The initiation of cannabis use in adolescence is predicted by sex‐specific psychosocial and neurobiological features. (15th October 2018)

• Record Type: Journal Article
• Authors: Spechler, Philip A.; Allgaier, Nicholas; Chaarani, Bader; Whelan, Robert; Watts, Richard; Orr, Catherine; Albaugh, Matthew D.; D'Alberto, Nicholas; Higgins, Stephen T.; Hudson, Kelsey E.; Mackey, Scott; Potter, Alexandra; Banaschewski, Tobias; Bokde, Arun L. W.; Bromberg, Uli; Büchel, Christian; Cattrell, Anna; Conrod, Patricia J.; Desrivières, Sylvane; Flor, Herta; Frouin, Vincent; Gallinat, Jürgen; Gowland, Penny; Heinz, Andreas; Ittermann, Bernd; Martinot, Jean‐Luc; Paillère Martinot, Marie‐Laure; Nees, Frauke; Papadopoulos Orfanos, Dimitri; Paus, Tomáš; Poustka, Luise; Smolka, Michael N.; Walter, Henrik; Schumann, Gunter; Althoff, Robert R.; Garavan, Hugh;
• Other Names: Mann Karl investigator.; Struve Maren investigator.; Rietschel Marcella investigator.; Spanagel Rainer investigator.; Fauth‐Bühler Mira investigator.; Millenet Sabina investigator.; Grimmer Yvonne investigator.; Ivanov Nikolay investigator.; Strache Nicole investigator.; Rapp Michael investigator.; Ströhle Andreas investigator.; Reuter Jan investigator.; Barbot Alexis investigator.; Thyreau Benjamin investigator.; Schwartz Yannick investigator.; Lalanne Christophe investigator.; Bricaud Zuleima investigator.; Briand Fanny investigator.; Lemaitre Hervé investigator.; Massicotte Jessica investigator.; Vulser Helene investigator.; Pentillä Jani investigator.; Galinowski André investigator.; Jia Tianye investigator.; Werts Helen investigator.; Topper Lauren investigator.; Reed Laurence investigator.; Andrew Chris investigator.; Mallik Catherine investigator.; Ruggeri Barbara investigator.; Nymberg Charlotte investigator.; Smith Lindsay investigator.; Loth Eva investigator.; Havatzias Stephanie investigator.; Stueber Kerstin investigator.; Stringaris Argyris investigator.; Brühl Ruediger investigator.; Ihlenfeld Albrecht investigator.; Walaszek Bernadeta investigator.; Hübner Thomas investigator.; Müller Kathrin investigator.; Ripke Stephan investigator.; Rodehacke Sarah investigator.; Mennigen Eva investigator.; Schmidt Dirk investigator.; Vetter Nora investigator.; Ziesch Veronika investigator.; Poline Jean‐Baptiste investigator.; Fadai Tahmine investigator.; Yacubian Juliana investigator.; Lawrence Claire investigator.; Newman Craig investigator.; Head Kay investigator.; Heym Nadja investigator.; Pausova Zdenka investigator.; Tahmasebi Amir investigator.;
• Is Part Of: European journal of neuroscience. Volume 50:Number 3(2019)
• Page Start: 2346
• Page End: 2356
• Publication Date: 2018-10-15
• Subjects: marijuana -- neuroimaging -- prediction -- specificity; Nervous system -- Periodicals; 612.8
• DOI: 10.1111/ejn.13989
• Languages: English
• ISSNs: 0953-816X

Abstract

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. Abstract : Machine learning techniques were used to predict the initiation of cannabis use by age 16 from a large sample of cannabis‐naïve 14‐year‐olds. Neurobiological, psychosocial and genetic features were measured prior to cannabis exposure. Results identified a sparse set of structural and functional brain features that were likely to precede use. The brain features also exhibited sex‐specific and drug‐specific effects.