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.
Adult
Aged
Aged, 80 and over
Aging
/ physiology
Amyloid beta-Peptides
/ metabolism
Atrophy
Biomarkers
Brain
/ growth & development
Cerebral Small Vessel Diseases
/ metabolism
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
Young Adult
Alzheimer's disease pathology
Dementia
MRI
Machine Learning
Neuroimaging
PET
beta-amyloid
brain aging
brain signatures
cognitive testing
harmonized neuroimaging cohorts
preclinical Alzheimer's disease
small vessel ischemic disease
tau
Journal
Alzheimer's & dementia : the journal of the Alzheimer's Association
ISSN: 1552-5279
Titre abrégé: Alzheimers Dement
Pays: United States
ID NLM: 101231978
Informations de publication
Date de publication:
01 2021
01 2021
Historique:
received:
27
11
2019
revised:
12
07
2020
accepted:
24
07
2020
pubmed:
14
9
2020
medline:
26
10
2021
entrez:
13
9
2020
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 32920988
doi: 10.1002/alz.12178
pmc: PMC7923395
mid: NIHMS1640231
doi:
Substances chimiques
Amyloid beta-Peptides
0
Biomarkers
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, N.I.H., Intramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
89-102Subventions
Organisme : NIBIB NIH HHS
ID : R01 EB022573
Pays : United States
Organisme : NIA NIH HHS
ID : U01 AG068057
Pays : United States
Organisme : NIA NIH HHS
ID : U19 AG033655
Pays : United States
Organisme : NIA NIH HHS
ID : P30 AG049638
Pays : United States
Organisme : NIA NIH HHS
ID : RF1 AG059869
Pays : United States
Organisme : NIA NIH HHS
ID : RF1 AG054409
Pays : United States
Organisme : NIH HHS
ID : S10 OD023495
Pays : United States
Organisme : NIA NIH HHS
ID : P30 AG066507
Pays : United States
Organisme : NIDA NIH HHS
ID : HHSN271201600059C
Pays : United States
Organisme : NIA NIH HHS
ID : P30 AG062715
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG063887
Pays : United States
Informations de copyright
© 2020 the Alzheimer's Association.
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