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

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.

Fig. 1.

Mean Receiver-operating characteristic (ROC) AUC For Each Use Level by Sex. Mean ROC AUC indicates the performance of the predictive models on independent samples across 100 runs for each use level by sex.

Fig. 2.

Sex-Specific Brain Predictors of Adolescent Cannabis Use. Panels a and b: Brain regions where age 16 cannabis users displayed higher average group-level activation or grey matter volume relative to their nonusing peers. Panel a: Male-Specific Predictive ROIs. Stop success refers to successful inhibition trials minus implicit baseline during the stop signal task; ROI (red) in left inferior temporal gyrus. GMV ROI (yellow) in right medial prefrontal cortex. Panel b: Female-Specific Predictive ROIs. Stop Failure refers to failed inhibition trials minus implicit baseline during the stop signal task; ROIs (pink) in left lateral paravermis, left midbrain, left pre- and postcentral gyrus, right postcentral gyrus. Angry faces refer to passive viewing of angry faces minus control images; ROI (orange) in left ventromedial prefrontal cortex. Reward anticipation refers to the processing of monetary reward cues; ROI (dark green) in left middle frontal gyrus. Stop failure and GMV overlapping ROI (purple) in right presupplementary motor area. Panels c and d: Brain regions where age 16 cannabis users displayed lower average group-level activation or grey matter volume relative to their nonusing peers. Panel c: Male-Specific ROIs. Stop success ROIs (dark blue) in left cerebellum include the anterior cerebellum, paravermis and posterior-lateral portion of the left hemisphere. GMV ROI (bright green) in left middle cingulate. Neutral Faces (passive viewing of neutral faces minus control images) and GMV overlapping ROI (teal) in right midbrain with extent into thalamus. Panel d: Female-Specific ROIs. Angry faces ROI (light blue) in right cerebellar tonsil. Stop success ROIs (dark blue) in bilateral orbitofrontal cortex and two contiguous regions in the right middle temporal gyrus. GMV ROI (bright green) in right middle frontal gyrus. Neutral faces ROIs (maroon) in right superior frontal gyrus and lingual gyrus. Stop failure ROI (dark yellow) in right inferior frontal gyrus.

Fig. 3.

Correlations Between Identified Predictors and Outcome Measure by Sex. Pearson’s point-biserial correlation (r) between predictor and outcome. Error bars represent 95% confidence intervals generated from 5,000 bootstrap samples. Circles = drug use (ESPAD). Triangles = personality (from TCI and SURPS). Squares = life event (from LEQ). Pentagon = verbal IQ. Diamonds = neuroimaging data.