Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA.
Montreal Neurological Institute, Brain Imaging Centre, McGill University, Canada.
Neuroimage. 2019 May 15;192:178-194. doi: 10.1016/j.neuroimage.2019.03.001. Epub 2019 Mar 6.
Growing evidence suggests that a "prion-like" mechanism underlies the pathogenesis of many neurodegenerative disorders, including Parkinson's disease (PD). We extend and tailor previously developed quantitative and predictive network diffusion model (NDM) to PD, by specifically modeling the trans-neuronal spread of alpha-synuclein outward from the substantia nigra (SN). The model demonstrated the spatial and temporal patterns of PD from neuropathological and neuroimaging studies and was statistically validated using MRI deformation of 232 Parkinson's patients. After repeated seeding simulations, the SN was found to be the most likely seed region, supporting its unique lynchpin role in Parkinson's pathology spread. Other alternative spread models were also evaluated for comparison, specifically, random spread and distance-based spread; the latter tests for Braak's original caudorostral transmission theory. We showed that the distance-based spread model is not as well supported as the connectivity-based model. Intriguingly, the temporal sequencing of affected regions predicted by the model was in close agreement with Braak stages III-VI, providing what we consider a "computational Braak" staging system. Finally, we investigated whether the regional expression patterns of implicated genes contribute to regional atrophy. Despite robust evidence for genetic factors in PD pathogenesis, NDM outperformed regional genetic expression predictors, suggesting that network processes are far stronger mediators of regional vulnerability than innate or cell-autonomous factors. This is the first finding yet of the ramification of prion-like pathology propagation in Parkinson's, as gleaned from in vivo human imaging data. The NDM is potentially a promising robust and clinically useful tool for diagnosis, prognosis and staging of PD.
越来越多的证据表明，一种“类朊病毒”机制是许多神经退行性疾病（包括帕金森病）发病机制的基础。我们通过专门模拟α-突触核蛋白从黑质（SN）向神经元外的跨神经元传播，扩展和调整了以前开发的定量和预测性网络扩散模型（NDM），以应用于帕金森病。该模型展示了来自神经病理学和神经影像学研究的 PD 的时空模式，并使用 232 名帕金森病患者的 MRI 变形进行了统计学验证。经过多次播种模拟，发现 SN 是最有可能的播种区域，支持其在帕金森病病理传播中的独特关键作用。还评估了其他替代传播模型进行比较，特别是随机传播和基于距离的传播；后者检验了 Braak 的原始头尾传播理论。我们表明，基于距离的传播模型不如基于连接的模型得到很好的支持。有趣的是，模型预测的受影响区域的时间顺序与 Braak 阶段 III-VI 非常吻合，为我们提供了一个“计算 Braak”分期系统。最后，我们研究了受影响基因的区域表达模式是否会导致区域萎缩。尽管有大量证据表明遗传因素在帕金森病发病机制中起作用，但 NDM 优于区域遗传表达预测器，这表明网络过程是导致区域易感性的远强于固有或细胞自主因素。这是首次从体内人类成像数据中发现类朊病毒样病理传播的分支。NDM 可能是一种有前途的、强大的、临床有用的工具，可用于诊断、预后和分期帕金森病。
