ArticleFrontiers in genetics2025
Multi-omics identification and validation of oxidative phosphorylation-related hub genes in schizophrenia.
Article in Frontiers in genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Machine learning-based predictive models and subtypes patterns in peripheral blood of schizophrenia based on a machine learning computational framework.Schizophrenia (Heidelberg, Germany) · 2026Article
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9 authors.
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Abstract
Introduction: Dysfunction in mitochondrial oxidative phosphorylation (OXPHOS) has been implicated in the pathophysiology of schizophrenia, yet its molecular underpinnings remain poorly defined. In this study, we performed an integrative multi-omics analysis to delineate these molecular signatures. Methods: Bulk transcriptomic datasets of schizophrenia patients and controls were obtained from the Gene Expression Omnibus. Differentially expressed genes (DEGs) associated with OXPHOS were identified through a combination of differential expression analysis, single-sample gene set enrichment analysis (ssGSEA), and weighted gene co-expression network analysis (WGCNA). Hub genes were prioritized by machine learning algorithms (LASSO, SVM-RFE, and random forest). These hub genes were validated using an independent dataset and further corroborated by RT-qPCR in an MK-801-induced mouse model. Single-nucleus RNA sequencing (snRNA-seq) was employed to delineate cell type-specific oxidative phosphorylation activity and transcriptional profiles. Results: Transcriptomic analysis identified 130 DEGs between schizophrenia and controls, significantly enriched in oxidative phosphorylation and mitochondrial respiration pathways. Subsequent ssGSEA confirmed the reduced OXPHOS enrichment scores in schizophrenia. Furthermore, WGCNA uncovered two hub modules significantly associated with OXPHOS, which also showed strong correlations with schizophrenia. Intersecting their 2,609 module genes with 130 DEGs yielded 69 OXPHOS-related DEGs. From these, machine learning prioritized six hub genes, four of which demonstrated strong diagnostic potential and robust correlations with OXPHOS scores. Extending these findings Conclusion: This finding suggests a potential link between OXPHOS dysfunction and schizophrenia, with MALAT1, PPIL3, and ITM2A emerging as candidate regulators of this process.
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