ORIGINAL RESEARCH article
Front. Immunol.
Sec. Multiple Sclerosis and Neuroimmunology
Single-cell transcriptome-wide Mendelian randomization identifies mitochondrial targets in immune cells for Major Depressive Disorder
Provisionally accepted- 1Guangzhou University of Chinese Medicine, Guangzhou, China
- 2Gannan Medical University, Ganzhou, China
- 3Fujian University of Traditional Chinese Medicine, Fuzhou, China
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Background: A critical need exists for objective biomarkers and novel therapeutic targets in major depressive disorder (MDD). Although dysfunction in mitochondrial immunometabolism is implicated in MDD, the specific causal genes suitable for clinical translation remain largely unidentified. This study aimed to bridge this gap by identifying mitochondria-related genes that have a causal impact on MDD risk through their expression in specific immune cells. Methods: We integrated multi-omics data with machine learning to pinpoint key mitochondria-related energy metabolism genes (MEMRGs) linked to immune cell infiltration, assessed via ssGSEA and CIBERSORT algorithms. Cell-type-specific two-sample Mendelian randomization (MR) was employed to evaluate causal relationships between gene expression and MDD risk. Findings were validated in a chronic unpredictable mild stress (CUMS) rat model. Results: Our analysis identified five genes—HK2, NDUFS4, NEU1, SOD1, and UCP2— whose expression in distinct immune populations had significant causal effects on MDD risk. Notably, HK2, NDUFS4, and NEU1 were identified as protective factors, while UCP2 and SOD1 were risk factors in specific cell types. The clinical relevance of this panel was supported by its diagnostic performance in an independent cohort, and the upregulation of the principal risk gene, UCP2, was confirmed in the hippocampus of CUMS rats. Conclusion: This study provides robust genetic evidence establishing a causal link between the expression of specific mitochondrial genes in immune cells and the risk of MDD. By prioritizing UCP2, SOD1, HK2, NDUFS4, and NEU1, our findings highlight novel, immune-mediated pathways in depression and nominate promising targets for future diagnosis and therapeutic intervention.
Keywords: Immune cell eQTL, machine learning, Major Depressive Disorder, Mendelian randomization, Mitochondrial energy metabolism
Received: 07 Sep 2025; Accepted: 15 Dec 2025.
Copyright: © 2025 Zhang, Zhang, Shen, Ni, Zhang, Zhang, Lin, Yang and Lei. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Zhaoyang Yang
Huangwei Lei
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
