Citation

Spechler PA, Allgaier N, Chaarani B, Whelan R, Watts R, Orr C, Albaugh MD, D'Alberto N, Higgins ST, Hudson KE, Mackey S, Potter A, Banaschewski T, Bokde ALW, Bromberg U, Büchel C, Cattrell A, Conrod PJ, Desrivieres S, Flor H, Frouin V, Gallinat J, Gowland P, Heinz A, Ittermann B, Martinot JL, Martinot MP, Nees F, Orfanos DP, Paus T, Smolka MN, Walter H, Schumann G, Althoff RR, Garavan H. Eur. J. Neurosci. 2018; ePub(ePub): ePub.

Affiliation

Department of Psychiatry, University of Vermont, Burlington, VT, USA, 05401.

Copyright

(Copyright © 2018, Federation of European Neuroscience Societies, Publisher John Wiley and Sons)

DOI

10.1111/ejn.13989

PMID

29889330

Abstract

Cannabis use initiated during adolescence might precipitate negative consequences in adulthood. Thus, predicting adolescent cannabis use prior to any exposure will inform the etiology 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 6 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. This article is protected by copyright. All rights reserved.

This article is protected by copyright. All rights reserved.

Language: en

Keywords

Marijuana; Neuroimaging; Prediction; Specificity