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Alzheimers Dement (N Y). 2018 Dec 7;4:669-676. doi: 10.1016/j.trci.2018.10.009. eCollection 2018.

Simultaneously evaluating the effect of baseline levels and longitudinal changes in disease biomarkers on cognition in dominantly inherited Alzheimer's disease.

Author information

1
Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA.
2
Department of Neurology, Washington University School of Medicine, Saint Louis, MO, USA.
3
Department of Radiology, Washington University School of Medicine, Saint Louis, MO, USA.

Abstract

Introduction:

As the role of biomarkers is increasing in Alzheimer's disease (AD) clinical trials, it is critical to use a comprehensive temporal biomarker profile that reflects both baseline and longitudinal assessments to establish a more precise association between the change in biomarkers and change in cognition. Because age of onset of dementia symptoms is highly predictable, and there are relatively few age-related comorbidities, the Dominantly Inherited Alzheimer Network autosomal dominant AD population affords a unique opportunity to investigate these relationships in a well-characterized population.

Methods:

A novel joint statistical model was used to simultaneously evaluate how a comprehensive AD biomarker profile predicts change in cognition using amyloid positron emission tomography (PET), CSF Aβ42, CSF total tau and Ptau181, cortical metabolism using [F-18] fluorodeoxyglucose-PET, and hippocampal volume from participants enrolled in the Dominantly Inherited Alzheimer Network (n = 262) with mean (SD) duration of follow-up of 2.7 (1.2) years.

Results:

Baseline amyloid PET levels and CSF biomarkers were associated with change in cognition in contrast to the rate of change of brain metabolism and hippocampal volume, which predicted change in cognition.

Conclusions:

This study suggests that the baseline value of amyloid PET and CSF Aβ42 measures may be useful for screening participants for AD trials; however, brain hippocampus atrophy and hypometabolism are only useful as repeated longitudinal assessments for tracking cognition and disease progression. This suggests that measures of amyloid plaques predict future cognitive decline, but only longitudinal measures of neurodegeneration correlate with cognitive decline. The novel statistical model used in this study can be easily applied to any pair of outcomes and has potential to be widely used by the AD research community.

KEYWORDS:

Biomarker; Cognition; Dominantly Inherited Alzheimer Network; Joint model; Two-stage method

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