Dataset Information

Identification of crucial genes mediating abdominal aortic aneurysm pathogenesis based on gene expression profiling of perivascular adipose tissue by WGCNA.

ABSTRACT:

Background

With a mortality rate of 65-85%, a ruptured abdominal aortic aneurysm (AAA) can have catastrophic consequences for patients. However, few effective pharmaceutical treatments are available to treat this condition. Therefore, elucidating the pathogenesis of AAA and finding the potential molecular targets for medical therapies are vital lines of research.

Methods

An mRNA microarray dataset of perivascular adipose tissue (PVAT) in AAA patients was downloaded and differentially expressed gene (DEG) screening was performed. Weighted gene co-expression networks for dilated and non-dilated PVAT samples were constructed via weighted correlation network analysis (WGCNA) and used to detect gene modules. Functional annotation analysis was performed for the DEGs and gene modules. We identified the hub genes of the modules and created a DEG co-expression network. We then mined crucial genes based on this network using Molecular Complex Detection (MCODE) in Cytoscape. Crucial genes with top-6 degree in the crucial gene cluster were visualized, and their potential clinical significance was determined.

Results

Of the 173 DEGs screened, 99 were upregulated and 74 were downregulated. Co-expression networks were built and we detected 6 and 5 modules for dilated and non-dilated PVAT samples, respectively. The turquoise and black modules for dilated PVAT samples were related to inflammation and immune response. MAP4K1 and PROK2 were the hub genes of these 2 modules, respectively. Then a DEG co-expression network with 112 nodes and 953 edges was created. PLAU was the crucial gene with the highest connectivity and showed potential clinical significance.

Conclusions

Using WGCNA, gene modules were detected and hub genes and crucial genes were identified. These crucial genes might be potential targets for pharmaceutic therapies and have potential clinical significance. Future in vitro and in vivo experiments are required to more comprehensively explore the biological mechanisms by which these genes affect AAA pathogenesis.

SUBMITTER: Chen S

PROVIDER: S-EPMC7859787 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Publications

Identification of crucial genes mediating abdominal aortic aneurysm pathogenesis based on gene expression profiling of perivascular adipose tissue by WGCNA.

Chen Siliang S Yang Dan D Liu Bao B Chen Yuexin Y Ye We W Chen Mengyin M Zheng Yuehong Y

Annals of translational medicine 20210101 1

<h4>Background</h4>With a mortality rate of 65-85%, a ruptured abdominal aortic aneurysm (AAA) can have catastrophic consequences for patients. However, few effective pharmaceutical treatments are available to treat this condition. Therefore, elucidating the pathogenesis of AAA and finding the potential molecular targets for medical therapies are vital lines of research.<h4>Methods</h4>An mRNA microarray dataset of perivascular adipose tissue (PVAT) in AAA patients was downloaded and differentia ...[more]

PMID: 33553345

Similar Datasets

Project description:Background:Abdominal aortic aneurysm (AAA) is the full thickness dilation of the abdominal aorta. However, few effective medical therapies are available. Thus, elucidating the molecular mechanism of AAA pathogenesis and exploring the potential molecular target of medical therapies for AAA is of vital importance. Methods:Three expression datasets (GSE7084, GSE47472 and GSE57691) were downloaded from the Gene Expression Omnibus (GEO). These datasets were merged and then normalized using the "sva" R package. Differential expressed gene (DEG) analysis and weighted gene co-expression network analysis (WGCNA) were conducted. We compared the co-expression patterns between AAA and normal conditions, and hub genes of each functional module were identified. DEGs were mapped to co-expression network under AAA condition and a DEG co-expression network was generated. Crucial genes were identified using molecular complex detection (MCODE) (a plugin in Cytoscape). Results:In our study, 6 and 10 gene modules were detected for the AAA and normal conditions, respectively, while 143 DEGs were screened. Compared to the normal condition, genes associated with immune response, inflammation and muscle contraction were clustered in three gene modules respectively under the AAA condition; the hub genes of the three modules were MAP4K1, NFIB and HPK1, respectively. A DEG co-expression network with 102 nodes and 303 edges was identified, and a hub gene cluster with 10 genes from the DEG co-expression network was detected. YIPF6, RABGAP1, ANKRD6, GPD1L, PGRMC2, HIGD1A, GMDS, MGP, SLC25A4 and FAM129A were in the cluster. The expression levels of these 10 genes showed potential diagnostic value. Conclusion:Based on WGCNA, we detected 6 modules under the AAA condition and 10 modules in the normal condition. Hub genes of each module and hub gene clusters of the DEG co-expression network were identified. These genes may act as potential targets for medical therapy and diagnostic biomarkers. Further studies are needed to elucidate the detailed biological function of these genes in the pathogenesis of AAA.

