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Construction and Bioinformatics Analysis of circRNA-miRNA-mRNA Network in Acute Myocardial Infarction

Background: Acute myocardial infarction (AMI) is one of the main fatal diseases of cardiovascular diseases. Circular RNA (circRNA) is a non-coding RNA (ncRNA), which plays a role in cardiovascular disease as a competitive endogenous RNA (ceRNA). However, their role in AMI has not been fully clarifie...

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Autores principales: Zhou, Jin, He, Shaolin, Wang, Boyuan, Yang, Wenling, Zheng, Yuqi, Jiang, Shijiu, Li, Dazhu, Lin, Jibin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9002054/
https://www.ncbi.nlm.nih.gov/pubmed/35422846
http://dx.doi.org/10.3389/fgene.2022.854993
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author Zhou, Jin
He, Shaolin
Wang, Boyuan
Yang, Wenling
Zheng, Yuqi
Jiang, Shijiu
Li, Dazhu
Lin, Jibin
author_facet Zhou, Jin
He, Shaolin
Wang, Boyuan
Yang, Wenling
Zheng, Yuqi
Jiang, Shijiu
Li, Dazhu
Lin, Jibin
author_sort Zhou, Jin
collection PubMed
description Background: Acute myocardial infarction (AMI) is one of the main fatal diseases of cardiovascular diseases. Circular RNA (circRNA) is a non-coding RNA (ncRNA), which plays a role in cardiovascular disease as a competitive endogenous RNA (ceRNA). However, their role in AMI has not been fully clarified. This study aims to explore the mechanism of circRNA-related ceRNA network in AMI, and to identify the corresponding immune infiltration characteristics. Materials and Methods: The circRNA (GSE160717), miRNA (GSE24548), and mRNA (GSE60993) microarray datasets of AMI were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed circRNAs (DEcircRNAs), miRNAs (DEmiRNAs), and mRNAs (DEmRNAs) were identified by the “limma” package. After integrating the circRNA, miRNA and mRNA interaction, we constructed a circRNA-miRNA-mRNA network. The “clusterProfiler” package and String database were used for functional enrichment analysis and protein-protein interaction (PPI) analysis, respectively. After that, we constructed a circRNA-miRNA-hub gene network and validated the circRNAs and mRNAs using an independent dataset (GSE61144) as well as qRT-PCR. Finally, we used CIBERSORTx database to analyze the immune infiltration characteristics of AMI and the correlation between hub genes and immune cells. Results: Using the “limma” package of the R, 83 DEcircRNAs, 54 DEmiRNAs, and 754 DEmRNAs were identified in the microarray datasets of AMI. Among 83 DEcircRNAs, there are 55 exonic DEcircRNAs. Then, a circRNA-miRNA-mRNA network consists of 21 DEcircRNAs, 11 DEmiRNAs, and 106 DEmRNAs were predicted by the database. After that, 10 hub genes from the PPI network were identified. Then, a new circRNA-miRNA-hub gene network consists of 14 DEcircRNAs, 7 DEmiRNAs, and 9 DEmRNAs was constructed. After that, three key circRNAs (hsa_circ_0009018, hsa_circ_0030569 and hsa_circ_0031017) and three hub genes (BCL6, PTGS2 and PTEN) were identified from the network by qRT-PCR. Finally, immune infiltration analysis showed that hub genes were significantly positively correlated with up-regulated immune cells (neutrophils, macrophages and plasma cells) in AMI. Conclusion: Our study constructed a circRNA-related ceRNA networks in AMI, consists of hsa_circ_0031017/hsa-miR-142-5p/PTEN axis, hsa_circ_0030569/hsa-miR-545/PTGS2 axis and hsa_circ_0009018/hsa-miR-139-3p/BCL6 axis. These three hub genes were significantly positively correlated with up-regulated immune cells (neutrophils, macrophages and plasma cells) in AMI. It helps improve understanding of AMI mechanism and provides future potential therapeutic targets.
