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Posts Tagged ‘University of Pennsylvania’


Reporter: Aviva Lev-Ari, PhD, RN

MRI cortical thickness biomarker predicts AD-like CSF and cognitive decline in normal adults

Bradford C. Dickerson, MD and David A. Wolk, MD On behalf of the Alzheimer’s Disease Neuroimaging Initiative

Author Affiliations

From the Frontotemporal Dementia Unit, Department of Neurology, Massachusetts Alzheimer’s Disease Research Center, and Athinoula A. Martinos Center for Biomedical Imaging (B.C.D.), Massachusetts General Hospital and Harvard Medical School, Boston; and Department of Neurology, Alzheimer’s Disease Core Center, and Penn Memory Center (D.A.W.), University of Pennsylvania, Philadelphia.

Correspondence & reprint requests to Dr. Dickerson: bradd@nmr.mgh.harvard.edu

ABSTRACT

Objective: New preclinical Alzheimer disease (AD) diagnostic criteria have been developed using biomarkers in cognitively normal (CN) adults. We implemented these criteria using an MRI biomarker previously associated with AD dementia, testing the hypothesis that individuals at high risk for preclinical AD would be at elevated risk for cognitive decline.

Methods: The Alzheimer’s Disease Neuroimaging Initiative database was interrogated for CN individuals. MRI data were processed using a published set of a priori regions of interest to derive a single measure known as the AD signature (ADsig). Each individual was classified as ADsig-low (≥1 SD below the mean: high risk for preclinical AD), ADsig-average (within 1 SD of mean), or ADsig-high (≥1 SD above mean). A 3-year cognitive decline outcome was defined a priori using change in Clinical Dementia Rating sum of boxes and selected neuropsychological measures.

Results: Individuals at high risk for preclinical AD were more likely to experience cognitive decline, which developed in 21% compared with 7% of ADsig-average and 0% of ADsig-high groups (p = 0.03). Logistic regression demonstrated that every 1 SD of cortical thinning was associated with a nearly tripled risk of cognitive decline (p = 0.02). Of those for whom baseline CSF data were available, 60% of the high risk for preclinical AD group had CSF characteristics consistent with AD while 36% of the ADsig-average and 19% of the ADsig-high groups had such CSF characteristics (p = 0.1).

Conclusions: This approach to the detection of individuals at high risk for preclinical AD—identified in single CN individuals using this quantitative ADsig MRI biomarker—may provide investigators with a population enriched for AD pathobiology and with a relatively high likelihood of imminent cognitive decline consistent with prodromal AD.

 

Copyright © 2011 by AAN Enterprises, Inc.

http://www.neurology.org/content/early/2011/12/21/WNL.0b013e31823efc6c.abstract

 

 

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