Identification of biomarkers in Alzheimer's disease and COVID-19 by bioinformatics combining single-cell data analysis and machine learning algorithms.

ABSTRACT:

Background

Since its emergence in 2019, COVID-19 has become a global epidemic. Several studies have suggested a link between Alzheimer's disease (AD) and COVID-19. However, there is little research into the mechanisms underlying these phenomena. Therefore, we conducted this study to identify key genes in COVID-19 associated with AD, and evaluate their correlation with immune cells characteristics and metabolic pathways.

Methods

Transcriptome analyses were used to identify common biomolecular markers of AD and COVID-19. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were performed on gene chip datasets (GSE213313, GSE5281, and GSE63060) from AD and COVID-19 patients to identify genes associated with both conditions. Gene ontology (GO

SUBMITTER: Li J 

PROVIDER: S-EPMC11835241 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature