The Brain Chart of Aging: Machine-learning analytics reveals links between brain aging, white matter disease, amyloid burden, and cognition in the iSTAGING consortium of 10,216 harmonized MR scans.
Alzheimers Dement
; 17(1): 89-102, 2021 01.
Article
em En
| MEDLINE
| ID: mdl-32920988
ABSTRACT
INTRODUCTION:
Relationships between brain atrophy patterns of typical aging and Alzheimer's disease (AD), white matter disease, cognition, and AD neuropathology were investigated via machine learning in a large harmonized magnetic resonance imaging database (11 studies; 10,216 subjects).METHODS:
Three brain signatures were calculated Brain-age, AD-like neurodegeneration, and white matter hyperintensities (WMHs). Brain Charts measured and displayed the relationships of these signatures to cognition and molecular biomarkers of AD.RESULTS:
WMHs were associated with advanced brain aging, AD-like atrophy, poorer cognition, and AD neuropathology in mild cognitive impairment (MCI)/AD and cognitively normal (CN) subjects. High WMH volume was associated with brain aging and cognitive decline occurring in an ≈10-year period in CN subjects. WMHs were associated with doubling the likelihood of amyloid beta (Aß) positivity after age 65. Brain aging, AD-like atrophy, and WMHs were better predictors of cognition than chronological age in MCI/AD.DISCUSSION:
A Brain Chart quantifying brain-aging trajectories was established, enabling the systematic evaluation of individuals' brain-aging patterns relative to this large consortium.Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Encéfalo
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Envelhecimento
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Imageamento por Ressonância Magnética
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Peptídeos beta-Amiloides
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Substância Branca
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Aprendizado de Máquina
Tipo de estudo:
Prognostic_studies
Limite:
Adult
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Aged
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Aged80
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Revista:
Alzheimers Dement
Ano de publicação:
2021
Tipo de documento:
Article
País de afiliação:
Estados Unidos