Potential structural trait markers of depression in the form of alterations in the structures of subcortical nuclei and structural covariance network properties

Neuroimage Clin. 2021:32:102871. doi: 10.1016/j.nicl.2021.102871. Epub 2021 Nov 3.

Abstract

It has been proposed recently that major depressive disorder (MDD) could represent an adaptation to conserve energy after the perceived loss of an investment in a vital source, such as group identity, personal assets, or relationships. Energy conserving behaviors associated with MDD may form a persistent marker in brain regions and networks involved in cognition and emotion regulation. In this study, we examined whether subcortical regions and volume-based structural covariance networks (SCNs) have state-independent alterations (trait markers). First-episode drug-naïve currently depressed (cMDD) patients (N = 131), remitted MDD (RD) patients (N = 67), and healthy controls (HCs, N = 235) underwent structural magnetic resonance imaging (MRI). Subcortical gray matter volumes (GMVs) were calculated in FreeSurfer software, and group differences in GMVs and SCN were analyzed. Compared to HCs, major findings were decreased GMVs of left pallidum and pulvinar anterior of thalamus in the cMDD and RD groups, indicative of a trait marker. Relative to HCs, subcortical SCNs of both cMDD and RD patients were found to have reduced small-world-ness and path length, which together may represent a trait-like topological feature of depression. In sum, the left pallidum, left pulvinar anterior of thalamus volumetric alterations may represent trait marker and reduced small-world-ness, path length may represent trait-like topological feature of MDD.

Keywords: Major depressive disorder; Remitted depression; State-independent alteration; Structural covariance network; Subcortical volume.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Brain / diagnostic imaging
  • Cerebral Cortex
  • Depression / diagnostic imaging
  • Depressive Disorder, Major* / diagnostic imaging
  • Gray Matter / diagnostic imaging
  • Humans
  • Magnetic Resonance Imaging