Depression severity is correlated to the integrity of white matter fiber tracts in late-onset major depression

Psychiatry Res. 2010 Oct 30;184(1):38-48. doi: 10.1016/j.pscychresns.2010.06.008. Epub 2010 Sep 15.

Abstract

Cerebral white matter lesions (WMLs) are believed to play an important role in a subset of major depression (MD). We aimed to describe the impact of WMLs on white matter pathways in MD using diffusion tensor imaging (DTI) and magnetization transfer imaging. As a novel approach, we used DTI tractography to assess pathways intersected by WMLs. We examined 22 patients with late-onset MD and 22 age- and gender-matched controls. Parametric maps of fractional anisotropy (FA), apparent diffusion coefficient (ADC), and magnetization transfer ratio (MTR) were obtained to describe tissue integrity. The association between depression severity and the tract-specific localization of WMLs was analyzed on a voxel-by-voxel basis. We showed a significant positive association between depression severity and fiber tracts intersected by WMLs in the left superior longitudinal fasciculus and the right uncinate fasciculus. In both groups, WMLs had significantly lower FA and MTR, and higher ADC than both the tracts they intersected and the normal-appearing white matter (NAWM). In turn, the tracts intersected by WMLs had significantly lower FA and higher ADC than the NAWM. In conclusion, depression severity correlates with the tract-specific localization of WMLs. WMLs have a pronounced effect on white matter integrity in the pathways they intersect.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age of Onset
  • Aged
  • Anisotropy
  • Brain / pathology*
  • Case-Control Studies
  • Depressive Disorder, Major / pathology*
  • Depressive Disorder, Major / physiopathology
  • Female
  • Humans
  • Image Processing, Computer-Assisted / methods
  • Magnetic Resonance Imaging / methods
  • Male
  • Middle Aged
  • Nerve Fibers, Myelinated / pathology*
  • Psychiatric Status Rating Scales
  • Statistics as Topic
  • Statistics, Nonparametric