Machine learning identification and immune infiltration of disulfidptosis-related Alzheimer's disease molecular subtypes.

ABSTRACT:

Background

Alzheimer's disease (AD) is a common neurodegenerative disorder. Disulfidptosis is a newly discovered form of programmed cell death that holds promise as a therapeutic strategy for various disorders. However, the functional roles of disulfidptosis-related genes (DRGs) in AD remain unknown.

Methods

Microarray data and clinical information from patients with AD and healthy controls were downloaded from the Gene Expression Omnibus database. A thorough examination of DRG expression and immune characteristics in both groups was performed. Based on the identified DRGs, we performed an unsupervised clustering analysis to categorize the AD samples into various disulfidptosis-related molecular clusters. Weighted gene co-expression network analysis was performed to select h

SUBMITTER: Zhu Y 

PROVIDER: S-EPMC10566450 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature