Evidence map›Paper›PMID 41837371›Full record

ArticleThe journals of gerontology. Series A, Biological sciences and medical sciences2026

Substituting blood-based biomarkers for imaging measures in Alzheimer's disease studies: implications for sample size and bias.

Sarah F Ackley, Renaud La Joie, Michelle Caunca, Shubhabrata Mukherjee, Seo-Eun Choi, Emily H Trittschuh, Paul K Crane, Eleanor Hayes-Larson, Alzheimer’s Disease Neuroimaging Initiative

Abstract read
In one paragraph

Article in The journals of gerontology. Series A, Biological sciences and medical sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Sarah F AckleyDepartment of Epidemiology, Brown University, Providence, Rhode Island, United States.ORCID 0000-0003-0181-6063
Renaud La JoieEdward and Pearl Fein Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, United States.ORCID 0000-0003-2581-8100
Michelle CauncaNeurovascular Division, Department of Neurology, University of California, San Francisco, San Francisco, California, United States.ORCID 0000-0002-5177-9048
Shubhabrata MukherjeeDepartment of Medicine, University of Washington, Seattle, Washington, United States.
Seo-Eun ChoiDepartment of Medicine, University of Washington, Seattle, Washington, United States.
Emily H TrittschuhGRECC, VA Puget Sound Health Care System, Seattle, Washington, United States.
Paul K CraneDepartment of Medicine, University of Washington, Seattle, Washington, United States.ORCID 0000-0003-4278-7465
Eleanor Hayes-LarsonLeonard Davis School of Gerontology, University of Southern California, Los Angeles, California, United States.ORCID 0000-0001-8299-2389
Alzheimer’s Disease Neuroimaging Initiative

Funding

Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
MVP Data Integration into the ADSP Phenotype Harmonization ConsortiumU24AG074855 · NIA · VANDERBILT UNIVERSITY MEDICAL CENTER · PI CUCCARO, MICHAEL L, HOHMAN, TIMOTHY J · 2021 to 2025
$37.5M
Genetic Architecture of Pure Alzheimer's Disease and Mixed PathologyR01AG082730 · NIA · UNIVERSITY OF WASHINGTON · PI David William Fardo, Shubhabrata Mukherjee · 2023 to 2026
$4.0M
Building an unbiased pooled cohort for the study of lifecourse social and vascular determinants of Alzheimer's Disease and Related DisordersR01AG072681 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GLYMOUR, MEDELLENA MARIA, ZEKI AL HAZZOURI, ADINA · 2021 to 2025
$4.0M
NINDS Research Education Programs for Residents and Fellows in Neurology, Neurosurgery, Neuropathology, Neuroradiology and Emergency Medicine (R25)UE5NS070680 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Scott Andrew Josephson · 2024 to 2026
$2.6M
Mathematical Models of Tau-PET Measures and Cognitive Decline in Alzheimer's Disease Across the LifespanR00AG073454 · NIA · BROWN UNIVERSITY · PI Sarah Ackley · 2024 to 2026
$742k
Effects of lifecourse traumatic stress on late-life cognitive decline, dementia, and neuroimaging biomarkersR00AG075317 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Eleanor Louise Hayes-Larson · 2024 to 2026
$742k
Methods in Longitudinal Dementia (MELODEM) InitiativeR13AG064971 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI Jennifer Weuve · 2019 to 2026
$400k
National Institute on Aging grants R00AG073454National Institute on Aging grants R00AG075317National Institute on Aging grants R01AG072681National Institute on Aging grants R01AG082730National Institute on Aging grants R13AG064971NIA NIH HHS R00 AG073454NIA NIH HHS R00 AG075317NIA NIH HHS R01 AG072681NIA NIH HHS R01 AG082730NIA NIH HHS R13 AG064971NIA NIH HHS U01 AG024904NIA NIH HHS U24 AG074855NIH HHSNINDS NIH HHS UE5 NS070680
6 · The paper itself

Abstract

backgroundBlood-based biomarkers for Alzheimer's disease (AD) pathology are appealing options in large population-based studies due to their low cost, minimal invasiveness, and feasibility of collection in non-clinical settings. Despite these benefits, blood-based biomarkers have lower test-retest reliability than neuroimaging measures like amyloid positron emission tomography (amyloid-PET) Centiloids; trade-offs in power and bias remain unexplored.

methodsWe use data from Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4) studies, which include both amyloid-PET and blood-based measures, to assess differences in statistical power, required sample size, and bias when replacing a neuroimaging measure with a blood-based measure. We use simulations parameterized based on these studies to show potential implications of using plasma p-tau 181 or p-tau 217, blood-based AD biomarkers, in place of Centiloids from amyloid-PET, when the biomarker is either the exposure or the outcome in an analysis of interest.

resultsWe demonstrated that substituting amyloid-PET Centiloids with a blood-based measure of p-tau can substantially reduce power, requiring 1.5-6.5 times the sample size to achieve 80% power compared to amyloid-PET. In addition, using a blood-based biomarker as the exposure can introduce significant regression dilution bias, attenuating estimated associations.

conclusionsWhile blood-based biomarkers are lower cost and easier to collect than neuroimaging measures, their use as proxies for AD pathology may introduce substantial methodological challenges, depending on the p-tau isoform. Consideration of the sample sizes they necessitate and their potential for bias is critical for the design and interpretation of studies employing these biomarkers.

Indexed as

Alzheimer DiseaseBiomarkerstau ProteinsAgedAmyloid beta-PeptidesBiasFemaleHumansMaleNeuroimagingPositron-Emission TomographyReproducibility of ResultsSample SizeAmyloid beta-PeptidesBiomarkerstau ProteinsAmyloid-PETBlood-based biomarkersCentiloidsMeasurement errorRegression dilution bias

Identifiers

PMID41837371
PMCPMC13071402

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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.