Identification of key genes and pathways in calcific aortic valve disease by bioinformatics analysis.

ABSTRACT:

Background

Calcific aortic valve disease (CAVD) is the most common type of valvular heart disease in the elderly. This study is aimed to explore molecular mechanism of CAVD via bioinformatics analysis.

Methods

The gene expression profiles of GSE51472 (including 5 normal aortic valve and 5 calcified aortic valve) and GSE83453 (including 8 normal aortic valve and 19 calcified aortic valve) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened using the MetaDE package in R software. Functional and pathway enrichment analysis were performed based on Gene ontology (GO) and KEGG pathway database. Then, STRING database, Cytoscape and MCODE were applied to construct the protein-protein interaction (PPI) network and scree

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC6988017 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature