Wu Zongkai, Fan Hongzhen, Qin Lu, Niu Xiaoli, Chu Bao, Zhang Kaihua, Gao Yaran, Wang Hebo
Department of Neurology, Hebei General Hospital, Shijiazhuang, China.
Hebei Provincial Key Laboratory of Cerebral Networks and Cognitive Disorders, Hebei General Hospital, Shijiazhuang, China.
J Mol Neurosci. 2025 Jan 2;75(1):4. doi: 10.1007/s12031-024-02241-3.
Acute ischemic stroke (AIS) is a severe disorder characterized by complex pathophysiological processes, which can lead to disability and death. This study aimed to determine necroptosis-associated genes in acute ischemic stroke (AIS) and to investigate their potential as diagnostic and therapeutic targets for AIS. Expression profiling data were acquired from the Gene Expression Omnibus database, and necroptosis-associated genes were retrieved from GeneCards. The differentially expressed genes (DEGs) and necroptosis-related genes were intersected to obtain the necroptosis-related DEGs (NRDEGs) in AIS. In AIS, a total of 76 genes associated with necroptosis (referred to as NRDEGs) were identified. Enrichment analysis of these genes revealed that they were primarily enriched in pathways known to induce necroptosis. Using weighted gene co-expression network analysis (WGCNA), five co-expression modules consisting of NRDEGs were identified, along with two modules that exhibited a strong correlation with AIS. Protein-protein interaction (PPI) analysis resulted in the identification of 20 hub genes. The Least absolute shrinkage and selection operator (LASSO) regression model demonstrated promising potential for diagnostic prediction. The receiver operating characteristic (ROC) curve validated the diagnostic model and selected nine characteristic genes that exhibited statistically significant differences (p < 0.05). By employing consensus clustering, distinct patterns of necroptosis were identified using these nine signature genes. The results were validated by quantitative PCR (qPCR) in venous blood from patients with AIS and healthy controls and HT22 cells, as well as external datasets. Furthermore, the analyzed ceRNA network included nine lncRNAs, six miRNAs, and three mRNAs. Overall, this study offers novel insights into the molecular mechanisms underlying NRDEGs in AIS. The findings provide valuable evidence and contribute to our understanding of the disease.
急性缺血性卒中(AIS)是一种严重的疾病,其特征在于复杂的病理生理过程,可导致残疾和死亡。本研究旨在确定急性缺血性卒中(AIS)中与坏死性凋亡相关的基因,并研究它们作为AIS诊断和治疗靶点的潜力。从基因表达综合数据库获取表达谱数据,并从基因卡片中检索坏死性凋亡相关基因。对差异表达基因(DEGs)和坏死性凋亡相关基因进行交集分析,以获得AIS中与坏死性凋亡相关的差异表达基因(NRDEGs)。在AIS中,共鉴定出76个与坏死性凋亡相关的基因(称为NRDEGs)。对这些基因的富集分析表明,它们主要富集在已知可诱导坏死性凋亡的途径中。使用加权基因共表达网络分析(WGCNA),鉴定出由NRDEGs组成的五个共表达模块,以及两个与AIS呈强相关的模块。蛋白质-蛋白质相互作用(PPI)分析鉴定出20个枢纽基因。最小绝对收缩和选择算子(LASSO)回归模型显示出有前景的诊断预测潜力。受试者工作特征(ROC)曲线验证了诊断模型,并选择了9个表现出统计学显著差异(p < 0.05)的特征基因。通过采用一致性聚类,使用这9个特征基因鉴定出不同的坏死性凋亡模式。结果通过对AIS患者和健康对照的静脉血以及HT22细胞中的定量PCR(qPCR)以及外部数据集进行了验证。此外,分析的ceRNA网络包括9个lncRNA、6个miRNA和3个mRNA。总体而言,本研究为AIS中NRDEGs的分子机制提供了新的见解。这些发现提供了有价值的证据,并有助于我们对该疾病的理解。