White matter abnormalities in major depression: a tract-based spatial statistics and rumination study

PLoS One. 2012;7(5):e37561. doi: 10.1371/journal.pone.0037561. Epub 2012 May 30.

Abstract

Increasing evidence indicates that major depressive disorder (MDD) is usually accompanied by altered white matter in the prefrontal cortex, the parietal lobe and the limbic system. As a behavioral abnormity of MDD, rumination has been believed to be a substantial indicator of the mental state of the depressive state. So far, however, no report that we are aware of has evaluated the relationship between white matter alterations and the ruminative state. In this study, we first explored the altered white matter using a tract-based spatial statistics (TBSS) method based on diffusion tensor imaging of 19 healthy and 16 depressive subjects. We then investigated correlations between the altered white matter microstructure in the identified altered regions and the severity of ruminations measured by the ruminative response scale. Our results demonstrated altered white matter microstructure in circuits connecting the prefrontal lobe, the parietal lobe and the limbic system (p<0.005, uncorrected), findings which support previous research. More importantly, the result also indicated that a greater alteration in the white matter is associated with a more ruminative state (p<0.05, Bonferroni corrected). The detected abnormalities in the white matter should be interpreted cautiously because of the small sample size in this study. This finding supports the psychometric significance of white matter deficits in MDD.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Affect / physiology
  • Brain / pathology*
  • Brain / physiopathology
  • Cerebrum / pathology
  • Depressive Disorder, Major / pathology*
  • Depressive Disorder, Major / psychology*
  • Female
  • Humans
  • Magnetic Resonance Imaging
  • Male
  • Nerve Net / pathology
  • Nerve Net / physiopathology
  • Neurons / pathology
  • Statistics as Topic