• Wei Peng, Ziqi Chen, Li Yin, Zhiyun Jia, and Qiyong Gong.
• Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, PR China.
• J Affect Disord. 2016 Jul 15; 199: 114-23.

BackgroundBecause brain morphological abnormalities in major depressive disorder (MDD) may be modulated by medication and episodes, previous meta-analyses of voxel-based morphometry (VBM) studies therefore have been biased for including medicated patients or medication-free patients who had ever received drugs, as well as patients with different episodes. We sought to identify the essential morphological features without the interference of medication and episodes in MDD.MethodsSeed-based d Mapping was applied to analyze the gray matter differences between all first episode (FE), medication-naive MDD patients and healthy controls. Subgroup meta-analyses and meta-regression were used to explore the effects of methodology, demographics and clinical characteristics.ResultsWe identified 10 studies comprising 329 FE, medication-naive MDD patients and 340 healthy controls. Gray matter volumes were increased in the bilateral thalamus, cuneus, left paracentral lobule and medial superior frontal gyrus, and decreased in the right dorsolateral superior frontal gyrus, left insula and middle frontal gyrus in patients. Decreased volume in the right inferior temporal gyrus was only observed in patients with short illness duration and studies with threshold corrections. Moreover, there were different results between 3.0T MRI and 1.5T MRI studies. Meta-regression analyses revealed that mean age and the percentage of female patients were not significantly correlated with gray matter changes.LimitationsThere are heterogeneities in demographics, clinical features and analyzing methods of selected studies.ConclusionsThe present meta-analysis revealed that structural abnormalities in the fronto-limbic networks are the essential characteristics in MDD and could contribute to the high risk of suicide in patients.Copyright © 2016 Elsevier B.V. All rights reserved.

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