Shen Nan-Nan, Zhang Zai-Li, Li Zheng, Zhang Chi, Li Hao, Wang Jia-Liang, Wang Jun, Gu Zhi-Chun
Department of Pharmacy.
Department of Geriatrics, Affiliated Hospital of Shaoxing University, Shao Xing, Zhejiang Province.
Medicine (Baltimore). 2019 Jul;98(30):e16538. 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.
心房颤动（AF）被认为是最常见的心律失常，其随后引发的心力衰竭和血栓栓塞等严重并发症一直备受社会关注。迄今为止，AF的分子发病机制在很大程度上仍不清楚。当代研究的出版物评估了AF患者个体miRNA表达特征，但不同研究的结果并不一致，而且并非所有报道的miRNA在AF发病机制中都真正重要。
将全面检索Medline、Embase和Cochrane图书馆数据库（截至2019年4月30日），以查找识别有或无AF受试者中miRNA表达谱的研究。将使用随机效应模型计算log10比值比（logORs）和相关的95%置信区间（95%CI）。将根据miRNA检测方法、物种、样本类型和种族进行亚组分析。将进行敏感性分析以检测研究结果的稳健性。将使用诊断准确性研究质量评估（QUADAS-2）采用的标准独立评估研究的方法学质量。此外，将进行生物信息学分析，以识别AF中的潜在靶基因以及失调miRNA的相应途径。两名评审员将独立筛选潜在研究，并以结构化的合格项目提取数据，任何分歧将通过协商解决。
本系统评价将通过汇总AF研究中所有差异表达的miRNA来识别潜在生物标志物，并使用生物信息学分析预测miRNA-靶标相互作用并识别潜在的生物计量功能。
本系统评价和生物信息学分析将识别几种miRNA作为AF的潜在生物标志物，并探索合格miRNA调控的生物学途径。
PROSPERO注册号：CRD42019127594。
