The Second Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, 510405, China.
Department of Hematology and Oncology, The Third Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510378, China.
BMC Genomics. 2023 Apr 25;24(1):216. doi: 10.1186/s12864-023-09304-6.
Major depressive disorder (MDD) is a life-threatening and debilitating mental health condition. Mitophagy, a form of selective autophagy that eliminates dysfunctional mitochondria, is associated with depression. However, studies on the relationship between mitophagy-related genes (MRGs) and MDD are scarce. This study aimed to identify potential mitophagy-related biomarkers for MDD and characterize the underlying molecular mechanisms.
The gene expression profiles of 144 MDD samples and 72 normal controls were retrieved from the Gene Expression Omnibus database, and the MRGs were extracted from the GeneCards database. Consensus clustering was used to determine MDD clusters. Immune cell infiltration was evaluated using CIBERSORT. Functional enrichment analyses were performed to determine the biological significance of mitophagy-related differentially expressed genes (MR-DEGs). Weighted gene co-expression network analysis, along with a network of protein-protein interactions (PPI), was used to identify key modules and hub genes. Based on the least absolute shrinkage and selection operator analysis and univariate Cox regression analysis, a diagnostic model was constructed and evaluated using receiver operating characteristic curves and validated with training data and external validation data. We reclassified MDD into two molecular subtypes according to biomarkers and evaluated their expression levels.
In total, 315 MDD-related MR-DEGs were identified. Functional enrichment analyses revealed that MR-DEGs were mainly enriched in mitophagy-related biological processes and multiple neurodegenerative disease pathways. Two distinct clusters with diverse immune infiltration characteristics were identified in the 144 MDD samples. MATR3, ACTL6A, FUS, BIRC2, and RIPK1 have been identified as potential biomarkers of MDD. All biomarkers showed varying degrees of correlation with immune cells. In addition, two molecular subtypes with distinct mitophagy gene signatures were identified.
We identified a novel five-MRG gene signature that has excellent diagnostic performance and identified an association between MRGs and the immune microenvironment in MDD.
重度抑郁症（MDD）是一种危及生命和使人虚弱的心理健康状况。自噬是一种选择性自噬形式，可以消除功能失调的线粒体，与抑郁症有关。然而，关于自噬相关基因（MRGs）与 MDD 之间关系的研究很少。本研究旨在确定 MDD 的潜在自噬相关生物标志物，并描述其潜在的分子机制。
从基因表达综合数据库中检索了 144 例 MDD 样本和 72 例正常对照的基因表达谱，并从基因卡片数据库中提取了 MRGs。采用共识聚类确定 MDD 聚类。使用 CIBERSORT 评估免疫细胞浸润。进行功能富集分析以确定自噬相关差异表达基因（MR-DEGs）的生物学意义。采用加权基因共表达网络分析和蛋白质-蛋白质相互作用网络（PPI），鉴定关键模块和枢纽基因。基于最小绝对收缩和选择算子分析以及单变量 Cox 回归分析，构建并使用接收者操作特征曲线评估诊断模型，并使用训练数据和外部验证数据进行验证。根据生物标志物将 MDD 重新分类为两种分子亚型，并评估它们的表达水平。
共鉴定出 315 个与 MDD 相关的 MR-DEGs。功能富集分析表明，MR-DEGs 主要富集在自噬相关的生物学过程和多种神经退行性疾病途径中。在 144 例 MDD 样本中鉴定出两个具有不同免疫浸润特征的截然不同的聚类。MATR3、ACTL6A、FUS、BIRC2 和 RIPK1 已被确定为 MDD 的潜在生物标志物。所有生物标志物与免疫细胞均显示出不同程度的相关性。此外，还鉴定出两种具有不同自噬基因特征的分子亚型。
我们发现了一个新的五-MRG 基因特征，具有出色的诊断性能，并确定了 MRGs 与 MDD 免疫微环境之间的关联。
