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Identifying Immunological Biomarkers for Major Depressive Disorder: Insights From Machine Learning, Single-Nucleus
Long Kangsheng1, Yang Xiaohui2, Pei Xin2
1The First Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, Hunan, China, hnctcm.edu.cn.
Background:
Major depressive disorder (MDD) is a chronic mental illness rapidly approaching the status of a significant global burden of disease. This study is aimed at investigating novel biomarkers in MDD and performing a comprehensive analysis of immune infiltration through an integrated bioinformatics approach.
Methods:
The study involved differential gene expression analysis, weighted gene coexpression network analysis (WGCNA), single-nucleus RNA sequencing (snRNA-seq), and the application of three machine learning methods. Additionally, we constructed the chronic unpredictable mild stress (CUMS) rat model of MDD, and their brain tissues were analyzed by transcriptional sequencing to explore the differentially expressed genes (DEGs). Finally, quantitative reverse transcription-polymerase chain reaction (RT-qPCR) and western blot experiments were conducted to verify the expression level of hub gene in brain tissues.
Results:
A total of 132 DEGs were discovered, with enrichment analysis revealing their significant involvement in immune-related functions and pathways. WGCNA analysis yielded three hub genes (DACH1, FZD7, and GULP1). These hub genes were identified by intersecting candidate signature genes obtained from three machine learning analyses with DEGs. SnRNA-seq analysis revealed significant differences in immune cell-related expression patterns between MDD patients and healthy controls. The presence of three hub genes was found by DEGs in brain tissues of CUMS rats. Further RT-qPCR and western blot experiments demonstrated that DACH1 and GULP1 were upregulated, and FZD7 was downregulated in brain tissues of CUMS rats.
Conclusion:
Our findings contribute to the understanding of the relationship between MDD and immune infiltration. DACH1, FZD7, and GULP1 may be key biomarkers and potential therapeutic targets for MDD.
