Introduction: Blood-based biomarkers of pathophysiological brain amyloid β (Aβ) accumulation, particularly for preclinical target and large-scale interventions, are warranted to effectively enrich Alzheimer's disease clinical trials and management.
Methods: We investigated whether plasma concentrations of the Aβ1-40/Aβ1-42 ratio, assessed using the single-molecule array (Simoa) immunoassay, may predict brain Aβ positron emission tomography status in a large-scale longitudinal monocentric cohort (N = 276) of older individuals with subjective memory complaints. We performed a hypothesis-driven investigation followed by a no-a-priori hypothesis study using machine learning.
Results: The receiver operating characteristic curve and machine learning showed a balanced accuracy of 76.5% and 81%, respectively, for the plasma Aβ1-40/Aβ1-42 ratio. The accuracy is not affected by the apolipoprotein E (APOE) ε4 allele, sex, or age.
Discussion: Our results encourage an independent validation cohort study to confirm the indication that the plasma Aβ1-40/Aβ1-42 ratio, assessed via Simoa, may improve future standard of care and clinical trial design.
Keywords: Alzheimer's disease; Amyloid PET; Classification and regression trees (CART); Machine learning; Plasma amyloid β; Simoa immunoassay; Subjective memory complainers.
Copyright © 2019 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.