Dataset Information

Bioinformatics analysis of key genes and miRNAs associated with Stanford type A aortic dissection.

ABSTRACT:

Background

Aortic dissection is one of the most detrimental cardiovascular diseases with a high risk of mortality and morbidity. This study aimed to examine the key genes and microRNAs associated with Stanford type A aortic dissection (AAD).

Methods

The expression data of AAD and healthy samples were downloaded from two microarray datasets in the Gene Expression Omnibus (GEO) database to identify highly preserved modules by weighted gene co-expression network analysis (WGCNA). Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRNAs) were selected and functionally annotated. The predicted interactions between the DEGs and DEmiRNAs were further illustrated.

Results

In two highly preserved modules, 459 DEGs were identified. These DEGs were functionally enriched in the HIF1, Notch, and PI3K/Akt pathways. Furthermore, 6 DEmiRNAs that were enriched in the regulation of vasculature development and HIF1 pathway, were predicted to target 23 DEGs.

Conclusions

Our study presented several promising modulators, both DEGs and DEmiRNAs, as well as possible pathological pathways for AAD, which narrows the scope for further fundamental research.

SUBMITTER: Bi S

PROVIDER: S-EPMC7578500 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Publications

Bioinformatics analysis of key genes and miRNAs associated with Stanford type A aortic dissection.

Bi Siwei S Liu Ruiqi R Shen Yinzhi Y Gu Jun J

Journal of thoracic disease 20200901 9

<h4>Background</h4>Aortic dissection is one of the most detrimental cardiovascular diseases with a high risk of mortality and morbidity. This study aimed to examine the key genes and microRNAs associated with Stanford type A aortic dissection (AAD).<h4>Methods</h4>The expression data of AAD and healthy samples were downloaded from two microarray datasets in the Gene Expression Omnibus (GEO) database to identify highly preserved modules by weighted gene co-expression network analysis (WGCNA). Dif ...[more]

PMID: 33145057

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Project description:BackgroundThe expression levels of long noncoding RNAs (lncRNAs) and mRNAs in human acute Stanford type A aortic dissecting aneurysm and normal active vascular tissues were compared using the array lncRNA/mRNA expression profile chip technology.MethodsThe tissue samples of 5 patients who presented with Stanford type A aortic dissections and the normal ascending aorta tissues from 5 donor heart transplantation patients receiving surgical treatment in Ganzhou People's Hospital were collected. Hematoxylin and eosin (HE) staining were performed to investigate the structural features of the ascending aortic vascular tissue. Nanodropnd-100 was used to detect the surface level of RNA in 10 samples included in the experiment, to ensure that the quality of the standard was consistent with the core plate detection. NanoDrop ND-1000 was used to detect the RNA expression levels in 10 specimens included in the experiment to ensure that the quality of specimens satisfied the requirements of the microarray detection experiment. The Arraystar Human LncRNA/mRNAV3.0 expression profile chip (8×60K, Arraystar) was used to detect the expression levels of lncRNAs and mRNAs in the tissue samples.ResultsA total of 29,198 lncRNAs and 22,959 mRNA target genes could be detected in the above tissue samples after the initial data were standardized and low-expression information was filtered. The data in the middle of the range of 50% value consistency was higher. The scatterplot results preliminarily suggested that there were large numbers of lncRNAs with increased and decreased expression in Stanford type A aortic dissection tissues compared with normal aortic tissues. The differentially expressed lncRNAs were enriched in BPs including apoptosis, nitric oxide synthesis, estradiol response, angiogenesis, inflammatory response, oxidative stress, and acute response; cell components (CCs) including cytoplasm, nucleus, cytoplasmic matrix, extracellular space, protein complex, and platelet α granule lumen; and MFs including protease binding, zinc ion binding, steroid compound binding, steroid hormone receptor activity, heme binding, protein kinase, cytokine, superoxide dismutase, and nitric oxide synthase activities.ConclusionsGene ontology analysis demonstrated that many genes in Stanford type A aortic dissection were involved in cell biological functions, cell components, and molecular functions through upregulating and downregulating the levels of expression.

