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Voxel-based meta-analysis of grey matter changes in Alzheimer’s disease
BACKGROUND: Voxel-based morphometry (VBM) using structural brain MRI has been widely used for the assessment of impairment in Alzheimer’s disease (AD), but previous studies in VBM studies on AD remain inconsistent. OBJECTIVE: We conducted meta-analyses to integrate the reported studies to determine...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4381413/ https://www.ncbi.nlm.nih.gov/pubmed/25834730 http://dx.doi.org/10.1186/s40035-015-0027-z |
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author | Wang, Wen-Ying Yu, Jin-Tai Liu, Yong Yin, Rui-Hua Wang, Hui-Fu Wang, Jun Tan, Lin Radua, Joaquim Tan, Lan |
author_facet | Wang, Wen-Ying Yu, Jin-Tai Liu, Yong Yin, Rui-Hua Wang, Hui-Fu Wang, Jun Tan, Lin Radua, Joaquim Tan, Lan |
author_sort | Wang, Wen-Ying |
collection | PubMed |
description | BACKGROUND: Voxel-based morphometry (VBM) using structural brain MRI has been widely used for the assessment of impairment in Alzheimer’s disease (AD), but previous studies in VBM studies on AD remain inconsistent. OBJECTIVE: We conducted meta-analyses to integrate the reported studies to determine the consistent grey matter alterations in AD based on VBM method. METHODS: The PubMed, ISI Web of Science, EMBASE and Medline database were searched for articles between 1995 and June 2014. Manual searches were also conducted, and authors of studies were contacted for additional data. Coordinates were extracted from clusters with significant grey matter difference between AD patients and healthy controls (HC). Meta-analysis was performed using a new improved voxel-based meta-analytic method, Effect Size Signed Differential Mapping (ES-SDM). RESULTS: Thirty data-sets comprising 960 subjects with AD and 1195 HC met inclusion criteria. Grey matter volume (GMV) reduction at 334 coordinates in AD and no GMV increase were found in the current meta-analysis. Significant reductions in GMV were robustly localized in the limbic regions (left parahippocampl gyrus and left posterior cingulate gyrus). In addition, there were GM decreases in right fusiform gyrus and right superior frontal gyrus. The findings remain largely unchanged in the jackknife sensitivity analyses. CONCLUSIONS: Our meta-analysis clearly identified GMV atrophy in AD. These findings confirm that the most prominent and replicable structural abnormalities in AD are in the limbic regions and contributes to the understanding of pathophysiology underlying AD. |
format | Online Article Text |
id | pubmed-4381413 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-43814132015-04-02 Voxel-based meta-analysis of grey matter changes in Alzheimer’s disease Wang, Wen-Ying Yu, Jin-Tai Liu, Yong Yin, Rui-Hua Wang, Hui-Fu Wang, Jun Tan, Lin Radua, Joaquim Tan, Lan Transl Neurodegener Research BACKGROUND: Voxel-based morphometry (VBM) using structural brain MRI has been widely used for the assessment of impairment in Alzheimer’s disease (AD), but previous studies in VBM studies on AD remain inconsistent. OBJECTIVE: We conducted meta-analyses to integrate the reported studies to determine the consistent grey matter alterations in AD based on VBM method. METHODS: The PubMed, ISI Web of Science, EMBASE and Medline database were searched for articles between 1995 and June 2014. Manual searches were also conducted, and authors of studies were contacted for additional data. Coordinates were extracted from clusters with significant grey matter difference between AD patients and healthy controls (HC). Meta-analysis was performed using a new improved voxel-based meta-analytic method, Effect Size Signed Differential Mapping (ES-SDM). RESULTS: Thirty data-sets comprising 960 subjects with AD and 1195 HC met inclusion criteria. Grey matter volume (GMV) reduction at 334 coordinates in AD and no GMV increase were found in the current meta-analysis. Significant reductions in GMV were robustly localized in the limbic regions (left parahippocampl gyrus and left posterior cingulate gyrus). In addition, there were GM decreases in right fusiform gyrus and right superior frontal gyrus. The findings remain largely unchanged in the jackknife sensitivity analyses. CONCLUSIONS: Our meta-analysis clearly identified GMV atrophy in AD. These findings confirm that the most prominent and replicable structural abnormalities in AD are in the limbic regions and contributes to the understanding of pathophysiology underlying AD. BioMed Central 2015-03-27 /pmc/articles/PMC4381413/ /pubmed/25834730 http://dx.doi.org/10.1186/s40035-015-0027-z Text en © Wang et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Wang, Wen-Ying Yu, Jin-Tai Liu, Yong Yin, Rui-Hua Wang, Hui-Fu Wang, Jun Tan, Lin Radua, Joaquim Tan, Lan Voxel-based meta-analysis of grey matter changes in Alzheimer’s disease |
title | Voxel-based meta-analysis of grey matter changes in Alzheimer’s disease |
title_full | Voxel-based meta-analysis of grey matter changes in Alzheimer’s disease |
title_fullStr | Voxel-based meta-analysis of grey matter changes in Alzheimer’s disease |
title_full_unstemmed | Voxel-based meta-analysis of grey matter changes in Alzheimer’s disease |
title_short | Voxel-based meta-analysis of grey matter changes in Alzheimer’s disease |
title_sort | voxel-based meta-analysis of grey matter changes in alzheimer’s disease |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4381413/ https://www.ncbi.nlm.nih.gov/pubmed/25834730 http://dx.doi.org/10.1186/s40035-015-0027-z |
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