Identification of Immune-Associated Genes in Diagnosing Aortic Valve Calcification With Metabolic Syndrome by Integrated Bioinformatics Analysis and Machine Learning.

ABSTRACT:

Background

Immune system dysregulation plays a critical role in aortic valve calcification (AVC) and metabolic syndrome (MS) pathogenesis. The study aimed to identify pivotal diagnostic candidate genes for AVC patients with MS.

Methods

We obtained three AVC and one MS dataset from the gene expression omnibus (GEO) database. Identification of differentially expressed genes (DEGs) and module gene via Limma and weighted gene co-expression network analysis (WGCNA), functional enrichment analysis, protein-protein interaction (PPI) network construction, and machine learning algorithms (least absolute shrinkage and selection operator (LASSO) regression and random forest) were used to identify candidate immune-associated hub genes for diagnosing AVC with MS. To assess the dia

SUBMITTER: Zhou Y 

PROVIDER: S-EPMC9295723 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature