Combined Model of Aggregation and Network Diffusion Recapitulates Alzheimer's Regional Tau-Positron Emission Tomography

Ashish Raj, Veronica Tora, Xiao Gao, Hanna Cho, Jae Yong Choi, Young Hoon Ryu, Chul Hyoung Lyoo, Bruno Franchi

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Alzheimer's disease involves widespread and progressive deposition of misfolded protein tau (τ), first appearing in the entorhinal cortex, coagulating in longer polymers and insoluble fibrils. There is mounting evidence for "prion-like"trans-neuronal transmission, whereby misfolded proteins cascade along neuronal pathways, giving rise to networked spread. However, the cause-effect mechanisms by which various oligomeric τ species are produced, aggregate, and disseminate are unknown. The question of how protein aggregation and subsequent spread lead to stereotyped progression in the Alzheimer brain remains unresolved. Materials and Methods: We address these questions by using mathematically precise parsimonious modeling of these pathophysiological processes, extrapolated to the whole brain. We model three key processes: τ monomer production; aggregation into oligomers and then into tangles; and the spatiotemporal progression of misfolded τ as it ramifies into neural circuits via the brain connectome. We model monomer seeding and production at the entorhinal cortex, aggregation using Smoluchowski equations; and networked spread using our prior Network-Diffusion model. Results: This combined aggregation-network-diffusion model exhibits all hallmarks of τ progression seen in human patients. Unlike previous theoretical studies of protein aggregation, we present here an empirical validation on in vivo imaging and fluid τ measurements from large datasets. The model accurately captures not just the spatial distribution of empirical regional τ and atrophy but also patients' cerebrospinal fluid phosphorylated τ profiles as a function of disease progression. Conclusion: This unified quantitative and testable model has the potential to explain observed phenomena and serve as a test-bed for future hypothesis generation and testing in silico. The presented aggregation-network-diffusion model exhibits all hallmarks of tau progression in human patients; it accurately captures not just the spatial distribution of empirical regional tau and atrophy but also patients' cerebrospinal fluid phosphorylated tau profiles. Thus, it serves to fill a theoretical gap between microscopic biophysical processes and empirical macroscopic measurements of pathological patterns in Alzheimer's disease. This unified quantitative and testable model has the potential to explain observed phenomena and serve as a test-bed for future hypothesis generation and testing in silico.

Original languageEnglish
Pages (from-to)624-638
Number of pages15
JournalBrain Connectivity
Volume11
Issue number8
DOIs
Publication statusPublished - 2021 Oct

Bibliographical note

Funding Information:
A.R. was supported by NIH grant number R01NS092802, RF1AG062196, and R56AG064873. H.C., Y.H.R., J.Y.C., and C.H.L. were supported by Yonsei University College of Medicine Grant number 6-2015-0076 and National Research Foundation of Korea Grant number 2015R1C1A2A01054507. B.F. was supported by the University of Bologna, funds for selected research topics, by MAnET Marie Curie Initial Training Network, and by GNAMPA of INdAM (Istituto Nazionale di Alta Matematica ‘‘F. Severi’’), Italy, and by PRIN of the MIUR, Italy.

Publisher Copyright:
© 2021 Mary Ann Liebert Inc.

All Science Journal Classification (ASJC) codes

  • Neuroscience(all)

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