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bioRxiv · 10.1101/2021.09.20.461165

Predicting brain atrophy from tau pathology: A summary of clinical findings and their translation into personalized models

Schäfer, A.·Chaggar, P.·Thompson, T. B.·Goriely, A.·Kuhl, E.
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Abstract

For more than 25 years, the amyloid hypothesis-the paradigm that amyloid is the primary cause of Alzheimers disease-has dominated the Alzheimers community. Now, increasing evidence suggests that tissue atrophy and cognitive decline in Alzheimers disease are more closely linked to the amount and location of misfolded tau protein than to amyloid plaques. However, the precise correlation between tau pathology and tissue atrophy remains unknown. Here we integrate multiphysics modeling and Bayesian inference to create personalized tau-atrophy models using longitudinal clinical images from the the Alzheimers Disease Neuroimaging Initiative. For each subject, we infer three personalized parameters, the tau misfolding rate, the tau transport coefficient, and the tau-induced atrophy rate from four consecutive annual tau positron emission tomography scans and structural magnetic resonance images. Strikingly, the tau-induced atrophy coefficient of 0.13/year (95% CI: 0.097-0.189) was fairly consistent across all subjects suggesting a strong correlation between tau pathology and tissue atrophy. Our personalized whole brain atrophy rates of 0.68-1.68%/year (95% CI: 0.5-2.0) are elevated compared to healthy subjects and agree well with the atrophy rates of 1-3%/year reported for Alzheimers patients in the literature. Once comprehensively calibrated with a larger set of longitudinal images, our model has the potential to serve as a diagnostic and predictive tool to estimate future atrophy progression from clinical tau images on a personalized basis.

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Schäfer, A., Chaggar, P., Thompson, T. B., Goriely, A., Kuhl, E.. 2021-09-23. Predicting brain atrophy from tau pathology: A summary of clinical findings and their translation into personalized models. https://doi.org/10.1101/2021.09.20.461165

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