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Identification of key genes associated with the human abdominal aortic aneurysm based on the gene expression profile.

ABSTRACT: The present study was aimed at screening the key genes associated with abdominal aortic aneurysm (AAA) in the neck, and to investigate the molecular mechanism underlying the development of AAA. The gene expression profile, GSE47472, including 14 AAA neck samples and eight donor controls, was downloaded from the Gene Expression Omnibus database. The total AAA samples were grouped into two types to avoid bias. Differentially expressed genes (DEGs) were screened in patients with AAA and subsequently compared with donor controls using linear models for microarray data, or the Limma package in R, followed by gene ontology enrichment analysis. Furthermore, a protein?protein interaction (PPI) network based on the DEGs was constructed to detect highly connected regions using a Cytoscape plugin. In total, 388 DEGs in the AAA samples were identified. These DEGs were predominantly associated with limb development, including embryonic limb development and appendage development. Nuclear receptor co?repressor 1 (NCOR1), histone 4 (H4), E2F transcription factor 4 (E2F4) and hepatocyte nuclear factor 4? (HNF4A) were the four transcription factors associated with AAA. Furthermore, HNF4A indirectly interacted with the other three transcription factors. Additionally, six clusters were selected from the PPI network. The DEG screening process and the construction of an interaction network enabled an understanding of the mechanism of AAA to be gleaned. HNF4A may exert an important role in AAA development through its interactions with the three other transcription factors (E2F4, NCOR1 and H4), and the mechanism of this coordinated regulation of the transcription factors in AAA may provide a suitable target for the development of therapeutic intervention strategies.

SUBMITTER: Chen X

PROVIDER: S-EPMC4758287 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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Identification of key genes associated with the human abdominal aortic aneurysm based on the gene expression profile.

Chen Xudong X Zheng Chengfei C He Yunjun Y Tian Lu L Li Jianhui J Li Donglin D Jin Wei W Li Ming M Zheng Shusen S

Molecular medicine reports 20151015 6

The present study was aimed at screening the key genes associated with abdominal aortic aneurysm (AAA) in the neck, and to investigate the molecular mechanism underlying the development of AAA. The gene expression profile, GSE47472, including 14 AAA neck samples and eight donor controls, was downloaded from the Gene Expression Omnibus database. The total AAA samples were grouped into two types to avoid bias. Differentially expressed genes (DEGs) were screened in patients with AAA and subsequentl ...[more]

PMID: 26498477

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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:BackgroundWith 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.MethodsAn 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.ResultsOf 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.ConclusionsUsing 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.

Project description:Approximately 13,000 people die of an abdominal aortic aneurysm (AAA) every year. This study aimed to identify the immune response-related genes that play important roles in AAA using bioinformatics approaches. We downloaded the GSE57691 and GSE98278 datasets related to AAA from the Gene Expression Omnibus database, which included 80 AAA and 10 normal vascular samples. CIBERSORT was used to analyze the samples and detect the infiltration of 22 types of immune cells and their differences and correlations. The principal component analysis showed significant differences in the infiltration of immune cells between normal vascular and AAA samples. High proportions of CD4+ T cells, activated mast cells, resting natural killer cells, and 12 other types of immune cells were found in normal vascular tissues, whereas high proportions of macrophages, CD8+ T cells, resting mast cells, and six other types of immune cells were found in AAA tissues. In the selected samples, we identified 39 upregulated (involved in growth factor activity, hormone receptor binding, and cytokine receptor activity) and 133 downregulated genes (involved in T cell activation, cell chemotaxis, and regulation of immune response mediators). The key differentially expressed immune response-related genes were screened using the STRING database and Cytoscape software. Two downregulated genes, PI3 and MAP2K1, and three upregulated genes, SSTR1, GPER1, and CCR10, were identified by constructing a protein-protein interaction network. Functional enrichment of the differentially expressed genes was analyzed, and the expression of the five key genes in AAA samples was verified using quantitative polymerase chain reaction, which revealed that MAP2K1 was downregulated in AAA, whereas SSTR1, GEPR1, and CCR10 were upregulated; there was no significant difference in PI3 expression. Our study shows that normal vascular and AAA samples can be distinguished via the infiltration of immune cells. Five genes, PI3, MAP2K1, SSTR1, GPER1, and CCR10, may play important roles in the development, diagnosis, and treatment of AAA.

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Identification of key genes associated with the human abdominal aortic aneurysm based on the gene expression profile.

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Identification of key genes associated with the human abdominal aortic aneurysm based on the gene expression profile.

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