Li Yuanyuan, Cao Ying, Liu Wei, Chen Fangzheng, Zhang Hongdao, Zhou Haisheng, Zhao Aonan, Luo Ningdi, Liu Jun, Wu Ligang
Department of Neurology & Institute of Neurology, Ruijin Hospital affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China.
Key Laboratory of RNA Science and Engineering, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, China.
NPJ Parkinsons Dis. 2024 Jan 10;10(1):18. doi: 10.1038/s41531-023-00628-4.
Parkinson's disease (PD) lacks reliable, non-invasive biomarker tests for early intervention and management. Thus, a minimally invasive test for the early detection and monitoring of PD and REM sleep behavior disorder (iRBD) is a highly unmet need for developing drugs and planning patient care. Extracellular vehicles (EVs) are found in a wide variety of biofluids, including plasma. EV-mediated functional transfer of microRNAs (miRNAs) may be viable candidates as biomarkers for PD and iRBD. Next-generation sequencing (NGS) of EV-derived small RNAs was performed in 60 normal controls, 56 iRBD patients and 53 PD patients to profile small non-coding RNAs (sncRNAs). Moreover, prospective follow-up was performed for these 56 iRBD patients for an average of 3.3 years. Full-scale miRNA profiles of plasma EVs were evaluated by machine-learning methods. After optimizing the library construction method for low RNA inputs (named EVsmall-seq), we built a machine learning algorithm that identified diagnostic miRNA signatures for distinguishing iRBD patients (AUC 0.969) and PD patients (AUC 0.916) from healthy individuals; and PD patients (AUC 0.929) from iRBD patients. We illustrated all the possible expression patterns across healthy-iRBD-PD hierarchy. We also showed 20 examples of miRNAs with consistently increasing or decreasing expression levels from controls to iRBD to PD. In addition, four miRNAs were found to be correlated with iRBD conversion. Distinct characteristics of the miRNA profiles among normal, iRBD and PD samples were discovered, which provides a panel of promising biomarkers for the identification of PD patients and those in the prodromal stage iRBD.
帕金森病（PD）缺乏用于早期干预和管理的可靠、非侵入性生物标志物检测方法。因此，一种用于早期检测和监测PD及快速眼动睡眠行为障碍（iRBD）的微创检测方法，对于药物研发和患者护理规划而言是一种迫切未得到满足的需求。细胞外囊泡（EVs）存在于包括血浆在内的多种生物流体中。EV介导的微小RNA（miRNAs）功能转移可能是作为PD和iRBD生物标志物的可行候选物。对60名正常对照、56名iRBD患者和53名PD患者进行了EV衍生小RNA的下一代测序（NGS），以分析小非编码RNA（sncRNAs）。此外，对这56名iRBD患者进行了平均3.3年的前瞻性随访。通过机器学习方法评估了血浆EVs的全规模miRNA谱。在优化了低RNA输入量的文库构建方法（命名为EVsmall-seq）后，我们构建了一种机器学习算法，该算法可识别用于区分iRBD患者（曲线下面积[AUC]为0.969）和PD患者（AUC为0.916）与健康个体的诊断性miRNA特征；以及区分PD患者（AUC为0.929）与iRBD患者的特征。我们展示了健康-iRBD-PD层级中所有可能的表达模式。我们还展示了20个miRNAs的例子，其表达水平从对照到iRBD再到PD持续增加或减少。此外，发现有4种miRNAs与iRBD转化相关。发现了正常、iRBD和PD样本中miRNA谱的不同特征，这为识别PD患者和处于iRBD前驱期的患者提供了一组有前景的生物标志物。
