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Neuropsychosocial markers of binge drinking in young adults

Molecular Psychiatry volume 26, pages 4931–4943 (2021)Cite this article

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Abstract

Binge drinking is associated with disease and death, and developing tools to identify risky drinkers could mitigate its damage. Brain processes underlie risky drinking, so we examined whether neural and psychosocial markers could identify binge drinkers. Reward is the most widely studied neural process in addiction, but processes such as emotion, social cognition, and self-regulation are also involved. Here we examined whether neural processes apart from reward contribute to predicting risky drinking behaviors. From the Human Connectome Project, we identified 177 young adults who binged weekly and 309 nonbingers. We divided the sample into a training and a testing set and used machine-learning algorithms to classify participants based on psychosocial, neural, or both (neuropsychosocial) data. We also developed separate models for each of the seven fMRI tasks used in the study. An ensemble model developed in the training dataset was then applied to the testing dataset. Model performance was assessed by the area under the receiver operating characteristic curve (AUC) and differences between models were assessed using DeLong’s test. The three models performed better than chance in the test sample with the neuropsychosocial (AUC = 0.86) and psychosocial (AUC = 0.84) performing better than the neural model (AUC = 0.64). Two fMRI-based models predicted binge drinking status better than chance, corresponding to the social and language tasks. Models developed with psychosocial and neural variables could contribute as diagnostic tools to help classify risky drinkers. Since social and language fMRI tasks performed best among the neural discriminators (including those from gambling and emotion tasks), it suggests the involvement of a broader range of brain processes than those traditionally associated with binge drinking in young adults.

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Fig. 1: Schematic of Analytic Approach.
Fig. 2: Group differences.
Fig. 3: Performance of neuropsychosocial, psychosocial, and neural models.
Fig. 4: Performance of language, motor, and social fMRI models.
Fig. 5: Neural contributions to classification.

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Acknowledgements

Data were provided by the Human Connectome Project, WU-Minn Consortium (principal investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 National Institutes of Health (NIH) institutes and centers that support the NIH Blueprint for Neuroscience Research, and by the McDonnell Center for Systems Neuroscience at Washington University. We thank Francisco Pereira for suggestions on setting up the analysis. Support for time on this manuscript was provided by the National Institute on Alcohol Abuse and Alcoholism (Z1A AA000466 to VAR and R00 AA024778 to JLG).

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Authors and Affiliations

  1. Department of Radiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA

    Joshua L. Gowin

  2. Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD, USA

    Peter Manza & Nora D. Volkow

  3. Section on Human Psychopharmacology, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD, USA

    Vijay A. Ramchandani

  4. National Institute on Drug Abuse, Bethesda, MD, USA

    Nora D. Volkow

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Correspondence to Joshua L. Gowin.

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Gowin, J.L., Manza, P., Ramchandani, V.A. et al. Neuropsychosocial markers of binge drinking in young adults. Mol Psychiatry 26, 4931–4943 (2021). https://doi.org/10.1038/s41380-020-0771-z

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