Identification of microRNA biomarkers in atrial fibrillation: A protocol for systematic review and bioinformatics analysis

• Published in: Medicine (Baltimore) Vol. 98; no. 30; p. e16538
• Main Authors: Shen, Nan-Nan, Zhang, Zai-Li, Li, Zheng, Zhang, Chi, Li, Hao, Wang, Jia-Liang, Wang, Jun, Gu, Zhi-Chun
• Format: Journal Article
• Language: English
• Published: United States the Author(s). Published by Wolters Kluwer Health, Inc 01.07.2019; Wolters Kluwer Health
• Subjects: Atrial Fibrillation - genetics; Biomarkers - analysis; Computational Biology - methods; Female; Humans; Male; MicroRNAs - analysis; Research Design; Study Protocol Systematic Review; Systematic Reviews as Topic
• ISSN: 0025-7974; 1536-5964; 1536-5964
• DOI: 10.1097/MD.0000000000016538

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. 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. 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. 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. CRD42019127594.