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Personalised regional modelling predicts tau progression in the human brain

Chaggar, Pavanjit LU ; Vogel, Jacob LU ; Binette, Alexa Pichet LU ; Thompson, Travis B. ; Strandberg, Olof LU ; Mattsson-Carlgren, Niklas LU orcid ; Karlsson, Linda LU orcid ; Stomrud, Erik LU orcid ; Jbabdi, Saad and Magon, Stefano , et al. (2025) In PLoS Biology 23(7).
Abstract

Aggregation of the hyperphosphorylated tau protein is a central driver of Alzheimer’s disease, and its accumulation exhibits a rich spatiotemporal pattern that unfolds during the course of the disease, sequentially progressing through the brain across axonal connections. It is unclear how this spatiotemporal process is orchestrated, namely, to what extent the spread of pathologic tau is governed by transport between brain regions, local production, or both. To address this, we develop a mechanistic model from tau PET data to describe tau dynamics along the Alzheimer’s disease timeline. Our analysis reveals longitudinal changes in production and transport dynamics in two independent cohorts, with subjects in the early stage of the... (More)

Aggregation of the hyperphosphorylated tau protein is a central driver of Alzheimer’s disease, and its accumulation exhibits a rich spatiotemporal pattern that unfolds during the course of the disease, sequentially progressing through the brain across axonal connections. It is unclear how this spatiotemporal process is orchestrated, namely, to what extent the spread of pathologic tau is governed by transport between brain regions, local production, or both. To address this, we develop a mechanistic model from tau PET data to describe tau dynamics along the Alzheimer’s disease timeline. Our analysis reveals longitudinal changes in production and transport dynamics in two independent cohorts, with subjects in the early stage of the disease exhibiting transport-dominated spread, consistent with an initial spread of pathological tau seeds, and subjects in the late stage disease characterized primarily by local tau production. Further, we demonstrate that the model can predict accurately subject-specific longitudinal tau accumulation at the regional level, potentially providing a new clinical tool to monitor and classify patient disease progression.

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author collaboration
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
PLoS Biology
volume
23
issue
7
article number
e3003241
publisher
Public Library of Science (PLoS)
external identifiers
  • pmid:40690524
  • scopus:105011509450
ISSN
1544-9173
DOI
10.1371/journal.pbio.3003241
language
English
LU publication?
yes
additional info
Publisher Copyright: © 2025 Chaggar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
id
58b94d7b-dccf-4d6a-b347-047b6322f2aa
date added to LUP
2025-12-11 09:58:46
date last changed
2025-12-12 03:22:52
@article{58b94d7b-dccf-4d6a-b347-047b6322f2aa,
  abstract     = {{<p>Aggregation of the hyperphosphorylated tau protein is a central driver of Alzheimer’s disease, and its accumulation exhibits a rich spatiotemporal pattern that unfolds during the course of the disease, sequentially progressing through the brain across axonal connections. It is unclear how this spatiotemporal process is orchestrated, namely, to what extent the spread of pathologic tau is governed by transport between brain regions, local production, or both. To address this, we develop a mechanistic model from tau PET data to describe tau dynamics along the Alzheimer’s disease timeline. Our analysis reveals longitudinal changes in production and transport dynamics in two independent cohorts, with subjects in the early stage of the disease exhibiting transport-dominated spread, consistent with an initial spread of pathological tau seeds, and subjects in the late stage disease characterized primarily by local tau production. Further, we demonstrate that the model can predict accurately subject-specific longitudinal tau accumulation at the regional level, potentially providing a new clinical tool to monitor and classify patient disease progression.</p>}},
  author       = {{Chaggar, Pavanjit and Vogel, Jacob and Binette, Alexa Pichet and Thompson, Travis B. and Strandberg, Olof and Mattsson-Carlgren, Niklas and Karlsson, Linda and Stomrud, Erik and Jbabdi, Saad and Magon, Stefano and Klein, Gregory and Hansson, Oskar and Goriely, Alain}},
  issn         = {{1544-9173}},
  language     = {{eng}},
  number       = {{7}},
  publisher    = {{Public Library of Science (PLoS)}},
  series       = {{PLoS Biology}},
  title        = {{Personalised regional modelling predicts tau progression in the human brain}},
  url          = {{http://dx.doi.org/10.1371/journal.pbio.3003241}},
  doi          = {{10.1371/journal.pbio.3003241}},
  volume       = {{23}},
  year         = {{2025}},
}