Project description:Background: Aortic dissection (AD) is a life-threatening cardiovascular disease. Pathophysiologically, it has been shown that aortic wall inflammation promotes the occurrence and development of aortic dissection. Thus, the aim of the current research was to determine the inflammation-related biomarkers in AD. Methods: In this study, we conducted differentially expressed genes (DEGs) analysis using the GSE153434 dataset containing 10 type A aortic dissection (TAAD) and 10 normal samples downloaded from the Gene Expression Omnibus (GEO) database. The intersection of DEGs and inflammation-related genes was identified as differential expressed inflammation-related genes (DEIRGs). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed for DEIRGs. We then constructed the protein-protein interaction (PPI) network using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database and identified hub genes using the Cytoscape plugin MCODE. Finally, least absolute shrinkage and selection operator (LASSO) logistic regression was used to construct a diagnostic model. Results: A total of 1728 DEGs were identified between the TAAD and normal samples. Thereafter, 61 DEIRGs are obtained by taking the intersection of DEGs and inflammation-related genes. The GO indicated that DEIRGs were mainly enriched in response to lipopolysaccharide, in response to molecules of bacterial origin, secretory granule membrane, external side of plasma, receptor ligand activity, and signaling receptor activator activity. KEGG analysis indicated that DEIRGs were mainly enriched in cytokine-cytokine receptor interaction, TNF signaling pathway, and proteoglycans in cancer. We identified MYC, SELL, HIF1A, EDN1, SERPINE1, CCL20, IL1R1, NOD2, TLR2, CD69, PLAUR, MMP14, and HBEGF as hub genes using the MCODE plug-in. The ROC indicated these genes had a good diagnostic performance for TAAD. Conclusion: In conclusion, our study identified 13 hub genes in the TAAD. This study will be of significance for the future development of a preventive therapy of TAAD.

Project description:Background: Stanford type A aortic dissection (AAD) is a catastrophic disease. An immune infiltrate has been found within the aortic wall of dissected aortic specimens. The recall and activation of macrophages are key events in the early phases of AAD. Herein, the immune filtration profile of AAD was uncovered. Methods: Gene expression data from the GSE52093, GSE98770 and GSE153434 datasets were downloaded from the Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) of each dataset were calculated and then integrated. A protein-protein interaction (PPI) network was established with the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and the hub genes were identified in Cytoscape. Furthermore, gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of hub genes were performed. Finally, we set GSE52093 and GSE98770 as the training set and GSE153434 as the validation set to assess immune infiltration in AAD using CIBERSORTx and analyzed the correlations between immune cells and hub genes in both the training and validation sets. Results: Sixty-one integrated DEGs were identified. The top 10 hub genes were selected from the PPI network, and 140 biological process (BP) terms and 12 pathways were enriched among the top 10 hub genes. The proportions of monocytes and macrophages were significantly higher in AAD tissues than in normal tissues. Notably, this result was consistent in the training set and the validation set. In addition, we found that among the hub genes, CA9, CXCL5, GDF15, VEGFA, CCL20, HMOX1, and SPP1 were positively correlated with CD14, a cell marker of monocytes, while CA9, CXCL5, GDF15, and VEGFA were positively correlated with CD68, a cell marker of macrophages in the training set. Finally, according to the results of the GO and KEGG analysis of hub genes, we found that the monocyte/macrophage-related genes were involved in immune-inflammatory responses through degradation of the extracellular matrix, endothelial cell apoptosis, hypoxia and the interaction of cytokines and chemokines. Conclusion: The monocyte-macrophage system plays a major role in immune-inflammatory responses in the development of AAD. Several hub genes are involved in this process via diverse mechanisms.

