Microarray Analysis of Differential Gene Expression in Alzheimer's Disease Identifies Potential Biomarkers with Diagnostic Value.

ABSTRACT: BACKGROUND Alzheimer disease (AD) is a common and fatal subtype of dementia that remains a challenge to diagnose and treat. This study aimed to identify potential biomarkers that influence the prognosis of AD. MATERIAL AND METHODS A total of 6 gene expression profiles from the Gene Expression Omnibus (GEO) database were assessed for their potential as AD biomarkers. We identified differentially expressed genes (DEGs) using the prediction analysis for microarray (PAM) algorithm and obtained hub genes through the analysis of the protein-protein interaction (PPI) network and module analysis. RESULTS We identified 6 gene expression profiles from the GEO database and assessed their potential as AD biomarkers. Shared gene sets were extracted and integrated into large expression profile matrices.

SUBMITTER: Liu L 

PROVIDER: S-EPMC7001516 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature