Reward-related neural activity and structure predict future substance use in dysregulated youth. Issue 8 (21st December 2016)

• Record Type: Journal Article
• Authors: Bertocci, M. A.; Bebko, G.; Versace, A.; Iyengar, S.; Bonar, L.; Forbes, E. E.; Almeida, J. R. C.; Perlman, S. B.; Schirda, C.; Travis, M. J.; Gill, M. K.; Diwadkar, V. A.; Sunshine, J. L.; Holland, S. K.; Kowatch, R. A.; Birmaher, B.; Axelson, D. A.; Frazier, T. W.; Arnold, L. E.; Fristad, M. A.; Youngstrom, E. A.; Horwitz, S. M.; Findling, R. L.; Phillips, M. L.
• Is Part Of: Psychological medicine. Volume 47:Issue 8(2017)
• Page Start: 1357
• Page End: 1369
• Publication Date: 2016-12-21
• Subjects: Functional magnetic resonance imaging, -- GLMNET, -- LASSO, -- substance use, -- youth; Psychiatry -- Periodicals; Medicine and psychology -- Periodicals; Clinical psychology -- Periodicals; 616.89
• DOI: 10.1017/S0033291716003147
• Languages: English
• ISSNs: 0033-2917

Abstract

Abstract : Background: Identifying youth who may engage in future substance use could facilitate early identification of substance use disorder vulnerability. We aimed to identify biomarkers that predicted future substance use in psychiatrically un-well youth. Method: LASSO regression for variable selection was used to predict substance use 24.3 months after neuroimaging assessment in 73 behaviorally and emotionally dysregulated youth aged 13.9 (s.d. = 2.0) years, 30 female, from three clinical sites in the Longitudinal Assessment of Manic Symptoms (LAMS) study. Predictor variables included neural activity during a reward task, cortical thickness, and clinical and demographic variables. Results: Future substance use was associated with higher left middle prefrontal cortex activity, lower left ventral anterior insula activity, thicker caudal anterior cingulate cortex, higher depression and lower mania scores, not using antipsychotic medication, more parental stress, older age. This combination of variables explained 60.4% of the variance in future substance use, and accurately classified 83.6%. Conclusions: These variables explained a large proportion of the variance, were useful classifiers of future substance use, and showed the value of combining multiple domains to provide a comprehensive understanding of substance use development. This may be a step toward identifying neural measures that can identify future substance use disorder risk, and act as targets for therapeutic interventions.