帕金森病(PD)是一种复杂的异质性疾病,涉及多种遗传和环境影响。尽管已经确定了广泛的PD危险因素和疾病症状运动阶段的临床标志物,仍然没有可靠的生物标志物可用于PD运动前早期和预测疾病进展.基于高通量RNA的生物标志物谱分析和建模可以提供一种手段来利用来自众多标志物的联合信息内容来获得诊断和预后特征。在PD生物标志物研究领域,目前,没有临床验证的基于RNA的生物标志物模型可用,但是以前的研究报道了多种人体组织和体液中RNA丰度和活性的一些与疾病相关的显著变化。这里,我们回顾了PD中非编码RNA的调控和功能的最新知识,专注于microRNAs,长链非编码RNA,和环状RNA。由于越来越多的证据表明心脏和大脑之间的功能相互作用,我们讨论了在破译参与PD进展的复杂调控网络时研究非编码RNA在器官相互作用中的作用的益处.最后,我们回顾了高通量数据集的协调和管理的重要概念,我们讨论了生物医学系统从高通量表达数据中获取和评估RNA生物标记特征的潜力。
Parkinson\'s disease (PD) is a complex and heterogeneous disorder involving multiple genetic and environmental influences. Although a wide range of PD risk factors and clinical markers for the symptomatic motor stage of the disease have been identified, there are still no reliable biomarkers available for the early pre-motor phase of PD and for predicting disease progression. High-throughput RNA-based biomarker profiling and modeling may provide a means to exploit the joint information content from a multitude of markers to derive diagnostic and prognostic signatures. In the field of PD biomarker research, currently, no clinically validated RNA-based biomarker models are available, but previous studies reported several significantly disease-associated changes in RNA abundances and activities in multiple human tissues and body fluids. Here, we review the current knowledge of the regulation and function of non-coding RNAs in PD, focusing on microRNAs, long non-coding RNAs, and circular RNAs. Since there is growing evidence for functional interactions between the heart and the brain, we discuss the benefits of studying the role of non-coding RNAs in organ interactions when deciphering the complex regulatory networks involved in PD progression. We finally review important concepts of harmonization and curation of high throughput datasets, and we discuss the potential of systems biomedicine to derive and evaluate RNA biomarker signatures from high-throughput expression data.