Abstract

There is evidence that disruption of white matter (WM) microstructure is an early event in the course of Alzheimer's disease (AD). However, the neurobiological bases of WM microstructural declines in presymptomatic AD are unknown. In the present study we address this issue using a multimodal imaging approach to the study of presymptomatic AD. Participants were 37 high-risk (both family history of dementia and one or more APOE4 alleles) women and 20 low-risk (neither family history nor APOE4) women. Groups were matched for age, education, neuropsychological performance, and vascular factors that could affect white matter. Whole-brain analyses of diffusion tensor imaging data [including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (DA) and radial diffusivity (DR)] and volumetric comparisons of medial temporal lobe (MTL) structures were conducted. Results indicated equivalent entorhinal cortex and hippocampal volumes between risk groups. Nevertheless, the high risk group showed decreased microstructural integrity in WM tracts with direct and secondary connections to the MTL. The predominant alteration in WM integrity in the high AD-risk group was decreased FA not solely driven by either DA or DR changes alone in regions where no MD changes were observed. A second pattern observed in a smaller number of regions involved decreased FA and increased DR. These results suggest that disconnection of MTL-neocortical fiber pathways represents a very early event in the course of AD and suggest that demyelination may represent one contributing mechanism.

Document Type

Article

Publication Date

10-1-2010

Notes/Citation Information

Published in NeuroImage, v. 52, issue 4, p. 1487–1494.

© 2010 Elsevier Inc. All rights reserved.

This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/

Digital Object Identifier (DOI)

http://dx.doi.org/10.1016/j.neuroimage.2010.05.036

Funding Information

This study was supported by NINDS Grant R01 NS-36660, NIA Grant R01 AG033036 and NSF Grant BCS-0814302.

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