ArticleMolecular neurobiology2025
Identification of Mitochondrial and Succinylation Modification-Related Gene Signature in Ischemic Stroke.
Article in Molecular neurobiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Mechanisms Involved in Pathological Succinate-Mediated Signaling.International journal of molecular sciences · 2026Review
- Identification of Mitochondrial Dysfunction Genes as Diagnostic Biomarkers for Ischemic Stroke by Integrated Bioinformatics Analysis and Machine Learning.Journal of molecular neuroscience : MN · 2026Article
- Aging-related gene signatures as potential biomarkers in ischemic stroke: an integrated bioinformatics and machine learning study.BMC neurology · 2026Article
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Authors and funding
8 authors.
Funding
Abstract
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 interactions were explored using DGIdb. qRT-PCR validation was performed on blood samples from IS patients and controls. We identified 317 DEGs enriched in immune response and inflammation pathways in 108 IS patients and 47 healthy controls using data from the merged datasets. WGCNA identified 101 hub genes in the yellow module and 65 in the brown module. Seven overlapping genes related to mitochondrial and succinylation processes were identified. Feature gene analysis revealed six key genes (MRPL41, NGRN, SLC25A42, SPTLC2, TUBB, and TXN) with robust diagnostic potential across both the merged and individual datasets (all AUCs > 0.7). Nomogram integration demonstrated predictive reliability. Feature genes exhibited significant correlations with immune cell infiltration. qRT-PCR validation confirmed the differential expression of four feature genes. TUBB and TXN showed interactions with various drugs. Mitochondrial and succinylation-related genes have diagnostic significance in IS, providing insights into disease pathogenesis and clinical applications.
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