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Identification of microRNA biomarkers in atrial fibrillation: A protocol for systematic review and bioinformatics analysis
BACKGROUND: Atrial fibrillation (AF) is recognized as the most prevalent arrhythmia, and its subsequently serious complications of heart failure and thromboembolism always raise the social attention. To date, the molecular pathogenesis of AF has largely remained unclear. Publications of contemporary...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6708903/ https://www.ncbi.nlm.nih.gov/pubmed/31348272 http://dx.doi.org/10.1097/MD.0000000000016538 |
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author | Shen, Nan-Nan Zhang, Zai-Li Li, Zheng Zhang, Chi Li, Hao Wang, Jia-Liang Wang, Jun Gu, Zhi-Chun |
author_facet | Shen, Nan-Nan Zhang, Zai-Li Li, Zheng Zhang, Chi Li, Hao Wang, Jia-Liang Wang, Jun Gu, Zhi-Chun |
author_sort | Shen, Nan-Nan |
collection | PubMed |
description | BACKGROUND: Atrial fibrillation (AF) is recognized as the most prevalent arrhythmia, and its subsequently serious complications of heart failure and thromboembolism always raise the social attention. To date, the molecular pathogenesis of AF has largely remained unclear. Publications of contemporary studies have evaluated individual miRNAs expression signatures for AF, and findings of different studies are inconsistent and not all miRNAs reported are actually important in the pathogenesis of AF. METHODS: Medline, Embase, and Cochrane Library databases will be comprehensively searched (up to April 30, 2019) for studies identifying miRNA expression profiling in subjects with and without AF. Log10 odds ratios (logORs) and associated 95% confidence interval (95%CI) will be calculated using random-effects models. Subgroup analysis will be performed according to miRNA detecting methods, species, sample types, and ethnicities. Sensitivity analysis will be conducted to detect the robustness of the findings. The methodological quality of studies will be independently assessed using criteria adopted from the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). Furthermore, bioinformatics analysis will be performed to identify the potential target genes in AF and the corresponding pathways of dysregulated miRNAs. Two reviewers will independently screen potential studies and extract data in a structured eligibility items, with any disagreements being resolved by consensus. RESULTS: The present systematic review will identify potential biomarkers by pooling all differentially expressed miRNAs in AF studies, as well as to predict miRNA-target interactions and to identify the potential biometric functions using bioinformatics analysis. CONCLUSIONS: This systematic review and bioinformatics analysis will identify several miRNAs as potential biomarkers for AF, and explore the biological pathways regulated by the eligible miRNAs. PROSPERO REGISTRATION NUMBER: CRD42019127594 |
format | Online Article Text |
id | pubmed-6708903 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
spelling | pubmed-67089032019-10-01 Identification of microRNA biomarkers in atrial fibrillation: A protocol for systematic review and bioinformatics analysis Shen, Nan-Nan Zhang, Zai-Li Li, Zheng Zhang, Chi Li, Hao Wang, Jia-Liang Wang, Jun Gu, Zhi-Chun Medicine (Baltimore) Research Article BACKGROUND: Atrial fibrillation (AF) is recognized as the most prevalent arrhythmia, and its subsequently serious complications of heart failure and thromboembolism always raise the social attention. To date, the molecular pathogenesis of AF has largely remained unclear. Publications of contemporary studies have evaluated individual miRNAs expression signatures for AF, and findings of different studies are inconsistent and not all miRNAs reported are actually important in the pathogenesis of AF. METHODS: Medline, Embase, and Cochrane Library databases will be comprehensively searched (up to April 30, 2019) for studies identifying miRNA expression profiling in subjects with and without AF. Log10 odds ratios (logORs) and associated 95% confidence interval (95%CI) will be calculated using random-effects models. Subgroup analysis will be performed according to miRNA detecting methods, species, sample types, and ethnicities. Sensitivity analysis will be conducted to detect the robustness of the findings. The methodological quality of studies will be independently assessed using criteria adopted from the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). Furthermore, bioinformatics analysis will be performed to identify the potential target genes in AF and the corresponding pathways of dysregulated miRNAs. Two reviewers will independently screen potential studies and extract data in a structured eligibility items, with any disagreements being resolved by consensus. RESULTS: The present systematic review will identify potential biomarkers by pooling all differentially expressed miRNAs in AF studies, as well as to predict miRNA-target interactions and to identify the potential biometric functions using bioinformatics analysis. CONCLUSIONS: This systematic review and bioinformatics analysis will identify several miRNAs as potential biomarkers for AF, and explore the biological pathways regulated by the eligible miRNAs. PROSPERO REGISTRATION NUMBER: CRD42019127594 Wolters Kluwer Health 2019-07-26 /pmc/articles/PMC6708903/ /pubmed/31348272 http://dx.doi.org/10.1097/MD.0000000000016538 Text en Copyright © 2019 the Author(s). Published by Wolters Kluwer Health, Inc. http://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 |
spellingShingle | Research Article Shen, Nan-Nan Zhang, Zai-Li Li, Zheng Zhang, Chi Li, Hao Wang, Jia-Liang Wang, Jun Gu, Zhi-Chun Identification of microRNA biomarkers in atrial fibrillation: A protocol for systematic review and bioinformatics analysis |
title | Identification of microRNA biomarkers in atrial fibrillation: A protocol for systematic review and bioinformatics analysis |
title_full | Identification of microRNA biomarkers in atrial fibrillation: A protocol for systematic review and bioinformatics analysis |
title_fullStr | Identification of microRNA biomarkers in atrial fibrillation: A protocol for systematic review and bioinformatics analysis |
title_full_unstemmed | Identification of microRNA biomarkers in atrial fibrillation: A protocol for systematic review and bioinformatics analysis |
title_short | Identification of microRNA biomarkers in atrial fibrillation: A protocol for systematic review and bioinformatics analysis |
title_sort | identification of microrna biomarkers in atrial fibrillation: a protocol for systematic review and bioinformatics analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6708903/ https://www.ncbi.nlm.nih.gov/pubmed/31348272 http://dx.doi.org/10.1097/MD.0000000000016538 |
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