Abstract
Background: Ischemic stroke (IS) is a major cause of disability and mortality worldwide, with mitochondrial dysfunction playing a critical role in its pathogenesis. This study aimed to identify immune-related mitochondrial biomarkers associated with IS and evaluate their diagnostic potential. Methods: IS-related gene expression datasets were obtained from the GEO database. Differentially expressed genes (DEGs) were identified from the GSE58294 dataset, followed by functional enrichment analysis, immune infiltration assessment, and weighted gene co-expression network analysis (WGCNA). Immune-related mitochondrial genes were screened using the MITOCARTA 3.0 database. Four machine learning algorithms-random forest (RF), support vector machine (SVM), generalized linear model (GLM), and extreme gradient boosting (XGB)-were applied to identify hub genes. External validation was performed using the GSE16561 dataset, and RT-qPCR confirmed key gene expression. Functional enrichment and single-cell RNA sequencing analyses explored biological pathways and cellular localization. Results: Five key genes (ECHDC3, EPHX2, SPTLC2, MSRB2, and TK2) were identified, among which ECHDC3, EPHX2, and SPTLC2 showed strong diagnostic potential (AUC > 0.7). These genes were significantly enriched in apoptosis, JAK-STAT, MAPK, and VEGF signaling pathways and were closely associated with neutrophil infiltration. Single-cell analysis revealed increased immune cell populations and distinct expression patterns of key genes in the ischemic mouse brain. Conclusions: This study identifies novel immune-related mitochondrial biomarkers for IS, providing insights into its pathogenesis and offering potential targets for early diagnosis and therapeutic intervention.