Exploring the Key Genes and Identification of Potential Diagnosis Biomarkers in Alzheimer's Disease Using Bioinformatics Analysis.

ABSTRACT:

Background

Alzheimer's disease (AD) is one of the major threats of the twenty-first century and lacks available therapy. Identification of novel molecular markers for diagnosis and treatment of AD is urgently demanded, and genetic biomarkers show potential prospects.

Method

We identify and intersected differentially expressed genes (DEGs) from five microarray datasets to detect consensus DEGs. Based on these DEGs, we conducted Gene Ontology (GO), performed the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, constructed a protein-protein interaction (PPI) network, and utilized Cytoscape to identify hub genes. The least absolute shrinkage and selection operator (LASSO) logistic regression was applied to identify potential diagnostic biomarkers. Gene set enr

SUBMITTER: Yu W 

PROVIDER: S-EPMC8236887 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature