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

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 w...

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Autores principales: Bi, Siwei, Liu, Ruiqi, Shen, Yinzhi, Gu, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7578500/
https://www.ncbi.nlm.nih.gov/pubmed/33145057
http://dx.doi.org/10.21037/jtd-20-1337
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author Bi, Siwei
Liu, Ruiqi
Shen, Yinzhi
Gu, Jun
author_facet Bi, Siwei
Liu, Ruiqi
Shen, Yinzhi
Gu, Jun
author_sort Bi, Siwei
collection PubMed
description 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.
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spelling pubmed-75785002020-11-02 Bioinformatics analysis of key genes and miRNAs associated with Stanford type A aortic dissection Bi, Siwei Liu, Ruiqi Shen, Yinzhi Gu, Jun J Thorac Dis Original Article 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. AME Publishing Company 2020-09 /pmc/articles/PMC7578500/ /pubmed/33145057 http://dx.doi.org/10.21037/jtd-20-1337 Text en 2020 Journal of Thoracic Disease. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Bi, Siwei
Liu, Ruiqi
Shen, Yinzhi
Gu, Jun
Bioinformatics analysis of key genes and miRNAs associated with Stanford type A aortic dissection
title Bioinformatics analysis of key genes and miRNAs associated with Stanford type A aortic dissection
title_full Bioinformatics analysis of key genes and miRNAs associated with Stanford type A aortic dissection
title_fullStr Bioinformatics analysis of key genes and miRNAs associated with Stanford type A aortic dissection
title_full_unstemmed Bioinformatics analysis of key genes and miRNAs associated with Stanford type A aortic dissection
title_short Bioinformatics analysis of key genes and miRNAs associated with Stanford type A aortic dissection
title_sort bioinformatics analysis of key genes and mirnas associated with stanford type a aortic dissection
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7578500/
https://www.ncbi.nlm.nih.gov/pubmed/33145057
http://dx.doi.org/10.21037/jtd-20-1337
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