Ontology highlight
ABSTRACT: Objective
The inability to intervene in Alzheimer's disease (AD) forces the search for promising gene-targeted therapies. This study was aimed at exploring molecular signatures and mechanistic pathways to improve the diagnosis and treatment of AD.Methods
Microarray datasets were collected to filter differentially expressed genes (DEGs) between AD and nondementia controls. Weight gene correlation network analysis (WGCNA) was employed to analyze the correlation of coexpression modules with AD phenotype. A global regulatory network was established and then visualized using Cytoscape software to determine hub genes and their mechanistic pathways. Receiver operating characteristic (ROC) analysis was conducted to estimate the diagnostic performance of hub genes in AD prediction.<
SUBMITTER: Chen F
PROVIDER: S-EPMC9006080 | biostudies-literature | 2022
REPOSITORIES: biostudies-literature