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spelling pubmed-90020542022-04-13 Construction and Bioinformatics Analysis of circRNA-miRNA-mRNA Network in Acute Myocardial Infarction Zhou, Jin He, Shaolin Wang, Boyuan Yang, Wenling Zheng, Yuqi Jiang, Shijiu Li, Dazhu Lin, Jibin Front Genet Genetics Background: Acute myocardial infarction (AMI) is one of the main fatal diseases of cardiovascular diseases. Circular RNA (circRNA) is a non-coding RNA (ncRNA), which plays a role in cardiovascular disease as a competitive endogenous RNA (ceRNA). However, their role in AMI has not been fully clarified. This study aims to explore the mechanism of circRNA-related ceRNA network in AMI, and to identify the corresponding immune infiltration characteristics. Materials and Methods: The circRNA (GSE160717), miRNA (GSE24548), and mRNA (GSE60993) microarray datasets of AMI were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed circRNAs (DEcircRNAs), miRNAs (DEmiRNAs), and mRNAs (DEmRNAs) were identified by the “limma” package. After integrating the circRNA, miRNA and mRNA interaction, we constructed a circRNA-miRNA-mRNA network. The “clusterProfiler” package and String database were used for functional enrichment analysis and protein-protein interaction (PPI) analysis, respectively. After that, we constructed a circRNA-miRNA-hub gene network and validated the circRNAs and mRNAs using an independent dataset (GSE61144) as well as qRT-PCR. Finally, we used CIBERSORTx database to analyze the immune infiltration characteristics of AMI and the correlation between hub genes and immune cells. Results: Using the “limma” package of the R, 83 DEcircRNAs, 54 DEmiRNAs, and 754 DEmRNAs were identified in the microarray datasets of AMI. Among 83 DEcircRNAs, there are 55 exonic DEcircRNAs. Then, a circRNA-miRNA-mRNA network consists of 21 DEcircRNAs, 11 DEmiRNAs, and 106 DEmRNAs were predicted by the database. After that, 10 hub genes from the PPI network were identified. Then, a new circRNA-miRNA-hub gene network consists of 14 DEcircRNAs, 7 DEmiRNAs, and 9 DEmRNAs was constructed. After that, three key circRNAs (hsa_circ_0009018, hsa_circ_0030569 and hsa_circ_0031017) and three hub genes (BCL6, PTGS2 and PTEN) were identified from the network by qRT-PCR. Finally, immune infiltration analysis showed that hub genes were significantly positively correlated with up-regulated immune cells (neutrophils, macrophages and plasma cells) in AMI. Conclusion: Our study constructed a circRNA-related ceRNA networks in AMI, consists of hsa_circ_0031017/hsa-miR-142-5p/PTEN axis, hsa_circ_0030569/hsa-miR-545/PTGS2 axis and hsa_circ_0009018/hsa-miR-139-3p/BCL6 axis. These three hub genes were significantly positively correlated with up-regulated immune cells (neutrophils, macrophages and plasma cells) in AMI. It helps improve understanding of AMI mechanism and provides future potential therapeutic targets. Frontiers Media S.A. 2022-03-29 /pmc/articles/PMC9002054/ /pubmed/35422846 http://dx.doi.org/10.3389/fgene.2022.854993 Text en Copyright © 2022 Zhou, He, Wang, Yang, Zheng, Jiang, Li and Lin. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Zhou, Jin
He, Shaolin
Wang, Boyuan
Yang, Wenling
Zheng, Yuqi
Jiang, Shijiu
Li, Dazhu
Lin, Jibin
Construction and Bioinformatics Analysis of circRNA-miRNA-mRNA Network in Acute Myocardial Infarction
title Construction and Bioinformatics Analysis of circRNA-miRNA-mRNA Network in Acute Myocardial Infarction
title_full Construction and Bioinformatics Analysis of circRNA-miRNA-mRNA Network in Acute Myocardial Infarction
title_fullStr Construction and Bioinformatics Analysis of circRNA-miRNA-mRNA Network in Acute Myocardial Infarction
title_full_unstemmed Construction and Bioinformatics Analysis of circRNA-miRNA-mRNA Network in Acute Myocardial Infarction
title_short Construction and Bioinformatics Analysis of circRNA-miRNA-mRNA Network in Acute Myocardial Infarction
title_sort construction and bioinformatics analysis of circrna-mirna-mrna network in acute myocardial infarction
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9002054/
https://www.ncbi.nlm.nih.gov/pubmed/35422846
http://dx.doi.org/10.3389/fgene.2022.854993
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