4.6 Article

Voxelwise meta-analysis of gray matter reduction in major depressive disorder

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.pnpbp.2011.09.014

关键词

Activation likelihood estimation; Genome scan meta-analysis; Major depressive disorder; Meta-analysis; Voxel-based morphometry

资金

  1. National Natural Science Foundation of China [81030027, 30900362]
  2. National Basic Research Program of China (973 Program) [2007CB512302/5]
  3. Royal Society [2008/R3NSFC]

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Background: Voxel-based morphometry (VBM) has been widely used in studies of major depressive disorder (MDD) and has provided cumulative evidence of gray matter abnormalities in patients relative to controls. Thus we performed a meta-analysis to integrate the reported studies to determine the consistent gray matter alterations in MDD. Methods: A systematic search was conducted to identify VBM studies which contrasted MDD patients against a comparison group. The coordinates of gray matter change across studies were meta-analyzed using the activation likelihood estimation (ALE) method hybridized with the rank-based Genome Scan Meta-Analysis (GSMA) to quantitatively estimate regional gray matter reductions in MDD. Results: A total of 20 VBM studies comparing 543 major depressive patients with 750 healthy control subjects were included. Consistent gray matter reductions in all MDD patients relative to healthy controls were identified in the bilateral anterior cingulate cortex (ACC), right middle and inferior frontal gyrus, right hippocampus and left thalamus. Conclusions: Meta-analysis of all primary VBM studies indicates that significant gray matter reductions in MDD are localized in a distributed neural network which includes frontal, limbic and thalamic regions. Future studies will benefit from the use of a longitudinal approach to examine anatomical and functional abnormalities within this network and their relationship to clinical profile, particularly in first-episode and drug-naive MDD patients. (C) 2011 Elsevier Inc. All rights reserved.

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