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Patient-centered connectivity-based prediction of tau pathology spread in Alzheimer’s disease
In Alzheimer’s disease (AD), the Braak staging scheme suggests a stereotypical tau spreading pattern that does, however, not capture interindividual variability in tau deposition. This complicates the prediction of tau spreading, which may become critical for defining individualized tau-PET readouts...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7695466/ https://www.ncbi.nlm.nih.gov/pubmed/33246962 http://dx.doi.org/10.1126/sciadv.abd1327 |
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author | Franzmeier, Nicolai Dewenter, Anna Frontzkowski, Lukas Dichgans, Martin Rubinski, Anna Neitzel, Julia Smith, Ruben Strandberg, Olof Ossenkoppele, Rik Buerger, Katharina Duering, Marco Hansson, Oskar Ewers, Michael |
author_facet | Franzmeier, Nicolai Dewenter, Anna Frontzkowski, Lukas Dichgans, Martin Rubinski, Anna Neitzel, Julia Smith, Ruben Strandberg, Olof Ossenkoppele, Rik Buerger, Katharina Duering, Marco Hansson, Oskar Ewers, Michael |
author_sort | Franzmeier, Nicolai |
collection | PubMed |
description | In Alzheimer’s disease (AD), the Braak staging scheme suggests a stereotypical tau spreading pattern that does, however, not capture interindividual variability in tau deposition. This complicates the prediction of tau spreading, which may become critical for defining individualized tau-PET readouts in clinical trials. Since tau is assumed to spread throughout connected regions, we used functional connectivity to improve tau spreading predictions over Braak staging methods. We included two samples with longitudinal tau-PET from controls and AD patients. Cross-sectionally, we found connectivity of tau epicenters (i.e., regions with earliest tau) to predict estimated tau spreading sequences. Longitudinally, we found tau accumulation rates to correlate with connectivity strength to patient-specific tau epicenters. A connectivity-based, patient-centered tau spreading model improved the assessment of tau accumulation rates compared to Braak stage–specific readouts and reduced sample sizes by ~40% in simulated tau-targeting interventions. Thus, connectivity-based tau spreading models may show utility in clinical trials. |
format | Online Article Text |
id | pubmed-7695466 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-76954662020-12-04 Patient-centered connectivity-based prediction of tau pathology spread in Alzheimer’s disease Franzmeier, Nicolai Dewenter, Anna Frontzkowski, Lukas Dichgans, Martin Rubinski, Anna Neitzel, Julia Smith, Ruben Strandberg, Olof Ossenkoppele, Rik Buerger, Katharina Duering, Marco Hansson, Oskar Ewers, Michael Sci Adv Research Articles In Alzheimer’s disease (AD), the Braak staging scheme suggests a stereotypical tau spreading pattern that does, however, not capture interindividual variability in tau deposition. This complicates the prediction of tau spreading, which may become critical for defining individualized tau-PET readouts in clinical trials. Since tau is assumed to spread throughout connected regions, we used functional connectivity to improve tau spreading predictions over Braak staging methods. We included two samples with longitudinal tau-PET from controls and AD patients. Cross-sectionally, we found connectivity of tau epicenters (i.e., regions with earliest tau) to predict estimated tau spreading sequences. Longitudinally, we found tau accumulation rates to correlate with connectivity strength to patient-specific tau epicenters. A connectivity-based, patient-centered tau spreading model improved the assessment of tau accumulation rates compared to Braak stage–specific readouts and reduced sample sizes by ~40% in simulated tau-targeting interventions. Thus, connectivity-based tau spreading models may show utility in clinical trials. American Association for the Advancement of Science 2020-11-27 /pmc/articles/PMC7695466/ /pubmed/33246962 http://dx.doi.org/10.1126/sciadv.abd1327 Text en Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/ https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (https://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited. |
spellingShingle | Research Articles Franzmeier, Nicolai Dewenter, Anna Frontzkowski, Lukas Dichgans, Martin Rubinski, Anna Neitzel, Julia Smith, Ruben Strandberg, Olof Ossenkoppele, Rik Buerger, Katharina Duering, Marco Hansson, Oskar Ewers, Michael Patient-centered connectivity-based prediction of tau pathology spread in Alzheimer’s disease |
title | Patient-centered connectivity-based prediction of tau pathology spread in Alzheimer’s disease |
title_full | Patient-centered connectivity-based prediction of tau pathology spread in Alzheimer’s disease |
title_fullStr | Patient-centered connectivity-based prediction of tau pathology spread in Alzheimer’s disease |
title_full_unstemmed | Patient-centered connectivity-based prediction of tau pathology spread in Alzheimer’s disease |
title_short | Patient-centered connectivity-based prediction of tau pathology spread in Alzheimer’s disease |
title_sort | patient-centered connectivity-based prediction of tau pathology spread in alzheimer’s disease |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7695466/ https://www.ncbi.nlm.nih.gov/pubmed/33246962 http://dx.doi.org/10.1126/sciadv.abd1327 |
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