Identification and Analysis of Key Genes Related to Metabolism in the Brain of Major Depressive Disorder

Background Major depressive disorder (MDD) is a prevalent neuropsychiatric condition and has become the second leading cause of mortality after cancer. The prefrontal cortex (PFC) is recognized as one of the brain regions most consistently affected by MDD. While both functional and structural abnormalities in the PFC have been shown to be associated with disruptions in energy metabolism, the specific genes involved in metabolic processes within this region remain poorly understood. Methods Datasets related to major depressive disorder (MDD) from the Gene Expression Omnibus (GEO) database were analyzed in this study. Initially, differentially expressed metabolism-related genes (DE-MRGs) were identified by intersecting differentially expressed genes from normal and MDD patient samples with metabolism-related genes. Subsequently, a protein-protein interaction (PPI) network was constructed based on the DE-MRGs, and hub genes were identified using the Molecular Complex Detection (MCODE) plugin. A logistic regression prediction model was then developed. To further assess the findings, Spearman correlations, Gene Set Enrichment Analysis (GSEA), and predictions of transcription factors and microRNAs targeting the hub genes were conducted. Finally, the expression of the hub genes and their potential mechanisms were validated and predicted using an animal model of depression. Results In this study, we identified 223 differentially expressed metabolism-related genes. Utilizing the MCODE plugin methods, we further identified 12 hub genes among these differentially expressed genes. Expression validation results indicated that the expression of ACLY, DLD, DLAT, FH, and SLC25A3 were consistent across various datasets for both MDD and control samples. GSEA revealed that these genes were significantly enriched in pathways associated with oxidative phosphorylation, Parkinson's disease, and the proteasome. Furthermore, animal experiments demonstrated that the expression levels of ACLY, DLD, DLAT, and FH were significantly reduced in the PFC of rats subjected to chronic unpredictable mild stress (CUMS) induction. Additionally, further investigation into the transcription factors and regulatory signals of ACLY revealed a significant decrease in the mRNA expression of SREBF1, along with marked reductions in the protein levels of PI3K, Akt, and p-ACLY. Conclusions Four key genes were identified based on metabolic characteristic genes. The PI3K/AKT/ACLY signaling pathway may play a significant role in the regulation of metabolism in major depressive disorder (MDD). These findings establish a theoretical foundation and provide valuable references for the study of central metabolism in MDD.