Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorFarrell, Michelle E-
dc.contributor.authorJiang, Shu-
dc.contributor.authorSchultz, Aaron P-
dc.contributor.authorProperzi, Michael J-
dc.contributor.authorPrice, Julie C-
dc.contributor.authorBecker, J Alex-
dc.contributor.authorJacobs, Heidi I L-
dc.contributor.authorHanseeuw, Bernard J-
dc.contributor.authorRentz, Dorene M-
dc.contributor.authorVillemagne, Victor L-
dc.contributor.authorPapp, Kathryn V-
dc.contributor.authorMormino, Elizabeth C-
dc.contributor.authorBetensky, Rebecca A-
dc.contributor.authorJohnson, Keith A-
dc.contributor.authorSperling, Reisa A-
dc.contributor.authorBuckley, Rachel F-
dc.identifier.citationNeurology 2020; 96(4): e619-e631en
dc.description.abstractAs clinical trials move towards earlier intervention, we sought to redefine the Aβ-PET threshold based on the lowest point in a baseline distribution that robustly predicts future Aβ accumulation and cognitive decline in 3 independent samples of clinically normal individuals. Sequential Aβ cut-offs were tested to identify the lowest cutoff associated with future change in cognition (PACC) and Aβ-PET in clinically-normal participants from the Harvard Aging Brain Study (n = 342), Australian Imaging, Biomarker and Lifestyle study of ageing (n = 157) and Alzheimer's Disease Neuroimaging Initiative (n = 356). Within sample, cutoffs derived from future Aβ-PET accumulation and PACC decline converged on the same inflection point beyond which trajectories diverged from normal. Across samples, optimal cutoffs fell within a short range (Centiloid 15-18.5). These optimized thresholds can help to inform future research and clinical trials targeting early Aβ. Threshold convergence raises the possibility of contemporaneous early changes in Aβ and cognition. This study provides Class II evidence that among clinically normal individuals a specific Aβ-PET threshold is predictive of cognitive decline.en
dc.titleDefining the lowest threshold for amyloid-PET to predict future cognitive decline and amyloid accumulation.en
dc.typeJournal Articleen
dc.identifier.affiliationDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USAen
dc.identifier.affiliationDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USAen
dc.identifier.affiliationDivision of Public Health Sciences, Department of Surgery, Washington University School of Medicine in St. Louisen
dc.identifier.affiliationDepartment of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USAen
dc.identifier.affiliationFaculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, Maastricht, the Netherlandsen
dc.identifier.affiliationCliniques Universitaires Saint-Luc, Université Catholique de Louvain, Brussels, Belgiumen
dc.identifier.affiliationCenter for Alzheimer Research and Treatment, Brigham and Womens Hospital, Boston, MA, USAen
dc.identifier.affiliationMolecular Imaging and Therapyen
dc.identifier.affiliationDepartment of Neuroscience, Stanford University, Palo Alto, CA, USAen
dc.identifier.affiliationDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USAen
dc.identifier.affiliationDepartment of Biostatistics, New York University School of Global Public Health, New York, NY, USAen
dc.identifier.affiliationMelbourne School of Psychological Sciences, University of Melbourne, Melbourne, Australiaen
Appears in Collections:Journal articles
Show simple item record

Page view(s)

checked on Jun 24, 2021

Google ScholarTM


Items in AHRO are protected by copyright, with all rights reserved, unless otherwise indicated.