biostudies-literatureWang LDali University longitudinal research projectJoint special fund project for Basic research of local undergraduate universities in Yunnan Province11130-11144https://www.ebi.ac.uk/biostudies/studies/S-EPMC12367933biostudies-literatureUnknown62(9)Ischemic stroke (IS) is a leading cause of death and disability worldwide, often associated with immune dysregulation, mitochondrial dysfunction, and altered protein succinylation. This study aimed to identify mitochondrial and succinylation-related gene signatures with diagnostic potential in IS. Differentially expressed genes (DEGs) associated with IS were identified using transcriptome expression profiles from merged GSE16561 and GSE58294 GEO datasets. Functional enrichment and WGCNA identified hub genes. Mitochondrial and succinylation-related gene expression was assessed via ssGSEA. Feature genes were selected using machine learning. A prognostic nomogram was constructed. PPI networks were generated using GeneMANIA. Immune infiltration was assessed through ssGSEA. Drug-gene interactioMolecular neurobiologyIdentification of Mitochondrial and Succinylation Modification-Related Gene Signature in Ischemic Stroke.PMC12367933KYBS2023035202101AO070200Liu YYang LLuo ZYing XChen HZhao JCai HWang LfalseIdentification of Mitochondrial and Succinylation Modification-Related Gene Signature in Ischemic Stroke.Ischemic stroke (IS) is a leading cause of death and disability worldwide, often associated with immune dysregulation, mitochondrial dysfunction, and altered protein succinylation. This study aimed to identify mitochondrial and succinylation-related gene signatures with diagnostic potential in IS. Differentially expressed genes (DEGs) associated with IS were identified using transcriptome expression profiles from merged GSE16561 and GSE58294 GEO datasets. Functional enrichment and WGCNA identified hub genes. Mitochondrial and succinylation-related gene expression was assessed via ssGSEA. Feature genes were selected using machine learning. A prognostic nomogram was constructed. PPI networks were generated using GeneMANIA. Immune infiltration was assessed through ssGSEA. Drug-gene interactio2025-01-01T00:00:00Z2025 Sep2026-07-15T14:18:48.353Z2026-07-09T10:15:25.624ZS-EPMC123679334026160810.1007/s12035-025-04953-y