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

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)