Journal Article

DZNE-2021-00874

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png 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.

Habes, M.Extern* ; Pomponio, R. ; Shou, H. ; Doshi, J. ; Mamourian, E. ; Erus, G. ; Nasrallah, I. ; Launer, L. J. ; Rashid, T. ; Bilgel, M. ; Fan, Y. ; Toledo, J. B. ; Yaffe, K. ; Sotiras, A. ; Srinivasan, D. ; Espeland, M. ; Masters, C. ; Maruff, P. ; Fripp, J. ; Völzk, H. ; Johnson, S. C. ; Morris, J. C. ; Albert, M. S. ; Miller, M. I. ; Bryan, R. N. ; Grabe, H. J.DZNE* ; Resnick, S. M. ; Wolk, D. A. ; Davatzikos, C. ; iSTAGING consortium, t. P. A. c. ; studies, t. C. (Collaboration Author)

2021
Wiley Hoboken, NJ

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Please use a persistent id in citations: doi:10.1002/alz.12178

Abstract: 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.

Keyword(s): Adult (MeSH) ; Aged (MeSH) ; Aged, 80 and over (MeSH) ; Aging: physiology (MeSH) ; Amyloid beta-Peptides: metabolism (MeSH) ; Atrophy (MeSH) ; Biomarkers (MeSH) ; Brain: growth & development (MeSH) ; Cerebral Small Vessel Diseases: metabolism (MeSH) ; Cerebral Small Vessel Diseases: psychology (MeSH) ; Cognitive Dysfunction (MeSH) ; Disease Progression (MeSH) ; Female (MeSH) ; Humans (MeSH) ; Image Processing, Computer-Assisted (MeSH) ; Machine Learning (MeSH) ; Magnetic Resonance Imaging: methods (MeSH) ; Male (MeSH) ; Middle Aged (MeSH) ; Neuropsychological Tests (MeSH) ; White Matter: growth & development (MeSH) ; White Matter: pathology (MeSH) ; Young Adult (MeSH) ; 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

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Contributing Institute(s):

1. Biomarkers of Dementia in the General Population (AG Grabe)

Research Program(s):

1. 353 - Clinical and Health Care Research (POF4-353) (POF4-353)

Appears in the scientific report 2021

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Database coverage:
; Clarivate Analytics Master Journal List ; Current Contents - Clinical Medicine ; DEAL Wiley ; Essential Science Indicators ; IF >= 15 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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