Lateralized grey matter volume changes in adolescents versus adults with major depression: SDM-PSI meta-analysis

Psychiatry Res Neuroimaging. 2023 Oct:335:111691. doi: 10.1016/j.pscychresns.2023.111691. Epub 2023 Jul 22.

Abstract

The current study is the first meta-analysis to examine grey matter volume (GMV) changes in adolescents and across the lifespan in major depressive disorder (MDD). Seed-based d mapping-with permutation of subject images (SDM-PSI) has advantages over previous coordinate-based meta-analytical methods (CBMA), such as reducing bias (via the MetaNSUE algorithm) and including non-statistically significant unreported effects. SDM-PSI was used to analyze 105 whole-brain GMV voxel-based morphometry (VBM) studies comparing 6,530 individuals with MDD versus 6,821 age-matched healthy controls (HC). A laterality effect was observed in which adults with MDD showed lower GMV than adult HC in left fronto-temporo-parietal structures (superior temporal gyrus, insula, Rolandic operculum, and inferior frontal gyrus). However, these abnormalities were not statistically significant for adolescent MDD versus adolescent HC. Instead, adolescent MDD showed lower GMV than adult MDD in right temporo-parietal structures (angular gyrus and middle temporal gyrus). These regional differences may be used as potential biomarkers to predict and monitor treatment outcomes as well as to choose the most effective treatments in adolescents versus adults. Finally, due to the paucity of youth, older adult, and longitudinal studies, future studies should attempt to replicate these GMV findings and examine whether they correlate with treatment response and illness severity.

Keywords: Age effects; Biomarkers; Magnetic resonance imaging (MRI); Major depressive disorder (MDD); Neurobiology; Voxel-based morphometry (VBM).

Publication types

  • Meta-Analysis

MeSH terms

  • Adolescent
  • Aged
  • Cerebral Cortex
  • Depression
  • Depressive Disorder, Major* / diagnostic imaging
  • Gray Matter* / diagnostic imaging
  • Humans

Substances

  • SDM