Predicting amyloid‐beta pathology in the general population

INTRODUCTION Reliable models to predict amyloid beta (Aβ) positivity in the general aging population are lacking but could become cost‐efficient tools to identify individuals at risk of developing Alzheimer's disease. METHODS We developed Aβ prediction models in the clinical Anti‐Amyloid Treatment in Asymptomatic Alzheimer's (A4) Study (n = 4,119) including a broad range of easily ascertainable predictors (demographics, cognition and daily functioning, health and lifestyle factors). Importantly, we determined the generalizability of our models in the population‐based Rotterdam Study (n = 500). RESULTS The best performing model in the A4 Study (area under the curve [AUC] = 0.73 [0.69–0.76]), including age, apolipoprotein E (APOE) ε4 genotype, family history of dementia, and subjective and objective measures of cognition, walking duration and sleep behavior, was validated in the independent Rotterdam Study with higher accuracy (AUC = 0.85 [0.81–0.89]). Yet, the improvement relative to a model including only age and APOE ε4 was marginal. DISCUSSION Aβ prediction models including inexpensive and non‐invasive measures were successfully applied to a general population–derived sample more representative of typical older non‐demented adults.