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Am J Psychiatry. 2018 Oct 19:appiajp201817040415. doi: 10.1176/appi.ajp.2018.17040415. [Epub ahead of print]

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

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1
From the Department of Psychiatry and the Department of Mathematics and Statistics, University of Vermont, Burlington; Orygen, the National Centre of Excellence in Youth Mental Health, Parkville, Australia; the Department of Psychology, University of Oregon, Eugene; the Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, Australia; the Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York; the Department of Psychiatry and Psychology, University of Barcelona, Barcelona, Spain; the Department of Psychiatry, Donders Institute for Brain, Cognition, and Behavior, Radboud University Medical Center, Nijmegen, the Netherlands; the Department of Psychiatry, Yale University School of Medicine, New Haven, Conn; the Department of Psychiatry and the MRC Unit on Anxiety and Stress Disorders, University of Cape Town, Cape Town, South Africa; the Neuroimaging Research Branch, Intramural Research Program, National Institute on Drug Abuse, Baltimore; the Monash Institute of Cognitive and Clinical Neurosciences and the School of Psychological Sciences, Monash University, Melbourne, Australia; the Departments of Developmental and Experimental Psychology, Utrecht University, Utrecht, the Netherlands; the Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal; the Centre for Population Neuroscience and Precision Medicine, Institute of Psychiatry, Psychology, and Neuroscience, King's College London; the Department of Psychiatry, Oregon Health and Science University, Portland; the Department of Neuroscience and the Ernest J. Del Monte Institute for Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, N.Y.; the Department of Psychiatry, University of Amsterdam, Amsterdam; the Amsterdam Institute for Addiction Research and Arkin Mental Health Care, Amsterdam; the Department of Psychiatry, University of Michigan, Ann Arbor; the Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, Australia; the Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder; the Department of Psychiatry, Washington University School of Medicine, St. Louis; the David Geffen School of Medicine, University of California at Los Angeles, Los Angeles; the School of Psychology, Faculty of Health Sciences, Australian Catholic University, Melbourne, Australia; the Department of Psychological Sciences, University of Liverpool, Liverpool, U.K.; the Behavioral Science Institute, Radboud University, Nijmegen, the Netherlands; the Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California, San Diego; the Clinical Neuroimaging Research Core, Division of Intramural Clinical and Biological Research, National Institute on Alcohol Abuse and Alcoholism, Bethesda, Md.; the VA San Diego Healthcare System and the Department of Psychiatry, University of California San Diego, La Jolla; the Laureate Institute for Brain Research, Tulsa, Okla.; the Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia; the Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; the Institute of Psychology, Cognitive Psychology Unit, and the Leiden Institute for Brain and Cognition, Leiden University, Leiden, the Netherlands; the School of Psychology and the Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, Australia; the Department of Psychiatry, University of California San Diego, La Jolla; the Department of Psychiatry, VU University Medical Center, Amsterdam; the Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia; the QIMR Berghofer Medical Research Institute, Brisbane, Australia; the Department of Psychiatry, University of Utah School of Medicine, Salt Lake City; the Imaging Genetics Center, Department of Neurology, Keck School of Medicine, University of Southern California, Marina del Rey; and the Department of Psychiatry, University of Montreal, CHU Sainte-Justine Hospital, Montreal.

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.

KEYWORDS:

Mega-Analysis; Structural MRI; Substance-Related Disorders

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