Evidence map›Paper›PMID 41959766›Full record

ArticlemedRxiv : the preprint server for health sciences2026

Estimating tau onset age from tau PET imaging in two longitudinal cohorts using sampled iterative local approximation.

Tobey J Betthauser, Jordan P Teague, Hailey Bruzzone, Margo B Heston, William Coath, Jacob D Morse, Elena L Ruiz de Chavez, Finnuella J Carey, Ruvini Navaratna, Karly A Cody and 1 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Tobey J BetthauserWisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.ORCID 0000-0001-8856-1352
Jordan P TeagueWisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
Hailey BruzzoneWisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
Margo B HestonWisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
William CoathWisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
Jacob D MorseWisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
Elena L Ruiz de ChavezWisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
Finnuella J CareyWisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
Ruvini NavaratnaWisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
Karly A CodyDepartment of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA.
Rebecca E LanghoughWisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.

Funding

Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
Wisconsin Alzheimer's Disease Research CenterP30AG062715 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI Dorothy Farrar Edwards · 2019 to 2026
$34.5M
Multi-cohort study of factors that influence Alzheimer's disease biomarker and dementia timingR01AG080766 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI TOBEY JAMES BETTHAUSER · 2023 to 2026
$3.1M
High Performance Gradient System for Advanced Neuroimaging ResearchS10OD030415 · OD · UNIVERSITY OF WISCONSIN-MADISON · PI ALEXANDER, ANDREW L · 2021 to 2021
$2.0M
The Disadvantage Exposome as a Driver of Alzheimer’s Disease PathologyF99NS130922 · NINDS · UNIVERSITY OF WISCONSIN-MADISON · PI HESTON, MARGO · 2022 to 2022
$48k
NIA NIH HHS P30 AG062715NIA NIH HHS R01 AG080766NIA NIH HHS U01 AG024904NIH HHS S10 OD030415NINDS NIH HHS F99 NS130922
6 · The paper itself

Abstract

Understanding the time course of Alzheimer's disease biomarkers of amyloid and tau pathology and their temporal relation to clinical symptoms is key to identifying optimal windows for disease intervention and planning future drug trials. The goal of this work was to determine the extent to which Sampled Iterative Local Approximation (SILA), an algorithm extensively validated for amyloid PET, is capable of modeling longitudinal tau (T) PET trajectories and estimating person-level tau positivity onset ages in two commonly analyzed brain regions and two tracers from two different cohorts. Methods: 385 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI; mean (SD) age = 73.4 (7.3) years) with longitudinal flortaucipir tau PET and 288 participants from the Wisconsin Registry for Alzheimer's Prevention and Wisconsin Alzheimer's Disease Research Center (collectively referred to as WISC; mean (SD) age = 67.4 (6.7) years) with longitudinal MK-6240 tau PET were included in the study. Standard uptake value ratios (SUVRs) in the entorhinal cortex and a meta-temporal ROI were modeled with SILA separately, for each cohort and region. Forward and backward SUVR and T+/- prediction were characterized with ten-fold cross-validation and in-sample validation techniques. Accuracy of estimated T+ onset ages (ETOA) was characterized in T- to T+ converters. Differences in ETOA were tested between Results: SILA was able to accurately estimate retrospective change in tau SUVR in the meta-temporal region regardless of age, sex, Conclusions: Our results suggest SILA can be used to accurately model longitudinal tau PET trajectories and retrospectively estimate individual T+ onset ages in the meta-temporal region. The accuracy of SILA time estimates in entorhinal cortex worsened amongst those with dementia in ADNI suggesting entorhinal cortex may only be suitable for studying the temporal progression of tau during the preclinical time frame.

Indexed as

Alzheimer’smulticohortPETSILATautemporal modeling

Identifiers

PMID41959766
PMCPMC13060405

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.