A network aggregation model for the dynamics and treatment of neurodegenerative diseases at the brain scale

TL;DR

This paper introduces a spatially-extended model to simulate the spread of neurodegenerative protein aggregates in the brain, aiding in understanding disease progression and potential therapeutic interventions.

Contribution

It develops a novel network aggregation model that captures the dynamics of protein spreading at the brain scale, integrating mechanisms for growth, transport, and drug effects.

Findings

Model predicts how protein aggregates propagate through brain networks.

Simulation results suggest potential therapeutic targets to slow disease progression.

Provides a framework for testing drug efficacy in silico.

Abstract

Neurodegenerative diseases are associated with the assembly of specific proteins into oligomers and fibrillar aggregates. At the brain scale, these protein assemblies can diffuse through the brain and seed other regions, creating an autocatalytic protein progression. The growth and transport of these assemblies depend on various mechanisms that can be targeted therapeutically. Here, we use spatially-extended nucleation-aggregation-fragmentation models for the dynamics of prion-like neurodegenerative protein-spreading in the brain to study the effect of different drugs on whole-brain Alzheimer's disease progression.