Srinivasan Vairavan, Nicholas Griffin, David Wilson, Gallen Triana-Baltzer, Victoria Brugada-Ramentol, Elena Vera-Campuzano, Daniel Alcolea, Silvia Fallone, Lucy Mackintosh, Lindsey Mette, James D Doecke, Joanne Robertson, Larry Ward, Gonzalo Sánchez Benavides, Carolina Minguillon, Clàudia Porta Mas, Adrià Tort-Merino, Mircea Balasa, Oriol Grau Rivera, Marc Suárez Calvet, Lewis Taylor, Íñigo Rodríguez-Baz, Javier Arranz, Juan Fortea, Ioannis Tarnanas, Marc Jones, Gayle Wittenberg, Emmanuel Streel, Maria Florencia Iulita
The Altoida NeuroMarker accurately identified MCI (receiver operating characteristic area under the curve [ROC AUC] = 0.89 ± 0.01) and p-tau217 elevation (ROC AUC = 0.77 ± 0.08). Predicted MCI was significantly associated with elevated pTau217 (p = 0.004). When used upstream, the Altoida NeuroMarker ruled out 64.4% of participants (negative predictive value 90.2%), shifting the pre-test probability of AD pathology to 66.6%, and improving the modeled positive predictive value of plasma p-tau217 from 81.7% to 95.3%.
INTRODUCTION: Blood biomarkers like phosphorylated tau (p-tau)217 offer high diagnostic accuracy for Alzheimer's disease (AD) but face implementation challenges in low-prevalence settings. We evaluated the Altoida NeuroMarker Platform as a digital cognitive triage tool before plasma p-tau217 testing.
METHODS: XGBoost models were trained to predict mild cognitive impairment (MCI) and p-tau217 status in 688 individuals across Australia, Spain, and the United States using the Altoida NeuroMarker. p-tau217 status was dichotomized using a threshold of 0.04 pg/mL (LucentAD). We modeled a two-step workflow (Altoida, plasma p-tau217) to enrich downstream biomarker testing, assuming 30% prevalence of AD pathology.
RESULTS: The Altoida NeuroMarker accurately identified MCI (receiver operating characteristic area under the curve [ROC AUC] = 0.89 ± 0.01) and p-tau217 elevation (ROC AUC = 0.77 ± 0.08). Predicted MCI was significantly associated with elevated pTau217 (p = 0.004). When used upstream, the Altoida NeuroMarker ruled out 64.4% of participants (negative predictive value 90.2%), shifting the pre-test probability of AD pathology to 66.6%, and improving the modeled positive predictive value of plasma p-tau217 from 81.7% to 95.3%.
DISCUSSION: This workflow outlines a scalable path to enrich blood-based biomarker testing after digital cognitive screening.