Dataset Information

Mega-Analysis of Gray Matter Volume in Substance Dependence: General and Substance-Specific Regional Effects.

ABSTRACT: OBJECTIVE:Although lower brain volume has been routinely observed in individuals with substance dependence compared with nondependent control subjects, the brain regions exhibiting lower volume have not been consistent across studies. In addition, it is not clear whether a common set of regions are involved in substance dependence regardless of the substance used or whether some brain volume effects are substance specific. Resolution of these issues may contribute to the identification of clinically relevant imaging biomarkers. Using pooled data from 14 countries, the authors sought to identify general and substance-specific associations between dependence and regional brain volumes. METHOD:Brain structure was examined in a mega-analysis of previously published data pooled from 23 laboratories, including 3,240 individuals, 2,140 of whom had substance dependence on one of five substances: alcohol, nicotine, cocaine, methamphetamine, or cannabis. Subcortical volume and cortical thickness in regions defined by FreeSurfer were compared with nondependent control subjects when all sampled substance categories were combined, as well as separately, while controlling for age, sex, imaging site, and total intracranial volume. Because of extensive associations with alcohol dependence, a secondary contrast was also performed for dependence on all substances except alcohol. An optimized split-half strategy was used to assess the reliability of the findings. RESULTS:Lower volume or thickness was observed in many brain regions in individuals with substance dependence. The greatest effects were associated with alcohol use disorder. A set of affected regions related to dependence in general, regardless of the substance, included the insula and the medial orbitofrontal cortex. Furthermore, a support vector machine multivariate classification of regional brain volumes successfully classified individuals with substance dependence on alcohol or nicotine relative to nondependent control subjects. CONCLUSIONS:The results indicate that dependence on a range of different substances shares a common neural substrate and that differential patterns of regional volume could serve as useful biomarkers of dependence on alcohol and nicotine.

SUBMITTER: Mackey S

PROVIDER: S-EPMC6427822 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Mega-Analysis of Gray Matter Volume in Substance Dependence: General and Substance-Specific Regional Effects.

Mackey Scott S Allgaier Nicholas N Chaarani Bader B Spechler Philip P Orr Catherine C Bunn Janice J Allen Nicholas B NB Alia-Klein Nelly N Batalla Albert A Blaine Sara S Brooks Samantha S Caparelli Elisabeth E Chye Yann Ying YY Cousijn Janna J Dagher Alain A Desrivieres Sylvane S Feldstein-Ewing Sarah S Foxe John J JJ Goldstein Rita Z RZ Goudriaan Anna E AE Heitzeg Mary M MM Hester Robert R Hutchison Kent K Korucuoglu Ozlem O Li Chiang-Shan R CR London Edythe E Lorenzetti Valentina V Luijten Maartje M Martin-Santos Rocio R May April A Momenan Reza R Morales Angelica A Paulus Martin P MP Pearlson Godfrey G Rousseau Marc-Etienne ME Salmeron Betty Jo BJ Schluter Renée R Schmaal Lianne L Schumann Gunter G Sjoerds Zsuzsika Z Stein Dan J DJ Stein Elliot A EA Sinha Rajita R Solowij Nadia N Tapert Susan S Uhlmann Anne A Veltman Dick D van Holst Ruth R Whittle Sarah S Wright Margaret J MJ Yücel Murat M Zhang Sheng S Yurgelun-Todd Deborah D Hibar Derrek P DP Jahanshad Neda N Evans Alan A Thompson Paul M PM Glahn David C DC Conrod Patricia P Garavan Hugh H

The American journal of psychiatry 20181019 2

<h4>Objective</h4>Although lower brain volume has been routinely observed in individuals with substance dependence compared with nondependent control subjects, the brain regions exhibiting lower volume have not been consistent across studies. In addition, it is not clear whether a common set of regions are involved in substance dependence regardless of the substance used or whether some brain volume effects are substance specific. Resolution of these issues may contribute to the identification o ...[more]

