子(HLTF)、驱动蛋白家族成员3A(KIF3A)、3-氧代酸辅酶A转移酶1(OXCT1)和VPS13A在内的五个关键基因可能与MI的不同亚型相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a91/10238209/ade2fcd19215/IJGM-16-2111-g0001.jpg

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