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Computational markers of risky decision-making predict for relapse to alcohol

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European Archives of Psychiatry and Clinical Neuroscience Aims and scope Submit manuscript

Abstract

Background

Relapse remains the major challenge in treatment of alcohol use disorder (AUD). Aberrant decision-making has been found as important cognitive mechanism underlying relapse, but factors associated with relapse vulnerability are unclear. Here, we aim to identify potential computational markers of relapse vulnerability by investigating risky decision-making in individuals with AUD.

Methods

Forty-six healthy controls and fifty-two individuals with AUD were recruited for this study. The risk-taking propensity of these subjects was investigated using the balloon analog risk task (BART). After completion of clinical treatment, all individuals with AUD were followed up and divided into a non-relapse AUD group and a relapse AUD group according to their drinking status.

Results

The risk-taking propensity differed significantly among healthy controls, the non-relapse AUD group, and the relapse AUD group, and was negatively associated with the duration of abstinence in individuals with AUD. Logistic regression models showed that risk-taking propensity, as measured by the computational model, was a valid predictor of alcohol relapse, and higher risk-taking propensity was associated with greater risk of relapse to drink.

Conclusion

Our study presents new insights into risk-taking measurement and identifies computational markers that provide prospective information for relapse to drink in individuals with AUD.

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Funding

This study was provided by the Shandong Mental Health Center grant. The funding source had no role in the study design, collection, analysis of the data, writing the manuscript, or the decision to submit the paper for publication.

Author information

Author notes

  1. Wei Yuan, Meng Chen, Duan-Wei Wang, and Qian-Hui Li contributed equally to this work.

Authors and Affiliations

  1. Department of Addiction Medicine, Shandong Mental Health Center, Jinan, 250014, China

    Wei Yuan, Duan-Wei Wang, Bin Li, Hai-Rong Wang, Yuan-Dong Gong & Tian-Gui Yu

  2. Brain and Cognitive Neuroscience Research Center, Liaoning Normal University, Dalian, 116029, China

    Meng Chen

  3. Division of Gastroenterology, Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, 518107, China

    Qian-Hui Li

  4. School of Mental Health, Wenzhou Medical University, Wenzhou, 325035, China

    Yuan-Yuan Yin

  5. School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China

    Ji Hu

  6. Shanghai Key Laboratory of Psychotic Disorders, Brain Health Institute, National Center for Mental Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China

    Ti-Fei Yuan

  7. Co-Innovation Center of Neuroregeneration, Nantong University, Nantong, Jiangsu, China

    Ti-Fei Yuan

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  1. Wei Yuan
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Correspondence to Yuan-Dong Gong, Ti-Fei Yuan or Tian-Gui Yu.

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Yuan, W., Chen, M., Wang, DW. et al. Computational markers of risky decision-making predict for relapse to alcohol. Eur Arch Psychiatry Clin Neurosci 274, 353–362 (2024). https://doi.org/10.1007/s00406-023-01602-0

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