Abstract

Qualitative models of Alzheimer’s pathology often posit that amyloid accumulation follows a sigmoid curve, indicating that the rate of deposition wanes over time. Longitudinal PET data now allow us to investigate amyloid accumulation trajectories with greater detail and over longer follow-up periods. We combine inferences from simulated amyloid trajectories, empirical PET data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), and the sampled iterative local approximation algorithm (SILA) to assess whether amyloid accumulation reaches a physiologic ceiling. We find that SILA reliably detects a ceiling, when present, across a range of simulated scenarios that impose a sigmoid shape. When fit to empirical data from ADNI, however, SILA does not appear to indicate the presence of a ceiling. Thus, we conclude that amyloid trajectories may not reach a physiologic ceiling during the stages of Alzheimer’s disease typically observed while patients remain under follow-up in cohort studies. Fits using SILA indicate that illustrative models of biomarker cascades, while useful tools for conceptualizing and interrogating pathologic processes, may not represent the shapes of amyloid trajectories accurately.

Summary for General Public Amyloid, a protein implicated in Alzheimer’s disease, is thought to reach a plateau in the brain, but methods that estimate how amyloid changes over time suggest it grows unabated. Gantenberg et al. use one such method and simulations to argue that amyloid does not reach a plateau during the typical course of Alzheimer’s.

Competing Interest Statement

JRG has received past salary support from a collaborative research agreement between Sanofi and Brown University for unrelated work involving respiratory syncytial virus. RLJ has received payment as a consultant for GE healthcare, and travel/meeting reimbursement from the Society for Nuclear Medicine and Molecular Imaging, the European Association of Nuclear Medicine, and the Alzheimer's Association. SFA receives salary support from Sanofi to serve as a mentor on an unrelated Brown-Sanofi student fellowship.

Funding Statement

SFA and JRG were funded by NIH NIA R00AG073454. MBH is funded by NIA/NINDS K00AG097172. RLJ and MBH receive funding for NIH/NIA P30AG062422.

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While this project was approved by the Brown Institutional Review Board (IRB), the current analyses used de-identified data from the Alzheimer's Disease Neuroimaging Initiative and are not considered human subjects research. ADNI participants provided informed consent at the time of enrollment, and IRB approval was obtained at each site.

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AbbreviationsAAPOage at amyloid positivity onsetADAlzheimer’s diseaseADNIAlzheimer’s Disease Neuroimaging InitiativeBLSABaltimore Longitudinal Study of AgingPETpositron emission tomographySILAsampled iterative local approximationWRAPWisconsin Registry for Alzheimer’s Prevention