Integrated Bioinformatics Analysis Identifies Hub Genes Associated with Viral Infection and Alzheimer’s Disease

Autor: Xiaoru, Sun, Hui, Zhang, Dongdong, Yao, Yaru, Xu, Qi, Jing, Silu, Cao, Li, Tian, Cheng, Li
Rok vydání: 2022
Předmět:
Zdroj: Journal of Alzheimer's Disease. 85:1053-1061
ISSN: 1875-8908
1387-2877
Popis: Background: Alzheimer’s disease (AD) is a fatal neurodegenerative disease, the etiology of which is unclear. Previous studies have suggested that some viruses are neurotropic and associated with AD. Objective: By using bioinformatics analysis, we investigated the potential association between viral infection and AD. Methods: A total of 5,066 differentially expressed genes (DEGs) in the temporal cortex between AD and control samples were identified. These DEGs were then examined via weighted gene co-expression network analysis (WGCNA) and clustered into modules of genes with similar expression patterns. Of identified modules, module turquoise had the highest correlation with AD. The module turquoise was further characterized using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis. Results: Our results showed that the KEGG pathways of the module turquoise were mainly associated with viral infection signaling, specifically Herpes simplex virus, Human papillomavirus, and Epstein-Barr virus infections. A total of 126 genes were enriched in viral infection signaling pathways. In addition, based on values of module membership and gene significance, a total of 508 genes within the module were selected for further analysis. By intersecting these 508 genes with those 126 genes enriched in viral infection pathways, we identified 4 hub genes that were associated with both viral infection and AD: TLR2, COL1A2, NOTCH3, and ZNF132. Conclusion: Through bioinformatics analysis, we demonstrated a potential link between viral infection and AD. These findings may provide a platform to further our understanding of AD pathogenesis.
Databáze: OpenAIRE
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