Mechtcheriakov S, Brenneis C, Egger K, Koppelstaetter F, Schocke M, Marksteiner J. A widespread distinct pattern of cerebral atrophy in patients with alcohol addiction revealed by voxel-based morphometry. J Neurol Neurosurg Psychiatry 78: 610-614

Department of General Psychiatry, Medical University Innsbruck, Anichstrasse 35, A-6020 Innsbruck, Austria.
Journal of neurology, neurosurgery, and psychiatry (Impact Factor: 6.81). 07/2007; 78(6):610-4. DOI: 10.1136/jnnp.2006.095869
Source: PubMed


Patients with alcohol addiction show a number of transient or persistent neurological and psychiatric deficits. The complexity of these brain alterations suggests that several brain areas are involved, although the definition of the brain alteration patterns is not yet accomplished.
To determine brain atrophy patterns in patients with alcohol dependence.
Voxel-based morphometry (VBM) of grey matter (GM) and white matter (WM) was performed in 22 patients with alcohol dependence and in 22 healthy controls matched for age and sex.
In patients with alcohol dependence, VBM of GM revealed a significant decrease in density (p<0.001) in the precentral gyrus, middle frontal gyrus, insular cortex, dorsal hippocampus, anterior thalamus and cerebellum compared with controls. Reduced density of WM was found in the periventricular area, pons and cerebellar pedunculi in patients with alcohol addiction.
Our findings provide evidence that alcohol addiction is associated with altered density of GM and WM of specific brain regions. This supports the assumption that alcohol dependence is associated with both local GM dysfunction and altered brain connectivity. Also, VBM is an effective tool for in vivo investigation of cerebral atrophy in patients with alcohol addiction.

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    • "In addition to the changes in the polar regions, there are also changes in the medial temporal cortex, which is one of the structures often reported to be associated with cannabis addiction and where we find a strong bilateral decrease of grey matter volume in the population of regular cannabis users. Such a pattern of atrophy has been also described in other forms of addiction such as alcohol addiction (Mechtcheriakov et al, 2007), but not in heroin users (Denier et al, 2013). However, other patients with severe – non-toxic – behavioral addiction such as pathological gambling (Levine et al, 2005) do not present the same form of atrophy, suggesting that temporal atrophy is indeed associated with cannabis consumption rather than with addictive behavior itself. "
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    • "We observed volume loss in the frontal, prefrontal and temporal GM areas as well as WM losses in the cerebellum, brainstem, and around the ventricles, which is consistent with the findings in literature (Chanraud et al., 2007; Pfefferbaum et al., 1992; Pitel et al., 2012; Shear et al., 1996; Sullivan, 2003; Sullivan et al., 2003). Contrary to previously reported findings (Mechtcheriakov et al., 2007), we did not observe a significant reduction in thalamic volume in alcoholics at treatment entry. However, atrophy of the thalamus would have been observed with a less stringent statistical threshold (p < 0.05, FDR). "
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    Full-text · Article · Jan 2014 · Alcoholism Clinical and Experimental Research
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    • "IFC, STC, ITC, LOC, PCAL, PoCG, MTC.R, IPC.L, LING.R OFC, INS, MFC, ACC, TPC, cerebellum Basal ganglia structures Index Subjects Method Regions significantly different from controls Refs 1 Alcohol 22 users (56.3 years) 22 controls (53.7 years) VBM PreCG, MFG, INS, dHIP, THA, cerebellum Mechtcheriakov et al. (2007) 2 Alcohol 9 users 21 controls VBM THA Reid et al. (2008) 3 Alcohol 69 users (13.4 ± 1.9 years) 58 controls (13.0 ± 2.0 years) SBM Yang et al. (2012) 4 Cocaine 13 users (42 ± 6.3 years) 16 controls (32 ± 6.9 years) VBM AVI, vmOFC, ACC.R, STC Franklin et al. (2002) 5 Cocaine 14 users (36.3 ± 4.7 years) 11 controls (33.8 ± 4.5 years) VBM ACC, mOFC.R, lOFC.R, PFC.R Matochik et al. (2003) 6 Cocaine 19 users (39.5 ± 10.3 years) 17 controls (37.9 ± 12.9 years) VBM PFC, cerebellum.R Brody et al. (2004) 7 Cocaine 22 users (30.8 ± 7.5 years) 23 controls (30.3 ± 7.9 years) "
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