Zhejiang Provincial Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, Zhejiang, China.
Zhejiang Pharmaceutical College, Ningbo, Zhejiang, China.
J Alzheimers Dis. 2022;85(2):729-744. doi: 10.3233/JAD-215086.
COVID-19 pandemic is a global crisis which results in millions of deaths and causes long-term neurological sequelae, such as Alzheimer's disease (AD).
We aimed to explore the interaction between COVID-19 and AD by integrating bioinformatics to find the biomarkers which lead to AD occurrence and development with COVID-19 and provide early intervention.
The differential expressed genes (DEGs) were found by GSE147507 and GSE132903, respectively. The common genes between COVID-19 and AD were identified. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interactions (PPI) network analysis were carried out. Hub genes were found by cytoscape. A multivariate logistic regression model was constructed. NetworkAnalyst was used for the analysis of TF-gene interactions, TF-miRNA coregulatory network, and Protein-chemical Interactions.
Forty common DEGs for AD and COVID-19 were found. GO and KEGG analysis indicated that the DEGs were enriched in the calcium signal pathway and other pathways. A PPI network was constructed, and 5 hub genes were identified (ITPR1, ITPR3, ITPKB, RAPGEF3, MFGE8). Four hub genes (ITPR1, ITPR3, ITPKB, RAPGEF3) which were considered as important factors in the development of AD that were affected by COVID-19 were shown by nomogram. Utilizing NetworkAnalyst, the interaction network of 4 hub genes and TF, miRNA, common AD risk genes, and known compounds is displayed, respectively.
COVID-19 patients are at high risk of developing AD. Vaccination is required. Four hub genes can be considered as biomarkers for prediction and treatment of AD development caused by COVID-19. Compounds with neuroprotective effects can be used as adjuvant therapy for COVID-19 patients.
COVID-19 大流行是一场全球性危机，导致数百万人死亡，并引发长期的神经后遗症，如阿尔茨海默病（AD）。
通过整合生物信息学，寻找与 COVID-19 相关的导致 AD 发生和发展的生物标志物，为 AD 的早期干预提供依据。
分别通过 GSE147507 和 GSE132903 找到差异表达基因（DEGs）。找出 COVID-19 和 AD 之间的共同基因。进行基因本体论（GO）、京都基因与基因组百科全书（KEGG）和蛋白质-蛋白质相互作用（PPI）网络分析。通过 cytoscape 找到枢纽基因。构建多变量逻辑回归模型。使用 NetworkAnalyst 分析 TF-gene 相互作用、TF-miRNA 核心调控网络和 Protein-chemical Interactions。
发现了 40 个 AD 和 COVID-19 的共同 DEGs。GO 和 KEGG 分析表明，这些 DEGs 富集在钙信号通路和其他通路中。构建了一个 PPI 网络，确定了 5 个枢纽基因（ITPR1、ITPR3、ITPKB、RAPGEF3、MFGE8）。通过列线图显示了 4 个枢纽基因（ITPR1、ITPR3、ITPKB、RAPGEF3），这些基因被认为是 COVID-19 影响 AD 发展的重要因素。利用 NetworkAnalyst，分别显示了 4 个枢纽基因和 TF、miRNA、常见 AD 风险基因以及已知化合物的相互作用网络。
COVID-19 患者发生 AD 的风险较高，需要接种疫苗。四个枢纽基因可以作为 COVID-19 引起的 AD 发展预测和治疗的生物标志物。具有神经保护作用的化合物可作为 COVID-19 患者的辅助治疗药物。
