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Predictive value of miRNA-126 on in-stent restenosis in patients with coronary heart disease: A protocol for meta-analysis and bioinformatics analysis

BACKGROUND: In-stent restenosis (ISR) is one of the most important complications and impacts the long-term effects after percutaneous coronary intervention (PCI) in patients with coronary heart disease (CHD). Related studies have revealed that microRNA (miRNA) can predict ISR in CHD patients. MiRNA-...

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Autores principales: Qiu, Xianke, Wang, Jun, Shi, Zhongping, Ji, Xiaojun, Huang, Yiwei, Dai, Haiyue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8183766/
https://www.ncbi.nlm.nih.gov/pubmed/34087832
http://dx.doi.org/10.1097/MD.0000000000025887
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author Qiu, Xianke
Wang, Jun
Shi, Zhongping
Ji, Xiaojun
Huang, Yiwei
Dai, Haiyue
author_facet Qiu, Xianke
Wang, Jun
Shi, Zhongping
Ji, Xiaojun
Huang, Yiwei
Dai, Haiyue
author_sort Qiu, Xianke
collection PubMed
description BACKGROUND: In-stent restenosis (ISR) is one of the most important complications and impacts the long-term effects after percutaneous coronary intervention (PCI) in patients with coronary heart disease (CHD). Related studies have revealed that microRNA (miRNA) can predict ISR in CHD patients. MiRNA-126 may be a potential biomarker for the diagnosis of ISR. However, the accuracy of miRNA-126 in the diagnosis of ISR is still controversial. Therefore, this study carried out meta-analysis to further evaluate the accuracy of miRNA-126 in the diagnosis of ISR. At the same time, bioinformatics is used to predict the target genes and miRNA-126 may be involved in regulation, so as to provide theoretical support for the precise treatment of CHD. METHODS: The literatures on the miRNA-126 diagnosis of ISR in CHD patients were collected by searching on computer through China National Knowledge Infrastructure, Wanfang, China Biology Medicine disc, PubMed, EMBASE, Cochrane Library and Web of Science. The retrieval time is set to build the database until April 2021. The meta-analysis of the literatures that meet the quality standards was conducted by Stata 16.0 software. TargetScan database, PicTar database, miRanda database, and miRDB database were used to predict miRNA-126 intersection target genes. Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signal pathway enrichment analysis of miRNA-126 target genes were performed by using DAVID database. STRING database was applied to analyze the protein-protein interaction (PPI) network of miRNA-126 target genes. The “Networkanalyzer” function of Cytoscape3.7.2 software is adopted to analyze the network topology attributes, so as to find out the core genes of PPI network. RESULTS: The results of this meta-analysis will be submitted to a peer-reviewed journal for publication. CONCLUSION: In this study, meta-analysis and bioinformatics analysis were adopted to further evaluate the accuracy of miRNA-126 in the diagnosis of ISR in CHD patients, and to explore the mechanism of the action of miRNA-126 and understand related pathways. ETHICS AND DISSEMINATION: The private information from individuals will not be published. This systematic review also should not damage participants’ rights. Ethical approval is not available. The results may be published in a peer-reviewed journal or disseminated in relevant conferences. OSF REGISTRATION NUMBER: DOI 10.17605/OSF.IO/9FMR5.
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spelling pubmed-81837662021-06-07 Predictive value of miRNA-126 on in-stent restenosis in patients with coronary heart disease: A protocol for meta-analysis and bioinformatics analysis Qiu, Xianke Wang, Jun Shi, Zhongping Ji, Xiaojun Huang, Yiwei Dai, Haiyue Medicine (Baltimore) 3400 BACKGROUND: In-stent restenosis (ISR) is one of the most important complications and impacts the long-term effects after percutaneous coronary intervention (PCI) in patients with coronary heart disease (CHD). Related studies have revealed that microRNA (miRNA) can predict ISR in CHD patients. MiRNA-126 may be a potential biomarker for the diagnosis of ISR. However, the accuracy of miRNA-126 in the diagnosis of ISR is still controversial. Therefore, this study carried out meta-analysis to further evaluate the accuracy of miRNA-126 in the diagnosis of ISR. At the same time, bioinformatics is used to predict the target genes and miRNA-126 may be involved in regulation, so as to provide theoretical support for the precise treatment of CHD. METHODS: The literatures on the miRNA-126 diagnosis of ISR in CHD patients were collected by searching on computer through China National Knowledge Infrastructure, Wanfang, China Biology Medicine disc, PubMed, EMBASE, Cochrane Library and Web of Science. The retrieval time is set to build the database until April 2021. The meta-analysis of the literatures that meet the quality standards was conducted by Stata 16.0 software. TargetScan database, PicTar database, miRanda database, and miRDB database were used to predict miRNA-126 intersection target genes. Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signal pathway enrichment analysis of miRNA-126 target genes were performed by using DAVID database. STRING database was applied to analyze the protein-protein interaction (PPI) network of miRNA-126 target genes. The “Networkanalyzer” function of Cytoscape3.7.2 software is adopted to analyze the network topology attributes, so as to find out the core genes of PPI network. RESULTS: The results of this meta-analysis will be submitted to a peer-reviewed journal for publication. CONCLUSION: In this study, meta-analysis and bioinformatics analysis were adopted to further evaluate the accuracy of miRNA-126 in the diagnosis of ISR in CHD patients, and to explore the mechanism of the action of miRNA-126 and understand related pathways. ETHICS AND DISSEMINATION: The private information from individuals will not be published. This systematic review also should not damage participants’ rights. Ethical approval is not available. The results may be published in a peer-reviewed journal or disseminated in relevant conferences. OSF REGISTRATION NUMBER: DOI 10.17605/OSF.IO/9FMR5. Lippincott Williams & Wilkins 2021-06-04 /pmc/articles/PMC8183766/ /pubmed/34087832 http://dx.doi.org/10.1097/MD.0000000000025887 Text en Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0 (https://creativecommons.org/licenses/by/4.0/)
spellingShingle 3400
Qiu, Xianke
Wang, Jun
Shi, Zhongping
Ji, Xiaojun
Huang, Yiwei
Dai, Haiyue
Predictive value of miRNA-126 on in-stent restenosis in patients with coronary heart disease: A protocol for meta-analysis and bioinformatics analysis
title Predictive value of miRNA-126 on in-stent restenosis in patients with coronary heart disease: A protocol for meta-analysis and bioinformatics analysis
title_full Predictive value of miRNA-126 on in-stent restenosis in patients with coronary heart disease: A protocol for meta-analysis and bioinformatics analysis
title_fullStr Predictive value of miRNA-126 on in-stent restenosis in patients with coronary heart disease: A protocol for meta-analysis and bioinformatics analysis
title_full_unstemmed Predictive value of miRNA-126 on in-stent restenosis in patients with coronary heart disease: A protocol for meta-analysis and bioinformatics analysis
title_short Predictive value of miRNA-126 on in-stent restenosis in patients with coronary heart disease: A protocol for meta-analysis and bioinformatics analysis
title_sort predictive value of mirna-126 on in-stent restenosis in patients with coronary heart disease: a protocol for meta-analysis and bioinformatics analysis
topic 3400
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8183766/
https://www.ncbi.nlm.nih.gov/pubmed/34087832
http://dx.doi.org/10.1097/MD.0000000000025887
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