Validation of plasma biomarker immunoassay‐based models for predicting brain amyloid positivity in cognitively impaired individuals
Year: 2026
Type: article
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.
Source: Alzheimer s & Dementia
DOI: 10.1002/alz.71946
Authors: Jeremy A. Syrjanen, Daniel J. Figdore, Michael E. Griswold, Heather J. Wiste, Ross A. Dierkhising, Walter K. Kremers, Christian Lachner, Neill R. Graff‐Radford, Gregory S. Day, Jonathan Graff‐Radford, Clifford R. Jack, David S. Knopman, Ronald C. Petersen, Joshua A. Bornhorst, Alicia Algeciras‐Schimnich, for the Alzheimer's Disease Neuroimaging Initiative
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,200
Funders: Foundation for the National Institutes of Health, Alzheimer's Drug Discovery Foundation, Eli Lilly and Company, Biogen, Novartis Pharmaceuticals Corporation, Takeda Pharmaceutical Company, Fujirebio US, Eisai, Servier, IXICO, National Institutes of Health, GE Healthcare, Canadian Institutes of Health Research, National Institute on Aging, National Institute of Biomedical Imaging and Bioengineering
OpenAlex ID: W7225243581
