A network-level transport model of tau progression in the Alzheimer's brain

TL;DR

This paper introduces a network transport model for tau protein spread in Alzheimer's disease that incorporates active axonal transport mechanisms, providing a more detailed understanding of disease progression at the regional level.

Contribution

The paper develops a macroscopic network transport model that accounts for active tau transport along axons, extending previous diffusion-based models with microscopic process parameters.

Findings

The model predicts distinct tau spread dynamics based on microscopic parameters.

Simulations on hippocampal subnetworks show varied progression patterns.

The model offers new insights into the directional bias of tau propagation.

Abstract

One of the hallmarks of Alzheimer's disease (AD) is the accumulation and spread of toxic aggregates of tau protein. The progression of AD tau pathology is thought to be highly stereotyped, which is in part due to the fact that tau can spread between regions via the white matter tracts that connect them. Mathematically, this phenomenon has been described using models of "network diffusion", where the rate of spread of tau between brain regions is proportional to its concentration gradient and the amount of white matter between them. Although these models can robustly predict the progression of pathology in a wide variety of neurodegenerative diseases, including AD, an under explored aspect of tau spreading is that it is governed not simply by diffusion but also active transport along axonal microtubules. Spread can therefore take on a directional bias, resulting in distinct patterns of deposition, but current models struggle to capture this phenomenon. Recently, we have developed a mathematical model of the axonal transport of toxic tau proteins that takes into account the effects tau exerts on the molecular motors. Here we describe and implement a macroscopic version of this model, which we call the Network Transport Model (NTM). A key feature of this model is that, while it predicts tau dynamics at a regional level, it is parameterized in terms of only microscopic processes such as aggregation and transport rates; that is, differences in brain-wide tau progression can be explained by its microscopic properties. We provide numerical evidence that, as with the two-neuron model that the NTM extends, there are distinct and rich dynamics with respect to the overall rate of spread and the staging of pathology when we simulated the NTM on the hippocampal subnetwork. The theoretical insights provided by the NTM have broad implications for understanding AD pathophysiology more generally.