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

Aging Neuroscience

Jun Xiao¹  Fang Ye¹  Yang Xiang¹  Xiaojia Li¹  Ji Zhang² 

[1] Department of Neurology, Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital, Chengdu, China;Department of Neurology, Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu, China;Department of Neurology, West China Hospital of Sichuan University, Chengdu, China;

关键词: Alzheimer’s disease;    lifespan;    differentially expressed genes;    functional enrichment analysis;    hub gene;   

DOI  :  10.3389/fnagi.2023.1072184

 received in 2022-10-17, accepted in 2023-01-30,  发布年份 2023

来源: Frontiers

【 摘 要 】

ObjectiveAlzheimer’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.MethodsQualified 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.ResultSixty-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.ConclusionThese 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.

【 授权许可】

Unknown   
Copyright © 2023 Zhang, Li, Xiao, Xiang and Ye.