Evidence map›Paper›PMID 36575454›Full record

ReviewAlzheimer's research & therapy2022

The performance of plasma amyloid beta measurements in identifying amyloid plaques in Alzheimer's disease: a literature review.

Abby L Brand, Paige E Lawler, James G Bollinger, Yan Li, Suzanne E Schindler, Melody Li, Samir Lopez, Vitaliy Ovod, Akinori Nakamura, Leslie M Shaw and 3 more

Open access · goldAbstract readReview
In one paragraph

Review in Alzheimer's research & therapy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
88citing papers in PubMed, 3 pooled it
15.9field-weighted citation impact, top 1% of its field
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

88 citing papers in PubMed, 3 syntheses or guidelines pooled it, 143 citations in OpenAlex.

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  7. Purpose in life and blood-based biomarkers of brain health.The journals of gerontology. Series B, Psychological sciences and social sciences · 2026
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28 more citing papers are in PubMed but not listed here.

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

13 authors at 5 institutions in 4 countries.

Abby L BrandDepartment of Neurology, Washington University School of Medicine, St. Louis, MO, USA.
Paige E LawlerDepartment of Neurology, Washington University School of Medicine, St. Louis, MO, USA.
James G BollingerDepartment of Neurology, Washington University School of Medicine, St. Louis, MO, USA.
Yan LiDepartment 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.
Melody LiDepartment of Neurology, Washington University School of Medicine, St. Louis, MO, USA.
Samir LopezDepartment of Neurology, Washington University School of Medicine, St. Louis, MO, USA.
Vitaliy OvodDepartment of Neurology, Washington University School of Medicine, St. Louis, MO, USA.
Akinori NakamuraDepartment of Biomarker Research, National Center for Geriatrics and Gerontology, Obu, Japan.
Leslie M ShawDepartment of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Henrik ZetterbergDepartment of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.
Oskar HanssonClinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden.
Randall J BatemanDepartment of Neurology, Washington University School of Medicine, St. Louis, MO, USA. batemanr@wustl.edu.
Washington University in St. Louis · USNational Center for Geriatrics and Gerontology · JPSkåne University Hospital · SEUniversity College London · GBUniversity of Pennsylvania · US

Funding

Project 1U19AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI William J. Jagust · 2016 to 2026
$226.7M
Research Education ComponentP30AG072979 · NIA · UNIVERSITY OF PENNSYLVANIA · PI DAVID A WOLK · 2021 to 2026
$24.8M
Blood amyloid-beta relationship with amyloid plaques and CSF amyloid-betaRF1AG061900 · NIA · WASHINGTON UNIVERSITY · PI BATEMAN, RANDALL J · 2019 to 2020
$6.9M
Staging Alzheimer disease with blood-based biomarkersR01AG070941 · NIA · WASHINGTON UNIVERSITY · PI SCHINDLER, SUZANNE ELIZABETH · 2021 to 2025
$4.3M
Predicting populations at-risk of developing pathological hoardingR01MH117114 · NIMH · UNIVERSITY OF FLORIDA · PI MACKIN, ROBERT SCOTT, MATHEWS, CAROL A · 2018 to 2022
$3.7M
CNS TAU KINETICS IN ALZHEIMER'S DISEASER01NS095773 · NINDS · WASHINGTON UNIVERSITY · PI BATEMAN, RANDALL J · 2016 to 2020
$3.6M
Characterization of Neurofilament Light Chain in Alzheimer's Disease and Other Neurodegenerative DisordersR21AG067559 · NIA · WASHINGTON UNIVERSITY · PI BATEMAN, RANDALL J · 2020 to 2020
$433k
NIA NIH HHS P30 AG072979NIA NIH HHS R01 AG070941NIA NIH HHS R21 AG067559NIA NIH HHS RF1 AG061900NIA NIH HHS U19 AG024904NIMH NIH HHS R01 MH117114NINDS NIH HHS R01 NS095773
6 · The paper itself

Abstract

The extracellular buildup of amyloid beta (Aβ) plaques in the brain is a hallmark of Alzheimer's disease (AD). Detection of Aβ pathology is essential for AD diagnosis and for identifying and recruiting research participants for clinical trials evaluating disease-modifying therapies. Currently, AD diagnoses are usually made by clinical assessments, although detection of AD pathology with positron emission tomography (PET) scans or cerebrospinal fluid (CSF) analysis can be used by specialty clinics. These measures of Aβ aggregation, e.g. plaques, protofibrils, and oligomers, are medically invasive and often only available at specialized medical centers or not covered by medical insurance, and PET scans are costly. Therefore, a major goal in recent years has been to identify blood-based biomarkers that can accurately detect AD pathology with cost-effective, minimally invasive procedures.To assess the performance of plasma Aβ assays in predicting amyloid burden in the central nervous system (CNS), this review compares twenty-one different manuscripts that used measurements of 42 and 40 amino acid-long Aβ (Aβ42 and Aβ40) in plasma to predict CNS amyloid status. Methodologies that quantitate Aβ42 and 40 peptides in blood via immunoassay or immunoprecipitation-mass spectrometry (IP-MS) were considered, and their ability to distinguish participants with amyloidosis compared to amyloid PET and CSF Aβ measures as reference standards was evaluated. Recent studies indicate that some IP-MS assays perform well in accurately and precisely measuring Aβ and detecting brain amyloid aggregates.

Indexed as

Alzheimer DiseaseAmyloidAmyloid beta-PeptidesAmyloidogenic ProteinsBiomarkersBrainHumansPeptide FragmentsPlaque, AmyloidPositron-Emission TomographyAmyloidAmyloid beta-PeptidesAmyloidogenic ProteinsBiomarkersPeptide FragmentsAlzheimer’s diseaseAmyloid betaAmyloidosisBiomarkerBloodPlasma

Identifiers

PMID36575454
PMCPMC9793600
OpenAlexW4312200695

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.