Functional brain age prediction suggests accelerated aging in preclinical familial Alzheimer's disease, irrespective of fibrillar amyloid-beta pathology
Gonneaud, J.; Baria, A. T.; Pichet Binette, A.; Gordon, B. A.; Chhatwal, J. P.; Cruchaga, C.; Jucker, M.; Levin, J.; Salloway, S.; Farlow, M.; Gauthier, S.; Benzinger, T. L.; Morris, J. C.; Bateman, R. J.; Breitner, J. C. S.; Poirier, J.; Vachon-Presseau, E.; Villeneuve, S.; Alzheimer's Disease Neuroimaging Initiative (ADNI), ; Dominantly Inherited Alzheimer Network (DIAN), ; PREVENT-AD Research Group,
Show abstract
We aimed at developing a model able to predict brain aging from resting state functional connectivity (rs-fMRI) and assessing whether genetic risk/determinants of Alzheimers disease (AD) and amyloid (A{beta}) pathology contributes to accelerated brain aging. Using data collected in 1340 cognitively unimpaired participants from 18 to 94 years old selected across multi-site cohorts, we showed that chronological age can be predicted across the whole lifespan from topological properties of graphs constructed from rs-fMRI. We subsequently used the difference between the model-predicted age and the chronological age in pre-symptomatic autosomal dominant AD (ADAD) mutation carriers and asymptomatic individuals at risk of sporadic AD and assessed the influence of genetics and A{beta} pathology on brain age. Applying our predictive model in the context of preclinical AD revealed that the pre-symptomatic phase of ADAD is characterized by accelerated functional brain aging. This phenomenon is independent from, and might precede, detectable fibrillar A{beta} deposition.
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