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Eur J Neurosci. 2018 Jun 11. doi: 10.1111/ejn.13989. [Epub ahead of print]

The initiation of cannabis use in adolescence is predicted by sex-specific psychosocial and neurobiological features.

Author information

1
Vermont Center on Behavior and Health, University of Vermont, Burlington, VT, USA.
2
Department of Psychological Science, University of Vermont, Burlington, VT, 05401, USA.
3
Department of Psychiatry, University of Vermont, Burlington, VT, USA.
4
School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland.
5
Department of Radiology, University of Vermont, Burlington, VT, USA.
6
Medical Faculty Mannheim, Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Heidelberg University, Mannheim, Germany.
7
Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neurosciences, Trinity College Dublin, Dublin, Ireland.
8
University Medical Centre Hamburg-Eppendorf, Hamburg, Germany.
9
Centre for Population Neuroscience and Stratified Medicine (PONS) and MRC-SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
10
Department of Psychiatry, Universite de Montreal, CHU Ste Justine Hospital, Montreal, Canada.
11
Medical Faculty Mannheim, Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Heidelberg University, Mannheim, Germany.
12
Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim, Germany.
13
NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France.
14
Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany.
15
Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK.
16
Department of Psychiatry and Psychotherapy, Charité, Universitätsmedizin Berlin, Campus Charité Mitte, Berlin, Germany.
17
Physikalisch-Technische Bundesanstalt (PTB), Braunschweig, Germany.
18
DIGITEO Labs, Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 "Neuroimaging & Psychiatry", University Paris Sud - University Paris Saclay, Gif sur Yvette, France.
19
Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 "Neuroimaging & Psychiatry", University Paris Sud - Paris Saclay, University Paris Descartes, Paris, France.
20
Department of Adolescent Psychopathology and Medicine, AP-HP, Maison de Solenn, Cochin Hospital, Paris, France.
21
Baycrest and Departments of Psychology and Psychiatry, Rotman Research Institute, University of Toronto, Toronto, ON, M6A 2E1, Canada.
22
Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, 37075, Göttingen, Germany.
23
Clinic for Child and Adolescent Psychiatry, Medical University of Vienna, Vienna, Austria.
24
Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany.

Abstract

Cannabis use initiated during adolescence might precipitate negative consequences in adulthood. Thus, predicting adolescent cannabis use prior to any exposure will inform the aetiology of substance abuse by disentangling predictors from consequences of use. In this prediction study, data were drawn from the IMAGEN sample, a longitudinal study of adolescence. All selected participants (n = 1,581) were cannabis-naïve at age 14. Those reporting any cannabis use (out of six ordinal use levels) by age 16 were included in the outcome group (N = 365, males n = 207). Cannabis-naïve participants at age 14 and 16 were included in the comparison group (N = 1,216, males n = 538). Psychosocial, brain and genetic features were measured at age 14 prior to any exposure. Cross-validated regularized logistic regressions for each use level by sex were used to perform feature selection and obtain prediction error statistics on independent observations. Predictors were probed for sex- and drug-specificity using post-hoc logistic regressions. Models reliably predicted use as indicated by satisfactory prediction error statistics, and contained psychosocial features common to both sexes. However, males and females exhibited distinct brain predictors that failed to predict use in the opposite sex or predict binge drinking in independent samples of same-sex participants. Collapsed across sex, genetic variation on catecholamine and opioid receptors marginally predicted use. Using machine learning techniques applied to a large multimodal dataset, we identified a risk profile containing psychosocial and sex-specific brain prognostic markers, which were likely to precede and influence cannabis initiation.

KEYWORDS:

marijuana; neuroimaging; prediction; specificity

PMID:
29889330
DOI:
10.1111/ejn.13989

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