Literature DB >> 26827648

Local and distributed PiB accumulation associated with development of preclinical Alzheimer's disease.

Matthew R Brier1, John E McCarthy2, Tammie L S Benzinger3, Ari Stern2, Yi Su4, Karl A Friedrichsen4, John C Morris5, Beau M Ances6, Andrei G Vlassenko3.   

Abstract

Amyloid-beta plaques are a hallmark of Alzheimer's disease (AD) that can be assessed by amyloid imaging (e.g., Pittsburgh B compound [PiB]) and summarized as a scalar value. Summary values may have clinical utility but are an average over many regions of interest, potentially obscuring important topography. This study investigates the longitudinal evolution of amyloid topographies in cognitively normal older adults who had normal (N = 131) or abnormal (N = 26) PiB scans at baseline. At 3 years follow-up, 16 participants with a previously normal PiB scan had conversion to PiB scans consistent with preclinical AD. We investigated the multivariate relationship (canonical correlation) between baseline and follow-up PiB topographies. Furthermore, we used penalized regression to investigate the added information derived from PiB topography compared to summary measures. PiB accumulation can be local, that is, a topography predicting the same topography in the future, and/or distributed, that is, one topography predicting another. Both local and distributed PiB accumulation was associated with conversion of PiB status. Additionally, elements of the multivariate topography, and not the commonly used summary scalar, correlated with future PiB changes. Consideration of the entire multivariate PiB topography provides additional information regarding the development of amyloid-beta pathology in very early preclinical AD.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Amyloid beta; Canonical correlation; Lasso; Multivariate statistics

Mesh:

Substances:

Year:  2015        PMID: 26827648      PMCID: PMC5279747          DOI: 10.1016/j.neurobiolaging.2015.10.025

Source DB:  PubMed          Journal:  Neurobiol Aging        ISSN: 0197-4580            Impact factor:   4.673


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