A multiscale closed-loop neurotoxicity model of Alzheimer’s disease progression explains functional connectivity alterations

Abstract

AbstractWhile the accumulation of amyloid-beta (Aβ) and hyperphosphorylated-tau (hp-tau) as two classical histopathological biomarkers are crucial in Alzheimer’s disease (AD), their detailed interaction with the electrophysiological changes at the meso- and macroscale are not yet fully understood. We developed a mechanistic mequltiscale model of AD progression, linking proteinopathy to its effects on neural activity and vice-versa. We integrated a heterodimer model of prion-like protein propagation, and a network of Jansen-Rit electrical oscillators whose model parameters varied due to neurotoxicity. Changes in inhibition guided the electrophysiological alterations found in AD, and bothAβand hp-tau-related inhibition changes were able to produce similar effects independently. Additionally, we found a causal disconnection between cellular hyperactivity and interregional hypersynchrony. Finally, we demonstrated that earlyAβand hp-tau depositions’ location determine the spatiotemporal profile of the proteinopathy. The presented model combines the molecular effects of bothAβand hp-tau together with a mechanistic protein propagation model and network effects within a unique closed-loop model. This holds the potential to enlighten the interplay between AD mechanisms on various scales, aiming to develop and test novel hypotheses on the contribution of different AD-related variables to the disease evolution.Significance StatementThis research presents a groundbreaking closed-loop model of AD mechanisms, bridging the gap between protein distribution and neural activity. Contrary to prior assumptions, the study reveals that interregional hyper-synchrony and cellular hyperactivity are not directly linked. Notably, the model identifies neural inhibition as a potential causal factor in neurophysiological AD alterations and posits early depositions ofAβas a determinant of the spatiotemporal profile of proteinopathy. The significance of this mechanistic disease framework lies in its potential to produce insights into AD evolution and to guide novel treatment strategies. It underscores the importance of further experiments and modelling efforts to refine our understanding of AD, offering hope for more effective treatments and personalized care in the fight against dementia.