The initiation of cannabis use in adolescence is predicted by sex-specific psychosocial and neurobiological features
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The initiation of cannabis use in adolescence is predicted by sex-specific psychosocial and neurobiological features. / 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; IMAGEN Consortium.
In: EUR J NEUROSCI, Vol. 50, No. 3, 08.2019, p. 2346-2356.Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review
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TY - JOUR
T1 - The initiation of cannabis use in adolescence is predicted by sex-specific psychosocial and neurobiological features
AU - Spechler, Philip A
AU - Allgaier, Nicholas
AU - Chaarani, Bader
AU - Whelan, Robert
AU - Watts, Richard
AU - Orr, Catherine
AU - Albaugh, Matthew D
AU - D'Alberto, Nicholas
AU - Higgins, Stephen T
AU - Hudson, Kelsey E
AU - Mackey, Scott
AU - Potter, Alexandra
AU - Banaschewski, Tobias
AU - Bokde, Arun L W
AU - Bromberg, Uli
AU - Büchel, Christian
AU - Cattrell, Anna
AU - Conrod, Patricia J
AU - Desrivières, Sylvane
AU - Flor, Herta
AU - Frouin, Vincent
AU - Gallinat, Jürgen
AU - Gowland, Penny
AU - Heinz, Andreas
AU - Ittermann, Bernd
AU - Martinot, Jean-Luc
AU - Paillère Martinot, Marie-Laure
AU - Nees, Frauke
AU - Papadopoulos Orfanos, Dimitri
AU - Paus, Tomáš
AU - Poustka, Luise
AU - Smolka, Michael N
AU - Walter, Henrik
AU - Schumann, Gunter
AU - Althoff, Robert R
AU - Garavan, Hugh
AU - IMAGEN Consortium
N1 - © 2018 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
PY - 2019/8
Y1 - 2019/8
N2 - 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.
AB - 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.
KW - Journal Article
U2 - 10.1111/ejn.13989
DO - 10.1111/ejn.13989
M3 - SCORING: Journal article
C2 - 29889330
VL - 50
SP - 2346
EP - 2356
JO - EUR J NEUROSCI
JF - EUR J NEUROSCI
SN - 0953-816X
IS - 3
ER -
