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Connectome-wide network analysis of white matter connectivity in Alzheimer's disease
A multivariate analytical strategy may pinpoint the structural connectivity patterns associated with Alzheimer's disease (AD) pathology in connectome-wide association studies. Diffusion magnetic resonance imaging data from 161 participants including subjects with healthy controls, AD, stable an...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6396432/ https://www.ncbi.nlm.nih.gov/pubmed/30825712 http://dx.doi.org/10.1016/j.nicl.2019.101690 |
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author | Ye, Chenfei Mori, Susumu Chan, Piu Ma, Ting |
author_facet | Ye, Chenfei Mori, Susumu Chan, Piu Ma, Ting |
author_sort | Ye, Chenfei |
collection | PubMed |
description | A multivariate analytical strategy may pinpoint the structural connectivity patterns associated with Alzheimer's disease (AD) pathology in connectome-wide association studies. Diffusion magnetic resonance imaging data from 161 participants including subjects with healthy controls, AD, stable and converting mild cognitive impairment, were selected for group-wise comparisons. A multivariate distance matrix regression (MDMR) analysis was performed to detect abnormality in brain structural network along with disease progression. Based on the seed regions returned by the MDMR analysis, supervised learning was applied to evaluate the disease predictive performance. Nine brain regions, including the left orbital part of superior and middle frontal gyrus, the bilateral supplementary motor area, the bilateral insula, the left hippocampus, the left putamen, and the left thalamus demonstrated extremely significant structural pattern changes along with the progression of AD. The disease classification was more efficient when based on the key connectivity related to these seed regions than when based on whole-brain structural connectivity. MDMR analysis reveals brain network reorganization caused by AD pathology. The key structural connectivity detected in this study exhibits promising distinguishing capability to predict prodromal AD patients. |
format | Online Article Text |
id | pubmed-6396432 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-63964322019-03-11 Connectome-wide network analysis of white matter connectivity in Alzheimer's disease Ye, Chenfei Mori, Susumu Chan, Piu Ma, Ting Neuroimage Clin Regular Article A multivariate analytical strategy may pinpoint the structural connectivity patterns associated with Alzheimer's disease (AD) pathology in connectome-wide association studies. Diffusion magnetic resonance imaging data from 161 participants including subjects with healthy controls, AD, stable and converting mild cognitive impairment, were selected for group-wise comparisons. A multivariate distance matrix regression (MDMR) analysis was performed to detect abnormality in brain structural network along with disease progression. Based on the seed regions returned by the MDMR analysis, supervised learning was applied to evaluate the disease predictive performance. Nine brain regions, including the left orbital part of superior and middle frontal gyrus, the bilateral supplementary motor area, the bilateral insula, the left hippocampus, the left putamen, and the left thalamus demonstrated extremely significant structural pattern changes along with the progression of AD. The disease classification was more efficient when based on the key connectivity related to these seed regions than when based on whole-brain structural connectivity. MDMR analysis reveals brain network reorganization caused by AD pathology. The key structural connectivity detected in this study exhibits promising distinguishing capability to predict prodromal AD patients. Elsevier 2019-02-21 /pmc/articles/PMC6396432/ /pubmed/30825712 http://dx.doi.org/10.1016/j.nicl.2019.101690 Text en © 2019 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Regular Article Ye, Chenfei Mori, Susumu Chan, Piu Ma, Ting Connectome-wide network analysis of white matter connectivity in Alzheimer's disease |
title | Connectome-wide network analysis of white matter connectivity in Alzheimer's disease |
title_full | Connectome-wide network analysis of white matter connectivity in Alzheimer's disease |
title_fullStr | Connectome-wide network analysis of white matter connectivity in Alzheimer's disease |
title_full_unstemmed | Connectome-wide network analysis of white matter connectivity in Alzheimer's disease |
title_short | Connectome-wide network analysis of white matter connectivity in Alzheimer's disease |
title_sort | connectome-wide network analysis of white matter connectivity in alzheimer's disease |
topic | Regular Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6396432/ https://www.ncbi.nlm.nih.gov/pubmed/30825712 http://dx.doi.org/10.1016/j.nicl.2019.101690 |
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