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

• Verfasst von: Spechler, Philip A. [VerfasserIn]
• Verfasst von: Banaschewski, Tobias [VerfasserIn]
• Verfasst von: Flor, Herta [VerfasserIn]
• Verfasst von: Nees, Frauke [VerfasserIn]
• Verfasst von: Mann, Karl [VerfasserIn]
• Verfasst von: Rietschel, Marcella [VerfasserIn]
• Verfasst von: Spanagel, Rainer [VerfasserIn]
• Titel: The initiation of cannabis use in adolescence is predicted by sex-specific psychosocial and neurobiological features
• Verf.angabe: Philip A. Spechler, Nicholas Allgaier, Bader Chaarani, Robert Whelan, Richard Watts, Catherine Orr, Matthew D. Albaugh, Nicholas D'Alberto, Stephen T. Higgins, Kelsey E. Hudson, Scott Mackey, Alexandra Potter, Tobias Banaschewski, Arun L.W. Bokde, Uli Bromberg, Christian Büchel, Anna Cattrell, Patricia J. Conrod, Sylvane Desrivières, Herta Flor, Vincent Frouin, Jürgen Gallinat, Penny Gowland, Andreas Heinz, Bernd Ittermann, Jean-Luc Martinot, Marie-Laure Paillère Martinot, Frauke Nees, Dimitri Papadopoulos Orfanos, Tomáš Paus, Luise Poustka, Michael N. Smolka, Henrik Walter, Gunter Schumann, Robert R. Althoff, Hugh Garavan and the IMAGEN Consortium
• Jahr: 2019
• Jahr des Originals: 2018
• Umfang: 11 S.
• Fussnoten: Gesehen am 28.11.2019 ; Members of the IMAGEN Consortium not listed as individual authors include: Karl Mann, Maren Struve, Marcella Rietschel, Rainer Spanagel, ; First published: 11 June 2018
• Titel Quelle: Enthalten in: European journal of neuroscience
• Ort Quelle: Oxford [u.a.] : Wiley, 1989
• Jahr Quelle: 2019
• Band/Heft Quelle: 50(2019), 3, Seite 2346-2356
• ISSN Quelle: 1460-9568
• DOI: doi:10.1111/ejn.13989
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: marijuana
• Sach-SW: neuroimaging
• Sach-SW: prediction
• Sach-SW: specificity
• K10plus-PPN: 1683708350

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.