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Related Concept Videos

Amyloid Fibrils03:03

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Amyloid fibrils are aggregates of misfolded proteins.  Under most circumstances, misfolded proteins are either refolded by chaperone proteins or degraded by the proteasome. However, in the case of a mutation or a disease, these proteins can accumulate to form large clusters and often further assemble to form elongated fibers, called fibrils. 
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Alzheimer Disease ll: Pathophysiology01:23

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Alzheimer disease involves structural changes in the brain that begin long before symptoms appear. The most distinctive features are extracellular neuritic plaques and intracellular neurofibrillary tangles.Neuritic plaques form in the cerebral cortex and around blood vessels. These plaques contain a dense core of beta-amyloid (Aβ)—a toxic protein fragment that clumps outside neurons. The core is surrounded by damaged neuronal extensions, as well as reactive astrocytes and...
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Do Amyloid Trajectories Reach a Physiologic Ceiling? Evidence from Iterative Approximation and Simulation.

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Alzheimer's disease models suggest amyloid protein accumulation plateaus. However, analysis of PET data indicates amyloid may not reach a ceiling during typical study follow-up periods.

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Area of Science:

  • Neuroscience
  • Biomarkers
  • Alzheimer's Disease Research

Background:

  • Alzheimer's disease (AD) pathology models often propose amyloid accumulation follows a sigmoid curve, implying deposition rate decreases over time.
  • Longitudinal Positron Emission Tomography (PET) data offer enhanced resolution to examine amyloid deposition trajectories over extended periods.

Purpose of the Study:

  • To assess whether amyloid accumulation in Alzheimer's disease reaches a physiological ceiling.
  • To evaluate the accuracy of current models in representing amyloid accumulation shapes.

Main Methods:

  • Utilized simulated amyloid trajectories and empirical PET data from the Alzheimer's Disease Neuroimaging Initiative (ADNI).
  • Employed the sampled iterative local approximation algorithm (SILA) to detect amyloid accumulation ceilings in simulated and real-world data.

Main Results:

  • SILA successfully identified ceilings in simulated sigmoid amyloid accumulation scenarios.
  • When applied to ADNI empirical data, SILA did not indicate the presence of an amyloid accumulation ceiling.
  • Amyloid trajectories may not reach a physiological ceiling within the typical follow-up duration of Alzheimer's disease cohort studies.

Conclusions:

  • Current illustrative models of biomarker cascades may not accurately reflect the actual shapes of amyloid accumulation trajectories in Alzheimer's disease.
  • Amyloid deposition may continue to increase throughout the stages of Alzheimer's disease observed in cohort studies, rather than plateauing.