Alzheimer's disease biomarkers are crucial to understanding disease pathophysiology, aiding accurate diagnosis and identifying target treatments. Although the number of biomarkers continues to grow, the relative utility and uniqueness of each is poorly understood as prior work has typically calculated serial pairwise relationships on only a handful of markers at a time. The present study assessed the cross-sectional relationships among 27 Alzheimer's disease biomarkers simultaneously and determined their ability to predict meaningful clinical outcomes using machine learning.
View Article and Find Full Text PDFBackground: In MAPT (Multidomain Alzheimer Preventive Trial), a cognitive effect of multidomain intervention (MI) was showed in non-demented subjects with positive amyloid PET. However, screening eligible patients for multidomain intervention by PET is difficult to generalize in real-world settings.
Methods: MAPT study was a 3-year, randomized, placebo-controlled trial followed by a 2-year observational and optional extension.
Objective: In Alzheimer's disease, hyperphosphorylated tau is associated with formation of insoluble paired helical filaments that aggregate as neurofibrillary tau tangles and are associated with neuronal loss and cognitive symptoms. Dual orexin receptor antagonists decrease soluble amyloid-β levels and amyloid plaques in mouse models overexpressing amyloid-β, but have not been reported to affect tau phosphorylation. In this randomized controlled trial, we tested the acute effect of suvorexant, a dual orexin receptor antagonist, on amyloid-β, tau, and phospho-tau.
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