Abstract：
Alzheimer\'s disease (AD) is a neurodegenerative disorder with early autophagy deficits. Our study probed the role of lysosomal-related genes (LRGs) in AD. Using the Gene Expression Omnibus (GEO) database, we analyzed differentially expressed genes (DEGs) in AD. AD-related genes and lysosomal-related genes (LRGs) were extracted from public databases. Leveraging the UpSetR package, we identified differentially expressed LRGs (DE-LRGs). Subsequently, consensus cluster analysis was used to stratify AD patients into distinct molecular subtypes based on DE-LRGs. Immune cell patterns were studied via Single-Sample Gene Set Enrichment Analysis (ssGSEA). Molecular pathways were assessed through Gene Set Variation Analysis (GSVA), while Mendelian Randomization (MR) discerned potential gene-AD causations. To reinforce our bioinformatics findings, we conducted in vitro experiments. In total, 52 DE-LRGs were identified, with LAMP1, VAMP2, and CTSB as standout hub genes. Leveraging the 52 DE-LRGs, AD patients were categorized into three distinct molecular subtypes. Interestingly, the three aforementioned hub genes exhibited significant predictive accuracy for AD differentiation across the subtypes. The ssGSEA further illuminated correlations between LAMP1, VAMP2, and CTSB with plasma cells, fibroblasts, eosinophils, and endothelial cells. GSVA analysis underscored significant associations of LAMP1, VAMP2, and CTSB with NOTCH, TGFβ, and P53 pathways. Compellingly, MR findings indicated a potential causative relationship between LAMP1, CTSB, and AD. Augmenting our bioinformatics conclusions, in vitro tests revealed that LAMP1 potentially alleviates AD progression by amplifying autophagic processes. LAMP1 and CTSB emerge as potential AD biomarkers, paving the way for innovative therapeutic interventions.
摘要：
阿尔茨海默病(AD)是一种早期自噬缺陷的神经退行性疾病。我们的研究探讨了溶酶体相关基因（LRGs）在AD中的作用。使用基因表达综合（GEO）数据库，我们分析了AD中的差异表达基因（DEGs）。从公共数据库中提取AD相关基因和溶酶体相关基因(LRGs)。利用UpSetR包，我们鉴定了差异表达的LRGs(DE-LRGs)。随后，基于DE-LRGs,使用共识聚类分析将AD患者分为不同的分子亚型.通过单样品基因组富集分析(ssGSEA)研究免疫细胞模式。通过基因集变异分析（GSVA）评估分子途径，而孟德尔随机化（MR）识别潜在的基因-AD病因。为了加强我们的生物信息学发现，我们进行了体外实验。总的来说,确定了52个DE-LRG，与LAMP1，VAMP2和CTSB作为突出的枢纽基因。利用52个DE-LRG，AD患者分为三种不同的分子亚型。有趣的是,上述3个hub基因对不同亚型的AD分化表现出显著的预测准确性.ssGSEA进一步阐明了LAMP1，VAMP2和CTSB与浆细胞之间的相关性，成纤维细胞,嗜酸性粒细胞,和内皮细胞。GSVA分析强调了LAMP1、VAMP2和CTSB与NOTCH的显著关联，TGFβ,和P53途径。令人信服的是，MR结果表明，LAMP1、CTSB、和AD。增强我们的生物信息学结论，体外试验显示,LAMP1可能通过放大自噬过程来缓解AD进展.LAMP1和CTSB成为潜在的AD生物标志物，为创新的治疗干预措施铺平道路。
