Biophysically realistic network-level transport model of tau progression with exosome-mediated release and uptake processes
The spatiotemporal progression of tau in neurodegenerative diseases like Alzheimers follows the brains structural connectome, yet a gap exists between the macroscopic spread observed over years and the protein kinetics occurring over hours. Current models fail to reconcile this disparity or incorporate the cellular mechanisms driving transmission. Here, we advance the Network Transport Model (NTM) to bridge these scales by integrating active transport along microtubules, continuous toxic tau production, and exosome-mediated release and uptake. This framework constitutes one of the most biologically detailed models of tau spread on a whole brain to date, representing a significant innovation in how multiscale proteinopathies are simulated. Simulations on the mouse connectome demonstrate that this framework replicates empirical tau propagation patterns. Our results identify trans-neuronal release and uptake rates as the primary "bottleneck" on macroscopic spread, providing a biologically grounded explanation for the diseases slow progression. Furthermore, we find that high aggregation sequesters tau within regions, limiting global transmission, while increasing the abundance of toxic polymeric tau fibrils. Meanwhile, tau transport polarity bias (anterograde vs. retrograde) dictates spatial patterning. By linking molecular mechanics to system-wide pathology, this model provides an "in-silico" framework to evaluate how cellular-targeted interventions might alter the trajectory of tauopathic dementias. Author SummaryIn Alzheimers disease and related dementias, a protein called tau forms misfolded aggregates and gradually spreads through the brain along its neuronal wiring. A long-standing puzzle is linking the microscopic protein dynamics taking minutes to hours to the multiyear macroscopic spread of the disease. We developed a new mathematical model that is capable to explain macroscopic spreading behavior of tau as an emerging process from the underlying biophysical mechanics of tau pathology. Our simulations reproduce real patterns of tau spread, and our framework will pave the way for testing how treatments targeting specific cellular mechanisms might reshape disease progression.