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Which tau target to select for drug discovery? Insights from an advanced quantitative systems pharmacology model
Author(s) -
Spiros Athan,
Geerts Hugo
Publication year - 2020
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1002/alz.038609
Subject(s) - neuroscience , tauopathy , in vivo , genetically modified mouse , microtubule , in silico , internalization , neuronal circuits , drug discovery , tau pathology , in vitro , biology , microbiology and biotechnology , computational biology , chemistry , transgene , bioinformatics , pathology , biochemistry , cell , medicine , disease , neurodegeneration , alzheimer's disease , gene , genetics
Background Although tau pathology is a major driver of Alzheimer’s Disease (AD) pathology and remains a very interesting target, the mere complexity of tau biology significantly hampers the identification and validation of the most impactful target. Method We developed a Quantitative Systems Pharmacology (QSP) platform integrating diverse preclinical and clinical knowledge about tau biology processes in an actionable computer model. The computer model includes tau species diversity, activity‐dependent tau secretion, tau binding to HSPG at the synaptic cleft and along the axonal membrane following a diffusion gradient and subsequent internalization, slow axonal transport over microtubules, intracellular degradation and templating of monomeric tau by seed‐competent tau into aggregates and insoluble Neurofibrillary Tangles. Polysynaptic progression is implemented by modeling secretion into the second synapse and subsequent uptake in the second axon. Result The platform was calibrated with preclinical experiments from in‐vitro cellular assays and injected brain extract in transgene mouse models. The model reproduced experimentally determined in vivo monomeric tau progression speeds at 0.25 mm/day; the rate of oligomerization was estimated to not less than 58 nM/year and the presence of each additional synapse reduces the peak of oligomeric tau about tenfold. We modified the platform to reproduce clinical AD pathology, based on stationary levels of seed‐competent tau from experimental measures in post‐mortem brains at diverse Braak stages. Using sensitivity analysis on this in silico platform we rank ordered various possible therapeutic interventions on the accumulation of seed‐competent tau in distal regions such as passive immunization using antibodies with different epitopes on the tau protein, reduced binding to HSPG, reduction of oligomerization, decreased secretion and increased degradation and identified interesting synergistic interactions. Interestingly this order was not the same as for the simulated conditions of injected brain extract in mouse models, possible identifying another problem of translationability. Conclusion Advanced computer modeling allows to ‘humanize’ preclinical experiments and can be an additional tool to support innovative disease modifying tauopathy R&D projects.