Non-Coding RNAs in the Brain-Heart Axis: The Case of Parkinson's Disease.
Non-Coding RNAs in the Brain-Heart Axis: The Case of Parkinson's Disease.
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DOI：
10.3390/ijms21186513
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发表时间：
2020-09-06
影响因子：
5.6
通讯作者：
Devaux Y
中科院分区：
文献类型：
--
作者：
Acharya S;Salgado-Somoza A;Stefanizzi FM;Lumley AI;Zhang L;Glaab E;May P;Devaux Y
帕金森病（Parkinson's disease，PD）是一种复杂的异质性疾病，涉及多种遗传和环境因素。虽然已经确定了广泛的PD风险因素和疾病症状性运动阶段的临床标志物，但仍然没有可靠的生物标志物可用于PD的早期运动前期和预测疾病进展。基于RNA的高通量生物标志物分析和建模可以提供一种利用来自多个标志物的联合信息内容以获得诊断和预后特征的手段。在PD生物标志物研究领域，目前还没有经过临床验证的基于RNA的生物标志物模型，但先前的研究报告了多种人体组织和体液中RNA丰度和活性的几种显著疾病相关变化。在这里，我们回顾了非编码RNA在PD中的调节和功能的现有知识，重点是microRNA，长非编码RNA和环状RNA。由于越来越多的证据表明心脏和大脑之间存在功能性相互作用，因此我们讨论了在解读PD进展中涉及的复杂调控网络时，研究非编码RNA在器官相互作用中的作用的好处。最后，我们回顾了高通量数据集的协调和管理的重要概念，并讨论了系统生物医学从高通量表达数据中获得和评估RNA生物标志物签名的潜力。
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.
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影响因子：
2.6
作者：
Wang G;Cui HL;Liu J;Xiao Q;Wang Y;Ma JF;Zhou HY;Pan J;Tan YY;Chen SD;Chinese Movement Disorders Society
通讯作者：
Chinese Movement Disorders Society
影响因子：
3
作者：
Catlett NL;Bargnesi AJ;Ungerer S;Seagaran T;Ladd W;Elliston KO;Pratt D
通讯作者：
Pratt D
帕金森病患者血清microRNA 29家族的下调
影响因子：
4.6
作者：
Bai X;Tang Y;Yu M;Wu L;Liu F;Ni J;Wang Z;Wang J;Fei J;Wang W;Huang F;Wang J
通讯作者：
Wang J
影响因子：
5.3
作者：
Baghi, Masoud;Delavar, Mahsa Rostamian;Ghaedi, Kamran
通讯作者：
Ghaedi, Kamran
影响因子：
5.1
作者：
Bauer, M.;Kinkl, N.;Ueffing, M.
通讯作者：
Ueffing, M.