Danielle V Mayblyum1, J Alex Becker1, Heidi I L Jacobs1,2, Rachel F Buckley3,4,5, Aaron P Schultz6, Jorge Sepulcre1, Justin S Sanchez1, Zoe B Rubinstein1, Samantha R Katz1, Kirsten A Moody1, Patrizia Vannini3, Kathryn V Papp3, Dorene M Rentz3, Julie C Price1, Reisa A Sperling3, Keith A Johnson1,3, Bernard J Hanseeuw1,6,7. 1. Department of Radiology, Massachusetts General Hospital, Gordon Center for Medical Imaging and the Athinoula A. Martinos Center for Biomedical Imaging, Boston, MA 02114, USA. 2. Faculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, the Netherlands. 3. Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Womens Hospital, Harvard Medical School, Boston, MA 02115, USA. 4. The Florey Institute, The University of Melbourne, Victoria, Australia. 5. Melbourne School of Psychological Science, University of Melbourne, Victoria Australia. 6. Department of Neurology, Massachusetts General Hospital, Harvard Medical School. 7. Department of Neurology, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium.
Abstract
OBJECTIVE: To compare how structural MRI, Fluorodeoxyglucose (FDG), and Flortaucipir (FTP) PET signal predict cognitive decline in high-amyloid versus low-amyloid participants with the goal of determining which biomarker combination would result in the highest increase of statistical power for prevention trials. METHODS: In this prospective cohort study, we analyzed data from clinically-normal adults from the Harvard Aging Brain Study with MRI, FDG, FTP, and PiB-PET acquired within a year, and prospective cognitive evaluations over a mean three-year follow-up. We focused analyses on pre-defined regions-of-interest: inferior temporal, isthmus cingulate, hippocampus, and entorhinal cortex. Cognition was assessed using the Preclinical Alzheimer's Cognitive Composite (PACC5). We evaluated the association between biomarkers and cognitive decline using linear-mixed-effect models with random intercepts and slopes, adjusting for demographics. We generated power curves simulating prevention trials. RESULTS: Data from 131 participants [52 females, 73.98±8.29 years old] were analyzed in the study. In separate models, most biomarkers had a closer association with cognitive decline in the high-PiB compared to the low-PiB participants. A backward stepwise regression including all biomarkers demonstrated that only neocortical PiB, entorhinal FTP, and entorhinal FDG were independent predictors of subsequent cognitive decline. Power analyses revealed that using both high-PiB and low entorhinal FDG as inclusion criteria reduced 3-fold the number of participants needed in a hypothetical trial compared to using only high-PiB. DISCUSSION: In preclinical Alzheimer's disease, entorhinal hypometabolism is a strong and independent predictor of subsequent cognitive decline, making FDG a potentially useful biomarker to increase power in clinical trials. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that in people with preclinical Alzheimer's disease, entorhinal hypometabolism identified by FDG-PET is predictive of subsequent cognitive decline.
OBJECTIVE: To compare how structural MRI, Fluorodeoxyglucose (FDG), and Flortaucipir (FTP) PET signal predict cognitive decline in high-amyloid versus low-amyloid participants with the goal of determining which biomarker combination would result in the highest increase of statistical power for prevention trials. METHODS: In this prospective cohort study, we analyzed data from clinically-normal adults from the Harvard Aging Brain Study with MRI, FDG, FTP, and PiB-PET acquired within a year, and prospective cognitive evaluations over a mean three-year follow-up. We focused analyses on pre-defined regions-of-interest: inferior temporal, isthmus cingulate, hippocampus, and entorhinal cortex. Cognition was assessed using the Preclinical Alzheimer's Cognitive Composite (PACC5). We evaluated the association between biomarkers and cognitive decline using linear-mixed-effect models with random intercepts and slopes, adjusting for demographics. We generated power curves simulating prevention trials. RESULTS: Data from 131 participants [52 females, 73.98±8.29 years old] were analyzed in the study. In separate models, most biomarkers had a closer association with cognitive decline in the high-PiB compared to the low-PiB participants. A backward stepwise regression including all biomarkers demonstrated that only neocortical PiB, entorhinal FTP, and entorhinal FDG were independent predictors of subsequent cognitive decline. Power analyses revealed that using both high-PiB and low entorhinal FDG as inclusion criteria reduced 3-fold the number of participants needed in a hypothetical trial compared to using only high-PiB. DISCUSSION: In preclinical Alzheimer's disease, entorhinal hypometabolism is a strong and independent predictor of subsequent cognitive decline, making FDG a potentially useful biomarker to increase power in clinical trials. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that in people with preclinical Alzheimer's disease, entorhinal hypometabolism identified by FDG-PET is predictive of subsequent cognitive decline.
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