Evidence map›Paper›PMID 39108526›Full record

ArticlemedRxiv : the preprint server for health sciences2024

The CentiMarker Project: Standardizing Quantitative Alzheimer's disease Fluid Biomarkers for Biologic Interpretation.

Guoqiao Wang, Yan Li, Chengjie Xiong, Yuchen Cao, Suzanne E Schindler, Eric McDade, Kaj Blennow, Oskar Hansson, Jeffrey L Dage, Clifford R Jack and 8 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. 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

5 · Who and what money

Authors and funding

18 authors.

Guoqiao WangDepartment of Neurology, Washington University, School of Medicine, St. Louis, MO, USA.ORCID 0000-0002-6808-8737
Yan LiDepartment of Neurology, Washington University, School of Medicine, St. Louis, MO, USA.
Chengjie XiongDivision of Biostatistics, Washington University, School of Medicine, St. Louis, MO, USA.
Yuchen CaoDepartment of Neurology, Washington University, School of Medicine, St. Louis, MO, USA.
Suzanne E SchindlerDepartment of Neurology, Washington University, School of Medicine, St. Louis, MO, USA.
Eric McDadeDepartment of Neurology, Washington University, School of Medicine, St. Louis, MO, USA.
Kaj BlennowInstitute of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden.
Oskar HanssonClinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden.
Jeffrey L DageDepartment of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA.ORCID 0000-0002-2192-1699
Clifford R JackDepartment of Radiology, Mayo Clinic, Rochester, MN, USA.ORCID 0000-0001-7916-622X
Charlotte E TeunissenNeurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam Neuroscience, Amsterdam, Netherlands.ORCID 0000-0002-4061-0837
Leslie M ShawDepartment of Pathology & Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
Henrik ZetterbergInstitute of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden.
Ibanez LauraDepartment of Neurology, Washington University, School of Medicine, St. Louis, MO, USA.ORCID 0000-0003-2381-7059
Jigyasha TimsinaDepartment of Psychiatry, Washington University, St. Louis, 63110, MO, USA.
Cruchaga CarlosDepartment of Neurology, Washington University, School of Medicine, St. Louis, MO, USA.ORCID 0000-0002-0276-2899
DIAN-TU Study Team
Randall J BatemanDepartment of Neurology, Washington University, School of Medicine, St. Louis, MO, USA.ORCID 0000-0002-7729-1702

Funding

WU INSTITUTE OF CLINICAL AND TRANSLATIONAL SCIENCESUL1TR002345 · NCATS · WASHINGTON UNIVERSITY · PI William G. Powderly · 2017 to 2026
$97.8M
Imaging CoreU19AG032438 · NIA · WASHINGTON UNIVERSITY · PI BATEMAN, RANDALL J · 2010 to 2025
$53.9M
DIAN-TU Next Generation Prevention Trial - Data Request Management SupplementR01AG053267 · NIA · WASHINGTON UNIVERSITY · PI BATEMAN, RANDALL J · 2017 to 2023
$34.9M
Dominantly Inherited Alzheimer's Network Trials Unit - Adaptive Prevention TrialR01AG046179 · NIA · WASHINGTON UNIVERSITY · PI BATEMAN, RANDALL J · 2014 to 2019
$26.6M
DOMINANTLY INHERITED ALZHEIMER NETWORK TRIAL: AN OPPORTUNITY TO PREVENT DEMENTIAU01AG042791 · NIA · WASHINGTON UNIVERSITY · PI BATEMAN, RANDALL J · 2013 to 2018
$8.9M
NCATS NIH HHS UL1 TR002345NIA NIH HHS R01 AG046179NIA NIH HHS R01 AG053267NIA NIH HHS U01 AG042791NIA NIH HHS U19 AG032438
6 · The paper itself

Abstract

Introduction: Biomarkers have been essential to understanding Alzheimer's disease (AD) pathogenesis, pathophysiology, progression, and treatment effects. However, each biomarker measure is a representation of the biological target, the assay used to measure it, and the variance of the assay. Thus, biomarker measures are difficult to compare without standardization, and the units and magnitude of effect relative to the disease are difficult to appreciate, even for experts. To facilitate quantitative comparisons of AD biomarkers in the context of biologic and treatment effects, we propose a biomarker standardization approach between normal ranges and maximum abnormal AD ranges, which we refer to as CentiMarker, similar to the Centiloid approach used in PET. Methods: We developed a standardization scale that creates percentile values ranging from 0 for a normal population to 100 for the most abnormal measures across disease stages. We applied this scale to CSF and plasma biomarkers in autosomal dominant AD, assessing the distribution by estimated years from symptom onset, between biomarkers, and across cohorts. We then validated this approach in a large national sporadic AD cohort. Results: We found the CentiMarker scale provided an easily interpretable metric of disease abnormality. The biologic changes, range, and distribution of several AD fluid biomarkers including amyloid-β, phospho-tau and other biomarkers, were comparable across disease stages in both early onset autosomal dominant and sporadic late onset AD. Discussion: The CentiMarker scale offers a robust and versatile framework for the standardized biological comparison of AD biomarkers. Its broader adoption could facilitate biomarker reporting, allowing for more informed cross-study comparisons and contributing to accelerated therapeutic development.

Identifiers

PMID39108526
PMCPMC11302716

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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.