Zhang Qian, Li Jian, Weng Ling
Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China.
Hydrocephalus Center, Xiangya Hospital, Central South University, Changsha, China.
Front Neurosci. 2022 May 9;16:905722. doi: 10.3389/fnins.2022.905722. eCollection 2022.
Aging is recognized as the key risk factor for Alzheimer's disease (AD). This study aimed to identify and verify potential aging-related genes associated with AD using bioinformatics analysis. Aging-related differential expression genes (ARDEGs) were determined by the intersection of limma test, weighted correlation network analysis (WGCNA), and 1153 aging and senescence-associated genes. Potential biological functions and pathways of ARDEGs were determined by GO, KEGG, GSEA, and GSVA. Then, LASSO algorithm was used to identify the hub genes and the diagnostic ability of the five ARDEGs in discriminating AD from the healthy control samples. Further, the correlation between hub ARDEGs and clinical characteristics was explored. Finally, the expression level of the five ARDEGs was validated using other four GEO datasets and blood samples of patients with AD and healthy individuals. Five ARDEGs (GFAP, PDGFRB, PLOD1, MAP4K4, and NFKBIA) were obtained. For biological function analysis, aging, cellular senescence, and Ras protein signal transduction regulation were enriched. Diagnostic ability of the five ARDEGs in discriminating AD from the control samples demonstrated a favorable diagnostic value. Eventually, quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) validation test revealed that compared with healthy controls, the mRNA expression level of PDGFRB, PLOD1, MAP4K4, and NFKBIA were elevated in AD patients. In conclusion, this study identified four ARDEGs (PDGFRB, PLOD1, MAP4K4, and NFKBIA) associated with AD. They provide an insight into potential novel biomarkers for diagnosing AD and monitoring progression.
衰老被认为是阿尔茨海默病（AD）的关键风险因素。本研究旨在通过生物信息学分析识别并验证与AD相关的潜在衰老相关基因。通过limma检验、加权基因共表达网络分析（WGCNA）以及1153个衰老和衰老相关基因的交集来确定衰老相关差异表达基因（ARDEGs）。通过基因本体论（GO）、京都基因与基因组百科全书（KEGG）、基因集富集分析（GSEA）和基因集变异分析（GSVA）来确定ARDEGs的潜在生物学功能和通路。然后，使用套索算法识别枢纽基因以及这五个ARDEGs在区分AD与健康对照样本中的诊断能力。此外，还探讨了枢纽ARDEGs与临床特征之间的相关性。最后，使用其他四个基因表达综合数据库（GEO）数据集以及AD患者和健康个体的血液样本验证了这五个ARDEGs的表达水平。获得了五个ARDEGs（胶质纤维酸性蛋白（GFAP）、血小板衍生生长因子受体β（PDGFRB）、赖氨酰氧化酶1（PLOD1）、丝裂原活化蛋白激酶4激酶4（MAP4K4）和核因子κB抑制蛋白α（NFKBIA））。对于生物学功能分析，富集了衰老、细胞衰老和Ras蛋白信号转导调控。这五个ARDEGs在区分AD与对照样本中的诊断能力显示出良好的诊断价值。最终，定量实时逆转录聚合酶链反应（qRT-PCR）验证试验表明，与健康对照相比，AD患者中PDGFRB、PLOD1、MAP4K4和NFKBIA的mRNA表达水平升高。总之，本研究识别出了四个与AD相关的ARDEGs（PDGFRB、PLOD1、MAP4K4和NFKBIA）。它们为诊断AD和监测疾病进展提供了潜在的新型生物标志物。
