TY - JOUR
T1 - The Brain Chart of Aging
T2 - 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
AU - for the iSTAGING consortium, the Preclinical AD consortium, the ADNI, and the CARDIA studies
AU - Habes, Mohamad
AU - Pomponio, Raymond
AU - Shou, Haochang
AU - Doshi, Jimit
AU - Mamourian, Elizabeth
AU - Erus, Guray
AU - Nasrallah, Ilya
AU - Launer, Lenore J.
AU - Rashid, Tanweer
AU - Bilgel, Murat
AU - Fan, Yong
AU - Toledo, Jon B.
AU - Yaffe, Kristine
AU - Sotiras, Aristeidis
AU - Srinivasan, Dhivya
AU - Espeland, Mark
AU - Masters, Colin
AU - Maruff, Paul
AU - Fripp, Jurgen
AU - Völzk, Henry
AU - Johnson, Sterling C.
AU - Morris, John C.
AU - Albert, Marilyn S.
AU - Miller, Michael I.
AU - Bryan, R. Nick
AU - Grabe, Hans J.
AU - Resnick, Susan M.
AU - Wolk, David A.
AU - Davatzikos, Christos
N1 - Publisher Copyright:
© 2020 the Alzheimer's Association
PY - 2021/1
Y1 - 2021/1
N2 - 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 (Aβ) 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.
AB - 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 (Aβ) 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.
KW - Alzheimer's disease pathology
KW - Dementia
KW - MRI
KW - Machine Learning
KW - Neuroimaging
KW - PET
KW - beta-amyloid
KW - brain aging
KW - brain signatures
KW - cognitive testing
KW - harmonized neuroimaging cohorts
KW - preclinical Alzheimer's disease
KW - small vessel ischemic disease
KW - tau
UR - http://www.scopus.com/inward/record.url?scp=85090840116&partnerID=8YFLogxK
U2 - 10.1002/alz.12178
DO - 10.1002/alz.12178
M3 - Article
C2 - 32920988
AN - SCOPUS:85090840116
SN - 1552-5260
VL - 17
SP - 89
EP - 102
JO - Alzheimer's and Dementia
JF - Alzheimer's and Dementia
IS - 1
ER -