PMID: 30336705

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Project description:BackgroundDespite decades of research, there is continued uncertainty regarding whether autism is associated with a specific profile of gray matter (GM) structure. This inconsistency may stem from the widespread use of voxel-based morphometry (VBM) methods that combine indices of GM density and GM volume. If GM density or volume, but not both, prove different in autism, the traditional VBM approach of combining the two indices may obscure the difference. The present study measures GM density and volume separately to examine whether autism is associated with alterations in GM volume, density, or both.MethodsDifferences in MRI-based GM density and volume were examined in 6-25 year-olds with a diagnosis of autism spectrum disorder (n = 213, 80.8% male, IQ 47-154) and a typically developing (TD) sample (n = 190, 71.6% male, IQ 67-155). High-resolution T1-weighted anatomical images were collected on a single MRI scanner. Regional density and volume were estimated via whole-brain parcellation comprised of 1625 parcels. Parcel-wise analyses were conducted using generalized additive models while controlling the false discovery rate (FDR, q < 0.05). Volume differences in the 68-region Desikan-Killiany atlas derived from Freesurfer were also examined, to establish the generalizability of findings across methods.ResultsNo density differences were observed between the autistic and TD groups, either in individual parcels or whole brain mean density. Increased volume was observed in autism compared to the TD group when controlling for Age, Sex, and IQ, both at the level of the whole brain (total volume) and in 45 parcels (2.8% of total parcels). Parcels with greater volume included inferior, middle, and superior temporal gyrus, inferior and superior frontal gyrus, precuneus, and fusiform gyrus. Converging evidence from a standard Freesurfer pipeline also identified greater volume in a number of overlapping regions.LimitationsThe method for determining "density" is not a direct measure of neuronal density, and this study cannot reveal underlying cellular differences. While this study represents possibly the largest single-site sample of its kind, it is underpowered to detect very small differences.ConclusionsThese results provide compelling evidence that autism is associated with regional GM volumetric differences, which are more prominent than density differences. This underscores the importance of examining volume and density separately, and suggests that direct measures of volume (e.g. region-of-interest or tensor-based morphometry approaches) may be more sensitive to autism-relevant differences in neuroanatomy than concentration/density-based approaches.

Project description:ImportanceSubstance use disorders (SUDs) are among the most common sequelae of childhood maltreatment, yet the independent contributions of SUDs and childhood maltreatment to neurobiological changes and the effect of the latter on relapse risk (a critical variable in addiction treatment) are relatively unknown.ObjectivesTo identify structural neural characteristics independently associated with childhood maltreatment (CM; a common type of childhood adversity), comparing a sample with SUD with a demographically comparable control sample, and to examine the relationship between CM-related structural brain changes and subsequent relapse.Design, setting, and participantsStructural magnetic resonance imaging study comparing 79 treatment-engaged participants with SUD in acute remission in inpatient treatment at a community mental health center vs 98 healthy control participants at an outpatient research center at an academic medical center. Both groups included individuals with a range of CM experiences. Participants with SUD were followed up prospectively for 90 days to assess relapse and relapse severity.InterventionStandard 12-step, recovery-based, inpatient addiction treatment for all participants with SUD.Main outcomes and measuresGray matter volume (GMV), subsequent substance use relapse, days to relapse, and severity of relapse.ResultsControlling for SUD and psychiatric comorbidity, CM (dichotomously classified) was uniquely associated with lower GMV across all participants in the left hippocampus (cornu ammonis 1-3, dentate gyrus), parahippocampus (presubiculum, parasubiculum, prosubiculum, subiculum, and entorhinal cortex), and anterior fusiform gyrus (corrected P < .05; uncorrected P = .001). Among the sample with SUD, CM prospectively predicted a shorter relapse to use of any drug (P = .048), while CM-related GMV reductions predicted severity of substance use relapse (P = .04).Conclusions and relevanceFindings indicate that CM was related to decreased GMV in limbic regions, which in turn predicted increased risk of relapse in SUD. These results suggest that CM may significantly affect the course of SUD treatment outcomes and that SUD treatment planning may benefit from identifying and addressing CM.

Dataset Information

Mega-Analysis of Gray Matter Volume in Substance Dependence: General and Substance-Specific Regional Effects.

Publications

Mega-Analysis of Gray Matter Volume in Substance Dependence: General and Substance-Specific Regional Effects.

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