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整合生物信息学与实验验证确定溶酶体和免疫浸润相关基因作为晚发性重度抑郁症的治疗靶点。

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

作者信息

Hu Jian-Zhen, Gao Yao, Song Xiao-Na, Wang Dan, Du Xin-Zhe, Wang Xiao, Hu Xiao-Dong, Liu Sha

机构信息

Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China.

Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorders, First Hospital of Shanxi Medical University, Taiyuan, China.

出版信息

Sci Rep. 2025 Jul 31;15(1):27946. doi: 10.1038/s41598-025-10283-9.

DOI:10.1038/s41598-025-10283-9
PMID:40744973
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12313857/
Abstract

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.

摘要

本研究利用生物信息学来识别与晚发性重度抑郁症(LOD)患者溶酶体改变相关的差异基因,并探索潜在的治疗药物。我们使用加权基因共表达网络分析(WGCNA)分析GSE76826数据集中的差异基因,以识别与LOD相关的模块。与溶酶体基因进行交集分析后,我们利用受试者工作特征曲线(ROC)和套索回归来评估诊断意义。对关键模块进行通路富集分析,随后使用CIBESORT、MCPcounter和quanTIseq分析LOD患者的免疫浸润情况。通过慢性不可预测轻度应激模型证实了所选基因表达的变化。ITCM数据库预测了靶向溶酶体相关基因的小分子药物。我们从绿色模块中选择了ANK3、BIN1、CKAP4、GPRASP1、MYO7A和RAB20,这些基因具有诊断价值。基因本体(GO)生物学过程揭示了与T细胞分化及其调控的联系。免疫浸润分析表明LOD患者与CD8 + T细胞和中性粒细胞之间存在关联,BIN1与CD8 + T细胞呈正相关。动物模型中的逆转录-定量聚合酶链反应(RT-qPCR)验证证实了我们的生物信息学研究结果。ITCM数据库表明,17-β-雌二醇和镍化合物可能是LOD的潜在治疗药物。LOD的病因涉及多个基因和通路,CD8 + T细胞和中性粒细胞可能会加剧该疾病。17-β-雌二醇和镍可能为LOD提供有针对性的治疗选择。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a6b/12313857/61fd9d10512a/41598_2025_10283_Fig8_HTML.jpg
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