Alladi Ramakrishnan Hall

Bifurcations in Coupled Aggregation-Inflammation System: Implications for Alzheimer's Disease

Kalyan Chakrabarti

Department of Biological Science and Chemistry, Krea University, Sri City

A complex interplay between various processes underlies neuropathology of Alzheimer's disease (AD) and its progressive course. Several lines of evidence point to the coupling between A$\beta$ aggregation and neuroinflammation and its role in maintaining brain homeostasis during the long prodromal phase of AD. Little is, however, known about how this protective mechanism fails, and as a result, an irreversible and progressive transition to clinical AD occurs. Here, we introduce a minimal model of a coupled system of A$\beta$ aggregation and inflammation, numerically simulate its dynamical behavior, and analyze its bifurcation properties. The introduced model represents the following events: generation of A$\beta$ monomers, aggregation of A$\beta$ monomers into oligomers and fibrils, induction of inflammation by A$\beta$ aggregates, and clearance of various A$\beta$ species. Crucially, the A$\beta$ generation and clearance rates are modulated by inflammation level following a Hill-type response function. Despite its relative simplicity, the model exhibits enormously rich dynamics ranging from overdamped kinetics to sustained oscillations. We then specify the region of inflammation- and coupling-related parameters space where a transition to oscillatory dynamics occurs and demonstrate how changes in A$\beta$ aggregation parameters could shift this oscillatory region in parameter space. Our results reveal the propensity of coupled A$\beta$ aggregation-inflammation systems to oscillatory dynamics. We propose prolonged sustained oscillations and their consequent immune system exhaustion as a potential mechanism underlying the transition to a more progressive phase of amyloid pathology in AD. The implications of our results in regard to early diagnosis of AD and anti-AD drug development are discussed.