Validation of plasma biomarker immunoassay‐based models for predicting brain amyloid positivity in cognitively impaired individuals
- 1Mayo Clinic Rochester Minnesota USA
- 2University of Mississippi Medical Center Jackson Mississippi USA
- 3Mayo Clinic Jacksonville Florida USA
Abstract
INTRODUCTION: Combining Alzheimer's disease blood biomarkers may improve prediction of amyloid positivity (A+) compared with single biomarkers.
METHODS: Logistic regression models using plasma phosphorylated tau 217 (p‐tau217), amyloid beta (Aβ) 42, and Aβ40 were developed in cognitively impaired (CI) participants from Mayo Clinic Rochester (MCR) and validated in Alzheimer's Disease Neuroimaging Initiative (ADNI) and Mayo Clinic Florida (MCF) cohorts. Performance was measured by area under the curve (AUC) and Probability of Amyloid Positivity Score (PAPS).
RESULTS: Plasma p‐tau217 alone showed high AUC (95% confidence intervals) across cohorts MCR, 0.928 (0.900–0.953); ADNI, 0.938 (0.915–0.959); MCF, 0.935 (0.893–0.970). Adding Aβ42 to regression models yielded marginal model improvement MCR, 0.940 (0.915–0.963); ADNI, 0.945 (0.922–0.965); MCF, 0.960 (0.925–0.986). Utilization of two cutpoints (≥ 90% sensitivity and specificity), yielded ≤ 10% intermediate results for p‐tau217, and ≤ 8% for p‐tau217+Aβ42. Addition of Aβ40 did not improve models’ performance.
DISCUSSION: An immunoassay‐based p‐tau217 PAPS model accurately predicted amyloid positivity across independent CI cohorts and achieved confirmatory‐test performance with two cutpoints. The added value of Aβ42 was modest and cohort dependent, supporting the potential of use of p‐tau217–based PAPS in clinical workflows.
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BibTeX
@article{syrjanen2026validation,
title = {{Validation of plasma biomarker immunoassay‐based models for predicting brain amyloid positivity in cognitively impaired individuals}},
author = {Jeremy A. Syrjanen and Daniel J. Figdore and Michael E. Griswold and Heather J. Wiste and Ross A. Dierkhising and Walter K. Kremers and Christian Lachner and Neill R. Graff‐Radford and Gregory S. Day and Jonathan Graff‐Radford and Clifford R. Jack and David S. Knopman and Ronald C. Petersen and Joshua A. Bornhorst and Alicia Algeciras‐Schimnich and for the Alzheimer's Disease Neuroimaging Initiative},
journal = {Alzheimer's \& Dementia},
year = {2026},
month = nov,
doi = {10.1002/alz.71946},
url = {https://doi.org/10.1002/alz.71946},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - Validation of plasma biomarker immunoassay‐based models for predicting brain amyloid positivity in cognitively impaired individuals
AU - Jeremy A. Syrjanen
AU - Daniel J. Figdore
AU - Michael E. Griswold
AU - Heather J. Wiste
AU - Ross A. Dierkhising
AU - Walter K. Kremers
AU - Christian Lachner
AU - Neill R. Graff‐Radford
AU - Gregory S. Day
AU - Jonathan Graff‐Radford
AU - Clifford R. Jack
AU - David S. Knopman
AU - Ronald C. Petersen
AU - Joshua A. Bornhorst
AU - Alicia Algeciras‐Schimnich
AU - for the Alzheimer's Disease Neuroimaging Initiative
PY - 2026
DA - 2026/11/04
JO - Alzheimer's & Dementia
DO - 10.1002/alz.71946
UR - https://doi.org/10.1002/alz.71946
AB - INTRODUCTION: Combining Alzheimer's disease blood biomarkers may improve prediction of amyloid positivity (A+) compared with single biomarkers. METHODS: Logistic regression models using plasma phosphorylated tau 217 (p‐tau217), amyloid beta (Aβ) 42, and Aβ40 were developed in cognitively impaired (CI) participants from Mayo Clinic Rochester (MCR) and validated in Alzheimer's Disease Neuroimaging Initiative (ADNI) and Mayo Clinic Florida (MCF) cohorts. Performance was measured by area under the curve (AUC) and Probability of Amyloid Positivity Score (PAPS). RESULTS: Plasma p‐tau217 alone showed high AUC (95% confidence intervals) across cohorts MCR, 0.928 (0.900–0.953); ADNI, 0.938 (0.915–0.959); MCF, 0.935 (0.893–0.970). Adding Aβ42 to regression models yielded marginal model improvement MCR, 0.940 (0.915–0.963); ADNI, 0.945 (0.922–0.965); MCF, 0.960 (0.925–0.986). Utilization of two cutpoints (≥ 90% sensitivity and specificity), yielded ≤ 10% intermediate results for p‐tau217, and ≤ 8% for p‐tau217+Aβ42. Addition of Aβ40 did not improve models’ performance. DISCUSSION: An immunoassay‐based p‐tau217 PAPS model accurately predicted amyloid positivity across independent CI cohorts and achieved confirmatory‐test performance with two cutpoints. The added value of Aβ42 was modest and cohort dependent, supporting the potential of use of p‐tau217–based PAPS in clinical workflows.
SN - 1552-5260
SN - 1552-5279
ER -