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Identification of key miRNAs and mRNAs related to coronary artery disease by meta-analysis
BACKGROUND: To illustrate the mechanism of miRNA and mRNA in coronary artery diseasen (CAD), differentially expressed microRNAs (DEmiRNAs) and genes (DEGs) were analyzed. METHODS: The mRNA transcription profiles of GSE20680 (including 87 blood samples of CAD and 52 blood samples of control), GSE2068...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8447760/ https://www.ncbi.nlm.nih.gov/pubmed/34530741 http://dx.doi.org/10.1186/s12872-021-02211-2 |
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author | Liu, Long Zhang, Jingze Wu, Mei Xu, Haiming |
author_facet | Liu, Long Zhang, Jingze Wu, Mei Xu, Haiming |
author_sort | Liu, Long |
collection | PubMed |
description | BACKGROUND: To illustrate the mechanism of miRNA and mRNA in coronary artery diseasen (CAD), differentially expressed microRNAs (DEmiRNAs) and genes (DEGs) were analyzed. METHODS: The mRNA transcription profiles of GSE20680 (including 87 blood samples of CAD and 52 blood samples of control), GSE20681 (including 99 blood samples of CAD and 99 blood samples of control) and GSE12288 (including 110 blood samples of CAD and 112 blood samples of control) and the miRNA transcription profiles of GSE59421 (including 33 blood samples of CAD and 37 blood samples of control), GSE49823 (including 12 blood samples of CAD and 12 blood samples of control) and GSE28858 (including 13 blood samples of CAD and 13 blood samples of control) were downloaded from Gene Expression Omnibus (GEO; http://www.ncbi.nlm.nih.gov/geo/). Then, the homogenous expressed mRNAs and miRNAs across the three mRNA transcription profiles and three miRNA transcription profiles were screened using the Fishers exact test in MetaDE. ES package. The weighted gene co-expression network analysis (WGCNA) was used to analyze gene modules. Additionally, the integrated miRNAs–targets regulatory network using the DEmiRNA and their targets was constructed using Cytoscape. RESULTS: A total of 1201 homogenously statistically significant DEGs were identified including 879 up-regulated and 322 down-regulated DEGs, while a total of 47 homogenously statistically significant DEmiRNAs including 37 up-regulated and 10 down-regulated DEmiRNAs in CAD compared with the controls across the three mRNA transcription profiles and the three miRNA transcription profiles. A total of 5067 genes were clustered into 9 modules in the training dataset, among which, 8 modules were validated. In the miRNAs-targets network, there existed 267 interaction relationships among 5 miRNAs (hsa-miR-361-5p, hsa-miR-139-5p, hsa-miR-146b-5p, hsa-miR-502-5p and hsa-miR-501-5p) and 213 targets. CAV1 could be the target of hsa-miR-361-5 while HSF2 was the target of both hsa-miR-361-5p and hsa-miR-146b-5p. CAV1 was significantly enriched in the GO term of regulation of cell proliferation. CONCLUSION: hsa-miR-361-5p, has-miR-146b-5p, CAV1 and HSF2 could play an important role in CAD. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12872-021-02211-2. |
format | Online Article Text |
id | pubmed-8447760 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-84477602021-09-20 Identification of key miRNAs and mRNAs related to coronary artery disease by meta-analysis Liu, Long Zhang, Jingze Wu, Mei Xu, Haiming BMC Cardiovasc Disord Research Article BACKGROUND: To illustrate the mechanism of miRNA and mRNA in coronary artery diseasen (CAD), differentially expressed microRNAs (DEmiRNAs) and genes (DEGs) were analyzed. METHODS: The mRNA transcription profiles of GSE20680 (including 87 blood samples of CAD and 52 blood samples of control), GSE20681 (including 99 blood samples of CAD and 99 blood samples of control) and GSE12288 (including 110 blood samples of CAD and 112 blood samples of control) and the miRNA transcription profiles of GSE59421 (including 33 blood samples of CAD and 37 blood samples of control), GSE49823 (including 12 blood samples of CAD and 12 blood samples of control) and GSE28858 (including 13 blood samples of CAD and 13 blood samples of control) were downloaded from Gene Expression Omnibus (GEO; http://www.ncbi.nlm.nih.gov/geo/). Then, the homogenous expressed mRNAs and miRNAs across the three mRNA transcription profiles and three miRNA transcription profiles were screened using the Fishers exact test in MetaDE. ES package. The weighted gene co-expression network analysis (WGCNA) was used to analyze gene modules. Additionally, the integrated miRNAs–targets regulatory network using the DEmiRNA and their targets was constructed using Cytoscape. RESULTS: A total of 1201 homogenously statistically significant DEGs were identified including 879 up-regulated and 322 down-regulated DEGs, while a total of 47 homogenously statistically significant DEmiRNAs including 37 up-regulated and 10 down-regulated DEmiRNAs in CAD compared with the controls across the three mRNA transcription profiles and the three miRNA transcription profiles. A total of 5067 genes were clustered into 9 modules in the training dataset, among which, 8 modules were validated. In the miRNAs-targets network, there existed 267 interaction relationships among 5 miRNAs (hsa-miR-361-5p, hsa-miR-139-5p, hsa-miR-146b-5p, hsa-miR-502-5p and hsa-miR-501-5p) and 213 targets. CAV1 could be the target of hsa-miR-361-5 while HSF2 was the target of both hsa-miR-361-5p and hsa-miR-146b-5p. CAV1 was significantly enriched in the GO term of regulation of cell proliferation. CONCLUSION: hsa-miR-361-5p, has-miR-146b-5p, CAV1 and HSF2 could play an important role in CAD. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12872-021-02211-2. BioMed Central 2021-09-16 /pmc/articles/PMC8447760/ /pubmed/34530741 http://dx.doi.org/10.1186/s12872-021-02211-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Liu, Long Zhang, Jingze Wu, Mei Xu, Haiming Identification of key miRNAs and mRNAs related to coronary artery disease by meta-analysis |
title | Identification of key miRNAs and mRNAs related to coronary artery disease by meta-analysis |
title_full | Identification of key miRNAs and mRNAs related to coronary artery disease by meta-analysis |
title_fullStr | Identification of key miRNAs and mRNAs related to coronary artery disease by meta-analysis |
title_full_unstemmed | Identification of key miRNAs and mRNAs related to coronary artery disease by meta-analysis |
title_short | Identification of key miRNAs and mRNAs related to coronary artery disease by meta-analysis |
title_sort | identification of key mirnas and mrnas related to coronary artery disease by meta-analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8447760/ https://www.ncbi.nlm.nih.gov/pubmed/34530741 http://dx.doi.org/10.1186/s12872-021-02211-2 |
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