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Decoding Parkinson's disease - iPSC-derived models in the OMICs era.
Molecular and Cellular Neuroscience ( IF 3.5 ) Pub Date : 2020-05-18 , DOI: 10.1016/j.mcn.2020.103501
Florian Krach 1 , Marios-Evangelos Bogiongko 1 , Beate Winner 1
Affiliation  

Parkinson's disease (PD) is a neurodegenerative disorder characterized by the loss of dopaminergic neurons in the midbrain. In recent years, researchers have started studying PD using induced pluripotent stem cell (iPSC) models of the disease. Surprisingly, few studies have combined iPSC-technology with the so-called powerful 'omics' approaches. Here, we review the current state of omics applications used in combination with iPSC-derived models to study PD. Our focus is on studies investigating transcriptional changes and publications using proteomic applications. Lastly, we discuss current caveats in the field and identify potential future directions to obtain novel insights into PD pathology.

中文翻译:

解码帕金森氏病-OMIC时代iPSC衍生的模型。

帕金森氏病(PD)是一种神经退行性疾病,其特征是中脑多巴胺能神经元的丢失。近年来,研究人员已开始使用该疾病的诱导性多能干细胞(iPSC)模型研究PD。令人惊讶的是,很少有研究将iPSC技术与所谓的强大“组学”方法相结合。在这里,我们回顾了结合iPSC衍生模型研究PD的组学应用程序的当前状态。我们的重点是利用蛋白质组学应用研究转录变化和出版物的研究。最后,我们讨论了该领域的当前警告,并确定了潜在的未来方向,以获得对PD病理学的新颖见解。
更新日期:2020-05-18
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