Project description:Objective: Abdominal aortic aneurysm (AAA) refers to unusual permanent dilation of the abdominal aorta, and gradual AAA expansion can lead to fatal rupture. However, we lack clear understanding of the pathogenesis of this disease. The effect of perivascular adipose tissue (PVAT) on vascular functional status has attracted increasing attention. Here, we try to identify the potential mechanisms linking AAA and PVAT. Methods: We downloaded dataset GSE119717, including 30 dilated AAA PVAT samples and 30 non-dilated aorta PVAT samples from AAA cases, from Gene Expression Omnibus to identify differentially expressed genes (DEGs). We performed pathway enrichment analysis by Metascape, ClueGo and DAVID to annotate PVAT functional status according to the DEGs. A protein-protein interaction network, the support vector machine (SVM)-recursive feature elimination and the least absolute shrinkage and selection operator regression model were constructed to identify feature genes. Immune infiltration analysis was explored by CIBERSORT. And the correlation between feature gene and immune cells was also calculated. Finally, we used the angiotensin II (Ang II)-ApoE-/- mouse model of AAA to verify the effect of feature gene expression by confirming protein expression using immunohistochemistry and western blot. Results: We identified 22 DEGs, including 21 upregulated genes and 1 downregulated gene. The DEGs were mainly enriched in neutrophil chemotaxis and IL-17 signaling pathway. FOS was identified as a good diagnostic feature gene (AUC = 0.964). Immune infiltration analysis showed a higher level of T cells follicular helper, activated NK cells, Monocytes, activated Mast cells in AAA group. And FOS was correlated with immune cells. Immunohistochemistry and western blot confirmed higher FOS expression in PVAT of the AAA mouse model compared to control group. Conclusion: The differentially expressed genes and pathways identified in this study provide further understanding of how PVAT affects AAA development. FOS was identified as the diagnostic gene. There was an obvious difference in immune cells infiltration between normal and AAA groups.

Project description:BackgroundAbdominal aortic aneurysms (AAAs) represent a complex multifactorial hemodynamic, thrombotic, and inflammatory process that can ultimately result in aortic rupture and death. Despite improved screening and surgical management of AAAs, the mortality rates have remained high after rupture, and little progress has occurred in the development of nonoperative treatments. Intraluminal thrombus (ILT) is present in most AAAs and might be involved in AAA pathogenesis. The present review examined the latest clinical and experimental evidence for possible involvement of the ILT in AAA growth and rupture.MethodsA literature review was performed after a search of the PubMed database from 2012 to June 2020 using the terms "abdominal aortic aneurysm" and "intraluminal thrombus."ResultsThe structure, composition, and hemodynamics of ILT formation and propagation were reviewed in relation to the hemostatic and proteolytic factors favoring ILT deposition. The potential effects of the ILT on AAA wall degeneration and rupture, including a review of the current controversies regarding the position, thickness, and composition of ILT, are presented. Although initially potentially protective against increased wall stress, increasing evidence has shown that an increased volume and greater age of the ILT have direct detrimental effects on aortic wall integrity, which might predispose to an increased rupture risk.ConclusionsILT does not appear to be an innocent bystander in AAA pathophysiology. However, its exact role remains elusive and controversial. Despite computational evidence of a possible protective role of the ILT in reducing wall stress, increasing evidence has shown that the ILT promotes AAA wall degeneration in humans and in animal models. Further research, with large animal models and with more chronic ILT is crucial for a better understanding of the role of the ILT in AAAs and for the potential development of targeted therapies to slow or halt AAA progression.

Dataset Information

Identification of crucial genes mediating abdominal aortic aneurysm pathogenesis based on gene expression profiling of perivascular adipose tissue by WGCNA.

Background

Methods

Results

Conclusions

Publications

Identification of crucial genes mediating abdominal aortic aneurysm pathogenesis based on gene expression profiling of perivascular adipose tissue by WGCNA.

Similar Datasets

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