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Network Diffusion Modeling Explains Longitudinal Tau PET Data
Alzheimer's disease is associated with the cerebral accumulation of neurofibrillary tangles of hyperphosphorylated tau protein. The progressive occurrence of tau aggregates in different brain regions is closely related to neurodegeneration and cognitive impairment. However, our current understa...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785976/ https://www.ncbi.nlm.nih.gov/pubmed/33424532 http://dx.doi.org/10.3389/fnins.2020.566876 |
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author | Schäfer, Amelie Mormino, Elizabeth C. Kuhl, Ellen |
author_facet | Schäfer, Amelie Mormino, Elizabeth C. Kuhl, Ellen |
author_sort | Schäfer, Amelie |
collection | PubMed |
description | Alzheimer's disease is associated with the cerebral accumulation of neurofibrillary tangles of hyperphosphorylated tau protein. The progressive occurrence of tau aggregates in different brain regions is closely related to neurodegeneration and cognitive impairment. However, our current understanding of tau propagation relies almost exclusively on postmortem histopathology, and the precise propagation dynamics of misfolded tau in the living brain remain poorly understood. Here we combine longitudinal positron emission tomography and dynamic network modeling to test the hypothesis that misfolded tau propagates preferably along neuronal connections. We follow 46 subjects for three or four annual positron emission tomography scans and compare their pathological tau profiles against brain network models of intracellular and extracellular spreading. For each subject, we identify a personalized set of model parameters that characterizes the individual progression of pathological tau. Across all subjects, the mean protein production rate was 0.21 ± 0.15 and the intracellular diffusion coefficient was 0.34 ± 0.43. Our network diffusion model can serve as a tool to detect non-clinical symptoms at an earlier stage and make informed predictions about the timeline of neurodegeneration on an individual personalized basis. |
format | Online Article Text |
id | pubmed-7785976 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-77859762021-01-07 Network Diffusion Modeling Explains Longitudinal Tau PET Data Schäfer, Amelie Mormino, Elizabeth C. Kuhl, Ellen Front Neurosci Neuroscience Alzheimer's disease is associated with the cerebral accumulation of neurofibrillary tangles of hyperphosphorylated tau protein. The progressive occurrence of tau aggregates in different brain regions is closely related to neurodegeneration and cognitive impairment. However, our current understanding of tau propagation relies almost exclusively on postmortem histopathology, and the precise propagation dynamics of misfolded tau in the living brain remain poorly understood. Here we combine longitudinal positron emission tomography and dynamic network modeling to test the hypothesis that misfolded tau propagates preferably along neuronal connections. We follow 46 subjects for three or four annual positron emission tomography scans and compare their pathological tau profiles against brain network models of intracellular and extracellular spreading. For each subject, we identify a personalized set of model parameters that characterizes the individual progression of pathological tau. Across all subjects, the mean protein production rate was 0.21 ± 0.15 and the intracellular diffusion coefficient was 0.34 ± 0.43. Our network diffusion model can serve as a tool to detect non-clinical symptoms at an earlier stage and make informed predictions about the timeline of neurodegeneration on an individual personalized basis. Frontiers Media S.A. 2020-12-23 /pmc/articles/PMC7785976/ /pubmed/33424532 http://dx.doi.org/10.3389/fnins.2020.566876 Text en Copyright © 2020 Schäfer, Mormino and Kuhl. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Schäfer, Amelie Mormino, Elizabeth C. Kuhl, Ellen Network Diffusion Modeling Explains Longitudinal Tau PET Data |
title | Network Diffusion Modeling Explains Longitudinal Tau PET Data |
title_full | Network Diffusion Modeling Explains Longitudinal Tau PET Data |
title_fullStr | Network Diffusion Modeling Explains Longitudinal Tau PET Data |
title_full_unstemmed | Network Diffusion Modeling Explains Longitudinal Tau PET Data |
title_short | Network Diffusion Modeling Explains Longitudinal Tau PET Data |
title_sort | network diffusion modeling explains longitudinal tau pet data |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785976/ https://www.ncbi.nlm.nih.gov/pubmed/33424532 http://dx.doi.org/10.3389/fnins.2020.566876 |
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