Leveraging genetic data to investigate molecular targets and drug repurposing candidates for treating alcohol use disorder and hepatotoxicity

BackgroundNovel treatments for alcohol use disorder (AUD) and alcohol-related liver disease (ALD) are greatly needed. Genetic information can improve drug discovery rates by facilitating the identification of novel biological targets and potential drugs for repurposing. MethodsThe present study utilized a recently developed Bayesian approach, Integrative Risk Gene Selector (iRIGS), to identify additional risk genes for alcohol consumption using SNPs from the largest alcohol consumption GWAS to date (N = 941,280). iRIGS incorporates several genomic features and closeness of these genes in network space to compute a posterior probability for protein coding genes near each SNP. We subsequently used the Target Central Resource Database to search for drug-protein interactions for these newly identified genes and previously identified risk genes for alcohol consumption. ResultsWe identified several genes that are novel contributions to the previously published alcohol consumption GWAS. Namely, ACVR2A, which is critical for liver function and linked to anxiety and cocaine self-administration, and PRKCE, which has been linked to alcohol self-administration. Notably, only a minority of the SNPs (18.4%) were linked to genes with confidence ([≥].75), underscoring the need to apply multiple methods to assign function to loci. Finally, several previously identified risk genes for alcohol consumption code for proteins that are implicated in liver function and are targeted by drugs that are promising candidates for managing hepatotoxicity (e.g., metformin). ConclusionsThis study demonstrates the value of incorporating regulatory information and drug-protein interaction data to highlight additional molecular targets and drug repurposing candidates for treating AUD and ALD.