Bifurcations in coupled amyloid-β aggregation-inflammation systems

Area of Science:

• Neuroscience
• Computational Biology
• Pathology

Background:

• Alzheimer's disease (AD) involves complex interactions between amyloid-beta (Aβ) aggregation and neuroinflammation.
• The failure of protective mechanisms linking these processes contributes to AD progression.
• The transition from the prodromal phase to clinical AD remains poorly understood.

Purpose of the Study:

• To model the coupled dynamics of Aβ aggregation and neuroinflammation in AD.
• To analyze the system's behavior and identify parameters influencing disease progression.
• To explore potential mechanisms driving the transition to advanced AD pathology.

Main Methods:

• Developed a minimal mathematical model of coupled Aβ aggregation and inflammation.
• Simulated the model's dynamics and analyzed bifurcation properties.
• Investigated the impact of inflammation on Aβ generation and clearance rates.

Main Results:

• The model exhibits rich dynamics, including sustained oscillations.
• Identified parameter regions where oscillatory dynamics emerge.
• Demonstrated that Aβ aggregation parameters can shift the oscillatory region.
• Prolonged oscillations and immune exhaustion are proposed as a transition mechanism.

Conclusions:

• Coupled Aβ aggregation-inflammation systems show a propensity for oscillatory dynamics.
• Sustained oscillations may underlie immune system exhaustion and AD progression.
• Findings suggest potential targets for early AD diagnosis and therapeutic intervention.