Identification and validation of diagnostic markers of atherosclerosis progression via bioinformatics strategies.

ABSTRACT:

Background

Arteriosclerosis (AS) is a leading cause of cardiovascular disease, imposing significant burdens on families and society. However, the underlying mechanisms remain unclear. This study aims to elucidate these mechanisms and explore potential pharmacological treatments through the integration of bioinformatics.

Methods

The GSE28829 dataset was retrieved from the GEO database. Differential gene expression between early- and late-stage AS plaques in GSE28829 was identified via the limma package. We focused on the intersecting genes associated with endoplasmic reticulum stress and mitochondrial damage. LASSO regression analysis was applied to pinpoint potential core genes associated with AS. An protein interaction network was constructed, with a focus on the hub genes

SUBMITTER: Mao Y 

PROVIDER: S-EPMC12680236 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature