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Grey matter network trajectories across the Alzheimer’s disease continuum and relation to cognition

Biomarkers are needed to monitor disease progression in Alzheimer’s disease. Grey matter network measures have such potential, as they are related to amyloid aggregation in cognitively unimpaired individuals and to future cognitive decline in predementia Alzheimer’s disease. Here, we investigated ho...

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Autores principales: Dicks, Ellen, Vermunt, Lisa, van der Flier, Wiesje M, Barkhof, Frederik, Scheltens, Philip, Tijms, Betty M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7751002/
https://www.ncbi.nlm.nih.gov/pubmed/33376987
http://dx.doi.org/10.1093/braincomms/fcaa177
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author Dicks, Ellen
Vermunt, Lisa
van der Flier, Wiesje M
Barkhof, Frederik
Scheltens, Philip
Tijms, Betty M
author_facet Dicks, Ellen
Vermunt, Lisa
van der Flier, Wiesje M
Barkhof, Frederik
Scheltens, Philip
Tijms, Betty M
author_sort Dicks, Ellen
collection PubMed
description Biomarkers are needed to monitor disease progression in Alzheimer’s disease. Grey matter network measures have such potential, as they are related to amyloid aggregation in cognitively unimpaired individuals and to future cognitive decline in predementia Alzheimer’s disease. Here, we investigated how grey matter network measures evolve over time within individuals across the entire Alzheimer’s disease cognitive continuum and whether such changes relate to concurrent decline in cognition. We included 190 cognitively unimpaired, amyloid normal (controls) and 523 individuals with abnormal amyloid across the cognitive continuum (preclinical, prodromal, Alzheimer’s disease dementia) from the Alzheimer’s Disease Neuroimaging Initiative and calculated single-subject grey matter network measures (median of five networks per individual over 2 years). We fitted linear mixed models to investigate how network measures changed over time and whether such changes were associated with concurrent changes in memory, language, attention/executive functioning and on the Mini-Mental State Examination. We further assessed whether associations were modified by baseline disease stage. We found that both cognitive functioning and network measures declined over time, with steeper rates of decline in more advanced disease stages. In all cognitive stages, decline in network measures was associated with concurrent decline on the Mini-Mental State Examination, with stronger effects for individuals closer to Alzheimer’s disease dementia. Decline in network measures was associated with concurrent cognitive decline in different cognitive domains depending on disease stage: In controls, decline in networks was associated with decline in memory and language functioning; preclinical Alzheimer’s disease showed associations of decline in networks with memory and attention/executive functioning; prodromal Alzheimer’s disease showed associations of decline in networks with cognitive decline in all domains; Alzheimer’s disease dementia showed associations of decline in networks with attention/executive functioning. Decline in grey matter network measures over time accelerated for more advanced disease stages and was related to concurrent cognitive decline across the entire Alzheimer’s disease cognitive continuum. These associations were disease stage dependent for the different cognitive domains, which reflected the respective cognitive stage. Our findings therefore suggest that grey matter measures are helpful to track disease progression in Alzheimer’s disease.
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spelling pubmed-77510022020-12-28 Grey matter network trajectories across the Alzheimer’s disease continuum and relation to cognition Dicks, Ellen Vermunt, Lisa van der Flier, Wiesje M Barkhof, Frederik Scheltens, Philip Tijms, Betty M Brain Commun Original Article Biomarkers are needed to monitor disease progression in Alzheimer’s disease. Grey matter network measures have such potential, as they are related to amyloid aggregation in cognitively unimpaired individuals and to future cognitive decline in predementia Alzheimer’s disease. Here, we investigated how grey matter network measures evolve over time within individuals across the entire Alzheimer’s disease cognitive continuum and whether such changes relate to concurrent decline in cognition. We included 190 cognitively unimpaired, amyloid normal (controls) and 523 individuals with abnormal amyloid across the cognitive continuum (preclinical, prodromal, Alzheimer’s disease dementia) from the Alzheimer’s Disease Neuroimaging Initiative and calculated single-subject grey matter network measures (median of five networks per individual over 2 years). We fitted linear mixed models to investigate how network measures changed over time and whether such changes were associated with concurrent changes in memory, language, attention/executive functioning and on the Mini-Mental State Examination. We further assessed whether associations were modified by baseline disease stage. We found that both cognitive functioning and network measures declined over time, with steeper rates of decline in more advanced disease stages. In all cognitive stages, decline in network measures was associated with concurrent decline on the Mini-Mental State Examination, with stronger effects for individuals closer to Alzheimer’s disease dementia. Decline in network measures was associated with concurrent cognitive decline in different cognitive domains depending on disease stage: In controls, decline in networks was associated with decline in memory and language functioning; preclinical Alzheimer’s disease showed associations of decline in networks with memory and attention/executive functioning; prodromal Alzheimer’s disease showed associations of decline in networks with cognitive decline in all domains; Alzheimer’s disease dementia showed associations of decline in networks with attention/executive functioning. Decline in grey matter network measures over time accelerated for more advanced disease stages and was related to concurrent cognitive decline across the entire Alzheimer’s disease cognitive continuum. These associations were disease stage dependent for the different cognitive domains, which reflected the respective cognitive stage. Our findings therefore suggest that grey matter measures are helpful to track disease progression in Alzheimer’s disease. Oxford University Press 2020-08-20 /pmc/articles/PMC7751002/ /pubmed/33376987 http://dx.doi.org/10.1093/braincomms/fcaa177 Text en © The Author(s) (2020). 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 Article
Dicks, Ellen
Vermunt, Lisa
van der Flier, Wiesje M
Barkhof, Frederik
Scheltens, Philip
Tijms, Betty M
Grey matter network trajectories across the Alzheimer’s disease continuum and relation to cognition
title Grey matter network trajectories across the Alzheimer’s disease continuum and relation to cognition
title_full Grey matter network trajectories across the Alzheimer’s disease continuum and relation to cognition
title_fullStr Grey matter network trajectories across the Alzheimer’s disease continuum and relation to cognition
title_full_unstemmed Grey matter network trajectories across the Alzheimer’s disease continuum and relation to cognition
title_short Grey matter network trajectories across the Alzheimer’s disease continuum and relation to cognition
title_sort grey matter network trajectories across the alzheimer’s disease continuum and relation to cognition
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7751002/
https://www.ncbi.nlm.nih.gov/pubmed/33376987
http://dx.doi.org/10.1093/braincomms/fcaa177
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