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High-Risk Drinkers Engage Distinct Stress-Predictive Brain Networks

  • Elizabeth V. Goldfarb
    Correspondence
    Address correspondence to Elizabeth V. Goldfarb, Ph.D.
    Affiliations
    Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut

    Yale Stress Center, Yale University School of Medicine, New Haven, Connecticut

    Department of Psychology, Yale University, New Haven, Connecticut

    Wu Tsai Institute, Yale University, New Haven, Connecticut
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  • Dustin Scheinost
    Affiliations
    Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut

    Child Study Center, Yale University School of Medicine, New Haven, Connecticut

    Department of Biomedical Engineering, Yale University, New Haven, Connecticut

    Department of Statistics and Data Science, Yale University, New Haven, Connecticut
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  • Nia Fogelman
    Affiliations
    Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut

    Yale Stress Center, Yale University School of Medicine, New Haven, Connecticut
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  • Dongju Seo
    Affiliations
    Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut

    Yale Stress Center, Yale University School of Medicine, New Haven, Connecticut
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  • Rajita Sinha
    Correspondence
    Rajita Sinha, Ph.D.
    Affiliations
    Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut

    Yale Stress Center, Yale University School of Medicine, New Haven, Connecticut

    Child Study Center, Yale University School of Medicine, New Haven, Connecticut

    Department of Neuroscience, Yale University School of Medicine, New Haven, Connecticut
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Published:March 07, 2022DOI:https://doi.org/10.1016/j.bpsc.2022.02.010

      Abstract

      Background

      Excessive alcohol intake is a major public health problem and can be triggered by stress. Heavy drinking in patients with alcohol use disorder also alters neural, physiological, and emotional stress responses. However, it is unclear whether adaptations in stress-predictive brain networks can be an early marker of risky drinking behavior.

      Methods

      Risky social drinkers (regular bingers; n = 53) and light drinker control subjects (n = 51) aged 18 to 53 years completed a functional magnetic resonance imaging–based sustained stress protocol with repeated measures of subjective stress state, during which whole-brain functional connectivity was computed. This was followed by prospective daily ecological momentary assessment for 30 days. We used brain computational predictive modeling with cross-validation to identify unique brain connectivity predictors of stress in risky drinkers and determine the prospective utility of stress-brain networks for subsequent loss of control over drinking.

      Results

      Risky drinkers had anatomically and functionally distinct stress-predictive brain networks (showing stronger predictions from visual and motor networks) compared with light drinkers (default mode and frontoparietal networks). Stress-predictive brain networks defined for risky drinkers selectively predicted future real-world stress levels for risky drinkers and successfully predicted prospective future real-world loss of control over drinking across all participants.

      Conclusions

      These results indicate adaptations in computationally derived stress-related brain circuitry among high-risk drinkers, suggesting potential targets for early preventive intervention and revealing the malleability of the neural processes that govern stress responses.

      Keywords

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