Crucial Genes in Aortic Dissection Identified by Weighted Gene Coexpression Network Analysis

Area of Science:

• Vascular Biology
• Genomics
• Bioinformatics

Background:

• Aortic dissection (AD) is a life-threatening vascular condition with significant mortality.
• While AD's clinical aspects are known, its underlying molecular mechanisms require further elucidation.
• Gene expression profiling offers insights into AD's genetic regulation and risk factor modifications.

Purpose of the Study:

• To identify critical genes and molecular pathways involved in aortic dissection.
• To utilize bioinformatics approaches for understanding AD pathogenesis.
• To explore the role of gene expression in AD development.

Main Methods:

• Gene expression profiling via next-generation RNA sequencing in 9 AD patients and 10 controls.
• Differential gene expression (DEG) analysis using DEGseq.
• Weighted gene coexpression network analysis (WGCNA) and VisANT for identifying crucial genes and modules.
• Gene Ontology (GO) analysis utilizing DAVID.

Main Results:

• DEG analysis identified 1,113 genes associated with AD, with 812 downregulated and 301 upregulated.
• DEGs were significantly enriched in immune response categories, including MHC class II activity.
• WGCNA revealed three gene modules correlated with AD; module 37 showed the strongest positive correlation (0.72).
• Five hub genes (AGFG1, MCEMP1, IRAK3, KCNE1, CLEC4D) within module 37 exhibited high connectivity and potential clinical significance.

Conclusions:

• The study suggests a significant involvement of the immune system in aortic dissection pathogenesis.
• The identified hub genes (AGFG1, MCEMP1, IRAK3, KCNE1, CLEC4D) in module 37 are strongly associated with AD.
• These genes may serve as potential biomarkers or therapeutic targets for understanding and managing aortic dissection.