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Influence of cerebrovascular disease on brain networks in prodromal and clinical Alzheimer’s disease

Network-sensitive neuroimaging methods have been used to characterize large-scale brain network degeneration in Alzheimer’s disease and its prodrome. However, few studies have investigated the combined effect of Alzheimer’s disease and cerebrovascular disease on brain network degeneration. Our study...

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Autores principales: Chong, Joanna Su Xian, Liu, Siwei, Loke, Yng Miin, Hilal, Saima, Ikram, Mohammad Kamran, Xu, Xin, Tan, Boon Yeow, Venketasubramanian, Narayanaswamy, Chen, Christopher Li-Hsian, Zhou, Juan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5841199/
https://www.ncbi.nlm.nih.gov/pubmed/29053778
http://dx.doi.org/10.1093/brain/awx224
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author Chong, Joanna Su Xian
Liu, Siwei
Loke, Yng Miin
Hilal, Saima
Ikram, Mohammad Kamran
Xu, Xin
Tan, Boon Yeow
Venketasubramanian, Narayanaswamy
Chen, Christopher Li-Hsian
Zhou, Juan
author_facet Chong, Joanna Su Xian
Liu, Siwei
Loke, Yng Miin
Hilal, Saima
Ikram, Mohammad Kamran
Xu, Xin
Tan, Boon Yeow
Venketasubramanian, Narayanaswamy
Chen, Christopher Li-Hsian
Zhou, Juan
author_sort Chong, Joanna Su Xian
collection PubMed
description Network-sensitive neuroimaging methods have been used to characterize large-scale brain network degeneration in Alzheimer’s disease and its prodrome. However, few studies have investigated the combined effect of Alzheimer’s disease and cerebrovascular disease on brain network degeneration. Our study sought to examine the intrinsic functional connectivity and structural covariance network changes in 235 prodromal and clinical Alzheimer’s disease patients with and without cerebrovascular disease. We focused particularly on two higher-order cognitive networks—the default mode network and the executive control network. We found divergent functional connectivity and structural covariance patterns in Alzheimer’s disease patients with and without cerebrovascular disease. Alzheimer’s disease patients without cerebrovascular disease, but not Alzheimer’s disease patients with cerebrovascular disease, showed reductions in posterior default mode network functional connectivity. By comparison, while both groups exhibited parietal reductions in executive control network functional connectivity, only Alzheimer’s disease patients with cerebrovascular disease showed increases in frontal executive control network connectivity. Importantly, these distinct executive control network changes were recapitulated in prodromal Alzheimer’s disease patients with and without cerebrovascular disease. Across Alzheimer’s disease patients with and without cerebrovascular disease, higher default mode network functional connectivity z-scores correlated with greater hippocampal volumes while higher executive control network functional connectivity z-scores correlated with greater white matter changes. In parallel, only Alzheimer’s disease patients without cerebrovascular disease showed increased default mode network structural covariance, while only Alzheimer’s disease patients with cerebrovascular disease showed increased executive control network structural covariance compared to controls. Our findings demonstrate the differential neural network structural and functional changes in Alzheimer’s disease with and without cerebrovascular disease, suggesting that the underlying pathology of Alzheimer’s disease patients with cerebrovascular disease might differ from those without cerebrovascular disease and reflect a combination of more severe cerebrovascular disease and less severe Alzheimer’s disease network degeneration phenotype.
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spelling pubmed-58411992018-03-28 Influence of cerebrovascular disease on brain networks in prodromal and clinical Alzheimer’s disease Chong, Joanna Su Xian Liu, Siwei Loke, Yng Miin Hilal, Saima Ikram, Mohammad Kamran Xu, Xin Tan, Boon Yeow Venketasubramanian, Narayanaswamy Chen, Christopher Li-Hsian Zhou, Juan Brain Original Articles Network-sensitive neuroimaging methods have been used to characterize large-scale brain network degeneration in Alzheimer’s disease and its prodrome. However, few studies have investigated the combined effect of Alzheimer’s disease and cerebrovascular disease on brain network degeneration. Our study sought to examine the intrinsic functional connectivity and structural covariance network changes in 235 prodromal and clinical Alzheimer’s disease patients with and without cerebrovascular disease. We focused particularly on two higher-order cognitive networks—the default mode network and the executive control network. We found divergent functional connectivity and structural covariance patterns in Alzheimer’s disease patients with and without cerebrovascular disease. Alzheimer’s disease patients without cerebrovascular disease, but not Alzheimer’s disease patients with cerebrovascular disease, showed reductions in posterior default mode network functional connectivity. By comparison, while both groups exhibited parietal reductions in executive control network functional connectivity, only Alzheimer’s disease patients with cerebrovascular disease showed increases in frontal executive control network connectivity. Importantly, these distinct executive control network changes were recapitulated in prodromal Alzheimer’s disease patients with and without cerebrovascular disease. Across Alzheimer’s disease patients with and without cerebrovascular disease, higher default mode network functional connectivity z-scores correlated with greater hippocampal volumes while higher executive control network functional connectivity z-scores correlated with greater white matter changes. In parallel, only Alzheimer’s disease patients without cerebrovascular disease showed increased default mode network structural covariance, while only Alzheimer’s disease patients with cerebrovascular disease showed increased executive control network structural covariance compared to controls. Our findings demonstrate the differential neural network structural and functional changes in Alzheimer’s disease with and without cerebrovascular disease, suggesting that the underlying pathology of Alzheimer’s disease patients with cerebrovascular disease might differ from those without cerebrovascular disease and reflect a combination of more severe cerebrovascular disease and less severe Alzheimer’s disease network degeneration phenotype. Oxford University Press 2017-11 2017-09-19 /pmc/articles/PMC5841199/ /pubmed/29053778 http://dx.doi.org/10.1093/brain/awx224 Text en © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Original Articles
Chong, Joanna Su Xian
Liu, Siwei
Loke, Yng Miin
Hilal, Saima
Ikram, Mohammad Kamran
Xu, Xin
Tan, Boon Yeow
Venketasubramanian, Narayanaswamy
Chen, Christopher Li-Hsian
Zhou, Juan
Influence of cerebrovascular disease on brain networks in prodromal and clinical Alzheimer’s disease
title Influence of cerebrovascular disease on brain networks in prodromal and clinical Alzheimer’s disease
title_full Influence of cerebrovascular disease on brain networks in prodromal and clinical Alzheimer’s disease
title_fullStr Influence of cerebrovascular disease on brain networks in prodromal and clinical Alzheimer’s disease
title_full_unstemmed Influence of cerebrovascular disease on brain networks in prodromal and clinical Alzheimer’s disease
title_short Influence of cerebrovascular disease on brain networks in prodromal and clinical Alzheimer’s disease
title_sort influence of cerebrovascular disease on brain networks in prodromal and clinical alzheimer’s disease
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5841199/
https://www.ncbi.nlm.nih.gov/pubmed/29053778
http://dx.doi.org/10.1093/brain/awx224
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