Personalised regional modelling predicts tau progression in the human brain

Area of Science:

• Neuroscience
• Biophysics
• Medical Imaging

Background:

• Tau protein aggregation is a key factor in Alzheimer's disease (AD) pathogenesis.
• The spatiotemporal spread of tau pathology across the brain is not fully understood.
• Distinguishing between tau transport and local production is crucial for understanding AD progression.

Purpose of the Study:

• To develop a mechanistic model to analyze tau dynamics in Alzheimer's disease.
• To investigate the contributions of tau transport versus local production to disease progression.
• To assess the model's ability to predict subject-specific tau accumulation.

Main Methods:

• Utilized tau Positron Emission Tomography (PET) data from two independent patient cohorts.
• Developed a mechanistic model to quantify tau production and transport dynamics over time.
• Analyzed longitudinal changes in tau PET imaging data to infer disease mechanisms.

Main Results:

• Early-stage Alzheimer's disease is characterized by transport-dominated tau spread, suggesting initial seeding.
• Late-stage Alzheimer's disease shows a shift towards predominantly local tau production.
• The developed model accurately predicts subject-specific longitudinal tau accumulation at a regional level.

Conclusions:

• Tau spread in Alzheimer's disease evolves from transport-driven to production-driven mechanisms.
• This mechanistic model offers a potential clinical tool for monitoring and classifying Alzheimer's disease progression.
• Understanding these dynamics can inform targeted therapeutic strategies for Alzheimer's disease.