Tang Zhiqi, Nong Jiacong, Qiu Xue, Huang Junwen, Feng Xueyi, Tu Guangpeng, Li Lang
Department of Cardiology, The First Affiliated Hospital of Guangxi Medical University, No. 6 Shuangyong Road, Qingxiu District, Nanning, 530021, Guangxi, China.
Biochem Genet. 2025 May 3. doi: 10.1007/s10528-025-11121-3.
Acute myocardial infarction (AMI) continues to pose a substantial risk to human lives worldwide. Endoplasmic reticulum stress (ERS) is increasingly recognized as one of the potential mechanisms of myocardial injury following AMI. The primary goal of this study is to investigate the correlation between ERS and AMI through machine learning-based bioinformatics analysis, explore key genes, and conduct in vivo and in vitro experimental validation. We performed differential analysis and Weighted Gene Co-expression Network Analysis (WGCNA) on gene expression data from the GEO database (GSE62646). The intersection with ERS-related genes (ERSRGs) was taken to obtain AMI-ERS-related genes (MIEGs), and machine learning algorithms were further used to identify key genes (Hubs) from the MIEGs. The validation set GSE59867 was used to assess the expression levels and predictive capabilities of the Hubs for AMI. An AMI rat model was established to detect the mRNA and protein expression levels of the Hubs. The protein inhibitor of the key gene FURIN was used to treat H9C2 cells under oxygen-glucose deprivation (OGD) to explore the effects of FURIN on ERS and apoptosis. Bioinformatics analysis identified 27 MIEGs, and machine learning further determined 5 Hubs highly associated with AMI and ERS: RELA, FURIN, ERGIC3, TPP1, and BGLAP. The expression of these Hubs was significantly elevated in AMI patients within both the training and validation sets, and the area under the curve (AUC) indicated good diagnostic value. Our experiments confirmed that the mRNA levels of Furin and RelA were significantly elevated in AMI rats. Furin protein was increased in AMI rats and OGD H9C2. Furin inhibitor could alleviate OGD-induced ERS and apoptosis in H9C2. Our study demonstrates that Hubs play a pivotal role in myocardial infarction. Notably, Furin and its mediated ERS and apoptosis are significant in the pathogenesis of AMI, potentially serving as target for AMI diagnosis and treatment.
急性心肌梗死(AMI)在全球范围内仍然对人类生命构成重大风险。内质网应激(ERS)日益被认为是AMI后心肌损伤的潜在机制之一。本研究的主要目的是通过基于机器学习的生物信息学分析来研究ERS与AMI之间的相关性,探索关键基因,并进行体内和体外实验验证。我们对来自GEO数据库(GSE62646)的基因表达数据进行了差异分析和加权基因共表达网络分析(WGCNA)。与ERS相关基因(ERSRGs)进行交集运算以获得AMI-ERS相关基因(MIEGs),并进一步使用机器学习算法从MIEGs中识别关键基因(枢纽基因)。使用验证集GSE59867评估枢纽基因对AMI的表达水平和预测能力。建立AMI大鼠模型以检测枢纽基因的mRNA和蛋白质表达水平。使用关键基因弗林蛋白酶(FURIN)的蛋白抑制剂在氧糖剥夺(OGD)条件下处理H9C2细胞,以探索FURIN对ERS和细胞凋亡的影响。生物信息学分析确定了27个MIEGs,机器学习进一步确定了5个与AMI和ERS高度相关的枢纽基因:RELA、FURIN、ERGIC3、TPP1和BGLAP。在训练集和验证集中,这些枢纽基因在AMI患者中的表达均显著升高,曲线下面积(AUC)表明具有良好的诊断价值。我们的实验证实,Furin和RelA的mRNA水平在AMI大鼠中显著升高。Furin蛋白在AMI大鼠和OGD处理的H9C2细胞中增加。Furin抑制剂可减轻OGD诱导的H9C2细胞中的ERS和细胞凋亡。我们的研究表明,枢纽基因在心肌梗死中起关键作用。值得注意的是,Furin及其介导的ERS和细胞凋亡在AMI的发病机制中具有重要意义,可能成为AMI诊断和治疗的靶点。