Dataset Information

Biomarkers and cognitive endpoints to optimize trials in Alzheimer's disease.

ABSTRACT:

Objective

To find the combination of candidate biomarkers and cognitive endpoints to maximize statistical power and minimize cost of clinical trials of healthy elders at risk for cognitive decline due to Alzheimer's disease.

Methods

Four-hundred and twelve cognitively normal participants were followed over 7 years. Nonlinear methods were used to estimate the longitudinal trajectories of several cognitive outcomes including delayed memory recall, executive function, processing speed, and several cognitive composites by subgroups selected on the basis of biomarkers, including APOE-?4 allele carriers, cerebrospinal fluid biomarkers (A? 42, total tau, and phosphorylated tau), and those with small hippocampi.

Results

Derived cognitive composites combining Alzheimer's Disease Assessment Scale (ADAS)-cog scores with additional delayed memory recall and executive function components captured decline more robustly across biomarker groups than any measure of a single cognitive domain or ADAS-cog alone. Substantial increases in power resulted when including only participants positive for three or more biomarkers in simulations of clinical trials.

Interpretation

Clinical trial power may be improved by selecting participants on the basis of amyloid and neurodegeneration biomarkers and carefully tailoring primary cognitive endpoints to reflect the expected decline specific to these individuals.

SUBMITTER: Insel PS

PROVIDER: S-EPMC4435707 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature

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Publications

Biomarkers and cognitive endpoints to optimize trials in Alzheimer's disease.

Insel Philip S PS Mattsson Niklas N Mackin R Scott RS Kornak John J Nosheny Rachel R Tosun-Turgut Duygu D Donohue Michael C MC Aisen Paul S PS Weiner Michael W MW

Annals of clinical and translational neurology 20150321 5

<h4>Objective</h4>To find the combination of candidate biomarkers and cognitive endpoints to maximize statistical power and minimize cost of clinical trials of healthy elders at risk for cognitive decline due to Alzheimer's disease.<h4>Methods</h4>Four-hundred and twelve cognitively normal participants were followed over 7 years. Nonlinear methods were used to estimate the longitudinal trajectories of several cognitive outcomes including delayed memory recall, executive function, processing spee ...[more]

PMID: 26000325

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Project description:Alzheimer's disease biomarkers are widely accepted as surrogate markers of underlying neuropathological changes. However, few studies have evaluated whether preclinical Alzheimer's disease biomarkers predict Alzheimer's neuropathology at autopsy. We sought to determine whether amyloid PET imaging or CSF biomarkers accurately predict cognitive outcomes and Alzheimer's disease neuropathological findings. This study included 720 participants, 42-91 years of age, who were enrolled in longitudinal studies of memory and aging in the Washington University Knight Alzheimer Disease Research Center and were cognitively normal at baseline, underwent amyloid PET imaging and/or CSF collection within 1 year of baseline clinical assessment, and had subsequent clinical follow-up. Cognitive status was assessed longitudinally by Clinical Dementia Rating®. Biomarker status was assessed using predefined cut-offs for amyloid PET imaging or CSF p-tau181/amyloid-β42. Subsequently, 57 participants died and underwent neuropathologic examination. Alzheimer's disease neuropathological changes were assessed using standard criteria. We assessed the predictive value of Alzheimer's disease biomarker status on progression to cognitive impairment and for presence of Alzheimer's disease neuropathological changes. Among cognitively normal participants with positive biomarkers, 34.4% developed cognitive impairment (Clinical Dementia Rating > 0) as compared to 8.4% of those with negative biomarkers. Cox proportional hazards modelling indicated that preclinical Alzheimer's disease biomarker status, APOE ɛ4 carrier status, polygenic risk score and centred age influenced risk of developing cognitive impairment. Among autopsied participants, 90.9% of biomarker-positive participants and 8.6% of biomarker-negative participants had Alzheimer's disease neuropathological changes. Sensitivity was 87.0%, specificity 94.1%, positive predictive value 90.9% and negative predictive value 91.4% for detection of Alzheimer's disease neuropathological changes by preclinical biomarkers. Single CSF and amyloid PET baseline biomarkers were also predictive of Alzheimer's disease neuropathological changes, as well as Thal phase and Braak stage of pathology at autopsy. Biomarker-negative participants who developed cognitive impairment were more likely to exhibit non-Alzheimer's disease pathology at autopsy. The detection of preclinical Alzheimer's disease biomarkers is strongly predictive of future cognitive impairment and accurately predicts presence of Alzheimer's disease neuropathology at autopsy.

Dataset Information

Biomarkers and cognitive endpoints to optimize trials in Alzheimer's disease.

Objective

Methods

Results

Interpretation

Publications

Biomarkers and cognitive endpoints to optimize trials in Alzheimer's disease.

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