TY - JOUR
T1 - Accelerated functional brain aging in pre-clinical familial Alzheimer’s disease
AU - Gonneaud, Julie
AU - Baria, Alex T.
AU - Pichet Binette, Alexa
AU - Gordon, Brian A.
AU - Chhatwal, Jasmeer P.
AU - Cruchaga, Carlos
AU - Jucker, Mathias
AU - Levin, Johannes
AU - Salloway, Stephen
AU - Farlow, Martin
AU - Gauthier, Serge
AU - Benzinger, Tammie L.S.
AU - Morris, John C.
AU - Bateman, Randall J.
AU - Breitner, John C.S.
AU - Poirier, Judes
AU - Vachon-Presseau, Etienne
AU - Villeneuve, Sylvia
AU - Weiner, Michael
AU - Rosen, Howard J.
AU - Miller, Bruce L.
AU - Aisen, Paul
AU - Thomas, Ronald G.
AU - Donohue, Michael
AU - Walter, Sarah
AU - Gessert, Devon
AU - Sather, Tamie
AU - Jiminez, Gus
AU - Petersen, Ronald
AU - Jack, Clifford R.
AU - Bernstein, Matthew
AU - Borowski, Bret
AU - Gunter, Jeff
AU - Senjem, Matt
AU - Vemuri, Prashanthi
AU - Jones, David
AU - Kantarci, Kejal
AU - Ward, Chad
AU - Mason, Sara S.
AU - Albers, Colleen S.
AU - Knopman, David
AU - Johnson, Kris
AU - Jagust, William
AU - Landau, Susan
AU - Trojanowki, John Q.
AU - Toga, Arthur W.
AU - Crawford, Karen
AU - Neu, Scott
AU - Jicha, Greg
AU - King, Richard
N1 - Publisher Copyright:
© 2021, The Author(s).
PY - 2021/12
Y1 - 2021/12
N2 - Resting state functional connectivity (rs-fMRI) is impaired early in persons who subsequently develop Alzheimer’s disease (AD) dementia. This impairment may be leveraged to aid investigation of the pre-clinical phase of AD. We developed a model that predicts brain age from resting state (rs)-fMRI data, and assessed whether genetic determinants of AD, as well as beta-amyloid (Aβ) pathology, can accelerate brain aging. Using data from 1340 cognitively unimpaired participants between 18–94 years of age from multiple sites, we showed that topological properties of graphs constructed from rs-fMRI can predict chronological age across the lifespan. Application of our predictive model to the context of pre-clinical AD revealed that the pre-symptomatic phase of autosomal dominant AD includes acceleration of functional brain aging. This association was stronger in individuals having significant Aβ pathology.
AB - Resting state functional connectivity (rs-fMRI) is impaired early in persons who subsequently develop Alzheimer’s disease (AD) dementia. This impairment may be leveraged to aid investigation of the pre-clinical phase of AD. We developed a model that predicts brain age from resting state (rs)-fMRI data, and assessed whether genetic determinants of AD, as well as beta-amyloid (Aβ) pathology, can accelerate brain aging. Using data from 1340 cognitively unimpaired participants between 18–94 years of age from multiple sites, we showed that topological properties of graphs constructed from rs-fMRI can predict chronological age across the lifespan. Application of our predictive model to the context of pre-clinical AD revealed that the pre-symptomatic phase of autosomal dominant AD includes acceleration of functional brain aging. This association was stronger in individuals having significant Aβ pathology.
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U2 - 10.1038/s41467-021-25492-9
DO - 10.1038/s41467-021-25492-9
M3 - Article
C2 - 34504080
AN - SCOPUS:85115969502
SN - 2041-1723
VL - 12
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 5346
ER -