. Amyloid Deposition, Hypometabolism, and Cognitive Trajectories in the ADNI Population. Human Amyloid Imaging Abstract. 2012 Jan 1;

Abstract:

A greater understanding of the relationship between amyloid deposition and cognitive performance is critical for determining the utility of amyloid imaging for identifying individuals likely to progress to AD. We examined associations between amyloid deposition, hypometabolism, and cognitive function in a large sample of ADNI participants (N =25; Normal=102, early MCI =29, MCI =4, AD =0) with recent florbetapir F18 scans. Subjects were categorized as florbetapir +/- based on uptake in cortical grey matter relative to cerebellar grey matter, and using a threshold derived from a previously validated PiB threshold. A concurrent FDG-PET scan was available for most subjects (N =94), and subjects were also categorized as hypometabolic or not (+/-) using a previously determined set of regions of interest and threshold. Longitudinal episodic memory performance was assessed at regular intervals prior to and concurrently with the florbetapir scans (average followup time =.4 years) for a subset of participants (N =55). Proportions of florbetapir+ individuals were comparable to those reported previously for PiB [Normal1/102(30%), EMCI5/129(43%), MCI2/64(66%)], with the exception of a low proportion of florbetapir+ AD patients in this sample [22/30(73%)]. We carried out mixed effects regression to determine whether florbetapir (+/-) and FDG (+/-) status were associated with longitudinal cognitive trajectories. Florbetapir+ normals and MCI subjects had greater episodic memory decline than florbetapir- subjects. When FDG status was added to the model, florbetapir status remained a significant predictor for normals but not for MCI subjects. Our findings indicate that subclinical change in cognitive performance is associated with amyloid deposition and hypometabolism in normals. Tracking changes in cognitive function, particularly in normal and mildly impaired individuals, will help clarify the predictive role of amyloid PET imaging.

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