循环长非编码 RNA 作为阿尔茨海默病 (AD) 的新型诊断生物标志物：系统评价和荟萃分析。
Circulating long non-coding RNAs as novel diagnostic biomarkers for Alzheimer's disease (AD): A systematic review and meta-analysis.
机构信息
Children's Medical Center Hospital, School of Medicine, Tehran University of Medical Sciences (TUMS), Tehran, Iran.
Network of Immunity in Infection, Malignancy and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), Tehran, Iran.
出版信息
PLoS One. 2023 Mar 22;18(3):e0281784. doi: 10.1371/journal.pone.0281784. eCollection 2023.
BACKGROUND
Long non-coding RNAs (lncRNAs) have been reported to be involved in the pathogenesis of neurodegenerative diseases. It has also been hypothesized that plasma exosomal lncRNAs may be used as Alzheimer's disease (AD) biomarkers. In this systematic review, we compiled all studies on the subject to evaluate the accuracy of lncRNAs in identifying AD cases through meta-analysis.
METHODS
A PRISMA-compliant systematic search was conducted in PubMed/MEDLINE, EMBASE, and Web of Science databases for English publications till September 2022. We included all observational studies published which investigated the sensitivity and specificity of various lncRNAs in plasma samples of AD diagnosis. Our search strategy included lncRNA and all the related spelling and abbreviation variations combined with the keyword Alzheimer's disease. Methodological quality was assessed using the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines and the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-II) tool. The meta-analysis was carried out using the area under the Receiver Operator Characteristic (ROC) curves (AUC) and sensitivity and specificity values to assess the accuracy of the identified lncRNAs in AD diagnosis. To account for the predicted heterogeneity of the study, a random-effects model was used. All the statistical analyses and visualizations were conducted using Stata 17.0 software.
RESULTS
A total of seven studies (AD patients = 553, healthy controls = 513) were included in the meta-analysis. Three lncRNAs were upregulated (RNA BACE-AS1, RNA NEAT1, RNA GAS5), and one lncRNA (MALAT1) was downregulated in plasma samples of AD patients. RNA 51A and RNA BC200 were reported to have variable expression patterns. A lncRNA (RNA 17A) was not significantly different between AD and control groups. The pooled sensitivity, specificity, and AUC values of lncRNAs in identifying AD were (0.74; 95% CI [0.63, 0.82], I2 = 79.2%), (0.88; 95% CI [0.75, 0.94], I2 = 88.9%), and 0.86; 95% CI [0.82, 0.88], respectively. In addition, the pooled diagnostic odds ratio (DOR) of the five individual lncRNAs in AD diagnosis was 20.
CONCLUSION
lncRNAs had high accuracy in identifying AD and must be seen as a promising diagnostic biomarker of the disease.
背景
长链非编码 RNA（lncRNA）已被报道参与神经退行性疾病的发病机制。人们还假设，血浆外泌体 lncRNA 可作为阿尔茨海默病（AD）的生物标志物。在这项系统评价中，我们汇集了所有关于该主题的研究，通过荟萃分析评估 lncRNA 识别 AD 病例的准确性。
方法
我们在 PubMed/MEDLINE、EMBASE 和 Web of Science 数据库中进行了符合 PRISMA 标准的系统搜索，以查找截至 2022 年 9 月发表的所有关于研究各种 lncRNA 在 AD 诊断中血浆样本中的敏感性和特异性的观察性研究。我们的搜索策略包括 lncRNA 及其所有相关拼写和缩写变体，以及与“阿尔茨海默病”相关的关键词。使用观察性研究的报告质量强化标准（STROBE）指南和诊断准确性研究的质量评估（QUADAS-II）工具评估方法学质量。使用接收者操作特征（ROC）曲线下面积（AUC）和敏感性和特异性值进行荟萃分析，以评估识别 AD 诊断中 lncRNA 的准确性。为了考虑研究的预测异质性，使用了随机效应模型。所有统计分析和可视化均使用 Stata 17.0 软件进行。
结果
共有 7 项研究（AD 患者=553，健康对照组=513）纳入荟萃分析。在 AD 患者的血浆样本中，有 3 个 lncRNA（RNA BACE-AS1、RNA NEAT1、RNA GAS5）上调，1 个 lncRNA（MALAT1）下调。RNA 51A 和 RNA BC200 的表达模式报告存在差异。RNA 17A 在 AD 组和对照组之间无显著差异。lncRNA 识别 AD 的汇总敏感性、特异性和 AUC 值分别为（0.74；95%CI [0.63, 0.82]，I2=79.2%）、（0.88；95%CI [0.75, 0.94]，I2=88.9%）和 0.86；95%CI [0.82, 0.88]。此外，5 个单独 lncRNA 在 AD 诊断中的汇总诊断优势比（DOR）为 20。
结论
lncRNA 对 AD 的识别具有很高的准确性，必须被视为该疾病有前途的诊断生物标志物。
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