The Integrative Analysis of Competitive Endogenous RNA Regulatory Networks in Coronary Artery Disease

Background: Coronary artery disease (CAD) is the leading cause of cardiovascular death. The competitive endogenous RNAs (ceRNAs) hypothesis is a new theory that explains the relationship between lncRNAs and miRNAs. The mechanism of ceRNAs in the pathological process of CAD has not been fully elucida...

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Main Authors: Yuyao Ji, Tao Yan, Shijie Zhu, Runda Wu, Miao Zhu, Yangyang Zhang, Changfa Guo, Kang Yao
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-09-01
Series:Frontiers in Cardiovascular Medicine
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fcvm.2021.647953/full
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spelling doaj-b4dba5674502467390d762e4c67b276e2021-09-22T04:52:18ZengFrontiers Media S.A.Frontiers in Cardiovascular Medicine2297-055X2021-09-01810.3389/fcvm.2021.647953647953The Integrative Analysis of Competitive Endogenous RNA Regulatory Networks in Coronary Artery DiseaseYuyao Ji0Tao Yan1Shijie Zhu2Runda Wu3Miao Zhu4Yangyang Zhang5Changfa Guo6Kang Yao7Department of Cardiology, Zhongshan Hospital, Shanghai Institute of Cardiovascular Diseases, Fudan University, Shanghai, ChinaDepartment of Cardiovascular Surgery, Zhongshan Hospital, Fudan University, Shanghai, ChinaDepartment of Cardiovascular Surgery, Zhongshan Hospital, Fudan University, Shanghai, ChinaDepartment of Cardiology, Zhongshan Hospital, Shanghai Institute of Cardiovascular Diseases, Fudan University, Shanghai, ChinaDepartment of Cardiovascular Surgery, Zhongshan Hospital, Fudan University, Shanghai, ChinaDepartment of Cardiovascular Surgery, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, ChinaDepartment of Cardiovascular Surgery, Zhongshan Hospital, Fudan University, Shanghai, ChinaDepartment of Cardiology, Zhongshan Hospital, Shanghai Institute of Cardiovascular Diseases, Fudan University, Shanghai, ChinaBackground: Coronary artery disease (CAD) is the leading cause of cardiovascular death. The competitive endogenous RNAs (ceRNAs) hypothesis is a new theory that explains the relationship between lncRNAs and miRNAs. The mechanism of ceRNAs in the pathological process of CAD has not been fully elucidated. The objective of this study was to explore the ceRNA mechanism in CAD using the integrative bioinformatics analysis and provide new research ideas for the occurrence and development of CAD.Methods: The GSE113079 dataset was downloaded, and differentially expressed lncRNAs (DElncRNAs) and genes (DEGs) were identified using the limma package in the R language. Weighted gene correlation network analysis (WGCNA) was performed on DElncRNAs and DEGs to explore lncRNAs and genes associated with CAD. Functional enrichment analysis was performed on hub genes in the significant module identified via WGCNA. Four online databases, including TargetScan, miRDB, miRTarBase, and Starbase, combined with an online tool, miRWalk, were used to construct ceRNA regulatory networks.Results: DEGs were clustered into ten co-expression modules with different colors using WGCNA. The brown module was identified as the key module with the highest correlation coefficient. 188 hub genes were identified in the brown module for functional enrichment analysis. DElncRNAs were clustered into sixteen modules, including seven modules related to CAD with the correlation coefficient more than 0.5. Three ceRNA networks were identified, including OIP5-AS1-miR-204-5p/miR-211-5p-SMOC1, OIP5-AS1-miR-92b-3p-DKK3, and OIP5-AS1-miR-25-3p-TMEM184B.Conclusion: Three ceRNA regulatory networks identified in this study may play crucial roles in the occurrence and development of CAD, which provide novel insights into the ceRNA mechanism in CAD.https://www.frontiersin.org/articles/10.3389/fcvm.2021.647953/fullcoronary artery diseasenon-coding RNAceRNAbioinformaticsWGCNA
collection DOAJ
language English
format Article
sources DOAJ
author Yuyao Ji
Tao Yan
Shijie Zhu
Runda Wu
Miao Zhu
Yangyang Zhang
Changfa Guo
Kang Yao
spellingShingle Yuyao Ji
Tao Yan
Shijie Zhu
Runda Wu
Miao Zhu
Yangyang Zhang
Changfa Guo
Kang Yao
The Integrative Analysis of Competitive Endogenous RNA Regulatory Networks in Coronary Artery Disease
Frontiers in Cardiovascular Medicine
coronary artery disease
non-coding RNA
ceRNA
bioinformatics
WGCNA
author_facet Yuyao Ji
Tao Yan
Shijie Zhu
Runda Wu
Miao Zhu
Yangyang Zhang
Changfa Guo
Kang Yao
author_sort Yuyao Ji
title The Integrative Analysis of Competitive Endogenous RNA Regulatory Networks in Coronary Artery Disease
title_short The Integrative Analysis of Competitive Endogenous RNA Regulatory Networks in Coronary Artery Disease
title_full The Integrative Analysis of Competitive Endogenous RNA Regulatory Networks in Coronary Artery Disease
title_fullStr The Integrative Analysis of Competitive Endogenous RNA Regulatory Networks in Coronary Artery Disease
title_full_unstemmed The Integrative Analysis of Competitive Endogenous RNA Regulatory Networks in Coronary Artery Disease
title_sort integrative analysis of competitive endogenous rna regulatory networks in coronary artery disease
publisher Frontiers Media S.A.
series Frontiers in Cardiovascular Medicine
issn 2297-055X
publishDate 2021-09-01
description Background: Coronary artery disease (CAD) is the leading cause of cardiovascular death. The competitive endogenous RNAs (ceRNAs) hypothesis is a new theory that explains the relationship between lncRNAs and miRNAs. The mechanism of ceRNAs in the pathological process of CAD has not been fully elucidated. The objective of this study was to explore the ceRNA mechanism in CAD using the integrative bioinformatics analysis and provide new research ideas for the occurrence and development of CAD.Methods: The GSE113079 dataset was downloaded, and differentially expressed lncRNAs (DElncRNAs) and genes (DEGs) were identified using the limma package in the R language. Weighted gene correlation network analysis (WGCNA) was performed on DElncRNAs and DEGs to explore lncRNAs and genes associated with CAD. Functional enrichment analysis was performed on hub genes in the significant module identified via WGCNA. Four online databases, including TargetScan, miRDB, miRTarBase, and Starbase, combined with an online tool, miRWalk, were used to construct ceRNA regulatory networks.Results: DEGs were clustered into ten co-expression modules with different colors using WGCNA. The brown module was identified as the key module with the highest correlation coefficient. 188 hub genes were identified in the brown module for functional enrichment analysis. DElncRNAs were clustered into sixteen modules, including seven modules related to CAD with the correlation coefficient more than 0.5. Three ceRNA networks were identified, including OIP5-AS1-miR-204-5p/miR-211-5p-SMOC1, OIP5-AS1-miR-92b-3p-DKK3, and OIP5-AS1-miR-25-3p-TMEM184B.Conclusion: Three ceRNA regulatory networks identified in this study may play crucial roles in the occurrence and development of CAD, which provide novel insights into the ceRNA mechanism in CAD.
topic coronary artery disease
non-coding RNA
ceRNA
bioinformatics
WGCNA
url https://www.frontiersin.org/articles/10.3389/fcvm.2021.647953/full
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