eNeuro. 2024 Apr 2:ENEURO.0345-23.2023. doi: 10.1523/ENEURO.0345-23.2023. Online ahead of print.

ABSTRACT

The accumulation of amyloid-beta (Αβ) and hyperphosphorylated-tau (hp-tau) are two classical histopathological biomarkers in Alzheimer’s disease (AD). However, their detailed interactions with the electro physiological changes at the meso- and macroscale are not yet fully understood. We developed a mechanistic multiscale 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 brain network model of Jansen-Rit neural masses derived from human neuroimaging data whose parameters varied due to neurotoxicity. Results showed that changes in inhibition guided the electrophysiological alterations found in AD, and these changes were mainly attributed to Αβ effects. Additionally, we found a causal disconnection between cellular hyperactivity and interregional hypersynchrony contrary to previous beliefs. Finally, we demonstrated that early Αβ and hp-tau depositions’ location determine the spatiotemporal profile of the proteinopathy. The presented model combines the molecular effects of both Αβ and hp-tau together with a mechanistic protein propagation model and network effects within a 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 Statement This research presents a closed-loop model of AD mechanisms, bridging the gap between protein distribution and neural activity. Contrary to prior beliefs, the study reveals that interregional hypersynchrony 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 of Aβ as 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.

PMID:38565295 | DOI:10.1523/ENEURO.0345-23.2023