Analysis of gene expression profiles in Alzheimer’s disease patients with different lifespan: A bioinformatics study focusing on the disease heterogeneity

Zhang, Ji and Li, Xiaojia and Xiao, Jun and Xiang, Yang and Ye, Fang (2023) Analysis of gene expression profiles in Alzheimer’s disease patients with different lifespan: A bioinformatics study focusing on the disease heterogeneity. Frontiers in Aging Neuroscience, 15. ISSN 1663-4365

[thumbnail of pubmed-zip/versions/1/package-entries/fnagi-15-1072184/fnagi-15-1072184.pdf] Text
pubmed-zip/versions/1/package-entries/fnagi-15-1072184/fnagi-15-1072184.pdf - Published Version

Download (4MB)

Abstract

Objective: Alzheimer’s disease (AD) as the most frequent neurodegenerative disease is featured by gradual decline of cognition and social function in the elderly. However, there have been few studies focusing on AD heterogeneity which exists both genetically and clinically, leading to the difficulties of AD researches. As one major kind of clinical heterogeneity, the lifespan of AD patients varies significantly. Aiming to investigate the potential driving factors, the current research identified the differentially expressed genes (DEGs) between longer-lived AD patients and shorter-lived ones via bioinformatics analyses.

Methods: Qualified datasets of gene expression profiles were identified in National Center of Biotechnology Information Gene Expression Omnibus (NCBI-GEO). The data of the temporal lobes of patients above 60 years old were used. Two groups were divided according to the lifespan: the group ≥85 years old and the group <85 years old. Then GEO2R online software and R package of Robust Rank Aggregation (RRA) were used to screen DEGs. Bioinformatic tools were adopted to identify possible pathways and construct protein–protein interaction network.

Result: Sixty-seven AD cases from four qualified datasets (GSE28146, GSE5281, GSE48350, and GSE36980) were included in this study. 740 DEGs were identified with 361 upregulated and 379 downregulated when compared longer-lived AD patients with shorter-lived ones. These DEGs were primarily involved in the pathways directly or indirectly associated with the regulation of neuroinflammation and cancer pathogenesis, as shown by pathway enrichment analysis. Among the DEGs, the top 15 hub genes were identified from the PPI network. Notably, the same bioinformatic procedures were conducted in 62 non-AD individuals (serving as controls of AD patients in the four included studies) with distinctly different findings from AD patients, indicating different regulatory mechanisms of lifespan between non-AD controls and AD, reconfirming the necessity of the present study.

Conclusion: These results shed some lights on lifespan-related regulatory mechanisms in AD patients, which also indicated that AD heterogeneity should be more taken into account in future investigations.

Item Type: Article
Subjects: STM Library Press > Medical Science
Depositing User: Unnamed user with email support@stmlibrarypress.com
Date Deposited: 22 Jun 2024 08:53
Last Modified: 22 Jun 2024 08:53
URI: http://journal.scienceopenlibraries.com/id/eprint/1834

Actions (login required)

View Item
View Item