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. 2017 Jun;47(8):1357-1369.
doi: 10.1017/S0033291716003147. Epub 2016 Dec 21.

Reward-related neural activity and structure predict future substance use in dysregulated youth

Affiliations

Reward-related neural activity and structure predict future substance use in dysregulated youth

M A Bertocci et al. Psychol Med. 2017 Jun.

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.

Keywords: Functional magnetic resonance imaging; GLMNET; LASSO; substance use; youth.

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Figures

Figure 1
Figure 1. LASSO plots generated in GLMNET
A. Plot of variable fit. Each curve corresponds to an independent variable in the full model prior to optimization. Curves indicate the path of each variable coefficient as λ varies. B. Plot of non-zero variable fit after cross validation. Representation of the 10-fold cross validation performed in GLMNET using LASSO which evaluates the error associated with each lambda. Lambda.min corresponds to the λ which minimizes mean squared error. Lambda.1se corresponds to the λ that is one standard error from the lambda.min. Solid black line corresponds to the optimal lambda selected due to significantly improved model fit over the Lambda.min and Lamba.1se based on chi square residual deviance comparisons ( supplemental).
Figure 2
Figure 2. Comparisons of neural measures of substance users and non-users 24.3 months post-scan and representation of the region on an average brain image
A. Reward-related left mPFC and left ventral anterior insula activity. B. Left caudal anterior cingulate thickness between the two groups (representative image). Thickness variables were adjusted for individual mean cortical thickness. Bars represent the standard error.

References

    1. Abuse S. Mental Health Services Administration (2013) Results from the 2012 National Survey on Drug Use and Health: Summary of National Findings. Rockville, MD: Substance Abuse and Mental Health Services Administration; 2014. No. NSDUH Series H-46, HHS Publication No.(SMA) 13–4795.
    1. Amrock SM, Weitzman M. Parental psychological distress and children's mental health: results of a national survey. Academic Pediatrics. 2014;14:375–81. - PubMed
    1. Axelson D, Birmaher BJ, Brent D, Wassick S, Hoover C, Bridge J, Ryan N. A preliminary study of the Kiddie Schedule for Affective Disorders and Schizophrenia for School-Age Children mania rating scale for children and adolescents. Journal of Child Adolescent Psychopharmacology. 2003;13:463–70. - PubMed
    1. Bebko G, Bertocci MA, Fournier JC, Hinze AK, Bonar L, Almeida JR, Perlman SB, Versace A, Schirda C, Travis M, Gill MK, Demeter C, Diwadkar VA, Ciuffetelli G, Rodriguez E, Olino T, Forbes E, Sunshine JL, Holland SK, Kowatch RA, Birmaher B, Axelson D, Horwitz SM, Arnold LE, Fristad MA, Youngstrom EA, Findling RL, Phillips ML. Parsing dimensional vs diagnostic category-related patterns of reward circuitry function in behaviorally and emotionally dysregulated youth in the Longitudinal Assessment of Manic Symptoms study. Journal of the American Medical Association Psychiatry. 2014;71:71–80. - PMC - PubMed
    1. Berkman ET, Falk EB. Beyond Brain Mapping Using Neural Measures to Predict Real-World Outcomes. Current Directions in Psychological Science. 2013;22:45–50. - PMC - PubMed

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