Frontiers in Neuroscience (Nov 2023)

Apolipoprotein-E deficiency leads to brain network alteration characterized by diffusion MRI and graph theory

  • Margaret Caroline Stapleton,
  • Margaret Caroline Stapleton,
  • Stefan Paul Koch,
  • Stefan Paul Koch,
  • Stefan Paul Koch,
  • Devin Raine Everaldo Cortes,
  • Devin Raine Everaldo Cortes,
  • Devin Raine Everaldo Cortes,
  • Samuel Wyman,
  • Samuel Wyman,
  • Kristina E. Schwab,
  • Kristina E. Schwab,
  • Susanne Mueller,
  • Susanne Mueller,
  • Susanne Mueller,
  • Christopher Gordon McKennan,
  • Philipp Boehm-Sturm,
  • Philipp Boehm-Sturm,
  • Philipp Boehm-Sturm,
  • Yijen Lin Wu,
  • Yijen Lin Wu

DOI
https://doi.org/10.3389/fnins.2023.1183312
Journal volume & issue
Vol. 17

Abstract

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Late-onset Alzheimer’s disease (LOAD) is a major health concern for senior citizens, characterized by memory loss, confusion, and impaired cognitive abilities. Apolipoprotein-E (ApoE) is a well-known risk factor for LOAD, though exactly how ApoE affects LOAD risks is unknown. We hypothesize that ApoE attenuation of LOAD resiliency or vulnerability has a neurodevelopmental origin via changing brain network architecture. We investigated the brain network structure in adult ApoE knock out (ApoE KO) and wild-type (WT) mice with diffusion tensor imaging (DTI) followed by graph theory to delineate brain network topology. Left and right hemisphere connectivity revealed significant differences in number of connections between the hippocampus, amygdala, caudate putamen and other brain regions. Network topology based on the graph theory of ApoE KO demonstrated decreased functional integration, network efficiency, and network segregation between the hippocampus and amygdala and the rest of the brain, compared to those in WT counterparts. Our data show that brain network developed differently in ApoE KO and WT mice at 5 months of age, especially in the network reflected in the hippocampus, amygdala, and caudate putamen. This indicates that ApoE is involved in brain network development which might modulate LOAD risks via changing brain network structures.

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