You Hongjun, Han Wenqi
Department of Cardiovascular Medicine, Shaanxi Provincial People's Hospital, Xi'an, 710068, Shaanxi, China.
Heliyon. 2024 Apr 25;10(9):e30269. doi: 10.1016/j.heliyon.2024.e30269. eCollection 2024 May 15.
The implication of necroptosis in cardiovascular disease was already recognized. However, the molecular mechanism of necroptosis has not been extensively studied in coronary heart disease (CHD).
The differentially expressed genes (DEGs) between CHD and control samples were acquired in the GSE20681 dataset downloaded from the GEO database. Key necroptosis-related DEGs were captured and ascertained by bioinformatics analysis techniques, including weighted gene co-expression network analysis (WGCNA) and two machine learning algorithms, while single-gene gene set enrichment analysis (GSEA) revealed their molecular mechanisms. The diagnostic biomarkers were selected via receiver operating characteristic (ROC) analysis. Moreover, an analysis of immune elements infiltration degree was carried out. Authentication of pivotal gene expression at the mRNA level was investigated in vitro utilizing quantitative real-time PCR (qRT-PCR).
A total of 94 DE-NRGs were recognized here, among which, FAM166B, NEFL, POLDIP3, PRSS37, and ZNF594 were authenticated as necroptosis-related biomarkers, and the linear regression model based on them presented an acceptable ability to different sample types. Following regulatory analysis, the ascertained biomarkers were markedly abundant in functions pertinent to blood circulation, calcium ion homeostasis, and the MAPK/cAMP/Ras signaling pathway. Single-sample GSEA exhibited that APC co-stimulation and CCR were more abundant, and aDCs and B cells were relatively scarce in CHD patients. Consistent findings from bioinformatics and qRT-PCR analyses confirmed the upregulation of NEFL and the downregulation of FAM166B, POLDIP3, and PRSS37 in CHD.
Our current investigation identified 5 necroptosis-related genes that could be diagnostic markers for CHD and brought a novel comprehension of the latent molecular mechanisms of necroptosis in CHD.
坏死性凋亡在心血管疾病中的作用已得到认可。然而，坏死性凋亡的分子机制在冠心病（CHD）中尚未得到广泛研究。
从GEO数据库下载的GSE20681数据集中获取冠心病样本与对照样本之间的差异表达基因（DEG）。通过生物信息学分析技术，包括加权基因共表达网络分析（WGCNA）和两种机器学习算法，捕获并确定关键的坏死性凋亡相关DEG，而单基因基因集富集分析（GSEA）揭示其分子机制。通过受试者工作特征（ROC）分析选择诊断生物标志物。此外，还进行了免疫细胞浸润程度分析。利用定量实时PCR（qRT-PCR）在体外研究关键基因在mRNA水平的表达验证。
在此共识别出94个差异表达的坏死性凋亡相关基因（DE-NRG），其中，FAM166B、NEFL、POLDIP3、PRSS37和ZNF594被鉴定为坏死性凋亡相关生物标志物，基于它们的线性回归模型对不同样本类型具有可接受的区分能力。经过调控分析，确定的生物标志物在与血液循环、钙离子稳态和MAPK/cAMP/Ras信号通路相关的功能中明显丰富。单样本GSEA显示，冠心病患者中APC共刺激和CCR更丰富，而aDC和B细胞相对较少。生物信息学和qRT-PCR分析的一致结果证实了冠心病中NEFL的上调以及FAM166B、POLDIP3和PRSS37的下调。
我们目前研究确定了5个与坏死性凋亡相关的基因，它们可能是冠心病的诊断标志物，并为冠心病中坏死性凋亡潜在分子机制带来了新的认识。
