2018 - Montreux - Switzerland

PAGE 2018: Drug/Disease modelling - CNS
Oleg Demin

Simulations of tau-targeted therapies using quantitative systems pharmacology model of tau pathology

Tatiana Karelina (1), Alexander Stepanov (1), Oleg Demin (1)

(1) InSysBio, Moscow, Russia

Objectives: Accumulation of pathological forms of tau protein is one of the key hallmarks of neurodegenerative diseases. Unlike amyloid pathology, tau pathology in intracellular and thus it is even more complicated target in the context Alzheimer’s disease treatment, although it probably may be more related to neurodegeneration. Long timescale of the related processes and lower clearance rate (in comparison with, ex. amyloid beta) makes clinical studies especially challenging and does not allow to obtain information from short term PD studies. Therefore, for quantitative analysis and simulations systems pharmacology modelling can be especially valuable tool. For the prediction of the results of tau targeted therapy we propose a mechanistic model describing such tauopathies as Alzheimer’s disease (AD), and frontotemporal degeneration (FTD) in human and tau accumulation in preclinical tauopathy model, mice carrying P301S(L) tau mutation.

Methods: The model describes tau production, tau-microtubules interaction, tau modification, aggregation and propagation through different brain compartments. The compartments of the brain have been constructed specifically to capture Braak stages of Alzheimer’s disease: 1-2 (transentorhinal), 3-4 (limbic) and 5-6 (isocortical). It was shown that the tau pathology propagation is determined by the connectivity, but not proximity [1], thence our model reproduces the key memory retrieval model components for simplification [2] which also correspond approximately to the Braak stages of AD.  Thus, three regions of the brain were considered: EC (entorhinal), HP (hippocampus and limbic system), CT (neocortex). To describe multisite tau protein phosphorylation, we developed the specific approach based on the partial independence of site phosphorylation [3] and taking into account the key kinases (GSK3b, CDK5) and phosphatase PP2A. Tau oligomers serve as the key intermediates for fibril growth and as mediators of tau pathology connectivity-driven propagation from entorhinal cortex through limbic system to neocortex. The driver of longitudinal disease progression in AD model is the decrease of degradation of tau fibrils. For FTD case we use the information about tau mutation influence on polymerization and microtubule binding obtained from the in vitro data. The phosphorylation model parameters were calibrated using in vitro data on tau phosphorylation. The in vivo human model versions were calibrated across published biochemical data for soluble, insoluble tau, CSF tau and PET (18F-AV-1451 SUVR) data [4]. The mouse model was calibrated across biochemical data for soluble (RAB, RIPA soluble fractions), insoluble tau (FA soluble fraction) in several brain structures, interstitial fluid and CSF of mouse.

Results: The model describes reliably consecutive appearance of PET signal in different regions corresponding to Braak stages of AD. Model verification on FTD patient data revealed that tau propagation parameters differ from AD patient. The mouse model version satisfactorily describes reduction of soluble tau and accumulation of insoluble tau in the brain of the mouse P301S(L). Tau pathology propagation and gradual appearance of polymerized tau starting from entorhinal cortex through the limbic system to neocortex is also predicted correctly and follows the experimentally observed trend. Data on immunotherapy by antibodies HJ8.5 in mouse are described satisfactorily only if significant (10 times) increase of insoluble tau degradation is assumed, while blocking the tau propagation only does not allow for description of the mouse data. Analogous degradation activation in humans would lead to complete disappearance of tau in AD patient but would cause moderate effect in FTD patient according to the model.

Conclusions: The proposed QSP model could be considered as a platform for investigation of therapeutic impact on tau pathology and translational analysis. It can be further integrated with amyloid pathology model [5] for better understanding of AD pathology.

[1] Braak H and Braak E, Acta Neuropathol (1991)  82,  239–259.
[2] Ahmed Z et al.  Acta Neuropathol. (2014) 127, 667–683.
[3] Diana RA et al. Trends Cogn. Sci. (2007) 11, 379–386.
[4] Schwarz AJ et al.  Brain (2016) 139, 1539–1550.
[5] Karelina T et al. CPT:PSP (2017) 6, 676-685.

Reference: PAGE 27 (2018) Abstr 8603 [www.page-meeting.org/?abstract=8603]
Poster: Drug/Disease modelling - CNS