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Patterns of Cortical and Subcortical Amyloid Burden across Stages of Preclinical Alzheimer’s Disease

Published online by Cambridge University Press:  01 December 2016

Emily C. Edmonds*
Affiliation:
Department of Psychiatry, University of California San Diego, School of Medicine, La Jolla, California
Katherine J. Bangen
Affiliation:
Department of Psychiatry, University of California San Diego, School of Medicine, La Jolla, California Veterans Affairs San Diego Healthcare System, San Diego, California
Lisa Delano-Wood
Affiliation:
Department of Psychiatry, University of California San Diego, School of Medicine, La Jolla, California Veterans Affairs San Diego Healthcare System, San Diego, California
Daniel A. Nation
Affiliation:
Department of Psychology, University of Southern California, Los Angeles, California
Ansgar J. Furst
Affiliation:
War Related Illness and Injury Study Center (WRIISC), VA Palo Alto Health Care System, Palo Alto, California Depts. of Psychiatry and Behavioral Sciences and Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
David P. Salmon
Affiliation:
Department of Neurosciences, University of California San Diego, School of Medicine, La Jolla, California
Mark W. Bondi
Affiliation:
Department of Psychiatry, University of California San Diego, School of Medicine, La Jolla, California Veterans Affairs San Diego Healthcare System, San Diego, California
*
Correspondence and reprint requests to: Emily C. Edmonds, 3350 La Jolla Village Drive #151B, San Diego, CA 92161. E-mail: ecedmonds@ucsd.edu

Abstract

Objectives: We examined florbetapir positron emission tomography (PET) amyloid scans across stages of preclinical Alzheimer’s disease (AD) in cortical, allocortical, and subcortical regions. Stages were characterized using empirically defined methods. Methods: A total of 312 cognitively normal Alzheimer’s Disease Neuroimaging Initiative participants completed a neuropsychological assessment and florbetapir PET scan. Participants were classified into stages of preclinical AD using (1) a novel approach based on the number of abnormal biomarkers/cognitive markers each individual possessed, and (2) National Institute on Aging and the Alzheimer’s Association (NIA-AA) criteria. Preclinical AD groups were compared to one another and to a mild cognitive impairment (MCI) sample on florbetapir standardized uptake value ratios (SUVRs) in cortical and allocortical/subcortical regions of interest (ROIs). Results: Amyloid deposition increased across stages of preclinical AD in all cortical ROIs, with SUVRs in the later stages reaching levels seen in MCI. Several subcortical areas showed a pattern of results similar to the cortical regions; however, SUVRs in the hippocampus, pallidum, and thalamus largely did not differ across stages of preclinical AD. Conclusions: Substantial amyloid accumulation in cortical areas has already occurred before one meets criteria for a clinical diagnosis. Potential explanations for the unexpected pattern of results in some allocortical/subcortical ROIs include lack of correspondence between (1) cerebrospinal fluid and florbetapir PET measures of amyloid, or between (2) subcortical florbetapir PET SUVRs and underlying neuropathology. Findings support the utility of our novel method for staging preclinical AD. By combining imaging biomarkers with detailed cognitive assessment to better characterize preclinical AD, we can advance our understanding of who is at risk for future progression. (JINS, 2016, 22, 978–990)

Type
Research Articles
Copyright
Copyright © The International Neuropsychological Society 2016 

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Footnotes

*

Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf

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