2. Phenotyping Individuals with Alcohol Use Disorder: Implications for Precision Medicine and Predicting Non-Abstinent Recovery from Alcohol Use Disorder

Wednesday, 23 November, 2022 - 13:20 to 14:50

Abstract

Alcohol use disorder (AUD) is a heterogeneous disorder. In order to advance our field in the direction of precision medicine approaches to the treatment of AUD, it is imperative to identify clear behavioral phenotypes, which can serve to advance basic research and clinical translation. The alcohol and addiction research domain criteria (AARDoC) has been proposed to provide a framework for understanding AUD in terms of psychological and biological constructs, including: negative emotionality, incentive salience for alcohol, and impairments in executive functioning. Yet, no studies have examined whether the AARDoC domains predict recovery from AUD.

 

Individuals with AUD (n=1468) who participated in two multisite alcohol clinical trials in the United States, completed a range of self-report measures before treatment. Factor analysis were used to derive AARDoC negative emotionality, incentive salience, and executive functioning domains, and these were then separately included as predictors of harm reduction focused non-abstinent recovery outcomes three years after treatment via latent profile modeling.

 

Fifteen self-report items were used as indicators of the three AARDoC domains. The models provided an excellent fit to the observed data and were significantly associated with recovery outcomes. Negative emotionality was most strongly associated with recovery outcomes, such that lower negative emotionality predicted high functioning recovery profiles. Higher incentive salience and greater executive function predicted high functioning non-abstinent recovery.

 

The results from the current study provide support for the utility of pre-treatment AARDoC domains predicting variability in non-abstinent recovery outcomes among individuals who sought treatment for AUD.

 

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23 A2 1320 Katie Witkiewitz_v1.0.pdf701.62 KBDownload

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