Dataset Information

Integrative bioinformatics analysis of miRNA and mRNA expression profiles and identification of associated miRNA-mRNA network in aortic dissection.

ABSTRACT:

Background

Aortic dissection (AD) is one of the most lethal cardiovascular diseases. The aim of this study was to identify core genes and pathways revealing pathogenesis in AD.

Methods

We screened differentially expressed mRNAs and miRNAs using mRNA and miRNA expression profile data of AD from Gene Expression Omnibus. Then functional and pathway enrichment analyses of differential expression genes (DEGs) was performed utilizing the database for annotation, visualization, and integrated discovery (DAVID). Target genes with differential expression miRNAs (DEMIs) were predicted using the miRWalk database, and the intersection between these predictions and DEGs was selected as differentially expressed miRNA-target genes. In addition, a protein-protein interaction (PPI) network and miRNA-mRNA regulatory network were constructed.

Results

In total, 130 DEGs and 47 DEMIs were identified from mRNA and miRNA microarray, respectively, and 45 DEGs were DEMI-target genes. The PPI and miRNA-mRNA network included 79 node genes and 74 node genes, respectively, while 23 hub genes and 2 hub miRNAs were identified. The DEGs, PPI and modules differential expression miRNA-target genes were all mainly enriched in cell cycle, cell proliferation and cell apoptosis signaling pathways.

Conclusion

Taken above, the study reveals some candidate genes and pathways potentially involving molecular mechanisms of AD. These findings provide a new insight for research and treatment of AD.

SUBMITTER: Su Y

PROVIDER: S-EPMC6587623 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Publications

Integrative bioinformatics analysis of miRNA and mRNA expression profiles and identification of associated miRNA-mRNA network in aortic dissection.

Su Yiming Y Li Qiyi Q Zheng Zhiyong Z Wei Xiaomin X Hou Peiyong P

Medicine 20190601 24

<h4>Background</h4>Aortic dissection (AD) is one of the most lethal cardiovascular diseases. The aim of this study was to identify core genes and pathways revealing pathogenesis in AD.<h4>Methods</h4>We screened differentially expressed mRNAs and miRNAs using mRNA and miRNA expression profile data of AD from Gene Expression Omnibus. Then functional and pathway enrichment analyses of differential expression genes (DEGs) was performed utilizing the database for annotation, visualization, and integ ...[more]

PMID: 31192949

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Project description:Background: Osteoarthritis (OA) is a degenerative joint disease that seriously affects the quality of people. Unfortunately, the pathogenesis of OA has not been fully known. Therefore, this study aimed to construct a ceRNA regulatory network related to OA to explore the pathogenesis of OA. Methods: Differentially expressed circRNAs (DEcircRNAs), microRNAs (DEmiRNAs), and mRNAs (DEmRNAs) were obtained from the Gene Expression Omnibus microarray data (GSE175959, GSE105027, and GSE169077). The miRNA response elements and target mRNAs were identified using bioinformatics approaches. Additionally, a circRNA-miRNA-mRNA network was established using Cytoscape version 3.8.0. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of mRNAs in the network were conducted to explore the possible mechanisms underlying OA development. Protein-protein interaction (PPI) analysis was performed to determine the hub genes. Based on the hub genes, a sub network was constructed using Cytoscape 3.8.0 version. Finally, connectivity map (CMap) and drug-gene interaction database (DGIdb) analyses were performed to identify the potential therapeutic targets for OA. Results: Altogether, five DEcircRNAs, 89 DEmiRNAs, and 345 DEmRNAs were identified. Moreover, a circRNA-miRNA-mRNA network was established using three circRNAs, seven miRNAs, and 37 mRNAs. GO and KEGG analyses demonstrated that the mRNAs in the network could be related to the occurrence and development of OA. PPI analysis was performed and six key genes, namely serpin family H member 1 [SERPINH1], collagen type VIII alpha 2 chain [COL8A2], collagen type XV alpha 1 chain [COL15A1], collagen type VI alpha 3 chain [COL6A3], collagen type V alpha 1 chain [COL5A1], and collagen type XI alpha 1 chain [COL11A1], were identified. Furthermore, a circRNA-miRNA-hub gene subnetwork was established in accordance with two circRNAs (hsa_circ_0075320 and hsa_circ_0051428), two miRNAs (hsa-miR-6124 and hsa-miR-1207-5p), and six hub genes (COL11A1, SERPINH1, COL6A3, COL5A1, COL8A2, and COL15A1). Finally, three chemicals (noscapine, diazepam, and TG100-115) based on CMap analysis and two drugs (collagenase Clostridium histolyticum and ocriplasmin) based on DGIdb were discovered as potential treatment options for OA. Conclusion: This study presents novel perspectives on the pathogenesis and treatment of OA based on circRNA-related competitive endogenous RNA regulatory networks.

Dataset Information

Integrative bioinformatics analysis of miRNA and mRNA expression profiles and identification of associated miRNA-mRNA network in aortic dissection.

Background

Methods

Results

Conclusion

Publications

Integrative bioinformatics analysis of miRNA and mRNA expression profiles and identification of associated miRNA-mRNA network in aortic dissection.

Similar Datasets

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