Jiangli Zhou

Background: Astrocytes play an important role in depression. However, their specific mechanisms, especially their subcellular mechanisms, remain unclear. Objective: We aimed to identify key genes associated with mitochondrial dynamics and astrocytes in Major Depressive Disorder (MDD), construct a diagnostic prediction model, and elucidate their regulatory mechanisms in neuroinflammation. Methods: Depression-related transcriptome datasets were retrieved from the GEO database. Overlapping differentially expressed genes between mitochondrial dynamics-related and astrocytes-associated genes were screened, followed by functional enrichment analysis. Machine learning algorithms were employed to establish a diagnostic model and identify hub genes. An LPS-induced mouse depression model was established, and depressive-like phenotypes were assessed through behavioral tests. Hub gene expression was validated by using quantitative real-time PCR and Western blotting. Results: A machine learning model with favorable diagnostic performance was constructed. LPS markedly upregulated hexokinase 2 (HK2) and ribosomal protein S7 (RPS7) expression in the prefrontal cortex and hippocampus, suggesting that glycolytic metabolism and ribosomal function contribute to LPS-induced neuropathological changes. Conclusions: HK2 and RPS7 were identified and validated as crucial hub genes responsive to neuroinflammation. The combined action of mitochondrial dynamics and astrocyte metabolic abnormalities may play a key role in depression’s pathogenesis, providing novel candidate biomarkers and theoretical support for the molecular diagnosis of MDD and anti-inflammatory targeted therapy.