Integrated bioinformatics and experimental validation identify lysosome and immune infiltration-related genes as therapeutic targets in late-onset major depressive disorder

This study leverages bioinformatics to identify differential genes linked to lysosomal alterations in late-onset major depressivedisorder (LOD) patients and explores potential therapeutic drugs. We analyzed differential genes in the GSE76826 dataset usingWGCNA to identify modules associated with LOD. After intersecting with lysosomal genes, we utilized ROC and Lasso regression toassess diagnostic significance. Pathway enrichment analysis was conducted on key modules, followed by CIBESORT, MCPcounter,and quanTIseq to analyze immune infiltration in LOD patients. The changes in the expression of selected genes were confirmedthrough a chronic unpredictable mild stress model. The ITCM database predicted small molecule drugs targeting lysosome-relatedgenes. We selected ANK3, BIN1, CKAP4, GPRASP1, MYO7A, and RAB20 from the Green module, which showed diagnostic value.GO biological processes revealed a link to T cell differentiation and its regulation. Immune infiltration analysis indicated a relationshipbetween LOD patients and CD8 + T cells and neutrophils, with BIN1 positively correlating with CD8 + T cells. RT-qPCR verification inanimal models confirmed our bioinformatics findings. The ITCM database suggested that 17-beta-estradiol and nickel compoundscould be potential treatments for LOD. LOD's etiology involves multiple genes and pathways, with CD8 + T cells and Neutrophils cellspotentially advancing the disorder. 17-beta-estradiol and nickel may offer targeted therapeutic options for LOD.