免疫系统
重性抑郁障碍
基因
计算生物学
线粒体
生物
诊断生物标志物
生物信息学
遗传学
生物标志物
神经科学
认知
作者
Xiao‐Lan Liu,Yong Wu,Mingxing Li
标识
DOI:10.1016/j.jad.2024.01.011
摘要
Major depressive disorder (MDD) is one of the most prevalent and debilitating psychiatric disorders. It becomes more recognized that mitochondrial dysfunction contributes to the pathophysiology of depression. However, little research has systematically investigated the mitochondria-related biomarkers for MDD diagnosis. This study aimed to develop a novel diagnostic gene signature in MDD based on mitochondria-related genes. We identified the differentially expressed mitochondrial-related genes (DeMRGs) by combing the gene expression data of the GEO database with mitochondria-related gene lists obtained from the MitoCarta3.0 database. Next, three kinds of machine-learning algorithms were used to screen characteristic DeMRGs. Then, we constructed a multivariable diagnostic model based on these characteristic genes and evaluated the diagnostic ability of this model. Subsequently, the immune landscape of infiltrated immune cells between MDD patients and controls was evaluated by CIBERSORT. Using consensus clustering analysis, we divided MDD patients into different clusters based on the characteristic DeMRGs expression patterns. Finally, the variations in immune cell infiltration between different clusters, and the correlation between characteristic DeMRGs and immune cell infiltration were analyzed. Seven characteristic genes, including PMPCB, MRPS28, LYRM2, MGST1, COX20, PTPMT1, and STX17, were identified from the 31 DeMRGs. Based on the seven characteristic genes, we successfully constructed a diagnostic model which had relatively good diagnostic performance and potential application in the clinical diagnosis of MDD. In addition, our results also imply an intimate and comprehensive association between the characteristic DeMRGs and immune infiltrating cells. A novel mitochondria-related gene signature with a good diagnostic performance and a relationship with immune microenvironment were identified in major depressive disorder.
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