探索小型非编码RNA作为基于血液的生物标志物,以预测阿尔茨海默病的发生
Laia Gutierrez-Tordera1,2,3, Christopher Papandreou4,5,6, Nil Novau-Ferré1,2,3
1Nutrition and Metabolic Health Research Group, Department of Biochemistry and Biotechnology, Rovira i Virgili University (URV), 43201, Reus, Spain.
Cell & bioscience
|January 16, 2024
概括
在血液中使用小非编码RNA (sncRNA) 的新型阿尔茨海默病 (AD) 签名显示了预测疾病进展的潜力. 这种基于血液的生物标志物可以改善早期检测,并为AD的预防策略提供信息.
科学领域:
- 生物标志物和诊断方法
- 神经科学和神经病学 神经科学和神经病学
- 遗传学和基因组学 在
背景情况:
- 阿尔茨海默病 (AD) 诊断将临床症状和生物标志物整合到粉样神经退行 (ATN) 框架内.
- 血液中的小非编码RNAs (sncRNAs) 正在成为AD的有希望的预测因子.
- 这项研究旨在识别特定于ATN和AD的sncRNA特征,以提高AD转换的预测.
研究的目的:
- 为了识别与粉样神经退行 (ATN) 框架和阿尔茨海默病 (AD) 转换相关的sncRNA签名.
- 为了评估这些sncRNA签名对AD发展的预测性能.
- 评估sncRNA签名对改善超越现有的ATN状态和传统风险因素的AD转化预测的贡献.
主要方法:
- 在ACE队列内的一项嵌套病例对照研究中,使用小RNA测序分析了MCI患者的血sncRNA.
- 有条件的后勤和Cox回归与弹性净处罚确定了ATN和AD的sncRNA签名.
- 计算了权重得分,并使用多变量考克斯回归评估了它们与AD风险的关联;进行了功能丰富分析 (GO,KEGG).
主要成果:
- 一个6-microRNA (miRNA) 签名将MCI患者分类为ATN组,其AUC为0.7335.
- 与AD相关的15-sncRNA签名表现出优异的预测性能 (C统计:0.849) 与传统模型加上ATN状态相比.
- 纳入ATN状态进一步提高了0.875的预测,鉴定出miRNAs与AD相关的神经通路有关.
结论:
- 已识别的与AD相关的sncRNA签名显示了预测AD转换的重大前景.
- 这些发现为AD的早期病原发生提供了有价值的见解.
- 该研究强调了AD预防策略的潜在新目标.
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