Plasma Aβ42/Aβ40 and phospho‐tau217 concentration ratios increase the accuracy of amyloid PET classification in preclinical Alzheimer's disease

Abstract INTRODUCTION Incorporating blood‐based Alzheimer's disease biomarkers such as tau and amyloid beta (Aβ) into screening algorithms may improve screening efficiency. METHODS Plasma Aβ, phosphorylated tau (p‐tau)181, and p‐tau217 concentration levels from AHEAD 3–45 study participants were measured using mass spectrometry. Tau concentration ratios for each proteoform were calculated to normalize for inter‐individual differences. Receiver operating characteristic (ROC) curve analysis was performed for each biomarker against amyloid positivity, defined by > 20 Centiloids. Mixture of experts analysis assessed the value of including tau concentration ratios into the existing predictive algorithm for amyloid positron emission tomography status. RESULTS The area under the receiver operating curve (AUC) was 0.87 for Aβ42/Aβ40, 0.74 for phosphorylated variant p‐tau181 ratio (p‐tau181/np‐tau181), and 0.92 for phosphorylated variant p‐tau217 ratio (p‐tau217/np‐tau217). The Plasma Predicted Centiloid (PPC), a predictive model including p‐tau217/np‐tau217, Aβ42/Aβ40, age, and apolipoprotein E improved AUC to 0.95. DISCUSSION Including plasma p‐tau217/np‐tau217 along with Aβ42/Aβ40 in predictive algorithms may streamline screening preclinical individuals into anti‐amyloid clinical trials. ClinicalTrials.gov Identifier: NCT04468659 Highlights The addition of plasma phosphorylated variant p‐tau217 ratio (p‐tau217/np‐tau217) significantly improved plasma biomarker algorithms for identifying preclinical amyloid positron emission tomography positivity. Prediction performance at higher NAV Centiloid levels was improved with p‐tau217/np‐tau217. All models generated for this study are incorporated into the Plasma Predicted Centiloid (PPC) app for public use.