Differences in structural covariance brain networks between behavioral variant frontotemporal dementia and Alzheimer's disease

Anne Hafkemeijer, Christiane Möller, Elise G. P. Dopper, Lize C. Jiskoot, Annette A. van den Berg-Huysmans, John C. van Swieten, Wiesje M. van der Flier, Hugo Vrenken, Yolande A. L. Pijnenburg, Frederik Barkhof, Philip Scheltens, Jeroen van der Grond, Serge A. R. B. Rombouts

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43 Citations (Scopus)

Abstract

Disease‐specific patterns of gray matter atrophy in Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) overlap with distinct structural covariance networks (SCNs) in cognitively healthy controls. This suggests that both types of dementia target specific structural networks. Here, we study SCNs in AD and bvFTD. We used structural magnetic resonance imaging data of 31 AD patients, 24 bvFTD patients, and 30 controls from two centers specialized in dementia. Ten SCNs were defined based on structural covariance of gray matter density using independent component analysis. We studied group differences in SCNs using F‐tests, with Bonferroni corrected t‐tests, adjusted for age, gender, and study center. Associations with cognitive performance were studied using linear regression analyses. Cross‐sectional group differences were found in three SCNs (all P < 0.0025). In bvFTD, we observed decreased anterior cingulate network integrity compared with AD and controls. Patients with AD showed decreased precuneal network integrity compared with bvFTD and controls, and decreased hippocampal network and anterior cingulate network integrity compared with controls. In AD, we found an association between precuneal network integrity and global cognitive performance (P = 0.0043). Our findings show that AD and bvFTD target different SCNs. The comparison of both types of dementia showed decreased precuneal (i.e., default mode) network integrity in AD and decreased anterior cingulate (i.e., salience) network integrity in bvFTD. This confirms the hypothesis that AD and bvFTD have distinct anatomical networks of degeneration and shows that structural covariance gives valuable insights in the understanding of network pathology in dementia.
Original languageEnglish
Pages (from-to)978-988
JournalHuman brain mapping
Volume37
Issue number3
DOIs
Publication statusPublished - Mar 2016

Keywords

  • AD
  • SCN
  • T1 weighted
  • frontotemporal lobar degeneration
  • gray matter
  • independent component analysis
  • magnetic resonance imaging

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