Spatial Patterning of Tissue Volume Loss in Schizophrenia Reflects Brain Network Architecture

Biol Psychiatry. 2020 Apr 15;87(8):727-735. doi: 10.1016/j.biopsych.2019.09.031. Epub 2019 Oct 24.

Abstract

Background: There is growing recognition that connectome architecture shapes cortical and subcortical gray matter atrophy across a spectrum of neurological and psychiatric diseases. Whether connectivity contributes to tissue volume loss in schizophrenia in the same manner remains unknown.

Methods: Here, we relate tissue volume loss in patients with schizophrenia to patterns of structural and functional connectivity. Gray matter deformation was estimated in a sample of 133 individuals with chronic schizophrenia (48 women, mean age 34.7 ± 12.9 years) and 113 control subjects (64 women, mean age 23.5 ± 8.4 years). Deformation-based morphometry was used to estimate cortical and subcortical gray matter deformation from T1-weighted magnetic resonance images. Structural and functional connectivity patterns were derived from an independent sample of 70 healthy participants using diffusion spectrum imaging and resting-state functional magnetic resonance imaging.

Results: We found that regional deformation is correlated with the deformation of structurally and functionally connected neighbors. Distributed deformation patterns are circumscribed by specific functional systems (the ventral attention network) and cytoarchitectonic classes (limbic class), with an epicenter in the anterior cingulate cortex.

Conclusions: Altogether, the present study demonstrates that brain tissue volume loss in schizophrenia is conditioned by structural and functional connectivity, accounting for 25% to 35% of regional variance in deformation.

Keywords: Anterior cingulate; Connectome; Disease epicenter; Intrinsic networks; Schizophrenia; Ventral attention network.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Brain / diagnostic imaging
  • Connectome*
  • Female
  • Gray Matter / diagnostic imaging
  • Humans
  • Magnetic Resonance Imaging
  • Middle Aged
  • Schizophrenia* / diagnostic imaging
  • Young Adult

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