TY - JOUR
T1 - Simultaneously evaluating the effect of baseline levels and longitudinal changes in disease biomarkers on cognition in dominantly inherited Alzheimer's disease
AU - the Dominantly Inherited Alzheimer Network (DIAN)
AU - Wang, Guoqiao
AU - Xiong, Chengjie
AU - McDade, Eric M.
AU - Hassenstab, Jason
AU - Aschenbrenner, Andrew J.
AU - Fagan, Anne M.
AU - Benzinger, Tammie L.S.
AU - Gordon, Brian A.
AU - Morris, John C.
AU - Li, Yan
AU - Bateman, Randall J.
N1 - Publisher Copyright:
© 2018 The Authors
PY - 2018/1/1
Y1 - 2018/1/1
N2 - 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.
AB - 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.
KW - Biomarker
KW - Cognition
KW - Dominantly Inherited Alzheimer Network
KW - Joint model
KW - Two-stage method
UR - http://www.scopus.com/inward/record.url?scp=85057767555&partnerID=8YFLogxK
U2 - 10.1016/j.trci.2018.10.009
DO - 10.1016/j.trci.2018.10.009
M3 - Article
C2 - 30569014
AN - SCOPUS:85057767555
SN - 2352-8737
VL - 4
SP - 669
EP - 676
JO - Alzheimer's and Dementia: Translational Research and Clinical Interventions
JF - Alzheimer's and Dementia: Translational Research and Clinical Interventions
ER -