Identification of crucial genes involved in pathogenesis of regional weakening of the aortic wall

Hong Lin Zu,Hai Yang Wang,Hong Wei Liu

doi:10.1186/s41065-021-00200-1

Abstract

BackgroundThe diameter of the abdominal aortic aneurysm (AAA) is the most commonly used parameter for the prediction of occurrence of AAA rupture. However, the most vulnerable region of the aortic wall may be different from the most dilated region of AAA under pressure. The present study is the first to use weighted gene coexpression network analysis (WGCNA) to detect the coexpressed genes that result in regional weakening of the aortic wall.MethodsThe GSE165470 raw microarray dataset was used in the present study. Differentially expressed genes (DEGs) were filtered using the “limma” R package. DEGs were assessed by Gene Ontology biological process (GO-BP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. WGCNA was used to construct the coexpression networks in the samples with regional weakening of the AAA wall and in the control group to detect the gene modules. The hub genes were defined in the significant functional modules, and a hub differentially expressed gene (hDEG) coexpression network was constructed with the highest confidence based on protein–protein interactions (PPIs). Molecular compound detection (MCODE) was used to identify crucial genes in the hDEG coexpression network. Crucial genes in the hDEG coexpression network were validated using the GSE7084 and GSE57691 microarray gene expression datasets.ResultA total of 350 DEGs were identified, including 62 upregulated and 288 downregulated DEGs. The pathways were involved in immune responses, vascular smooth muscle contraction and cell–matrix adhesion of DEGs in the samples with regional weakening in AAA. Antiquewhite3 was the most significant module and was used to identify downregulated hDEGs based on the result of the most significant modules negatively related to the trait of weakened aneurysm walls. Seven crucial genes were identified and validated: ACTG2, CALD1, LMOD1, MYH11, MYL9, MYLK, and TPM2. These crucial genes were associated with the mechanisms of AAA progression.ConclusionWe identified crucial genes that may play a significant role in weakening of the AAA wall and may be potential targets for medical therapies and diagnostic biomarkers. Further studies are required to more comprehensively elucidate the functions of crucial genes in the pathogenesis of regional weakening in AAA.

Highlights

Ruptured abdominal aortic aneurysm (AAA) is an important complication caused by AAA, resulting in severe haemorrhagic shock, and is associated with a mortality rate as high as 81% [1]
We identified crucial genes that may play a significant role in weakening of the AAA wall and may be potential targets for medical therapies and diagnostic biomarkers
Upregulated and downregulated Differentially expressed genes (DEGs) were used for Gene Ontology biological process (GO-Biological process (BP)) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses by using the Database for Annotation, Visualization and Integrated Discovery (DAVID) v6.8 [14]

Summary

Introduction

Ruptured abdominal aortic aneurysm (AAA) is an important complication caused by AAA, resulting in severe haemorrhagic shock, and is associated with a mortality rate as high as 81% [1]. Most patients with AAA are asymptomatic, and population-based screening studies have reported the prevalence rates of AAA ranging from 1.6% to 7.2% of the general population from 60 to 65 years of age or older [2]. Smoking, uncontrolled blood pressure, older age, female sex and aneurysm diameter are risk factors for AAA rupture. The diameter of the aneurysm is the most commonly used parameter for the prediction of occurrence of AAA rupture, and patients with larger diameter aneurysms are at the highest risk of aortic rupture. The diameter of the abdominal aortic aneurysm (AAA) is the most commonly used parameter for the prediction of occurrence of AAA rupture. The present study is the first to use weighted gene coexpression network analysis (WGCNA) to detect the coexpressed genes that result in regional weakening of the aortic wall

Methods

Results

Discussion

Conclusion