School of Biomedical and Pharmaceutical Sciences, Guangdong University of Technology, 510006 Guangzhou, Guangdong, China.
The Second School of Clinical Medicine, Southern Medical University, 510515 Guangzhou, Guangdong, China.
J Integr Neurosci. 2023 Oct 18;22(6):138. doi: 10.31083/j.jin2206138.
Alzheimer's disease (AD) is a common progressive neurodegenerative disease. The Ubiquitin-Protease system (UPS), which plays important roles in maintaining protein homeostasis in eukaryotic cells, is involved in the development of AD. This study sought to identify differential UPS-related genes (UPGs) in AD patients by using bioinformatic methods, reveal potential biomarkers for early detection of AD, and investigate the association between the identified biomarkers and immune cell infiltration in AD.
The differentially expressed UPGs were screened with bioinformatics analyses using the Gene Expression Omnibus (GEO) database. A weighted gene co-expression network analysis (WGCNA) analysis was performed to explore the key gene modules associated with AD. A Single-sample Gene Set Enrichment Analysis (ssGSEA) analysis was peformed to explore the patterns of immune cells in the brain tissue of AD patients. Real-time quantitative PCR (RT-qPCR) was performed to examine the expression of hub genes in blood samples from healthy controls and AD patients.
In this study, we identified four UPGs (, , , and ) using multiple bioinformatic analyses. Furthermore, three UPGs (, , ) that are strongly correlated with the clinical features of AD were used to construct risk score prediction markers to diagnose and predict the severity of AD. Subsequently, we analyzed the patterns of immune cells in the brain tissue of AD patients and the associations between immune cells and the three key UPGs. Finally, the risk score model was verified in several datasets of AD and showed good accuracy.
Three key UPGs are identified as potential biomarker for AD patients. These genes may provide new targets for the early identification of AD patients.
阿尔茨海默病(AD)是一种常见的进行性神经退行性疾病。泛素-蛋白酶体系统(UPS)在真核细胞中维持蛋白质内稳态方面发挥着重要作用,其与 AD 的发生发展有关。本研究旨在通过生物信息学方法鉴定 AD 患者差异表达的 UPS 相关基因(UPGs),揭示 AD 早期检测的潜在生物标志物,并探讨鉴定出的生物标志物与 AD 中免疫细胞浸润的关系。
使用基因表达综合数据库(GEO)进行生物信息学分析,筛选差异表达的 UPGs。采用加权基因共表达网络分析(WGCNA)分析探讨与 AD 相关的关键基因模块。采用单样本基因集富集分析(ssGSEA)分析探讨 AD 患者脑组织中免疫细胞的模式。采用实时定量 PCR(RT-qPCR)检测健康对照者和 AD 患者血液中关键基因的表达。
本研究通过多种生物信息学分析鉴定了 4 个 UPGs(、、、)。此外,还构建了风险评分预测标志物,以诊断和预测 AD 的严重程度,该标志物与 AD 的临床特征密切相关。进一步分析了 AD 患者脑组织中免疫细胞的模式及其与 3 个关键 UPG 之间的关系。最后,在多个 AD 数据集验证了风险评分模型,显示出良好的准确性。
鉴定出的 3 个关键 UPG 可作为 AD 患者的潜在生物标志物,这些基因可能为 AD 患者的早期识别提供新的靶点。