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A bioinformatics analysis of the susceptibility genes in Stanford type A aortic dissection

BACKGROUND: The 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. METHODS: The tissue samples of 5 patients who presen...

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Autores principales: Peng, Xinghua, Li, Zhanghong, Cai, Longren, Li, Haiping, Zhong, Fengwen, Luo, Lie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10183510/
https://www.ncbi.nlm.nih.gov/pubmed/37197519
http://dx.doi.org/10.21037/jtd-23-308
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author Peng, Xinghua
Li, Zhanghong
Cai, Longren
Li, Haiping
Zhong, Fengwen
Luo, Lie
author_facet Peng, Xinghua
Li, Zhanghong
Cai, Longren
Li, Haiping
Zhong, Fengwen
Luo, Lie
author_sort Peng, Xinghua
collection PubMed
description BACKGROUND: The 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. METHODS: The 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. RESULTS: A 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. CONCLUSIONS: Gene 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.
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spelling pubmed-101835102023-05-16 A bioinformatics analysis of the susceptibility genes in Stanford type A aortic dissection Peng, Xinghua Li, Zhanghong Cai, Longren Li, Haiping Zhong, Fengwen Luo, Lie J Thorac Dis Original Article BACKGROUND: The 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. METHODS: The 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. RESULTS: A 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. CONCLUSIONS: Gene 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. AME Publishing Company 2023-04-25 2023-04-28 /pmc/articles/PMC10183510/ /pubmed/37197519 http://dx.doi.org/10.21037/jtd-23-308 Text en 2023 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
Peng, Xinghua
Li, Zhanghong
Cai, Longren
Li, Haiping
Zhong, Fengwen
Luo, Lie
A bioinformatics analysis of the susceptibility genes in Stanford type A aortic dissection
title A bioinformatics analysis of the susceptibility genes in Stanford type A aortic dissection
title_full A bioinformatics analysis of the susceptibility genes in Stanford type A aortic dissection
title_fullStr A bioinformatics analysis of the susceptibility genes in Stanford type A aortic dissection
title_full_unstemmed A bioinformatics analysis of the susceptibility genes in Stanford type A aortic dissection
title_short A bioinformatics analysis of the susceptibility genes in Stanford type A aortic dissection
title_sort bioinformatics analysis of the susceptibility genes in stanford type a aortic dissection
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10183510/
https://www.ncbi.nlm.nih.gov/pubmed/37197519
http://dx.doi.org/10.21037/jtd-23-308
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