Aging related cognitive changes associated with Alzheimer's disease in Down syndrome

Nicholas C Firth, Carla M Startin, Rosalyn Hithersay, Sarah Hamburg, Peter A Wijeratne, Kin Y Mok, John Hardy, Daniel C Alexander, LonDownS Consortium, André Strydom, Nicholas C Firth, Carla M Startin, Rosalyn Hithersay, Sarah Hamburg, Peter A Wijeratne, Kin Y Mok, John Hardy, Daniel C Alexander, LonDownS Consortium, André Strydom

Abstract

Objective: Individuals with Down syndrome (DS) have an extremely high genetic risk for Alzheimer's disease (AD), however, the course of cognitive decline associated with progression to dementia is ill-defined. Data-driven methods can estimate long-term trends from cross-sectional data while adjusting for variability in baseline ability, which complicates dementia assessment in those with DS.

Methods: We applied an event-based model to cognitive test data and informant-rated questionnaire data from 283 adults with DS (the largest study of cognitive functioning in DS to date) to estimate the sequence of cognitive decline and individuals' disease stage.

Results: Decline in tests of memory, sustained attention/motor coordination, and verbal fluency occurred early, demonstrating that AD in DS follows a similar pattern of change to other forms of AD. Later decline was found for informant measures. Using the resulting staging model, we showed that adults with a clinical diagnosis of dementia and those with APOE 3:4 or 4:4 genotype were significantly more likely to be staged later, suggesting that the model is valid.

Interpretation: Our results identify tests of memory and sustained attention may be particularly useful measures to track decline in the preclinical/prodromal stages of AD in DS whereas informant-measures may be useful in later stages (i.e. during conversion into dementia, or postdiagnosis). These results have implications for the selection of outcome measures of treatment trials to delay or prevent cognitive decline due to AD in DS. As clinical diagnoses are generally made late into AD progression, early assessment is essential.

Figures

Figure 1
Figure 1
Positional variance diagrams show the maximum likelihood event sequence. Each entry represents the proportion of samples with each biomarker in each position ranging from 0 in white to 1 in black. (A) Positional variance diagram of the Markov chain Monte Carlo samples generated during fitting of the event‐based model (B) diagram of the samples generated during bootstrapping of the model.
Figure 2
Figure 2
Histogram of event‐based model stages for all participants, colored by age group.
Figure 3
Figure 3
Histogram of event‐based model stages for old adult participants, colored by clinical diagnosis.
Figure 4
Figure 4
Histogram of event‐based model stages colored by APOE genotype. (A) Young adults (B) Old adults.

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