Combined Model of Aggregation and Network Diffusion Recapitulates Alzheimer's Regional Tau-Positron Emission Tomography.
Combined Model of Aggregation and Network Diffusion Recapitulates Alzheimer's Regional Tau-Positron Emission Tomography.
复制标题
聚集和网络扩散的组合模型概括了阿尔茨海默病的区域 Tau 正电子发射断层扫描。
DOI：
10.1089/brain.2020.0841
复制
发表时间：
2021
影响因子：
3.4
通讯作者：
Franchi,Bruno
中科院分区：
文献类型：
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作者：
Raj,Ashish;Tora,Veronica;Gao,Xiao;Cho,Hanna;Choi,JaeYong;Ryu,YoungHoon;Lyoo,ChulHyoung;Franchi,Bruno
背景：阿尔茨海默病涉及广泛和进行性的错误折叠蛋白tau （τ）沉积，首先出现在内嗅皮层，凝结成更长的聚合物和不溶性原纤维。越来越多的证据表明“类似朊病毒”的跨神经元传播，即错误折叠的蛋白质沿着神经元通路级联，导致网络传播。然而，各种寡聚体τ产生、聚集和传播的因果机制尚不清楚。蛋白质聚集和随后的扩散如何导致阿尔茨海默病大脑的定型进展的问题仍未解决。材料和方法：我们通过使用这些病理生理过程的数学精确简约模型来解决这些问题，并推断到整个大脑。我们模拟了三个关键过程：τ单体生产；聚集成低聚物，然后形成缠结；当错误折叠τ通过大脑连接组延伸到神经回路时，它的时空进展。我们用Smoluchowski方程模拟了内嗅皮层的单体播种和生产，聚合；使用我们之前的网络扩散模型进行网络传播。结果：这种结合的聚集-网络-扩散模型显示了在人类患者中看到的τ进展的所有特征。与以往的蛋白质聚集理论研究不同，我们在这里提出了一项来自大数据集的活体成像和流体τ测量的实证验证。该模型不仅准确地捕获了经验区域τ和萎缩的空间分布，而且还捕获了患者脑脊液磷酸化τ曲线作为疾病进展的函数。结论：这个统一的定量和可测试的模型有可能解释观察到的现象，并作为未来假设生成和测试的测试平台。所提出的聚集-网络-扩散模型显示了人类患者tau进展的所有特征；它不仅准确地捕获了经验区域tau和萎缩的空间分布，而且还捕获了患者脑脊液磷酸化的tau谱。因此，它填补了阿尔茨海默病病理模式的微观生物物理过程和经验宏观测量之间的理论空白。这种统一的定量和可测试的模型有可能解释观察到的现象，并作为未来假设生成和测试的测试平台。
Background:Alzheimer's disease involves widespread and progressive deposition of misfolded protein tau (τ), first appearing in the entorhinal cortex, coagulating in longer polymers and insoluble fibrils. There is mounting evidence for “prion-like” trans-neuronal transmission, whereby misfolded proteins cascade along neuronal pathways, giving rise to networked spread. However, the cause–effect mechanisms by which various oligomericτspecies are produced, aggregate, and disseminate are unknown. The question of how protein aggregation and subsequent spread lead to stereotyped progression in the Alzheimer brain remains unresolved.Materials and Methods:We address these questions by using mathematically precise parsimonious modeling of these pathophysiological processes, extrapolated to the whole brain. We model three key processes:τmonomer production; aggregation into oligomers and then into tangles; and the spatiotemporal progression of misfoldedτas it ramifies into neural circuits via the brain connectome. We model monomer seeding and production at the entorhinal cortex, aggregation using Smoluchowski equations; and networked spread using our prior Network-Diffusion model.Results:This combined aggregation-network-diffusion model exhibits all hallmarks ofτprogression seen in human patients. Unlike previous theoretical studies of protein aggregation, we present here an empirical validation onin vivoimaging and fluidτmeasurements from large datasets. The model accurately captures not just the spatial distribution of empirical regionalτand atrophy but also patients' cerebrospinal fluid phosphorylatedτprofiles as a function of disease progression.Conclusion:This unified quantitative and testable model has the potential to explain observed phenomena and serve as a test-bed for future hypothesis generation and testingin silico.Impact statementThe presented aggregation-network-diffusion model exhibits all hallmarks of tau progression in human patients; it accurately captures not just the spatial distribution of empirical regional tau and atrophy but also patients' cerebrospinal fluid phosphorylated tau profiles. Thus, it serves to fill a theoretical gap between microscopic biophysical processes and empirical macroscopic measurements of pathological patterns in Alzheimer's disease. This unified quantitative and testable model has the potential to explain observed phenomena and serve as a test-bed for future hypothesis generation and testingin silico.