Potential biomarkers of aortic dissection based on expression network analysis.

ABSTRACT:

Background

Aortic dissection (AD) is a rare disease with severe morbidity and high mortality. Presently, the pathogenesis of aortic dissection is still not completely clear, and studying its pathogenesis will have important clinical significance.

Methods

We downloaded 28 samples from the Gene Expression Omnibus (GEO) database (Accession numbers: GSE147026 and GSE190635), including 14 aortic dissection samples and 14 healthy controls (HC) samples. The Limma package was used to screen differentially expressed genes. The StarBasev2.0 tool was used to predict the upstream molecular circRNA of the selected miRNAs, and Cytoscape software was used to process the obtained data. STRING database was used to analyze the interacting protein pairs of differentially expressed genes under

SUBMITTER: Feng J 

PROVIDER: S-EPMC10035273 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature