Voxel-Based Meta-Analytical Evidence of Structural Disconnectivity in Major Depression and Bipolar Disorder

Abstract

Background: Identification of white matter microstructure differences and similarities between major depression and bipolar disorder is a necessary step to better understand the underlying brain abnormalities in affective disorders and target more effective treatments. However, research has not yet yielded robust conclusions. We report here a meta-analysis of diffusion tensor imaging studies in these conditions.

Methods: A comprehensive literature search was conducted up to 2014 to identify studies comparing fractional anisotropy (FA) between patients and control subjects. Results were combined to identify white matter abnormalities in major depression (736 patients vs. 668 control subjects) and bipolar disorder (536 patients vs. 489 control subjects). Effect size comparison and conjunction analysis allowed identification of similarities and differences between the disorders.

Results: A significant decrease in FA in the genu of the corpus callosum characterized both conditions. The comparison between unipolar and bipolar disorders revealed a greater decrease in FA in the left posterior cingulum in bipolar disorder. Studies that adopted tract-based spatial statistics methodology showed more pronounced reductions in these regions compared with voxel-based analyses.

Conclusions: Major depression and bipolar disorder are characterized by abnormalities in white matter tracts of the genu of the corpus callosum that connect the two hemispheres of the prefrontal cortex implicated in mood regulation. Bipolar disorder was associated with reduced white matter integrity in the left posterior cingulum, which may contribute to cognitive impairment described in this condition. Tract-based spatial statistics may be a more sensitive technique to detect white matter abnormalities in these regions compared with voxel-based analyses.

Keywords: Bipolar; Connectivity; Depression; Diffusion; Imaging; MRI.