Project description:ObjectiveAcute aortic dissection is a life-threatening condition. Thoracic endovascular aortic repair (TEVAR), together with optimized medical treatment, is currently the first line treatment for acute Stanford type B aortic dissection. TEVAR can close the entry tear and reduce mortality. Aortic remodeling after TEVAR can directly affect the patient's long-term prognosis. The factors that influence aortic remodeling have, however, received insufficient clinical attention and remain unclear. It is very important to identify these factors.MethodsA total of 100 patients were continuously enrolled from 2011 to 2018 in 2 centers. Relevant data, including time from hospital admission to surgery, medicine use and aortic computed tomography angiography images obtained before and 6 months after surgery were collected. Patients were divided into favorable and adverse aortic remodeling groups, according to the degree of aortic remodeling. Analysis of variance and the chi-square test were performed using SPSS software to compare differences between groups and to determine the factors that influence postoperative aortic remodeling.ResultsThe proportion of single-stent implantations was higher in the favorable remodeling group than in the adverse remodeling group (79.5% vs. 53.8% in distal end of stent-graft level and 81.3% vs. 56.4% in diaphragm level, respectively, p < 0.05). The earlier the TEVAR procedure was performed, the better the aortic remodeling (3.4 days vs. 4.8 days in distal stent graft levels, and 3.6 days vs. 4.9 days in diaphragm level, respectively, p < 0.05), the presence of residual distal entry tears in the abdominal aorta also improved aortic remodeling after TEVAR (85.7% vs. 55.1% in the celiac trunk level, and 92.0% vs. 48.9% in the right renal artery level, respectively, p < 0.05).ConclusionSingle stent-graft implantation and early surgery were associated with favorable aortic remodeling. Distal entry tears were also conducive to aortic remodeling after surgery for aortic dissection.

Project description:BackgroundStanford type A aortic dissection (TAAD) is one of the most life-threatening cardiovascular emergencies with high mortality and morbidity, and necroptosis is a newly identified type of programmed cell death and contributes to the pathogenesis of various cardiovascular diseases. However, the role of necroptosis in TAAD has not been elucidated. This study was aimed at determining the role of necroptosis in TAAD using bioinformatics analyses.MethodsThe RNA sequencing dataset GSE153434 and the microarray dataset GSE52093 were obtained from Gene Expression Omnibus (GEO) database. Differentially expressed genes of necroptosis (NRDEGs) were identified based on differentially expressed genes (DEGs) and necroptosis gene set. Gene set enrichment analysis (GSEA) was applied to evaluate the gene enrichment signaling pathway in TAAD. The STRING database and Cytoscape software were used to establish and visualize protein-protein interaction (PPI) networks and identify the key functional modules of NRDEGs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of NRDEGs were also performed. Additionally, Spearman correlations were used to construct the necroptosis-related transcription factor-target genes regulatory network, immune infiltration patterns were analyzed using the ImmuCellAI algorithm, and the correlation between immune cell-type abundance and NRDEGs expression was investigated. The expression levels of NRDEGs and immune infiltration were additionally verified in the GSE52093 dataset.ResultsWe found that the necroptosis pathway was considerably enriched and activated in TAAD samples. Overall, 25 NRDEGs were identified including MLKL, RIPK1, and FADD, and among them, 18 were verified in the validation set. Moreover, GO and KEGG enrichment analyses found that NRDEGs were primarily involved in the tumor necrosis factor signaling pathway, nucleotide-binding oligomerization domain-like receptor signaling pathway, and interleukin-17 signaling pathway. The imbalance of Th17/Treg cells was identified in the TAAD samples. Furthermore, correlation analysis indicated that expression of NRDEGs was positively associated with proinflammatory immune-cell infiltrations and negatively associated with anti-inflammatory or regulatory immune-cell infiltrations.ConclusionsThe present findings suggest that necroptosis phenomenon exists in TAAD and correlates with immune cell infiltration, which indicate necroptosis may promote the development of TAAD through activating immune infiltration and immune response. This study paves a new road to future investigation of the pathogenic mechanisms and therapeutic strategies for TAAD.

Dataset Information

Bioinformatics analysis of key genes and miRNAs associated with Stanford type A aortic dissection.

Background

Methods

Results

Conclusions

Publications

Bioinformatics analysis of key genes and miRNAs associated with Stanford type A aortic dissection.

Similar Datasets

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