Alzheimer’s Research & Therapy (Jan 2020)

The effect of amyloid deposition on longitudinal resting-state functional connectivity in cognitively normal older adults

  • Chemin Lin,
  • Maria Ly,
  • Helmet T. Karim,
  • Wenjing Wei,
  • Beth E. Snitz,
  • William E. Klunk,
  • Howard J. Aizenstein

DOI
https://doi.org/10.1186/s13195-019-0573-1
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 10

Abstract

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Abstract Background Pathological processes contributing to Alzheimer’s disease begin decades prior to the onset of clinical symptoms. There is significant variation in cognitive changes in the presence of pathology, functional connectivity may be a marker of compensation to amyloid; however, this is not well understood. Methods We recruited 64 cognitively normal older adults who underwent neuropsychological testing and biannual magnetic resonance imaging (MRI), amyloid imaging with Pittsburgh compound B (PiB)-PET, and glucose metabolism (FDG)-PET imaging for up to 6 years. Resting-state MRI was used to estimate connectivity of seven canonical neural networks using template-based rotation. Using voxel-wise paired t-tests, we identified neural networks that displayed significant changes in connectivity across time. We investigated associations among amyloid and longitudinal changes in connectivity and cognitive function by domains. Results Left middle frontal gyrus connectivity within the memory encoding network increased over time, but the rate of change was lower with greater amyloid. This was no longer significant in an analysis where we limited the sample to only those with two time points. We found limited decline in cognitive domains overall. Greater functional connectivity was associated with better attention/processing speed and executive function (independent of time) in those with lower amyloid but was associated with worse function with greater amyloid. Conclusions Increased functional connectivity serves to preserve cognitive function in normal aging and may fail in the presence of pathology consistent with compensatory models.

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