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Amyloid-independent atrophy patterns predict time to progression to dementia in mild cognitive impairment
BACKGROUND: Amyloid pathology in subjects with mild cognitive impairment (MCI) is an important risk factor for progression to dementia due to Alzheimer’s disease. Predicting the onset of dementia is challenging even in the presence of amyloid, as time to progression varies considerably among patient...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5596472/ https://www.ncbi.nlm.nih.gov/pubmed/28899429 http://dx.doi.org/10.1186/s13195-017-0299-x |
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author | ten Kate, Mara Barkhof, Frederik Visser, Pieter Jelle Teunissen, Charlotte E. Scheltens, Philip van der Flier, Wiesje M. Tijms, Betty M. |
author_facet | ten Kate, Mara Barkhof, Frederik Visser, Pieter Jelle Teunissen, Charlotte E. Scheltens, Philip van der Flier, Wiesje M. Tijms, Betty M. |
author_sort | ten Kate, Mara |
collection | PubMed |
description | BACKGROUND: Amyloid pathology in subjects with mild cognitive impairment (MCI) is an important risk factor for progression to dementia due to Alzheimer’s disease. Predicting the onset of dementia is challenging even in the presence of amyloid, as time to progression varies considerably among patients and depends on the onset of neurodegeneration. Survival analysis can account for variability in time to event, but has not often been applied to MRI measurements beyond singular predefined brain regions such as the hippocampus. Here we used a voxel-wise survival analysis to identify in an unbiased fashion brain regions where decreased gray matter volume is associated with time to dementia, and assessed the effects of amyloid on these associations. METHODS: We included 276 subjects with MCI (mean age 67 ± 8, 41% female, mean Mini-Mental State Examination 26.6 ± 2.4), baseline 3D T1-weighted structural MRI, baseline cerebrospinal fluid (CSF) biomarkers, and prospective clinical follow-up. We fitted for each voxel a proportional Cox hazards regression model to study whether decreased gray matter volume predicted progression to dementia in the total sample, and stratified for baseline amyloid status. RESULTS: Dementia at follow-up occurred in 122 (44%) subjects over an average follow-up period of 2.5 ± 1.5 years. Baseline amyloid positivity was associated with progression to dementia (hazard ratio 2.4, p < 0.001). Within amyloid-positive subjects, decreased gray matter volume in the hippocampal, temporal, parietal, and frontal regions was associated with more rapid progression to dementia (median (interquartile range) hazard ratio across significant voxels 1.35 (1.32–1.40)). Repeating the analysis in amyloid-negative subjects revealed similar patterns (median (interquartile range) hazard ratio 1.76 (1.66–1.91)). CONCLUSIONS: In subjects with MCI, both abnormal amyloid CSF and decreased gray matter volume were associated with future progression to dementia. The spatial pattern of decreased gray matter volume associated with progression to dementia was consistent for amyloid-positive and amyloid-negative subjects. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13195-017-0299-x) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5596472 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-55964722017-09-15 Amyloid-independent atrophy patterns predict time to progression to dementia in mild cognitive impairment ten Kate, Mara Barkhof, Frederik Visser, Pieter Jelle Teunissen, Charlotte E. Scheltens, Philip van der Flier, Wiesje M. Tijms, Betty M. Alzheimers Res Ther Research BACKGROUND: Amyloid pathology in subjects with mild cognitive impairment (MCI) is an important risk factor for progression to dementia due to Alzheimer’s disease. Predicting the onset of dementia is challenging even in the presence of amyloid, as time to progression varies considerably among patients and depends on the onset of neurodegeneration. Survival analysis can account for variability in time to event, but has not often been applied to MRI measurements beyond singular predefined brain regions such as the hippocampus. Here we used a voxel-wise survival analysis to identify in an unbiased fashion brain regions where decreased gray matter volume is associated with time to dementia, and assessed the effects of amyloid on these associations. METHODS: We included 276 subjects with MCI (mean age 67 ± 8, 41% female, mean Mini-Mental State Examination 26.6 ± 2.4), baseline 3D T1-weighted structural MRI, baseline cerebrospinal fluid (CSF) biomarkers, and prospective clinical follow-up. We fitted for each voxel a proportional Cox hazards regression model to study whether decreased gray matter volume predicted progression to dementia in the total sample, and stratified for baseline amyloid status. RESULTS: Dementia at follow-up occurred in 122 (44%) subjects over an average follow-up period of 2.5 ± 1.5 years. Baseline amyloid positivity was associated with progression to dementia (hazard ratio 2.4, p < 0.001). Within amyloid-positive subjects, decreased gray matter volume in the hippocampal, temporal, parietal, and frontal regions was associated with more rapid progression to dementia (median (interquartile range) hazard ratio across significant voxels 1.35 (1.32–1.40)). Repeating the analysis in amyloid-negative subjects revealed similar patterns (median (interquartile range) hazard ratio 1.76 (1.66–1.91)). CONCLUSIONS: In subjects with MCI, both abnormal amyloid CSF and decreased gray matter volume were associated with future progression to dementia. The spatial pattern of decreased gray matter volume associated with progression to dementia was consistent for amyloid-positive and amyloid-negative subjects. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13195-017-0299-x) contains supplementary material, which is available to authorized users. BioMed Central 2017-09-12 /pmc/articles/PMC5596472/ /pubmed/28899429 http://dx.doi.org/10.1186/s13195-017-0299-x Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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 ten Kate, Mara Barkhof, Frederik Visser, Pieter Jelle Teunissen, Charlotte E. Scheltens, Philip van der Flier, Wiesje M. Tijms, Betty M. Amyloid-independent atrophy patterns predict time to progression to dementia in mild cognitive impairment |
title | Amyloid-independent atrophy patterns predict time to progression to dementia in mild cognitive impairment |
title_full | Amyloid-independent atrophy patterns predict time to progression to dementia in mild cognitive impairment |
title_fullStr | Amyloid-independent atrophy patterns predict time to progression to dementia in mild cognitive impairment |
title_full_unstemmed | Amyloid-independent atrophy patterns predict time to progression to dementia in mild cognitive impairment |
title_short | Amyloid-independent atrophy patterns predict time to progression to dementia in mild cognitive impairment |
title_sort | amyloid-independent atrophy patterns predict time to progression to dementia in mild cognitive impairment |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5596472/ https://www.ncbi.nlm.nih.gov/pubmed/28899429 http://dx.doi.org/10.1186/s13195-017-0299-x |
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