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Interactions Between Aging and Alzheimer’s Disease on Structural Brain Networks

Normative aging and Alzheimer’s disease (AD) propagation alter anatomical connections among brain parcels. However, the interaction between the trajectories of age- and AD-linked alterations in the topology of the structural brain network is not well understood. In this study, diffusion-weighted mag...

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Autores principales: Wu, Zhanxiong, Gao, Yunyuan, Potter, Thomas, Benoit, Julia, Shen, Jian, Schulz, Paul E., Zhang, Yingchun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8222527/
https://www.ncbi.nlm.nih.gov/pubmed/34177548
http://dx.doi.org/10.3389/fnagi.2021.639795
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author Wu, Zhanxiong
Gao, Yunyuan
Potter, Thomas
Benoit, Julia
Shen, Jian
Schulz, Paul E.
Zhang, Yingchun
author_facet Wu, Zhanxiong
Gao, Yunyuan
Potter, Thomas
Benoit, Julia
Shen, Jian
Schulz, Paul E.
Zhang, Yingchun
author_sort Wu, Zhanxiong
collection PubMed
description Normative aging and Alzheimer’s disease (AD) propagation alter anatomical connections among brain parcels. However, the interaction between the trajectories of age- and AD-linked alterations in the topology of the structural brain network is not well understood. In this study, diffusion-weighted magnetic resonance imaging (MRI) datasets of 139 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database were used to document their structural brain networks. The 139 participants consist of 45 normal controls (NCs), 37 with early mild cognitive impairment (EMCI), 27 with late mild cognitive impairment (LMCI), and 30 AD patients. All subjects were further divided into three subgroups based on their age (56–65, 66–75, and 71–85 years). After the structural connectivity networks were built using anatomically-constrained deterministic tractography, their global and nodal topological properties were estimated, including network efficiency, characteristic path length, transitivity, modularity coefficient, clustering coefficient, and betweenness. Statistical analyses were then performed on these metrics using linear regression, and one- and two-way ANOVA testing to examine group differences and interactions between aging and AD propagation. No significant interactions were found between aging and AD propagation in the global topological metrics (network efficiency, characteristic path length, transitivity, and modularity coefficient). However, nodal metrics (clustering coefficient and betweenness centrality) of some cortical parcels exhibited significant interactions between aging and AD propagation, with affected parcels including left superior temporal, right pars triangularis, and right precentral. The results collectively confirm the age-related deterioration of structural networks in MCI and AD patients, providing novel insight into the cross effects of aging and AD disorder on brain structural networks. Some early symptoms of AD may also be due to age-associated anatomic vulnerability interacting with early anatomic changes associated with AD.
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spelling pubmed-82225272021-06-25 Interactions Between Aging and Alzheimer’s Disease on Structural Brain Networks Wu, Zhanxiong Gao, Yunyuan Potter, Thomas Benoit, Julia Shen, Jian Schulz, Paul E. Zhang, Yingchun Front Aging Neurosci Neuroscience Normative aging and Alzheimer’s disease (AD) propagation alter anatomical connections among brain parcels. However, the interaction between the trajectories of age- and AD-linked alterations in the topology of the structural brain network is not well understood. In this study, diffusion-weighted magnetic resonance imaging (MRI) datasets of 139 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database were used to document their structural brain networks. The 139 participants consist of 45 normal controls (NCs), 37 with early mild cognitive impairment (EMCI), 27 with late mild cognitive impairment (LMCI), and 30 AD patients. All subjects were further divided into three subgroups based on their age (56–65, 66–75, and 71–85 years). After the structural connectivity networks were built using anatomically-constrained deterministic tractography, their global and nodal topological properties were estimated, including network efficiency, characteristic path length, transitivity, modularity coefficient, clustering coefficient, and betweenness. Statistical analyses were then performed on these metrics using linear regression, and one- and two-way ANOVA testing to examine group differences and interactions between aging and AD propagation. No significant interactions were found between aging and AD propagation in the global topological metrics (network efficiency, characteristic path length, transitivity, and modularity coefficient). However, nodal metrics (clustering coefficient and betweenness centrality) of some cortical parcels exhibited significant interactions between aging and AD propagation, with affected parcels including left superior temporal, right pars triangularis, and right precentral. The results collectively confirm the age-related deterioration of structural networks in MCI and AD patients, providing novel insight into the cross effects of aging and AD disorder on brain structural networks. Some early symptoms of AD may also be due to age-associated anatomic vulnerability interacting with early anatomic changes associated with AD. Frontiers Media S.A. 2021-06-10 /pmc/articles/PMC8222527/ /pubmed/34177548 http://dx.doi.org/10.3389/fnagi.2021.639795 Text en Copyright © 2021 Wu, Gao, Potter, Benoit, Shen, Schulz, Zhang and The Alzheimer’s Disease Neuroimaging Initiative. https://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
Wu, Zhanxiong
Gao, Yunyuan
Potter, Thomas
Benoit, Julia
Shen, Jian
Schulz, Paul E.
Zhang, Yingchun
Interactions Between Aging and Alzheimer’s Disease on Structural Brain Networks
title Interactions Between Aging and Alzheimer’s Disease on Structural Brain Networks
title_full Interactions Between Aging and Alzheimer’s Disease on Structural Brain Networks
title_fullStr Interactions Between Aging and Alzheimer’s Disease on Structural Brain Networks
title_full_unstemmed Interactions Between Aging and Alzheimer’s Disease on Structural Brain Networks
title_short Interactions Between Aging and Alzheimer’s Disease on Structural Brain Networks
title_sort interactions between aging and alzheimer’s disease on structural brain networks
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8222527/
https://www.ncbi.nlm.nih.gov/pubmed/34177548
http://dx.doi.org/10.3389/fnagi.2021.639795
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