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Preserved Structural Network Organization Mediates Pathology Spread in Alzheimer's Disease Spectrum Despite Loss of White Matter Tract Integrity

  • Author(s): Powell, F
  • Tosun, D
  • Sadeghi, R
  • Weiner, M
  • Raj, A
  • Initia, ADN
  • et al.

Published Web Location

https://content.iospress.com/articles/journal-of-alzheimers-disease/jad170798
No data is associated with this publication.
Abstract

Models of Alzheimer's disease (AD) hypothesize stereotyped progression via white matter (WM) fiber connections, most likely via trans-synaptic transmission of toxic proteins along neuronal pathways. An important question in the field is whether and how organization of fiber pathways is affected by disease. It remains unknown whether fibers act as conduits of degenerative pathologies, or if they also degenerate with the gray matter network. This work uses graph theoretic modeling in a longitudinal design to investigate the impact of WM network organization on AD pathology spread. We hypothesize if altered WM network organization mediates disease progression, then a previously published network diffusion model will yield higher prediction accuracy using subject-specific connectomes in place of a healthy template connectome. Neuroimaging data in 124 subjects from ADNI were assessed. Graph topology metrics show preserved network organization in patients compared to controls. Using a published diffusion model, we further probe the effect of network alterations on degeneration spread in AD. We show that choice of connectome does not significantly impact the model's predictive ability. These results suggest that, despite measurable changes in integrity of specific fiber tracts, WM network organization in AD is preserved. Further, there is no difference in the mediation of putative pathology spread between healthy and AD-impaired networks. This conclusion is somewhat at variance with previous results, which report global topological disturbances in AD. Our data indicates the combined effect of edge thresholding, binarization, and inclusion of subcortical regions to network graphs may be responsible for previously reported effects.

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