Multi-method investigation of factors influencing amyloid onset and impairment in three cohorts.

Autor:	Betthauser TJ; Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.; Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA., Bilgel M; Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA., Koscik RL; Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.; Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA.; Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA., Jedynak BM; Department of Mathematics and Statistics, Portland State University, Portland, OR, USA., An Y; Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA., Kellett KA; Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.; Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA., Moghekar A; Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA., Jonaitis EM; Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.; Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA.; Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA., Stone CK; Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA., Engelman CD; Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.; Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.; Department of Population Health Sciences, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA., Asthana S; Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.; Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA.; Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.; Geriatric Research Education and Clinical Center, William S. Middleton Veterans Hospital, Madison, WI, USA., Christian BT; Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.; Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison, Madison, WI, USA.; Department of Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA., Wong DF; Department of Radiology, Mallinckrodt Institute of Radiology, Neurology, Psychiatry and Neuroscience, Washington University School of Medicine, St. Louis, MO, USA., Albert M; Department of Neurology, Division of Cognitive Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA., Resnick SM; Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA., Johnson SC; Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.; Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA.; Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.; Geriatric Research Education and Clinical Center, William S. Middleton Veterans Hospital, Madison, WI, USA.
Jazyk:	angličtina
Zdroj:	Brain : a journal of neurology [Brain] 2022 Nov 21; Vol. 145 (11), pp. 4065-4079.
DOI:	10.1093/brain/awac213
Abstrakt:	Alzheimer's disease biomarkers are becoming increasingly important for characterizing the longitudinal course of disease, predicting the timing of clinical and cognitive symptoms, and for recruitment and treatment monitoring in clinical trials. In this work, we develop and evaluate three methods for modelling the longitudinal course of amyloid accumulation in three cohorts using amyloid PET imaging. We then use these novel approaches to investigate factors that influence the timing of amyloid onset and the timing from amyloid onset to impairment onset in the Alzheimer's disease continuum. Data were acquired from the Alzheimer's Disease Neuroimaging Initiative (ADNI), the Baltimore Longitudinal Study of Aging (BLSA) and the Wisconsin Registry for Alzheimer's Prevention (WRAP). Amyloid PET was used to assess global amyloid burden. Three methods were evaluated for modelling amyloid accumulation using 10-fold cross-validation and holdout validation where applicable. Estimated amyloid onset age was compared across all three modelling methods and cohorts. Cox regression and accelerated failure time models were used to investigate whether sex, apolipoprotein E genotype and e4 carriage were associated with amyloid onset age in all cohorts. Cox regression was used to investigate whether apolipoprotein E (e4 carriage and e3e3, e3e4, e4e4 genotypes), sex or age of amyloid onset were associated with the time from amyloid onset to impairment onset (global clinical dementia rating ≥1) in a subset of 595 ADNI participants that were not impaired before amyloid onset. Model prediction and estimated amyloid onset age were similar across all three amyloid modelling methods. Sex and apolipoprotein E e4 carriage were not associated with PET-measured amyloid accumulation rates. Apolipoprotein E genotype and e4 carriage, but not sex, were associated with amyloid onset age such that e4 carriers became amyloid positive at an earlier age compared to non-carriers, and greater e4 dosage was associated with an earlier amyloid onset age. In the ADNI, e4 carriage, being female and a later amyloid onset age were all associated with a shorter time from amyloid onset to impairment onset. The risk of impairment onset due to age of amyloid onset was non-linear and accelerated for amyloid onset age >65. These findings demonstrate the feasibility of modelling longitudinal amyloid accumulation to enable individualized estimates of amyloid onset age from amyloid PET imaging. These estimates provide a more direct way to investigate the role of amyloid and other factors that influence the timing of clinical impairment in Alzheimer's disease. (© The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain.)
Databáze:	MEDLINE
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