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Basic Science and Pathogenesis.

Sarah F Ackley1, Jason R Gantenberg1, Margo B Heston2

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Alzheimer's disease research suggests amyloid accumulation may not have a plateau, challenging existing models. New analysis methods applied to longitudinal neuroimaging data indicate amyloid levels continue to rise over time.

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Area of Science:

  • Neuroimaging and biomarker analysis in neurodegenerative diseases.
  • Quantitative modeling of disease progression.

Background:

  • Alzheimer's disease (AD) research is advancing with longitudinal amyloid positron emission tomography (PET) neuroimaging.
  • New quantitative methods are enabling empirical determination of amyloid trajectories.
  • Previous models suggesting a physiologic ceiling for amyloid accumulation are being re-evaluated.

Purpose of the Study:

  • To empirically determine amyloid accumulation trajectories using advanced quantitative methods.
  • To investigate the presence or absence of a physiologic ceiling in amyloid burden over time.
  • To compare observed amyloid trajectories with those predicted by existing theoretical models of AD pathogenesis.

Main Methods:

  • Simulated amyloid trajectories using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Jack model.
  • Employed Sampled Iterative Local Approximation (SILA), a nonparametric algorithm, to analyze longitudinal PET data.
  • Incorporated empirically informed stochastic parameters including age at first PET scan and inter-scan intervals.

Main Results:

  • Analysis of ADNI data using SILA indicated an apparent lack of a physiologic ceiling for amyloid accumulation.
  • Simulations assuming a physiologic ceiling generated trajectories qualitatively different from observed ADNI data.
  • High Centiloid density, indicative of approaching a ceiling, was not observed in individuals with high amyloid burden.

Conclusions:

  • Amyloid trajectories in ADNI, aligned by SILA-estimated onset age, suggest no physiologic ceiling.
  • Findings contrast with prior studies that inferred a ceiling based on clinical stage and baseline amyloid levels.
  • Current influential models of AD biomarker evolution do not align with observed longitudinal data, necessitating further evaluation with growing data and new tools.