Identification of Blood Biomarkers Related to Energy Metabolism and Construction of Diagnostic Prediction Model Based on Three Independent Alzheimer's Disease Cohorts.

ABSTRACT:

Background

Blood biomarkers are crucial for the diagnosis and therapy of Alzheimer's disease (AD). Energy metabolism disturbances are closely related to AD. However, research on blood biomarkers related to energy metabolism is still insufficient.

Objective

This study aims to explore the diagnostic and therapeutic significance of energy metabolism-related genes in AD.

Methods

AD cohorts were obtained from GEO database and single center. Machine learning algorithms were used to identify key genes. GSEA was used for functional analysis. Six algorithms were utilized to establish and evaluate diagnostic models. Key gene-related drugs were screened through network pharmacology.

Results

We identified 4 energy metabolism genes, NDUFA1, MECOM, RPL26, and RPS27. These ge

SUBMITTER: Wang H 

PROVIDER: S-EPMC11380308 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature