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Predictive Model of Spread of Progressive Supranuclear Palsy Using Directional Network Diffusion

Several neurodegenerative disorders including Alzheimer’s disease (AD), frontotemporal dementia (FTD), Parkinson’s disease (PD), amyotrophic lateral sclerosis, and Huntington’s disease report aggregation and transmission of pathogenic proteins between cells. The topography of these diseases in the h...

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Autores principales: Pandya, Sneha, Mezias, Chris, Raj, Ashish
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5742613/
https://www.ncbi.nlm.nih.gov/pubmed/29312121
http://dx.doi.org/10.3389/fneur.2017.00692
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author Pandya, Sneha
Mezias, Chris
Raj, Ashish
author_facet Pandya, Sneha
Mezias, Chris
Raj, Ashish
author_sort Pandya, Sneha
collection PubMed
description Several neurodegenerative disorders including Alzheimer’s disease (AD), frontotemporal dementia (FTD), Parkinson’s disease (PD), amyotrophic lateral sclerosis, and Huntington’s disease report aggregation and transmission of pathogenic proteins between cells. The topography of these diseases in the human brain also, therefore, displays a well-characterized and stereotyped regional pattern, and a stereotyped progression over time. This is most commonly true for AD and other dementias characterized by hallmark misfolded tau or alpha-synuclein pathology. Both tau and synuclein appear to propagate within brain circuits using a shared mechanism. The most canonical synucleopathy is PD; however, much less studied is a rare disorder called progressive supranuclear palsy (PSP). The hallmark pathology and atrophy in PSP are, therefore, also highly stereotyped: initially appearing in the striatum, followed by its neighbors and connected cortical areas. In this study, we explore two mechanistic aspects hitherto unknown about the canonical network diffusion model (NDM) of spread: (a) whether the NDM can apply to other common degenerative pathologies, specifically PSP, and (b) whether the directionality of spread is important in explaining empirical data. Our results on PSP reveal two important findings: first, that PSP is amenable to the connectome-based ND modeling in the same way as previously applied to AD and FTD and, second, that the NDM fit with empirical data are significantly enhanced by using the directional rather than the non-directional form of the human connectome. Specifically, we show that both the anterograde model of transmission (some to axonal terminal) and retrograde mode explain PSP topography more accurately than non-directional transmission. Collectively, these data show that the intrinsic architecture of the structural network mediates disease spread in PSP, most likely via a process of trans-neuronal transmission. These intriguing results have several ramifications for future studies.
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spelling pubmed-57426132018-01-08 Predictive Model of Spread of Progressive Supranuclear Palsy Using Directional Network Diffusion Pandya, Sneha Mezias, Chris Raj, Ashish Front Neurol Neuroscience Several neurodegenerative disorders including Alzheimer’s disease (AD), frontotemporal dementia (FTD), Parkinson’s disease (PD), amyotrophic lateral sclerosis, and Huntington’s disease report aggregation and transmission of pathogenic proteins between cells. The topography of these diseases in the human brain also, therefore, displays a well-characterized and stereotyped regional pattern, and a stereotyped progression over time. This is most commonly true for AD and other dementias characterized by hallmark misfolded tau or alpha-synuclein pathology. Both tau and synuclein appear to propagate within brain circuits using a shared mechanism. The most canonical synucleopathy is PD; however, much less studied is a rare disorder called progressive supranuclear palsy (PSP). The hallmark pathology and atrophy in PSP are, therefore, also highly stereotyped: initially appearing in the striatum, followed by its neighbors and connected cortical areas. In this study, we explore two mechanistic aspects hitherto unknown about the canonical network diffusion model (NDM) of spread: (a) whether the NDM can apply to other common degenerative pathologies, specifically PSP, and (b) whether the directionality of spread is important in explaining empirical data. Our results on PSP reveal two important findings: first, that PSP is amenable to the connectome-based ND modeling in the same way as previously applied to AD and FTD and, second, that the NDM fit with empirical data are significantly enhanced by using the directional rather than the non-directional form of the human connectome. Specifically, we show that both the anterograde model of transmission (some to axonal terminal) and retrograde mode explain PSP topography more accurately than non-directional transmission. Collectively, these data show that the intrinsic architecture of the structural network mediates disease spread in PSP, most likely via a process of trans-neuronal transmission. These intriguing results have several ramifications for future studies. Frontiers Media S.A. 2017-12-21 /pmc/articles/PMC5742613/ /pubmed/29312121 http://dx.doi.org/10.3389/fneur.2017.00692 Text en Copyright © 2017 Pandya, Mezias and Raj. 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) or licensor 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
Pandya, Sneha
Mezias, Chris
Raj, Ashish
Predictive Model of Spread of Progressive Supranuclear Palsy Using Directional Network Diffusion
title Predictive Model of Spread of Progressive Supranuclear Palsy Using Directional Network Diffusion
title_full Predictive Model of Spread of Progressive Supranuclear Palsy Using Directional Network Diffusion
title_fullStr Predictive Model of Spread of Progressive Supranuclear Palsy Using Directional Network Diffusion
title_full_unstemmed Predictive Model of Spread of Progressive Supranuclear Palsy Using Directional Network Diffusion
title_short Predictive Model of Spread of Progressive Supranuclear Palsy Using Directional Network Diffusion
title_sort predictive model of spread of progressive supranuclear palsy using directional network diffusion
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5742613/
https://www.ncbi.nlm.nih.gov/pubmed/29312121
http://dx.doi.org/10.3389/fneur.2017.00692
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