Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA 94305, USA; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
Department of Genetics, Stanford University, Stanford, CA 94305, USA.
Cell Rep. 2022 Nov 8;41(6):111631. doi: 10.1016/j.celrep.2022.111631.
An emerging view regarding neurodegenerative diseases is that discreet seeding of misfolded proteins leads to widespread pathology. However, the mechanisms by which misfolded proteins seed distinct brain regions and cause differential whole-brain pathology remain elusive. We used whole-brain tissue clearing and high-resolution imaging to longitudinally map pathology in an α-synuclein pre-formed fibril injection model of Parkinson's disease. Cleared brains at different time points of disease progression were quantitatively segmented and registered to a standardized atlas, revealing distinct phases of spreading and decline. We then fit a computational model with parameters that represent α-synuclein pathology spreading, aggregation, decay, and gene expression pattern to this longitudinal dataset. Remarkably, our model can generalize to predicting α-synuclein spreading patterns from several distinct brain regions and can even estimate their origins. This model empowers mechanistic understanding and accurate prediction of disease progression, paving the way for the development and testing of therapeutic interventions.
一种新兴的观点认为，神经退行性疾病是由错误折叠的蛋白质的离散播种导致广泛的病理学。然而，错误折叠的蛋白质如何播种不同的大脑区域并导致不同的全脑病理学仍然难以捉摸。我们使用全脑组织清除和高分辨率成像技术，对帕金森病的α-突触核蛋白预形成纤维注射模型进行了纵向病理学研究。在疾病进展的不同时间点清除的大脑进行了定量分割，并注册到标准化图谱中，揭示了传播和衰退的不同阶段。然后，我们将具有表示α-突触核蛋白病理传播、聚集、衰减和基因表达模式的参数的计算模型拟合到这个纵向数据集。值得注意的是，我们的模型可以推广到从几个不同的大脑区域预测α-突触核蛋白的传播模式，甚至可以估计它们的起源。该模型使我们能够对疾病进展进行机制理解和准确预测，为治疗干预措施的开发和测试铺平了道路。
