Identify Key Mitochondrial Autophagy Genes in Schizophrenia through Integrated Bioinformatics Approaches
10.12259/j.issn.2095-610X.S20250104
- VernacularTitle:综合生物信息学方法识别精神分裂症状中关键线粒体自噬基因
- Author:
Kun LIAN
1
;
Yongmei LI
;
Chenglong SHI
;
Yilan CHEN
;
Lei ZHANG
;
Wei YANG
;
Xiufeng XU
Author Information
1. 昆明医科大学第二附属医院神经外科,云南 昆明 650101
- Keywords:
Schizophrenia;
Mitochondrial autophagy;
Neurons;
Single-cell sequencing;
Machine learning
- From:
Journal of Kunming Medical University
2025;46(1):23-35
- CountryChina
- Language:Chinese
-
Abstract:
Objective To utilize single-cell and peripheral blood transcriptomic data from 3D brain organoids,combined with machine learning,to analyze the role of mitochondrial autophagy genes in schizophrenia(SCZ).Methods By integrating two machine learning algorithms,we identified differentially expressed mitochondrial autophagy-related genes between schizophrenia patients and healthy controls using peripheral blood RNA sequencing data.The relationship between mitophagy gene,immune cells and inflammatory factors was further explored.Comprehensive single-cell analysis was used to explore the signaling pathways and specific transcription factors based on mitophagy genes.Results Using machine learning,seven key mitophagy genes expressed in schizophrenia patients were identified.Based on Mitoscore analysis,at the single-cell level,neurons with high mitochondrial autophagy activity(Mitohigh_Neuron)formed new interactions with endothelial cells via the SPP1 signaling pathway.Conclusion This study identified two subtypes of mitophagy and seven key mitophagy genes in schizophrenia,providing new insights into the pathogenesis of the disease.
