Evaluating the Presence of a Physiologic Ceiling in Amyloid Trajectories: Insights from the Sampled Iterative Local Approximation (SILA) Algorithm and Simulations

Amyloid trajectories in ADNI aligned based on SILA-estimated age of amyloid-positivity onset suggest an apparent lack of a physiologic ceiling for amyloid. This result is in contrast to prior studies which argue for a ceiling based on differences in amyloid by clinical stage and baseline amyloid level. Additionally, generating data based on influential models of temporal AD biomarker evolution does not produce trajectories consistent with those observed in ADNI. Growing longitudinal data availability and new quantitative tools should allow us to formally evaluate prevailing models of AD biomarker evolution.

Authors

Institutions

Publication Details

Journal
Alzheimer s & Dementia
Published
2025-12-01
DOI
https://doi.org/10.1002/alz70855_106959
Primary Topic
Dementia and Cognitive Impairment Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluating the Presence of a Physiologic Ceiling in Amyloid Trajectories: Insights from the Sampled Iterative Local Approximation (SILA) Algorithm and Simulations

Margo B. Heston, Renaud La Joie, Jason R. Gantenberg, Sarah F. Ackley
Alzheimer s & Dementia
Dementia and Cognitive Impairment Research
article

Evaluating the Presence of a Physiologic Ceiling in Amyloid Trajectories: Insights from the Sampled Iterative Local Approximation (SILA) Algorithm and Simulations

Margo B. Heston, Renaud La Joie, Jason R. Gantenberg, Sarah F. Ackley
article en

Abstract

Amyloid trajectories in ADNI aligned based on SILA-estimated age of amyloid-positivity onset suggest an apparent lack of a physiologic ceiling for amyloid. This result is in contrast to prior studies which argue for a ceiling based on differences in amyloid by clinical stage and baseline amyloid level. Additionally, generating data based on influential models of temporal AD biomarker evolution does not produce trajectories consistent with those observed in ADNI. Growing longitudinal data availability and new quantitative tools should allow us to formally evaluate prevailing models of AD biomarker evolution.

Alzheimer s & DementiaVol. 21(S1)
University of California, San Francisco (US), Brown University (US), University Memory and Aging Center (US)
Openalex Percentile: Top 33%
Dementia and Cognitive Impairment Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.