Identification of Methylated Gene Biomarkers in Patients with Alzheimer's Disease Based on Machine Learning.

ABSTRACT:

Background

Alzheimer's disease (AD) is a neurodegenerative disorder and characterized by the cognitive impairments. It is essential to identify potential gene biomarkers for AD pathology.

Methods

DNA methylation expression data of patients with AD were downloaded from the Gene Expression Omnibus (GEO) database. Differentially methylated sites were identified. The functional annotation analysis of corresponding genes in the differentially methylated sites was performed. The optimal diagnostic gene biomarkers for AD were identified by using random forest feature selection procedure. In addition, receiver operating characteristic (ROC) diagnostic analysis of differentially methylated genes was performed.

Results

A total of 10 differentially methylated sites including 5 h

SUBMITTER: Ren J 

PROVIDER: S-EPMC7139879 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature