Staging of Alzheimer's disease progression in Down syndrome using mixed clinical and plasma biomarker measures with machine learning

TY - JOUR

T1 - Staging of Alzheimer's disease progression in Down syndrome using mixed clinical and plasma biomarker measures with machine learning

AU - Idris, Mina

AU - Saini, Fedal

AU - Ivain, Phoebe

AU - Baksh, R. Asaad

AU - Bianchi, Leda A.

AU - Pape, Sarah E.

AU - Zetterberg, Henrik

AU - Wijeratne, Peter A.

AU - Strydom, André

N1 - Publisher Copyright: © 2025 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.

PY - 2025/7/19

Y1 - 2025/7/19

N2 - INTRODUCTION: Adults with Down syndrome (DS) have a high risk for Alzheimer's disease (AD). Although the sequence of plasma biomarker and cognitive changes in AD in DS is well studied, their related trajectories are not fully characterized. Data-driven methods can estimate disease progression from cross-sectional data. METHODS: In 57 adults with DS and no AD, we used the event-based model to sequence plasma biomarker and cognitive changes in preclinical AD. Generalized additive models assessed the relationship between age and plasma biomarkers. RESULTS: The earliest changes occurred in the amyloid beta 42/40 ratio, followed by memory changes. Later alterations in neurofilament light and tau concentrations preceded executive and visuomotor function changes, with glial fibrillary acidic protein levels changing last. The highest rate of plasma biomarker changes occurred between ages 39 and 52. CONCLUSION: Changes in DS follow a pattern similar to that of sporadic and familial AD. Event-based modeling offers individual-level staging, potentially optimizing diagnosis and clinical trial patient selection. Highlights: The pre-clinical stages of Alzheimer's disease (AD) development in Down syndrome (DS) are not well defined, despite the extremely high prevalence of AD. Better understanding of early AD progression would aid in diagnostics and treatment. Data-driven methods, such as the event-based model, can aid in clarifying the sequence of cognitive and plasma biomarker changes in the early stages of AD while accounting for baseline variability. We find that plasma amyloid beta 42/40 ratio and memory changes precede changes in plasma biomarker levels of neurodegeneration, with changes in executive and visuomotor functions occurring later, before neuroinflammatory marker changes. Combining plasma biomarkers could be a useful measure of preclinical AD for trials, particularly in individuals between 39 and52 years of age.

AB - INTRODUCTION: Adults with Down syndrome (DS) have a high risk for Alzheimer's disease (AD). Although the sequence of plasma biomarker and cognitive changes in AD in DS is well studied, their related trajectories are not fully characterized. Data-driven methods can estimate disease progression from cross-sectional data. METHODS: In 57 adults with DS and no AD, we used the event-based model to sequence plasma biomarker and cognitive changes in preclinical AD. Generalized additive models assessed the relationship between age and plasma biomarkers. RESULTS: The earliest changes occurred in the amyloid beta 42/40 ratio, followed by memory changes. Later alterations in neurofilament light and tau concentrations preceded executive and visuomotor function changes, with glial fibrillary acidic protein levels changing last. The highest rate of plasma biomarker changes occurred between ages 39 and 52. CONCLUSION: Changes in DS follow a pattern similar to that of sporadic and familial AD. Event-based modeling offers individual-level staging, potentially optimizing diagnosis and clinical trial patient selection. Highlights: The pre-clinical stages of Alzheimer's disease (AD) development in Down syndrome (DS) are not well defined, despite the extremely high prevalence of AD. Better understanding of early AD progression would aid in diagnostics and treatment. Data-driven methods, such as the event-based model, can aid in clarifying the sequence of cognitive and plasma biomarker changes in the early stages of AD while accounting for baseline variability. We find that plasma amyloid beta 42/40 ratio and memory changes precede changes in plasma biomarker levels of neurodegeneration, with changes in executive and visuomotor functions occurring later, before neuroinflammatory marker changes. Combining plasma biomarkers could be a useful measure of preclinical AD for trials, particularly in individuals between 39 and52 years of age.

KW - Alzheimer's disease

KW - blood plasma biomarkers

KW - cognition

KW - cognitive decline

KW - dementia

KW - Down syndrome

KW - event-based model

KW - machine learning

KW - memory

KW - trisomy 21

UR - https://www.scopus.com/pages/publications/105011339752

U2 - 10.1002/alz.70446

DO - 10.1002/alz.70446

M3 - Article

C2 - 40684252

AN - SCOPUS:105011339752

SN - 1552-5260

VL - 21

JO - Alzheimer's and Dementia

JF - Alzheimer's and Dementia

IS - 7

M1 - e70446

ER -