Can integration of Alzheimer's plasma biomarkers with MRI, cardiovascular, genetics, and lifestyle measures improve cognition prediction?

ABSTRACT: There is increasing interest in Alzheimer's disease related plasma biomarkers due to their accessibility and scalability. We hypothesized that integrating plasma biomarkers with other commonly used and available participant data (MRI, cardiovascular factors, lifestyle, genetics) using machine learning (ML) models can improve individual prediction of cognitive outcomes. Further, our goal was to evaluate the heterogeneity of these predictors across different age strata. This longitudinal study included 1185 participants from the Mayo Clinic Study of Aging who had complete plasma analyte work-up at baseline. We used the Quanterix Simoa immunoassay to measure neurofilament light, Aβ_1-42 and Aβ_1-40 (used as Aβ₄₂/Aβ₄₀ ratio), glial fibrillary acidic pr

SUBMITTER: Gebre RK 

PROVIDER: S-EPMC11406552 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature