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Chronic Intermittent Ethanol Vapor Exposure Paired with Two-Bottle Choice to Model Alcohol Use Disorder
Published on: June 23, 2023
Genome-wide meta-analyses of cross substance use disorders in diverse populations
Dongbing Lai1, Michael Zhang2, Nick Green2
1Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA. dlai@iu.edu.
Abstract:
Substance use disorders (SUDs, including alcohol, cannabis, opioids, and tobacco) represent significant public health challenges. The estimated heritability of SUDs is ~50% and many individuals experience multiple SUDs concurrently. Studies have demonstrated the existence of genes shared across multiple SUDs, and identifying these SUD-shared genes is critical to developing novel prevention and treatment strategies. Here, we conducted the largest cross SUD meta-analysis to date to identify SUD-shared genes using samples genetically similar to 1000 Genomes Project European (1kg-EUR-like), African (1kg-AFR-like), and American mixed (1kg-AMR-like) populations. We defined variants that had the same direction of effects across different SUDs (i.e., concordant variants) as SUD-shared. In total, we identified 220 loci, including 40 novel loci that were not reported as SUD-associated in previous genome-wide association studies. Through gene-based analyses, gene mapping, and gene prioritization, we identified 785 SUD-shared genes. These genes are highly expressed in the amygdala, cortex, hippocampus, hypothalamus, and thalamus; and are primarily highly expressed in neuronal cells, suggesting that more brain regions may be involved in SUDs than previously reported. Concordant variants explained 56-96% of the SNP-heritability of each SUD in the 1kg-EUR-like sample. Furthermore, the top 10% of individuals in the 1kg-EUR-like and 1kg-AMR-like samples with the highest polygenic scores had odds ratios ranging from 1.95-2.87 to develop SUDs, and these polygenic scores could potentially be used to identify high-risk individuals. Lastly, using a real-world dataset, we identified seven SUD-shared genes targeting drugs that may be repurposed for treating SUDs, particularly in those suffering from comorbid SUDs.
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