342. Pharmacogenomics in alcohol use disorder: multi-omics meets brain organoids

Abstract

Abstract Background We previously conducted an open label acamprosate trial (n=442) in patients with alcohol use disorder (AUD). Acamprosate is an FDA-approved medication for the treatment of AUD, however, only about 50% of patients will respond to acamprosate. To date, no biological measures are utilized to predict response to acamprosate treatment. Aims & Objectives To address this gap, we aimed to identify potential biomarkers associated with alcohol craving intensity using multi-omics data from the Mayo Clinic acamprosate study—the largest acamprosate trial of its kind and the only one with multi-omics data. Method Our open-label acamprosate clinical trial recruited 442 patients with AUD, all of whom were treated with acamprosate for three months. The primary outcomes were 1) relapse to alcohol use and 2) relapse to heavy drinking. Alcohol consumption was measured using the self-reported timeline follow back method. Plasma protein levels were measured using Olink proximity extension immunoassays. We performed functional genomic studies using patient-derived induced pluripotent stem cell (iPSC) as a cell model system. Results Our findings revealed that baseline craving intensity was the most significant clinical predictor of relapse (p: 9.36E-06). Baseline plasma levels of HSD11B1, an enzyme that converts inactive cortisone to active cortisol, were associated with both craving intensity and acamprosate treatment outcomes. Additionally, baseline plasma cortisol levels showed a positive correlation with craving intensity. Notably, a genome-wide association study (GWAS) for plasma cortisol levels identified significant signals within the KHNYN and CBLN3 gene cluster on chromosome 14. Even more striking, this SNP was also associated with acamprosate treatment outcomes. Functional genomic studies using patient-derived iPSC further suggest that KHNYN and CBLN3 could regulate cortisol metabolism and interferon signaling. Discussion & Conclusions Our study represents a systematic approach to identifying biomarkers for acamprosate treatment outcomes and their biological insights using multi-omics data. This series of analyses could enhance our understanding of AUD pathophysiology at the single-cell level, thereby facilitating the discovery of novel anti-craving targets for patients suffering from AUD.