1. Regional gray matter deficits in alcohol dependence: A meta-analysis of voxel-based morphometry studies
- Author
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YingLing Zhu, HaiCun Shi, JianGuo Zhong, PingLei Pan, ZhenYu Dai, and PeiRong Xiao
- Subjects
Cerebral Cortex ,Pharmacology ,Brain Mapping ,Alcohol dependence ,Voxel-based morphometry ,Toxicology ,medicine.disease ,Gyrus Cinguli ,Alcoholism ,Psychiatry and Mental health ,medicine.anatomical_structure ,Atrophy ,Meta-analysis ,Posterior cingulate ,Signed differential mapping ,medicine ,Humans ,Pharmacology (medical) ,Gray Matter ,Nerve Net ,Prefrontal cortex ,Psychology ,Neuroscience ,Anterior cingulate cortex - Abstract
Background Many studies have revealed a widespread pattern of gray matter (GM) atrophy by using voxel-based morphometry (VBM) studies involving the pathophysiology of alcohol dependence. However, the spatial localization of GM abnormalities reported in previous studies is heterogeneous. Here, we aimed to investigate the concurrence across VBM studies to help clarify the structural abnormalities underpinning this condition. Methods A systematic search from January, 2000 to November, 2014 was performed to identify VBM studies that compared alcohol dependent patients and healthy controls. A quantitative meta-analysis of whole-brain VBM studies to estimate regional GM abnormalities in alcohol dependent patients was performed using the Anisotropic Effect Size version of the Signed Differential Mapping (AES-SDM) software package. Results Nine studies consisting of 296 alcohol dependent patients and 359 healthy controls were included in the present meta-analyses. Regional GM atrophy in alcohol dependent patients was found in the prefrontal cortex (including the anterior cingulate cortex), the dorsal striatum/insula, and the posterior cingulate cortex consistently across studies. The results remained largely unchanged in the following jackknife sensitivity analyses. Conclusions By conducting the first comprehensive meta-analysis of VBM studies, we identified consistent regional GM atrophy particularly within several neurofunctional networks associated with alcohol dependence. Our study demonstrated a characteristic pattern of GM abnormalities and provided further insights into understanding the underlying nature of alcohol dependence.
- Published
- 2015