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

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). Three brain signatur...

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Vydané v:Alzheimer's & dementia Ročník 17; číslo 1; s. 89
Hlavní autori: Habes, Mohamad, Pomponio, Raymond, Shou, Haochang, Doshi, Jimit, Mamourian, Elizabeth, Erus, Guray, Nasrallah, Ilya, Launer, Lenore J, Rashid, Tanweer, Bilgel, Murat, Fan, Yong, Toledo, Jon B, Yaffe, Kristine, Sotiras, Aristeidis, Srinivasan, Dhivya, Espeland, Mark, Masters, Colin, Maruff, Paul, Fripp, Jurgen, Völzk, Henry, Johnson, Sterling C, Morris, John C, Albert, Marilyn S, Miller, Michael I, Bryan, R Nick, Grabe, Hans J, Resnick, Susan M, Wolk, David A, Davatzikos, Christos
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States 01.01.2021
Predmet:
Adult
Aged
Aged, 80 and over
Aging - physiology
Amyloid beta-Peptides - metabolism
Atrophy
Biomarkers
Brain - growth & development
Cerebral Small Vessel Diseases - metabolism
Cerebral Small Vessel Diseases - psychology
Cognitive Dysfunction
Disease Progression
Female
Humans
Image Processing, Computer-Assisted
Machine Learning
Magnetic Resonance Imaging - methods
Male
Middle Aged
Neuropsychological Tests
White Matter - growth & development
White Matter - pathology
Young Adult
Neuroimaging
MRI
small vessel ischemic disease
harmonized neuroimaging cohorts
brain aging
tau
Machine Learning
cognitive testing
beta-amyloid
brain signatures
Alzheimer's disease pathology
preclinical Alzheimer's disease
PET
Dementia
ISSN:1552-5279, 1552-5279
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Popis
Shrnutí: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). 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. 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 (Aβ) positivity after age 65. Brain aging, AD-like atrophy, and WMHs were better predictors of cognition than chronological age in MCI/AD. A Brain Chart quantifying brain-aging trajectories was established, enabling the systematic evaluation of individuals' brain-aging patterns relative to this large consortium.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1552-5279
1552-5279
DOI:10.1002/alz.12178