Evidence map›Paper›PMID 41562409›Full record

ArticleBrain : a journal of neurology2026

Plasma pTau 217/β-amyloid 1-42 ratio for enhanced accuracy and reduced uncertainty in detecting amyloid pathology.

Natalya Benina, Luna Buitrago, Francesca I De Simone, Rachel R Radwan, M Craig Miller, Katie Martin, Diana Dickson, Sara Ho, Abhay Moghekar, Marilyn Albert and 10 more

Abstract read
In one paragraph

Article in Brain : a journal of neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Trial
  2. Article
  3. Observational
  4. Multicenter validation of plasma p-tau217/ amyloid beta 1-42 ratio in symptomatic Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
  5. Molecular and statistical weaknesses of the p-tau217/AβJournal of molecular medicine (Berlin, Germany) · 2026
    Review
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

20 authors.

Natalya BeninaFujirebio Diagnostics, Inc., Malvern, PA 19355, USA.
Luna BuitragoFujirebio Diagnostics, Inc., Malvern, PA 19355, USA.
Francesca I De SimoneFujirebio Diagnostics, Inc., Malvern, PA 19355, USA.
Rachel R RadwanFujirebio Diagnostics, Inc., Malvern, PA 19355, USA.
M Craig MillerFujirebio Diagnostics, Inc., Malvern, PA 19355, USA.
Katie MartinFujirebio Diagnostics, Inc., Malvern, PA 19355, USA.
Diana DicksonFujirebio Diagnostics, Inc., Malvern, PA 19355, USA.
Sara HoDepartment of Neurology, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA.
Abhay MoghekarDepartment of Neurology, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA.
Marilyn AlbertDepartment of Neurology, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA.
Niklas Mattsson-CarlgrenClinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund 221 00, Sweden.ORCID 0000-0002-8885-7724
Sebastian PalmqvistClinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund 221 00, Sweden.ORCID 0000-0002-9267-1930
Rik OssenkoppeleClinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund 221 00, Sweden.
Magnus Förnvik JonssonDepartment of Clinical Chemistry and Pharmacology, Skåne University Hospital, Lund 221 85, Sweden.
Oskar HanssonClinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund 221 00, Sweden.ORCID 0000-0001-8467-7286
Erik StomrudClinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund 221 00, Sweden.
Pallavi SachdevEisai Inc., Nutley, NJ 07110, USA.
Hongmei NiuEisai Inc., Nutley, NJ 07110, USA.
David VerbelEisai Inc., Nutley, NJ 07110, USA.
Douglas M HawkinsSchool of Statistics, University of Minnesota, Minneapolis, MN 55455, USA.

Funding

Alzheimer's Association ALZSI-26-1523522Alzheimer's Association #SG-23-1061717Bundy Academy and MultiParkFamily Rönström FRS-0004Family Rönström #FRS-0011Family Rönström FRS-0013GE HealthcareKamprad Foundation #20243058Lilly Research Award ProgramLund UniversityMichael J. Fox Foundation 2022-Projekt0107Michael J. Fox Foundation MJFF-025507NIA NIH HHS #P30AG066507NIA NIH HHS #R01AG083740NIA NIH HHS #U19AG033655Swedish Alzheimer Foundation AF-1011799Swedish Alzheimer Foundation #AF-1011949Swedish Brain Foundation #FO2024-0284Swedish Brain Foundation FO2025-0055
6 · The paper itself

Abstract

Blood biomarkers have the potential to revolutionize Alzheimer's disease diagnosis, offering advantages over CSF and PET due to their accessibility, scalability and cost-effectiveness. This study evaluated the effectiveness of individual plasma biomarkers, such as phosphorylated Tau (pTau) 217, as well as biomarker combinations, with a focus on the pTau 217/β-Amyloid (Aβ) 1-42 ratio to predict amyloid positivity. To improve clinical utility, a dual threshold approach was applied to maximize predictive values and positive likelihood ratios while minimizing the proportion of indeterminate results. Plasma samples from 208 participants (including seven with subjective cognitive decline, 150 with mild cognitive impairment, 12 with Alzheimer's disease dementia and 39 with other cognitive conditions) from three cohorts (BioFINDER2, BIOCARD and MissionAD) were analysed to measure Aβ1-42, Aβ1-40 and pTau217 levels using the Fujirebio LUMIPULSE® G1200 platform. Amyloid status was determined by FDA-cleared PET imaging and/or CSF biomarker ratios. Logistic regression modelling evaluated biomarkers either individually or in combination to identify those that best distinguished amyloid positivity. Clinically applicable thresholds were established through likelihood ratio analysis and further evaluated based on predictive values. When assessing the ability of individual plasma biomarkers to differentiate between amyloid-positive and amyloid-negative participants, plasma pTau217 (P < 0.001) and plasma Aβ1-42 (P = 0.0056) demonstrated significant discriminative power, whereas Aβ1-40 (P = 0.30) did not. Notably, the integration of these biomarkers into the plasma pTau217/Aβ1-42 ratio demonstrated enhanced classification performance (P < 0.001). Using a two-threshold approach based on positive and negative likelihood ratios (PLR/NLR) targets of 14/20, respectively, the plasma pTau217/Aβ1-42 ratio achieved a positive predictive value (PPV) of 94.44% and negative predictive value (NPV) of 94.28%, in the parametric model, comparable to plasma pTau217 alone (PPV: 94.44%, NPV: 94.28%), but yielded fewer indeterminate results (26.5% versus 38.6%). Using a non-parametric model, the plasma ratio achieved a PPV and NPV of 94.62% and 91.78%, respectively, while plasma pTau217 alone achieved 92.41% and 92.86%; the ratio once again reduced the proportion of indeterminate results (20.2% versus 35.1%). The plasma pTau217/Aβ1-42 ratio demonstrated superior performance in identifying amyloid pathology and reduced the frequency of indeterminate results compared to plasma pTau217 alone. These findings support the evaluation of the clinical utility of the plasma pTau217/Aβ1-42 ratio as a tool for identifying amyloid pathology in patients presenting with cognitive complaints.

Indexed as

Alzheimer DiseaseAmyloid beta-PeptidesPeptide Fragmentstau ProteinsAgedAged, 80 and overBiomarkersCognitive DysfunctionCohort StudiesFemaleHumansMaleMiddle AgedPhosphorylationPositron-Emission TomographyUncertaintyAmyloid beta-Peptidesamyloid beta-protein (1-42)BiomarkersMAPT protein, humanPeptide Fragmentstau ProteinsAlzheimer’s diseaseamyloid pathologyblood-based biomarkersFujirebio Lumipulsephosphorylated Tau 217 plasma assayphosphorylated Tau 217/β-Amyloid 1–42 plasma ratio

Identifiers

PMID41562409
PMCPMC13058457

What OpenQuestion holds

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Registered trials

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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.