ABSTRACT Major Depressive Disorder (MDD) is linked to increased neurodegenerative risk. Emerging evidence implicates ferroptosis in neuropsychiatric disorders, prompting investigation of its role in MDD through key gene identification. Three microarray datasets from the GEO database were analysed. Weighted gene co‐expression network analysis (WGCNA) identified MDD‐related module genes (MRGs) while ferroptosis‐related genes (FRGs) were extracted from the FerrDb database. Overlapping genes between MRGs and FRGs were prioritised for mechanistic exploration. Functional enrichment (GO/KEGG) and protein‐protein interaction (PPI) network analyses (via Cytoscape and CytoHubba) highlighted hub genes. Machine learning algorithms were applied to develop a diagnostic model, validated through nomogram analysis, calibration curves, decision curve analysis (DCA), ROC curves (AUC evaluation), gene set enrichment analysis (GSEA), and DGIdb‐based drug prediction. Differential expression analysis identified 1878 MDD‐associated genes (715 downregulated, 1163 upregulated). Four FRGs—MAPK14, WIPI1, DUSP1, and ULK1—emerged as diagnostic biomarkers, showing significant immune cell infiltration correlations (e.g., neutrophils, dendritic cells) and enrichment in pathways like MAPK signalling. The study highlights ferroptosis‐related genes (ULK1, MAPK14, WIPI1, DUSP1) as potential diagnostic and therapeutic targets in MDD, linked to neuroimmune interactions and cellular stress responses. These findings underscore MDD's pathophysiological complexity and may guide strategies for managing MDD and neurodegenerative comorbidities.
Huang et al. (Wed,) studied this question.