Structural covariance pattern abnormalities of insula in major depressive disorder: A CAN-BIND study report Academic Article uri icon

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abstract

  • BACKGROUND AND METHODS: Investigation of the insula may inform understanding of the etiopathogenesis of major depressive disorder (MDD). In the present study, we introduced a novel gray matter volume (GMV) based structural covariance technique, and applied it to a multi-centre study of insular subregions of 157 patients with MDD and 93 healthy controls from the Canadian Biomarker Integration Network in Depression (CAN-BIND, https://www.canbind.ca/). Specifically, we divided the unilateral insula into three subregions, and investigated their coupling with whole-brain GMV-based structural brain networks (SBNs). We compared between-group difference of the structural coupling patterns between the insular subregions and SBNs. RESULTS: The insula was divided into three subregions, including an anterior one, a superior-posterior one and an inferior-posterior one. In the comparison between MDD patients and controls we found that patients' right anterior insula showed increased inter-network coupling with the default mode network, and it showed decreased inter-network coupling with the central executive network; whereas patients' right ventral-posterior insula showed decreased inter-network coupling with the default mode network, and it showed increased inter-network coupling with the central executive network. We also demonstrated that patients' loading parameters of the right ventral-posterior insular structural covariance negatively correlated with their suicidal ideation scores; and controls' loading parameters of the right ventral-posterior insular structural covariance positively correlated with their motor and psychomotor speed scores, whereas these phenomena were not found in patients. Additionally, we did not find significant inter-network coupling between the whole-brain SBNs, including salience network, default mode network, and central executive network. CONCLUSIONS: Our work proposed a novel technique to investigate the structural covariance coupling between large-scale structural covariance networks, and provided further evidence that MDD is a system-level disorder that shows disrupted structural coupling between brain networks.

authors

  • Ge, Ruiyang
  • Hassel, Stefanie
  • Arnott, Stephen R
  • Davis, Andrew D
  • Harris, Jacqueline K
  • Zamyadi, Mojdeh
  • Milev, Roumen
  • Frey, Benicio
  • Strother, Stephen C
  • Müller, Daniel J
  • Rotzinger, Susan
  • MacQueen, Glenda M
  • Kennedy, Sidney H
  • Lam, Raymond W
  • Vila-Rodriguez, Fidel

publication date

  • December 2020